{ "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": "2024-08-26T07:38:49.486836Z", "iopub.status.busy": "2024-08-26T07:38:49.486692Z", "iopub.status.idle": "2024-08-26T07:38:49.639393Z", "shell.execute_reply": "2024-08-26T07:38:49.638952Z", "shell.execute_reply.started": "2024-08-26T07:38:49.486822Z" } }, "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": "2024-08-26T07:38:49.640281Z", "iopub.status.busy": "2024-08-26T07:38:49.640026Z", "iopub.status.idle": "2024-08-26T07:38:52.936491Z", "shell.execute_reply": "2024-08-26T07:38:52.935954Z", "shell.execute_reply.started": "2024-08-26T07:38:49.640267Z" } }, "outputs": [], "source": [ "# pip install psycopg2-binary\n", "# make sure sqlalchemy is >=2\n", "import ast\n", "import json\n", "from collections import Counter, defaultdict\n", "from datetime import datetime\n", "from urllib.parse import quote\n", "\n", "import boto3\n", "import matplotlib.dates as mdates\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import pandas as pd\n", "import seaborn as sns\n", "import sqlalchemy\n", "import tqdm\n", "from botocore.exceptions import ClientError\n", "from preference_data_selection import (\n", " gather_data,\n", " get_concat_clip_ids,\n", " merge_concat_clips_with_reactions,\n", " parse_metadata_for_basics,\n", " plot_clip_basic_distributions,\n", " plot_clip_distribution,\n", " print_out_value_counts_nicely,\n", " run_bot_detection,\n", " validate_preference_data,\n", ")\n", "from preference_helper import get_preferfence_counts\n", "from suno_utils.audio import Audio\n", "from suno_utils.utils.s3 import open_from_s3\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 = \"rds!cluster-a3b66c33-40a7-47dd-bd6e-32b1c17c9124\"\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", "# engine = sqlalchemy.create_engine(\"postgresql://tony:123@localhost/mydatabase\")\n", "# alternative...\n", "engine = sqlalchemy.create_engine(\n", " \"postgresql://postgres:%s@suno-main-pgdb-prod-analytics.cnfvffydbwvc.us-east-2.rds.amazonaws.com/suno_main\"\n", " % quote(my_secrets[\"password\"])\n", ")\n", "\n", "# !pip install snowflake\n", "from snowflake.core import Root\n", "from snowflake.snowpark import Session\n", "\n", "snow_password_path = \"/home/tony/.aws/snow_pw.txt\"\n", "with open(snow_password_path, \"r\") as fp:\n", " snow_password = fp.readlines()[0].strip()\n", "\n", "CONNECTION_PARAMETERS = {\n", " \"account\": \"fu90569.us-east-2.aws\",\n", " \"user\": \"TONY\",\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": "2024-08-26T07:38:52.937453Z", "iopub.status.busy": "2024-08-26T07:38:52.937207Z", "iopub.status.idle": "2024-08-26T07:38:52.955394Z", "shell.execute_reply": "2024-08-26T07:38:52.954956Z", "shell.execute_reply.started": "2024-08-26T07:38:52.937438Z" } }, "outputs": [], "source": [ "# cutoff_date = \"2024-05-24 05:14:04\" # v3.5 early\n", "# cutoff_date = \"2024-05-30 02:03:11\" # v3.5 - 6\n", "# cutoff_date = \"2024-06-02 01:55:17\"\n", "# cutoff_date = \"2024-06-04 13:21:36\"\n", "# cutoff_date = \"2024-06-12 13:00:00\" # v3.5 extend\n", "# cutoff_date = \"2024-06-18 00:00:00\" # user feedback out\n", "# cutoff_date = \"2024-06-24 16:34:00\" # current time\n", "# 2 cutoff_date = \"2024-06-26 03:50:00\" # s-11 out\n", "# cutoff_date = \"2024-06-27 03:50:00\" # s-8 out\n", "# cutoff_date = \"2024-06-27 03:50:00\" # s-12 out\n", "# cutoff_date = \" 2024-06-29 03:00:00\" # s-13 end\n", "# cutoff_date = \"2024-07-01 05:00:00\" # s-14 out\n", "# cutoff_date = \"2024-07-05 03:10:00\" # s-14 out\n", "# cutoff_date = \"2024-07-10 04:10:00\" # ft-1 out\n", "# cutoff_date = \"2024-07-10 14:45:00\" # no-top-p out\n", "# cutoff_date = \"2024-07-10 19:35:00\" # 2h ft end ~ 4hr difference\n", "# cutoff_date = \"2024-07-11 23:35:00\" # v4 first test\n", "# cutoff_date = \"2024-07-13 04:30:00\" # s-18/19 out\n", "# cutoff_date = \"2024-07-14 04:45:00\" # ft-2 out\n", "# cutoff_date = \"2024-07-15 12:45:00\" # test\n", "# cutoff_date = \"2024-07-16 00:00:00\" # v4 collection out\n", "# cutoff_date = \"2024-07-28 00:33:00\" # v4-t1-5 test\n", "# cutoff_date = \"2024-07-30 02:00:00\" # v4-t1-7 test\n", "# cutoff_date = \"2024-07-31 00:30:00\" # v4-t1-fast-sem test\n", "# cutoff_date = \"2024-07-31 00:30:00\" # v4-t1-fast-sem test\n", "# cutoff_date = \"2024-07-31 19:41:00\" # paged attn test -- ab test worked but worker failure is there\n", "# cutoff_date = \"2024-08-01 04:00:00\" # s-20 out\n", "# cutoff_date = \"2024-08-02 05:29:00\" # v4-t1-10 test\n", "# cutoff_date = \"2024-08-02 16:00:00\" # s-21 out\n", "# cutoff_date = \"2024-08-03 22:30:00\" # v4-t1-11 test\n", "# cutoff_date = \"2024-08-04 21:30:00\" # v4-t1-12 test\n", "# cutoff_date = \"2024-08-05 23:20:00\" # v4-t1-12-1 test\n", "# cutoff_date = \"2024-08-06 23:20:00\" # v4-t1-14 test\n", "# cutoff_date = \"2024-08-07 04:00:00\" # v4-t1-15 test\n", "# cutoff_date = \"2024-08-07 21:00:00\" # v4-t1 t1-12 test\n", "# cutoff_date = \"2024-08-09 00:00:00\" # v4-t1 t12-17-18 test\n", "# cutoff_date = \"2024-08-09 13:00:00\" # v4-t1 t12-17-18-sft test\n", "# cutoff_date = \"2024-08-09 19:00:00\" # v4-t1 t19 test\n", "# cutoff_date = \"2024-08-09 21:00:00\" # v4-t2 out\n", "# cutoff_date = \"2024-08-11 18:00:00\" # v4-t2-s8-v2 out\n", "# cutoff_date = \"2024-08-13 04:00:00\" # s-23 out\n", "# cutoff_date = \"2024-08-14 21:00:00\" # v4-t1-19 test out\n", "# cutoff_date = \"2024-08-15 22:00:00\" # v4-t2-s8-v5 test out\n", "# cutoff_date = \"2024-08-16 6:00:00\" # v4-t2-v2 test out\n", "# cutoff_date = \"2024-08-16 6:00:00\" # v4-t2-v2 test out\n", "# cutoff_date = \"2024-08-17 03:30:00\" # v4-t2-v3 test out\n", "# cutoff_date = \"2024-08-18 00:20:00\" # v4-t2-v3-cfg test out\n", "# cutoff_date = \"2024-08-18 06:15:00\" # v4-t2-s8-v5-s test out\n", "# cutoff_date = \"2024-08-18 23:00:00\" # v4 t2 cfg exp param test out\n", "# cutoff_date = \"2024-08-20 01:50:00\" # v4 t2 r\n", "# cutoff_date = \"2024-08-20 04:00:00\" # v4 t2 rr\n", "# cutoff_date = \"2024-08-20 21:00:00\" # v4 t2 v7\n", "# cutoff_date = \"2024-08-21 15:20:00\" # v4 t2 v7\n", "cutoff_date = \"2024-08-24 18:30:00\" # v4-t2-12 out\n", "\n", "\n", "target_model_name = \"chirp-v3p5-engine-t-2\"" ] }, { "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": "2024-08-26T07:38:52.956127Z", "iopub.status.busy": "2024-08-26T07:38:52.955981Z", "iopub.status.idle": "2024-08-26T07:38:53.234468Z", "shell.execute_reply": "2024-08-26T07:38:53.234020Z", "shell.execute_reply.started": "2024-08-26T07:38:52.956114Z" } }, "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": "2024-08-26T07:38:53.235220Z", "iopub.status.busy": "2024-08-26T07:38:53.235077Z", "iopub.status.idle": "2024-08-26T08:40:56.664603Z", "shell.execute_reply": "2024-08-26T08:40:56.664006Z", "shell.execute_reply.started": "2024-08-26T07:38:53.235207Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Start gather data from 2024-08-24 18:30:00\n", "Bots Action: 6,611,121 rows\n", " ---- Execution time: 98.73 seconds\n", "Reactions: 7,683,991 rows\n", " ---- Execution time: 87.47 seconds\n", "Total Clips: 6,852,854 rows\n", " ---- Execution time: 3526.30 seconds\n", "Playlist Clips: 84,154 rows\n", " ---- Execution time: 1.28 seconds\n", "Authenticated Users: 373,378 rows\n", " ---- Execution time: 0.91 seconds\n", "Discord Info: 299,930 rows\n", "subscription_status\n", "active 283788\n", "past_due 16142\n", "Name: count, dtype: int64\n", " ---- Execution time: 8.73 seconds\n" ] } ], "source": [ "gathered_data = gather_data(engine, cutoff_date) # target_model_name)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "execution": { "iopub.execute_input": "2024-08-26T08:40:56.666402Z", "iopub.status.busy": "2024-08-26T08:40:56.666227Z", "iopub.status.idle": "2024-08-26T08:40:57.018896Z", "shell.execute_reply": "2024-08-26T08:40:57.018448Z", "shell.execute_reply.started": "2024-08-26T08:40:56.666386Z" } }, "outputs": [], "source": [ "# unpack the information\n", "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", "auth_user_df = gathered_data[\"auth_user_df\"]\n", "discord_info_df = gathered_data[\"discord_info_df\"]" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "execution": { "iopub.execute_input": "2024-08-26T08:40:57.021989Z", "iopub.status.busy": "2024-08-26T08:40:57.021863Z", "iopub.status.idle": "2024-08-26T08:41:01.348640Z", "shell.execute_reply": "2024-08-26T08:41:01.348117Z", "shell.execute_reply.started": "2024-08-26T08:40:57.021975Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "total clips: 6852854\n", "total uploads: 227686 (62942, 26)\n" ] }, { "data": { "image/png": 