{ "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": "2024-07-15T13:25:37.179312Z", "iopub.status.busy": "2024-07-15T13:25:37.179130Z", "iopub.status.idle": "2024-07-15T13:25:37.329113Z", "shell.execute_reply": "2024-07-15T13:25:37.328671Z", "shell.execute_reply.started": "2024-07-15T13:25:37.179296Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Update available: 1.68.0 -> 1.68.1, run `tailscale update` or `tailscale set --auto-update` to update\n" ] } ], "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": "2024-07-15T13:25:37.330211Z", "iopub.status.busy": "2024-07-15T13:25:37.330060Z", "iopub.status.idle": "2024-07-15T13:25:40.482500Z", "shell.execute_reply": "2024-07-15T13:25:40.481846Z", "shell.execute_reply.started": "2024-07-15T13:25:37.330196Z" } }, "outputs": [], "source": [ "# pip install psycopg2-binary\n", "# make sure sqlalchemy is >=2\n", "import ast\n", "import json\n", "from urllib.parse import quote\n", "\n", "import boto3\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import pandas as pd\n", "import sqlalchemy\n", "import tqdm\n", "from botocore.exceptions import ClientError\n", "from preference_helper import *\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", "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", "# connection = engine.raw_connection()\n", "\n", "# !pip install snowflake\n", "import snowflake.connector\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_X_SMAL\",\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": "2024-07-15T13:25:40.483594Z", "iopub.status.busy": "2024-07-15T13:25:40.483319Z", "iopub.status.idle": "2024-07-15T13:25:40.501523Z", "shell.execute_reply": "2024-07-15T13:25:40.500997Z", "shell.execute_reply.started": "2024-07-15T13:25:40.483576Z" } }, "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\" # 2h ft 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" ] }, { "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": "2024-07-15T13:25:40.502411Z", "iopub.status.busy": "2024-07-15T13:25:40.502253Z", "iopub.status.idle": "2024-07-15T13:25:40.795586Z", "shell.execute_reply": "2024-07-15T13:25:40.795028Z", "shell.execute_reply.started": "2024-07-15T13:25:40.502394Z" } }, "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": { "ExecuteTime": { "end_time": "2024-05-26T00:11:16.899029Z", "start_time": "2024-05-26T00:11:09.351909Z" }, "execution": { "iopub.execute_input": "2024-07-15T13:25:40.797058Z", "iopub.status.busy": "2024-07-15T13:25:40.796895Z", "iopub.status.idle": "2024-07-15T13:26:02.127632Z", "shell.execute_reply": "2024-07-15T13:26:02.127041Z", "shell.execute_reply.started": "2024-07-15T13:25:40.797042Z" } }, "outputs": [], "source": [ "# bots_generatedclipextra\n", "# these are all the logged actions\n", "query = f\"\"\"\n", "SELECT * FROM bots_generatedclipextra\n", "WHERE updated_at>='{cutoff_date}'\n", "\"\"\"\n", "bots_action_df = pd.read_sql_query(query, engine)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:12:13.867775Z", "start_time": "2024-05-26T00:11:16.900416Z" }, "execution": { "iopub.execute_input": "2024-07-15T13:26:02.128490Z", "iopub.status.busy": "2024-07-15T13:26:02.128336Z", "iopub.status.idle": "2024-07-15T13:29:10.090517Z", "shell.execute_reply": "2024-07-15T13:29:10.089963Z", "shell.execute_reply.started": "2024-07-15T13:26:02.128473Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "18,511,795 rows\n" ] } ], "source": [ "# ~ 4 min...X.x\n", "# bots_userreaction\n", "# id\tplay_count\tskip_count\tflagged\tflagged_reason\treaction_type\tupdated_at\tclip_id\tuser_id\n", "# this turns out to be much smaller ~ 570k\n", "query = f\"\"\"\n", "SELECT * FROM bots_userreaction\n", "WHERE updated_at>='{cutoff_date}' AND play_count>0\n", "\"\"\"\n", "reaction_df = pd.read_sql_query(query, engine)\n", "print(f\"{reaction_df.shape[0]:,} rows\")" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:12:14.002431Z", "start_time": "2024-05-26T00:12:13.869298Z" }, "execution": { "iopub.execute_input": "2024-07-15T13:29:10.091354Z", "iopub.status.busy": "2024-07-15T13:29:10.091196Z", "iopub.status.idle": "2024-07-15T13:29:10.916274Z", "shell.execute_reply": "2024-07-15T13:29:10.915712Z", "shell.execute_reply.started": "2024-07-15T13:29:10.091338Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "number of upvoates: 1,104,519 rows\n", "number of flagged reports: 29,196 rows\n", "reaction_type\n", "L 0.602845\n", "D 0.397155\n", "Name: proportion, dtype: float64\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\"] == True].copy()\n", "print(f\"number of flagged reports: {flagged_df.shape[0]:,} rows\")\n", "flagged_ids = flagged_df[\"clip_id\"]\n", "\n", "# check basic reaction -- the rate should be very low\n", "print(reaction_df.tail(n=10000)[\"reaction_type\"].value_counts(normalize=True))" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:12:14.504607Z", "start_time": "2024-05-26T00:12:14.296331Z" }, "execution": { "iopub.execute_input": "2024-07-15T13:29:10.917361Z", "iopub.status.busy": "2024-07-15T13:29:10.916975Z", "iopub.status.idle": "2024-07-15T14:22:46.065718Z", "shell.execute_reply": "2024-07-15T14:22:46.065009Z", "shell.execute_reply.started": "2024-07-15T13:29:10.917342Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "19,512,417 rows\n" ] } ], "source": [ "# these are continues, ~ 1,485k (much more than likes) ~ takes 3.5 mins\n", "# columns are:\n", "# 'id', 'created_at', 'updated_at', 'time_used', 'metadata', 'user_id',\n", "# 'status', 'discord_message_id', 'prompt_id', 'request_id',\n", "# 'is_generated', 's3_id', 'upvote_count', 'batch_index', 'model_name',\n", "# 'prompt_text', 'daily_theme_id', 'is_deleted', 'image_s3_id',\n", "# 'is_public', 'dislike_count', 'flag_count', 'play_count', 'skip_count',\n", "# 'title', 'is_public_approved', 'slug'\n", "\n", "# find all the complete clips -- this query takes ~ 10 sec\n", "# query = \"\"\"\n", "# SELECT COUNT(*) FROM bots_generatedclip\n", "# \"\"\"\n", "# clip_counts = pd.read_sql_query(query, engine)\n", "# all_total_clip_counts = clip_counts[\"count\"][0]\n", "# print(f\"all version total clips: {all_total_clip_counts}\")\n", "\n", "# query = \"\"\"\n", "# SELECT COUNT(*) FROM bots_generatedclip\n", "# WHERE status='complete' AND model_name::text LIKE '%%v3%%'\n", "# \"\"\"\n", "# clip_counts = pd.read_sql_query(query, engine)\n", "# all_total_clip_counts = clip_counts[\"count\"][0]\n", "# print(f\"v3 version total clips: {all_total_clip_counts}\")\n", "\n", "# ~ 1h 25 mins...or, 3 days takes ~ 15 mins\n", "# NOTE that we need to query everything cause contact / continue can come from another model\n", "\n", "# TODO: query only v3 here....\n", "# This is still a lot...we will have to do this in steps very soon\n", "# Some data eng required, disk is much cheaper\n", "# the generated clips table has play count issues (we need to read it without filtering on playcounts)\n", "# AND model_name::text LIKE '%%v3%%' AND play_count>=1\n", "# AND model_name::text LIKE '%%v3p5%%'\n", "query = f\"\"\"\n", "SELECT * FROM bots_generatedclip\n", "WHERE status='complete' AND created_at>='{cutoff_date}'\n", "\"\"\"\n", "total_clip_df = pd.read_sql_query(query, engine)\n", "print(f\"{total_clip_df.shape[0]:,} rows\")" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:22:56.476914Z", "start_time": "2024-05-26T00:22:06.973099Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:22:46.066803Z", "iopub.status.busy": "2024-07-15T14:22:46.066614Z", "iopub.status.idle": "2024-07-15T14:22:49.346465Z", "shell.execute_reply": "2024-07-15T14:22:49.345899Z", "shell.execute_reply.started": "2024-07-15T14:22:46.066784Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "258,200 playlists updated\n" ] } ], "source": [ "# get playlists\n", "query = f\"\"\"\n", "SELECT * FROM bots_playlistclip\n", "WHERE updated_at>='{cutoff_date}'\n", "\"\"\"\n", "playlist_clip_df = pd.read_sql_query(query, engine)\n", "print(f\"{playlist_clip_df.shape[0]:,} playlists updated\")" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:22:49.347321Z", "iopub.status.busy": "2024-07-15T14:22:49.347164Z", "iopub.status.idle": "2024-07-15T14:22:50.346291Z", "shell.execute_reply": "2024-07-15T14:22:50.345734Z", "shell.execute_reply.started": "2024-07-15T14:22:49.347304Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "authenticated users (411683, 3)\n" ] } ], "source": [ "query = \"\"\"\n", "SELECT *\n", "FROM auth_user_groups\n", "\"\"\"\n", "auth_user_df = pd.read_sql_query(query, engine)\n", "print(\"authenticated users\", auth_user_df.shape)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:22:50.347263Z", "iopub.status.busy": "2024-07-15T14:22:50.346951Z", "iopub.status.idle": "2024-07-15T14:22:58.396706Z", "shell.execute_reply": "2024-07-15T14:22:58.395950Z", "shell.execute_reply.started": "2024-07-15T14:22:50.347245Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "subscription_status\n", "active 261588\n", "past_due 11452\n", "Name: count, dtype: int64\n" ] } ], "source": [ "query = f\"\"\"\n", "SELECT * FROM bots_discordinfo\n", "WHERE subscription_status IN ('active', 'past_due')\n", "\"\"\"\n", "df_discord_info = pd.read_sql_query(\n", " query,\n", " engine,\n", ")\n", "# current active subscribers?\n", "print(df_discord_info[\"subscription_status\"].value_counts())\n", "# this is probably the right way to figure out the pro user group\n", "pro_users = set(df_discord_info[\"user_id\"].unique())" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:22:58.397768Z", "iopub.status.busy": "2024-07-15T14:22:58.397592Z", "iopub.status.idle": "2024-07-15T14:23:07.552025Z", "shell.execute_reply": "2024-07-15T14:23:07.551264Z", "shell.execute_reply.started": "2024-07-15T14:22:58.397750Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "total clips: 19512417\n", "total uploads: 214159 (214159, 26)\n" ] } ], "source": [ "# filter on versions\n", "# clip_df = total_clip_df[\n", "# ((total_clip_df[\"model_name\"].str.contains(\"v3\")) | (total_clip_df[\"model_name\"].str.contains(\"v4\"))) # or v3...