{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "dfe43d4b", "metadata": {}, "outputs": [], "source": [ "import os\n", "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"\"" ] }, { "cell_type": "code", "execution_count": 2, "id": "6cfd5458", "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "from matplotlib import pyplot as plt" ] }, { "cell_type": "code", "execution_count": 3, "id": "52422f0d", "metadata": {}, "outputs": [], "source": [ "import math\n", "import numpy as np\n", "import tqdm\n", "import time\n", "import torch\n", "import funcy\n", "import json\n", "import gc\n", "import re\n", "import random\n", "import tempfile\n", "import collections\n", "import pandas as pd\n", "from suno_utils.utils.text import write_jsonl, read_jsonl, write_json, read_json, normalize_whitespace\n", "from suno_utils.utils.s3 import read_from_s3, check_s3_file_exists\n", "\n", "METAS_DIR = \"/app/suno/data/chirp_v4/metadata\"\n", "DATA_DIR = \"/app/suno/data/chirp_v4/multi\"" ] }, { "cell_type": "code", "execution_count": 4, "id": "989be1e7", "metadata": {}, "outputs": [], "source": [ "# randomly listen to some stuff\n", "from suno_utils.tasks.dac_2c_12cb import preload_models as preload_codec_models\n", "from suno_utils.tasks.dac_2c_12cb import (\n", " preload_models as preload_codec_models,\n", " encode as codec_encode,\n", " decode as codec_decode,\n", ")\n", "\n", "_ = preload_codec_models(\"/app/suno/data/chirp_v4/models/dac_2c_25x12.pt\")" ] }, { "cell_type": "code", "execution_count": 5, "id": "5a026189", "metadata": {}, "outputs": [], "source": [ "mm = np.memmap(os.path.join(DATA_DIR, \"data_tr.bin\"), dtype=np.uint16, mode=\"r\")\n", "mm = mm.reshape(-1, 6016, 13)\n", "metas = read_jsonl(os.path.join(DATA_DIR, \"metas_tr.jsonl\"))" ] }, { "cell_type": "code", "execution_count": 8, "id": "dd0d978d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "18G\t/app/suno/data/dpo/chirp_v4_multi/eval_2b_raw_bt28_tr/loss.jsonl\n", "90665991 /app/suno/data/dpo/chirp_v4_multi/eval_2b_raw_bt28_tr/loss.jsonl\n", "90972737 /app/suno/data/chirp_v4/multi/metas_tr.jsonl\n" ] } ], "source": [ "!du -hs /app/suno/data/dpo/chirp_v4_multi/eval_2b_raw_bt28_tr/loss.jsonl\n", "!wc -l /app/suno/data/dpo/chirp_v4_multi/eval_2b_raw_bt28_tr/loss.jsonl\n", "!wc -l /app/suno/data/chirp_v4/multi/metas_tr.jsonl" ] }, { "cell_type": "code", "execution_count": null, "id": "10529ca1", "metadata": {}, "outputs": [], "source": [ "# info = read_json(\"/app/suno/data/chirp_v4/multi/info_tr.json\")\n", "# n = 0\n", "# for k in info.keys():\n", "# if \"idx_list\" in info[k]:\n", "# n += len(info[k][\"idx_list\"])\n", "# else:\n", "# for k, v in info[k][\"idx_map\"].items():\n", "# n += 1 + len(v)\n", "# n\n", "# # 90665990" ] }, { "cell_type": "code", "execution_count": 14, "id": "73393fcb", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "90665991\n" ] }, { "data": { "text/html": [ "
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idxloss_semloss_sem_10sloss_sem_last_20sloss_sem_no_textloss_sem_no_text_10sloss_sem_no_text_last_20sloss_coarseloss_coarse_10sloss_coarse_last_20s...loss_coarse_2loss_coarse_3loss_coarse_4loss_coarse_5loss_coarse_6loss_coarse_7loss_coarse_8loss_coarse_9loss_coarse_10loss_coarse_11
002.453121.835942.437502.50002.265622.140625.333330.964684.52083...5.468755.50005.281255.406255.437505.468755.500005.468755.468755.50000
132.062500.000012.109382.06253.093752.093753.890620.000003.86979...4.031253.93753.781253.859383.968754.000004.156254.062504.031254.09375
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2 rows × 25 columns

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" ], "text/plain": [ " idx loss_sem loss_sem_10s loss_sem_last_20s loss_sem_no_text \\\n", "0 0 2.45312 1.83594 2.43750 2.5000 \n", "1 3 2.06250 0.00001 2.10938 2.0625 \n", "\n", " loss_sem_no_text_10s loss_sem_no_text_last_20s loss_coarse \\\n", "0 2.26562 2.14062 5.33333 \n", "1 3.09375 2.09375 3.89062 \n", "\n", " loss_coarse_10s loss_coarse_last_20s ... loss_coarse_2 loss_coarse_3 \\\n", "0 0.96468 4.52083 ... 5.46875 5.5000 \n", "1 0.00000 3.86979 ... 