{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Select Preference Data" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:11:04.757824Z", "start_time": "2024-05-26T00:11:04.555293Z" }, "execution": { "iopub.execute_input": "2024-12-18T03:54:40.283819Z", "iopub.status.busy": "2024-12-18T03:54:40.283687Z", "iopub.status.idle": "2024-12-18T03:54:40.441568Z", "shell.execute_reply": "2024-12-18T03:54:40.441106Z", "shell.execute_reply.started": "2024-12-18T03:54:40.283805Z" } }, "outputs": [], "source": [ "# setup tailscale if you haven't\n", "# https://tailscale.com/kb/1031/install-linux\n", "!sudo tailscale up --accept-routes=true\n", "\n", "# setup autoload\n", "%load_ext autoreload\n", "%autoreload 2" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:11:08.392310Z", "start_time": "2024-05-26T00:11:04.759383Z" }, "execution": { "iopub.execute_input": "2024-12-18T03:54:40.442223Z", "iopub.status.busy": "2024-12-18T03:54:40.442086Z", "iopub.status.idle": "2024-12-18T03:54:46.126826Z", "shell.execute_reply": "2024-12-18T03:54:46.126264Z", "shell.execute_reply.started": "2024-12-18T03:54:40.442209Z" } }, "outputs": [], "source": [ "# make sure sqlalchemy is >=2\n", "# pip install psycopg2-binary\n", "# pip install \"sqlalchemy>=2\"\n", "import os\n", "import datetime\n", "from collections import defaultdict, Counter\n", "import json\n", "from urllib.parse import quote\n", "import time\n", "\n", "import boto3\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import pandas as pd\n", "import sqlalchemy\n", "from sqlalchemy.pool import QueuePool\n", "import tqdm\n", "from botocore.exceptions import ClientError\n", "from suno_analytics.preference_helper import get_preference_counts\n", "from suno_analytics.preference_data_selection import (\n", " gather_data,\n", " gather_data_with_snowflake,\n", " plot_clip_distribution,\n", " parse_metadata_for_basics,\n", " get_concat_clip_ids,\n", " validate_preference_data,\n", " run_bot_detection,\n", " print_out_value_counts_nicely,\n", " merge_concat_clips_with_reactions,\n", " plot_clip_basic_distributions,\n", ")\n", "\n", "\n", "# setup some pandas display stuff\n", "pd.set_option(\"display.max_rows\", 500)\n", "pd.set_option(\"display.max_columns\", 500)\n", "pd.set_option(\"display.width\", 1000)\n", "\n", "\n", "def get_secret():\n", " secret_name = \"app-user-main-db-secret\"\n", " region_name = \"us-east-2\"\n", " # Create a Secrets Manager client\n", " session = boto3.session.Session()\n", " client = session.client(service_name=\"secretsmanager\", region_name=region_name)\n", " try:\n", " get_secret_value_response = client.get_secret_value(SecretId=secret_name)\n", " except ClientError as e:\n", " raise e\n", " secret = get_secret_value_response[\"SecretString\"]\n", " return json.loads(secret)\n", "\n", "\n", "my_secrets = get_secret()\n", "\n", "# alternative...\n", "engine = sqlalchemy.create_engine(\n", " \"postgresql://suno:%s@suno-main-postgres-prod-analytics.cnfvffydbwvc.us-east-2.rds.amazonaws.com/suno_main\"\n", " % quote(my_secrets[\"password\"]),\n", ")\n", "\n", "\n", "home_dir = os.path.expanduser(\"~\")\n", "snow_password_path = os.path.join(home_dir, \".aws\", \"snow_pw.txt\")\n", "if os.path.exists(snow_password_path):\n", " # !pip install snowflake\n", " from snowflake.core import Root\n", " from snowflake.snowpark import Session\n", "\n", " with open(snow_password_path, \"r\") as fp:\n", " fp_lines = fp.readlines()\n", " snow_password = fp_lines[0].strip()\n", " snow_username = fp_lines[1].strip()\n", "\n", " CONNECTION_PARAMETERS = {\n", " \"account\": \"fu90569.us-east-2.aws\",\n", " \"user\": snow_username,\n", " \"password\": snow_password,\n", " \"role\": \"ACCOUNTADMIN\",\n", " \"database\": \"SUNO_PROD\",\n", " \"warehouse\": \"SUNO_PROD_LARGE\",\n", " \"schema\": \"PROD\",\n", " }" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Validate some info" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:11:08.550447Z", "start_time": "2024-05-26T00:11:08.397196Z" }, "execution": { "iopub.execute_input": "2024-12-18T03:54:46.127620Z", "iopub.status.busy": "2024-12-18T03:54:46.127392Z", "iopub.status.idle": "2024-12-18T03:54:46.144756Z", "shell.execute_reply": "2024-12-18T03:54:46.144291Z", "shell.execute_reply.started": "2024-12-18T03:54:46.127605Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2024-12-16 20:40:00\n" ] } ], "source": [ "# there are 4 hr time difference between eastern time and utc\n", "# cutoff_date = \"2024-08-26 21:00:00\" # v4-t3 out\n", "# cutoff_date = \"2024-09-12 21:00:00\" # covers beta out\n", "# cutoff_date = \"2024-09-22 00:00:00\" # pre fe exp out\n", "# cutoff_date = \"2024-09-26 12:00:00\" # s29 out\n", "# cutoff_date = \"2024-10-09 15:20:00\" # 30b t5 out\n", "# cutoff_date = \"2024-10-31 16:00:00\" # 30b t6 out\n", "# cutoff_date = \"2024-11-12 13:00:00\" # 30b t6-2 out\n", "# cutoff_date = \"2024-11-19 16:00:00\" # v4 out\n", "# cutoff_date = \"2024-12-06 16:00:00\" # diff v2 out\n", "# cutoff_date = \"2024-12-11 14:00:00\" # diff v3 out\n", "cutoff_date = \"2024-12-16 20:40:00\" # v4 s32 out\n", "# cutoff_date = (\n", "# (datetime.datetime.now() - datetime.timedelta(hours=4))\n", "# .astimezone(datetime.timezone.utc)\n", "# .strftime(\"%Y-%m-%d %H:%M:%S\")\n", "# )\n", "print(cutoff_date)\n", "\n", "target_model_name = \"chirp-v3p5-engine-t-6\"" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:11:09.349857Z", "start_time": "2024-05-26T00:11:08.551408Z" }, "execution": { "iopub.execute_input": "2024-12-18T03:54:46.145361Z", "iopub.status.busy": "2024-12-18T03:54:46.145227Z", "iopub.status.idle": "2024-12-18T03:54:46.468120Z", "shell.execute_reply": "2024-12-18T03:54:46.467666Z", "shell.execute_reply.started": "2024-12-18T03:54:46.145348Z" } }, "outputs": [], "source": [ "df_all_tables = pd.read_sql_query(\n", " \"SELECT table_name FROM information_schema.tables WHERE table_schema = 'public'\",\n", " engine,\n", ")\n", "# should have all the basic table names here\n", "assert df_all_tables[\"table_name\"].nunique() >= 61" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Query the DB" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "execution": { "iopub.execute_input": "2024-12-18T03:54:46.468744Z", "iopub.status.busy": "2024-12-18T03:54:46.468608Z", "iopub.status.idle": "2024-12-18T03:54:46.841944Z", "shell.execute_reply": "2024-12-18T03:54:46.841467Z", "shell.execute_reply.started": "2024-12-18T03:54:46.468731Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "PROD\n" ] } ], "source": [ "if not os.path.exists(snow_password_path):\n", " raise Exception(\"you are not authorized to access snowflake -- please setup\")\n", "\n", "snow_session = Session.builder.configs(CONNECTION_PARAMETERS).create()\n", "\n", "snow_root = Root(snow_session)\n", "snow_schema = snow_root.databases[\"SUNO_PROD\"].schemas[\"PROD\"]\n", "print(snow_schema.name)\n", "\n", "from snowflake.snowpark.functions import col\n", "# !pip install \"snowflake-connector-python[pandas]\"" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "execution": { "iopub.execute_input": "2024-12-18T03:54:46.843741Z", "iopub.status.busy": "2024-12-18T03:54:46.843454Z", "iopub.status.idle": "2024-12-18T04:22:21.218555Z", "shell.execute_reply": "2024-12-18T04:22:21.217962Z", "shell.execute_reply.started": "2024-12-18T03:54:46.843726Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Start gather data from 2024-12-16 20:40:00\n", "Bots Action: 9,921,141 rows\n", " ---- Execution time: 21.47 seconds\n", "Reactions: 11,978,233 rows\n", " ---- Execution time: 27.85 seconds\n", "Discord Info: 416,437 rows\n", "subscription_status\n", "active 398638\n", "past_due 17799\n", "Name: count, dtype: int64\n", " ---- Execution time: 7.30 seconds\n", "Playlist Clips: 284,809 rows\n", " ---- Execution time: 3.44 seconds\n", "Total Clips: 9,854,335 rows\n", " ---- Execution time: 419.72 seconds\n" ] } ], "source": [ "# gathered_data = gather_data(engine, cutoff_date)\n", "gathered_data = gather_data_with_snowflake(snow_session, cutoff_date)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "execution": { "iopub.execute_input": "2024-12-18T04:22:21.219333Z", "iopub.status.busy": "2024-12-18T04:22:21.219182Z", "iopub.status.idle": "2024-12-18T04:22:21.246225Z", "shell.execute_reply": "2024-12-18T04:22:21.245763Z", "shell.execute_reply.started": "2024-12-18T04:22:21.219318Z" } }, "outputs": [], "source": [ "bots_action_df = gathered_data[\"bots_action_df\"]\n", "reaction_df = gathered_data[\"reaction_df\"]\n", "total_clip_df = gathered_data[\"total_clip_df\"]\n", "playlist_clip_df = gathered_data[\"playlist_clip_df\"]\n", "discord_info_df = gathered_data[\"discord_info_df\"]" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "execution": { "iopub.execute_input": "2024-12-18T04:22:21.246866Z", "iopub.status.busy": "2024-12-18T04:22:21.246726Z", "iopub.status.idle": "2024-12-18T04:23:18.847510Z", "shell.execute_reply": "2024-12-18T04:23:18.846928Z", "shell.execute_reply.started": "2024-12-18T04:22:21.246852Z" } }, "outputs": [], "source": [ "# parse out the necessary metadata early\n", "total_clip_df[[\"continued_parent\", \"duration\", \"source\", \"clip_type\", \"task\"]] = (\n", " pd.DataFrame(\n", " total_clip_df[\"metadata\"].map(parse_metadata_for_basics).tolist(),\n", " index=total_clip_df.index,\n", " )\n", ")" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "execution": { "iopub.execute_input": "2024-12-18T04:23:18.848280Z", "iopub.status.busy": "2024-12-18T04:23:18.848125Z", "iopub.status.idle": "2024-12-18T04:24:00.248654Z", "shell.execute_reply": "2024-12-18T04:24:00.248119Z", "shell.execute_reply.started": "2024-12-18T04:23:18.848265Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "total clips: 9854335\n", "gen: 9351744 (94.90%)\n", "upsample: 298715 (3.03%)\n", "upload: 90821 (0.92%)\n", "concat: 57642 (0.58%)\n", "stem: 28196 (0.29%)\n", "edit_crop: 14292 (0.15%)\n", "concat_infilling: 12922 (0.13%)\n", "edit_fade: 2 (0.00%)\n", "edit_speed: 1 (0.00%)\n", "total without model: 119369\n" ] }, { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Total number of hours: 45\n", "Average clips per hour: 218985.22\n", "Max clips in an hour: 285869\n", "Min clips in an hour: 83600\n" ] } ], "source": [ "# filter on versions\n", "clip_df = total_clip_df.copy()\n", "total_clip_counts = clip_df.shape[0]\n", "print(f\"total clips: {total_clip_counts}\")\n", "print_out_value_counts_nicely(clip_df, \"clip_type\")\n", "# check the number of audio uploads\n", "upload_clip_df = total_clip_df[total_clip_df[\"clip_type\"] == \"upload\"].copy()\n", "stem_clip_df = total_clip_df[total_clip_df[\"clip_type\"] == \"stem\"].copy()\n", "print(\"total without model:\", (total_clip_df[\"model_name\"] == \"\").sum())\n", "\n", "# Call the function\n", "plot_clip_distribution(total_clip_df)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Proceed with feature engineering and cleaning up" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "execution": { "iopub.execute_input": "2024-12-18T04:24:00.249379Z", "iopub.status.busy": "2024-12-18T04:24:00.249222Z", "iopub.status.idle": "2024-12-18T04:24:01.556749Z", "shell.execute_reply": "2024-12-18T04:24:01.556180Z", "shell.execute_reply.started": "2024-12-18T04:24:00.249364Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "number of upvoates: 1,478,696 rows\n", "number of flagged reports: 31,857 rows\n" ] } ], "source": [ "upvoted_df = reaction_df[reaction_df[\"reaction_type\"] == \"L\"].copy()\n", "print(f\"number of upvoates: {upvoted_df.shape[0]:,} rows\")\n", "upvoted_ids = upvoted_df[\"clip_id\"]\n", "\n", "flagged_df = reaction_df[reaction_df[\"flagged\"]].copy()\n", "print(f\"number of flagged reports: {flagged_df.shape[0]:,} rows\")\n", "flagged_ids = flagged_df[\"clip_id\"]" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "execution": { "iopub.execute_input": "2024-12-18T04:24:01.557476Z", "iopub.status.busy": "2024-12-18T04:24:01.557322Z", "iopub.status.idle": "2024-12-18T04:24:03.288962Z", "shell.execute_reply": "2024-12-18T04:24:03.288395Z", "shell.execute_reply.started": "2024-12-18T04:24:01.557460Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Reactions fraction by pro user:\n", "False: 6496520 (54.24%)\n", "True: 5481713 (45.76%)\n", "------------\n", "Clip generated fraction by pro user:\n", "False: 4966429 (50.40%)\n", "True: 4887906 (49.60%)\n" ] } ], "source": [ "# this is probably the right way to figure out the pro user group\n", "pro_users = set(discord_info_df[\"user_id\"].unique())\n", "reaction_df[\"is_pro_user\"] = reaction_df[\"user_id\"].isin(pro_users)\n", "clip_df[\"is_pro_user\"] = clip_df[\"user_id\"].isin(pro_users)\n", "\n", "# this is very interesting....\n", "# reaction check\n", "print(\"Reactions fraction by pro user:\")\n", "print_out_value_counts_nicely(reaction_df, \"is_pro_user\")\n", "print(\"------------\")\n", "# clip check\n", "print(\"Clip generated fraction by pro user:\")\n", "print_out_value_counts_nicely(clip_df, \"is_pro_user\")" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "execution": { "iopub.execute_input": "2024-12-18T04:24:03.289685Z", "iopub.status.busy": "2024-12-18T04:24:03.289535Z", "iopub.status.idle": "2024-12-18T04:24:03.430799Z", "shell.execute_reply": "2024-12-18T04:24:03.430291Z", "shell.execute_reply.started": "2024-12-18T04:24:03.289670Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "stem parent ids: 13745\n" ] } ], "source": [ "# find out the stem parent ids\n", "stem_parent_ids = set(\n", " stem_clip_df[\"metadata\"].apply(lambda x: x.get(\"stem_from_id\", \"xxx\"))\n", ")\n", "print(\"stem parent ids:\", len(stem_parent_ids))" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:12.019778Z", "start_time": "2024-05-26T00:22:57.637371Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:24:03.431466Z", "iopub.status.busy": "2024-12-18T04:24:03.431314Z", "iopub.status.idle": "2024-12-18T04:24:16.773433Z", "shell.execute_reply": "2024-12-18T04:24:16.772871Z", "shell.execute_reply.started": "2024-12-18T04:24:03.431451Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Clips in a splaylist:\n", "False: 9741600 (98.86%)\n", "True: 112735 (1.14%)\n", "------------\n", "Clips has stem children:\n", "False: 9844212 (99.90%)\n", "True: 10123 (0.10%)\n" ] } ], "source": [ "# add clip is in playlist feature\n", "clip_df[\"is_in_playlist\"] = clip_df[\"id\"].isin(playlist_clip_df[\"clip_id\"].unique())\n", "print(\"Clips in a splaylist:\")\n", "print_out_value_counts_nicely(clip_df, \"is_in_playlist\")\n", "clip_df[\"has_stems\"] = clip_df[\"id\"].astype(str).isin(stem_parent_ids)\n", "print(\"------------\")\n", "print(\"Clips has stem children:\")\n", "print_out_value_counts_nicely(clip_df, \"has_stems\")" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:17.912428Z", "start_time": "2024-05-26T00:23:12.021726Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:24:16.774143Z", "iopub.status.busy": "2024-12-18T04:24:16.773988Z", "iopub.status.idle": "2024-12-18T04:24:27.466153Z", "shell.execute_reply": "2024-12-18T04:24:27.465619Z", "shell.execute_reply.started": "2024-12-18T04:24:16.774127Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "clips that have children: 966821 \n", "clips that are parents: 172887 \n", " Average continues from clip = 5.59\n", "web: 8381706 (85.67%)\n", "ios: 850100 (8.69%)\n", "android: 551931 (5.64%)\n" ] } ], "source": [ "# parse the metadata for histories and types\n", "clip_history_df = clip_df[~clip_df[\"continued_parent\"].isna()].copy()\n", "# these are the direct parent's ids -- not grandparents\n", "has_continued_children_ids = clip_history_df[\"continued_parent\"]\n", "print(\n", " \"clips that have children:\",\n", " len(has_continued_children_ids),\n", " \"\\nclips that are parents:\",\n", " has_continued_children_ids.nunique(),\n", " \"\\n\",\n", " \"Average continues from clip = \",\n", " round(\n", " len(has_continued_children_ids) / len(has_continued_children_ids.unique()), 2\n", " ),\n", ")\n", "# Get value counts\n", "print_out_value_counts_nicely(clip_df, \"source\")" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:22.092835Z", "start_time": "2024-05-26T00:23:17.914456Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:24:27.466859Z", "iopub.status.busy": "2024-12-18T04:24:27.466696Z", "iopub.status.idle": "2024-12-18T04:24:48.675685Z", "shell.execute_reply": "2024-12-18T04:24:48.675098Z", "shell.execute_reply.started": "2024-12-18T04:24:27.466844Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "total uploads: 119369\n", "clips without request id: 203876\n", "clips without request id: 203876 clip_type\n", "upload 90821\n", "concat 57642\n", "stem 28196\n", "edit_crop 14292\n", "concat_infilling 12922\n", "edit_fade 2\n", "edit_speed 1\n", "Name: count, dtype: int64\n", "Clips without request id (concat, uploads...) frac = 0.00716\n" ] } ], "source": [ "print(\"total uploads:\", (clip_df[\"model_name\"] == \"\").sum())\n", "print(\"clips without request id:\", (clip_df[\"request_id\"].isna()).sum())\n", "# the nans are concats, we want to drop them for now\n", "concated_clips = clip_df[\n", " (clip_df[\"clip_type\"] == \"concat\") | (clip_df[\"clip_type\"] == \"concat_infilling\")\n", "].copy()\n", "non_request_clips = clip_df[clip_df[\"request_id\"].isna()].copy()\n", "print(\n", " \"clips without request id:\",\n", " non_request_clips.shape[0],\n", " non_request_clips[\"clip_type\"].value_counts(),\n", ")\n", "# need to kick them out...\n", "clip_df = clip_df[~clip_df[\"request_id\"].isna()]\n", "print(\n", " f\"Clips without request id (concat, uploads...) frac = {concated_clips.shape[0] / total_clip_counts:.5f}\"\n", ")" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:22.833148Z", "start_time": "2024-05-26T00:23:22.094796Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:24:48.676416Z", "iopub.status.busy": "2024-12-18T04:24:48.676265Z", "iopub.status.idle": "2024-12-18T04:24:49.974028Z", "shell.execute_reply": "2024-12-18T04:24:49.973479Z", "shell.execute_reply.started": "2024-12-18T04:24:48.676400Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "chirp-v3p5-engine-s-8: 4327811 (44.85%)\n", "chirp-v4-h-s-32: 3080181 (31.92%)\n", "chirp-v4-h-t-6: 791697 (8.20%)\n", "chirp-v4-up-u-3: 288333 (2.99%)\n", "chirp-v3p5-engine-upload-4: 242076 (2.51%)\n", "chirp-v3p5-engine-t-6: 237170 (2.46%)\n", "chirp-v4-h-s-31: 168000 (1.74%)\n", "chirp-v3-5: 140015 (1.45%)\n", "chirp-v4-engine-b: 107345 (1.11%)\n", "chirp-v4: 56851 (0.59%)\n", "chirp-v3p5-engine-b: 53887 (0.56%)\n", "chirp-v3-engine-i: 51790 (0.54%)\n", "chirp-v3p5-engine-b-r: 49119 (0.51%)\n", "chirp-v2-xxl-alpha: 15693 (0.16%)\n", "chirp-v3p5-engine-short: 13605 (0.14%)\n", "chirp-v4-h-t-6-artist-cfg: 13136 (0.14%)\n", "chirp-v4-up-u-3-c-3: 8091 (0.08%)\n", "chirp-v3-5-short: 2482 (0.03%)\n", "chirp-v3-0: 1649 (0.02%)\n", "chirp-up: 566 (0.01%)\n", "chirp-v4-up-u-2: 358 (0.00%)\n", "chirp-v4-tau: 276 (0.00%)\n", "chirp-v3-5-upload: 115 (0.00%)\n", "chirp-v4-h-s-31-l-30-2: 60 (0.00%)\n", "chirp-v3-5-tau: 48 (0.00%)\n", "chirp-v4-up-u-2-d-2: 34 (0.00%)\n", "chirp-v4-h-api: 34 (0.00%)\n", "chirp-v3.5: 16 (0.00%)\n", "v3.5: 15 (0.00%)\n", "chirp-v4-upload: 3 (0.00%)\n", "chirp-v3.5-0: 2 (0.00%)\n", "chirp-v3-5|chirp-v3-0: 1 (0.00%)\n" ] } ], "source": [ "# check the model conts\n", "print_out_value_counts_nicely(clip_df, \"model_name\")" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:26.317699Z", "start_time": "2024-05-26T00:23:22.835074Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:24:49.974755Z", "iopub.status.busy": "2024-12-18T04:24:49.974601Z", "iopub.status.idle": "2024-12-18T04:25:14.858447Z", "shell.execute_reply": "2024-12-18T04:25:14.857884Z", "shell.execute_reply.started": "2024-12-18T04:24:49.974740Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "pre-filter model type clip_df shape: (9650459, 37)\n", "post-filter model type clip_df shape: (9448457, 37)\n", "chirp-v3p5-engine-s-8: 4327811 (45.80%)\n", "chirp-v4-h-s-32: 3080181 (32.60%)\n", "chirp-v4-h-t-6: 791697 (8.38%)\n", "chirp-v4-up-u-3: 288333 (3.05%)\n", "chirp-v3p5-engine-upload-4: 242076 (2.56%)\n", "chirp-v3p5-engine-t-6: 237170 (2.51%)\n", "chirp-v4-h-s-31: 168000 (1.78%)\n", "chirp-v4-engine-b: 107345 (1.14%)\n", "chirp-v3p5-engine-b: 53887 (0.57%)\n", "chirp-v3-engine-i: 51790 (0.55%)\n", "chirp-v3p5-engine-b-r: 49119 (0.52%)\n", "chirp-v2-xxl-alpha: 15693 (0.17%)\n", "chirp-v3p5-engine-short: 13605 (0.14%)\n", "chirp-v4-h-t-6-artist-cfg: 13136 (0.14%)\n", "chirp-v4-up-u-3-c-3: 8091 (0.09%)\n", "chirp-v4-up-u-2: 358 (0.00%)\n", "chirp-v4-h-s-31-l-30-2: 60 (0.00%)\n", "chirp-v4-up-u-2-d-2: 34 (0.00%)\n", "chirp-v4-h-api: 34 (0.00%)\n", "chirp-v3.5: 16 (0.00%)\n", "v3.5: 15 (0.00%)\n", "chirp-v4-upload: 3 (0.00%)\n", "chirp-v3.5-0: 2 (0.00%)\n", "chirp-v3-5|chirp-v3-0: 1 (0.00%)\n" ] } ], "source": [ "print(\"pre-filter model type clip_df shape:\", clip_df.shape)\n", "clip_df = clip_df[\n", " (clip_df[\"model_name\"] != \"chirp-v3-5\")\n", " & (clip_df[\"model_name\"] != \"chirp-v3-0\")\n", " & (clip_df[\"model_name\"] != \"chirp-v3-5-tau\")\n", " & (clip_df[\"model_name\"] != \"chirp-v3-5-upload\")\n", " & (clip_df[\"model_name\"] != \"chirp-v3-5-short\")\n", " & (clip_df[\"model_name\"] != \"chirp-v4\")\n", " & (clip_df[\"model_name\"] != \"chirp-v4-tau\")\n", " & (clip_df[\"model_name\"] != \"chirp-up\")\n", "]\n", "print(\"post-filter model type clip_df shape:\", clip_df.shape)\n", "print_out_value_counts_nicely(clip_df, \"model_name\")" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "execution": { "iopub.execute_input": "2024-12-18T04:25:14.859150Z", "iopub.status.busy": "2024-12-18T04:25:14.859001Z", "iopub.status.idle": "2024-12-18T04:25:20.595486Z", "shell.execute_reply": "2024-12-18T04:25:20.594913Z", "shell.execute_reply.started": "2024-12-18T04:25:14.859135Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "concat reactions: 86107 unique concat clips: 54638\n", "total concats (70564, 40)\n", "check \n", " reaction_play_count reaction_upvote_count reaction_dislike_count\n", "count 54638.000000 54638.000000 54638.000000\n", "mean 3.441543 0.311999 0.021194\n", "std 49.370871 1.999086 0.149641\n", "min 1.000000 0.000000 0.000000\n", "25% 1.000000 0.000000 0.000000\n", "50% 1.000000 0.000000 0.000000\n", "75% 3.000000 0.000000 0.000000\n", "max 7585.000000 225.000000 7.000000\n", "All concats 70564\n", "total concats with plays 54638\n" ] } ], "source": [ "concated_clips = merge_concat_clips_with_reactions(concated_clips, reaction_df)\n", "# TODO: why so many clips are concats without plays??? -- oh probably they concat multiple times?\n", "print(\"All concats\", concated_clips.shape[0])\n", "concated_clips = concated_clips[concated_clips[\"reaction_play_count\"] > 0]\n", "print(\"total concats with plays\", concated_clips.shape[0])" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:38.974479Z", "start_time": "2024-05-26T00:23:34.385507Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:25:20.596211Z", "iopub.status.busy": "2024-12-18T04:25:20.596063Z", "iopub.status.idle": "2024-12-18T04:25:31.196447Z", "shell.execute_reply": "2024-12-18T04:25:31.195877Z", "shell.execute_reply.started": "2024-12-18T04:25:20.596196Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "19676it [00:01, 18965.31it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "6356bfbf-f645-469a-a4e6-ee56423f4bd7 chirp-v3p5-engine-s-8\n", "7846601c-364d-4ddd-a7f6-7f409b891158 chirp-v3p5-engine-upload-4\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "23467it [00:01, 18912.97it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "924bbd5f-c9d4-4ae7-930c-1ace83ca8344 chirp-v4-h-s-32\n", "6ba5c68a-581c-4eda-aa5f-1f78504ff572 chirp-v4-h-s-32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "32973it [00:01, 18989.78it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "ee95617a-014e-4c57-bea5-bb7878c3ae04 chirp-v4-h-s-32\n", "2e4b9984-d520-4b2b-85c7-656564b6082c chirp-v4-h-s-32\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "51988it [00:02, 18971.03it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "57327cbf-ddbd-4cf8-b5ed-f2305901d300 chirp-v3p5-engine-upload-4\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "54638it [00:02, 18552.10it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "total concat unique clips are: 101422 with error: 410, duplicate 10083 \n", " uploads are in concats 179 frac 0.002\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "concat_clips_ids = get_concat_clip_ids(concated_clips, clip_df, upload_clip_df)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Features" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:40.236690Z", "start_time": "2024-05-26T00:23:39.995713Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:25:31.197190Z", "iopub.status.busy": "2024-12-18T04:25:31.197034Z", "iopub.status.idle": "2024-12-18T04:25:34.899210Z", "shell.execute_reply": "2024-12-18T04:25:34.898626Z", "shell.execute_reply.started": "2024-12-18T04:25:31.197175Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "count 9.448457e+06\n", "mean 1.377585e+02\n", "std 3.347608e+02\n", "min 1.000000e+00\n", "25% 1.000000e+01\n", "50% 2.000000e+01\n", "75% 1.040000e+02\n", "max 3.932000e+03\n", "Name: user_n_clips, dtype: float64\n" ] } ], "source": [ "# set user number of clips generated\n", "clip_df[\"user_n_clips\"] = clip_df[\"user_id\"].map(clip_df[\"user_id\"].value_counts())\n", "print(clip_df[\"user_n_clips\"].describe())" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:44.826860Z", "start_time": "2024-05-26T00:23:40.238330Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:25:34.902647Z", "iopub.status.busy": "2024-12-18T04:25:34.902241Z", "iopub.status.idle": "2024-12-18T04:25:40.308206Z", "shell.execute_reply": "2024-12-18T04:25:40.307628Z", "shell.execute_reply.started": "2024-12-18T04:25:34.902630Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "has upvoted upvoted\n", "False 8937466\n", "True 510991\n", "Name: count, dtype: int64 upvoted\n", "False 0.945918\n", "True 0.054082\n", "Name: proportion, dtype: float64 upvote_count\n", "False 0.942645\n", "True 0.057355\n", "Name: proportion, dtype: float64\n" ] } ], "source": [ "# add upvoted column\n", "clip_df[\"upvoted\"] = clip_df[\"id\"].isin(upvoted_ids)\n", "print(\n", " \"has upvoted\",\n", " clip_df[\"upvoted\"].value_counts(),\n", " clip_df[\"upvoted\"].value_counts(normalize=True),\n", " (clip_df[\"upvote_count\"] >= 1).value_counts(normalize=True),\n", ")\n", "# clip_df = clip_df.drop(columns=['upvote_count'])" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:48.404433Z", "start_time": "2024-05-26T00:23:44.857788Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:25:40.308923Z", "iopub.status.busy": "2024-12-18T04:25:40.308773Z", "iopub.status.idle": "2024-12-18T04:25:49.199597Z", "shell.execute_reply": "2024-12-18T04:25:49.199016Z", "shell.execute_reply.started": "2024-12-18T04:25:40.308909Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "downvoted fraction by category:\n", "False: 9100933 (96.32%)\n", "True: 347524 (3.68%)\n" ] } ], "source": [ "disliked_ids = reaction_df[reaction_df[\"reaction_type\"] == \"D\"][\"clip_id\"].unique()\n", "\n", "clip_df[\"downvoted\"] = clip_df[\"id\"].isin(disliked_ids)\n", "print(\"downvoted fraction by category:\")\n", "print_out_value_counts_nicely(clip_df, \"downvoted\")" ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:56.590022Z", "start_time": "2024-05-26T00:23:48.405668Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:25:49.200313Z", "iopub.status.busy": "2024-12-18T04:25:49.200164Z", "iopub.status.idle": "2024-12-18T04:25:55.486070Z", "shell.execute_reply": "2024-12-18T04:25:55.485492Z", "shell.execute_reply.started": "2024-12-18T04:25:49.200297Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "has_continued fraction by category:\n", "False: 9381700 (99.29%)\n", "True: 66757 (0.71%)\n" ] } ], "source": [ "# add continued column -- uuid and str are not compatible X.x\n", "clip_df[\"has_continued\"] = (\n", " clip_df[\"id\"].astype(str).isin(set(list(has_continued_children_ids)))\n", ")\n", "print(\"has_continued fraction by category:\")\n", "print_out_value_counts_nicely(clip_df, \"has_continued\")" ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "execution": { "iopub.execute_input": "2024-12-18T04:25:55.486779Z", "iopub.status.busy": "2024-12-18T04:25:55.486618Z", "iopub.status.idle": "2024-12-18T04:25:55.690916Z", "shell.execute_reply": "2024-12-18T04:25:55.690446Z", "shell.execute_reply.started": "2024-12-18T04:25:55.486764Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "has upvoted in exp 0.05408\n", "has downvoted out of exp 0.03678\n" ] } ], "source": [ "print(\n", " \"has upvoted in exp\",\n", " # clip_df[in_exp_mask][\"upvoted\"].value_counts(),\n", " round(clip_df[\"upvoted\"].value_counts(normalize=True)[True], 5),\n", " # (clip_df[clip_df[\"in_fe_exp\"]][\"upvote_count\"] >= 1).value_counts(normalize=True),\n", ")\n", "print(\n", " \"has downvoted out of exp\",\n", " # clip_df[out_exp_mask][\"downvoted\"].value_counts(),\n", " round(clip_df[\"downvoted\"].value_counts(normalize=True)[True], 5),\n", ")" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:04.704306Z", "start_time": "2024-05-26T00:23:56.591353Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:25:55.691566Z", "iopub.status.busy": "2024-12-18T04:25:55.691420Z", "iopub.status.idle": "2024-12-18T04:26:01.667507Z", "shell.execute_reply": "2024-12-18T04:26:01.666913Z", "shell.execute_reply.started": "2024-12-18T04:25:55.691552Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "part_of_concat fraction by category:\n", "False: 9373325 (99.20%)\n", "True: 75132 (0.80%)\n", "------------\n", "Model distribution for part_of_concat clips:\n", "chirp-v4-h-s-32: 44.32%\n", "chirp-v3p5-engine-s-8: 20.38%\n", "chirp-v4-h-t-6: 19.08%\n", "chirp-v3p5-engine-upload-4: 4.45%\n", "chirp-v3p5-engine-t-6: 4.26%\n", "chirp-v4-up-u-3: 2.48%\n", "chirp-v4-h-s-31: 2.34%\n", "chirp-v4-engine-b: 0.92%\n", "chirp-v3-engine-i: 0.57%\n", "chirp-v3p5-engine-b: 0.42%\n", "chirp-v3p5-engine-b-r: 0.30%\n", "chirp-v4-h-t-6-artist-cfg: 0.29%\n", "chirp-v2-xxl-alpha: 0.11%\n", "chirp-v4-up-u-3-c-3: 0.07%\n", "chirp-v4-up-u-2: 0.00%\n", "chirp-v4-h-s-31-l-30-2: 0.00%\n" ] } ], "source": [ "# add concat column\n", "clip_df[\"part_of_concat\"] = clip_df[\"id\"].astype(str).isin(concat_clips_ids)\n", "print(\"part_of_concat fraction by category:\")\n", "print_out_value_counts_nicely(clip_df, \"part_of_concat\")\n", "\n", "print(\"------------\")\n", "print(\"Model distribution for part_of_concat clips:\")\n", "for model, fraction in (\n", " clip_df[clip_df[\"part_of_concat\"]][\"model_name\"]\n", " .value_counts(normalize=True)\n", " .items()\n", "):\n", " print(f\"{model}: {fraction:.2%}\")" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:09.954233Z", "start_time": "2024-05-26T00:24:04.705554Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:26:01.668239Z", "iopub.status.busy": "2024-12-18T04:26:01.668084Z", "iopub.status.idle": "2024-12-18T04:26:06.137972Z", "shell.execute_reply": "2024-12-18T04:26:06.137394Z", "shell.execute_reply.started": "2024-12-18T04:26:01.668223Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "has_action fraction by category:\n", "False: 9336228 (98.81%)\n", "True: 112229 (1.19%)\n" ] } ], "source": [ "# verify bots action are all non-empty\n", "action_mask = (\n", " bots_action_df[\"download_audio_count\"]\n", " + bots_action_df[\"download_video_count\"]\n", " + bots_action_df[\"download_audio_wav_count\"]\n", " # + bots_action_df[\"share_count\"] # will remove share cause it can be negative, just can be...\n", ") >= 1\n", "has_action_ids = set(i for i in bots_action_df[action_mask][\"clip_id\"].unique())\n", "clip_df[\"has_action\"] = clip_df[\"id\"].isin(has_action_ids)\n", "print(\"has_action fraction by category:\")\n", "print_out_value_counts_nicely(clip_df, \"has_action\")" ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:14.579841Z", "start_time": "2024-05-26T00:24:09.955568Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:26:06.138706Z", "iopub.status.busy": "2024-12-18T04:26:06.138552Z", "iopub.status.idle": "2024-12-18T04:26:11.558419Z", "shell.execute_reply": "2024-12-18T04:26:11.557847Z", "shell.execute_reply.started": "2024-12-18T04:26:06.138690Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "flagged fraction by category:\n", "False: 9426651 (99.77%)\n", "True: 21806 (0.23%)\n" ] } ], "source": [ "# add downvoted column\n", "clip_df[\"flagged\"] = clip_df[\"id\"].isin(flagged_ids)\n", "print(\"flagged fraction by category:\")\n", "print_out_value_counts_nicely(clip_df, \"flagged\")" ] }, { "cell_type": "code", "execution_count": 28, "metadata": { "execution": { "iopub.execute_input": "2024-12-18T04:26:11.559138Z", "iopub.status.busy": "2024-12-18T04:26:11.558988Z", "iopub.status.idle": "2024-12-18T04:26:11.678003Z", "shell.execute_reply": "2024-12-18T04:26:11.677461Z", "shell.execute_reply.started": "2024-12-18T04:26:11.559123Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "deleted fraction by category:\n", "False: 7924772 (83.87%)\n", "True: 1523685 (16.13%)\n" ] } ], "source": [ "clip_df[\"deleted\"] = clip_df[\"is_deleted\"]\n", "print(\"deleted fraction by category:\")\n", "print_out_value_counts_nicely(clip_df, \"deleted\")" ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:15.382315Z", "start_time": "2024-05-26T00:24:14.581073Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:26:11.678720Z", "iopub.status.busy": "2024-12-18T04:26:11.678571Z", "iopub.status.idle": "2024-12-18T04:26:15.300878Z", "shell.execute_reply": "2024-12-18T04:26:15.300293Z", "shell.execute_reply.started": "2024-12-18T04:26:11.678703Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Total clips: 9,448,457\n", "Must be positive: 701,536 (7.42%)\n", "Definitely not negative: 7,599,011 (80.43%)\n", "Must be negative: 1,849,446 (19.57%)\n" ] } ], "source": [ "# This is probably the most important cell of this notebook -- what are good labels, and not having good label makes it a bad label\n", "must_be_positive_mask = (\n", " (clip_df[\"upvoted\"])\n", " | (clip_df[\"has_action\"])\n", " | (clip_df[\"part_of_concat\"])\n", " | (clip_df[\"is_in_playlist\"])\n", ")\n", "must_be_not_negative_mask = (\n", " (~clip_df[\"downvoted\"]) & (~clip_df[\"deleted\"]) & (~clip_df[\"flagged\"])\n", ")\n", "must_be_negative_mask = (\n", " (clip_df[\"downvoted\"]) | (clip_df[\"flagged\"]) | (clip_df[\"deleted\"])\n", ")\n", "total_clips_count = clip_df.shape[0]\n", "must_be_positive_count = sum(must_be_positive_mask)\n", "definitely_not_negative_count = sum(must_be_not_negative_mask)\n", "must_be_negative_count = sum(must_be_negative_mask)\n", "\n", "print(\n", " f\"Total clips: {total_clips_count:,}\\n\"\n", " f\"Must be positive: {must_be_positive_count:,} ({must_be_positive_count/total_clips_count:.2%})\\n\"\n", " f\"Definitely not negative: {definitely_not_negative_count:,} ({definitely_not_negative_count/total_clips_count:.2%})\\n\"\n", " f\"Must be negative: {must_be_negative_count:,} ({must_be_negative_count/total_clips_count:.2%})\"\n", ")" ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:31.095990Z", "start_time": "2024-05-26T00:24:15.383572Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:26:15.301710Z", "iopub.status.busy": "2024-12-18T04:26:15.301558Z", "iopub.status.idle": "2024-12-18T04:27:08.101207Z", "shell.execute_reply": "2024-12-18T04:27:08.100583Z", "shell.execute_reply.started": "2024-12-18T04:26:15.301695Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Liked requests: 535,168\n", "Not liked requests: 4,694,966\n", "Requests with preference paired generations: 409,749\n", "Percentage of total unique requests: 8.50%\n" ] } ], "source": [ "mask = must_be_positive_mask & must_be_not_negative_mask\n", "total_unique_requests = clip_df[\"request_id\"].nunique()\n", "liked_requests = clip_df[mask][\"request_id\"].unique() # requests with at least 1 like\n", "unliked_requests = clip_df[~mask][\"request_id\"].unique() # requests without like\n", "has_liked_requests = set(liked_requests).intersection(\n", " set(unliked_requests)\n", ") # the request must have 1 like and one without like\n", "print(f\"Liked requests: {len(liked_requests):,}\")\n", "print(f\"Not liked requests: {len(unliked_requests):,}\")\n", "print(f\"Requests with preference paired generations: {len(has_liked_requests):,}\")\n", "print(\n", " f\"Percentage of total unique requests: {len(has_liked_requests) / total_unique_requests:.2%}\"\n", ")" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "execution": { "iopub.execute_input": "2024-12-18T04:27:08.101951Z", "iopub.status.busy": "2024-12-18T04:27:08.101793Z", "iopub.status.idle": "2024-12-18T04:27:44.640011Z", "shell.execute_reply": "2024-12-18T04:27:44.639413Z", "shell.execute_reply.started": "2024-12-18T04:27:08.101935Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Disliked requests: 1,097,043\n", "Not disliked requests: 4,038,953\n", "Requests with preference paired generations: 315,611\n", "Percentage of total unique requests: 6.55%\n" ] } ], "source": [ "# introduce a negative preference count\n", "has_disliked_half_requests = clip_df[must_be_negative_mask][\n", " \"request_id\"\n", "].unique() # requests with at least 1 dislike\n", "not_have_disliked_requests = clip_df[~must_be_negative_mask][\n", " \"request_id\"\n", "].unique() # request without dislike\n", "has_disliked_requests = set(has_disliked_half_requests).intersection(\n", " set(not_have_disliked_requests)\n", ") # the request must have 1 dislike and one without dislike\n", "print(f\"Disliked requests: {len(has_disliked_half_requests):,}\")\n", "print(f\"Not disliked requests: {len(not_have_disliked_requests):,}\")\n", "print(f\"Requests with preference paired generations: {len(has_disliked_requests):,}\")\n", "print(\n", " f\"Percentage of total unique requests: {len(has_disliked_requests) / total_unique_requests:.2%}\"\n", ")" ] }, { "cell_type": "code", "execution_count": 32, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:31.099372Z", "start_time": "2024-05-26T00:24:31.097244Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:27:44.640742Z", "iopub.status.busy": "2024-12-18T04:27:44.640593Z", "iopub.status.idle": "2024-12-18T04:27:44.871525Z", "shell.execute_reply": "2024-12-18T04:27:44.870949Z", "shell.execute_reply.started": "2024-12-18T04:27:44.640727Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Total selected pairs of requests: 630,435\n", "Percentage of total unique requests: 13.08%\n" ] } ], "source": [ "requests = has_liked_requests.union(has_disliked_requests)\n", "print(f\"Total selected pairs of requests: {len(requests):,}\")\n", "print(\n", " f\"Percentage of total unique requests: {len(requests) / total_unique_requests:.2%}\"\n", ")" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:31.239254Z", "start_time": "2024-05-26T00:24:31.100389Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:27:44.872248Z", "iopub.status.busy": "2024-12-18T04:27:44.872099Z", "iopub.status.idle": "2024-12-18T04:27:45.287065Z", "shell.execute_reply": "2024-12-18T04:27:45.286481Z", "shell.execute_reply.started": "2024-12-18T04:27:44.872233Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Difference in preference counts:\n", "0: 6,948,284 (73.54%)\n", "-1: 1,849,446 (19.57%)\n", "1: 650,727 (6.89%)\n" ] } ], "source": [ "# this used to be a terrible bug...X.x\n", "assert mask.shape[0] == clip_df.shape[0]\n", "clip_df[\"pos_preference\"] = mask\n", "clip_df[\"neg_preference\"] = must_be_negative_mask\n", "# note that this is along the same row, so a positive clip can't be negative\n", "clip_df[\"diff_preference\"] = clip_df[\"pos_preference\"].astype(int) - clip_df[\n", " \"neg_preference\"\n", "].astype(int)\n", "print(\"Difference in preference counts:\")\n", "value_counts = clip_df[\"diff_preference\"].value_counts()\n", "total = value_counts.sum()\n", "for value, count in value_counts.items():\n", " fraction = count / total\n", " print(f\"{value}: {count:,} ({fraction:.2%})\")" ] }, { "cell_type": "code", "execution_count": 34, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:37.322031Z", "start_time": "2024-05-26T00:24:31.240829Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:27:45.287776Z", "iopub.status.busy": "2024-12-18T04:27:45.287625Z", "iopub.status.idle": "2024-12-18T04:27:55.866639Z", "shell.execute_reply": "2024-12-18T04:27:55.866049Z", "shell.execute_reply.started": "2024-12-18T04:27:45.287761Z" } }, "outputs": [], "source": [ "# creation of interesting_clips\n", "interesting_clips = clip_df[clip_df[\"request_id\"].isin(requests)].copy()" ] }, { "cell_type": "code", "execution_count": 35, "metadata": { "execution": { "iopub.execute_input": "2024-12-18T04:27:55.867375Z", "iopub.status.busy": "2024-12-18T04:27:55.867221Z", "iopub.status.idle": "2024-12-18T04:28:08.777931Z", "shell.execute_reply": "2024-12-18T04:28:08.777412Z", "shell.execute_reply.started": "2024-12-18T04:27:55.867360Z" } }, "outputs": [ { "data": { "text/html": [ "
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\n", "
" ], "text/plain": [ " request_id pos_preference neg_preference diff_preference\n", "0 000020bb-54ad-4a46-b0bc-1fadc31f2666 False True -1\n", "1 000020bb-54ad-4a46-b0bc-1fadc31f2666 True False 1\n", "2 00002fa7-9769-463f-988e-436c1dde8622 False True -1\n", "3 00002fa7-9769-463f-988e-436c1dde8622 False False 0\n", "4 000040a3-cffc-41cb-a814-d60238f72613 False False 0\n", "5 000040a3-cffc-41cb-a814-d60238f72613 True False 1" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "interesting_clips = interesting_clips.sort_values(\n", " by=[\"request_id\", \"diff_preference\"]\n", ").reset_index()\n", "interesting_clips[\n", " [\"request_id\", \"pos_preference\", \"neg_preference\", \"diff_preference\"]\n", "].head(n=6)" ] }, { "cell_type": "code", "execution_count": 36, "metadata": { "execution": { "iopub.execute_input": "2024-12-18T04:28:08.778636Z", "iopub.status.busy": "2024-12-18T04:28:08.778491Z", "iopub.status.idle": "2024-12-18T04:28:09.890860Z", "shell.execute_reply": "2024-12-18T04:28:09.890311Z", "shell.execute_reply.started": "2024-12-18T04:28:08.778622Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Difference 0: 535,510 (42.47%)\n", "Difference 1: 409,749 (32.50%)\n", "Difference -1: 315,611 (25.03%)\n" ] } ], "source": [ "# this is a mix now\n", "value_counts = interesting_clips[\"diff_preference\"].value_counts()\n", "total = value_counts.sum()\n", "for value, count in value_counts.items():\n", " fraction = count / total\n", " print(f\"Difference {value}: {count:,} ({fraction:.2%})\")" ] }, { "cell_type": "code", "execution_count": 37, "metadata": { "execution": { "iopub.execute_input": "2024-12-18T04:28:09.891581Z", "iopub.status.busy": "2024-12-18T04:28:09.891421Z", "iopub.status.idle": "2024-12-18T04:28:10.012673Z", "shell.execute_reply": "2024-12-18T04:28:10.012166Z", "shell.execute_reply.started": "2024-12-18T04:28:09.891565Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Value 1.0: 535,510 (84.94%)\n", "Value 2.0: 94,925 (15.06%)\n" ] } ], "source": [ "diff_series = interesting_clips[\"diff_preference\"].diff()\n", "value_counts = diff_series[1::2].value_counts()\n", "total = value_counts.sum()\n", "for value, count in value_counts.items():\n", " fraction = count / total\n", " print(f\"Value {value}: {count:,} ({fraction:.2%})\")\n", "# 1 is pos, not neg pair or nothing, neg; 2 is pos / neg (hence the larger difference)\n", "# there are only two values for this positive pair\n", "assert diff_series[1::2].nunique() == 2" ] }, { "cell_type": "code", "execution_count": 38, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:38.960130Z", "start_time": "2024-05-26T00:24:37.323369Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:28:10.013334Z", "iopub.status.busy": "2024-12-18T04:28:10.013189Z", "iopub.status.idle": "2024-12-18T04:28:25.204143Z", "shell.execute_reply": "2024-12-18T04:28:25.203531Z", "shell.execute_reply.started": "2024-12-18T04:28:10.013320Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of unique request_ids: 630,435\n", "Number of unique ids: 1,260,870\n", "Validation passed!\n" ] } ], "source": [ "# assign the labels now\n", "interesting_clips[\"preference\"] = interesting_clips.index % 2 == 1\n", "# get df of requests -- let's move on!\n", "print(f\"Number of unique request_ids: {interesting_clips['request_id'].nunique():,}\")\n", "print(f\"Number of unique ids: {interesting_clips['id'].nunique():,}\")\n", "validate_preference_data(interesting_clips)" ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:43.332222Z", "start_time": "2024-05-26T00:24:43.166461Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:28:25.204897Z", "iopub.status.busy": "2024-12-18T04:28:25.204744Z", "iopub.status.idle": "2024-12-18T04:28:25.224874Z", "shell.execute_reply": "2024-12-18T04:28:25.224424Z", "shell.execute_reply.started": "2024-12-18T04:28:25.204881Z" } }, "outputs": [], "source": [ "# # listen to some pairs\n", "# test_requests = interesting_clips[\"request_id\"].sample(10)\n", "\n", "# for i in range(1):\n", "# rows = interesting_clips[interesting_clips[\"request_id\"] == test_requests.iloc[i]]\n", "# assert rows.shape[0] == 2\n", "# # Audio.from_s3(f\"s3://suno-data-uploads/studio/uploads/{row['s3_id']}.mp3\").play()\n", "# # sort by likes\n", "# rows = rows.sort_values(\"upvoted\", ascending=True)\n", "# print(rows.iloc[0][\"prompt_text\"])\n", "# print(rows.iloc[0][\"metadata\"])\n", "# for _, row in rows.iterrows():\n", "# print(row[\"id\"], row[\"preference\"], row[\"upvoted\"])\n", "# Audio.from_s3(\n", "# f\"s3://suno-data-uploads/studio/uploads/{row['s3_id']}.mp3\"\n", "# ).play()\n", "# with open_from_s3(\n", "# f\"s3://suno-data-uploads/studio/uploads/{row['s3_id']}.npz\", as_binary=True\n", "# ) as f:\n", "# # read numpy array\n", "# npz_a = np.load(f)\n", "# if \"v1_raw\" in npz_a:\n", "# a = np.load(f)[\"v1_raw\"]\n", "# elif \"v3.0_raw\" in npz_a:\n", "# a = np.load(f)[\"v3.0_raw\"]\n", "# else:\n", "# print(\"npz_a\", npz_a)\n", "# raise ValueError\n", "# print(a.shape)\n", "# print()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Further cuts and selections" ] }, { "cell_type": "code", "execution_count": 40, "metadata": { "execution": { "iopub.execute_input": "2024-12-18T04:28:25.225505Z", "iopub.status.busy": "2024-12-18T04:28:25.225366Z", "iopub.status.idle": "2024-12-18T04:29:13.349013Z", "shell.execute_reply": "2024-12-18T04:29:13.348429Z", "shell.execute_reply.started": "2024-12-18T04:28:25.225492Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of interesting clips: 1,260,870\n", "Unique request and clip counts in interesting_clips:\n", "Request IDs: 630,435\n", "Clip IDs: 1,260,870\n" ] } ], "source": [ "# need the reaction play counts\n", "# Filter reaction_df for relevant clip_ids\n", "partial_reaction_df = reaction_df[\n", " reaction_df[\"clip_id\"].isin(set(interesting_clips[\"id\"]))\n", "].copy()\n", "\n", "# Calculate total play counts\n", "total_play_counts = (\n", " partial_reaction_df.groupby(\"clip_id\")[\"play_count\"].sum().reset_index()\n", ")\n", "total_play_counts = total_play_counts.rename(\n", " columns={\"clip_id\": \"id\", \"play_count\": \"reaction_play_count\"}\n", ")\n", "\n", "# Calculate pro user play counts\n", "pro_play_counts = (\n", " partial_reaction_df[partial_reaction_df[\"is_pro_user\"]]\n", " .groupby(\"clip_id\")[\"play_count\"]\n", " .sum()\n", " .reset_index()\n", ")\n", "pro_play_counts = pro_play_counts.rename(\n", " columns={\"clip_id\": \"id\", \"play_count\": \"reaction_pro_play_count\"}\n", ")\n", "\n", "# Merge with user_intersting_clips\n", "interesting_clips = interesting_clips.merge(total_play_counts, on=\"id\", how=\"left\")\n", "interesting_clips = interesting_clips.merge(pro_play_counts, on=\"id\", how=\"left\")\n", "\n", "print(f\"Number of interesting clips: {len(interesting_clips):,}\")\n", "# Get unique counts for request_id and id\n", "unique_request_ids = interesting_clips[\"request_id\"].nunique()\n", "unique_clip_ids = interesting_clips[\"id\"].nunique()\n", "\n", "# Print the results in a formatted manner\n", "print(\"Unique request and clip counts in interesting_clips:\")\n", "print(f\"{'Request IDs:':<15} {unique_request_ids:,}\")\n", "print(f\"{'Clip IDs:':<15} {unique_clip_ids:,}\")" ] }, { "cell_type": "code", "execution_count": 41, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:43.737067Z", "start_time": "2024-05-26T00:24:43.563216Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:29:13.349763Z", "iopub.status.busy": "2024-12-18T04:29:13.349604Z", "iopub.status.idle": "2024-12-18T04:29:14.636461Z", "shell.execute_reply": "2024-12-18T04:29:14.635893Z", "shell.execute_reply.started": "2024-12-18T04:29:13.349747Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Preference counts and fractions by batch index:\n", "--------------------------------------------------\n", "Batch Index: 0\n", " Preference False: Count: 321,153 Fraction: 50.94%\n", " Preference True: Count: 309,282 Fraction: 49.06%\n", "\n", "Batch Index: 1\n", " Preference False: Count: 309,282 Fraction: 49.06%\n", " Preference True: Count: 321,153 Fraction: 50.94%\n", "\n" ] } ], "source": [ "preference_counts = interesting_clips.groupby(\"batch_index\")[\n", " \"preference\"\n", "].value_counts()\n", "total_counts = preference_counts.groupby(level=0).sum()\n", "\n", "print(\"Preference counts and fractions by batch index:\")\n", "print(\"-\" * 50)\n", "for batch_index in [0, 1]:\n", " print(f\"Batch Index: {batch_index}\")\n", " for preference in [False, True]:\n", " count = preference_counts[batch_index, preference]\n", " fraction = count / total_counts[batch_index]\n", " print(f\" Preference {preference}: Count: {count:,} Fraction: {fraction:.2%}\")\n", " print()" ] }, { "cell_type": "code", "execution_count": 42, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:44.304573Z", "start_time": "2024-05-26T00:24:43.973218Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:29:14.637201Z", "iopub.status.busy": "2024-12-18T04:29:14.637044Z", "iopub.status.idle": "2024-12-18T04:29:14.876503Z", "shell.execute_reply": "2024-12-18T04:29:14.875994Z", "shell.execute_reply.started": "2024-12-18T04:29:14.637185Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "chirp-v4-h-s-32: 487716 (38.68%)\n", "chirp-v3p5-engine-s-8: 428222 (33.96%)\n", "chirp-v4-h-t-6: 155932 (12.37%)\n", "chirp-v4-up-u-3: 67834 (5.38%)\n", "chirp-v3p5-engine-t-6: 44586 (3.54%)\n", "chirp-v3p5-engine-upload-4: 29122 (2.31%)\n", "chirp-v4-h-s-31: 25954 (2.06%)\n", "chirp-v3-engine-i: 4918 (0.39%)\n", "chirp-v4-engine-b: 4574 (0.36%)\n", "chirp-v4-h-t-6-artist-cfg: 2906 (0.23%)\n", "chirp-v3p5-engine-b: 2086 (0.17%)\n", "chirp-v3p5-engine-b-r: 1936 (0.15%)\n", "chirp-v2-xxl-alpha: 1934 (0.15%)\n", "chirp-v4-up-u-3-c-3: 1706 (0.14%)\n", "chirp-v3p5-engine-short: 1346 (0.11%)\n", "chirp-v4-up-u-2: 78 (0.01%)\n", "chirp-v4-h-s-31-l-30-2: 12 (0.00%)\n", "chirp-v4-up-u-2-d-2: 8 (0.00%)\n" ] } ], "source": [ "print_out_value_counts_nicely(interesting_clips, \"model_name\")" ] }, { "cell_type": "code", "execution_count": 43, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:44.533983Z", "start_time": "2024-05-26T00:24:44.305722Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:29:14.877155Z", "iopub.status.busy": "2024-12-18T04:29:14.877005Z", "iopub.status.idle": "2024-12-18T04:29:15.050303Z", "shell.execute_reply": "2024-12-18T04:29:15.049781Z", "shell.execute_reply.started": "2024-12-18T04:29:14.877141Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Time Validation:\n", "--------------------\n", "Interesting Clips:\n", " Earliest: 2024-12-16 20:40:00.222000\n", " Latest: 2024-12-18 16:59:59.718000\n", "\n", "All Clips:\n", " Earliest: 2024-12-16 20:40:00.001000\n", " Latest: 2024-12-18 16:59:59.964000\n" ] } ], "source": [ "print(\"Time Validation:\")\n", "print(\"-\" * 20)\n", "print(\"Interesting Clips:\")\n", "print(f\" Earliest: {interesting_clips['created_at'].min()}\")\n", "print(f\" Latest: {interesting_clips['created_at'].max()}\")\n", "print(\"\\nAll Clips:\")\n", "print(f\" Earliest: {clip_df['created_at'].min()}\")\n", "print(f\" Latest: {clip_df['created_at'].max()}\")" ] }, { "cell_type": "code", "execution_count": 44, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:50.674838Z", "start_time": "2024-05-26T00:24:46.366677Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:29:15.050993Z", "iopub.status.busy": "2024-12-18T04:29:15.050846Z", "iopub.status.idle": "2024-12-18T04:29:22.277945Z", "shell.execute_reply": "2024-12-18T04:29:22.277370Z", "shell.execute_reply.started": "2024-12-18T04:29:15.050978Z" } }, "outputs": [], "source": [ "# make sure we sort here before proceed\n", "interesting_clips = interesting_clips.sort_values(by=[\"request_id\", \"preference\"])" ] }, { "cell_type": "code", "execution_count": 45, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:51.600621Z", "start_time": "2024-05-26T00:24:50.676186Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:29:22.278703Z", "iopub.status.busy": "2024-12-18T04:29:22.278545Z", "iopub.status.idle": "2024-12-18T04:29:25.052784Z", "shell.execute_reply": "2024-12-18T04:29:25.052223Z", "shell.execute_reply.started": "2024-12-18T04:29:22.278687Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Ratio of preferred clips to total clips for each model:\n", "------------------------------------------------------------\n", "chirp-v2-xxl-alpha 6.16% ± 0.19%\n", "chirp-v3-5|chirp-v3-0 nan% ± nan%\n", "chirp-v3-engine-i 4.75% ± 0.09%\n", "chirp-v3.5 nan% ± nan%\n", "chirp-v3.5-0 nan% ± nan%\n", "chirp-v3p5-engine-b 1.94% ± 0.06%\n", "chirp-v3p5-engine-b-r 1.97% ± 0.06%\n", "chirp-v3p5-engine-s-8 4.95% ± 0.01%\n", "chirp-v3p5-engine-short 4.95% ± 0.19%\n", "chirp-v3p5-engine-t-6 9.40% ± 0.06%\n", "chirp-v3p5-engine-upload-4 6.02% ± 0.05%\n", "chirp-v4-engine-b 2.13% ± 0.04%\n", "chirp-v4-h-api nan% ± nan%\n", "chirp-v4-h-s-31 7.35% ± 0.06%\n", "chirp-v4-h-s-31-l-30-2 10.00% ± 3.87%\n", "chirp-v4-h-s-32 7.94% ± 0.02%\n", "chirp-v4-h-t-6 9.88% ± 0.03%\n", "chirp-v4-h-t-6-artist-cfg 9.24% ± 0.25%\n", "chirp-v4-up-u-2 11.17% ± 1.67%\n", "chirp-v4-up-u-2-d-2 8.82% ± 4.86%\n", "chirp-v4-up-u-3 11.75% ± 0.06%\n", "chirp-v4-up-u-3-c-3 11.01% ± 0.35%\n", "chirp-v4-upload nan% ± nan%\n", "v3.5 nan% ± nan%\n" ] } ], "source": [ "# Calculate the ratio of preferred clips to total clips for each model\n", "clip_df_model_counts = clip_df[\"model_name\"].value_counts()\n", "preference_ratio = (\n", " interesting_clips[interesting_clips[\"preference\"]][\"model_name\"].value_counts()\n", " / clip_df_model_counts\n", ")\n", "\n", "# Print the results in a formatted manner\n", "print(\"Ratio of preferred clips to total clips for each model:\")\n", "print(\"-\" * 60)\n", "for model, ratio in preference_ratio.items():\n", " n = clip_df_model_counts[model]\n", " uncertainty = (ratio * (1 - ratio) / n) ** 0.5\n", " print(f\"{model:<30} {ratio:.2%} ± {uncertainty:.2%}\")" ] }, { "cell_type": "code", "execution_count": 46, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:56.302599Z", "start_time": "2024-05-26T00:24:51.601863Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:29:25.053494Z", "iopub.status.busy": "2024-12-18T04:29:25.053344Z", "iopub.status.idle": "2024-12-18T04:29:43.429926Z", "shell.execute_reply": "2024-12-18T04:29:43.429345Z", "shell.execute_reply.started": "2024-12-18T04:29:25.053479Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "len pos models: 630435\n", "differing counts: 30506\n", "chirp-v2-xxl-alpha_win_over_chirp-v2-xxl-alpha, win ratio 1.000, (1.000, 1.000), counts 967, total 967.