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/+MOsssoqOe2001JeXr7I9vfeey+33HJLkmTQoEFJUv34c6NHj66xPfnPe//888/X2O/uu+/+0quhl0SbNm0W+2fki0ufJP9ZmuUb3/hGjT93Re66665UVVVVP77jjjsyb9686u/dNttsk7Zt2+baa6+tsd/nKisrl+bLWCalfg8AABoyS7sAAKwEHn/88bz99tuZP39+ysvL88wzz+Spp57K2muvnauvvrpw2YUrr7wyzz//fAYNGpR11lknFRUVuf3227PWWmtl8803T5J84xvfyGqrrZY777wzq666alZZZZVsuumm1VfbLq327dvngAMOyN57752KiorccsstWXfddbPvvvtW7zNkyJD84Q9/yA9/+MPssssuee+99/Lggw8uskzN0sy2/fbbp1+/fvnVr36V999/P927d89TTz2VP//5zznkkEMKl8BZGvvtt1/uuuuuDB8+PK+88krWWWed/OEPf8jf/va3nHLKKYusi72khg8fnsmTJ+ecc87JH//4x2y33XZZbbXV8q9//SsPP/xw3n777ey2225LfdwleT8W5xvf+EYuvPDC/OQnP8muu+6aPffcM926dcvcuXMzceLEPPzww9U3oe3Ro0f22muv3HXXXZk+fXq23HLL/OMf/8jYsWOzww47ZKuttqo+7pAhQ3LGGWfkRz/6UQYMGJDXXnstTz75ZFZfffWl/to+t8kmm+SOO+7IVVddlXXXXTcdOnRI//79s9tuu+Vb3/pWNtlkk3zta1/LP/7xj/zhD3/IQQcdtETHraqqyqGHHppddtkl77zzTm6//fZsvvnmGTx4cJL/LIEzYsSInHTSSdl7772z6667pkOHDpk6dWr++te/pm/fvjn99NNr/XUtjVK/BwAADZmQDgCwErjsssuSJC1atMjXvva1dOvWLaecckr23nvvr4y222+/fd5///3ce++9+fjjj7P66qvnW9/6Vn70ox+lXbt21cc977zzcvHFF2fEiBGZN29eRo0aVeuQftRRR2XSpEm57rrr8tlnn6V///4544wzqq8uT/5zJe/w4cMzevTojBw5Mj179sw111yTX/7ylzWOtTSzNW3aNFdffXUuu+yyjBs3Lvfdd1/WWWednHTSSfnBD35Qq69lcVq3bp1bb701F154YcaOHZsZM2Zk/fXXz6hRo6rDcm20adMm119/fe67777cf//9ueqqqzJ79uysscYa6devXy688MKsueaaS33cJXk/vszgwYPzwAMP5MYbb8yf//zn3HHHHWnZsmW6d++e4cOH14jx55xzTjp37pyxY8fmkUceSceOHXPkkUfmuOOOq3HMfffdN1OmTMk999yTJ554IptvvnlGjx6dQw89dKm/ts8de+yxmTp1am644YZ89tln+da3vpX+/ftn6NCh+ctf/pKnnnoqc+fOzdprr50f//jHGTZs2BId9/TTT8+DDz6Yyy67LFVVVdltt91y2mmn1VhKZo899sgaa6yR6667LjfeeGPmzp2bNddcM1tsscUy/XmojVK+BwAADVmThaW4ExIAANDgPfPMMzn44INz6aWXZueddy71OCuU++67LyeffHLuueee9OrVq9TjAACwjKyRDgAAAAAABYR0AAAAAAAoIKQDAAAAAEABa6QDAAAAAEABV6QDAAAAAEABIR0AAAAAAAoI6QAAAAAAUEBIBwAAAACAAs1LPcDKqKLi07jFKwAAAABA/WrSJCkra7fMxxHSS2DhwgjpAAAAAAArCEu7AAAAAABAASEdAAAAAAAKCOkAAAAAAFBASAcAAAAAgAJCOgAAAAAAFBDSAQAAAACggJAOAAAAAAAFhHQAAAAAACggpAMAAAAAQAEhHQAAAAAACgjpAAAAAABQQEgHAAAAAIACQjoAAAAAABQQ0gEAAAAAoICQDgAAAAAABYR0AAAAAAAoIKQDAAAAAEABIR0AAAAAAAoI6QAAAAAAUEBIBwAAAACAAkI6AAAAAAAUENIBAAAAAKCAkA4AAAAAAAWEdAAAAAAAKCCkAwAAAABAgealHgAAAGBlMmXK5FRWVizTMTp0KEvnzl3qaCIAAL6KkA4AALCcTJkyOf0HbJE5s2ct03FatW6TCeOfF9MBAJYTIR0AAGA5qaysyJzZs1K2+4lpUVa7CF5VMTkVD12UysoKIR0AYDkR0gEAAJazFmVd0mqtrqUeAwCAJeRmowAAAAAAUEBIBwAAAACAApZ2AQAAVhpTpkxOZWXFMh2jQ4cya5MDAKxkhHQAAGClMGXK5PQfsEXmzJ61TMdp1bpNJox/XkwHAFiJCOkAAMBKobKyInNmz0rZ7iemRVntInhVxeRUPHRRKisrhHQAgJWIkA4AAKxUWpR1Sau1upZ6DAAAViBuNgoAAAAAAAVckQ4AAMBy58avAMCKREgHAABguXLjVwBgRSOkAwAAsFy58SsAsKIR0gEAACgJN34FAFYUQjoAAMBKxvrkAABLR0gHAABYiVifHABg6QnpAAAAKxHrkwMALD0hHQAAYCVkfXIAgCXXtNQDAAAAAABAQyakAwAAAABAASEdAAAAAAAKCOkAAAAAAFBASAcAAAAAgAJCOgAAAAAAFBDSAQAAAACggJAOAAAAAAAFhHQAAAAAACggpAMAAAAAQIHmpR4AAAAASmHKlMmprKxYpmN06FCWzp271NFEAEBDJaQDAACw0pkyZXL6D9gic2bPWqbjtGrdJhPGPy+mA0AjJ6QDAACw0qmsrMic2bNStvuJaVFWuwheVTE5FQ9dlMrKCiEdABo5IR0AAICVVouyLmm1VtdSjwEANHBuNgoAAAAAAAWEdAAAAAAAKGBpFwAAACiRKVMmp7KyYpmO0aFDmTXaAaCeCekAAABQAlOmTE7/AVtkzuxZy3ScVq3bZML458V0AKhHQjoAAACUQGVlRebMnpWy3U9Mi7LaRfCqismpeOiiVFZWCOkAUI+EdAAAACihFmVd0mqtrqUeAwAo4GajAAAAAABQQEgHAAAAAIACQjoAAAAAABSwRjorlSlTJqeysqLWr+/QocwNfAAAAABgJSOks9KYMmVy+g/YInNmz6r1MVq1bpMJ458X0wEAAABgJSKks9KorKzInNmzUrb7iWlRtvQhvKpicioeuiiVlRVCOgAAAACsRIR0Vjotyrqk1VpdSz0GAAAAALCCcLNRAAAAAAAoIKQDAAAAAEABS7sAAADASmzKlMmprKxYpmN06FDmXlIANGpCOgAAAKykpkyZnP4Dtsic2bOW6TitWrfJhPHPi+kANFpCOgAAAKykKisrMmf2rJTtfmJalNUugldVTE7FQxelsrJCSAeg0RLSAQCA5WJZl4+wdATUnxZlXdJqra6lHgMAGiwhHQAAqHd1sXyEpSMAACgVIR0AAKh3y7p8hKUjAAAoJSEdljMfaQYAVmaWjwAAYEUkpMNy5CPNAAAAALDiEdJhOfKRZgAAAABY8QjpUAI+0gwAAAAAK46mpR4AAAAAAAAaMiEdAAAAAAAKCOkAAAAAAFBASAcAAAAAgAJCOgAAAAAAFBDSAQAAAACggJAOAAAAAAAFhHQAAAAAACggpAMAAAAAQAEhHQAAAAAACgjpAAAAAABQQEgHAAAAAIACQjoAAAAAABQQ0gEAAAAAoICQDgAAAAAABYR0AAAAAAAoIKQDAAAAAEABIR0AAAAAAAoI6QAAAAAAUEBIBwAAAACAAkI6AAAAAAAUKGlIv/baa7PPPvukT58+6d+/f4455pi8/fbbNfaZM2dOzjzzzPTr1y99+vTJj370o5SXl9fYZ+rUqTniiCOy2WabpX///vnlL3+ZefPm1djnmWeeyV577ZWePXtmxx13zH333bfIPLfddlu233779OrVK0OGDMlLL7201LMAAAAAANC4lDSkP/vssznwwANz9913Z/To0Zk3b16GDRuWmTNnVu8zcuTIPProo7nkkkty66235qOPPspxxx1XvX3+/Pk58sgjU1VVlTvvvDPnnXdexo4dm8suu6x6n8mTJ+fII49Mv3798tvf/jaHHHJITjvttDzxxBPV+4wbNy6jRo3Ksccem7Fjx6ZHjx4ZNmxYKioqlngWAAAAAAAan5KG9BtvvDF77713Ntpoo/To0SPnnXdepk6dmldeeSVJ8umnn+bee+/N8OHD079///Ts2TMjR47MxIkT8+KLLyZJnnzyybz55pu54IILsvHGG2fQoEE54YQTctttt2Xu3LlJkjvvvDOdO3fO8OHDs+GGG+aggw7KTjvtlJtvvrl6ltGjR2fffffNPvvsk65du+bMM89M69atc++99y7xLAAAAAAAND7NSz3AF3366adJkvbt2ydJXn755VRVVWXAgAHV+2y44YZZe+218+KLL6Z379558cUX061bt3Ts2LF6n4EDB2bEiBF58803881vfjMvvvhi+vfvX+NcAwcOzMiRI5Mkc+fOzSuvvJIjjzyyenvTpk0zYMCATJw4cYlngRXFlCmTU1lZ8dU7fokOHcrSuXOXOpwIAAAAABquBhPSFyxYkJEjR6Zv377p1q1bkqS8vDwtWrTIaqutVmPfsrKyTJs2rXqfL0b0JNWPv2qfGTNmZPbs2fnkk08yf/78lJWVLXKez9dsX5JZYEUwZcrk9B+wRebMnlXrY7Rq3SYTxj8vpgPAcrKsPwRP/CAcAACWRYMJ6WeeeWbeeOON3H777aUeBRq1ysqKzJk9K2W7n5gWZUv/H9NVFZNT8dBFqays8B/jALAc1MUPwRM/CAcAgGXRIEL6WWedlcceeyy//vWvs9Zaa1U/37Fjx1RVVWX69Ok1rgSvqKhIp06dqvd56aWXahyvvLw8SWrs8/lzX9ynbdu2ad26dZo2bZpmzZrVuLHo5+f5/Er2JZkFViQtyrqk1VpdSz0GAPAVlvWH4IkfhAMAwLIq6c1GFy5cmLPOOit/+tOfcsstt6RLl5r/qO/Zs2datGiRCRMmVD/39ttvZ+rUqdVrkvfu3Tuvv/56jQg+fvz4tG3bNl27dq3e5+mnn65x7PHjx1cfo2XLltlkk01qnGfBggWZMGFC+vTps8SzAABAffn8h+C1+VXbAA8AAPxHSa9IP/PMM/PQQw/lqquuyqqrrlq91ni7du3SunXrtGvXLvvss0/OO++8tG/fPm3bts0555yTPn36VMfrgQMHpmvXrjnppJPyv//7v5k2bVouueSSHHjggWnZsmWS5Pvf/35uu+22nH/++dlnn33y9NNP5/e//32uvfba6lkOO+yw/PznP0/Pnj2z6aab5pZbbsmsWbOy9957V8/0VbMAAAAAS8+9IABo6Eoa0u+4444kydChQ2s8P2rUqOqAfcopp6Rp06Y5/vjjM3fu3AwcODBnnHFG9b7NmjXLNddckxEjRmS//fZLmzZtstdee+X444+v3qdLly659tprM2rUqIwZMyZrrbVWzjnnnGyzzTbV++y6666prKzMZZddlmnTpmXjjTfODTfcUOMmpV81CwAAALB03AsCgBVBSUP6pEmTvnKfVq1a5YwzzigM1uuss06uv/76wuP069cv999/f+E+Bx10UA466KBlmgUAAABYcu4FAcCKoEHcbBQAAABYuX1+LwgAaIhKerNRAAAAAABo6IR0AAAAAAAoIKQDAAAAAEABIR0AAAAAAAoI6QAAAAAAUEBIBwAAAACAAkI6AAAAAAAUENIBAAAAAKCAkA4AAAAAAAWEdAAAAAAAKCCkAwAAAABAASEdAAAAAAAKCOkAAAAAAFBASAcAAAAAgAJCOgAAAAAAFBDSAQAAAACggJAOAAAAAAAFhHQAAAAAACggpAMAAAAAQAEhHQAAAAAACgjpAAAAAABQQEgHAAAAAIACQjoAAAAAABRoXuoBAACgIZsyZXIqKyuW6RgdOpSlc+cudTQRAACwvAnpAADwJaZMmZz+A7bInNmzluk4rVq3yYTxz4vpAACwghLSAQDgS1RWVmTO7Fkp2/3EtCirXQSvqpiciocuSmVlhZAOAAArKCEdAAC+QouyLmm1VtdSjwEAAJSIkA6UxLKuN2utWQAAAACWFyEdWO7qYr1Za80CAAAAsLwI6cByt6zrzVprFgAAAIDlSUgHSsZ6swAAAACsCJqWegAAAAAAAGjIhHQAAAAAACggpAMAAAAAQAEhHQAAAAAACgjpAAAAAABQQEgHAAAAAIACQjoAAAAAABQQ0gEAAAAAoICQDgAAAAAABYR0AAAAAAAoIKQDAAAAAEABIR0AAAAAAAoI6QAAAAAAUEBIBwAAAACAAs1LPQAAAABAqU2ZMjmVlRXLdIwOHcrSuXOXOpoIgIZESAcAAABWalOmTE7/AVtkzuxZy3ScVq3bZML458V0gEZISAcAAABWapWVFZkze1bKdj8xLcpqF8GrKian4qGLUllZIaQDNEJCOgAADZaP2QOwPLUo65JWa3Ut9RgANEBCOgAADZKP2QMAAA2FkA4AQIPkY/YAAEBDIaQDANCg+Zg9AABQak1LPQAAAAAAADRkQjoAAAAAABSwtAsAAAAASf5zs+/KyoplOkaHDmXuTQI0OkI6AAAAAJkyZXL6D9gic2bPWqbjtGrdJhPGPy+mA42KkA4AAABAKisrMmf2rJTtfmJalNUugldVTE7FQxelsrJCSAcaFSEdAAAAgGotyrqk1VpdS3Z+y8sADZGQDgAAAECDYHkZoKES0gEAAABoECwvAzRUQjoAAAAADUqpl5cB+G9COgAAAAB8gXXagf8mpAMAAADA/8867cDiCOkAAAAA8P+zTjuwOEI6QAkt68cFfVQQAACgflinHfgiIR2gROri44I+KgjUJ2uDAgAA/IeQDlAiy/pxwbr6qKCr4oHFsTYoAADA/yOkA5RYKT8u6Kp44MtYGxQAAOD/EdKBlZYrsRvOVfFAw2VtUAAAACEdWEm5ErsmoQwAAADgywnpwErJldgAAAAALCkhHVipuRIbAAAAgK8ipANQcsu6Xn3SONasBwAAABomIR2AkqqL9eqTxrVmPSR+wAQAANCQCOkAlNSyrlefWLOexscPmAAAABoWIR2ABsF69fD/+AETAABAwyKkAwA0UH7ABAAA0DA0LfUAAAAAAADQkAnpAAAAAABQwNIuAAAAANAATZkyOZWVFbV+fYcOZe6XA3VESAcAAACABmbKlMnpP2CLzJk9q9bHaNW6TSaMf15MhzogpAMAAABAA1NZWZE5s2elbPcT06Js6UN4VcXkVDx0USorK4R0qANCOgAAAAA0UC3KuqTVWl1LPQas9NxsFAAAAAAACgjpAAAAAABQQEgHAAAAAIACQjoAAAAAABQQ0gEAAAAAoICQDgAAAAAABZqXegAAAAAAkilTJqeysmKZjtGhQ1k6d+5SRxMB8DkhHQAAAKDEpkyZnP4Dtsic2bOW6TitWrfJhPHPi+kAdUxIBwAAACixysqKzJk9K2W7n5gWZbWL4FUVk1Px0EWprKwQ0gHqmJAOAPExWmry5wEAKJUWZV3Saq2upR4DgP8ipAOw0vMxWr7InwcAAAD+m5AOwErPx2j5In8eAACA/7asn1r1idUVn5AOAP8/H6Pli/x5AAAAkrr51KpPrK74hHQAAAAAgC+xrJ9a9YnVxkFIBwAAAAD4Cj61unJrWuoBAAAAAACgIRPSAQAAAACggJAOAAAAAAAFrJEOAAAAACzWlCmTU1lZUevXd+hQ5gabNApCOgA0EMv6D9TEP1IBAIC6M2XK5PQfsEXmzJ5V62O0at0mE8Y/779TWOEJ6QDQANTFP1AT/0gFAADqTmVlRebMnpWy3U9Mi7Kl/2+MqorJqXjoolRWVvhvFFZ4QjoANADL+g/UxD9SAQCA+tGirEtardW11GNASQnpANCA+AcqAAAANDxNSz0AAAAAAAA0ZEI6AAAAAAAUsLQLANCgTJkyOZWVFct0jA4dyqwTDwAAQJ0paUh/7rnncuONN+bll1/OtGnTcuWVV2aHHXao3j58+PCMHTu2xmsGDhyYG2+8sfrxv//975x99tl59NFH07Rp03z729/OqaeemlVXXbV6n9deey1nnXVW/vGPf6RDhw456KCDcvjhh9c47u9///tceumlef/997PeeuvlZz/7WQYNGlS9feHChbnsssvym9/8JtOnT0/fvn0zYsSIrLfeenX8XQGAldeUKZPTf8AWmTN71jIdp1XrNpkw/nkxHQAAgDpR0pA+c+bMdO/ePfvss0+OO+64xe6zzTbbZNSoUdWPW7ZsWWP7z372s0ybNi2jR49OVVVVTjnllJx++um56KKLkiQzZszIsGHD0r9//5x55pl5/fXXc8opp2S11VbLfvvtlyT529/+lhNPPDE//elPs9122+XBBx/Msccem/vuuy/dunVLklx//fW59dZbc95556Vz58659NJLM2zYsIwbNy6tWrWqj28PAKx0KisrMmf2rJTtfmJalNUugldVTE7FQxelsrJCSAcAAKBOlDSkDxo0qMZV34vTsmXLdOrUabHb3nrrrTzxxBO555570qtXryTJaaedliOOOCInnXRS1lxzzTzwwAOpqqrKyJEj07Jly2y00UZ59dVXM3r06OqQPmbMmGyzzTb54Q9/mCT58Y9/nPHjx+fXv/51zjrrrCxcuDBjxozJ0UcfXX3F/Pnnn58BAwbkkUceyW677VZX3xIAIEmLsi5ptVbXUo8BAAAASVaANdKfffbZ9O/fP6uttlq22mqr/PjHP87qq6+eJJk4cWJWW2216oieJAMGDEjTpk3z0ksvZccdd8yLL76YLbbYosaV7AMHDsz111+fTz75JO3bt8+LL76YQw89tMZ5Bw4cmEceeSRJMmXKlEybNi0DBgyo3t6uXbtsttlmmThxopAOAAAAAPVkWe+j5B5K1IUGHdK32Wab7LjjjuncuXMmT56ciy++OIcffnjuuuuuNGvWLOXl5enQoUON1zRv3jzt27fPtGnTkiTl5eXp3LlzjX06duxYva19+/YpLy+vfu5zZWVlKS8vT5LqY5WVlX3pPgAAAABA3aqL+yi5hxJ1oUGH9C9e6d29e/d07949O+ywQ/VV6gBA3VrWKz0SV3sAAAB1Z1nvo+QeStSVBh3S/1uXLl2y+uqr5913303//v3TsWPHVFZW1thn3rx5+eSTT6rXVe/YseMiV41//vjzq9AXt09FRUX19s+PVVFRkTXWWKPGPj169KjDrxAASqcurvRIXO0BAADUPfdRotRWqJD+wQcf5N///nd12O7Tp0+mT5+el19+OT179kySPP3001mwYEE23XTTJEnv3r1zySWXpKqqKi1atEiSjB8/Puuvv37at29fvc/TTz9dY5308ePHp3fv3kmSzp07p1OnTpkwYUI23njjJMmMGTPy97//Pfvvv//y+NIBoN4t65Ueias9AAAAaJxKGtI/++yzvPfee9WPp0yZkldffTXt27dP+/btc8UVV2SnnXZKx44dM3ny5FxwwQVZd911s8022yRJNtxww2yzzTb5xS9+kTPPPDNVVVU5++yzs9tuu2XNNddMkuyxxx658sorc+qpp+bwww/PG2+8kTFjxuTkk0+uPu/BBx+coUOH5qabbsqgQYMybty4vPzyyznrrLOSJE2aNMnBBx+cq6++Ouuuu246d+6cSy+9NGussUZ22GGH5fgdA4D650oPAAAAqKmkIf3ll1/OwQcfXP141KhRSZK99torI0aMyOuvv577778/n376adZYY41svfXWOeGEE9KyZcvq11x44YU5++yzc8ghh6Rp06b59re/ndNOO616e7t27XLjjTfmrLPOyt57753VV189xxxzTPbbb7/qffr27ZsLL7wwl1xySS6++OKst956ufLKK9OtW7fqfQ4//PDMmjUrp59+eqZPn57NN988N9xwQ1q1alWf3yIAAAAAAEqspCG9X79+mTRp0pduv/HGG7/yGF/72tdy0UUXFe7To0eP3H777YX77LLLLtlll12+dHuTJk1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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Total number of hours: 38\n", "Average clips per hour: 180338.26\n", "Max clips in an hour: 234332\n", "Min clips in an hour: 110203\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", "# check the number of audio uploads\n", "upload_clip_df = total_clip_df[total_clip_df[\"s3_id\"].str.startswith(\"m_\")].copy()\n", "print(\"total uploads:\", (total_clip_df[\"model_name\"] == \"\").sum(), upload_clip_df.shape)\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": 8, "metadata": { "execution": { "iopub.execute_input": "2024-08-26T08:41:01.349459Z", "iopub.status.busy": "2024-08-26T08:41:01.349307Z", "iopub.status.idle": "2024-08-26T08:41:01.579810Z", "shell.execute_reply": "2024-08-26T08:41:01.579253Z", "shell.execute_reply.started": "2024-08-26T08:41:01.349444Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "number of upvoates: 747,490 rows\n", "number of flagged reports: 11,951 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": 9, "metadata": { "execution": { "iopub.execute_input": "2024-08-26T08:41:01.580654Z", "iopub.status.busy": "2024-08-26T08:41:01.580498Z", "iopub.status.idle": "2024-08-26T08:41:02.005899Z", "shell.execute_reply": "2024-08-26T08:41:02.005387Z", "shell.execute_reply.started": "2024-08-26T08:41:01.580639Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Pro reactions fraction