4.03125 3.9375 \n", "\n", " loss_coarse_4 loss_coarse_5 loss_coarse_6 loss_coarse_7 loss_coarse_8 \\\n", "0 5.28125 5.40625 5.43750 5.46875 5.50000 \n", "1 3.78125 3.85938 3.96875 4.00000 4.15625 \n", "\n", " loss_coarse_9 loss_coarse_10 loss_coarse_11 \n", "0 5.46875 5.46875 5.50000 \n", "1 4.06250 4.03125 4.09375 \n", "\n", "[2 rows x 25 columns]" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "metas_loss = read_jsonl(\n", " \"/app/suno/data/dpo/chirp_v4_multi/eval_2b_raw_bt28_tr/loss.jsonl\"\n", ")\n", "print(len(metas_loss))\n", "loss_df = pd.DataFrame(metas_loss[1:], columns=metas_loss[0])\n", "del metas_loss\n", "gc.collect()\n", "loss_df.head(2)" ] }, { "cell_type": "code", "execution_count": 79, "id": "b1909e3d", "metadata": {}, "outputs": [], "source": [ "loss_df[\"n_lyrics_chars\"] = [len(metas[idx].get(\"text\", \"\")) for idx in loss_df[\"idx\"].values]\n", "loss_df[\"n_tags\"] = [len(metas[idx].get(\"tags\", [])) for idx in loss_df[\"idx\"].values]" ] }, { "cell_type": "code", "execution_count": 113, "id": "fc08073d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'dataset': 'youtube_music_lyrics',\n", " 'task': 'default',\n", " 'id': 'H6iYuHu0K7g',\n", " 'start_s': 0.0,\n", " 'end_s': 230.0,\n", " 'original_duration_s': 230.0,\n", " 'vocal_start_s': None,\n", " 'vocal_end_s': None,\n", " 'tags': ['country & americana', 'feel good'],\n", " 'text': \"Now they tell me the streets of heaven\\nAre paved with diamonds & gold\\nI may not get there but if I do\\nI believe I gonna take off my shoes\\n\\nGonna walk around heaven\\nGonna walk around heaven\\nBarefooted singing God's praise\\nGonna walk around heaven\\nGonna walk around heaven\\nWhere there ain't no end of days\\n\\nAin't a secret if you know me\\nI been no account most of my life\\nBut I been converted and now I got the spirit\\nSo there's a chance I gonna see this paradise\\n\\nWhen I get to heaven preachers tell me\\nI get a halo some wings and a harp\\nThat's well and good\\nBut what I do hear\\nIs Sister Rosetta Tharpe\",\n", " 'text_lang': 'en',\n", " 'n_tokens': 5750}" ] }, "execution_count": 113, "metadata": {}, "output_type": "execute_result" } ], "source": [ "metas[0]" ] }, { "cell_type": "code", "execution_count": 109, "id": "3fc4e914", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 109, "metadata": {}, "output_type": "execute_result" }, { "data": { 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "(loss_df[\"loss_sem_no_text\"]-loss_df[\"loss_sem\"]).clip(-1,2).hist(bins=50)" ] }, { "cell_type": "code", "execution_count": 119, "id": "2302caa1", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 119, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "(\n", " loss_df[\n", " (loss_df[\"n_lyrics_chars\"] == 0) & (loss_df[\"n_tags\"] >= 1)\n", " ][\"loss_sem_no_text\"]-\n", " loss_df[\n", " (loss_df[\"n_lyrics_chars\"] == 0) & (loss_df[\"n_tags\"] >= 1)\n", " ][\"loss_sem\"]\n", ").clip(-0.25,0.5).hist(bins=50)" ] }, { "cell_type": "code", "execution_count": 120, "id": "6a79654b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 120, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "(\n", " loss_df[loss_df[\"n_lyrics_chars\"] >= 100][\"loss_sem_no_text\"]-\n", " loss_df[loss_df[\"n_lyrics_chars\"] >= 100][\"loss_sem\"]\n", ").clip(-0.5,1).hist(bins=50)" ] }, { "cell_type": "code", "execution_count": 92, "id": "60eaaa21", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(573185, 27)" ] }, "execution_count": 92, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# find entries with long lyrics that don't seem to help\n", "df = loss_df[\n", " (loss_df[\"n_lyrics_chars\"] >= 100) &\n", " ((loss_df[\"loss_sem_no_text\"]-loss_df[\"loss_sem\"]) <= 0)\n", "]\n", "df.shape" ] }, { "cell_type": "code", "execution_count": 110, "id": "823df08e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "4787249\n" ] }, { "data": { "text/html": [ "\n", "\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "row = df.sample(1).iloc[0]\n", "idx = int(row[\"idx\"])\n", "print(idx)\n", "arr = mm[idx][:,1:].astype(np.int32)\n", "arr = arr[:np.where(arr[:,0] != 2048)[0][-1], :]\n", "codec_decode(arr[:25*60,:]).play()" ] }, { "cell_type": "code", "execution_count": 111, "id": "123e201e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2.23438\n", "2.26562\n", "-0.031\n" ] } ], "source": [ "print(round(row[\"loss_sem_no_text\"], 5))\n", "print(round(row[\"loss_sem\"], 5))\n", "print(round(row[\"loss_sem_no_text\"] - row[\"loss_sem\"], 3))" ] }, { "cell_type": "code", "execution_count": 112, "id": "ac7356f7", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'dataset': 'genius_hq_lyrics',\n", " 'task': 'default',\n", " 'id': '47c24449-f479-4900-bf22-68b8bdfe8fe1',\n", " 'start_s': 0.0,\n", " 'end_s': 137.92,\n", " 'original_duration_s': 137.92,\n", " 'vocal_start_s': None,\n", " 'vocal_end_s': None,\n", " 'original_id': 'Late-of-the-pier-random-firl-lyrics',\n", " 'artist': 364428,\n", " 'tags': ['Alternative Dance',\n", " 'Electronica',\n", " 'Indie Electronic',\n", " 'UK',\n", " 'Rock',\n", " 'Alternative',\n", " 'British Rock'],\n", " 'text': \"Lately\\nI've been thinking this whole world seems too hard\\nAnd I'd be better off to undo everything\\nBut maybe\\nIt was only the sun behind the clouds\\nThat was making everything seem nasty\\n\\nBehind the clouds it's lovely\\nBehind the clouds it's lovely\\nBehind the clouds\",\n", " 'text_lang': 'en',\n", " 'n_tokens': 