\n", "chirp-v3-engine-i_win_over_chirp-v3-engine-i, win ratio 1.000, (1.000, 1.000), counts 2459, total 2459.\n", "chirp-v3p5-engine-b-r_win_over_chirp-v3p5-engine-b-r, win ratio 1.000, (1.000, 1.000), counts 968, total 968.\n", "chirp-v3p5-engine-b_win_over_chirp-v3p5-engine-b, win ratio 1.000, (1.000, 1.000), counts 1043, total 1043.\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-8, win ratio 1.000, (1.000, 1.000), counts 214111, total 214111.\n", "chirp-v3p5-engine-short_win_over_chirp-v3p5-engine-short, win ratio 1.000, (1.000, 1.000), counts 673, total 673.\n", "chirp-v3p5-engine-t-6_win_over_chirp-v3p5-engine-t-6, win ratio 1.000, (1.000, 1.000), counts 22293, total 22293.\n", "chirp-v3p5-engine-upload-4_win_over_chirp-v3p5-engine-upload-4, win ratio 1.000, (1.000, 1.000), counts 14561, total 14561.\n", "chirp-v4-engine-b_win_over_chirp-v4-engine-b, win ratio 1.000, (1.000, 1.000), counts 2287, total 2287.\n", "chirp-v4-h-s-31-l-30-2_win_over_chirp-v4-h-s-31, win ratio 0.500, (0.217, 0.783), counts 6, total 12.\n", "chirp-v4-h-s-31_win_over_chirp-v4-h-s-31, win ratio 1.000, (1.000, 1.000), counts 34, total 34.\n", "chirp-v4-h-s-31_win_over_chirp-v4-h-s-31-l-30-2, win ratio 0.500, (0.217, 0.783), counts 6, total 12.\n", "chirp-v4-h-s-31_win_over_chirp-v4-h-s-32, win ratio 0.475, (0.469, 0.482), counts 12302, total 25874.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-31, win ratio 0.525, (0.518, 0.531), counts 13572, total 25874.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32, win ratio 1.000, (1.000, 1.000), counts 230921, total 230921.\n", "chirp-v4-h-t-6-artist-cfg_win_over_chirp-v4-h-t-6, win ratio 0.418, (0.400, 0.436), counts 1214, total 2906.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6, win ratio 1.000, (1.000, 1.000), counts 76513, total 76513.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6-artist-cfg, win ratio 0.582, (0.564, 0.600), counts 1692, total 2906.\n", "chirp-v4-up-u-2-d-2_win_over_chirp-v4-up-u-2, win ratio 0.375, (0.040, 0.710), counts 3, total 8.\n", "chirp-v4-up-u-2_win_over_chirp-v4-up-u-2, win ratio 1.000, (1.000, 1.000), counts 35, total 35.\n", "chirp-v4-up-u-2_win_over_chirp-v4-up-u-2-d-2, win ratio 0.625, (0.290, 0.960), counts 5, total 8.\n", "chirp-v4-up-u-3-c-3_win_over_chirp-v4-up-u-3, win ratio 0.522, (0.499, 0.546), counts 891, total 1706.\n", "chirp-v4-up-u-3_win_over_chirp-v4-up-u-3, win ratio 1.000, (1.000, 1.000), counts 33064, total 33064.\n", "chirp-v4-up-u-3_win_over_chirp-v4-up-u-3-c-3, win ratio 0.478, (0.454, 0.501), counts 815, total 1706.\n", "tournament players: ['chirp-v4-h-s-31', 'chirp-v4-h-s-31-l-30-2', 'chirp-v4-h-s-32', 'chirp-v4-h-t-6', 'chirp-v4-h-t-6-artist-cfg', 'chirp-v4-up-u-2', 'chirp-v4-up-u-2-d-2', 'chirp-v4-up-u-3', 'chirp-v4-up-u-3-c-3']\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "100%|██████████| 1000/1000 [00:01<00:00, 510.57it/s]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "ELOs\n", "chirp-v4-h-s-31: 994.7, (919, 1082)\n", "chirp-v4-h-s-31-l-30-2: 993.6, (820, 1150)\n", "chirp-v4-h-s-32: 1011.7, (937, 1099)\n", "chirp-v4-h-t-6: 1028.8, (1023, 1036)\n", "chirp-v4-h-t-6-artist-cfg: 971.2, (964, 977)\n", "chirp-v4-up-u-2: 1044.3, (905, 1925)\n", "chirp-v4-up-u-2-d-2: 955.7, (93, 1095)\n", "chirp-v4-up-u-3: 992.3, (984, 1001)\n", "chirp-v4-up-u-3-c-3: 1007.7, (999, 1016)\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "get_preference_counts(interesting_clips)" ] }, { "cell_type": "code", "execution_count": 47, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:57.443236Z", "start_time": "2024-05-26T00:24:56.306473Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:29:43.430694Z", "iopub.status.busy": "2024-12-18T04:29:43.430536Z", "iopub.status.idle": "2024-12-18T04:29:44.787319Z", "shell.execute_reply": "2024-12-18T04:29:44.786804Z", "shell.execute_reply.started": "2024-12-18T04:29:43.430679Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "<__array_function__ internals>:180: RuntimeWarning: Converting input from bool to for compatibility.\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_clip_basic_distributions(interesting_clips)" ] }, { "cell_type": "code", "execution_count": 48, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:58.153310Z", "start_time": "2024-05-26T00:24:57.858363Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:29:44.788059Z", "iopub.status.busy": "2024-12-18T04:29:44.787907Z", "iopub.status.idle": "2024-12-18T04:29:44.813041Z", "shell.execute_reply": "2024-12-18T04:29:44.812581Z", "shell.execute_reply.started": "2024-12-18T04:29:44.788043Z" } }, "outputs": [], "source": [ "# FUCK THIS FOR NOW\n", "# MAX_PREFERENCE_PER_USER = 400\n", "# grouped_interesting_clips = interesting_clips.groupby([\"user_id\"])\n", "# user_top_df = (\n", "# interesting_clips.sort_values(\n", "# [\"preference\", \"upvote_count\", \"part_of_concat\", \"is_in_playlist\"], ascending=False\n", "# )\n", "# .groupby(\"user_id\")\n", "# .head(MAX_PREFERENCE_PER_USER)\n", "# )\n", "# print(user_top_df.shape, interesting_clips.shape)\n", "\n", "# user_top_requests = user_top_df[\"request_id\"].unique()\n", "# user_intersting_clips = interesting_clips[\n", "# interesting_clips[\"request_id\"].isin(user_top_requests)\n", "# ].copy()\n", "# print(user_intersting_clips.shape)" ] }, { "cell_type": "code", "execution_count": 49, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:58.890520Z", "start_time": "2024-05-26T00:24:58.154350Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:29:44.813680Z", "iopub.status.busy": "2024-12-18T04:29:44.813540Z", "iopub.status.idle": "2024-12-18T04:30:05.552699Z", "shell.execute_reply": "2024-12-18T04:30:05.552117Z", "shell.execute_reply.started": "2024-12-18T04:29:44.813666Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of clips in interesting_clips:\n", "1,260,870\n", "Number of clips in user_interesting_clips:\n", "1,165,132\n", "Ratio of preferred clips to total clips for each model:\n", "------------------------------------------------------------\n", "chirp-v2-xxl-alpha nan% ± nan%\n", "chirp-v3-5|chirp-v3-0 nan% ± nan%\n", "chirp-v3-engine-i nan% ± nan%\n", "chirp-v3.5 nan% ± nan%\n", "chirp-v3.5-0 nan% ± nan%\n", "chirp-v3p5-engine-b 1.23% ± 0.05%\n", "chirp-v3p5-engine-b-r 1.30% ± 0.05%\n", "chirp-v3p5-engine-s-8 4.57% ± 0.01%\n", "chirp-v3p5-engine-short 3.11% ± 0.15%\n", "chirp-v3p5-engine-t-6 8.96% ± 0.06%\n", "chirp-v3p5-engine-upload-4 5.74% ± 0.05%\n", "chirp-v4-engine-b 1.82% ± 0.04%\n", "chirp-v4-h-api nan% ± nan%\n", "chirp-v4-h-s-31 6.81% ± 0.06%\n", "chirp-v4-h-s-31-l-30-2 10.00% ± 3.87%\n", "chirp-v4-h-s-32 7.41% ± 0.01%\n", "chirp-v4-h-t-6 9.39% ± 0.03%\n", "chirp-v4-h-t-6-artist-cfg 8.53% ± 0.24%\n", "chirp-v4-up-u-2 11.17% ± 1.67%\n", "chirp-v4-up-u-2-d-2 8.82% ± 4.86%\n", "chirp-v4-up-u-3 10.48% ± 0.06%\n", "chirp-v4-up-u-3-c-3 9.03% ± 0.32%\n", "chirp-v4-upload nan% ± nan%\n", "v3.5 nan% ± nan%\n" ] } ], "source": [ "# subselect interesting clips\n", "interesting_clips_masks = (interesting_clips[\"model_name\"].str.contains(\"v3p5|v4\")) & (\n", " interesting_clips[\"reaction_play_count\"] > 0\n", ")\n", "# make sure we have pairs\n", "extra_compare_mask = interesting_clips[interesting_clips_masks][\"request_id\"].isin(\n", " interesting_clips[interesting_clips_masks][\"request_id\"]\n", " .value_counts()\n", " .index[interesting_clips[interesting_clips_masks][\"request_id\"].value_counts() == 2]\n", ")\n", "user_intersting_clips = interesting_clips[\n", " interesting_clips_masks & extra_compare_mask\n", "].copy()\n", "\n", "print(\"Number of clips in interesting_clips:\")\n", "print(f\"{interesting_clips.shape[0]:,}\")\n", "print(\"Number of clips in user_interesting_clips:\")\n", "print(f\"{user_intersting_clips.shape[0]:,}\")\n", "# Calculate the ratio of preferred clips to total clips for each model\n", "preference_ratio = (\n", " user_intersting_clips[user_intersting_clips[\"preference\"]][\n", " \"model_name\"\n", " ].value_counts()\n", " / clip_df_model_counts\n", ")\n", "\n", "# Print the results in a formatted manner\n", "print(\"Ratio of preferred clips to total clips for each model:\")\n", "print(\"-\" * 60)\n", "for model, ratio in preference_ratio.items():\n", " n = clip_df_model_counts[model]\n", " uncertainty = (ratio * (1 - ratio) / n) ** 0.5\n", " print(f\"{model:<30} {ratio:.2%} ± {uncertainty:.2%}\")" ] }, { "cell_type": "code", "execution_count": 50, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:59.204547Z", "start_time": "2024-05-26T00:24:58.891851Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:30:05.553444Z", "iopub.status.busy": "2024-12-18T04:30:05.553282Z", "iopub.status.idle": "2024-12-18T04:30:05.948295Z", "shell.execute_reply": "2024-12-18T04:30:05.947773Z", "shell.execute_reply.started": "2024-12-18T04:30:05.553428Z" } }, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Calculate the number of preferences per user\n", "preferences_per_user = user_intersting_clips[\"user_id\"].value_counts()\n", "\n", "# Determine the maximum number of preferences\n", "max_preferences = preferences_per_user.max()\n", "\n", "# Choose bins using Sturges' rule, but ensure a minimum of 15 bins and a maximum of 30\n", "n_bins = max(30, min(100, int(np.ceil(np.log2(len(preferences_per_user)) + 1))))\n", "\n", "# Calculate bin edges using a linear scale\n", "bin_edges = np.linspace(preferences_per_user.min(), max_preferences, n_bins)\n", "\n", "plt.figure(figsize=(10, 6))\n", "plt.hist(preferences_per_user, bins=bin_edges, edgecolor=\"black\")\n", "plt.yscale(\"log\")\n", "plt.xlabel(\"Number of preferences per user\")\n", "plt.ylabel(\"Number of users (log scale)\")\n", "plt.title(\"Distribution of User Preferences\")\n", "plt.grid(axis=\"both\", linestyle=\"--\", alpha=0.7)\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 51, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:59.207707Z", "start_time": "2024-05-26T00:24:59.205659Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:30:05.949029Z", "iopub.status.busy": "2024-12-18T04:30:05.948867Z", "iopub.status.idle": "2024-12-18T04:30:06.747324Z", "shell.execute_reply": "2024-12-18T04:30:06.746746Z", "shell.execute_reply.started": "2024-12-18T04:30:05.949013Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Summary of user_interesting_clips:\n", "Total requests: 1,165,132\n", "Unique clips: 582,566\n", "Fraction of total clips: 11.82%\n", "Time Validation:\n", "Earliest timestamp: 2024-12-16 20:40:00.222000\n", "Latest timestamp: 2024-12-18 15:59:23.764000\n", "Earliest timestamp: 2024-12-16 20:40:00.791000\n", "Latest timestamp: 2024-12-18 15:57:59.490000\n" ] } ], "source": [ "print(\"Summary of user_interesting_clips:\")\n", "print(f\"Total requests: {user_intersting_clips.shape[0]:,}\")\n", "print(f\"Unique clips: {user_intersting_clips.shape[0] // 2:,}\")\n", "print(\n", " f\"Fraction of total clips: {user_intersting_clips.shape[0] / total_clip_counts:.2%}\"\n", ")\n", "print(\"Time Validation:\")\n", "print(f\"Earliest timestamp: {user_intersting_clips['created_at'].min()}\")\n", "print(f\"Latest timestamp: {user_intersting_clips['created_at'].max()}\")\n", "model_to_test = target_model_name\n", "# model_to_test = \"chirp-v4-up-u-2\"\n", "print(\n", " f\"Earliest timestamp: {user_intersting_clips[user_intersting_clips['model_name'] == model_to_test]['created_at'].min()}\"\n", ")\n", "print(\n", " f\"Latest timestamp: {user_intersting_clips[user_intersting_clips['model_name'] == model_to_test]['created_at'].max()}\"\n", ")" ] }, { "cell_type": "code", "execution_count": 52, "metadata": { "execution": { "iopub.execute_input": "2024-12-18T04:30:06.748052Z", "iopub.status.busy": "2024-12-18T04:30:06.747894Z", "iopub.status.idle": "2024-12-18T04:30:06.768279Z", "shell.execute_reply": "2024-12-18T04:30:06.767815Z", "shell.execute_reply.started": "2024-12-18T04:30:06.748036Z" } }, "outputs": [], "source": [ "def parse_for_instrumental(x):\n", " if \"make_instrumental\" not in x:\n", " return False\n", " out = x.get(\"make_instrumental\", False)\n", " return out\n", "\n", "\n", "# from suno_analytics.preference_data_selection import parse_for_tag, parse_for_one_box\n", "# user_intersting_clips[\"tags\"] = user_intersting_clips[\"metadata\"].apply(parse_for_tag)\n", "# user_intersting_clips[\"is_onebox\"] = user_intersting_clips[\"metadata\"].apply(parse_for_one_box)\n", "# user_intersting_clips[\"is_instrumental\"] = user_intersting_clips[\"metadata\"].apply(parse_for_instrumental)" ] }, { "cell_type": "code", "execution_count": 53, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:00.893917Z", "start_time": "2024-05-26T00:25:00.485775Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:30:06.768942Z", "iopub.status.busy": "2024-12-18T04:30:06.768798Z", "iopub.status.idle": "2024-12-18T04:30:19.255111Z", "shell.execute_reply": "2024-12-18T04:30:19.254489Z", "shell.execute_reply.started": "2024-12-18T04:30:06.768927Z" } }, "outputs": [], "source": [ "user_compare_mask = (\n", " user_intersting_clips[\"created_at\"] >= cutoff_date\n", " # & (\n", " # (user_intersting_clips[\"model_name\"].str.startswith(\"chirp-v3p5-engine-t\"))\n", " # | (user_intersting_clips[\"model_name\"].str.startswith(\"chirp-v3p5-engine-s\"))\n", " # )\n", " # & (~user_intersting_clips[\"is_pro_user\"])\n", " # & (~user_intersting_clips[\"is_onebox\"])\n", " # & user_intersting_clips[\"is_instrumental\"]\n", ")\n", "# # this is fucked up sometimes one box doesn't give prompt to one generation\n", "extra_compare_mask = user_intersting_clips[user_compare_mask][\"request_id\"].isin(\n", " user_intersting_clips[user_compare_mask][\"request_id\"]\n", " .value_counts()\n", " .index[user_intersting_clips[user_compare_mask][\"request_id\"].value_counts() == 2]\n", ")\n", "\n", "user_compare_mask = user_compare_mask & extra_compare_mask" ] }, { "cell_type": "code", "execution_count": 54, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:01.140472Z", "start_time": "2024-05-26T00:25:00.895575Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:30:19.255884Z", "iopub.status.busy": "2024-12-18T04:30:19.255729Z", "iopub.status.idle": "2024-12-18T04:32:11.907022Z", "shell.execute_reply": "2024-12-18T04:32:11.906435Z", "shell.execute_reply.started": "2024-12-18T04:30:19.255868Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(1165132, 53)\n", "Model Name Value Counts and Fractions:\n", "chirp-v3p5-engine-s-8: 395362 (33.93%)\n", "chirp-v4-h-s-32: 353054 (30.30%)\n", "chirp-v4-h-t-6: 125402 (10.76%)\n", "chirp-v4-up-u-3: 45097 (3.87%)\n", "chirp-v3p5-engine-t-6: 39849 (3.42%)\n", "chirp-v3p5-engine-upload-4: 27772 (2.38%)\n", "chirp-v4-h-s-31: 24138 (2.07%)\n", "chirp-v4-h-s-32_n_tag_3: 11044 (0.95%)\n", "chirp-v4-h-s-32_temp_s_85: 10847 (0.93%)\n", "chirp-v4-h-s-32_temp_s_70: 10842 (0.93%)\n", "chirp-v4-h-s-32_step_16: 10747 (0.92%)\n", "chirp-v4-h-s-32_step_8: 10704 (0.92%)\n", "chirp-v4-h-s-32_temp_s_75: 10700 (0.92%)\n", "chirp-v4-h-s-32_text_1: 10694 (0.92%)\n", "chirp-v4-h-s-32_step_10: 10663 (0.92%)\n", "chirp-v4-h-s-32_temp_s_90: 10642 (0.91%)\n", "chirp-v4-h-s-32_step_16_text_1: 5155 (0.44%)\n", "chirp-v4-engine-b: 3918 (0.34%)\n", "chirp-v4-h-t-6_text_1: 3145 (0.27%)\n", "chirp-v4-h-t-6_step_8: 3140 (0.27%)\n", "chirp-v4-h-t-6_temp_s_90: 3115 (0.27%)\n", "chirp-v4-h-t-6_temp_s_80: 3074 (0.26%)\n", "chirp-v4-h-t-6_step_16: 3063 (0.26%)\n", "chirp-v4-h-t-6_step_10: 3005 (0.26%)\n", "chirp-v4-h-t-6_temp_s_70: 3002 (0.26%)\n", "chirp-v4-up-u-3_step_16: 2989 (0.26%)\n", "chirp-v4-up-u-3_step_10: 2987 (0.26%)\n", "chirp-v4-up-u-3_step_8: 2957 (0.25%)\n", "chirp-v4-h-t-6-artist-cfg: 2695 (0.23%)\n", "chirp-v3p5-engine-t-6_s_max_t_12_tag_2: 2644 (0.23%)\n", "chirp-v4-up-u-3_text_15: 1498 (0.13%)\n", "chirp-v4-up-u-3_text_1: 1476 (0.13%)\n", "chirp-v4-up-u-3_text_25: 1464 (0.13%)\n", "chirp-v4-up-u-3_text_3: 1435 (0.12%)\n", "chirp-v4-up-u-3-c-3: 1412 (0.12%)\n", "chirp-v3p5-engine-b: 1324 (0.11%)\n", "chirp-v3p5-engine-b-r: 1276 (0.11%)\n", "chirp-v4-h-t-6_step_16_text_1: 1227 (0.11%)\n", "chirp-v3p5-engine-short: 846 (0.07%)\n", "chirp-v4-up-u-3_step_16_text_1: 578 (0.05%)\n", "chirp-v4-up-u-2: 63 (0.01%)\n", "chirp-v4-h-t-6_text_15: 12 (0.00%)\n", "chirp-v4-h-s-31-l-30-2: 12 (0.00%)\n", "chirp-v4-up-u-2-d-2: 8 (0.00%)\n", "chirp-v4-h-t-6_text_3: 7 (0.00%)\n", "chirp-v4-h-t-6_temp_s_95: 7 (0.00%)\n", "chirp-v4-up-u-2_step_8: 6 (0.00%)\n", "chirp-v4-h-t-6_a_25_r_30: 4 (0.00%)\n", "chirp-v4-up-u-2_text_3: 4 (0.00%)\n", "chirp-v4-up-u-2_text_25: 3 (0.00%)\n", "chirp-v4-h-t-6_text_25: 3 (0.00%)\n", "chirp-v4-h-s-31_s_15_full: 3 (0.00%)\n", "chirp-v3p5-engine-t-6_s_30_t_12_tag_2: 2 (0.00%)\n", "chirp-v4-h-s-31_n_tag_3: 2 (0.00%)\n", "chirp-v3p5-engine-t-6_s_max_t_14_tag_2: 2 (0.00%)\n", "chirp-v4-h-s-31_temp_s_70: 2 (0.00%)\n", "chirp-v4-h-s-31_temp_s_95: 1 (0.00%)\n", "chirp-v3p5-engine-t-6_s_max_t_13_tag_2: 1 (0.00%)\n", "chirp-v4-h-s-31_temp_s_80: 1 (0.00%)\n", "chirp-v4-h-t-6-artist-cfg_step_8: 1 (0.00%)\n", "chirp-v4-h-t-6_temp_s_85: 1 (0.00%)\n", "chirp-v4-up-u-3-c-3_step_16: 1 (0.00%)\n", "chirp-v4-up-u-2_step_16: 1 (0.00%)\n", "chirp-v4-h-s-31_temp_s_75: 1 (0.00%)\n", "chirp-v4-h-t-6_n_tag_3: 1 (0.00%)\n", "chirp-v4-up-u-2_text_15: 1 (0.00%)\n" ] } ], "source": [ "user_intersting_clips_3p5 = (\n", " user_intersting_clips[user_compare_mask].reset_index().copy()\n", ")\n", "\n", "\n", "def modify_model_name(model_name, metadata):\n", " if (\n", " model_name.startswith(\"chirp-v3p5-engine-t\")\n", " or model_name.startswith(\"chirp-v3p5-engine-s\")\n", " or model_name.startswith(\"chirp-v4\")\n", " or model_name.startswith(\"chirp-v3p5-h-s-31\")\n", " ):\n", " if \"param_experiment\" in metadata:\n", " exp = metadata.get(\"param_experiment\", \"\")\n", " if exp:\n", " return f\"{model_name}_{exp}\"\n", " return model_name\n", "\n", "\n", "user_intersting_clips_3p5[\"model_name\"] = user_intersting_clips_3p5.apply(\n", " lambda row: modify_model_name(row[\"model_name\"], row[\"metadata\"]), axis=1\n", ")\n", "user_intersting_clips_3p5 = user_intersting_clips_3p5.sort_values(\n", " by=[\"request_id\", \"preference\"]\n", ")\n", "print(user_intersting_clips_3p5.shape)\n", "model_counts = user_intersting_clips_3p5[\"model_name\"].value_counts()\n", "model_fracs = model_counts / model_counts.sum()\n", "\n", "print(\"Model Name Value Counts and Fractions:\")\n", "print_out_value_counts_nicely(user_intersting_clips_3p5, \"model_name\")" ] }, { "cell_type": "code", "execution_count": 55, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:02.009450Z", "start_time": "2024-05-26T00:25:01.523515Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:32:11.907740Z", "iopub.status.busy": "2024-12-18T04:32:11.907588Z", "iopub.status.idle": "2024-12-18T04:33:52.454013Z", "shell.execute_reply": "2024-12-18T04:33:52.453419Z", "shell.execute_reply.started": "2024-12-18T04:32:11.907724Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "len pos models: 582566\n", "differing counts: 171090\n", "chirp-v3p5-engine-b-r_win_over_chirp-v3p5-engine-b-r, win ratio 1.000, (1.000, 1.000), counts 638, total 638.\n", "chirp-v3p5-engine-b_win_over_chirp-v3p5-engine-b, win ratio 1.000, (1.000, 1.000), counts 662, total 662.\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-8, win ratio 1.000, (1.000, 1.000), counts 197681, total 197681.\n", "chirp-v3p5-engine-short_win_over_chirp-v3p5-engine-short, win ratio 1.000, (1.000, 1.000), counts 423, total 423.\n", "chirp-v3p5-engine-t-6_s_30_t_12_tag_2_win_over_chirp-v3p5-engine-t-6, win ratio 1.000, (1.000, 1.000), counts 2, total 2.\n", "chirp-v3p5-engine-t-6_s_max_t_12_tag_2_win_over_chirp-v3p5-engine-t-6, win ratio 0.518, (0.499, 0.537), counts 1368, total 2642.\n", "chirp-v3p5-engine-t-6_s_max_t_12_tag_2_win_over_chirp-v3p5-engine-t-6_s_max_t_12_tag_2, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v3p5-engine-t-6_s_max_t_13_tag_2_win_over_chirp-v3p5-engine-t-6, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v3p5-engine-t-6_s_max_t_14_tag_2_win_over_chirp-v3p5-engine-t-6, win ratio 0.500, (-0.193, 1.193), counts 1, total 2.\n", "chirp-v3p5-engine-t-6_win_over_chirp-v3p5-engine-t-6, win ratio 1.000, (1.000, 1.000), counts 18601, total 18601.\n", "chirp-v3p5-engine-t-6_win_over_chirp-v3p5-engine-t-6_s_max_t_12_tag_2, win ratio 0.482, (0.463, 0.501), counts 1274, total 2642.\n", "chirp-v3p5-engine-t-6_win_over_chirp-v3p5-engine-t-6_s_max_t_14_tag_2, win ratio 0.500, (-0.193, 1.193), counts 1, total 2.\n", "chirp-v3p5-engine-upload-4_win_over_chirp-v3p5-engine-upload-4, win ratio 1.000, (1.000, 1.000), counts 13886, total 13886.\n", "chirp-v4-engine-b_win_over_chirp-v4-engine-b, win ratio 1.000, (1.000, 1.000), counts 1959, total 1959.\n", "chirp-v4-h-s-31-l-30-2_win_over_chirp-v4-h-s-31, win ratio 0.500, (0.217, 0.783), counts 6, total 12.\n", "chirp-v4-h-s-31_n_tag_3_win_over_chirp-v4-h-s-31, win ratio 1.000, (1.000, 1.000), counts 2, total 2.\n", "chirp-v4-h-s-31_s_15_full_win_over_chirp-v4-h-s-31, win ratio 0.667, (0.133, 1.200), counts 2, total 3.\n", "chirp-v4-h-s-31_temp_s_70_win_over_chirp-v4-h-s-31, win ratio 0.500, (-0.193, 1.193), counts 1, total 2.\n", "chirp-v4-h-s-31_temp_s_80_win_over_chirp-v4-h-s-31, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-s-31_win_over_chirp-v4-h-s-31, win ratio 1.000, (1.000, 1.000), counts 22, total 22.\n", "chirp-v4-h-s-31_win_over_chirp-v4-h-s-31-l-30-2, win ratio 0.500, (0.217, 0.783), counts 6, total 12.\n", "chirp-v4-h-s-31_win_over_chirp-v4-h-s-31_s_15_full, win ratio 0.333, (-0.200, 0.867), counts 1, total 3.\n", "chirp-v4-h-s-31_win_over_chirp-v4-h-s-31_temp_s_70, win ratio 0.500, (-0.193, 1.193), counts 1, total 2.\n", "chirp-v4-h-s-31_win_over_chirp-v4-h-s-31_temp_s_95, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-s-31_win_over_chirp-v4-h-s-32, win ratio 0.473, (0.467, 0.480), counts 11395, total 24071.\n", "chirp-v4-h-s-31_win_over_chirp-v4-h-s-32_step_8, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-s-31_win_over_chirp-v4-h-s-32_temp_s_90, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-s-32_n_tag_3_win_over_chirp-v4-h-s-32, win ratio 0.504, (0.494, 0.513), counts 5562, total 11044.\n", "chirp-v4-h-s-32_step_10_win_over_chirp-v4-h-s-32, win ratio 0.506, (0.496, 0.515), counts 5393, total 10663.\n", "chirp-v4-h-s-32_step_16_text_1_win_over_chirp-v4-h-s-32, win ratio 0.487, (0.474, 0.501), counts 2512, total 5155.\n", "chirp-v4-h-s-32_step_16_win_over_chirp-v4-h-s-32, win ratio 0.506, (0.497, 0.516), counts 5442, total 10747.\n", "chirp-v4-h-s-32_step_8_win_over_chirp-v4-h-s-32, win ratio 0.491, (0.482, 0.500), counts 5255, total 10703.\n", "chirp-v4-h-s-32_temp_s_70_win_over_chirp-v4-h-s-32, win ratio 0.512, (0.503, 0.521), counts 5551, total 10841.\n", "chirp-v4-h-s-32_temp_s_75_win_over_chirp-v4-h-s-32, win ratio 0.499, (0.490, 0.509), counts 5343, total 10700.\n", "chirp-v4-h-s-32_temp_s_85_win_over_chirp-v4-h-s-32, win ratio 0.495, (0.486, 0.505), counts 5371, total 10844.\n", "chirp-v4-h-s-32_temp_s_85_win_over_chirp-v4-h-s-32_temp_s_70, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-s-32_temp_s_85_win_over_chirp-v4-h-s-32_temp_s_85, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-s-32_temp_s_90_win_over_chirp-v4-h-s-32, win ratio 0.498, (0.488, 0.507), counts 5297, total 10641.\n", "chirp-v4-h-s-32_text_1_win_over_chirp-v4-h-s-32, win ratio 0.484, (0.474, 0.493), counts 5175, total 10694.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-31, win ratio 0.527, (0.520, 0.533), counts 12676, total 24071.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-31_temp_s_75, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32, win ratio 1.000, (1.000, 1.000), counts 113475, total 113475.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_n_tag_3, win ratio 0.496, (0.487, 0.506), counts 5482, total 11044.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_step_10, win ratio 0.494, (0.485, 0.504), counts 5270, total 10663.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_step_16, win ratio 0.494, (0.484, 0.503), counts 5305, total 10747.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_step_16_text_1, win ratio 0.513, (0.499, 0.526), counts 2643, total 5155.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_step_8, win ratio 0.509, (0.500, 0.518), counts 5448, total 10703.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_temp_s_70, win ratio 0.488, (0.479, 0.497), counts 5290, total 10841.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_temp_s_75, win ratio 0.501, (0.491, 0.510), counts 5357, total 10700.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_temp_s_85, win ratio 0.505, (0.495, 0.514), counts 5473, total 10844.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_temp_s_90, win ratio 0.502, (0.493, 0.512), counts 5344, total 10641.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_text_1, win ratio 0.516, (0.507, 0.526), counts 5519, total 10694.\n", "chirp-v4-h-t-6-artist-cfg_win_over_chirp-v4-h-t-6, win ratio 0.416, (0.397, 0.434), counts 1120, total 2695.\n", "chirp-v4-h-t-6_a_25_r_30_win_over_chirp-v4-h-t-6, win ratio 0.500, (0.010, 0.990), counts 2, total 4.\n", "chirp-v4-h-t-6_n_tag_3_win_over_chirp-v4-h-t-6, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-t-6_step_10_win_over_chirp-v4-h-t-6, win ratio 0.504, (0.486, 0.522), counts 1515, total 3005.\n", "chirp-v4-h-t-6_step_16_text_1_win_over_chirp-v4-h-t-6, win ratio 0.461, (0.433, 0.489), counts 566, total 1227.\n", "chirp-v4-h-t-6_step_16_win_over_chirp-v4-h-t-6, win ratio 0.493, (0.475, 0.511), counts 1510, total 3063.\n", "chirp-v4-h-t-6_step_8_win_over_chirp-v4-h-t-6, win ratio 0.473, (0.456, 0.491), counts 1486, total 3139.\n", "chirp-v4-h-t-6_temp_s_70_win_over_chirp-v4-h-t-6, win ratio 0.523, (0.505, 0.541), counts 1571, total 3002.\n", "chirp-v4-h-t-6_temp_s_80_win_over_chirp-v4-h-t-6, win ratio 0.505, (0.487, 0.522), counts 1551, total 3074.\n", "chirp-v4-h-t-6_temp_s_85_win_over_chirp-v4-h-t-6, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-t-6_temp_s_90_win_over_chirp-v4-h-t-6, win ratio 0.499, (0.482, 0.517), counts 1555, total 3114.\n", "chirp-v4-h-t-6_temp_s_90_win_over_chirp-v4-h-t-6_step_8, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-t-6_temp_s_95_win_over_chirp-v4-h-t-6, win ratio 0.714, (0.380, 1.049), counts 5, total 7.\n", "chirp-v4-h-t-6_text_15_win_over_chirp-v4-h-t-6, win ratio 0.417, (0.138, 0.696), counts 5, total 12.\n", "chirp-v4-h-t-6_text_1_win_over_chirp-v4-h-t-6, win ratio 0.493, (0.476, 0.511), counts 1552, total 3145.\n", "chirp-v4-h-t-6_text_3_win_over_chirp-v4-h-t-6, win ratio 0.286, (-0.049, 0.620), counts 2, total 7.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6, win ratio 1.000, (1.000, 1.000), counts 49951, total 49951.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6-artist-cfg, win ratio 0.584, (0.566, 0.603), counts 1575, total 2695.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6-artist-cfg_step_8, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_a_25_r_30, win ratio 0.500, (0.010, 0.990), counts 2, total 4.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_step_10, win ratio 0.496, (0.478, 0.514), counts 1490, total 3005.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_step_16, win ratio 0.507, (0.489, 0.525), counts 1553, total 3063.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_step_16_text_1, win ratio 0.539, (0.511, 0.567), counts 661, total 1227.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_step_8, win ratio 0.527, (0.509, 0.544), counts 1653, total 3139.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_temp_s_70, win ratio 0.477, (0.459, 0.495), counts 1431, total 3002.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_temp_s_80, win ratio 0.495, (0.478, 0.513), counts 1523, total 3074.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_temp_s_90, win ratio 0.501, (0.483, 0.518), counts 1559, total 3114.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_temp_s_95, win ratio 0.286, (-0.049, 0.620), counts 2, total 7.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_text_1, win ratio 0.507, (0.489, 0.524), counts 1593, total 3145.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_text_15, win ratio 0.583, (0.304, 0.862), counts 7, total 12.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_text_25, win ratio 1.000, (1.000, 1.000), counts 3, total 3.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_text_3, win ratio 0.714, (0.380, 1.049), counts 5, total 7.\n", "chirp-v4-up-u-2-d-2_win_over_chirp-v4-up-u-2, win ratio 0.375, (0.040, 0.710), counts 3, total 8.\n", "chirp-v4-up-u-2_step_8_win_over_chirp-v4-up-u-2, win ratio 0.500, (0.100, 0.900), counts 3, total 6.\n", "chirp-v4-up-u-2_text_3_win_over_chirp-v4-up-u-2, win ratio 0.500, (0.010, 0.990), counts 2, total 4.\n", "chirp-v4-up-u-2_win_over_chirp-v4-up-u-2, win ratio 1.000, (1.000, 1.000), counts 20, total 20.\n", "chirp-v4-up-u-2_win_over_chirp-v4-up-u-2-d-2, win ratio 0.625, (0.290, 0.960), counts 5, total 8.\n", "chirp-v4-up-u-2_win_over_chirp-v4-up-u-2_step_16, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-up-u-2_win_over_chirp-v4-up-u-2_step_8, win ratio 0.500, (0.100, 0.900), counts 3, total 6.\n", "chirp-v4-up-u-2_win_over_chirp-v4-up-u-2_text_15, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-up-u-2_win_over_chirp-v4-up-u-2_text_25, win ratio 1.000, (1.000, 1.000), counts 3, total 3.\n", "chirp-v4-up-u-2_win_over_chirp-v4-up-u-2_text_3, win ratio 0.500, (0.010, 0.990), counts 2, total 4.\n", "chirp-v4-up-u-3-c-3_step_16_win_over_chirp-v4-up-u-3, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-up-u-3-c-3_win_over_chirp-v4-up-u-3, win ratio 0.517, (0.491, 0.543), counts 730, total 1412.\n", "chirp-v4-up-u-3_step_10_win_over_chirp-v4-up-u-3, win ratio 0.483, (0.465, 0.501), counts 1440, total 2983.\n", "chirp-v4-up-u-3_step_10_win_over_chirp-v4-up-u-3_step_10, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-up-u-3_step_10_win_over_chirp-v4-up-u-3_text_25, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-up-u-3_step_16_text_1_win_over_chirp-v4-up-u-3, win ratio 0.414, (0.374, 0.454), counts 239, total 577.\n", "chirp-v4-up-u-3_step_16_text_1_win_over_chirp-v4-up-u-3_step_16, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-up-u-3_step_16_win_over_chirp-v4-up-u-3, win ratio 0.500, (0.482, 0.518), counts 1492, total 2986.\n", "chirp-v4-up-u-3_step_16_win_over_chirp-v4-up-u-3_step_10, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-up-u-3_step_16_win_over_chirp-v4-up-u-3_text_3, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-up-u-3_step_8_win_over_chirp-v4-up-u-3, win ratio 0.491, (0.473, 0.509), counts 1452, total 2957.\n", "chirp-v4-up-u-3_text_15_win_over_chirp-v4-up-u-3, win ratio 0.474, (0.449, 0.499), counts 710, total 1498.\n", "chirp-v4-up-u-3_text_1_win_over_chirp-v4-up-u-3, win ratio 0.448, (0.422, 0.473), counts 661, total 1476.\n", "chirp-v4-up-u-3_text_25_win_over_chirp-v4-up-u-3, win ratio 0.506, (0.480, 0.531), counts 740, total 1463.\n", "chirp-v4-up-u-3_text_3_win_over_chirp-v4-up-u-3, win ratio 0.472, (0.446, 0.498), counts 677, total 1434.\n", "chirp-v4-up-u-3_win_over_chirp-v4-up-u-3, win ratio 1.000, (1.000, 1.000), counts 14155, total 14155.\n", "chirp-v4-up-u-3_win_over_chirp-v4-up-u-3-c-3, win ratio 0.483, (0.457, 0.509), counts 682, total 1412.\n", "chirp-v4-up-u-3_win_over_chirp-v4-up-u-3_step_10, win ratio 0.517, (0.499, 0.535), counts 1543, total 2983.\n", "chirp-v4-up-u-3_win_over_chirp-v4-up-u-3_step_16, win ratio 0.500, (0.482, 0.518), counts 1494, total 2986.\n", "chirp-v4-up-u-3_win_over_chirp-v4-up-u-3_step_16_text_1, win ratio 0.586, (0.546, 0.626), counts 338, total 577.\n", "chirp-v4-up-u-3_win_over_chirp-v4-up-u-3_step_8, win ratio 0.509, (0.491, 0.527), counts 1505, total 2957.\n", "chirp-v4-up-u-3_win_over_chirp-v4-up-u-3_text_1, win ratio 0.552, (0.527, 0.578), counts 815, total 1476.\n", "chirp-v4-up-u-3_win_over_chirp-v4-up-u-3_text_15, win ratio 0.526, (0.501, 0.551), counts 788, total 1498.\n", "chirp-v4-up-u-3_win_over_chirp-v4-up-u-3_text_25, win ratio 0.494, (0.469, 0.520), counts 723, total 1463.\n", "chirp-v4-up-u-3_win_over_chirp-v4-up-u-3_text_3, win ratio 0.528, (0.502, 0.554), counts 757, total 1434.\n", "tournament players: ['chirp-v3p5-engine-t-6', 'chirp-v3p5-engine-t-6_s_30_t_12_tag_2', 'chirp-v3p5-engine-t-6_s_max_t_12_tag_2', 'chirp-v3p5-engine-t-6_s_max_t_13_tag_2', 'chirp-v3p5-engine-t-6_s_max_t_14_tag_2', 'chirp-v4-h-s-31', 'chirp-v4-h-s-31-l-30-2', 'chirp-v4-h-s-31_n_tag_3', 'chirp-v4-h-s-31_s_15_full', 'chirp-v4-h-s-31_temp_s_70', 'chirp-v4-h-s-31_temp_s_75', 'chirp-v4-h-s-31_temp_s_80', 'chirp-v4-h-s-31_temp_s_95', 'chirp-v4-h-s-32', 'chirp-v4-h-s-32_n_tag_3', 'chirp-v4-h-s-32_step_10', 'chirp-v4-h-s-32_step_16', 'chirp-v4-h-s-32_step_16_text_1', 'chirp-v4-h-s-32_step_8', 'chirp-v4-h-s-32_temp_s_70', 'chirp-v4-h-s-32_temp_s_75', 'chirp-v4-h-s-32_temp_s_85', 'chirp-v4-h-s-32_temp_s_90', 'chirp-v4-h-s-32_text_1', 'chirp-v4-h-t-6', 'chirp-v4-h-t-6-artist-cfg', 'chirp-v4-h-t-6-artist-cfg_step_8', 'chirp-v4-h-t-6_a_25_r_30', 'chirp-v4-h-t-6_n_tag_3', 'chirp-v4-h-t-6_step_10', 'chirp-v4-h-t-6_step_16', 'chirp-v4-h-t-6_step_16_text_1', 'chirp-v4-h-t-6_step_8', 'chirp-v4-h-t-6_temp_s_70', 'chirp-v4-h-t-6_temp_s_80', 'chirp-v4-h-t-6_temp_s_85', 'chirp-v4-h-t-6_temp_s_90', 'chirp-v4-h-t-6_temp_s_95', 'chirp-v4-h-t-6_text_1', 'chirp-v4-h-t-6_text_15', 'chirp-v4-h-t-6_text_25', 'chirp-v4-h-t-6_text_3', 'chirp-v4-up-u-2', 'chirp-v4-up-u-2-d-2', 'chirp-v4-up-u-2_step_16', 'chirp-v4-up-u-2_step_8', 'chirp-v4-up-u-2_text_15', 'chirp-v4-up-u-2_text_25', 'chirp-v4-up-u-2_text_3', 'chirp-v4-up-u-3', 'chirp-v4-up-u-3-c-3', 'chirp-v4-up-u-3-c-3_step_16', 'chirp-v4-up-u-3_step_10', 'chirp-v4-up-u-3_step_16', 'chirp-v4-up-u-3_step_16_text_1', 'chirp-v4-up-u-3_step_8', 'chirp-v4-up-u-3_text_1', 'chirp-v4-up-u-3_text_15', 'chirp-v4-up-u-3_text_25', 'chirp-v4-up-u-3_text_3']\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "100%|██████████| 1000/1000 [00:56<00:00, 17.75it/s]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "ELOs\n", "chirp-v3p5-engine-t-6: 622.7, (2, 1032)\n", "chirp-v3p5-engine-t-6_s_30_t_12_tag_2: 1690.4, (1000, 2365)\n", "chirp-v3p5-engine-t-6_s_max_t_12_tag_2: 635.1, (0, 1044)\n", "chirp-v3p5-engine-t-6_s_max_t_13_tag_2: 1404.9, (1000, 2001)\n", "chirp-v3p5-engine-t-6_s_max_t_14_tag_2: 646.9, (-252, 1754)\n", "chirp-v4-h-s-31: 961.3, (807, 1097)\n", "chirp-v4-h-s-31-l-30-2: 962.4, (691, 1214)\n", "chirp-v4-h-s-31_n_tag_3: 1820.1, (1000, 2552)\n", "chirp-v4-h-s-31_s_15_full: 1168.5, (76, 2405)\n", "chirp-v4-h-s-31_temp_s_70: 944.4, (-128, 2067)\n", "chirp-v4-h-s-31_temp_s_75: 446.2, (-335, 1000)\n", "chirp-v4-h-s-31_temp_s_80: 1511.5, (1000, 2211)\n", "chirp-v4-h-s-31_temp_s_95: 419.8, (-448, 1000)\n", "chirp-v4-h-s-32: 979.8, (826, 1115)\n", "chirp-v4-h-s-32_n_tag_3: 982.3, (826, 1120)\n", "chirp-v4-h-s-32_step_10: 983.8, (829, 1121)\n", "chirp-v4-h-s-32_step_16: 984.2, (829, 1120)\n", "chirp-v4-h-s-32_step_16_text_1: 971.0, (817, 1110)\n", "chirp-v4-h-s-32_step_8: 973.5, (820, 1109)\n", "chirp-v4-h-s-32_temp_s_70: 988.2, (833, 1128)\n", "chirp-v4-h-s-32_temp_s_75: 979.4, (827, 1117)\n", "chirp-v4-h-s-32_temp_s_85: 976.6, (821, 1113)\n", "chirp-v4-h-s-32_temp_s_90: 978.3, (823, 1118)\n", "chirp-v4-h-s-32_text_1: 968.6, (813, 1105)\n", "chirp-v4-h-t-6: 1039.3, (886, 1194)\n", "chirp-v4-h-t-6-artist-cfg: 980.3, (825, 1133)\n", "chirp-v4-h-t-6-artist-cfg_step_8: 485.1, (-288, 1000)\n", "chirp-v4-h-t-6_a_25_r_30: 1050.1, (-158, 2206)\n", "chirp-v4-h-t-6_n_tag_3: 1576.9, (1000, 2337)\n", "chirp-v4-h-t-6_step_10: 1042.2, (888, 1195)\n", "chirp-v4-h-t-6_step_16: 1034.5, (886, 1190)\n", "chirp-v4-h-t-6_step_16_text_1: 1012.3, (864, 1168)\n", "chirp-v4-h-t-6_step_8: 1020.7, (865, 1180)\n", "chirp-v4-h-t-6_temp_s_70: 1055.6, (911, 1209)\n", "chirp-v4-h-t-6_temp_s_80: 1042.5, (892, 1195)\n", "chirp-v4-h-t-6_temp_s_85: 1576.9, (1000, 2407)\n", "chirp-v4-h-t-6_temp_s_90: 1039.0, (886, 1194)\n", "chirp-v4-h-t-6_temp_s_95: 1175.5, (914, 2984)\n", "chirp-v4-h-t-6_text_1: 1034.8, (881, 1192)\n", "chirp-v4-h-t-6_text_15: 986.7, (689, 1238)\n", "chirp-v4-h-t-6_text_25: -57.5, (-922, 1000)\n", "chirp-v4-h-t-6_text_3: 905.1, (-506, 1211)\n", "chirp-v4-up-u-2: 1419.8, (1058, 1865)\n", "chirp-v4-up-u-2-d-2: 1342.9, (32, 1812)\n", "chirp-v4-up-u-2_step_16: 624.4, (35, 1000)\n", "chirp-v4-up-u-2_step_8: 1405.0, (470, 2460)\n", "chirp-v4-up-u-2_text_15: 624.4, (-24, 1000)\n", "chirp-v4-up-u-2_text_25: 145.4, (-565, 1000)\n", "chirp-v4-up-u-2_text_3: 1438.1, (330, 2597)\n", "chirp-v4-up-u-3: 958.6, (883, 1018)\n", "chirp-v4-up-u-3-c-3: 970.5, (888, 1039)\n", "chirp-v4-up-u-3-c-3_step_16: 1549.7, (1000, 2307)\n", "chirp-v4-up-u-3_step_10: 946.6, (871, 1012)\n", "chirp-v4-up-u-3_step_16: 958.5, (880, 1023)\n", "chirp-v4-up-u-3_step_16_text_1: 899.7, (817, 970)\n", "chirp-v4-up-u-3_step_8: 952.4, (876, 1017)\n", "chirp-v4-up-u-3_text_1: 922.2, (842, 989)\n", "chirp-v4-up-u-3_text_15: 940.5, (863, 1009)\n", "chirp-v4-up-u-3_text_25: 962.4, (883, 1030)\n", "chirp-v4-up-u-3_text_3: 939.0, (859, 1008)\n" ] }, { "data": { "image/png": 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xxfPSkvjevXu36XPC30hqHl9z4ciRI3z66afJts2VKxdFixZNsb/HH4zdunUr0fHo6GizhZ4//PDDNMWZlOd9vyIiIvLfoqS+iIiIiMgzlCNHDsqXL8/Bgwf5888/CQwMxMPDg+3bt5sWXH3SWfoXLlwgLi4OAHt7e3x8fFI9p3DhwqZEcFxcHOfPn6dMmTKm4wmJXYgvwZIaCwsLSpYsyW+//ZZsm+PHj5s++/v7M2LEiFT7hUcL0RqNRvz9/V9oUn/fvn3s27cvxTbu7u6MGjWKGjVqpNgutSQymI/RhQsX0jxGCUJCQhI9oHkSj18/MjIyzde/ceOG6bO/v3+KSf20jMPji87+9ttvHDp0KNVzwsLCTJ8ff+CSlIIFC6ban6urq+lzwvoGjzt37hxRUVFA/MK4CesXPI3nfb8iIiLy36KkvoiIiIjIM9a4cWMOHjxIXFwc69ato23btqxZswaIT44/aVL//v37ps/ZsmVLchHOf7K0tCRr1qxcuXIlUR+AacHdhD7TIrV2d+7cMX2+cOECFy5cSFO/jwsJCXnic54lCwsLHBwccHNzo3DhwlSrVo3//e9/qZaogfjyPKl5fIyOHDnCkSNHnjjG0NDQp07qP359X19fU7mkJ5Ha7+hJxyG5evYpSXgQlJy0PBh6vDRPbGxsouN37941fc6aNWuypXzS4nnfr4iIiPy3KKkvIiIiIvKM1a1bl6+//pqHDx+yevVqGjduzB9//AFA2bJlyZUr1xP19+DBA9PnpBbWTM7jbR/vA+IXPX3SPlNr9/jM4qeV8EbCizJmzBiz2ur/RloS/89ijJJKQKfVi/gdpaWkUFIz459lDGl58JWax/9mnvYhSoLnfb8iIiLy36KkvoiIiIjIM+bo6Mjbb7/N+vXruXDhAhMnTjQlYps0afLE/T1ex/3hw4dpPu/xtv+sBf94kjKtfabW7vGkf5s2bRg8eHCa+v0veXyMBgwYwCeffPLSrl+zZk2mT5/+Qq//eBwJDxhWrVqV4sLPL8vjfzOPPwR7GunhfkVERCT9sHzZAYiIiIiIvI4eT96vXLkSiJ/BXLdu3Sfu6/FFbP39/TEajameYzAY8Pf3T7IPMC+RktZ63Y/3lxR3d3fT58dLl8gjj49RYGDgS73+y/wdPb6I8ssYh7R4fKz8/f3/1RsS6eF+RUREJP1QUl9ERERE5DmoXLkyHh4eZvvefvvtp1oE1sfHBysrKyC+JEhaatWfP3/eNLvYysoq0cKmhQsXNn1+fPHU5BiNRk6cOJFimxIlSpg+Hzt2LE0PH/5rHh+jo0ePvvDrP77Y67lz5/71DPRnEcfLGIe0KFy4sKmU0MOHD1P9/qckPdyviIiIpB9K6ouIiIiIPAdWVlY0bNjQbN/TlN6B+HI+xYoVM22vWrUq1XOWL19u+lyiRIlENcErVKhg+rx7926Cg4NT7G///v2pztQvW7Yszs7OQPzM5h07dqQa539N1apVTQuuHjt2jPPnz7/Q6+fKlYt8+fIBEBMTY/Y9eZFq1Khh+rxixQqioqJeShwpyZAhg9nfydMsKpwgPdyviIiIpB9K6ouIiIiIPCedOnVi+fLlpp8qVao8dV+tWrUyfV60aFGKyeDTp0+zZMkS03br1q0TtalSpQrZsmUD4mchT5gwIdn+oqKiGDt2bKoxZsiQgY8//ti0PXz4cAICAlI9L8F/oWSPp6cnjRo1AuLffujbt2+aF1E1GAwEBQX96xg6dOhg+vzdd9+l6c2PBM+qdEydOnXw9vY29Tls2LA0v9nx4MGDF/aGwaeffmr6vGHDBjZs2PBU/aSX+xUREZH0QUl9EREREZHnxNnZmeLFi5t+EkroPI2GDRuaSujExMTQvn179u/fn6jdn3/+SYcOHUz1v4sWLUqDBg0StbOysqJ79+6m7eXLlzNq1KhEM4gDAwP5/PPPOX/+PDY2NqnG+emnn1KgQAEAAgICaN68OZs2bcJgMCTZPigoiCVLltC0aVPmzJmTav+vgx49ephKM124cIEWLVqwZ8+eZNv7+/szb9486taty8aNG//19Rs1akTFihWB+ITx+++/z+LFi4mOjk6yfXh4OGvXrqVNmzaMHDnyX18f4r9/w4YNM/1NrFy5ks8++4zLly8ne865c+eYMGECNWrUwNfX95nEkZrKlSubrYPRp08fpk6dmuSi0QaDgf379/PFF1+YFsVNkF7uV0RERNIH65cdgIiIiIiIpC5Dhgx8++23fPjhhwQFBREYGMjHH39MoUKFTPXxz507ZzaDP3PmzHzzzTfJJuObNm3K77//zqZNmwCYP38+a9asoUKFCri6unL79m0OHDhAdHQ0OXPm5O233+bnn39OMU4HBwemT5/OJ598gq+vL4GBgfTo0YNMmTJRqlQp3N3dMRqNhISE8Ndff3H9+nVTwj8h0fy68/T0ZNq0aXz22Wfcv3+fq1ev0q5dOzw9PSlRogRubm7ExMRw//59Ll269MwTulZWVnz33Xe0bduWs2fPEh4eztChQ5kwYQKlSpXC09MTKysrQkJCuHr1KleuXDE9JKpTp84zi6Ny5coMGzaMYcOGERcXx+7du/njjz/Inz8/Pj4+ODg4EBkZSWBgIOfPn38mbyk8jVGjRuHn58fJkyeJi4tjypQpzJkzhzJlypA1a1aMRiMBAQGcPn3aVMYqqVn46eV+RURE5NWnpL6IiIiISDqRL18+fvnlF7788kvOnj0LxC+Im1QpnqJFi/Ldd9/h5eWVYp8TJkzAzs7OVKc/JCSE3377zaxN3rx5mTp1appniefKlYsVK1YwdOhQtmzZgtFo5P79++zcuTPZc5ydnSlYsGCa+n8dlChRghUrVjBo0CD27dsHxL/ZsHXr1mTPcXd3N5Vw+bcyZcrEr7/+ypgxY1i+fDmxsbGEh4en+MaAnZ0dRYsWfSbXT9CyZUu8vLwYOnQo165dw2g0cunSJS5dupTsOQUKFMDFxeWZxpESR0dHFixYwKhRo1ixYgVxcXFEREQkO1a2trZYWib9Unx6uF8RERF59SmpLyIiIiKSjuTJk4cVK1awefNmfvvtN06ePGma0evm5kbJkiWpU6cOderUwcLCItX+bGxsGDt2LI0bN2bp0qUcPXqUe/fu4eLigpeXF/Xq1aN58+Y4ODg8UZyurq58//33XLx4kQ0bNnDgwAF8fX0JDg7G0tISZ2dnvLy8KFKkCJUrV+bNN9/E1tb2qcYkvcqRIwfz5s3j2LFjbN68mUOHDuHv709oaChWVla4urri7e1NsWLFqFKlCm+88YZpkd1nwc7OjuHDh9OhQwfWrl3L/v37uXbtGsHBwRgMBpycnMiVKxeFChWiYsWKVKtWDUdHx2d2/QQVK1Zk48aNbNu2jV27dnHixAnu3r1LeHg4dnZ2uLu7kzdvXkqXLk21atVMb6a8SHZ2dowcOZJPPvmENWvWsG/fPm7dukVISAg2NjZ4eHjg4+ND5cqVqV+/forjlB7uV0RERF5tFsa0rs4jIiIiIiIiIiIiIiIvlRbKFRERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ5TUFxERERERERERERFJJ6xfdgAiIq+yerl7vuwQUhR7w/dlhyAiIiIiIiIir7ithmUvOwR5hjRTX0REREREREREREQknVBSX0REREREREREREQknVBSX0REREREREREREQknVBSX0REREREREREREQknVBSX0REREREREREREQknVBSX0REREREREREREQknbB+2QGIiLzqbGyt6TrqXfIXy4lXfk8O7DjLyM/mpnhO8Yr5GL+4S5LHujf6losnb/JBjzp82KNuouOREVE0LdIfACtrS1p1rkWt5uXJnNUF3yt3mDt2PUd+P//vb0xERERERERERNIdJfVFRFJhaWlJdGQMa+f9wZv1SqTpnHNHrvF++SFm+9p8WY9Sbxbk4smbAKyYuZONi/40azNmUWcunrxh2v64d33ealKWyf2XcvPyHcpW9+GrGZ/Sq/lkLp+59S/vTERERERERERE0huV3xERSUXUw2imDl7O5sX7uR8YlqZzYmPiuB8YZvoJvf+ASrWLsXXZAVObyIhoszau7k54F8zKliWP2tRsWo4lP2zj0K5z+N+8x4aFf3Jo5zmata/xrG9TRERERERERETSASX1RURegIq1iuGUyYGtyw4m26Zuq4r4Xr7DmUNXTPtsMlgTHRVr1i46Moai5fM+t1hFREREREREROTVpaS+iMgLUKdVBY7uPs9d/5Akj9vYWvNWkzJsWXrAbP+R3edp1r4G2XO7Y2FhQekqBalctwRuHs4vImwREREREREREXnFKKkvIvKcuWd1oUy1QmZldf6pcp3iZHSwY9sK85n8M4av4ta1QGZuH8C6SxPoPLw5W5cdxGA0PO+wRURERERERETkFaSFckVEnrPa775B2P0H7N92Otk2dVtV5OCOMwTfDTfbHxL0gJGfzcXG1hpnVwfuBYTQtv//8L8R9LzDFhERERERERGRV1C6manv6+uLj48P586dS7bNypUrKVeu3AuM6r+nTZs2jBo16mWHIZKu1H63AttXHiYuNunZ9Z453ShRKX+KM/ljomK5FxCClbUlb9Ytwb6tp55XuCIiIiIiIiIi8gpLN0n9tKhfvz5btmx5adf//PPPqVGjBsWLF6dKlSr06dOHgICAJ+rjwIED+Pj4JPoJDAx8TlE/mSlTptC9e/fnfp0neXhgNBqZM2cOderUoVixYlStWpXp06c/5whfTT4+Pmzbti3N7e/cuUOvXr2oU6cOhQoVSnLMly5dyvvvv0/58uUpX748n3zyCSdPnkzzNWrWrMm8efPS3P5ZiImJYcKECTRs2JBSpUpRpUoV+vbt+8R/j4/zyu9J3iLZcXKxx8HJjrxFspO3SHbT8YIlvZi5vT+ZPV3MzitVuQDZvDKzecn+ZPt+p2UFgu6EcnhX4oeWPqW8qFynOFlzZaZo+bx8/XNHLCwtWT5jx1Pfi4iIiIiIiIiIpF+vVfkdOzs77Ozskj0eHR1NhgwZntv1K1asyOeff46HhwcBAQGMHz+e7t27s3jx4ifua/PmzTg6Opq2M2fO/CxDfWqurq4vO4RERo0axZ49e+jbty8FCxYkJCSEkJCkFyMVc9HR0WTKlIlOnTolm3g/cOAADRo0oEyZMmTIkIHZs2fTtm1bNmzYgKen54sNOI0iIyM5e/YsnTp1olChQoSGhjJq1Cg6derEypUrn6rPEfM+wzOnm2n7h419AKiXuycAthltyJXPEysb82el77SqwJnDV/G9fCfJfi0sLKjdojzblh/CYDAmOp7B1oaPe9cnq1dmHj6I4tDOc0zouYgHoZFPdR8iIiIiIiIiIpK+WRiNxsRZpJfIYDAwZ84cli5dyu3bt3F3d6dVq1Y0bNiQt99+mylTprBgwQJOnjyJt7c3w4cPp3Tp0kB8+Z3Ro0dz+PBhIH5W+bZt2/jwww+ZPn06fn5+nD9/njZt2lCgQAEA1qxZg7W1Ne+99x7du3fHwsIiUUzh4eFUrlyZKVOmUL16ddP+rVu30rdvX/78808yZsyY6Lzt27fzxRdfcOrUKWxsbEzxjR07lvHjx3P79m3eeOMNvv76a7JlywbEJ1A/+ugjDh06hLOzc5rHLTo6mkmTJrF+/XrCwsIoUKAAvXv3pkKFCmZjM2nSJEaPHo2/vz9lypRhzJgxZMmSBYDY2FjGjh3L6tWrsbKyokWLFty9e5ewsDCmTZsGxM+gL1SoEIMGDQLiZ2G3bNmS69evs3nzZlxcXOjUqROtWrUyxXb79m3Gjh3L3r17sbS0pGzZsgwaNIicOXMmeS/9+/dn1apVicYyqfaXL1+mUaNGrFu3jrx586Z5vBKcP3+eUaNGcfr0aSwsLMidOzfDhw+nePHiKZ6XMJ4TJkxg7Nix+Pv7U716dcaNG8fmzZuZMmUKYWFhNG7cmAEDBmBlZQXA6tWrmT9/PlevXsXe3p6KFSsycOBA00ObqVOnsnjxYtatW0emTJkA+Oyzz3j48CE///wzlpbJv1xTs2ZNbt26ZdrOkSMHO3akfTb3P3+3yYmLi6N8+fIMGTKEJk2apNrnwYPmC79euHCB+/fvM3LkSA4dOkRoaCheXl507NiR//3vf6Z24eHhDB06lO3bt+Po6Ej79u3Zvn17mmJMysmTJ3n33XfZuXMn2bNnT/2EvyUk7V9VsTd8X3YIIiIiIiIiIvKK22pY9rJDkGfolSu/88033zBr1iw6d+7Mxo0bmThxIu7u7qbjkyZNol27dqxevZrcuXPTq1cvYmNjk+3vxo0bbNmyhalTp7J69WrT/lWrVmFlZcWyZcsYNGgQ8+bNY9mypL/cjo6O1KhRg/Xr15vtX7duHbVq1UoyoR8cHMy6desoXbo0NjY2pv2RkZFMnz6dcePG8euvvxIaGkrPnomThk2aNKFKlSp8+umnHDlyJNn7SzBixAiOHTvGpEmTWLt2LXXr1qV9+/Zcu3bN7Npz585l/PjxLFy4kNu3bzNu3DjT8VmzZrFu3TrGjBnDL7/8Qnh4eJpKufz0008UK1aM1atX8/777zNs2DCuXLkCxJdBadeuHQ4ODixatIhff/0Ve3t72rdvT3R0dJL9DRo0iNKlS9OyZUv27NnDnj17TA89/mnHjh3kzJmTXbt2UbNmTWrWrMmgQYMIDg5ONW6A3r17kzVrVpYvX87KlSvp0KGD2e8rJZGRkSxYsIBJkyYxe/ZsDhw4QJcuXfj999+ZOXMm48ePZ/HixWYloWJjY+nevTtr167lhx9+4NatW/Tv3990vFOnTuTMmZPBgwcDsGjRIo4dO8a4ceNSTOgDLF++HIAxY8awZ88e0/az9vDhQ2JjY3FxcUm17ZQpU8iaNSvdunUz/S4h/iFU0aJFmTlzJuvXr6dly5b07dvXrKzP2LFjOXbsGNOnT2fu3LkcPnyYM2fOPHXc4eHhWFhYPNHDMhERERERERERkVfNK1V+Jzw8nPnz5zNkyBCaNm0KgJeXF+XKlcPXN342atu2balRowYA3bp1o0GDBly/fp18+fIl2WdMTAzjx4/Hzc3NbH+2bNkYOHAgFhYW5M2bl4sXLzJv3jxatmyZZD+NGjWiT58+PHz4kIwZMxIeHs6uXbuYOnWqWbsJEyawaNEiHj58SKlSpfjxxx8TxTNkyBBKliwJxCcu69evz8mTJylRogQeHh4MHz6cYsWKER0dzbJly/joo49YunQpRYsWTTI2Pz8/Vq5cyc6dO03lUNq1a8cff/zBypUr+fLLL03XHj58OF5eXgB88MEHphn4AAsXLuSzzz6jdu3aAAwZMoTdu3cnec3HVatWjQ8++ACADh06MG/ePA4cOEDevHnZuHEjBoOBUaNGmd6CGDNmDOXLl+fgwYNUqVIlUX9OTk7Y2NhgZ2eHh4dHite+efMmfn5+bN68mfHjxxMXF8eYMWPo1q0b8+fPTzV2Pz8/2rVrZ/r+5M6dO9VzEsTExDBs2DDTeNapU4e1a9eyd+9eHBwcyJ8/PxUqVGD//v3Ur18fgBYtWpjOz5UrF4MGDaJFixY8ePAABwcHrKysmDBhAo0bN2bixIksWLCAr7/+Ok0zyxO+487OzqmO278xceJEsmTJQuXKlVNt6+rqipWVFQ4ODmYxeXp60q5dO9N2mzZt2LNnD5s2baJEiRKEh4ezevVqJk6cSKVKlYD4703VqlWfKuaoqCgmTpxIgwYNzMpaiYiIiIiIiIiIpDevVFL/ypUrREdHU7FixWTb+Pj4mD4nJAmDgoKSTepnz549UUIfoGTJkmaldkqVKsVPP/1EXFwcs2bNYsaMGaZjGzZsoFq1atjY2LBjxw4aNGjAli1bcHR0TJTYbNeuHS1atMDPz4+pU6fSr18/ZsyYYbqWtbW1WWmXfPny4ezszOXLlylRogR58+Y1KyNTpkwZbt68ybx585gwYQJr165l6NChpuOzZs0iPDycuLg46tataxZLdHS0WQ38jBkzmhLQAFmyZOHevXsAhIWFcffuXUqUKGE6bmVlRdGiRTEYDEmObYLHfycWFha4u7ub+j1//jw3btygTJkyZudERUVx48YNDh8+TIcOHUz7hw8fTqNGjZK8ToMGDfDz8wOgbNmyzJ49G6PRSHR0NOPGjSNPnjxAfI39Zs2aceXKlVRL8nz66acMHjyYNWvWULlyZerWrWs2Rin553i6u7uTI0cOHBwczPYFBQWZtk+fPs3UqVM5f/48ISEhJFS/un37Nvnz5wfik/39+vVjyJAh1K9fn4YNG6Ypnhdh5syZbNy4kfnz52Nra/vU/cTFxfHjjz+yefNmAgICiImJITo62rQmhq+vLzExMWbfRycnJ9Pv+EnExMTQvXt3jEYjw4cPf+qYRUREREREREREXgWvVFI/LUnCx0ujJCTKU0o6J1UaJzWtW7emXr16pu0sWbJgbW1NnTp1WLduHQ0aNGD9+vXUr18fa2vzIXRzc8PNzY08efKQL18+qlevzvHjx011/59G8eLFOXr0KBBfNz1hlj/Ez3jesWMHVlZWrFixwlS7PYG9vb3p8z9jtbCw4FksqZBSvxERERQtWpSJEycmOs/NzQ0bGxuzskgpLQg8c+ZMU6mlhOSvh4cH1tbWZsnehAc8t2/fTjWp37VrV/73v//x+++/s3v3biZPnsykSZNMbyukJKn7TmpfwvczIiKCdu3aUaVKFSZOnEimTJm4ffs27dq1IyYmxuy8Q4cOYWVlxa1bt4iNjU3U78swZ84cZs6cyU8//UShQoX+dV/z589n4MCB+Pj4kDFjRkaPHp1oHP6tmJgYevTogZ+fHz///LNm6YuIiIiIiIiISLr3StXUz507N3Z2duzfv/+5X+vx2t0AJ06cwNvbGysrK1xdXfH29jb9JCRUGzZsyJ49e7h06RL79+9PdQZ1QjL38drxsbGxnD592rR95coVQkNDk33TAOJnuye8leDo6GgWm52dHYULFyYuLo6goCCzY97e3mkuw+Lk5IS7uzunTp0y7YuLi+Ps2bNpOj85RYsW5fr162TOnDlRbE5OTtjZ2ZntS0i62tjYJHpYkyNHDlO7hDJDZcqUITY2lhs3bpjaJawjkNbFUPPkycMnn3zC3Llzeeedd1ixYsW/uufkXLlyheDgYHr37k25cuXIly+f6Y2Gx23cuJGtW7cyf/58/Pz8zEokpcbGxoa4uLhnGTYQ/0bItGnTmD17dqqLCCcV0z9/l0ePHuXtt9+mcePGFCpUiFy5cpmt/5AzZ05sbGzMvo9hYWFmbVKTkNC/fv068+bNMy08LCIiIiIiIiIikp69/Om/j7G1taVDhw5MmDABGxsbypQpQ1BQEJcuXTLV1X5W/Pz8GDNmDK1ateLs2bMsXLiQfv36pXhO+fLlcXd3p3fv3uTMmdNsxvyJEyc4deoUZcuWxdnZmRs3bvD999/j5eVlNkvfxsaGkSNHMnjwYKysrBg5ciSlSpUylRmZN28eOXPmpECBAkRFRbFs2TL279/P3Llzk40rT548NGzYkL59+9K/f38KFy7M/fv32bdvHz4+PqY1CFLz4YcfMmPGDLy8vMibNy8LFy4kJCTErEzRk2rYsCFz5syhU6dOdO/eHU9PT/z8/Ni6dSvt27cna9asSZ6XI0cOTpw4ga+vL/b29ri6uia5UGzlypUpWrQoAwcOZODAgRgMBkaMGMGbb76ZaqmWyMhIxo8fT506dciZMyf+/v6cOnWKd95556nvNyXZs2fHxsaGBQsW8N5773Hx4sVECXt/f3+GDRtmSvyPGTOGzz//nGrVqlGqVKlUr5EjRw727dtHmTJlyJAhQ5oWsz137hwADx48ICgoiHPnzmFjY2MqBzRz5kwmT57MN998Q44cOQgMDATi3wJ5vNRQSjEdOnSIBg0aYGNjg5ubG97e3mzZsoWjR4/i4uLCTz/9xN27d00PtxwdHWnSpAnjx4/HxcWFzJkzM2XKFCwsLNL0fYyJiaFbt26cPXuWGTNmEBcXZ4rbxcWFDBkypNpHWji62NN5eDMqvF0Ug9HI3k0n+HH4KiIjkl4EGiCbV2baD2pE0XJ5sclgzeHfzzN92AqC74YDULxiPsYv7pLkud0bfcvFkzcpXjEfTdtVx6ekNxkdMuB3yZ+lE9ew45c9z+S+RERERERERETk1fVKJfUBOnfujJWVFZMnT+bOnTt4eHjQunXrZ36dJk2aEBkZybvvvouVlRUfffQRrVq1SvEcCwsLGjRowOzZs/niiy/MjtnZ2fHbb78xZcoUIiIi8PDwoGrVqnTu3NksgWhnZ0eHDh3o1asXAQEBlCtXjlGjRpmOx8TEMG7cOAICAsiYMSMFCxbkp59+SnGdAYhfRHT69OmMHTuWO3fu4OrqSqlSpdKc0If4RW7v3r1Lv379sLKyomXLllSpUiVRSZ8nkTFjRhYuXMjEiRPp0qULDx48wNPTk0qVKqVYCqVt27b079+fBg0aEBkZyfbt28mZM2eidpaWlkyfPp2vv/6aDz74AHt7e6pVq5bqA5qEc4ODg+nXrx93794lU6ZMvPPOO3Tr1u2p7zclbm5ujB07lm+//ZYFCxZQtGhR+vXrR6dOnQAwGo3079+f4sWL8+GHHwJQtWpV3nvvPfr06cPq1atTTaL369ePsWPHsmzZMlNpptQ0adLE9PnMmTOsX7+eHDlymM5dvHixKUn+uC5dutC1a9dU++/WrRtDhgyhVq1aREdHc+HCBTp16sTNmzdp164dGTNmpGXLltSqVYuwsDDTef3792fo0KF8/vnnODo60r59e27fvp2mMl0BAQGm+Bs3bmx2bP78+VSoUCHVPhKMW/wFW5cfZNvyQ4mO9f3+Q9yyODOwzXSsra3oOeE9uo1pyfjuC5PsyzZjBkYt+Jwr5/zo/378A502veoxbHZ7ejb9HqPRyLkj13i//BCz89p8WY9Sbxbk4smbABQpk4er526zbPoO7p68RMX/laXvz115EBLBgQ1H03xvIiIiIiIiIiKS/lgYn0VR9XSmTZs2FCpUiEGDBr3Q665cuZLRo0dz+PDhF3rdp2UwGKhXrx716tWjR48eLzsc+Y+LiIgwPbB59913X9h1T+7/K8mkfq58WZi5fQDdGn7LpVPxyfay1Qsx4qcOtKk4nKA7oYn6KlPVhxHzPqNlyYFEhEcBYO9kx7IToxjUZgbH915MdI6VtSUL9w9j7c9/8OuUrYmOx97wBeDrdQO4fyeYb9pN/9f3LCIiIiIiIiKvl62GZS87BHmGXrmZ+vLy3Lp1i71791K+fHmio6NZtGgRt27dSnXtAJHn4ezZs1y5coUSJUoQFhbGDz/8AMDbb7/9kiOLV7hMbsJCIkwJfYBjey5iNBgpVNqbP7ecSnSOTQZrMBqJiY417YuJisFoMFK0fJ4kk/oVaxXDKZMDW5cdTDEeBxd7bpz3/Rd3JCIiIiIiIiIi6YGS+mJiaWnJypUrGTduHEaj0VT6J6VFfF91DRo0wM/