by category:\n", "False: 5118366 (66.61%)\n", "True: 2565625 (33.39%)\n", "Pro reactions fraction by user:\n", "False: 3948605 (57.62%)\n", "True: 2904249 (42.38%)\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(\"Pro reactions fraction by category:\")\n", "print_out_value_counts_nicely(reaction_df, \"is_pro_user\")\n", "# clip check\n", "print(\"Pro reactions fraction by user:\")\n", "print_out_value_counts_nicely(clip_df, \"is_pro_user\")" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:12.019778Z", "start_time": "2024-05-26T00:22:57.637371Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:41:02.006708Z", "iopub.status.busy": "2024-08-26T08:41:02.006560Z", "iopub.status.idle": "2024-08-26T08:41:04.967025Z", "shell.execute_reply": "2024-08-26T08:41:04.966456Z", "shell.execute_reply.started": "2024-08-26T08:41:02.006694Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Clips in a splaylist:\n", "False: 6809803 (99.37%)\n", "True: 43051 (0.63%)\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\")" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:17.912428Z", "start_time": "2024-05-26T00:23:12.021726Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:41:04.967883Z", "iopub.status.busy": "2024-08-26T08:41:04.967723Z", "iopub.status.idle": "2024-08-26T08:41:15.363110Z", "shell.execute_reply": "2024-08-26T08:41:15.362529Z", "shell.execute_reply.started": "2024-08-26T08:41:04.967867Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "clips that have children: 724800 \n", "clips that are parents: 128879 \n", " Average continues from clip = 5.62\n", "web: 6679006 (98.43%)\n", "ios: 106513 (1.57%)\n" ] } ], "source": [ "# parse the metadata for histories and types\n", "clip_df[[\"continued_parent\", \"duration\", \"source\"]] = pd.DataFrame(\n", " clip_df[\"metadata\"].map(parse_metadata_for_basics).tolist(), index=clip_df.index\n", ")\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": 12, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:22.092835Z", "start_time": "2024-05-26T00:23:17.914456Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:41:15.363971Z", "iopub.status.busy": "2024-08-26T08:41:15.363814Z", "iopub.status.idle": "2024-08-26T08:41:19.752797Z", "shell.execute_reply": "2024-08-26T08:41:19.752211Z", "shell.execute_reply.started": "2024-08-26T08:41:15.363957Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "total uploads: 227686\n", "Clips without request id (concat, uploads...) frac = 0.04045\n" ] } ], "source": [ "print(\"total uploads:\", (clip_df[\"model_name\"] == \"\").sum())\n", "# the nans are concats, we want to drop them for now\n", "concated_clips = clip_df[clip_df[\"request_id\"].isna()].copy()\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": 13, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:22.833148Z", "start_time": "2024-05-26T00:23:22.094796Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:41:19.753650Z", "iopub.status.busy": "2024-08-26T08:41:19.753493Z", "iopub.status.idle": "2024-08-26T08:41:20.456556Z", "shell.execute_reply": "2024-08-26T08:41:20.456075Z", "shell.execute_reply.started": "2024-08-26T08:41:19.753634Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "chirp-v3p5-engine-s-8: 5009728 (76.19%)\n", "chirp-v3p5-engine-upload-4: 325670 (4.95%)\n", "chirp-v3p5-engine-s-24: 280763 (4.27%)\n", "chirp-v3p5-engine-t-2: 263379 (4.01%)\n", "chirp-v3p5-engine-b: 183592 (2.79%)\n", "chirp-v3-engine-i: 175872 (2.67%)\n", "chirp-v3p5-engine-t-2-10: 104752 (1.59%)\n", "chirp-v3p5-engine-t-2-12: 85426 (1.30%)\n", "chirp-v3p5-engine-t-2-13: 72866 (1.11%)\n", "chirp-v2-xxl-alpha: 27188 (0.41%)\n", "chirp-v3-5: 24733 (0.38%)\n", "chirp-v2-engine-msft-60s: 17823 (0.27%)\n", "chirp-v3p5-engine-ft-1: 2387 (0.04%)\n", "chirp-v3-0: 990 (0.02%)\n", "chirp-v3p5-engine-short: 466 (0.01%)\n", "chirp-v3-5-short: 10 (0.00%)\n", "chirp-v3-5-upload: 6 (0.00%)\n" ] } ], "source": [ "# check the model conts\n", "print_out_value_counts_nicely(clip_df, \"model_name\")" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:26.317699Z", "start_time": "2024-05-26T00:23:22.835074Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:41:20.457327Z", "iopub.status.busy": "2024-08-26T08:41:20.457182Z", "iopub.status.idle": "2024-08-26T08:41:24.817987Z", "shell.execute_reply": "2024-08-26T08:41:24.817417Z", "shell.execute_reply.started": "2024-08-26T08:41:20.457313Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "pre-filter model type clip_df shape: (6575651, 31)\n", "post-filter model type clip_df shape: (6549928, 31)\n", "chirp-v3p5-engine-s-8: 5009728 (76.49%)\n", "chirp-v3p5-engine-upload-4: 325670 (4.97%)\n", "chirp-v3p5-engine-s-24: 280763 (4.29%)\n", "chirp-v3p5-engine-t-2: 263379 (4.02%)\n", "chirp-v3p5-engine-b: 183592 (2.80%)\n", "chirp-v3-engine-i: 175872 (2.69%)\n", "chirp-v3p5-engine-t-2-10: 104752 (1.60%)\n", "chirp-v3p5-engine-t-2-12: 85426 (1.30%)\n", "chirp-v3p5-engine-t-2-13: 72866 (1.11%)\n", "chirp-v2-xxl-alpha: 27188 (0.42%)\n", "chirp-v2-engine-msft-60s: 17823 (0.27%)\n", "chirp-v3p5-engine-ft-1: 2387 (0.04%)\n", "chirp-v3p5-engine-short: 466 (0.01%)\n", "chirp-v3-5-short: 10 (0.00%)\n", "chirp-v3-5-upload: 6 (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\") & (clip_df[\"model_name\"] != \"chirp-v3-0\")\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": 15, "metadata": { "execution": { "iopub.execute_input": "2024-08-26T08:41:24.818851Z", "iopub.status.busy": "2024-08-26T08:41:24.818693Z", "iopub.status.idle": "2024-08-26T08:41:29.416045Z", "shell.execute_reply": "2024-08-26T08:41:29.415469Z", "shell.execute_reply.started": "2024-08-26T08:41:24.818836Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "concat reactions: 112596 unique concat clips: 75366\n", "total concats (277203, 34)\n", "check \n", " reaction_play_count reaction_upvote_count reaction_dislike_count\n", "count 75366.000000 75366.000000 75366.000000\n", "mean 3.014330 0.127286 0.013269\n", "std 60.552581 0.729418 0.116720\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% 2.000000 0.000000 0.000000\n", "max 11168.000000 87.000000 6.000000\n", "All concats 277203\n", "total concats with plays 75366\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": 16, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:38.974479Z", "start_time": "2024-05-26T00:23:34.385507Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:41:29.416903Z", "iopub.status.busy": "2024-08-26T08:41:29.416750Z", "iopub.status.idle": "2024-08-26T08:41:32.443750Z", "shell.execute_reply": "2024-08-26T08:41:32.443196Z", "shell.execute_reply.started": "2024-08-26T08:41:29.416888Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "75366it [00:02, 25332.21it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "total concat unique clips are: 63610 with error: 0, duplicate 7461 \n", " uploads are in concats 5147 frac 0.082\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": 17, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:40.236690Z", "start_time": "2024-05-26T00:23:39.995713Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:41:32.444593Z", "iopub.status.busy": "2024-08-26T08:41:32.444429Z", "iopub.status.idle": "2024-08-26T08:41:32.809048Z", "shell.execute_reply": "2024-08-26T08:41:32.808479Z", "shell.execute_reply.started": "2024-08-26T08:41:32.444578Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "count 6.549928e+06\n", "mean 2.957717e+02\n", "std 1.183499e+03\n", "min 1.000000e+00\n", "25% 1.000000e+01\n", "50% 1.800000e+01\n", "75% 9.800000e+01\n", "max 1.782300e+04\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": 18, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:44.826860Z", "start_time": "2024-05-26T00:23:40.238330Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:41:32.809915Z", "iopub.status.busy": "2024-08-26T08:41:32.809755Z", "iopub.status.idle": "2024-08-26T08:41:38.629600Z", "shell.execute_reply": "2024-08-26T08:41:38.629024Z", "shell.execute_reply.started": "2024-08-26T08:41:32.809899Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "has upvoted upvoted\n", "False 6253638\n", "True 296290\n", "Name: count, dtype: int64 upvoted\n", "False 0.954764\n", "True 0.045236\n", "Name: proportion, dtype: float64 upvote_count\n", "False 0.954255\n", "True 0.045745\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", ")" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:48.404433Z", "start_time": "2024-05-26T00:23:44.857788Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:41:38.632886Z", "iopub.status.busy": "2024-08-26T08:41:38.632614Z", "iopub.status.idle": "2024-08-26T08:41:41.914160Z", "shell.execute_reply": "2024-08-26T08:41:41.913594Z", "shell.execute_reply.started": "2024-08-26T08:41:38.632870Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "downvoted fraction by category:\n", "False: 6338924 (96.78%)\n", "True: 211004 (3.22%)\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": 20, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:56.590022Z", "start_time": "2024-05-26T00:23:48.405668Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:41:41.915014Z", "iopub.status.busy": "2024-08-26T08:41:41.914857Z", "iopub.status.idle": "2024-08-26T08:41:49.165078Z", "shell.execute_reply": "2024-08-26T08:41:49.164513Z", "shell.execute_reply.started": "2024-08-26T08:41:41.914999Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "has_continued fraction by category:\n", "False: 6498904 (99.22%)\n", "True: 51024 (0.78%)\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": 21, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:04.704306Z", "start_time": "2024-05-26T00:23:56.591353Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:41:49.165937Z", "iopub.status.busy": "2024-08-26T08:41:49.165775Z", "iopub.status.idle": "2024-08-26T08:41:56.082028Z", "shell.execute_reply": "2024-08-26T08:41:56.081452Z", "shell.execute_reply.started": "2024-08-26T08:41:49.165922Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "part_of_concat fraction by category:\n", "False: 6504121 (99.30%)\n", "True: 45807 (0.70%)\n", "\n", "Model distribution for part_of_concat clips:\n", "chirp-v3p5-engine-s-8: 67.18%\n", "chirp-v3p5-engine-upload-4: 12.66%\n", "chirp-v3-engine-i: 5.94%\n", "chirp-v3p5-engine-t-2: 5.12%\n", "chirp-v3p5-engine-s-24: 3.55%\n", "chirp-v3p5-engine-t-2-10: 1.87%\n", "chirp-v3p5-engine-t-2-12: 1.82%\n", "chirp-v3p5-engine-t-2-13: 1.33%\n", "chirp-v2-xxl-alpha: 0.41%\n", "chirp-v3p5-engine-b: 0.11%\n", "chirp-v3p5-engine-ft-1: 0.03%\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(\"\\nModel 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": 22, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:09.954233Z", "start_time": "2024-05-26T00:24:04.705554Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:41:56.082889Z", "iopub.status.busy": "2024-08-26T08:41:56.082726Z", "iopub.status.idle": "2024-08-26T08:41:58.488217Z", "shell.execute_reply": "2024-08-26T08:41:58.487651Z", "shell.execute_reply.started": "2024-08-26T08:41:56.082873Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "has_action fraction by category:\n", "False: 6508624 (99.37%)\n", "True: 41304 (0.63%)\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": 23, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:14.579841Z", "start_time": "2024-05-26T00:24:09.955568Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:41:58.489087Z", "iopub.status.busy": "2024-08-26T08:41:58.488932Z", "iopub.status.idle": "2024-08-26T08:42:02.839901Z", "shell.execute_reply": "2024-08-26T08:42:02.839349Z", "shell.execute_reply.started": "2024-08-26T08:41:58.489072Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "flagged fraction by category:\n", "False: 6541187 (99.87%)\n", "True: 8741 (0.13%)\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": 24, "metadata": { "execution": { "iopub.execute_input": "2024-08-26T08:42:02.840732Z", "iopub.status.busy": "2024-08-26T08:42:02.840577Z", "iopub.status.idle": "2024-08-26T08:42:02.884160Z", "shell.execute_reply": "2024-08-26T08:42:02.883691Z", "shell.execute_reply.started": "2024-08-26T08:42:02.840717Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "deleted fraction by category:\n", "False: 5611393 (85.67%)\n", "True: 938535 (14.33%)\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": 25, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:15.382315Z", "start_time": "2024-05-26T00:24:14.581073Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:42:02.884944Z", "iopub.status.busy": "2024-08-26T08:42:02.884797Z", "iopub.status.idle": "2024-08-26T08:42:03.690646Z", "shell.execute_reply": "2024-08-26T08:42:03.690174Z", "shell.execute_reply.started": "2024-08-26T08:42:02.884929Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Total clips: 6,549,928\n", "Must be positive: 381,379 (5.82%)\n", "Definitely not negative: 5,407,926 (82.56%)\n", "Must be negative: 1,142,002 (17.44%)\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": 26, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:31.095990Z", "start_time": "2024-05-26T00:24:15.383572Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:42:03.691409Z", "iopub.status.busy": "2024-08-26T08:42:03.691264Z", "iopub.status.idle": "2024-08-26T08:42:21.458685Z", "shell.execute_reply": "2024-08-26T08:42:21.458094Z", "shell.execute_reply.started": "2024-08-26T08:42:03.691395Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Liked requests: 296,841\n", "Not liked requests: 3,240,854\n", "Requests with preference paired generations: 234,189\n", "Percentage of total unique requests: 7.09%\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": 27, "metadata": { "execution": { "iopub.execute_input": "2024-08-26T08:42:21.459567Z", "iopub.status.busy": "2024-08-26T08:42:21.459404Z", "iopub.status.idle": "2024-08-26T08:42:30.430159Z", "shell.execute_reply": "2024-08-26T08:42:30.429578Z", "shell.execute_reply.started": "2024-08-26T08:42:21.459552Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Disliked requests: 673,860\n", "Not disliked requests: 2,826,088\n", "Requests with preference paired generations: 196,442\n", "Percentage of total unique requests: 5.95%\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": 28, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:31.099372Z", "start_time": "2024-05-26T00:24:31.097244Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:42:30.431027Z", "iopub.status.busy": "2024-08-26T08:42:30.430875Z", "iopub.status.idle": "2024-08-26T08:42:30.490139Z", "shell.execute_reply": "2024-08-26T08:42:30.489623Z", "shell.execute_reply.started": "2024-08-26T08:42:30.431013Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Total selected pairs of requests: 375,310\n", "Percentage of total unique requests: 11.36%\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": 29, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:31.239254Z", "start_time": "2024-05-26T00:24:31.100389Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:42:30.490938Z", "iopub.status.busy": "2024-08-26T08:42:30.490787Z", "iopub.status.idle": "2024-08-26T08:42:30.563684Z", "shell.execute_reply": "2024-08-26T08:42:30.563191Z", "shell.execute_reply.started": "2024-08-26T08:42:30.490924Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Difference in preference counts:\n", "0: 5,050,977 (77.12%)\n", "-1: 1,142,002 (17.44%)\n", "1: 356,949 (5.45%)\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": 30, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:37.322031Z", "start_time": "2024-05-26T00:24:31.240829Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:42:30.564418Z", "iopub.status.busy": "2024-08-26T08:42:30.564276Z", "iopub.status.idle": "2024-08-26T08:42:36.443621Z", "shell.execute_reply": "2024-08-26T08:42:36.443015Z", "shell.execute_reply.started": "2024-08-26T08:42:30.564404Z" } }, "outputs": [], "source": [ "# creation of interesting_clips\n", "interesting_clips = clip_df[clip_df[\"request_id\"].isin(requests)].copy()" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "execution": { "iopub.execute_input": "2024-08-26T08:42:36.444519Z", "iopub.status.busy": "2024-08-26T08:42:36.444351Z", "iopub.status.idle": "2024-08-26T08:42:39.283496Z", "shell.execute_reply": "2024-08-26T08:42:39.282976Z", "shell.execute_reply.started": "2024-08-26T08:42:36.444504Z" } }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " request_id pos_preference neg_preference diff_preference\n", "0 00002fa2-c9b8-4a2c-a891-d61ac2330aae False False 0\n", "1 00002fa2-c9b8-4a2c-a891-d61ac2330aae True False 1\n", "2 0000327a-0955-4520-8730-3aeb215c9d8b False True -1\n", "3 0000327a-0955-4520-8730-3aeb215c9d8b False False 0\n", "4 000061aa-2991-4b50-84be-a73af2ac9bc9 False False 0\n", "5 000061aa-2991-4b50-84be-a73af2ac9bc9 True False 1" ] }, "execution_count": 31, "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": 32, "metadata": { "execution": { "iopub.execute_input": "2024-08-26T08:42:39.284323Z", "iopub.status.busy": "2024-08-26T08:42:39.284166Z", "iopub.status.idle": "2024-08-26T08:42:39.308006Z", "shell.execute_reply": "2024-08-26T08:42:39.307514Z", "shell.execute_reply.started": "2024-08-26T08:42:39.284309Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Difference 0: 319,989 (42.63%)\n", "Difference 1: 234,189 (31.20%)\n", "Difference -1: 196,442 (26.17%)\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": 33, "metadata": { "execution": { "iopub.execute_input": "2024-08-26T08:42:39.308756Z", "iopub.status.busy": "2024-08-26T08:42:39.308617Z", "iopub.status.idle": "2024-08-26T08:42:39.350575Z", "shell.execute_reply": "2024-08-26T08:42:39.350113Z", "shell.execute_reply.started": "2024-08-26T08:42:39.308742Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Value 1.0: 319,989 (85.26%)\n", "Value 2.0: 55,321 (14.74%)\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": 34, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:38.960130Z", "start_time": "2024-05-26T00:24:37.323369Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:42:39.351453Z", "iopub.status.busy": "2024-08-26T08:42:39.351307Z", "iopub.status.idle": "2024-08-26T08:42:42.708213Z", "shell.execute_reply": "2024-08-26T08:42:42.707631Z", "shell.execute_reply.started": "2024-08-26T08:42:39.351439Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of unique request_ids: 375,310\n", "Number of unique ids: 750,620\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": 35, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:43.332222Z", "start_time": "2024-05-26T00:24:43.166461Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:42:42.709087Z", "iopub.status.busy": "2024-08-26T08:42:42.708922Z", "iopub.status.idle": "2024-08-26T08:42:42.729210Z", "shell.execute_reply": "2024-08-26T08:42:42.728767Z", "shell.execute_reply.started": "2024-08-26T08:42:42.709072Z" } }, "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": 36, "metadata": { "execution": { "iopub.execute_input": "2024-08-26T08:42:42.729961Z", "iopub.status.busy": "2024-08-26T08:42:42.729820Z", "iopub.status.idle": "2024-08-26T08:43:00.905785Z", "shell.execute_reply": "2024-08-26T08:43:00.905194Z", "shell.execute_reply.started": "2024-08-26T08:42:42.729947Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of interesting clips: 750,620\n", "Unique request and clip counts in interesting_clips:\n", "Request IDs: 375,310\n", "Clip IDs: 750,620\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": 37, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:43.737067Z", "start_time": "2024-05-26T00:24:43.563216Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:43:00.906662Z", "iopub.status.busy": "2024-08-26T08:43:00.906495Z", "iopub.status.idle": "2024-08-26T08:43:01.273556Z", "shell.execute_reply": "2024-08-26T08:43:01.273019Z", "shell.execute_reply.started": "2024-08-26T08:43:00.906647Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Preference counts and fractions by batch index:\n", "--------------------------------------------------\n", "Batch Index: 0\n", " Preference False: Count: 191,233 Fraction: 