3448}" ] }, "execution_count": 112, "metadata": {}, "output_type": "execute_result" } ], "source": [ "metas[idx]" ] }, { "cell_type": "code", "execution_count": null, "id": "7d4d60af", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "8fe8e408", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "d295c02b", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "06f796a5", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "1c320514", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "c760d1c8", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "f0906c0d", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "id": "9bd1d5a5", "metadata": {}, "source": [ "## Playground" ] }, { "cell_type": "code", "execution_count": null, "id": "2a3a95b2", "metadata": {}, "outputs": [], "source": [ "# filter to \n", "# duration >= 10s\n", "# loss_sem <= 7.5\n", "# loss_coarse <= 8" ] }, { "cell_type": "code", "execution_count": null, "id": "62c8d9bf", "metadata": {}, "outputs": [], "source": [ "## general loss here indicative of 'hard' but probably lots of bias\n", "# df[\"loss_coarse_10s\"].hist(bins=50)\n", "# filter to <= 5" ] }, { "cell_type": "code", "execution_count": null, "id": "e12bdd94", "metadata": {}, "outputs": [], "source": [ "## general loss here indicative of 'easy' (confounded with duration but we don't want short anyways)\n", "# df[\"loss_coarse_10s\"].hist(bins=50)\n", "# filter to >= 1.5" ] }, { "cell_type": "code", "execution_count": 26, "id": "3f58e3a5", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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4mpub45RTTolhw4Z1/HnggQe6aj4AoIqU/FAIAEAh3isEAEhGWAAAyQgLACAZYQEAJCMsAIBkhAUAkIywAACSERYAQDLCAgBIRlgAAMkICwAgGWEBACQjLACAZIQFAJCMsAAAkhEWAEAywgIASEZYAADJCAsAIBlhAQAkIywAgGSEBQCQjLAAAJIRFgBAMsICAEhGWAAAyQgLACAZYQEAJCMsAIBkhAUAkIywAACSERYAQDLCAgBIRlgAAMkICwAgGWEBACQjLACAZIQFAJCMsAAAkhEWAEAywgIASEZYAADJCAsAIBlhAQAkIywAgGSEBQCQjLAAAJIRFgBAMsICAEhGWAAAyQgLACAZYQEAJCMsAIBkhAUAkIywAACSERYAQDLCAgBIRlgAAMkICwAgGWEBACQjLACAZIQFAJCMsAAAkik5LJYvXx7Tpk2LhoaGqKmpiYceeqgLxgIAqlHJYbFt27YYM2ZMLFq0qCvmAQCqWM9SP2HKlCkxZcqUrpgFAKhyJYdFqbLZbGSz2Y7LLS0tERGRy+Uil8slu53t15Xpkd+t8/Y127/uffXr3xX7Kc5+CrOb4uynuGraz+7OWJPP54v/JC72yTU1sWTJkjjzzDMLnjNv3ryYP39+p+ONjY3Rt2/fPb1pAGAvam1tjenTp0dzc3PU19cXPK/Lw2Jn91gMHz48Nm/eXHSwUuVyuWhqaoq5q3pEtr2m4Hnr5k1OdpvVZPt+Jk2aFHV1deUep+LYT3H2U5jdFGc/xVXTflpaWmLw4MG7DIsufygkk8lEJpPpdLyurq5Llphtr4lsW+GwqPS/uK7WVXvvLuynOPspzG6Ks5/iqmE/uzuf32MBACRT8j0WW7dujVdeeaXj8oYNG2Lt2rUxcODAGDFiRNLhAIDqUnJYrFq1Kk499dSOy3PmzImIiJkzZ8a9996bbDAAoPqUHBannHJKfIznewIA3ZjnWAAAyQgLACAZYQEAJCMsAIBkhAUAkIywAACSERYAQDLCAgBIRlgAAMkICwAgGWEBACQjLACAZIQFAJCMsAAAkhEWAEAywgIASEZYAADJCAsAIBlhAQAkIywAgGSEBQCQjLAAAJIRFgBAMsICAEhGWAAAyQgLACAZYQEAJNOz3ANQWT552f/t8px/XjN1L0wCQDUSFvuYo+Y9Edm2mnKPAUA35aEQACAZYQEAJCMsAIBkPMeCknmCJwCFuMcCAEhGWAAAyXgopJvY1cMTmdp8XDduLw0DwD7LPRYAQDLCAgBIRlgAAMkICwAgGWEBACTjVSFVYHd+IRUAVAJhQZfw2zkB9k0eCgEAkhEWAEAywgIASEZYAADJCAsAIBlhAQAk4+WmZeZ3VADQnQgLysbvugDofjwUAgAkIywAgGSEBQCQjLAAAJIRFgBAMl4V0oW8lBSAfY2woKJ5SSpAdfFQCACQjLAAAJIRFgBAMp5jQdXzPAyAyrFHYbFo0aK4/vrrY+PGjTFmzJi45ZZbYty4calnq2he8QEAnZUcFg888EDMmTMnbrvtthg/fnzcdNNNMXny5Fi/fn0MGTKkK2aEj21XIZipzcd1+1YbA3SJkp9jceONN8b3v//9OP/882PUqFFx2223Rd++fePuu+/uivkAgCpS0j0WH374YaxevTouv/zyjmM9evSIiRMnxrPPPrvTz8lms5HNZjsuNzc3R0TEe++9F7lcbk9m3qlcLhetra3RM9cj2tprCp737rvv7vK6xi98apfnVNuTU3q256O1tX2X+9lXbd/PMT/9bWSL7Oe5y0/bi1NVju3/f7377rtRV1dX7nEqit0UZz/FVdN+tmzZEhER+Xy+6Hkl/XzcvHlztLW1xUEHHbTD8YMOOij+9re/7fRzFi5cGPPnz+90fOTIkaXcdDKDbyjLzVaE6eUeoMLtzn725f9+ACL+ExgDBgwo+PEu/4f35ZdfHnPmzOm43N7eHu+9914MGjQoamrS/cu5paUlhg8fHq+//nrU19cnu97uwn6Ks5/i7KcwuynOfoqrpv3k8/nYsmVLNDQ0FD2vpLAYPHhw1NbWxttvv73D8bfffjuGDh2608/JZDKRyWR2OLb//vuXcrMlqa+vr/i/nHKyn+Lspzj7KcxuirOf4qplP8XuqdiupCdv9urVK44//vh46qn/Pgehvb09nnrqqZgwYULpEwIA3UrJD4XMmTMnZs6cGWPHjo1x48bFTTfdFNu2bYvzzz+/K+YDAKpIyWHxzW9+M95555244oorYuPGjXHMMcfE448/3ukJnXtbJpOJK6+8stPDLvyH/RRnP8XZT2F2U5z9FNcd91OT39XrRgAAdpM3IQMAkhEWAEAywgIASEZYAADJdJuwWLRoUXzyk5+M3r17x/jx4+P5558v90gVYeHChXHCCSdE//79Y8iQIXHmmWfG+vXryz1WRbrmmmuipqYmZs+eXe5RKsYbb7wR3/72t2PQoEHRp0+fOProo2PVqlXlHqsitLW1xdy5c2PkyJHRp0+fOPTQQ+NnP/vZLt9Hobtavnx5TJs2LRoaGqKmpiYeeuihHT6ez+fjiiuuiGHDhkWfPn1i4sSJ8fLLL5dn2DIotp9cLheXXnppHH300dGvX79oaGiI8847L958883yDfwxdIuw2P5W7ldeeWWsWbMmxowZE5MnT45NmzaVe7SyW7ZsWcyaNStWrFgRTU1Nkcvl4vTTT49t27aVe7SKsnLlyrj99ttj9OjR5R6lYvz73/+Ok046Kerq6uKxxx6LF198MW644YY44IADyj1aRbj22mtj8eLFceutt8Zf//rXuPbaa+O6666LW265pdyjlcW2bdtizJgxsWjRop1+/Lrrroubb745brvttnjuueeiX79+MXny5Pjggw/28qTlUWw/ra2tsWbNmpg7d26sWbMmfvvb38b69evjjDPOKMOkCeS7gXHjxuVnzZrVcbmtrS3f0NCQX7hwYRmnqkybNm3KR0R+2bJl5R6lYmzZsiV/2GGH5ZuamvJf/OIX8xdddFG5R6oIl156af7kk08u9xgVa+rUqfkLLrhgh2Nf//rX8zNmzCjTRJUjIvJLlizpuNze3p4fOnRo/vrrr+849v777+czmUz+V7/6VRkmLK+P7mdnnn/++XxE5F999dW9M1RCVX+Pxfa3cp84cWLHsV29lfu+bPvb1g8cOLDMk1SOWbNmxdSpU3f