PL8ljw4cPp1GjRkkea9++PUeOHEnyWMeOHfn888+fWYxptXbtWoYOHZrksezZs7Nhw4ZE+5/2/tPq8OHDdOjQIdnjx44d+1f9z507l6tXr2JjY0PRokVZtGgRbm5uz/26jytaPi+FSnvTeXhz076OtceSycOZkL/r4CcwxBkIC44gk4dTkn2dP3aNyIho2vZvyLzxG8DCgrb9/oeVtRVuWZyTPKdOqwoc3X2eu/4hycZY7d1KFCyfj+8+n/EUdygiIiIiIiIiIunJf7L8jvx33Lp1i9jY2CSPZc6cOdm6/gEBAURGRiZ5zMXFBVdX12cVYpqFh4dz7969JI9ZW1uTI0eORPuf9v7TKjIykoCAgGSPe3t7/6v+X4Xrnj9+nb2bTrJ380nTvgDfIN7tWJNazcvT4e0xZu1/PTyChd9tZsPCP5Psr0xVH7p83QLPXG4YDUZ2rT2GVwFPLp64wdTBy83aumd1Yd7eIYz54mez6z+uaF4XRq7rz+TOs9i2YPe/vFsREREREREReR29iuV3DP4FX/g1LbMmrpKQHmmmvrzWkkp0p4Wnp+czjuTfc3R0fOIk/NPef1rZ2dk9t8T9q3Ld6MgYgu+Fcfv6XbP99wNDcXE3/31YWlni5GrP/cAwknP0jwu0rT4K50wOxMXF8SA0kkWHhnN7XeIHNrXffYOw+w/Yv+10kn0Vr5CP4XPa8+OXPyuhLyIiIiIiIiLyH2H5sgMQEUmPzh29hpOLPfmL5TTtK1W5ABaWFpw/dj3V80PvP+BBaCQlK+XHNbNjkon72u9WYPvKw8TFGhIdK14xH8PndmB2/4VsnLXt392MiIiIiIiIiIikG5qpLyKSgrFd5wOY1ckPuRfOzct3OLTrHN3HtmLKoGVYW1vRaXgzfl93jKA7oQBk9nRhzC+dmPjlL1w8cQOIn31/868AQu6FU6hMbj4f2pRVc37n1pVAs+uWqlyAbF6Z2bxkf6KYSlTKz/A57Vn9027+WHGATJ6uAMRGxxJ2PzxRexERERERERGRV42BxJMYn7fXZYa7kvoiIin45dCIRPs+rjKCO773Gd99IZ1HNGPMok4YDUb2bj7J9GErTe2sbCzJlc8T24w2pn0582bhk74NcHKxJ8A3iMVTt7Jqzu+JrvFOqwqcOXwV38t3Eh2r1bw8dva2tP6iNq2/qG3af2LXGXrXHPbvblhERERERERERF5pWihXRCQF9XL3fNkhpCj2hu/LDkFEREREREREXnGv4kK5UbfzvvBr2ma78sKv+Ty8Lm8ciIiIiIiIiIiIiIi89lR+R0REREREREREREReKAMqIPO0NFNfRERERERERERERCSd0Ex9EREREREREREREXmhDBhedgjplmbqi4iIiIiIiIiIiIikE5qpLyIiIiIiIiIiIiIvVJxRNfWflmbqi4iIiIiIiIiIiIikE5qpLyKSgtgbvi87hBQVOfJq/zN+tmzsyw5BREREREREROS18mpng0RERERERERERETktWNA5XeelsrviIiIiIiIiIiIiIikE5qpLyIiIiIiIiIiIiIvVJxm6j81zdQXEREREREREREREUknNFNfRERERERERERERF4o1dR/epqpLyIiIiIiIiIiIiKSTmimvohIOmK0MBCU5RbRtg+JyRBJ5EQXyvTOl6idIcbAXytu47fnPlHBMdi62pC/eVZyvuWeYv++u+5xbWMAEbejsM5oRdaKrhRp6/Xo+kYj19bf4eb2uzy8G00GJ2u83nEnX9NsAJycdg2/3UGPOiwQ/39somzJdsPn3w+AiIiIiIiIiLwW4oyaqf+0lNQXEUlHjICFwQKn4MxEOIYk2+74d1eJComhWEcv7D1tiQqOIbW32q5uCODa+jv4fJAD1/wOxEXF8TAw2qzNuZ99uXcylEIf5sDRKyMx4XHEhMeajhf+JBc+7+cwbV+oE4O/1yUyhrs81f2KiIiIiIiIiIg5JfVFRNIRS6MlboE5AYjKGAEYErUJPB5C0Llwqk0uSgbH+H/m7bPYpthvTHgsl5b4UbZPPjIXdzbtd/K2N30Ov/WQm1sDeXNCERyz28XvzGLej429FdhbmbajbUMxWMbhGOr2JLcpIiIiIiIiIiLJUFJfROQ1c+dICC557bm6NgC/P4KwsrUkS1kXCrTKjlWGpJdSuXsqDIwQeT+GP748Q2ykgUwFHfD5MCcZ3TOY+s2YxZbAoyEcGfMXRiO4F3ei4Ac5TA8P/incOQi7CEesYzM8t/sVERERERERkfQn8TRFSSstlCsi8pp5eCea+xfCCb/5kNK98lL445z4Hwjm7JwbKZwThdEAV1b7U+jjXJTumZeY8DgOj76EIdZg6jfybjT+++9TvHNuinfyJuRqBMcnXUmyz8igaCIdwnDQLH0RERERERERkWdGSX0RkdeM0RBfPL9E1zy45nfAo7QLhT7Kwa3dQcRFJ/0c3GgAY5yRwh/nwqOkM64FHCjZLTcPbkdx70y4qV9DjJESnXPjVtiRzEWdKNbRm6Az4YT7RSbq89buICwNVtiHOyc6JiIiIiIiIiL/bXEYX/jP60JJfRGR14xtJhvs3DLE17f/m2MOu/jyOveikz0HwDGnnWlfBmcbMjhbE3k32tTGwgocsj9q45gj/nNCmwRGo5Fbu+7hEJoJC/2nRkRERERERETkmVGmRV4YX19ffHx8OHfuXLJtVq5cSbly5V5gVP/elClTaNy48csO47W3ZMkSqlevTqFChZg3b16azmnTpg2jRo0ybdesWTPN56ZnmQo6Enk/mtjIONO+B7ejwALsMidd2z5TQYf4do/NuI8OjyU6NNZUUz9TQUeMcRDhH/VYv/HtE9okCDobToR/lErviIiIiIiIiEiS4owv/ud1oaS+vFLq16/Pli1bXnYYREdH07hx41QfQrxIU6ZMoW7dupQqVYry5cvzySefcOLECbM206dPp3Xr1pQsWfKFPhxJy3V9fHwS/WzYsCFN/YeHhzNy5Eg6dOjA7t27adWq1bMMP92JyRBJdIaHGCxjiY2II/RaBKHXIkzHs1XJRAZHa05Nv06470OCzoVxYeEtcr6V2bRQbsDBYP748ozpHIfsdmQp58K5n325fyGcsJsPOTXtGo457HAr6gRA5uJOOOfJyKkZ1wm9GkHIlQjOzLpB5uJOZrP3AW7tvIdLfnsyRJvvFxERERERERGRf8f6ZQcg8jg7Ozvs7JJPAkZHR5MhQ9IzjZ+l8ePHkyVLFs6fP//cr5VWuXPnZsiQIeTKlYvIyEjmzZtH27Zt2bp1K25u8bOhY2JiTIn/5cuXv7DY0nrdMWPGULVqVdO2s3Paaq37+fkRExND9erVyZIly7+ON727k/0qcTYxADw8C3/2j/+e1l1cBgBrOyvKDSrAuXk3+XPgeTI4WpO1UiYKtMpu6iMmIo4HflFm/ZbonJtz8305Mv4yFhbgVtiRsv3zY2ltAYCFpQVl+uTj3DxfDgy/iJWtJR6lnPFpk9Osn5iIOPwP3qfwx7kI2/TchkFERERERERE0rGkV/2TtFBSX545g8HAnDlzWLp0Kbdv38bd3Z1WrVrRsGFDAG7evMno0aM5efIk3t7eDB8+nNKlSwPx5XdGjx7N4cOHgfjZ6du2bePDDz9k+vTp+Pn5cf78edq0aUOBAgUAWLNmDdbW1rz33nt0794dCwuLRDGFh4dTuXJlpkyZQvXq1U37t27dSt++ffnzzz/JmDEjAL///jt79+5lypQp7N69O833vXr1aiZPnkxISAjVqlVj5MiRODo6Jtt+0aJF/Pzzz9y+fRsnJyfKlSvH5MmTk22fMH4JBgwYwPLly7lw4QKVKlUCoFu3bkD8OD6pkJAQRowYwd69e4mIiCBr1qx07NiR5s2bp3puWq/r7OyMh4fHE8W1cuVKBgwYAECtWrUA2L59O1OnTiU0NJRp06aZ2o4aNYrz58+zYMGCJ7pGepPjWmHT5yJHkv5n3DGHHeUHFUi2j5w1MpOzRmazfdb2VhT/3Jvin3sne56dWwZKf5k3xfhs7K14Z3783/RZYlNsKyIiIiIiIiIiT0ZJfXnmvvnmG5YtW8aAAQMoW7Ysd+7c4erVq6bjkyZNol+/fnh7ezNp0iR69erFb7/9hrV10l/HGzdusGXLFqZOnYql5aOKUatWraJFixYsW7aM06dPM2TIELJnz07Lli0T9eHo6EiNGjVYv369WVJ/3bp11KpVy5TQv3v3Ll999RU//PBDim8MJBXj9u3b+fHHHwkNDaVHjx7MmjWLnj17Jtn+1KlTjBo1ivHjx1O6dGlCQkJMDzLSIjo6miVLluDk5ISPj0+az0vJ999/z+XLl5k1axaZMmXixo0bREZGpn7iExg+fDiDBg0iV65ctG7dmubNmyf5EOZx9evXJ1u2bHzyyScsW7aMbNmymd5MEBERERERERGR9CmOlHNCkjwl9eWZCg8PZ/78+QwZMoSmTZsC4OXlRbly5fD19QWgbdu21KhRA4if4d2gQQOuX79Ovnz5kuwzJiaG8ePHJ0rkZsuWjYEDB2JhYUHevHm5ePEi8+bNSzKpD9CoUSP69OnDw4cPyZgxI+Hh4ezatYupU6cCYDQa6d+/P61bt6Z48eKmeNPCaDQyZswY08z8Ro0asW/fvmST+rdv3yZjxozUqFEDR0dHcuTIQZEiRVK9zs6dO/nyyy95+PAhHh4ezJ0795kluP38/ChcuDDFixcHIGfOnKmc8WS6detGxYoVyZgxI3v27GH48OFERETw0UcfpXienZ0drq6uALi5uT3xTH8REREREREREZHXiRbKlWfqypUrREdHU7FixWTbPD6zPCFBGxQUlGz77NmzJ5m4LlmypNks71KlSnH9+nXi4uL48ccfKV26tOnHz8+PatWqYWNjw44dOwDYsmULjo6OVK5cGYAFCxbw4MEDOnbsmGwsj/c5ZMgQ0/4cOXKYldrJkiUL9+7dA2Dt2rVm5x0+fJjKlSuTPXt2atWqRZ8+fVi7di0PHz5Mtn2CChUqsHr1ahYvXkzVqlXp0aOH6Tr/1nvvvcfGjRtp3Lgx48eP5+jRo8+k3wRffPEFZcuWpUiRInz22We0b9+eOXPmPNNriIiIiIiIiIiIvO40U1+eKVtb21Tb2NjYmD4nJOUNhuSXxkgojfMkWrduTb169UzbWbJkwdramjp16rBu3ToaNGjA+vXrqV+/vqnsz/79+zl+/LhppnqC5s2b07BhQ8aNG8fq1atN+x9P4idVOshoNAJQs2ZNSpYsadrv6emJnZ0dq1at4uDBg+zZs4fJkyczdepUli9fnmT7BPb29nh7e+Pt7U2pUqV45513WL58eYoPItKqevXq7Ny507SmwCeffMIHH3xAv379/nXfSSlZsiTTpk176sWPLSwsTGOcIDZW9dtFRERERERERNIDgzH1Ni/LjBkz+O2337hy5Qp2dnaULl2a3r17kzfvo3UGo6KiGDt2LBs3biQ6OpoqVaowdOhQ3N3dk+3XaDQyefJkli1bRmhoKGXKlGHYsGHkzp37ieLTTH15pnLnzo2dnR379+9/7tc6efKk2faJEyfw9vbGysoKV1dXU/Lb29vblHRv2LAhe/bs4dKlS+zfv99s8dnBgwezZs0aVq9ezerVq5k5cyYQvwZAQhmdx/vMnNl8kdHkODo6mp2XUKvf2tqaypUr07dvX9auXcutW7fYv39/su2TYjAYiI6OTvugpcLNzY2mTZsyceJEBg4cyJIlS55Z3/907tw5XFxcniqhD/GxBgYGJupTRERERERERETk3zh48CAffPABS5cu5aeffiI2NpZ27doRERFhajN69Gh27tzJd999x4IFC7hz5w5dunRJsd9Zs2axYMEChg0bxtKlS8mYMSPt2rUjKirqieLTTH15pmxtbenQoQMTJkzAxsaGMmXKEBQUxKVLl6hUqdIzvZafnx9jxoyhVatWnD17loULF6Y6q7x8+fK4u7vTu3dvcubMaTYjPnv27GZt7e3tgfg1AbJmzfpMY9+5cyc3b96kfPnyODs78/vvv2MwGMiTJ0+S7SMiIvjxxx+pWbMmHh4e3L9/n0WLFhEQEEDdunVN7fz8/AgJCcHPz4+4uDhTktvLywsHB4cUY/r+++8pWrQoBQoUIDo6ml27diW7zsE/pXbdHTt2cO/ePUqWLImtrS179+5lxowZtG3bNk39J6VixYrMmTOH1atXU6pUKdauXculS5fStDbB6ybiThSXV/oTdCaMqOAYbDPZkL2qG/maZsXSOv7Z7aVlflxe4Z/oXCtbS2r/XCrJfkOvR3BlTQDB58OJDoslo0cGctXyIHf9LKY2kfdjuLDAl5ArEUQEROFd14PCH+cy6ycgx2Wi7B8k6t/ugRNZ/JL+zouIiIiIiIjI6+1VXij3nyWjx44dS6VKlThz5gzly5cnLCyMFStWMHHiRFPOc/To0dSvX5/jx49TqlSpRH0ajUbmz59Pp06dqFWrFgDjx4+ncuXKbNu2jQYNGqQ5PiX15Znr3LkzVlZWTJ48mTt37uDh4UHr1q2f+XWaNGlCZGQk7777LlZWVnz00Ue0atUqxXMsLCxo0KABs2fP5osvvnjmMaWVk5MTW7duZerUqURFReHt7c0333xDgQIFkmxvZWXFlStXWLVqFffv38fV1ZXixYuzaNEis3MmT57MqlWrTNtNmjQBYP78+VSoUCHFmGxsbPj222+5desWdnZ2lC1blm+//TZN95Pada2trVm0aBGjR48G4pP9/fv3T3ZR47SoWrUqnTt3ZsKECURFRdG8eXOaNGnCxYsXn7rPV11Ajss4hGbCMcx8jYkHfpFgNFK0vRf2WW0Jv/mQ07NuEBdpoFCb+AWP8zT0xKu2+SLDh76+hHNe+2SvF3olAltna0p0yY1d5gwEXwzn9KwbWFiCd934xL4hxkAGZ2vyNcvKtY13kuzH/bY3WDx6py7OKg5/r4vYh7k81TiIiIiIiIiIiDyN6OjoRFUvMmTIkGolibCwMABcXOJzGadPnyYmJsa0VidAvnz5yJ49e7JJfV9fXwIDA83OcXJyomTJkhw7duyJkvoWxn8WpRZJB9q0aUOhQoUYNGjQyw5FXnO1Ld992SGYJJXUL3Ik6WezV9cFcGNrINUnF0vyeOj1CP7sd543hhbErbBjkm2ScnbuDcJvRfLGVwUTHTsw/CLOuTOazdQ/WzbxOgehroGEuAWQ42oRLI2qAiciIiIiIiLyvG01LHvZISRy6mbOF37NXav7MXXqVLN9Xbp0oWvXrsmeYzAY6NSpE6Ghofz6668ArFu3jgEDBnD69Gmzti1atKBChQr06dMnUT9Hjx7lvffe448//iBLlkdVELp3746FhQXfffddmu9DM/VFRF5DMRFx2Dgm/0+874572GezfaKEvqlfh3/3n44HzvexD3dVQl9EREREREREXqiOHTvy6aefmu1LbZb+8OHDuXTpEr/88svzDO2JKKkv8h8xZMgQ1q1bl+Sxhg0bMmLEiCSP/fjjj8yYMSPJY2XLlmX27Nn/OrYGDRrg5+eX5LHhw4fTqFGjf32N9Cgk0x1C3R6VtDFaGIiyi+B+lkdjleduETK6m//H54F/JDc238Hnw6SfeMdFG7i9J4g8jT2fKJ77F8Lx33efsn3zP9F5j4uyjSDGNhK3gBf/NF5EREREREREXh0G44uvqZ+WUjuPGzFiBLt27WLhwoVma266u7sTExNDaGgozs7Opv337t3Dw8Mjqa5M++/du2c2U//evXsUKlToie5DSX1JlxYsWPCyQ0h3unfvTrt27ZI85uiY/Gzt1q1bU69evSSP2dnZPZPYZs6cSWxs4jItAJkzZ34m10iPHEPcsA9/VHf+XtYb2Ie7kPGxfbaZbMzOiQyK5siYy2StmIlcb7sn2W/AoWBiI+PIUS3tYxt28yFHJ14hf/NsuJd0Tv2EZDxwCcImyg7bqORr+YuIiIiIiIiIvExGo5GRI0eydetWFixYQK5cucyOFytWDBsbG/bt20edOnUAuHLlCn5+fknW0wfImTMnHh4e7Nu3j8KFCwMQHh7OiRMneO+9954oPiX1Rf4jMmfO/FQJcldXV1xdXZ99QI/JkSPHc+0/vbIyWGNlePTPtIXBEstYa2xibE37LK0ePdWODIrm4IhLuBZ0oGgHr2T79d1xD48yLti62iTb5nHhvg859PUlcr2dmXzNsj3FncQzWBh44BiMS1DW1BuLiIiIiIiIyGstjhc/Uz+thg8fzvr165k2bRoODg4EBgYC8Qvb2tnZ4eTkRPPmzRk7diwuLi44Ojry9ddfU7p0abOkft26denVqxe1a9fGwsKCjz76iOnTp+Pt7U3OnDn5/vvvyZIlC7Vq1Xqi+JTUFxF5DSQk9J3z2lO8kzcWlkn/hzHiThRBZ8Mo0ztfmvoNuxmf0M9RzY2Crf/dw5cIx2CMFkYcQl3/VT8iIiIiIiIiIs9TwoK4bdq0Mds/ZswYmjVrBsDAgQOxtLSkW7duREdHU6VKFYYOHWrW/urVq4SFhZm2O3TowMOHDxkyZAihoaGm0ta2trY8CQuj0Wh8mhsTEfkvqG357ku7tsEiDqOlIcU2xfbbERUcw8ERl8jonoHinc0T+v+cjX9piR++u+5R44diiRL/AQeDubj4FlW/LQr8ndAfeQn3Es74fPgooW9hCRmcH/Ubei0CgNMzb+CQzZY8DT2xtLbAMWdGzpZ9VFYpIOdfWMXa4O7v/YQjISIiIiIiIiL/xlbDspcdQiJHbyRfZeB5KeN144Vf83nQTH0RkVdUaKZAQjPfSbFNvrtFCTobToR/FBH+UezqfNrseN3FZUyfjQYjt36/R47qbknO5I+JiOOBX5Rp23//faJDY/HbE4TfniDTfjv3DNSYWsy0/Wf/849ivhLB7b33E7WJsYkkKmMEHrfypOHORUREREREROR1F4flyw4h3dJMfRGRFLzMmfppUeTIq/1s9vGZ+iIiIiIiIiLycryKM/UP3cj9wq9Z3uvaC7/m8/BqZ4NERERERERERERE5LVjML66C+W+6vSOg4iIiIiIiIiIiIhIOqGZ+iIiIiIiIiIiIiLyQsWhmfpPSzP1RURERERERERERETSCc3UFxEREREREREREZEXKs6o+eZPSyMnIiIiIiIiIiIiIpJOaKa+iEg6duGjvC87hFRcfNkBpMg6i8fLDiFFxqjolx1CiuJCQl52CCmytLV72SGkyBgb87JDSJFVVs+XHUKKYm/5vewQRERERETkXzBovvlT08iJiIiIiIiIiIiIiKQTSuqLiIiIiIiIiIiIiKQTKr8jIiIiIiIiIiIiIi9UHBYvO4R0SzP1RURERERERERERETSCc3UFxEREREREREREZEXKs6o+eZPSyMnIiIiIiIiIiIiIpJOaKa+iEg6V6JcHpp+9CY+xXJi72DLrRv3WD7vD3ZuOJHqubUbl6bZR1XI4Z2ZiPAo/th6mh9GrTNr0/zjKtRrUZ4s2V0JvR/B+iUHWDxrFwBu7k506FOPAkVykN3LjTWL9jFj/MbncZvPjY2tNV3Hv0f+El54FcjKga2nGfnpjBTPyZLLjfd71qdklYJk8nAmKCCEHSsOsvi7zcTGxAHwQe8GfNi7QaJzIyOiaJq3JwBePtlo0+d/FCjphWeuzMz4ahmrZ+1MdE6eojn5YsL7FCydh5B7YayZuYPlkzenGGOpaoX4aFATchfOSWREFNsW/8m8kaswxBnS3G/dj6pSq3UlvAvnAOCv49f5aeQqLh69ah5fcS+6Tm2PT/l8BAeGsmbqJpZOWJtifB653Ok+rQMl3yrKw/BIts7/nTkDFpnFZ5PBmg+HvMvbH1QlU1ZXgm7fZ+HI5Wz5KX6M3vm4Bn1++sKs3+jIaBrYf2AeX7FcdPnuYwqWzUPI3TDWTN/Ksm83pBhfAic3R6YfHIVHDjeaZe3Ig5AIAHrN/Ix32lRN1P76WV8+KzvAtN2wYy1a9KyPm6cLV07dZNqX87lw+Ip5fMW96DK5LT7l8hISGMbqHzaz7Jt1/+zaJG8JL1r1aUyxNwvh7O5EwLVA1s/axuopm0xt3mxSnoYda5O3ZG5sbK25ftaXBSOWc2TrSVOb4lUK8W6vhhQok4fM2d0Y1nwif649bHYtG1truo5pSf7iufDK78mB7WcY2X5OmsaufM0ivN+jDnkKZyc6MpZTB/4yO9cjeya6jH6XEpULEPkgim3LD/LT2PVm34G3mpSlRae3yZ7Hg4jQhxzedY7ZX68hLDgiTTGIiIiIiMiry6Ca+k9NSX0RkXSucCkvrl70Z+mc3QTfC+eN6j70HtWCB2GRHNx9Idnzmn30Js0+qsLsbzdx4aQvdvY2eGbPZNamU/8GlKlcgNnfbOLqpQCcXDLi5JLRdNwmgxUhQQ/4deZOmrZ587nd4/NkaWVJdGQMa2fv4s0GpdJ0Tq78WbGwtGBKn1/xu3oH70LZ6f7NB9jZ2zJ7+EoAVkzbxsaf/zA7b8zyblw8ft20bZcxA/437rJn3VE+G9EiyWvZO9kxakVPjv9+jilfLiR3kRz0nPIJD0Ii2PTz7iTPyVMsJyOWdmfxNxuY8Plc3LO50vXbNlhaWjJ7yLI091uiig+7Vhzk7IHLREfF0LJ7PUav7EnHSkO4dzv4734yMnbLVxzddpLvO80kT3Eves3pTHhwBBtnbUt6zC0tGbV+AEH+wfR4czBu2Vzp+3NX4mJimTvoV1O7wUu+JJOnC9+0n47fX/64ZcuEpaX5/+h7EBLBp4W6m7aNRmOi8Ru9ri/Hdp5hctefyF0sF1/+2J7w4Ag2zU38AOWfvvyxPVdP3cQjh5vZ/um9FzD3qyWmbStrS6YfGMXulQdN+6q3qMBn495nStefOH/oMk271GXU2r60K9mXkMBQ0/iN2TiQYztOMfmL2eQplosvZ33Og5AINs7enmRMBcrkJTgwlLEfTyXQ9x5FKxWk+/QOGOIMrJ22BYDiVQtzZNsp5n61mPDgCOp8XIMRq/vS7c3BXD5+DQA7BzuunLzOlnm7GLq8V5LXsrT8++9j7m7erF8y1fFK8Ga9knQf34p54zZwYu9FrKwt8fbJ9li/Fgz/+TPu3wmjV5PvcMviTO/vPiQ21sDP49YDUKRcHnp99yEzh6/iwLbTuGd1pcuYlnQf35qvP5ub5lhEREREREReN0rqi4ikc0tm/262vWbRPspWLsCbtYomm9R3dLbjoy61GNZ1AccPPJo1fPVigOlzrjweNGhZgc+bTcb32l0AAm7dN+snwC+YH8fFz3iu07TsM7mfFy0qIpqp/RYDUOSNvDg426d6zpGdZzmy86xp2//GPVZM30aDj6uZkvqREVFERkSZ2uQpkgNvn+xM6fsoaX3x+HVTkv/TwU2SvNZb71bEJoM133b5idiYOK6f9yNvcS+ada6dbFK/etPyXDvjyy8T4pOjt6/eYc6w5Qyc25FF49fyMDwqTf2O/2y2Wb/fdZvHmw3LUKpaYbYv2QdAzQ+qYp3Bmm/aTSc2JpbrZ33JVyoPzXv+L9mkftl3SuBVJCd9a48g+E4Il0/Az0MW037sh8wftozYmFjK1SlFiepF+ChfF8LuhwMQcD0wUV9Go5H7AcFJXgegZus34++z46z4+zx3i3wlvGjerW6qSf3/dXgbBxd7Fo1ezRt1zRPaEaEPiQh9aNqu1LAsjpkc+G3Bo99Js2712PzTLn5bEP9wZ3LXn3ijXknqfFyNpRPjfzc1368SP37tf4yP76wveUvmpnn3+skm9bfM22W27X/1DoUrFqBKk/KmpP6Pveabtfnpq8VUaliWig3KmJL6h7Yc59CW4ymOQdTDaKYOjH8QVKR8HhycM6bYHuIflH0+vBmzv17Lb0v2m/bfuPTo35cy1QrhVSArA9+bRvDdMK6cvcX8iRtpO6Ahi77dRGxMHIXL5uaObxBrf4of04CbQWxauJd3O9dKNQYREREREXn1xaky/FPTyImIvIYcHG0JC0m+PEXpSvmxtLQgcxZnZq7pzoJtfRk4sTXuni6mNhVqFMLfN4g3qvkwb1Mvft7cmx7DmuKYhqTef5GDU0bCgh8ke7zuB2/i+1cAZw5cfqJ+C5fPy6k/L5rK+gAc2X6aXAWz4eiS9AMImww2REfFmO2LfhiNbcYMFCiZ+6n7tbXPgLWNldl9FqlYkFO7zxIbE2vad3jLcbwK5cDR1SHJfopU8uHaqRsE3wl57JwTOLjY4100JwCVGpXj4uHLtOzbmF9vzuCn89/z2YQ2ZLDLYNZXRkc7Fl6dxqLr0xm+qi/eRXKaHS9cIT+n9l4wv8+tp8jlkx1H1+Qf4HgVys77A5owof0MjAZDsu0S1P24Osd2nOHOjXsAWNtYUaB0bo7uOGNqYzQaObbjDEXeyP8ovooFOP3HOfP4fjtBrhTGLykOLvaEBSX//bOwsMDeKSNh95Nv86zkL54T92yuGI1Gpm7qw6LDIxgxv6PZTP3CZXNz7bwfwXfDTPuO/H4OB+eMeBfMCsC5I9dwz+ZK+beKAODq7kSVBqU4tOMsIiIiIiIi/2VK6ouIvGaq1ilGgWI52br6aLJtsuV0w8LSgtYdajBj3AZGffkrTi4ZGTPrU6ytrUxtsmR3peo7xZgwaDnfDF5B/iLZGfztey/qVtKNbLk9aNSuBpvm70nyuI2tNW81K8+WX/984r4zZXEh+O9SLQkStjM99hDmcUd2nKbwG/mp0fyN+Ic32Vx5v29DANyyujx1v22HteCefzDHdj1KqrpldeX+Y8l5gPsBIaZjSd5TVtdEs+sTthPOyZbHk2JVCpG7aC6GNZvA9J7zqNq8It1+aG865+YFPya2m8bQJuMZ12YKFpYWfL93FO6PlcrJ5Oliisd0rb/jzeSZdHw2GawZ8PMXzB74K4E37yXZ5nFu2VwpX6cEmx+bQe/s7oSVtZXZg4v4a4eS6bFxcfNMYvwS4sua9O/hn4pUKkj1dyslO7MfoMWX/8PO0Y7dy/alqc9/I5tXZgA+6FmXXyf/xtBPZxIe8pBxS7uYHqRk8nA2S+gDBAeGmY4BnD18lfHdFtB/2sesu/Itvx77mgdhD/lh8LLnfg8iIiIiIiKvMiX1RUReIyXK56HXiOZ8P2wV1y/fSbadhYUFNjbWTB+zniN//sX5kzcZ23cJ2b0yU/KNPPFtLC3IYGvDxEHLOXP0OicPX+W7oasoVSEfOXO7v6hbeuVlzurC179+wR/rjrJ50d4k21SuV4qMjnZse6wUyfN0dOdZ5gxZRtdvP2RdwI/MOTSKQ1tPAWAwGFM5O2kte9SjRrM3GNlmGjFRsamf8C9ZWlpgNMKYDydz4dBfHNx0jBm9fqb2x9VNs/XP7b/ItgW7uXziGid3n2V484kEB4bSoGPtf3XtT0e25MYFP3YsTttDmNofVCU8OII/1x75V9d9GrmL5mTYit4sHLmCI9tOJtnmrdZv0uar5ox677tED3KeBwvL+P95uWTKb+zddIK/TvkyqdciMELVNK5bAeBVwJPPhzfjl++20LX+RAZ9OB3PnJnpOqbVc4pcRERERERepDij5Qv/eV2opr6IyGuieLncDJ/ahhkTNrJ93fEU2wb9PUP2xpVHif+Q+xGEBkfgkc01vk1gGLExcdy6/mimckJ7j2wupjr7/2Vuni6MXdGDs4evMrn3L8m2q/tBZQ5uPZVoZnJa3L8TguvfM5cTJGz/cwb641ZO28rKaVtxy+pCeHAEnl7utB3aHP9rgU/cb/Mu79CyRz0GNPmGq2d8zY4F+QeTKYv5jPKEmf5B/sFJ35N/MIXK5zfblzBrPuGce7fvc/dWEBGhj8pI3Th3C0tLSzxyunHrL/9E/cbFxnH52FVy5Mv66FoBIYnePEiIN7la/KWqFyF3sVxUbVo+fodF/OK8y3yn8eu4tSz4eqVZ+zofV2P7r3vNSuiE3g0jLjYO13+OTRZn7j82LkEBSYxfQnz+yf9+AbwK52DclsFsnL2dX8asSrJNjZaV6DnjM75u/R3HdpxOsb9nJejv78/jNfRjouO4feMuWXLEL8Z9PzCUgqW8zM5z9XAyHQNo+UVtzh66wooZOwC4dt6PHyKimbiyOz9P2EDgLb/nfi8iIiIiIiKvotfn8YRIOuPr64uPjw/nzp1Lts3KlSspV67cC4zq35syZQqNGzd+2WH855Qol4cRP3zE3Elb2LT8UKrtzx6LX5z18Rn3js4ZcXa1545fsKmNtY0V2XI+KmWSwzu+fUKb/7LMWV0Yt7IHf528waTu8zEak54B7+mVmRJvFnyq0jsA5w5doXjlglj9XRYJoMxbRbh58TbhKaybkCDIP4ToyBhqNH+DO773+OvE9Sfqt0W3urzf538MbvEdl/5e1PdxZ/dfpHi1Imb9lK1dghvnbxGezBoDZ/ddIHdxL7OHCmVql+BBSAQ3zsY/NDjz5wUyZ8+EnYOdqU2OgtmIizMQ6BuUZL+WlpbkLu7FvceS5ucO/EXxN33M7/PtYty84Ed4cNLjN/K9yXR6YxCdKgymU4XBfNcpfsHgXrW+Zu0M88V/S1QtRI78Wdk8z3zB6tiYOC4du0bpv+vBQ/wbMqXeKsrZg389im//JYpVLWweX60S3Exh/AC8i+Rkwtav2LpgN/OGLEmyTY1Wlek1uxNjPpzMwU3Hku3rWfvr1E2iI2PIkTeLaZ+VtSWeOTNz5+/f3bkj18hdKDsumR1NbcpU9eFB6ENuXIp/YGObMQOGf/xdxcXFr2/w93MWERERERFJxwxYvvCf18Xrcycir6H69euzZcuWlx0G0dHRNG7cONWHEC/SlClTqFu3LqVKlaJ8+fJ88sknnDhxwnTc19eXgQMHUrNmTUqUKEGtWrWYPHky0dHRLzHq56NE+fiE/ppF+9iz9QyZMjuSKbOj2YK2lWsWYdbaHqbtW9fv8eeOs3ze738ULumFd/4s9B7VAt+rgZw4dAWAY/svc+nsLXqObEa+QtnIXyQ73YY05sifl8xm7+f1yUZen2zY2dvi4uZAXp9seOX1eGH3/yx4FcxK3qI5cXJ1wME5I3mL5iRv0UcLrhYs7c3MP4aQ+e8a5/EJ/Z4E3rrP7OErccnsRCYPZ1Mt8Me907oSQQGhHN5+JtExaxsr07WsbazInM2VvEVzki33o/HbufwAMdGx9JzyMd6FslOtaXmadKzFymlbTW0qNyjNrAMjzfpu0bUOuYvkwLtQdt7v/T9a9qjH9H6/msrvpKXfd7vX5aOBjfm2yzwCbtwlUxZnMmVxxs7B1tRmxy97iI2OpdfsTngXyUn1lpVp0q0+KyatN7V5s8kbzDn7nWn7yG8nuXHWl37zu5K3hDfl3inJJyNbs3baZmKiY039ht4Lo8/czngVzknxqoX5bHwbtvy0g+jI+L/jD79qQdnaJciaJwv5S+eh/4KueHp7sOmx2vI7lvxJTHQsX/7YHu/COajeogJNvqjDismbH41fo7LMPj7OtH376h2un/U1/SS83XDjvB8h/yhfU+eT6pw7+BfXz5q/wQCwcvIm6n1ag1ofVCGXT3a6Tv4EO3tbfpu/+1F8v8aP35ezOsaP37uVaNq1Liu+3/ho/BqXZ86pb0zbuYvGJ/SPbDvFiu82kMnThUyeLri4O5navNX6Tfr+1JmZfRdw/uBfpjb2j/27YOdgS96S3uQt6Q1A1jxZyFvSG49cmc3uw6uAJ3mL5MDJ1R4Hp4zkLZKDvEVymI4XLOXFzJ0DTX8fEeFRbFy4lza96lGmmg858mahy+iWAPyx4TgAR3ef58Ylf/p8/yF5CmenTPVCfNSnAevm7yEmOv6NhwPbTvNm3ZI0aPMmWb0yU6RcHjqNaM75Y9cICnj+ZYREREREREReVSq/I/IKs7Ozw87OLtnj0dHRZMiQ4bnHMX78eLJkycL58+ef+7XSKnfu3AwZMoRcuXIRGRnJvHnzaNu2LVu3bsXNzY0rV65gNBoZMWIE3t7eXLx4ka+++oqHDx/Sr1+/lx3+M1W7cRns7DPQukMNWneoYdp/8tAV+radA4CDky258pgn2icOXE7HvvUZMe0jjAYjpw5fZdDnPxMXGz8T1mg0MrTLAjoP+B8T5nUg8mE0h/dcZOaETWb9TFvexfS5YNEc1GxQioBb9/m47sTndMfP3ohFX+D5WCLzh+0DAaiXtTMQP2M4V4GsWNnEz6YuXb0wOfJmIUfeLCw8Psasr4RzIH5mdu1Wldi2ZH+StezdsrqYrgXQonNtWnSuzck/L9Kv2XcARIQ+ZFDzSXwx4X2m7PyKkHthLJqwjk0/P0oMOzhnJFfBbGZ9l6tVjNa9GmCTwZorp28y/IOpHN72qPxKWvr9X9saZLC14av5nc36Xjh2LQvHrf27nwj61xlJ16ntmXZ4HCF3w1g0cjkbZz2a0e7gYo9XoUdJYIPBwOCGY+g+rQPf/zmKyAdRbJ2/y2zGeeSDSPq/M5IvJrfjh0NjCb0Xxu5l+/hp8GJTG8dMDvSc+TmZsroSfv8Bl45cofubg7hx7lGCPSL0IQMbjqfLdx8z9c8RhNwLZ9GYVWyau/Ox8bMnl0/2RL+f1Ng7Z6RKk/L82Hthksd/X34AF3cnPhrSnEyeLlw5eYNBjScQfOdRQjoi9CED6o+my+S2/HBgNCF3w1j49UqzRW/tXezJ9dj4VW1WEdcsLtT6oCq1Pqhq2u9/LZCPCnQFoH77t7G2sabrlHZ0ndLO1Oa3+b8zsd10AAqWzcfE7UNMxz6f+FGiNgAjfu5o/vexpS8A9XJ1B8DWLgO58nuavW0we9Qa4uIM9P6uDbZ2Npw/dp3+racSHvIQiF/bYdgnM+kyuiXfrulJVEQ025YfZMHERw8zti07iL2DLQ0/rkr7r5rwIPQhJ/ZeYu6Ytcn8RkREREREJD2JM+oV3KdlYUyuXoCIPBMGg4E5c+awdOlSbt++jbu7O61ataJhw4a8/fbbTJkyhQULFnDy5Em8vb0ZPnw4pUuXBuLL74wePZrDhw8D8bPTt23bxocffsj06dPx8/Pj/PnztGnThgIFCgCwZs0arK2tee+99+jevTsWSdQoCA8Pp3LlykyZMoXq1aub9m/dupW+ffvy559/kjFj/GzO33//nbFjxzJlyhQaNGjA6tWrKVy4cLL3mxDjp59+yuTJkwkJCaFatWqMHDkSR0fHZM9btGgRP//8M7dv38bJyYly5coxefLkNI9zeHg4ZcuWZd68eVSqVCnJNrNnz+bXX39l+/btSR5PSm3Ld9Pc9mWwKlrwZYeQorgzF192CCmyzvJqv1FgjHq13yyJC0m55vvLZmmb/EPRV4ExNuZlh5Aiq6yeLzuEFMWqpr6IiIiISJptNSx72SEksvJy6Rd+zWb5Xlxp0udJM/VFnrNvvvmGZcuWMWDAAMqWLcudO3e4evWq6fikSZPo168f3t7eTJo0iV69evHbb79hbZ30n+eNGzfYsmULU6dOxdLyUQWtVatW0aJFC5YtW8bp06cZMmQI2bNnp2XLlon6cHR0pEaNGqxfv94sqb9u3Tpq1aplSujfvXuXr776ih9++CHFNwaSinH79u38+OOPhIaG0qNHD2bNmkXPnj2TbH/q1ClGjRrF+PHjKV26NCEhIaYHGWkRHR3NkiVLcHJywsfHJ9l2YWFhuLi4JHtcRERERERERERejDhVhn9qSuqLPEfh4eHMnz+fIUOG0LRpUwC8vLwoV64cvr7x5SHatm1LjRo1AOjWrRsNGjTg+vXr5MuXL8k+Y2JiGD9+PG5ubmb7s2XLxsCBA7GwsCBv3rxcvHiRefPmJZnUB2jUqBF9+vTh4cOHZMyYkfDwcHbt2sXUqVOB+NIr/fv3p3Xr1hQvXtwUb1oYjUbGjBljmpnfqFEj9u3bl2xS//bt22TMmJEaNWrg6OhIjhw5KFKkSJJtH7dz506+/PJLHj58iIeHB3Pnzk00LgmuX7/OwoULX7vSOyIiIiIiIiIi8t+ixyEiz9GVK1eIjo6mYsWKybZ5fGa5h0d8KZCgoKBk22fPnj3JxHXJkiXNSu2UKlWK69evExcXx48//kjp0qVNP35+flSrVg0bGxt27NgBwJYtW3B0dKRy5coALFiwgAcPHtCxY8dkY3m8zyFDHtVlzpEjh1mpnSxZsnDvXvzCqmvXrjU77/Dhw1SuXJns2bNTq1Yt+vTpw9q1a3n48GGy7RNUqFCB1atXs3jxYqpWrUqPHj1M13lcQEAA7du3p27dusk+5BARERERERERkRfHYLR84T+vC83UF3mObG1tU21jY2Nj+pyQlDcYDMm2TyiN8yRat25NvXr1TNtZsmTB2tqaOnXqsG7dOho0aMD69eupX7++qezP/v37OX78OMWLFzfrq3nz5jRs2JBx48axevVq0/7Hk/hJlQ5KWL6jZs2alCxZ0rTf09MTOzs7Vq1axcGDB9mzZw+TJ09m6tSpLF++PMn2Cezt7fH29sbb25tSpUrxzjvvsHz5crMHEQEBAXz00UeULl2akSNHPunQiYiIiIiIiIiIvFKU1Bd5jnLnzo2dnR379+8nV65cz/VaJ0+eNNs+ceIE3t7eWFlZ4erqiqura6JzGjZsSNu2bbl06RL79++nR48epmODBw82275z5w7t2rVj0qRJpiS7t7f3E8fp6OiY5IK51tbWVK5cmcqVK9OlSxfKly/P/v37eeedd1JcYPdxBoOB6OhHC4smJPSLFi3KmDFjzNYgEBERERERERERSY+U1Bd5jmxtbenQoQMTJkzAxsaGMmXKEBQUxKVLl6hUqdIzvZafnx9jxoyhVatWnD17Nk3148uXL4+7uzu9e/cmZ86cZjPis2fPbtbW3t4eiF8TIGvWrM809p07d3Lz5k3Kly+Ps7Mzv//+OwaDgTx58iTZPiIigh9//JGaNWvi4eHB/fv3WbRoEQEBAdStWxeIT+i3adOG7Nmz069fP7OSRglljl53js4Z6Tzwf1SoXgijwcjebWeYPnYDkQ+jkz2n25DGlKqYj8wezjyMiObciRvMmbQZ36t3AchTMCut2lWjaBlvnF0dCPC7z4alB1mzaJ+pjzffLkKDVhXI65MNG2sLrp/xZcHwpRz+7cRzv+dnydHVns6jWlLhneIYDEb2bjjOj4OXERkRleJ5hcrm4eMBjShUJjeGOAOXT/sy+L2pREfGAJCveC7aDm5CwVLeGOIM7N1wnJlDVyTqt1arijT7rCY58nkSEfaQP9Yc5oc+vzwWnwOdx79HhTolMRqN7F17hOkDFhP5IOX4Eoxc1p3ytYoz/IOp7Nt43LS/YOncfDq0OQVKeWM0Grl45Cqzhy3n6un4dTVy5vek67dt8PLJjoOzHff87rPj1z0sGL6MuNg4Uz9OmRz5YnJbKjYsi9Fg5I+VB5jW/SciH0SmKb5RGwbyRr3SDG06nj/XHHoUX7l8tB/zAQXK5sVoNHLh4F/M6reQKyevx8dXMDvdp3fAu0hOHFzsuXc7mJ1L9rFw1Kp/xOdA528/okL90hgNBvasPsz03gvSPH5fr+5N+TolGdbyO/atO/IovrJ5aDuyFQVK58ZohAuHLzNn0BKunLphapOnWC66fPcxBcvmISQwjNU/bGbZN+vM+nfK5MAX339KhQZlMBqM7Fl1kGk956U5vlHr+lO+bimGNZ/In2sflS0rWC4v7Ua9T4EyeeLH79BlZg9YxJWT8fF5enuw4K8pifrr2ehbzh+7btp2dLWn84jmVKhVDIPBwN5NJ/lx6AoiI5L/9+VxI+Z3pPxbRRjRfjb7tpx6FF9JLz7t35D8xXNiNMLFE9eZM2otV8/5AZAjbxa6jmmJV4GsODjZJvv9ExERERGRV58Wyn16GjmR56xz5858+umnTJ48mfr169OzZ88Ua+Y/rSZNmhAZGcm7777LiBEj+Oijj2jVqlWK51hYWNCgQQPOnz9Pw4YNn3lMaeXk5MTWrVv5+OOPqV+/PosXL+abb76hQIECSba3srLiypUrdO3alTp16vD5558THBzMokWLTOfs3buX69evs2/fPqpVq0aVKlVMP6+T8XPbUbtx6SSP9RvXEu98ngz87CeGdllAsbK56T6sSYr9XTrrx7dfreSzxt8x+PN5WACjZ3yKpWV8aagCRXIQHPSA8QOW0bHp9yyetYtPu79Dw/cerRtRrGxuju77iyGdf+aLcv04ses0I9b2J1+p3M/orp+dcSt7UKtV0mte9J32KV4+2RjYcgrD2kynWMX8dJv4for9FSqbh69/7cLRXefoXm883eqOY91Pv2M0xJefcvN0YczSbty+FkiP+uP56v0f8PLJRq/Jbcz6adqxJh/3b4SVtSXzR69mQNNvObLjjFmbfrPa410oOwObfcvQ1pMpVrkg3b/7KE333bRTbf6uiGXGzsGWr5f3INA3iB61RtG73jgiwiMZtbwnVtZWAMTGxLFt8T4GNv+Wv45fY9+6w9Rv/zYfDzdfr6L/wm7kLpqL/u+MZHDDsZSoWpieM5Jfo+NxzXo0IKkA7RzsGLNpEHdu3KVrxYH0rPoVEWGRjNk8+LH4Ytm24Hf61/mayydusH/DUep9WoOPvmpm1le/nzrhXTgHA/43jiHNv6V4FR96/NA2TfE17Vo32fEbtaYPgTfv0b3aMHq9PZKH4ZGMWtvHFJ+9kx2j1/Ul4MZdrp66yf6NR2gzpAX1279t1lf/+V3xLpKTAfVG81WT8RSvUoge0z9LU3zNutc3lTz7Z3yj1w/gzs27dHtzMF/WGMbDsEhGbxhoii9B33e+5uzhq/w4dAXvlxnMpVM3zY9PboNXwawMfH8awz6dRbEK+eg2rnWa4mvSvgYkNX72GRi54HPu+N2nR6NJ9G7+PQ/Do/h6YSesrOP/J2tcbBzbVxxi0AfT+LRQd6b3nJfk909EREREROR1ppn6Is+ZpaUlnTp1olOnTomOXbhwwWzb2dnZbF+zZs1o1uxRIqpr16507do1yetYW1szaNAghg8f/kTx9enThz59+qTaLmfOnIniTUpSMX7yySd88sknyZ5Trlw5FixYkGrfCWxtbZk6dWqKbf45dv81ufJ4UL5KQbq2msals7cAmDZmPSOnfcSsiZsICgxL8rxNyx/NiA7wC+bnqVuZvqIbntkzcds3iN9WHzFr7+97n8IlvXjz7SKs+3U/ADPGbzQdj/vLn7mDfqVSo/JUaliOy8evPeM7fT5yFchK+ZpF6VZnLJdOxM9gnj5oKSMWdWb28JUEBYQkeV7HES1YM3sny6b+Ztp36/Id0+cKtYsRGxvHD/2XmJKuU/v+yvRdg8mW24Pb1wJxdMnIR/0aMfyj6bzXoy4hd8O4esaXq2d8H8VXMBvlaxWn61sjuXQ8fvb0tH6/MHJpd2Z9tZQg/6TjA8hbLBfNvqhNt5pf8+uFbxPdt7ObI/PHrOburfsALBq/jh/3DidLrszcvnoH/+t38b8e/+ZGTGQMl49fw2AwUqxKYVM/XoVy8Ea90nxRvh8Xj1yJv89ucxm1YQAz+8zn3u37ycaXr2RuWnzZkC/K92fp7Vlmx7wKZcc5sxM/D11CoG/8otgLRixj1slv8PT2wO+yP/5X7+B/NX7Mo6NiuHziRnx8bz5alDyXT3bK1ylJlzeHcOno1fjx+3I+I1f3ZuaAXwm6HZz8+JXwonn3enR9cwiLr5n/O5TLJz6++SNXEOgb//B24ahVzDg8Bk+vzPhduUPN1m9ik8GabzvOYvS6vpw/eJkHIQ9p3r0+G2dvj++nUHbK1y3FFxUHcunv8fuhxzy+XtePmf0WEpTC+OUt6U3zHg3oUnEgS3xnmMdXKEd8fMOWPRq/r5cz89gEPL3d8bscYGobGhRGbEwsD8Iiuf+Pfy9y5fek/FtF6NZgIpdOxif7pw9ZzoifOzL769UEBYQmH1+RHDT/7C26NZjIL0e/TtSvcyYHFkzcyN2/fweLvtvM9K39yZLTjdvX7uJ/4x7+N+Jjj711lzs37lLil6Jm3z8REREREUkf4owWLzuEdEsz9UVEXkOFS3oRFvrQlNAHOLb/MkaDkULF07a+g21GG2o3Kctt3yACU0gSOzjaERbyMNnjFhYW2DtlJCwoPO038JIVLpeHsOAIU0If4Nju8/HjVyZ3kue4uDtSqGweQu6F88263vxyaizjV/Wk6Bv5TG1sbG2IjY4zm0Ud9XdZnqIV4tuVrl4YS0sLMmdzpWCZ3HQY1ZKBczviniPTo/jK5yUs+IEpoQ9wbNe5+PjK5k32vmwzZqDfrA780OcX7t9JnHj1/cufkHth1P2wKtY2VmSws6HOh1W4ft6PgBt3k+zTNYsL5euU4uTus4/iq1SQsPvhpoQ+wNFtJ+Pjq5D0GzgJ8Q1Y1J0pXWZzPyA40fGbF/wIuRtK3XY1sbaxJoNdBuq1q8n1s774X7uTuEPANYsz5WqX4OQf5x/FVyE/YfcfmBL6AEd3nImPr3y+pLoxxdd/Xmd+6PEz95N4sON78TYhd8Oo83F10/jV/aQ618/dMj0IKVwhP6f2XiA25lGpmCO/nSBXoRw4ujoAUKRi/Phdenz8tp/CaDBS+I38KcY3YH5Xpnabm3R8CeP36VuP4vv0rb/HL9Cs7YiVfShSLg+tu9SmQu1iZscKl80d//dx8tHs/WN/XIwfv9K5k4/PzoZ+Uz7ih8HLEj0oAPC9fIeQoHDqtK746PvXqiI3LvoTcDPpN9yy58ua6PsnIiIiIiLyutNMfRGRdOS9AU15b8CjNxAyZMxAoRK56DzwUfmkzxp/TyZ3R0LumSfRDXEGwkIeksk95YWH/9eqAu2+rENGe1tuXg1kYIefiE2mVnXhkl5Uq1OcIV/MT7a/d3s3xM7Rjt+X/pmWW3yukhy/MnnoPPpR6Y6O1UaSycOZkLvmSUdDnIGw4AgyZXFOsu9sXu4AfNCrPrNHrOTKaV/efrcCY5Z14/MaX+N3NZDjey7QYVhzmneuxZpZO7Gzz0DbwY0BcMviQqtudfigdwOsbaz48vs2YAQrayvebFSWKo3LEvUwms8qDiGTpwshgUnEd/8BmTxdkr3/jqNbce7gZfZvOp7k8YfhUfRtOIGhC7vwXp//AeB3OYBBLSZhiDPQ6sv6tO5ZH4hPIFtYWlCyRlFiY2Jp1r0Bzbo3oF3RnrhldSX4Hw8NDHEGQoPCyZTVNdn4Pp/0CWf3XWDfYzXgzeOLpPdbwxi2qi8fDG4BwK1LtxlQ92sMcQaz32+GjBmwtLSgZLXCxMbE0rRLHZp2qUOHMv1x83QhODBxfGFBD3DzTD6+juM/4Oz+S+xbfzTZ+PrUGc2wpT14f0CT+PH7y5+BjcZjiDPQuk9D3mpVCaPRyOrAWWTImIHCFfJj+Ls80y/Xp9Gu2Jdk8kx6/MJSG79vPuLs/otmNf4TxVdrBEOX9+b9QfHj5HfpNgMajImPr18T3hvQhJioGFzcnbC0tCSrV2aGzmlPTFQscXEGOtYcE//3cS+Zvw8Pp2Tj+2xoU84eucr+304nHd+DKPq1nMqQ2e14r3ud+PiuBjL4w+kY4gxmbb9Z1YP8xXKQwS4D62du5echS5K9roiIiIiIvJoMmm/+1JTUF3kNPEnpGknf1v+4ld+XPlqUdsCKvuzZdoa92x7VW7+XTGmdtNqx4ThH9/2Fm4cTLT6uwsBvWvNlm5nERMeatfPOn4Whkz9k0Y87OLrvryT7euu9Knw45F2GNhmfKIn6MiQavyVfsnfDcfZuOG7ady+FtxJSYmEZ/z9GNi7Yw9bF8aWILp/2pVTVQrzzXmXmjV7DjQu3+abbz3QY3pxPBzbGEGdgzZxdBN0JwWg0sHHBXpwyOdC8Uy2+7b6ABh9VYc+6o5zcc55Jvw1kWt9fuJdCaZiUVKxXkpJVC/FF9RHJtslgZ0PPyZ9w5sBfjG0/E0srS5p3eYcRS7rTrebXbJj7O7tXxSfc3Tyd+WLce1w7fYOSbxVj24Lf2ThrO/f8nm7NkEoNy1H6rWJ8XqZvCvFl4MvZnTiz9zyj3/8OKytLWvRqxNfrB9DljQFmv1+3rK50ndaBa2d9KVm9CNsX7WHT3J3c80u+dE1KKjYoTakaRehccXAK8dnw5Y/tObPvImM+/gFLK0ta9KjPyJW96VplCBtm76B8nZIE3gpi/vDl9PupE3+sPMDVU9cZvWEgw1t88/Tx/a8spWoUpVP5/inHN/Nzzu67wJg2k7G0suTdng35ek0/ulQayIaZW9m9/NHfR/9fe7J34wkKlcmNR3ZXxnaZz71kSk+lpkLtYpR8syBd6o5PMb4eE1pz9tBVxnWZj6WlBc071mT4zx3p/r9vTItNA4zpPI8MD0LJV9KbDuPb8G7vhiydsPapYhMREREREUlvlNQXEUlHwu6HE3b/0Qz86KgYQoLCuf2P0hT374bjktl8Rr6llSVOLhm5fzflMjgR4VFEhEfhd+Me50/cZPnewbz5dhF2bTppauOV14Oxs9uxafkhfp25K8l+qtctTs/hTRnZ8luObT/1hHf6fCQav8gYgu+GcfsfpUfuB4bi4m4+49jSyhInV/sky9YABN2JT3beuOhvtv/GJX+yPFY6Z9eqw+xadRhXdyciI6IxYqRpx7e5ff0u4cERXL/gB8DxP85Tu2UFQgJDuXj0GqH3wrGytsIQZ+B+QAguHknEl8khybIrACWrFiJbHg9WXJtstn/w/M6c2XeJvg0n8FaLCnh6udPznTGmEkHjOsxi+dXJVKpfit9XHiI8+AEAt6/eISwonCNbT3Jw0zF6zOjI3IG/YjAYCPIPxvUfbzRYWlni7ObIff/gJOMrVbMY2fJ5svr+PLP9Q5b35vQf5+hdcxg1369C1twedK88yBTfmA++Z2XQT1RuXI5dS/40/X79LvsTdv8BR7ed5tDmE3T/oS0/DVmKwWAkKCAEV4/E8Tm5ORCURNkfgFI1ipAtbxZW+pvXqf/q126c3nuBvnVG81arynh6udOj+nBTfGM/nsaK2zOo1LAsvy/bj/+1QOydM+J35Q5RD6MJDgwlJir+gdmFQ5f//v0mPX5OKY3fW0XJls+TVXfnmse39EtO7zlPn1ojqPleFTy93ele5atH49dmMisD51C5UTl2Ld1H2P0HpnOjI2MIvhfO8b0Xea/rO9y+Fl9C6H5gKC6Zk/n7SOahYqnKBcjmnZnlZ8aa7R80oy1nDl6mX8up1GhcFs+cmfmy8XePvn9d57Ps9BgqvVOM39ceM51393Ywsbf8uHHOF0srS3rM6Mjyb9ZjMJjP6BcRERERkVdXnFEz9Z+WkvoiIq+hcydu4OSckfxFsvPX2fgkcak38mJhacH5UzdTOfsRCwvAAmwyWJn2eefLwtg57di25ig/T9ma5Hk16pWg54hmjGr9LQc3Jl2q5FV27vBVnFztyV8iF3/9XTe8VBWf+PE7ei3JcwJu3OPu7WBy5stitj9n3iwc2nEmUfvgv8v7vPNeJWKiYjj2e3zN97MH4+uo58znaWrr6OqAc2ZH7tyMXyD03KErOLk6kL+kN3+diK+rX6paofj4HqvD/ril321i84I/zPbN+HMEMwcuYf/mE0B8SR2jwWBW899gMGI0GrGwTH4BIwtLC6xtrOLbGODcvos4ZXKkQJm8XDoaH0/pmsXi4ztwKck+Fo9dzaa/F4pNMOvUt/z45Tz2/11OxtY+gymeR/EZwPjoTYmkWJriswRDHOcO/IVTJgfyl87NX8euAfFJewtLC84fupxkH0smrmfTT7+b7Zt5ZAwz+i5i/4ZjKcQXv2359/idO/AXnwxrgZX1o7+pMrVKcPP8LdMDk7P7E8Yvj6nuf+m34sfv3MGk34pZMn4Nm+fuMI/v+ERm9J7P/vUpjZ8RYyrjl7dIDoIee5h17si1+L+P4jn561T8As6l3iwQP35/j+c/LZ22jc1/v8GS4Mdt/Zk5fBUHtsWX47HLaJPM9y/l+P75/RMREREREXnd6XGIiEg6YudgRyZPV9PPmD5LOLznEpkyO5p+LC0tuHk1kEN7LtJjaFMKFstJkVJedB7YkN83nyLo75m0mbM4M2ttDwoWywlA1pyZaNWuGvmLZMcjqwuFS3ox6Jv3iI6K5eAfF4H4kjvj5rTj6J+XWDl/r+maLpnsTTHWqF+C3qNaMGviJs4f+MsUq72zfeIbesH+OX5jO87lyI6zZPJwNv1YWlpw85I/h3acofvEDyhY2psi5fPSaXTL/7N33/E1nv8fx1/ZEYkkSBAiQYm9VaVW1VZF1WolalVrlNqjtKjGqKbfxCxKjdaq3aJ2a2+qdhEhxEhkSCKRc35/pA6nGUJJqr/38/E4j4f7uq/ruj/3cU7H577O52LHqkNE/LUSPk9+Z775bRQlKnmZ5v9x2iZadHuNmm9UooC3G36D36DQS/n45fuH+wk071KHYuU8KVjUnTc61+bDce2YO241d6PjsXewIy4mgQNb/qBnQDuWT9nI9cu3GDbnfcL+DOfymWsp8Z29xoHNv9Pvf/6UqFyE0tVfoufEd9ix4gARf5UPylPAhVn7xlKichEAIm9EE3IqzOwFcOPKbdMmuIe3n8TRJSe9vnwXzxIF8CrpwYCpnUlONnD8tzPY57Tjja51aexfizKvFGfWkIVY2VjRbXxHdq8+QK48KXXYL5++yv71R/j4mx74VHuJMr4+9A7uyvbFu7l9LaW8TB6P3Mw5+TU+1VI2fo0Mv8OlP0LNXgA3Lt8ybYJ7eNNxnFxz0mdqNwqXLIhX6UIM+rYXyfeTObbtBPY57Wn+YUOadHudsjVLMmfEYqxtregyrh171h0m14Pvx5kwDmw8Rr+pXfGpWpTSNYrTK9CfHcv2EvFXeaM8Hq7MPjoBn6pF/4ovipCTV8xeADdCbxMekvJLjyNbTuDk6kDvrzvh6eOBV6mCDPime0p8O05in9OOw1tPcP9+MkPnfcj80cuwsbWm1UeNWT93G675nFPiOx3GgQ1H6TfjfXyqFaO0bwl6/a8z25fsIcL0/rky5/fJ+Py1sW9keBSX/rhi9nr4/qXEd3jz7ynvX3AXPEt64FW6EAPnfJgS3/Y/sM9pR8tejWj2fn3K+Prw3aSfKFTUnYbtXmHzjwdwdXNKie98OAe2naTvhPaUqFiY0lWL8OHYt9mx5ggR4dEPvx/bhlOiYuGU+G7GEHLmmtkL4GZYpGkT3MO/ncHR2YFe49rg+VI+CpfIT//J76TEtzvlYdBrLatQ642KeL6Uj/xF3KndpgZdv3iX7Ut2k5zO3h8iIiIiIvLvZMAiy1//FVqpLyLyAmkzsDn+n7bNsE+nRpMID7vDhCFL6TWiOeNnd8FoMLJz8x9MD1hn6mdtbYlnETfs7W0ASLx3nzJVvGnp9yqOuey5czuW3w9dor/fTKIiUlYQ12pQFpc8jrzevBKvN69kmiv8aiSdGn8JQNO3q2FtY0XvT96k9ydvmvr8Mm87k7pMfWbvxdPI1PtX7RNuhEYwsedcen7RjoBlfTEajOz66QjTRywz9bOyscKzeH7sctia2lbN2oaNnQ3vj34bJ1cHLvxxlRHtgrkWcsvUp0QlbzoObEaOnHaEng8nePD3bF2+H4DWPevTcWAzU98xiz8yi23hH5PoVH4I4aG3mdB9Nr0mvcP4VQMwGg3sXHOY6UN/MPW1trbCs0QB7B+J73GunLvOpx2C6TikOYG/DMNoMHL++GU+eftrIsKj6DjkTToOfTPNsbXfrkHtt2vQsUhPwkNuMr5jEL2DuzJx8yiMBiO/rdjL1I/mPozPxorCJQti55D5+ELPhDHyzQn4jWrD/3aPw2Aw8ueRiwxvMo6I63fw+7RNun+/tVq9TK1WL+Pv8zHhl28xofN0egX6M/7noSnfj1UHmDbg4f4k1tZWePp4mP39Pja+s9f4tHUg745oydfbU+77/LEQRrSYRMT1KDqOaIXfJykb1NZuXZ3araubxr4/oSPvT+iI30t9Ut4//2B6/a8LEzZ+kvL+rdzHtH7zHnn/rPEsWRC7HHZP9P6NajmJjiNb87/fxqa8f0cvMfyNgJT3b+Tb+I16O82xH3z2Fh989hadaozmxpUIJn60gJ5j3ybgh14p34/1x5g+6kdTfytrKzxfyoed/RN8/v68wWddZvFuv8Z8taofRqORP09cZaTfDFPZq+RkA20+rE/Bom5YAOEhN1k9dT0/Bv6U6euIiIiIiIi86CyMj/7GWUREzDSwbJPdIWTIqkyJ7A4hQ8l/nM3uEDJk7e6W3SFkyHgvMbtDyFBy1NNtmppVLO3sszuEDBnvJz2+Uzayyp/v8Z2y0f2rYdkdgoiIiIjIC2OTYdnjO2Wx2WdrZfk1u5X47fGdXgBaqS8iIiIiIiIiIiIiWUob5T49vXMiIiIiIiIiIiIiIi8IrdQXERERERERERERkSyVrPXmT03vnIiIiIiIiIiIiIjIC0Ir9UVEREREREREREQkSxmMFtkdwgtLK/VFRERERERERERERF4QWqkvIiIiIiIiIiIiIllKNfWfnpL6IiIvsOQ/zmZ3CBmytLXN7hAydP/GzewOQZ4jw72E7A7hhXb/alh2hyAiIiIiIiJp0OMQEREREREREREREZEXhFbqi4iIiIiIiIiIiEiWMhi13vxp6Z0TEREREREREREREXlBaKW+iIiIiIiIiIiIiGSpZCyyO4QXllbqi4iIiIiIiIiIiIi8ILRSX0RERERERERERESy1L+9pv6BAweYM2cOJ06c4ObNm0ydOpX69eubzvv4+KQ5btCgQXTr1i3Nc8HBwUyZMsWsrUiRImzYsOGJYlNSX0REnrsiZT3p/b/3KFGlKFG3Ylg97ReWfbUu3f5OuR0ZOq8nRcoWximPI1E3o9mz9hBzRy0lLibe1M/G1pp3R7SiXoeauOZzJuL6HRZ9sZJfvtsBQJMur1H/3Zp4lfYE4PyRi8wdtYQzBy883xsWERERERERkRdaXFwcPj4+tG7dmt69e6c6v3PnTrPjX3/9lREjRtCoUaMM5y1evDhz5841HVtZWT1xbErqi4jIc+XglIMv1g3lyLYTBPX+Fu+ynvSf+T6xUXdZP2dbmmOMBgN71h5i3mfLiLoVg0exfPT++j2ccjsyvtNUU78Riz7Cxd2ZwA++IezPcHLnd8HC8uGT/vK1S7FtyR5O7p1PUkIibQc254t1Q3m/8hBuh0U+93sXERERERERkbT922vq16lThzp16qR73s3Nzex4y5YtVK9eHU9PzwzntbKySjX2SSmpLyIiz1W99r7Y2Frz1fvfcD8pmZBTVylW3ovWHzVNN6kfeyeOdbO2mI5vXL7F2pmbadO/mamtaoPylKtVkvdKfUxM5F0AwkNumc0z4b1pZseBH8zi1ZYvU+m1MmxeZP5EXURERERERET+2xITE0lMTDRrs7W1xdbW9h/Ne+vWLXbs2MH48eMf2zckJISaNWtiZ2dHxYoVGTBgAB4eHk90vX934SIREXnhlXqlOL/vPM39pGRT26HNv+Pp44Gji0Om5shdwIVXW1bl+G+nTG2vvFGZc4cv0qb/Gyz6M5g5v39J94B3sLW3SXceOwc7rG2siIm4+/Q3JCIiIiIiIiL/mMFomeWvmTNnUqVKFbPXzJkz//G9rFy5kpw5c9KwYcMM+5UvX56AgABmz57NZ599xtWrV3n33XeJjY19outppb6IiDxXrvlcuH7phllbZHiU6Vzsnbh0xw6d34sab1TB3sGOPesOEfjBbNO5AkXcKeNbgsSEJMa0CyRXHid6B3UmVx5HJr//TZrzdR3XntvXIjm89cQzuDMREREREREReZH06NGDzp07m7X901X6AD/++CPNmzfHzs4uw36PlvMpWbIkFSpU4LXXXmP9+vW0adMm09fTSn0REfnXmjloIb1fGcGnrSfjUTQfPSa+azpnYWmJ0Qjj35vKmYMXOLDxGN8MXkj9jrXSXK3fdmBz6rapwZi2gSTdS8rK2xARERERERGRfwFbW1scHR3NXv80qX/w4EEuXrz4REn5B3LlyoW3tzeXL19+onFaqS8iIs9VZPgdXN2dzdpc8zmbzmU8NorI8ChCz14jJjKWr7Z+yvcBq4i4foeI65HcDosgLjre1P/y6TAsLS3JWzA3YX+Gm9rf7teUdgObM7RpABdPhD67mxMRERERERGRp5Js/G+sN1++fDllypShZMmSTzz27t27hIaGPvHGuf+Nd05eaFeuXMHHx4dTp06l22fFihVUrVo1C6P654KDg2nRokV2hyGS7U7tPUe5miWxsrYytVV+vSyhZ8IyLL3zdxaWKf/KsrFLeR79x56z5C7gin3Ohz9tK1S8AMnJBm5djTC1ten/Bu8Ma8WINydy7vDFf3o7IiIiIiIiIvL/wN27dzl16pQpZ3nlyhVOnTpFWFiYqU9sbCwbNmxId5V+p06dWLhwoel4woQJ7N+/nytXrnD48GF69+6NpaUlb7zxxhPFpqS+vBCaNm3Kxo0bszsMEhMTadGixWMfQmSl4OBgGjduTMWKFalWrRrvvfcex44dM52/cuUKw4cPp169epQvX5769esTFBSUaqfv52Xo0KH07NkzS671qF9++YW33nqLqlWrUrFiRVq0aMGqVauyPA6BrUt2k5R4n/4zu+NVqiB13n6Flr0a8WPQz6Y+vm9WZfaxSabjao0q0NC/Nl6lC5HPKy8vN67IR8FdOLH7DOEhtwDYtng3MRGxDPimB4VLFqRszZJ0C+jAL9/tIDEhpbxO2wFv4P/p23zV4xvCQ27ims8Z13zOZg8CRERERERERCTrGbDI8teTOHHiBC1btqRly5YABAQE0LJlS4KCgkx9fvrpJ4xGY7pJ+dDQUCIjI03H169fp3///jRu3Jh+/frh4uLC0qVLyZ079xPFpvI78kKwt7fH3t4+3fOJiYnPZFOLx5k4cSLu7u6cPn36uV8rs7y9vRk1ahSenp4kJCQwb948unTpwqZNm8idOzcXLlzAaDQyZswYvLy8OHv2LCNHjiQ+Pp4hQ4Zkd/jPjbOzMx9++CFFixbFxsaGbdu2MXz4cPLkyUOtWrWyO7z/V+Ki4xn+xnh6/+89puz5nKhbsSz6YiXr52wz9cnp7ICnj4fpODEhiSadX6PHxI7Y2Nlw88ptdq06wJIv15r6JNy9x7CmAfQM7ETw7rHERMTy6/J9zPtsqalPs/frY2tnw8jF/cxiWvD5jyz8fMXzu2kREREREREReaFVr16dM2fOZNinXbt2tGvXLt3zW7duNTsODAx8JrFZGI1G4zOZSeQxDAYDc+bMYenSpVy7do28efPSrl07mjdvzuuvv05wcDALFizg+PHjeHl5MXr0aCpVqgSklN/54osvOHjwIJCyOn3z5s107NiR6dOnExYWxunTp/Hz86N48eIArF69Gmtrazp06EDfvn2xsEj9NC42NhZfX1+Cg4PNdp/etGkTgwcPZvfu3eTIkQOAHTt2MH78eIKDg2nWrBmrVq2iVKlS6d7vgxg7d+5MUFAQUVFR1K5dm7Fjx+Lo6JjuuEWLFvHdd99x7do1nJycqFq1qtkTwMeJjY2lSpUqzJs3jxo1aqTZZ/bs2fzwww9s2bLlsfM9eO8DAwP54osvuH79OpUrVyYgIAB3d/cMxwYHBzNlyhSztvnz51O9enUmTZrE5s2buX79Onnz5qV58+b06tULG5uHG5xOmzaNBQsWkJCQQNOmTXF1deW3335j9erVmXgnUmvVqhV16tShX79+mR7TwPLJNzmRhyyz4GHbP2HIol+siIiIiIiIiGSnTYZl2R1CKiN/b5Xl1xxbbmWWX/N5UPkdyTKTJ09m1qxZ9OzZk59//pkvv/ySvHnzms4HBgbStWtXVq1ahbe3NwMGDOD+/fvpznf58mU2btzIlClTzMqqrFy5EisrK5YtW8aIESOYN28ey5al/Q8uR0dH6taty7p168za165dS/369U0J/Vu3bjFy5EgmTpyY4S8G0opxy5YtzJgxg5kzZ3LgwAFmzZqVbv/ff/+dcePG8dFHH7FhwwZmz579RHsJJCYmsmTJEpycnPDx8Um3X0xMDM7Ozume/7uEhAS+/fZbJk6cyMKFC7l27RoTJkx47LguXbrQpEkTatWqxc6dO9m5c6fpQU3OnDkJCAjgp59+YsSIESxbtox58+aZxq5Zs4YZM2YwcOBAVqxYQYECBfjhhx8yHfOjjEYje/bs4eLFi1SrVu2p5hAREREREREREfk3UPkdyRKxsbHMnz+fUaNG0apVylO4woULU7VqVa5cuQKkJIDr1q0LwEcffUSzZs0ICQmhWLFiac6ZlJTExIkTU9WcKlCgAMOHD8fCwoKiRYty9uxZ5s2bR9u2bdOc580332TQoEHEx8eTI0cOYmNj2b59u2mFudFoZOjQobRv355y5cqZ4s0Mo9FIQECAaWX+m2++yZ49e/j444/T7H/t2jVy5MhB3bp1cXR0pGDBgpQuXfqx19m2bRv9+/cnPj4eNzc3vv3223RrcYWEhLBw4cInKr2TlJTE6NGjKVy4MADvvvsu06ZNe+y4nDlzYm9vT2JiYqpdvB+ts1+oUCEuXrzITz/9RPfu3QFYuHAhb7/9Nq1btwagd+/e7Nq1i7i4zG+sGhMTQ+3atUlMTMTS0pJPP/2UV199NdPjRURERERERETk+TAYn6zGvTyklfqSJS5cuEBiYiKvvPJKun0eXVn+IAEcERGRbn8PD480E9cVKlQwK7VTsWJFQkJCSE5OZsaMGVSqVMn0CgsLo3bt2tjY2JhqXG3cuBFHR0d8fX0BWLBgAXfv3qVHjx7pxvLonKNGjTK1FyxY0KzUjru7O7dv3wZSVqI/Ou7gwYP4+vri4eFB/fr1GTRoEGvWrCE+Pj7d/g9Ur16dVatWsXjxYmrVqkW/fv1M13lUeHg43bp1o3Hjxuk+5EhLjhw5TAn9v9/H0/r5559p3749r776KpUqVeLrr7/m2rVrpvMXL16kfPnyZmP+fvw4OXPmZNWqVSxfvpyPP/6Y8ePHs2/fvn8Ut4iIiIiIiIiISHbSSn3JEnZ2do/t82gt9QdJeYPBkG7/B6VxnkT79u1p0qSJ6djd3R1ra2saNWrE2rVradasGevWraNp06ZYW6d8Pfbu3cvRo0cpV66c2VytW7emefPmTJgwwaz8z6NJ/AdzPOrBNhb16tWjQoUKpvZ8+fJhb2/PypUr2b9/Pzt37iQoKIgpU6awfPnyNPs/4ODggJeXF15eXlSsWJGGDRuyfPlyswcR4eHh+Pv7U6lSJcaOHftE79vf78PCwoJ/sh3HkSNHGDhwIH369KFmzZo4OTnx008/MXfu3KeeMy2WlpZ4eXkBUKpUKf7880+++eYbqlev/kyvIyIiIiIiIiIiTyZZ682fmpL6kiW8vb2xt7dn7969eHp6PtdrHT9+3Oz42LFjeHl5YWVlhYuLCy4uLqnGNG/enC5dunDu3Dn27t1rtpHqJ598YnZ848YNunbtSmBgoCnJ/iBx/CQcHR3T3DDX2toaX19ffH196d27N9WqVWPv3r00bNgwww12H2UwGEh8ZAPQBwn9MmXKEBAQgKVl1v1D08bGJtXDmSNHjuDh4cGHH35oagsLCzPrU6RIEX7//Xdatmxpavv999//USx/f19EREREREREREReNErqS5aws7Oje/fuTJo0CRsbGypXrkxERATnzp2jRo0az/RaYWFhBAQE0K5dO06ePJmp+vHVqlUjb968DBw4kEKFCpmtiPfw8DDr6+DgAKTsCZA/f/5nGvu2bdsIDQ2lWrVq5MqVix07dmAwGChSpEia/ePi4pgxYwb16tXDzc2NyMhIFi1aRHh4OI0bNwZSEvp+fn54eHgwZMgQs5JGf69z/zwULFiQnTt3cuHCBVxcXHBycsLLy4tr167x008/Ua5cObZv387mzZvNxnXs2JGRI0dStmxZKlWqxM8//8yZM2cy/VBo5syZlC1blsKFC5OYmMiOHTtYs2YNn3322XO4S3kaTq456RnYiepNK2M0GNi56gDTB8wn4e69TI3/fPVgqjWqwGdtvmLP2kMANPCrzcBZaZfKauv5IVE3owGwsbXm3RGtqNf+VVzzuxBxLZKFY5ezce62Z3NzIiIiIiIiIiLPiZL6kmV69uyJlZUVQUFB3LhxAzc3N9q3b//Mr9OyZUsSEhJo06YNVlZW+Pv7065duwzHWFhY0KxZM2bPnk2vXr2eeUyZ5eTkxKZNm5gyZQr37t3Dy8uLyZMnU7x48TT7W1lZceHCBVauXElkZCQuLi6UK1eORYsWmcbs2rWLkJAQQkJCqF27ttn4M2fOPPd7atu2Lfv376d169bExcUxf/58Xn/9dTp16sSYMWNITEykbt26fPjhh6bNiSFlU+HQ0FAmTJjAvXv3aNKkCa1atcr0av24uDhGjx7N9evXsbe3p2jRokyaNImmTZs+r1uVNEz8ZQSbFvzGpgW/pjo3ZF4vcud3YVizAKxtrBjwTQ/6TevG+E5THztvqz6N0ywBtWPZHg7+csysbeCsHtjY25gS+gAjFn2Ei7szk7tNJ+z8dXIXcMXSUhv0iIiIiIiIiGQVbZT79CyM/6Qwtsi/jJ+fHyVLlmTEiBHZHYo8B507dyZv3rxMmjQpy67ZwLJNll3rv+jL7aPTTOp7+ngw+9gkevt+wrnDFwGo2qA8Y1cP4t1ifYi4difdOYuW92LMioH0efUTFodMM1up/3fOeZ1YdGEKgR/MYsv3O03XGbagN++V+pio8Mhnc6MiIiIiIiIi/2KbDMuyO4RUBh/L+pzLxAr/vvfhaWilvoj8K8XHx7N48WJq1qyJpaUlP/30E7t3737mm+lK9ij1SnFiIu+aEvoAh7eewGgwUrLaS+xeczDNcXY5bBn6XS+m9ptHZHjUY69T/91a3Iu7x28r9pnaXnmjMucOX6RN/zd4/Z2aJNxNYM/ag8wbuYTEBO25ICIiIiIiIpIVDNoo96kpqS/y/1y3bt04dCjtVc49evTggw8+yHB8pUqV0j03a9Ysqlat+lRxWVhYsGPHDmbMmMG9e/coUqQIwcHB+Pr6Ptfryj/TYVgrOgx7y3Rsm8OWUi+/RK/ATqa27pUGkzufM3dumiflDckGYiJiyZ3POd35e0zqyMm9Z9mzLu3P7N81eq8u25bsJjEhydRWoIg7ZXxLkJiQxGdvTcI5rxN9pnYjV24nvuw6LbO3KiIiIiIiIiKSLZTUl/+UBQsWZHcIL5xx48aRkJCQ5jln5/STqw+sWrUq3XP58uV72rCwt7dn3rx5WX5d+WfWzdjEjqV7TMfDFvVl56oD7Fp1wNR2O+zpSt680qwyFeuWoWf14ZnqX6r6S3iVKsjELuaJegtLS4xGGP/eVGJvpTxYmDngO0YuG0BQr9larS8iIiIiIiKSBZJVU/+pKakv8v/cP02Ae3l5PaNIXozrSsZiImOJiYw1Hd9LSOTOzWjCLoSb9YsIj8LFzfyhkaWVJU65HYlIp6xOxbqlKVDUnRXhs8zaRy7ux4ldpxnccJxZe+POr3H+6CXOH7lkfu3rkdwOiyAuOt7UdvnUVSwtLXErlJur569n+n5FRERERERERLKakvoiIpLlTu09h5NrTl6q5G1Kuld8rQwWlhacPnA+zTFLvlzL+rnbzdq+OTyBmYMWsvfnw2bt9jntqN26OnNHLkk1zx97zlLrrerY57QjLjFlVX7BEgVITjZw80rEP785EREREREREXksg1bqPzXtRiAiIs+MfU57XPO5mF4BflM4+MsxXPM5m16WlhaEngnjwMZj9JvWDZ+qRSldowS9AjuxY9leIq7dASCPhyuzj03Cp2pRACLDowg5ecXsBXAj9Bbhl26axVGnzStYWVux5YddqWLctng3MRGxDPimB4VLFaJcrVK8P9GPjXO3qvSOiIiIiIiIiPzraaW+iIg8M20GNsf/07YZ9vH36Ut4yC0mvDeVXl+/x/j1wzEajOxctZ9p/eeb+lnbWOHp44Gdg90Tx9G4U112rT7A3ai4VOcS7t5jWNMAegZ2YuqB8UTfjuHXZXuY+8niJ76OiIiIiIiIiDwdg1HrzZ+WhdFoNGZ3ECIi/1YNLNtkdwgvNEtb2+wOIUOGRK3MFxERERERkf++TYZl2R1CKn0Ov5vl1wyuvCjLr/k86HGIiIiIiIiIiIiIiMgLQuV3RERERERERERERCRLJaONcp+WVuqLiIiIiIiIiIiIiLwgtFJfRERERERERERERLKUwaiV+k9LK/VFRERERERERERERF4QWqkvIiIiIiIiIiIiIlnKYNR686elpL6IiDw/VlbZHYGIiIiIiIiIyH+KkvoiIiIiIiIiIiIikqUMqKb+09JvHEREREREREREREREXhBK6ouIiIiIiIiIiIiIvCBUfkdEREREREREREREslSyUeV3npZW6ouIiIiIiIiIiIiIvCC0Ul9EREREREREREREspTBqPXmT0tJfRERee6KlPWk91f+lKhShKhbMayesYllgT9nOGbj3fmp2r7oNJUdy/cBMGBmdxp2rJWqT8jJK7xfbTgA352cTH4vt1R91szczNT+qecXEREREREREfm3U1JfRESeKwcne75YM4gj2/4gqO88vMsUov/0bsTeiWP93O0Zjv2yxzcc3PS76Tj2Tpzpz9MHLeTbUUtNx1ZWlkzfO45fVx4wtX1U+zMsrR4++fcuXYjx64bw28r9z+DORERERERERORpGVRT/6kpqS8iIs9VvXa+2NhY89UHs7mflEzIqasUK+9F6z6NH5vUj70TR2R4VJrn4qLjiYuONx3XeKMyjq4O/LLgV1Nb1K0YszHtBrxB2J/hHP/t9NPfkIiIiIiIiIhINlLhIhERea5KVX+J33ed4X5Ssqnt0Obf8fTxwNHFIcOxvQP9WRoylaAdn9LQv3aGfRt3qsORbX9wI/R2muetbayo186XjfN/TfO8iIiIiIiIiGQdAxZZ/vqv0Ep9ERF5rlzzOXP90k2ztsgbUX+dczErqfOo78b8yNEdJ7kXn0iV18vSJ9CfHDntWD19U6q+ufO7UK1hecZ3np5uHL7Nq+Do4sAvC3/7B3cjIiIiIiIiIpK9lNQXEZF/pe8nrDb9+c9jIdg72NGmX9M0k/oNOtYk9k4cu9ceSne+Rp3qcOCX40Rcv/M8whURERERERGRJ6Ca+k9P5XdEROS5igyPwtXd2aztwXFk+J1Mz3P6wJ+4FcqDjW3q59GN/GqzZfEusxI/j3L3zEOl18qwYd6OzAcuIiIiIiIiIvIvpKS+ZLsrV67g4+PDqVOn0u2zYsUKqlatmoVR/XPBwcG0aNEiu8MQyXan9p2n3Ks+WFlbmdoq1ytD6JmwdEvvpKVY+cLERMSSlHjfrL18rZIUfCk/G75LP2Hf0K82d25Gs2/D0SeOX0RERERERETk30RJfXkhNG3alI0bN2Z3GCQmJtKiRYvHPoTISsHBwTRu3JiKFStSrVo13nvvPY4dO2Y6f+XKFYYPH069evUoX7489evXJygoiMTExH987X379uHj40N0dPQ/nutJ3Lt3j6FDh9K8eXNKly5Nz549042vVatWlC1blgYNGrBixYosjVNSbF26h6Sk+/Sf3hWvUgWp07o6LXs24sfgDaY+vs2rMPvweNNx9SYVadypDl6lC+JR1J03utWj/aA3WT0jdemdRp3qcGr/eUJOXk3z+hYWFjT0q8XmRTsxJBue/Q2KiIiIiIiIyBMzGC2z/PVfoZr68kKwt7fH3t4+3fOJiYnY2to+9zgmTpyIu7s7p0+ffu7Xyixvb29GjRqFp6cnCQkJzJs3jy5durBp0yZy587NhQsXMBqNjBkzBi8vL86ePcvIkSOJj49nyJAh2R3+U0lOTsbOzg4/P790H/aEhobSo0cP2rdvz5dffsmePXv45JNPcHNzo1atWlkc8f9vcdHxDH9zEr2/8mfKztFE3Y5l0fhVrJ+73dQnp3MOPH08TMfJ95Np3qM+PSa8g4WFBWEXwpk59HuzMQAOuXJQs0VVZgxalO71K9UrQ77Cedk4/9dnfWsiIiIiIiIiIlnOwmg0GrM7CPn/wWAwMGfOHJYuXcq1a9fImzcv7dq1o3nz5rz++usEBwezYMECjh8/jpeXF6NHj6ZSpUpASvmdL774goMHDwIpq9M3b95Mx44dmT59OmFhYZw+fRo/Pz+KFy8OwOrVq7G2tqZDhw707dsXC4vUm2/Exsbi6+tLcHAwderUMbVv2rSJwYMHs3v3bnLkyAHAjh07GD9+PMHBwTRr1oxVq1ZRqlSpdO/3QYydO3cmKCiIqKgoateuzdixY3F0dEx33KJFi/juu++4du0aTk5OVK1alaCgoEy/z7GxsVSpUoV58+ZRo0aNNPvMnj2bH374gS1btjx2vqtXrzJ27FgOHTpEUlISBQsWZPDgwRQrVozXX3/drG+rVq0YP348BoOBWbNmsWTJEm7duoW3tzc9e/akcePGQMoKen9/f2bOnMnkyZO5dOkSpUqV4vPPP6dEiRKZvleAoUOHEh0dzbRp08zaJ02axI4dO1i3bp2p7eOPPyY6Opo5c+Zkev4Glm2eKB4xZ/nX9+ffyhAfn90hiIiIiIiIiDx3mwzLsjuEVNrs/jDLr7nMd3qWX/N50Ep9yTKTJ09m2bJlDBs2jCpVqnDjxg0uXrxoOh8YGMiQIUPw8vIiMDCQAQMG8Msvv2BtnfbH9PLly2zcuJEpU6Zgafnw5zMrV67k7bffZtmyZZw4cYJRo0bh4eFB27ZtU83h6OhI3bp1WbdunVlSf+3atdSvX9+U0L916xYjR45k6tSpGf5iIK0Yt2zZwowZM4iOjqZfv37MmjWLjz/+OM3+v//+O+PGjWPixIlUqlSJqKgo04OMzEhMTGTJkiU4OTnh4+OTbr+YmBicnZ3TPf+oMWPGkJSUxMKFC3FwcOD8+fM4ODhQoEABgoOD6dOnDxs2bMDR0dH03sycOZM1a9YwevRovL29OXDgAIMGDSJ37ty8/PLLprknTpzIiBEjyJs3L4GBgXzwwQds3LgRGxubTN9zeo4ePZrqoUbNmjX54osv/vHcIiIiIiIiIiIi2UVJfckSsbGxzJ8/n1GjRtGqVSsAChcuTNWqVbly5QoAXbp0oW7dugB89NFHNGvWjJCQEIoVK5bmnElJSUycOJHcuXObtRcoUIDhw4djYWFB0aJFOXv2LPPmzUszqQ/w5ptvMmjQIOLj48mRIwexsbFs376dKVOmAGA0Ghk6dCjt27enXLlypngzw2g0EhAQYFqZ/+abb7Jnz550k/rXrl0jR44c1K1bF0dHRwoWLEjp0qUfe51t27bRv39/4uPjcXNz49tvv031vjwQEhLCwoULM116JywsjEaNGpkeEnh6eprOPXgwkCdPHnLlygWkPFiYOXMmc+fONf3SwtPTk0OHDrFkyRKzpH7v3r159dVXARg/fjx16tRh06ZNNG3aNFOxZeTWrVvkzZvXrC1v3rzExsaSkJDwRA9nRERERERERETk2TKQuqqGZM5/Z3cA+Ve7cOECiYmJvPLKK+n2eXRluZubGwARERHp9vfw8EgzcV2hQgWzUjsVK1YkJCSE5ORkZsyYQaVKlUyvsLAwateujY2NDVu3bgVg48aNODo64uvrC8CCBQu4e/cuPXr0SDeWR+ccNWqUqb1gwYJmpXbc3d25ffs2AGvWrDEbd/DgQXx9ffHw8KB+/foMGjSINWvWEP9XeZC0+j9QvXp1Vq1axeLFi6lVqxb9+vUzXedR4eHhdOvWjcaNG6f7kOPv/P39mT59Ou3btycoKOix+wmEhIQQHx9Ply5dzOJdvXo1ly9fNutbsWJF059dXFwoUqQIFy5cyFRcIiIiIiIiIiIi/x9ppb5kCTs7u8f2ebTkyoOkvMFgSLd/jqeo1d2+fXuaNGliOnZ3d8fa2ppGjRqxdu1amjVrxrp162jatKmp7M/evXs5evQo5cqVM5urdevWNG/enAkTJrBq1SpT+6NJ/LRKBz3YxqJevXpUqFDB1J4vXz7s7e1ZuXIl+/fvZ+fOnQQFBTFlyhSWL1+eZv8HHBwc8PLywsvLi4oVK9KwYUOWL19u9iAiPDwcf39/KlWqxNixYzP9nrVp04aaNWuyfft2du3axTfffMOQIUPw8/NLs39cXByQUoLn0RiBLNnM+IG8efNy69Yts7Zbt26ZlQkSEREREREREZHsYTBqpf7TUlJfsoS3tzf29vbs3bvXrHzL83D8+HGz42PHjuHl5YWVlRUuLi64uLikGtO8eXO6dOnCuXPn2Lt3L/369TOd++STT8yOb9y4QdeuXQkMDDQl2b28vJ44TkdHxzQ3zLW2tsbX1xdfX1969+5NtWrV2Lt3Lw0bNsxwg91HGQwGEhMTTccPEvplypQhICDAbA+CzChQoAAdOnSgQ4cOTJ48maVLl+Ln52d6EJOcnGzqW6xYMWxtbQkLCzMrtZOWo0eP4uHhAUBUVBSXLl2iaNGiTxRbeipWrMivv/5q1rZ7926zXweIiIiIiIiIiIi8aJTUlyxhZ2dH9+7dmTRpEjY2NlSuXJmIiAjOnTuXajPTfyosLIyAgADatWvHyZMnM1U/vlq1auTNm5eBAwdSqFAhsxXxD5LODzg4OAApewLkz5//mca+bds2QkNDqVatGrly5WLHjh0YDAaKFCmSZv+4uDhmzJhBvXr1cHNzIzIykkWLFhEeHk7jxo2BlIS+n58fHh4eDBkyxKyk0YMyRxkZN24ctWvXxtvbm+joaPbt22fa56BgwYJYWFiwfft26tSpg52dHY6OjnTp0oWAgACMRiNVqlQhJiaGw4cP4+joaNpTAWDatGm4urqSJ08eAgMDcXV1pX79+pl6r86fP09SUhJ37tzh7t27nDp1CoBSpUoBKb/KWLRoERMnTqR169bs3buX9evXM3PmzEzNL8+fk2tOek72o3qTShgNBnauPsj0QQtJuHsvU+M/XzmAag0r8Fm7r9mz7rCpvUTlInQZ25biFb0xGuHMoQvM+WQxF34PTTWHR7H8TD88EUOygVa533tWtyYiIiIiIiIij6GV+k9PSX3JMj179sTKyoqgoCBu3LiBm5sb7du3f+bXadmyJQkJCbRp0wYrKyv8/f1p165dhmMsLCxo1qwZs2fPplevXs88psxycnJi06ZNTJkyhXv37uHl5cXkyZMpXrx4mv2trKy4cOECK1euJDIyEhcXF8qVK8eiRYtMY3bt2kVISAghISHUrl3bbPyZM2ceG5PBYGDMmDFcv34dR0dHatWqxbBhw4CUEkB9+vRh8uTJDBs2jJYtWzJ+/Hj69etH7ty5mTlzJleuXMHJyYnSpUvzwQcfmM09YMAAxo0bx6VLlyhVqhTTp0/PdIme999/n6tXr5qOW7ZsaXZPnp6ezJw5k4CAAObPn0/+/Pn5/PPPqVWrVqbml2dj4vphbFr0G5sW7kx1bsi3H5A7vwvDmk/A2saaATO60W9KF8Z3nv7YeVv1bsRflazM2Oe0Y9yqQez9+TBT+n2HlbUVfiNaMW71IDqW+Jjk+w9/VWJlbcXw7/ty4rdTlPb1ST2ZiIiIiIiIiMi/kIXRmFZaROTF5OfnR8mSJRkxYkR2hyIZ2LdvH/7+/hw4cIBcuXJldzgZamDZJrtDeKF9uX1Mmkl9Tx8PZh8eT++an3LuyEUAqjYox9gVA3i3eD8irt9Jd86i5QszZnl/+tT6lMUXgs1W6hevVIQpO0fTsUQ/bl5N+VWKd5lCzNz/BZ3LDSTswg3TPF3HtiW3Wy6ObP2dDwPf00p9ERERERER+c/aZFiW3SGk0mJn7yy/5uqaU7L8ms/DkxXWFhEReQZKVX+JmMi7poQ+wOGtf2A0GClZrVi64+xy2DL02w+Z+vF8IsOjUp2/cu4aUbdiaNSpDtY2Vtja29C4Ux1CTl3lesjDjZMr1ClFrVYvE9x79rO9MRERERERERHJFIPRIstf/xUqvyPy/1y3bt04dOhQmud69OiRqmROVvg3xiSZ02FYKzoMe8t0bJvDllIvF6PXZH9TW/cqw8jt7sydm9FmYw3JBmIi75I7n3O68/eY8A4n951jz0+H0zwfH5vAoCZf8NnifrwztAUAYeevM7zFJAzJBgCccjsycOb7TOg6g7iY+Ke+VxERERERERGR7KCkvvynLFiwILtDeOGMGzeOhISENM85O6efXP0nqlevnmE9/+yISZ6NdTM2sWPpHtPxsO/7sXP1AXatPmhqu30t8qnmfqVpJSrWKU1P35Hp9rG1t6H/tG78sfccAe9Nw9LKkrf7NmHsigH0qfUpiQlJ9JvShW1L93Bi1+P3lBARERERERGR5+O/tHI+qympL/L/XL58+bI7hFT+jTFJ5sRExhITGWs6vhefyJ2b0Wa17AEibkTh4ma+n4KllSVOrjmJSKOsDkDFuqUpUNSdFWEzzNpHfv8RJ3adYXCTAF5rW4N8Xnnp99oYHmwZM77zdH68OoMab1Rmx/J9VKxTihrNKvF23yYpE1hYYGVlyYbExQT2mMnGudv+6dsgIiIiIiIiIvLcKKkvIiJZ7tS+8zi55uSlit6cP3oJSEnaW1hacPrAn2mOWTJ5HevnbTdr++ZAADOHLGLvz0cAsHOww2Aw8uge8A+OLS1TtpHpV28sllYpqwGMCffwbVGNtoNb0O/VT7j11+a6IiIiIiIiIvJ8GdBK/aelpL6IiDwz9jntyeFobzoOeG8aAK6P1MmPuhlN6JkwDvxyjH5TuxD80TysbKzoNdmfHcv3EXH9DgB5Crgy4achTOr+DWcOXSAyPCrNzXFvhN4m/K9NcI9sPUH3ce3oHdiJ1TM2YWlpQdsBb5B8P5ljv54EIPRMmGmsIT6eElWLYTQYufRH6DN/P0REREREREREnjUl9UVE5JlpM7A5/p+2zbCPf6n+hF++xYQuM+j1lT/jfxqC0WBk5+qDTBv4cF8MaxsrPH08sHOwzfT1Q89e49M2gbw7rBVfbx2J0WDk/PEQRrT8kojraZf1EREREREREZGs92+vqX/gwAHmzJnDiRMnuHnzJlOnTqV+/fqm80OHDmXlypVmY2rWrMmcOXMynHfRokXMmTOHmzdvUrJkSUaOHEn58uWfKDYL46M1CkRExEwDyzbZHcILzTJHjuwOIUOG+PjsDkFERERERETkudtkWJbdIaTSaEe/LL/mxjpfZ7rvjh07OHz4MGXLlqV3795pJvVv3bpFQECAqc3W1hZnZ+e0pgPg559/ZvDgwYwePZoKFSrw3XffsWHDBjZs2ECePHkyHZtW6ouIiIiIiIiIiIhIlvq3r9SvU6cOderUybCPra0tbm5umZ5z7ty5tG3bltatWwMwevRotm/fzo8//sj777+f6XmU1BcRERERERERERGR/7zExEQSExPN2mxtbbG1zXzp30ft37+fGjVqkCtXLl555RX69euHq6trutf+448/6NGjh6nN0tISX19fjhw58kTXVVJfRERERERERERERP7zZs6cyZQpU8zaevfuTZ8+fZ54rlq1atGgQQMKFSpEaGgoX331Fd27d2fJkiVYWVml6h8ZGUlycnKqMjt58uThwoULT3RtJfVFREREREREREREJEtlR/mdHj160LlzZ7O2p12l36xZM9OffXx88PHxoX79+qbV+8+T5XOdXURERERERERERETkX8DW1hZHR0ez19Mm9f/O09MTV1dXQkJC0jzv6uqKlZUVt2/fNmu/ffs2efPmfaJrKakvIiIiIiIiIiIiIlnKYLTI8tfzdP36de7cuZPuxrm2traUKVOGPXv2PHwPDAb27NlDpUqVnuhaKr8jIiIiIiIiIiIiIvKIu3fvcvnyZdPxlStXOHXqFM7Ozjg7OzNlyhQaNWpE3rx5CQ0NZdKkSXh5eVGrVi3TmE6dOtGgQQM6duwIQOfOnRkyZAhly5alfPnyfPfdd8THx/PWW289UWxK6ouIyPNjkfX18URERERERETk38+YDTX1n8SJEyfw9/c3HQcEBADQqlUrPvvsM86ePcuqVauIiYnB3d2dV199lb59+5qV8wkNDSUyMtJ03LRpUyIiIggKCuLmzZuUKlWK2bNnP3H5HQuj0Wj8h/cnIvKf1cCyTXaH8EKzdHDI7hAyZIiLy+4QRERERERERJ67TYZl2R1CKnW3DMzya25//cssv+bzoJX6IiIiIiIiIiIiIpKlDPy7V+r/m2mjXBERERERERERERGRF4SS+iIiIiIiIiIiIiIiLwiV3xERERERERERERGRLGX4l2+U+2+mlfoiIiIiIiIiIiIiIi8IrdQXEZHnrkgZT3oH+lGichGibsWwesZmln3982PHNXi3Jm/1aUyhl/IRF5PAryv3M7X/AgAKFc/PR/97j8IlPciZKwe3r91h27K9LPxiFcn3kwGYuH4oFWqVSjXvvg1HGfV24LO9SRERERERERHJNKNW6j81JfVFROS5cnCy54s1Azmy7SRBfb/Du0wh+k/rSmxUHOvnbk933Fu9G9H6oybMHrGY0wcvYO9gRz6vvKbz95OS2fz9Ls4fvURsVBxFyxWm35TOWFpYMHf0cgDGvhOMtc3Df9XlyuPI9D1j+W3lged2vyIiIiIiIiIiz5OS+iIi8lzVa+eLjY01X304m/tJyYScukqxcoVp3adRukl9RxcHOo1qzadtv+bo9pOm9ot/hJr+fP3STa5fumk6vhF6m61LSlL21RKmtpjIu2bz1n27Oglxify6cv8zujsREREREREReRqqqf/0VFNfRESeq1Ivv8Tvu85wPynZ1HZoy+94lvDA0cUhzTGV65XF0tKCvAVcmXUogIVnAhkxvxduBXOnex2Pou5UbVCO4zvPpNunUafa7PhxH/fiEp/+hkREREREREREspGS+iIi8ly55nMm8ma0WVvkjWjTubTk93bDwtKS9oPeYMbgRXzecQpOrjkJWDsIaxsrs76Bmz9h7a1ZzD0+iRO7zzJ/7Io05/SpUpQiZTzZMG/HM7grEREREREREfknjEaLLH/9VyipLyIi/zqWlhbY2FozbeAiDm05wekDfxLQeToexfJTobb5xrdfdJpGr5qfEtB5Oi83qsDbfZukOWejTrW5cCKUM4cuZMUtiIiIiIiIiIg8F6qpLyIiz1VkeBSubrnM2lzdc5nOpSXiekr75dNXTW1Rt2KIvh2Du2ces743r0b81TcMS0tL+ga/x49B6zEYjKY+dg621G1dnfnj0l7FLyIiIiIiIiJZSzX1n55W6ku2u3LlCj4+Ppw6dSrdPitWrKBq1apZGNU/FxwcTIsWLbI7DJFsd2r/ecq96oOV9cOyOZVfK0vo2TBi78SlOeaPvWcBKFSigKnNyTUnufI4EX75drrXsrS0wNrGCgtL83+91W71MjZ21mxZvPuf3IqIiIiIiIiISLZTUl9eCE2bNmXjxo3ZHQaJiYm0aNHisQ8hslJwcDCNGzemYsWKVKtWjffee49jx46Zzl+5coXhw4dTr149ypcvT/369QkKCiIx8Z9vFLpv3z58fHyIjo5+fOdn6N69ewwdOpTmzZtTunRpevbsmWa/xMREAgMDee211yhbtiz16tVj+fLlWRqrwNale0hKuk//aV3xKlWQOq1fpmXPhvwY/PA77du8CrMPB5iOr54PZ/faQ3w48V1KV38Jr9IFGTizO1fOXuPYrynfvdfa1qD2Wy/j6VOA/N5u1H7rZTqPbsOOH/eTfD/ZLIbGnWqze91hYiLuZs1Ni4iIiIiIiIg8Jyq/Iy8Ee3t77O3t0z2fmJiIra3tc49j4sSJuLu7c/r06ed+rczy9vZm1KhReHp6kpCQwLx58+jSpQubNm0id+7cXLhwAaPRyJgxY/Dy8uLs2bOMHDmS+Ph4hgwZkt3hP5Xk5GTs7Ozw8/PL8GFP3759uX37NuPGjaNw4cLcvHkTg8GQhZEKQFx0PMPf/JLegX5M+e0zom7Hsmj8KtbP3W7qkzNXDjxLeJiNm/T+N/QY/w5jlvfHaDByfNdpRrT80pSwNyQn0/bjZhR8KR8WFhbcCL3NmpmbWTHF/DNRqHh+yvr6MKz5xOd+ryIiIiIiIiKSOUbj4/tI2iyMRr19kjUMBgNz5sxh6dKlXLt2jbx589KuXTuaN2/O66+/TnBwMAsWLOD48eN4eXkxevRoKlWqBKSU3/niiy84ePAgkLI6ffPmzXTs2JHp06cTFhbG6dOn8fPzo3jx4gCsXr0aa2trOnToQN++fbGwSF2nKzY2Fl9fX4KDg6lTp46pfdOmTQwePJjdu3eTI0cOAHbs2MH48eMJDg6mWbNmrFq1ilKlSqWa84EHMXbu3JmgoCCioqKoXbs2Y8eOxdHRMd1xixYt4rvvvuPatWs4OTlRtWpVgoKCMv0+x8bGUqVKFebNm0eNGjXS7DN79mx++OEHtmzZ8tj5rl69ytixYzl06BBJSUkULFiQwYMHU6xYMV5//XWzvq1atWL8+PEYDAZmzZrFkiVLuHXrFt7e3vTs2ZPGjRsDKSv8/f39mTlzJpMnT+bSpUuUKlWKzz//nBIlSmT6XgGGDh1KdHQ006ZNM2v/9ddf6d+/P5s3b8bFxeWJ5nxUA8s2Tz1WwNLBIbtDyJAhLu3yPyIiIiIiIiL/JZsMy7I7hFSqrR+e5dc80OSLLL/m86CV+pJlJk+ezLJlyxg2bBhVqlThxo0bXLx40XQ+MDCQIUOG4OXlRWBgIAMGDOCXX37B2jrtj+nly5fZuHEjU6ZMwfKR+tkrV67k7bffZtmyZZw4cYJRo0bh4eFB27ZtU83h6OhI3bp1WbdunVlSf+3atdSvX9+U0L916xYjR45k6tSpGf5iIK0Yt2zZwowZM4iOjqZfv37MmjWLjz/+OM3+v//+O+PGjWPixIlUqlSJqKgo04OMzEhMTGTJkiU4OTnh4+OTbr+YmBicnZ0zNeeYMWNISkpi4cKFODg4cP78eRwcHChQoADBwcH06dOHDRs24OjoaHpvZs6cyZo1axg9ejTe3t4cOHCAQYMGkTt3bl5++WXT3BMnTmTEiBHkzZuXwMBAPvjgAzZu3IiNjU2m7zk9W7dupWzZssyePZvVq1fj4OBAvXr16Nu37xP9HYqIiIiIiIiIyLNnQBvlPi0l9SVLxMbGMn/+fEaNGkWrVq0AKFy4MFWrVuXKlSsAdOnShbp16wLw0Ucf0axZM0JCQihWrFiacyYlJTFx4kRy585t1l6gQAGGDx+OhYUFRYsW5ezZs8ybNy/NpD7Am2++yaBBg4iPjydHjhzExsayfft2pkyZAoDRaGTo0KG0b9+ecuXKmeLNDKPRSEBAgGll/ptvvsmePXvSTepfu3aNHDlyULduXRwdHSlYsCClS5d+7HW2bdtG//79iY+Px83NjW+//TbV+/JASEgICxcuzHTpnbCwMBo1amR6SODp6Wk69+DBQJ48eciVKxeQ8mBh5syZzJ071/RLC09PTw4dOsSSJUvMkvq9e/fm1VdfBWD8+PHUqVOHTZs20bRp00zFlpHQ0FAOHTqEnZ0dU6dOJTIyktGjR3Pnzh0CAgIeP4GIiIiIiIiIiMi/kDbKlSxx4cIFEhMTeeWVV9Lt8+jKcjc3NwAiIiLS7e/h4ZFm4rpChQpmpXYqVqxISEgIycnJzJgxg0qVKpleYWFh1K5dGxsbG7Zu3QrAxo0bcXR0xNfXF4AFCxZw9+5devTokW4sj845atQoU3vBggXNSu24u7tz+/ZtANasWWM27uDBg/j6+uLh4UH9+vUZNGgQa9asIT4+Pt3+D1SvXp1Vq1axePFiatWqRb9+/UzXeVR4eDjdunWjcePG6T7k+Dt/f3+mT59O+/btCQoKeux+AiEhIcTHx9OlSxezeFevXs3ly5fN+lasWNH0ZxcXF4oUKcKFCxcyFdfjGI1GLCws+PLLLylfvjx16tRh6NChrFy5koSEhGdyDREREREREREReTpGo0WWv/4rtFJfsoSdnd1j+zxacuVBUj6jTU0flMZ5Eu3bt6dJkyamY3d3d6ytrWnUqBFr166lWbNmrFu3jqZNm5rK/uzdu5ejR49Srlw5s7lat25N8+bNmTBhAqtWrTK1P5rET6t00INtLOrVq0eFChVM7fny5cPe3p6VK1eyf/9+du7cSVBQEFOmTGH58uVp9n/AwcEBLy8vvLy8qFixIg0bNmT58uVmDyLCw8Px9/enUqVKjB07NtPvWZs2bahZsybbt29n165dfPPNNwwZMgQ/P780+8f9VaN85syZZjECWbKZ8QNubm7ky5cPJycnU1uxYsUwGo1cv34db2/vLItFRERERERERETkWVFSX7KEt7c39vb27N2716x8y/Nw/Phxs+Njx47h5eWFlZUVLi4uaW6a2rx5c7p06cK5c+fYu3cv/fr1M5375JNPzI5v3LhB165dCQwMNCXZvby8njhOR0fHNDfMtba2xtfXF19fX3r37k21atXYu3cvDRs2zHCD3UcZDAYSExNNxw8S+mXKlCEgIMBsD4LMKFCgAB06dKBDhw5MnjyZpUuX4ufnZ3oQk5ycbOpbrFgxbG1tCQsLMyu1k5ajR4/i4eEBQFRUFJcuXaJo0aJPFFt6KleuzIYNG7h79y45c+YE4OLFi1haWpI/f/5ncg0REREREREREXk6hv/QyvmspqS+ZAk7Ozu6d+/OpEmTsLGxoXLlykRERHDu3Dlq1KjxTK8VFhZGQEAA7dq14+TJk5mqH1+tWjXy5s3LwIEDKVSokNmK+AdJ5wccHByAlD0BnnVyeNu2bYSGhlKtWjVy5crFjh07MBgMFClSJM3+cXFxzJgxg3r16uHm5kZkZCSLFi0iPDycxo0bAykJfT8/Pzw8PBgyZIhZSaMHZY4yMm7cOGrXro23tzfR0dHs27fPtM9BwYIFsbCwYPv27dSpUwc7OzscHR3p0qULAQEBGI1GqlSpQkxMDIcPH8bR0dG0pwLAtGnTcHV1JU+ePAQGBuLq6kr9+vUz9V6dP3+epKQk7ty5w927dzl16hQApUqVAuCNN95g2rRpDBs2jI8++ojIyEgmTZpE69attVHuv4STa056ftmR6k0qYTQY2Ln6INMHLyLh7r1Mjf98xQCqNSzPZ+3/x551h03tJSoXocuYNhSv6I3RCGcOXWDOJ0u4cCIUgPK1SvJWr0aUqFoUByd7ws5dZ+mXq9n6/c7ncp8iIiIiIiIiIs+SkvqSZXr27ImVlRVBQUHcuHEDNzc32rdv/8yv07JlSxISEmjTpg1WVlb4+/vTrl27DMdYWFjQrFkzZs+eTa9evZ55TJnl5OTEpk2bmDJlCvfu3cPLy4vJkydTvHjxNPtbWVlx4cIFVq5cSWRkJC4uLpQrV45FixaZxuzatYuQkBBCQkKoXbu22fgzZ848NiaDwcCYMWO4fv06jo6O1KpVi2HDhgEpJYD69OnD5MmTGTZsGC1btmT8+PH069eP3LlzM3PmTK5cuYKTkxOlS5fmgw8+MJt7wIABjBs3jkuXLlGqVCmmT5+e6RI977//PlevXjUdt2zZ0uyecubMybfffsvnn39O69atcXFxoUmTJma/upDnb+L6oWxauJNNi1InzIfM+YDc+Z0Z9uZErG2sGDC9G/2COzO+y4zHztuqVyNTKatH2ee0Y9zKgez9+QhTPp6PlbUVfiNaMW71QDr69Cf5fjKlq7/EhT9CWRr4E7dDwnnljSoM/q4Pd6Pi2PfT4TSuJiIiIiIiIiLPWhr/Wy+ZZGFMKysi8oLy8/OjZMmSjBgxIrtDkQzs27cPf39/Dhw4QK5cubI7nAw1sGyT3SG80L7cMSbNpL6nTwFmHxpP71qfcu7IJQCq1i/H2BX9ebfEx0Rcv5PunEXLFWbM8o/pU+szFl8IMlupX7ySN1N+G01Hn4+5eTXlVyneZQoxc984OpcfRNiFG2ZzGf7aA+LztcOIvHGHyV2nP6M7FxEREREREfn32GRYlt0hpFJh3cgsv+axNzK/z+S/2ZMV1hYREXkGSr38EjGRd00JfYDD2/7AaDBSslqxdMfZ5bBl6NwPmNp/PpE3olKdv3LuOlG3Y2jUqTbWNlbY2tvQ2L82Iaevcj3kVrrz5nR2ICYi9h/dk4iIiIiIiIhIVlD5HZH/57p168ahQ4fSPNejR49UJXOywr8xJsmcDsNa0WHYW6Zj2xy2lKpWjF6T/Uxt3asOI3c+Z+7cjDYba0g2EBN5l9z5nNOdv8eEdzi59zx7fjqS5vn42AQGNQngsx/68s6QFgCE/Xmd4S2+xJBsSHNM7TY1KFGtGF9/MDPT9ykiIiIiIiIi/4xRG+U+NSX15T9lwYIF2R3CC2fcuHEkJCSkec7ZOf3k6j9RvXr1DOv5Z0dM8mysm7GJHUv3mI6Hfd+PnasPsmvNQVPb7Wt3nmruV5pWomLtUvR8dVS6fWztbeg/tSt/7D1HQOfpWFpZ8nbfJoz9sT99an9GYkKSWf8Kdcsw8NueBL4/g5CTV54qLhERERERERGRrKSkvsj/c/ny5cvuEFL5N8YkmRMTGUtM5MMyNvcSErlzMzpVLfuI8Chc3Mz3U7C0ssTJNScR4anL6gBUrFOKAkXdWXHVvO79yEV9OLH7DIObjOe1tjXI55WXfvXGmjbSHd95Oj9emU6NNyqzY/k+07hyNX0Yu7w/M/p/x+YFv/6j+xYRERERERGRJ6OV+k9PSX0REclyp/afx8k1Jy9V9Ob80UsAVKxTGgtLC04f+DPNMUsm/8T673aYtX2z/wtmDv2evT+nlOOxc7DFYDDy6B7wD44tLR7+x0L5WiUZs+xjZg9dyM+zNj/juxMREREREREReX6U1BcRkWfGPqc9ORztTccBnVJW1bu6PyybFHUrmtAz1zjwy3H6TelMcN/vsLKxotdkP3Ys30fE9TsA5CngyoSfBjOp+yzOHLpA5I2oNDfHvRF6m/C/NsE9svUPun/ejt6B/qyesQlLS0va9m9G8v1kjv16CoAKtUsyZll/Vk37hd9+3IdrPhcA7ifeN/uVgYiIiIiIiIg8Pwat1H9qSuqLiMgz02Zgc/w/bZthH//SAwi/fIsJXWfQa7If49cNxmgwsnP1QaYNWmjqZ21jhWcJD+wcbDN9/dCz1/i0zde8O6wlX28ZidFg5PzxEEa0mmwq61P/nZrY57Sj/aDmtB/U3DT22PY/GFjvsye6XxERERERERGRrGZhfLRGgYiImGlg2Sa7Q3ihWTo4ZHcIGTLExWV3CCIiIiIiIiLP3SbDsuwOIZXSqz7L8muebJn113weLLM7ABERERERERERERERyRyV3xERERERERERERGRLGVUTf2nppX6IiIiIiIiIiIiIiIvCCX1RUREREREREREREReECq/IyIiIiIiIiIiIiJZSuV3np5W6ouIiIiIiIiIiIiIvCC0Ul9ERJ4by5wO2R1ChgxxcdkdgoiIiIiIiMj/S8bsDuAFppX6IiIiIiIiIiIiIiIvCK3UFxEREREREREREZEspZr6T08r9UVEREREREREREREXhBaqS8iIiIiIiIiIiIiWUtF9Z+aVuqLiIiIiIiIiIiIiLwglNQXEREREREREREREXlBqPyOiIg8VzZ21vSZ+A4vVShM4eL52bfpd8a+NzPDMe6euXmnf1Mq1PTB1S0XEeFRbF2+n8Vfr+d+UrKpn3fpgvQKaE+Jil5E3Y5hzZztLJ+6Kc0567SsytCZXdm9/uhjry8iIiIiIiIiz5c2yn16SuqLiMhzZWllSWJCEmtmb+PVZpUyNcbzpfxYWFgQPPB7wi7dxKukB30nv4u9gy2zR68AwMHRnnFL+nD019MED/6eIqUK0i/Qj7vR8axfsNNsPnfP3HT79C1+33Pumd+fiIiIiIiIiEhWUlJfRESeq3txiUwZ8gMApasVI6dzjseOObTtJIe2nTQdXw+5xY/F8tHsvdqmpP5rrV/GxsaawH4LuJ+UzOUz1yhathCterxultS3tLRg8LQuLJi0jrLVX8rU9UVERERERETk+TJqo9ynppr6IiLyQsiZKwcxkXdNxyWrFuH3vefMyvEc2nYSz+L5cXR2MLW9M6AZUbdi+OX73Vkar4iIiIiIiIjI86CkvoiI/OsV8Hbjza51Wb/gN1Nbbvdc3LkZY9bvzs1oAFzdcwFQ5uViNHrHl/8NWJh1wYqIiIiIiIjIYxmNFln++q9QUl9ERP7V8uR35vPFvflt7WE2LNyV6XE5ctoxcOp7/G/AIqIj7j5+gIiIiIiIiIjIC0A19UVE5F8rdz5nxq/4mJMHLhA0YJHZuYgb0bi4OZm1ubilrNCPvBFNAW838hfOy2cLPjSdt7BMeSq/7uoUuvt+RujNW8/5DkREREREREQkTf+hlfNZTSv15YlduXIFHx8fTp06lW6fFStWULVq1SyM6p8LDg6mRYsW2R2GiPwlT35nJqz8mPPHLxPYdz7Gv+2gc/rgRcq9Uhwr64f/KqtUpxSh564TGxVH6PnrfFBnLL1e/8L02rvxOMd3naXX619wMywyq29JREREREREROQfU1JfnoumTZuycePG7A6DxMREWrRo8diHEFkpODiYxo0bU7FiRapVq8Z7773HsWPHTOevXLnC8OHDqVevHuXLl6d+/foEBQWRmJiYqflfxAcqT8PHxyfN1+zZs0197ty5w4ABA6hcuTJVq1Zl+PDh3L2rMizZoXCJ/BQtUwgn15zkzJWDomUKUbRMIdP5EpW8+Gbnp+TJ7ww8SOj35+bVSGZ/9iPOeZxwdcuF618r8QG2rdhPUtJ9+gX6UdinALVbVKFl99dYOXMLAEn37hNyOszsdTcqnrjYBEJOh5ltsCsiIiIiIiIiWctozPrXf4XK78hzYW9vj729fbrnExMTsbW1fe5xTJw4EXd3d06fPv3cr5VZ3t7ejBo1Ck9PTxISEpg3bx5dunRh06ZN5M6dmwsXLmA0GhkzZgxeXl6cPXuWkSNHEh8fz5AhQ7I7/H+NnTt3mh3/+uuvjBgxgkaNGpnaBg4cyM2bN5k7dy5JSUkMHz6cUaNGMXny5KwO9/+9MYt6k69wHtPx1K0jAGiSL6U0jl0OWzyL58fKxgpIWXFfsKg7BYu6s/DYeLO5HoyJi0lgRLtgegW0J/iXYURHxPL95J9Zv8D8syEiIiIiIiIi8l9iYfx7PQORvxgMBubMmcPSpUu5du0aefPmpV27djRv3pzXX3+d4OBgFixYwPHjx/Hy8mL06NFUqlQJSFkt/sUXX3Dw4EEgZXX65s2b6dixI9OnTycsLIzTp0/j5+dH8eLFAVi9ejXW1tZ06NCBvn37YmGRuq5WbGwsvr6+BAcHU6dOHVP7pk2bGDx4MLt37yZHjhwA7Nixg/HjxxMcHEyzZs1YtWoVpUqVSvd+H8TYuXNngoKCiIqKonbt2owdOxZHR8d0xy1atIjvvvuOa9eu4eTkRNWqVQkKCsr0+xwbG0uVKlWYN28eNWrUSLPP7Nmz+eGHH9iyZUuGc+3btw9/f3+ztt69e9OnTx8SExMJDAxk3bp1xMTEULx4cQYOHEj16tWBh39nkyZNYvz48Vy/fp06deowYcIENmzYQHBwMDExMbRo0YJhw4ZhZZWSfK1Xrx6tW7fmzz//ZOvWrTg5OfHBBx/w7rvvPvbejUYjU6ZM4ccff+TWrVu4uLjQuHFjPvnkk8y8dWZ69uzJ3bt3+e677wD4888/adq0KcuXL6dcuXJASuL//fffZ8eOHeTLly9T8zawbPPEschD1m55szuEDN1XTX0RERERERH5f2CTYVl2h5BK0R++yPJrXugwPNN9Dxw4wJw5czhx4gQ3b95k6tSp1K9fH4CkpCS+/vprfv31V0JDQ3F0dMTX15cBAwZkmHMKDg5mypQpZm1FihRhw4YNT3QfWqkv6Zo8eTLLli1j2LBhVKlShRs3bnDx4kXT+cDAQIYMGYKXlxeBgYEMGDCAX375BWvrtD9Wly9fZuPGjUyZMgVLy4eVn1auXMnbb7/NsmXLOHHiBKNGjcLDw4O2bdummsPR0ZG6deuybt06s6T+2rVrqV+/vimhf+vWLUaOHMnUqVMz/MVAWjFu2bKFGTNmEB0dTb9+/Zg1axYff/xxmv1///13xo0bx8SJE6lUqRJRUVGmBxmZkZiYyJIlS3BycsLHxyfdfjExMTg7Oz92vkqVKjF8+HCCgoJM/zBwcHAAYMyYMZw/f57AwEDc3d3ZtGkT3bp1Y+3atXh7ewOQkJDAggULCAwM5O7du/Tu3ZvevXvj5OTEN998Q2hoKH369KFy5co0bdrUdN05c+bwwQcf0KdPH3bu3Mm4cePw9vbm1VdfzTDejRs3Mm/ePL766iuKFy/OrVu3nupXFbdu3TI9xHngyJEj5MqVy5TQB/D19cXS0pLjx4/ToEGDJ76OiIiIiIiIiIg8I//ypeZxcXH4+PjQunVrevfubXYuISGBkydP8uGHH1KyZEmio6MZN24cH374IStWrMhw3uLFizN37lzT8YOFs09CSX1JU2xsLPPnz2fUqFG0atUKgMKFC1O1alWuXLkCQJcuXahbty4AH330Ec2aNSMkJIRixYqlOWdSUhITJ04kd+7cZu0FChRg+PDhWFhYULRoUc6ePcu8efPSTOoDvPnmmwwaNIj4+Hhy5MhBbGws27dvNz3lMhqNDB06lPbt21OuXDlTvJlhNBoJCAgwrcx/88032bNnT7pJ/WvXrpEjRw7q1q2Lo6MjBQsWpHTp0o+9zrZt2+jfvz/x8fG4ubnx7bffpnpfHggJCWHhwoWZKr1ja2uLk5MTFhYWuLm5mdrDwsJYsWIF27ZtMz0t7Nq1K7/99hsrVqygf//+QMrf0WeffUbhwoUBaNSoEWvWrGHXrl3kzJmTl156ierVq7N3716zpH7lypV5//33gZSni4cPH2bevHmPTeo/+AWIr68vNjY2eHh4UL58+cfe59+tXLmSnDlz0rBhQ1PbrVu3Ur2n1tbWODs7c/PmzSe+hoiIiIiIiIiI/P9Rp04ds0XFj3JycjJLzAOMHDmSNm3aEBYWhoeHR7rzWllZmeXtnoY2ypU0XbhwgcTERF555ZV0+zy6svzBBzEiIiLd/h4eHmkmritUqGBWaqdixYqEhISQnJzMjBkzqFSpkukVFhZG7dq1sbGxYevWrUDKau8HP3EBWLBgAXfv3qVHjx7pxvLonKNGjTK1FyxY0KzUjru7O7dv3wZgzZo1ZuMOHjyIr68vHh4e1K9fn0GDBrFmzRri4+PT7f9A9erVWbVqFYsXL6ZWrVr069fPdJ1HhYeH061bNxo3bpzuQ47MOHv2LMnJyTRu3NgspgMHDnD58mVTvxw5cpgS+gB58+alYMGC5MyZ06zt73/PFStWTHX8559/Pjauxo0bc+/ePerXr88nn3zCpk2buH///hPf348//kjz5s2xs7N74rEiIiIiIiIiIpL1jEaLLH8lJiYSGxtr9kpMTHwm9xMbG4uFhQW5cuXKsF9ISAg1a9bk9ddfZ8CAAYSFhT3xtbRSX9KUmeSojY2N6c8PkvIGgyHd/g9K4zyJ9u3b06RJE9Oxu7s71tbWNGrUiLVr19KsWTPWrVtH06ZNTWV/9u7dy9GjR83KrgC0bt2a5s2bM2HCBFatWmVqfzSJn1bpoAfbTtSrV48KFSqY2vPly4e9vT0rV65k//797Ny5k6CgIKZMmcLy5cvT7P+Ag4MDXl5eeHl5UbFiRRo2bMjy5cvNHkSEh4fj7+9PpUqVGDt27JO+dWbi4uKwsrLixx9/TPWTngfledK6fwsLizTbMvp7fhIFChRgw4YN7N69m927dzN69GjmzJnDggULzD5fGTl48CAXL17k66+/NmtP6+HD/fv3iYqK+sdPQ0VERERERERE5MUzc+bMVDXtH+xH+U/cu3ePL7/8kmbNmmW4N2f58uUJCAigSJEipjr97777LmvXrs1w3N8pqS9p8vb2xt7enr179+Lp6flcr3X8+HGz42PHjuHl5YWVlRUuLi64uLikGtO8eXO6dOnCuXPn2Lt3L/369TOd++STT8yOb9y4QdeuXQkMDDQl2b28vJ44TkdHxzS/XNbW1vj6+uLr60vv3r2pVq0ae/fupWHDhpn+MhoMBrOngg8S+mXKlCEgIMBsD4LHsbGxITk52aytVKlSJCcnExERQdWqVTM9V2YdO3Ys1XF6ZZj+zt7ennr16lGvXj3eeecdmjRpwtmzZylTpkymxi9fvpwyZcpQsmRJs/ZKlSoRHR3NiRMnKFu2LJDywMdgMDxViR8REREREREREXmGsqGmfo8ePejcubNZm62t7T+aMykpib59+2I0Ghk9enSGfR8t51OyZEkqVKjAa6+9xvr162nTpk2mr6mkvqTJzs6O7t27M2nSJGxsbKhcuTIRERGcO3eOGjVqPNNrhYWFERAQQLt27Th58mSm6sdXq1aNvHnzMnDgQAoVKmS2Iv7vNaserEQvXLgw+fPnf6axb9u2jdDQUKpVq0auXLnYsWMHBoOBIkWKpNk/Li6OGTNmUK9ePdzc3IiMjGTRokWEh4fTuHFjICWh7+fnh4eHB0OGDDFbbZ6ZFeYFCxYkLi6OPXv24OPjQ44cOShSpAjNmzdn8ODBDB06lFKlShEZGWnq82BvhKd1+PBhZs2aRf369dm9ezcbNmxg5syZjx23YsUKkpOTqVChAjly5GDNmjXY29tnWHfsUbGxsWzYsCHNz0uxYsWoVasWI0eOZPTo0SQlJTF27FiaNWuW4S7kknUcXRzo+UU7qjcsh8FgZNdPR5gxYhkJcfcyNX7M972p9noZxrw3gz3rHz5YKlHRi86ftOSl8oUxGuHskUvMGbOCiyevmvp4ly5Ir4D2lKhYmDs3o1k9ZT1LJ6155vcoIiIiIiIiIv8etra2/ziJ/6ikpCT69etHWFgY33333ROttgfIlSsX3t7eZuWxM0NJfUlXz549sbKyIigoiBs3buDm5kb79u2f+XVatmxJQkICbdq0wcrKCn9/f9q1a5fhGAsLC5o1a8bs2bPp1avXM48ps5ycnNi0aRNTpkzh3r17eHl5MXnyZIoXL55mfysrKy5cuMDKlSuJjIzExcWFcuXKsWjRItOYXbt2ERISQkhICLVr1zYbf+bMmcfGVLlyZdq3b0+/fv24c+eO6SdEAQEBTJ8+nfHjx3Pjxg1cXFyoWLHiP07oA3Tu3JkTJ04wdepUHB0dGTp0KLVq1XrsuFy5cvHNN98wfvx4DAYDJUqUYMaMGbi6umbquj/99BNGo5E33ngjzfNffvklY8eOpVOnTlhaWtKwYUM++eSTJ7o3+WcmrPiYTUv2sHnJ3lTnBk/rQu58uRjeNghrays+/p8/H01+l4kffvvYeVv2qAfG1I/07R3sGPtDb/ZuPM6UIYuxsrbEb9AbfL6kD/6VhpN834CDoz3jlvTh6K+n+brbVIqUK8yAOT2JvRPHz7M2P5P7FhEREREREZGMGY0Wj+/0L/YgoR8SEsL8+fMznc961N27dwkNDX3iUtEWRmMaWRGRLOLn50fJkiUZMWJEdociT6levXr4+/vz3nvvZXcoz0UDy8z/9ElSm/zbuDST+p7F8/PNzk/5qGEA546lPI2u8lppxnzfC7+Kw4kIj0p3zqJlCjF6YU8+ajie709MMFupX7xCYYJ+GYZfpeHcCosEwLuUB9O3j6RL9VFcu3STZp1q02nYm7xTbggJYeEAdA14F98W1ehaut9zeBdEREREREREstcmw7LsDiEV7wXjs/yal/yGZrrv3bt3TSvoW7ZsybBhw6hevTrOzs64ubnx0UcfcfLkSWbOnEmePHlM45ydnU2/BujUqRMNGjSgY8eOAEyYMIHXXnsNDw8Pbty4QXBwMKdOneLnn38md+7cmY5NK/VFRCTLlapahJg7caaEPsCRX09jNBgpWdmb3euPpTnOLocNQ6Z3YeqwxUTejE51/sr5cKJux9LoHV+W/G8DllaWNHrnVS6fuUZ46G0ASlYtwu97z3E/6eHeEwc3HqX9kJY4uuQk9s7dZ3y3IiIiIiIiIpLKv3yp+YkTJ/D39zcdBwQEANCqVSt69+7N1q1bAWjRooXZuPnz51O9enUAQkNDiYyMNJ27fv06/fv3586dO+TOnZsqVaqwdOnSJ0rog5L6Ii+cbt26cejQoTTP9ejRgw8++CCLI0rfmjVr+PTTT9M85+HhwU8//ZTmuYMHD9K9e/d05z1y5MgziU+evQ7DWtFh2FumY9sctpSsUoSeAQ9LavWoNQZXd2eibsWYjTUkG4i5E4eru3O6878/pg0nD15g74bjaZ6Pv3uPIW8FMmpeDzr0bwpA2IUbfNI+GEOyAYDc7rm4fvm22bjIv34ZkDu/i5L6IiIiIiIiIkL16tUzLIWdmTLZDxL/DwQGBv7juEBJfclmCxYsyO4QXjjjxo0jISEhzXPOzuknQ5+Xv//D6VH16tUz28T4UdbW6f/jp2zZsqxateqfhibZYN2MTexYusd0PGxJf3atO8Kun46a2m5fT7+0TkaqNypPhZo+9H79i3T72Nrb0C+wIyf3X2DCB99iaWVJ6w/rM3pRL/o2Gk9iQtJTXVtERERERERE5N9CSX2RF0y+fPmyO4RMc3R0fOJdvwHs7e3x8vJ6DhHJ8xYTGUtMZKzpODE+iTu3Yrh26aZZv8gbUTjndTJrs7SyxMnFgcgbaSf9K9b0oYB3Xpafm2zWPmLO+/yx9zxD3gqk7lvVyOeZh/5NJ/Fgy5gJH37LsrOTqdG4AjtWHSTiRjQububXds2X8kAs4vqdp7pvEREREREREXlSL/ZGudlJSX0REclypw5exMnFgZfKF+b88ZS6+hVr+mBhacHpw5fSHLM0aCMbFu0ya5uxYyTfjFrOvl9SyvHY57DFaDDy6B7whr+OLSxT/mPh9MGLdBr2JlbWltz/q0+VBuW5fPqqSu+IiIiIiIiIyL+eZXYHICIi/x32Oe1xzedieo3vMYdDW0/i6pbL9LK0tCD03HUObPmDvpPfpUQlL0pXK8qHAe3YseoQEX/Vt8+T35lvdn5KiUopv9qIvBlNyOkwsxfAzasRhP9VI//wjlM4OjvQa3x7PIvnp7BPAfr/z5/k+waO7UypdbdtxX6Sku7TL9APr9KFqNPWl5YfNeXHwHXZ8I6JiIiIiIiI/D9lzIbXf4RW6ouIyDPTZmBz/D9tm2GfTlVHcCM0gok9v6VnQHsClvfDaDCy66cjTB++1NTPysYKz+L5scthm+nrXzkfzmd+03h3YDO++mkQRoORP0+EMrLDFCJvRAMQF5PAiHbB9Apoz7SDE4i6FcOiscv5edbmp7tpEREREREREZEsZGF8tEaBiIiYaWDZJrtDeKFZu+XN7hAydP/mrewOQUREREREROS522RYlt0hpOI9b0KWX/PSe0Oy/JrPg8rviIiIiIiIiIiIiIi8IFR+R0RERERERERERESyltEiuyN4YWmlvoiIiIiIiIiIiIjIC0Ir9UVEREREREREREQkS2mn16enlfoiIiIiIiIiIiIiIi8IJfVFRERERERERERERF4QKr8jIiIiIiIiIiIiIllL5XeempL6IiLy3Ny/eSu7QxARyRZhg3yzO4QMeU4/nt0hZOh+peLZHUKGrCPuZncIGUr+42x2h5AhSweH7A4hQ1d7VszuEDJ0vP/07A4hQ408KmR3CCIiIv95SuqLiIiIiIiIiIiISNYyWmR3BC8s1dQXEREREREREREREXlBaKW+iIiIiIiIiIiIiGQpC9XUf2paqS8iIiIiIiIiIiIi8oLQSn0RERERERERERERyVpaqf/UtFJfREREREREREREROQFoZX6IiIiIiLPyaslvOjVoAYv5cvDvaT7HLp4lYk//UpYZPRjx9pYWbG4d3tKerjT+uuFnL52M1WfwnmcWd63I8kGAzU+m25qf/vlsrxZuTQv5csDwMmrN/jfhp38fiXcbHyRMoXoNdmPEpWLEHUrhtUzN7P8f+vTjanBO68yYEa3NM+1K/oRUbdiAChf04f3v+hA4VIe3LoawQ8T17Lp+10P+/ZvxqtvVqFQ8fwkJiRxct95vh21jCvnr5v6FPLMTb8BTfDyykvOnHbcvh3D1s0nmT/vN5KTDenG6FOyAF3ff40SJfJjxMiZU9f4ZsZWLvx5AwD/92rh37lWqnHx8Yk0b/wlAF7eeXmvS22Kl8hP/gIuTAvexIrlB8z6l69ahFb+r+JTthAOOe24evk2y+f9xrafjqUbm+l9bFGJt/xrUtArD3Gx9/ht0wmmjltr1qd1p5o0ebsa7h4uREfGsW7JPhbP2m52/fcHNaXwS+7cuh7FD99sY9PqI2ZzFClXmD5TuuFTrRh3bkazesp6lk5ak2Fsbp556TutOxVeK0N8bAKb5u9gzrBFGB55z21srek4qg2vv1sL1/wuRFyLZOHY5Wycuy3VfHXb+TLih4/ZtWo/n701yTy+Mp70Dnzk8zdjM8u+/vnx79+7NXmrT2MKvZSPuJgEfl25n6n9FwCQr3Be5p+cnGpM39fGcPrAnwA0ea8O9d95Fa9ShQA4f/QScz9bzplDF8zG+D74/uZ/+P2dtC7j72/we29SsoAbuR0diI6/x95zl/lq/W/cjL4LgLebK6Peep1i7rlxtLfjRvRdfj56mumb9nLfkPIe1y/7Et3rvYxnHmesraz4afNWps74hmuXLsD9RFr9AV3aQ/MGD6977iIEfwt/nIWw6xYM7W2kU5vHvpUmIVfgrW5gZQX7f3rYvnQtrNmYMj9AaR/4uDuUL/Wwz60ImDwTdh2AmFjA4wKuNwtik2SX+QBERETkiSipLyIiIiLyHBR0zUWw/5t899thhvywHkd7O4Y0r8P//N6gTdD3jx0/oGktbkTfpaRH2uetLS2Z1KEphy5epaJXAbNz1YoW4uejpzkaco179+/TtW41vun2Fi2+ms+Nv5KLDk72jFs1kKPbTxLc7zu8yxTi46lduBsVx/p5O9K85o4V+zm4+XfzOGd0w9bOxpTQz+eVlzHLPuanb7cxodtMKtYtTb8pnYkIj+LQlhMAlKvpw9pvtnD28EUsra3o/Glrxq0awPsvj+BeXCIAyfcNbNr4O+fOXic2NoFixfLRf1BTLCzh21lpx2efw4aAie3YvfscQYEbsLKypFPn2oyf1J4ObaaQnGxg6ZK9rF1z2GzcpK/e4czpaw/nsbfhWtgddmw/zYe966d5rVIVC3Px7HWWzvmVO7djebmODwPHvc3dmAT2/3omzTEAb/m/ylv+NZn91XrOHL+CvYMN+Txczfp8OLQZlX2LM3vyei6eC8fJOQdOzjlM5/MVdGXMVH9+WrafCUOXUvGVYvT7rBURN2M4tPs8AA5OORi/cSSHNx/nfx9+Q5FyhRkwpyexd+L4edbmNGOztLRk3LphRFy/Q79XPyF3ARcGf9eH5KT7fDviB1O/T5b0xzWfM5O7TSfs/HVyF3DF0tIi1Xz5vNx4f5I/x389meqcg5M9X6wZyJFtJwnqm/L56z+tK7FRcayfuz399693I1p/1ITZIxZz+uAF7B3syOeVN1W/IW9MIOTkVdNxdESs6c/la5Vk27K9nNx7nqR7SbT9uBlfrB7I+9VGcPtaJPDX97fTm8z/7TBDf1iPYw47Bjevw9f+b9D2f+l/f/f/Gcqsrfu5GX2XfM6ODGxWm8COb9Bx2hIA7icbWHPoJKeu3iA6/h4+Hm6Mbl0fSwsL/rch5cFXVFwC32zZx8WbkSTdT8bl2mnefK0m+6JrcuJGFK1Kfc/QL8AxJ7zmm3LdhATw9IBGdWH8lCerZZB0HwaOgSrl4egf5ucOHIWmr0OlsmBnC7O/h24DYe08yOcGRiP0HgHW1jB1XEpMbd+05UbBCxQI8cHSqOIAIiKSAWPq/36QzFFSX0RERETkOShTKB+WlhYE/bIL4185tnm/HiLY/02sLS1Nq3LTUtPHG98Shfl4wTpqlyySZp+PGvly4WYk+85fTpXUH7J4g9nxqOWbaFD2JV55qTBrDp8C4LW2NbCxteKrnnO4n5RMyOkwipYrzFu9G6Wb1E9MSCIxIcl07JzHiQq1S/F1729Nbc26vMb1kJvMGpGSxAw9e40yNYrTqldDU1L/k7e+Mpt38gdzWHIxiOIVvTmx+ywA167d4dq1O6Y+N8Kj2bL5BOXKF073fStcOA+5nB34bs6v3LyZ8pBhwXe/MWtud/LldybsaiQJ8UkkxD+8h6LF3PEu4sbXXz18z86cvmZK8nd7v26a11oy2/w9Wr1oD1V8i/Nq/TLpJvUdc9nj37s+n/VZwNF9D1eFXzz78BcUnkXcaNa2Oh+8FcSVS7cACL8aaTZPs7Yvc/1qJLO+TPlVRejFm5Sp5EUrv1dNSf1679bC2taayV2ncz/pPiEnr1CsYhFaf/xGukn9Kg3LU7h0IQY3GMOdG1H8eQy+G7WYbuM7Mv+zZdxPuk/VRhUpX6c0/sV6ExOZkigPD0n9KxJLS0uGLfyI+Z8tpVzNUuR0cTA7X6+dLzY21nz14eyUz9+pqxQrV5jWfRqlm9R3dHGg06jWfNr2a45uf/ig4OIfoan6Rt+OJfJGVJrzTOg60+w4sNccXm1RlUp1S7P5h5TEeukH39+Nj3x/dxwiuFPG398Fvz38tcS1OzHM3n6AoEe+81ciorgSEWXWZ13R01QuUtDUduDCFbM5Q+0KMLLtOzicusgfv+zB/+2UVfGbf32Y1C9XKuUF8NU3aYaWrv/NhiKFoUaV1En9SSPNj8cOhl9+hT2HoGVjuHQFjp20YM08I8X/+keV642CxBU5SZxTJI7ReZ4sGBEREckUPTYXEREREXkO/rgSjtFopFXVMlhaWOBob0vzyqXYc/5yhgn9PI4OjG5dn2GLNxKfdD/NPtWLedKwXAk+X7U1U7HY21hjbWVFVFyCqa3Uy8X4fddZ7iclm9oObTmBZ4kCOP4tAZue1zv4ci8ukd9WHTSb98h285XZhzafoFS1YunO4/DXKvSYyLvp9vEo6Eq1l4tx/OjldPuEXo4g6k4cTZpVxNraEltbaxo3rUDIpVtcv34nzTFN36hI6OXbnDieOjH8pHI62hETFZfu+Uo1XsLS0oI87rn4ZnVfFmwezPAv25M3n7OpT/W6Jbl+JYKXa/swb/0AvtswkH6ftcIx18OV+qUqeHJk73mzuQ/tPkepCg8feJR+pQS//3qS+498hg5uPErhkgVxdMmZZnyla/hw6ffL3HkkGX5w4zFyOjvgVSalVE2NN6ty9uCftB3cgh9CZzL39P94f5Iftva2ZnN1HPU2kTei2fBt2p/RUi+/xO+7zvzt8/c7niU80v38Va5XFktLC/IWcGXWoQAWnglkxPxeuBXMnarv6KX9WHIxmMm/jOCVppXSnO8BOwc7rG2sTA8pAE6m8/3d+5jv76Ny5bDjjUolORoSlu4YzzzO1PTx5uDfEvmPqv6SJ95uuTl08eEvD2LvgnOuTIWRob2HYeN2GPVx5von3IP79x9eOynlhzXYPfLXb4EFFkZL7uVI/7sgIiICpGyUm9Wv/wit1BcREREReQ6uRkbTffYKJr/bjE9b1cfaypIjIWF8+O2qDMeNa9uQpXuP88fVcDxcU2ftnB3sGde2IUMWb+DuvcRMxZJSyieWPecfJsRd8zkT/tdK8Afu3EipFe7q7kzsnccn5Br512Lb8r1mq/dd8zmb5jHNezOanM4O2NrbmPUFsLCw4IPxHfhjz1lCTl3l7/431Z/ixfNja2fNujVHmPdt2r8igJS6+AP6LWL056151/9VAK5eiWTooB8wJKf+vzgbWyvq1S/D4u/3PPZeH6dWo7IUL1uIoDGr0+1ToFBuLCwtaN+9LjPGr+Nu7D069alPwKzOfPhWMPfvJ1OgUG7cPVyo1bAsk0Ysx8rSkvcHN+WTrzowtFvKLyJc8zhx53as2dx3bseS08keWztr4oHc+V24dumGWZ/I8JRkfe78LsTeSf0AxTW/C5Hhd/425o5pzJ9AgSL5KFuzJIkJSXz21iSc8zrRZ2o3cuV24suu0wAo82pJGnepxweVBqX7Xrjmc+b631b4Rz74/OVL+/OX39sNC0tL2g96g+mDFnE3Op73RrUmYO0gPqj+CfeTkom/m8DMod/zx95zGA1GaraoyqeLP2J0+yD2/nwk1ZwAXce25fa1Oxze9vBh1NXIaN7/6/s76q2U7+/RS4///gJ83KQmHV6tiIOtDUdDwug1N/VnYmHPdpQq6I6djTVL9x5nyi+7zc472tuydUR3bKytMBiMfL5yK3vOpXx/12+F30/DZwMeG0qGIqNgeABM+CSlbE5mfDkD3POCb5WU4yJeUCCfkcBv4LOBkMMeol1vkGyTRHJiUsaTiYiIyFPTSn0RERERkecgr6MDo1s3YM2hU7Sb8j3+M5aSdD+ZwI5vpDvmXd+K5LS1Zda2A+n2Gd26Pj8dOWO2ajcj3epWo0kFH/rOX0vi/eTHD8ikUi8Xw6tkQTbO//UfzdNrcke8SxUioPOMNM9//tlKPuj+LePGrKL6K8Vo0/6VdOeytbVmwOCm/HHiCh/1/I5+vedz6eJNxo1vh61t6vVMNWv54OBgyy8bfk9jtswrX60IA8a05n+frSTkzxvp9rOwsMDGxprpAes4tPs8p4+HMn7wEjwK56HCyym1SywsLbC1s+HLEcv543AIxw9e5OtPV1KxejEKeaeuHZ/VLC0tMBohoGMQZw6cZ//6I8wc8B0NOtXB1t6WHI72DJnfh8D3ZxB9O+aZX9vG1pppAxdxaMsJTh/4k4DO0/Eolp8KtVNqz0TfjmXFlI2cOXiBs4cv8u2ny9i6eA9t+jVJc862/ZtRt3V1xnQIIunewyR0HkcHPmvdgNWHTtE++Hs6TV9KUnIyX/ml//19YO6Og7T5eiHdZ/2IwWAkoF2jVH0GLvqJNv9bxKDvf6Z2ySK8V7uq2fm79xJp/fVC2gf9QNDGXQxqXptqRQthuHmVERNgzEBM5W6e1qhJ0Kw+VKuQuf6zFqU8UAj+HOz+2gPXxhqCx6aU4XnlDQsqN4KEHLHY33UCVCdZREQeQyv1n5pW6ouIiIiIPAcdfCsQm3CPyet/M7UNXbKBrcO7U75wfo5fvp5qTPWXPKngVYAj4z4ya1/S5x1+Onqa4Us3Ur2YJ6+VKsZ7tVOWylpYgJWlJce+6MtnKzaz8uDDotjv1a5C17pV6TZrBWevm6/KjwyPwsXd/JcAD47Tq0X+qMb+tTl/LITzR0MeP69bLu5GxaVapd/zy45Ub1yRgU0CuBVmXjf+gZTa+DFcDrmFpaUFHw9syvIl+zAYUv9fWb36Zcif34WPen5nqoP+xdhVrFzXH9+aJdi+1bwsUJNmFdm75zx3Mij78zjlqnozeoofMyf9zJa1RzPsG/HXZsKXLzxM/EdFxhF9Jw63Ai4pfW7GcD8pmasht019HvR3K+DMlUu3iLwdg0seR7O5XfI4cjcmgcR7KeV2Iq7fwdXd2ayP619lfiLSKUUUef0OJau99LcxLmZjbl+L5NbVCOKiH66kv3zqKpaWlrgVyo19TnsKFHFn7JqhpvMWf22iuyFxMZ1L9iX8egyR4VG4upl/TlwffP7C0/78RVxPab98+uEDrahbMUTfjsHdM/3a7acP/kmlemVStb/9URPa9W/G0OYTU9Xlf/D9/ernR76/izewZUT6398H7sQlcCcugZBbd7hwI4ItI7pToXABjl1+uBnz9aiUX1pcuBGBlYUFn7auz3e/HsLw1wfXaITQ2yn3e+baTYq656aWmx27961naL+Uevb/1L4jsG03zE3Z/gKjEQwGC8rWMzJ6ALRu9rDvt4th1vfw7WTw+VslrTI+sHIOxMQaSboPHUoX5brnOWwTMlfGS0RERJ6ckvoi/3JXrlzh9ddfZ9WqVZQqVSrNPitWrOCLL77g4MGDaZ7/NwoODmbz5s2sXp3+T9RFREReZPY2NqYE3QPJfyWiLS3SXsEasGY7QRsfluFwz5WTWd1aM/D7nzgempJEfHfaErPx9UoXo2vdqrw7bQk3oh+WZOlSpyrv13uZ9+es4I+rDzdifeDU/j95b9RbWFlbkfzXCv7Kr5Uh9Oy1x5besc9pR61W1Zg7+sc0563WsLxZW+V6ZTh14E+ztp5fdsT3jcoMbjaB8BDzBw7psbS0wNraEgsLC9JaamVvn/KeP/q2G4xGMILl336jnD+/MxUreTFy+LJMXTst5asWYfRUP74N3Mj65en/uuKBk0dSHoAU8s7LrfCUUjOOuXKQy8WBG2F3TH2sbawoUCg3165EAFDQK2WF/oM+p46FUq1WCbO5K9d4iVPHHpZXOrn3LJ0/72D291ulQXkun76aZukdgJN7ztBh+Fu4uOXizs2U+Co3KM/dqDgun0yp+f7H7jPUblMD+5z2JNxN2aOhYIkCJCcbuHklAqPRSPdy/c3mfW9sexyccjCt31xuht4GG1tO7T/Pe6Na/+3zV5bQs2Hpfv7+2JuyiXKhEgVMD4GcXHOSK48T4ZdvpzkGoFi5wqkeZLTp15QOg5ozvOWXnDtyKdUYe9sn//6mxeKvvrbWVun2sbSwwNrKEksLi1TXfODiqT+Y/1UAlqVfoe2bv6XZ50n9MBWSHyn1v3UXzP7eyPdTIZ/bw/bZ38PMhTBrEpQtmf58Tn89Z0qyuUeiXTzOt/M/kzhFROQ/7D+0cj6rqfyOyH9A06ZN2bhxY3aHQWJiIi1atMDHx4dTp049l2vUq1ePefPmZTqewMBAXnvtNcqWLUu9evVYvnz5c4lLRETk7349fZGyhfLz4evVKZzHhVIe7oxr05CrEVGcupqy8rpcoXysHdAJ91wpBa2v3YnhfPht0+vSrTtAyord8EdW9j7a50Z0LAajkfPht4mOvwdA1zpV6dOwBiOX/UJYRDR5HR3I6+iAg62NKb5ty/aSlJjMx1M741XSg9pvvUzLDxuwYsrD/6bwfaMysw5+kere6rz1MlbWVmxdsjvVuZ++3UYBbze6jmlDoeL5eaPba9RuVY2VU38x9en1lR/12tZgQteZxMfE4+qeC1f3XNjaP4yvXv0y1HmtFIW98lCggAt1XitF1+6vsX3rKZL/ykS+WqsE387vYRpz6OBFnBzt+ejjRhT2yoOXd14GDX2D5GQDRw+b/6KgcdMKRNyO5cA+84cNANbWlhR7yZ1iL7ljbWNF3rxOFHvJHY+CrqY+5asVYcxUf1Yv2sPOTX/gmscR1zyOZhva+tYrzaw1/UzHV0Nus3vrST4Y8galKhTG6yV3Bo57mysXb3LswAUAjuz9k3Mnr/Lx2LcoVrIAL5X24KNRLTi0+5xp9f5PS/dToGBuun7ciEJF8vJGu+rUbliWlQt2ma619fud3E+8z4DZH+JVuhB12vrS8qOm/Bi4ztTn1ZYvM+fk1w/fv1+Oc/nkFYbM70PR8l5UbViB98a2Z820DSQl3jfNG307hkHf9qRwqUKUq1WK9yf6sXHuVhITEkm6l8SlP0LNXnfvxBEXE8+lP0JNG/duXbqHpKT79J/WFa9SBanT+mVa9mzIj8GPfP6aV2H24YCH79/5cHavPcSHE9+ldPWX8CpdkIEzu3Pl7DWO/Zry357133mVum1ewbNEATxLFKD9wDdo6F+bNTM2m+Zp+3FT/Ee+xVc95xAecgtXd2dc3Z2xz2ln6vPrqZTv7wf1q1M4rwulCrrzeVvz729Zz3ysGfjw+1vOMz8dfCvgU8CNAi5OvFzMk0nvNOXyrTscDUlZpd+sUkkalS9BUffcFMrtTKPyJejbpCYbj501babb7bVq1ChemEK5nSnqnpsGHg4sDBxP0eq1sfQoys3bcPM23Hlk64rEJDh1LuWVlAQ3bqX8OeSR/XcXrYDOj2yIW8wbShR9+MqXN+XhV4mi4OyU0mfW9xD0LYwbAgXzY7r23Ueeu2zYBvuPQGgYbNkJNwpeIMfdXOSIc0JERESeD63UF/kPsLe3x97ePt3ziYmJ2NraPvc4Jk6ciLu7O6dPn37u18qMvn37cvv2bcaNG0fhwoW5efMmBoPh8QNFRESegX1/hjJ48c90qVOVLnWqEp90n2Mh1+jx7Uru/bUy2d7WhqLuubG2Sn8V79No90p5bK2t+dqvuVn71E17mLZ5LwBx0fGMaPklvSb7EfzrZ0TdjmHRhDWsn/dwI9qcuXLgWaJAqvkb+ddm19pD3I2KT3UuPOQWo9oE8n5AB1p82IBbYZF83Xsuh7acMPVp3q0eAJPWDzUbO/mD2Wz6PiUxbUg20K7DKxTyzI0FFoSHR7F65UGWL9v/ML6cdhT2elh2JfTybT4ZvhT/TrUImtop5WHHuXCGDV5MRMTD1ekWFtCwSXk2bjieZhmfPHmdmDmnm+m4bYdXaNvhFY4dCWFAv0UANGhRGXsHW9p3r0v77nVNfY8fuMDgLnNS4nOyw7OIm9ncXw5fTo/BTRkzzR+jwcjvBy8y4oPvSL6f8t8oRqORT3svoOewN5g0rzsJ8Ykc3HmWbyatf/geX41kVK/5vD+4KS06+nIrPIqvP1vJod3nTX3iouMY2mgsfaZ0Y9rBCUTdimHR2OX8POthcjunswOFSxY0HRsMBj5pHkDfad353+5xJNy9x6b525k3aompT8LdBIY2HEuvoK5MPTCe6Nsx/LpsD3M/WZzqfcxIXHQ8w9/8kt6Bfkz57TOibseyaPwq1s/d/jC+XDnwLOFhNm7S+9/QY/w7jFneH6PByPFdpxnR8kvTan+Ad4a8ST7PvCTfTyb07DW+6DSVnase/qK1Wbd62NrZMHJRH7O5F3yxkoVfrAJg/5+hDPnhZzrXNf/+fjDn4fc3h4359zchKYn6ZV+iV4Ma5LC14WbMXXaducTMLftISk4Zk2ww0KVuVbzdXLEAwiJj+GH3Ueb/dtgURw5bGz5pVY98zk7cS7rPoMGDiY+P59SOlAdjtTemrP6vVtHI/P+ljLl5C97q9vAXBN8uTnk92icyCi6HPcnfEixeDUlJFvQdZd7e6z0jvTv/de3bMGEq3I6EvHkgZ7QrzhHuT3YhERH5/8mo/VeeloXRmM7v+0QkSxkMBubMmcPSpUu5du0aefPmpV27djRv3pzXX3+d4OBgFixYwPHjx/Hy8mL06NFUqlQJSF1+50Fpm44dOzJ9+nTCwsI4ffo0fn5+FC9eHIDVq1djbW1Nhw4d6Nu3r+mnwY+KjY3F19eX4OBg6tSpY2rftGkTgwcPZvfu3eTIkbIabceOHYwfP57g4GCaNWuWYbmgR2Ps3LkzQUFBREVFUbt2bcaOHYujo2OaY/z8/Ni/f79Z25kzZ9Ls++uvv9K/f382b96Mi4tLunE8TgPLNk89VkRE/v8KG+Sb3SFkyHP68ewOIUP3KxXP7hAyZB3x9DX4s0LyH2ezO4QMWTr8u2utX+1ZMbtDyNDx/tOzO4QMNfLI5M67IiKSpTYZnr7k4P+xd9/xNZ59HMc/J1sGkUmMxIy9R6lVo2rErFWjNkVtNUtpK8QqsakqOh5aYpQqVW2NoFS1VrXUCkISicTIOOf5I3U4TUISI7Tf9+t1Xk/u676u6/7dx6lHfvd1fteT4jdvxlO/5l/9hz31az4JKr8j8oyYMWMGS5YsoV+/fmzevJnp06fj4eFhPj9r1ix69OhBSEgIfn5+DBs2jMTExDTnO3fuHFu3bmXu3LmEhISY29etW4e1tTVr1qxh7NixLF++nDVrUv+L3dnZmTp16rBp0yaL9o0bN1K/fn1zQv/atWu8/fbbBAUFPfAbA6nF+O2337Jw4UIWLVrEgQMHWLJkSZr9g4ODyZUrFwMHDmTXrl3s2rUrzb47duygVKlSLF26lJo1a9KwYUOmTp3K7du30x2fiIiIiIiIiIjIs0bld0SeAbGxsaxYsYLx81OV5QABAABJREFU48fTsmVLAPLnz0+lSpW4cCG5EGb37t2pU6cOAAMHDqRJkyacPXuWQoUKpTpnQkICQUFBuLm5WbTnzp2bMWPGYDAYKFiwIL///jvLly+nbdu2qc7TrFkzRowYwa1bt8iWLRuxsbHs3LmTuXPnAslfER81ahTt27endOnS5njTw2QyERgYaF6Z36xZM/bu3cuQIUNS7e/q6oq1tTVOTk54enqm2ueu8+fPc/DgQezt7Zk3bx5RUVFMnDiR69evExgY+MCxIiIiIiIiIiLyZBlUPybTtFJf5Blw+vRp4uPjeeGFF9Ls4+/vb/75bkI7MjIyzf4+Pj4pEvoAZcuWtSi1U65cOc6ePUtSUhILFy6kfPny5ldYWBi1atXC1taWHTt2ALB161acnZ2pXj25rMDKlSuJi4ujT58+Ka511/1zjh9/ryBnnjx5LErteHl5ERGRvAHchg0bLMbdLS2U3vlNJhMGg4Hp06dTpkwZateuzahRo1i3bp1W64uIiIiIiIiIyHNLK/VFngH29vYP7WNra2v++W5S/kGbvt4tjZMR7du3p1GjRuZjLy8vbGxsaNiwIRs3bqRJkyZs2rSJxo0bY2OT/NdHaGgohw8fpnTp0hZztW7dmoCAAKZOnWpR/uf+JP7dOe53d5uPunXrUrbsvXqc3t7eacad2vyenp54e3vj4uJiPleoUCFMJhOXL1/Gz8/vAe+EiIiIiIiIiIg8UVqpn2lK6os8A/z8/HBwcCA0NJR8+fI90WsdOWK5Md4vv/yCr68v1tbWuLq6prqpbEBAAN27d+fUqVOEhoYyePBg87lx48ZZHIeHh9OjRw9mzZplTsr7+vpmOE5nZ+dUN8y1tbVN8TAjtfkrVKjA119/TVxcHE5OTgCcOXMGKysrcuXKleF4REREREREREREngVK6os8A+zt7enVqxfTpk3D1taWChUqEBkZyalTp6hWrdpjvVZYWBiBgYG0a9eOY8eOsWrVKkaOHPnAMZUrV8bDw4Phw4eTN29eixX0Pj4+Fn0dHR2B5D0BnkTyPE+ePBw4cIAmTZpga2ubaokhgKZNmzJ//nxGjx7NwIEDiYqKYtq0abRu3TpDm/mKiIg8bjmy2TOm+UvUKV4Qo8nEtt/+YMqGndyMT0hzTD63HAxvUosKfj7Y2Viz6/ezTF7/HRGxN1P0tbW25vMB7Snm40XrD1Zx4tJV87mGZYrS+6XK+E3oR/S1G2xc/C1fzPnaYrxzTif6TetI1VfKYTKa2L3hJxaM/JTbcXfSjC93AU96vteOktWKYmtnw8HtvzJ/xCdcvxqT7nnzFs7Fmx90IX8xH5xyOBERcYMd24+xYvmPJCXde6D/WqfqVK1WmEKFvUlMSKJF05kPf9PvM2joKwQ0r8D84G2s/eIAAN65ctCpy4uUq+CHm5sTEddi2b7tNz5duZvExORr583nxuBhjfD19cDJyY6IqzfYufkXVi3YQVLivfics2ej35imVK1dLPk+tx9lwZSvuH0rPs2Ycro703PYK5SvVhhHR3su/HWNz5bsZPf2o+Y+hYv70H1IQ4qWzIPRaGLX9qMsDtpsMe8bo5pQorwvvoW8OH/8In0rjEhxLZeczvSf050XAipiMpr4ce0+5g/6iNtxaZcnzOntSu+gzlRoUIZsLg5cOBnGp5PXsmvtvnvxlS9Azymd8K9cCGOSkR/X7mPh0I9TzPvy63VoPawZeQt7c/PGbX5Yt595Q1feF58T/aZ3omqj8piMRnat/4kFb33ywM9fTq8c9Hy/HRXqlsTRORvnT13i82kb2bX+XvnGwmV96fFuW4pWKIAxycSuDT+xaNS9z1/BUvloO6wppaoVwcU7B2GR0ZyPjCZHNgf8fTxJSEqi+oQFacaQw9GBLwd3IperC9XGz+fG7dTj9cmZnb71qlKlcD48XJy4GhPLpkMnWLRjH4l/f879PHMyvlU9Cnm54exgT3hMHJsPn2DBtlAS7y5uydaWRSth548nOHHid2xtrdi/tTAk3FvAs24LjJliSC0MdoWYcM+Z+r1cj4H3Z8N3e8DKChrUgjFvglPyP/OZ+xHMW55y3mwOJg5tTf451iWSyFz/2GvLaCD/n6VTjBMREZGMU019kWdEv3796NatG3PmzKFx48YMGTLkgTXzM6tFixbcvn2bNm3aMGnSJLp06UK7du0eOMZgMNCkSRNOnDhBQEDAY48pIwYOHMjFixepX7/+Ax94ODk5sWzZMm7cuEHr1q0ZPnw4L730EuPGjXuK0YqIyH/VR71fpUXFEqmem9qhEYW93em5dC39l6+nUoE8vNOqfppzZbO1YXHPVpgw0X3JF3Ra8D9sra2Y17U5hlTydcMa1yQ8Ji5Few1/P6a2f4X/hf7KX0cvsHvjQVr2f5mA3vUs+o1c2hvfYnkY02I6E9p+QKkX/Rk0p2ua8dk72vF+yHAwwaimQQx7eTI2djZMXD3IYh+fh82bmJjE9s/2MKbFDP744wp7d5+icdNyvN69psX1bGyt+WHncTauP5RmTGl5sWZRipfIw7WrNyza8+d3x2Bl4IPpW+j5+hIWzN1OQLMKdO9Vx9wnKdHItq2/MnL4Z/x54hL7dh7nldaV6dzvH+/f1Lb4FvJmTO+PmDBgJaUq+jHonRYPjGv45FfJ6+fJO2+uom/rOez+9ihjprenULHcALh5uhC4pBth5yIY3HEh4/oux7eQF8Pea51irm/WHSQ2Kg4Xt5TfeAQYtWogfiXzMerldxkXMIUyNYszZFHaeyMBjPx4AHn9fRjffCq9ywxj17p9jPvfUAqV8wPAPXdOpm4bT9ifl3nzhTGMbvQ+fiXyMuKj/hbztB7SlG7vdcDGxooV761jVNMgDm7/zfJaH/bFt3geRjcLYnybWZR+0Z/Bwd0eGN+IJb3JVyQ377SdTZ+qY9m94SBjVvSnUJn8ye9fLlembHyLsNPhDHppEmNbTse3WB6GL+pF0JZRNOhYg8Ll/bh+NYapPRfRYsYKFu/YT/Wivly9Ecf/Qo888PoAk15twO+Xrz20XwHPnBgMBiZ9uZ0WM1YwdeP3tH2hNINfedHcJzHJyIaDx+i9dC2V673CoPen82qVUvR/+d6/fQ12VYi/dZyGNa/Qvrk9mEwYci4Dq3slKxvVhR/WmixeNaqYqFwu7YQ+wFvvwh9/wYczYEEg/PQLTJh+73y3dinnLeRnomEdy3kMSVbkOV383uuvYg99f0RERCR9tFJf5BlhZWXFG2+8wRtvvJHi3MmTJy2Os2fPbtHWqlUrWrVqZT5+8803efPNN1O9jo2NDWPHjmXixIkZim/EiBGMGJFytdc/5c2bN0W8qUktxq5du9K1a9cHjitXrhwbNmx46PyQXEP/o48+SldfERGRp6Gglxs1/QvQds6nHL14BYDJ679jQbeWTPvqB67eSJmML+/nQ56c2Xl19ifE3UlelT1m9Vb2TuhH1UL5Cf3jnLlvDX8/qhfNz5CVm6hVrIDFPM3KF2fH0T9Zve8ILT3zcObX81z+6yptBzdm4+JvAchXNDeVG5ThzdoTOfXzXwDMH7GKd78YwpKx/yPy8vUU8ZV8oQje+T0YUGMCN28kr8qe3ncpX5ybS7naxfl557F0zXv5r6tc/iv5WwUJ8Yn88ccVjCYTpf9OzN614qMfAXj5lYyt+HX3cGbAwJcZNeJz3p/S1uLcgf2nObD/tPn40qXrrPlfKAHNK7B4wQ5z26VL183x/XniEkajiVIV/Mzj8hXwpHKNorzZbj6njl1Mvs/ATbw7vwtLpm8h8h8PE+4qUS4/c9/dwO+/Ja9s/mzxTlp2fpEiJfLw54lLVK1djMREI/Pe32jefyj43fUsXDuQ3PncuHQ+eSHIgilfAdC64wtYWaVcv5W/WB6qNCpP/8oj+f1g8v3OHbiM978azeIRK4i4FJV6fNX9mdNvCScP/AHAp++vpfXgphStWJA/D/9F1aYVSUpIJLj/UnN8H7yxhCVHZuBTKBdhf17G2dWJru+2Z3yzKXSc0JbrV2M4c/Q8Z46ev/f++eem8stlGFBzwr3PyfBVvLt2KIvHfJ7q5w+gRNXCBA/+mJN/39NnQRto1b8hRcoX4M8j56jaqByJiUnMHbLCHN+cwctZtO99Thz4E4BvVv5onu9imWxciIymrG9uCnq5sfPYg5P17V4oQ/Zs9izYvi/Ff3f/tPv3s+z+/az5+EJkNMs9D9L2hbJM/+pHc9uFyGgAEhMTOREWzqafT1ChQB7zOFP0cN7snPzzui0ABsAK7KrB7RAAHOyTX3dFXod9h+Ddt9KO78+/4Mf9BtYsMlHq7xz8uEHQZyS81Q+8PJJX7N9dtQ9w4g/48y8D7wxNWRjZOsk2RZuIiMhdBtXUz7RHWqm/Z88eevXqxQsvvEDJkiUpXrx4ileJEqmvUBIRERER+a8pmz830TdvmxP6AHv/OIfRZKJM/tTL1tnZ2GAyQXxikrntTkISRpOJCn73yuC5OzsysXV9Rn++lVsJianMY82d++YAiL+VgGdeN7zzuwNQvEphbkTFmROqAD9/dwyT0USxSgVTjc/WzgZMJhLu3Ltmwu0ETEYTJasVyfS8rjmdqFylEEcOn0v1fEYYDDBqbDNWf76Ps389fDU1gJOTAzExaZekyeHmTMUXi/LrwTPmtuJl83Mj5pY5oQ/wc+ifyfdZOu19k44dPketV0rjnD0bBoOB2q+Uxs7Ohl8OJCepbe2sSUxINCekAe7cTi7XVKpC+vcuKl6tKDeiYs0JfYBD248kx1e1SNrx7TlJ7bbVccnpjMFgoE676tg62PLLzmPJ8dnbkBBvGV/832WBStVIzgxXaFAGKysD7nnc8K9YkN5TOjB2RX8889wrpZja5+TQd0eT46tcKO349v1B7dZVccnplPz+vVoVOwdbjvx43BxfYhrxOWXPlua8Lg72RN9Mu+wPJD+o61v/BUb/b6vF/Bnh7GBPzK20P2tuzo7U8Pfjp9MX0uwDgMEGTNfTPL1+Kzg4kGJF/f0OH4XszvcS+gDVKiaX4fnlWOpjvtgEfvlMVCpr2W6yMnLR7zgX/Y5zNfdfxNulfY8iIiKSMZleqb9161aGDBmC0WjEx8eHggULYm1t/ThjExERERF5LnQY3ZIOo+99a87O0Y6y+XMztvlL5rZmM1fg4eJIZJxlHfwko4noW7fxcHFKde5fzl3iVkICwxrX4IOvd2MAhjSqgY21FZ7Z7415v+3LrA49wtGLV/DJmd1ijl4vVaZ28QLYWlvzcuki2FpZUbxKIaxtk//9vvjAZHpWHE1O7+xEX4uxGGtMMnIjKo6c3jlSje/EgdPcjrtD90ltWD7xSzBA94ltsLaxxs3bFeCh87Yb1oT2w5oCYJ/NDoOVgbLlfUlMTKJVm8q0erUyPV5fTHh4zD8vny7tX6tGUpKRdV8eSFd/nzw5adGqIov+XqXfoVN1XutYHQA7exusrAyUqVyQxMQkWnSqTotO1endfDY5PZyJjohNeZ/Rt8jpkXo5HIDJwz9nzLT2fLF7HIkJSdy5ncCkwZ+YV+D/su80vYc35tWuNQhZtRcHR1u6D24IgJuHC+161qZ9r9rm+ewdbAEDG2Lu1arvUXIIbrlcuR6e8s8hJjKWnLlc04zv3XYzGff5ENZGfERiQiJ3bsYzsdU0wv68DMDhHb/Rd8brtBnejHWzN+PgZE+PwI7J8eV2pcPolnQe3wYbO5vkkjwmsLax5sVmFanRohJ3bsbTq9Jo3LxzWOzDYH7/ouJwS+PzB/B+l3mM+bgfX5yffy++DnMIOx2e/P59f5w+gR14dVAj7BxsaTu0CXb2ySvI8xTJzcDZr9N/RmfzfAFzVpErhzMNyxal/7IQPLOn/mdna23NtNcaM+OrH7h8/Qb53NKOMS353HPwWvVyTP/qBwCSfj+E8ffk0lL2tjYY4uOJ3redFg2+NT/YC+sIPt7/nMkeksLhzp40r/XlV9CknuXq/X+6Fglu/yjNY2MDOVySz/3TnTuwaTv0fM2y3TbBHrcr+bC744DROokY16tcyfsHuc8VxSbRLu0ARETkv8WU+t4v8nCZTurPmzcPe3t75s+f/9g38hSRJ2PlypUP7yQiIiIZtmnhNr5fvdd8POzbMWz77Q+2/3bK3BYeE5va0IeKirvF0FWbeLtlPTpWL4/RZGLzLyc5euEKRmPyyuCO1cvhZGfHku9ST1qvDj3C1iO/0612JZpXKIGVlYHEJCNfLdtJizcaENRrMRF/l5bJqOiIG7z/+nwGzOpC8771MRlN7PxiH6d+/guj0fjwCYCvlu3kh3XJsbt556D//J6cORNOufK+bNv6G5s3HeZaROqlax6mSNFctGxdmTd6LUtXf3cPZwKD2vH9zhNs3nQYgE3rD/H9d8mrvt3cnBg08GX+OnWFMlUL8u2Gn9nyxQEi0iitkx5dBtTHycWBUT0/JDrqJtXrlmDM9PYM77qEv05d4eyf4Uwf9wW9RzSm26CXSTKa2PDJXiKv3cBoMrFlzQF+2Pqreb6gxV2xsjIwtPYEc1tEWOb3aur6bnucXJ14q/5Eoq/doHqLyoz731CG1BrPX7+d4+yxCwR1nUffGa/TY/JrJCUZCQneQuTl65iMJr5ash0XN2faDGvG9O7zCOjXiF3rf+KXH4/zwY7xzBu2MtOfP4DX326Fcw5HRjadSsy1G1QLqMjYFf0Y1nAyfx29wNnjF5neewm9p3Qgh7sLSUlGtq78keoBFYi/lcCGRdvZveHeprrZu5ZhzuvNWLAtlD2nztE8jf0xBjd6kdPhkWz6+USm4vbK7sSiHq345tff+XJ/8t4CVn4lsPJJ/lZCThdHru/eQoGyFRjXtwcbDh7jy/2/4eX+qeVE9nXAcBDT9f5A6hsy//wb/HnWwNSxj7fOwfYfIe4mtHjlHyHddsL+9r2Hjva3nLjke5LY7JG4Rqb+rSQRERFJv0wn9c+cOUPz5s2V0BcRERGR/7wbUbHciLqXtL+dkEhk7E3ORURb9Lt24yZu9xejBqytDOTI5sC1VOrp37Xn1DkaBX2Eq6MDSUYTN27f4ftxvdnyS/L8VQvno6xvbn5+f6DFuP+9+RpfHT7BmNVbib51h4lrv+XddTv4X8umbF35AxGXrtPijQb8tvt3jElGoq7EkMPDcpW/lbUVLjmdiLpieS/3O7TjKN3LjiS7mzNJSUnERd/i01MfcPnL5Br5D5s3NiqO2Kjk+790OpwbMbc4eOAM+0P/ZMjwxixbstP8ACOjSpfJh2tOJz5dPcDcZm1jRZ9+9Wj1amU6tZ9vbnd3d2bGBx05dvQis6ZvNrffuHGbG3/vFxB2MYob0Tc5tPcUB3adZOD4Fiyf/Q1Go4moa7HkcLdc1W1lbYVLjmxEXUv9oU7uvG40f60afVrM5uyfySvLz/x+mVIVfQlo/wLB764HYOfmI+zcfARXdydu30zAhImWXV7k8oUoYmNuERtzyzxnUmISJisr80r6uyIvX8fVK+WfQ3Y3Z6LSqFefu6A3LQY0omepIZw9llz+5fSRs5SuUZzm/Rsy+40lAHz32S6++2wXrl45uB13B0wmWg9pyqXTV7gRFcvZv2vnH9r+Ky93r8f1qzH8fvAMMRE3sLG1xphkJPJKNK6eqX9OItP4/OUu4EXzvg3oXXkMZ48nlz06/dt5SlcvSrPe9Zgz6OPk+NaE8t2aUFy9snM77g4mk4mGXWpx4eolrl+NMa/qz1/MhyW9WvHFvl9ZvGN/qte8q2rhfBTJ5UGD0oMAzBtX/zihL0t27Gfetr1pjvXM7sSyPm04fDaMd77cbm432DmAnQMAESZINJr4PSKWL347y4TXmhNy/AI29/8W79gd7POB6UdITHtfqy++guKFTZT0f+At4eEGkf/YWiExEaJvJJ9Lbd7a1VI/dz8DBmzvZCPR7sHljERERCR9Mp3Ud3V1xcHB4XHGIiIiIiLyr/bLuUvkcHSgRB4vjl1MTiJWLZQPK4OBI+cuP2Q0XL952zzGzcmR744l10YP3LCTOVvvld3wyu7Ekp6tGf7pVxw5bzmv0WQiMT4RY6KROq9W5di+P4j+exX88f1/4JLTicLlfPnjcPJmnuVqF8dgZeDET6d5mJjI5MR12VrFcfV0IXTz4Uea18rKgI2NFQaDAchcUn/7N79x6OBfFm1TprVn+ze/8vWWI+Y2d4/khP7vv19m2pRNpKc8usFgwMbGGoOVAYwmjv9yDpfs2Shcwoc/joUBUK5KweT7/PV8qnPYZ0suA/PPhxbGJFPyvP9wPSL54cfLLSqScCeRQ3v/eHigfzu+93dccjpTpEJBTh1Kft/L1y2VHN++U6mOsXdMrtViShGfEUMqm/FeD09Ovjfs9hLxt+M5uC35Pf5td3LCOZ//vX0gXHI6kd3dhSvnIpLjM39O/Pjj8F8AlKtdIjm+vze0TRlfcimXf34rJCnN+JLL+7zcuSYJtxO4EXXvYZpv8TxM/Wok6w4et/jvKS1DVmzC3vber9Sl8nnzXtuGvL5gNecjrqc5zuvvhP6xi1cYt/qbdH3WrAwGbKytsDLc95lw6onB6Q2IawEkpTWUuJvw9XcwtPfDr1OuJMTEGjh68t4DgH0/g9EIZf/xhYULl5LPzZv88HlNmEiwv022OJeHdxYRkf8ObZSbaZneKLdhw4bs3buXxMSUm3CJiIiIiPyXODg5kNPb1fwa8elmdp38Cw9nR/PLymDgdHgkP548w8TW9Smd15vyvj6MbV6XLb+c5OrfK/W9sjuxcdjrlM57r2h2i0olKJM/F/ncctC0fDFmdmzCil2H+Ota8pLaS9dv8MeVCPPrr2vXATgfEc2V6Fgc7Wwp6JmTbrUqUd7Xh0+DNlDihSLUbFGZT6auJ6dXdqysDJz//RIHth1h8JxuFK1YgBJVC9Nveie+/3I/kX+v5HbP7cqSnyZTtGIBc3wNOtagWOWC5C7gSd121Ri7oh/r5n3DhT+SHyg8bF4HJ3ua9nyJV7rWomS1IixZuAMbW2t69q7Lnl2nyJ4jG1Z/J7i9vLJTqLAXXt45sLI2UKiwF4UKe+Hwd3IcYNmKPrxYsygAMTG3+OvMVYtXYmISkZFxXPi7Zr27hzMzZnci/EoMi+Z/Sw5XR3K6OZHTLbl8iEM2WwKaV6BxQDlKlcnLh7O+xtrWmu5DXiF053Gy53BMfv/OXOXArt8ZPKElRUvlpUS5/PQbE8D3X/9K5N/ledy9srNkw2CKlsqb/N6cucrFs9cYOKE5RUvlJXdeN1p1eZHy1Qqxd8e9nUkDOrxA4eI+5PF1J6B9VfqNacpHs78h7sZtHLLZkdPdGf8yeSlXtRC//nCMhPhEytctTfm6pfHM646VlRXnTlxk/5afGbK4D/6VC1Oyuj8Dgnuw8/M9RFxK/iy5+7jx4bEP8K9cODm+Exe5eOoSgxb2xr9yYXIX9ObVoU2p0KAMe0LurWRv3v8VCpcvQJ4iuWnWryEDgnuwbMynxEXfxMHJgZsxt9i/5WcGzO3Bl7O3cPncVUZ/9AZhf17h3ImLye/fyUsc+OYIg+d2w79iQUq8UIT+Mzrz/Rf77vv85WTpoUD8KyZvsHz+5CUu/nGZQXOSx+Qu4EXrN1+hQt2S7Nl40Bxfsz71KVzWl4Kl89FuWBP6z+jMZzM28l6nufy07VdK1/Rn2pbR/Lr7JCt/PIS7syPFfbyoXDAvuXO6YG1lhX9uT/xze5LNLvmzdj4y2uK/u4uRyQ8MTodHEhmX/M2JUvm82TD8dbz+3v/CK7sTH/Vtw6XrN5i+6QdyOmXD3dkRd+fkb/CYEhOoV9iH2gVzkd/Zjrz1W/FSnTp0qlyMNd/vI+FmLElJgFMvLsW049iBAYRdiiApycDxP105/ocD/9i2gy3fQVISBDQghSPHoXFnuJL8pRoK+UHNKibenpZ87tCv8O4H0LgueHlYjv1yM3i6Q62qKeeNdrvCLccbJNrcId7+JhG5zpFkE49zzEOW9IuIiEi6ZHql/tChQ+nevTtDhgxh9OjR+Pj4PHyQiIiIiMi/UJvhAXSZ0PaBfRpM+ZCwqBhGfraFsc3r8mHvVzGaTGz79RSBG3aa+9lYW1PQyw0Hu3tJ6gIebgx5pQY5sjlwMSqGxd/t5+MfD6U7vq61KtK/wX1lM/vd+/H9tcMAeL3UcK6ci2Bqz8X0n96JKRtGYDKa2LXhIAve+uRefLbW5CuaG4ds9za7zFskF93eeRWXnE5cOXeNz6dtZO28byxieNC8rw58hU6jW6Qae606xahVpxgd283jyuVoXu9ei4aNypjPL/qwJwDDBq3il8PnAMjv646T0wN2A/2HipUKkDevG3nzuvG/Ly1LGNWvPZm27V6gS7eaqY6t0aAUNRqU4vWG07gSdp2pI1fTf2wAU5Z2T77P7UdZELjJ3N/Gxop8BTxxcEj+801KNPJ2vxV0H/wyE+d2Jls2O8LORzBj7Jcc+PF38zj/Unnp3K8eDo52XDhzleBJ6/n275r/r3atQad+9VLEFrR9vPnnTgX6ceXsVaZ0msOA4B4EbR+PyWjix7WhzBv40b34bK3JXyyPeQV8UmISY5tMpkdgR97dMBIHZwfC/rjMtK7z2L/l53vxVS5Ml3fa4uDswPkTF5nddzHbVyVv/vrP/z4mfTHUIs5Pfv+ALiWGceXcNab2WEj/GZ2Zsumt5Pdv/U/MH7HKIr58RX0s4hvXeiY9JrVh4prBZHNyIOz0Fab3XsKBb+59E8O/YkE6j2mJU45sWNskbxDdbfyrdBv/qkUstVpW4buWVVL+QQNfDumUPG7hGg6cvpBqn3/KZmtLQS83bKyTr1mtiC++Hjnx9cjJjnGWS+dLvTUL4x+H+fqrDy3azwPbZ907vtwN8ubqQPD7c1m3LtTc3qp78rckPv4AqpS/L+6voEEtyJ7KIvnbt+HMOQOJifeWSga9De99AN2GgJUVvFwLxlj+Z4HRCCFboOUr8PetWZ63SiLS6wJJ1olYGa2xu5MN7wuFsY3Xt/1FROQ+WqmfaQaTKT1f9kupXr16JCYmEh6e/LXh7Nmz4+zsnKKfwWBg+/btKdpFRJ4HDazaZHUIIiLyHAobUT2rQ3igfAuOPLxTFkosXySrQ3ggm8i09z94FiQd/f3hnbKQlaPjwztloYv9ymV1CA90ZOiCrA7hgRr6lM3qEEREJBXbjGuyOoQUCs6a+dSveXrI0Id3eg5keqW+yWTC2tqa3LlzW7Sl1k9ERERERERERERE5C6D0saZlumk/o4dOx5nHCIiIiIiIiIiIiIi8hCZTuqLiIiIiIiIiIiIiGSKVupnmlVWByAiIiIiIiIiIiIiIumT7pX6c+fOxWAw0LFjR1xdXZk7d266xhkMBvr375/pAEVERERERERERETkX0Yr9TMtw0n9xo0bK6kvIiIiIiIiIiIiIpIF0p3UX7FiBQA+Pj4WxyIiIiIiT5uVnV1Wh/BAPtP2ZHUID5SU1QE8hOHHn7M6hAd61t+/Z53x5s2sDuGBck9/tv/7bTi9bFaHICIiIlks3Un9KlWqMGfOHAwGA2XLlqVKlSpPMi4RERERERERERER+ZcyqPxOpmVoo9z58+fTpUsXKleuTNeuXZk/fz4HDx4kMTHxScUnIiIiIiIiIiIiIvJUHThwgL59+1KjRg38/f3Zvn27xXmTycTs2bOpUaMGZcqUoWvXrvz1118PnfeTTz6hbt26lC5dmjZt2nDkyJEMx5ahpP6oUaN46aWXcHBwIDQ0lDlz5tCpUycqV65Mjx49WLx4MUeOHMFoNGY4EBERERERERERERH5jzAZnv4rA27evIm/vz8TJkxI9fySJUtYuXIl77zzDqtXryZbtmz06NGDO3fupDnn5s2bCQwMpH///qxbt45ixYrRo0cPIiIiMhSbwWQyZfiLDiaTiRMnTrBv3z5CQ0M5dOgQMTExyRMaDDg6OlKpUiWqVq1K1apVKVmyZEYvISLyTGhg1SarQxARkVQ86zX1jfHxWR2CiIiIiIjZNuOarA4hhcJBs576Nf94a0imxvn7+zNv3jzq168PJOfHa9asSbdu3ejRowcAN27coHr16kyZMoUmTZqkOk+bNm0oXbo048ePB8BoNFK7dm06d+5M79690x1Pumvq389gMFC8eHGKFy9O165dMZlMHD9+nNDQUPbv38/Bgwf5/vvv+eGHHzAYDBw7diwzlxERERERERERERGRf6MsqKkfHx9P/D8W4NjZ2WGXwUVDFy5c4OrVq1SvXt3c5uLiQtmyZfn5559TTerHx8dz9OhR+vTpY26zsrKievXq/Pzzzxm6fqaS+v9kMBgoUaIEJUqU4JVXXmH37t2sWLGCU6dOPY7pRUREREREREREREQeyaJFi5g7d65F24ABA3jzzTczNM/Vq1cBcHd3t2h3d3fn2rVrqY6JiooiKSkp1TGnT5/O0PUfOal/5coV9u3bZ35dvHgRAEdHR2rWrEnlypUf9RIiIiIiIqkqUCofA2Z3pWjFgkRfu8H6+d+wZuamdI11cXNmwf5APPO60cq7F3HRNwFwy+VK76kdKVKhAD6FvFk/bysLR6xKMd4phyNdJ7blxeaVcHFzJvzcNRYOX8mBrb881nsUEREREfk3MmTBSv0+ffrQrVs3i7aMrtJ/FmQ4qR8REWGupb9v3z7OnTuHyWTCxcWFihUr8tprr1G5cmVKliyJlVWG9uEVEREREUk3R5dsTN40ip+/+405A5bhVyofQxf1JjY6ji0ffvfQ8UMX9uLMb+fwzOtm0W5rb8P1qzF8NiWElm82SnWsja01gV+N4vrVGN57bQ4RYZF45fcg7vrNx3JvIiIiIiLy+GWm1E5qPD09geRcuZeXl7k9IiKCYsWKpTomZ86cWFtbp9gUNyIiAg8PjwxdP0NJ/caNG3PmzBkAsmfPTqVKlejQoQNVqlShePHiGAwZ20FYRERERCSz6ravjq2dDTN7LyYxIYmzxy9SqIwvrQc2fmhSv2mveji5OvLJ5HVUeaWcxbkrZ5NX3AO8/HrtVMc3fL0OLm7ODKkzkaTEJPM4ERERERH598ubNy+enp7s3buX4sWLAxAbG8svv/xChw4dUh1jZ2dHyZIl2bt3r3nDXaPRyN69e+nUqVOGrp+hpP7p06exsrKifv36dOnShbJly2Jra5uhC4qIiIiIPA7FXyjCr7tOkJiQZG47uP1X2o1ohrOrI7FprJrPXywPr41pyaBaE8hdwCvVPg/zQtMKHN93igGzu1KtaUWir8Xw3f/2sHr6RozGLPgesYiIiIjI8+YZ/2dzXFwc586dMx9fuHCB48ePkyNHDnx8fOjSpQsLFizA19eXvHnzMnv2bLy8vMwJe4DXX3+dBg0amJP23bp1Y+TIkZQqVYoyZcrw8ccfc+vWLVq1apWh2DKU1O/cuTP79+9n27ZtbNu2DQcHB8qWLUuVKlWoUqWKkvwiIiIi8tTk9Hbl8l/hFm1RV6LN51JL6tva2TB6RX+WjvmMq+cjMp3Uz13Ai3J1SrDj8z2MaxFEnkK5GDC7K9a2Nnzy/tpMzSkiIiIiIs+O3377jS5dupiPAwMDAWjZsiVTpkyhV69e3Lp1i/HjxxMTE0PFihVZunQp9vb25jHnz58nKirKfNy4cWMiIyOZM2cOV69epXjx4ixduvTJlt8ZO3YsANevX2f//v3s27eP/fv3ExwcDIC9vb05yV+1alUl+UVERETkmdLt3XacOxHGjs92P9I8BisD16/GMLvfUoxGE3/8/BfuPjl5dUgTJfVFRERERNIhKzbKzYiqVaty8uTJNM8bDAYGDRrEoEGD0uyzY8eOFG2dOnXKcLmdf8rwRrkArq6uvPzyy7z88ssAREZGmhP8d5P8c+fOxd7ennLlyrF8+fJHClJERERE5J+irlwnp1cOi7ac3jnM51JTrk5J/Erlo2arKskNf+8JtebiQj6bup6V736ZrmtHXr5OUkKSRamdcyfCcM+dExtba+LjM3gzIiIiIiIi6WT1OCZxc3OjUaNGTJgwgZCQEGbPnk3hwoW5ffs2+/btexyXEOHChQv4+/tz/PjxNPusXbuWSpUqPcWoHl1wcDDNmzfP6jBERESeO8dDT1G6RjGsbazNbRXqleL8ybA06+m/2+ED3qg8mjeqjOGNKmP44I0lAAyrN4kNC7el+9rH9v5O7kLeGP5+KACQt0guIsKiLGr8i4iIiIhIGkxZ8PqXeOSkflJSEj///DMLFy6ke/fuVKlShcGDB3Pq1CkAcubM+chBiqRX48aN2bp1a1aHQXx8PM2bN3/oQ4hHUbdu3XR/CyY+Pp5Zs2bx0ksvUapUKerWrcsXX3zxyDFk1QOJU6dO8eabb1K3bl38/f3TfB8++eQT6tatS+nSpWnTpg1Hjhx5uoGKiMgTteN/e0iIT2Tool74Fs9D7VdfoEX/hnw5Z7O5T/VmlVj6yzTz8aXT4Zw9dsH8uvzXVSB5lX301Rhzv4JlfClYxpdsTg7k8MxOwTK+5C+Wx3x+0+LtuOR05o0ZnclTOBdVXilH+7eas3FR+h8MiIiIiIiIZEaGy+8YjUZ+/fVX9u3bx759+/j555+5desWJlPyo44cOXLw4osvUrVqVapWrUrRokUfe9AiaXFwcMDBwSHN8/Hx8djZ2T3xOIKCgvDy8uLEiRNP/FrpMWjQICIiInj//ffJnz8/V69exWg0ZnVYmXbr1i3y5s3LK6+8Yt6k5J82b95MYGAgEydOpGzZsnz88cf06NGDr7/+Gnd396ccsYiIPAk3Y24xpukUBszuyty97xF9LZZPJq9jy4ffmfs45XAkn79PhudesH+y+eeiFQtSt/2LXD57ldf9BwNw9UIkYwOm0CeoMwt/CuRaWBQh875m9fSNj3xfIiIiIiL/Cf+ilfNPm8F0NxufDr169eLQoUPcvHnTnMR3cXGhUqVK5iR+sWLFLL6GLJJRRqORDz/8kNWrV3Pp0iU8PDxo164dAQEB1KtXj+DgYFauXMmRI0fw9fVl4sSJlC9fHkguvzN58mR++uknIHkl+fbt2+nUqRMLFiwgLCyMEydO0LlzZ4oUKQLA+vXrsbGxoUOHDgwaNCjVz29sbCzVq1cnODiY2rVrm9u3bdvGW2+9xZ49e8iWLRsA33//PVOmTCE4OJgmTZoQEhJC8eLF07zfuzF269aNOXPmEB0dTa1atXj33XdxdnZOdUznzp3Zv3+/RVtaG3f88MMPDB06lO3bt+Pq6ppmHGnZt28f06ZN448//sDGxobChQszY8YM9u3bx+jRoy36BgYG0qpVK2JiYpg6dSrffvst8fHxlCpVijFjxlCsWDGLe+7QoQMLFizg+vXr1KlTh/feew8XF5cMxVe3bl26dOlC165dLdrbtGlD6dKlGT9+PJD8uapduzadO3emd+/e6Z6/gVWbDMUjIiJPh9VTeEj/KIwqqi8iIiIiz5BtxjVZHUIKRd+b9dSv+fu4IU/9mk9Chlbq//jjjzg6OlKzZk1zEr9EiRJYWT2W0vwiAMyYMYM1a9YwevRoKlasSHh4OGfOnDGfnzVrFiNHjsTX15dZs2YxbNgwvvnmG2xsUv84nzt3jq1btzJ37lyLz+q6det49dVXWbNmDb/99hvjx4/Hx8eHtm3bppjD2dmZOnXqsGnTJouk/saNG6lfv745oX/t2jXefvtt5s2b98BvDKQW47fffsvChQuJiYlh8ODBLFmyhCFDUv+L5m7Zm7Zt26Ya7/127NhBqVKlWLp0KevXr8fR0ZG6desyaNCgh8aYmJhI//79adOmDTNnziQhIYEjR45gMBho3Lgxp06d4scff+Sjjz4CMCfkBw0ahL29PUuWLMHFxYX//e9/vP7662zdutX8YOHcuXNs2bKFhQsXEhsby9ixY3nnnXeYMWNGut+3tMTHx3P06FH69OljbrOysqJ69er8/PPPjzy/iIiIiIiIiIg8GoNW6mdahpL6//vf/yhVqhTW1tYP7yySCbGxsaxYsYLx48fTsmVLAPLnz0+lSpW4cOECAN27d6dOnToADBw4kCZNmnD27FkKFSqU6pwJCQkEBQXh5uZm0Z47d27GjBmDwWCgYMGC/P777yxfvjzNJHmzZs0YMWIEt27dIlu2bMTGxrJz507mzp0LgMlkYtSoUbRv357SpUub400Pk8lEYGCgeWV+s2bN2Lt3b5pJfVdXV6ytrXFycsLT0/OBc58/f56DBw9ib2/PvHnziIqKYuLEiVy/fj3N0jV3xcbGcuPGDV566SXy588PYPE+Ozo6Ym1tbRHDTz/9xJEjR9i7d6+51NHIkSPZvn07W7dupV27dgDcuXOHoKAgvL29ARg3bhx9+vRh1KhRD72nh4mKiiIpKSlFmR13d3dOnz79SHOLiIiIiIiIiIhkpQwtsS9btqwS+vJEnT59mvj4eF544YU0+/j7+5t/vpv8jYyMTLO/j49PioQ+JH+e7y+1U65cOc6ePUtSUhILFy6kfPny5ldYWBi1atXC1taWHTt2ALB161acnZ2pXr06ACtXriQuLs5idfg/3T/n3bIwAHny5LEotePl5UVERAQAGzZssBh3t7RQeuc3mUwYDAamT59OmTJlqF27NqNGjWLdunXcvn07zbkg+eFBq1at6NGjB3379uXjjz8mPDz8gWNOnjzJzZs3qVq1qkU8Fy5c4Ny5c+Z+uXPnNif078ZuNBotvpUhIiIiIiIiIiIiljK8Ua7Ik2Rvb//QPra2tuaf7yblH7Tp693SOBnRvn17GjVqZD728vLCxsaGhg0bsnHjRpo0acKmTZto3LixuexPaGgohw8fpnTp0hZztW7dmoCAAKZOnUpISIi5/f4kfmqlg+7uW1G3bl3Kli1rbr8/Ef5Pqc3v6emJt7e3Ra36QoUKYTKZuHz5Mn5+fg94J5Lr5Hfu3Jkff/yRLVu28MEHH/DRRx9Rrly5VPvHxcXh6enJypUrU5zLaL38zMqZMyfW1tbmByN3RURE4OHh8VRiEBEREREREREReRKU1Jdnip+fHw4ODoSGhpIvX74neq0jR45YHP/yyy/4+vpibW2Nq6trqpvKBgQE0L17d06dOkVoaCiDBw82nxs3bpzFcXh4OD169GDWrFnmpLyvr2+G43R2dk51w1xbW9sUDzNSm79ChQp8/fXXxMXF4eTkBMCZM2ewsrIiV65c6YqhRIkSlChRgj59+tCuXTs2bdpEuXLlUo2hZMmSXLt2DWtra/LmzZvmnJcuXeLKlSvmhxSHDx/GysqKAgUKpCumB7Gzs6NkyZLs3buX+vXrA8kPfvbu3UunTp0eeX4REREREREREZGsoqS+PFPs7e3p1asX06ZNw9bWlgoVKhAZGcmpU6eoVq3aY71WWFgYgYGBtGvXjmPHjrFq1SpGjhz5wDGVK1fGw8OD4cOHkzdvXosV9D4+PhZ9HR0dgeQ9AdKbPM+IPHnycODAAZo0aYKtrW2qJYYAmjZtyvz58xk9ejQDBw4kKiqKadOm0bp164dulHv+/HlWr15N3bp18fLy4syZM/z11180b97cHMOFCxc4fvw43t7e5nJE5cqVo3///owYMQI/Pz/Cw8P5/vvvqV+/vvmbDPb29owaNYqRI0cSGxvLe++9R6NGjdJVTz8+Pp4///zT/POVK1c4fvw4jo6O5gcb3bp1Y+TIkZQqVYoyZcrw8ccfc+vWLVq1apXu91hERJ5PLjmd6Dfrdao2roDJaGRXyAEWDFvB7bg7aY7JXdCLXoGvUbK6P7b2thz85hfmDf2Y6+Ex5j4dRjanyivlKFjWl8T4RFrn6m0xR8HS+Wk7IoBS1f3J7u7Clb/C2bRoG+vmbH5i9yoiIiIi8tzSRrmZpqS+PHP69euHtbU1c+bMITw8HE9PT9q3b//Yr9OiRQtu375NmzZtsLa2pkuXLuZNXNNiMBho0qQJS5cupX///o89powYOHAg48ePp379+sTHx3Py5MlU+zk5ObFs2TLee+89WrdujaurK40aNbL4VkFasmXLxunTp1m3bh3Xr1/Hy8uLjh07mv88GjZsyLZt2+jSpQsxMTEEBgbSqlUrFi9ezAcffMDo0aOJiorCw8ODSpUqWZS+yZ8/Pw0aNKBXr15ER0dTp04dJkyYkK57Dw8Pp0WLFubjZcuWsWzZMqpUqWIu+9O4cWMiIyOZM2cOV69epXjx4ixdulTld0RE/iWCvhnLtpU/sm3lDynOjVzeH7dcroxuEoiNrTXDFvdh8PyeTHl9Xqpz2TvaM3nTKE4fOcfIVyYD8PqEV5n05XAG1ZpgLolnY2fDD2v3cXzfHzTsWjvFPIUrFOB6eAxTu83nyunLlKzuz+BFfTAmGVk/7+vHePciIiIiIvJfZjDd/S1F5D+kc+fOFCtWjLFjx2Z1KP9JwcHBbN++nfXr12d1KA/VwKpNVocgIiKpmL5zYqpJ/Xz+Piz9ZRoDqo/j1KHkzdcrNSjDu+tH0LHQm0Reup5irgr1S/Pe+rd4NVdvbt64BYBj9mx8eXkxY5pO4ecdRy36N+hci77TOqVYqX8/Y3w8AG/O7UG+Ynl5q/7ER7ldEREREZFHss24JqtDSKHYxFlP/ZonJgx56td8EqyyOgARERERkcel+AtFuBEVZ07oAxza8Rsmo4lilQunOsbWzgZMJhLuJJjbEm4nYDKaKFnd/5HicczuyI3I2EeaQ0RERERE5H4qvyPyH1e+fPk0zy1ZsoRKlSo9xWiSPYsxiYhI1uowuiUdRt/bF8Uumx3FqxSm/6zXzW29yr+Fm3cOrl+NthhrTDJyIzIWN+8cqc59Yv8f3I67Q4/32/PR+NVgMNDjvXZY21jjlss10zGXqFaUOu2qM65pYKbnEBERERH511L9mExTUl/+k+7WXRcICQlJ85y3t/cTueabb77Jm2++meb5rIhJRESebZsWbuP71XvNx6M/GcSukAPsDjlgbosIi8rU3NHXbvBexzm8Oacbzfs3xGQ08d3qvZw6dAaTMXO/afiVzMfEkJGsnLSGg9uOZGoOERERERGR1CipL/If5+vrm9UhpPAsxiQiIlnrRlQsN6LulbG5czue61djCDt9xaJf5JVoXD0tV+RbWVvh4uZM5BXLFfz3O7T9V7qVGEp2d2eSEo3ERd/ks7/mcelMeIZjzV8sD0Fbx7B5yXY+fX9thseLiIiIiPwnaKV+pqmmvoiIiIj8axwPPYVLTicKl/czt5V7qSQGKwMnDvzx0PExEbHERd+kbJ0SuHplJ3TToQxd37d4HoK2juWbFd/z0bjPMhq+iIiIiIjIQ2mlvoiIiIg88xycHMjm7GA+Duw8F4Cc99XJj74aw/mTYRzY+guD5/ck+M1lWNva0H/W63y/JpTIS9cBcPfJydQtY5jWYwEnfzoNwMtdanHuRBjR12IoXrUIb0zvzLo5X3Ph1CXz/J753HHJ6YxXPnesrK0oWCb5m2Vhf17mdtwdfEvkJejrMfy0/Ve+nLmJnN6uQHJN/+hrMU/y7RERERERkf8QJfVFRERE5JnXZngAXSa0fWCfLv6DuHL2GlO7zqP/B12ZsmUMJqOJXSH7mT90hbmfja01+fx9sHe0N7flLZKbbpPa4eLmzJWzV/ls6nrWztliOf/4V3m5cy3z8YL9kwEY8fJ7HPnhODVbVcHVKwf1X6tB/ddqmPtd/iuczgX7P9L9i4iIiIj82xhUfifTDCaTSW+fiEgaGli1yeoQREQkFVZ2dlkdwgMZ4+OzOgQREREREbNtxjVZHUIKxcfPeurXPD5pyFO/5pOglfoiIiIiIiIiIiIi8nRpqXmmaaNcEREREREREREREZHnhFbqi4iIiIiIiIiIiMhTpZr6maeV+iIiIiIiIiIiIiIizwmt1BcRERERERERERGRp0sr9TNNK/VFRERERERERERERJ4TSuqLiIiIiIiIiIiIiDwnVH5HRERERJ47Vr75sjqEBzKe+jOrQxARERERebap/E6maaW+iIiIiIiIiIiIiMhzQiv1RUREREREREREROSpMmilfqZppb6IiIiIiIiIiIiIyHNCK/VFRERERERERERE5OnSSv1M00p9EREREREREREREZHnhFbqi4iIiIiIiIiIiMjTpZX6maakvoiIiIg8l0pXKUjLrjXwL50XR2cHLp69xpcf/sB3Gw+nOcbF1ZG3prejgH9usrs6cj0ilr3fHuPjmVu5GXcHgJIVfek2vBH5Cnhin82O8LAoNn++n5CPd5nnadu7Di++XJK8Bb2Iv53AsZ/Psmz6Fi6eufakb1tERERERP7jlNQXERERkedSifL5OXPyEmuW7OT6tViqvFScYVPbEnfjNvt3nkh1jMloIvTbY6z44BuiI+Pwye9OvwnNccnhSNDwzwG4fTOBjav2cubkJW7fSqBkRV8GTmzFnVvxbFm9H4DSVQqw8ZNQfv/1PNbW1nQd2pD3P+xBnyYzuXMr4am9ByIiIiIizyuDVupnmpL6IiIiIvJc+t+inRbH61fspsKLRXjx5VJpJvVjY27x1Wf7zMfhYdfZ9Gkor/aoZW7783gYfx4Pu9fnYhQvNihFyUp+5qT+2z0/sph35qg1fB76NkVK5uW3n8486q2JiIiIiIikSRvlioiIiMi/hpOLAzeu30x3fzcvF15sUIpfD6SdiC9U3Ifi5X35dX/afRxdHAC4EZ3+a4uIiIiIiGSGVuqLiIiIyL9CzUalKVo6L3PGr31o35Ez2vNCvRI4ZLMjdMcxPhj7ZYo+K78fTQ43J6ysrfhk7na2fnEg1bkMBgN9xjTl6MG/OHvqyiPfh4iIiIjIf4LK72SakvoiIiIi8twrU7UgQye3Yfa4tZz7I/yh/RcHbuKTed+Sx8+DbkNfoffoJsybuN6iz/COC8nmaEexsvnpNuwVws5G8P1Xv6SYq/+E5vgVycXw1xY8tvsRERERERFJi5L6IiIiIvJcK125AO8seJ3FgZv4dv2hdI2JuhZL1LVYLpy+Smz0TaZ/+gafzt9B1NUb5j5XLkQB8NfvV3D1cKHTm/VTJPXfeLsZVeoUY0SnRVy7EvP4bkpERERE5F9OG+VmnmrqyxNz4cIF/P39OX78eJp91q5dS6VKlZ5iVI8uODiY5s2bZ3UYIiIiApSuUpCJi7qybPoW8ya2GWUwJP+T2NYu7fUuVlYGbG0tz7/xdjOqNyjJqNeXmB8AiIiIiIiIPGlK6kuWaty4MVu3bs3qMIiPj6d58+YPfQjxKOrWrcvy5cvTHc+sWbN46aWXKFWqFHXr1uWLL75I19hRo0bRr1+/R4j02bdv3z78/f1TfR05csTc78SJE7z22muULl2a2rVrs2TJkiyMWkREHrcyVQsyaVFX1q/cw+5vfiOnhzM5PZxxzpHN3Kd6/ZIs3jLUfFy5lj8NWlXEt4g3XnlyUrm2P29ObMHRg38RfjE5Md/0tReo+lJxfHzd8fF15+VXK9G6e012bPzZPE//Cc2p26w8QcM+51bcHfO17ez1RVgRERERkXQxZcHrX0K/dUiWcnBwwMHBIc3z8fHx2NnZPfE4goKC8PLy4sSJE0/8WukxaNAgIiIieP/998mfPz9Xr17FaDRmdVjPjPLly7Nr1y6LttmzZ7N3715Kly4NQGxsLD169KBatWpMnDiR33//nTFjxpA9e3batWuXFWGLiMhjVr9FRRwc7Wjf9yXa933J3H5k32lGdlkMgKOLA/kKepnP3bmTwCttqtB7dFNs7Wy4euk6e7YdZfXineY+VlZWdB3akFx53UhKMnLpXATLpm9h8+f3vgnQ9LVqAASt6mMR04xRa9i+7uCTuF0RERERERFASX15DIxGIx9++CGrV6/m0qVLeHh40K5dOwICAgA4f/48kydP5siRI/j6+jJx4kTKly8PJJffmTx5Mj/99BOQXNpm+/btdOrUiQULFhAWFsaJEyfo3LkzRYoUAWD9+vXY2NjQoUMHBg0ahMFgSBFTbGws1atXJzg4mNq1a5vbt23bxltvvcWePXvIli15Fd/333/P7t27CQ4O5ocffkj3fYeEhDBnzhyio6OpVasW7777Ls7Ozqn27dy5MxcvXiQwMJDAwEAATp48mWrfH374gQMHDrB9+3ZcXV0ByJs3b7piCg4OZt26dQD4+/sDsGLFCqpWrcqlS5eYMmUKu3fvxsrKiooVKzJ27Fjz3KNGjSImJoYyZcqwYsUK4uPj6dq1K3379mXGjBl8+eWXODg4MGjQIFq3bg0kl1iqV68eM2fOZOXKlRw9ehRfX1/Gjx9PlSpVHhpvdHQ0kyZNYvfu3dy8eZNcuXLRp08f8/xpsbOzw9PT03yckJDAt99+S6dOncyfhw0bNpCQkMDkyZOxs7OjSJEiHD9+nI8++khJfRGRf4mZo9cwc/SaB/bZvu6gRZL9yL7TDOvw4A1tN6zaw4ZVex7Yp5H/qPQHKiIiIiIiKf2LVs4/bSq/I49sxowZLFmyhH79+rF582amT5+Oh4eH+fysWbPo0aMHISEh+Pn5MWzYMBITE9Oc79y5c2zdupW5c+cSEhJibl+3bh3W1tasWbOGsWPHsnz5ctasSf0XeWdnZ+rUqcOmTZss2jdu3Ej9+vXNCf1r167x9ttvExQU9MBvDKQW47fffsvChQtZtGgRBw4ceGBpl+DgYHLlysXAgQPZtWtXilXm99uxYwelSpVi6dKl1KxZk4YNGzJ16lRu37790Li6d+9Oo0aNqFmzpvk65cuXJyEhgR49euDk5MQnn3zCZ599hqOjIz179iQ+Pt48PjQ0lPDwcFatWsWoUaMIDg6mT58+5MiRg9WrV9O+fXsmTJjA5cuXLa4bFBREt27dCAkJoVy5cvTt25eoqIfXFp49ezZ//vknS5YsYfPmzbzzzjvkzJnzoeNSe8+uX79u8TDg8OHDVKpUyeKbHjVq1ODMmTNER0dn+BoiIiIiIiIiIiLPAiX15ZHExsayYsUKRowYQcuWLcmfPz+VKlWiTZs25j7du3enTp06FChQgIEDB3Lx4kXOnj2b5pwJCQkEBQVRokQJihUrZm7PnTs3Y8aMoWDBgjRr1oxOnTo9sEZ9s2bN2L59O7du3TLHunPnTvM3CEwmE6NGjaJ9+/bmki3pZTKZCAwMpGjRolSqVIlmzZqxd+/eNPu7urpibW2Nk5MTnp6eFqvM/+n8+fMcPHiQU6dOMW/ePMaMGcPWrVuZOHHiQ+NycnLCwcHBvJLd09MTOzs7Nm/ejNFo5P3338ff359ChQoRGBjIpUuX2L//XikBV1dXxo0bR8GCBXn11VcpUKAAt2/fpm/fvvj5+dGnTx9sbW05eNCyrEDHjh1p2LAhhQoV4p133sHFxSVdewCEhYVRvHhxSpcuTd68ealevTp169Z96Lh/+uKLL6hRowa5cuUyt127ds3i4RJgPr527VqGryEiIiIiIiIiIo+PIQte/xZK6ssjOX36NPHx8bzwwgtp9rlbBgYwJ7MjIyPT7O/j44Obm1uK9rJly1qU2ilXrhxnz54lKSmJhQsXUr58efMrLCyMWrVqYWtry44dOwDYunUrzs7OVK9eHYCVK1cSFxdHnz59UlzrrvvnHD9+vLk9T548FqV2vLy8iIiIAJLLvtw/7m5pofTObzKZMBgMTJ8+nTJlylC7dm1GjRrFunXr0rVaPzUnTpzg3LlzVKhQwXy9qlWrcufOHc6dO2fuV7hwYays7v214OHhQdGiRc3H1tbWuLq6mu/1/vu4y8bGhlKlSnH69OmHxtWhQwc2b95M8+bNCQoK4tChQxm+t8uXL7Nr1y5effXVDI8VERERERERERF53qimvjwSe3v7h/axtbU1/3w3Kf+gTV/vlsbJiPbt29OoUSPzsZeXFzY2NjRs2JCNGzfSpEkTNm3aROPGjbGxSf7Yh4aGcvjw4RSr9Fu3bk1AQABTp061KP9zfxL/7hz3M5mSC4HVrVuXsmXLmtu9vb3TjDu1+T09PfH29sbFxcV8rlChQphMJi5fvoyfn98D3onU3bx5k5IlSzJ9+vQU5+5/gPLP+zIYDKm2Pa5Ne2vXrs13331n3tega9eudOzYkZEjR6Z7ji+//BJXV9cUK/w9PDxSrMi/e/zPFfwiIiIiIiIiIiLPCyX15ZH4+fnh4OBAaGgo+fLle6LXOnLkiMXxL7/8gq+vr3n1+N1NZe8XEBBA9+7dOXXqFKGhoQwePNh8bty4cRbH4eHh9OjRg1mzZpmT8r6+vhmO09nZOdUNc21tbVMkw1Obv0KFCnz99dfExcXh5OQEwJkzZ7CysrIoL5OW1K5TsmRJtmzZgru7e5qb+T6Kw4cPU7lyZQASExM5evQoHTt2TNdYNzc3WrZsScuWLfn8888JCgpKd1LfZDKxdu1aWrRoYfHwCJK/yfHBBx+QkJBgPrdnzx4KFChAjhw5MnB3IiIiIiIiIiLy2Gmj3ExTUl8eib29Pb169WLatGnY2tpSoUIFIiMjOXXqFNWqVXus1woLCyMwMJB27dpx7NgxVq1a9dDkb+XKlfHw8GD48OHkzZvXYgW9j4+PRV9HR0cA8ufPn67keUblyZOHAwcO0KRJE2xtbVMtMQTQtGlT5s+fz+jRoxk4cCBRUVFMmzaN1q1bp2sz3zx58rBr1y5Onz6Nq6srLi4uBAQE8OGHH/LGG28waNAgvL29CQsLY9u2bfTs2fOR7/fTTz/Fz8+PggUL8vHHHxMdHW2xaW1aZs+eTcmSJSlSpAjx8fHs3LmTQoUKpfu6oaGhXLhwIdXSOwEBAcybN4+xY8fSq1cvTp06xYoVKxg9enSG7k1ERJ4/zjmy0e/tZlR9qThGo4nd3/zGwvc3cvtmfJpjcudzo+fIJpSs6IutnQ0//fg7C97dwPWIWHOf9n1fonLtYhQsnpvEhCTaVLbc76aAf27a9q5NyYp+ZHd15Mpf4WxatI11czY/sXsVEREREZH/HiX15ZH169cPa2tr5syZQ3h4OJ6enrRv3/6xX6dFixbcvn2bNm3aYG1tTZcuXWjXrt0DxxgMBpo0acLSpUvp37//Y48pIwYOHMj48eOpX78+8fHxnDx5MtV+Tk5OLFu2jPfee4/WrVvj6upKo0aNLL5V8CBt27Zl//79tG7dmps3b7JixQqqVq3KqlWrmD59OgMGDCAuLg5vb2+qVav2WFbuDxs2jMWLF3P8+HF8fX1ZsGBBmg8t7mdra8vMmTO5ePEiDg4OVKxYkZkzZ6b7ul988QXly5dP9UGAi4sLH374IZMmTaJVq1bkzJmTfv36PfQzIyIiz4epK3qzbd1Btq87mOLcW9Pb4+bpwphuH2Jja8WQyW0YOKkVQcM/T3Uu+2y2vL+sB6dPXGLU60sA6DzoZd5Z+DpD2s43l9izsbXmx69/5fjhczR8tVKKeYqUysP1yDimjfgfl/YeoWR1fwYv6oMxycj6eV8/xrsXEREREXn+GbRSP9MMpru/pYg8wzp37kyxYsUYO3ZsVoci97lw4QL16tUjJCSE4sWLZ3U4T0QDqzZZHYKIiKRixt6pqSb18xX0ZPGWYQxsHcyp3y4CULFmUSYt7krn2oFEht9IMVeFF4swaUk32laeyM24OwA4Otuz5sAExnZfxuG9f1j0r9+yIn3GNE2xUv9+iaf+BODNuT3IVywvb9VPu6+IiIiIyJO2zbgmq0NIoezgWU/9mr98MOSpX/NJsMrqAEREREREHpfi5X25EX3LnNAH+HnPH5iMJoqVyZ/qGFs7GzCZSIhPNLcl3EnEZDRRsqLfI8XjmN2RG5GxD+8oIiIiIvJfY8qC17+Eyu+IPGfKly+f5rklS5ZQqVLKcgBZZfz48WzcuDHVcwEBAUyaNCnVcwsXLmTRokWpnqtYsSJLly59bDGKiMjzocPolnQY3cp8bJfNjmLl8tHv7Wbmtj5NZpLTw5nofyTRjUlGbkTfIqdn6iXnThw+x+1bCXQf0YjlM7eCAboPa4S1jTVuni6ZjrlEtaLUaVedcU0DMz2HiIiIiIg8fXXr1uXixYsp2l977TUmTJiQon3t2rUp9nG0s7Pj119/fSLxKakvz4WVK1dmdQjPjJCQkDTPeXt7P71AgLx586a5NwDAoEGD6NGjR6rnHlTLv3379jRq1CjVc+nZLFhERP59Ni3cxver95qPR38xgt3f/Mbub46a2yJSKa2THtFRcUwe9AkD3mlBs87VMRlN7PzqF079doHMVqr0K5mPiSEjWTlpDQe3HcnUHCIiIiIi/2rP8Mr5L774gqSkJPPxqVOn6NatG6+88kqaY5ydnfn663t7aRkMhicWn5L6Is8ZX1/frA4h3dzd3XF3d8/wOFdXV1xdXR9/QCIi8ty6ERXLjah7K/DjbydyPSKOS+ciLPpFXYslh5vlg2MraytccmQj6mraZXAO7T5F9wbTyJ7TkaREI3E3bvPJrrFc2pzxhHz+Ql5M+ag7m5ds59P312Z4vIiIiIiIZC03NzeL48WLF5M/f36qVKmS5hiDwYCnp+eTDg1QUl9ERERE/kWO/3wWlxzZKFwyD38cTf66bLkXCmGwMnDiyLmHjo+JuglA2RcK4eruROiOYxm6fv7CXkz5uBfffLSDj8Z9lvEbEBERERH5jzBkwUr9+Ph44uPjLdrs7Oyws7N74JgNGzbQrVu3B66+v3nzJi+99BJGo5ESJUowdOhQihQp8thiv5+S+iIiIiLyzHNwciCb870SbFOGfgpATo97q/KjI+M4f/oqB344yaB3WxE8YR02tta88XYzvv/qCJF/l+dx98pO4Mc9mf7Wan7/9QIADVpV5Pyf4URHxlGsfH76jglg3fLdXDxzzTy/Z+4cuORwxMvHFStrKwoWyw1A2LkIbt+Mx7eIN1M+7sXBXb/z5cxN5PR2BZJr+kdfi3mi74+IiIiIiDzcokWLmDt3rkXbgAEDePPNN9Mcs337dm7cuEHLli3T7FOgQAEmT56Mv78/N27cYNmyZbRv356vvvqKXLlyPbb47zKYMlsoVETkP6CBVZusDkFERIDOE9rQZULbB/Z5ve5Uwi9G4ZwjG/3ebk7VusUxGU3s/uY3Fry3gds3k1fkeOXJycc7RvJW58X8uv80AN2GvUL9lhVxyZGNKxej2Pz5PtYt32Ux/9DANjRoVTHFde/O03FAfTq9WT/F+ct/hdO5YP/M3rqIiIiIyCPbZlyT1SGkUO7NWU/9mvtn9M/wSv0ePXpga2vLwoUL032dhIQEGjduTJMmTRg8eHBmw02TkvoiIg+gpL6IyLPJpkihrA7hgRJP/ZnVIYiIiIiImD2TSf0BTz+pf3jukAz1v3jxIvXr1yc4OJj69VMu4HmQgQMHYmNjw8yZMzM0Lj2sHvuMIiIiIiIiIiIiIiLPubVr1+Lu7k6dOnUyNC4pKYnff//9iW2cq5r6IiIiIiIiIiIiIvJUZcVGuRlhNBpZu3YtLVq0wMbGMo3+1ltv4e3tzbBhwwCYO3cu5cqVw9fXl5iYGD788EPCwsJo0+bJVIBQUl9ERERERERERERE5D579uwhLCyM1q1bpzh36dIlrKzuFcGJiYnh7bff5urVq+TIkYOSJUvy+eefU7hw4ScSm2rqi4g8gGrqi4g8m1RTX0REREQk/Z7Fmvrl+z39mvo/z89YTf1nlWrqi4iIiIiIiIiIiIg8J1R+R0RERERERERERESeqme9pv6zTEl9EREREXnuGM9dzOoQREREREREsoTK74iIiIiIiIiIiIiIPCe0Ul9EREREREREREREni6V38k0rdQXEREREREREREREXlOaKW+iIiIiIiIiIiIiDxdWqmfaVqpLyIiIiIiIiIiIiLynNBKfRERERERERERERF5qgxaqZ9pSuqLiIiIyHOrQKl8DPjgdYpWLED0tRusX7CNNTO/StdYFzdnFux/H888brTK1Ye46JsAlKlZjGnfjE3Rv73fAKKuRAPQaWxLOo9rZXH+/MkwepYb+Yh3JCIiIiIi8mBK6ouIiIjIc8nRxYHJG9/i5++OMufNj/ArlY+hC3sSe/0mW5Z999DxQxf25Myv5/HM45bq+e6lR3Dzxi3z8fXwGIvzfx29wKgmU8zHSYlJmbwTEREREZH/IK3UzzQl9UVERETkuVS3/YvY2tkws88SEhOSOHv8IoXK5Kf1wFcemtRv2qseTjkc+WRyCFVeKZtqn+tXY8yr91OTlJhkXrkvIiIiIiLytCipLyIiIiLPpeJVC/Pr7pMkJtxbIX9w26+0Gx6As6sjsddTT8jnL+bDa6NbMKj2O+T280xz/vn73sPWzpazxy6w8v21HNt7yuJ8nsK5+PT0HOJvJ3B83x8sG7+aq+cjHs/NiYiIiIj8yxlMWqqfWVZZHYCIiIiISGbk9M6RYqV8VHj03+dcUx1ja2fD6I/7s3TMZ2km4CMvX2f2gGW822EO7702h6sXIpi2dQyFy/ma+5w48CfTey9mbLNpBA9cTi4/T2ZsH0c2Z4fHc3MiIiIiIiJp0Ep9EREREfnP6PZuW86dDGPH53vS7HPh1GUunLpsPj4WeorcBb1p+eYrTOuxCICfvjliPn/mt/OcOPAnK0/Oolbrqmz9+PsndwMiIiIiIvKfp6S+iIiIiDyXoq5Ek9M7h0VbTq8cf5+7nuqYcrVL4FcqHzVbVk5uMBgAWHNhPp9N3cDK99amOu7kT39SsnrRNGOJi77JhT8u41PIO4N3ISIiIiLyH6XqO5mm8jvyxFy4cAF/f3+OHz+eZp+1a9dSqVKlpxjVowsODqZ58+ZZHYaIiMh/3vF9f1D6RX+sbazNbRXqleL8ybA06+m/22EOb1QZyxtVx/FG1XF88MZSAIbVf48Ni7anea1CZXyJvHw9zfMOTvb4FPB6YB8REREREZHHQUl9yVKNGzdm69atWR0G8fHxNG/e/KEPIR5F3bp1Wb58ebrjmTVrFi+99BKlSpWibt26fPHFF+kaO2rUKPr16/cIkT4fzpw5wxtvvEHVqlWpUKECHTp0IDQ01KJPWFgYvXv3pmzZslSrVo2pU6eSmJiYRRGLiMjjtuN/e0iIT2Towp74Fs9D7Ver0qJ/Q76c87W5T/VmFVl6eKr5+NKZcM4eu2B+Xf7rKgDnToQRfTUGgJYDGlKtaQV8CnrhWyIvfad1pGydEmxceC/p3yuwA6VrFMM7vwclXijChP8NJinJyM7Ve5/S3YuIiIiIPN8Mpqf/+rdQ+R3JUg4ODjg4pL2hXHx8PHZ2dk88jqCgILy8vDhx4sQTv1Z6DBo0iIiICN5//33y58/P1atXMRqNWR3WM6Vv3774+vry8ccf4+DgwMcff0zfvn3Ztm0bnp6eJCUl0adPHzw8PPj8888JDw9n5MiR2NraMnTo0KwOX0REHoObMbcYExDEgA9eZ+6eSURHxPJJ4Dq2LPvO3McpuyP5/H0yNK+NnQ29p7yGu09O7ty8w5nfzjO68RR++eHeg3+PPG6MXtEPFzdnoq/d4Oie3xlceyLR1248tvsTERERERFJjcFkMv2LnlFIVjAajXz44YesXr2aS5cu4eHhQbt27QgICKBevXoEBwezcuVKjhw5gq+vLxMnTqR8+fJAcvmdyZMn89NPPwHJpW22b99Op06dWLBgAWFhYZw4cYLOnTtTpEgRANavX4+NjQ0dOnRg0KBBGP6uhXu/2NhYqlevTnBwMLVr1za3b9u2jbfeeos9e/aQLVs2AL7//numTJlCcHAwTZo0ISQkhOLFi6d5v3dj7NatG3PmzCE6OppatWrx7rvv4uzsnOqYzp07s3//fou2kydPptr3hx9+YOjQoWzfvh1XV9c040grtrlz51q0rVixgqpVq3Lp0iWmTJnC7t27sbKyomLFiowdO5a8efMCySv8Y2JiKFOmDCtWrCA+Pp6uXbvSt29fZsyYwZdffomDgwODBg2idevWQHKJpXr16jFz5kxWrlzJ0aNH8fX1Zfz48VSpUuWh8UZHRzNp0iR2797NzZs3yZUrF3369DHPn5bIyEiqVavGJ598Yi7fFBsbS8WKFfnoo4+oXr0633//PX379uXHH3/Ew8MDgM8++4zp06ezd+/edD8samDVJl39RETk6bKyT3tRwLPAeOd2VocgIiIiImK2zbgmq0NIoXK3mU/9mgc++ncs9FT5HXlkM2bMYMmSJfTr14/Nmzczffp0cxIVYNasWfTo0YOQkBD8/PwYNmzYA0ugnDt3jq1btzJ37lxCQkLM7evWrcPa2po1a9YwduxYli9fzpo1qf+F5OzsTJ06ddi0aZNF+8aNG6lfv745oX/t2jXefvttgoKCHviNgdRi/Pbbb1m4cCGLFi3iwIEDLFmyJM3+wcHB5MqVi4EDB7Jr1y527dqVZt8dO3ZQqlQpli5dSs2aNWnYsCFTp07l9u2HJwe6d+9Oo0aNqFmzpvk65cuXJyEhgR49euDk5MQnn3zCZ599hqOjIz179iQ+Pt48PjQ0lPDwcFatWsWoUaMIDg6mT58+5MiRg9WrV9O+fXsmTJjA5cuXLa4bFBREt27dCAkJoVy5cvTt25eoqKiHxjt79mz+/PNPlixZwubNm3nnnXfImTPnQ8flzJmTAgUKEBISws2bN0lMTOR///sf7u7ulCxZEoDDhw9TtGhRi89ijRo1iI2N5Y8//njoNURERERERERERJ5FKr8jjyQ2NpYVK1Ywfvx4WrZsCUD+/PmpVKkSFy5cAJITzXXq1AFg4MCBNGnShLNnz1KoUKFU50xISCAoKAg3NzeL9ty5czNmzBgMBgMFCxbk999/Z/ny5bRt2zbVeZo1a8aIESO4desW2bJlIzY2lp07d5pXsptMJkaNGkX79u0pXbq0Od70MJlMBAYGmlfmN2vWjL179zJkyJBU+7u6umJtbY2TkxOenp4PnPv8+fMcPHgQe3t75s2bR1RUFBMnTuT69esEBgY+cKyTkxMODg7Ex8dbXGf9+vUYjUbef/998zcbAgMDqVy5Mvv376dGjRrmOMeNG4eVlRUFCxZk6dKl3L59m759+wLQp08flixZwsGDB2nSpIl5/o4dO9KwYUMA3nnnHX788Ue++OILevXq9cB4w8LCKF68OKVLlwYwf2vgYQwGA8uXL6dfv35UqFABKysr3NzcWLp0KTly5ACSH9jcn9AHzMdXr15N13VEREREREREROTJ+DfVuH/atFJfHsnp06eJj4/nhRdeSLOPv7+/+ee7iebIyMg0+/v4+KRI6AOULVvWotROuXLlOHv2LElJSSxcuJDy5cubX2FhYdSqVQtbW1t27NgBwNatW3F2dqZ69eoArFy5kri4OPr06ZNmLPfPOX78eHN7njx5LErteHl5ERERAcCGDRssxt0tLZTe+U0mEwaDgenTp1OmTBlq167NqFGjWLduXbpW66fmxIkTnDt3jgoVKpivV7VqVe7cucO5c+fM/QoXLoyV1b2/Fjw8PChatKj52NraGldXV/O93n8fd9nY2FCqVClOnz790Lg6dOjA5s2bad68OUFBQRw6dChd92MymZg4cSLu7u588sknrFmzhvr169O3b1/Cw8PTNYeIiIiIiIiIiMjzSCv15ZHY29s/tI+tra3557tJ+Qdt+nq3NE5GtG/fnkaNGpmPvby8sLGxoWHDhmzcuJEmTZqwadMmGjdujI1N8sc+NDSUw4cPm1eJ39W6dWsCAgKYOnWqRfmf+5P4d+e4393tKerWrUvZsmXN7d7e3mnGndr8np6eeHt74+LiYj5XqFAhTCYTly9fxs/P7wHvROpu3rxJyZIlmT59eopz9z9A+ed9GQyGVNse16a9tWvX5rvvvuP7779n9+7ddO3alY4dOzJy5MgHjgsNDWXnzp0cOHDA/L6VLFmSPXv2EBISQu/evfHw8ODIkSMW465duwbw0G9LiIiIiIiIiIjIE6aV+pmmpL48Ej8/PxwcHAgNDSVfvnxP9Fr/TND+8ssv+Pr6mlePp7apbEBAAN27d+fUqVOEhoYyePBg87lx48ZZHIeHh9OjRw9mzZplTsr7+vpmOE5nZ+dUN8y1tbVNkQxPbf4KFSrw9ddfExcXh5OTEwBnzpzBysqKXLlyPfT6qV2nZMmSbNmyBXd39zQ3830Uhw8fpnLlygAkJiZy9OhROnbsmK6xbm5utGzZkpYtW/L5558TFBT00KT+rVu3AFJsknz/A4dy5cqxcOFCIiIicHd3B2DPnj04OztTuHDhDN2fiIiIiIiIiIjIs0JJfXkk9vb29OrVi2nTpmFra0uFChWIjIzk1KlTVKtW7bFeKywsjMDAQNq1a8exY8dYtWrVQ5O/lStXxsPDg+HDh5M3b16LFfQ+Pj4WfR0dHYHkPQHSkzzPqDx58nDgwAGaNGmCra1tqiWGAJo2bcr8+fMZPXo0AwcOJCoqimnTptG6det0beabJ08edu3axenTp3F1dcXFxYWAgAA+/PBD3njjDQYNGoS3tzdhYWFs27aNnj17PvL9fvrpp/j5+VGwYEE+/vhjoqOjad269UPHzZ49m5IlS1KkSBHi4+PZuXNnmnst3K9cuXJkz56dUaNG0b9/f+zt7Vm9ejUXL140799Qo0YNChcuzFtvvcWIESO4evUqH3zwAR07dsTOzu6R7ldERJ5tLjmd6DezC1Ubl8dkNLIr5CcWDF/J7bg7aY7JXcCLXlM6ULJaUWztbTm47Qjzhq7genhMuuctU7MYrd58haKVCuGY3YGwU5dZPX09Oz7d9cTvWURERERE/jtUU18eWb9+/ejWrRtz5syhcePGDBky5IE18zOrRYsW3L59mzZt2jBp0iS6dOlCu3btHjjGYDDQpEkTTpw4QUBAwGOPKSMGDhzIxYsXqV+//gMfeDg5ObFs2TJu3LhB69atGT58OC+99BLjxo1L13Xatm1LgQIFaN26NdWqVePQoUNky5aNVatW4ePjw4ABA2jcuDFjx47lzp07j2Xl/rBhw1i8eDHNmzfn4MGDLFiwIM2HFveztbVl5syZNGvWjE6dOmFlZcXMmTMfOu7uprg3b97k9ddfp3Xr1hw6dIh58+ZRrFgxILn+/8KFC7GysqJdu3aMGDGCFi1aMHDgwEe+XxERyXpBW8fQoFPNVM+N/OgNfIvnYXTTqYxvPZPSNfwZPK97mnPZO9ozedNbmEwmRjYKZGjdSdjY2TDpy6EW3wp72LwlXijC6d/O895rc+hTdjhbl3/HWx+/SdUmFR7fjYuIiIiI/EsYTE//9W9hMN0tBC7yDOvcuTPFihVj7NixWR2K3OfChQvUq1ePkJAQihcvntXhPBENrNpkdQgiIpKK6TsnsW3lj2xb9aNFez5/H5YensqAF8dz6tAZACo1KM27IcPpWHgQkZeup5irQr1SvLd+BK/m7sPNG8mb0jtmz8aXlxYypmkQP393NMPzGu8kz/PextFEhV9nRo8Fj/kdEBERERFJv23GNVkdQgpVuzx8Yefjtm/F0Kd+zSdBK/VFRERE5F+jeNXC3IiKMyfeAQ7tOIrJaKJY5dRLvNna24LJRMKdRHNbwu0ETEYTJasXzfS8AE45HLkRGfuotyUiIiIi8u9jyoLXv4Rq6os8Z8qXL5/muSVLllCpUqWnGM2DjR8/no0bN6Z6LiAggEmTJqV6buHChSxatCjVcxUrVmTp0qWPLUYREXk+dBjdkg6jW5mP7bLZUbxKIfrP6mJu61VhFG7eObh+NcZirDHJyI3IONy8XVOd+8T+P7gdd4ce77fjo/FrwGCgx3ttsbaxxi1X8pjMzFurTTWKVi7EB31T//80ERERERGRzFBSX54LK1euzOoQnhkhISFpnvP29n56gQB58+bl5MmTaZ4fNGgQPXr0SPXcg2r5t2/fnkaNGqV6Lj2bBYuIyL/PpoXb+H71XvPx6E8HsyvkALtDDpjbIsKiMjV39LUbvNcxmDfndKV5v5cxGU18t3ovpw6dwWTM3HKesnVKMnxZP2b1XsjZYxcyNYeIiIiIyL/Zv6nG/dOmpL7Ic8bX1zerQ0g3d3d33N3dMzzO1dUVV1fXxx+QiIg8t25ExXIj6l4Zmzu34rkeHkPY6XCLfpFXonH1zG7RZmVthYubE5FXrqc5/6Fvf6NbyeFkd3cmKdFIXPRNPjsTzKW/wjM8b+kaxXh33TAWDv2Y7St/yMTdioiIiIiIpE019UVERETkX+P4vj9wyelE4fJ+5rZydUpgsDJw4sCfDx0fExFLXPRNytYugatXdkI3HcrQvGVqJif0l45axeYl2x/bfYmIiIiI/OuYTE//9S+hlfoiIiIi8sxzcHIgm/O9EmyBXeYBkNM7h7kt+moM50+GcWDrLwye14PggR9hbWtN/1ld+H5NKJGXrgPg7pOTqZtHMa3nIk7+dBqAlzvX5NzJMKKv3qB41cK8Mb0T64K/5sKpywDpmrdsreJMWjuMkHlb+fHLfeT8u9Z+YnyixbcMREREREREHoWS+iIiIiLyzGszPIAuE9o+sE8X/yFcOXeNqd0W0H9WF6ZsHoXJaGJXyAHmD7u3P4+NjTX5/H2wz2ZnbstbNDfdJrXFxc2ZK2ev8lnQBtbO+dpi/ofNW79TTRyc7Gn/VjPav9XM3P7LzqMMr/vOo70BIiIiIiL/Mqqpn3kGk+lf9L0DEZHHrIFVm6wOQUREUmFl/2xvnG68czurQxARERERMdtmXJPVIaRQ7bUZT/2aez8d9tSv+SSopr6IiIiIiIiIiIiIyHNC5XdERERERERERERE5OlS/ZhM00p9EREREREREREREZHnhFbqi4iIiIiIiIiIiMhTZTBmdQTPL63UFxERERERERERERF5TmilvoiIiIiIiIiIiIg8Xaqpn2laqS8iIiIiIiIiIiIi8pzQSn0RERERee5sObMvq0N4oIY+ZbM6BBERERGRZ5pBK/UzTSv1RURERERERERERESeE0rqi4iIiIiIiIiIiIg8J1R+R0RERERERERERESeLpPq72SWVuqLiIiIiIiIiIiIiDwntFJfRERERERERERERJ4qbZSbeVqpLyIiIiIiIiIiIiLynNBKfRERERF55t3OFssN12vccbiJySqJlj2ge3sIaHCvz6kzELwMjv4OYZcNjBpg4vU26b/G2QvQqidYW8P+r+61r94IG7Ymzw9Qwh+G9IIyxe/1uRYJMxbB7gNwIxbwOU3Oq3mwTbB/pPsWEREREfnX0kr9TNNKfRERERF55t1xuIntHQc8L/mS61xRWjaCUZPhuz33+ty+Dfl8YGhv8HDL2G8ICYkwfBJULJPy3IHD0LgeLP8APpsPuT2h53C4cjX5vMkEA8bC+TCY9z6sXQo2iXaE5zmN0WDM9D2LiIiIiIikRiv1RUREROSZlyPKy+K4y6vJq+K3/wAvVU9uK108+QUwc3HG5p+9FArkh2oV4fBRy3PT3rY8fvct+OYH2HsQWrwCf12AX44Z2LDcRJECyX1yhufhZoFj3HSJwjnGPWPBiIiIiIj8B6imfuZppb6IiIiIPJdi4yBH9kefJ/QQbN0J44ekr//tO5CYeO/aCfHJ/2tvd6+PAQMGkxV3st189ABFRERERETuo6S+iIiIiDx3tuyAX09Ay0aPNk9UNIwJhMmjwdkpfWOmLwQvD6heMfm4gC/k9jYxazFE34D4BIjJGU6SbQJJ1gmPFqCIiIiIyL+VyfT0X/8SSuqLiIiIyHPldrZYxk6FScMxl7vJrPHToEl9qFw2ff2XfJL8QCH4PbD/ew9cWxsIfje5DM8LTQ1UaJgco0OcC2B4tABFRERERET+QUl9EREREXlu3M4Wy1WfvxjVP7me/aPa9zN89D8oVTf5NS4IbsQaKFUXvvzKsu+yz2HJp7B0OvgXsjxX0h/WfQj7vzLxw1rwCiuI0ToRmwQ7RERERETk+RIcHIy/v7/F65VXHvwLyJYtW3jllVcoXbo0AQEBfP/9908sPiX15Ym5cOEC/v7+HD9+PM0+a9eupVKlSk8xqkcXHBxM8+bNszoMERGR/5y7CX3Xa7lo2+zxzPnZPFi79N7rze7g5Ghi7VKoX+tev6WfwoIVsDgIShVLez4XZ3BzhQTbO8Tb3yJb3GMo+i8iIiIi8i9kMD39V0YUKVKEXbt2mV+ffvppmn0PHTrEsGHDePXVVwkJCaFevXr079+f33///RHfpdQpqS9ZqnHjxmzdujWrwyA+Pp7mzZs/9CHEo6hbty7Lly9PdzyzZs3ipZdeolSpUtStW5cvvvgiXWNHjRpFv379HiHS58PRo0fp1q0blSpVomrVqrz99tvExcVZ9PnnE1V/f3+++uqrNGYUEZFnWXJC/wwu191xjM3B1Qi4GgHXY+71iU+A46eSXwkJEH4t+eezF+71+WQtdLtvQ9xCflC04L2XtwdYWSX/nMMluc+ST2HOMnh/JOTJhfnacfftgfv1d7D/ZzgfBt/ugvA8p8kWl51sN12e6PsiIiIiIiLpFx8fT2xsrMUrPj4+1b7W1tZ4enqaX25ubmnOu2LFCmrWrEnPnj0pVKgQgwcPpkSJEqxateqJ3IfNE5lVJJ0cHBxwcHBI83x8fDx2dk/+a+tBQUF4eXlx4sSJJ36t9Bg0aBARERG8//775M+fn6tXr2I0GrM6rGfGlStX6NatG40aNeLtt98mNjaWyZMnM3r0aObMmWPRNzAwkJo1a5qPs2fXikkRkedRXPYoTFYmYtyuEuN2lVqtkmvVVy5nYsXs5D5Xr0Grnvdq2C/7PPl1f5+oaDgXlrFrf74eEhIMDBpv2d6/q4kB3f6+dgRMnQcRUeDhDk4xOckR6ZWZWxURERER+W/Ign1rFy1axNy5cy3aBgwYwJtvvpmi79mzZ6lRowb29vaUK1eOYcOG4ePjk+q8hw8fpmvXrhZtNWrUYPv27Y8t9vspqS+PzGg08uGHH7J69WouXbqEh4cH7dq1IyAgAIDz588zefJkjhw5gq+vLxMnTqR8+fJAcvmdyZMn89NPPwHJpW22b99Op06dWLBgAWFhYZw4cYLOnTtTpEgRANavX4+NjQ0dOnRg0KBBGAwpN6CLjY2levXqBAcHU7t2bXP7tm3beOutt9izZw/ZsmUD4Pvvv2f37t0EBwfzww8/pPu+Q0JCmDNnDtHR0dSqVYt3330XZ2fnVPt27tyZixcvEhgYSGBgIAAnT55Mte8PP/zAgQMH2L59O66urgDkzZs3XTEFBwezbt06IHmVOiQ/KaxatSqXLl1iypQp7N69GysrKypWrMjYsWPNc48aNYqYmBjKlCnDihUriI+Pp2vXrvTt25cZM2bw5Zdf4uDgwKBBg2jdujWQXGKpXr16zJw5k5UrV3L06FF8fX0ZP348VapUeWi80dHRTJo0id27d3Pz5k1y5cpFnz59zPOnZefOndjY2DBhwgSsrJK/cDRx4kSaNWvG2bNn8fX1NffNnj07np6e6Xr/RETk2eV+JR/uV/KZj7eG/ZKiT57ccPz7B/9mMKAb5kR8alo2Sn7d79v/wcN+4+j8avLrroY+uR7YX0REREREnr4+ffrQrZvlLwSpLSguU6YMgYGBFChQgKtXrzJv3jw6duzIxo0bU83/Xbt2DQ8PD4s2d3d3rl279nhv4G8qvyOPbMaMGSxZsoR+/fqxefNmpk+fbvEhnjVrFj169CAkJAQ/Pz+GDRtGYmJimvOdO3eOrVu3MnfuXEJCQszt69atw9ramjVr1jB27FiWL1/OmjVrUp3D2dmZOnXqsGnTJov2jRs3Ur9+fXNC/9q1a7z99tsEBQU98BsDqcX47bffsnDhQhYtWsSBAwdYsmRJmv2Dg4PJlSsXAwcONNfhSsuOHTsoVaoUS5cupWbNmjRs2JCpU6dy+/bth8bVvXt3GjVqRM2aNc3XKV++PAkJCfTo0QMnJyc++eQTPvvsMxwdHenZs6fFV4xCQ0MJDw9n1apVjBo1iuDgYPr06UOOHDlYvXo17du3Z8KECVy+fNniukFBQXTr1o2QkBDKlStH3759iYqKemi8s2fP5s8//2TJkiVs3ryZd955h5w5cz50XHx8PLa2tuaEPmD+8zt48KBF34kTJ1K1alVeffVVvvjiC0ymLHgMLCIiIiIiIiIiFrKipr6dnR3Ozs4Wr9SS+rVr16ZRo0YUK1aMmjVrsnjxYmJiYtiyZUsWvFMpKakvjyQ2NpYVK1YwYsQIWrZsSf78+alUqRJt2rQx9+nevTt16tShQIECDBw4kIsXL3L27Nk050xISCAoKIgSJUpQrNi9nehy587NmDFjKFiwIM2aNaNTp04PrFHfrFkztm/fzq1bt8yx7ty50/wNApPJxKhRo2jfvj2lS5fO0H2bTCYCAwMpWrQolSpVolmzZuzduzfN/q6urlhbW+Pk5GSuw5WW8+fPc/DgQU6dOsW8efMYM2YMW7duZeLEiQ+Ny8nJCQcHB+zs7MzXsbOzY/PmzRiNRt5//338/f0pVKgQgYGBXLp0if3791vEOW7cOAoWLMirr75KgQIFuH37Nn379sXPz48+ffpga2ubInHesWNHGjZsSKFChXjnnXdwcXFJ1x4AYWFhFC9enNKlS5M3b16qV69O3bp1HzruhRde4Nq1ayxdupT4+Hiio6OZMWMGAFevXjX3GzhwIB988AEfffQRL7/8MhMnTmTlypUPnV9EREREREREROSu7Nmz4+fnx7lz51I97+HhkWJVfkRERIrV+4+LkvrySE6fPk18fDwvvPBCmn3uloEBzMnsyMjINPv7+PikuvFE2bJlLUrtlCtXjrNnz5KUlMTChQspX768+RUWFkatWrWwtbVlx44dAGzduhVnZ2eqV68OwMqVK4mLi6NPnz5pxnL/nOPH3yukmydPHouv2nh5eREREQHAhg0bLMbdLS2U3vlNJhMGg4Hp06dTpkwZateuzahRo1i3bl26Vuun5sSJE5w7d44KFSqYr1e1alXu3Llj8ZdR4cKFLVa/e3h4ULRoUfOxtbU1rq6u5nu9/z7usrGxoVSpUpw+ffqhcXXo0IHNmzfTvHlzgoKCOHToULrup0iRIkyZMoWPPvqIcuXK8eKLL5InTx48PDwsPiP9+/enYsWKlChRgt69e9OzZ08+/PDDdF1DRERERERERESeIKPp6b8yKS4ujvPnz6e5ULdcuXKEhoZatO3Zs4dy5cpl+poPopr68kjs7e0f2sfW1tb8892E64M2fb1bGicj2rdvT6NG9wrgenl5YWNjQ8OGDdm4cSNNmjRh06ZNNG7cGBub5I99aGgohw8fTrFKv3Xr1gQEBDB16lSL8j/3J/HvznG/u2Vd6tatS9myZc3t3t7eacad2vyenp54e3vj4uJiPleoUCFMJhOXL1/Gz8/vAe9E6m7evEnJkiWZPn16inP3P0D5530ZDIZU2x7Xpr21a9fmu+++M+9r0LVrVzp27MjIkSMfOjYgIICAgACuXbtGtmzZMBgMLF++nHz58qU5pmzZssyfP/+pbcAsIiIiIiIiIiLPn6lTp/LSSy/h4+NDeHg4wcHBWFlZ0bRpUwDeeustvL29GTZsGABdunShc+fOLFu2jNq1a7N582Z+++03Jk2a9ETiU1JfHomfnx8ODg6EhoY+MJn6OBw5csTi+JdffsHX19e8evzuprL3CwgIoHv37pw6dYrQ0FAGDx5sPjdu3DiL4/DwcHr06MGsWbPMSfn7N1xNr7v1uP7J1tY2RTI8tfkrVKjA119/TVxcHE5OTgCcOXMGKysrcuV6+KZ7qV2nZMmSbNmyBXd39zQ3830Uhw8fpnLlygAkJiZy9OhROnbsmK6xbm5utGzZkpYtW/L5558TFBSUrqT+XXe/xvTFF19gb2/Piy++mGbf48ePkyNHDiX0RURERERERESy2jO87eHly5cZOnQo169fx83NjYoVK7J69Wrz4thLly5ZVLuoUKEC06dP54MPPmDmzJn4+fkxb948iwoYj5OS+vJI7O3t6dWrF9OmTcPW1pYKFSoQGRnJqVOnqFat2mO9VlhYGIGBgbRr145jx46xatWqhyZ/K1eujIeHB8OHDydv3rwWK+h9fHws+jo6OgKQP3/+dCXPMypPnjwcOHCAJk2aYGtrm2qJIYCmTZsyf/58Ro8ezcCBA4mKimLatGm0bt06XZv55smTh127dnH69GlcXV1xcXEhICCADz/8kDfeeINBgwbh7e1NWFgY27Zto2fPno98v59++il+fn4ULFiQjz/+mOjoaFq3bv3QcbNnz6ZkyZIUKVKE+Ph4du7cSaFChdJ1zVWrVlG+fHkcHR3Zs2cPQUFBDBs2jOzZswPJGw5HRERQtmxZ7O3t2b17N4sWLaJ79+6PdK8iIvJsWbgSvt8LJ/4AW1vY/5Xl+XVbYMwUQ6pjd4WYcE9jf/brMfD+bPhuD1hZQYNaMOZNcEr+5wJzP4J5y1POm83BxKGtyT/HukQSmeuCZQejgfx/ZmwvHxERERERebpmzZr1wPOp7dnYqFEji0oiT5KS+vLI+vXrh7W1NXPmzCE8PBxPT0/at2//2K/TokULbt++TZs2bbC2tqZLly60a9fugWMMBgNNmjRh6dKl9O/f/7HHlBEDBw5k/Pjx1K9fn/j4eE6ePJlqPycnJ5YtW8Z7771H69atcXV1pVGjRhbfKniQtm3bsn//flq3bs3NmzdZsWIFVatWZdWqVUyfPp0BAwYQFxeHt7c31apVeywr94cNG8bixYs5fvw4vr6+LFiwIM2HFveztbVl5syZXLx4EQcHBypWrMjMmTPTdc0jR44QHBxMXFwcBQsWZOLEibRo0cJ83sbGhk8++YTJkycDyQ9rRo0aRdu2bTN1jyIiknWu5PkTp5icON9I+f8tCQnQsA6UKwlfbk45tlFdqFHFcgnQmClwJ540E/oAb70LVyPhwxmQmJg8ZsJ0mP73Fjvd2kG7ZpbzdhsKpYtZzmNIssLnrD8iIiIiIiKPi8F0txC4yDOsc+fOFCtWjLFjx2Z1KHKfCxcuUK9ePUJCQihevHhWh/NENLBqk9UhiIj856WW1N8a9otFn3VbIHBuypX6/xR5Heq0hnffguYNU+/z51/Q9HUDaxaZKPV3kv7HfdBnJOz8Arw8Uo458Qe07GFg5RwTlcpCQ5+yxLpEEuUZRr7TpdJ/syIiIiIiT8A245qsDiGFOo2Cnvo1d25566lf80mwengXEREREZF/h/VbwcEheXV/Wg4fhezO9xL6ANUqJpfh+eVY6mO+2AR++ZIT+vczWRm56Heci37HuZr7L+Ltbj/yPYiIiIiIyH+byu+IPGfKly+f5rklS5ZQqVKlpxjNg40fP56NGzemei4gICDNHcAXLlzIokWLUj1XsWJFli5d+thiFBGRZ090znBi3MLNxyaDkTsON4nyCjO3hV0BH++Mz/3lV9CkHjjYp93nWiS4/aM0j40N5HBJPvdPd+7Apu3Q8zXLdtsEe9yu5MPujgNG6yRiXK9yJe8f5D5XFJtEbdouIiIiIv9xKiCTaUrqy3Mhtc0n/qtCQkLSPOftnYnsxiPImzdvmnsDAAwaNIgePXqkeu5Btfzbt2+f5sYi6dksWEREnm/O0W44xuYwH0fkOodjbA6y3dfm5X4iw/P+/Bv8edbA1LGP95eH7T9C3E1o8Yplu/1tJ+xvO907vuXEJd+TxGaPxDXy0TapFxERERGR/y4l9UWeM76+vlkdQrq5u7vj7u6e4XGurq64uro+/oBEROS5YG20wdp475+pBqMVVok22CbcW15vk4l/xX7xFRQvbKLkQ/at9XCDyCjLtsREiL6RfC61eWtXS/3c/QwYsL2TjUS7OxkLXERERETkX8ighfqZppr6IiIiIvKvF3cTvv4OWjd5eN9yJSEm1sDR+76Mtu9nMBqhbAnLvhcuJZ9Lz7wmTCTY38Y60TZjwYuIiIiIiNxHSX0REREReaYYDUkkWSeYXx6X85PtpotFW1JSct+wK3D8VPL/JiUl/3z8VHIS/35bvks+H9Ag5fWOHIfGneHK1eTjQn5Qs4qJt6clnzv0K7z7ATSuC14elmO/3Aye7lCrasp5o92ucMvxBok2d4i3v0lErnMk2cTjHPOQJf0iIiIiIv8Fpix4/Uuo/I6IiIiIPFNicl4lxj38gX0uh0Oe3BC8DEK+NpjbW/VM/t+PPzBR5b695b/8ChrUguwuKee6fRvOnDOQmHjvX/lBb8N7H0C3IWBlBS/XgjEDLccZjRCyBVq+AtbWKec1WiUR6XWBJOtErIzW2N3JhveFwtjGa38YERERERHJPIPJpG2GRUTS0sCqTVaHICIiqdga9ktWh/BADX3KZnUIIiIiIiJm24xrsjqEFOo2mPLUr7lj26infs0nQeV3RERERERERERERESeE0rqi4iIiIiIiIiIiIg8J1RTX0RERERERERERESeLmNWB/D80kp9EREREREREREREZHnhFbqi4iIiIiIiIiIiMhTZTCZsjqE55ZW6ouIiIiIiIiIiIiIPCe0Ul9EREREnjsNfcpmdQgiIpKKP1ZWyOoQHqhw50NZHYKIiNylhfqZppX6IiIiIiIiIiIiIiLPCa3UFxEREREREREREZGnSzX1M00r9UVEREREREREREREnhNK6ouIiIiIiIiIiIiIPCdUfkdEREREREREREREniqDqu9kmlbqi4iIiIiIiIiIiIg8J7RSX0REREREREQyxdbelsELelOkYkHyF8/Dt5f+pM8PX1r0aZivKJ2KVKB4Tm/srK05df0as3/9kR8unUlz3jxOOdjVol+K9pZff8zhiDDzceP8xRhaphZ5nXP8n737jq/p/uM4/sqODJLIQEKIPULsPVrUKjVqtahZtbX2bO1das/afi21lSo1WjVq1ChS1BY7ZBEZN78/Upcrw84NfT8fjzzkfM/3fM/nnBv3Jp/zPZ/DubBgxvy5gx1B/5hs83nB8jTJEUBaGztOeJ1kcsc5XDlz7SWPXEREXpoelPvClNQXERERERERkRdiZWXJg8goVk/ZSPn6pSC/Q4I+JTyzsOvaOcYd3klodCQf+hVkTsWG1Nu8kBN3ric7/sdbl3Eq5JZx+e6D+8bvi7h7803ZDxh3eAe/XDnDB1nzM6tCA2pv+ta4Tft8pWiZuxg992zgUvhdBsUUYtRPA2mT/3OiH0S/orMgIiKSslR+R0REREREREReSOS9B0zuOIdNc3/hzrW7ifYZdnArs07s42jwVc6H3WH8kZ2cDwumsneOp45/J+o+tyIjjF8xcQbjulZ5irHz6llmn9zHP6G3+frorxy/c40WuYsa+7TOU5ypf/3OlsunCbx7kzGfTCV9JlfK1i3+0scuIiIvx8KQ8l9vCyX1RURERERERCTFWACONraEREU+te+cih+yv0FXlldtRpUnLgIUdvfm96vnTdp+DTpHEXdvADI7ueCZxold1x71uRd6j8B9Z8hXOvfLHoaIiIjZqPyOiIiIiIiIiKSYT/OVxNHalh8vnEyyz72YKIYf3MrBm1cwxMVRPUtuZlX8kPY7f2DrlTMAeNg7cSsywmS7W5EReNg7/bveMb7tvmmfO9fv4url8gqPSEREXohq6r8wJfVFREREREREJEXUyZqPrv7l+HTnSm4/uJdkvzsP7jMvcL9x+WjwVbzSOPFpvlLGpL6IiMh/lcrviIiIiIiIiMhr975vXkaXrEnn39bw+2MlcZ7V4dtB+Dq7GpdvRobj/u9s/Ifc7R25GRn+7/r4GfruaUz7uHq5cOf63efev4iIvGJxZvh6SyipL5LCLl++TO7cuTl5MulbTVetWkWxYsVSMCoREREREZHXp7ZvPsaVqkW339eyPeifFxojn6sXN+6HG5f/vHWFshl8TfqUy5iVQ7euAHAp/C437odT1iurcb2DcxrylMzBiT1/v1AMIiIiqYGS+iKpUM2aNdm8ebO5wyAqKooPPvjgqRchUqN9+/bRoUMHypUrR0BAAB988AHr1q0zd1giIiIiIm+dLHl9yF4oK85uTjjb2JHX1ZO8rp7G9XWy5mNCmfcZcWgbf94Kwt3eEXd7R5xt7Ix9WuQqypLKTY3L9bP5U9s3H35p3fBL60bH/KVp6FeQhX8fMPaZH3iACpn8aJunBH5p3ejmXw5/t4ws+vugsc+3gfvpXKAMVbxzkNvFg94LO3M76A6/r3lU2kdERORNo5r6IqmQvb099vb2Sa6PiorC1tb2tccxduxYPD09CQwMfO37etX+/PNPcufOTbt27XB3d2f79u306dMHZ2dn3nnnHXOHJyIiIiLy1hjxYz8yZH2UxN9Ysw0A2ZaOAqBpjgBsLK0YVqIaw0pUM/b74Z+j9Nr7IwCudmnwdXIxGbeLf1m8HdMSYzBwNjSYLrvWsOnSoxn2h25dofvv6+hRqAI9AypyPuwO7X9dyamQW8Y+s07sxcHahpEla5DW1p7j20/Qr8YIoh9Ev/LzICIiz8dCD8p9YRZxcTp7Iq+DwWBg3rx5LF++nKtXr+Lu7k7jxo2pXbs2lStXZsqUKSxevJijR4/i6+vLkCFDKFy4MBBffmfkyJEcOBA/C2XKlCls3bqVZs2aMWPGDIKCgggMDKR58+bkzJkTgLVr12JtbU3Tpk3p1q0bFhYWCWIKDw+nTJkyTJkyhYoVKxrbt2zZQu/evdm9ezdp0qQBYOfOnYwePZopU6ZQq1Yt1qxZQ968eZM83r59+xIaGsr06dONbSNGjCAwMJDFixcDPHe8EF+uqHLlyib7Dw0NpXjx4ixatIiSJUs+2wsCfPrpp6RPn55Ro0Y98zZVLRs+c18RERERkf+6M4uLmDuEZOVofsjcIYiImMUWwwpzh5DAe6WHpfg+f94zKMX3+Tqo/I7IazJhwgTmzJlDx44d2bhxI+PHj8fd3d24fuLEibRp04Y1a9aQNWtWevToQUxMTJLjXbx4kc2bNzN16lTWrFljbF+9ejVWVlasWLGCAQMGsGDBAlasSPyN2snJiUqVKrFhwwaT9vXr11OlShVjQv/WrVsMGjSIsWPHJnvHwIt4nnhftbCwMFxcXFJkXyIiIiIiIiIikoy4uJT/eksoqS/yGoSHh7No0SJ69epFvXr1yJIlC8WKFaNhw0ezvlu3bk2lSpXIli0bXbt25cqVK1y4cCHJMaOjoxk7diz58uUjT548xvaMGTPSv39//Pz8qFOnDs2aNWPBggVJjlOnTh22bt3K/fv3jbHu2LGD2rVrAxAXF0ffvn1p0qQJ/v7+L3kmEnreeF+VjRs3cuzYMerXr//a9yUiIiIiIiIiIvK6KKkv8hqcPXuWqKgoSpUqlWSf3LlzG7/38PAAIDg4OMn+mTJlws3NLUF7oUKFTErXBAQEcOHCBWJjY5k5cyaFCxc2fgUFBVGhQgVsbGzYtm0bAJs3b8bJyYkyZcoAsHjxYiIiImjfvn2SsTw+5uDBg5Psl5jnjfdZ1KpVy7hN27ZtE6zfu3cv/fv3Z/jw4cbyPyIiIiIiIiIiYkYGM3y9JfSgXJHXwM7O7ql9bGxsjN8/THIbDEm/uzwsjfM8mjRpQo0aNYzLnp6eWFtbU61aNdavX0+tWrXYsGEDNWvWxNo6/u1g7969HD58OMEs/QYNGlC7dm3GjBljUv7HycnJeAxPPqIjuXJCzxrvjRs3AEzGfnLc2bNnG9ueLBf0xx9/0KFDB/r160fdunWfKx4REREREREREZHURkl9kdcga9as2Nvbs3fvXjJnzvxa93X06FGT5SNHjuDr64uVlRUuLi6J1pCvXbs2rVu35vTp0+zdu5fu3bsb1w0cONBk+caNG7Rp04aJEydSqFAhAHx9fROM6ebmxunTp03aTp48aXLx4kXifXh3ws2bN03GfZy3t3eCeAD27dvHZ599Rs+ePWncuHGifUREREREREREJOVZvEU17lOakvoir4GdnR3t2rVj3Lhx2NjYUKRIEYKDgzl9+jSlS5d+pfsKCgpi1KhRNG7cmBMnTrBkyRL69OmT7DbFixfH3d2dnj174uPjY0zWQ3yZn8c5ODgAkCVLFjJkyJDkmKVKlWLevHmsWbOGgIAA1q1bx+nTp8mXL99LxWtvb09AQACzZ8/Gx8eH27dvM2nSpGSPD+LvOPjss89o0aIF7733nvGigI2NjR6WKyIiIiLymnXKX4Z3vLOTz9WLaEMshVZMNFnfwM+f8aXfT3TbYj98w+0H915oXIAvi1alqIc3uVw8+CfkNrU2fZvoWB/2qE2tdlXw9PUg9FYY62dsZtnIVc95pCIiIilPSX2R16Rjx45YWVkxefJkbty4gYeHB02aNHnl+6lbty6RkZE0bNgQKysrWrRo8dRZ6RYWFtSqVYu5c+fSqVOnVxJH+fLl6dixI+PGjePBgwc0aNCAunXrcurUqZeOd+TIkQwYMID69euTLVs2evXqRevWrZPdZs2aNdy/f59Zs2Yxa9YsY3uJEiVYvHjxix+oiIiIiIgAMH7bV/y8cAc/L9yRYJ2NpRUbLwby560rNMpeKMH6DRdOsjPorOl4pd/HzsoqyYT+s4z70IqzRwlIn4k8Lp6Jru/4TSuKVi3E7F6LOXfsIs5uTji7OSU5noiIvAaaqf/CLOKeLIItIm+M5s2bkydPHgYMGGDuUJ7JmxYvQFXLhuYOQUREREQkVUosqX9mcRGTPg38/BlctEqiM+of52aXhj31utB330ZWn/vrqft+lnG7+ZfjPZ9cJjP1czQ/RJY83sw6Mp52/j24fCroqfsSEXkbbDGsMHcICVQr9lWK73PzgZTf5+ugmfoiIiIiIiIiYlb1s/kTGRvNxouBr31fpWoX5erZG5R6vwh1Og3AwgL+/OUYc3ovIexO+Gvfv4iIyMtSUl9EREREREREnqppv3o07VffuGybxpa8pXLSeUobY1uVLfMIuhf63GM3ylGItedP8CA25pXEmpyMfl54+bpT4cPSjP1kCpZWlnT4uiWDVvSgd5Uhr33/IiLyLxWQeWFK6ou8wd602vBvWrwiIiIiIvLIhplb2Ll8j3G575Ku7Fq1l12r/jC2XR/i/dzjFnb3Jmc6d77Yvf6VxPk0FpaW2NrbMuaTqVw5fRWACW1nMOPgWHxyZVJJHhERSfWU1BcRERERERGRpwq7E25SnibqfhR3b4QS9M81Y1tsXKbnHrdx9kIcD77GX8HXnt75FQi+eoeY6BhjQh/g4skrAHhmcVdSX0QkpRjMHcCby9LcAYiIiIiIiIjIf5ODtQ21fPOw/J+jKbbP478HYm1jTUY/L2ObT66MAFy/cDPF4hAREXlRmqkvIiIiIiIiIk9l72hPGid74/KIppMAcPVyMbZZWlhgiIsjk0Na0tnZk8khLZYWFuR19QTgQtgd7sVEG/u/75sXawtLVp/7K8H+CqXPyITStfn4l2Vcvx9/h8CzjOvr5IqDjQ0eaRyxt7Y29jkTcguAQ1uPcergWXrO68j0z+djaWlJl6ltOPjzEZPZ+yIi8npZqKb+C1NSX0RERERERESeqmHP2rT4slGyfcqtmc6ViBA+L1ieD7MXNLZvrBn/MN0mW5ay78ZFY3uj7IX46dIpwqIfJBjL3sqG7OnSY21pZWx7lnFHl6pBKS/fBH3KrZkOQFxcHIPrjKbT5NZ8vXMokREP2L/pT2b1XPRsJ0JERMTMLOLidElERCQpVS0bmjsEEREREZE3xpnFRcwdQrJyND9k7hBERMxii2GFuUNIoHqhQSm+z5+ODEvxfb4OqqkvIiIiIiIiIiIiIvKGUPkdEREREREREREREUlZKiDzwjRTX0RERERERERERETkDaGkvoiIiIiIiIiIiIjIG0Lld0REREREREREREQkZan8zgtTUl9ERERERERERERE5F+zZs3i559/5uzZs9jb21O4cGF69uyJn59fktusWrWKfv36mbTZ2tpy7NixVx6fkvoiIiIiIiIiIiIikrIM5g4gaX/88Qcff/wx/v7+xMbG8vXXX9OmTRt+/PFHHBwcktzOycmJn376ybhsYWHxWuJTUl9EREREREREXokczQ+ZO4Q3mrWPt7lDSFbM5SvmDiFZQX3KmDuEZGWeedzcISQrolIec4eQLMczd8wdQvIs9ejSN0FUVBRRUVEmbba2ttja2pq0zZs3z2R59OjRlC5dmuPHj1O8ePEkx7ewsMDDw+PVBZwEJfVFREREREREREREJEVZmKGm/qxZs5g6dapJW+fOnenSpUuy24WFhQGQLl26ZPvdu3ePd955B4PBQL58+fjiiy/ImTPnywWdCCX1RUREREREREREROSt1759e1q1amXS9uQs/ScZDAZGjhxJkSJFyJUrV5L9smXLxsiRI8mdOzdhYWF8++23NGnShB9//JEMGTK8kvgfUlJfRERERERERERERFKWGWbqJ1Zq52mGDBnC6dOnWbZsWbL9ChcuTOHChU2Wa9asyXfffUf37t1fJNwkKakvIiIiIiIiIiIiIvKEoUOHsmPHDpYsWfLcs+1tbGzImzcvFy9efOVx6QkOIiIiIiIiIiIiIiL/iouLY+jQoWzZsoWFCxeSOXPm5x4jNjaWU6dOvZYH52qmvoiIiIiIiIiIiIikLEPKl995VkOGDGHDhg1Mnz4dR0dHbt68CYCzszP29vYA9O7dGy8vL3r06AHA1KlTCQgIwNfXl9DQUObNm0dQUBANGzZ85fEpqS8iIiIiIiIikkrY2FnTZWQjcvj7kCWHF/t+OcGwdvOS3ca/VA7GLu+c6Lpu70/g1NFL+JfKQb22FckdkAUHJ3uunLvFylnb2L7moEl/x7Rp+KRXTcrWKIhzOkeuXwlm9pDV7N9+0tgnm38WukxtS+7i2bl7M5S1UzexfNy6ZGP0yOxOt+ntKPROfu6HR7Jl0U7m9VuKIdYAQP6yeWg3+mMy5/HGzsGO6xdu8uPsLaya9KNxjPc/e4/an72HV9b4Wa8Xjl9mybAV7P/psMm+yub0pVOV0uTwSs+D6BgOnr/C2B9/JehuaJLx/dy7Nd6u6UzaJv60i7k79wPQsXIpOlUpnWC7e1HRFP9yKgDWlpa0q1ScOkXy4ZXWifO37vD1T7+x69QFk22y5feh07iPyFU4GyG3w1g7exs/TP4p2fOXq3BWWn3ZgJwBvsTFxXHq4DnmfvUD5/66bOxTvm4xmnxRE+/sXoTcDmf9nG38MGWzyTg2ttZ81Ls27zYqhatnWu5cD2Hp2PX8vPR3ADJ4pGXF7E8T7L99n6WcOHU10diyZ/WgWf0S+Of1xsU5DVdvhrJ28xF+2HDI2Ce9qyOdWlYiTw4vvDO48sOPh5jy7XaTcSYPa0zhAglnQ+85cJbeI1YBULBYNuq1KEvuAj44ONpx5eJtfljwG9t/PJLs+QOo+kFh6rcoh7dveu6FP+C3LX8xbcR64/psubzo1L8OuQp4E3IngrXL9vLD/N+M68tWzkfjdpXIlNkNa2srrly8zaqFu/hlw2Fjn4LFslKvWZn4+JzsuHLhNj8s3MX2jUeTjqtOYXoMq5/ousbvjCYkOAKAd2oWpGHL8mTK4sa98Afs//0Uc7/eTFjIfQCsrC1p3KYCVWoXxt3TmcvnbzNv0mYO7j7z1HMjCf3vf/8DoHnz5ibto0aNon79+Nfr6tWrWFo+KoQTGhrKoEGDuHnzJunSpSN//vx899135MiR45XHp6S+iIiIiIiIiEgqYWlpSVRkNOvm/0rZGoWeaZuTB8/xUdFBJm3Ne9YkoGxOTh29BEC+olk5dzKIFTN+4e6tMEpUzk+PiR8TEXafP345AYC1jRUjl3bg7q0wRny2gFvXQvDydiU89L5xXAfnNIzePIhDW4/yTYfZZPPPQo95HQm/e4+Nc7YmeUwjNvQj+NpdupcdiFtGF3ov7EJsdAzfDohPnEVGRLJ22k+cPXqByIgHFCiXh24zPyUy4oFx3FuXbzOv31KunL4KFha890klhqzpQ4civbhwIj657e2alinN67Bw1yH6fL8JJ3s7+tSqyDfN3qfh1OQfcjlly25++OOYcTniQZTx+wW/HWT5PtPE7Ly2H/LX5WvG5a7vleH9gLx8uXoL527coWwuX75pVoePZ3xH4NWb/54/e0as/JzDO08y5YslZM3nzedTWhIRco9NC39NNC57RzuG/9CdvZuOMK3nEqysrWjWtw4jfvic5gV6ExsTS7EqBegzuy3T+/yPQ9uOkyV3RrpN+oQHkVGsn/Moed5/fntcPNIyqcsCgs7ewC1DOiwsE1bn7j54Oecu3TIuh4RFJnnecmf34k7IPYZP2sj1W2H458lErw7vYYiNY9WmPwGwsbbibug9Fq7YS6PaRRMdZ8CYtdhYP4olrXMa5k/8hO27/za25Q3IwrlT11g+71fu3g6nRMXc9BzxIRFhkfzx69+JDQtA/RZlqd+iHHO/3sTfRy9j72CDVyZX43oHRztGzGrF4b3/MGXYWrLm9OLzofWJCItk0w/xF3bCQu7z3ewdXDp3k5joWEpUzM0Xw+pzNzjcmDjPWygL505fZ/n83+Ljq5CbnsMbEBEeyR+/nko0tp2bj3Hg99MmbT2G1cfW1tqY0M8XkIWewxswe/wm9u4MxN0zLV0G1qH7l3UZ9kX8/6FPOlfh3VqF+GbIGi6du0XRMjkYPPEjvvhkDv8EJn5BxuzM8KDcZ/X330n/PD20ePFik+X+/fvTv3//1xWSCSX1RURERERERERSiQf3o5g6YAUA+Yr54Zg2zVO3iYmO5c7NMOOylbUlpasWYN2CR7OMv59mmnBf++2vFCmfm7LVCxmT+u81LomziwNf1JtEbEz8DPobl4NNtnv34/JY21ozoc0MYqJjuHDiMtkDstHg8/eTTOoXfa8gWfL50LvqUO7eCOGfI7Bw8He0Hd2MRV+tICY6hn8On+efw+eN21y/cJNy9UriXy6vcdy9G0zvKpg/8H+8/9l75C2Vy5jUz+/thaWlBZO3/G7MFy747SBTmtfB2tKSGIMhyfMY8SCKW+H3El13Lyqae1HRxuXcGdzJ4ZWeIWt+MbbVLpyX2dv/4Le/44/j+31HKZ0jCy3LF6Xv8viZ+O80LIWNrTVfd55PTHQsFwKD8PPPQv2OVZNM6mfOmYG0bk4sGrWGW1fuALB07Hpm/j4Ez8zpuXruBpUbl2bPj4fZOH8nANcu3OL7iRtp1K2GMalftHJ+/MvmpmVAP8LvxieLr1+6neg+Q8LuE3w38XPxpI2//GWyfPV6CPlzZ6JC6ZzGpP61m6FMnhcfR63K/omOExZueuGgcrk8PHgQzfbdj5Lh38/dadJn7dI9FC2Tk7JV8ieZ1HdKa0+LzlX4qstiDu87a2w/d+q68ft3ahXCxsaKrwetIiYmlgv/3MAvT0bqtyhrTOofPXAuwb6r1ilC/iJZjUn97+eZvoZrl+2laOkclK2cL8mkftSDGKIehBuX07k6UKhENiZ9tcbYlrdgZq4H3WXtsr0AXL9yl40/7Kdhq/KPzletQnw3dyf7d8VfIPhxxX4Kl8pOgxZlGdv/h0T3LW8uPShXREREREREROQtUqpqAZxdHdmyfF+y/RzTpiHs3+QuQKkqBTh58Dydhn/IsoPDmLGlD407VcHS0sLYJ1+pXBz79QQx0THGtgObD5MljzdOLo6J7idf6dycP3aRuzdCHtvmCI7pHPDN75PoNtkDspKvTG6O/no80fWWlpZUalwGe0c7Tux5lCw9fuU6cXFx1CuaH0sLC5zsbKldOC97/rmYbEIfoG3F4vw+6DN+6PIxrcoXxeqx435Sg+IFOHczmEPnrxjbbK2teBATY9IvMjqGIlkzGZfzFvfj2O5TxETHGtsO/vIXmXNlxCmdQ6L7unzmGiG3w6jerDzWNlbY2ttQrVk5LgQGcf1i/Gx6G1troh5Em2wXFRmNh7cbXpnTA1CqRgCn/zxPw27VWXJ8HHP3D6ft0IbY2tsk2Ofo/vVYt6Aj00Y2oWzx7Emeh6Q4OdgRlszs/mdRq4o/v+wKJPKJ43qSo5MdYSFJX4AoXDoHlpYWpPdMy+y13Vi8tTf9xzfB3etRuaW8hbJw7OB5YmIee11+P03mbB44pbVPdNyAkn74ZHXn2MFzia43xudsbyyR8ywq1w7gwf1oftvy6Gf/5NFLeGRIS/FyOQFwcXOkXJX87P/t0c++ja01UVGmP39RD2LIH5Dlmfed4uLiUv7rLaGZ+iIiIiIiIiIib5FqjUtxaGcgt66FJNmn/PsB5CqYhcn9lhvbMmRJT6EyOdm+5iCDW84iU1YPOg3/ECsbK5ZNiq/N7pbBhavnb5iMded6iHFd+GMXCR5yzeDCnet3n9jmrnGbfx5rX3ZxJuk80mJlbcXiIcvZNG+byXZZC2Rh8u4R2NrbcD88kiH1x3Hx5KO68lfuhNLu21VMaFqLL+tWwdrKkj8vBNFhwZokzwXA0t2HOXHlBiH3IwnIkonu1cvikdaRsT8mnD1va23F+wF5jfX2H/r91AU+KVeUA+eucCn4LqWyZ6FK/hwmFwdcPdMZE/EP3b0ZX+vf1Ssd4Ykkp++HP6B37XF8uaQzTXu9D0DQP9cZ8OFE4zMJDm47TvsRjdlS4XeO/PY3mfw8qd/pvX/PcTquX7pNRl8P8pfKSdSDaIY2n0669E50Hv8xad2c+Lrz/Ph9RUYzdf52jp28giEOKpbOyci+dek/eg2/7/8nQWyJKZA7E++WzU3v4aueqX9i8ubMQHZfD8ZM25xsv/LVCpCzgA+Th65Nsk9GHzcsLC1o0q4SM0dvICL8AZ90qcKoOa3oUH8KMTGxuLo7cf3fuyAeuns7fva8a3pnwkPjL1A4ONmx9Jc+2NhYYzAYmDp8PX/uSfq8lH+vADnzezN5WPLPnHhctbpF2b7pKFEPHiXoTxy+yNh+P9BvbGNsba2xtrFi745Apo3aYOxzcPcZ6jcvy7GD57l66Q4BJf0o825eLK00p/ttpKS+iIiIiIiIiMhbwj1DOopUzMOojguS7FOwdA6+GN+Ub/p+z8VTj2rCW1hacPd2OJP7fo/BEMeZY5dJ75WODz97x5jUf92+qDAYeyd78pbKSdtRHxN05hrbv/vduP7y30F8VrgXjukcKP9hKXot6EyPSl8aE/vuTg4MqV+VdYdO8uORQBztbOlctTQTP36ftvNWJrnfhbsePdT11LVbRMfG8mW9ykz86XeiY2NN+lbJnwMHOxvWHjph0j5qww6G1KvChi8+IS4OLgXfZc3B49QrVuClzomtvQ2fT27J8X1nGN12NpZWljTo/B5Dv+9G13eHExUZzaaFv5IxmwdDvuuKtY0V98IiWTNzK837fYDBED872cLSgri4OMZ8Opd7/z4nYfaA5QxY+BlTey4hgviyO9+ve1TmKPDMNdxdnWhat/gzJfWzZXFnVL+6zP9+D/uPXHhq/6TUquzPP+dvcvL0tST7FCyejR5DG/DNV6u58M+NJPtZWFhgY2PNjFEbOLQnvkzO6N7fs2x7PwqVyPZcD5K9HxFFxw+nksbBjoCSfnzaqwbXLgcnKM3zKL56fDNkbbLxPS5vwcz4Zvdk3ADTn9Usfh581rsmy2Zt5+DuM7h5ONP282p0HViHif+W6Zk59ke6Da7LnDXdIC6Oq5fvsGXtn7xXt8gzH1+Ke4tmzqc0JfVFRERERERERN4SVRuVJOxOBHu3/JXoev+S2fnq23bMHrqGX1aazjS/cyOUmJhYYxIY4NKZ67h5psPaxooYIPjaXVw905ls5/pvGZPga3cT3eeda3fJUzzHE9u4JLrNtX/vAjj/10VcvdLR/MtGJkn9mOgYgv6JT/SePnSW3MWyU69bTb75bDYATUsXIjzyARN+evQ8gb7f/8S2fu0omDkDRy8lnSR+3NFL17CxssLbNS3nb5nO4G5QrAA7A89x+4n6+3ci7tN1yXpsra1wcbDnRmgEX1Qvx+XgR3dM3LkRgotHWpPtHi4/vOPhSe98WBKvLO58/t4o4v5Ngo5pN4cfzk2mdM0Adq6Kfx2//WolC4auwtUrHSG3wgiomBeAa+fjH9IbfD2E21fvGhP6ABdPXcXS0hL3TK7cIXEnTl+leCHf5E4XAFl90jNpSEPWbTnKoh/2PrV/UuztbKhcLg/zHnvdn+RfLCtDpjZn1riN/LL+cLLjBd+Kf97ExbOPEushd+4RevceHhldALhzKxyX9E4m2z1cvnP70fMq4uLiuHop/jkTZ/++ShY/Txq3rZggqe9fNCtDJn/MrHGb+GVD8vE9rnr9opwJvMqZk0Em7Y3bVODE4Yv8sDD+nJw7fZ3I+1FMWNCOhVO3EnwrnJA79xj6+TJsbK1J65KG2zfCaN39Pa5dSeqVlTeZ7r8QSWGXL18md+7cnDx5Msk+q1atolixYikYlYiIiIiIiLwNqjYqwS8r9xsfdPs4/1I5GLLgU74dtZ5Ny/YkWH/8wDky+XpgYfGoXIy3nwe3r4cYa8Cf2HsK/wr5sLK2MvYpWrUgFwOvJFp6B+DEnr/J6p/FJJldpGpBIkLucfHE5US3gfi6+TZ2yc9HtbC0xNb2UU14exsbDE/M/o39d9nSIuka+U/Kk8mDWIOB4CcS996uaSnhl5lVBxK/aAIQFRPLjdAIrC0tqVogJ9tOPJrhfnL/WfzL5DI5f0XeycelU1cTLb0DYJfGljiDwZjQBzAY4oiLi8Piibr/BkMct6/eJSY6lkoNSnDijzOE/FtG5sS+M7hlSIe9o92j48nuRWysgVtBSSd+c2bz5PadxF/bh7JmTs83wxrx0/bjzFm6K9m+T/NOmVzY2Fjx884Tia4vWCwbQ6e14NuJm40PsU3OiT/j7xjwyepubHNKm4a0Lg7cCLoLwMkjF/EvmhUr60ep0iKlc3Dp3E1j6Z3EWFhaYGNrZdJWsFhWhk5txreTfmbTygNPje8h+zS2lH+vAJtXH0ywzs4+4c+1Ifbf5Sd+rqOjYrh9Iwwra0vKVc7Hnu1J55/MzhCX8l9vCSX1RVKhmjVrsnlzytzamJyoqCg++OCDp16ESI3Onj1L8+bNKVOmDP7+/lSuXJmJEycSHZ38A3ZERERERETMLUtOL/zyeePs4oCjsz1++bzxy+dtXJ+rUBZmb+tH+sce9AkQUDYnGbO489N3CWdJFyydg6EL2rF2/q/8vukIrh7OuHo4mzyc9cfFv+Ps4sBnX9XDO5sHxd/NR+NOVdmw8FGSdtuyXcRExdBjbgd88/lQsVEZ6natycqJj2p7l61bgnknJhmXD/58lIsnLtNnURf8CvpS7L1CtBzWhHXTfyL63wd71ulYjVLvF8U7Rwa8c2Sgeut3+bBHbX5Z+mjGfeuRH+FfPi9evh5kLZCF1iM/olClfPyy7FGfXwPPUcA7Ax3eLUmW9C7kzeTJiA/f48qdEE4Gxc/U9vfxYv3nn+CZNv7BvoWyZKR52cLkzuCOj2s6agXkoU+timw4HEho5AOT81i/WH5uhkXw29/nE5xj/8wZqJI/Bz6u6SiS1ZtZrephYWHBt78+Suxu/2Ef0VExfD7lE3zzZKJCveLUbV+FVdO3GPuUqVWYOfuGGZcP7TiBk4sjncZ/TOZcGfHNk4ke01oRG2vg6G9/A5DWzYmarSrikzMDfgUy89moJpT/oBgz+31vsu+wOxH0mNqKLLkzUqBMTtoO/ZCfl+wiKjL+b+Xq7+Sncrk8ZPF2I4u3G80blKTmuwVYufFP4zjlS+ZgyZRWxuVsWdyZPKwx+w+f5/t1B3BzccDNxQGXtGlMzk+OrB7kyOpBGnsbXNKmIUdWD7L6pE9wHmtV8WfXvjOEJvKg3YLF4xP6a5fuYdeW47imd8I1vRNOj+2rzLv5mLOuu3H5yoXb7N52gs/6vE/eQlnwzeFJzxEfcvncTY7sPxt/bjYeITo6ls+H1Mc3uycVqvlT9+MyrFr06G6Bxm0qULh0djL4uJI5mwf1W5Sl8vsBbNtwxDS+qc1Zu2wvu7aeSCK+vMxZ0zXBsVWsXgArK0u2/Xgkwbp9O/+m7Lv5qNWwOBm8XckXkIUOfWoSeOwSwTfj7yTI7e9D2cr5yODtSv7Cvgyf3gILSwtWLHi5iyySOqn8jkgqZG9vj7194k9Xh/hku62t7WuPY+zYsXh6ehIYGPja9/Wq2djYULduXfLnz4+zszOBgYEMGjSIuLg4vvjiC3OHJyIiIiIikqShC9rjldnNuDztp14A1MjSHYifuZ05hxdWNqYzhN9rXIrjB85yOZH63VU+LIG9gx1NOlelSeeqxvaje87Qp/FUAG5dvcuA5jNpP7gu0zf35vb1ENZ+u5MVM34x9r8Xeo++1YbRZWpbph8YQ8itMJYO+4GNc7Ya+zimcyBLnkcXIQwGAwNrj6Lb9HZ8s3sEkREP2LJoBwsGP0o4W1ha0HrkR2TI5okhxkDQP9eY23cpP856lOx28UxH74WdccvoSkTIPc4dvUC/6iM4tPWosc++s5fo/f1GWlcoRusKxbgfHcORi1dpP381D2Li7zawt7HBz9MNa8v48xcVE0uNgrnpWLkUttbWXAkOYdGuQyZ19iF+QvQHRfKz5tDxBLOmAeysrehatQw+bum4FxXNr3+fo+/ynwh77MLAvdD7DGgwkU7jPmLK9kGE3A5j6bj1bFr46IG8jmnTkDlXRuPy5dPX+LLpFJr1qc3En/sRZ4jjzNGLDPxwEsGPleyp2qQM7YY2xMLCgpP7/6F37XGcOvSoLExkxAP61fuajmM+YvK2gYTdieDX1QdYOGK1yXG0bFQaL4+0xMYauHglmK8mbGDHnlPG9U4Odvg+loyvVDoXrukcqFYpP9Uq5Te2X70RQqP2c4zL8yd+Yvw+T44MvFcxX4I+mTO5UiifD59/tSLB+QWo+kER7B1sadKuEk3aVTK2H91/lt6t58WfP2c7MmfzMNlufP8faN+7JkOntyDOEMexA+cY8NlC4x0t98IfMKD9fDr1r8OU7zsScvceS2dtM7kTwN7Bls4D6uDulY6oB9FcOneTsf1W8OvmY4/iqx2AfRpbmrStSJO2FR+L7xy9234bH5+TfYL4IP4Bub//coKIRC5mbFn3J2kcbanTtBTtelQnIiySI/vPMe+xZ13Y2lrTolNlMvq4cv9eFPt3nWbcgJWJjidvPou4OD2RQOR1MBgMzJs3j+XLl3P16lXc3d1p3LgxtWvXpnLlykyZMoXFixdz9OhRfH19GTJkCIULFwbiy++MHDmSAwfir+ZPmTKFrVu30qxZM2bMmEFQUBCBgYE0b96cnDlzArB27Vqsra1p2rQp3bp1M7ld8qHw8HDKlCnDlClTqFjx0YfLli1b6N27N7t37yZNmvirxzt37mT06NFMmTKFWrVqsWbNGvLmzZvk8fbt25fQ0FCmT59ubBsxYgSBgYEsXrwY4LnjhfhyRZUrVzbZf2hoKMWLF2fRokWULFny2V4QYNSoURw7doxly5Y98zZVLRs+c18REREREZGXYe3j/fROZhRz+Yq5Q0hWUJ8y5g4hWZlnHjd3CMmKqJTH3CEky/FMKq8Nb5m6C6L8dGTY0zulsBrZUn7S5aZzX6f4Pl+H1P3TJvIGmzBhAnPmzKFjx45s3LiR8ePH4+7+qH7bxIkTadOmDWvWrCFr1qz06NGDmJiYJMe7ePEimzdvZurUqaxZs8bYvnr1aqysrFixYgUDBgxgwYIFrFiR+BVtJycnKlWqxIYNG0za169fT5UqVYwJ/Vu3bjFo0CDGjh2b7B0DL+J54n2VLly4wG+//Ubx4sVf+75EREREREREREReF5XfEXkNwsPDWbRoEYMHD6ZevXoAZMmShWLFinH5cvxDgFq3bk2lSpUA6Nq1K7Vq1eLChQtkz5490TGjo6MZO3Ysbm5uJu0ZM2akf//+WFhY4Ofnx6lTp1iwYAGNGjVKdJw6derQq1cv7t+/T5o0aQgPD2fHjh1MnRp/u2VcXBx9+/alSZMm+Pv7G+N9VZ433pfVpEkTjh8/TlRUFI0bN6Zbt26vZT8iIiIiIiIiIvIcVEDmhWmmvshrcPbsWaKioihVqlSSfXLnzm383sMjvpZacHBwkv0zZcqUIKEPUKhQIZPSNQEBAVy4cIHY2FhmzpxJ4cKFjV9BQUFUqFABGxsbtm3bBsDmzZtxcnKiTJn42xQXL15MREQE7du3TzKWx8ccPHhwkv0S87zxPotatWoZt2nbtq3JuokTJ7J69WomTJjAjh07mDdv3nPFKyIiIiIiIiIikppopr7Ia2BnZ/fUPjY2NsbvHya5DQZDkv0flsZ5Hk2aNKFGjRrGZU9PT6ytralWrRrr16+nVq1abNiwgZo1a2JtHf92sHfvXg4fPoy/v7/JWA0aNKB27dqMGTPGpPyPk5OT8RiefERHcuWEnjXeGzfiH/D0+NhPjjt79mxj25PlgjJmjH+4UI4cOYiNjWXw4MG0bt0aKyvTB0qJiIiIiIiIiEgKMmim/otSUl/kNciaNSv29vbs3buXzJkzv9Z9HT161GT5yJEj+Pr6YmVlhYuLCy4uLgm2qV27Nq1bt+b06dPs3buX7t27G9cNHDjQZPnGjRu0adOGiRMnUqhQIQB8fX0TjOnm5sbp06dN2k6ePGly8eJF4n14d8LNmzdNxn2ct/ezPUwqLi6OmJgYDAaDkvoiIiIiIiIiIvJGUlJf5DWws7OjXbt2jBs3DhsbG4oUKUJwcDCnT5+mdOnSr3RfQUFBjBo1isaNG3PixAmWLFlCnz59kt2mePHiuLu707NnT3x8fIzJeogv8/M4BwcHIP6ZABkyZEhyzFKlSjFv3jzWrFlDQEAA69at4/Tp0+TLl++l4rW3tycgIIDZs2fj4+PD7du3mTRpUrLHB7Bu3Tqsra3JnTs3tra2HDt2jAkTJlCjRo0EFxpERERERERSO6d0DnQcWp+SVQpgMMTx+6YjzPxqFZH3opLcJqNvetoO+ID8xf2wsbXmwM6TzBi8kru3wo19mnSuSvF38+GX35uYqFga+vdLMM6mi5MStI1oOpEd3+82Lju7OtFpcmtK1S5KnCGO31btY3q3+URGRCYdn58Xn45rQYFyebCxs+bAT4eZ2vVb7t4IMfb5qH99StQsQvaArMRExVDPrWWCcbYYViRo6/m/H9l09BQAmVzS8tm7JSmZPTPuzo7cCA1nw+FAZm/fR3Rs0nfM21pb0btmBWoUyo2tlRW/n77AsLXbuB1+z9jn+KjPk923u7MjvWtWIL+PF1lGpGPtrF+Y1f/7BNs4uTjScWxTSlYrRFxcHL+vO8iMft8RGfEg6fOX1YO2wxqSv1RObGytOfjLX0zv8z/u3gw19mnSoxYl3vPHr0BmYqJj+TBr1wTjBFTIQ4sBdcnqn4X7kdH8tP04c5b+Ruxjs6ibf1iS0kX9yJnNk+iYWGo2m5pkXABWVpa0+6gcpYpmI5OXCxH3HnDgyAVmLv6V23cijP1y+XnyWfMK5MmZAYMhjp17TjF1/g7uR0YnGNM5XRqmr+yCh1c6GpQZRkTYo5+tJu0qUaJCLvxyZ4w/zrLDk4/P2pJPulSlePlcZPR2IyI8kj/3/sO3kzYTfDPM2C9H3ky0/rwaufJ7YzDEsWvrcWaP3Ujk/Uf/7zwypKPLoA8oWDwbkfej2LruMN9O3oLhsZ+tJm0rUqJ8LvxyZ4iPr/zIZOMDaPbZO1Ss7o9HhnRER8dy5kQQC6Zu5e9jj559+Czj5srvTatuVZ+6P7NQTf0Xppr6Iq9Jx44dadWqFZMnT6ZmzZp8/vnnydbMf1F169YlMjKShg0bMnToUFq0aEHjxo2T3cbCwoJatWoRGBhI7dq1X0kc5cuXp2PHjowbN44PP/yQiIgI6tat+0riHTlyJLGxsdSvX5+RI0ea3EmQFGtra+bOncuHH35InTp1mDZtGs2aNWPEiBEveIQiIiIiIiKv15jvO1PlwxKJrus9uTlZcmWk/8cz+Kr1bAqUzE7X0Un/LWWXxpYRSzoQFxdH3ybT6FH/G6xtrPnq23YmzzmztrXitx8P8+Pi35ONbcIXyzi++2+mdZtPo4zt+H3NfpP1fZd0JWv+zPR9bxgDa4+mYPm8fD4r6We12TvYMXrzQIiLo1flIXQvNwhrW2uGrev7RHzW/PrDHjbM/DnZ+Ma1msafF4IYtX47FUfM4pcT/xjX+Xm6YmlhwZA1W/lg4iLG/riTRiX86fZe2WTH7FOrIpXy+vHF0h/5ZPYKPNI68s3HCf+GHrBiMxVHzDJ+Pb5vWysrgiPuM2vbPh7ciyJL7oyJ72tOW3zzZKJ//a/5sslkCpTJRbdJLZKMzc7BlhGrPoc46PvBeHrUGI21rTVD/tfF9PzZWPHbmoP8+O3ORMfJVsCHocu7cWDrX5y/dJtN2/6ibInstG9ewaSfjbUVO3afYs1PR5I9Zw/Z21mTy8+Thcv30qbHIgaMWUsWbzdG969n7JPe1ZGJXzXkyrW7tO+9lJ5DV5Itszv9u9RIdMy56z8n7O69RNdZ21jx289/8ePyP54pPjt7G3LkzcSyWdvp3Hgawz5fhk9Wd76a0tzYx83DmVFzWhF08TbdP57JwM8W4Jvdkx7DGxj7WFpaMHR6C6xtrLh49ia/bDhClTqFadHx3YTxbfmLH1eY/r9JzuULt5k+agOfNZhKz5ZzuR50h5EzPiGdq8Mzj2ufxpbh01tw81pIouvlzaWZ+iKviaWlJR06dKBDhw4J1v39998my2nTpjVpq1+/PvXr1zcud+nShS5duiS6H2trawYMGMCQIUOeK75evXrRq1evp/bz8fFJEG9SunbtSteuCa/6P+5F4s2ePTvfffedSdvTYqpZsyY1a9Z85n2IiIiIiIikVplzeFH8nbx0fX8Cp49eAmDG4JUMXfgpc0esJfh6aIJt8hfLhqePG51rjONeePxs7wlfLGXFsZEUKpuTw7viZ5Iv+fongCQvJjwUEXqfmKgY7oXe4871uybrsuTxpkSNwnQq3odTB88CMLXrt4z4sR+zey3i9tU7CeMrmxuvrJ50KNKbe2H3ARjbchqrg+cT8G4B/vzlGACLvloOwHufVEo2vvC7EUTHxhIeGcWtcNPE765TF9h16oJx+fKdELK6H6RxqUKM3/RbouM52dnSoFgBen+/iX1n48/5wB9+ZsMXLSmYOQNHL10z9g2NfJBgnw8F3Q1l9IYdAAyoViHRPplzZaR4FX+6vDOM04fj45zeZxnDlndjzqDlBCeSkM1fMgdeWdzpXHEo9/6dsT6+47f8cO4bAirk4c+d8WVrl4xeB0DVpmUS3XfFesU5f/wyy8ZtwL9OUS5eCWbGwp0M7Vmb+d/vNs6Y//a7+LsyaryTP9FxnhRxL4ovhvxg0jZxzi/MGdcMT3dnbtwKo0yx7MTEGvh69lbjhO3xM7ew8JuWeGdw4cq1u8Zt61YrhJWVJQd+P41fIhdGlkz/Jf44Pyj8TPHdC39A/0/nm7RNH7meyd91xCNDOm5eC6FkxTzExBiYNmK98Tl/U4atZeaqrmTM7MbVS8EUKZOTLH6e9Gv3Lf3HNeX86essmv4Lbbq9x5IZ24mJiY2Pb8a2+PjqPFt8ADs2mZYvnj3+J6rXL0a2nBk4/MfZZxo3czZ30ro4sGjaL7z3QZFn3neK0Uz9F6aZ+iIiIiIiIiIiqVjeIlkJC7lnTOgD/LnrFHGGOPIEJHzmGYCNnTXExREdFWNsi34QTZwhjvzF/Z47ho7DG5C/bG6aDfqQaq3eMY2vdC7C7oQbE/oAh7YejY+vZM4k4rOJj+/BozIr0ZFRxBniKFAuz3PH12VqWwr7ZuKzd0tRr+jTE8/O9naE3Eu6NFB+by9srK3Yc+aise3czTsE3QklIItpUnlgnXfZNfAzvuvY9Jn2/aS8xf0IuxthTOgD/LnjZPz5K5r4a/Xo/D32+kb++/qWSvycJzqOrQ1RD0xL3TyIisHOzobc2ZMuwfsiHB1sMRjiCP+3pJCtjRXRMbEmed0H//68Fsz76Nl5WX3S07JRaS6du0nca3ywqqOzPQaDwVjWx8bWipjoGGNCH+DBvxc5ChSJ/3+Xt1Bmzp++zt3bj0oKHdx9Gkdne3xzeL6y2KytrajRoBjhofc5e+ra0zf41+Xztwi5E0H1ekVfWSySOmimvoiIiIiIiIiIGTTtV4+m/R7dpW2bxpY8hX3pOOxReY/2lUfh6uFMyGN18AEMsQbC7t7D1SNtomMHHjpP5L0oWverw4IxG8DCgtZ938fK2go3z8S3eVLjTlVo3Lkq0VExOKdzwNLSEo/M7vSY24Fu09sREx1Lm/yf45bBhbs3TO8WMMQaCA0OxzWDS6Jjn9x7msiIB7Qd04xv+y/DwsKCNqM/jo8vo+szxffw/EU/iMbZ1RFLCwsyujgzrEFVBtd9l5hYA3UmLuJqSJjJdlnSp+OjMgGM3/hrkmO7OzsQFRNDWKRpTfvb4fdwd3Y0Lk/Zspt9/1ziflQ0ZXP6MuiDd3Gws2Hp7sO0q1ScTys9ugMija0NARXysvrSo3r0n5YejKtXOkJumsZoiDUQdicCV690icYXuP8fIu89oPVXDVgwbDVYQOsvG8SfvwyJb/Okxl/U5P02lbC1t2Hd1RlY2ViRP3dGrCzj5wBPGNyApp3mceNW2FNGejpbGys6tKjA1t9Ocu/fevQHj12kc6tKNK1bnBUbDmJvZ8Nn/5b9Se/qSPMGJWn+YUnsbK2JiTHgUsCHHPninwO4ZGsfII5PP/jmlZSWsbG1pvXn1dix6Sj3/r3ocGTfWT7tWZMPW5ZjzZI92DvY0Lp7NQDc3J1p3LYijdtWxMLCgtX7BmNrZ0Oegj7ExsZfBPh6YTvavmR8JSrkot+YRtjZ2xB8K5z+ny0kNIkSRIm5fy+K3m2/5cuJH71wDJI6Kakv8gZbvHixuUN4Lm9avCIiIiIiIq/Thplb2Ll8j3G53/Ke/L7pCL8/VnbjdiKldZ5FSHAEIzssoPPIhtRpVZ44Qxw71h3i9LFLzzzb+cclu/l1w2Hjcq/xjdm1ai8emd0p36AkX1T4kttBL/bsuJBboQxrNIGu09tRt0sN4gxxbP/f75w6ePaZ43vy/PXY1p8tf50hQzonqhbIySezl3MjzPRiiGdaR2a1qs/mY6f4Yf9fLxT742Zu22f8PvDqTdLY2tCqfDGW7j7M8n1H2XzslHH9yvZNOfvXJSZ0WmBsu3317gvtN+R2OCNazqTzhGZ80L5y/Ou78g9OH76A4Vlf32938uvqA1T7uCx1Pn0XGztrDAYLvl9/gI/qlmDGop3cDg5/+kBPYWVlyZCetbHAggmzthrbz1+6zYjJm+jc6h0+bVYeg8HAyh//5PadCAxxsP7nI3hndME1rQOTv93OVx2q8U/gVWo1KkHPT2ZzL+IBt2++/AUHK2tLBoxvggUWTB22zth+4Z8bjB/4A5/2qkmrbu8Ra4hj3dI9BN8KwxAXx6YV+8mWKwPunmmZMGglfcY0YtfWE+zfdYpZK7swbdSGl47vyP5zdGw0nXQuDtRoUIz+4xrTrdksQoIjnr4xYGtnzedf1eX44YtkypL+pWJ5LVR+54UpqS8iIiIiIiIiYgZhd8IJu/MoaRoVGc3dW+FcvXDLpN+dm2Gkc3cyabO0ssTZxYE7N5NO+h/67W9alx9OWldHYmMNRITeZ+mBoVy9eCvJbR4XHnKP8JBHs4Kj7kdx90Yo549fpm7nGty8dAtDrIHga3dxeWL2v6WVJWndnLjzWF30Jx3ccpRPcnYhbXpnYmNiiQi5x/dBc9jx/fVniu/J8xcZHUNw+D3OXL/Nx2UKc/VuOLGPJbg9nB2Z364hf14I4qvVWxMb0uhW2D1sra1xtrczma2f3smBW2FJJ1SPXrpGh8qlsLGyIuT+A0LuP9rWYIjjwf0orp67YbLNneshpPNwNmmztLLE2dWRO9eTnuV9aPsJWhfpT1o3p/jzF3qfZYETuHb+ZrLH9lD43QjC70awYPhqFgxfzfg9Q9i47ThHT17mo7ol+Ovvqybn70VYWVkytGdtMnikpduXy42z9B/a+lsgW38LxDWdA5EPoomLg0a1ixJ0/S5h4ZHk8vPCL4s7S4pkw8rSglwF4svyTP5fB/43Z6exlv4Lx2dtSf/xTfHM5EKfNvOMs/Qf2rHxKDs2HsUlvSOR96KJI456Lcpy7fIdwkPvc+XCLTJn8+DqpWCiImMICY4g8t9j/CfwKoZYw0vF9+B+NFcvBXP1UjCBxy4zb113qtctyvffJn2XyePeqVkQr0yufN58znPV85fUT0l9EREREREREZFU7OSh8zincyCHvw9njl0GIKBMTiwsLQh8rA57UkLvxCehC5XJiYu7E3u3HH+peHIEZCU0ONxYr//knlM4uzqRs4gfpw/F19Uv/G6B+Pj2nX56fLfjZzMHvFMAF8+07Fl34KXiy5PRg5B7kUTHxhrbPNPGJ/RPXLnOwB9+fuoE4eNXrhMdE0up7JnZcvwMAFndXcnkmpbDF68+176f5uT+szi7OJKjkC9njsS/ngEV8sSfv8eeU5CU0H9n0xcqnwcXD2f2bjr8zPt+XHSMgZiYWKqUz8v1m6GcOvtsF1eS8jCh75PJlW6Dvic0LOlnGNz59+JRzcoFiIqO5cC/P9cDx67FztYGgAHtqnDu1DWq1y9Gz5ZzCLr0YneJGOP7N6HvnSU9fdrMJSzkfpJ9H9bMf69uUaIfxHBoT/zPxMkjl2jSrhLp3B6VZCpSKgcRYZFc/OdGomO9DAtLC2xsrZ65v529DXGGOJPnAqQqhpe76PFfpgflioiIiIiIiIiYgb2jPa5eLsav0Z0XcnDnSVw9nI1flpYWXDpznf3bT9JtdGNyFcpCvmLZ6DCsATvX/Unwv+V50nulY/a2fuQqlMU4ftWGJchT2JeMvul5p15R+s9oyeq5O7ly9lGy0SOTC375vPH0dsXSygK/fN745fPG3sEWewdbKtcvRr22lfAvmZ15/Zbi4pWOJv3rsXn+Nly9XLC0tORi4BX+2PQnn89uT+7iOchfJjedp7Rhx3e7uX31Tnx8mdyYd2ISuYvnMO67WstK5C2Zk4x+XlT+uDyDln/Bqkk/cvlU0KP4MruTvVBWPLO4Y2llSfZCWcleKCv2jvbYO9pTpVkFGnxei4IV8jHpp124OTnQ7p0SrDp4HHcnBywtLPBM68iCdg25ejeMcRt/xc0xDe5ODrg7ORj345nWkfWff4K/jxcA4Q+iWHngL3rXqkgJPx/yZfJk+Ifv8eeFII5ein9QaaU8fjQoVoAcXunJkj4djUsWpN07JVi65zAADrY2uDs5UCp7Zkplz8z1i7e5H/6AgAp5KFA6J66eaeNf31NX2b/1GN2/aUGuItnIVzIHHcd+xM5V+wn+tx57+owuzNk3jFxFsj16fT8qS55ifmTM6sG7jUoxYMFnrJ6+lctnHiXjPXzc8CuQGQ8fNywtLfErkBm/Apmxd7TD3tEOV8+0NO9Xh4LlcjPvf7/j6+PGx/VKMO9/v+OSNg2Wlhbx58fdmRxZPfDySIuVpSU5snqQI6sHaextjPtaMqUV5UvGv75WVpYM612H3Dm8GDrxRywtLXBzccDNxQFr60fpyPo1CpPLz5PMmVypVyOAz9tVZtaSXwm/94A09jZERkYTEnqPkNB7fNV5MX/s/BuA0Lv3sLSwMMbnkSEdfrkz4pHRBUsrS/xyZ8Qvd0bs09ga9zVnXXfKvJsvPj5rSwZ+/RG58mdiTN/lWFpa4preCdf0TlhbP0qa125aihx5M+Htm57aTUrSsf/7zP/mZyLCIrFPY8u5v69y5cIt+o9rwtLZO4iKiqZllypsWXcIp8fOX3x8GfDImO7f+DLglzuDaXxrulLm3bwA2KWxoWWXKuTx98EzYzpy5M3E50Pq4u7pzG+PXZR72riH9vyDU1p7OvV/H3m7WMSl2ks1IiLmV9WyoblDEBERERGRt1TzLxvS4stGyfb5pMxQblwOximdAx2HNaBklfzEGeL4fdNRZny5ksh78aU+PH3cWLh7ML0bTeXY3vhZxK36vk+VD0vg7OLA9cvBbFyym9Vzd5iM/8WEj6jasMSTu6V3o6kULJ2DZp9XTza+Ztk6cv3CTZxdneg8pQ2lahclzhDHb6v2Mq3rfCIj4mdne/l6sOTcdHq88yVHd54AoM2oj3nvk0o4uzlx/fwNNszawsqJG0zG7/VtJ95rWSnBfnu88yWFKuV/6vmrOmYeJfx8GNGwWqLr8/ebCEAml7Rs6dOGlrNXsP9c/N0QttZW9K5ZgZqF8mBjbcXvp84zfO02boXHzyovl8uX7tXKkSW9CxbAxdt3+W7fUX7Yf4y4OOhYuRSdqpRONr5PCvbh+qXbOLk40mncR5SsVoi4OAO71h1iRt//EflvORivzOlZeHQMvd8fx9Hf4xPbrb5sQNWmZXB2deT6xVtsnL+TVdO3mJ6naa2o+lHZBPvt/f44CpbLTbO+dZKNr+Gns7l2M5T+XapT490CCdZ3Gfg9h49fAuC31T0ZOXkTm7YfJ4NHWlbM/jTRMR/fZkDXGpQu5kcaexsuXg7mu7UH2Pzvz0erxmVo3aRMsvF9Um0c14Pu0mN4A6p+UCThcbaay9ED5wD46dgIJgz8gS1r/8QrkwsLN/dKdMzHt+k54kNKVMiNvYMtl8/dZOWCXfzy73MmmnV4l2YdKycfX40J8fENrZd4fG3mcfTA+fj4jgxjwqBVbFn3Jza21vQd3ZDc/j6kdXEg7O49Th2/wv/m7OTU8SvG7Z9l3MKlstPss3fIX9g32VjNoUaGjim+z03Xpqf4Pl8HJfVFRJKhpL6IiIiIiKQUax9vc4eQrJjLV57eyYyC+iSfADa3zDNfruzR6xZRKY+5Q0iW45k75g4heZapuyDKT0eGmTuEBJTUf3GqqS8iIiIiIiIiIiIiKUtzzV9Y6r6EJCIiIiIiIiIiIiIiRpqpLyIiIiIiIiIiIiIpy6CZ+i9KM/VFRERERERERERERN4QSuqLiIiIiIiIiIiIiLwhVH5HRERERERERERERFJUXJzB3CG8sZTUFxEREREREZH/BGsfb3OHkKyYy1fMHcIbLdOY3eYOIVmx5g7gKezX7jN3CMlK7edPJCUpqS8iIiIiIiIiIiIiKUsPyn1hqqkvIiIiIiIiIiIiIvKG0Ex9EREREREREREREUlZcZqp/6I0U19ERERERERERERE5A2hmfoiIiIiIiIiIiIikrIMBnNH8MbSTH0RERERERERERERkTeEZuqLiIiIiIiIyH+GjZ01XUY2Ioe/D1lyeLHvlxMMazcv2W38S+Vg7PLOia7r9v4ETh29BEDWPBnpNPxDchXMQkhwOOsW/MYPM7eZ9C9XqxAtetTEy8eNK+dvMn/UevZvP/lqDk5ERP4TlNQXERERERERkf8MS0tLoiKjWTf/V8rWKPRM25w8eI6Pig4yaWvesyYBZXMaE/oOTnaMWNKBw7tOMaX/CrLlzkj38U2JCL3PpmV7AMhbNCt9p7Rg/pgN/PHLCSp9UIRBc9rQpeZ4Lpy69moPVEQktdODcl+YkvoiIiIiIiIi8p/x4H4UUwesACBfMT8c06Z56jYx0bHcuRlmXLaytqR01QKsW/Cbse2dusWwsbViYq//ERMdy8VT1/DL7029tpWMSf0PWlfkwM5AVs7aDsDiCZsoUj43tVuWZ2r/Fa/yMEVE5C2mmvoiIiIiIiIiIs+hVNUCOLs6smX5PmNbnqJZObbvLDHRsca2gzsDyZzDC6d08RcO8hbJyuFdp0zGOvhrIHmLZE2RuEVEUpM4gyHFv94WSuqLiIiIiIiIiDyHao1LcWhnILeuhRjb3DycuXsrzKTfw2VXj7T//utsMuMf4M7NMON6ERGRZ6GkvoiIiIiIiIjIM3LPkI4iFfOw+fu95g5FROTNFheX8l9vCSX1RURERERERESeUdVGJQm7E8HeLX+ZtAffDMPF3dmk7eHynZuh//4bhquHaZ/42fuhrzFiERF52yipL/Kvy5cvkzt3bk6ePJlkn1WrVlGsWLEUjEpERERERERSk6qNSvDLyv3ExpjWZg48eB7/kn5YWT9KtRQun5tLZ64THnIfgJOHzhNQNqfJdoXL5ebkofOvPW4RkVTHEJfyX28JJfVFnkPNmjXZvHmzucMgKiqKDz744KkXIVKjs2fP0rx5c8qUKYO/vz+VK1dm4sSJREdHv9L93LlzhzZt2lCuXDkKFChAxYoVGTp0KOHh4a90PyIiIiIi8ubJktMLv3zeOLs44Ohsj18+b/zyeRvX5yqUhdnb+pHeK53JdgFlc5Ixizs/fZew9M72tQeJjoql+7imZMmVgQq1C1O3dQVWz91h7LP2250UrZiX+u0q4ZPdk48/r07OgplZv+C313asIiLy9rE2dwAibxJ7e3vs7e2TXB8VFYWtre1rj2Ps2LF4enoSGBj42vf1qtnY2FC3bl3y58+Ps7MzgYGBDBo0iLi4OL744otXth9LS0sqV65M9+7dcXNz4+LFiwwZMoSQkBAmTJjwyvYjIiIiIiJvnqEL2uOV2c24PO2nXgDUyNIdALs0tmTO4YWVjZXJdu81LsXxA2e5/M+NBGPeC4tkQLMZdBr+IVM29CD0TgTLvvmZTcv2GPucPHieMV0X8UnPWrTs/T5Xzt9kWLt5XDh17TUcpYhIKhdneHofSZRFXNxb9IQAkWdgMBiYN28ey5cv5+rVq7i7u9O4cWNq165N5cqVmTJlCosXL+bo0aP4+voyZMgQChcuDMSX3xk5ciQHDhwAYMqUKWzdupVmzZoxY8YMgoKCCAwMpHnz5uTMGX9L5dq1a7G2tqZp06Z069YNCwuLBDGFh4dTpkwZpkyZQsWKFY3tW7ZsoXfv3uzevZs0adIAsHPnTkaPHs2UKVOoVasWa9asIW/evEkeb9++fQkNDWX69OnGthEjRhAYGMjixYsBnjteiC9XVLlyZZP9h4aGUrx4cRYtWkTJkiWf7QUBRo0axbFjx1i2bFmSfZJ63Tp06PDM+1m0aBHz5s1j586dz7xNVcuGz9xXRERERERSN2sf76d3MqOYy1fMHYKIvKW2GFaYO4QEqtl/nOL73By5NMX3+Tqo/I7850yYMIE5c+bQsWNHNm7cyPjx43F3dzeunzhxIm3atGHNmjVkzZqVHj16EBMTk+R4Fy9eZPPmzUydOpU1a9YY21evXo2VlRUrVqxgwIABLFiwgBUrEn8DdXJyolKlSmzYsMGkff369VSpUsWY0L916xaDBg1i7Nixyd4x8CKeJ95X6cKFC/z2228UL1482X5Pe92e5vr162zZsuWp+xEREREREREREUnNVH5H/lPCw8NZtGgRgwcPpl69egBkyZKFYsWKcfnyZQBat25NpUqVAOjatSu1atXiwoULZM+ePdExo6OjGTt2LG5ubibtGTNmpH///lhYWODn58epU6dYsGABjRo1SnScOnXq0KtXL+7fv0+aNGkIDw9nx44dTJ06FYC4uDj69u1LkyZN8Pf3N8b7qjxvvC+rSZMmHD9+nKioKBo3bky3bt2S7Jvc6/Y0X3zxBb/88guRkZG88847jBgx4pUdg4iIiIiIiIiIvJi4t+jBtSlNM/XlP+Xs2bNERUVRqlSpJPvkzp3b+L2HhwcAwcHBSfbPlClTgoQ+QKFChUxK1wQEBHDhwgViY2OZOXMmhQsXNn4FBQVRoUIFbGxs2LZtGwCbN2/GycmJMmXKALB48WIiIiJo3759krE8PubgwYOT7JeY5433WdSqVcu4Tdu2bU3WTZw4kdWrVzNhwgR27NjBvHnzADhw4IDJvtatW/fU161t27bG/rVq1TJZ169fP1atWsX06dO5dOkSo0aNep7TIiIiIiIiIiIikqpopr78p9jZ2T21j42NjfH7h0lugyHpB3c8LI3zPJo0aUKNGjWMy56enlhbW1OtWjXWr19PrVq12LBhAzVr1sTaOv6/6d69ezl8+DD+/v4mYzVo0IDatWszZswYk/I/Tk5OxmN48tEZyZUTetZ4b9yIfzDU42M/Oe7s2bONbU+WC8qYMSMAOXLkIDY2lsGDB9O6dWsKFChgchzp06fnypXk60qOGDGCyMhIAOP5esjDwwMPDw+yZ89OunTp+Pjjj+nYsSOenp7PcugiIiIiIiIiIvI66EG5L0xJfflPyZo1K/b29uzdu5fMmTO/1n0dPXrUZPnIkSP4+vpiZWWFi4sLLi4uCbapXbs2rVu35vTp0+zdu5fu3bsb1w0cONBk+caNG7Rp04aJEydSqFAhAHx9fROM6ebmxunTp03aTp48aXLx4kXifXh3ws2bN03GfZy397M9hCouLo6YmBgMBgP29vYJjuNpr5uXl9cz7wcgKirqmfqLiIiIiIiIiIikNkrqy3+KnZ0d7dq1Y9y4cdjY2FCkSBGCg4M5ffo0pUuXfqX7CgoKYtSoUTRu3JgTJ06wZMkS+vTpk+w2xYsXx93dnZ49e+Lj42NM1kN8mZ/HOTg4APG15TNkyJDkmKVKlWLevHmsWbOGgIAA1q1bx+nTp8mXL99LxWtvb09AQACzZ8/Gx8eH27dvM2nSpGSPD2DdunVYW1uTO3dubG1tOXbsGBMmTKBGjRoJLjQ8lNzr1rBhw0S32blzJ7du3cLf3x8HBwfOnDnD2LFjKVKkCD4+Pk+NU0RERERE/luadK5K8Xfz4Zffm5ioWBr693vqNh9/Xp2KtQvjkcmF6OhYzhy7xMKxG/n78AVjny/ntcUvnzcu6Z0ID73Hn7tO8e2o9QRfDzX2yZonI52Gf0iugpm5ezOUtVM3sXzcutdynCIiqYVq6r84JfXlP6djx45YWVkxefJkbty4gYeHB02aNHnl+6lbty6RkZE0bNgQKysrWrRoQePGjZPdxsLCglq1ajF37lw6der0SuIoX748HTt2ZNy4cTx48IAGDRpQt25dTp069dLxjhw5kgEDBlC/fn2yZctGr169aN26dbLbWFtbM3fuXM6dOwfEX6xo1qwZLVu2THa7533d7OzsWLFiBaNGjSIqKoqMGTNStWpVPv3002T3IyIiIiIib68x33dmy4o/2PrDHwnWWdta8duPhzl56DzVGif9HLbHXTl7g+mDV3Lt4m1s7W2o16YiI5Z8RpsKwwkJjgDgyO7TfD91C8E3QkmfIR1tB3zAgBmt6FH/GwAcnOwYsaQDh3edYlLrqWTzz0KPeR0Jv3uPjXO2vrqDFxGR57Z06VLmzZvHzZs3yZMnD4MGDaJgwYJJ9t+0aRPffPMNV65cIWvWrPTs2ZOKFSu+8rgs4p4sti0iL6158+bkyZOHAQMGmDuUZ/KmxZuSqlomfieAiIiIiIi8eSb8PirJpP5DVT4sQfsv6z3TTP0nOTjZsfLEGPo1ncbh308n2qdk1fwMntOGOjl6EhtjoFazsnzSuyYfFR1M5LmLALQZ9TFlPihOm3zdnzsGEZHEbDGsMHcICZgj5/I852Hjxo307t2bIUOGUKhQIRYuXMhPP/3ETz/9RPr06RP0P3ToEM2aNeOLL77gnXfeYf369cydO5dVq1aRK1euV3kYWL7S0URERERERERE/oOsbayo8VEZwkPuc/ZEUKJ9nNI58E7dYpw8eJ7YmPgHROYpmpVj+84SEx1r7Hdg82Gy5PHGycUxRWIXEfmviIqKIjw83OQrqWcvzp8/n0aNGtGgQQNy5MjBkCFDsLe3Z+XKlYn2X7RoEeXLl6dt27Zkz56d7t27ky9fPpYsWfLKj0Pld0RERERERETkrdS0Xz2a9qtvXLZNY0uewr50HNbA2Na+8ihuBt194X2UqJyPvlM/wS6NDcE3Qhnw8XRC70SY9Gndrza1PymHvYMdJw+e58tWs43r3DycuXYp2KT/nesh8esyuBB+13QsEZG3hTnuHpgyZQpTp041aevcuTNdunQxaYuKiuL48eO0b9/e2GZpaUmZMmX4888/Ex378OHDCcpLlytXjq1bX30pNSX1RV6DxYsXmzuE5/KmxSsiIiIiIvIsNszcws7le4zL/Zb35PdNR/h901Fj2+3HHlj7Io7sPkOn6uNI5+ZI9aal6Te9Jd0/mEjI7XBjnx9mbmPzd3vx9HHl4+7V6TnxY75sNeel9isiIs+vffv2tGrVyqTN1tY2Qb87d+4QGxuboMxO+vTpOXv2bKJj37p1C3d39wT9b9269ZJRJ6SkvoiIiIiIiIi8lcLuhBN251FyPSoymru3wrl64dUlWB7cj+LqhVtcvXCLwD8vMHfnAKo1KcXyaY9mZobeiSD0TgRXzt3k0unrLP5jCHmKZCXw0HmCb4bh4u5sMqarVzoAgq/dfWVxiohIfAI/sST+m0Y19UVEREREREREXhFLSwtsbJOeQ2lhaQFg7BN48Dz+Jf2wsn6UoilatSAXA6+o9I6IiJm4urpiZWXF7du3Tdpv376dYDb+Q+7u7glm5SfX/2UoqS8iIiIiIiIibyV7R3tcvVyMX6M7L+TgzpO4ejgbvyz/TbJ7ZHLBL583nt6uWFpZ4JfPG7983tg7PJrROXtbP8pU8wfALo0tn/SuRZ7Cvnh6u5LD34fPxzUlvVc6fvvxMAC5A3yp/Uk547iFyuSkz9QWBJ2/SeChcwBsX3uQ6KhYuo9rim8+Hyo2KkPdrjVZOXFDyp4sERExsrW1JX/+/OzZ86iEm8FgYM+ePRQuXDjRbQICAti7d69J2+7duwkICHjl8an8joiIiIiIiIi8lRr2rE2LLxsl2+eTMkO5cTmY5j1qUrVhCWP7tJ96AdC70VSO7T0DQOYcXjg4pwHikzuZs3tS5cNWpHN1IvRuBKeOXKTXh5O5eOoaEF+ap0z1gjT7ogb2aWwJvhHKwZ2BjJq8kOioWADuhUUyoNkMOg3/kOkHxhByK4ylw35g45xX/2BFERF5dq1ataJPnz4UKFCAggULsnDhQu7fv0/9+vEPYO/duzdeXl706NEDgBYtWtC8eXO+/fZbKlasyMaNG/nrr78YOnToK4/NIi4uLu6Vjyoi8paoatnQ3CGIiIiIiMgrYu3jbe4QkhVz+Yq5QxCRt9QWwwpzh/BGWrJkCfPmzePmzZvkzZuXgQMHUqhQIQCaN2+Ot7c3o0ePNvbftGkTkyZN4sqVK2TNmpVevXpRsWLFVx6XkvoiIslQUl9ERERE5O2hpL6I/Fcpqf92UU19EREREREREREREZE3hJL6IiIiIiIiIiIiIiJvCCX1RURERERERERERETeEErqi4iIiIiIiIiIiIi8IZTUFxERERERERERERF5QyipLyIiIiIiIiIiIiLyhrA2dwAiIiIiIiIiIinBcDvY3CGIiIi8NM3UFxERERERERERERF5QyipLyIiIiIiIiIiIiLyhlBSX0RERERERERERETkDaGkvoiIiIiIiIiIiIjIG0JJfRERERERERERERGRN4SS+iIiIiIiIiIiIiIibwhrcwcgIiIiIiIiIpKSshXITOevW5CraDZCboWxduYWVkzcmOw2myMWJWgb+ck0dv6wz7j8TuPSNPq8FpmyexERep8DPx9lzoDvCAsOB8A3rzctBtYnR+GsZPD1YGbvpayetvnVHpyIiLz1lNQXERERERERkf8MB2d7Rq7rxZ/bjzO52wKy5vfhixltCb97j03zdyS77fj2szmw5ZhxOfzuPeP3+UrlpNec9szqs5S9G//EPZMbXSe3pPvU1gz7aDIAdmlsuXr+Jr+u/oP2Yz5+LccnIiJvPyX1RUREREREROQ/493GZbCxsebrz+YSEx3LhZNXyF7QlwZdqj81qR9+9x53rockui5fyRxcv3CTtTO2AHD9wi1+nLedRl/UMvY5degcpw6dA6D10Eav5oBEROQ/RzX1RUREREREROQ/I2/JHBz7/W9iomONbQe3HiNz7kw4uTgku23niS1YfmEak3d+yXstKpisO7HvDB4+6SlerSAALp5pKV+3OPs3H3n1ByEiIv9pmqkvIiIiIiIiIv8Zrl7puHb+pknbnRsh/65zMSmp87iFQ1dyeOcJHtyPomjlAnSZ2II0jnbGmfkn9p5mTOsZ9F/YCVt7G6xtrNnz4yGmfp6wFr+IiMjLUFJfREREREREROQplo1Za/z+nyMXsHewo2H3msakfpY8megwrhlLR6/l4NZjuGVwoe2IxnSd3JKJHeeZK2wREXkLqfyOiIiIiIiIiPxn3LkegqtnOpO2h8t3rt995nEC9/+Dh096bGzj50s27lmb43tO88OkjZz76xIHtx5javdFVP+kIm4Z0j1lNBERkWenpL6kCpcvXyZ37tycPHkyyT6rVq2iWLFiKRiViIiIiIiIvG1O7juDf9ncWFlbGduKvJufS38HJVl6JzHZC2YhLDic6KgYAOzT2BJniDPpY4g1/PudxUvHLSIi8pCS+vLGqFmzJps3bzZ3GERFRfHBBx889SJEanT27FmaN29OmTJl8Pf3p3LlykycOJHo6Ohn2r5v37507Njxlcf1vONevnyZ/v378+6771KwYEGqVKnC5MmTiYqKMumTO3fuBF+HDx9+5fGLiIiIiMibY9vyPURHx/DFjDb45vWmYoOS1O1YjZVTfjL2KVO7KHMPjTYul6wRQPVPKuKbz5tMfp683/ZdmvSqw9qZW4x99m76k7IfFOX9tu+SIasH+UrlpMP4ZgTu/4fga3cBsLaxwq9gFvwKZsHG1pr0mVzxK5iFTH6eKXb8IiLy5lNNfXlj2NvbY29vn+T6qKgobG1tX3scY8eOxdPTk8DAwNe+r1fNxsaGunXrkj9/fpydnQkMDGTQoEHExcXxxRdfmDu8Z3b27Fni4uIYOnQovr6+nDp1ikGDBnH//n369Olj0nfBggXkyJHDuOzi4pLC0YqIiIiISGpyL/Q+/euMo/PXLZi6awght8NZOnoNm+bvMPZxTJeGzLkzGZdjY2Kp3b4K7cd8hIWFBUFnrzOr7zKTbbYs2UUapzTUaV+FdqOaEhFyj8M7TzBv4HJjn/QZXZmxZ7hxuWH3mjTsXpMjv56kd41Rr/W4RUTk7WERFxcX9/RuIq+GwWBg3rx5LF++nKtXr+Lu7k7jxo2pXbs2lStXZsqUKSxevJijR4/i6+vLkCFDKFy4MBBffmfkyJEcOHAAgClTprB161aaNWvGjBkzCAoKIjAwkObNm5MzZ04A1q5di7W1NU2bNqVbt25YWCS85TE8PJwyZcowZcoUKlasaGzfsmULvXv3Zvfu3aRJkwaAnTt3Mnr0aKZMmUKtWrVYs2YNefPmTfJ4+/btS2hoKNOnTze2jRgxgsDAQBYvXgzw3PFC/Cz0ypUrm+w/NDSU4sWLs2jRIkqWLPlsLwgwatQojh07xrJly5LtN2XKFKZOnWrS9nBfV69eZfTo0fz+++9YWlpStGhRBgwYgI+PD//88w/169dn+PDh1K5dG4CNGzfSt29fVq1axaZNm5Ic93nMnTuX//3vf/zyyy9A4ufoRVS1bPjC24qIiIiISOpi+e/fdqmV4f59c4cgIm+pLYYV5g5BXiGV35EUNWHCBObMmUPHjh3ZuHEj48ePx93d3bh+4sSJtGnThjVr1pA1a1Z69OhBTExMkuNdvHiRzZs3M3XqVNasWWNsX716NVZWVqxYsYIBAwawYMECVqxI/M3LycmJSpUqsWHDBpP29evXU6VKFWNC/9atWwwaNIixY8cme8fAi3ieeF+lCxcu8Ntvv1G8ePGn9m3dujU1atSgfPny7Nq1i127dlG4cGGio6Np06YNjo6OLF26lP/97384ODjQtm1boqKiyJ49O71792bIkCEEBQVx7do1vvrqK3r27EmOHDmSHPd5hYWFkS5dwodPdejQgdKlS9O0aVNjwl9ERERERERERORNpfI7kmLCw8NZtGgRgwcPpl69egBkyZKFYsWKcfnyZSA+cVypUiUAunbtSq1atbhw4QLZs2dPdMzo6GjGjh2Lm5ubSXvGjBnp378/FhYW+Pn5cerUKRYsWECjRo0SHadOnTr06tWL+/fvkyZNGsLDw9mxY4dxBnlcXBx9+/alSZMm+Pv7G+N9VZ433pfVpEkTjh8/TlRUFI0bN6Zbt25P3cbR0RF7e3uioqLw8PAwtq9duxaDwcCIESOMdxaMGjWK4sWL88cff1CuXDk+/vhjfv31V3r16oWNjQ3+/v40b9482XGfx4ULF1iyZIlJ6R0HBwf69u1LkSJFsLCw4Oeff6ZTp05MmzaNypUrv9B+REREREREREREzE1JfUkxZ8+eJSoqilKlSiXZJ3fu3MbvHyZ4g4ODk0zqZ8qUKUFCH6BQoUImpWsCAgKYP38+sbGxzJkzh1mzZhnX/fjjj1SoUAEbGxu2bdtGrVq12Lx5M05OTpQpUwaAxYsXExERQfv27ZOM/fHZ5bVr12bo0KFJ9n3ZeJ9FrVq1CAoKAqBo0aLMnTvXuG7ixIlEREQQGBjI2LFjmTdvHu3atXvmeB8XGBjIxYsXKVKkiEn7gwcPuHjxonF55MiRVKtWDUtLSzZs2JBkaaHndf36ddq2bUv16tVNLoK4ubnRqlUr43LBggW5ceMG8+bNU1JfRERERERERETeWErqS4qxs7N7ah8bGxvj9w+TvgaDIcn+aV6gHmKTJk2oUaOGcdnT0xNra2uqVavG+vXrqVWrFhs2bKBmzZpYW8f/F9m7dy+HDx/G39/fZKwGDRpQu3ZtxowZY1L+x8nJyXgMTz62IrlyQs8a740bNwBMxn5y3NmzZxvbniwXlDFjRgBy5MhBbGwsgwcPpnXr1lhZWT1XbAD37t0jf/78jB8/PsG6xy+4BAYGcv/+fSwsLLh58yaenp7Pva8nXb9+nRYtWlC4cGGGDRv21P6FChVi9+7dL71fERERERERERERc1FSX1JM1qxZsbe3Z+/evWTOnPm17uvo0aMmy0eOHMHX1xcrKytcXFxwcXFJsE3t2rVp3bo1p0+fZu/evXTv3t24buDAgSbLN27coE2bNkycOJFChQoB4Ovrm2BMNzc3Tp8+bdJ28uRJk4sXLxLvw2T5zZs3TcZ9nLe3d4J4EhMXF0dMTAwGg+GpSX0bG5sEF1ny58/Ppk2bSJ8+vfFixpPu3r1L3759+eyzz7h58yY9e/Zk9erVxosNiY37NA8T+vnz52fUqFFYWj79ESEnT5584RI/IiIiIiIiIiIiqYGS+pJi7OzsaNeuHePGjcPGxoYiRYoQHBzM6dOnKV269CvdV1BQEKNGjaJx48acOHEiQb31xBQvXhx3d3d69uyJj4+PMVkP8WV+Hufg4ADEPxMgQ4YMSY5ZqlQp5s2bx5o1awgICGDdunWcPn2afPnyvVS89vb2BAQEMHv2bHx8fLh9+zaTJk1K9vgA1q1bh7W1Nblz58bW1pZjx44xYcIEatSokeBCQ2K8vb3ZtWsXZ8+excXFBWdnZ2rXrs28efPo0KED3bp1w8vLi6CgILZs2ULbtm3JkCEDX375JRkzZqRDhw5ERUVRr149xowZw5dffpnkuMnFc/36dZo3b06mTJno06cPwcHBxnUPk/arV6/GxsaGvHnzArBlyxZWrlzJ8OHDn3qcIiIiIiLy39O0V21KVA/Ar2AWYqJiaODd4anbNOtfj0oflsTDJz3RUTGcOXye+V+t4O8DZ419nF0d6TihOSVrFCbOYGDX2gPM6LWEyIgHxjGaD6iXYOz7EZHUcW7+6g5QRETeGkrqS4rq2LEjVlZWTJ48mRs3buDh4UGTJk1e+X7q1q1LZGQkDRs2xMrKihYtWtC4ceNkt7GwsKBWrVrMnTuXTp06vZI4ypcvT8eOHRk3bhwPHjygQYMG1K1bl1OnTr10vCNHjmTAgAHUr1+fbNmy0atXL1q3bp3sNtbW1sydO5dz584B8RcrmjVrRsuWLZ/peBo1asQff/xBgwYNuHfvHosWLaJkyZIsWbKE8ePH07lzZyIiIvDy8qJ06dI4OTmxZs0afv31V1avXo21tTXW1taMGzeOjz76iEqVKlGxYsUkx03K77//zoULF7hw4QIVKlQwWff3338bv58+fTpBQUFYWVnh5+fHxIkTqV69+jMdq4iIiIiIvH3GburHlqW/sWXJrgTrrG2t+XX1H5z84wzVWlRIZOuErpy5xrQei7l67gZ2aWyp17kao9b1plXBXoTcCgOgz7ef4ZbBhX61x2BtY02PmW3pPrU1o1vNAOCHbzby47xtABjuR8bHuXUwp/b/8yoOWURE3kIWcU8W/BZ5wzVv3pw8efIwYMAAc4fyTN60eP9rqlo2NHcIIiIiIiLyiozfMTTJpP5DVZuV47MxHz/TTP0nOTjbs/rabPrUGs3hHSfInDsTcw+NpnO5Lzn9Z/zkqmJV/Rm2qgcf5+xO8LW7Jtsb7t/Hr6Avsw6P5/MKg/hrV+BzxyAikpgthhXmDkFeoacXoRYRERERERERkWRZ21hRs/U7hN+N4OyxiwDkLZmDsDsRxoQ+wKFtx4kzxJGnePZEx6nRtjKX/g5SQl9ERJKk8jsiYlS4cOEk182ZM4dixYqlSBwzZ85k1qxZia4rWrQoc+fOTZE4RERERETkzda0Xz2a9qtvXLZNY0veEtnpNKGFsa1d0X7cvHz7hfdRsnoA/RZ2xM7BluBrd+lXeyyht8MBcPNMx92boSb9DbEGwu5E4OaVLsFYNnY2vPtReb4fs/qF4xERkbefkvry1lm8eLG5Q3guqSneNWvWJLnOy8srxeJo0qQJNWrUSHSdvb19isUhIiIiIiJvtg0zt7Bz+R7jcr9l3dm1dj+/rz1gbLt99c5L7ePwryfoWHogadM7U6NVJQYs7kzXSl8RcjPsuccqV68EDs72/Lxw50vFJCIibzcl9UXEyNfX19whAODi4oKLi4u5wxARERERkTdc2J1wwu6EG5cf3I/i7s1Qgs7eeGX7eHAviqCzNwg6e4PA/f/w7ZGxVP+kIt+P30DwjRBcPNKa9Le0ssTZ1ZHg6yEJxqrRpjJ7Nxzi7o2E60RERB5STX0RERERERERkVfEwtICG1sbAE7uO4OzqyM5ArIa1wdUyoeFpQWB+/8x2c7L151C7+Tnp29/SclwRUTkDaSZ+iIiIiIiIiLyVrJ3tCeN06MSnqNaTgfA9bF69iE3QzEY4vDwSY+zmyOePumxtLLEr2AWAIL+uU5kxAMA5h4azbdfrmD3+oPYOdjyUe867PnxT4Kv3SVtemfqtK+CeyZXflv9BwCX/g5i/89H6D6tNVO6LsDKxopOE1qw84d9BF+7axJrtRYVCb56l/2bDr/GMyIiIm8DJfVFRERERERE5K3UsGdtWnzZKNk+LfJ+wfWLt2gxqD7vNStvbJ+xZzgAvaqP5OhvgQBkzp0Jx3RpADDExuGTKxODPi5H2vTOhAWHc+rgOXpUHcGFk1eM44xpPZNOX7dg9I99iDPEsWvtAab3NH22moWFBe81K8fPC3dgMBheybGLiMjbyyIuLi7O3EGIiKRWVS0bmjsEERERERF5RSzTpDF3CMky3L9v7hBE5C21xbDC3CHIK6Sa+iIiIiIiIiIiIiIibwgl9UVERERERERERERE3hBK6ouIiIiIiIiIiIiIvCGU1BcREREREREREREReUMoqS8iIiIiIiIiIiIi8oZQUl9ERERERERERERE5A1hERcXF2fuIERERERERERERERE5Ok0U19ERERERERERERE5A2hpL6IiIiIiIiIiIiIyBtCSX0RERERERERERERkTeEkvoiIiIiIiIiIiIiIm8IJfVFRERERERERERERN4QSuqLiIiIiIiIiIiIiLwhlNQXEREREREREREREXlDKKkvIiIiIiIiIiIiIvKGUFJfREREREREREREROQNoaS+iIiIiIiIiIiIiMgbQkl9EREREREREREREZE3hJL6IiIiIiIiIiIiIiJvCGtzByAi8jY5f/48V69eJVOmTPj6+po7nGTdu3eP48ePU7x4cXOH8kZKLecvNjYWKysr4/LRo0cxGAzky5cPW1tbM0aWUHR0NFeuXCF9+vQ4OzubO5wELl26xMWLF/Hw8CBXrlzmDgeIfz3//PNPbt26BYC7uzuFCxemYMGCZo7szRMVFcW1a9fIkCFDqvu/If8dcXFxWFhYmDsMAGJiYjhz5gw3b94EwMPDg+zZs2NjY2PmyJKXWj5/nxQdHZ2qzt2Tvx8cOXKEqKgoAgICUkWcBoMBS8uEcwwNBgPXrl0jU6ZMZogqaXFxcRgMBpNzKpKSUtPnR1L0/vxsUvv7s7w5LOLi4uLMHYSIyJto1qxZFCxYkNKlSxMSEkK3bt3Yu3cvABYWFpQtW5avv/6atGnTmjnSxAUGBlKvXj1Onjxplv1HR0czceJEtmzZQrp06WjSpAkffvihcf2tW7coX7682eJ7GnOfvytXrtClSxcCAwMpU6YMkyZNokuXLuzZswcAHx8f5syZQ7Zs2cwS35w5c2jevDn29vbExsYyfvx4Fi9eTGxsLJaWltSpU4ehQ4ea7RfXr776il69euHo6EhkZCS9e/dmy5Ytxj+YihcvzowZM3B0dDRLfLdv36ZLly4cOnSITJkykT59emN7UFAQRYoUYcqUKcb21ObWrVt89913dO7c2Sz7X7VqFdmyZaNw4cI8ePCAIUOGsGbNGuLi4rC0tKRBgwYMHDjQ7Mn9RYsWJdpuYWGBnZ0dWbJkoXjx4imeRDp+/Dhp06Ylc+bMAKxZs4bvvvvOeNG6WbNm1KpVK0Vjeh7mfn+Oiopi4sSJHD16lIoVK/Lpp58yffp05syZA8C7777LkCFDcHJyMkt8BoOBb775hmXLlhEWFmayztnZmY8//piuXbsmmnBNDcz9+m7cuJEqVaoY3z+WLFnCvHnzuHbtGmnTpqV58+Zme+8DuHHjBt26dePIkSMUKVKEadOm0bt3b3bu3AmAr68vixcvxtPT0yzxhYeHM2DAALZv346TkxONGzemc+fOxvc5c//+FxMTw5QpUzh48CAlSpSga9euzJ07l6lTpxITE0OtWrUYNmyYWT8/goODWblyJYcPH05w0b9+/fq4ubmZLTZ9fryc1P758TTmPn96f5b/mtT5m5qIyBtg2bJlpEuXDoBx48YREhLCqlWrOHLkCKtXryYsLIwxY8aYOcrUa+bMmaxdu5YmTZpQtmxZRo8ezeDBg0366Lpz0saMGYOjoyPTpk3DycmJdu3aERMTw86dO/n111/x9fVl/PjxZovv66+/JiIiAoAFCxawcuVKhgwZwvr16xk1ahQ7d+5kwYIFZovv+++/JzIyEoDp06dz5MgR5s+fz59//smSJUu4evUqM2fONFt8Q4YMwWAwsHHjRrZt28aKFStYsWIF27ZtY+PGjRgMBoYMGWK2+J7m1q1bTJs2zWz7nzZtmjEhOWnSJPbu3cs333zDhg0b+Oabb9i3bx+TJk0yW3wPLViwgIkTJzJy5EimTZvGtGnTGDlyJF9//TXffPMNLVu2pHr16ly9ejVF4+rXrx+XLl0CYMWKFXz55ZcUKFCAzz77DH9/fwYOHMgPP/yQojE9L3N+fkyYMIENGzZQsGBB1qxZw5AhQ1ixYgVDhgxh2LBhHDt2zKw/f+PHj2f58uX06NGDrVu3cvjwYQ4fPszWrVvp2bMny5cvZ8KECWaLL7Xr0aOH8WLIypUrGTt2LPXq1WPmzJm0bNmSefPmsWLFCrPFN378eOLi4pg6dSoeHh60b9+e8PBwdu7cybZt23BzczPr59ukSZMIDAxk7NixfP7556xdu5aOHTsSFRVl7GPO/79Tp07lhx9+oECBAmzevJkvv/ySJUuWMHToUIYPH86ePXtYuHCh2eI7evQo1atXZ/HixTg7O1OsWDGKFSuGs7MzixcvpkaNGhw7dsxs8enz4+Wk9s+P1E7vz/Jfo/I7IiIvKDg42JjU3717N2PGjCFfvnwA5MmTh0GDBvHZZ5+ZLb4SJUokuz42NjaFIknc+vXrGT58OO+88w4A9evXp127dvTr14+RI0cCmPUW09R+/vbv38+3335L3rx5KVasGMWLF2fJkiV4eXkB8MUXX/Dpp5+aLb7H/yDasGEDPXr0oEGDBgDkyJEDgNmzZ9OuXTuzx7d9+3Z69epFqVKlAChatCh9+/Zl7Nix9OjRwyzx/fbbbyxduhQ/P78E6/z8/Bg4cCDNmzc3Q2TxAgMDk11/9uzZFIokcTdu3MDDwwOAbdu28dVXX1GhQgUAsmfPTrp06ejduze9e/c2Z5h88cUXfP/994wYMYIsWbIAcOHCBQYPHkzjxo0pUqQIn3/+OaNGjWLy5MkpFteFCxeMJeSWLVvGgAEDaNSokXG9v78/M2fONLm7KiU9bZZdWFiYWT8/Nm/ezJgxYyhTpgwfffQR7733HlOmTKFKlSoAuLq6MmjQIAYOHGiW+NauXcvYsWMpX768SbuPjw+NGzcmU6ZM9OnTh169epklvtT++fv458d3331H165dadu2LQAVK1YkXbp0LFu2jIYNG5olvt27dzN16lQCAgIoUqQIpUqVYv78+cbfD7p27cqgQYPMEhvAL7/8wujRoylZsiQAlStXpn379nTo0IEZM2YA5v39b8OGDcbfT5s2bUr16tWZMGECNWvWBMDW1pYZM2aY7feX4cOHU716dYYMGZLgPMXFxfHll18yfPhwvv/+e7PEp8+Pl5PaPz/0/vxyUvv7s7x5lNQXEXlBmTJl4vTp03h7e2NhYZGgPIKVlRX37983U3Txt282bdo0ydrgV65cMetM2uvXr5MzZ07j8sPbDVu0aEGvXr3Mlkx4KLWfvwcPHhhvvXV0dMTKysrkVlwnJyez/vzBoz/Kg4KCKFy4sMm6woULc/nyZXOEZfQwvps3b5I7d26TdXny5OHatWvmCAuITxqEh4cnuT4iIsKst/7XrVsXCwuLRGezPWw35x/FHh4eXLx4kUyZMnH//n1cXV1N1ru5uXH37l3zBPeYSZMmMWXKFGNCH+LfC/v06UOXLl345Zdf6NWrF127dk3RuOzt7blz5w7e3t5cv349wTMcChUqZNb/v9u3b6dMmTK4u7snut7cSYU7d+6QNWtWADJnzoyVlZXJc3Z8fX0JDg42U3Tx7x/J3drv4eGh31+e4uH726VLlyhXrpzJunLlypn1TrnQ0FBjgsjFxYU0adKY1Kf39fU1PkfBHIKDg03icXNzY/78+bRt25Z27doxfPhws8UG8ReF8+TJA8SfKxsbG5PfEfz9/bly5Yq5wiMwMJBRo0Yl+hlrYWHBJ598Qr169cwQWTx9fryc1P75offnl5Pa35/lzaOkvojIC2rUqBFjx44lW7ZsNGvWjLFjxzJ27FiyZMnCpUuXGDlyJGXLljVbfHny5CFDhgxJ/mIfGBho1l+63N3duXTpEj4+PsY2Ly8vFi1aRIsWLejXr5/ZYoPUf/5y5szJypUr6d69O6tXr8bFxYUff/zR+Ifohg0bjH8UmMvy5ctxcHDAxsaGkJAQk3XmTkpDfEI1TZo0WFpacuPGDZOLTHfv3iVNmjRmi61mzZr07duXfv36Ubp0aeMFm/DwcPbs2cOoUaN4//33zRZfunTp6NWrF6VLl050/ZkzZ8x6p1Lt2rWZNGkSs2fP5oMPPmDatGlMmDABR0dH7t+/z5QpUyhSpIjZ4nvo5s2bxMTEJGiPiYkx1kn29PQ0lrJKKRUqVOB///sfI0aMoHjx4vz000/G9xaATZs2mVyISGl+fn689957Sc60O3nyJDt27EjZoB6TMWNGDh8+TKZMmTh69CgQXzLj4XvM0aNHjX/Um0OJEiUYO3Ys48aNS1B7Ozg4mPHjxz91NubrlNo/fwF+/fVXnJ2dsbOzS3AB5MGDB2a9qJk+fXpu3rxJxowZAfj444+Nd5ZCfFLJnJ9vGTNm5OzZs8aa6xA/EWHevHm0adPGrPWuIf65EqGhocbzly9fPpNJE1FRUWZ9fd3d3Tl27BjZs2dPdP2xY8eSTFinBH1+vJzU/vmh9+eXk9rfn+XNo6S+iMgLatOmDVevXqVWrVpkzpyZK1euUK1aNaysrIiNjSVfvnx8/fXXZouvUqVKCR6A97h06dJRt27dlAvoCaVKlWL9+vUJkoIPE/vmLC0Cqf/8de7cmU6dOjF37lwsLS2ZN28eAwcOZO/evVhaWnLs2DGzzkTJlCkTy5cvB+JnnR8/fpzixYsb1+/bt89sD/EFKF68OOfOnQPiy7EEBQWZrN+5c6dJkj+l9evXD4PBwOeff05sbKzxgcLR0dFYWVnx4Ycf0qdPH7PFV6BAAW7cuIG3t3ei68PCwsxak7ZTp06cOnWKKlWqUKBAAQ4cOEDZsmXx8vLixo0buLi48O2335otvodKlixpLJXwsHzbiRMn+Oqrr4zloE6dOmVy8TMl9OzZk6ZNm9KsWTMKFCjA/Pnz+eOPP8iePTvnzp3j8OHDZv2jvUCBApw4cSLJ9ba2tsY/mM2hSZMm9O3blxUrVnD8+HH69OnDxIkTOXv2LJaWlvzvf/+jVatWZotvyJAhfPrpp5QvX55cuXKZPIj71KlTZM+enVmzZpktvtT++QvQt29f4/d79+41uRvt8OHDZk1a5smThz///NM4Q7pnz54m6w8ePJjg7rSUVK5cOVauXEnFihVN2h0dHZk7dy6tW7c2U2TxsmfPzokTJ4zn6LvvvjNZf+rUKZOZ0ymtTZs2DBo0iL/++ovSpUsbE/i3bt1iz549rFixwqyl5fT58XJS++eH3p9fTmp/f5Y3j0WcnkIoIvJS/vnnH7Zv386lS5eIi4vDw8ODIkWKUKZMGbPOBEjtrly5wtmzZxPU9H3o+vXr7N6926y3EKd2ly9f5vjx4+TPnx8fHx9u3brF0qVLiYyMpGLFisakYGp0+PBhbG1tjYnM1ObSpUvY2NiQIUMGs8YRHh7OsWPHuH37NhA/Q69AgQImswbNYcuWLdy7d48PPvgg0fUhISFs27bN7P9/f/3110Tfn99//30cHBzMGhvEz9Tv3bs3e/bswdo6fq5NbGwspUuXZuzYsbi7u7N3715iYmIS3EL+uoWGhjJ79mzj+TMYDHh6elK4cGFatmyJv79/isbzuKioKGJjY1P1bLb169dz+PBhChcuzPvvv8++ffuYPHky9+/f591336Vjx47Ghzmbg8Fg4LfffuPIkSPGu0Lc3d0JCAigXLlyZo3tTbd9+3asra2T/P3G3I4ePYq9vX2S5TNet5CQkAR3xz0uPDycEydOmO1ukXPnzmFtbW1yJ8Hj1q9fj5WVlbHGvjls3LiRBQsWcPz4cWO5GCsrK/Lnz0/Lli3NGhvo8+NlpfbPjzeZ3p/lbaOkvoiIyCvw6aefMnz48GTrFJvT7NmzadKkCWnTpjV3KCL/aeHh4Qkuypw9e9Z450i2bNkSfUCyvLjU/v538OBB/P39zV6S7E2V2j9/U7vUcP6uXbuGp6enEpXPKTo6mjt37gDxD1B9eFefvDr6/Hg5qeH95U2m8ydPo09NEZFX6NNPP+XGjRvmDsPozp077N271/hAyODgYGbPns3UqVP5559/zBscqT++57F//34ePHhg7jCSNHPmzAR17V+nb7/91uwPwn2a7du3880333Dw4EEA9uzZQ7t27WjTpg3ff/+9maODyMhIfvjhB/r160fbtm359NNPGTZsGHv27DF3aM+tSJEiXLp0yawxfPXVV2Z9uNxDxYsXN9550aJFC0JDQ/Hz86Ny5cpUrlxZCf3XIKXf/55Xu3btuH79eorv99KlS6xZs4bZs2czd+5cfv7552Qf0J1apbbP33v37rF//35zh/HMUsP5q1mzplkfPvs0qe33+4dsbGzw9PTE09NTCf3XRJ8fLyc1vL88Tu/P8rZRUl9E5BVKTR+8R48epWrVqrRs2ZL33nuPv/76i4YNG7Jy5UrWrl1L/fr1OX78uOL7j0jpG/PGjh3Le++9R6tWrdi4cSNRUVEpuv+n+e677+jcuTM7d+7k008/Ze3atXTq1AkvLy+8vb0ZOXIkCxcuNFt8Fy5coGbNmnz99dfs2bOHXbt2YWFhwbFjx2jTpg3dunVL9AGrqVVquDF03bp1Kf7A2cQ4ODgYL2T+8ccfb9Tr+NDFixdp0aKFucN4Zqnh5y85KR3fvXv36Nq1K1WrVqVv375MnDiRBQsW0L17d8qXL8/SpUtTNJ63zZv2/yM1SO3/R1PT7/dPk9p//lJ7fE9K7T+bqT2+1OZN+/kTeRo9KFdE5C01ceJEqlevTt++ffn+++/p1KkT5cuXZ/jw4UD8gzinT59utodVpfb45OUNHz6crVu30rt3bxwdHalTpw4NGzZMFXUiFy9ezJdffkmjRo3Yu3cvn376KX369OHjjz8GICAggLlz5/LJJ5+YJb7hw4dTrlw5hgwZgoWFBbNnz2b//v0sX76c8+fP07p1a2bMmEGXLl3MEt+bKLX84VumTBlatGhhnJHfqVOnJGdYLlq0KCVDe2Zv2kw3MTV69Ghu3rzJunXrsLOzY8KECWT+P3v3Hpfz/f8P/HGhnEpJB4mPnI3SYViYw5DmcClz2ExiktEIkyb6OEWkhqZ+DpmR+YQapdjM2BxHaZnN0BhlcshpJDpevz/6Xpfr6rpK1K7X883zfrvt9tH7um63Hp9X9X6/r9f79Xy+mjXD1KlTsXfvXixZsgQNGjSAXC4XHZUx9oKon5+p52OMMSnhSX3GGKtGNjY2qs0ORTt37hyCgoJgZGQELy8vhIeHY9SoUarXPT09MWXKFM7H/jW9e/fGe++9h7t372LXrl3YtWsXvv76a3Ts2BGjRo3CoEGDhG34+vfff6s2HnVxcUFJSQm6dOmier1r165YvHixkGxA6arAhIQE1Wbb48ePxxdffIH79+/D1tYWc+fORUhICE/qS1BYWBh2796NrKwspKamok2bNqhTp47oWBqe9zCBcqk/e77vv/8eGzduVD1gDQ4ORs+ePTF16lSMGDEC+fn5+PLLL3lSvxzP28BVuXEpq7zJkyfDxMREdIxyUbq/p35+pp6Pvdr4/MxeNzSuTIwxJmHZ2dmwtraGTCZDcnKy6rhCocCNGzfQpEkTIbkKCwtRu3ZtAKU9N+vUqYOGDRuqXm/YsKGqBYQI1POx6tOoUSP4+PjAx8cHp0+fRnx8PJYtW4Zly5YhPT1dSCZTU1NkZ2ejSZMmuHXrFoqKinDjxg3VJFd2drbQCQZjY2ONVjFPnz5FUVGRakV3u3btkJOTIyqeJIn6XSurTp06GD16NADg999/h7+/P7kN+EJCQmBhYVFuBUFhYaGeE7HqVFxcrPFAtV69eiguLsaTJ09Qt25d9OjRA6GhoQIT0lZQUIDRo0eXW3V2/fp1rjJ8QR9//LHoCBVSv78Xjfr5mXo+9mrj8zN73fCkPmOMVVG/fv1w7NgxNGrUSOP4gwcP0K9fP5w/f15IrsaNG+PatWto2rQpgNJ2NxYWFixPEMkAAQAASURBVKrXc3JyNCbR9Y16PlY1yhXmZXXu3BmdO3dGUFAQ9u3bp+dUz/Tr1w/z5s2Dh4cHDh06BA8PDyxfvhwymQwymQwrVqxAjx49hOXr0aMHli9fjoULF8LQ0BArV67EG2+8oZqIu3HjhtY5h7Lyfh/+bW+88YbO8/P9+/fRvXt3Yednpa1btwr9/uVp0qQJ/P39MWjQIJ2vnz9/Hu+9956eU7269P33YW9vj5iYGMyfPx9A6crahg0bwszMDEBpe4x69erpNZOUtG/fHo0bN8awYcN0vn7hwgWeNCrHsmXLKv3ewMDAfzHJ8z2vRYx6dZ8+UT8/U8/3qhF1f0UVn5/Z64Yn9RljrIoUCoXOG6q8vDzVSnQRBg8ejHv37qm+7tOnj8brhw4dQqdOnfSc6hnq+ZRSU1Ph5OSkVXZdVFSE9PR01Yc66qXjnTt31uvv4/P6lxsZGWm0W9I3f39/FBYWYt++fXByckJQUBC2bt0KX19fFBUVoUuXLpg1a5awfLNnz4avry8GDx4MmUwGa2trREZGql6/d+8evL29heV7UaL62Zf3fQsKCspdRahP06ZNg729PSZNmqRxPDo6Gr/99hu++OILIbns7Oxw7ty5cidlZDIZmT0KKkPf578Xpe+xnDVrFiZMmIDvv/8eBgYGyMnJ0ViZn56ejt69e+s1ky5Ur799+vTBo0ePyn3dxMQEHh4eestTHorj98cff2h9XVxcjBYtWgAArl69iho1aqBjx456yVORsWPHah1Tv98X9VCY+vmZer4XxdcP3SieXwA+P7PXj0whpTMqY4wRolxtFBMTg5EjR6Ju3bqq14qLi3H27FnUqFED27dvFxWxQk+ePEHNmjVhaGgoOopOVPJRX+kLlP6+HThwAJcvXwYAtGrVCv379yfT/1VK8vPzUVhYKKzXf1lXr15FQUEBWrZsSfLnGRkZCW9vb43zH1DaLmjjxo2YOnUqAOD06dPo1KmT3v6elT19ly1bhunTp2usOi4pKUFqaiquX7+OhIQEveQpj4uLC7Zs2YJ27dppHL948SI++ugjnDhxQkiuS5cu4cmTJ7C3t9f5emFhIW7fvg0bGxs9J9MkhfMzANy9exdXrlwBALRo0YJElc3t27fx008/oaCgAC4uLmjdurXoSFqk8vOlivr4ffXVVzh16hRCQ0NVk1b//PMPAgMD0blzZ0yYMEFovrITg4WFhTh//jwiIiIwc+ZMdOvWTUgu6udn6vmUqP99KFG8fgDSGT+qePxYdaH36ZAxxiRCudpIoVAgIyNDY9WnoaEh2rdvL/wDSVlpaWmwt7eHoaGh1iQcBRTzlVeJ8eDBAxIZ//zzT0yZMgV37txRrXTbuHEjVqxYgXXr1pXbU5IaZ2dnJCYmolmzZkJz1K5dW+eKLFH5bG1tK/U+UfmioqIwevRorb+FJ0+eICoqSjWp37lzZ73m2rx5M4DSv9/t27ejRo0aqtcMDAzQtGlTLFq0SK+ZdMnLy9NZMVCrVi3k5uYKSFTqeRO8BgYGGhMy6udufaJeiZGbm4tFixZh3759qs35atasiYEDB2LBggUwNjYWls3S0rLS1VKTJk3CkiVLYGlp+S+n0kT9+ltZPH66bdq0CZs2bdJYhWpiYoIZM2ZgwoQJwu+hdf199ujRAwYGBli+fDl27dolIBX98zP1fEp8/aga6ueXyuLzM5M6ntRnjLGXpOyFHBgYiHnz5pFZ2VsRHx8fEhOn5aGUTzkZKZPJMGfOHI0PG8XFxbh48SKcnJxExVMJCgpC69at8c0332isdJszZw7mz59PtlKkLOqFg5yv/O+r60PJhQsXhJYLHzp0CEBp+4TIyEiypctt27bFvn37VOcbpX379pFcOV0efZ+7lZUYMpkMcXFxOisxWrZsqZcsFQkKCsL58+exbt061fUiPT0dS5cuxfz587Fq1SrBCSsnNTUV+fn5evt+Urn+VhaPn265ubkabRiV7t27p7FRPDWNGjVSrZyWAkr31rrw9UM3qtcPqZxfKovPz0zqeFKfMcaqSH3Tr+TkZPTt25fsBnM8MVl5yhUwCoUC9evXR506dVSvGRgYwNHRESNHjhQVT+X8+fMaE/pA6Uq3mTNnYsSIEQKTsVdZly5dVJsKu7m5aUzsFxcXIy8vDx988IHAhKXUN6IVtRqwIr6+vpg2bRquXbsGFxcXAMDPP/+MvXv3IiIiQnC6ytP3uVsqlRg//fQTNm7cqFGp0rNnTyxZsgQTJ04UmIw2qVx/qZLK+Lm6uiIwMBBz5sxR7aH066+/YsWKFRgwYIDgdKUPp8u6ffs2oqOj0b59ewGJXg6le2td+PqhG9Xrh1TOL1Tx+LHqxpP6jDFWjebPnw8HBweyk/qs8pQPa2xsbDBhwgSyP1NbW1vcuXMHbdq00Th+9+5dNG/eXFAq9qqbO3cuFAoF5s6di2nTpmmUgStL66mtNKK4WrFv376IiorCunXrsH//ftSuXRvt2rXDV199ha5du4qOR5ZUKjFMTU11tkgwMjJCgwYNBCSSBqlcf6mSyvgtWrQIoaGhmDVrFoqKigCUthcZMWIEAgICBKcDPDw8dG7q6ujoiKVLlwpKxaqKrx9VI5XzC1U8fqy68aQ+Y4xVI+qrYRYvXkxmgyVdKOYbOHBguTdcR48eRc+ePfWcSNOsWbOwdOlSTJ06FY6OjgCAM2fOICoqCv7+/hp9uaXQIopJw7BhwwAATZs2hZOTE4n+s89D9fzcp08f9OnTR3QMSdq4caPOPTCA0hW1+u6RW9aUKVOwfPlyrFixAhYWFgCAnJwchIWFwdfXV2g2KaB+/aWO+vjVrVsXCxcuREBAALKysgAA//nPf8hMch08eFDj6xo1asDMzKzccw6TFr5+VA318wt1PH6sutR4/lsYY4y9KuRyOUpKSvDDDz/g8uXLouNooZjvvffew7Zt2zSOFRQUYPHixSRuqj/++GNcunQJM2bMwDvvvIN33nkHM2bMwJ9//onJkyejS5cu6Ny5M7p06SI6aoV09WWnhPPp9vfff+uc0C8qKsLnn38uIJF0LVy4UGd/aVa+YcOG4fz581rH9+/fj6FDhwpIpCk2NhZnzpzBO++8A1dXV7i6uuKdd97BL7/8gh07dmDYsGGq/5g26tdf6qQyfvXq1cOlS5dITegDpStplf/VrFkTVlZWPKH/CuHrR9VI5fxCFY8fqy68Up8xxqpRdHQ0rKysRMfQMH36dHTp0gWenp54+vQphg8fjuvXr0OhUGDlypVwc3PjfBVYtmwZFi1ahJ9++gnLli1DTk4OZs2ahZKSEq2bMRGUG35JHdVV1EqcT7clS5bgp59+QnBwsKqE/a+//oK/vz8ePHiAWbNmCcmlC8VKIHV79uyBt7c3zMzMREd5YaIeKnXt2hWjRo3CtGnTMGnSJOTl5WHx4sX49ttvMXPmTCGZ1PXv3190BEmjfv2lTkrjR7195aBBg8i1b6ssXpSgG18/qkZK5xeKePxYtVEwxhirssLCQsXx48cVsbGxikePHikUCoXi5s2bitzcXMHJFIru3bsrzp8/r1AoFIo9e/YoXF1dFXl5eYpt27Yp3N3dxYZT0M+nUCgUN27cUIwfP17RtWtXhb29vWL+/PmKvLw80bEkqaioSPHHH38oHjx4oHE8NTVVkZ+fLyjVM5zvxWRmZipGjRql6Nmzp+LYsWOKr7/+WuHg4KD49NNPFQ8fPtR7HilzdHRUZGVliY7xUkRm//HHHxU9evRQjB49WtG/f3/F0KFDFRcvXhSS5VW1bt06xT///CPke1O+/qakpCgKCwu1jhcWFipSUlJUX/P4PR/18x/1fBWhnp2vH9JF+fzC52f2uuCV+owxVkXXr1/HxIkTcePGDRQUFKBHjx4wMjJCdHS0qoxOpEePHqlW0B49ehQDBgxA3bp10adPH4SFhQnNBtDPp1RYWIiSkhKUlJTAwsKCVAn26dOnsX37dvz999+IiIiAlZUVEhIS0LRpU3Tu3FlotqVLl6Jt27YYOXIkiouL4enpifT0dNStWxfr1q3DW2+9BQDCcnK+qvnPf/6D2NhYhISEYOLEiahZsyaWL1+OIUOGCMlTVl5eHjZs2ICTJ0/i7t27KCkp0Xi9bM9kptvdu3dx5coVAECLFi20Kh7S09NFxAIA9OrVC66uroiNjUWtWrWwdu1atG3bVliesh4+fIj9+/cjKysL3t7eMDU1xblz52Bubi68sm/37t1o2LChak+HFStWYOfOnWjdujU+//xz2NjYACht8yYS1euvl5cXjh07pvX38OjRI3h5ealae/D4sX8T5fMzQDsfXz+qjur5hc/P7HXBPfUZY6yKli5dCjs7O6SkpGhciF1dXXHy5EmByUpZW1sjPT0deXl5OHr0KHr06AGg9EbR0NBQcDr6+fbu3Qu5XA4jIyPs378f69evx86dO/Hhhx/i2rVrouNh//798Pb2Rp06dXDu3DkUFBQAAHJzc7F+/XrB6UrztW/fHgDw448/4u+//8a3336LcePGYdWqVYLTcb7q8NNPP2Hv3r1wdHSEsbEx4uPjcevWLdGxAABBQUGIj4/Hm2++iTFjxsDLy0vjP0rS09PJtXbIzc3F7Nmz0atXL3h6esLT0xO9evWCv78/Hj16JDoesrKy8P777+Onn37Cl19+CW9vb0yZMgUrVqxAYWGh6Hi4cOEC3NzcEB0djU2bNqnG7Pvvvyex58S6detU9y3p6en43//+h9mzZ8PU1BTLli0TnI7+9VehUOhsHfLgwQPUrVtXQCJN1MdPHcX2leomT56sWoBCBfXzM/V8fP2oGurnFz4/s9eG6FIBxhiTuq5duyouX76sUCg0S0ivXbum6NSpk8hoCoVCofj6668VHTp0UHTu3Fkhl8sVxcXFCoVCoYiJiVF4enoKTkc/n4ODg2Lbtm0axx48eKDw8/NTODk5CUr1jLu7u2L37t0KhULz9+/cuXOK7t27C0xWys7OTnHjxg2FQqFQBAUFKZYsWaJQKBSKrKwsEuPH+armv//9r8LOzk7x5ZdfKkpKShS3b99WTJw4UdG1a1fF3r17RcdTvPnmm4rTp0+LjlGu9u3bK+7cuaN1/N69e4r27dsLSKRp+vTpigEDBiiOHDmiePTokeLRo0eKI0eOKNzc3BQzZswQHU/h6OiomDFjhkbpfFpamqJ///4k2reNGzdOERoaqlAoNM/PaWlpinfeeUdkNIVCoVB06tRJcf36dYVCoVCsWLFCMXv2bIVCoVBkZGQo3nrrLZHRFAoF3evvJ598ovjkk08U7du3V/j4+Ki+/uSTTxSTJ09WvPPOO4oJEyYIy6dEdfykqKSkRFFSUiI6hgbq52fq+fj6UTVUzy98fmavG26/wxhjVaQsmSvr5s2bqF+/voBEmsaMGQMHBwfcuHED3bt3R40apUVazZo1w4wZM8SGA/18u3btQsuWLTWOmZiYICIiAgkJCWJCqbly5YrO1ivGxsZ4+PChgESazM3NcenSJVhYWODo0aNYuHAhAODp06eoWbOm2HDgfFX1yy+/IC4uTlVNYGFhgejoaGzbtg3z5s3DoEGDhOZr0KABTE1NhWaoiKKcDY4LCgpgYGCg5zTafvrpJ2zcuFHjHNOzZ08sWbIEEydOFJis1IIFC+Dh4aFxzNnZGbt370ZISIiYUGp+++03nS34rKyskJOTIyCRpnr16uHBgwdo0qQJjh8/jvHjxwMAateujfz8fLHhQPf6a2xsDKD077d+/fqoU6eO6jUDAwM4Ojpi5MiRouKpUB0/ADh8+DC+//57mJiYYPjw4WjVqpXqtX/++QfTpk1DTEyMwISl4uLisGXLFly9ehUAYGtri3HjxpH4+VI/P1PPx9ePqqF6fuHzM3vd8KQ+Y4xVUY8ePbBlyxYEBwerjj1+/Bhr1qxB7969BSZ7xs7ODnZ2dkhLS4O9vT0MDQ1VPXQpoJyvZcuWKCoqQkpKCrKysjBkyBAYGRnh1q1bcHV1FR0P5ubmyMrKQtOmTTWOp6WlkWjl8d5772HGjBmwsLCATCZD9+7dAQC//vqr1s2sCJyvanbt2qWzTdaYMWPQrVs3AYk0TZ8+HREREQgNDSVRbq2knKySyWSIi4tDvXr1VK+VlJQgNTWVxM/X1NRU9QFZnZGRERo0aCAgkSblhExBQQH+/vtv/Oc//0GtWrVgZGREYlLG0NAQubm5WsevXr0KMzMzAYk0de/eHUFBQXjjjTdw9epV1T3Ln3/+qeqnLxLV66+yNZGNjQ0mTJig8fdLCdXxS0pKwmeffYaePXviypUr+Prrr7FkyRIMHToUQGmP6dTUVGH5lCIiIrB582Z4enrC0dERAHDmzBmEhIQgOzsb06dPF5qP+vmZej6+flQN1fMLn5/Z64Yn9RljrIrmzJkDb29vDBo0CAUFBfD398fVq1fRsGFDrFy5UnQ8DT4+PkhMTCQx2asLxXzUN0IeNWoUli5dipCQEMhkMty6dQvp6ekIDQ2Fr6+v0GwAMG3aNLRp0wY3b97Eu+++q5oArlmzJnx8fASn43xVZWhoiKysLHzzzTe4du0a5s2bh0aNGuHw4cNo0qSJkEweHh4afVQzMzPRvXt3NG3aFLVqad767t69W9/xAACbN28GULqSbPv27aoKJaB0JVnTpk2xaNEiIdnUTZkyBcuXL8eKFStgYWEBAMjJyUFYWBiJ88vTp0+xePFi1aq2/fv3o1mzZggODoaVlRUmTZokNF/fvn0RFRWF1atXq45lZ2cjPDwcAwYMEBfs/yxYsACrV6/GjRs38MUXX6Bhw4YAgHPnzmHw4MGC09G//g4cOLDcCaOjR4+iZ8+eek6kier4ffnll5gzZ45qX5N9+/Zh3rx5yM/PJ7GCVik2NhbBwcEaG7/369cP7dq1Q3BwsPBJfernZ+r5+PpRNVTPL0p8fmavC57UZ4yxKmrcuDESExOxd+9eXLx4EXl5eRgxYgTkcrlGyR8F5bV6oIJiPuVGyImJiXjrrbdUx11dXfHf//5XYLJSkyZNQklJCcaPH48nT57A09MThoaGmDBhAsaOHSs6HgDg3Xff1To2bNgwja/lcjk2bNgAa2trfcVS4XwvLyUlBT4+PnB2dkZqaipmzpyJRo0a4eLFi/jmm2/wxRdf6DUPAPTv31/v3/NFHTp0CAAwduxYREZGktuAUSk2NhaZmZl45513VL9bN27cgIGBAe7du4cdO3ao3iviAUl4eDguXLiAmJgYjYdc3bp1Q2RkpPBJmTlz5sDPzw/du3dHfn4+xo4dizt37sDR0REzZ84Umg0obU81f/58reN+fn4aXy9cuBB+fn56Xx1K/fr73nvvISAgAGPGjFEdKygowPLlyxEXF4fffvtNYDq646c8pygNGjQIZmZmmDJlCoqKisisUi0qKoKdnZ3W8Y4dO6K4uFhAIk3Uz8/U8/H1o2qonl+U+PzMXhc8qc8YY9WgVq1acHd3Fx2D/QvS0tIQGxur1WLExsYGt27dEpTqGZlMhilTpsDb2xtZWVnIy8tDq1atSOzn8CL+/vtvFBUViY5RLs6n2+eff44ZM2bgo48+gpOTk+q4i4sLvv76a73nAYCpU6cK+b4vY+vWrRpfFxcXIyMjA02aNCEx0U/9AcnBgwexatUqVWsMpTZt2iArK0tMKDXGxsb46quvkJaWhgsXLiAvLw8dO3ZUtdGSij179sDb21vvk/rUr7/Lli3DokWL8NNPP2HZsmXIycnBrFmzUFJSgm3btomOR3b86tevj7t372pUZbq4uGD9+vX4+OOPcfPmTWHZ1Lm7uyM2NhaBgYEax3fu3Am5XC4o1TPUz8/U8/H1o2qonl+U+PzMXhc8qc8YY9Xg6tWrOHXqFO7evau1aS6lCabFixejUaNGomOUi2I+6hshBwYGYt68eTAyMkLr1q1Vx/Py8hAcHKzqLcnYvyEjIwPh4eFax83MzHD//n0BiconarVxRZYuXYq2bdti5MiRKC4uxpgxY3DmzBnUrVsX69at01i9JQKl65cu9+7d03nNePLkiUYLJlESEhIwaNAgvPnmm3jzzTdVxwsKCrBv3z6tTRqpElVFR/36O2jQIDg7OyMwMBCDBw/GkydPMGzYMMyZM4fEHh5Ux69Tp044cuSI1mRq165dsW7dOkyePFlMMB3i4+Nx/PhxODg4AADOnj2L7OxseHh4aNxflZ341wfq52fq+fj6UTVUzy9KfH5mr4saz38LY4yxiuzcuRODBg3CF198gf379+OHH35Q/Xfw4EHR8TTI5XKyGwYBNPMpN0JWR2kj5ISEBOTn52sdf/r0KRITEwUkYq8TY2Nj5OTkaB0/f/48rKysBCQq3549e/D48WPRMTR89913aN++PQDgxx9/xPXr1/Htt99i3LhxWLVqleB0pR4+fIi4uDh8/vnnePDgAYDSnusUVpLZ2dnhp59+0joeFxenNWEoQmBgIB49eqR1/PHjx0ImAaWG+vVXqbCwUDVBY2Fhgdq1a4uOBIDu+I0fP77cMXrrrbewdu1a4ROWQOlD6w4dOqBhw4bIyspCVlYWTE1N0aFDB2RkZOCPP/7AH3/8gfPnzwvLSPn8DNDOx9ePqqF6fimLz8/sVccr9RljrIrWrl2LGTNmCO+9WJ68vDxs2LABJ0+e1FlJIPrBA/V8VDdCzs3NhUKhgEKhwOPHjzVuUouLi3HkyBFSK5LZq2nw4MEIDw9HREQEZDIZSkpKkJaWhtDQUBKTMuoo7tnx4MED1QaChw8fxrvvvosWLVpg+PDhiImJEZwOuHDhAj766CMYGxvj+vXrGDVqFExNTfH999/jxo0bWLFihdB8M2fOhI+PDy5duoTi4mLExMTg8uXLSE9P12ptJIJCodC54vPWrVswNjYWkEhaqF5/lfbu3YuFCxfizTffxP79+3H+/HkEBgbi2LFjCAsL02gvIwLV8evatSu6du1a7usuLi5wcXHRYyLdKJxDKkL9/Ew9H18/qobq+UWJz8/sdcGT+owxVkX//PMPBg4cKDpGuYKCgpCSkgJ3d3dYWFiQKClVRz2fciPkffv2qXpaUtgIuXPnzpDJZJDJZHBzc9N6XSaTYdq0aQKSsdfJzJkzsXjxYvTp0wfFxcUYPHgwiouLMWTIEEyZMkV0PPLMzc1x6dIlWFhY4OjRo1i4cCGA0kqbmjVrig0HYPny5Rg2bBgCAgI09kzo3bs3/P39BSYr1blzZyQmJmLDhg1o27Ytjh8/jg4dOmD79u1o166dsFweHh6q8/O4ceNQq9azj1zFxcX4+++/0bNnT2H5pILq9Vdp3rx5CAgIwIcffgigdOVlUlIS5s+fD3d3d/zyyy9C81EfP3WTJk3CkiVLYGlpKTqKZFA/P1PPx9ePqqF+fuHzM3td8KQ+Y4xV0bvvvotjx45h9OjRoqPodOTIEaxfv16jHyMl1POlpqbCyckJQ4cOxdChQ1XHi4qKkJqaii5dugjJFRMTA4VCgXHjxmHNmjUam2oaGBigSZMm5NqfsFePoaEhlixZgk8++QQZGRl4/PgxOnToAFtbW9HRtKSnp4uOoOW9997DjBkzVA80lRvg/frrr2jZsqXgdMBvv/2GxYsXax23srLS2XZJhP/85z9YsmSJ6BgalBtEnj9/Hm+//bZGf1wDAwPY2NhgwIABouJJBtXrr9KuXbu0/k5NTEwQERGBhIQEMaHUUB8/dampqTpbCYo0duzYCheaiK6mon5+pp4P4OtHVVA/v/D5mb0ueFKfMcaqqHnz5oiIiMCvv/6Ktm3baqyoAAAvLy9ByUo1aNAApqamQjNUhHo+Ly8vHDt2TGszrUePHsHLy0tYL1Vl6frBgwfRpEkTchUOL4riJsnqOJ9ukZGR8Pb2hrW1NaytrVXHnz59io0bN5LbKC8wMBAzZswg88Br2rRpaNOmDW7evIl3330XhoaGAICaNWvCx8dHcLrShza5ublax69evUqivdcbb7yh8/x8//59dO/eXdj5Wfl7b2Njg8GDB6t+rlI1dOhQIRv3Ub3+KrVs2RJFRUVISUlBVlYWhgwZAiMjI9y6dQuurq5CswH0x4+6N954Q+ProqIinD9/Hn/++SeJ9nLUz8/U8/H1o2qon1/4/MxeFzypzxhjVbRjxw7Uq1cPKSkpSElJ0XhNJpMJn9SfPn06IiIiEBoairp16wrNogv1fOX1tHzw4AGJvJcvX8aNGzfQuXNnAMC2bduwc+dOtG7dGvPnz9dYwS/Kzz//jM2bN+Py5csAgFatWmHcuHGqVclA6SbJonC+lxcVFYXRo0dr/S08efIEUVFRwib1L1y4oPN4UlIS+vXrh/v37wOAapNakd59912tY8OGDROQRFvfvn0RFRWF1atXq45lZ2cjPDycxErB8vZJKCgogIGBgZ7TaHNxccG9e/fQuHFjAMDZs2eRlJSE1q1b4/333xecrtQ///yD+Ph4jfPL8OHDNR62L1q0SEg26tff69evY+LEibhx4wYKCgrQo0cPGBkZITo6GgUFBTpXKesT9fFTZ2Njo7UoRrS5c+fqPL5mzRrk5eXpOY026udn6vn4+lE11M8vfH5mrwuZguKuYYwxxqpE2Y9RKTMzEwqFAk2bNtX60LR79259xyOfD3i2UubgwYPo2bOnxkqZ4uJiXLx4ES1atMCXX34pJJ+SXC6Hv78/evfujYsXL2L48OGYMGECTp06hZYtW2LZsmVC823btg0hISFwc3ODo6MjgNLWIvv370dgYCDGjBnD+SScr3379jhx4oTWqruff/4ZM2fOxMmTJ4XlkslkOj+0K4/LZDIhK6FiYmLw/vvvo3bt2s9t3yD6ofCjR4/g5+eH33//HY8fP4alpSXu3LkDR0dHbNiwAfXq1ROSSzluy5Ytw/Tp0zVylJSUIDU1FdevXxdeYv/hhx9i1KhR8PDwQE5ODtzc3NC2bVtcvXoVnp6ewitZUlNTMWXKFBgZGcHOzg4AcO7cOTx8+BDr1q0TVv4vleuvr68v6tevj6VLl+Ktt97Cnj170KxZM5w6dQr//e9/8f333wvJJZXxk6rMzEyMHDlSayGPvlE9P1PPx9ePqpHK+YXPz+x1QetxOGOMsWqh7MdIFfV8AGBsbAygdCVF/fr1NTYtMjAwgKOjI0aOHCkqnsrff/+NVq1aAQC+//579O3bF59++inOnTuHSZMmCU4HrF+/HoGBgfD09NQ47uzsjHXr1gmflOZ8L6dLly4aGzWrP6QrLi5GXl4ePvjgAyHZAKBdu3Zo3LgxAgICVH+7CoUCbm5uiI6ORvPmzYVl27x5M+RyOWrXro3NmzeX+z4KlV7Gxsb46quvkJaWptrIrWPHjhpVIiIox02hUGD79u2oUaOG6jUDAwM0bdpU2OpydX/++Sc6deoEAPj222/Rtm1bbN++HceOHcOCBQuET+ovXrwYAwcOxMKFC1UbMxcXF2PRokVYvHgxkpKShOSSyvU3LS0NsbGxWu0xbGxscOvWLUGppDN+qampFb5Otad0eno6iZYoVM/PSlTz8fWjaqRyfuHzM3td8KQ+Y4y9BPXVHc9bCR0YGKinVM+Inih4Hur5AKh+rjY2NpgwYcJzVxSlpaXB3t5e7x/0DAwM8PTpUwDAiRMnVH1eTUxMdPYy1bdHjx6hZ8+eWsd79OiB8PBwAYk0cb6XM3fuXCgUCsydOxfTpk1TfUgBnm3k5uTkJCxfXFwcwsLC4Ofnh7CwMHTo0EH1mqWlJWxsbIRlO3TokM5/U5SQkIBBgwbhzTff1NjMvKCgAPv27RPWV1o5bmPHjkVkZCSJNmO6FBUVqa4JJ06cQN++fQGU9vqlsFFkZmYmIiIiVBP6QOl+DuPHjxe6SlUq19+SkhKUlJRoHb9586aQPQiUpDJ+Y8eO1Tqm/oBYdE/psveqCoUCOTk5+P333+Hr6yso1TNUz89KVPPx9aNqpHJ+4fMze13UeP5bGGOMlfXHH3+gqKhI9e/y/hP9gaSshQsX4t69e6JjlItivqlTp1aqRNjHx0fIyg9nZ2csW7YMUVFR+O2339CnTx8ApRuRKftwitS3b18cOHBA6/jBgwdVWUXifC9n2LBheO+99xATE4MPP/wQw4YNU/03ZMgQrQn9DRs24OHDh3rLZ2hoiHnz5iEgIABTpkzB+vXrdX64Ey0yMhJPnjzROv706VNERkYKSKQpMDAQjx490jr++PFjIQ+sy9q6dWulJmScnZ1x7do1PSTS1Lp1a2zfvh2nT5/GiRMn0KtXLwDA7du3SWwQ36FDB/z1119ax//66y8S+01Qv/726NEDW7Zs0Tj2+PFjrFmzBr1799Z7nrKoj19qaqrGfydOnMDGjRthb2+PTZs26T1PWcbGxhr/mZiYoGvXrtiwYQOJxSnUz8/U8/H1o2qon1/4/MxeF7xSnzHGXsLWrVt1/pu6PXv2wNvbW6v/NRXU81VE1BY18+fPx6JFi7B//34sWLAAVlZWAIAjR47oXOGtb61atcK6deuQkpKi0RP+l19+wUcffaTRU1xEqxHOVzVdu3at1PvWrVuHgQMHokGDBv9yIk29e/fGN998g8DAQBw5ckSv37syqG40rFTeRm63bt3SqM6gTtT52d/fH1OnTsWXX34JDw8P1UT5oUOHVG0VRPLy8sLSpUuRmZkJBwcHAKXnl23btsHf319jw2kKk/zlEfXznTNnDry9vTFo0CAUFBTA398fV69eRcOGDbFy5UohmV6GqPHTdQ7p0aMHDAwMsHz5cuzatUtAqmdE70n0PNTPz9TzVRZfP6qGz89Vw1ugsufhSX3GGHuNUL8xoJ6PoiZNmmD9+vVax+fOnavx9YYNG/DBBx/ofVI1Pj4eDRo0wKVLl3Dp0iXVcWNjY8THx6u+FtU/nPPph8i/bXNzc0RHRyMmJgampqYwMjISlqWs8iY9Lly4ILQlgHIzc5lMhnHjxmlsYF5cXIy///6bxEND6t566y2cPHkSubm5Gj/PUaNGaTzIEVVe/+mnnwIAwsLCdL4melNp6ho3bozExETs27dP1TN8xIgRkMvlGn2S2Ytp1KgRrly5IjqGhoULF8LPz4/EohPq52fq+aSC+vWDOj4/s9cFT+ozxlgVffLJJzonZWQyGQwNDdG8eXMMGTIELVu2FJCOsVKiVkpT7xnO+V5t+fn5qF27NoDSVclUHnxQ32hYuZn5+fPn8fbbb2v0n1XumTBgwABR8SSlZs2aWg9omjZtqvG1j48PEhMT0axZM31Gw8GDB/X6/V41qampcHJywtChQzF06FDV8aKiIqSmppLd6JUK9UoQpdu3byM6OppcZQilSlLq52fq+aSE8vWDOj4/s9cFT+ozxlgVGRsb44cffkCDBg3QsWNHAMC5c+fw6NEj9OjRA/v27UN0dDQ2b96ssVGUCOnp6UK///NQzydlXAXBXkfdunXDgAEDIJfL0a1bN9SoQWM7KeobDSvb/tjY2GDw4MG8AvBfJur8LHLD6FeBl5cXjh07hkaNGmkcf/ToEby8vLi64TmUK7rL/v47Ojpi6dKlglLpRukeivr5mXq+Vw2l301K+PzMXhc8qc8YY1Vkbm6OIUOGYP78+aoJo5KSEixduhT169fHqlWrsGDBAoSHhyM2NlZw2tKNq2bMmKHqvU4N9Xzl0VWtwUo/bHz33Xc4deoU7t27p7VZqejNQDnfqy00NBRJSUnw9fWFsbExBg4ciKFDh8Le3l5ormHDhqGoqAgymQwuLi6wtrYWmqc8Li4uuHfvnmrT7bNnzyIpKQmtW7fG+++/Lzhd5fH5uXy3bt1CWlqazvMLlcqW5xH18y2vfdaDBw+09smgTNT4la0UqVGjBszMzFTVVaxi1M/P1PNVFl8/qobPz1XDv3/seXhSnzHGqig+Ph6xsbEaK0Br1KgBT09PfPDBB/j0008xZswYjBkzRq+5dJU1A0BSUhL69euH+/fvAxC3+R31fC+KV8rotnTpUuzYsQNvvfUWzM3Nyd2ccr5Xm6urK1xdXZGbm4v9+/dj7969eP/999GsWTPI5XKhG9HWqlULCxcuxL59+4RleJ5Zs2Zh1KhR8PDwQE5ODsaPH4+2bdsiKSkJOTk5wjfyrSw+P+u2a9cuzJ8/HwYGBmjYsKHGa9T36VCn75+v8vdeJpNhzpw5GiuRi4uLcfHiRaGVNi+KQqXIzZs3YWlpSaaaqiyKlaTUz8/U81UWXz+qhs/PVcO/f+x5eFKfMcaqqLi4GH/99RdatGihcfyvv/5SrXqrXbu23ifjyitrBoBp06YJ3/yOej5dCgoKcPPmTTRu3FirnJjiBz4K9uzZg8jISPTu3Vt0FJ04n3507txZ6OpLIyMjDB8+HMOHD8elS5fg7++PqKgo4ZMKnTp1wvnz58m2Qfnzzz/RqVMnAMC3336Ltm3bYvv27Th27BgWLFggfPwqKzo6WnLVX/oQERGBTz75BB9//DHZyVQlStdfZbsshUKB+vXra2y6aGBgAEdHR4wcOVKvmZ6H0vjpMmjQIPJ9walVklI/P1PPV1l8/agchUKBkpIS1KxZU+M4n58rh8r4MenhSX3GGKsid3d3zJs3D9euXYOdnR0A4Pfff8e6devg7u4OoHSzntatW+s1V7t27dC4cWMEBASobmgUCgXc3NwQHR2N5s2b6zWP1PLt2rULLVq0gJOTE/Lz87Fo0SIkJCRAoVCgRo0aGD58OIKCgrhX6HMYGRlpbepFCefTj+joaKHfPz8/HwcPHkRycjKOHj0Kc3NzeHt7C80EAKNHj8by5ctx8+ZNdOzYUaskXHSlUlFRkeocd+LECfTt2xcA0LJlS+Tk5AjLde7cOTRo0EA1AZiQkIDt27fjxo0baNKkCTw9PTF48GDV+zt37iwqaqWIqsB5+vQpBg8eTG5Cn/r1d9myZQBKV5pPmDAB9erVq/D9aWlpsLe311te6uOnC6XVqFKpJKV6flaimo+vH1VTVFSENWvWIC0tDV27doWfnx82btyIyMhIFBUVYfDgwQgODubzczmojx+THlp3cIwxJkGBgYEYN24cNm7cCE9PT3h6emLjxo0YP348AgMDAQA9evTAqlWr9JorLi4O//nPf+Dn54d//vkHNjY2qslBS0tL2NjYCF0dSj1fVFSUaqJj9erVOHnyJCIiIpCcnIyIiAicOnUKq1evFpbvRYlaKT1t2jRERUXh6dOnev/elcH5Xk5hYSFWrFgBV1dXjBgxAvHx8Rqv37lzB2+88YagdM8cPXoUn332Gbp3745FixbB3NwcmzZtwo8//gh/f3/R8fDpp5/i77//xpIlSzB69Gh4eHhg2LBhqv8VrXXr1ti+fTtOnz6NEydOoFevXgCA27dvw9TUVFiuwMBAXLt2DUDptWTBggWws7PD5MmTYW9vj6CgIK3fScpETWgOHz4c3333nZDvXRGpXH+nTp363AkjAPDx8cGtW7f0kKiUVMaPKvXzsPp/RUVFmDZtGp+fK4lqPr5+VE1kZCTi4+NhZ2eH/fv3Y8GCBfj666+xePFiLFmyBD///DO2bNmi10y6UD0/S2X8mHTwSn3GGKuimjVrYsqUKZgyZQpyc3MBlK6uVdekSRO95zI0NMS8efNw+PBhTJkyBR9++CF8fHz0nqM81PPdvn0bFhYWAIBDhw5h4cKFqg8krVq1gomJCQICAhAQECAyZqWJWik9cOBAJCcno1u3bmjatClq1dK89di9e7eQXEqc7+WsW7cOiYmJmDBhAh4+fIjly5fj7NmzWLx4seo9FFZeTp06FX369EFoaCh69+4NAwMD0ZE0lN0okhp/f39MnToVX375JTw8PFQrUw8dOqRqqyBCZmamqprrf//7H+bNm4dRo0apXre3t8e6deswYsQIURG1UGx/MmvWLHz88cc4evQo2rZtq3V+US5M0LdX7fqr73OhFMdv8uTJMDExER0DAP1KUiWq52clqvmkeP0A6LRnSU5OxpIlS/DOO+9g9OjRePfdd/H5559j0KBBAEo/361du5bUZ7qK6Pv8/KqNHxOPJ/UZY6walZ3Mp6B379745ptvEBgYiCNHjoiOo4VqPgsLC2RlZaFJkyZ48uSJ1iaCZmZmePDggZhwKF0pvWrVKhw4cAAmJib44IMPND6A3LlzBz179hS+J8Fnn32Gc+fOYejQoSQ3euV8LycpKUn1oQQA3nvvPfj4+CAwMBAhISEAxLUUUXf8+HHVeZniRoxUe+krvfXWWzh58iRyc3M1JtxGjRql0SpI3+XrderUwf3792FjY4Nbt25pTRA5ODjg77//1ksWXaTS/mT9+vU4duyY1p5AgNi/X+rXX+qkOH6TJk0SHUElLi4OYWFh8PPzQ1hYGDp06KB6TVlJSgHV8zP1fNSvH9Tbs9y+fVv1gKZ58+YwMDBAu3btVK/b29vj+vXrQrJJAY8fq248qc8YY1V0584dhIaG4ueff8a9e/e0nviLnlQFAHNzc0RHRyMmJgampqbkHj5QzCeXy7F69Wps2LAB7u7uiIqKwueff4769evjyZMnWLNmDZydnYXlk8pK6cOHD2Pjxo1ke5Jyvpdz69YttGnTRvV18+bNsXXrVnh5eWH27NmYPXu2wHTPqJ9LKG/EeOnSJWRnZ6OwsFDjeL9+/QQleqZmzZpaK2jL7vPg4+Oj17Ht1asXYmNjsXTpUnTp0gXfffedRn/rb7/9Fv/5z3/0kkWXqKgorFy5EoBm+5OWLVviypUrCAsLw+rVq4WvlP7qq68QEhKC9957T2iOsqhff6mT0vjFxcVhy5YtuHr1KgDA1tYW48aNE7qRJfVKUnUUz8/qKOajfv1QtmeRy+XYv38/7t69i8OHD2Px4sUoKSnBypUrsWXLFmG/k8bGxnj48CGsra0BAB06dNC41yooKCCxqIMqHj9W3XhSnzHGqmjOnDm4ceMGfH19YWlpKTqOlvz8fFUvdS8vL3h5eQlOpIlqvk8++QQZGRno378/7OzscPr0afTo0QNWVlaqfqCbNm0Slk8qK6UbN25M4iFNeTjfyzE3N8e1a9c0PpxbWVkhJiYGXl5ewtp2VITCQ66yrl27pjrXyGQyVUbl3y6Fh8KVoe+x9ff3x+jRo+Hp6Qk7Ozt89dVXSElJQatWrXDlyhWcOXMGUVFRes2kTirtTwwNDclM7qqjfv2lTirjFxERgc2bN8PT0xOOjo4AgDNnziAkJATZ2dmYPn260HxUK0lfFMVrnzq+fmii3p6lVatW+OOPP1Sry7dv367xekZGBpkWVRTx+LHqxpP6jDFWRWlpafjf//5HYlNIXbp164YBAwZALpejW7dupFpPAHTzKW+ajxw5gh9//BE1atSAQqGAhYUFnJ2dMWTIkEptwPRvkcpK6Tlz5iAsLAyLFi3SWp1FAed7OS4uLkhKSkK3bt00jisn9seOHSsombQsXboUTZs2xebNm9GvXz/Ex8fj/v37CA0NxWeffSY6HllWVlZISEjAhg0b8OOPP0KhUODs2bO4efMmnJycEBsbC3t7e2H5pNL+xMvLC19//TWCgoJER9FA/fr7ovT9gF0q4xcbG4vg4GAMGTJEdaxfv35o164dgoODhU/qAzQrSVnVUL9+UG/PsmjRIq39V9QVFRVh4sSJekxUNfo+P79q48fE40l9xhirImtra9KrYEJDQ5GUlARfX18YGxtj4MCBGDp0qNAbVnXU8/Xq1Uu1wpISqayUnj17Np48eQJXV1fUqVNHa6PSlJQUQclKcb6X4+vri7/++kvna1ZWVti6dStOnDih51QVo7QRo1J6ejq2bNkCMzMz1KhRAzKZDJ07d8ann36KJUuWICEhQXREsho0aAB/f3/4+/uLjqJFKu1Pzp49i5MnT+LHH39EmzZttCYaIiMjBSUrRfX6+6JE3SNSH7+ioiLY2dlpHe/YsSOKi4sFJNJEtZKUVR3l6wf19iy69mBRJ5fL9ZSkeuj7/PyqjR8Tjyf1GWOsiubOnYvPP/+c3EpaJVdXV7i6uiI3Nxf79+/H3r178f7776NZs2aQy+WYOnUq55MgqayUnjt3rugIFeJ8L8fGxqbCzQKtrKwwbNgwPSZ6PkobMSqVlJSgfv36AICGDRvi9u3baNmyJWxsbHDlyhXB6djLkkr7kwYNGmDAgAGiY1TKwoUL4efnBzMzM9FRdCooKMDNmzfRuHFjrQ0s09PTBaV6huL4ubu7IzY2VmsRws6dO0lMbFGtJGWvNim2Z5k0aRKWLFlCsg2tkkKhQElJCWrWrKlxnML5WQrjx+iSKSgvL2WMMQno0qULnjx5guLiYlIraSty6dIl+Pv74+LFiyR7NlPPBwAXLlzAsGHDhOW7fv06/vrrL/Ts2VPn67du3cKJEyfITayyV8f9+/dx8eJFtG/fHqamprh37x7i4+NRUFCAgQMHolWrVqIjAqC5EaPShx9+iAkTJqB///6YNWsW/vnnH0yZMgU7d+7EuXPnkJycLDpipTg7O5PahDgrKwtBQUGIiYkRmkPZ/uTatWsk259ICaXfsV27dqFFixZwcnJCfn4+Fi1ahISEBCgUCtSoUQPDhw9HUFCQ1uS+SJTGTyk4OBgJCQmwtraGg4MDgNLqkezsbHh4eGhUjoioPjxw4ACSkpJw+PBhkpWklUXxZ6+OWj7R148rV66gVq1a5Y5HUlISatasqeqxT4GTkxP27NlD4mdYVFSENWvWIC0tDV27doWfnx82btyIyMhIFBUVYfDgwQgODiZ1fqY0fkx6eKU+Y4xVEdWVtGXl5+fj4MGDSE5OxtGjR2Fubg5vb2/RsVSo59NF5HNxKa2UzsrKwjfffINr165h3rx5aNSoEQ4fPowmTZpo7AvA+aST7+zZs5gwYQJyc3PRoEEDbNq0CdOnT0etWrVQUlKC6Oho/O9//0PHjh2F5FOivhHjlClT8OTJEwCAn58fPv74Y4wZMwampqZYtWqV0Gwvgtoaoby8PKSmpoqOQb79CVA6AZKSkoKsrCwMGTIERkZGuHXrFoyMjFRVJBRQ+h2LiorCypUrAQCrV6/GyZMnERERgZYtW+LKlSsICwvD6tWrhW+ErI7S+CllZGSgQ4cOAEqvcwBgamoKU1NTZGRkqN4nqtXIq1JJSvFnr45aPtHXD27PUjWRkZGIj4+HXC7H/v37cffuXRw+fBiLFy9GSUkJVq5ciS1btgjbaJix6sYr9Rlj7BV39OhRJCcn44cffkCtWrXg5uYGuVyOLl26iI4GgG6+531Ye/ToEVJSUoRWEkhhpXRKSgp8fHzg7OyM1NRUfPvtt2jWrBk2bNiA33//HV988QXnk2C+jz76CDY2NpgzZw527NiBmJgY9OzZE0uWLAFQuqry4cOHiIqKEpJPycXFBUFBQRobMQJAcnIygoODcerUKUHJyvfgwQOYmJgI7ZmrS0XtRfTteSsob926hU2bNpGq9KLY/uT69euYOHEibty4gYKCAuzfvx/NmjXDkiVLUFBQgMWLF4uOqEJpJaO9vT3279+PJk2awM3NDfPmzdN4eJOamoqAgAD8+OOPAlNqojR+Uka5krS89iJUUMknxesH9fYsQ4YMQXR0tGofAJH69++PefPm4Z133kFmZibeffddfP7556rKhn379mHt2rVISkoSnPQZSuPHpIdX6jPGWDWguJJWaerUqejTpw9CQ0PRu3dvrfZAolHN9+OPP6J79+4wNzfX+broTdykslL6888/x4wZM/DRRx/ByclJddzFxQVff/21wGSlON/LOXfuHIKCgmBkZAQvLy+Eh4dj1KhRqtc9PT0xZcoUYfmUqG/EqC45ORl9+/aFqamp6Cjk24uEhITAwsKi3OtFYWGhnhM93549e+Dt7U1qUn/p0qWws7NDYmIi3nrrLdVxV1dX/Pe//xWYTBuFvsdKFhYWyMrKQpMmTfDkyRM0bNhQ43UzMzM8ePBATLhyUBo/qaFWSUq9vQj1fFK8fqSmpiI/P190jHJRahV4+/ZttG/fHgDQvHlzGBgYqPYnAEofyl6/fl1UPJ0ojR+THp7UZ4yxKiq7knbmzJlo1KgRLl68iG+++Ub4St/jx4/DyMgIAHDz5k1YWlqS2uyLar6WLVtiwIAB5fbdPn/+PH766Sf9hlKzatUqvPvuu6qV0p988onWSun/9//+n/CV0hkZGQgPD9c6bmZmhvv37wtIpInzvZzCwkLUrl0bAGBgYIA6depoTGw1bNiQxKQW9Y0Y1c2fPx8ODg4keq1Tby/SpEkT+Pv7l9tT+Pz583jvvff0nKpiFIuj09LSEBsbqzW5ZmNjg1u3bglK9cwbb7yBY8eOoVGjRhrH79+/j+7duwtbSSuXy7F69Wps2LAB7u7uiIqKwueff4769evjyZMnWLNmDZydnYVkU0d1/JTGjh1bYUWS6D0xdFWSbtq0SXglKfX2ItTzSfH6QdHzWhSJ+jsxNjbGw4cPVaveO3TooPqcCZRWHVKohKQ6fkx6eFKfMcaqiOpKWiX1G5lBgwaR2owKoJvPzs4Of/zxR7mvGxoaCi2TlMpKaWNjY+Tk5Gj9TM+fPw8rKytBqZ7hfC+ncePGuHbtGpo2bQqg9CGThYWF6vWcnByt1auixMfH4/jx4zo3Yly2bJnqfSI2YlRHadL39u3bqp/noUOHsHDhQlV7kVatWsHExAQBAQHCJvXt7Oxw7ty5cidlZDIZqfGkqqSkBCUlJVrHb968SaKffnk/w4KCAqFVfZ988gkyMjLQv39/2NnZ4fTp0+jRowesrKxw+/ZtmJqaYtOmTcLyKVEdP6U33nhD4+uioiKcP38ef/75Jzw8PMSEUkO1kjQ5ORlLlizBO++8g9GjR2u1FzE0NMTatWuFTZpTzyfF64eNjY3GxtEUjB07VuuY+mS5qIeGrVq1wh9//KFanb99+3aN1zMyMtC8eXMR0TRQHT8mPbTODIwxJkFUV9LqQu0mtSxK+RYtWlRhe45WrVrh0KFDekykSSorpQcPHozw8HBERERAJpOhpKQEaWlpCA0NJfGhnfO9fK579+6pvu7Tp4/G64cOHUKnTp30nEob9Y0YqaLeXsTPz0+1wbAurVq1wsGDB/WY6Pkotj/p0aMHtmzZguDgYNWxx48fY82aNejdu7ewXMoV2jKZDHFxcRrVKyUlJUhNTUXLli1FxVNNSh45cgQ//vgjatSoAYVCAQsLCzg7O2PIkCFCK26oj5/S3LlzdR5fs2YN8vLy9JxGG9VKUurtRajnk+L1g2J7lrIrzQsLC3H+/HlERERg5syZglKVfn6r6AFIUVERJk6cqMdEulEdPyY9PKnPGGNVRHUlLauaF+31uWHDBnzwwQdo0KDBv5RIk1RWSs+cOROLFy9Gnz59UFxcjMGDB6O4uBhDhgwhUUnA+V7O8zaSnjx5svDN8ABg69atoiNUWnR0NJlrBvX2Iq1bt67wdQMDA9jY2Ki+TktLg729vd57OFNvfzJnzhx4e3tj0KBBKCgogL+/P65evYqGDRuq2i+JsHnzZgClD/q3b9+uMZFqYGCApk2bYtGiRYLSPdOrVy+NDXKpkMr4lWfo0KEYOXIkPvvsM6E5qFaSUm8vQj2fVK4f1NuzGBsbax3r0aMHDAwMsHz5cuzatUtAKqBFixYVvk6l9SLV8WPSw5P6jDFWRVRX0uoyefJkmJiYiI5RLur5KrJu3ToMHDhQb5P6UlkpbWhoiCVLlqjaFTx+/BgdOnSAra2t6GgAOF91Uv/gW7duXdFxUFhYCAcHByQkJKBt27ai4zxXp06dcPPmTTRu3FjYBoJKUmkvUlk+Pj5CJuSotz9p3LgxEhMTsW/fPly4cAF5eXkYMWIE5HI56tSpIyyXsgpu7NixiIyMlMR9wcKFC+Hn50diI2Qpjp+69PR04efAsihVklJvL0I934sSdf2QanuWRo0a4cqVK6JjaJg0aRKWLFkCS0tL0VGei+L4Mdp4Up8xxqqI6kpaXSZNmiQ6QoWo56uIvj/wSWWldGRkJLy9vWFtba2xB8HTp0+xcePG5/7/+Ldxvuoj6oNveQwMDGBtba2zZ7hou3btQosWLeDk5IT8/HwsWrQICQkJUCgUqFGjBoYPH46goCBhE1vU24u8KH2fn6XS/iQ1NRVOTk4YOnQohg4dqjpeVFSE1NRU4StB1SttRK2Wraw9e/bA29ubxKS+EvXxK3v9UigUyMnJwe+//w5fX19Bqeij3l6Eer4XJeqBDvX2LBcuXNA6dvv2bURHR6vaL1GRmpqK/Px80TE0SGn8GG0yBaXHzowxJmE3btwgu5I2Li4OW7ZswdWrVwEAtra2GDduHEaOHCk22P+hnq8ynJycsGfPHqETmhQ/tFNvP8H5qg+Fv4Gy4uLicODAAaxYsQKmpqai46j069cPK1euhIODA0JDQ7F//34EBgaiZcuWuHLlCsLCwtCvXz9hG9G+avT9u9m3b18AQHZ2Nho3bqyz/Ymfn59q82ZRpHR+cXZ2JvXQsCyK5z91FMev7ObkMpkMZmZmcHFxwdtvvy0olW7r16/H6NGj9VaNyeig9redkpJCoj1L+/btdW4q7OjoiKVLl6JVq1aCkmmj9jMEpDV+jDZeqc8YY9XE2toa2dnZ6NatG6lJ1YiICGzevBmenp5wdHQEAJw5cwYhISHIzs7G9OnTOd8rgtpKaaB0hZOu3qkXLlwg0RKA873atm3bhszMTPTs2RNNmjTRWl2+e/duIblu376t2gPj0KFDWLhwoao3d6tWrWBiYoKAgABSk/qU2otQJ5X2J+WdXx48eECihZY6XodWNRTHb9myZaIjVBr1SlLq7UWo55MSKu1Zym4mXKNGDZiZmaF27dqCEpXPxsamwuoREaQ0fow2Wr/ZjDEmcRQnVWNjYxEcHIwhQ4aojvXr1w/t2rVDcHCw8Elz6vmkhNKH9i5dukAmk0Emk8HNzU1j4qi4uBh5eXn44IMPOJ9E8+myePFirRW/ovXv3190BJ0sLCyQlZWFJk2a4MmTJ1qbWpuZmeHBgwdiwpWDYnsR6qi2P1G2PZHJZJgzZ45GpuLiYly8eBFOTk6i4klSenq66AiSRvWhoVQqSSm2F1FHPR9F1NuzqG8mfPPmTVhaWmpUpVGSnJwsOoIWKY0fo40n9RljrBpRmlRVKioqgp2dndbxjh07ori4WEAiTdTzsZczd+5cKBQKzJ07F9OmTYOxsbHqNQMDA9jY2AidNOJ81U8ulyM3Nxc//PADWrRoQaJ0mNKeA+rkcjlWr16NDRs2wN3dHVFRUfj8889Rv359PHnyBGvWrIGzs7PomBooXt8qS9dqdH2j9NBfeT5RKBSoX7++xqa4BgYGcHR0JDdpSfGhoZTaF1EcP3UUHxpyJSkDxF0/PDw8KmzPQsmgQYPIXN+Uyu5JUJboPWPUURw/Jh08qc8YY684d3d3xMbGavUu3blzJ+RyuaBUz1DPV1mdO3cWXjJJ6UP7sGHDAABNmzaFs7Pzc8teN2zYgA8++EBv/Wo5X/WYPn06unTpAk9PTzx9+hTDhw/H9evXoVAosHLlSri5uek1j1R88sknyMjIQP/+/WFnZ4fTp0+jR48esLKywu3bt2FqaopNmzaJjvnKoPBAgkIGJWXbExsbG0yYMOG5mx5TqDKgeD9Q3s+0oKAABgYGek5TMYrjp47S34eSlCpJKbYXUUc9X0VE/W5KqT0Lxb/fsWPHah1Tf0BD6aErxfFj0iHNMytjjBFFaVJVXXx8PI4fP67alO/s2bPIzs6Gh4eHRk/TshPrnK9UcXExDhw4gMuXLwMo7Xndv39/jQ8o0dHRQrKpo7hSumvXrpV637p16zBw4EC9T0pzvqo5ffo0pkyZAgA4cOAAFAoFUlNTsXv3bqxdu1bIpH7Xrl3x3XffwczMTNXGqDwpKSl6TPaMoaEh1q5diyNHjuDHH39EjRo1oFAoYGFhAWdnZwwZMuS5E636Rrm9yN27d1U9hlu0aKF1HaacXaTKVrKIqjLIy8vDhg0bcPLkSdy9exclJSUar5ed9NKXmJgYAKUTRHFxcRp/qyUlJUhNTUXLli2FZFNHdfykQkqVpBTbi6ijnI/q9YPbs1RN2ZX6hYWFOH/+PCIiIjBz5kxBqRirfjypzxhj1YjiSqiMjAx06NABAJCVlQUAMDU1hampKTIyMlTvE1VeSj3fn3/+iSlTpuDOnTto0aIFAGDjxo1YsWIF1q1bh7Zt2wrJpfSqrJSmvkqF8+n26NEj1SagR48exYABA1C3bl306dMHYWFhQjIFBgbCyMgIQGkbI8p69eql2iCXIurtRXJzc7Fo0SLs27dPNclWs2ZNDBw4EAsWLNBoWyUa1Yf+lSHq/BIUFISUlBS4u7vDwsKCRBslANi8eTOA0nHZvn27xkSbgYEBmjZtikWLFglK9wzV8dOF4oM36pWk1NuLUM8npesH9fYskydPJrchvK6fX48ePWBgYIDly5dj165dAlLpRnH8mHTwpD5jjL2ku3fvanxAP3/+PDZv3ozMzExYWlpizJgxeOuttwQmLKW+UR9F1PMFBQWhdevW+Oabb1Q3XP/88w/mzJmD+fPnY/v27ULzUVwpzV4f1tbWSE9Ph4mJCY4ePYqVK1cCAB4+fCisVYeydVHZf1NHcaNI6u1FgoKCcP78eaxbt061x0R6ejqWLl2K+fPnY9WqVYITPkNhElBqjhw5gvXr1+PNN98UHUXDoUOHAJS2d4iMjCQ7GUN1/MoTGBiIGTNmwMrKSnQUFcqVpNTbi1DPJ6XrB/WFJZMmTRIdodIaNWqkqsygQkrjx+jhSX3GGHtJb7/9tmoF4y+//AIvLy84OTnB2dkZFy5cwIQJE7B582ahK1EKCwvh4OCAhIQE4SvKdaGeDyj90KE+oQ8AJiYmmDlzJkaMGCEwWSmKK6XZ68PLywuzZ89GvXr1YG1trXqQmZqaSuZvuqSkBJmZmbh7967WB2PRKwXVUdooUirtRX766Sds3LgRnTt3Vh3r2bMnlixZgokTJwpMVorbn1RNgwYNYGpqKjpGudQXJVDYd6AsquN34cIFnceTkpLQr18/3L9/HwDQvn17fcbSQr2SlHp7Eer5qF8/pCAuLg5btmzB1atXAQC2trYYN24ciY3WdZ1nbt++jejoaOHnFiXK48ekgyf1GWPsJalPDkVGRmLo0KEICQlRHVu6dCkiIyOxZcsWEfEAlJaBW1tba00kUEE9H1B6g3Xnzh20adNG4/jdu3fRvHlzQameobhSmr0+xowZAwcHB9y4cQPdu3dXtaFo1qwZZsyYITYcgDNnzmDWrFnIzs7WmtCXyWTCVwqqo7QSTyrtRUxNTXWW2BsZGel9fwldpNT+hKLp06cjIiICoaGhqFu3rug4FRK170BFqI6fh4cHZDKZznPetGnToFAoSJyfqVeSUm8vQj0f9euHOortWSIiIrB582Z4enrC0dERQOk9V0hICLKzs4VvJF3eecbR0RFLly4VlOoZ6uPHpIMn9RljrBpkZGTAz89P49ioUaN0lp7q2+TJk7Fy5UqsWLGC5Iot6vlmzZqFpUuXYurUqRo3XVFRUfD390dubq7qvco+3vokhZXS7NVmZ2cHOzs7jZWqffr0ER0LALBgwQLY2dlhw4YNPKn6AqTSXmTKlClYvnw5VqxYAQsLCwBATk4OwsLC4OvrKzid9NqflEeffzfKiRilzMxMdO/eHU2bNtXYnB4Adu/erbdcz0PloZwUxq9du3Zo3LgxAgICUKdOHQCl4+fm5obo6GgSCyakUElaHortRdRRyUf9+qGOYnuW2NhYBAcHY8iQIapj/fr1Q7t27RAcHCx8UrpsJVyNGjVgZmaG2rVrC0qkifr4MengSX3GGKuCx48fo3bt2qhdu7bWqujatWvj6dOngpI9s23bNmRmZqJnz55o0qSJRhsFQPyHYur5Pv74YwDAjBkzVB+UlR/eJ0+erPpa1Koy6iulK6tz585kbrR14XzPR3GlamZmJr744gsSk0TPQ3GjSOrtRWJjY5GZmYl33nkH1tbWAIAbN27AwMAA9+7dw44dO1TvFXEtodr+5EXpc8K6f//+evteryIpjF9cXBzCwsLg5+eHsLAwVYsbALC0tISNjY3AdKWkUElKvb0I9XzUrx8A7fYsRUVFsLOz0zresWNH1cbDIqmfR27evAlLS0uNqkPRqI8fkw6e1GeMsSpQbkKqUCjw+++/a3ww+fPPP2FpaSkqmgr1D3jU8yl7S1NGeaV0ZUVHR4uOUCHO93xUVqqq69SpEzIzM8lO6r/xxhuqvVnU3b9/H927dxfefkIdxYc21K8fVNuf6FJQUICbN2+icePGWg9u9PnAaerUqXr7XtVp8eLFWn/HIkhh/AwNDTFv3jwcPnwYU6ZMwYcffggfHx/RsbRQrySl3l6Eej7q1w/q7Vnc3d0RGxurtUn0zp07yW0MP2jQIHL3L1IaP0abTEHxExhjjElASkqKxtcWFhZo0aKF6ustW7agsLCQN1tieuPs7EzmprWwsBCrVq3CgQMHYGJigg8++EBjY+E7d+6gZ8+ewiYtOV/1c3Jywp49e4T//qmvDrx27RpWr14Nb29vtG3bVqv9hOjVgu3bt8fx48e1JgNv3boFV1dXnD17VlAybVR+vtTpan+iUChItT/ZtWsXWrRoAScnJ+Tn52PRokVISEiAQqFAjRo1MHz4cAQFBZGqyli4cCH8/PxIbCQtRVTH786dOwgMDEReXh7OnDmDxMREtG7dWnQsAKV/y5mZmSgqKiJZSXr9+nWNr6m1F6GejzoXFxcEBQVptGcBgOTkZAQHB+PUqVOCkpUKDg5GQkICrK2t4eDgAAA4e/YssrOz4eHhoXG9KztxrW8U71+kNH6MNl6pzxhjL6lr164Vvj5u3Dg9JWH/ttOnT2P79u34+++/ERERASsrKyQkJKBp06bo3Lmz6HgqlJ7Tr1u3DomJiZgwYQIePnyI5cuX4+zZs1i8eLHqPSLzcr7qR2Wlqq7VgXPnzlX9W/mayI0YlRVAMpkMcXFxGpNFJSUlSE1NRcuWLYVkk5qHDx9i//79yMrKgre3N0xNTXHu3DmYm5vDyspK73mor/4EgKioKNWm6qtXr8bJkycRERGBli1b4sqVKwgLC8Pq1asREBAgOOkze/bsgbe3N6lJ6by8PGzYsAEnT57E3bt3tVq1lO3pLBLF8QMAc3NzREdHIyYmBqampkL2JioP9b9l6u1FqOcD6F0/1FFvz5KRkaGqUM/KygJQuvmwqakpMjIyVO/jvYx04/Fj1YUn9RljrJr89ttvuHz5MgCgVatWsLe3F5ala9eu+O6772BmZoYuXbpUeENQtuJAH6jnU7d//34EBARALpfj3LlzKCgoAADk5uZi/fr1pCb1KUlKSsKSJUvwzjvvAADee+89+Pj4IDAwECEhIQDE3qhyvupHpVyY0kRaeTZv3gyg9MHM9u3bNSY6DAwM0LRpUyxatEhQOt2oPLRRd+HCBXz00UcwNjbG9evXMWrUKJiamuL777/HjRs3sGLFCr1nkkL7k9u3b6s2hjx06BAWLlyIXr16ASi9fzExMUFAQACpSX1qDzEBICgoCCkpKXB3dye/ETfF8cvPz1et2vby8oKXl5fgRJqk8LesRLG9iDqK+SheP9RRb8+ivucOdZMnT4aJiYnoGBqkNH6MNp7UZ4yxKrp58yY+/fRT/PLLL2jQoAGA0pUfTk5OWLVqFRo3bqz3TIGBgarVTuorVKmgnk/d2rVrsWjRInh4eGDv3r2q487Ozli7dq3AZNooTbrdunULbdq0UX3dvHlzbN26FV5eXpg9ezZmz54tMB3nqy4UV6qqrw5cv349GjVqpNG6CADi4+Nx7949TJo0Sd/xAJROpALA2LFjERkZSe7Dpi4UJhHKWr58OYYNG4aAgAA4OTmpjvfu3Rv+/v4Ck2mj1P7EwsICWVlZaNKkCZ48eYKGDRtqvG5mZoYHDx6ICSchR44cwfr16/Hmm2+KjiJJ3bp1w4ABAyCXy9GtWzdyq7ilhOJDG3UU80nh+hEfH4/jx4/rbM+ybNky1fu4PUvFRN3rMaYPPKnPGGNVNG/ePBQVFWHfvn2qdgl//fUX5s6di3nz5uHLL7/Ue6Zhw4bp/DcV1POpu3Llis7V+MbGxnj48KGAROWjNOlmbm6Oa9euoWnTpqpjVlZWiImJgZeXl/APIJyvelBfqbpjxw6Eh4drHW/Tpg1mzpwp/IOe+kot9Y2uqaD40Ebdb7/9ptGSSsnKygo5OTkCEpWPUvsTuVyO1atXY8OGDXB3d0dUVBQ+//xz1K9fH0+ePMGaNWvg7OwsOqYGfW7WW1kNGjQguYGqLhTHLzQ0FElJSfD19YWxsTEGDhyIoUOHcqUr0wvq1w/q7VnGjh1b4fdWthkUKS4uDlu2bMHVq1cBALa2thg3bhxGjhwpNhikMX5MGnhSnzHGqig1NRXbt2/X6H/csmVLBAUFYcyYMQKTPVNSUoLMzEzcvXtXa7VMly5dBKV6hnI+c3NzZGVlaUyuAqUTcBTKiKlOurm4uCApKQndunXTOK6cmB47dqyQXEqcr3pQX6mak5OjajOizszMjMSHdnU+Pj7k2hNQf2hjaGiI3NxcreNXr14lMXmujtJK1U8++QQZGRno378/7OzscPr0afTo0QNWVla4ffs2TE1NsWnTJtExtQQGBmLGjBnCe10rTZ8+HREREQgNDUXdunVFx3kuauPn6uoKV1dX5ObmYv/+/di7dy/ef/99NGvWDHK5XEj7GylVkqqj2F5EHcV81K8f1NuzvPHGGxpfFxUV4fz58/jzzz/h4eEhJpSaiIgIbN68GZ6ennB0dAQAnDlzBiEhIcjOzsb06dOF5qM+fkw6eFKfMcaqyNraGkVFRVrHS0pKYGlpKSCRpjNnzmDWrFnIzs7WmlQQuVGkEvV8o0aNwtKlSxESEgKZTIZbt24hPT0doaGh8PX1FZoNoDvp5uvri7/++kvna1ZWVti6dStOnDih51TPcL7qQX2lqrW1NX755RetifK0tDQS52d1lCZ9lag/tOnbty+ioqKwevVq1bHs7GyEh4djwIAB4oIRZ2hoiLVr1+LIkSP48ccfUaNGDSgUClhYWMDZ2RlDhgzR2LxZ3y5cuKDzeFJSEvr164f79+8DANq3b6/PWACebcStlJmZie7du6Np06aoVUvzo/Xu3bv1HQ8A7fHTxcjICMOHD8fw4cNx6dIl+Pv7IyoqSsikvpQqSdWJrjp7Hor5+PpRNeU99FqzZg3y8vL0nEZbbGwsgoODMWTIENWxfv36oV27dggODhY+qU99/Jh0yBQUP0EwxpiE/PDDD1i/fj3mz5+vKhn+7bffsGTJEvj4+KB///5C87m7u8PW1hZ+fn46J32NjY0FJStFPZ9CocC6deuwYcMGPHnyBEDphMiECRMwY8YModkAoHPnzqQn3dirLTExEQcPHiS7UjU6OhobN25EQEAAXFxcAAA///wzwsLCMGHCBHz88ceCEz7j5OSEPXv2kFqp37dvX0RHR6NVq1aio+j06NEj+Pn54ffff8fjx49haWmJO3fuwNHRERs2bBA6Mc1eXvv27SGTyXQ+6FIeF/XQPzIystLvFbXRKuXx0yU/Px8HDx5EcnIyjh49CnNzcwwePJhEX3PKlaQA7fYiAO181K8fUm3PkpmZiZEjRwpvT9W5c2fEx8fD1tZW4/iVK1cwcuRInD59Wkyw56Ayfkw6eFKfMcaqqEuXLnjy5AmKi4tRs2ZNAFD9u+wNoYgLtKOjIxITE9G8eXO9f+/KoJ5PqaCgAFlZWcjLy0OrVq1Qv3590ZEA0J50u3//Pi5evIj27dvD1NQU9+7dQ3x8PAoKCjBw4EDhmTnfy9G1UlWhUJBaqaqkUCgQHh6OrVu3orCwEABQu3ZtTJw4UdiEW3mUq2hFTySoo/7QRiktLQ0XLlxAXl4eOnbsiO7du4uOpBO19ifqKG3k6+7ujsaNGyMgIAB16tQBUPq37ObmhujoaNX9gvqm2OwZqYzf0aNHkZycjB9++AG1atWCm5sb5HI5iclygH4laXntRb7++muMHz9e+Epk6vmUqF4/QkJCNL4u254lKChIULKKJSQkIDw8HMeOHROaIzg4GLVq1dLagyo0NBRPnz7FggULBCWrGJXxY9LBk/qMMVZFLzJpJaKU18vLCxMnTkSvXr30/r0rg3q+wMBAzJs3T9VjVSkvLw/BwcFYtmyZoGSlqE66nT17FhMmTEBubi4aNGiATZs2Yfr06ahVqxZKSkpw+/Zt/O9//0PHjh05n8TySWGlalmPHz/G5cuXUadOHdja2pLajJYaKT20SUhIwKBBg7R+ngUFBdi3b5+wvrTltT8ZMWIEVq9erdqjhUr7EwBwdnYms6dDQUEBwsLCcOLECYSFhak2i+zYsSMSExPRunVrwQm1UXooIpXxc3BwQJ8+fSCXy9G7d28YGBiIjqSBeiWpi4sLgoKCNNqLAEBycjKCg4Nx6tQpQclKUc9H9frxPMr2LJ999pnQHGXv7xQKBXJycvD777/D19dX+P1fcHAwEhISYG1tDQcHBwCl99bZ2dnw8PDQuJ8pO/GvD9THj0kHT+ozxtgrSH1C4dq1a1i9ejW8vb3Rtm1brUkZEZMK1POpe+ONN3Ds2DE0atRI4/i9e/fw9ttv448//tB7JilMun300UewsbHBnDlzsGPHDsTExKBnz55YsmQJgNIb6IcPHyIqKorzSTAfqx4UN7qW0kOb8s7P9+/fR/fu3YWtpJVa+xOAZvunw4cPY/78+fjwww/h4+MDe3t7UpPS6ig9FFGiPn65ubmqBRM3b96EpaUlatSoITjVM9QrSam3F6Gej+r143motGcpOxEuk8lgZmYGFxcXvP3224JSPTN27NhKvU8mkwlpZUR9/Jh08Ea5jDFWReptdwDg119/RUFBARwdHYWtOlJO+qpPKKhvyCN6UoF6PqD0w6ZCoYBCocDjx49Ru3Zt1WvFxcU4cuSIsBV5ovdpqIxz584hKCgIRkZG8PLyQnh4OEaNGqV63dPTE1OmTOF8Es2nC6WVqlJBcaNr0RP1L0J5nSjr1q1bQlfRtmvXrlLtT1jFevfujW+++QaBgYE4cuSI6DgVorhOjvr4qVdADho0iNxDkU6dOiEzM5Ps36u7uztiY2O1Jgd37twJuVwuKNUz1PNRvX48T3p6OolqQ9GVys+zdetW0REqRH38mHTwpD5jjL2k27dvY/r06fj111/h7OyMqKgoBAQE4PDhwwCA5s2bY+vWrbC0tNR7NhGrO18E9XxA6QojmUwGmUwGNzc3rddlMhmmTZsmIJk0Jt0KCwtVD0IMDAxQp04dNGzYUPV6w4YN8eDBA0HpON+/Yc+ePfD29uZJ/Rdw5MgRyWx0TemhjfLBsEwmw7hx4zQqlIqLi/H333+jZ8+ewvLFxcUhLCwMfn5+Gu1PAMDS0lJ4L3Nd0tPTRUfQydzcHNHR0YiJiYGpqalWKzxWMamMH5WHIuqVpGPHjkVoaCju3LlDspIUAOLj43H8+HGd7UXUJw1FtBehmo/69UPpee1ZKKF0fyBFPH6sKnhSnzHGXlJ4eDgUCgUiIyORlJSEjz/+GDVr1sThw4dRXFyMWbNmYd26dZg/f77es6lPGKxfvx6NGjXCiBEjNN4THx+Pe/fuYdKkSfqORz4fAMTExEChUGDcuHFYs2YNTExMVK8ZGBigSZMm5DY7pHRT2LhxY1y7dk3VO3rVqlWwsLBQvZ6Tk6MxSa1vnK/6UZmUkZIGDRrA1NRUdIxKofTQRlmtdP78ebz99tsaG5cbGBjAxsYGAwYMEBUPhoaGmDdvHg4fPowpU6ao2p9QQ739RH5+vurhppeXF7y8vITmqQjFhyJSGj8qpFBJqpSRkaF6YJiVlQUAMDU1hampKTIyMlTvE1UBRjUf9euHUtlqAZlMhhYtWsDPz49cexZK9wdKY8eOrfB3S0TLnfJQHD8mHTypzxhjL+nEiROIjIyEo6MjnJ2d4eLigq+++ko10evn54f//ve/glMCO3bsQHh4uNbxNm3aYObMmcImzZWo5uvatSuA0qqCJk2akGiL8TyUbgoHDx6Me/fuqb7u06ePxuuHDh1Cp06d9JzqGc7HKJg+fToiIiLIbXStC6WHNsoVjDY2Nhg8eDCJVgS6UG9/Ut7PtKCggMSmpd26dcOAAQMgl8vRrVs3Uv3WdQkMDMSMGTPIPPCX0vhNnjxZY/GEKFKoJFWi3l6Eaj6pXD+k1J6F0v2B0htvvKHxdVFREc6fP48///yT3CbIFMePSQdP6jPG2Et6+PCh6oObqakp6tatiyZNmqheb968OXJyckTFU8nJydFY4atkZmbG+Srh8uXLuHHjBjp37gwA2LZtG3bu3InWrVtj/vz5JD6EKlG6KXxei6DJkydr7EWhb5yv+lFcqUqRro2uu3fvTmqja6lwcXHBvXv30LhxYwClrR2SkpLQunVrvP/++4LTlaLY/kS5QlEmkyEuLg716tVTvVZSUoLU1FS0bNlSVDyV0NBQJCUlwdfXF8bGxhg4cCCGDh0Ke3t7obnUW7SoS0pKQr9+/XD//n0A4tuzUB0/XUQvMFGSQiUpqx5SuH4oUarElQr1Cht1a9asQV5enp7TMPbv4Ul9xhh7SY0aNUJOTg6sra0BAGPGjNGY4H348CGJlZfW1tb45ZdftDYfS0tLE9Lvvyzq+cLCwuDv7w8AuHjxIpYtW4YJEybg1KlTWL58uaRW0oiWlpYGe3t7GBoakvjbKIvzVR21laoUSWGja10oPrSZNWsWRo0aBQ8PD+Tk5GD8+PFo27YtkpKSkJOTI3z/EartTzZv3gyg9EHw9u3bNVZwGxgYoGnTpli0aJGgdM+4urrC1dUVubm52L9/P/bu3Yv3338fzZo1g1wuF/bz1dWiRWnatGlk2rNQHT91cXFx2LJlC65evQoAsLW1xbhx4zBy5EixwUC3klSJensR6vmoXz/UUarE1YXi/UF5hg4dipEjR+Kzzz4THUVFSuPH6OFJfcYYe0nt27dHenq6qgWGcuJXKS0tDe3atRMRTcPIkSMREhKCoqIiuLi4AAB+/vlnhIWFYcKECYLT0c/3999/o1WrVgCA77//Hn379sWnn36Kc+fOCf9AVxb1m0IfHx8kJiZqPcChgvNVnlRWqlJEaaLgRVF7aPPnn3+qrsHffvst2rZti+3bt+PYsWNYsGCB8LGm2v7k0KFDAEon3SIjI0lVnOliZGSE4cOHY/jw4bh06RL8/f0RFRUl7Ofbrl07NG7cGAEBAahTpw6A0gckbm5uiI6ORvPmzYXkKg+18VOKiIjA5s2b4enpCUdHRwDAmTNnEBISguzsbEyfPl1oPuqVpNTbi1DPR/36oY5SJW55qN0flCc9PZ1kyyWpjB+jhyf1GWPsJa1du7bC1+3t7dGlSxc9pSnfxIkT8eDBAyxatAiFhYUAgNq1a2PixIn4+OOPBaejn8/AwABPnz4FULqPgvKDiImJCXJzcwUm043yTSH1DyWcr/KkslJVSiiV10vloU1RUZHqw/mJEyfQt29fAEDLli1JTLpRb3+i3vNavRKImvz8fBw8eBDJyck4evQozM3N4e3tLSxPXFwcwsLC4Ofnh7CwMNVmoABgaWmp0cKFAmrjpxQbG4vg4GAMGTJEdaxfv35o164dgoODhU/qU68kpd5ehHo+6tcPqqRyf1D2oYxCoUBOTg5+//13+Pr6CkolnfFj0sGT+owxVkXq5fXqqGxiKZPJMHv2bPj6+uLy5cuoU6cObG1tyXxwp57P2dkZy5Ytg7OzM3777TesXr0aAHD16lVVH04R+KaQiSS1lapSQKm8XioPbVq3bo3t27ejT58+OHHiBGbMmAEAuH37NkxNTYVmA6TR/kSJUiWQ0tGjR5GcnIwffvgBtWrVgpubGzZt2iR8wYShoSHmzZuHw4cPY8qUKfjwww/h4+MjNJMuVMdPqaioCHZ2dlrHO3bsiOLiYgGJNFGvJC0PxfYi6qjko379UEepElcq9wfGxsYaX8tkMrRo0QJ+fn54++23BaWSzvgx6eBJfcYYqyKq5fVl1a9fn8yDBl2o5ps/fz4WLVqE/fv3Y8GCBaoV8EeOHEHPnj2F5ZLiTeHixYvRqFEj0THKxfkqT2orVaWAUiWGVB7a+Pv7Y+rUqfjyyy/h4eGheoh56NAhUtcTqu1P1FH6/VOaOnUq+vTpg9DQUPTu3RsGBgaiI2no3bs3vvnmGwQGBuLIkSOi42ihPn7u7u6IjY1FYGCgxvGdO3dCLpcLSvUM9UrS8lBtL6JEJZ9Urh9KVCpxpXJ/QHXPM6mMH5MOmYLiHRxjjEnIgQMHkJSUhMOHD5Msr2f6sWHDBnzwwQdo0KCBXr6fu7t7pW4KqU2u5ubm4uTJk2jRooVqrwJKON+LOXz4MObPn69aqWpvb4/ExES0bt1adDTJcXJywp49e0islC4oKEBYWBhOnDih8dCmY8eO5H6+xcXFyM3N1egL//fff6Nu3bqqh2CiW8voan8yePBgrb14RKL0+6eUm5sLIyMjAMDNmzdhaWlJduFETEwMTp06hf/+979Cq/jUUR+/4OBgJCQkwNraGg4ODgCAs2fPIjs7Gx4eHqhV69n6w7IT//r0+PFjkpWkz2svIvqhIfV8AM3rR3mVuCNGjMDq1avRtGlTAOIqcaV0f6BEqb2hFMeP0caT+owxVk3Uy+tPnjxJsrye/XucnZ312rpAKjeF06dPR5cuXeDp6YmnT5/C3d0d169fh0KhwMqVK+Hm5sb5JJwPAO7cuYPAwEDk5eXhzJkzpH7/WNW8Kg9t9H1+VtLV/kQul5Npf6JO2bqtXr16oqPoJOpnWJHy2i9SRHH8xo4dW6n3yWQyxMTE/MtppKfsgw6ZTAYzMzO4uLgIbS+iRD1fZen7b6d9+/blVuIqj1OoxJXS/QHF85+Uxo/Rxu13GGOsmkihvJ79e/T9jFwqPX1Pnz6NKVOmACitalEoFEhNTcXu3buxdu1a4ZPSnK/qzM3NER0djZiYGJiamqpWhrIXR6W8Xol6e5HKErWGiXr7E3UU2p1UhOI6NKm0XwRojp/6Rs3sxVFtL6JEPV9l6ftvRyrtWaR0f0Dx/Cel8WO00b3zYIwxicnPz8e+ffvg6+uLYcOG4Z9//oG3t7foWOwVp7wpPH36dKVXvenTo0ePVGXNR48exYABA1C3bl306dMHmZmZgtNxvqrKz89X/dvLywtRUVFkWk9QduHCBZ3/JSUl4bffflN9TYHyoY2bmxv69OnDD21ewPHjxxEREYH+/fvj7t27KCkpER1JQ15eHlavXo0PPvgArq6u6Nevn8Z/rGKhoaHIy8uDr68vevXqhaVLl+K3334THUsSCgsL0aFDB2RkZIiO8kpYuHAh7t27JzpGuajnoyQuLg7/+c9/4Ofnh3/++Qc2NjaqljvKPYuotNbk+4Oq4fFj1YFX6jPGWBXpKq/ftGkTyfJ69mqivFLa2toa6enpMDExwdGjR7Fy5UoAwMOHD0n0peV8VSOllaqUSGWja/X2Il5eXvDy8hKaR2rUz8WDBg0iV/4fFBSElJQUuLu7w8LCAjKZTHSkck2ePFmj7zUFrq6ucHV11Wi/+P7775Nsv0ht/AwMDGBtbU3uQZdU7dmzB97e3iR6hutCPR8lUqnEldL9QXp6uugIWqQ0fow2ntRnjLEqklJ5PXv1UL8p9PLywuzZs1GvXj1YW1vjrbfeAgCkpqaibdu2gtNxvqoKDQ1FUlISfH19eaPwFyCV8np+aFN9KJb/HzlyBOvXr8ebb74pOspzTZo0SXSEckmh/SLF8Zs8eTJWrlyJFStWwNTUVHQcSaN4flFHPR9F1NuzSO3+gFp7Q6mNH6OLJ/UZY6yKjh8/rlqNd/PmTVhaWvKFmekN9ZvCMWPGwMHBATdu3ED37t1V+Zo1a4YZM2aIDQfOV1VSWqlKSVxcHMLCwuDn56ex0TXwrLyeglfloQ3lFegiNWjQgPxkalxcHLZs2YKrV68CAGxtbTFu3DiMHDlSbDA1+fn5OHjwIJKTk3H06FGYm5uTab9Iefy2bduGzMxM9OzZE02aNNHapHn37t2CkjH2jMjrB+VKXKr3B+W1LlRuBn///n0ApRsSi0R1/Jj0yBT82JQxxqqNs7MzufJ6ph8+Pj5YunQpLC0t9fp9Dxw4gKSkJBw+fJj8TWFaWhrs7e1JtI3RhfNVD+VK1YsXLwpvH0Pd4cOHMX/+fFV5vb29PRITE9G6dWvR0TSoP7Q5efKk5B7aODk5Yc+ePUKvzevXr8fo0aPRoEEDYRnKSkxMxMGDBxEaGoq6deuKjqMlIiICmzdvhqenJxwdHQEAZ86cwddff43x48dj+vTpQvPpar8ol8vJtF+kPn6RkZEVvi6V8wt7tYm6fqhX4lJG7f6gffv25bY3VB6n0N5Qidr4MenhSX3GGKtGFCYO2OtJCjeF1B96cb6Xp2ul6uDBg+Hv7y86Gnl37txBYGAg8vLycObMGZKT+uqoPrQpKCjAzZs30bhxY5IPvpQfuURXDSj3c1DKzMyEQqFA06ZNUauWZhG36JXSLi4uCAoKwpAhQzSOJycnIzg4GKdOnRKUrJSDgwP69OkDuVxOsv0i9fFj1Ytae5GyqOdTKBQoKSlBzZo1RUcBUHrPR7kSVxcK9wfu7u6Vam9IpSJSHYXxY9LD7XcYY4wxHQoLC7Fq1SocOHAAJiYm+OCDDzBixAjV63fu3EHPnj3J3HRJoacv9XUEnO/F8UbhVUe5vF6JWnuRXbt2oUWLFnByckJ+fj4WLVqEhIQEKBQK1KhRA8OHD0dQUBCJyX1q7U/69+8v5Pu+jKKiItjZ2Wkd79ixI4qLiwUk0kS9/SL18WMvh3p7Eer5ioqKsGbNGqSlpaFr167w8/PDxo0bERkZiaKiIgwePBjBwcHCrx9Sac9C7f5AKu0NlaiNH5MentRnjLFqNHnyZJiYmIiOwarBunXrkJiYiAkTJuDhw4dYvnw5zp49i8WLF6veQ2mSlW8KmQi8UXjVUN/omupDm6ioKKxcuRIAsHr1apw8eRIRERFo2bIlrly5grCwMKxevRoBAQFCc5bX/iQkJATZ2dlC2p9QetD7PO7u7oiNjUVgYKDG8Z07d0IulwtK9Yz6A7hBgwaRq6SiOH5du3bFd999BzMzM3Tp0qXCypWUlBQ9JpMOZbWNrnvQadOmCW8vQj1fZGQk4uPjIZfLsX//fty9exeHDx/G4sWLUVJSgpUrV2LLli3w8fERkk+J+p5FVO8PDA0NMW/ePBw+fBhTpkxRtTekhur4Menh9juMMVaNqJTXs6obMGAAAgMD8c477wAobVHg4+ODN998EyEhIbh79y6JlfrUe/qqU67SKrsZHhWc78Xl5uaSXqlKHfXyeqrtRezt7bF//340adIEbm5umDdvHnr16qV6PTU1FQEBAfjxxx8FppRW+5OFCxfCz88PZmZmoqOoBAcHIyEhAdbW1nBwcAAAnD17FtnZ2fDw8NBoF1R24lrfKLZfpDh+u3fvxuDBg2FoaPjc9k7Dhg3TSyapod5ehHq+/v37Y968eXjnnXeQmZmJd999F59//jkGDRoEANi3bx/Wrl2LpKQkIfkqQqk9C9X7A3WU2xtKYfyYNPBKfcYYqwbUyutZ1d26dQtt2rRRfd28eXNs3boVXl5emD17NmbPni0w3TNSWilNYWVlRTjfi6O+UpU66uX1VNuLWFhYICsrC02aNMGTJ0/QsGFDjdfNzMzw4MEDMeHUSKn9yZ49e+Dt7U1qUj8jI0PVOiErKwsAYGpqClNTU2RkZKjexwspdKM4fuoT9Txp/3Kotxehnu/27duq1j/NmzeHgYEB2rVrp3rd3t4e169fFxVPC9VKXKr3B+ootzeUwvgxaeBJfcYYqyKK5fWs6szNzXHt2jU0bdpUdczKygoxMTHw8vISvipQifpNYV5eHjZs2ICTJ0/i7t27KCkp0Xj94MGDgpKV4nzVh4s/Xxz18nqqD23kcjlWr16NDRs2wN3dHVFRUfj8889Rv359PHnyBGvWrIGzs7PomCTbn5SH4t/v1q1bRUeoNIrtF6UwfiUlJcjMzMTdu3e1fgcpVhxSQL29CPV8xsbGePjwIaytrQEAHTp00LjWFRQUkHhQSL09C9X7AyXq7Q2pjx+TDp7UZ4yxKoqNjUVwcLBGeX2/fv3Qrl07BAcH86S+RLm4uCApKQndunXTOK6c2B87dqygZJqo3xQGBQUhJSUF7u7usLCwIPFBSR3nYxTwRtcv5pNPPkFGRgb69+8POzs7nD59Gj169ICVlRVu374NU1NTbNq0SXRMAEB8fDyOHz+us/3JsmXLVO+j8qCYisLCQjg4OCAhIQFt27YVHee5Jk2aJDqCBimM35kzZzBr1ixkZ2drnV9E9lyXit69e+Obb75BYGAgjhw5IjqOFqr5WrVqhT/++EO1On/79u0ar2dkZKhaBIkkpUpcSvcHSt26dSPd3lAdxfFj0sGT+owxVkVSKq9nlefr64u//vpL52tWVlbYunUrTpw4oedUFaN4U3jkyBGsX78eb775pugoOnG+6kNxpapUUC2vp8rQ0BBr167FkSNH8OOPP6JGjRpQKBSwsLCAs7MzhgwZQmLvCYrtT8qTnp4uOoIGAwMDWFtba1UnUUO1/aIUxm/BggWws7PDhg0b+KH1S6LcXgSgmW/RokUa+0mUVVRUhIkTJ+oxkW7UK3Gpo97ekLHqwhvlMsZYFQUHB6NWrVpaq+xCQ0Px9OlTLFiwQFAy9rqhuFFf3759ER0djVatWomOohPnqz68UfiLk9JG1+vXr8fo0aPRoEED0VHYvyQwMBAzZsyAlZWV6CgASifMDxw4gBUrVsDU1FR0HC3ltV/8+uuvMX78eOGVmtTHz9HREYmJiSRWRUuRensRiqjnkxJnZ2dylbjqKN8fqLc3PHnyJJn2huoojx+jjyf1GWOsioKDg5GQkABra2ud5fXqq0G4vF5a7t+/j4sXL6J9+/YwNTXFvXv3EB8fj4KCAgwcOJDcRCvFm8LExEQcPHgQoaGhqFu3rug4Wjhf1VFdqSoFDg4O6NOnD+RyuWTK66k+tFm4cCH8/PzIbPRKuf3JhQsXdB4fMWIEVq9erdpLRrmZpCgeHh7IzMxEUVERmjRpolV9sXv3bkHJSrm4uCAoKEij/SIAJCcnIzg4GKdOnRKUrBT18fPy8sLEiRPRq1cvoTmkytnZmXR7Eer51E2aNAlLliyBpaWl6Cg6UVy0o476/YGSsr3hxYsXSbX3ksr4MZq4/Q5jjFWRlMrrWeWdPXsWEyZMQG5uLho0aIBNmzZh+vTpqFWrFkpKShAdHY3//e9/6Nixo+ioKlR6+np4eGj8vmdmZqJ79+5o2rSpVsmziEkFzld9eKPwqpFCeb1UHtrs2bMH3t7eZCb1Kbc/UZ5jdK3tmjZtGhQKBYme5v379xf6/Z+HevtFiuOn/kBp7NixCA0NxZ07d9C2bVut65voh0rUUW8vQj2futTUVOTn54uOITlSuD+g3N5QCuPH6OOV+owxxpgOH330EWxsbDBnzhzs2LEDMTEx6NmzJ5YsWQKgtOri4cOHiIqKEpyU3k1hZGRkpd8rovyV81Uf6itVpYRieT319iLqKK5kpNr+xN3dHY0bN0ZAQADq1KkDoHSloJubG6Kjo1XtUGxsbETGJI/bL7649u3bl/tACYDqNQoPlaSCensR6vkAmtcPdRQrcanfH1Bvb0h9/Jh08KQ+Y4xVAeXyelY1Xbt2RWxsLFq1aoXCwkJ06tQJO3bsQKdOnQAA586dw5QpU3DkyBGhOfmmkInUuXNnxMfHw9bWVuP4lStXMHLkSJw+fVpMMAmiOKkgpYc2FMePavuTgoIChIWF4cSJEwgLC1NVG3bs2BGJiYlo3bq1kFxSw+0XX9z169cr/V5+qPTiqLYXUaKab8iQIYiOjoa1tbXoKDpRbM9C/f6AentD6uPHpIPb7zDGWBVQLq9nVVNYWKja4MvAwAB16tRBw4YNVa83bNgQDx48EJTumdjYWAQHB2vcFPbr1w/t2rVDcHAwqUl9aj2vy+J8L87d3R2xsbFaE1Y7d+6EXC4XlIpVF+rtRdSlp6eLjqCFYvsTADA0NMS8efNw+PBhTJkyBR9++CF8fHxExwJQ+kD9u+++g5mZGbp06VLhJFZKSooek2mj2H6R+vipT9SvX78ejRo1wogRIzTeEx8fj3v37pFpKUgd5fYiAP18QOlEKkXUKnHVUb8/oN7ekPr4MengSX3GGKuiyZMnY+XKleTK61nVNG7cGNeuXVNtGLhq1SpYWFioXs/JydGY5BdFSjeF1Hpel8X5Xk58fDyOHz+uc6XqsmXLVO/jlaoVmzx5MkxMTETH0ED9oc0bb7yBY8eOoVGjRhrH79+/j+7duwtfCUqpvYQuvXv3xjfffIPAwEDhVWdKgYGBqomYuXPnCk5Tsa1bt4qOoEVK47djxw6Eh4drHW/Tpg1mzpzJk/rPoau9yKZNm8i0F6GeLzU1tcLXReekvmcR9fsD5XkQAAYNGkSuvSH18WPSwZP6jDFWRdu2bUNmZiZ69uxJqryeVc3gwYNx79491dd9+vTReP3QoUOqVjwiSemmkHrHP8734iiuVJUqqhNYlB/alPc3UVBQQK7Unipzc3NER0cjJiYGpqamGhMhIgwbNkznv6mh2n5RKuMHlC6OUF8soWRmZoacnBwBiaRl6tSp6NOnD0JDQ0m2F6Geb+zYsVrH1O9VRD8UlkIlLuX7A3UU758B6Ywfo40n9RljrIqoltezqnneCsvJkyejZs2aekpTMb4pZKJQXKkqNZTL66k+tImJiVF937i4OI2H6SUlJUhNTUXLli31mkmJevsTdfn5+ao2c15eXvDy8hKaR5eSkhJkZmbi7t27WhMzIlfSSqX9ItXxAwBra2v88ssvWqtn09LSYGlpKSiVdFBvL0I9X9mV+oWFhTh//jwiIiIwc+ZMQameoV6JS/X+QCp4/Fh14Y1yGWOMsUpKS0uDvb09DA0NRUdR0bXSSBeZTKaaCGOsOlBdqSolvNH1y+nbty8AIDs7G40bN9aYKDIwMEDTpk3h5+enetCpT7t378bgwYNhaGj43Eo90SupnZ2dMWDAAMjlcnTr1o3UhBtQ+rcwa9YsZGdna01Iy2Qy4Stp4+LicODAAbLtF6mPX3R0NDZu3IiAgAC4uLgAAH7++WeEhYVhwoQJ+Pjjj4XmkxJnZ2dy7UXUUc+nLiUlBcuXL8euXbuE5ggODkatWrW0FuSEhobi6dOnWLBggaBk0rN+/XqMHj0aDRo0EB2FsWrHk/qMMcZYJUnpQwlVgYGBmDFjBqysrERH0YnzvZh+/fohKioK7du3Fx1FklxcXBAUFKRRXg+UbtoXHByMU6dOCUomjYc2Y8eORWRkJLm9CKTiwIEDSEpKwuHDh2FsbIyBAwdi6NChsLe3Fx0NQGl7OVtbW/j5+cHCwkJrxaKxsbGgZKU8PDyQmZmJoqIiku0XqY+fQqFAeHg4tm7disLCQgBA7dq1MXHiRPL7UVDj5OSEPXv2kL0/pZ5P3eXLlzFixAjhm68HBwcjISEB1tbWOitxa9V61nRD35W4Urg/UKec8qSy6l1q48do4/Y7jDH2EqRUXs+qD7Xn4JRvCi9cuKDzeFJSEvr164f79+8DgLDJYM5XPXij8KqhXF4vhfYi6u2fKFZSAbTbn7i6usLV1RW5ubnYv38/9u7di/fffx/NmjWDXC4XPrGamZmJL774As2bNxeaozzU2y9SHz+ZTIbZs2fD19cXly9fRp06dWBra0vub5i9mnTdZ92+fRvR0dHC760A2u1ZpHB/ANBtbyiV8WPSwCv1GWPsJUipvJ5VH4orjaiulG7fvj1kMpnOByHK4yLL/zlf9aC+UpU66uX11NuLqKNYSUW9/Ykuly5dgr+/Py5evCg8n5eXFyZOnIhevXoJzSFVPH6vD+rtRSjmK+8+y9HREUuXLkWrVq0EJZMG6vcH1NsbUh8/Jh08qc8YY4xVknKVdNmJS5Go3hS6u7ujcePGCAgIQJ06dQCUVjq4ubkhOjpatXLQxsaG80kwn1JkZGSFr4te6Usd5fJ6QFoPbSg+dKXe/kQpPz8fBw8eRHJyMo4ePQpzc3MMHjwY/v7+es+ivnr22rVrWL16Nby9vdG2bVuNvwdAfKUSRTx+rydq7UXKopjv+vXrGl/XqFEDZmZmqs3DRaJciatE/f6AcntDgP74Meng9juMMVYNKJfXs+ojl8uRm5uLH374AS1atCCximfbtm3IzMxEz549Sd0UxsXFISwsDH5+fggLC1OVEAOApaWl8Mlozlc9eNK+aiiX1wP024tQR739ydGjR5GcnIwffvgBtWrVgpubGzZt2iT0vsXDw0Nr9ezcuXNV/xZdqUS9/SL18WPVi2p7ESXK+dTvo27evAlLS0sym4VLoT0L9fsDyu0NAfrjx6SDJ/UZY6yKpFhezypv+vTp6NKlCzw9PfH06VMMHz4c169fh0KhwMqVK+Hm5iY0H9WbQkNDQ8ybNw+HDx/GlClT8OGHH8LHx0d0LBXOxyhQ7wlPkZQe2ixevBiNGjUSHUNDp06dkJmZSXZSf+rUqejTpw9CQ0PRu3dvGBgYiI6EgwcPio5QocDAQBgZGQHQnCyngvr4sepTXnuRkJAQZGdnC28vQj2fukGDBpFr30Z9zyLq9wfu7u6IjY3VqnLcuXMn5HK5oFTPUB8/Jh3cfocxxqpIKuX17OX06NEDX375Jdq3b4+kpCSsWbMGiYmJ2L17N3bu3ImEhATREcm7c+cOAgMDkZeXhzNnziAxMRGtW7cWHUuF870Y6itVpUIK5fXsxUmp/Ulubq5qgpraSlWgtA93o0aNMGLECI3j8fHxuHfvHiZNmiQomTTw+L3aqLcXoZ5PHcX2bdyepWqotzdkrLrwSn3GGKsi6uX1rGoePXoEExMTAKWtCgYMGIC6deuiT58+CAsLE5xOGszNzREdHY2YmBiYmpqqJpGo4HwvhvpKVamgWl4vpYc2eXl52LBhA06ePIm7d+9qjaWIVctSan+ifi6huFJ1x44dCA8P1zrepk0bzJw5k8SkNOX2i1IYP/byqLcXoZ6POoqVuFK6P6DY3lBK48ekgyf1GWOsiqiX17Oqsba2Rnp6OkxMTHD06FGsXLkSAPDw4UMYGhoKySSlm8L8/HzVpmNeXl7w8vISmqcszvfihg0bpvPf7MVRLK+X0kOboKAgpKSkwN3dXWelnAhSbX9CsXg7JycHFhYWWsfNzMyQk5MjIJEm6u0XqY8fqxrq7UWo51M3efJk1QIeKii2Z5HS/QHF9oZSGj8mHTypzxhjL0G9vH7s2LEIDQ3FnTt3SJbXs6rx8vLC7NmzUa9ePVhbW+Ott94CAKSmpgprmSGlm8Ju3bphwIABkMvl6NatG6nWDgDnqw6UV6pSR3Gjayk9tDly5AjWr1+PN998U3QUFfXNF7n9SdVYW1vjl19+0aoeSEtLg6WlpaBUzyxYsAB2dnbYsGEDmYdK6qiPH6u6+Ph4HD9+XGd7kWXLlqneJ6q9CPV8Snwurhyp3B9QbW8olfFj0sKT+owx9hKkVF7PqmbMmDFwcHDAjRs30L17d9WkarNmzTBjxgwhmaR0UxgaGoqkpCT4+vrC2NgYAwcOxNChQ2Fvby86GgDOV1XUV6pSR7G8vizKD20aNGhApsJBFym1P6G4UnXkyJEICQlBUVERXFxcAAA///wzwsLCMGHCBMHp6LdfpD5+rGootheRUj4AiIuLw5YtW3D16lUAgK2tLcaNG4eRI0cKySOlSlyA7v0B1faGZVEdPyYtvFEuY4y9hOvXr1f6veqr9pi0paWlwd7eXljbnfJI4aYwNzcX+/fvx969e3Hy5Ek0a9YMcrmcTHkx53s5vFH4q436Q5vExEQcPHgQoaGhqFu3rtAsutjb22Pfvn1aK6WvXbuGQYMG4bfffhOUTJvy50tptblCoUB4eDi2bt2KwsJCAEDt2rUxceJE4ec+oLSSb+LEiejVq5foKDpRHz/GRIqIiMDmzZvh6ekJR0dHAKXXvK+//hrjx4/H9OnT9Z5p9+7dGDx4MAwNDZ9bqSd6UQ/1+4O4uDgcOHCAVHtDddTHj0kHT+ozxlgVcXn968PZ2ZncRoJSvCm8dOkS/P39cfHiRc73Eijlc3R0RGJiItmVqqxqKD60UVbKKWVmZkKhUKBp06Za7e9EtC9SN2DAAHzyySdwd3fXOJ6QkIA1a9aQ6L9PbaWqLo8fP8bly5dRp04d2NraCn2wrt5+8dq1a1i9ejW8vb1Jt1+kNH6selBtL6JEPR8AuLi4ICgoCEOGDNE4npycjODgYJw6dUpQMmmgeH+gzsPDA5mZmSgqKiLT3lAd9fFj0sHtdxhjrIqkVF7Pqobic3DqPX2V8vPzcfDgQSQnJ+Po0aMwNzeHt7e36FgqnO/l8EbhL05K5fUU24tIoWWREvX2J+WtVA0JCUF2draQlaq61K9fH506dRIdA4A02y9SGj9WPai3F6GeDwCKiopgZ2endbxjx44oLi4WkEgb5UpcivcH6qjfK1AfPyYdPKnPGGNVlJOTAwsLC63jZmZmyMnJEZCIvU6o3xQePXoUycnJ+OGHH1CrVi24ublh06ZNwj+MKHG+F8cbhVeNlDa6pvjQRkptQyZOnIgHDx5g0aJFWu1PPv74Y8HpgNjYWAQHB2usVO3Xrx/atWuH4OBgMpP6lFCormAMKN0HY+XKlWTbi1DP5+7ujtjYWK1Nenfu3Am5XC4o1TPUK3Ep3h+oo36vQH38mHRw+x3GGKsiKZTXs+qRlJSEfv36aZVwikS9p6+DgwP69OkDuVyO3r17w8DAQHQkDZzvxbVv315rpao6iitVWeVJsb0IACxcuBB+fn4wMzMTHUUL1fYnnTt3Rnx8PGxtbTWOX7lyBSNHjsTp06fFBJMIbr/IRKLeXoR6vuDgYCQkJMDa2hoODg4AgLNnzyI7OxseHh4a17uyE//6QLE9i1TvD6jg8WP/Bp7UZ4yxKoqOjsbGjRsREBCgs7yewmo89mqR0k1hbm6ualXyzZs3YWlpiRo1agjNpI7zvTjeKLx6USuvl+pDG4p7nlAXHByMWrVqaU1YhYaG4unTp1iwYIGgZNLQt29fhIeHw9nZWeP4r7/+ipkzZ+LQoUOCkrHXQWRkZIWvi16pTD3f2LFjK/U+mUyGmJiYfzmNNop7FlG/P6De3pD6+DFp4kl9xhirIoVCgfDwcGzdulWrvF70DSurury8PGzYsAEnT57E3bt3tfqDiqjEkOpNIfVJN8734nilatVQLK+X6kMbJycn7Nmzh9TfB3XUV6pSZ29vj3379mn9zl27dg2DBg3Cb7/9JigZY0zqKFbiUr8/2L17NwYPHgxDQ8PnVoIMGzZMT6meoT5+TJq4pz5jjFWRTCbD7Nmz4evrS7K8nlVNUFAQUlJS4O7uTmYjWqm2dKK+joDzvTjeKLxqKG50rf5Bkh/avNoyMjLQoUMHAEBWVhYAwNTUFKampsjIyFC9j8LvJUXW1tb45ZdftCb109LSYGlpKSgVY0yqqO9ZRP3+QH2iXsSk/fNQHz8mTTypzxhj1aR+/fro1KmT6Bismh05cgTr16/Hm2++KTqKCt8UMip4o/Cqob7RtZQe2qSnp4uOIDlbt24VHUHSRo4ciZCQEBQVFelsv8hYdaPeXoR6PnVjx46tMJ+IljseHh5albhz585V/ZtSJa4U7g+otTdUJ4XxY9LAk/qMMcZYBRo0aABTU1PRMcolpZvCyZMnw8TERHSMcnG+F8crVaumU6dOyMzMJDupL7WHNoGBgZgxYwasrKxERyGvsLAQDg4OSEhIQNu2bUXHkaSJEyfiwYMHWLRokVb7Rd5Pif0bAgMDVfvsqE/2UkE9n7o33nhD4+uioiKcP38ef/75Jzw8PIRkklIlLvX7A4rtDdVRHz8mHTypzxhjjFVg+vTpiIiIQGhoKOrWrSs6jhYp3RRSesCgC+d7cbxS9cVRL69XR/WhjfoYqktKSkK/fv1w//59AOLHjzIDAwNYW1tr7RPDKo/bLzJ9o95ehHo+deU9dFizZg3y8vL0nKaUlCpxqd4fKFFsb6iO+vgx6eBJfcYYY6wMZfmrUmZmJrp3746mTZtqTbo9byOmf5sUbgrj4uKwZcsWXL16FQBga2uLcePGYeTIkWKD/R/O9/J4peqLk1J5PdWHNrrGUGnatGlkxo+6yZMnY+XKlVixYgXpijTquP0iE4VyexGAfj5dhg4dipEjR+Kzzz4TmoN6JS7V+wMl6u0NqY8fkw6e1GeMMcbK6N+/v+gIlUb9pjAiIgKbN2+Gp6cnHB0dAZSWxIaEhCA7OxvTp0/nfBLOxytVX5yUyuupPrRp164dGjdujICAANSpUwdA6UbSbm5uiI6OJvshnppt27YhMzMTPXv2RJMmTVCvXj2N10U/tGaMlY96exHq+cqTnp5O4h6GeiUu1fsDJertDamPH5MOmULXEhfGGGOMSYJCoUB4eDi2bt2qdVM4depUwekAFxcXBAUFYciQIRrHk5OTERwcjFOnTglKVorzMZGol9crPX78mNRDm4KCAoSFheHEiRMICwtDhw4dAAAdO3ZEYmIiWrduLTSfVERGRlb4OoVrCGNMN3d3d9ja2sLPz09nexFjY2NByUpRz1f2/KZQKJCTk4Pff/8dvr6+ws9/AwYMwCeffAJ3d3eN4wkJCVizZg2ZBQKU7g/UW/Ndu3YNq1evhre3N8n2hkqUxo9JE6/UZ4wxxipp4cKF8PPzg5mZmegoKtRXShcVFcHOzk7reMeOHVFcXCwgkSbOx0SiXl6vRK29iKGhIebNm4fDhw9jypQp+PDDD+Hj4yM6luSInrRijL086u1FqOcr+1BBJpOhRYsW8PPzw9tvvy0o1TPUK3GVKN0fSKm9oRKl8WPSxJP6jDHGWCXt2bMH3t7epCb1lajeFLq7uyM2NhaBgYEax3fu3Am5XC4o1TOcj4lEvbyeut69e+Obb75BYGAgjhw5IjoOY4zpDfX2ItTzLVu2THSECnF7lhdHpXqBMX3iSX3GGGOskrhj3cuJj4/H8ePH4eDgAAA4e/YssrOz4eHhofGhquzENeeTRj728qSw0TV15ubmiI6ORkxMDExNTWFkZCQ6Emldu3bFd999BzMzM3Tp0kWrJYa6lJQUPSZjjD2PenuRsWPHIjQ0FHfu3CHTXoR6vvJwJe6rwcbGRvVvqbQ3ZKyquKc+Y4wxVklOTk7Ys2eP1gQcK9/YsWMr9T6ZTIaYmJh/OY02zsdEio6OxsaNGxEQEKCzvJ5X41UsPz8ftWvXFh1DUnbv3o3BgwfD0NDwuRvhDhs2TE+pGGOV0b59e632IupEtxehnq88zs7OSExM5Pv7V0jfvn0RHh4OZ2dnjeO//vorZs6ciUOHDglKxlj14kl9xhhjjDHGBKC+0TV1zs7OGDBgAORyObp164YaNWqIjsQYY/+a69evV/q96quW9YV6vvLwop1Xj729Pfbt26f1M7127RoGDRqE3377TVAyxqoX3/kyxhhjLyAwMBC3bt0SHUMSCgsL0aFDB2RkZIiOohPnY6Ipy+t//vln7NixA4mJiUhJSeEJ/UoKDQ1FXl4efH190atXLyxdupQ/qL+gkpISXLlyBadPn0ZqaqrGf4wxWmxsbFT/JScn4+eff9Y4ZmNjg59//hl79+7lfOy1pmxvWBa3N2SvGu6pzxhjjOmg3hdUXVJSEvr164f79+8DoNUTlBoDAwNYW1ujpKREdBSdOB+jgupG19S5urrC1dUVubm52L9/P/bu3Yv3338fzZo1g1wu54cjz3HmzBnMmjUL2dnZWu0yqLXHYIxp2rFjB8LDw7WOt2nTBjNnzhTeM5x6PnXp6emiI7BqNnLkSISEhKCoqEhne0PGXhXcfocxxhjToaK+oFR7glIUFxeHAwcOYMWKFTA1NRUdRwvnY+zVcunSJfj7++PixYt8fn4Od3d32Nraws/PDxYWFlqb5hobGwtKxhh7HurtRajnKyswMBAzZsyAlZWV6CisGnB7Q/a64JX6jDHGmA7t2rVD48aNERAQgDp16gAovUF0c3NDdHQ0mjdvLjihNGzbtg2ZmZno2bMnmjRpgnr16mm8/ryNGv9tnI8x6cvPz8fBgweRnJyMo0ePwtzcHN7e3qJjkZeZmYkvvviCr2eMSZCyvUjZSXMq7UWo5uNK3NeDsr2hr68vLl++jDp16sDW1haGhoaiozFWrXhSnzHGGNMhLi4OYWFh8PPzQ1hYGDp06KB6zdLSktQGX5T1799fdIQKcT7GpOvo0aNITk7GDz/8gFq1asHNzQ2bNm1Cly5dREeThE6dOiEzM5Mn9RmTIOrtRajm8/DwKLcSd9q0aVyJ+4rh9obsVcftdxhjjLEKHD58GPPnz8eHH34IHx8f2NvbIzExEa1btxYdjTHGXmsODg7o06cP5HI5evfuDQMDA9GRyFNfpXrt2jWsXr0a3t7eaNu2LWrV0lzvxStVGaOLensRqvnc3d0rVYnLi3cYY1LAk/qMMcbYc9y5cweBgYHIy8vDmTNneFKfMcYIyM3NhZGREQDg5s2bsLS0RI0aNQSnoq2i/WIA3jOGMal5/Pgx6fYi1PIVFBQgLCwMJ06c0KjE7dixI9/fM8Ykhyf1GWOMsUqKiYnBqVOn8N///heNGzcWHYesrl274rvvvoOZmRm6dOmitfmiupSUFD0mK8X5GHv1ODs7IzExUat/M9N0/fr1Sr+XV6oyxl5VXInLGHsVcE99xhhjrAL5+fmoXbs2AMDLywteXl6CE9EXGBioWj07d+5cwWm0cT7GXj28Tqly1Cfq169fj0aNGmHEiBEa74mPj8e9e/cwadIkfcdjjDG96N27N7755hsEBgbiyJEjouMwxthL4ZX6jDHGWAWcnZ0xYMAAyOVydOvWjVs7MMYYQU5OTtizZw+v1H8Bffv2RXh4OJydnTWO//rrr5g5cyYOHTokKBljjOkPV+IyxqSKV+ozxhhjFQgNDUVSUhJ8fX1hbGyMgQMHYujQobC3txcdTTJKSkqQmZmJu3fvaq2m7dKli6BUz3A+xqRv8uTJMDExER1DUnJycmBhYaF13MzMDDk5OQISMcaYfnAlLmPsVcCT+owxxlgFXF1d4erqitzcXOzfvx979+7F+++/j2bNmkEul2Pq1KmiI5J25swZzJo1C9nZ2VoT0hQ2YuR8jL0auFXMi7O2tsYvv/yiVd2QlpYGS0tLQakYY+zf161bN67EZYxJHrffYYwxxl7QpUuX4O/vj4sXL/Kk6nO4u7vD1tYWfn5+sLCw0Nr01djYWFCyUpyPMWmLi4vDli1bcPXqVQCAra0txo0bh5EjR4oNJgHR0dHYuHEjAgIC4OLiAgD4+eefERYWhgkTJuDjjz8WnJAxxv4dBw4cQFJSEg4fPsyVuIwxyeJJfcYYY6wS8vPzcfDgQSQnJ+Po0aMwNzfH4MGD4e/vLzoaaY6OjkhMTETz5s1FR9GJ8zEmXREREdi8eTM8PT3h6OgIoLS65euvv8b48eMxffp0sQGJUygUCA8Px9atW1FYWAgAqF27NiZOnMhVaIyx14J6Je7Jkye5EpcxJik8qc8YY4xV4OjRo0hOTsYPP/yAWrVqwc3NDXK5nHuZV5KXlxcmTpyIXr16iY6iE+djTLpcXFwQFBSEIUOGaBxPTk5GcHAwTp06JSiZtDx+/BiXL19GnTp1YGtrC0NDQ9GRGGNM77gSlzEmNdxTnzHGGKvA1KlT0adPH4SGhqJ3794wMDAQHYm8CxcuqP49duxYhIaG4s6dO2jbti1q1dK89Wjfvr2+43E+xl4RRUVFsLOz0zresWNHFBcXC0gkTfXr10enTp1Ex2CMMb3TVYnr7e0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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "get_preference_counts(user_intersting_clips_3p5)" ] }, { "cell_type": "code", "execution_count": 56, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:02.332947Z", "start_time": "2024-05-26T00:25:02.010694Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:33:52.454787Z", "iopub.status.busy": "2024-12-18T04:33:52.454628Z", "iopub.status.idle": "2024-12-18T04:34:28.396858Z", "shell.execute_reply": "2024-12-18T04:34:28.396255Z", "shell.execute_reply.started": "2024-12-18T04:33:52.454771Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "first gen\n", "len pos models: 394796\n", "differing counts: 105666\n", "chirp-v3p5-engine-b-r_win_over_chirp-v3p5-engine-b-r, win ratio 1.000, (1.000, 1.000), counts 406, total 406.\n", "chirp-v3p5-engine-b_win_over_chirp-v3p5-engine-b, win ratio 1.000, (1.000, 1.000), counts 261, total 261.\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-8, win ratio 1.000, (1.000, 1.000), counts 183616, total 183616.\n", "chirp-v4-engine-b_win_over_chirp-v4-engine-b, win ratio 1.000, (1.000, 1.000), counts 970, total 970.\n", "chirp-v4-h-s-31-l-30-2_win_over_chirp-v4-h-s-31, win ratio 0.500, (0.217, 0.783), counts 6, total 12.\n", "chirp-v4-h-s-31_n_tag_3_win_over_chirp-v4-h-s-31, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-s-31_s_15_full_win_over_chirp-v4-h-s-31, win ratio 0.667, (0.133, 1.200), counts 2, total 3.\n", "chirp-v4-h-s-31_temp_s_80_win_over_chirp-v4-h-s-31, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-s-31_win_over_chirp-v4-h-s-31, win ratio 1.000, (1.000, 1.000), counts 18, total 18.\n", "chirp-v4-h-s-31_win_over_chirp-v4-h-s-31-l-30-2, win ratio 0.500, (0.217, 0.783), counts 6, total 12.\n", "chirp-v4-h-s-31_win_over_chirp-v4-h-s-31_s_15_full, win ratio 0.333, (-0.200, 0.867), counts 1, total 3.\n", "chirp-v4-h-s-31_win_over_chirp-v4-h-s-31_temp_s_70, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-s-31_win_over_chirp-v4-h-s-32, win ratio 0.468, (0.461, 0.475), counts 9409, total 20114.