50.95%\n", " Preference True: Count: 184,077 Fraction: 49.05%\n", "\n", "Batch Index: 1\n", " Preference False: Count: 184,077 Fraction: 49.05%\n", " Preference True: Count: 191,233 Fraction: 50.95%\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": 38, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:44.304573Z", "start_time": "2024-05-26T00:24:43.973218Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:43:01.274381Z", "iopub.status.busy": "2024-08-26T08:43:01.274226Z", "iopub.status.idle": "2024-08-26T08:43:01.434067Z", "shell.execute_reply": "2024-08-26T08:43:01.433599Z", "shell.execute_reply.started": "2024-08-26T08:43:01.274367Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "chirp-v3p5-engine-s-8: 582937 (77.66%)\n", "chirp-v3p5-engine-upload-4: 45876 (6.11%)\n", "chirp-v3p5-engine-s-24: 36018 (4.80%)\n", "chirp-v3p5-engine-t-2: 34130 (4.55%)\n", "chirp-v3-engine-i: 14658 (1.95%)\n", "chirp-v3p5-engine-t-2-10: 13250 (1.77%)\n", "chirp-v3p5-engine-t-2-12: 11223 (1.50%)\n", "chirp-v3p5-engine-t-2-13: 9682 (1.29%)\n", "chirp-v2-xxl-alpha: 2232 (0.30%)\n", "chirp-v3p5-engine-b: 316 (0.04%)\n", "chirp-v3p5-engine-ft-1: 260 (0.03%)\n", "chirp-v3p5-engine-short: 38 (0.01%)\n" ] } ], "source": [ "print_out_value_counts_nicely(interesting_clips, \"model_name\")" ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:44.533983Z", "start_time": "2024-05-26T00:24:44.305722Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:43:01.434839Z", "iopub.status.busy": "2024-08-26T08:43:01.434690Z", "iopub.status.idle": "2024-08-26T08:43:01.497084Z", "shell.execute_reply": "2024-08-26T08:43:01.496605Z", "shell.execute_reply.started": "2024-08-26T08:43:01.434825Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Time Validation:\n", "--------------------\n", "Interesting Clips:\n", " Earliest: 2024-08-24 18:30:00.219675+00:00\n", " Latest: 2024-08-26 07:41:29.330412+00:00\n", "\n", "All Clips:\n", " Earliest: 2024-08-24 18:30:00.062052+00:00\n", " Latest: 2024-08-26 07:41:40.122982+00:00\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": 40, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:50.674838Z", "start_time": "2024-05-26T00:24:46.366677Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:43:01.497850Z", "iopub.status.busy": "2024-08-26T08:43:01.497710Z", "iopub.status.idle": "2024-08-26T08:43:03.416017Z", "shell.execute_reply": "2024-08-26T08:43:03.415433Z", "shell.execute_reply.started": "2024-08-26T08:43:01.497837Z" } }, "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": 41, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:51.600621Z", "start_time": "2024-05-26T00:24:50.676186Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:43:03.416928Z", "iopub.status.busy": "2024-08-26T08:43:03.416759Z", "iopub.status.idle": "2024-08-26T08:43:13.354274Z", "shell.execute_reply": "2024-08-26T08:43:13.353712Z", "shell.execute_reply.started": "2024-08-26T08:43:03.416912Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Ratio of preferred clips to total clips for each model:\n", "------------------------------------------------------------\n", "chirp-v2-engine-msft-60s nan% ± nan%\n", "chirp-v2-xxl-alpha 4.10% ± 0.12%\n", "chirp-v3-5-short nan% ± nan%\n", "chirp-v3-5-upload nan% ± nan%\n", "chirp-v3-engine-i 4.17% ± 0.05%\n", "chirp-v3p5-engine-b 0.09% ± 0.01%\n", "chirp-v3p5-engine-ft-1 5.45% ± 0.46%\n", "chirp-v3p5-engine-s-24 6.64% ± 0.05%\n", "chirp-v3p5-engine-s-8 5.87% ± 0.01%\n", "chirp-v3p5-engine-short 4.08% ± 0.92%\n", "chirp-v3p5-engine-t-2 5.78% ± 0.05%\n", "chirp-v3p5-engine-t-2-10 5.89% ± 0.07%\n", "chirp-v3p5-engine-t-2-12 6.04% ± 0.08%\n", "chirp-v3p5-engine-t-2-13 6.10% ± 0.09%\n", "chirp-v3p5-engine-upload-4 7.04% ± 0.04%\n" ] } ], "source": [ "# Calculate the ratio of preferred clips to total clips for each model\n", "preference_ratio = (\n", " interesting_clips[interesting_clips[\"preference\"]][\"model_name\"].value_counts()\n", " / clip_df[\"model_name\"].value_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_name\"].value_counts()[model]\n", " uncertainty = (ratio * (1 - ratio) / n) ** 0.5\n", " print(f\"{model:<30} {ratio:.2%} ± {uncertainty:.2%}\")" ] }, { "cell_type": "code", "execution_count": 42, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:56.302599Z", "start_time": "2024-05-26T00:24:51.601863Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:43:13.355136Z", "iopub.status.busy": "2024-08-26T08:43:13.354973Z", "iopub.status.idle": "2024-08-26T08:43:16.135968Z", "shell.execute_reply": "2024-08-26T08:43:16.135420Z", "shell.execute_reply.started": "2024-08-26T08:43:13.355121Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "chirp-v2-xxl-alpha_win_over_chirp-v2-xxl-alpha, win ratio 1.000, counts 1116\n", "chirp-v3-engine-i_win_over_chirp-v3-engine-i, win ratio 1.000, counts 7329\n", "chirp-v3p5-engine-b_win_over_chirp-v3p5-engine-b, win ratio 1.000, counts 158\n", "chirp-v3p5-engine-ft-1_win_over_chirp-v3p5-engine-ft-1, win ratio 1.000, counts 130\n", "chirp-v3p5-engine-s-24_win_over_chirp-v3p5-engine-s-24, win ratio 1.000, counts 2\n", "chirp-v3p5-engine-s-24_win_over_chirp-v3p5-engine-s-8, win ratio 0.517, counts 18636\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-24, win ratio 0.483, counts 17378\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-8, win ratio 1.000, counts 254706\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-t-2, win ratio 0.589, counts 11032\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-t-2-10, win ratio 0.569, counts 4167\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-t-2-12, win ratio 0.588, counts 3599\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-t-2-13, win ratio 0.583, counts 3105\n", "chirp-v3p5-engine-short_win_over_chirp-v3p5-engine-short, win ratio 1.000, counts 19\n", "chirp-v3p5-engine-t-2-10_win_over_chirp-v3p5-engine-s-8, win ratio 0.431, counts 3157\n", "chirp-v3p5-engine-t-2-10_win_over_chirp-v3p5-engine-t-2, win ratio 0.509, counts 3018\n", "chirp-v3p5-engine-t-2-12_win_over_chirp-v3p5-engine-s-8, win ratio 0.412, counts 2521\n", "chirp-v3p5-engine-t-2-12_win_over_chirp-v3p5-engine-t-2, win ratio 0.517, counts 2637\n", "chirp-v3p5-engine-t-2-13_win_over_chirp-v3p5-engine-s-8, win ratio 0.417, counts 2224\n", "chirp-v3p5-engine-t-2-13_win_over_chirp-v3p5-engine-t-2, win ratio 0.511, counts 2223\n", "chirp-v3p5-engine-t-2_win_over_chirp-v3p5-engine-s-8, win ratio 0.411, counts 7706\n", "chirp-v3p5-engine-t-2_win_over_chirp-v3p5-engine-t-2, win ratio 1.000, counts 5\n", "chirp-v3p5-engine-t-2_win_over_chirp-v3p5-engine-t-2-10, win ratio 0.491, counts 2908\n", "chirp-v3p5-engine-t-2_win_over_chirp-v3p5-engine-t-2-12, win ratio 0.483, counts 2466\n", "chirp-v3p5-engine-t-2_win_over_chirp-v3p5-engine-t-2-13, win ratio 0.489, counts 2130\n", "chirp-v3p5-engine-upload-4_win_over_chirp-v3p5-engine-upload-4, win ratio 1.000, counts 22938\n" ] }, { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "get_preferfence_counts(interesting_clips)" ] }, { "cell_type": "code", "execution_count": 43, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:57.443236Z", "start_time": "2024-05-26T00:24:56.306473Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:43:16.136854Z", "iopub.status.busy": "2024-08-26T08:43:16.136687Z", "iopub.status.idle": "2024-08-26T08:43:17.358308Z", "shell.execute_reply": "2024-08-26T08:43:17.357814Z", "shell.execute_reply.started": "2024-08-26T08:43:16.136838Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/tony/anaconda3/envs/suno_env/lib/python3.10/site-packages/matplotlib/axes/_axes.py:7001: RuntimeWarning: Converting input from bool to for compatibility.\n", " m, bins = np.histogram(x[i], bins, weights=w[i], **hist_kwargs)\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": 44, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:58.153310Z", "start_time": "2024-05-26T00:24:57.858363Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:43:17.359158Z", "iopub.status.busy": "2024-08-26T08:43:17.358998Z", "iopub.status.idle": "2024-08-26T08:43:17.378890Z", "shell.execute_reply": "2024-08-26T08:43:17.378447Z", "shell.execute_reply.started": "2024-08-26T08:43:17.359138Z" } }, "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": 45, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:58.890520Z", "start_time": "2024-05-26T00:24:58.154350Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:43:17.379672Z", "iopub.status.busy": "2024-08-26T08:43:17.379520Z", "iopub.status.idle": "2024-08-26T08:43:41.294130Z", "shell.execute_reply": "2024-08-26T08:43:41.293548Z", "shell.execute_reply.started": "2024-08-26T08:43:17.379658Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of clips in interesting_clips:\n", "750,620\n", "Number of clips in user_interesting_clips:\n", "695,416\n", "Ratio of preferred clips to total clips for each model:\n", "------------------------------------------------------------\n", "chirp-v2-engine-msft-60s nan% ± nan%\n", "chirp-v2-xxl-alpha nan% ± nan%\n", "chirp-v3-5-short nan% ± nan%\n", "chirp-v3-5-upload nan% ± nan%\n", "chirp-v3-engine-i nan% ± nan%\n", "chirp-v3p5-engine-b 0.07% ± 0.01%\n", "chirp-v3p5-engine-ft-1 5.11% ± 0.45%\n", "chirp-v3p5-engine-s-24 6.29% ± 0.05%\n", "chirp-v3p5-engine-s-8 5.55% ± 0.01%\n", "chirp-v3p5-engine-short 4.08% ± 0.92%\n", "chirp-v3p5-engine-t-2 5.47% ± 0.04%\n", "chirp-v3p5-engine-t-2-10 5.63% ± 0.07%\n", "chirp-v3p5-engine-t-2-12 5.72% ± 0.08%\n", "chirp-v3p5-engine-t-2-13 5.81% ± 0.09%\n", "chirp-v3p5-engine-upload-4 6.83% ± 0.04%\n", "Ratio of NOT-preferred clips to total clips for each model:\n", "------------------------------------------------------------\n", "chirp-v2-engine-msft-60s nan% ± nan%\n", "chirp-v2-xxl-alpha nan% ± nan%\n", "chirp-v3-5-short nan% ± nan%\n", "chirp-v3-5-upload nan% ± nan%\n", "chirp-v3-engine-i nan% ± nan%\n", "chirp-v3p5-engine-b 0.07% ± 0.01%\n", "chirp-v3p5-engine-ft-1 5.11% ± 0.45%\n", "chirp-v3p5-engine-s-24 5.77% ± 0.04%\n", "chirp-v3p5-engine-s-8 5.46% ± 0.01%\n", "chirp-v3p5-engine-short 4.08% ± 