4b4iIRx55JMaOHRtnn312DBkyJI499ti48847yz1WxTjxxBPjqaeeipdeeikiIv70pz/FM888E1OmTCnzZJVnw4YNsXHjxh3+HxswYECMHz/e9+kCmpubo6ampkvfW6urdPm7m3a1PXkr931Ve3t7zJ49O0466aQ46qijyj1ORbj//vtjzZo1sXLlynKPUnH+8Y9/xOLFi2POnDnxk5/8JFauXBk/+tGPolevXjFz5sxyj1d2l112WbS0tMQRRxwRtbW10dbWFgsWLIgZM2aUe7SKs3HjxoiInX6f3v4x/uuDDz6ISy+9NM4999yqeGOyj6r6sGD3zZo1K9atWxfPPPNMuUepCK+//npcdNFF0dTUFL179y73OBWnvb09xo4dG1dffXVERBx77LGxbt26uO2224RFRPz617+O++67LxobG+PII4+MtWvXxuzZs6OhocF+2GO5XC7OOeecyOfzsXjx4nKPs0eq/qGQPXkr933RhRdeGI8++mg8/fTTcfDBB5d7nIqwevXq2LRpUxx33HHRs2fP6NmzZyxbtixuvvnm6NmzZ7S1tZV7xLIaNmxYjBo1aodjn/3sZ+O1114r00SV5cc//nFcdtll8a1vfSuOPvro+M53vhMXX3xxLFy4sNyjVZzt34t9ny5ue1S8+uqr0dTUVJX3VkR0g7DwVu7F5fP5uPDCC2PJkiXx+9//PkaOHFnukSrGaaedFi+88EKsXbu248/YsWNjxowZsXbt2qitrS33iGV10kkndXpp8ksvvRSHHHJImSaqLK2trdGjx47fQmtra6O9vb1ME1WukSNHxtChQ3f4Pt3S0hLPPfec79P/3/aoePnll+PJJ5+MQYMGlXukPdYtHgrxVu6FzZo1KxobG+Phhx+O/v37dzyeOWDAgOjTp0+Zpyuv/v37d3quSb9+/WLQoEGegxIRF198cZx44olx9dVXxznnnBPPP/983HHHHXHHHXeUe7SKMG3atFiwYEGMGDEijjzyyPjjH/8YN954Y1xwwQXlHq0stm7dGq+88krH5Q0bNsTatWtj4MCBMWLEiJg9e3ZcddVVcdhhh8XIkSNj7ty50dDQEGeeeWb5ht6Liu1n2LBh8Y1vfCPWrFkTjz76aLS1tXV8rx44cGD06tWrXGPvmXK/LCWVW265JT9ixIh8r1698uPGjcuvWLGi3CNVhIjY6Z977rmn3KNVJC833dHvfve7/FFHHZXPZDL5I444In/HHXeUe6SK0dLSkr/ooovyI0aMyPfu3Tv/qU99Kv/Tn/40n81myz1aWTz99NM7/V4zc+bMfD7/n5eczp07N3/QQQflM5lM/rTTTsuvX7++vEPvRcX2s2HDhoLfq59++ulyj14yb5sOACRT9c+xAAAqh7AAAJIRFgBAMsICAEhGWAAAyQgLACAZYQEAJCMsAIBkhAUAkIywAACSERYAQDLCAgBI5v8BmOXD58bZ2i0AAAAASUVORK5CYII=", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "loss_df[\"loss_sem_last_20s\"].hist(bins=50)" ] }, { "cell_type": "code", "execution_count": 66, "id": "8bb48572", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 66, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "(loss_df[\"loss_coarse_no_text\"]-loss_df[\"loss_coarse\"]).clip(-0.25,0.25).hist(bins=50)" ] }, { "cell_type": "code", "execution_count": 67, "id": "8bbea234", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1.7 %\n" ] }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "(loss_df[\"loss_coarse_no_text\"]-loss_df[\"loss_coarse\"]).clip(-0.25,0.25).hist(bins=50)\n", "loss_df[\"h\"] = loss_df[\"loss_coarse_no_text\"]-loss_df[\"loss_coarse\"]\n", "print(round((loss_df[\"h\"]<=-0.05).mean()*100, 2), \"%\")\n", "df = loss_df[loss_df[\"h\"]<=-0.05]" ] }, { "cell_type": "code", "execution_count": 68, "id": "fb95d2a0", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "81220534\n" ] }, { "data": { "text/html": [ "\n", "\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "row = df.sample(1).iloc[0]\n", "idx = int(row[\"idx\"])\n", "print(idx)\n", "arr = mm[idx][:,1:].astype(np.int32)\n", "arr = arr[:np.where(arr[:,0] != 2048)[0][-1], :]\n", "codec_decode(arr[:25*60,:]).play()" ] }, { "cell_type": "code", "execution_count": 69, "id": "8eea9b6f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'dataset': 'discogs_lyrics_foreign',\n", " 'task': 'default',\n", " 'id': '0SUOhDMEIVs',\n", " 'start_s': 0.0,\n", " 'end_s': 129.24,\n", " 'original_duration_s': 129.24,\n", " 'vocal_start_s': None,\n", " 'vocal_end_s': None,\n", " 'artist': 'UCiZqWydpRrU3Nh2yTvylt7g',\n", " 'text': 'Tra gli scaffali dell\\'Eurospin\\nSuper offerte, super zingari\\nVedimi amor, non devi abbatterti\\nSe ad occhi chiusi hai ancora gli incubi\\nSiamo stracci e inchiostro, lividi\\nDal sole che ti mitraglia lentiggini\\nPotresti avere di meglio\\nInvece resti qui con queste mani sui tuoi zigomi\\n\\nE non chiudere gli occhi se non vuoi stare male\\nAbbiamo ancora due soldi, moriremo di fame\\nProveremo a mangiare dieci K di cose\\nIo volevo soltanto giocare a pallone\\n\\nE adesso invece non ci gioco più\\nAdesso invece non ci gioco più\\n\\nMa quanto è arrogante questa matita\\nChe scrive le cose che penso su com\\'è la vita\\nMe ne sono fatto una ragione\\nMa ci penso spesso a una vita normale\\nSarebbe bello guardare le cose\\nPoterle comprare o farmi arrestare\\nSarebbe bello e invece no\\nNon è così, palazzi in fiamme ed Eurospin\\nMi guardi e gridi: \"Amami\"\\n\\nE non chiudere gli occhi se ti fa stare male\\nAbbiamo ancora due sogni, moriremo di fame\\nGuarderemo cadere un decennio di cose\\nIo volevo soltanto fare l\\'amore\\n\\nE adesso invece non lo faccio più\\nE adesso invece non lo faccio più',\n", " 'text_lang': 'it',\n", " 'n_tokens': 3231}" ] }, "execution_count": 69, "metadata": {}, "output_type": "execute_result" } ], "source": [ "metas[idx]" ] }, { "cell_type": "code", "execution_count": 70, "id": "1f4417eb", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.312\n", "-0.09\n" ] } ], "source": [ "print(round(row[\"loss_sem_no_text\"] - row[\"loss_sem\"], 3))\n", "print(round(row[\"loss_coarse_no_text\"] - row[\"loss_coarse\"], 3))" ] }, { "cell_type": "code", "execution_count": 65, "id": "4726a4ff", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "-0.016\n", "0.007\n" ] } ], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "5c8a7872", "metadata": {}, "outputs": [], "source": [ "- loss filter -- TODOs: figure out issues and thresholds\n", "- dataset weights/filters -- TODOs: decide on general weights for different datasets\n", "- gpt (minz) tags -- TODOs: replace? metadata in existing files (maybe fulltext but not aligned)\n", "- rate your music data -- TODOs: merge tags into existing metadata\n", "- more hoot aligned data -- TODOs: tony working on it\n", "- midi -- TODOs: turn dataset into mp3s, make into bundle and embed (assign task?)