\n", "# & (total_clip_df[\"created_at\"] >= \"2024-02-20\")\n", "# ].copy()\n", "clip_df = total_clip_df.copy()\n", "# print(f\"total v3 selected fraction = {clip_df.shape[0] / all_total_clip_counts}\")\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)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Proceed with feature engineering and cleaning up" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:23:07.553145Z", "iopub.status.busy": "2024-07-15T14:23:07.552951Z", "iopub.status.idle": "2024-07-15T14:23:08.076415Z", "shell.execute_reply": "2024-07-15T14:23:08.067401Z", "shell.execute_reply.started": "2024-07-15T14:23:07.553125Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "is_pro_user\n", "False 0.663365\n", "True 0.336635\n", "Name: proportion, dtype: float64\n" ] } ], "source": [ "# this is very interesting....\n", "reaction_df[\"is_pro_user\"] = reaction_df[\"user_id\"].isin(pro_users)\n", "print(reaction_df[\"is_pro_user\"].value_counts(normalize=True))" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:12.019778Z", "start_time": "2024-05-26T00:22:57.637371Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:23:08.090831Z", "iopub.status.busy": "2024-07-15T14:23:08.083453Z", "iopub.status.idle": "2024-07-15T14:23:17.824435Z", "shell.execute_reply": "2024-07-15T14:23:17.823866Z", "shell.execute_reply.started": "2024-07-15T14:23:08.090787Z" } }, "outputs": [], "source": [ "# add clip is in playlist feature\n", "clip_df[\"is_in_playlist\"] = clip_df[\"id\"].isin(playlist_clip_df[\"clip_id\"].unique())" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:17.912428Z", "start_time": "2024-05-26T00:23:12.021726Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:23:17.825308Z", "iopub.status.busy": "2024-07-15T14:23:17.825156Z", "iopub.status.idle": "2024-07-15T14:23:36.012611Z", "shell.execute_reply": "2024-07-15T14:23:36.012092Z", "shell.execute_reply.started": "2024-07-15T14:23:17.825290Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "clips that have children 2138278 \n", " clips that are parents 384414 \n", " Average continues from clip = 5.56243529111843\n" ] } ], "source": [ "def parse_parent_id(x):\n", " if \"history\" not in x:\n", " return None\n", " out = x.get(\"history\", [])\n", " if not isinstance(out, list) or len(out) == 0:\n", " return None\n", " # take the last one cause we continue off the children?\n", " out = out[-1]\n", " if isinstance(out, dict):\n", " # this is the continued info, which is a dict with id and continue_at\n", " return out[\"id\"]\n", " else:\n", " return None\n", "\n", "\n", "clip_df[\"continued_parent\"] = clip_df[\"metadata\"].apply(lambda x: parse_parent_id(x))\n", "clip_history_df = clip_df[~clip_df[\"continued_parent\"].isna()].copy()\n", "continued_ids = clip_history_df[\"id\"]\n", "# these are the parent's ids\n", "has_continued_children_ids = clip_history_df[\"continued_parent\"]\n", "print(\n", " \"clips that have children\",\n", " len(has_continued_children_ids),\n", " \"\\n clips that are parents\",\n", " len(has_continued_children_ids.unique()),\n", " \"\\n\",\n", " \"Average continues from clip = \",\n", " len(has_continued_children_ids) / len(has_continued_children_ids.unique()),\n", ")" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:22.092835Z", "start_time": "2024-05-26T00:23:17.914456Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:23:36.013780Z", "iopub.status.busy": "2024-07-15T14:23:36.013305Z", "iopub.status.idle": "2024-07-15T14:23:50.592982Z", "shell.execute_reply": "2024-07-15T14:23:50.592391Z", "shell.execute_reply.started": "2024-07-15T14:23:36.013757Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "total uploads: 214159\n", "Clips without request id (concat, uploads...) frac = 0.018033644934915032\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}\"\n", ")" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:22.833148Z", "start_time": "2024-05-26T00:23:22.094796Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:23:50.593832Z", "iopub.status.busy": "2024-07-15T14:23:50.593678Z", "iopub.status.idle": "2024-07-15T14:23:53.361206Z", "shell.execute_reply": "2024-07-15T14:23:53.360704Z", "shell.execute_reply.started": "2024-07-15T14:23:50.593814Z" } }, "outputs": [ { "data": { "text/plain": [ "model_name\n", "chirp-v3p5-engine-s-8 14748379\n", "chirp-v3p5-engine-ft-1 1758526\n", "chirp-v3p5-engine-upload-4 1065762\n", "chirp-v3-engine-i 666718\n", "chirp-v3p5-engine-s-8-no-top-p 424363\n", "chirp-v3p5-engine-t 102218\n", "chirp-v3p5-engine-s-19 90029\n", "chirp-v3p5-engine-s-18 89973\n", "chirp-v2-xxl-alpha 86121\n", "chirp-v3p5-engine-ft-2 68768\n", "chirp-v2-engine-msft-60s 59319\n", "chirp-v3-5 330\n", "chirp-v3-5-upload 16\n", "chirp-v3-0 15\n", "Name: count, dtype: int64" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# check the model conts\n", "clip_df[\"model_name\"].value_counts()" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:26.317699Z", "start_time": "2024-05-26T00:23:22.835074Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:23:53.362218Z", "iopub.status.busy": "2024-07-15T14:23:53.362059Z", "iopub.status.idle": "2024-07-15T14:24:02.941636Z", "shell.execute_reply": "2024-07-15T14:24:02.941066Z", "shell.execute_reply.started": "2024-07-15T14:23:53.362201Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(19160537, 28)\n", "(19100857, 28)\n" ] } ], "source": [ "print(clip_df.shape)\n", "clip_df = clip_df[\n", " clip_df[\"model_name\"].isin(\n", " [\n", " # \"chirp-v3-engine-d\",\n", " # \"chirp-v3-engine-v0\",\n", " \"chirp-v2-xxl-alpha\",\n", " \"chirp-v3-engine-i\",\n", " # \"chirp-v3-engine-i-tp\",\n", " # \"chirp-v3-engine-s\",\n", " \"chirp-v3p5-engine-d\",\n", " \"chirp-v3p5-engine-s\",\n", " \"chirp-v3p5-engine-s-2\",\n", " \"chirp-v3p5-engine-s-3\",\n", " \"chirp-v3p5-engine-s-4\",\n", " \"chirp-v3p5-engine-s-5\",\n", " \"chirp-v3p5-engine-s-6\",\n", " \"chirp-v3p5-engine-s-7\",\n", " \"chirp-v3p5-engine-s-8\",\n", " \"chirp-v3p5-engine-s-9\",\n", " \"chirp-v3p5-engine-s-10\",\n", " \"chirp-v3p5-engine-s-11\",\n", " \"chirp-v3p5-engine-s-12\",\n", " \"chirp-v3p5-engine-s-13\",\n", " \"chirp-v3p5-engine-s-14\",\n", " \"chirp-v3p5-engine-s-18\",\n", " \"chirp-v3p5-engine-s-19\",\n", " \"chirp-v3p5-engine-t\",\n", " \"chirp-v3p5-engine-ft\",\n", " \"chirp-v3p5-engine-ft-1\",\n", " \"chirp-v3p5-engine-ft-2\",\n", " \"chirp-v3p5-engine-s-8-no-top-p\",\n", " \"\",\n", " \"chirp-v3p5-engine-upload\",\n", " \"chirp-v3p5-engine-upload-1\",\n", " \"chirp-v3p5-engine-upload-2\",\n", " \"chirp-v3p5-engine-upload-3\",\n", " \"chirp-v3p5-engine-upload-4\",\n", " ]\n", " )\n", "]\n", "print(clip_df.shape)" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:26.994407Z", "start_time": "2024-05-26T00:23:26.319359Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:24:02.942482Z", "iopub.status.busy": "2024-07-15T14:24:02.942324Z", "iopub.status.idle": "2024-07-15T14:24:05.094770Z", "shell.execute_reply": "2024-07-15T14:24:05.094048Z", "shell.execute_reply.started": "2024-07-15T14:24:02.942464Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "model_name\n", "chirp-v3p5-engine-s-8 14748379\n", "chirp-v3p5-engine-ft-1 1758526\n", "chirp-v3p5-engine-upload-4 1065762\n", "chirp-v3-engine-i 666718\n", "chirp-v3p5-engine-s-8-no-top-p 424363\n", "chirp-v3p5-engine-t 102218\n", "chirp-v3p5-engine-s-19 90029\n", "chirp-v3p5-engine-s-18 89973\n", "chirp-v2-xxl-alpha 86121\n", "chirp-v3p5-engine-ft-2 68768\n", "Name: count, dtype: int64\n" ] } ], "source": [ "print(clip_df[\"model_name\"].value_counts())" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:33.488829Z", "start_time": "2024-05-26T00:23:27.161663Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:24:05.095873Z", "iopub.status.busy": "2024-07-15T14:24:05.095701Z", "iopub.status.idle": "2024-07-15T14:24:21.367891Z", "shell.execute_reply": "2024-07-15T14:24:21.367128Z", "shell.execute_reply.started": "2024-07-15T14:24:05.095853Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "concat reactions (641046, 11) 236513\n" ] } ], "source": [ "# ~ only 1 min :)\n", "concat_reaction_df = reaction_df[\n", " reaction_df[\"clip_id\"].isin(concated_clips[\"id\"])\n", "].copy()\n", "print(\n", " \"concat reactions\",\n", " concat_reaction_df.shape,\n", " concat_reaction_df[\"clip_id\"].nunique(),\n", ")" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:34.169887Z", "start_time": "2024-05-26T00:23:33.491114Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:24:21.368952Z", "iopub.status.busy": "2024-07-15T14:24:21.368772Z", "iopub.status.idle": "2024-07-15T14:24:23.687125Z", "shell.execute_reply": "2024-07-15T14:24:23.686378Z", "shell.execute_reply.started": "2024-07-15T14:24:21.368933Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "total concats (351880, 29)\n", "total concats with plays (236513, 29)\n" ] } ], "source": [ "concat_total_play_reaction_df_sum = concat_reaction_df.groupby(\"clip_id\")[\n", " \"play_count\"\n", "].sum()\n", "concat_total_play_reaction_df_sum_df = (\n", " concat_total_play_reaction_df_sum.reset_index().rename(\n", " columns={\"clip_id\": \"id\", \"play_count\": \"reaction_play_count\"}\n", " )\n", ")\n", "concated_clips = concated_clips.merge(\n", " concat_total_play_reaction_df_sum_df, on=\"id\", how=\"left\"\n", ")\n", "\n", "print(\"total concats\", concated_clips.shape)\n", "concated_clips = concated_clips[concated_clips[\"reaction_play_count\"] > 0]\n", "print(\"total concats with plays\", concated_clips.shape)\n", "# TODO: why so many clips are concats without plays???" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:38.974479Z", "start_time": "2024-05-26T00:23:34.385507Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:24:23.688254Z", "iopub.status.busy": "2024-07-15T14:24:23.688082Z", "iopub.status.idle": "2024-07-15T14:24:32.672918Z", "shell.execute_reply": "2024-07-15T14:24:32.672368Z", "shell.execute_reply.started": "2024-07-15T14:24:23.688236Z" } }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "236513it [00:08, 26555.70it/s]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "total concat unique clips are: 195894 with error: 1, duplicate 22851\n", "uploads are in concats 18084 0.08444193332990908\n" ] } ], "source": [ "# this is each clip. and the mapped start time of the clip\n", "concat_clips_ids = {}\n", "history_error_counter = 0\n", "history_duplicate_error_counter = 0\n", "for _, row in tqdm.tqdm(concated_clips.iterrows()):\n", " if history_ids := row[\"metadata\"].get(\"concat_history\"):\n", " total_duration = row[\"metadata\"].get(\"duration\", 0)\n", " if total_duration == 0:\n", " print(row[\"metadata\"], row[\"model_name\"])\n", " continue\n", " start_s = 0\n", " for history_id in history_ids:\n", " # print(history_ids, row[\"metadata\"][\"duration\"])\n", " if isinstance(history_id, dict) and \"id\" in history_id:\n", " # the other key is `continue_at`\n", " if history_id[\"id\"]:\n", " if history_id[\"id\"] in concat_clips_ids:\n", " if (\n", " row[\"upvote_count\"]\n", " < concat_clips_ids[history_id[\"id\"]][\"concat_likes\"]\n", " ):\n", " continue\n", " if (\n", " row[\"reaction_play_count\"]\n", " < concat_clips_ids[history_id[\"id\"]][\"concat_play_counts\"]\n", " ):\n", " continue\n", " # multi-seed to concats\n", " history_duplicate_error_counter += 1\n", " concat_clips_ids[history_id[\"id\"]] = {\n", " \"total_start_s\": start_s,\n", " \"total_clip_s\": total_duration,\n", " \"concat_play_counts\": row[\"reaction_play_count\"],\n", " \"concat_in_playlist\": row[\"is_in_playlist\"],\n", " \"concat_likes\": row[\"upvote_count\"],\n", " \"concat_dislikes\": row[\"dislike_count\"],\n", " }\n", " else:\n", " history_error_counter += 1\n", " # but we always update the start_s\n", " start_s = history_id[\"continue_at\"]\n", "print(\n", " \"total concat unique clips are:\",\n", " len(concat_clips_ids),\n", " f\"with error: {history_error_counter}, duplicate {history_duplicate_error_counter}\",\n", ")\n", "\n", "n_unique_uploads_in_concats = len(\n", " set(i for i in concat_clips_ids if i.startswith(\"m_\"))\n", ")\n", "print(\n", " \"uploads are in concats\",\n", " n_unique_uploads_in_concats,\n", " n_unique_uploads_in_concats / upload_clip_df.shape[0],\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Features" ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:39.994495Z", "start_time": "2024-05-26T00:23:39.825228Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:24:32.673782Z", "iopub.status.busy": "2024-07-15T14:24:32.673621Z", "iopub.status.idle": "2024-07-15T14:24:33.205988Z", "shell.execute_reply": "2024-07-15T14:24:33.205430Z", "shell.execute_reply.started": "2024-07-15T14:24:32.673765Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "pro gen frac is_pro_user\n", "False 0.598472\n", "True 0.401528\n", "Name: proportion, dtype: float64\n", "pro users with generations 89539\n" ] } ], "source": [ "clip_df[\"is_pro_user\"] = clip_df[\"user_id\"].isin(pro_users)\n", "print(\"pro gen frac\", clip_df[\"is_pro_user\"].value_counts(normalize=True))\n", "print(\n", " \"pro users with generations\", clip_df[\"user_id\"][clip_df[\"is_pro_user\"]].nunique()\n", ")" ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:40.236690Z", "start_time": "2024-05-26T00:23:39.995713Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:24:33.206853Z", "iopub.status.busy": "2024-07-15T14:24:33.206696Z", "iopub.status.idle": "2024-07-15T14:24:33.869921Z", "shell.execute_reply": "2024-07-15T14:24:33.866587Z", "shell.execute_reply.started": "2024-07-15T14:24:33.206836Z" } }, "outputs": [], "source": [ "# set user number of clips generated\n", "clip_df[\"user_n_clips\"] = clip_df[\"user_id\"].map(clip_df[\"user_id\"].value_counts())" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:44.826860Z", "start_time": "2024-05-26T00:23:40.238330Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:24:33.871363Z", "iopub.status.busy": "2024-07-15T14:24:33.871127Z", "iopub.status.idle": "2024-07-15T14:24:48.618020Z", "shell.execute_reply": "2024-07-15T14:24:48.617289Z", "shell.execute_reply.started": "2024-07-15T14:24:33.871342Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "has upvoted upvoted\n", "False 18163118\n", "True 937739\n", "Name: count, dtype: int64 upvoted\n", "False 0.950906\n", "True 0.049094\n", "Name: proportion, dtype: float64 upvote_count\n", "False 0.950349\n", "True 0.049651\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": 26, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:48.404433Z", "start_time": "2024-05-26T00:23:44.857788Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:24:48.619084Z", "iopub.status.busy": "2024-07-15T14:24:48.618917Z", "iopub.status.idle": "2024-07-15T14:25:07.252793Z", "shell.execute_reply": "2024-07-15T14:25:07.252237Z", "shell.execute_reply.started": "2024-07-15T14:24:48.619065Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "total deleted (704798,) has deleted deleted\n", "False 18439131\n", "True 661726\n", "Name: count, dtype: int64 deleted\n", "False 0.965356\n", "True 0.034644\n", "Name: proportion, dtype: float64\n" ] } ], "source": [ "deleted_ids = reaction_df[reaction_df[\"reaction_type\"] == \"D\"][\"clip_id\"].unique()\n", "\n", "clip_df[\"deleted\"] = clip_df[\"id\"].isin(deleted_ids)\n", "print(\n", " \"total deleted\",\n", " deleted_ids.shape,\n", " \"has deleted\",\n", " clip_df[\"deleted\"].value_counts(),\n", " clip_df[\"deleted\"].value_counts(normalize=True),\n", ")" ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:23:56.590022Z", "start_time": "2024-05-26T00:23:48.405668Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:25:07.253673Z", "iopub.status.busy": "2024-07-15T14:25:07.253515Z", "iopub.status.idle": "2024-07-15T14:25:32.798587Z", "shell.execute_reply": "2024-07-15T14:25:32.797797Z", "shell.execute_reply.started": "2024-07-15T14:25:07.253655Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "has has_continued has_continued\n", "False 18933677\n", "True 167180\n", "Name: count, dtype: int64 has_continued\n", "False 0.991248\n", "True 0.008752\n", "Name: proportion, dtype: float64\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(\n", " \"has has_continued\",\n", " clip_df[\"has_continued\"].value_counts(),\n", " clip_df[\"has_continued\"].value_counts(normalize=True),\n", ")" ] }, { "cell_type": "code", "execution_count": 28, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:04.704306Z", "start_time": "2024-05-26T00:23:56.591353Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:25:32.799672Z", "iopub.status.busy": "2024-07-15T14:25:32.799495Z", "iopub.status.idle": "2024-07-15T14:25:56.035301Z", "shell.execute_reply": "2024-07-15T14:25:56.034493Z", "shell.execute_reply.started": "2024-07-15T14:25:32.799653Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "is part of a concat part_of_concat\n", "False 18952913\n", "True 147944\n", "Name: count, dtype: int64 part_of_concat\n", "False 0.992255\n", "True 0.007745\n", "Name: proportion, dtype: float64\n", "model countdowns model_name\n", "chirp-v3p5-engine-s-8 0.647042\n", "chirp-v3p5-engine-upload-4 0.156296\n", "chirp-v3p5-engine-ft-1 0.079077\n", "chirp-v3-engine-i 0.078489\n", "chirp-v3p5-engine-s-8-no-top-p 0.018379\n", "chirp-v3p5-engine-t 0.005272\n", "chirp-v3p5-engine-s-18 0.004556\n", "chirp-v3p5-engine-s-19 0.004177\n", "chirp-v3p5-engine-ft-2 0.003380\n", "chirp-v2-xxl-alpha 0.003332\n", "Name: proportion, dtype: float64\n" ] } ], "source": [ "# add concat column\n", "clip_df[\"part_of_concat\"] = clip_df[\"id\"].astype(str).isin(concat_clips_ids)\n", "print(\n", " \"is part of a concat\",\n", " clip_df[\"part_of_concat\"].value_counts(),\n", " clip_df[\"part_of_concat\"].value_counts(normalize=True),\n", ")\n", "print(\n", " \"model countdowns\",\n", " clip_df[clip_df[\"part_of_concat\"] == True][\"model_name\"].value_counts(\n", " normalize=True\n", " ),\n", ")" ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:09.954233Z", "start_time": "2024-05-26T00:24:04.705554Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:25:56.036469Z", "iopub.status.busy": "2024-07-15T14:25:56.036188Z", "iopub.status.idle": "2024-07-15T14:26:06.276745Z", "shell.execute_reply": "2024-07-15T14:26:06.271576Z", "shell.execute_reply.started": "2024-07-15T14:25:56.036449Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "has has_action has_action\n", "False 18984072\n", "True 116785\n", "Name: count, dtype: int64 has_action\n", "False 0.993886\n", "True 0.006114\n", "Name: proportion, dtype: float64\n" ] } ], "source": [ "# verify bots action are all non-empty\n", "# assert (\n", "# bots_action_df[\n", "# bots_action_df[\"download_audio_count\"]\n", "# + bots_action_df[\"download_video_count\"]\n", "# + bots_action_df[\"share_count\"]\n", "# == 0\n", "# ].shape[0]\n", "# == 0\n", "# )\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(\n", " \"has has_action\",\n", " clip_df[\"has_action\"].value_counts(),\n", " clip_df[\"has_action\"].value_counts(normalize=True),\n", ")" ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:14.579841Z", "start_time": "2024-05-26T00:24:09.955568Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:26:06.281180Z", "iopub.status.busy": "2024-07-15T14:26:06.277673Z", "iopub.status.idle": "2024-07-15T14:26:13.895796Z", "shell.execute_reply": "2024-07-15T14:26:13.895236Z", "shell.execute_reply.started": "2024-07-15T14:26:06.281141Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "has flagged flagged\n", "False 19072946\n", "True 27911\n", "Name: count, dtype: int64 flagged\n", "False 0.998539\n", "True 0.001461\n", "Name: proportion, dtype: float64\n" ] } ], "source": [ "# add downvoted column\n", "clip_df[\"flagged\"] = clip_df[\"id\"].isin(flagged_ids)\n", "print(\n", " \"has flagged\",\n", " clip_df[\"flagged\"].value_counts(),\n", " clip_df[\"flagged\"].value_counts(normalize=True),\n", ")" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:26:13.896686Z", "iopub.status.busy": "2024-07-15T14:26:13.896534Z", "iopub.status.idle": "2024-07-15T14:26:14.560069Z", "shell.execute_reply": "2024-07-15T14:26:14.559565Z", "shell.execute_reply.started": "2024-07-15T14:26:13.896669Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "has downvoted downvoted\n", "False 18402038\n", "True 698819\n", "Name: count, dtype: int64 downvoted\n", "False 0.963414\n", "True 0.036586\n", "Name: proportion, dtype: float64\n" ] } ], "source": [ "clip_df[\"downvoted\"] = clip_df[\"dislike_count\"] != 0\n", "print(\n", " \"has downvoted\",\n", " clip_df[\"downvoted\"].value_counts(),\n", " clip_df[\"downvoted\"].value_counts(normalize=True),\n", ")" ] }, { "cell_type": "code", "execution_count": 32, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:15.382315Z", "start_time": "2024-05-26T00:24:14.581073Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:26:14.560936Z", "iopub.status.busy": "2024-07-15T14:26:14.560783Z", "iopub.status.idle": "2024-07-15T14:26:17.283756Z", "shell.execute_reply": "2024-07-15T14:26:17.283176Z", "shell.execute_reply.started": "2024-07-15T14:26:14.560919Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "total_clips, 19100857, total preference, 1126328, \n", " must be pos 1132763, def not neg 18380174,\n", " must be neg 720683.\n", " \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\"] == True)\n", " | (clip_df[\"has_action\"] == True)\n", " | (clip_df[\"part_of_concat\"] == True)\n", ")\n", "must_be_not_negative_mask = (\n", " (clip_df[\"downvoted\"] == False)\n", " & (clip_df[\"deleted\"] == False)\n", " & (clip_df[\"flagged\"] == False)\n", ")\n", "must_be_negative_mask = (\n", " (clip_df[\"downvoted\"] == True)\n", " | (clip_df[\"deleted\"] == True)\n", " | (clip_df[\"flagged\"] == True)\n", ")\n", "mask = must_be_positive_mask & must_be_not_negative_mask\n", "print(\n", " f\"\"\"total_clips, {clip_df.shape[0]}, total preference, {sum(mask)}, \n", " must be pos {sum(must_be_positive_mask)}, def not neg {sum(must_be_not_negative_mask)},\n", " must be neg {sum(must_be_negative_mask)}.\n", " \"\"\"\n", ")" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:31.095990Z", "start_time": "2024-05-26T00:24:15.383572Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:26:17.284627Z", "iopub.status.busy": "2024-07-15T14:26:17.284476Z", "iopub.status.idle": "2024-07-15T14:27:18.607924Z", "shell.execute_reply": "2024-07-15T14:27:18.607213Z", "shell.execute_reply.started": "2024-07-15T14:26:17.284611Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "liked 944799 not liked 9391224\n", "757680 requests have preference paired generations, 0.079\n" ] } ], "source": [ "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(\"liked\", len(liked_requests), \"not liked\", len(unliked_requests))\n", "print(\n", " f\"{len(has_liked_requests)} requests have preference paired generations, {len(has_liked_requests) / total_unique_requests:.3f}\"\n", ")" ] }, { "cell_type": "code", "execution_count": 34, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:27:18.608912Z", "iopub.status.busy": "2024-07-15T14:27:18.608744Z", "iopub.status.idle": "2024-07-15T14:27:56.736748Z", "shell.execute_reply": "2024-07-15T14:27:56.735939Z", "shell.execute_reply.started": "2024-07-15T14:27:18.608894Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "disliked 460941 not disliked 9317129\n", "199727 requests have preference paired generations, 0.021\n" ] } ], "source": [ "# introduce a negative preference count\n", "has_disliked_requets = 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_requets).intersection(\n", " set(not_have_disliked_requests)\n", ") # the request must have 1 dislike and one without dislike\n", "print(\n", " \"disliked\",\n", " len(has_disliked_requets),\n", " \"not disliked\",\n", " len(not_have_disliked_requests),\n", ")\n", "print(\n", " f\"{len(has_disliked_requests)} requests have preference paired generations, {len(has_disliked_requests) / total_unique_requests:.3f}\"\n", ")" ] }, { "cell_type": "code", "execution_count": 35, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:31.099372Z", "start_time": "2024-05-26T00:24:31.097244Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:27:56.737824Z", "iopub.status.busy": "2024-07-15T14:27:56.737651Z", "iopub.status.idle": "2024-07-15T14:27:56.844383Z", "shell.execute_reply": "2024-07-15T14:27:56.843734Z", "shell.execute_reply.started": "2024-07-15T14:27:56.737805Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "total selected pairs of requests 884508, 0.092\n" ] } ], "source": [ "requests = has_liked_requests.union(has_disliked_requests)\n", "print(\n", " f\"total selected pairs of requests {len(requests)}, {len(requests) / total_unique_requests:.3f}\"\n", ")" ] }, { "cell_type": "code", "execution_count": 36, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:31.239254Z", "start_time": "2024-05-26T00:24:31.100389Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:27:56.845613Z", "iopub.status.busy": "2024-07-15T14:27:56.845147Z", "iopub.status.idle": "2024-07-15T14:27:57.171985Z", "shell.execute_reply": "2024-07-15T14:27:57.171382Z", "shell.execute_reply.started": "2024-07-15T14:27:56.845594Z" } }, "outputs": [ { "data": { "text/plain": [ "diff_preference\n", " 0 17253846\n", " 1 1126328\n", "-1 720683\n", "Name: count, dtype: int64" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "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", "clip_df[\"diff_preference\"] = clip_df[\"pos_preference\"].astype(int) - clip_df[\n", " \"neg_preference\"\n", "].astype(int)\n", "clip_df[\"diff_preference\"].value_counts()\n", "# clip_df[\"preference\"] = mask" ] }, { "cell_type": "code", "execution_count": 37, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:37.322031Z", "start_time": "2024-05-26T00:24:31.240829Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:27:57.173041Z", "iopub.status.busy": "2024-07-15T14:27:57.172795Z", "iopub.status.idle": "2024-07-15T14:28:13.311957Z", "shell.execute_reply": "2024-07-15T14:28:13.311398Z", "shell.execute_reply.started": "2024-07-15T14:27:57.173023Z" } }, "outputs": [], "source": [ "# creation of interesting_clips\n", "interesting_clips = clip_df[clip_df[\"request_id\"].isin(requests)].copy()" ] }, { "cell_type": "code", "execution_count": 38, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:28:13.315115Z", "iopub.status.busy": "2024-07-15T14:28:13.312664Z", "iopub.status.idle": "2024-07-15T14:28:22.408387Z", "shell.execute_reply": "2024-07-15T14:28:22.407736Z", "shell.execute_reply.started": "2024-07-15T14:28:13.315079Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
request_idpos_preferenceneg_preferencediff_preference
00000255b-b52d-4a29-a0df-3812d017f2b0FalseFalse0
10000255b-b52d-4a29-a0df-3812d017f2b0TrueFalse1
2000027b2-4f70-46aa-972a-fd31e1afa43eFalseFalse0
3000027b2-4f70-46aa-972a-fd31e1afa43eTrueFalse1
400003aa7-d769-47b1-bac8-1cd1364a1060FalseFalse0
\n", "
" ], "text/plain": [ " request_id pos_preference neg_preference diff_preference\n", "0 0000255b-b52d-4a29-a0df-3812d017f2b0 False False 0\n", "1 0000255b-b52d-4a29-a0df-3812d017f2b0 True False 1\n", "2 000027b2-4f70-46aa-972a-fd31e1afa43e False False 0\n", "3 000027b2-4f70-46aa-972a-fd31e1afa43e True False 1\n", "4 00003aa7-d769-47b1-bac8-1cd1364a1060 False False 0" ] }, "execution_count": 38, "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()" ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:28:22.409888Z", "iopub.status.busy": "2024-07-15T14:28:22.409227Z", "iopub.status.idle": "2024-07-15T14:28:22.943780Z", "shell.execute_reply": "2024-07-15T14:28:22.943292Z", "shell.execute_reply.started": "2024-07-15T14:28:22.409865Z" } }, "outputs": [ { "data": { "text/plain": [ "diff_preference\n", " 0 811609\n", " 1 757680\n", "-1 199727\n", "Name: count, dtype: int64" ] }, "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# this is a mix now\n", "interesting_clips[\"diff_preference\"].value_counts()" ] }, { "cell_type": "code", "execution_count": 40, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:28:22.944642Z", "iopub.status.busy": "2024-07-15T14:28:22.944488Z", "iopub.status.idle": "2024-07-15T14:28:23.021286Z", "shell.execute_reply": "2024-07-15T14:28:23.020674Z", "shell.execute_reply.started": "2024-07-15T14:28:22.944625Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "diff_preference\n", "1.0 811609\n", "2.0 72899\n", "Name: count, dtype: int64\n" ] } ], "source": [ "diff_series = interesting_clips[\"diff_preference\"].diff()\n", "print(\n", " diff_series[1::2].value_counts()\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": 41, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:28:23.026687Z", "iopub.status.busy": "2024-07-15T14:28:23.026268Z", "iopub.status.idle": "2024-07-15T14:28:23.061599Z", "shell.execute_reply": "2024-07-15T14:28:23.061167Z", "shell.execute_reply.started": "2024-07-15T14:28:23.026669Z" } }, "outputs": [ { "data": { "text/plain": [ "preference\n", "False 884508\n", "True 884508\n", "Name: count, dtype: int64" ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" } ], "source": [ "interesting_clips[\"preference\"] = interesting_clips.index % 2 == 1\n", "interesting_clips[\"preference\"].value_counts()" ] }, { "cell_type": "code", "execution_count": 42, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:38.960130Z", "start_time": "2024-05-26T00:24:37.323369Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:28:23.062347Z", "iopub.status.busy": "2024-07-15T14:28:23.062196Z", "iopub.status.idle": "2024-07-15T14:28:28.544370Z", "shell.execute_reply": "2024-07-15T14:28:28.543843Z", "shell.execute_reply.started": "2024-07-15T14:28:23.062332Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "884508 1769016\n" ] } ], "source": [ "# get df of requests -- let's move on!