\n", "chirp-v4-h-s-32_n_tag_3_win_over_chirp-v4-h-s-32, win ratio 0.504, (0.494, 0.514), counts 4623, total 9169.\n", "chirp-v4-h-s-32_step_10_win_over_chirp-v4-h-s-32, win ratio 0.505, (0.495, 0.516), counts 4520, total 8947.\n", "chirp-v4-h-s-32_step_16_text_1_win_over_chirp-v4-h-s-32, win ratio 0.489, (0.474, 0.504), counts 2143, total 4383.\n", "chirp-v4-h-s-32_step_16_win_over_chirp-v4-h-s-32, win ratio 0.507, (0.497, 0.518), counts 4575, total 9018.\n", "chirp-v4-h-s-32_step_8_win_over_chirp-v4-h-s-32, win ratio 0.489, (0.479, 0.500), counts 4383, total 8960.\n", "chirp-v4-h-s-32_temp_s_70_win_over_chirp-v4-h-s-32, win ratio 0.509, (0.498, 0.519), counts 4591, total 9027.\n", "chirp-v4-h-s-32_temp_s_75_win_over_chirp-v4-h-s-32, win ratio 0.501, (0.490, 0.511), counts 4493, total 8975.\n", "chirp-v4-h-s-32_temp_s_85_win_over_chirp-v4-h-s-32, win ratio 0.498, (0.488, 0.509), counts 4515, total 9058.\n", "chirp-v4-h-s-32_temp_s_85_win_over_chirp-v4-h-s-32_temp_s_70, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-s-32_temp_s_85_win_over_chirp-v4-h-s-32_temp_s_85, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-s-32_temp_s_90_win_over_chirp-v4-h-s-32, win ratio 0.501, (0.491, 0.512), counts 4498, total 8971.\n", "chirp-v4-h-s-32_text_1_win_over_chirp-v4-h-s-32, win ratio 0.484, (0.473, 0.494), counts 4363, total 9021.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-31, win ratio 0.532, (0.525, 0.539), counts 10705, total 20114.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-31_temp_s_75, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32, win ratio 1.000, (1.000, 1.000), counts 94933, total 94933.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_n_tag_3, win ratio 0.496, (0.486, 0.506), counts 4546, total 9169.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_step_10, win ratio 0.495, (0.484, 0.505), counts 4427, total 8947.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_step_16, win ratio 0.493, (0.482, 0.503), counts 4443, total 9018.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_step_16_text_1, win ratio 0.511, (0.496, 0.526), counts 2240, total 4383.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_step_8, win ratio 0.511, (0.500, 0.521), counts 4577, total 8960.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_temp_s_70, win ratio 0.491, (0.481, 0.502), counts 4436, total 9027.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_temp_s_75, win ratio 0.499, (0.489, 0.510), counts 4482, total 8975.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_temp_s_85, win ratio 0.502, (0.491, 0.512), counts 4543, total 9058.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_temp_s_90, win ratio 0.499, (0.488, 0.509), counts 4473, total 8971.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_text_1, win ratio 0.516, (0.506, 0.527), counts 4658, total 9021.\n", "chirp-v4-h-t-6_n_tag_3_win_over_chirp-v4-h-t-6, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-t-6_step_10_win_over_chirp-v4-h-t-6, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-t-6_temp_s_85_win_over_chirp-v4-h-t-6, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6, win ratio 1.000, (1.000, 1.000), counts 8925, total 8925.\n", "tournament players: ['chirp-v4-h-s-31', 'chirp-v4-h-s-31-l-30-2', 'chirp-v4-h-s-31_n_tag_3', 'chirp-v4-h-s-31_s_15_full', 'chirp-v4-h-s-31_temp_s_70', 'chirp-v4-h-s-31_temp_s_75', 'chirp-v4-h-s-31_temp_s_80', 'chirp-v4-h-s-32', 'chirp-v4-h-s-32_n_tag_3', 'chirp-v4-h-s-32_step_10', 'chirp-v4-h-s-32_step_16', 'chirp-v4-h-s-32_step_16_text_1', 'chirp-v4-h-s-32_step_8', 'chirp-v4-h-s-32_temp_s_70', 'chirp-v4-h-s-32_temp_s_75', 'chirp-v4-h-s-32_temp_s_85', 'chirp-v4-h-s-32_temp_s_90', 'chirp-v4-h-s-32_text_1', 'chirp-v4-h-t-6', 'chirp-v4-h-t-6_n_tag_3', 'chirp-v4-h-t-6_step_10', 'chirp-v4-h-t-6_temp_s_85']\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "100%|██████████| 1000/1000 [00:05<00:00, 183.87it/s]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "ELOs\n", "chirp-v4-h-s-31: 995.7, (460, 1393)\n", "chirp-v4-h-s-31-l-30-2: 995.7, (358, 1435)\n", "chirp-v4-h-s-31_n_tag_3: 2657.9, (1000, 4854)\n", "chirp-v4-h-s-31_s_15_full: 1118.2, (-1937, 6243)\n", "chirp-v4-h-s-31_temp_s_70: -856.8, (-3582, 1000)\n", "chirp-v4-h-s-31_temp_s_75: -759.0, (-3084, 1000)\n", "chirp-v4-h-s-31_temp_s_80: 2657.9, (1000, 4768)\n", "chirp-v4-h-s-32: 1018.1, (483, 1414)\n", "chirp-v4-h-s-32_n_tag_3: 1021.0, (484, 1414)\n", "chirp-v4-h-s-32_step_10: 1021.7, (483, 1417)\n", "chirp-v4-h-s-32_step_16: 1023.2, (485, 1421)\n", "chirp-v4-h-s-32_step_16_text_1: 1010.4, (472, 1410)\n", "chirp-v4-h-s-32_step_8: 1010.6, (472, 1407)\n", "chirp-v4-h-s-32_temp_s_70: 1024.0, (486, 1422)\n", "chirp-v4-h-s-32_temp_s_75: 1018.5, (476, 1413)\n", "chirp-v4-h-s-32_temp_s_85: 1017.1, (482, 1410)\n", "chirp-v4-h-s-32_temp_s_90: 1019.1, (483, 1418)\n", "chirp-v4-h-s-32_text_1: 1006.7, (471, 1401)\n", "chirp-v4-h-t-6: -3250.1, (-6264, 1000)\n", "chirp-v4-h-t-6_n_tag_3: 2416.7, (1000, 4261)\n", "chirp-v4-h-t-6_step_10: 2416.7, (1000, 4450)\n", "chirp-v4-h-t-6_temp_s_85: 2416.7, (1000, 4619)\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "print(\"first gen\")\n", "first_gen_slice_df = user_intersting_clips_3p5[\n", " (user_intersting_clips_3p5[\"continued_parent\"].isna())\n", " & (user_intersting_clips_3p5[\"task\"] == \"\")\n", "].copy()\n", "if first_gen_slice_df.shape[0] > 0:\n", " get_preference_counts(\n", " first_gen_slice_df,\n", " title_name=\"first generation\",\n", " )" ] }, { "cell_type": "code", "execution_count": 57, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:02.574659Z", "start_time": "2024-05-26T00:25:02.334214Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:34:28.397579Z", "iopub.status.busy": "2024-12-18T04:34:28.397426Z", "iopub.status.idle": "2024-12-18T04:34:37.106539Z", "shell.execute_reply": "2024-12-18T04:34:37.105942Z", "shell.execute_reply.started": "2024-12-18T04:34:28.397563Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "is continue\n", "len pos models: 47201\n", "differing counts: 15889\n", "chirp-v3p5-engine-b-r_win_over_chirp-v3p5-engine-b-r, win ratio 1.000, (1.000, 1.000), counts 157, total 157.\n", "chirp-v3p5-engine-b_win_over_chirp-v3p5-engine-b, win ratio 1.000, (1.000, 1.000), counts 139, total 139.\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-8, win ratio 1.000, (1.000, 1.000), counts 14038, total 14038.\n", "chirp-v3p5-engine-upload-4_win_over_chirp-v3p5-engine-upload-4, win ratio 1.000, (1.000, 1.000), counts 357, total 357.\n", "chirp-v4-engine-b_win_over_chirp-v4-engine-b, win ratio 1.000, (1.000, 1.000), counts 560, total 560.\n", "chirp-v4-h-s-31_n_tag_3_win_over_chirp-v4-h-s-31, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-s-31_temp_s_70_win_over_chirp-v4-h-s-31, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-s-31_win_over_chirp-v4-h-s-31, win ratio 1.000, (1.000, 1.000), counts 3, total 3.\n", "chirp-v4-h-s-31_win_over_chirp-v4-h-s-31_temp_s_95, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-s-31_win_over_chirp-v4-h-s-32, win ratio 0.499, (0.481, 0.516), counts 1529, total 3067.\n", "chirp-v4-h-s-31_win_over_chirp-v4-h-s-32_step_8, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-s-31_win_over_chirp-v4-h-s-32_temp_s_90, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-s-32_n_tag_3_win_over_chirp-v4-h-s-32, win ratio 0.499, (0.473, 0.524), counts 732, total 1468.\n", "chirp-v4-h-s-32_step_10_win_over_chirp-v4-h-s-32, win ratio 0.510, (0.483, 0.537), counts 681, total 1336.\n", "chirp-v4-h-s-32_step_16_text_1_win_over_chirp-v4-h-s-32, win ratio 0.471, (0.431, 0.511), counts 283, total 601.\n", "chirp-v4-h-s-32_step_16_win_over_chirp-v4-h-s-32, win ratio 0.503, (0.476, 0.529), counts 676, total 1345.\n", "chirp-v4-h-s-32_step_8_win_over_chirp-v4-h-s-32, win ratio 0.493, (0.467, 0.520), counts 668, total 1354.\n", "chirp-v4-h-s-32_temp_s_70_win_over_chirp-v4-h-s-32, win ratio 0.525, (0.499, 0.551), counts 730, total 1390.\n", "chirp-v4-h-s-32_temp_s_75_win_over_chirp-v4-h-s-32, win ratio 0.484, (0.458, 0.511), counts 648, total 1338.\n", "chirp-v4-h-s-32_temp_s_85_win_over_chirp-v4-h-s-32, win ratio 0.471, (0.445, 0.497), counts 659, total 1400.\n", "chirp-v4-h-s-32_temp_s_90_win_over_chirp-v4-h-s-32, win ratio 0.477, (0.450, 0.504), counts 617, total 1293.\n", "chirp-v4-h-s-32_text_1_win_over_chirp-v4-h-s-32, win ratio 0.492, (0.465, 0.520), counts 636, total 1292.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-31, win ratio 0.501, (0.484, 0.519), counts 1538, total 3067.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32, win ratio 1.000, (1.000, 1.000), counts 14402, total 14402.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_n_tag_3, win ratio 0.501, (0.476, 0.527), counts 736, total 1468.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_step_10, win ratio 0.490, (0.463, 0.517), counts 655, total 1336.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_step_16, win ratio 0.497, (0.471, 0.524), counts 669, total 1345.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_step_16_text_1, win ratio 0.529, (0.489, 0.569), counts 318, total 601.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_step_8, win ratio 0.507, (0.480, 0.533), counts 686, total 1354.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_temp_s_70, win ratio 0.475, (0.449, 0.501), counts 660, total 1390.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_temp_s_75, win ratio 0.516, (0.489, 0.542), counts 690, total 1338.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_temp_s_85, win ratio 0.529, (0.503, 0.555), counts 741, total 1400.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_temp_s_90, win ratio 0.523, (0.496, 0.550), counts 676, total 1293.\n", "chirp-v4-h-s-32_win_over_chirp-v4-h-s-32_text_1, win ratio 0.508, (0.480, 0.535), counts 656, total 1292.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6, win ratio 1.000, (1.000, 1.000), counts 1656, total 1656.\n", "tournament players: ['chirp-v4-h-s-31', 'chirp-v4-h-s-31_n_tag_3', 'chirp-v4-h-s-31_temp_s_70', 'chirp-v4-h-s-31_temp_s_95', 'chirp-v4-h-s-32', 'chirp-v4-h-s-32_n_tag_3', 'chirp-v4-h-s-32_step_10', 'chirp-v4-h-s-32_step_16', 'chirp-v4-h-s-32_step_16_text_1', 'chirp-v4-h-s-32_step_8', 'chirp-v4-h-s-32_temp_s_70', 'chirp-v4-h-s-32_temp_s_75', 'chirp-v4-h-s-32_temp_s_85', 'chirp-v4-h-s-32_temp_s_90', 'chirp-v4-h-s-32_text_1']\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "100%|██████████| 1000/1000 [00:02<00:00, 358.80it/s]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "ELOs\n", "chirp-v4-h-s-31: 829.9, (190, 1181)\n", "chirp-v4-h-s-31_n_tag_3: 3048.1, (1000, 8634)\n", "chirp-v4-h-s-31_temp_s_70: 3048.1, (1000, 8227)\n", "chirp-v4-h-s-31_temp_s_95: -1011.4, (-4663, 1000)\n", "chirp-v4-h-s-32: 830.7, (194, 1191)\n", "chirp-v4-h-s-32_n_tag_3: 829.8, (189, 1203)\n", "chirp-v4-h-s-32_step_10: 837.5, (205, 1209)\n", "chirp-v4-h-s-32_step_16: 832.5, (186, 1203)\n", "chirp-v4-h-s-32_step_16_text_1: 810.5, (176, 1188)\n", "chirp-v4-h-s-32_step_8: 825.9, (192, 1197)\n", "chirp-v4-h-s-32_temp_s_70: 848.2, (213, 1216)\n", "chirp-v4-h-s-32_temp_s_75: 819.8, (183, 1192)\n", "chirp-v4-h-s-32_temp_s_85: 810.4, (170, 1169)\n", "chirp-v4-h-s-32_temp_s_90: 814.6, (181, 1184)\n", "chirp-v4-h-s-32_text_1: 825.4, (195, 1200)\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "print(\"is continue\")\n", "get_preference_counts(\n", " user_intersting_clips_3p5[(user_intersting_clips_3p5[\"task\"] == \"extend\")],\n", " \"is extend\",\n", ")" ] }, { "cell_type": "code", "execution_count": 58, "metadata": { "execution": { "iopub.execute_input": "2024-12-18T04:34:37.107304Z", "iopub.status.busy": "2024-12-18T04:34:37.107145Z", "iopub.status.idle": "2024-12-18T04:34:45.343484Z", "shell.execute_reply": "2024-12-18T04:34:45.342898Z", "shell.execute_reply.started": "2024-12-18T04:34:37.107287Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "is cover\n", "len pos models: 41149\n", "differing counts: 13076\n", "chirp-v3p5-engine-b_win_over_chirp-v3p5-engine-b, win ratio 1.000, (1.000, 1.000), counts 34, total 34.\n", "chirp-v3p5-engine-t-6_s_max_t_12_tag_2_win_over_chirp-v3p5-engine-t-6, win ratio 0.517, (0.490, 0.544), counts 684, total 1323.\n", "chirp-v3p5-engine-t-6_s_max_t_12_tag_2_win_over_chirp-v3p5-engine-t-6_s_max_t_12_tag_2, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v3p5-engine-t-6_s_max_t_14_tag_2_win_over_chirp-v3p5-engine-t-6, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v3p5-engine-t-6_win_over_chirp-v3p5-engine-t-6, win ratio 1.000, (1.000, 1.000), counts 9558, total 9558.\n", "chirp-v3p5-engine-t-6_win_over_chirp-v3p5-engine-t-6_s_max_t_12_tag_2, win ratio 0.483, (0.456, 0.510), counts 639, total 1323.\n", "chirp-v4-engine-b_win_over_chirp-v4-engine-b, win ratio 1.000, (1.000, 1.000), counts 81, total 81.\n", "chirp-v4-h-t-6-artist-cfg_win_over_chirp-v4-h-t-6, win ratio 0.493, (0.464, 0.521), counts 585, total 1187.\n", "chirp-v4-h-t-6_a_25_r_30_win_over_chirp-v4-h-t-6, win ratio 0.500, (-0.193, 1.193), counts 1, total 2.\n", "chirp-v4-h-t-6_step_10_win_over_chirp-v4-h-t-6, win ratio 0.501, (0.474, 0.527), counts 696, total 1390.\n", "chirp-v4-h-t-6_step_16_text_1_win_over_chirp-v4-h-t-6, win ratio 0.451, (0.410, 0.492), counts 257, total 570.\n", "chirp-v4-h-t-6_step_16_win_over_chirp-v4-h-t-6, win ratio 0.486, (0.460, 0.512), counts 699, total 1439.\n", "chirp-v4-h-t-6_step_8_win_over_chirp-v4-h-t-6, win ratio 0.463, (0.437, 0.489), counts 656, total 1417.\n", "chirp-v4-h-t-6_temp_s_70_win_over_chirp-v4-h-t-6, win ratio 0.529, (0.503, 0.556), counts 726, total 1372.\n", "chirp-v4-h-t-6_temp_s_80_win_over_chirp-v4-h-t-6, win ratio 0.511, (0.486, 0.537), counts 736, total 1439.\n", "chirp-v4-h-t-6_temp_s_90_win_over_chirp-v4-h-t-6, win ratio 0.499, (0.473, 0.524), counts 720, total 1444.\n", "chirp-v4-h-t-6_temp_s_90_win_over_chirp-v4-h-t-6_step_8, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-t-6_temp_s_95_win_over_chirp-v4-h-t-6, win ratio 0.500, (0.010, 0.990), counts 2, total 4.\n", "chirp-v4-h-t-6_text_15_win_over_chirp-v4-h-t-6, win ratio 0.444, (0.120, 0.769), counts 4, total 9.\n", "chirp-v4-h-t-6_text_1_win_over_chirp-v4-h-t-6, win ratio 0.491, (0.466, 0.517), counts 722, total 1469.\n", "chirp-v4-h-t-6_text_3_win_over_chirp-v4-h-t-6, win ratio 0.333, (-0.044, 0.711), counts 2, total 6.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6, win ratio 1.000, (1.000, 1.000), counts 18399, total 18399.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6-artist-cfg, win ratio 0.507, (0.479, 0.536), counts 602, total 1187.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6-artist-cfg_step_8, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_a_25_r_30, win ratio 0.500, (-0.193, 1.193), counts 1, total 2.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_step_10, win ratio 0.499, (0.473, 0.526), counts 694, total 1390.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_step_16, win ratio 0.514, (0.488, 0.540), counts 740, total 1439.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_step_16_text_1, win ratio 0.549, (0.508, 0.590), counts 313, total 570.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_step_8, win ratio 0.537, (0.511, 0.563), counts 761, total 1417.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_temp_s_70, win ratio 0.471, (0.444, 0.497), counts 646, total 1372.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_temp_s_80, win ratio 0.489, (0.463, 0.514), counts 703, total 1439.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_temp_s_90, win ratio 0.501, (0.476, 0.527), counts 724, total 1444.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_temp_s_95, win ratio 0.500, (0.010, 0.990), counts 2, total 4.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_text_1, win ratio 0.509, (0.483, 0.534), counts 747, total 1469.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_text_15, win ratio 0.556, (0.231, 0.880), counts 5, total 9.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_text_25, win ratio 1.000, (1.000, 1.000), counts 2, total 2.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_text_3, win ratio 0.667, (0.289, 1.044), counts 4, total 6.\n", "tournament players: ['chirp-v3p5-engine-t-6', 'chirp-v3p5-engine-t-6_s_max_t_12_tag_2', 'chirp-v3p5-engine-t-6_s_max_t_14_tag_2', 'chirp-v4-h-t-6', 'chirp-v4-h-t-6-artist-cfg', 'chirp-v4-h-t-6-artist-cfg_step_8', 'chirp-v4-h-t-6_a_25_r_30', 'chirp-v4-h-t-6_step_10', 'chirp-v4-h-t-6_step_16', 'chirp-v4-h-t-6_step_16_text_1', 'chirp-v4-h-t-6_step_8', 'chirp-v4-h-t-6_temp_s_70', 'chirp-v4-h-t-6_temp_s_80', 'chirp-v4-h-t-6_temp_s_90', 'chirp-v4-h-t-6_temp_s_95', 'chirp-v4-h-t-6_text_1', 'chirp-v4-h-t-6_text_15', 'chirp-v4-h-t-6_text_25', 'chirp-v4-h-t-6_text_3']\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "100%|██████████| 1000/1000 [00:05<00:00, 193.83it/s]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "ELOs\n", "chirp-v3p5-engine-t-6: 425.4, (-842, 1001)\n", "chirp-v3p5-engine-t-6_s_max_t_12_tag_2: 437.2, (-830, 1014)\n", "chirp-v3p5-engine-t-6_s_max_t_14_tag_2: 2137.4, (1000, 4686)\n", "chirp-v4-h-t-6: 1235.3, (858, 1890)\n", "chirp-v4-h-t-6-artist-cfg: 1230.3, (851, 1883)\n", "chirp-v4-h-t-6-artist-cfg_step_8: -168.8, (-2670, 1000)\n", "chirp-v4-h-t-6_a_25_r_30: 1245.3, (-1547, 4574)\n", "chirp-v4-h-t-6_step_10: 1235.8, (850, 1883)\n", "chirp-v4-h-t-6_step_16: 1225.4, (848, 1889)\n", "chirp-v4-h-t-6_step_16_text_1: 1201.1, (819, 1850)\n", "chirp-v4-h-t-6_step_8: 1209.3, (834, 1873)\n", "chirp-v4-h-t-6_temp_s_70: 1255.7, (873, 1915)\n", "chirp-v4-h-t-6_temp_s_80: 1243.3, (866, 1894)\n", "chirp-v4-h-t-6_temp_s_90: 1234.6, (851, 1885)\n", "chirp-v4-h-t-6_temp_s_95: 1231.5, (-1827, 4901)\n", "chirp-v4-h-t-6_text_1: 1229.4, (850, 1879)\n", "chirp-v4-h-t-6_text_15: 1195.7, (647, 1983)\n", "chirp-v4-h-t-6_text_25: -914.0, (-4146, 1000)\n", "chirp-v4-h-t-6_text_3: 1110.1, (-3814, 1752)\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "print(\"is cover\")\n", "get_preference_counts(\n", " user_intersting_clips_3p5[(user_intersting_clips_3p5[\"task\"] == \"cover\")],\n", " \"is cover\",\n", ")" ] }, { "cell_type": "code", "execution_count": 59, "metadata": { "execution": { "iopub.execute_input": "2024-12-18T04:34:45.344266Z", "iopub.status.busy": "2024-12-18T04:34:45.344103Z", "iopub.status.idle": "2024-12-18T04:34:49.399313Z", "shell.execute_reply": "2024-12-18T04:34:49.398748Z", "shell.execute_reply.started": "2024-12-18T04:34:45.344251Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "is infill\n", "len pos models: 8668\n", "differing counts: 2947\n", "chirp-v3p5-engine-b_win_over_chirp-v3p5-engine-b, win ratio 1.000, (1.000, 1.000), counts 24, total 24.\n", "chirp-v3p5-engine-t-6_s_30_t_12_tag_2_win_over_chirp-v3p5-engine-t-6, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v3p5-engine-t-6_s_max_t_12_tag_2_win_over_chirp-v3p5-engine-t-6, win ratio 0.471, (0.405, 0.536), counts 105, total 223.\n", "chirp-v3p5-engine-t-6_win_over_chirp-v3p5-engine-t-6, win ratio 1.000, (1.000, 1.000), counts 1527, total 1527.\n", "chirp-v3p5-engine-t-6_win_over_chirp-v3p5-engine-t-6_s_max_t_12_tag_2, win ratio 0.529, (0.464, 0.595), counts 118, total 223.\n", "chirp-v4-engine-b_win_over_chirp-v4-engine-b, win ratio 1.000, (1.000, 1.000), counts 29, total 29.\n", "chirp-v4-h-t-6-artist-cfg_win_over_chirp-v4-h-t-6, win ratio 0.519, (0.461, 0.577), counts 150, total 289.\n", "chirp-v4-h-t-6_step_10_win_over_chirp-v4-h-t-6, win ratio 0.471, (0.416, 0.525), counts 152, total 323.\n", "chirp-v4-h-t-6_step_16_text_1_win_over_chirp-v4-h-t-6, win ratio 0.421, (0.337, 0.505), counts 56, total 133.\n", "chirp-v4-h-t-6_step_16_win_over_chirp-v4-h-t-6, win ratio 0.503, (0.449, 0.557), counts 168, total 334.\n", "chirp-v4-h-t-6_step_8_win_over_chirp-v4-h-t-6, win ratio 0.556, (0.504, 0.607), counts 199, total 358.\n", "chirp-v4-h-t-6_temp_s_70_win_over_chirp-v4-h-t-6, win ratio 0.521, (0.465, 0.577), counts 161, total 309.\n", "chirp-v4-h-t-6_temp_s_80_win_over_chirp-v4-h-t-6, win ratio 0.449, (0.393, 0.505), counts 137, total 305.\n", "chirp-v4-h-t-6_temp_s_90_win_over_chirp-v4-h-t-6, win ratio 0.478, (0.423, 0.533), counts 151, total 316.\n", "chirp-v4-h-t-6_temp_s_95_win_over_chirp-v4-h-t-6, win ratio 1.000, (1.000, 1.000), counts 2, total 2.\n", "chirp-v4-h-t-6_text_1_win_over_chirp-v4-h-t-6, win ratio 0.483, (0.431, 0.535), counts 171, total 354.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6, win ratio 1.000, (1.000, 1.000), counts 4141, total 4141.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6-artist-cfg, win ratio 0.481, (0.423, 0.539), counts 139, total 289.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_step_10, win ratio 0.529, (0.475, 0.584), counts 171, total 323.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_step_16, win ratio 0.497, (0.443, 0.551), counts 166, total 334.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_step_16_text_1, win ratio 0.579, (0.495, 0.663), counts 77, total 133.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_step_8, win ratio 0.444, (0.393, 0.496), counts 159, total 358.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_temp_s_70, win ratio 0.479, (0.423, 0.535), counts 148, total 309.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_temp_s_80, win ratio 0.551, (0.495, 0.607), counts 168, total 305.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_temp_s_90, win ratio 0.522, (0.467, 0.577), counts 165, total 316.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_text_1, win ratio 0.517, (0.465, 0.569), counts 183, total 354.\n", "tournament players: ['chirp-v3p5-engine-t-6', 'chirp-v3p5-engine-t-6_s_30_t_12_tag_2', 'chirp-v3p5-engine-t-6_s_max_t_12_tag_2', 'chirp-v4-h-t-6', 'chirp-v4-h-t-6-artist-cfg', 'chirp-v4-h-t-6_step_10', 'chirp-v4-h-t-6_step_16', 'chirp-v4-h-t-6_step_16_text_1', 'chirp-v4-h-t-6_step_8', 'chirp-v4-h-t-6_temp_s_70', 'chirp-v4-h-t-6_temp_s_80', 'chirp-v4-h-t-6_temp_s_90', 'chirp-v4-h-t-6_temp_s_95', 'chirp-v4-h-t-6_text_1']\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "100%|██████████| 1000/1000 [00:02<00:00, 367.01it/s]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "ELOs\n", "chirp-v3p5-engine-t-6: 299.6, (-934, 1026)\n", "chirp-v3p5-engine-t-6_s_30_t_12_tag_2: 2421.2, (1000, 4903)\n", "chirp-v3p5-engine-t-6_s_max_t_12_tag_2: 279.2, (-968, 1005)\n", "chirp-v4-h-t-6: 732.3, (505, 1012)\n", "chirp-v4-h-t-6-artist-cfg: 745.6, (518, 1037)\n", "chirp-v4-h-t-6_step_10: 711.9, (480, 1004)\n", "chirp-v4-h-t-6_step_16: 734.4, (498, 1026)\n", "chirp-v4-h-t-6_step_16_text_1: 677.0, (453, 975)\n", "chirp-v4-h-t-6_step_8: 771.3, (537, 1062)\n", "chirp-v4-h-t-6_temp_s_70: 746.9, (515, 1039)\n", "chirp-v4-h-t-6_temp_s_80: 696.9, (470, 990)\n", "chirp-v4-h-t-6_temp_s_90: 716.9, (486, 1010)\n", "chirp-v4-h-t-6_temp_s_95: 3746.4, (1000, 6069)\n", "chirp-v4-h-t-6_text_1: 720.5, (491, 1016)\n" ] }, { "data": { "image/png": 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o8OCgRo0apVy5chkdBrKw1HbhBdKrSpUqatOmjfr27atXXnlF8fHxGjVqlL777jsNGDDA6PAAAHjkjBs3TiNHjtTmzZs1btw4Xbp0SW+88YZSUlLuSswCtmYy851MAAAAmwsNDdXq1avpQ4wHtnnzZg0fPlwFChTQpUuX5OnpqUmTJqlEiRJGh4YsZs6cOWrfvr2yZ89udChwcDxreFiRkZEaOnSoDh48qISEBLVo0UJDhgxRtmzZjA4NWQwVsAAMsX//fn333Xc6f/78XZttzZw506Co4Gji4+M1d+5cbd++XVeuXFFKSorV8R9//NGgyOCIrly5ouPHj0uSChcufFfF9Z49e4wICw6kVq1aatCggb744gu5uLjoo48+IvmKTLVixQr5+fmpTp06kqSJEydq6dKlKlasmKZMmaLg4GBJUo8ePQyMEo6AZw32dOvWLaWkpCglJUUBAQFyd3c3OiRkQfSABWB33377rdq3b69jx45pw4YNSkpK0tGjR7V9+3b5+PgYHR4cyPDhw/X111/riSeeUIcOHdS5c2erF5AZYmNj9eabb6pWrVrq2LGjOnbsqFq1amngwIGKiYkxOjw4iFOnTqlt27bavHmzFixYoG7duunVV1/VxIkT7/ogE3hQs2fPtiQm9uzZo88//1xvvvmmfH19LbuKA5mBZw328O233yo8PFze3t5av3695syZo6VLl+qFF16wtMID7IUWBADsLjw8XO3atVOHDh0sX8nNly+fRowYoYCAAPXr18/oEOEgKlWqpDlz5uiJJ54wOhQ4sNdee02HDh3S8OHDFRoaKun2PybHjBmj0qVLa+rUqQZHCEcQGhqqOnXqaOTIkZav4u7evVuDBw+Wl5eXVq5caWyAcAgVKlTQd999p7x582rSpEm6dOmSJk6cqKNHj6pTp07avn270SHCQfCswR4qVqyoQYMG6YUXXrCMXbt2TSNGjNCvv/6q3bt3GxgdshoqYAHY3enTp1W7dm1Jkpubm+Lj42UymfTSSy9p6dKlBkcHR5I9e3b5+voaHQYc3ObNmzVmzBjVrFlT3t7e8vb2Vs2aNTV69Gj99NNPRocHB/HOO+9o6tSpVn0Qw8LCtGLFCpUpU8bAyOBIPD09dfXqVUnS1q1bVb16dUmSu7u7bt68aWBkcDQ8a7CH5cuXWyVfJSlHjhyaPn26RowYYVBUyKpIwAKwu+zZsysuLk6SFBgYqKNHj0qSrl+/roSEBCNDg4Pp37+/pk+fznMFm/L19U21fYq3tzebhiDTNG/eXJKUmJioY8eOKSkpSdLt52zs2LEGRgZHUr16dQ0fPlzDhg3TiRMnLB+YHz161NKTE8gMPGuwhyJFiigpKUm//fabvvzyS8XGxkqSLly4oAYNGhgcHbIaNuECYHeVK1fWb7/9ppIlS+rZZ5/VmDFjtH37dv3222+qVq2a0eHhMde8eXOZTCbL+5MnT6p69erKly+fXFysf+2tWLHC3uHBAb366qsaP368Jk6cqICAAEnSpUuXNGnSJPXq1cvg6OAobty4oVGjRllaDaxfv1758+fXe++9p6CgIL3yyivGBgiH8M4772jatGk6f/68PvjgA/n5+UmSDhw4oCZNmhgcHRwJzxrs4ezZs3r55Zd1/vx5JSYmqkaNGvL29ta8efOUmJioUaNGGR0ishB6wAKwu6tXr+rmzZsKCgpSSkqK5s+fr927d6tQoUJ69dVXlSNHDqNDxGNs5syZ6Z7bp08fG0aCrKJ58+Y6efKkbt26pTx58kiSzp8/L1dXVxUqVMhqLkl/PKjRo0dr9+7deuutt9S9e3etXr1a+fPn18aNGzVz5kx6wMKu3n33XfXr1085c+Y0OhQ4OJ41PIxevXrJy8tLY8aMUdWqVS2/O3fs2KG3335bP/zwg9EhIguhAhaA3f23J6eTkxNVO8hUJFVhb/Xr1zc6BGQBP/74o6ZOnaqKFStajRcvXlynTp0yJihkWatXr1a3bt1IisHmeNbwMHbt2qUvvvhCbm5uVuPBwcG6cOGCQVEhqyIBC8DuSpcurS1btihXrlxW49HR0apevboOHTpkUGRwZFRQwFZI+sMeoqKi7vq9KUkJCQlWbVcAe+BLlLAXnjU8jJSUFKWkpNw1HhkZKS8vLwMiQlbGJlwA7C6tv0glJibK1dXVztEgq1i9erVl8zcgs12/fl3Lli3TlClTLLs6HzhwgOoKZJqQkBBt3rz5rvFly5bdVRULAACkGjVq6JNPPrEai4uL04wZMywbvwH2QgUsALtZvHixJMlkMmnZsmXy9PS0HEtJSVFERISKFCliVHhwcFRQwFYOHz6sLl26yMfHR2fPnlWbNm3k6+urH374QefPn9fEiRONDhEOYMCAAerevbv+/vtvJScna/Hixfrnn3+0Z88eLVmyxOjwAAB45AwZMkTdunVT48aNlZiYqIEDB+rEiRPy8/PT+++/b3R4yGJIwAKwm0WLFkm6nQj78ssv5eT0bxG+q6ur8uXLp5EjRxoUHQA8mPHjx6tFixYaNGiQQkNDLeO1a9fWwIEDDYwMjqRSpUpatWqV5s6dqxIlSmjr1q0qU6aMvvzyS5UsWdLo8AAAeOTkzp1bq1at0rp163T48GHFx8fr+eefV3h4uDw8PIwOD1kMCVgAdrNp0yZJUqdOnTRz5kzlyJHD4IiQlezZs8foEOCg9u/fr1GjRt01HhQUpEuXLhkQERxVgQIFNHr0aKPDAADgsRAREaHQ0FA1bdpUTZs2tYwnJSUpIiJClStXNjA6ZDX0gAVgd0uWLElX8jUsLEynT5+2Q0TIKoYOHUpPTmQ6Nzc3xcbG3jV+4sQJNn1DpildurSuXLly13h0dLRKly5tQETIypo2bcoGNrALnjU8jM6dO+vatWt3jcfExKhz584GRISsjApYAI8senbiQR0+fDjV8TVr1ujpp59WdHS0JKlUqVL2DAsOql69epo1a5amTZtmGTt37pwmT56sZ555xrjA4FDYwBL2cu3aNX399df6559/JElFixZVq1at5Ovra5lDyyhkBp412JrZbJbJZLpr/OrVq8qWLZsBESErM5nJcAB4RIWGhmr16tXKnz+/0aHgMVOqVCmZTKZUExZ3xk0mkw4dOmRAdHA0MTEx6tevn/7880/FxcUpMDBQly9fVsWKFTV37lyrDQeBjLqzgeW4cePUv3//VDewPHv2rFauXGlQhHAkERERevXVV+Xt7a2QkBBJ0oEDB3T9+nXNnj2br+si0/CswZb69OkjSfrxxx9Vs2ZNubm5WY4lJyfryJEjKly4sBYsWGBUiMiCqIAFADickiVLKnfu3Bo0aJClwb7ZbFbDhg01b948FSxY0OAI4Uh8fHz08ccfa9euXZYNHsqWLavq1asbHRocABtYwp5GjRqlRo0a6d1335Wzs7Ok28mKkSNHatSoUVqzZo3BEcJR8KzBlnx8fCTd/t3p5eVlteGWq6urKlasqNatWxsVHrIoKmABPLKogMWDSkxM1KRJk/Tbb79p0qRJKlOmjCSpbNmyWrVqlYoVK2ZwhHAkK1euVOPGja2qK6Tbz+G6devUvHlzYwKDQ2EDS9hD+fLltXLlShUpUsRq/NixY2revLn27dtnUGRwNDxrsIeZM2eqa9eu9/020q5du1SuXLm7/i4HZCY24QLwyEqtXw+QHm5ubho2bJgGDRqkV199VXPmzFFKSorRYcFBDR06VDExMXeNx8XFaejQoQZEBEfEBpawhzJlyujYsWN3jR87doy+6chUPGuwhz59+qSrFVT37t3ZqBc2RwsCAI8sCvTxsGrXrq1vvvlGQ4cO1S+//GJ0OHBQaW3wcOHCBctX4AB74XcnHkbnzp01ZswYnTx5UhUqVJAk/fHHH/rss880cOBAq00uSZLhYfCs4VHC707YAy0IADyyfv/9d5UvX56vgiBTLF68WDt27NDbb7+t3LlzGx0OHEDz5s1lMpl0+PBhFStWTC4u/36unZycrDNnzqhmzZqaPn26gVEiq6F9Dx7G/RJdbGSJzMKzhkcJvzthD1TAArCrixcvatu2bfL19VW1atWskqvx8fFauHChZdfKSpUqGRUmHMTNmzfl7u4u6XalRefOnQ2OCI6kfv36kqRDhw7pqaeekpeXl+WYq6urgoOD9cwzzxgVHgBk2I8//mh0CMgieNYAZDUkYAHYzb59+9StWzelpKQoKSlJQUFBmjVrlooXLy7pdgJ21qxZlgQs8LCqVaumZ555RuHh4apWrZrV7uHAw7rz/6rg4GA1adKEan0Aj73g4GCjQ0AWwbMGIKshAQvAbqZOnar69etrzJgxio+P1+TJk9WxY0d9/PHHll3qgcw0YcIErVmzRr169ZKPj48aNWqkpk2bqly5ckaHBgfy5JNPKioqytLaYt++fVqzZo2KFSumtm3bGhwdsho2sMTDunDhgnbt2qWoqKi7NrDkmyTITDxreFTwuxP2QAIWgN0cOHBAI0aMkJOTk7y9vfXuu+8qb968eumllzR//nzlzZvX6BDhYBo0aKAGDRooNjZW69ev17fffqu2bdsqf/78Cg8Pp9oameKNN95QmzZt1Lx5c126dEkvvfSSSpQooTVr1ujSpUs8Z7ArtnfAw1i+fLlGjBghV1dX+fn5WR0zmUwkxZBpeNbwKOF3J+yBTbgA2E2VKlW0ePHiu5ruL1iwQLNnz9bYsWPVr18/Gu3Dpv7++28NHDhQR44c4VlDpqhcubK++uorFSlSRIsXL9a6dev05ZdfasuWLXrnnXfocwe7YgNLPIzatWurXbt26tGjB217YFM8a7C3xMRERUZGKnfu3PyOhCGogAVgN8WLF9eePXvuSsDe6Qv7+uuvGxQZHN3Nmzf1448/au3atfr111/l7++vbt26GR0WHERSUpLlL/K//fab6tWrJ0kqUqSILl26ZGRocAAHDhxQ9uzZLTszr1y5Ul9++aXOnz+vvHnzqmPHjmrSpIllPhtY4mHcuHFDTZo0ISEGm+NZgy0tX75chQsXVmhoqG7evKmRI0dq5cqVMpvNcnJyUqtWrTR8+HASsbAr/m8HwG6aN2+u3bt3p3qse/fu6tu3r/LkyWPnqODIfv31Vw0ePFjVq1fXyJEj5e/vr4ULF+qnn37SwIEDjQ4PDqJYsWL68ssv9fvvv+u3335TrVq1JEkXL16Ur6+vscHhsTd06FCdPn1akrRs2TK98847CgkJUc+ePVWuXDkNHz5cX3/9tcFRwlG0atVK33//vdFhIAvgWYMtzZo1y5LcnzZtmrZv367p06dr7dq1mj59unbs2KFp06YZGySyHFoQAAAcVoUKFVSnTh2Fh4erdu3acnV1NTokOKAdO3aoT58+io2NVfPmzTVu3DhJ0vvvv69jx45p5syZBkeIx1mFChW0bt06BQcHq0WLFmrfvr3atGljOb5mzRrNnj1b3377rYFRwlEkJyerR48eunnzpkqUKCEXF+svTA4dOtSgyOBoeNZgS+XKldP69euVN29eNWzYUMOGDbN8QC5JERERGjRokH766ScDo0RWQwsCAIDD2rp1q7y9vSVJkZGRCgwM5KtuyHRVq1bV9u3bFRsbqxw5cljG27Rpo2zZslne79q1S+XKlePrbsgQDw8PRUdHKzg4WBcuXFD58uWtjleoUEFnzpwxKDo4mjlz5mjLli0qXLjwXcfYJRyZiWcNthQQEKBTp04pb968SkhIuGujt5w5c+rq1avGBIcsiwpYAI+Mf/75R6+88gob1sAmwsLCtGrVKksfRcDeeAbxIN588025ublpzJgx6t+/vwoXLqzXXnvNcnzOnDlau3at1qxZY1yQcBiVK1fW0KFD1bJlS6NDgYPjWYMtTZ06VTt27NDcuXM1b948HT16VFOmTJGXl5cSEhI0dOhQxcTEaMGCBUaHiiyEClgAj4xbt27p3LlzRocBB8XnjTAazyAexMCBA9W+fXt17NhRISEh+vjjj7Vz504VLVpUx48f1969ezVr1iyjw4SDcHNzU1hYmNFhIAvgWYMt9e7dW3/99Zfq16+vkJAQ/f7776pRo4aCgoIsPfoXLlxodJjIYkjAArCbO30R0xIVFWWnSAAAeDwEBQVp5cqVmjt3rn766SeZzWbt27dPkZGRCg0N1RdffKFy5coZHSYcROfOnfXpp59q+PDhRocCB8ezBltyc3PTRx99pF9++UU//fSTnJycZDabFRAQoLCwMD333HPy9PQ0OkxkMbQgAGA3pUuXVunSpeXl5ZXq8fj4eB08eFCHDh2yc2TICubMmaP27dsre/bsRoeCLCo0NFSrV6+mBQGAR1bv3r21fft2+fr6qnjx4ndtjMSmgsgsPGsAshoqYAHYTYECBfTiiy+qWbNmqR4/dOgQfaBgM6+88orRIQAA8EjLnj27nnnmGaPDQBbAswZ7e/fdd9WvXz/lzJnT6FCQRZGABWA3ISEhOnDgQJoJWJPJRI9EZLply5bpk08+0YkTJyRJhQoV0osvvqjWrVsbGxiyHHZ1hi2cOnVKw4cP1+LFi40OBQ7gfu2igMzCswZ7W716tbp160YCFoYhAQvAboYMGaLExMQ0j5cqVUqHDx+2Y0RwdNOnT9eiRYvUsWNHVaxYUZK0d+9ejR07VufOnVP//v2NDRBZCh8wwRbi4+MVERFhdBhwIElJSdq5c6dOnTql5557Tt7e3rpw4YK8vb3TbCMFPAieNdgTfw+D0UjAArCbgICADM1fu3at6tWrR4N0PLAvvvhC7733np577jnL2NNPP62SJUvqvffeIwGLTJeYmKjIyEjlzp1bbm5uVsf27NljUFR4nN2vsvXChQt2igRZwdmzZ/Xyyy/r/PnzSkxMVI0aNeTt7a158+YpMTFRo0aNMjpEOAieNQBZDQlYAI+sESNGqEKFCiRg8cCSkpIUEhJy13jZsmWVnJxsQERwJMuXL1fhwoUVGhqqmzdvauTIkVq5cqXMZrOcnJzUqlUrDR8+/K5ELJARY8eOVUBAgFxdXVM9fuvWLTtHBEc2ZswYhYSEaNWqVapataplvEGDBnr77bcNjAyOhmcN9sYH4TCak9EBAEBa+JoIHlazZs30xRdf3DW+dOlShYeHGxARHMmsWbPk5HT7r1LTpk3T9u3bNX36dK1du1bTp0/Xjh07NG3aNGODxGMvb968Gjp0qDZt2pTqa+7cuUaHCAeya9cuvfrqq3d9cBQcHEy1NTIVzxrsoXTp0rpy5cpd49HR0SpdurQBESErowIWAODQvv76a23dulUVKlSQJO3bt0/nzp1T8+bNrTaAGDp0qFEh4jF18eJFS2uVTZs26d1331WtWrUkSUWLFlWOHDk0aNAgDRo0yMgw8Zi7s4Fl48aNUz3OBpbITCkpKUpJSblrPDIykp6cyFQ8a7CHtH4/JiYmpvnNEsBWSMACABzWX3/9pTJlyki6vVO4JPn6+srX11d//fWXZR670+NBBAQE6NSpU8qbN68SEhLk5+dndTxnzpy6evWqMcHBYfTr108JCQlpHi9atKh+/PFHO0YER1ajRg198skneu+99yxjcXFxmjFjhmrXrm1gZHA0PGuwpTv9000mk5YtW2bV0i4lJUUREREqUqSIUeEhizKZ+cgcwCMqNDRUq1evVv78+Y0OBQDuMnXqVO3YsUNz587VvHnzdPToUU2ZMkVeXl5KSEjQ0KFDFRMTowULFhgdKrKQXbt2qVy5cvQexgOJjIxUt27dZDabdfLkSYWEhOjEiRPy8/PTZ599ply5chkd4v+xd9/hUZT7//9fmw4EiCGhhQ5CqAEUBERBiogSioqVcgTxWBBUFAVREGyU40GFjwLHBipV6SgK8kVUehFRQhNCCUhCNbS0/f3Bj5WQAPeE7E529/m4Lq5rd2Z28p7XThLy3nvugY/gXIM7tWrVSpKUlJSk0qVLu6aMkqTg4GCVK1dO/fr1c10hB3gCDVgABRYNWFyL9PR0xcXFac6cOapevbrd5cAHpaWlqX///lq/fr3q1KmjdevWKSAgQKVKldLhw4cVERGhjz/+WJUrV7a7VPiRhg0bau7cufzuRJ5lZGRo0aJFSkhI0OnTp1W7dm3Fx8crLCzM7tLgYzjX4G7du3fXuHHjVLx4cbtLAZiCAEDBFRMTo6Agfkwhb4KDg1WmTJlc5xcD8kNISIg++OAD/fjjj1q2bJkCAgLkdDoVHR2thg0bqkOHDtkueQM8gbEVuBZr165VgwYN1LFjR3Xs2NG1PCMjQ2vXrlWjRo1srA6+hHMNnjBlyhTXY64Qgd0YAQvA41q3bq1Zs2blmC/x5MmT6tKlC3PZId/MnDlT33//vUaNGqWIiAi7ywEAt+PqEVyLmjVr6qeffspx+fexY8fUrFkzbd261abK4Gs41+BpXCECuzG0DIDHHThwINdRiWlpafrrr79sqAi+6osvvlBiYqJuueUWlS1bNsdoxNmzZ9tUGXzVsGHD1K9fP0VGRtpdCgBY5nQ6c70x5fHjx1WoUCEbKoKv4lyDpzH2EHajAQvAYy4e2bpixQoVLVrU9TwrK0srV65UTEyMHaXBR7Vp08buEuBn5s2bp969e9OABeBV+vbtK+n8HcNfeumlbJfoZmZmatu2bWrQoIFd5cGHcK4B8Fc0YAF4zFNPPSXpn/9wXSwoKEgxMTE5lgPX4sJ/8gFPYXQF7JbbiDLgai58KO50OlWkSJFsN0EKDg5W/fr11bVrV7vKgw/hXINdhg8fnmPKC8CTaMAC8JiEhARJUqtWrTRr1ixGiAEAkM/4EAB58dZbb0k6fwPUXr16XfUGgtzMBnnFuQa7xMfH210C/Bw34QJQYMXHx2vixIkqU6aM3aXAizRu3FjffvutIiMj1ahRoyuOBluzZo0HKwOAa3fkyBHt3r1bklS5cmVG88AW3MwGnsK5hmtx+vRpTZw4UatWrdKRI0dy3IeEmz/DkxgBC6DA2r9/vzIyMuwuA15m0KBBCg8PlyQNHjzY5mrgD7iTMzwhNTVVr732mhYtWqTMzExJUmBgoNq3b6+hQ4dmm1cdcDfG8MBTONdwLYYMGaI1a9aoU6dOio6OZpoe2IoGLADAp3Tp0iXXx4C7XO6Pw7S0NAUHB3u4GviqIUOGaOvWrfrwww9dN6jZuHGj3njjDb366qv673//a3OFAAAULD/++KMmTJigG264we5SABqwAADflpWVpcTERB05ciRHo6xRo0Y2VQVfMHnyZEnnb3o0c+bMbPPYZWVlae3atapSpYpd5cHH/L//9//0v//9TzfeeKNr2S233KLXX39djz76qI2VAQBQMBUrVkwRERF2lwFIogELAPBhmzZt0oABA5SUlJSj+epwOLg0HNfk008/lXR+BOy0adMUEBDgWhccHKxy5crptddes6k6+JqIiIhcpxkIDw9XsWLFbKgIAICCrX///nr33Xc1cuRIFSpUyO5y4OdowAIAfNbQoUNVp04dTZw4kXmfkO9++OEHSVL37t01btw4FS9e3OaK4MueeOIJvf322xo1apSio6MlScnJyRo9erSefPJJm6uDv+H3KTyFcw1Wde7cOdt5k5iYqGbNmqlcuXIKCsreAps9e7any4MfowELAPBZiYmJeu+991SxYkW7S4EPmzJliuvx+vXrVbduXYWEhNhYEXzR1KlTlZiYqNtuu01lypSRJB08eFDBwcE6evSopk+f7tqWPyjhbtwYCZ7CuQar2rRpY3cJQK5owAIoUM6cOeO6PGT48OE57ioOWFGvXj0lJibSgIXH9OnTR3PnzlX58uXtLgU+hj8o4WlpaWk6dOiQSpcuneNDpY0bN9pUFXwR5xryU9++fe0uAciVw8lHSgA8rGfPnho1apRKlSqVbfnmzZv1wgsvaPHixTZVBl+QkJDgerxv3z6NHTtWvXv3VvXq1XNcdhQbG+vp8uDjGjRooHnz5tGABeBVvv76a1WuXFkNGjTQuXPn9Nprr2nOnDlyOp0KCAjQPffcoyFDhjC6H9eMcw12GTZsmPr166fIyEi7S4GfYgQsAI8LDQ1Vx44dNXToUN15553KysrS+PHjNWHCBD344IN2lwcvd2Hep4s/Xxw8eLDr8YV13IQLgLc5efKkFi9erL1796p3796KiIjQ77//rqioqBwfagJWjB8/Xu+8844kaezYsVq1apXeffddValSRbt379bo0aM1duxYDRw40OZK4e0412CXefPmqXfv3jRgYRsasAA8buLEifriiy80ePBgLV26VAcOHNCBAwf04Ycfqnnz5naXBy+3dOlSu0uAH2PqFLhLQkKCHnnkERUtWlQHDhzQfffdp4iICH333Xc6ePCgRo0aZXeJ8GKHDx923dzthx9+0LBhw3TrrbdKkqpWrarixYtr4MCBNMVwzTjXYBcu/obdAuwuAIB/evjhh9W9e3ctXLhQW7Zs0bvvvkvzFfkiJibG9W/BggVauXJltmUxMTFauXKlFi5caHep8EHx8fEqXLiw3WXAB7399tvq0qWLvvvuu2yX5rZo0ULr1q2zsTL4gujoaO3du1fS+fn4r7vuumzrIyMjdfz4cRsqg6/hXAPgr2jAAvC4EydO6Omnn9bUqVM1fPhw3XHHHerdu7e++OILu0uDj5k+fbqqVKmSY/n111+vadOm2VARfNHp06c1duxYPfDAA2rbtq1at26d7R+QH3777Tc98MADOZaXKlVKycnJNlQEXxIfH6+xY8fq5MmT6tSpk8aPH69Tp05JOt8ke//999WwYUObq4Qv4FyDXTZu3Mgc/bAVUxAA8LgOHTqoXLlymj17tsqXL6/77rtPixYt0muvvably5dr4sSJdpcIH5GcnOy6zO1ikZGRNCyQb4YMGaI1a9aoU6dOio6OlsPhsLsk+KCQkBClpqbmWL5nzx7ms8M1e+qpp7R9+3a1adNGderU0bp163TzzTerVKlSOnz4sCIiIvTxxx/bXSZ8AOca7DRo0CA988wzzJsOW9CABeBxDzzwgJ544gkFBPwzCP/OO+9Uw4YNNWjQIBsrg68pU6aMNmzYkOPT7vXr16tkyZI2VQVf8+OPP2rChAm64YYb7C4FPqxVq1YaP368xo4d61qWlJSkMWPG6Pbbb7evMPiEkJAQffDBB/rxxx+1bNkyBQQEyOl0Kjo6Wg0bNlSHDh2YXgX5gnMNnpCQkJDr8vnz56t169Y6duyYJCk2NtaTZcHPOZzMRAwA8FGTJk3S//73Pw0cOFBNmjSRJK1cuVKjR49Wr1699O9//9vmCuELWrVqpUmTJqlq1ap2lwIf9vfff6tfv37asmWLTp06pZIlSyolJUX169fXxIkTaVgAAPD/i42NlcPhyPXGWxeWOxwObd261Ybq4K9owAKwzZkzZ5SUlKT09PRsy/kkEvnF6XRqzJgxmjJlius8Cw0N1aOPPqq+ffvaXB18xdy5c7V06VKNHDlShQoVsrsc+Lj169crISFBp0+fVu3atdWsWTO7S4KPGjZsmPr168cUF3A7zjXkt06dOql06dIaOHCgwsLCJJ3/u6Bdu3aaNGmSKlasKOn8zXsBT6EBC8Djjh49qkGDBunHH3/MdT2fRCK/nTp1Srt27VJYWJgqVaqU7Q7iQF507tw521yviYmJcjqdKleunIKCss/wNHv2bE+XBx80Z84c3XnnnTl+fqWlpWnRokXq3LmzPYXBZzVs2FBz587lpjVwO8415Le0tDSNHj1av/zyi0aPHq1atWpJkmrXrq25c+eqWrVqNlcIf8QcsAA87o033tDJkyc1Y8YM9ejRQ+PGjVNKSoo++OADvfTSS3aXBx9UpEgR1atXz+4y4EPatGljdwnwM4MGDdItt9yiEiVKZFt+6tQpDRo0iAYs8h3jdOApnGvIbyEhIXr55Ze1fPlyPfHEE3rooYfUp08fu8uCn6MBC8DjVq9erf/7v/9T3bp15XA4VLZsWd18880KDw/XhAkT1LJlS7tLBIArYgoLeNqF+eou9ddff6lo0aI2VAQAQMHWokULffXVV1e8+hLwFBqwADzu9OnTrjmeihcvrqNHj6py5cqqXr26/vjjD5urA4C8Yx475LcL0104HA717Nkz2xQXmZmZ2r9/v2655RYbK4Sv2rhxo90lwE9wrsGdoqKiNGnSJE2ePFkREREKDw+3uyT4KRqwADyucuXK2r17t8qVK6caNWpo+vTpKleunKZNm6bo6Gi7ywOAPJs3b5569+5NAxb55sJ0F1u3blXz5s1VpEgR17rg4GDFxMTo9ttvt6s8+JiaNWvqp59+yjHVxbFjx9SsWTPm6Ue+4VyDJ5w7d06hoaGSpB49eqhHjx42VwR/RgMWgMf16NFDycnJks5fxvvoo49q/vz5Cg4O1ttvv21zdQCQd8xjh/x2YbqLmJgY3XXXXdxEEG51uZ9haWlpCg4O9nA18GWca/CEpk2b6vbbb1d8fLyaNm2qgIAAu0uCH6MBC8DjOnXq5Hpcp04dLVu2TH/++afKlCnDqDEAAHLRpEkTHT16VKVLl5Ykbd68WfPnz1e1atV0//3321wdAwcZqQABAABJREFUvN3kyZMlSQ6HQzNnzlThwoVd67KysrR27VpVqVLFrvLgQzjX4EkjR47U/Pnz9eSTT6po0aJq3769OnbsqLp169pdGvyQw8lQDQAAAKBAe+ihh3Tfffepc+fOSk5OVrt27VS9enXt2bNH3bp148ZwuCatWrWSJCUlJal06dLZRokFBwerXLly6tevn+Li4uwqET6Ccw12SE1N1eLFi7Vw4UKtWrVK5cuXV3x8PL874VE0YAF4nNPp1LfffqvVq1fr6NGjysrKyrZ+3LhxNlUGANdu0KBBeuaZZ1SqVCm7S4EPadSokaZPn64qVapo8uTJWrRokaZNm6affvpJQ4cO1dKlS+0uET6ge/fuGjdunIoXL253KfBxnGuwy86dO/X8889r27ZtzDUMj2IKAgAe98Ybb2j69Om66aabFBUVJYfDYXdJAGBZQkJCrsvnz5+v1q1b69ixY5Kk2NhYT5YFH5WRkeGa//WXX35xjSKrUqWKa1514FpNmTLF9Xj9+vWqW7cu8w7DLTjX4Ennzp3T0qVLtWDBAq1YsUJRUVHq3bu33WXBzzACFoDHNW7cWKNHj1aLFi3sLgUA8iw2NlYOhyPXG4lcWO5wOBhdgXzRtWtX3XTTTWrZsqV69eqlGTNmKDY2Vps2bVK/fv30448/2l0ifEzDhg01d+5clS9f3u5S4OM41+AuK1as0IIFC7RkyRIFBQWpXbt2io+PV6NGjewuDX6IEbAAPC48PFzlypWzuwwAuCY1atRQ6dKlNXDgQIWFhUk6P8VKu3btNGnSJFWsWNHmCuFLnn/+efXt21cfffSROnfu7BpZ/cMPP6hevXo2VwdfxDgdeArnGtylb9++atmypUaOHKkWLVooODjY7pLgx2jAAvC4p59+WuPHj9ebb77paloAgLeZOXOmRo8erX79+mn06NGqVauWa13JkiUVExNjY3XwNTfddJNWrVql1NTUbHMm3nfffSpUqJDrOZfyAgBw3s8//6zw8HBJ0qFDh1SyZMlsN34DPIkpCAB43NmzZ/XUU09pw4YNKleunIKCsn8WNHv2bJsqAwDrli9frldffVUPPfSQ+vTpo7p162ru3LmqVq2a3aXBD3EpL/LLhfmsCxcubHcp8HGca/AEfj/CboyABeBxL774on7//Xd17NiRm3AB8HotWrTQV199pUGDBjEPJ2zH2Arkl/j4eLtLgJ/gXIMn8PsRdqMBC8Djli9frv/973+68cYb7S4FAPJFVFSUJk2apMmTJysiIsJ1uRsAeJPTp09r4sSJWrVqlY4cOaKsrKxs65cuXWpTZfA1nGsA/A0NWAAeV7p0aZoTAHzGuXPnFBoaKknq0aOHevToYXNFAJA3Q4YM0Zo1a9SpUydFR0dzlRLchnMNnvb4449nm0Md8DTmgAXgcf/v//0/TZkyRa+99prKlStndzkAcE0aNmyo22+/XfHx8WratCk3d4CtGjRooHnz5jHHHfLkxhtv1IQJE3TDDTfYXQp8HOcaPO1C64tmP+zCCFgAHvfCCy/ozJkzatu2rcLCwhQcHJxt/Zo1a2yqDACsGzlypObPn68nn3xSRYsWVfv27dWxY0fVrVvX7tLgh/jDEteiWLFiioiIsLsM+AHONXjKzJkz9dlnn2nPnj2SpEqVKqlnz57q2rWrvYXB7zACFoDHzZ49+4rru3Tp4qFKACD/pKamavHixVq4cKFWrVql8uXLKz4+Xn379rW7NPgRRsDiWsydO1dLly7VyJEjVahQIbvLgQ/jXIMnvPvuu/r000/VrVs31a9fX5K0adMmff755/rXv/6l/v3721sg/AoNWAAF1sSJE/XAAw+oWLFidpcCAJbs3LlTzz//vLZt26atW7faXQ58TFpamg4dOqTSpUsrJCTE7nLg5Tp37pxt5HRiYqKcTqfKlSunoKDsF0xe7UN04Eo41+BpTZo00ZAhQ9ShQ4dsyxcsWKARI0Zo9erVNlUGf8QUBAAKrA8//FDt27enAQvAK5w7d05Lly7VggULtGLFCkVFRal37952lwUv9/XXX6ty5cpq0KCBzp07p9dee01z5syR0+lUQECA7rnnHg0ZMoRGLPKsTZs2dpcAP8G5Bk/LyMhQnTp1ciyvXbu2MjMzbagI/owRsAAKLC6jBOANVqxYoQULFmjJkiUKCgpSu3btFB8fr0aNGtldGnxA69at9c477yguLk4jR47U4sWLNWjQIFWpUkW7d+/W6NGj1bp1aw0cONDuUgEAKFBGjBihoKAgDRo0KNvykSNH6uzZsxo6dKhNlcEfMQIWAADgGvTt21ctW7bUyJEj1aJFixw3FgSuxeHDhxUdHS1J+uGHHzRs2DDdeuutkqSqVauqePHiGjhwIA1Y5Lthw4apX79+ioyMtLsU+DjONbjTrFmz9PPPPysuLk6StHnzZiUlJalz58566623XNtd2qQF8hsNWAAAgGvw888/Kzw8XJJ06NAhlSxZUgEBATZXBV8RHR2tvXv3qmzZsjpz5oyuu+66bOsjIyN1/Phxe4qDT5s3b5569+5NUwxux7kGd9m+fbtq1aolSdq7d68kKSIiQhEREdq+fbtru4vnJgbchQYsAADANbjQfJWkO++8U3PnzmXqFOSb+Ph4jR07VhMnTlSnTp00fvx4/ec//1GRIkV05swZvf/++2rYsKHdZcIHMVMdPIVzDe4yZcoUu0sAXGjAAgAA5BP+iER+e+qpp7R9+3a1adNGderU0bp163TzzTerVKlSOnz4sCIiIvTxxx/bXSYAAAVKenq64uLiNGfOHFWvXt3ucgAasAAKrhtvvFGhoaF2lwEAgG1CQkL0wQcf6Mcff9SyZcsUEBAgp9Op6OhoNWzYUB06dFDhwoXtLhM+aOPGjXaXAD/BuQZ3CA4OVpkyZZSVlWV3KYAkyeFkqAYAD/v9998VFBSkGjVqSJKWLFmir7/+WtWqVVPfvn0VEhJic4UAkDcTJkzQgw8+qGLFitldCgBcs0GDBumZZ55RqVKl7C4FPo5zDe4wc+ZMff/99xo1apQiIiLsLgd+jgYsAI+755579Nhjj6ldu3bat2+f7rrrLrVt21a//fabWrRooZdfftnuEgEgTy78t4qbOcCduGM48ltCQkKuy++9916NHTtW5cqVkyTFxsZ6siz4IM41eFLnzp2VmJiojIwMlS1bNscVI7Nnz7apMvgjGrAAPO6GG27Q7NmzVaFCBU2cOFGrV6/WRx99pPXr1+u5557T8uXL7S4RACyZOXOmPvvsM+3Zs0eSVKlSJfXs2VNdu3a1tzD4pIYNG3KzN+Sr2NhYORyOXOexvrDc4XBo69atNlQHX8K5Bk8aN27cFdf37dvXQ5UAzAELwAZOp9M1F8/KlSvVsmVLSVKZMmV07NgxGysDAOveffddffrpp+rWrZvq168vSdq0aZPefPNNJSUlqX///vYWCJ/D+Anktxo1aqh06dIaOHCgwsLCJJ0/z9q1a6dJkyapYsWKNlcIX8G5Bk+iwYqCJMDuAgD4nzp16uiDDz7QnDlztHbtWlcDdv/+/YqKirK3OACwaOrUqRoxYoQGDBig1q1bq3Xr1howYIBGjBihL7/80u7yAOCqZs6cqQoVKqhfv346ceKEYmJiXJeClyxZUjExMYqJibG5SvgCzjUA/ooRsAA8bvDgwXrhhRe0ZMkSPf74465PuhcvXqwGDRrYXB0AWJORkaE6derkWF67dm1lZmbaUBF8HXcMR34LCQnRyy+/rOXLl+uJJ57QQw89pD59+thdFnwQ5xrcrXHjxvr2228VGRmpRo0aXXFe/jVr1niwMvg75oAFUGCcO3dOAQEBCg4OliQtWLBArVq1yjFZOgAUJCNGjFBQUJAGDRqUbfnIkSN19uxZDR061KbK4Etq1qypn376SSVKlMi2/NixY2rWrBnzJSLfpKSkaNCgQTp9+rQ2bdqkuXPnqlq1anaXBR/EuQZ3mD17tu666y6FhIRc9SZbXbp08VBVACNgARQgoaGh2Z6/+uqriouLowELoMCbNWuWfv75Z8XFxUmSNm/erKSkJHXu3FlvvfWWa7tLm7SAqcuNmUhLS3N9cAnkh6ioKE2aNEmTJ09WRESEwsPD7S4JPopzDe5wcVOVBisKEhqwAAosBugD8Abbt29XrVq1JEl79+6VJEVERCgiIkLbt293bXelS+CAy5k8ebKk8+fPzJkzs30omZWVpbVr16pKlSp2lQcfc+7cOdcH4j169FCPHj1srgi+inMNnpKVlaXExEQdOXIkx9+XjRo1sqkq+CMasAAAANdgypQpdpcAH/bpp59KOv+h5LRp0xQQ8M89dIODg1WuXDm99tprNlUHX9O0aVPdfvvtio+PV9OmTbOdb0B+4lyDJ2zatEkDBgxQUlJSjuarw+Fg+h54FHPAAiiwGjRooHnz5ql8+fJ2lwIAuUpPT1dcXJzmzJmj6tWr210OfFj37t01btw4FS9e3O5S4MO+//57zZ8/X8uXL1fRokXVvn17dezYUXXr1rW7NPgYzjV4QqdOnVSpUiX169dP0dHROa5GKlq0qE2VwR/RgAVQYNGABeANWrdurfHjxys2NtbuUuAn1q9fr7p16yokJMTuUuCjUlNTtXjxYi1cuFCrVq1S+fLlFR8fr759+9pdGnwM5xrcqX79+po7d64qVqxodymAGOcPAABwDR5//HG98847On78uN2lwE/06dNHf/31l91lwIeFh4frnnvu0ccff6x58+apUKFCGj9+vN1lwQdxrsGd6tWrp8TERLvLACQxByyAAiwmJkZBQfyYAlCwffHFF0pMTNQtt9yismXLZrtJkiTNnj3bpsrgq7iADe527tw5LV26VAsWLNCKFSsUFRWl3r17210WfBDnGvJbQkKC63H37t01cuRIpaSkqHr16jn+tuTqJXgSnQ0AttqzZ48OHjyosmXL5rg0ZMGCBTZVBQDm2rRpY3cJAJAvVqxYoQULFmjJkiUKCgpSu3bt9PHHH3OncOQ7zjW4S+fOneVwOLJ9WDl48GDX4wvruAkXPI05YAF4zIQJE1SvXj01bdpUJ06cUP/+/bVq1SpJ538R3nzzzXrnnXdUrFgxmysFAKDgmj9/vlq3bp1jtDVwreLi4tSyZUvFx8erRYsWCg4Otrsk+CjONbjLgQMHjLeNiYlxYyVAdjRgAXhMixYt9MEHH6hWrVoaMmSIfv/9d73xxhuqWrWqdu/eraFDh6patWp644037C4VAADA76Smpio8PFySdOjQIZUsWVIBAdw2BPmPcw2eMGHCBJUoUUL33ntvtuWzZs3S0aNH9dhjj9lUGfwRUxAA8JijR4+qePHikqRffvlFI0eOVK1atSSdn3/nlVde0eOPP25niQBgpHHjxvr2228VGRmpRo0ayeFwXHbbNWvWeLAy+KrTp09r4sSJWrVqlY4cOaKsrKxs65cuXWpTZfAlFxpiknTnnXdq7ty5Kl++vI0VwVdxrsETpk+frjFjxuRYfv311+vZZ5+lAQuPogELwGPKli2rHTt2KCYmRg6HQ4GBgdnWBwYG6syZMzZVBwDmBg0a5Prj8eJ5xQB3GTJkiNasWaNOnTopOjr6ik1/ID9woSQ8hXMN7pKcnKzo6OgcyyMjI5WcnGxDRfBnNGABeMx9992nUaNGqXLlyurWrZtGjRqlUaNGqUKFCtq3b5/efPNN3XzzzXaXCQBX1aVLl1wfA+7y448/asKECbrhhhvsLgUAAK9QpkwZbdiwIcfo6vXr16tkyZI2VQV/RQMWgMf07t1bBw8e1F133aXy5cvrwIEDateunQIDA5WZmalatWrpnXfesbtMALAsKytLiYmJOnLkSI6RPNzRGfmhWLFiioiIsLsM+JHHH3/cNXUU4E6ca3CXrl276s0331RGRoaaNGkiSVq5cqVGjx6tXr162Vwd/A034QLgcbt27dKyZcu0b98+OZ1ORUdHq2HDhmrWrBmXVALwOps2bdKAAQOUlJSUo/nqcDi0detWmyqDL5k7d66WLl2qkSNHqlChQnaXAz9w4ecZ/zeDu3GuwV2cTqfGjBmjKVOmKD09XZIUGhqqRx99VH379rW5OvgbGrAAAADXoFOnTqpUqZL69euX69ycRYsWtakyeLvOnTtnO58SExPldDpVrlw5BQVlv5Bt9uzZni4PPmrmzJn67LPPtGfPHklSpUqV1LNnT3Xt2tXewuBzONfgKadOndKuXbsUFhamSpUqKSQkxO6S4IeYggCArR577DG9/vrrzMEDwGslJibqvffeU8WKFe0uBT6mTZs2dpcAP/Puu+/q008/Vbdu3VS/fn1J50f5v/nmm0pKSlL//v3tLRA+g3MNnlSkSBHVq1fP7jLg5xgBC8BWDRo00Lx583JMjA4A3qJHjx569NFHdeutt9pdCgBckyZNmmjIkCHq0KFDtuULFizQiBEjtHr1apsqg6/hXAPgbxgBCwAAYFFCQoLrcffu3TVy5EilpKSoevXqOS4Nj42N9XR58HHDhg1Tv379FBkZaXcp8DEZGRmqU6dOjuW1a9dWZmamDRXBV3GuAfA3NGAB2ComJiZHswIACroLc3NefCHR4MGDXY8vrOMmXHCHefPmqXfv3jRgke86deqkqVOnatCgQdmWz5gxQ/Hx8TZVBV/EuQbA39D1AOBxSUlJKlOmjBwOhxYsWOBa7nQ6dfDgQZUtW9bG6gDg6pYuXWp3CfBjzCAGd5o1a5Z+/vlnxcXFSZI2b96spKQkde7cWW+99ZZru0sbZ4BVnGsA/AkNWAAe17p1a/30008qUaJEtuXHjx9X69atGS0GoMCLiYlxPZ4wYYJKlCihe++9N9s2s2bN0tGjR/XYY495ujwAyJPt27erVq1akqS9e/dKkiIiIhQREaHt27e7tnM4HLbUB9/BuQbA39CABeBxFy7LvdTp06cVGhpqQ0UAkHfTp0/XmDFjciy//vrr9eyzz9KARb7buHGj3SXAR02ZMsXuEuAnONcA+BsasAA85sKlRA6HQ2PHjlWhQoVc6zIzM7V582ZuVgPA6yQnJys6OjrH8sjISCUnJ9tQEfzBoEGD9Mwzz6hUqVJ2lwIfkZ6erri4OM2ZM0fVq1e3uxz4MM41AP6IBiwAj/njjz8knR8Bu337dgUHB7vWhYSEKDY2Vr169bKrPADIkzJlymjDhg0qX758tuXr169XyZIlbaoKviIhISHX5fPnz1fr1q117NgxSeIDTFyz4OBglSlTRllZWXaXAh/HuQbAHzmczOIPwMMGDRqkl19+WeHh4XaXAgDXbNKkSfrf//6ngQMHqkmTJpKklStXavTo0erVq5f+/e9/21whvFlsbKwcDkeuN966sNzhcDB/OvLFzJkz9f3332vUqFGKiIiwuxz4MM41AP6GBiwAWy1YsECtWrVS4cKF7S4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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "print(\"is infill\")\n", "get_preference_counts(\n", " user_intersting_clips_3p5[(user_intersting_clips_3p5[\"task\"] == \"infill\")],\n", " \"is infill\",\n", ")" ] }, { "cell_type": "code", "execution_count": 60, "metadata": { "execution": { "iopub.execute_input": "2024-12-18T04:34:49.400060Z", "iopub.status.busy": "2024-12-18T04:34:49.399909Z", "iopub.status.idle": "2024-12-18T04:34:56.761070Z", "shell.execute_reply": "2024-12-18T04:34:56.760503Z", "shell.execute_reply.started": "2024-12-18T04:34:49.400044Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "is artist\n", "len pos models: 36439\n", "differing counts: 12122\n", "chirp-v3p5-engine-b_win_over_chirp-v3p5-engine-b, win ratio 1.000, (1.000, 1.000), counts 150, total 150.\n", "chirp-v3p5-engine-t-6_s_30_t_12_tag_2_win_over_chirp-v3p5-engine-t-6, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v3p5-engine-t-6_s_max_t_12_tag_2_win_over_chirp-v3p5-engine-t-6, win ratio 0.528, (0.499, 0.558), counts 579, total 1096.\n", "chirp-v3p5-engine-t-6_s_max_t_13_tag_2_win_over_chirp-v3p5-engine-t-6, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v3p5-engine-t-6_win_over_chirp-v3p5-engine-t-6, win ratio 1.000, (1.000, 1.000), counts 7516, total 7516.\n", "chirp-v3p5-engine-t-6_win_over_chirp-v3p5-engine-t-6_s_max_t_12_tag_2, win ratio 0.472, (0.442, 0.501), counts 517, total 1096.\n", "chirp-v3p5-engine-t-6_win_over_chirp-v3p5-engine-t-6_s_max_t_14_tag_2, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-engine-b_win_over_chirp-v4-engine-b, win ratio 1.000, (1.000, 1.000), counts 183, total 183.\n", "chirp-v4-h-t-6-artist-cfg_win_over_chirp-v4-h-t-6, win ratio 0.316, (0.290, 0.342), counts 385, total 1219.\n", "chirp-v4-h-t-6_a_25_r_30_win_over_chirp-v4-h-t-6, win ratio 0.500, (-0.193, 1.193), counts 1, total 2.\n", "chirp-v4-h-t-6_step_10_win_over_chirp-v4-h-t-6, win ratio 0.516, (0.489, 0.543), counts 666, total 1291.\n", "chirp-v4-h-t-6_step_16_text_1_win_over_chirp-v4-h-t-6, win ratio 0.483, (0.440, 0.526), counts 253, total 524.\n", "chirp-v4-h-t-6_step_16_win_over_chirp-v4-h-t-6, win ratio 0.498, (0.471, 0.526), counts 643, total 1290.\n", "chirp-v4-h-t-6_step_8_win_over_chirp-v4-h-t-6, win ratio 0.463, (0.436, 0.489), counts 631, total 1364.\n", "chirp-v4-h-t-6_temp_s_70_win_over_chirp-v4-h-t-6, win ratio 0.518, (0.491, 0.545), counts 684, total 1321.\n", "chirp-v4-h-t-6_temp_s_80_win_over_chirp-v4-h-t-6, win ratio 0.510, (0.483, 0.537), counts 678, total 1330.\n", "chirp-v4-h-t-6_temp_s_90_win_over_chirp-v4-h-t-6, win ratio 0.505, (0.479, 0.532), counts 684, total 1354.\n", "chirp-v4-h-t-6_temp_s_95_win_over_chirp-v4-h-t-6, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-t-6_text_15_win_over_chirp-v4-h-t-6, win ratio 0.333, (-0.200, 0.867), counts 1, total 3.\n", "chirp-v4-h-t-6_text_1_win_over_chirp-v4-h-t-6, win ratio 0.498, (0.472, 0.525), counts 659, total 1322.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6, win ratio 1.000, (1.000, 1.000), counts 16468, total 16468.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6-artist-cfg, win ratio 0.684, (0.658, 0.710), counts 834, total 1219.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_a_25_r_30, win ratio 0.500, (-0.193, 1.193), counts 1, total 2.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_step_10, win ratio 0.484, (0.457, 0.511), counts 625, total 1291.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_step_16, win ratio 0.502, (0.474, 0.529), counts 647, total 1290.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_step_16_text_1, win ratio 0.517, (0.474, 0.560), counts 271, total 524.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_step_8, win ratio 0.537, (0.511, 0.564), counts 733, total 1364.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_temp_s_70, win ratio 0.482, (0.455, 0.509), counts 637, total 1321.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_temp_s_80, win ratio 0.490, (0.463, 0.517), counts 652, total 1330.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_temp_s_90, win ratio 0.495, (0.468, 0.521), counts 670, total 1354.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_text_1, win ratio 0.502, (0.475, 0.528), counts 663, total 1322.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_text_15, win ratio 0.667, (0.133, 1.200), counts 2, total 3.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_text_25, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-h-t-6_win_over_chirp-v4-h-t-6_text_3, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "tournament players: ['chirp-v3p5-engine-t-6', 'chirp-v3p5-engine-t-6_s_30_t_12_tag_2', 'chirp-v3p5-engine-t-6_s_max_t_12_tag_2', 'chirp-v3p5-engine-t-6_s_max_t_13_tag_2', 'chirp-v3p5-engine-t-6_s_max_t_14_tag_2', 'chirp-v4-h-t-6', 'chirp-v4-h-t-6-artist-cfg', 'chirp-v4-h-t-6_a_25_r_30', 'chirp-v4-h-t-6_step_10', 'chirp-v4-h-t-6_step_16', 'chirp-v4-h-t-6_step_16_text_1', 'chirp-v4-h-t-6_step_8', 'chirp-v4-h-t-6_temp_s_70', 'chirp-v4-h-t-6_temp_s_80', 'chirp-v4-h-t-6_temp_s_90', 'chirp-v4-h-t-6_temp_s_95', 'chirp-v4-h-t-6_text_1', 'chirp-v4-h-t-6_text_15', 'chirp-v4-h-t-6_text_25', 'chirp-v4-h-t-6_text_3']\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "100%|██████████| 1000/1000 [00:03<00:00, 262.58it/s]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "ELOs\n", "chirp-v3p5-engine-t-6: 491.0, (-7667, 3297)\n", "chirp-v3p5-engine-t-6_s_30_t_12_tag_2: 2444.4, (1000, 12327)\n", "chirp-v3p5-engine-t-6_s_max_t_12_tag_2: 510.6, (-7644, 3335)\n", "chirp-v3p5-engine-t-6_s_max_t_13_tag_2: 2444.4, (1000, 17625)\n", "chirp-v3p5-engine-t-6_s_max_t_14_tag_2: -890.5, (-11201, 1000)\n", "chirp-v4-h-t-6: 1126.6, (228, 3185)\n", "chirp-v4-h-t-6-artist-cfg: 992.2, (107, 3030)\n", "chirp-v4-h-t-6_a_25_r_30: 1125.9, (-5353, 8181)\n", "chirp-v4-h-t-6_step_10: 1137.7, (262, 3207)\n", "chirp-v4-h-t-6_step_16: 1125.5, (226, 3186)\n", "chirp-v4-h-t-6_step_16_text_1: 1114.8, (202, 3155)\n", "chirp-v4-h-t-6_step_8: 1100.6, (202, 3149)\n", "chirp-v4-h-t-6_temp_s_70: 1139.0, (245, 3194)\n", "chirp-v4-h-t-6_temp_s_80: 1133.4, (238, 3188)\n", "chirp-v4-h-t-6_temp_s_90: 1130.3, (215, 3190)\n", "chirp-v4-h-t-6_temp_s_95: 2740.1, (1000, 12509)\n", "chirp-v4-h-t-6_text_1: 1125.6, (222, 3177)\n", "chirp-v4-h-t-6_text_15: 1009.4, (-10355, 7463)\n", "chirp-v4-h-t-6_text_25: -500.5, (-9510, 1000)\n", "chirp-v4-h-t-6_text_3: -500.5, (-7949, 1000)\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "print(\"is artist\")\n", "get_preference_counts(\n", " user_intersting_clips_3p5[\n", " (user_intersting_clips_3p5[\"task\"] == \"artist_consistency\")\n", " ],\n", " \"is artist\",\n", ")" ] }, { "cell_type": "code", "execution_count": 61, "metadata": { "execution": { "iopub.execute_input": "2024-12-18T04:34:56.761832Z", "iopub.status.busy": "2024-12-18T04:34:56.761672Z", "iopub.status.idle": "2024-12-18T04:35:07.493365Z", "shell.execute_reply": "2024-12-18T04:35:07.492807Z", "shell.execute_reply.started": "2024-12-18T04:34:56.761816Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "upsample\n", "len pos models: 31030\n", "differing counts: 16814\n", "chirp-v4-engine-b_win_over_chirp-v4-engine-b, win ratio 1.000, (1.000, 1.000), counts 40, total 40.\n", "chirp-v4-up-u-2-d-2_win_over_chirp-v4-up-u-2, win ratio 0.375, (0.040, 0.710), counts 3, total 8.\n", "chirp-v4-up-u-2_step_8_win_over_chirp-v4-up-u-2, win ratio 0.500, (0.100, 0.900), counts 3, total 6.\n", "chirp-v4-up-u-2_text_3_win_over_chirp-v4-up-u-2, win ratio 0.500, (0.010, 0.990), counts 2, total 4.\n", "chirp-v4-up-u-2_win_over_chirp-v4-up-u-2, win ratio 1.000, (1.000, 1.000), counts 20, total 20.\n", "chirp-v4-up-u-2_win_over_chirp-v4-up-u-2-d-2, win ratio 0.625, (0.290, 0.960), counts 5, total 8.\n", "chirp-v4-up-u-2_win_over_chirp-v4-up-u-2_step_16, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-up-u-2_win_over_chirp-v4-up-u-2_step_8, win ratio 0.500, (0.100, 0.900), counts 3, total 6.\n", "chirp-v4-up-u-2_win_over_chirp-v4-up-u-2_text_15, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-up-u-2_win_over_chirp-v4-up-u-2_text_25, win ratio 1.000, (1.000, 1.000), counts 3, total 3.\n", "chirp-v4-up-u-2_win_over_chirp-v4-up-u-2_text_3, win ratio 0.500, (0.010, 0.990), counts 2, total 4.\n", "chirp-v4-up-u-3-c-3_step_16_win_over_chirp-v4-up-u-3, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-up-u-3-c-3_win_over_chirp-v4-up-u-3, win ratio 0.517, (0.491, 0.543), counts 730, total 1412.\n", "chirp-v4-up-u-3_step_10_win_over_chirp-v4-up-u-3, win ratio 0.483, (0.465, 0.501), counts 1440, total 2983.\n", "chirp-v4-up-u-3_step_10_win_over_chirp-v4-up-u-3_step_10, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-up-u-3_step_10_win_over_chirp-v4-up-u-3_text_25, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-up-u-3_step_16_text_1_win_over_chirp-v4-up-u-3, win ratio 0.414, (0.374, 0.454), counts 239, total 577.\n", "chirp-v4-up-u-3_step_16_text_1_win_over_chirp-v4-up-u-3_step_16, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-up-u-3_step_16_win_over_chirp-v4-up-u-3, win ratio 0.500, (0.482, 0.518), counts 1492, total 2986.