\n", "- control tags for tasks -- TODOs: pseudolabel tasks in cover dataset and turn into control tags\n", "- hooktheory -- TODOs: figure out chord-midi to text\n", "- quality/bpm pseudotags -- TODOs: need new stratified bundle and modal embed" ] }, { "cell_type": "code", "execution_count": null, "id": "d2340ba8", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "0eee5248", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "b9105f37", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 119, "id": "6290b91a", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 119, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(10, 4))\n", "plt.subplot(1,2,1)\n", "df[\"loss_sem_10s\"].hist(bins=50)\n", "plt.subplot(1,2,2)\n", "df[\"loss_sem_no_text_10s\"].hist(bins=50)" ] }, { "cell_type": "code", "execution_count": 110, "id": "39158984", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 110, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(10, 4))\n", "plt.subplot(1,2,1)\n", "df[\"loss_sem_10s\"].hist(bins=50)\n", "plt.subplot(1,2,2)\n", "df[\"loss_sem_no_text_10s\"].hist(bins=50)" ] }, { "cell_type": "code", "execution_count": 117, "id": "9f52f267", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 117, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(10, 4))\n", "plt.subplot(1,2,1)\n", "df[\"loss_sem\"].hist(bins=50)\n", "plt.subplot(1,2,2)\n", "df[\"loss_sem_no_text\"].hist(bins=50)" ] }, { "cell_type": "code", "execution_count": null, "id": "bc3225f0", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "9f9a6b76", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 136, "id": "2434f761", "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "11.22 %\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "df[\"loss_sem_10s\"].hist(bins=50)\n", "df[\"h\"] = df[\"loss_sem_10s\"]\n", "print(round((df[\"h\"]>=10).mean()*100, 2), \"%\")\n", "sub_df = df[df[\"h\"]>=10]" ] }, { "cell_type": "code", "execution_count": 144, "id": "7457bb42", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[6172965, 3795978, 65232958, 5747007, 84362693, 88885091, 88442691, 5216295, 1939647, 4933145, 81288692, 85448656, 3223384, 3310399, 47676734, 31668338, 3738205, 65524606, 44067377, 38689961, 28629664, 3512916, 33366326, 5628826, 77419723, 4168740, 88633688, 18204268, 5610594, 19084348, 74501451, 3344489, 67591084, 73066699, 5660462, 13509938, 22421811, 85273063, 42156280, 37003360, 71017642, 4901935, 13363526, 5776886, 4047972, 6107428, 19956831, 6098375, 3991024, 26846839, 55718234, 54479199, 3925080, 18972292, 3120261, 72503260, 86873267, 61547649, 78525370, 39532096, 44401848, 3293046, 17488131, 58621043, 68447302, 25557147, 39332691, 23150923, 62198916, 14838093, 5593600, 81787074, 15700986, 72448495, 5208310, 9447455, 9393028, 6401018, 39787032, 33023267, 5797147, 3122451, 43256104, 64171882, 25260880, 82130343, 39910582, 15031588, 88913, 16265509, 75372762, 3890825, 59643819, 3125759, 23792285, 49422935, 5005135, 5305334, 6368146, 9483969]\n" ] } ], "source": [ "print(sub_df.sample(100)[\"idx\"].tolist())" ] }, { "cell_type": "code", "execution_count": 137, "id": "9d0e90c4", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "70858415\n" ] }, { "data": { "text/html": [ "\n", "\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "row = sub_df.sample(1).iloc[0]\n", "idx = int(row[\"idx\"])\n", "print(idx)\n", "arr = mm[idx][:,1:].astype(np.int32)\n", "arr = arr[:np.where(arr[:,0] != 2048)[0][-1], :]\n", "codec_decode(arr[:25*60,:]).play()" ] }, { "cell_type": "code", "execution_count": 138, "id": "412cc635", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'dataset': 'discogs_lyrics_foreign',\n", " 'task': 'default',\n", " 'id': 'o2BipLvoWpw',\n", " 'start_s': 0.0,\n", " 'end_s': 116.8,\n", " 'original_duration_s': 116.8,\n", " 'vocal_start_s': None,\n", " 'vocal_end_s': None,\n", " 'artist': 'UCumucBkBKYHg42bdnSLhDfg',\n", " 'text': \"Yeah\\nMilion+\\nOhh, ohh, yeah, ohh, yeah, ohh\\nRobin Zoot, ay, ay\\nPořád za Sudety (Aussig)\\nMý boys to to-točej jako ruletu (yeah, yeah)\\nChci love, ko-ko-kód\\nK tomu spokojenej