\n", "print(interesting_clips[\"request_id\"].nunique(), interesting_clips[\"id\"].nunique())" ] }, { "cell_type": "code", "execution_count": 43, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:43.156873Z", "start_time": "2024-05-26T00:24:38.961258Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:28:28.545306Z", "iopub.status.busy": "2024-07-15T14:28:28.545065Z", "iopub.status.idle": "2024-07-15T14:28:37.229619Z", "shell.execute_reply": "2024-07-15T14:28:37.229031Z", "shell.execute_reply.started": "2024-07-15T14:28:28.545288Z" } }, "outputs": [], "source": [ "# some validations\n", "assert interesting_clips[interesting_clips[\"request_id\"].isna()].shape[0] == 0\n", "check_df = interesting_clips.groupby(\"request_id\")[\"id\"].nunique()\n", "check_df[check_df.values != 2]\n", "assert check_df[check_df.values != 2].shape[0] == 0" ] }, { "cell_type": "code", "execution_count": 44, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:43.164669Z", "start_time": "2024-05-26T00:24:43.158223Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:28:37.230580Z", "iopub.status.busy": "2024-07-15T14:28:37.230411Z", "iopub.status.idle": "2024-07-15T14:28:37.251505Z", "shell.execute_reply": "2024-07-15T14:28:37.251057Z", "shell.execute_reply.started": "2024-07-15T14:28:37.230562Z" } }, "outputs": [], "source": [ "# validation...\n", "# TODO: refactor this with above into a func\n", "# interesting_clips_must_be_positive_mask = (\n", "# (interesting_clips[\"upvoted\"] == True)\n", "# | (interesting_clips[\"has_action\"] == True)\n", "# | (interesting_clips[\"part_of_concat\"] == True)\n", "# )\n", "# interesting_clips_must_be_not_negative_mask = (\n", "# interesting_clips[\"downvoted\"] == False\n", "# ) & (interesting_clips[\"deleted\"] == False)\n", "# interesting_clips_mask = (\n", "# interesting_clips_must_be_positive_mask\n", "# & interesting_clips_must_be_not_negative_mask\n", "# )\n", "# assert interesting_clips_mask.eq(interesting_clips[\"preference\"]).all()" ] }, { "cell_type": "code", "execution_count": 45, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:43.332222Z", "start_time": "2024-05-26T00:24:43.166461Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:28:37.252294Z", "iopub.status.busy": "2024-07-15T14:28:37.252142Z", "iopub.status.idle": "2024-07-15T14:28:37.303243Z", "shell.execute_reply": "2024-07-15T14:28:37.302814Z", "shell.execute_reply.started": "2024-07-15T14:28:37.252278Z" } }, "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": 46, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:43.562167Z", "start_time": "2024-05-26T00:24:43.333784Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:28:37.304114Z", "iopub.status.busy": "2024-07-15T14:28:37.303970Z", "iopub.status.idle": "2024-07-15T14:28:37.351380Z", "shell.execute_reply": "2024-07-15T14:28:37.350929Z", "shell.execute_reply.started": "2024-07-15T14:28:37.304099Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1769016\n" ] } ], "source": [ "# interesting_clips[\"has_gpt_prompt\"] = interesting_clips[\"metadata\"].apply(\n", "# lambda x: ast.literal_eval(str(x)).get(\"gpt_description_prompt\", None) is not None\n", "# )\n", "# print(len(interesting_clips))\n", "# interesting_clips = interesting_clips[~interesting_clips[\"has_gpt_prompt\"]]\n", "print(len(interesting_clips))" ] }, { "cell_type": "code", "execution_count": 47, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:43.737067Z", "start_time": "2024-05-26T00:24:43.563216Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:28:37.352130Z", "iopub.status.busy": "2024-07-15T14:28:37.351980Z", "iopub.status.idle": "2024-07-15T14:28:37.447283Z", "shell.execute_reply": "2024-07-15T14:28:37.446760Z", "shell.execute_reply.started": "2024-07-15T14:28:37.352115Z" } }, "outputs": [ { "data": { "text/plain": [ "batch_index preference\n", "0 False 442780\n", " True 441728\n", "1 True 442780\n", " False 441728\n", "Name: count, dtype: int64" ] }, "execution_count": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ "interesting_clips.groupby(\"batch_index\")[\"preference\"].value_counts()" ] }, { "cell_type": "code", "execution_count": 48, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:43.972044Z", "start_time": "2024-05-26T00:24:43.738263Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:28:37.448067Z", "iopub.status.busy": "2024-07-15T14:28:37.447919Z", "iopub.status.idle": "2024-07-15T14:28:37.512622Z", "shell.execute_reply": "2024-07-15T14:28:37.512128Z", "shell.execute_reply.started": "2024-07-15T14:28:37.448051Z" } }, "outputs": [ { "data": { "text/plain": [ "(240979,\n", " user_id\n", " 28871507 632\n", " 3249194 622\n", " 25412804 552\n", " 21005554 546\n", " 16739905 542\n", " ... \n", " 1356250 2\n", " 29400338 2\n", " 26010739 2\n", " 27935211 2\n", " 28125120 2\n", " Name: count, Length: 240979, dtype: int64)" ] }, "execution_count": 48, "metadata": {}, "output_type": "execute_result" } ], "source": [ "interesting_clips[\"user_id\"].nunique(), interesting_clips[\"user_id\"].value_counts()" ] }, { "cell_type": "code", "execution_count": 49, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:44.304573Z", "start_time": "2024-05-26T00:24:43.973218Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:28:37.513534Z", "iopub.status.busy": "2024-07-15T14:28:37.513382Z", "iopub.status.idle": "2024-07-15T14:28:38.011031Z", "shell.execute_reply": "2024-07-15T14:28:38.010478Z", "shell.execute_reply.started": "2024-07-15T14:28:37.513517Z" } }, "outputs": [ { "data": { "text/plain": [ "model_name\n", "chirp-v3p5-engine-s-8 1373736\n", "chirp-v3p5-engine-ft-1 134499\n", "chirp-v3p5-engine-upload-4 131016\n", "chirp-v3-engine-i 52558\n", "chirp-v3p5-engine-s-8-no-top-p 39716\n", "chirp-v3p5-engine-t 11009\n", "chirp-v3p5-engine-s-19 8502\n", "chirp-v3p5-engine-s-18 8412\n", "chirp-v3p5-engine-ft-2 6054\n", "chirp-v2-xxl-alpha 3514\n", "Name: count, dtype: int64" ] }, "execution_count": 49, "metadata": {}, "output_type": "execute_result" } ], "source": [ "interesting_clips[\"model_name\"].value_counts()" ] }, { "cell_type": "code", "execution_count": 50, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:44.533983Z", "start_time": "2024-05-26T00:24:44.305722Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:28:38.012835Z", "iopub.status.busy": "2024-07-15T14:28:38.012355Z", "iopub.status.idle": "2024-07-15T14:28:38.147856Z", "shell.execute_reply": "2024-07-15T14:28:38.147327Z", "shell.execute_reply.started": "2024-07-15T14:28:38.012808Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "time validation 2024-07-10 19:35:00.176571+00:00 2024-07-15 13:27:34.743993+00:00 \n", " MIN_TIME 2024-07-10 19:35:00.026310+00:00 \n", " MAX_TIME 2024-07-15 13:28:52.855742+00:00\n" ] } ], "source": [ "print(\n", " \"time validation\",\n", " interesting_clips[\"created_at\"].min(),\n", " interesting_clips[\"created_at\"].max(),\n", " \"\\n MIN_TIME\",\n", " clip_df[\"created_at\"].min(),\n", " \"\\n MAX_TIME\",\n", " clip_df[\"created_at\"].max(),\n", ")" ] }, { "cell_type": "code", "execution_count": 51, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:46.365344Z", "start_time": "2024-05-26T00:24:44.535249Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:28:38.148699Z", "iopub.status.busy": "2024-07-15T14:28:38.148542Z", "iopub.status.idle": "2024-07-15T14:28:43.374272Z", "shell.execute_reply": "2024-07-15T14:28:43.373699Z", "shell.execute_reply.started": "2024-07-15T14:28:38.148683Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "884508 1769016\n" ] } ], "source": [ "print(interesting_clips[\"request_id\"].nunique(), interesting_clips[\"id\"].nunique())" ] }, { "cell_type": "code", "execution_count": 52, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:50.674838Z", "start_time": "2024-05-26T00:24:46.366677Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:28:43.375159Z", "iopub.status.busy": "2024-07-15T14:28:43.374997Z", "iopub.status.idle": "2024-07-15T14:28:49.866945Z", "shell.execute_reply": "2024-07-15T14:28:49.866344Z", "shell.execute_reply.started": "2024-07-15T14:28:43.375142Z" } }, "outputs": [], "source": [ "interesting_clips = interesting_clips.sort_values(by=[\"request_id\", \"preference\"])" ] }, { "cell_type": "code", "execution_count": 53, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:51.600621Z", "start_time": "2024-05-26T00:24:50.676186Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:28:49.867911Z", "iopub.status.busy": "2024-07-15T14:28:49.867734Z", "iopub.status.idle": "2024-07-15T14:28:52.864661Z", "shell.execute_reply": "2024-07-15T14:28:52.864143Z", "shell.execute_reply.started": "2024-07-15T14:28:49.867893Z" } }, "outputs": [ { "data": { "text/plain": [ "model_name\n", "chirp-v2-xxl-alpha 0.020402\n", "chirp-v3-engine-i 0.039415\n", "chirp-v3p5-engine-ft-1 0.038231\n", "chirp-v3p5-engine-ft-2 0.038681\n", "chirp-v3p5-engine-s-18 0.047036\n", "chirp-v3p5-engine-s-19 0.047929\n", "chirp-v3p5-engine-s-8 0.046742\n", "chirp-v3p5-engine-s-8-no-top-p 0.045148\n", "chirp-v3p5-engine-t 0.039083\n", "chirp-v3p5-engine-upload-4 0.061466\n", "Name: count, dtype: float64" ] }, "execution_count": 53, "metadata": {}, "output_type": "execute_result" } ], "source": [ "interesting_clips[interesting_clips[\"preference\"] == True][\n", " \"model_name\"\n", "].value_counts() / clip_df[\"model_name\"].value_counts()" ] }, { "cell_type": "code", "execution_count": 54, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:56.302599Z", "start_time": "2024-05-26T00:24:51.601863Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:28:52.865564Z", "iopub.status.busy": "2024-07-15T14:28:52.865405Z", "iopub.status.idle": "2024-07-15T14:29:01.362679Z", "shell.execute_reply": "2024-07-15T14:29:01.362012Z", "shell.execute_reply.started": "2024-07-15T14:28:52.865546Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "chirp-v3-engine-i_win_over_chirp-v3-engine-i, win ratio 1.000, counts 26279\n", "chirp-v3p5-engine-ft-1_win_over_chirp-v3p5-engine-ft-1, win ratio 1.000, counts 65935\n", "chirp-v3p5-engine-ft-1_win_over_chirp-v3p5-engine-ft-2, win ratio 0.493, counts 1295\n", "chirp-v3p5-engine-ft-2_win_over_chirp-v3p5-engine-ft-1, win ratio 0.507, counts 1334\n", "chirp-v3p5-engine-ft-2_win_over_chirp-v3p5-engine-s-8, win ratio 0.387, counts 1326\n", "chirp-v3p5-engine-s-18_win_over_chirp-v3p5-engine-s-8, win ratio 0.503, counts 4232\n", "chirp-v3p5-engine-s-19_win_over_chirp-v3p5-engine-s-8, win ratio 0.508, counts 4315\n", "chirp-v3p5-engine-s-8-no-top-p_win_over_chirp-v3p5-engine-s-8, win ratio 0.482, counts 19159\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-ft-2, win ratio 0.613, counts 2099\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-18, win ratio 0.497, counts 4180\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-19, win ratio 0.492, counts 4187\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-8, win ratio 1.000, counts 651336\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-8-no-top-p, win ratio 0.518, counts 20557\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-t, win ratio 0.637, counts 7014\n", "chirp-v3p5-engine-t_win_over_chirp-v3p5-engine-s-8, win ratio 0.363, counts 3995\n", "chirp-v3p5-engine-upload-4_win_over_chirp-v3p5-engine-upload-4, win ratio 1.000, counts 65508\n" ] }, { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "get_preferfence_counts(interesting_clips)" ] }, { "cell_type": "code", "execution_count": 55, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:56.305431Z", "start_time": "2024-05-26T00:24:56.303928Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:29:01.370099Z", "iopub.status.busy": "2024-07-15T14:29:01.363585Z", "iopub.status.idle": "2024-07-15T14:29:01.392095Z", "shell.execute_reply": "2024-07-15T14:29:01.391613Z", "shell.execute_reply.started": "2024-07-15T14:29:01.370060Z" } }, "outputs": [], "source": [ "# top_user_df = interesting_clips.groupby([\"user_id\"]).filter(lambda x: len(x) > 500)\n", "# get_preferfence_counts(top_user_df)" ] }, { "cell_type": "code", "execution_count": 56, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:57.443236Z", "start_time": "2024-05-26T00:24:56.306473Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:29:01.392981Z", "iopub.status.busy": "2024-07-15T14:29:01.392826Z", "iopub.status.idle": "2024-07-15T14:29:02.316066Z", "shell.execute_reply": "2024-07-15T14:29:02.315525Z", "shell.execute_reply.started": "2024-07-15T14:29:01.392964Z" } }, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stderr", "output_type": "stream", "text": [ "/home/tony/anaconda3/envs/suno_env/lib/python3.10/site-packages/matplotlib/axes/_axes.py:6862: 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": [ "plt.hist(interesting_clips[\"dislike_count\"], bins=np.linspace(0, 10, 30))\n", "plt.yscale(\"log\")\n", "plt.xlabel(\"number of dislike_count\")\n", "plt.ylabel(\"number of clips\")\n", "plt.show()\n", "plt.hist(interesting_clips[\"upvote_count\"], bins=np.linspace(0, 10, 30))\n", "plt.yscale(\"log\")\n", "plt.xlabel(\"number of like_count\")\n", "plt.ylabel(\"number of clips\")\n", "plt.show()\n", "plt.hist(interesting_clips[\"is_public\"], bins=np.linspace(0, 10, 30))\n", "plt.yscale(\"log\")\n", "plt.xlabel(\"number of is_public\")\n", "plt.ylabel(\"number of clips\")\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 57, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:57.802320Z", "start_time": "2024-05-26T00:24:57.444414Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:29:02.317002Z", "iopub.status.busy": "2024-07-15T14:29:02.316841Z", "iopub.status.idle": "2024-07-15T14:29:02.688015Z", "shell.execute_reply": "2024-07-15T14:29:02.687494Z", "shell.execute_reply.started": "2024-07-15T14:29:02.316983Z" } }, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjoAAAGwCAYAAACgi8/jAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8fJSN1AAAACXBIWXMAAA9hAAAPYQGoP6dpAAA6FUlEQVR4nO3de1yUZf7/8ffM4NlQArSsfpX6ZUAOgpkYqXg2NVsPqbWLlFlq2daa62q1fV0PhdnZcsuyr5lrWaZu22ZW1tpJMmzxhHhKDc8gooSYCHP9/midZRTNwYEZbl/Px4PHg7nua+77M7eIb+/7uq7bZowxAgAAsCC7vwsAAACoKgQdAABgWQQdAABgWQQdAABgWQQdAABgWQQdAABgWQQdAABgWQQdAABgWQQdAABgWUH+LiBQ5Of/JNaIBgCgZrDZpNDQS361H0HnP4wRQQcAAIvh1hUAALAsgg4AALAsgg4AALAsgg4AALAsgg4AALAsgg4AALAsgg4AALAsgg4AALAsgg4AALAsgg4AALAsgg4AALAsgg4AALAsgg4AALAsnl5ehex2m+x2m0eby2XkcvGYdAAAqgNBp4rY7TY1alxfQQ7Pi2alZS4dPVJM2AEAoBoQdKqI3W5TkMOuBxdmantukSSpZZOGeuG2BNntNoIOAADVgKBTxbbnFilrX6G/ywAA4KLEYGQAAGBZBB0AAGBZBB0AAGBZBB0AAGBZBB0AAGBZBB0AAGBZBB0AAGBZBB0AAGBZBB0AAGBZBB0AAGBZBB0AAGBZBB0AAGBZlnioZ9euXdWgQQPZ7XYFBwdr/vz5/i4JAAAEAEsEHUlauHChGjRo4O8yAABAAOHWFQAAsCy/B52MjAyNHj1aHTp0kNPp1IoVK87os2DBAnXt2lWxsbEaPHiw1q9ff0afYcOGadCgQfrHP/5RHWUDAIAawO9Bp7i4WE6nU5MmTapw+7Jly5SWlqYxY8Zo6dKlioyM1IgRI5Sfn+/u8/bbb2vJkiV6+eWXNXv2bG3evLm6ygcAAAHM70EnOTlZY8eOVY8ePSrcPnfuXA0ZMkSDBg1Sy5YtNXnyZNWtW1eLFy9292natKkkqUmTJurUqZM2bdpULbUDAIDA5vegcy4lJSXKyspSUlKSu81utyspKUmZmZmSfrkiVFRUJEk6duyYVq9erZYtW/qlXgAAEFgCetZVQUGBysrKFBoa6tEeGhqqHTt2SJLy8/M1ZswYSZLL5dLgwYMVFxdX7bUCAIDAE9BB53xcddVVDEAGAAAVCuhbVyEhIXI4HB4Dj6VfruKEhYX5qSoAAFBTBHTQqV27tqKjo5Wenu5uc7lcSk9PV0JCgh8rAwAANYHfb10dO3ZMOTk57td79uxRdna2GjVqpGbNmmn48OGaMGGCYmJiFBcXp3nz5un48eMaOHCgH6sGAAA1gd+DzsaNG5Wamup+nZaWJkkaMGCApk+frj59+ujw4cOaOXOm8vLyFBUVpTlz5nDrCgAA/Cq/B53ExERt2bLlnH1SUlKUkpJSTRUBAACrCOgxOgAAABeCoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACyLoAMAACwryN8FXIwcjv/mS5fLyOUyfqwGAADrIuhUo/CGdVTmMgoOruduKy1z6eiRYsIOAABVgKBTjYLrBclht+nBhZnanluklk0a6oXbEmS32wg6AABUAYKOH2zPLVLWvkJ/lwEAgOUxGBkAAFgWQQcAAFgWQQcAAFgWQQcAAFgWQQcAAFgWQQcAAFgWQQcAAFgWQQcAAFgWQQcAAFgWQQcAAFiWZYLO8ePH1aVLFz355JP+LgUAAAQIywSdV155Ra1bt/Z3GQAAIIBYIujs2rVLO3bsUKdOnfxdCgAACCB+DzoZGRkaPXq0OnToIKfTqRUrVpzRZ8GCBeratatiY2M1ePBgrV+/3mP7k08+qYceeqi6SgYAADWE34NOcXGxnE6nJk2aVOH2ZcuWKS0tTWPGjNHSpUsVGRmpESNGKD8/X5K0YsUKXXPNNbr22murs2wAAFADBPm7gOTkZCUnJ591+9y5czVkyBANGjRIkjR58mStXLlSixcv1siRI7Vu3TotW7ZMH3/8sY4dO6bS0lI1aNBA999/f3V9BAAAEKD8HnTOpaSkRFlZWRo1apS7zW63KykpSZmZmZKkcePGady4cZKkJUuWaNu2bYQcAAAgKQBuXZ1LQUGBysrKFBoa6tEeGhqqQ4cO+akqAABQUwT0FR1vDRw40N8lAACAABLQV3RCQkLkcDjcA49Pyc/PV1hYmJ+qAgAANUVAB53atWsrOjpa6enp7jaXy6X09HQlJCT4sTIAAFAT+P3W1bFjx5STk+N+vWfPHmVnZ6tRo0Zq1qyZhg8frgkTJigmJkZxcXGaN2+ejh8/zm0qAADwq/wedDZu3KjU1FT367S0NEnSgAEDNH36dPXp00eHDx/WzJkzlZeXp6ioKM2ZM4dbVwAA4Ff5PegkJiZqy5Yt5+yTkpKilJSUaqoIAABYRUCP0QEAALgQBB0AAGBZBB0AAGBZfh+jA8nh8MybLpeRy2X8VA0AANZB0PGj8IZ1VOYyCg6u59FeWubS0SPFhB0AAC4QQcePgusFyWG36cGFmdqeWyRJatmkoV64LUF2u42gAwDABSLoBIDtuUXK2lfo7zIAALAcBiMDAADLIugAAADLIugAAADLIugAAADLIugAAADLIugAAADLIugAAADLIugAAADLIugAAADLIugAAADLIugAAADLIugAAADLIugAAADLIugAAADLIugAAADL8jroLF26VCtXrnS/njFjhtq2bavbbrtNe/fu9WVtAAAAF8TroPPKK6+oTp06kqTMzEy99dZbGj9+vBo3bqy0tDSfF3ixcjjsCgr65ctut/m7HAAAaqQgb99w4MABXX311ZKkFStWqGfPnho6dKjatGmjYcOG+bzAi014wzoqcxkFB9dzt5WWuXT0SLFcLuPHygAAqHm8vqJTv359HTlyRJL0zTffKCkpSZJUp04dnThxwqfFXYyC6wXJYbfpwYWZ6jvzKz24MFNBDq7qAABQGV5f0UlKStKf//xnRUVFadeuXUpOTpYkbdu2TVdccYXPC7xYbc8tUta+Qn+XAQBAjeb1FZ1JkyYpISFBhw8f1syZMxUSEiJJysrKUt++fX1eIAAAQGV5dUWntLRUb775pu655x5ddtllHtseeOABnxYGAABwoby6ohMUFKTXX39dpaWlVVUPAACAz3h966p9+/bKyMioiloAAAB8yuvByJ06ddIzzzyjrVu3Kjo6WvXq1fPY3q1bN58VBwAAcCG8DjqTJ0+WJM2dO/eMbTabTdnZ2RdeFQAAgA94HXQ2b95cFXUAAAD43AU91JMFAgEAQCDzOuiUlZVp1qxZ6tixoxISErR7925J0vPPP69Fixb5vEAAAIDK8jrovPzyy1q6dKnGjx+vWrVqudsjIiL03nvv+bQ4AACAC+F10Hn//fc1depU3XLLLbLb//t2p9OpHTt2+LQ4AACAC+H1YOSDBw/q//2//3dGuzGGhQSrkMPhmUldLsPTzAEA+BVeB52WLVtqzZo1ZzzAc/ny5YqKivJZYfhFeMM6KnMZBQd7rldUWubS0SPFhB0AAM7B66Bz3333aeLEiTp48KCMMfrkk0+0c+dO/f3vf9fs2bOrosaLWnC9IDnsNj24MFPbc4skSS2bNNQLtyXIbrcRdAAAOAevx+h0795dr7zyitLT01WvXj3NnDlTP/zwg1555RXdeOONVVEjJG3PLVLWvkJl7St0Bx4AAHBuXl/RkaS2bdtWuDIyAABAIPE66Ozfv182m02XXXaZJGn9+vX64IMP1LJlSw0dOtTnBQIAAFSW17euxo0bp2+//VaSlJeXpzvvvFMbNmzQc889p5deesnnBQIAAFSW10Fn27ZtiouLkyR99NFHioiI0MKFC/X0009r6dKlPi8QAACgsrwOOqWlpapdu7YkadWqVerataskqXnz5srLy/NtdQAAABfA66DTsmVLLVy4UGvWrNGqVavUqVMnSVJubq4aN27s6/oAAAAqzeug88c//lHvvPOOhg0bpr59+yoyMlKS9Pnnn7tvaQEAAAQCr2ddJSYm6ttvv1VRUZEaNWrkbh8yZIjq1at3jndWjcLCQt15550qKytTWVmZUlNTNWTIkGqvAwAABJ5KraPjcDg8Qo4kXXnllT4pyFsNGjTQggULVK9ePRUXF+vmm29Wjx49FBIS4pd6AABA4PA66HTt2lU2m+2s2z/77LMLKshbDofDfSWppKRE0i8PGAUAAPA66Nxxxx0er0tLS7Vp0yZ9/fXXGjFihNcFZGRk6PXXX9fGjRuVl5enWbNmqXv37h59FixYoNdff115eXmKjIzUY4895jEeqLCwUCkpKfrxxx/1pz/9SZdeeqnXddREPNEcAIBzu+Cgc8qCBQu0ceNGrwsoLi6W0+nUoEGDdP/995+xfdmyZUpLS9PkyZPVunVrzZs3TyNGjNDy5csVGhoqSQoODtY//vEPHTp0SPfff7969eqlsLAwr2upKXiiOQAA58frWVdn06lTJ3388cdevy85OVljx45Vjx49Ktw+d+5cDRkyRIMGDVLLli01efJk1a1bV4sXLz6jb1hYmCIjI7VmzRqv66hJyj/RvO/Mr9R35ld6cGGmghx22e1nv60IAMDFxmdBZ/ny5T5fR6ekpERZWVlKSkpyt9ntdiUlJSkzM1OSdOjQIRUV/fI0759++klr1qzRtdde69M6AhVPNAcA4Ny8vnXVv39/j8HIxhgdOnRIhw8f1qRJk3xaXEFBgcrKyty3qE4JDQ3Vjh07JEn79u3TY489JmOMjDFKSUmR0+n0aR0AAKBm8jronD5Q2Gaz6dJLL1W7du3UokULnxV2vuLi4vT+++9X+3EBAEDg8zroVDRguKqEhITI4XAoPz/foz0/P9/Sg40BAIBv+GyMTlWoXbu2oqOjlZ6e7m5zuVxKT09XQkKCHysDAAA1QaVWRvalY8eOKScnx/16z549ys7OVqNGjdSsWTMNHz5cEyZMUExMjOLi4jRv3jwdP35cAwcO9GPVAACgJvB70Nm4caNSU1Pdr9PS0iRJAwYM0PTp09WnTx8dPnxYM2fOVF5enqKiojRnzhxuXZ1F+UUEWUAQAHCxO6+gs3nzZkVERMhu9/2drsTERG3ZsuWcfVJSUpSSkuLzY1tJRYsIsoAgAOBid17JZcCAASooKJAkdevWzf09AsfpiwiygCAAAOd5RSc4OFh79uxRaGio9u7dy0MzA9ipRQQBAMB5Bp2ePXsqJSVF4eHhstlsGjRo0FlvY1X308sBAADO5ryCztSpU9WjRw/l5ORo2rRpGjx4sBo0aFDVtQEAAFyQ85511alTJ0lSVlaWUlNT1bBhwyorCgAAwBe8nl5+avq3JB04cECSdNlll/muIgAAAB/xOui4XC799a9/1dy5c1VcXCxJatCggYYPH6577723SqagAwAAVIbXQee5557Te++9p3HjxqlNmzaSpO+//14vvfSSSkpKNHbsWJ8XCQAAUBleB52lS5dq2rRp6tatm7stMjJSTZs21eTJkwk6Aab8SskSqyUDAC4uXgedo0ePqnnz5me0N2/eXEePHvVJUbhwFa2ULLFaMgDg4uL1gJrIyEgtWLDgjPYFCxYoMjLSJ0Xhwp2+UjKrJQMALkZeX9EZP368Ro0apVWrVik+Pl6StHbtWu3fv1+vvfaar+vDBWKlZADAxczrKzrt2rXT8uXL1aNHD/3000/66aef1KNHDy1fvlxt27atihoBAAAqxesrOpLUtGlTBh0DAICAx6I3AADAsip1RQc1W/kp50w3BwBYGUHnIlLRlHOmmwMArMyroGOM0f79+xUaGqo6depUVU2oIuWnnG/PLVLLJg31wm0JstttBB0AgCV5NUbHGKOePXtq//79VVUPqsGpKefbc4v8XQoAAFXKq6Bjt9t19dVX68iRI1VUDgAAgO94Petq3LhxmjFjhrZu3VoV9QAAAPiM14ORJ0yYoOPHj+s3v/mNatWqpbp163ps/+6773xWHAAAwIXwOug88sgjVVEHAACAz3kddAYMGFAVdcCPyq+rI7G2DgDAOiq1jk5OTo4WL16s3bt369FHH1VoaKi++OILNWvWTP/zP//j6xpRRSpaV0dibR0AgHV4PRj5u+++U79+/bR+/Xp98sknKi4uliRt2bJFL774os8LRNUpv65O35lfqe/Mr/TgwkwFOeyy223+Lg8AgAvmddB55pln9Ic//EFz585VrVq13O3t27fX2rVrfVkbqsmpdXVYWwcAYDVeB52tW7eqe/fuZ7RfeumlKigo8ElRAAAAvuB10LnkkkuUl5d3Rnt2draaNm3qk6IAAAB8weug07dvXz399NPKy8uTzWaTy+XS999/ryeffFL9+/evghIBAAAqx+ugM3bsWDVv3lydO3dWcXGx+vbtq5SUFCUkJOjee++tihoBAAAqxevp5bVr19a0adN03333adu2bTp27JhatWqla665pgrKAwAAqLxKraMjSc2aNdPll18uSbLZmIoMAAACj9e3riRp0aJFuvnmmxUbG6vY2FjdfPPNWrRoka9rgx85HHYFBf3yxZo6AICayusrOi+88ILeeOMNpaSkKD4+XpK0du1aPfHEE9q3b58efPBBX9eIalTRasmslAwAqKm8Djpvv/22pk6dqptvvtnd1q1bNzmdTk2dOpWgU8OVXy15e26RWjZpqBduS5DdbiPoAABqHK+DTmlpqWJiYs5oj46OVllZmU+Kgv+dWi0ZAICazOsxOr/5zW/09ttvn9H+7rvvql+/fj4pCgAAwBfO64pOWlqa+3ubzaZFixbpm2++UevWrSVJ69ev1759+1gwEAAABJTzCjqbNm3yeB0dHS1JysnJkSQ1btxYjRs31rZt23xcHgAAQOWdV9CZP39+VdcBAADgc5VeMBAXF4fDcziXy2WYhQUACHheB50TJ05o/vz5Wr16tfLz82WM5z92S5cu9Vlx8L+K1tWRWFsHAFAzeB10HnnkEX3zzTfq1auX4uLiePyDxZ2+ro4k1tYBANQYXgedlStX6tVXX9V1111XFfUgQLGuDgCgJvJ6HZ2mTZuqQYMGVVELAACAT3kddCZMmKCnn35ae/furYp6AAAAfMbrW1exsbE6ceKEunfvrrp166pWrVoe27/77jufFQcAAHAhvA46Dz30kHJzczV27FiFhYUxGBkAAAQsr4NOZmam3nnnHUVGRlZFPV7bv3+//vSnPyk/P18Oh0P33Xefevfu7e+yAABAAPA66DRv3lw///xzVdRSKQ6HQ4888oiioqKUl5engQMHKjk5WfXr1/d3aZZXfhFBFhAEAAQirwcjjxs3TtOnT9fq1atVUFCgoqIij6/q1qRJE0VFRUmSwsPDFRISoqNHj1Z7HReT8osIhoQ0UEhIAzVqXF92O7cxAQCBxesrOnfffbck6c477/RoN8bIZrMpOzvbq/1lZGTo9ddf18aNG5WXl6dZs2ape/fuHn0WLFig119/XXl5eYqMjNRjjz2muLi4M/a1ceNGuVwuXX755d59KHjl9EUEWUAQABCovA46b775pk8LKC4ultPp1KBBg3T//fefsX3ZsmVKS0vT5MmT1bp1a82bN08jRozQ8uXLFRoa6u535MgRTZgwQVOnTvVpfTg7FhEEAAQ6r4NOu3btfFpAcnKykpOTz7p97ty5GjJkiAYNGiRJmjx5slauXKnFixdr5MiRkqSSkhKNGTNG99xzj9q0aePT+gAAQM3lddDJyMg45/brr7++0sWcrqSkRFlZWRo1apS7zW63KykpSZmZmZJ+uWU2ceJEtW/fXv379/fZseE9nnAOAAg0XgedYcOGndFWfi0db8fonEtBQYHKyso8blFJUmhoqHbs2CFJ+v7777Vs2TI5nU6tWLFCkjRjxgw5nU6f1YFz4wnnAIBAdcFXdE6ePKns7Gy98MILGjt2rM8KO19t27bV5s2bq/24+C+ecA4ACFReB51LLrnkjLYbb7xRtWrV0vTp07VkyRKfFCZJISEhcjgcys/P92jPz89XWFiYz44D32BwMgAg0Hi9js7ZhIaGaufOnb7anSSpdu3aio6OVnp6urvN5XIpPT1dCQkJPj0WqobDYVdQ0H+/WGsHAFCdvL6iU9FtotzcXL322muVeizEsWPHlJOT4369Z88eZWdnq1GjRmrWrJmGDx+uCRMmKCYmRnFxcZo3b56OHz+ugQMHen0sVB/G7QAAAoHXQad///6y2WwyxvMfqvj4eD3++ONeF7Bx40alpqa6X6elpUmSBgwYoOnTp6tPnz46fPiwZs6cqby8PEVFRWnOnDncugpwjNsBAAQCr4POZ5995vHabrfr0ksvVZ06dSpVQGJiorZs2XLOPikpKUpJSanU/uFfjNsBAPiT10HniiuuqIo6AAAAfM7roCNJ6enpSk9PV35+vlwul8e2U7eegLPhqecAgOriddB56aWXNGvWLMXExCg8PNxjsUDgXCoaoMzgZABAVfI66CxcuFBpaWk8bgFe46nnAIDq5nXQOXnyJA/OxAVhgDIAoLp4vWDgrbfeqg8++KAqagEAAPApr6/onDhxQu+++67S09PldDoVFOS5i4cffthnxQEAAFwIr4POli1b3Csgb9261WMbA5MBAEAg8TrozJ8/vyrqAAAA8DmfPdQTAAAg0BB0AACAZRF0AACAZRF0AACAZVXqWVdAVbLbbbLb/zuDj+dhAQAqi6ADvyv/kE+bzaaGl9RVULk2nocFAKgsgg78pqKHfJ7C87AAAL5A0IHfnP6QT0nq7AzX+F6RPA8LAOATBB34XflQ0yK8gZ+rAQBYCbOuAACAZXFFBzUSM7MAAOeDoIMax263qVHj+szMAgD8KoIOahy73aYgh52ZWQCAX0XQQY3FzCwAwK9hMDIAALAsgg4AALAsgg4AALAsxujAspiCDgAg6MCSmIIOAJAIOrAopqADACSCDiyOKegAcHEj6KBGcJS7BVX+ewAAzoWgg4AW3rCOylxGwcH1fLK/00MSA5QBwNoIOghowfWC5LDb3GNtJKmzM1zje0V6tZ+zBSYGKAOAtRF0UCOUH2vTIryB1++vKDAxQBkArI+gg4sKg5MB4OLCqE4AAGBZBB0AAGBZBB0AAGBZjNGBZbDWDgDgdAQd1Hi+XmsHAGAdBB3UeL5aawcAYD0EHVjGha61AwCwHgYyAAAAy+KKDlCO3W6T3W7zaON5WABQcxF0gP+w221q1Li+gk6bscXzsACg5iLoAP9ht9sU5LDzPCwAsBCCDnAanocFANbBYGQAAGBZBB0AAGBZlgg6Y8aM0fXXX68HHnjA36UAAIAAYomgk5qaqieffNLfZQAAgABjiaCTmJioBg1YCRdVx+GwKyjov1+nr7UDAAhMfg86GRkZGj16tDp06CCn06kVK1ac0WfBggXq2rWrYmNjNXjwYK1fv94PleJiVP6BoSEhDdxfjRrXJ+wAQA3g96BTXFwsp9OpSZMmVbh92bJlSktL05gxY7R06VJFRkZqxIgRys/Pr+ZKcTEq/8DQvjO/Ut+ZX+nBhZkKcnBVBwBqAr+vo5OcnKzk5OSzbp87d66GDBmiQYMGSZImT56slStXavHixRo5cmR1lQkLc/xnJWSH4+y5n7V1AKBm8vsVnXMpKSlRVlaWkpKS3G12u11JSUnKzMz0Y2WwgtNvSwUH1/N3SQAAH/P7FZ1zKSgoUFlZmUJDQz3aQ0NDtWPHDvfrO++8U5s3b9bx48fVqVMnvfDCC0pISKjuclHDlL8ttT23SJ2d4RrfK9LfZQEAfCigg875euONN/xdAmqwU7elWoR7N3Ov/K0unnAOAIEpoINOSEiIHA7HGQOP8/PzFRYW5qeqcLErf8vrFJ5wDgCBKaDH6NSuXVvR0dFKT093t7lcLqWnp3NrCn5z+kwsZmEBQODy+xWdY8eOKScnx/16z549ys7OVqNGjdSsWTMNHz5cEyZMUExMjOLi4jRv3jwdP35cAwcO9GPVADOxAKAm8HvQ2bhxo1JTU92v09LSJEkDBgzQ9OnT1adPHx0+fFgzZ85UXl6eoqKiNGfOHG5dAQCAX+X3oJOYmKgtW7acs09KSopSUlKqqSIAAGAVAT1GBwAA4EL4/YoOYBWnr6zMlHMA8D+CDnCBKppuLjHlHAACAUEHuECnr7AsSS2bNNQLtyXIbrcRdADAjwg6gI8w3RwAAg+DkQEAgGURdAAAgGURdAAAgGURdAAAgGURdAAAgGUx6wqoJna77YwnnPtqUcGq3DcA1GQEHaAa2O02NWpcX0GnrZ7si0UFq3LfAFDTEXSAamC32xTksFfJooJVuW8AqOkIOkA1qspFBVmwEADOxGBkAABgWQQdAABgWdy6AvzMUW4QsVVmSjELDECgIOgAfhLesI7KXEbBwfXcbVaYKcUsMACBhKAD+ElwvSA57Db3bCmrzJRiFhiAQELQAfzMqrOlrPq5ANQsDEYGAACWRdABAACWRdABAACWRdABAACWxWBkoAqdWiPH4aj8/ykqWpOmomN4u01ibRsA1kfQAapARWvkVEZFa9KUuYwc5wg+Zzt+Re9jbRsAVkfQAarA6WvkdHaGa3yvSK/3c/qaNKf2U36Nmor2fbbjs7YNgIsNQQeoQqfWkmkR3sCn+ym/Rs259n2u9wHAxYDByAAAwLIIOgAAwLIIOgAAwLIIOgAAwLIIOgAAwLIIOgAAwLIIOgAAwLJYRweA2689buJsfPUoiYqOf/q+z6dPZY9Vkao6PoDqQdABIKnix01IZz46oqoeJXG245ff9/n0uZBj/dpn89XxAVQfgg4ASWc+bkLSGY+OqMpHSVR0/NP3fT59fPVZq/L4AKoPQQeAh4oeL1Gdj5I4n3376vjn+qzVcXwAVY/ByAAAwLIIOgAAwLIIOgAAwLIIOgAAwLIIOgAAwLIIOgAAwLIIOgAAwLIIOgAAwLIIOgAAwLIIOgAAwLIIOgAAwLIsEXT+9a9/qVevXurZs6cWLVrk73IAAECAqPEP9SwtLdX06dP15ptvqmHDhho4cKC6d++ukJAQf5cGAAD8rMZf0Vm/fr1atmyppk2bqkGDBurUqZO++eYbf5cFAAACgN+DTkZGhkaPHq0OHTrI6XRqxYoVZ/RZsGCBunbtqtjYWA0ePFjr1693b8vNzVXTpk3dr5s2baqDBw9WS+0AACCw+T3oFBcXy+l0atKkSRVuX7ZsmdLS0jRmzBgtXbpUkZGRGjFihPLz86u5UsCaHA67goLscjgu7NdBZfZjt9sUFOSb459tvxV9eXssX50jX/i1zxYUZJfdbvN3mUDA8PsYneTkZCUnJ591+9y5czVkyBANGjRIkjR58mStXLlSixcv1siRI9WkSROPKzgHDx5UXFxcldcN1HThDeuozGUUHFzPL/ux221q1Li+gnwcHs623zKXkcPLAOCrc+Qr5/vZSstcOnqkWC6Xqe4SgYDj96BzLiUlJcrKytKoUaPcbXa7XUlJScrMzJQkxcXFadu2bTp48KAaNmyoL7/8Uvfdd5+/SgZqjOB6QXLYbXpwYaa25xapszNc43tFVtt+7Habghz2Cz7+r+1Xknvf3h7LV+fIV87ns7Vs0lAv3JYgu91G0AEU4EGnoKBAZWVlCg0N9WgPDQ3Vjh07JElBQUGaMGGCUlNT5XK5dPfddzPjCvDC9twiZe0rVIvwBn7Zj6+Of7b9SnLvO9BqrKxzfTYAngI66Jyvbt26qVu3bv4uAwAABBj/j6w7h5CQEDkcjjMGHufn5yssLMxPVQEAgJoioINO7dq1FR0drfT0dHeby+VSenq6EhIS/FgZAACoCfx+6+rYsWPKyclxv96zZ4+ys7PVqFEjNWvWTMOHD9eECRMUExOjuLg4zZs3T8ePH9fAgQP9WDUAAKgJ/B50Nm7cqNTUVPfrtLQ0SdKAAQM0ffp09enTR4cPH9bMmTOVl5enqKgozZkzh1tXAADgV/k96CQmJmrLli3n7JOSkqKUlJRqqggAAFhFQI/RAQAAuBAEHQAAYFkEHQAAYFkEHQAAYFkEHQAAYFkEHQAAYFkEHQAAYFl+X0cnUNhsVbPferUdaljnl9NcN8ju0Xb668r2qcp9X0w1+vtz1Kvt0Cmn/zwGSo2V7VPZz3a293nbpyr/rM/12apKZX+OACs5359vmzHGVG0pAAAA/sGtKwAAYFkEHQAAYFkEHQAAYFkEHQAAYFkEHQAAYFkEHQAAYFkEHQAAYFkEHQAAYFkEHQAAYFkEHQAAYFkEnSqyYMECde3aVbGxsRo8eLDWr1/v75JqjNmzZ2vQoEFKSEjQDTfcoPvuu087duzw6HPixAlNnjxZiYmJSkhI0O9//3sdOnTIo8++ffs0cuRItW7dWjfccIOefPJJlZaWVudHqVFeffVVOZ1OPf744+42zrPvHDx4UH/84x+VmJiouLg49evXTxs2bHBvN8bohRdeUIcOHRQXF6c777xTu3bt8tjHkSNHNG7cOLVp00Zt27bVI488omPHjlXzJwlcZWVlev7559W1a1fFxcWpe/fumjVrlso/6Yjz7L2MjAyNHj1aHTp0kNPp1IoVKzy2++qcbt68Wb/97W8VGxur5ORkvfbaa775AAY+9+GHH5ro6Gjz3nvvmW3btpk///nPpm3btubQoUP+Lq1GuOuuu8zixYvN1q1bTXZ2trnnnntM586dzbFjx9x9/vd//9ckJyebVatWmQ0bNpghQ4aYoUOHureXlpaam2++2dx5551m06ZNZuXKlSYxMdE888wz/vhIAW/dunWmS5cupl+/fmbatGnuds6zbxw5csR06dLFTJw40axbt87k5OSYr776yvz444/uPrNnzzbXXXed+fTTT012drYZPXq06dq1q/n555/dfUaMGGFuueUWs3btWpORkWF69OhhHnroIX98pID08ssvm3bt2pl//etfZvfu3eajjz4y8fHxZt68ee4+nGfvrVy50jz77LPmk08+MREREebTTz/12O6Lc/rTTz+ZpKQkM27cOLN161bzz3/+08TFxZmFCxdecP0EnSpw6623msmTJ7tfl5WVmQ4dOpjZs2f7saqaKz8/30RERJjvvvvOGGNMYWGhiY6ONh999JG7z/bt201ERITJzMw0xvzyFzMyMtLk5eW5+7z11lumTZs25sSJE9Vaf6ArKioyPXv2NN98841JSUlxBx3Os+889dRT5vbbbz/rdpfLZW688UYzZ84cd1thYaGJiYkx//znP40x/z3369evd/f54osvjNPpNAcOHKi64muQkSNHmocfftij7f777zfjxo0zxnCefeH0oOOrc7pgwQJz/fXXe/zeeOqpp0yvXr0uuGZuXflYSUmJsrKylJSU5G6z2+1KSkpSZmamHyuruX766SdJUqNGjSRJGzdu1MmTJz3OcYsWLdSsWTOtXbtWkrR27VpFREQoLCzM3adDhw4qKirS9u3bq6/4GmDKlClKTk72OJ8S59mXPv/8c8XExOiBBx7QDTfcoP79++vdd991b9+zZ4/y8vI8zvUll1yi1q1bu39vZGZmKjg4WLGxse4+SUlJstvt3Br/j4SEBH377bfauXOnpF9uhXz//ffq1KmTJM5zVfDVOV27dq3atm2r2rVru/t06NBBO3fu1NGjRy+oxqALejfOUFBQoLKyMoWGhnq0h4aGnjHOBL/O5XLpiSeeUJs2bRQRESFJOnTokGrVqqXg4GCPvqGhocrLy3P3Kf+PryT361N9IH344YfatGmT3nvvvTO2cZ59Z/fu3Xr77bc1fPhwjR49Whs2bNC0adNUq1YtDRgwwH2uKvq9cWpM1KFDh3TppZd6bA8KClKjRo041/8xcuRIFRUVqXfv3nI4HCorK9PYsWN1yy23SBLnuQr46pweOnRIV155pUefU79LDh065P6PbmUQdBDQJk+erG3btumtt97ydymWs3//fj3++OP6v//7P9WpU8ff5ViaMUYxMTF66KGHJEmtWrXStm3btHDhQg0YMMDP1VnHRx99pA8++EDPPPOMWrZsqezsbKWlpalJkyac54sYt658LCQkRA6HQ/n5+R7t+fn5Z/zPF+c2ZcoUrVy5UvPmzdNll13mbg8LC9PJkydVWFjo0T8/