\n", "chirp-v4-up-u-3_step_16_win_over_chirp-v4-up-u-3_step_10, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-up-u-3_step_16_win_over_chirp-v4-up-u-3_text_3, win ratio 1.000, (1.000, 1.000), counts 1, total 1.\n", "chirp-v4-up-u-3_step_8_win_over_chirp-v4-up-u-3, win ratio 0.491, (0.473, 0.509), counts 1452, total 2957.\n", "chirp-v4-up-u-3_text_15_win_over_chirp-v4-up-u-3, win ratio 0.474, (0.449, 0.499), counts 710, total 1498.\n", "chirp-v4-up-u-3_text_1_win_over_chirp-v4-up-u-3, win ratio 0.448, (0.422, 0.473), counts 661, total 1476.\n", "chirp-v4-up-u-3_text_25_win_over_chirp-v4-up-u-3, win ratio 0.506, (0.480, 0.531), counts 740, total 1463.\n", "chirp-v4-up-u-3_text_3_win_over_chirp-v4-up-u-3, win ratio 0.472, (0.446, 0.498), counts 677, total 1434.\n", "chirp-v4-up-u-3_win_over_chirp-v4-up-u-3, win ratio 1.000, (1.000, 1.000), counts 14155, total 14155.\n", "chirp-v4-up-u-3_win_over_chirp-v4-up-u-3-c-3, win ratio 0.483, (0.457, 0.509), counts 682, total 1412.\n", "chirp-v4-up-u-3_win_over_chirp-v4-up-u-3_step_10, win ratio 0.517, (0.499, 0.535), counts 1543, total 2983.\n", "chirp-v4-up-u-3_win_over_chirp-v4-up-u-3_step_16, win ratio 0.500, (0.482, 0.518), counts 1494, total 2986.\n", "chirp-v4-up-u-3_win_over_chirp-v4-up-u-3_step_16_text_1, win ratio 0.586, (0.546, 0.626), counts 338, total 577.\n", "chirp-v4-up-u-3_win_over_chirp-v4-up-u-3_step_8, win ratio 0.509, (0.491, 0.527), counts 1505, total 2957.\n", "chirp-v4-up-u-3_win_over_chirp-v4-up-u-3_text_1, win ratio 0.552, (0.527, 0.578), counts 815, total 1476.\n", "chirp-v4-up-u-3_win_over_chirp-v4-up-u-3_text_15, win ratio 0.526, (0.501, 0.551), counts 788, total 1498.\n", "chirp-v4-up-u-3_win_over_chirp-v4-up-u-3_text_25, win ratio 0.494, (0.469, 0.520), counts 723, total 1463.\n", "chirp-v4-up-u-3_win_over_chirp-v4-up-u-3_text_3, win ratio 0.528, (0.502, 0.554), counts 757, total 1434.\n", "tournament players: ['chirp-v4-up-u-2', 'chirp-v4-up-u-2-d-2', 'chirp-v4-up-u-2_step_16', 'chirp-v4-up-u-2_step_8', 'chirp-v4-up-u-2_text_15', 'chirp-v4-up-u-2_text_25', 'chirp-v4-up-u-2_text_3', 'chirp-v4-up-u-3', 'chirp-v4-up-u-3-c-3', 'chirp-v4-up-u-3-c-3_step_16', 'chirp-v4-up-u-3_step_10', 'chirp-v4-up-u-3_step_16', 'chirp-v4-up-u-3_step_16_text_1', 'chirp-v4-up-u-3_step_8', 'chirp-v4-up-u-3_text_1', 'chirp-v4-up-u-3_text_15', 'chirp-v4-up-u-3_text_25', 'chirp-v4-up-u-3_text_3']\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "100%|██████████| 1000/1000 [00:04<00:00, 200.97it/s]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "ELOs\n", "chirp-v4-up-u-2: 2116.7, (934, 4044)\n", "chirp-v4-up-u-2-d-2: 2027.4, (-1657, 4045)\n", "chirp-v4-up-u-2_step_16: 39.2, (-2163, 1000)\n", "chirp-v4-up-u-2_step_8: 2117.2, (-95, 6524)\n", "chirp-v4-up-u-2_text_15: 39.2, (-2032, 1000)\n", "chirp-v4-up-u-2_text_25: -1454.5, (-5517, 1000)\n", "chirp-v4-up-u-2_text_3: 2114.7, (-809, 6715)\n", "chirp-v4-up-u-3: 876.4, (621, 1018)\n", "chirp-v4-up-u-3-c-3: 888.2, (636, 1037)\n", "chirp-v4-up-u-3-c-3_step_16: 2372.1, (1000, 5251)\n", "chirp-v4-up-u-3_step_10: 864.4, (592, 1012)\n", "chirp-v4-up-u-3_step_16: 876.3, (620, 1023)\n", "chirp-v4-up-u-3_step_16_text_1: 817.0, (542, 974)\n", "chirp-v4-up-u-3_step_8: 870.2, (607, 1018)\n", "chirp-v4-up-u-3_text_1: 840.0, (582, 989)\n", "chirp-v4-up-u-3_text_15: 858.3, (595, 1008)\n", "chirp-v4-up-u-3_text_25: 880.2, (625, 1031)\n", "chirp-v4-up-u-3_text_3: 856.8, (599, 1006)\n" ] }, { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "print(\"upsample\")\n", "upsample_slice_df = user_intersting_clips_3p5[\n", " (user_intersting_clips_3p5[\"task\"] == \"upsample\")\n", "].copy()\n", "if upsample_slice_df.shape[0] > 0:\n", " get_preference_counts(\n", " upsample_slice_df,\n", " title_name=\"upsample\",\n", " )" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Clean up SHIT\n", "\n", "to get the right play conts, we need the right df..." ] }, { "cell_type": "code", "execution_count": 62, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:08.095035Z", "start_time": "2024-05-26T00:25:07.782738Z" }, "execution": { "iopub.execute_input": "2024-12-18T04:35:07.494116Z", "iopub.status.busy": "2024-12-18T04:35:07.493963Z" } }, "outputs": [], "source": [ "def unpack_dict(x):\n", " if v := concat_clips_ids.get(str(x)):\n", " return v\n", " else:\n", " return {\n", " \"total_start_s\": None,\n", " \"total_clip_s\": None,\n", " \"concat_play_counts\": None,\n", " \"concat_in_playlist\": None,\n", " \"concat_likes\": None,\n", " \"concat_dislikes\": None,\n", " }\n", "\n", "\n", "extra_cols = user_intersting_clips[\"id\"].apply(unpack_dict)\n", "extra_cols_df = pd.DataFrame.from_records(extra_cols.values, index=extra_cols.index)\n", "user_intersting_clips[\n", " [\n", " \"total_start_s\",\n", " \"total_clip_s\",\n", " \"concat_play_counts\",\n", " \"concat_in_playlist\",\n", " \"concat_likes\",\n", " \"concat_dislikes\",\n", " ]\n", "] = extra_cols_df" ] }, { "cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [], "source": [ "def unpack_dict(x):\n", " if v := concat_clips_ids.get(str(x)):\n", " return v\n", " else:\n", " return {\n", " \"total_start_s\": None,\n", " \"total_clip_s\": None,\n", " \"concat_play_counts\": None,\n", " \"concat_in_playlist\": None,\n", " \"concat_likes\": None,\n", " \"concat_dislikes\": None,\n", " }\n", "\n", "\n", "extra_cols = user_intersting_clips[\"id\"].apply(unpack_dict)\n", "extra_cols_df = pd.DataFrame.from_records(extra_cols.values, index=extra_cols.index)\n", "user_intersting_clips[\n", " [\n", " \"total_start_s\",\n", " \"total_clip_s\",\n", " \"concat_play_counts\",\n", " \"concat_in_playlist\",\n", " \"concat_likes\",\n", " \"concat_dislikes\",\n", " ]\n", "] = extra_cols_df" ] }, { "cell_type": "code", "execution_count": 64, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:08.361849Z", "start_time": "2024-05-26T00:25:08.199583Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Positive proportion of data meeting criteria: 39.14%\n", "Negative proportion of data meeting criteria: 100.00%\n" ] } ], "source": [ "pos_too_much_data_mask = (\n", " (user_intersting_clips[\"preference\"])\n", " & (\n", " (\n", " user_intersting_clips[\"reaction_play_count\"] >= 3\n", " ) # single play is super catchy\n", " | (\n", " user_intersting_clips[\"concat_play_counts\"] >= 3\n", " ) # or the concat play is super catchy\n", " )\n", " # & (user_intersting_clips[\"user_n_clips\"] >= 40)\n", " # & (user_intersting_clips[\"continued_parent\"].isna())\n", ")\n", "neg_too_much_data_mask = (\n", " (~user_intersting_clips[\"preference\"])\n", " & (user_intersting_clips[\"reaction_play_count\"] >= 1) # single play is super catchy\n", " # & (user_intersting_clips[\"user_n_clips\"] >= 40)\n", " # & (user_intersting_clips[\"continued_parent\"].isna())\n", ")\n", "# Calculate and print the proportion of data that meets our criteria\n", "pos_proportion = pos_too_much_data_mask.sum() / user_intersting_clips.shape[0] * 2\n", "print(f\"Positive proportion of data meeting criteria: {pos_proportion:.2%}\")\n", "neg_proportion = neg_too_much_data_mask.sum() / user_intersting_clips.shape[0] * 2\n", "print(f\"Negative proportion of data meeting criteria: {neg_proportion:.2%}\")" ] }, { "cell_type": "code", "execution_count": 65, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:08.523643Z", "start_time": "2024-05-26T00:25:08.367348Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Model Name Value Counts for Preferred Clips:\n", "----------------------------------------------------------------------\n", "Model Count Fraction\n", "----------------------------------------------------------------------\n", "chirp-v4-h-s-32 88,424 38.78%\n", "chirp-v3p5-engine-s-8 77,326 33.92%\n", "chirp-v4-h-t-6 28,768 12.62%\n", "chirp-v4-up-u-3 15,148 6.64%\n", "chirp-v3p5-engine-t-6 7,588 3.33%\n", "chirp-v3p5-engine-upload-4 4,706 2.06%\n", "chirp-v4-h-s-31 4,283 1.88%\n", "chirp-v4-engine-b 531 0.23%\n", "chirp-v4-h-t-6-artist-cfg 392 0.17%\n", "chirp-v4-up-u-3-c-3 321 0.14%\n", "chirp-v3p5-engine-short 163 0.07%\n", "chirp-v3p5-engine-b 159 0.07%\n", "chirp-v3p5-engine-b-r 154 0.07%\n", "chirp-v4-up-u-2 26 0.01%\n", "chirp-v4-h-s-31-l-30-2 3 0.00%\n", "chirp-v4-up-u-2-d-2 3 0.00%\n", "----------------------------------------------------------------------\n", "Total 227,995 100.00%\n" ] } ], "source": [ "final_good_enough_requests = set(\n", " user_intersting_clips[pos_too_much_data_mask][\"request_id\"].unique()\n", ").intersection(\n", " set(user_intersting_clips[neg_too_much_data_mask][\"request_id\"].unique())\n", ")\n", "final_interesting_clips = user_intersting_clips[\n", " user_intersting_clips[\"request_id\"].isin(final_good_enough_requests)\n", "].copy()\n", "# Get the value counts of model_name for preferred clips\n", "model_counts = final_interesting_clips[final_interesting_clips[\"preference\"]][\n", " \"model_name\"\n", "].value_counts()\n", "\n", "# Print the results in a nicely formatted way\n", "total_count = model_counts.sum()\n", "print(\"Model Name Value Counts for Preferred Clips:\")\n", "print(\"-\" * 70)\n", "print(f\"{'Model':<30} {'Count':>10} {'Fraction':>15}\")\n", "print(\"-\" * 70)\n", "for model, count in model_counts.items():\n", " fraction = count / total_count\n", " print(f\"{model:<30} {count:>10,d} {fraction:>15.2%}\")\n", "print(\"-\" * 70)\n", "print(f\"{'Total':<30} {total_count:>10,d} {1:>15.2%}\")" ] }, { "cell_type": "code", "execution_count": 66, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:09.198504Z", "start_time": "2024-05-26T00:25:08.885507Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Validation passed!\n" ] } ], "source": [ "validate_preference_data(final_interesting_clips)" ] }, { "cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of rows in final_interesting_clips for model chirp-v3p5-engine-t-6:\n", "15,176\n", "done (455990, 58)\n" ] } ], "source": [ "# Get the number of rows for final_interesting_clips with the specific model\n", "row_count = final_interesting_clips[\n", " final_interesting_clips[\"model_name\"] == target_model_name\n", "].shape[0]\n", "\n", "# Print the row count in a nicely formatted way\n", "print(f\"Number of rows in final_interesting_clips for model {target_model_name}:\")\n", "print(f\"{row_count:,}\")\n", "print(\"done\", final_interesting_clips.shape)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# For faster processing once" ] }, { "cell_type": "code", "execution_count": 68, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:10.265241Z", "start_time": "2024-05-26T00:25:09.934743Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Total Unique Users:\n", "--------------------\n", "690,647\n", "--------------------\n", "Series([], Name: count, dtype: int64)\n", "(0, 48)\n" ] } ], "source": [ "# Calculate the number of unique users\n", "total_unique_users = clip_df[\"user_id\"].nunique()\n", "\n", "# Print the result in a nicely formatted way\n", "print(\"Total Unique Users:\")\n", "print(\"-\" * 20)\n", "print(f\"{total_unique_users:,}\")\n", "print(\"-\" * 20)\n", "\n", "# This can take a while cause we have a lot of users...\n", "# query = \"\"\"\n", "# SELECT *\n", "# FROM auth_user\n", "# \"\"\"\n", "# user_df = pd.read_sql_query(query, engine)\n", "# user_df.head()\n", "\n", "test_user_id = 4688272\n", "print(\n", " clip_df[clip_df[\"user_id\"] == test_user_id][\"created_at\"]\n", " .apply(lambda x: str(x)[:10])\n", " .value_counts()\n", ")\n", "print(clip_df[clip_df[\"user_id\"] == test_user_id].shape)\n", "query = \"\"\"\n", "SELECT *\n", "FROM auth_user\n", "WHERE id=25400222\n", "\"\"\"\n", "# 3 keenan\n", "# 6 martin\n", "# 8 tony -- that's me!\n", "# 186417 georg\n", "# test_user_df = pd.read_sql_query(query, engine)\n", "# test_user_df" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Find some weird generations" ] }, { "cell_type": "code", "execution_count": 69, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Shape of no_reaction_clip_df:\n", "(1947010, 48)\n", "\n", "Proportion of clips without reactions:\n", "20.61%\n", "Ratio of clips without reactions to total clips from the same users:\n", "0.5772\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "free 18615\n", "pro 2012\n", "Ratio of clips from super bad users: 2.50%\n", "DONE\n" ] } ], "source": [ "not_known_bot_gens_mask = clip_df[\"model_name\"] != \"chirp-v3p5-engine-b\"\n", "# run_bot_detection(clip_df[not_known_bot_gens_mask], reaction_df, write_to_file=True, cut_off_freq=0.95)\n", "run_bot_detection(\n", " clip_df,\n", " reaction_df,\n", " write_to_file=True,\n", " cut_off_freq=0.95,\n", " min_generations_for_no_reaction=10,\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Alpha testing user selection" ] }, { "cell_type": "code", "execution_count": 70, "metadata": {}, "outputs": [], "source": [ "# Alpha testing user selection\n", "# we focus on the folks who are good good\n", "\n", "# # 0526 is v2 -- prod\n", "# # 0529 is v4 -- still good IMO, more data\n", "# early_v3p5_data = pd.read_csv(\"/home/tony/Data/Preference/13b_v0/interesting_clips_20240529.csv\")\n", "\n", "# print(\"uqniue users for vp5\", early_v3p5_data[\"user_id\"].nunique())\n", "\n", "# early_v3_data = pd.read_csv(\"/home/tony/Data/Preference/7b_v0_interesting_clips.csv\")\n", "\n", "# print(\"uqniue users for v3\", early_v3_data[\"user_id\"].nunique())\n", "\n", "# early_v2_data = pd.read_csv(\"/home/tony/Data/Preference/3b_v0_interesting_clips.csv\")\n", "\n", "# print(\"uqniue users for v2\", early_v2_data[\"user_id\"].nunique())\n", "\n", "# intersection_user_ids_super = set(early_v3p5_data[\"user_id\"].unique()).intersection(set(early_v3_data[\"user_id\"].unique())).intersection(set(early_v2_data[\"user_id\"].unique()))\n", "\n", "# intersection_user_ids_v3_on = set(early_v3p5_data[\"user_id\"].unique()).intersection(set(early_v3_data[\"user_id\"].unique())).difference(intersection_user_ids_super)\n", "\n", "# print(len(intersection_user_ids_super), len(intersection_user_ids_v3_on))\n", "\n", "# super_user_df = user_df[user_df[\"id\"].isin(intersection_user_ids_super)].copy()\n", "# print(super_user_df.shape)\n", "# v3_onward_user_df = user_df[user_df[\"id\"].isin(intersection_user_ids_v3_on)].copy()\n", "# print(v3_onward_user_df.shape)\n", "# super_user_df.to_csv(\"/home/tony/Data/Preference/alpha_users/super_user.csv\", index=False)\n", "# v3_onward_user_df.to_csv(\"/home/tony/Data/Preference/alpha_users/v3_onward_user.csv\", index=False)\n", "# print(\"Done!!\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# User generated clips lifetime filter" ] }, { "cell_type": "code", "execution_count": 71, "metadata": {}, "outputs": [], "source": [ "# query = \"\"\"\n", "# SELECT *\n", "# FROM bots_userstats\n", "# WHERE total_clips>=100\n", "# \"\"\"\n", "# user_stats_df = pd.read_sql_query(query, engine)\n", "# print(user_stats_df.shape)\n", "# user_stats_df[\"total_clips\"].describe()\n", "# top_users = user_stats_df[user_stats_df[\"total_clips\"] >= 100][\"user_id\"].unique()\n", "# print(len(top_users))" ] }, { "cell_type": "code", "execution_count": 72, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "89122\n" ] } ], "source": [ "top_users = clip_df[clip_df[\"user_n_clips\"] >= 20][\"user_id\"].unique()\n", "print(len(top_users))" ] }, { "cell_type": "markdown", "metadata": { "execution": { "iopub.execute_input": "2024-06-21T19:35:17.755108Z", "iopub.status.busy": "2024-06-21T19:35:17.754937Z", "iopub.status.idle": "2024-06-21T19:35:17.774581Z", "shell.execute_reply": "2024-06-21T19:35:17.774106Z", "shell.execute_reply.started": "2024-06-21T19:35:17.755091Z" } }, "source": [ "# Snow flake access" ] }, { "cell_type": "code", "execution_count": 73, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "PROD\n" ] } ], "source": [ "if not os.path.exists(snow_password_path):\n", " raise Exception(\"you are not authorized to access snowflake -- please setup\")\n", "\n", "snow_session = Session.builder.configs(CONNECTION_PARAMETERS).create()\n", "\n", "snow_root = Root(snow_session)\n", "snow_schema = snow_root.databases[\"SUNO_PROD\"].schemas[\"PROD\"]\n", "print(snow_schema.name)" ] }, { "cell_type": "code", "execution_count": 74, "metadata": {}, "outputs": [], "source": [ "def analyze_clip_data_with_snowflake(\n", " final_interesting_clips, target_model_name, top_users, snow_session\n", "):\n", " # select the df we want to squery for play counts\n", " subset_v4_clips_df_all = final_interesting_clips[\n", " final_interesting_clips[\"model_name\"] == target_model_name\n", " ].copy()\n", " print(subset_v4_clips_df_all.shape)\n", "\n", " # Filter for pairs\n", " pair_request_mask = subset_v4_clips_df_all[\"request_id\"].isin(\n", " subset_v4_clips_df_all[\"request_id\"]\n", " .value_counts()\n", " .index[subset_v4_clips_df_all[\"request_id\"].value_counts() == 2]\n", " )\n", " subset_v4_clips_df = subset_v4_clips_df_all[pair_request_mask].copy()\n", " print(subset_v4_clips_df.shape)\n", "\n", " # Get clip IDs and query Snowflake in batches\n", " v4_clip_ids = list(str(s) for s in subset_v4_clips_df[\"id\"].unique())\n", " snow_batch_size = 100_000\n", " snow_results = []\n", "\n", " for clip_ids_chunk in tqdm.tqdm(\n", " [\n", " v4_clip_ids[i : i + snow_batch_size]\n", " for i in range(0, len(v4_clip_ids), snow_batch_size)\n", " ]\n", " ):\n", " id_query_str = \",\".join(\"'\" + x + \"'\" for x in clip_ids_chunk)\n", " print(f\"Number of clip IDs in this chunk: {len(clip_ids_chunk)}\")\n", " print(f\"Length of the ID query string: {len(id_query_str)}\")\n", "\n", " session_query = snow_session.sql(\n", " f\"\"\" select *\n", " from ML_SONG_SUMMARY_INFO\n", " where p_date = DATE(SYSDATE() - INTERVAL '2 HOUR')\n", " and p_hour = hour(SYSDATE() - INTERVAL '2 HOUR')\n", " and song_id in ({id_query_str})\n", " order by p_hour desc;\"\"\"\n", " )\n", " temp_df_snow_test = pd.DataFrame(session_query.collect())\n", " snow_results.append(temp_df_snow_test)\n", " print(len(snow_results))\n", "\n", " # Process Snowflake results\n", " df_snow_test = pd.concat(snow_results)\n", " df_snow_test = df_snow_test.rename(columns=lambda x: x.lower())\n", " df_snow_test = df_snow_test.rename(columns={\"song_id\": \"str_id\"})\n", " print(\"Shape of df_snow_test:\")\n", " print(f\"Rows: {df_snow_test.shape[0]}\")\n", " print(f\"Columns: {df_snow_test.shape[1]}\")\n", "\n", " # Merge data and calculate normalized play fractions\n", " subset_v4_clips_df[\"str_id\"] = subset_v4_clips_df[\"id\"].astype(str)\n", " subset_v4_clips_df_test = subset_v4_clips_df.merge(\n", " df_snow_test, on=\"str_id\", how=\"left\"\n", " )\n", " subset_v4_clips_df_test[\"norm_play_frac\"] = (\n", " subset_v4_clips_df_test[\"total_play_time\"].fillna(0)\n", " / subset_v4_clips_df_test[\"duration\"]\n", " )\n", "\n", " # Create visualization\n", " fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(16, 6))\n", "\n", " # First subplot: Total play duration\n", " pos_play_time = subset_v4_clips_df_test[subset_v4_clips_df_test[\"preference\"]][\n", " \"total_play_time\"\n", " ]\n", " neg_play_time = subset_v4_clips_df_test[~subset_v4_clips_df_test[\"preference\"]][\n", " \"total_play_time\"\n", " ]\n", "\n", " pos_play_time.hist(\n", " bins=np.linspace(0, 400, 100),\n", " alpha=0.5,\n", " label=f\"pos (mean={pos_play_time.mean():.2f}, median={pos_play_time.median():.2f})\",\n", " ax=ax1,\n", " )\n", " neg_play_time.hist(\n", " bins=np.linspace(0, 400, 100),\n", " alpha=0.5,\n", " label=f\"neg (mean={neg_play_time.mean():.2f}, median={neg_play_time.median():.2f})\",\n", " ax=ax1,\n", " )\n", " ax1.legend()\n", " ax1.set_xlabel(\"Total play duration in seconds\")\n", " ax1.set_ylabel(\"counts\")\n", " ax1.set_title(\"Play duration comparison\")\n", "\n", " # Second subplot: Normalized play fraction\n", " pos_norm_play_frac = subset_v4_clips_df_test[subset_v4_clips_df_test[\"preference\"]][\n", " \"norm_play_frac\"\n", " ]\n", " neg_norm_play_frac = subset_v4_clips_df_test[\n", " ~subset_v4_clips_df_test[\"preference\"]\n", " ][\"norm_play_frac\"]\n", "\n", " pos_norm_play_frac.hist(\n", " bins=np.linspace(0, 10, 100),\n", " alpha=0.5,\n", " label=f\"pos (mean={pos_norm_play_frac.mean():.2f}, median={pos_norm_play_frac.median():.2f})\",\n", " ax=ax2,\n", " )\n", " neg_norm_play_frac.hist(\n", " bins=np.linspace(0, 10, 100),\n", " alpha=0.5,\n", " label=f\"neg (mean={neg_norm_play_frac.mean():.2f}, median={neg_norm_play_frac.median():.2f})\",\n", " ax=ax2,\n", " )\n", " ax2.legend()\n", " ax2.set_xlabel(\"Normalized play counts (play duration/duration)\")\n", " ax2.set_ylabel(\"Log counts\")\n", " ax2.set_yscale(\"log\")\n", " ax2.set_title(\"Normalized play duration comparison (Log scale)\")\n", "\n", " plt.tight_layout()\n", " plt.show()\n", "\n", " # Apply filters and analyze results\n", " play_duration_mask = (\n", " subset_v4_clips_df_test[\"preference\"]\n", " & (subset_v4_clips_df_test[\"norm_play_frac\"] >= 0.95)\n", " & (subset_v4_clips_df_test[\"total_play_time\"] >= 10)\n", " & (subset_v4_clips_df_test[\"user_id\"].isin(top_users))\n", " & (\n", " (subset_v4_clips_df_test[\"reaction_play_count\"] >= 3)\n", " | (subset_v4_clips_df_test[\"concat_play_counts\"] >= 3)\n", " )\n", " ) | (\n", " (~subset_v4_clips_df_test[\"preference\"])\n", " & (subset_v4_clips_df_test[\"norm_play_frac\"] <= 3.1)\n", " & (subset_v4_clips_df_test[\"total_play_time\"] >= 10)\n", " & (subset_v4_clips_df_test[\"user_id\"].isin(top_users))\n", " )\n", "\n", " # Calculate and print statistics\n", " frac_pass_play_duration = (\n", " play_duration_mask.sum() / subset_v4_clips_df_test.shape[0]\n", " )\n", " print(\n", " f\"Fraction of clips that pass the play duration cut: {frac_pass_play_duration:.4f}\"\n", " )\n", "\n", " unique_requests_pass_play_durations = subset_v4_clips_df_test[play_duration_mask][\n", " \"request_id\"\n", " ].unique()\n", " print(\n", " f\"Number of unique requests passing play duration criteria: {len(unique_requests_pass_play_durations)}\"\n", " )\n", "\n", " fraction_requests_pass = (\n", " len(unique_requests_pass_play_durations)\n", " / subset_v4_clips_df_test[\"request_id\"].nunique()\n", " )\n", " print(\n", " f\"Fraction of unique requests that pass play duration criteria: {fraction_requests_pass:.4f}\"\n", " )\n", "\n", " # Final filtering and analysis\n", " subset_v4_clips_df_pass_duration = subset_v4_clips_df_test[\n", " play_duration_mask\n", " ].copy()\n", " play_duration_mask_request_mask = subset_v4_clips_df_pass_duration[\n", " \"request_id\"\n", " ].isin(\n", " subset_v4_clips_df_pass_duration[\"request_id\"]\n", " .value_counts()\n", " .index[subset_v4_clips_df_pass_duration[\"request_id\"].value_counts() == 2]\n", " )\n", " final_subset_v4_clips_df = subset_v4_clips_df_pass_duration[\n", " play_duration_mask_request_mask\n", " ].copy()\n", "\n", " unique_request_count = final_subset_v4_clips_df[\"request_id\"].nunique()\n", " print(\n", " f\"Number of unique request IDs: {unique_request_count:,}, Total {subset_v4_clips_df_test['request_id'].nunique()}\"\n", " )\n", "\n", " print(\"Start --------------------------\")\n", " print_out_value_counts_nicely(subset_v4_clips_df_test, \"task\")\n", " print(\"End --------------------------\")\n", " print_out_value_counts_nicely(final_subset_v4_clips_df, \"task\")\n", "\n", " return final_subset_v4_clips_df" ] }, { "cell_type": "code", "execution_count": 75, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(30335, 58)\n", "(29732, 58)\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ " 0%| | 0/1 [00:00" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Fraction of clips that pass the play duration cut: 0.5297\n", "Number of unique requests passing play duration criteria: 9668\n", "Fraction of unique requests that pass play duration criteria: 0.6503\n", "Number of unique request IDs: 6,082, Total 14866\n", "Start --------------------------\n", "upsample: 29732 (100.00%)\n", "End --------------------------\n", "upsample: 12164 (100.00%)\n" ] } ], "source": [ "# final_subset_s31_clips_df = analyze_clip_data_with_snowflake(\n", "# final_interesting_clips, \"chirp-v4-h-s-31\", top_users, snow_session\n", "# )\n", "# final_subset_t6_clips_df = analyze_clip_data_with_snowflake(\n", "# final_interesting_clips, \"chirp-v4-h-t-6\", top_users, snow_session\n", "# )\n", "final_subset_upsample_clips_df = analyze_clip_data_with_snowflake(\n", " final_interesting_clips, \"chirp-v4-up-u-3\", top_users, snow_session\n", ")" ] }, { "cell_type": "code", "execution_count": 76, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "15045\n", "(9450, 36)\n", "4443\n", "(8929, 58)\n", "(8929, 58)\n", "(8813, 58)\n", "(8500, 58)\n" ] } ], "source": [ "upsample_final_interesting_clips = final_interesting_clips[\n", " (final_interesting_clips[\"model_name\"] == \"chirp-v4-up-u-3\")\n", "].copy()\n", "\n", "all_upsampled_parent_ids = set(\n", " upsample_final_interesting_clips[\"metadata\"].apply(lambda x: x[\"upsample_clip_id\"])\n", ")\n", "\n", "print(len(all_upsampled_parent_ids))\n", "upsample_parent_clip_df = total_clip_df[\n", " total_clip_df[\"s3_id\"].isin(set(all_upsampled_parent_ids))\n", "].copy()\n", "print(upsample_parent_clip_df.shape)\n", "\n", "v4_mask = upsample_parent_clip_df[\"model_name\"].str.contains(\"chirp-v4-h-\")\n", "upsample_parent_clip_df[v4_mask][\"model_name\"].value_counts()\n", "potential_bad_parents = upsample_parent_clip_df[v4_mask][\"s3_id\"].unique()\n", "print(len(potential_bad_parents))\n", "\n", "subset_of_bad_parents_df = upsample_final_interesting_clips[\n", " (\n", " upsample_final_interesting_clips[\"metadata\"].apply(\n", " lambda x: x[\"upsample_clip_id\"] in set(potential_bad_parents)\n", " )\n", " )\n", "].copy()\n", "print(subset_of_bad_parents_df.shape)\n", "\n", "subset_of_bad_parents_df[\"request_id\"] += \"_bad_p\"\n", "\n", "\n", "subset_of_bad_parents_df.loc[~subset_of_bad_parents_df[\"preference\"], \"id\"] = (\n", " subset_of_bad_parents_df[\"metadata\"]\n", " .loc[~subset_of_bad_parents_df[\"preference\"]]\n", " .apply(lambda x: x[\"upsample_clip_id\"])\n", ")\n", "subset_of_bad_parents_df.loc[~subset_of_bad_parents_df[\"preference\"], \"s3_id\"] = (\n", " subset_of_bad_parents_df[\"metadata\"]\n", " .loc[~subset_of_bad_parents_df[\"preference\"]]\n", " .apply(lambda x: x[\"upsample_clip_id\"])\n", ")\n", "\n", "print(subset_of_bad_parents_df.shape)\n", "subset_of_bad_parents_df = subset_of_bad_parents_df.drop_duplicates(\n", " subset=[\"id\"], keep=\"first\"\n", ")\n", "print(subset_of_bad_parents_df.shape)\n", "pair_request_mask = subset_of_bad_parents_df[\"request_id\"].isin(\n", " subset_of_bad_parents_df[\"request_id\"]\n", " .value_counts()\n", " .index[subset_of_bad_parents_df[\"request_id\"].value_counts() == 2]\n", ")\n", "subset_of_bad_parents_df = subset_of_bad_parents_df[pair_request_mask].copy()\n", "# TODO: WHY are there non-pairs?\n", "print(subset_of_bad_parents_df.shape)" ] }, { "cell_type": "code", "execution_count": 77, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(8500, 58)\n", "(8500, 58)\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ " 0%| | 0/1 [00:00" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Fraction of clips that pass the play duration cut: 0.5674\n", "Number of unique requests passing play duration criteria: 3057\n", "Fraction of unique requests that pass play duration criteria: 0.7193\n", "Number of unique request IDs: 1,766, Total 4250\n", "Start --------------------------\n", "upsample: 8500 (100.00%)\n", "End --------------------------\n", "upsample: 3532 (100.00%)\n" ] } ], "source": [ "final_subset_upsample_clips_bad_parents_df = analyze_clip_data_with_snowflake(\n", " subset_of_bad_parents_df, \"chirp-v4-up-u-3\", top_users, snow_session\n", ")" ] }, { "cell_type": "code", "execution_count": 78, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "upsample (12164, 85)\n", "upsample (3532, 85)\n" ] } ], "source": [ "# print(\"s-31\", final_subset_s31_clips_df.shape)\n", "# print(\"t-6\", final_subset_t6_clips_df.shape)\n", "print(\"upsample\", final_subset_upsample_clips_df.shape)\n", "print(\"upsample\", final_subset_upsample_clips_bad_parents_df.shape)" ] }, { "cell_type": "code", "execution_count": 79, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "upsample (15696, 85)\n" ] } ], "source": [ "final_subset_upsample_clips_df = pd.concat(\n", " [final_subset_upsample_clips_df, final_subset_upsample_clips_bad_parents_df]\n", ")\n", "print(\"upsample\", final_subset_upsample_clips_df.shape)" ] }, { "cell_type": "code", "execution_count": 80, "metadata": {}, "outputs": [], "source": [ "# final_subset_upsample_clips_df.to_pickle(\n", "# \"/home/tony/Data/Preference/up_v3/interesting_clips_up_u_3_20241217_full.pkl\",\n", "# )\n", "# print(\"up_v3\", final_subset_upsample_clips_df.shape)\n", "#\n", "# final_subset_t6_clips_df.to_pickle(\n", "# \"/home/tony/Data/Preference/30b_v6/interesting_clips_v4_h_t_6_20241207_full.pkl\",\n", "# )\n", "# print(\"t-6\", final_subset_t6_clips_df.shape)\n", "# final_subset_s31_clips_df.to_pickle(\n", "# \"/home/tony/Data/Preference/13b_v31/interesting_clips_v4_h_s_31_20241207_full.pkl\",\n", "# )\n", "# print(\"s-31\", final_subset_s31_clips_df.shape)\n", "# print(\"Saving done!\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Task usage stats" ] }, { "cell_type": "code", "execution_count": 81, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "task\n", " 7389140\n", "extend 513926\n", "cover 417817\n", "artist_consistency 362129\n", "upload_extend 354847\n", "upsample 298149\n", "infill 98838\n", "image_to_song 10607\n", "video_to_song 2998\n", "infill_outro 6\n", "Name: count, dtype: int64" ] }, "execution_count": 81, "metadata": {}, "output_type": "execute_result" } ], "source": [ "clip_df[\"task\"].value_counts()" ] }, { "cell_type": "code", "execution_count": 82, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "cover usage: 18471 out of 99866 (0.185) \n", " -------------->\n", "chirp-v4-h-t-6: 289277 (69.24%)\n", "chirp-v3p5-engine-t-6: 120329 (28.80%)\n", "chirp-v4-h-t-6-artist-cfg: 6050 (1.45%)\n", "chirp-v4-engine-b: 1289 (0.31%)\n", "chirp-v3p5-engine-b: 872 (0.21%)\n", "\n", " --------------------------\n", "infill usage: 6235 out of 99866 (0.0624) \n", " -------------->\n", "chirp-v4-h-t-6: 72829 (73.68%)\n", "chirp-v3p5-engine-t-6: 23725 (24.00%)\n", "chirp-v4-h-t-6-artist-cfg: 1550 (1.57%)\n", "chirp-v4-engine-b: 458 (0.46%)\n", "chirp-v3p5-engine-b: 282 (0.29%)\n", "\n", " --------------------------\n", "artist usage: 17967 out of 99866 (0.1799) \n", " -------------->\n", "chirp-v4-h-t-6: 259035 (71.53%)\n", "chirp-v3p5-engine-t-6: 93116 (25.71%)\n", "chirp-v4-h-t-6-artist-cfg: 5536 (1.53%)\n", "chirp-v4-engine-b: 2796 (0.77%)\n", "chirp-v3p5-engine-b: 1646 (0.45%)\n", "\n", " --------------------------\n", "image/video usage: 3288 out of 99866 (0.0329) \n", " -------------->\n", "chirp-v3p5-engine-short: 13605 (100.00%)\n", "\n", " --------------------------\n" ] } ], "source": [ "n_pro_created = clip_df[clip_df[\"is_pro_user\"]][\"user_id\"].nunique()\n", "task_mask_cover = clip_df[\"task\"] == \"cover\"\n", "task_mask_artist = clip_df[\"task\"] == \"artist_consistency\"\n", "task_mask_infill = (\n", " (clip_df[\"task\"] == \"infill\")\n", " | (clip_df[\"task\"] == \"infill_intro\")\n", " | (clip_df[\"task\"] == \"infill_outro\")\n", ")\n", "task_mask_image = (clip_df[\"task\"] == \"image_to_song\") | (\n", " clip_df[\"task\"] == \"video_to_song\"\n", ")\n", "\n", "\n", "def print_task_usage_stats(clip_df, task_mask, task_name, n_pro_created):\n", " n_created = clip_df[task_mask][\"user_id\"].nunique()\n", " print(\n", " f\"{task_name} usage: {n_created} out of {n_pro_created} ({round(n_created / n_pro_created, 4)})\",\n", " \"\\n\",\n", " \"-------------->\",\n", " )\n", " print_out_value_counts_nicely(clip_df[task_mask], \"model_name\")\n", " print(\"\\n\", \"--------------------------\")\n", "\n", "\n", "print_task_usage_stats(clip_df, task_mask_cover, \"cover\", n_pro_created)\n", "print_task_usage_stats(clip_df, task_mask_infill, \"infill\", n_pro_created)\n", "print_task_usage_stats(clip_df, task_mask_artist, \"artist\", n_pro_created)\n", "print_task_usage_stats(clip_df, task_mask_image, \"image/video\", n_pro_created)" ] }, { "cell_type": "code", "execution_count": 83, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "user_id\n", "64269340 123\n", "64319216 111\n", "64362914 93\n", "22025508 69\n", "5702748 58\n", "Name: count, dtype: int64" ] }, "execution_count": 83, "metadata": {}, "output_type": "execute_result" } ], "source": [ "clip_df[task_mask_image][\"user_id\"].value_counts().head(n=5)" ] }, { "cell_type": "code", "execution_count": 84, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "user_id\n", "4505328 1128\n", "6160051 846\n", "38116848 726\n", "12245548 710\n", "16524515 704\n", "Name: count, dtype: int64" ] }, "execution_count": 84, "metadata": {}, "output_type": "execute_result" } ], "source": [ "clip_df[task_mask_cover][\"user_id\"].value_counts().head(n=5)" ] }, { "cell_type": "code", "execution_count": 85, "metadata": {}, "outputs": [], "source": [ "# v4_clip_ids = list(str(s) for s in clip_df[\"s3_id\"].unique())\n", "# snow_batch_size = 100_000\n", "# snow_results = []\n", "\n", "# for clip_ids_chunk in tqdm.tqdm(\n", "# [\n", "# v4_clip_ids[i : i + snow_batch_size]\n", "# for i in range(0, len(v4_clip_ids), snow_batch_size)\n", "# ]\n", "# ):\n", "# id_query_str = \",\".join(\"'\" + x + \"'\" for x in clip_ids_chunk)\n", "# print(f\"Number of clip IDs in this chunk: {len(clip_ids_chunk)}\")\n", "# print(f\"Length of the ID query string: {len(id_query_str)}\")\n", "\n", "# session_query = snow_session.sql(\n", "# f\"\"\" select *\n", "# from ML_SONG_SUMMARY_INFO\n", "# where p_date = DATE(SYSDATE() - INTERVAL '2 HOUR')\n", "# and p_hour = hour(SYSDATE() - INTERVAL '2 HOUR')\n", "# and song_id in ({id_query_str})\n", "# order by p_hour desc;\"\"\"\n", "# )\n", "# temp_df_snow_test = pd.DataFrame(session_query.collect())\n", "# snow_results.append(temp_df_snow_test)\n", "# print(len(snow_results))\n", "\n", "# # Process Snowflake results\n", "# df_snow_test = pd.concat(snow_results)\n", "# df_snow_test = df_snow_test.rename(columns=lambda x: x.lower())\n", "# df_snow_test = df_snow_test.rename(columns={\"song_id\": \"str_id\"})\n", "# print(\"Shape of df_snow_test:\")\n", "# print(f\"Rows: {df_snow_test.shape[0]}\")\n", "# print(f\"Columns: {df_snow_test.shape[1]}\")\n", "# df_snow_test[\"clip_id\"] = df_snow_test[\"str_id\"]\n", "# run_bot_detection(\n", "# clip_df,\n", "# df_snow_test[df_snow_test[\"total_play_time\"] >= 5],\n", "# write_to_file=True,\n", "# cut_off_freq=0.95,\n", "# min_generations_for_no_reaction=10,\n", "# )" ] }, { "cell_type": "code", "execution_count": 86, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Shape of no_reaction_clip_df:\n", "(2085876, 37)\n", "\n", "Proportion of clips without reactions:\n", "21.17%\n", "Ratio of clips without reactions to total clips from the same users:\n", "0.5583\n" ] }, { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "free 21796\n", "pro 2045\n", "Ratio of clips from super bad users: 2.78%\n", "DONE\n" ] } ], "source": [ "total_clip_df[\"is_pro_user\"] = total_clip_df[\"user_id\"].isin(pro_users)\n", "run_bot_detection(\n", " total_clip_df,\n", " reaction_df,\n", " write_to_file=True,\n", " cut_off_freq=0.95,\n", " min_generations_for_no_reaction=10,\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Infill test" ] }, { "cell_type": "code", "execution_count": 87, "metadata": {}, "outputs": [], "source": [ "# def get_infill_type(x):\n", "# if max(x[\"infll_start_context\"], x[\"infll_end_context\"]) <= 30:\n", "# return \"short\"\n", "# elif max(x[\"infll_start_context\"], x[\"infll_end_context\"]) <= 60:\n", "# return \"mid\"\n", "# else:\n", "# return \"long\"" ] }, { "cell_type": "code", "execution_count": 88, "metadata": {}, "outputs": [], "source": [ "# clip_df_infill_task_mask_infill = (\n", "# (clip_df[\"task\"] == \"infill\")\n", "# | (clip_df[\"task\"] == \"infill_intro\")\n", "# | (clip_df[\"task\"] == \"infill_outro\")\n", "# ) & (clip_df[\"created_at\"] >= \"2024-11-06 02:00:00\")\n", "# clip_infill_df = clip_df[clip_df_infill_task_mask_infill].copy()\n", "# ##\n", "# user_intersting_clips_3p5_task_mask_infill = (\n", "# (user_intersting_clips_3p5[\"task\"] == \"infill\")\n", "# | (user_intersting_clips_3p5[\"task\"] == \"infill_intro\")\n", "# | (user_intersting_clips_3p5[\"task\"] == \"infill_outro\")\n", "# ) & (user_intersting_clips_3p5[\"created_at\"] >= \"2024-11-06 02:00:00\")\n", "# user_intersting_clips_3p5_infill = user_intersting_clips_3p5[\n", "# user_intersting_clips_3p5_task_mask_infill\n", "# ].copy()" ] }, { "cell_type": "code", "execution_count": 89, "metadata": {}, "outputs": [], "source": [ "# test_slice_series = clip_infill_df[\"metadata\"].apply(pd.Series)\n", "# df = pd.concat([clip_infill_df, test_slice_series], axis=1, join=\"inner\")\n", "# print(df.shape)\n", "# df = df.loc[:, ~df.columns.duplicated()].copy()\n", "# df[\"infll_start_context\"] = df[\"infill_start_s\"] - df[\"infill_context_start_s\"]\n", "# df[\"infll_end_context\"] = df[\"infill_context_end_s\"] - df[\"infill_end_s\"]\n", "# df[\"infill_type\"] = df[[\"infll_start_context\", \"infll_end_context\"]].apply(\n", "# lambda x: get_infill_type(x), axis=1\n", "# )\n", "# clip_df_model_counts = df[\"infill_type\"].value_counts()\n", "# print(clip_df_model_counts)" ] }, { "cell_type": "code", "execution_count": 90, "metadata": {}, "outputs": [], "source": [ "# plt.hist(df[\"infill_context_start_s\"], bins=np.linspace(-10, 300, 100))\n", "# plt.show()" ] }, { "cell_type": "code", "execution_count": 91, "metadata": {}, "outputs": [], "source": [ "# test_slice_series = user_intersting_clips_3p5_infill[\"metadata\"].apply(pd.Series)\n", "# df = pd.concat([user_intersting_clips_3p5_infill, test_slice_series], axis=1, join=\"inner\")\n", "# print(df.shape)\n", "# df = df.loc[:, ~df.columns.duplicated()].copy()\n", "# df[\"infll_start_context\"] = df[\"infill_start_s\"] - df[\"infill_context_start_s\"]\n", "# df[\"infll_end_context\"] = df[\"infill_context_end_s\"] - df[\"infill_end_s\"]\n", "# df[\"infill_type\"] = df[[\"infll_start_context\", \"infll_end_context\"]].apply(lambda x: get_infill_type(x), axis=1)" ] }, { "cell_type": "code", "execution_count": 92, "metadata": {}, "outputs": [], "source": [ "# plt.hist(df[\"infill_context_start_s\"], bins=np.linspace(-10, 300, 100))\n", "# plt.show()\n", "# plt.hist(df[\"infill_context_end_s\"], bins=np.linspace(-10, 300, 100))\n", "# plt.show()" ] }, { "cell_type": "code", "execution_count": 93, "metadata": {}, "outputs": [], "source": [ "# model_counts = df[df[\"part_of_concat\"]][\"infill_type\"].value_counts()\n", "\n", "# # Print the results in a nicely formatted way\n", "# total_count = model_counts.sum()\n", "# print(\"Model Name Value Counts for Preferred Clips:\")\n", "# print(\"-\" * 70)\n", "# print(f\"{'Model':<30} {'Count':>10} {'Fraction':>15}\")\n", "# print(\"-\" * 70)\n", "# for model, count in model_counts.items():\n", "# fraction = count / total_count\n", "# print(f\"{model:<30} {count:>10,d} {fraction:>15.2%}\")\n", "# print(\"-\" * 70)\n", "# print(f\"{'Total':<30} {total_count:>10,d} {1:>15.2%}\")\n", "\n", "# # Calculate the ratio of preferred clips to total clips for each model\n", "# preference_ratio = (\n", "# df[df[\"part_of_concat\"]][\"infill_type\"].value_counts() / clip_df_model_counts\n", "# )\n", "\n", "\n", "# # Print the results in a formatted manner\n", "# print(\"\\n Ratio of preferred clips to total clips for each model:\")\n", "# print(\"-\" * 60)\n", "# for model, ratio in preference_ratio.items():\n", "# n = clip_df_model_counts[model]\n", "# uncertainty = (ratio * (1 - ratio) / n) ** 0.5\n", "# print(f\"{model:<30} {ratio:.2%} ± {uncertainty:.2%}\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Playlists" ] }, { "cell_type": "code", "execution_count": 94, "metadata": {}, "outputs": [], "source": [ "from snowflake.snowpark.functions import col as snow_col\n", "\n", "playlist_df = (\n", " snow_session.table(\"rds_playlist\")\n", " .select(\"*\")\n", " .filter((snow_col(\"updated_at\") >= cutoff_date))\n", " .collect_nowait()\n", " .result(result_type=\"pandas\")\n", " .rename(columns=lambda x: x.lower())\n", ")" ] }, { "cell_type": "code", "execution_count": 95, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.6862292051756007" ] }, "execution_count": 95, "metadata": {}, "output_type": "execute_result" } ], "source": [ "playlist_df[\"user_id\"].nunique() / playlist_df.shape[0]" ] }, { "cell_type": "code", "execution_count": 96, "metadata": {}, "outputs": [], "source": [ "playlist_id_to_user_id = playlist_df.set_index(\"id\")[\"user_id\"].to_dict()" ] }, { "cell_type": "code", "execution_count": 97, "metadata": {}, "outputs": [], "source": [ "playlist_clip_df[\"user_id\"] = playlist_clip_df[\"playlist_id\"].apply(\n", " lambda x: playlist_id_to_user_id.get(x)\n", ")" ] }, { "cell_type": "code", "execution_count": 98, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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113484 rows × 10 columns

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" ], "text/plain": [ " id relative_index updated_at clip_id playlist_id updated_by_id p_date p_hour created_session_id user_id\n", "3 54104017 10 2024-12-17 12:52:34.226338+00:00 89fa743b-f4d1-49f1-902b-1584a921479c f453c867-d664-4047-bb66-d8cad11b5b70 NaN 2024-06-23 17 None None\n", "4 54101014 4 2024-12-18 12:38:31.927361+00:00 f23c42fe-7d5f-4bf1-b91d-e042e94a8143 d11064da-fc49-4ba0-838d-24ad068f525d NaN 2024-06-23 17 None None\n", "6 54113246 9 2024-12-17 19:26:01.374011+00:00 4755e697-59fa-4949-86ec-7bdd25f83ac5 6b20b417-db03-4bda-a9a5-f492709d313d NaN 2024-06-23 18 None None\n", "7 54110092 14 2024-12-17 19:26:01.411760+00:00 47cc274f-fd80-48af-a698-7f11d50e15cd 6b20b417-db03-4bda-a9a5-f492709d313d NaN 2024-06-23 18 None None\n", "8 54120659 6 2024-12-17 12:52:34.211731+00:00 cd97ea43-131f-4e6d-9491-28c9f059a5d4 f453c867-d664-4047-bb66-d8cad11b5b70 NaN 2024-06-23 19 None None\n", "... ... ... ... ... ... ... ... ... ... ...\n", "284804 39953019 10 2024-12-18 12:50:36.002892+00:00 83b38954-8803-48ae-b5cb-d771915c4118 e96b1dfc-73fe-4cea-b163-5d01073d2f4e NaN 2024-04-08 8 None None\n", "284805 39953039 8 2024-12-18 12:50:35.988504+00:00 1449a85b-085f-45cd-8fe5-2a5a14178484 e96b1dfc-73fe-4cea-b163-5d01073d2f4e NaN 2024-04-08 8 None None\n", "284806 39952913 7 2024-12-18 12:50:35.981713+00:00 f38e84eb-3ad2-425a-b406-ca5f4b3d2046 e96b1dfc-73fe-4cea-b163-5d01073d2f4e NaN 2024-04-08 8 None None\n", "284807 39956646 46 2024-12-17 23:32:37.158673+00:00 672c2999-cbe5-4799-bc12-0ff23b648f59 b9c8f588-07da-4514-9dd3-984d18316ff3 NaN 2024-04-08 9 None None\n", "284808 39960833 1 2024-12-18 12:50:35.927702+00:00 062edc84-b8dd-4157-bb83-de16d3c03bbc e96b1dfc-73fe-4cea-b163-5d01073d2f4e NaN 2024-04-08 10 None None\n", "\n", "[113484 rows x 10 columns]" ] }, "execution_count": 98, "metadata": {}, "output_type": "execute_result" } ], "source": [ "playlist_clip_df[playlist_clip_df[\"user_id\"].isna()]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Other ppl's clip in playlists" ] }, { "cell_type": "code", "execution_count": 99, "metadata": {}, "outputs": [], "source": [ "unique_clips_in_playlist = playlist_clip_df[\"clip_id\"].unique()" ] }, { "cell_type": "code", "execution_count": 100, "metadata": {}, "outputs": [], "source": [ "total_clip_id_to_user_id = (\n", " total_clip_df[total_clip_df[\"id\"].isin(unique_clips_in_playlist)]\n", " .set_index(\"s3_id\")[\"user_id\"]\n", " .to_dict()\n", ")" ] }, { "cell_type": "code", "execution_count": 101, "metadata": {}, "outputs": [], "source": [ "playlist_clip_df[\"clip_user_id\"] = playlist_clip_df[\"clip_id\"].apply(\n", " lambda x: total_clip_id_to_user_id.get(x)\n", ")" ] }, { "cell_type": "code", "execution_count": 102, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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284809 rows × 11 columns

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" ], "text/plain": [ " id relative_index updated_at clip_id playlist_id updated_by_id p_date p_hour created_session_id user_id clip_user_id\n", "0 54087536 25 2024-12-17 14:40:27.324143+00:00 11b99b0d-b84b-4458-b8ce-13017c454c5a b689e294-1c24-45b2-a56b-f361eb938cf5 NaN 2024-06-23 15 None 20374131 NaN\n", "1 54088953 20 2024-12-17 18:31:21.198011+00:00 ef3beec2-bc72-4e1d-bcb4-fd799ea39700 3fb5a697-17c8-48bb-bae5-ca4725fb11db NaN 2024-06-23 15 None 7262491 NaN\n", "2 54108718 125 2024-12-16 23:31:30.736112+00:00 679afd48-b64e-4742-a488-9cf03bf50a29 14abcbff-f2aa-4671-a0df-2839cba4626e NaN 2024-06-23 17 None 577400 NaN\n", "3 54104017 10 2024-12-17 12:52:34.226338+00:00 89fa743b-f4d1-49f1-902b-1584a921479c f453c867-d664-4047-bb66-d8cad11b5b70 NaN 2024-06-23 17 None None NaN\n", "4 54101014 4 2024-12-18 12:38:31.927361+00:00 f23c42fe-7d5f-4bf1-b91d-e042e94a8143 d11064da-fc49-4ba0-838d-24ad068f525d NaN 2024-06-23 17 None None NaN\n", "... ... ... ... ... ... ... ... ... ... ... ...\n", "284804 39953019 10 2024-12-18 12:50:36.002892+00:00 83b38954-8803-48ae-b5cb-d771915c4118 e96b1dfc-73fe-4cea-b163-5d01073d2f4e NaN 2024-04-08 8 None None NaN\n", "284805 39953039 8 2024-12-18 12:50:35.988504+00:00 1449a85b-085f-45cd-8fe5-2a5a14178484 e96b1dfc-73fe-4cea-b163-5d01073d2f4e NaN 2024-04-08 8 None None NaN\n", "284806 39952913 7 2024-12-18 12:50:35.981713+00:00 f38e84eb-3ad2-425a-b406-ca5f4b3d2046 e96b1dfc-73fe-4cea-b163-5d01073d2f4e NaN 2024-04-08 8 None None NaN\n", "284807 39956646 46 2024-12-17 23:32:37.158673+00:00 672c2999-cbe5-4799-bc12-0ff23b648f59 b9c8f588-07da-4514-9dd3-984d18316ff3 NaN 2024-04-08 9 None None NaN\n", "284808 39960833 1 2024-12-18 12:50:35.927702+00:00 062edc84-b8dd-4157-bb83-de16d3c03bbc e96b1dfc-73fe-4cea-b163-5d01073d2f4e NaN 2024-04-08 10 None None NaN\n", "\n", "[284809 rows x 11 columns]" ] }, "execution_count": 102, "metadata": {}, "output_type": "execute_result" } ], "source": [ "playlist_clip_df" ] }, { "cell_type": "code", "execution_count": 103, "metadata": {}, "outputs": [], "source": [ "# v4_users = clip_df[clip_df[\"model_name\"].str.contains(\"v4\")][\"user_id\"].unique()" ] }, { "cell_type": "code", "execution_count": 104, "metadata": {}, "outputs": [], "source": [ "# discord_info_df[discord_info_df[\"user_id\"].isin(v4_users)][[\"user_id\", \"subscription_status\", \"extra_credits_balance\", \"display_name\", \"handle\"]]" ] }, { "cell_type": "code", "execution_count": 105, "metadata": {}, "outputs": [], "source": [ "# bad_ids_dict = run_bot_detection(\n", "# total_clip_df,\n", "# reaction_df,\n", "# write_to_file=False,\n", "# cut_off_freq=0.5,\n", "# min_generations_for_no_reaction=10,\n", "# return_bad_user_ids=True\n", "# )" ] }, { "cell_type": "code", "execution_count": 106, "metadata": {}, "outputs": [], "source": [ "# print(len(bad_ids_dict[\"bad_pro_user_ids\"]))\n", "# print(len(pro_users))\n", "# good_pro_users = set(pro_users).difference(bad_ids_dict[\"bad_pro_user_ids\"])\n", "# print(len(good_pro_users))\n", "# with open(\"/home/tony/Work/good_pro_user_2024_11_22.json\", \"w\") as fp:\n", "# json.dump([int(x) for x in sorted(good_pro_users)], fp)" ] }, { "cell_type": "code", "execution_count": 107, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Shape of no_reaction_clip_df:\n", "(2085876, 37)\n", "\n", "Proportion of clips without reactions:\n", "21.17%\n", "Ratio of clips without reactions to total clips from the same users:\n", "0.6374\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "free 1452\n", "pro 1589\n", "Ratio of clips from super bad users: 0.43%\n", "DONE\n" ] } ], "source": [ "run_bot_detection(\n", " total_clip_df,\n", " reaction_df,\n", " write_to_file=False,\n", " cut_off_freq=0.95,\n", " min_generations_for_no_reaction=20,\n", ")" ] }, { "cell_type": "code", "execution_count": 108, "metadata": { "scrolled": true }, "outputs": [], "source": [ "upsample_slice_cycle_mask = upsample_slice_df[\"model_name\"].isin(\n", " [\"chirp-v4-up-u-1-c-3\", \"chirp-v4-up-u-1-c-1\"]\n", ")\n", "upsample_slice_cycle_requests = upsample_slice_df[upsample_slice_cycle_mask][\n", " \"request_id\"\n", "].unique()\n", "upsample_slice_cycle = upsample_slice_df[\n", " upsample_slice_df[\"request_id\"].isin(upsample_slice_cycle_requests)\n", "].copy()\n", "# get_preference_counts(upsample_slice_cycle)\n", "# upsample_slice_cycle.to_pickle(\"/home/tony/Data/Preference/up_v1/interesting_clips_up_cycle_debug.pkl\")" ] }, { "cell_type": "code", "execution_count": 109, "metadata": {}, "outputs": [ { "ename": "AssertionError", "evalue": "", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mAssertionError\u001b[0m Traceback (most recent call last)", "Cell \u001b[0;32mIn[109], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mget_preference_counts\u001b[49m\u001b[43m(\u001b[49m\u001b[43mupsample_slice_cycle\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[0;32m~/Work/glockenspiel/suno_analytics/suno_analytics/preference_helper.py:39\u001b[0m, in \u001b[0;36mget_preference_counts\u001b[0;34m(input_df, title_name)\u001b[0m\n\u001b[1;32m 37\u001b[0m preferences \u001b[38;5;241m=\u001b[39m input_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpreference\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mvalues\n\u001b[1;32m 38\u001b[0m neg_prefs, pos_prefs \u001b[38;5;241m=\u001b[39m preferences[::\u001b[38;5;241m2\u001b[39m], preferences[\u001b[38;5;241m1\u001b[39m::\u001b[38;5;241m2\u001b[39m]\n\u001b[0;32m---> 39\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28mset\u001b[39m(neg_prefs) \u001b[38;5;241m==\u001b[39m {\u001b[38;5;28;01mFalse\u001b[39;00m}\n\u001b[1;32m 40\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28mset\u001b[39m(pos_prefs) \u001b[38;5;241m==\u001b[39m {\u001b[38;5;28;01mTrue\u001b[39;00m}\n\u001b[1;32m 41\u001b[0m paired_models \u001b[38;5;241m=\u001b[39m input_df[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmodel_name\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mvalues\n", "\u001b[0;31mAssertionError\u001b[0m: " ] } ], "source": [ "get_preference_counts(upsample_slice_cycle)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "upsample_slice_cycle_1_mask = upsample_slice_cycle[\"model_name\"].isin(\n", " [\"chirp-v4-up-u-1-c-1\"]\n", ")\n", "upsample_slice_cycle_1_users = upsample_slice_cycle[upsample_slice_cycle_1_mask][\n", " \"user_id\"\n", "].unique()\n", "upsample_slice_cycle_2_mask = upsample_slice_cycle[\"model_name\"].isin(\n", " [\"chirp-v4-up-u-1-c-2\"]\n", ")\n", "upsample_slice_cycle_2_users = upsample_slice_cycle[upsample_slice_cycle_2_mask][\n", " \"user_id\"\n", "].unique()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "print(len(upsample_slice_cycle_1_users), len(upsample_slice_cycle_2_users))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "intersection_users = set(upsample_slice_cycle_1_users).intersection(\n", " set(upsample_slice_cycle_2_users)\n", ")\n", "print(len(intersection_users))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "user_intersting_clips[user_intersting_clips[\"user_id\"] == 176212]" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "final_subset_s31_clips_df_tony = analyze_clip_data_with_snowflake(\n", " user_intersting_clips[user_intersting_clips[\"user_id\"] == 176212],\n", " \"chirp-v4-h-t-6\",\n", " top_users,\n", " snow_session,\n", ")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "query = f\"\"\"\n", "SELECT *\n", "FROM auth_user\n", "WHERE date_joined>='2024-12-10' \n", "\"\"\"\n", "# 3 keenan\n", "# 6 martin\n", "# 8 tony -- that's me!\n", "# 186417 georg\n", "test_user_df = pd.read_sql_query(query, engine)\n", "test_user_df.shape" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "test_user_df[\"start_date\"] = pd.to_datetime(test_user_df[\"date_joined\"])" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "test_user_df[\"start_date\"].dt.date.value_counts()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# low_freq_hrs_mask = user_intersting_clips_3p5[\"created_at\"].dt.hour < 8" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.15" }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": {}, "toc_section_display": true, "toc_window_display": false } }, "nbformat": 4, "nbformat_minor": 4 }