0.92%\n", "chirp-v3p5-engine-t-2 6.85% ± 0.05%\n", "chirp-v3p5-engine-t-2-10 6.43% ± 0.08%\n", "chirp-v3p5-engine-t-2-12 6.79% ± 0.09%\n", "chirp-v3p5-engine-t-2-13 6.83% ± 0.09%\n", "chirp-v3p5-engine-upload-4 6.83% ± 0.04%\n" ] } ], "source": [ "# subselect interesting clips\n", "interesting_clips_masks = (interesting_clips[\"model_name\"].str.contains(\"v3p5\")) & (\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_name\"].value_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_name\"].value_counts()[model]\n", " uncertainty = (ratio * (1 - ratio) / n) ** 0.5\n", " print(f\"{model:<30} {ratio:.2%} ± {uncertainty:.2%}\")\n", "\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_name\"].value_counts()\n", ")\n", "\n", "# Print the results in a formatted manner\n", "print(\"Ratio of NOT-preferred clips to total clips for each model:\")\n", "print(\"-\" * 60)\n", "for model, ratio in preference_ratio.items():\n", " n = clip_df[\"model_name\"].value_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": "2024-05-26T00:24:59.204547Z", "start_time": "2024-05-26T00:24:58.891851Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:43:41.295018Z", "iopub.status.busy": "2024-08-26T08:43:41.294859Z", "iopub.status.idle": "2024-08-26T08:43:41.627197Z", "shell.execute_reply": "2024-08-26T08:43:41.626720Z", "shell.execute_reply.started": "2024-08-26T08:43:41.295003Z" } }, "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": 47, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:59.207707Z", "start_time": "2024-05-26T00:24:59.205659Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:43:41.628008Z", "iopub.status.busy": "2024-08-26T08:43:41.627860Z", "iopub.status.idle": "2024-08-26T08:43:41.948600Z", "shell.execute_reply": "2024-08-26T08:43:41.948080Z", "shell.execute_reply.started": "2024-08-26T08:43:41.627994Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Summary of user_interesting_clips:\n", "Total requests: 695,416\n", "Unique clips: 347,708\n", "Fraction of total clips: 10.15%\n", "Time Validation:\n", "Earliest timestamp: 2024-08-24 18:30:00.219675+00:00\n", "Latest timestamp: 2024-08-26 07:39:52.655272+00:00\n", "Earliest timestamp: 2024-08-24 18:35:39.459246+00:00\n", "Latest timestamp: 2024-08-26 05:48:25.726440+00:00\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", "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": 48, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:00.484734Z", "start_time": "2024-05-26T00:25:00.377280Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:43:41.949399Z", "iopub.status.busy": "2024-08-26T08:43:41.949247Z", "iopub.status.idle": "2024-08-26T08:43:41.967827Z", "shell.execute_reply": "2024-08-26T08:43:41.967390Z", "shell.execute_reply.started": "2024-08-26T08:43:41.949384Z" } }, "outputs": [], "source": [ "# from 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)" ] }, { "cell_type": "code", "execution_count": 49, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:00.893917Z", "start_time": "2024-05-26T00:25:00.485775Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:43:41.968723Z", "iopub.status.busy": "2024-08-26T08:43:41.968575Z", "iopub.status.idle": "2024-08-26T08:43:45.011212Z", "shell.execute_reply": "2024-08-26T08:43:45.010609Z", "shell.execute_reply.started": "2024-08-26T08:43:41.968710Z" } }, "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\"] == True)\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": 50, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:01.140472Z", "start_time": "2024-05-26T00:25:00.895575Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:43:45.012150Z", "iopub.status.busy": "2024-08-26T08:43:45.011983Z", "iopub.status.idle": "2024-08-26T08:44:06.728578Z", "shell.execute_reply": "2024-08-26T08:44:06.728001Z", "shell.execute_reply.started": "2024-08-26T08:43:45.012134Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(695416, 47)\n", "Model Name Value Counts and Fractions:\n", "chirp-v3p5-engine-s-8: 551549 (79.31%)\n", "chirp-v3p5-engine-upload-4: 44476 (6.40%)\n", "chirp-v3p5-engine-s-24: 33883 (4.87%)\n", "chirp-v3p5-engine-t-2: 32438 (4.66%)\n", "chirp-v3p5-engine-t-2-10: 12629 (1.82%)\n", "chirp-v3p5-engine-t-2-12: 10687 (1.54%)\n", "chirp-v3p5-engine-t-2-13: 9210 (1.32%)\n", "chirp-v3p5-engine-b: 262 (0.04%)\n", "chirp-v3p5-engine-ft-1: 244 (0.04%)\n", "chirp-v3p5-engine-short: 38 (0.01%)\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 model_name.startswith(\"chirp-v3p5-engine-t\"):\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": 51, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:02.009450Z", "start_time": "2024-05-26T00:25:01.523515Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:44:06.729427Z", "iopub.status.busy": "2024-08-26T08:44:06.729274Z", "iopub.status.idle": "2024-08-26T08:44:09.497757Z", "shell.execute_reply": "2024-08-26T08:44:09.497224Z", "shell.execute_reply.started": "2024-08-26T08:44:06.729413Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "chirp-v3p5-engine-b_win_over_chirp-v3p5-engine-b, win ratio 1.000, counts 131\n", "chirp-v3p5-engine-ft-1_win_over_chirp-v3p5-engine-ft-1, win ratio 1.000, counts 122\n", "chirp-v3p5-engine-s-24_win_over_chirp-v3p5-engine-s-24, win ratio 1.000, counts 2\n", "chirp-v3p5-engine-s-24_win_over_chirp-v3p5-engine-s-8, win ratio 0.522, counts 17671\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-24, win ratio 0.478, counts 16208\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-8, win ratio 1.000, counts 240960\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-t-2, win ratio 0.591, counts 10533\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-t-2-10, win ratio 0.569, counts 3985\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-t-2-12, win ratio 0.593, counts 3467\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-t-2-13, win ratio 0.584, counts 2963\n", "chirp-v3p5-engine-short_win_over_chirp-v3p5-engine-short, win ratio 1.000, counts 19\n", "chirp-v3p5-engine-t-2-10_win_over_chirp-v3p5-engine-s-8, win ratio 0.431, counts 3013\n", "chirp-v3p5-engine-t-2-10_win_over_chirp-v3p5-engine-t-2, win ratio 0.511, counts 2880\n", "chirp-v3p5-engine-t-2-12_win_over_chirp-v3p5-engine-s-8, win ratio 0.407, counts 2383\n", "chirp-v3p5-engine-t-2-12_win_over_chirp-v3p5-engine-t-2, win ratio 0.518, counts 2505\n", "chirp-v3p5-engine-t-2-13_win_over_chirp-v3p5-engine-s-8, win ratio 0.416, counts 2113\n", "chirp-v3p5-engine-t-2-13_win_over_chirp-v3p5-engine-t-2, win ratio 0.512, counts 2118\n", "chirp-v3p5-engine-t-2_win_over_chirp-v3p5-engine-s-8, win ratio 0.409, counts 7293\n", "chirp-v3p5-engine-t-2_win_over_chirp-v3p5-engine-t-2, win ratio 1.000, counts 5\n", "chirp-v3p5-engine-t-2_win_over_chirp-v3p5-engine-t-2-10, win ratio 0.489, counts 2751\n", "chirp-v3p5-engine-t-2_win_over_chirp-v3p5-engine-t-2-12, win ratio 0.482, counts 2332\n", "chirp-v3p5-engine-t-2_win_over_chirp-v3p5-engine-t-2-13, win ratio 0.488, counts 2016\n", "chirp-v3p5-engine-upload-4_win_over_chirp-v3p5-engine-upload-4, win ratio 1.000, counts 22238\n" ] }, { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "get_preferfence_counts(user_intersting_clips_3p5)" ] }, { "cell_type": "code", "execution_count": 52, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:02.332947Z", "start_time": "2024-05-26T00:25:02.010694Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:44:09.498606Z", "iopub.status.busy": "2024-08-26T08:44:09.498451Z", "iopub.status.idle": "2024-08-26T08:44:12.138039Z", "shell.execute_reply": "2024-08-26T08:44:12.137462Z", "shell.execute_reply.started": "2024-08-26T08:44:09.498591Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "first gen\n", "chirp-v3p5-engine-b_win_over_chirp-v3p5-engine-b, win ratio 1.000, counts 103\n", "chirp-v3p5-engine-ft-1_win_over_chirp-v3p5-engine-ft-1, win ratio 1.000, counts 102\n", "chirp-v3p5-engine-s-24_win_over_chirp-v3p5-engine-s-24, win ratio 1.000, counts 2\n", "chirp-v3p5-engine-s-24_win_over_chirp-v3p5-engine-s-8, win ratio 0.539, counts 16352\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-24, win ratio 0.461, counts 13966\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-8, win ratio 1.000, counts 214819\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-t-2, win ratio 0.604, counts 9617\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-t-2-10, win ratio 0.581, counts 3671\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-t-2-12, win ratio 0.606, counts 3172\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-t-2-13, win ratio 0.594, counts 2681\n", "chirp-v3p5-engine-short_win_over_chirp-v3p5-engine-short, win ratio 1.000, counts 19\n", "chirp-v3p5-engine-t-2-10_win_over_chirp-v3p5-engine-s-8, win ratio 0.419, counts 2648\n", "chirp-v3p5-engine-t-2-10_win_over_chirp-v3p5-engine-t-2, win ratio 0.515, counts 2559\n", "chirp-v3p5-engine-t-2-12_win_over_chirp-v3p5-engine-s-8, win ratio 0.394, counts 2062\n", "chirp-v3p5-engine-t-2-12_win_over_chirp-v3p5-engine-t-2, win ratio 0.517, counts 2202\n", "chirp-v3p5-engine-t-2-13_win_over_chirp-v3p5-engine-s-8, win ratio 0.406, counts 1831\n", "chirp-v3p5-engine-t-2-13_win_over_chirp-v3p5-engine-t-2, win ratio 0.512, counts 1867\n", "chirp-v3p5-engine-t-2_win_over_chirp-v3p5-engine-s-8, win ratio 0.396, counts 6311\n", "chirp-v3p5-engine-t-2_win_over_chirp-v3p5-engine-t-2, win ratio 1.000, counts 5\n", "chirp-v3p5-engine-t-2_win_over_chirp-v3p5-engine-t-2-10, win ratio 0.485, counts 2411\n", "chirp-v3p5-engine-t-2_win_over_chirp-v3p5-engine-t-2-12, win ratio 0.483, counts 2058\n", "chirp-v3p5-engine-t-2_win_over_chirp-v3p5-engine-t-2-13, win ratio 0.488, counts 1779\n" ] }, { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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", 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" ] }, "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", "].copy()\n", "if first_gen_slice_df.shape[0] > 0:\n", " get_preferfence_counts(\n", " user_intersting_clips_3p5[\n", " (user_intersting_clips_3p5[\"continued_parent\"].isna())\n", " ],\n", " title_name=\"first