bejt (ay)\\nA ty si mě neptej, co bude zítra, babe, ay\\nPořád jsem dole jako Texas (dole)\\nMý heslo: Se s tím nesrat (ne, ne)\\nUmim v tom jezdit, Lexus (brrmm)\\nSorry baby žiju dneska (dnes)\\nPeniaze daj do vrecky (davaj)\\nZbytek na osud nech už (yeah, yeah, yeah)\\nA zdravím svoje ex\\nNemyslim ty kurvy\\nAle panáky, co exnul 'sem (ha, ha)\\nTěším se do nebe (yes)\\nAž nepotkám ty křivý kurvy, co se měl kolem (sebe)\\nVe svý ruce držím drink, ay\\nDJ hraje můj song (skrrt)\\nNa mym krku její rty, ay\\nDělat rap je můj sport\\nMy nejsme kdo? bloggeři, ayy\\nBlogger má jenom blog\\nNám patří celý měšto\\nZbytek ještě támhleten rok\\nVe svý ruce držím driink\\nDJ hraje můj song\\nNa mym krku její rtyy\\nRap je můj sport\\nMy nejsme kdo? bloggeři (ne, ne)\\nBlogger má jenom blok\\nNám patří celý měšto (patří)\\nZbytek ještě tenhleten rok (ha)\\nMiluju počítat, (ay, ay) ay\\nBureše a talíře, (oh, oh) oh\\nTy mrtvý ksichty (na, na, na, na, na)\\nNa-na barevnejch papírech\\nUhh, yeah, uhh\\nBaby rozbalím si Tě, jak dárek, uhh\\nMý tělo je plný zakázanejch látek, ay\\nZaká-za-nej budu já až mě ukážeš mámě, ay\\nTvůj life jako dia\\nDo kina chodím s šáňem, ay\",\n", " 'text_lang': 'cs',\n", " 'n_tokens': 2920}" ] }, "execution_count": 138, "metadata": {}, "output_type": "execute_result" } ], "source": [ "metas[idx]" ] }, { "cell_type": "code", "execution_count": null, "id": "e41df224", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "f82c6e85", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "2a099896", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 148, "id": "daa2cf66", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 148, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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1coXFjTfeGPv27et37K677opLL700Pv/5zw+ICgDg10uusGhoaIj58+f3O3b22WfHtGnTBhwHAH79+MubAEAyZ/Trpu+3bdu2BGMAAGOBVywAgGSEBQCQjLAAAJIRFgBAMsICAEhGWAAAyQgLACAZYQEAJCMsAIBkhAUAkIywAACSERYAQDLCAgBIRlgAAMkICwAgGWEBACQjLACAZIQFAJCMsAAAkhEWAEAywgIASEZYAADJCAsAIBlhAQAkIywAgGSEBQCQjLAAAJIRFgBAMsICAEhGWAAAyQgLACAZYQEAJCMsAIBkhAUAkIywAACSyRUWjz32WCxYsCAaGxujsbExlixZElu2bKnWbADAKJMrLGbPnh3r16+PPXv2xO7du+MTn/hEfPKTn4yf/OQn1ZoPABhFxuc5eeXKlf1uP/LII/HYY4/Fzp074/LLL086GAAw+uQKi/fr6emJb37zm3H8+PFYsmTJkOeVSqUolUp9t7u7uyMiolwuR7lcPtOHH+C9a6W85lhTrKuc/Dyu/+f3s7/+PK/ysa/s7Co7u8qumrvKes1CpVIZ+NXlFPbt2xdLliyJd955JyZPnhwdHR3xe7/3e0Oe39bWFu3t7QOOd3R0xKRJk/I8NABQIydOnIjVq1dHV1dXNDY2Dnle7rB499134+DBg9HV1RX/9E//FE8++WRs3749LrvsskHPH+wVi+bm5jhy5MgpB8urXC5HZ2dnLF26NOrr65NddyyZ37Y1Ik6+UvHQot74wu5xUeot9Dtnf9uyWow2Ynle5WNf2dlVdnaVXTV31d3dHU1NTacNi9zfCpkwYUJcfPHFERFx1VVXxa5du+LLX/5yPPHEE4OeXywWo1gsDjheX19flSdIta47FpR6+kdEqbcw4JjdDc7zKh/7ys6usrOr7Kqxq6zX+8B/x6K3t7ffKxIAwK+vXK9YPPDAA7F8+fKYM2dOHD16NDo6OmLbtm2xdevWas0HAIwiucLi8OHDceedd8ahQ4diypQpsWDBgti6dWssXbq0WvMBAKNIrrD4u7/7u2rNAQCMAd4rBABIRlgAAMkICwAgGWEBACQjLACAZIQFAJCMsAAAkhEWAEAywgIASEZYAADJCAsAIBlhAQAkIywAgGSEBQCQjLAAAJIRFgBAMsICAEhGWAAAyQgLACAZYQEAJCMsAIBkhAUAkIywAACSERYAQDLCAgBIRlgAAMkICwAgGWEBACQjLACAZIQFAJCMsAAAkhEWAEAywgIASEZYAADJCAsAIBlhAQAkkyss1q1bF1dffXU0NDTEjBkz4tZbb42XXnqpWrMBAKNMrrDYvn17tLa2xs6dO6OzszPK5XLcfPPNcfz48WrNBwCMIuPznPz973+/3+2nnnoqZsyYEXv27Inf+Z3fSToYADD65AqLX9XV1RUREVOnTh3ynFKpFKVSqe92d3d3RESUy+Uol8sf5OH7ee9aKa851hTrKic/j+v/+f3srz/Pq3zsKzu7ys6usqvmrrJes1CpVAZ+dcmgt7c3fv/3fz/efvvteOGFF4Y8r62tLdrb2wcc7+joiEmTJp3JQwMAw+zEiROxevXq6OrqisbGxiHPO+OwuPvuu2PLli3xwgsvxOzZs4c8b7BXLJqbm+PIkSOnHCyvcrkcnZ2dsXTp0qivr0923bFkftvWiDj5SsVDi3rjC7vHRam30O+c/W3LajHaiOV5lY99ZWdX2dlVdtXcVXd3dzQ1NZ02LM7oWyH33HNPfPe7340dO3acMioiIorFYhSLxQHH6+vrq/IEqdZ1x4JST/+IKPUWBhyzu8F5XuVjX9nZVXZ2lV01dpX1ernColKpxOc+97nYvHlzbNu2LS666KIzGg4AGJtyhUVra2t0dHTEt7/97WhoaIg33ngjIiKmTJkSZ511VlUGBABGj1x/x+Kxxx6Lrq6uuP7662PmzJl9H9/4xjeqNR8AMIrk/lYIAMBQvFcIAJCMsAAAkhEWAEAywgIASEZYAADJCAsAIBlhAQAkIywAgGSEBQCQjLAAAJIRFgBAMsICAEhGWAAAyQgLACAZYQEAJCMsAIBkhAUAkIywAACSERYAQDLCAgBIRlgAAMkICwAgGWEBACQjLACAZIQFAJCMsAAAkhEWAEAywgIASEZYAADJCAsAIBlhAQAkIywAgGSEBQCQjLAAAJIRFgBAMrnDYseOHbFy5cqYNWtWFAqFeOaZZ6owFgAwGuUOi+PHj8fChQtjw4YN1ZgHABjFxue9w/Lly2P58uXVmAUAGOVyh0VepVIpSqVS3+3u7u6IiCiXy1Eul5M9znvXSnnNsaZYVzn5eVz/z+9nf/15XuVjX9nZVXZ2lV01d5X1moVKpTLwq0tGhUIhNm/eHLfeeuuQ57S1tUV7e/uA4x0dHTFp0qQzfWgAYBidOHEiVq9eHV1dXdHY2DjkeVUPi8FesWhubo4jR46ccrC8yuVydHZ2xtKlS6O+vj7ZdceS+W1bI+LkKxUPLeqNL+weF6XeQr9z9rctq8VoI5bnVT72lZ1dZWdX2VVzV93d3dHU1HTasKj6t0KKxWIUi8UBx+vr66vyBKnWdceCUk//iCj1FgYcs7vBeV7lY1/Z2VV2dpVdNXaV9Xr+jgUAkEzuVyyOHTsWBw4c6Lv9yiuvxN69e2Pq1KkxZ86cpMMBAKNL7rDYvXt33HDDDX2316xZExERLS0t8dRTTyUbDAAYfXKHxfXXXx8f4Oc9AYAxzM9YAADJCAsAIBlhAQAkIywAgGSEBQCQjLAAAJIRFgBAMsICAEhGWAAAyQgLACAZYQEAJCMsAIBkhAUAkIywAACSERYAQDLCAgBIRlgAAMkICwAgGWEBACQjLACAZIQFAJCMsAAAkhEWAEAywgIASEZYAADJCAsAIJnxtR6AkeXC+7932nN+vn7FMEwCwGjkFQsAIBlhAQAkIywAgGSEBQCQjLAAAJIRFgBAMn7dlBHNr78CjC7CgtyyfLEfTuIDYOQ4o7DYsGFD/