generation\",\n", " )" ] }, { "cell_type": "code", "execution_count": 53, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:02.574659Z", "start_time": "2024-05-26T00:25:02.334214Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:44:12.138928Z", "iopub.status.busy": "2024-08-26T08:44:12.138771Z", "iopub.status.idle": "2024-08-26T08:44:12.761882Z", "shell.execute_reply": "2024-08-26T08:44:12.761340Z", "shell.execute_reply.started": "2024-08-26T08:44:12.138913Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "is continue\n", "chirp-v3p5-engine-b_win_over_chirp-v3p5-engine-b, win ratio 1.000, counts 28\n", "chirp-v3p5-engine-ft-1_win_over_chirp-v3p5-engine-ft-1, win ratio 1.000, counts 20\n", "chirp-v3p5-engine-s-24_win_over_chirp-v3p5-engine-s-8, win ratio 0.370, counts 1319\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-24, win ratio 0.630, counts 2242\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-8, win ratio 1.000, counts 26141\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-t-2, win ratio 0.483, counts 916\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-t-2-10, win ratio 0.462, counts 314\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-t-2-12, win ratio 0.479, counts 295\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-t-2-13, win ratio 0.500, counts 282\n", "chirp-v3p5-engine-t-2-10_win_over_chirp-v3p5-engine-s-8, win ratio 0.538, counts 365\n", "chirp-v3p5-engine-t-2-10_win_over_chirp-v3p5-engine-t-2, win ratio 0.486, counts 321\n", "chirp-v3p5-engine-t-2-12_win_over_chirp-v3p5-engine-s-8, win ratio 0.521, counts 321\n", "chirp-v3p5-engine-t-2-12_win_over_chirp-v3p5-engine-t-2, win ratio 0.525, counts 303\n", "chirp-v3p5-engine-t-2-13_win_over_chirp-v3p5-engine-s-8, win ratio 0.500, counts 282\n", "chirp-v3p5-engine-t-2-13_win_over_chirp-v3p5-engine-t-2, win ratio 0.514, counts 251\n", "chirp-v3p5-engine-t-2_win_over_chirp-v3p5-engine-s-8, win ratio 0.517, counts 982\n", "chirp-v3p5-engine-t-2_win_over_chirp-v3p5-engine-t-2-10, win ratio 0.514, counts 340\n", "chirp-v3p5-engine-t-2_win_over_chirp-v3p5-engine-t-2-12, win ratio 0.475, counts 274\n", "chirp-v3p5-engine-t-2_win_over_chirp-v3p5-engine-t-2-13, win ratio 0.486, counts 237\n", "chirp-v3p5-engine-upload-4_win_over_chirp-v3p5-engine-upload-4, win ratio 1.000, counts 22238\n" ] }, { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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T5qKSu7uLXny5kcVzOz5fR5J0LuaKRVFp66ZjGjVssbr0eEKvvNZCV6/c0KK5mzR/1u/Z/hphHcqXLyZJesTXQ8OGZ/w58tqgBbp8+VSWz9++/S+FhQWpXbtgubu7KD4+UXv3ntaC+Zt07B9LIn1KFFH37pa/s9x5vHt3lLmotH/faVWtWkqNG1dR0aIFlZqaptOn4/Tpp2u15C6dVABsh8mgPbNnzJihqVOnWoz1799f//3vfzM9/4cfftDBgwf17bff5kU8AFbClJ7+cGztfy+dSv8mKSnprpX1BzVnzhwFBgbK29tb58+f1/jx4yVJixYtuudr3Ckq/fTTT3Jz+/8NYD09PWVnl39WK95rUWn69OlKSEjQE088IS8vL/36668aN26cPv30UzVq1CjL561fv147d+5UQECA+vfvn6GodP36dQ0YMEAdO3aUv7+/rl27pjFjxig1NVXff/99tr6WZnYds3U+cL9MtasbHQH5RGoBm/qbFKyY3W87jY6AfGJN2mKjI2QppPuHhrzupun977lTKSYmRk8//bS++OIL+fv7S2KFA5BfWF2VIi0tTTNnzlSzZs0UEBCghg0bWrROnj59Wl27dlWNGjXUtm1b7dq1y3zs+++/V61atcyPp0yZonbt2mnx4sVq3Lixqle/PeHq2rWrRo0apVGjRqlmzZqqXbu2Pv74Y2VVX4uPj1f16tW1fv16i/E1a9YoKChIt27dkiS9+OKLCgwMVKlSpRQcHKxevXpp9+7dSk5Otsi3du1aNW/eXNWqVVOPHj0UExOT4TU9PT3l7e1t/vi3glJSUpIiIiJUv359BQYGqmPHjtq6dWuG782GDRvUsmVLBQUFqUePHrpw4YL5nJSUFL3//vuqVauWateurQkTJmjIkCHq16+f+ZyuXbta3MWhcePGmj59uoYNG6agoCA1bNhQX3/9tUW2mJgYDRw4ULVq1dJjjz2mvn376syZM1l+LUOHDlVkZKTmzp2rSpUqqVKlSlme36dPH7366qsKDg5W6dKl9cILL6h+/fr6+eef7/r9atCggQYNGqRmzZpletzd3V2zZ89Wq1atVK5cOQUGBurtt9/WgQMHFB0dfddrAwAAADnGoD2VnJyc5ObmZvGR1R/oDxw4oLi4OD311FOqUqWKqlSposjISM2bN09VqlRRampqzn9fAFgFqysqffDBB5o5c6b69eunVatWaeLEifLy8jIf/+ijj9SjRw8tXbpUZcqU0euvv66UlJQsr3fq1CmtXr1aU6dO1dKlS83jS5Yskb29vRYvXqwRI0Zozpw5Wrw4879QuLm5qWHDhlq5cqXF+IoVK9S0aVMVKJBxE80rV65oxYoVCgoKkqOjo3k8ISFB06ZNU0REhBYuXKhr165p0KBBGZ7fvn171atXTy+99JJ27NiR5dd3x6hRo7Rr1y599NFHWr58uVq0aKGePXvq5MmTFq/9xRdfaPz48Zo/f75iYmIUERFhPj5z5kytWLFC4eHh+uqrrxQfH6+1a9dm8mqWZs+erYCAAC1dulTPP/+83n33XZ04cULS7WVkPXr0UMGCBbVgwQItXLhQrq6u6tmzZ4a/fNwxYsQIBQUFqVOnTtq4caM2btwoHx+fTM/NzPXr11WkSJF7Pv9excfHy2QyqVChQjl+bQAAAOBhFRoaqhUrVmjp0qXmj4CAAIWFhWnp0qWyt7c3OiKAXGJVRaX4+HjNnTtXb7zxhjp06KDSpUurVq1a6tjx/5cPde/eXQ0bNlTZsmU1YMAAnT17VlFRWW9SmZycrPHjx6tKlSrmVkxJ8vHx0fDhw1WuXDm1bdtWXbp00Zw5c7K8Ttu2bbV27VpzV1J8fLx+++03hYWFWZw3YcIEBQYGqnbt2oqJidGnn36aIc/IkSMVFBSkgIAAjRs3Trt27dLevbc3lPX29tZ7772nyZMna/LkySpRooS6deumAweyvn12dHS0vv/+e02aNEm1atVS6dKl1aNHD9WsWdNiqVZycrLee+89VatWTVWrVlXnzp21ZcsW8/H58+erd+/eatasmcqXL6+RI0feUwHliSeeUOfOneXn56devXqpaNGi5i6pVatWKS0tTWPGjFGlSpVUvnx5hYeHKyYmRpGRmd/Byd3dXY6OjnJxcTF3at3rD6JVq1Zp3759euqpp+7p/HuVmJioiRMnqnXr1hbLEgEAAID8zs3NTRUrVrT4cHV1VZEiRVSxYkWj4wHIRVZVVDpx4oSSkpIUGhqa5TmVKlUyf35n4+pLly5leX7JkiXl4eGRYbxGjRoymf7/NtCBgYGKiopSamqqpk+frqCgIPNHdHS0nnjiCTk6OuqXX36RJK1evdq8efPf9ejRQ0uWLNEXX3whOzs7DRkyxGJZnYODg6pV+/87F5UvX16FChXS8ePHJUnlypXTs88+q4CAAAUHBys8PFxBQUHmgtfy5cstsm3fvl1Hjx5VamqqWrRoYXFs27ZtOnXq/zcULVCggEqXLm1+XKxYMcXFxUm63d1z8eJF8xJBSbK3t1fVqpZ3vsnM3/+bmEwmeXl5ma97+PBhnTp1SsHBweZctWvXVmJiok6dOqXt27dbZF6+fHmWr9O6dWvzeT179sxwfMuWLRo+fLjef/99VahQQZKydf2sJCcna+DAgUpPT9d7772X7ecDAAAA98uUbswHANwLq9pp09nZ+V/P+ftSsjtFobS0tCzPz2xp2r959tln1bJlS/PjYsWKycHBQU8++aRWrFih1q1ba+XKlWrVqlWGO6F5eHjIw8NDZcuWVfny5dWgQQPt3r1bQUFB2c5xR7Vq1bRz5+2NKhs3bqwaNWqYjxUvXly//PKL7O3t9d1332Xo6HF1dTV//s+sJpMpy32ksuNu171586aqVq2qiRMnZnieh4eHHB0dLZYlenp6Zvk6n332mXmpo4uLi8WxyMhI9e3bV8OGDVP79u3N43eW5d3L9TOTnJysV199VdHR0fryyy/pUgIAAADuwbx584yOACAPWFVRqUyZMnJxcdGWLVvk6+ubq691Z7nZHXv27JGfn5/s7e1VpEiRTPfkCQsLU/fu3XXs2DFt2bJFr7766l1f406x6+97B6WkpGj//v3mjqATJ07o2rVrKl++fJbXOXz4sLkr684meX9XuXJlpaam6tKlSxYblWeHu7u7vLy8tG/fPoWEhEiSUlNTdfDgQYtlg9lVtWpV/fjjj/L09MyyIOPn55dhzNHRMUOxsFSpUpk+f+vWrerTp48GDx6sZ555xuKYi4tLpte/F3cKSlFRUZo7d66KFi16X9cBAAAA7htdQwCsmFUVlZydndWrVy9NmDBBjo6OCg4O1qVLl3Ts2DHVqVMnR18rOjpa4eHheuaZZ3Tw4EHNnz9fQ4YMuetzQkJC5OXlpcGDB+uRRx6x6Bjas2eP9u3bp5o1a6pQoUI6deqUJk2apNKlS1t0KTk6Omr06NF66623ZG9vr9GjRyswMNBcZJozZ44eeeQRVahQQYmJiVq8eLG2bNmiL774IstcZcuWVVhYmN58800NHTpUlStX1uXLl7V582ZVqlRJDRs2vKfvSZcuXTRjxgyVLl1a5cqV0/z583X16lWLZYLZFRYWplmzZqlv374aOHCgihcvrujoaK1Zs0Y9e/ZUiRIlMn1eqVKltGfPHp05c8a8HjuzO+Bt2bJFffr0Ubdu3dS8eXPFxsZKuv19vttm3Tdu3LBYGnjmzBkdOnRIhQsXVsmSJZWcnKwBAwbo4MGDmjFjhlJTU83XLly4cJZ3vgCQtwJrlVHjJ6spoLqvvIoV0uW4eO3ecVJffvabLsXF39M1PL3d1Wdgc9V8rJxMdibt2XFS0yf9rHPRVyzOa9OhpgJrlZF/lVIqVqKwfv5hjya+n3FJbbXA0vrP83X0aMXiKlykoOLjE3T82DktmL1BB/dmfedLWL+gID81aVpV1QJ85eXtrkuX4rV7V5Rmz/5dly7duKdreHm5qW+/pqpVq6xMJpN2747StE/XKSbmivmcJ5+spjeHtMnyGmPHLNe6df+/12KjRpX1zLOh8vPz0s2bSdr8xzF99tmvunbt1n1/rQAAAPfCqopKktSvXz/Z29tr8uTJunDhgry9vfXss8/m+Ou0b99eCQkJ6tixo+zt7dWtW7cMXS7/ZDKZ1Lp1a33++ed65ZVXLI65uLjo559/1pQpU3Tz5k15e3urfv366tevn0UBwsXFRb169dLrr7+u8+fPq1atWhozZoz5eHJysiIiInT+/HkVKFBAFStW1OzZs++6z5QkhYeHa9q0aRo3bpwuXLigIkWKKDAw8J4LSpLUq1cvXbx4UUOGDJG9vb06deqkevXqPdDdGgoUKKD58+dr4sSJ6t+/v27cuKHixYurTp06d11K1r17dw0dOlStW7dWQkKC1q1bp0ceeSTDeUuXLtWtW7c0Y8YMzZgxwzz+2GOP3bXldv/+/erWrZv5cXh4uCSpQ4cOGjdunM6fP2/eP6tdu3YWz507d65q1659b98AALmqZ78mci9UQL//ckhnT8fJp1RRtf1PiGrXraC+3T7T5X+Z6LsUcNSEqV1V0M1ZC7/cqNTUND31TG198Gk39ek2U9f/Ninv1PVxubo66cjBaHl4Zf3vVylfD6WnpWvlkp26fClebu4uavJkNX3w6Qt6e/Aibd9yPMe+fuStXr0byd3dRb+vP6yzZy/Lx6eI2rWvqdA6j6p3ry90+fK/vN9cHPXBB51VsKCzvlrwh1JS0/T00yH68KPOern3F+Yi0N69pxU+NmPB8un/hKh8+eLaufOkeSysbZBefbWFduz4S9M+XSdvb3d1eKqWKlYqoVf6fankZG7jDQAAco8pPSc21XnIdO3aVf7+/hoxYkSevu7333+vsWPHavv27Xn6uvcrLS1NLVu2VMuWLf91qR+y1syu47+fBOQAU+3q/37SQ2bCJ111PuZqph1B0u2uoP17TunvP8mqBZbWB9Ne0FezN2jOZ7/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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "print(\"is continue\")\n", "get_preferfence_counts(\n", " user_intersting_clips_3p5[(~user_intersting_clips_3p5[\"continued_parent\"].isna())],\n", " \"is continue\",\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": 54, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:08.095035Z", "start_time": "2024-05-26T00:25:07.782738Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:44:12.762764Z", "iopub.status.busy": "2024-08-26T08:44:12.762606Z", "iopub.status.idle": "2024-08-26T08:44:14.172807Z", "shell.execute_reply": "2024-08-26T08:44:14.172231Z", "shell.execute_reply.started": "2024-08-26T08:44:12.762749Z" } }, "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": 55, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:08.361849Z", "start_time": "2024-05-26T00:25:08.199583Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:44:14.173704Z", "iopub.status.busy": "2024-08-26T08:44:14.173548Z", "iopub.status.idle": "2024-08-26T08:44:14.200691Z", "shell.execute_reply": "2024-08-26T08:44:14.200190Z", "shell.execute_reply.started": "2024-08-26T08:44:14.173690Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Positive proportion of data meeting criteria: 73.81%\n", "Negative proportion of data meeting criteria: 98.59%\n" ] } ], "source": [ "pos_too_much_data_mask = (\n", " (user_intersting_clips[\"preference\"])\n", " & (\n", " (\n", " user_intersting_clips[\"reaction_play_count\"] >= 2\n", " ) # single play is super catchy\n", " | (\n", " user_intersting_clips[\"concat_play_counts\"] >= 2\n", " ) # or the concat play is super catchy\n", " )\n", " & (user_intersting_clips[\"user_n_clips\"] >= 4)\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\"] >= 4)\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": 56, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:08.523643Z", "start_time": "2024-05-26T00:25:08.367348Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:44:14.201476Z", "iopub.status.busy": "2024-08-26T08:44:14.201330Z", "iopub.status.idle": "2024-08-26T08:44:17.196888Z", "shell.execute_reply": "2024-08-26T08:44:17.196299Z", "shell.execute_reply.started": "2024-08-26T08:44:14.201462Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Model Name Value Counts for Preferred Clips:\n", "----------------------------------------------------------------------\n", "Model Count Fraction\n", "----------------------------------------------------------------------\n", "chirp-v3p5-engine-s-8 205,204 79.95%\n", "chirp-v3p5-engine-upload-4 16,359 6.37%\n", "chirp-v3p5-engine-s-24 13,216 5.15%\n", "chirp-v3p5-engine-t-2 10,556 4.11%\n", "chirp-v3p5-engine-t-2-10 4,402 1.72%\n", "chirp-v3p5-engine-t-2-12 3,657 1.42%\n", "chirp-v3p5-engine-t-2-13 3,078 1.20%\n", "chirp-v3p5-engine-ft-1 93 0.04%\n", "chirp-v3p5-engine-b 79 0.03%\n", "chirp-v3p5-engine-short 6 0.00%\n", "----------------------------------------------------------------------\n", "Total 256,650 100.00%\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": 57, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:09.198504Z", "start_time": "2024-05-26T00:25:08.885507Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:44:17.197736Z", "iopub.status.busy": "2024-08-26T08:44:17.197582Z", "iopub.status.idle": "2024-08-26T08:44:18.490000Z", "shell.execute_reply": "2024-08-26T08:44:18.489412Z", "shell.execute_reply.started": "2024-08-26T08:44:17.197721Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Validation passed!