PVf/3W88cYbsXDhwvjKV74SixcvTj0bJCM+AIZH7rD4xje+EWvWrInHH388rrnmmnj00Udj2bJl8dJLL8WMGTOqMSMMi8Hio1hXib9aHDG/bWuUegqZriNQgF9nucPiS1/6Unz2s5+Nu+66KyIiHn/88fje974XX/va1+L+++9PPiCMNim/VSRSgNEmV1i8++67sWfPnnjggQf6jo0bNy5uuummePHFFwe9T6lUilKp1He7q6srIiLeeuutKJfLZzLzoMrlcpw4cSJ++ctfRn19fbLrjiXj/9/xk597K3HiRG+ML4+Lnt5s/y/811Wtd3Xx2qeH/TE/iOK4SvzfK3vjiv/zrSh9wH396IEbE001MvnfrOzsKrtq7uro0aMREVGpVE55Xq6wOHLkSPT09MR5553X7/h5550X//Ef/zHofdatWxft7e0Djl900UV5HprEVtd6gFHErvJJta+mLya6EJDU0aNHY8qUKUP+e9V/K+SBBx6INWvW9N3u7e2Nt956K6ZNmxaFQrr/B9jd3R3Nzc3x6quvRmNjY7LrjkV2lZ1d5WNf2dlVdnaVXTV3ValU4ujRozFr1qxTnpcrLJqamqKuri7efPPNfsfffPPNOP/88we9T7FYjGKx2O/YOeeck+dhc2lsbPTEy8iusrOrfOwrO7vKzq6yq9auTvVKxXty/eXNCRMmxFVXXRXPPfdc37He3t547rnnYsmSJfknBADGlNzfClmzZk20tLTEokWLYvHixfHoo4/G8ePH+35LBAD49ZU7LG677bb4xS9+EX/+538eb7zxRlxxxRXx/e9/f8APdA63YrEYDz744IBvuzCQXWVnV/nYV3Z2lZ1dZTcSdlWonO73RgAAMvLupgBAMsICAEhGWAAAyQgLACCZMRkWjzzySPz2b/92TJo0qap/jGu02rBhQ1x44YUxceLEuOaaa+Lf/u3faj3SiLRjx45YuXJlzJo1KwqFQjzzzDO1HmlEWrduXVx99dXR0NAQM2bMiFtvvTVeeumlWo81Ij322GOxYMGCvj9etGTJktiyZUutxxoV1q9fH4VCIe67775ajzIitbW1RaFQ6Pdx6aWX1mSWMRkW7777bqxatSruvvvuWo8y4rz3tvcPPvhg/PjHP46FCxfGsmXL4vDhw7UebcQ5fvx4LFy4MDZs2FDrUUa07du3R2tra+zcuTM6OzujXC7HzTffHMePH6/1aCPO7NmzY/369bFnz57YvXt3fOITn4hPfvKT8ZOf/KTWo41ou3btiieeeCIWLFhQ61FGtMsvvzwOHTrU9/HCCy/UZpDKGLZx48bKlClTaj3GiLJ48eJKa2tr3+2enp7KrFmzKuvWravhVCNfRFQ2b95c6zFGhcOHD1ciorJ9+/ZajzIqnHvuuZUnn3yy1mOMWEePHq38xm/8RqWzs7Py8Y9/vHLvvffWeqQR6cEHH6wsXLiw1mNUKpVKZUy+YsHg3nvb+5tuuqnv2One9h7y6urqioiIqVOn1niSka2npyc2bdoUx48f95YIp9Da2horVqzo979bDO7ll1+OWbNmxYc+9KG444474uDBgzWZo+rvbsrIcSZvew959Pb2xn333RfXXnttzJ8/v9bjjEj79u2LJUuWxDvvvBOTJ0+OzZs3x2WXXVbrsUakTZs2xY9//OPYtWtXrUcZ8a655pp46qmn4pJLLolDhw5Fe3t7XHfddbF///5oaGgY1llGzSsW999//4AfTPnVD18cobZaW1tj//79sWnTplqPMmJdcsklsXfv3vjRj34Ud999d7S0tMRPf/rTWo814rz66qtx7733xte//vWYOHFirccZ8ZYvXx6rVq2KBQsWxLJly+Jf//Vf4+23346nn3562GcZNa9Y/Nmf/Vn80R/90SnP+dCHPjQ8w4xSZ/K295DVPffcE9/97ndjx44dMXv27FqPM2JNmDAhLr744oiIuOqqq2LXrl3x5S9/OZ544okaTzay7NmzJw4fPhwf/ehH+4719PTEjh074qtf/WqUSqWoq6ur4YQj2znnnBPz5s2LAwcODPtjj5qwmD59ekyfPr3WY4xq73/b+1tvvTUi/vdt7++5557aDseoValU4nOf+1xs3rw5tm3bFhdddFGtRxpVent7o1Qq1XqMEefGG2+Mffv29Tt21113xaWXXhqf//znRcVpHDt2LH72s5/FH/7hHw77Y4+asMjj4MGD8dZbb8XBgwejp6cn9u7dGxERF198cUyePLm2w9WYt73P7tixY/1q/5VXXom9e/fG1KlTY86cOTWcbGRpbW2Njo6O+Pa3vx0NDQ3xxhtvRETElClT4qyzzqrxdCPLAw88EMuXL485c+bE0aNHo6OjI7Zt2xZbt26t9WgjTkNDw4Cf0zn77LNj2rRpfn5nEGvXro2VK1fG3Llz4/XXX48HH3ww6urq4vbbbx/+YWr9aynV0NLSUomIAR/PP/98rUcbEb7yla9U5syZU5kwYUJl8eLFlZ07d9Z6pBHp+eefH/R51NLSUuvRRpTBdhQRlY0bN9Z6tBHn05/+dGXu3LmVCRMmVKZPn1658cYbKz/4wQ9qPdao4ddNh3bbbbdVZs6cWZkwYULlggsuqNx2222VAwcO1GQWb5sOACQzan4rBAAY+YQFAJCMsAAAkhEWAEAywgIASEZYAADJCAsAIBlhAQAkIywAgGSEBQCQjLAAAJIRFgBAMv8fR+WPXPIQxXwAAAAASUVORK5CYII=", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "(df[\"loss_sem\"]-df[\"loss_sem_no_text\"]).clip(-1,5).hist(bins=50)" ] }, { "cell_type": "code", "execution_count": null, "id": "abf96d39", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.01 %\n" ] } ], "source": [ "(df[\"loss_sem\"]-df[\"loss_sem_no_text\"]).clip(-1,5).hist(bins=50)\n", "df[\"h\"] = (df[\"loss_sem\"]-df[\"loss_sem_no_text\"])\n", "print(round((df[\"h\"]<=-0.1).mean()*100, 2), \"%\")\n", "sub_df = df[df[\"h\"]>=-0.1]" ] }, { "cell_type": "code", "execution_count": null, "id": "f41d1be6", "metadata": {}, "outputs": [], "source": [ "row = sub_df.sample(1).iloc[0]\n", "idx = int(row[\"idx\"])\n", "print(idx)\n", "arr = mm[idx][:,1:].astype(np.int32)\n", "arr = arr[:np.where(arr[:,0] != 2048)[0][-1], :]\n", "codec_decode(arr[:25*60,:]).play()" ] }, { "cell_type": "code", "execution_count": null, "id": "3b99b280", "metadata": {}, "outputs": [], "source": [ "metas[idx]" ] }, { "cell_type": "code", "execution_count": null, "id": "f404d797", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "2d1c8d8c", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "52b44e7f", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "e42e4c8c", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "d8c99690", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 81, "id": "3ba7fc8b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 81, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "df[\"loss_coarse_10s\"].hist(bins=50)" ] }, { "cell_type": "code", "execution_count": 50, "id": "91dd1c8b", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "8.93 %\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "(df[\"loss_coarse_10s\"]-df[\"loss_coarse_no_text_10s\"]).hist(bins=50)\n", "df[\"h\"] = df[\"loss_coarse_10s\"]-df[\"loss_coarse_no_text_10s\"]\n", "print(round((df[\"h\"]>=2.5).mean()*100, 2), \"%\")\n", "sub_df = df[df[\"h\"]>=2.5]" ] }, { "cell_type": "code", "execution_count": 74, "id": "eb4d5729", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [] }, { "cell_type": "code", "execution_count": 80, "id": "5e9fc61b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "idx 38235112\n", "loss_sem 4\n", "loss_sem_10s 15\n", "loss_sem_no_text 2\n", "loss_sem_no_text_10s 2\n", "loss_coarse 5\n", "loss_coarse_10s 7\n", "loss_coarse_no_text 4\n", "loss_coarse_no_text_10s 3\n", "loss_coarse_0 4\n", "loss_coarse_1 5\n", "loss_coarse_2 5\n", "loss_coarse_3 5\n", "loss_coarse_4 5\n", "loss_coarse_5 5\n", "loss_coarse_6 5\n", "loss_coarse_7 5\n", "loss_coarse_8 5\n", "loss_coarse_9 5\n", "loss_coarse_10 5\n", "loss_coarse_11 5\n", "h 3\n", "Name: 85706251, dtype: int64" ] }, "execution_count": 80, "metadata": {}, "output_type": "execute_result" } ], "source": [ "row.round(3).astype(int)" ] }, { "cell_type": "code", "execution_count": 75, "id": "c9645374", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'dataset': 'discogs_lyrics',\n", " 'task': 'default',\n", " 'id': 'f0tqPKFGtd8',\n", " 'start_s': 0.0,\n", " 'end_s': 207.96,\n", " 'original_duration_s': 207.96,\n", " 'vocal_start_s': None,\n", " 'vocal_end_s': None,\n", " 'artist': 'UCVYcMHNlx7yApQH-E0bOOAQ',\n", " 'text': \"He did it for me\\nHe'll do it for you\\nWhen He brings you up from the Bottom to the top\\nTell me what you gone do\\nSee me Imma praise His name\\nLet the blessings come through\\nRepresenting that G-O-D cause I Know His word is true\\nHe did it for me\\nHe'll do it for you\\nWhen He brings you up from the Bottom to the top\\nTell me what you gone do\\nSee me Imma praise His name\\nLet the blessings come through\\nRepresenting that G-O-D cause I Know His word is true\\n\\nPour out your love and your Blessings upon me Lord\\nI know you protecting yea you Watching up above\\nYou took me from lusting women\\nSelling all the drugs\\nThe blood of the lamb has cleansed My soul\\nNow its time to pay you back\\nPut down the pistol and the gat\\nBeing a dope ain't really where it's At\\nKnowledge is power\\nYou better read the Bible\\nPeople looking at me and their Faces turning sour\\nThinking I was gonna fall down Like the twin towers\\nBut I stand in His grace and mercy\\nEverything that I touch goes\\nBlazing\\nNo disbelief that God who saved Me\\nFrom darkness to light\\nYahweh I praise You\\nMama pray many nights\\nThe streets won't take me\\nMultiple nights\\nSpiritual fights\\nWants and needs take heed aight\\nFriends and relationships I had to Sacrifice\\nThis didn't happen overnight\\nBare my cross\\n2020 vision\\nFred Hammond\\nThis my commission\\nStanding for greatness\\nDistant from peons\\nGod word lives forever\\nI'm talking for eons\\n\\nHe did it for me\\nHe'll do it for you\\nWhen He brings you up from the Bottom to the top\\nTell me what you gone do\\nSee me Imma praise His name\\nLet the blessings come through\\nRepresenting that G-O-D cause I Know His word is true\\nHe did it for me\\nHe'll do it for you\\nWhen He brings you up from the Bottom to the top\\nTell me what you gone do\\nSee me Imma praise His name\\nLet the blessings come through\\nRepresenting that G-O-D cause I Know His word is true\\n\\nI know He gone do it cause He Done it\\nMercy favor grace oh yea He run it\\nForever reppin it for my Jehovah\\nIf you try it devil know it's ova\\nSee I got to give Him the praise\\nCause He's always making a way\\nOh Lord here I come again\\nIn your presence til the end\\nNever wanna see what life is like Without your mercy\\nAll the things I went through Didn't let the devil hurt me\\nSo imma keep on praising Him c\\nCause Lord You are deserving\\nIn spirit and in truth the only one You know You worth it\\nYou want it He got it\\nHis favor He bout it\\nHis angels surround me\\nHis grace abound me\\n\\nHe did it for me\\nHe'll do it for you\\nWhen He brings you up from the Bottom to the top\\nTell me what you gone do\\nSee me Imma praise His name\\nLet the blessings come through\\nRepresenting that G-O-D cause I Know His word is true\\nHe did it for me\\nHe'll do it for you\\nWhen He brings you up from the Bottom to the top\\nTell me what you gone do\\nSee me Imma praise His name\\nLet the blessings come through\\nRepresenting that G-O-D cause I Know His word is true\",\n", " 'text_lang': 'en',\n", " 'n_tokens': 5199}" ] }, "execution_count": 75, "metadata": {}, "output_type": "execute_result" } ], "source": [ "metas[idx]" ] }, { "cell_type": "code", "execution_count": null, "id": "5b18ceb1", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "a69e22e5", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "f69d7ca0", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 147, "id": "027349fc", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 147, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", 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