\n" ] } ], "source": [ "validate_preference_data(final_interesting_clips)" ] }, { "cell_type": "code", "execution_count": 58, "metadata": { "execution": { "iopub.execute_input": "2024-08-26T08:44:18.490857Z", "iopub.status.busy": "2024-08-26T08:44:18.490696Z", "iopub.status.idle": "2024-08-26T08:44:18.630361Z", "shell.execute_reply": "2024-08-26T08:44:18.629854Z", "shell.execute_reply.started": "2024-08-26T08:44:18.490842Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of rows in final_interesting_clips for model chirp-v3p5-engine-t-2:\n", "23,901\n", "done (513300, 52)\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": 59, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:10.265241Z", "start_time": "2024-05-26T00:25:09.934743Z" }, "execution": { "iopub.execute_input": "2024-08-26T08:44:18.631163Z", "iopub.status.busy": "2024-08-26T08:44:18.631011Z", "iopub.status.idle": "2024-08-26T08:44:18.775668Z", "shell.execute_reply": "2024-08-26T08:44:18.775179Z", "shell.execute_reply.started": "2024-08-26T08:44:18.631143Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Total Unique Users:\n", "--------------------\n", "528,264\n", "--------------------\n", "Series([], Name: count, dtype: int64)\n", "(0, 42)\n" ] }, { "data": { "text/html": [ "
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idpasswordlast_loginis_superuserusernamefirst_namelast_nameemailis_staffis_activedate_joined
08pbkdf2_sha256$390000$Pj04K3OODhsKlkcmmVFNeI$1B...NoneFalsetongbaojia@gmail.comtongbaojia@gmail.comFalseTrue2023-04-29 15:44:31+00:00
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" ], "text/plain": [ " id password last_login is_superuser username first_name last_name email is_staff is_active date_joined\n", "0 8 pbkdf2_sha256$390000$Pj04K3OODhsKlkcmmVFNeI$1B... None False tongbaojia@gmail.com tongbaojia@gmail.com False True 2023-04-29 15:44:31+00:00" ] }, "execution_count": 59, "metadata": {}, "output_type": "execute_result" } ], "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=8\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": 60, "metadata": { "execution": { "iopub.execute_input": "2024-08-26T08:44:18.776486Z", "iopub.status.busy": "2024-08-26T08:44:18.776329Z", "iopub.status.idle": "2024-08-26T08:44:36.290111Z", "shell.execute_reply": "2024-08-26T08:44:36.289545Z", "shell.execute_reply.started": "2024-08-26T08:44:18.776471Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Shape of no_reaction_clip_df:\n", "(1573825, 42)\n", "\n", "Proportion of clips without reactions:\n", "24.03%\n", "Ratio of clips without reactions to total clips from the same users:\n", "0.8585\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "free 3023\n", "pro 1215\n", "Ratio of clips from super bad users: 1.28%\n", "DONE\n" ] } ], "source": [ "run_bot_detection(clip_df, reaction_df)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Alpha testing user selection" ] }, { "cell_type": "code", "execution_count": 61, "metadata": { "execution": { "iopub.execute_input": "2024-08-26T08:44:36.290996Z", "iopub.status.busy": "2024-08-26T08:44:36.290837Z", "iopub.status.idle": "2024-08-26T08:44:36.311601Z", "shell.execute_reply": "2024-08-26T08:44:36.311158Z", "shell.execute_reply.started": "2024-08-26T08:44:36.290980Z" } }, "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": { "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": 62, "metadata": { "execution": { "iopub.execute_input": "2024-08-26T08:44:36.312374Z", "iopub.status.busy": "2024-08-26T08:44:36.312226Z", "iopub.status.idle": "2024-08-26T08:44:36.978551Z", "shell.execute_reply": "2024-08-26T08:44:36.977919Z", "shell.execute_reply.started": "2024-08-26T08:44:36.312359Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "PROD\n" ] } ], "source": [ "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": 63, "metadata": { "execution": { "iopub.execute_input": "2024-08-26T08:44:36.979518Z", "iopub.status.busy": "2024-08-26T08:44:36.979361Z", "iopub.status.idle": "2024-08-26T08:44:37.236090Z", "shell.execute_reply": "2024-08-26T08:44:37.235502Z", "shell.execute_reply.started": "2024-08-26T08:44:36.979502Z" } }, "outputs": [], "source": [ "# select the df we want to squery for play counts\n", "subset_v4_clips_df = final_interesting_clips[\n", " final_interesting_clips[\"model_name\"] == target_model_name\n", "].copy()\n", "\n", "v4_clip_ids = list(str(s) for s in subset_v4_clips_df[\"id\"].unique())" ] }, { "cell_type": "code", "execution_count": 64, "metadata": { "execution": { "iopub.execute_input": "2024-08-26T08:44:37.240983Z", "iopub.status.busy": "2024-08-26T08:44:37.240603Z", "iopub.status.idle": "2024-08-26T08:44:47.868781Z", "shell.execute_reply": "2024-08-26T08:44:47.868117Z", "shell.execute_reply.started": "2024-08-26T08:44:37.240964Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ " 0%| | 0/1 [00:00" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Create a figure with two subplots\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[~subset_v4_clips_df_test[\"preference\"]][\n", " \"norm_play_frac\"\n", "]\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", "# Adjust layout and display the plot\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 68, "metadata": { "execution": { "iopub.execute_input": "2024-08-26T08:44:48.884401Z", "iopub.status.busy": "2024-08-26T08:44:48.884236Z", "iopub.status.idle": "2024-08-26T08:44:48.948914Z", "shell.execute_reply": "2024-08-26T08:44:48.948341Z", "shell.execute_reply.started": "2024-08-26T08:44:48.884385Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Fraction of clips that pass the play duration cut: 0.7561\n", "Number of unique requests passing play duration criteria: 18070\n", "Fraction of unique requests that pass play duration criteria: 0.7562\n" ] } ], "source": [ "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", ") | (\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", ")\n", "# Calculate the fraction of clips that pass the play duration cut\n", "frac_pass_play_duration = play_duration_mask.sum() / subset_v4_clips_df_test.shape[0]\n", "\n", "# Print the result with a formatted string\n", "print(\n", " f\"Fraction of clips that pass the play duration cut: {frac_pass_play_duration:.4f}\"\n", ")\n", "\n", "# Get unique request IDs that pass the play duration criteria\n", "unique_requests_pass_play_durations = subset_v4_clips_df_test[play_duration_mask][\n", " \"request_id\"\n", "].unique()\n", "\n", "# Print the number of unique requests that pass the play duration criteria\n", "print(\n", " f\"Number of unique requests passing play duration criteria: {len(unique_requests_pass_play_durations)}\"\n", ")\n", "\n", "# Calculate the fraction of unique requests that pass play duration criteria\n", "fraction_requests_pass = (\n", " len(unique_requests_pass_play_durations)\n", " / subset_v4_clips_df_test[\"request_id\"].nunique()\n", ")\n", "\n", "# Print the result with a formatted string\n", "print(\n", " f\"Fraction of unique requests that pass play duration criteria: {fraction_requests_pass:.4f}\"\n", ")" ] }, { "cell_type": "code", "execution_count": 69, "metadata": { "execution": { "iopub.execute_input": "2024-08-26T08:44:48.949785Z", "iopub.status.busy": "2024-08-26T08:44:48.949634Z", "iopub.status.idle": "2024-08-26T08:44:49.053194Z", "shell.execute_reply": "2024-08-26T08:44:49.052642Z", "shell.execute_reply.started": "2024-08-26T08:44:48.949771Z" } }, "outputs": [], "source": [ "subset_v4_clips_df_pass_duration = subset_v4_clips_df_test[play_duration_mask].copy()\n", "play_duration_mask_request_mask = subset_v4_clips_df_pass_duration[\"request_id\"].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()" ] }, { "cell_type": "code", "execution_count": 70, "metadata": { "execution": { "iopub.execute_input": "2024-08-26T08:44:49.054002Z", "iopub.status.busy": "2024-08-26T08:44:49.053854Z", "iopub.status.idle": "2024-08-26T08:44:49.088316Z", "shell.execute_reply": "2024-08-26T08:44:49.087762Z", "shell.execute_reply.started": "2024-08-26T08:44:49.053988Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of unique request IDs: 2, Total 23897\n" ] } ], "source": [ "# Count and print the number of unique request IDs\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", ")" ] }, { "cell_type": "code", "execution_count": 71, "metadata": { "execution": { "iopub.execute_input": "2024-08-26T08:44:49.089375Z", "iopub.status.busy": "2024-08-26T08:44:49.088990Z", "iopub.status.idle": "2024-08-26T08:44:49.112690Z", "shell.execute_reply": "2024-08-26T08:44:49.112135Z", "shell.execute_reply.started": "2024-08-26T08:44:49.089359Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(4, 63)\n" ] } ], "source": [ "# final_subset_v4_clips_df.to_pickle(\n", "# \"/home/tony/Data/Preference/30b_v1/interesting_clips_v4_t_2_20240812_full.pkl\",\n", "# )\n", "# 173256\n", "print(final_subset_v4_clips_df.shape)" ] }, { "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": "3.10.14" }, "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 }