P1/h4eHuPqfPDjr1+lSfi11WVpby8/M1cOBAtWrVSq1atdJ3332n+fPnq1WrVpxnHwoPD1eLFi082po3b659+/a5t0s65++NsLAwHT582GN7aWmpjh49yrn+jxkzZmjkyJHq27evnE6n+vfvrzvuuEOzZ8+WxHmuCr46p+f6XXKh/3YSdHysdu3aio6OVnp6urvN5XIpPT1dCQkJfqys5jDGaMqUKfr00081b948XXXVVR7bY2JiVKtWLY9zvGPHDu3bt0/x8fGSpPj4eG3dutXjL9+qVavUsGFDtWzZslo+R6Br3769PvjgA/397393f8XExKhfv37u7znPvtGmTRv3uJFTdu3apSuuuEKSdOWVVyo8PNzjXBcVFWndunXu3xsJCQkqLCzUxo0b3X2+/fZbuVwuxcXFVcOnCHw///yzbDabR5vD4XBPL+c8+56vzml8fLzWrFmjkydPuvusWrVK11577QXdtpLE9PKq8OGHH5qYmBizZMkSs337dvPYY4+Ztm3besxMwdlNmjTJXHfddWb16tUmNzfX/XX8+HF3n//93/81nTt3Nunp6WbDhg1m6NChFU57vuuuu0x2drb58ssvTfv27Zn2/CvKz7oyhvPsK+vWrTOtWrUyL7/8stm1a5f5xz/+YVq3bm3ef/99d5/Zs2ebtm3bmhUrVpjNmzebe++9t8Ipuv379zfr1q0za9asMT179ryopz2fbsKECaZjx47u6eWffPKJSUxMNDNmzHD34Tx7r6ioyGzatMls2rTJREREmLlz55pNmzaZvXv3GmN8c04LCwtNUlKSGT9+vNm6dav58MMPTevWrZleHsjmz59vOnfubKKjo82tt95q1q5d6++SaoyIiIgKvxYvXuzu8/PPP5u//OUv5vrrrzetW7c2Y8aMMbm5uR772bNnj7n77rtNXFycSUxMNNOnTzcnT56s7o9To5wedDjPvvP555+bm2++2cTExJibbrrJvPPOOx7bXS6Xef75501SUpKJiYkxd9xxh9mxY4dHn4KCAvPQQw+Z+Ph406ZNGzNx4kRTVFRUnR8joP30009m2rRppnPnziY2NtZ069bNPPvssx5TljnP3vv2228r/J08YcIEY4zvzml2dra5/fbbTUxMjOnYsaPPlmSxGVNuyUgAAAALYYwOAACwLIIOAACwLIIOAACwLIIOAACwLIIOAACwLIIOAACwLIIOAACwLIIOAACwLIIOYFHDhg3T448/7u8y3Iwxeuyxx9SuXTs5nU5lZ2dXew3vvPOOkpOTFRkZqTfeeKPajx/InE6nVqxYIUnas2eP3/6MAF8L8ncBAC4OX375pZYuXao333xTV111lUJCQqr1+EVFRZo6daomTpyonj176pJLLqnW49ckl19+ub7++utq/zMCqgJBB8B5Kysrk81mk93u/cXg3bt3Kzw8XG3atPFpTSUlJapdu/av9tu3b59Onjyp5ORkNWnSpNLHO3nypGrVqlXp99cEDodD4eHh/i4D8AluXQFVaNiwYZo2bZpmzJihdu3a6cYbb9SLL77o3l7RLYLCwkI5nU6tXr1akrR69Wo5nU599dVX6t+/v+Li4pSamqr8/Hx98cUX6t27t9q0aaNx48bp+PHjHscvKyvTlClTdN111ykxMVHPP/+8yj/erqSkRE8++aQ6duyo+Ph4DR482H1cSVqyZInatm2rzz77TH369FFsbKz27dtX4Wf97rvvdOuttyomJkYdOnTQ008/rdLSUknSxIkTNXXqVO3bt09Op1Ndu3atcB+njrdixQr17NlTsbGxGjFihPbv3+/u8+KLL+o3v/mNFi1apK5duyouLs593h599FG1b99ebdq0UWpqqjZv3uzeb79+/SRJ3bt3l9Pp1J49eyRJK1as0IABAxQbG6tu3brppZdectct/XJL56233tLo0aMVHx+vV1555bzft2jRIo0ZM0atW7dWz5499dlnn3l83m3btmnUqFFq06aNEhIS9Nvf/lY5OTnu7YsWLVLv3r0VGxurm266SQsWLPD4s5syZYo6dOig2NhYdenSRbNnz67wvJ7y3nvvqW/fvu4/oylTplTY7/Sfy1M/gytXrlS/fv0UGxurIUOGaOvWre737N27V6NHj9b111+v+Ph49e3bV1988cU56wGqhU8eDQqgQikpKaZNmzbmxRdfNDt37jRLly41TqfTfP3118YYY3bv3m0iIiLMpk2b3O85evSoiYiIMN9++60x5r9PDh4yZIhZs2aNycrKMj169DApKSnmrrvuMllZWSYjI8O0a9fO42m/KSkpJj4+3kybNs388MMP5v333zetW7f2eGr2o48+aoYOHWoyMjLMjz/+aObMmWNiYmLMzp07jTHGLF682ERHR5uhQ4ea77//3vzwww+muLj4jM954MAB07p1a/OXv/zFbN++3Xz66acmMTHRzJw50xhjTGFhoXnppZdMp06dTG5ursnPz6/wfJ063sCBA82///1vs2HDBnPrrbeaoUOHuvvMnDnTxMfHmxEjRpisrCyTnZ1tjDHmzjvvNKNGjTLr1683O3fuNNOnTzft2rUzBQUF5vjx42bVqlUmIiLCrFu3zuTm5prS0lKTkZFh2rRpY5YsWWJycnLM119/bbp06WJefPFF9/EiIiLMDTfcYN577z2Tk5Nj9u7de97v69Spk/nggw/Mrl27zNSpU018fLwpKChwn7N27dqZ+++/36xfv97s2LHDvPfee+aHH34wxhjz/vvvmxtvvNF8/PHHJicnx3z88cemXbt2ZsmSJcYYY+bMmWOSk5NNRkaG2bNnj8nIyDAffPDBWX8WFyxYYGJjY80bb7xhduzYYdatW2fmzp3rUe+nn35qjDnz5/LUz2Dv3r3N119/bTZv3mxGjRplunTpYkpKSowxxowcOdIMHz7cbN682eTk5JjPP//cfPfdd2etB6guBB2gCqWkpJjbb7/do23QoEHmqaeeMsZ4F3RWrVrl7jN79mwTERFhcnJy3G2PPfaYueuuuzyO3bt3b+NyudxtTz31lOndu7cxxpi9e/eaqKgoc+DAAY/67rjjDvPMM88YY34JHhEREe4wcTbPPvus6dWrl8ex/va3v5n4+HhTVlZmjDFm7ty5pkuXLufcz6njrV271t22fft2d0Ax5pegEx0d7RGWTgWPEydOeOyve/fuZuHChcYYYzZt2mQiIiLM7t27PT7rK6+84vGev//97+bGG290v46IiDCPP/64R5/zfd9zzz3nfn3s2DETERFhvvjiC2OMMc8884zp2rWrOyicrnv37mcEl1mzZrlD39SpU01qaqrHOT+XDh06mGefffas288n6Hz44Yfu/gUFBSYuLs7ddvPNN3sEPSBQMEYHqGJOp9PjdXh4uPLz8y9oP6GhoapXr56uuuoqd1tYWJg2bNjg8Z7WrVvLZrO5X8fHx2vu3LkqKyvT1q1bVVZWpptuusnjPSUlJWrcuLH7da1atc74DKf74YcflJCQ4HGs6667TsXFxTpw4ICaNWt23p8zKChIsbGx7tctWrRQcHCwfvjhB/dtqmbNmunSSy9199myZYuKi4uVmJjosa+ff/7Z41bQ6TZv3qx///vf7ttR0i+3+06cOKHjx4+rXr16kqSYmJhKva/8eatfv74aNmyow4cPS5Kys7PVtm3bCsf7FBcXKycnR48++qgee+wxd3tpaal7EPWAAQN011136aabblLHjh3VuXNndejQocLPmZ+fr9zcXN1www1nPRfnIz4+3v1948aNde2112rHjh2SpNTUVP3lL3/R119/raSkJPXs2VORkZEXdDzAFwg6QBULCvL8a2az2dzjZE4N6jXlxs2UH+dxtv3YbLYK9+tyuc67ruLiYjkcDi1evFgOh8NjW/369d3f161b1yPABIJTQeKUY8eOKTw8XPPnzz+j77lmVxUXF+v3v/+9evbseca2OnXquL8vfz68ed/pIab8n1HdunXPWZckTZ06Va1bt/bYdupnJjo6Wp999pm+/PJLrVq1Sn/4wx+UlJSkmTNnnrOmqjJ48GB16NBBK1eu1DfffKNXX31VEyZM0LBhw6r82MC5EHQAPzp1VSIvL8/d5su1S9avX+/xet26dbr66qvlcDgUFRWlsrIyHT58WG3btr2g47Ro0UIff/yxjDHuUPT999+rQYMGuuyyy7zaV2lpqTZu3Oi+erNjxw4VFhaqRYsWZ31PdHS0Dh06JIfDoSuvvPK8j9WqVSvt3LlTV199tVc1VvZ95TmdTi1durTCWVxhYWFq0qSJdu/erVtuueWs+2jYsKH69OmjPn36qFevXrr77rt15MgRjytyp/pdccUVSk9PV/v27Std89q1a91X544ePapdu3apefPm7u2XX365br/9dt1+++165pln9O677xJ04HcEHcCP6tatq/j4eL366qu68sorlZ+fr+eff95n+9+3b5/S0tI0dOhQbdq0SX/72980YcIESdK1116rfv366U9/+pMmTpyoqKgoFRQUKD09XU6nU507dz7v4/z2t7/VvHnzNHXqVP3ud7/Tzp079eKLL2r48OFeT0WvVauWpk6dqj//+c9yOByaOnWq4uPj3cGnIklJSYqPj9eYMWM0fvx4XXPNNcrNzdUXX3yh7t27e9wKK2/MmDEaPXq0mjVrpl69eslut2vz5s3aunWrxo4de9bjVfZ95f3ud7/T/Pnz9dBDD2nkyJG65JJLtHbtWsXFxal58+Z64IEHNG3aNF1yySXq2LGjSkpKtHHjRhUWFmr48OGaO3euwsPDFRUVJbvdruXLlys8PFzBwcEVHu/3v/+9Jk2apNDQUHXq1EnHjh3Tv//9b6+CyF//+leFhIQoNDRUzz33nEJCQtS9e3dJ0uOPP65OnTrpmmuuUWFhoVavXn3OcApUF4IO4GdPPPGEHn30UQ0cOFDXXnutxo8fr7vuussn++7fv79+/vlnDR48WA6HQ6mpqRo6dKh7e1paml5++WVNnz5dubm5aty4seLj470KOZLUtGlTvfrqq5oxY4beffddNW7cWLfeeqvuvfder2uuW7eu7rnnHo0bN04HDx5U27Ztf3WFZ5vNpldffVXPP/+8Hn74YRUUFCgsLExt27ZVWFjYWd/XsWNHvfLKK5o1a5Zee+01BQUFqXnz5ho8ePA5j1fZ95UXEhKiefPm6amnntKwYcNkt9sVFRWl6667TtIvt4Lq1q2r119/XTNmzFD9+vUVERGhO+64Q5LUoEEDzZkzRz/++KPsdrtiY2P16quvnjVYDhgwQCdOnNAbb7yhGTNmqHHjxmeMz/o148aN0+OPP65du3YpKipKL7/8snsNI5fLpSlTpujAgQNq2LChOnbsqIcfftir/QNVwWbKDw4AAD9asmSJnnjiCa1Zs8bfpaCc1atXKzU1VRkZGWe9YgQEKhYMBAAAlkXQAQAAlsWtKwAAYFlc0QEAAJZF0AEAAJZF0AEAAJZF0AEAAJZF0AEAAJZF0AEAAJZF0AEAAJZF0AEAAJb1/wEODKp7cA8x/wAAAABJRU5ErkJggg==", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.hist(interesting_clips[\"user_id\"].value_counts(), bins=np.linspace(0, 1000, 100))\n", "plt.yscale(\"log\")\n", "plt.xlabel(\"number of preferences clips\")\n", "plt.ylabel(\"number of users\")\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 58, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:58.153310Z", "start_time": "2024-05-26T00:24:57.858363Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:29:02.688944Z", "iopub.status.busy": "2024-07-15T14:29:02.688779Z", "iopub.status.idle": "2024-07-15T14:29:02.710554Z", "shell.execute_reply": "2024-07-15T14:29:02.710093Z", "shell.execute_reply.started": "2024-07-15T14:29:02.688926Z" } }, "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": 59, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:58.890520Z", "start_time": "2024-05-26T00:24:58.154350Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:29:02.711357Z", "iopub.status.busy": "2024-07-15T14:29:02.711205Z", "iopub.status.idle": "2024-07-15T14:29:05.022956Z", "shell.execute_reply": "2024-07-15T14:29:05.022291Z", "shell.execute_reply.started": "2024-07-15T14:29:02.711340Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(1712944, 42)\n" ] } ], "source": [ "user_intersting_clips = interesting_clips[\n", " interesting_clips[\"model_name\"].str.contains(\"v3p5\") # general 3.5\n", " # interesting_clips[\"model_name\"].str.contains(\"upload\") # only uploads\n", "].copy()\n", "print(user_intersting_clips.shape)" ] }, { "cell_type": "code", "execution_count": 60, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:59.204547Z", "start_time": "2024-05-26T00:24:58.891851Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:29:05.023959Z", "iopub.status.busy": "2024-07-15T14:29:05.023780Z", "iopub.status.idle": "2024-07-15T14:29:05.416849Z", "shell.execute_reply": "2024-07-15T14:29:05.416311Z", "shell.execute_reply.started": "2024-07-15T14:29:05.023939Z" } }, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.hist(user_intersting_clips[\"user_id\"].value_counts(), bins=np.linspace(0, 802, 100))\n", "plt.yscale(\"log\")\n", "plt.xlabel(\"number of preferences\")\n", "plt.ylabel(\"number of users\")\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 61, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:59.207707Z", "start_time": "2024-05-26T00:24:59.205659Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:29:05.417772Z", "iopub.status.busy": "2024-07-15T14:29:05.417608Z", "iopub.status.idle": "2024-07-15T14:29:05.440094Z", "shell.execute_reply": "2024-07-15T14:29:05.439616Z", "shell.execute_reply.started": "2024-07-15T14:29:05.417753Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "finally 1712944 requests 856472.0 frac 0.0877873817477353\n" ] } ], "source": [ "print(\n", " \"finally\",\n", " user_intersting_clips.shape[0],\n", " \"requests\",\n", " user_intersting_clips.shape[0] / 2,\n", " \"frac\",\n", " user_intersting_clips.shape[0] / total_clip_counts,\n", ")" ] }, { "cell_type": "code", "execution_count": 62, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:59.496996Z", "start_time": "2024-05-26T00:24:59.208750Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:29:05.440888Z", "iopub.status.busy": "2024-07-15T14:29:05.440738Z", "iopub.status.idle": "2024-07-15T14:29:05.875433Z", "shell.execute_reply": "2024-07-15T14:29:05.874871Z", "shell.execute_reply.started": "2024-07-15T14:29:05.440871Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
indextime_useduser_idupvote_countbatch_indexdislike_countflag_countplay_countskip_countuser_n_clipsdiff_preference
count1.712944e+061.712944e+061.712944e+061.712944e+061712944.01.712944e+061.712944e+061.712944e+061712944.01.712944e+061.712944e+06
mean9.656475e+061.395188e+021.784845e+073.597356e-010.51.052352e-011.019590e-022.609816e+000.01.448244e+023.147178e-01
std5.602627e+065.708663e+019.540311e+065.362078e-010.53.070541e-011.085210e+002.660276e+010.02.649325e+026.651682e-01
min4.000000e+002.271236e+002.000000e+01-1.000000e+000.0-1.000000e+000.000000e+000.000000e+000.02.000000e+00-1.000000e+00
25%4.840176e+061.019368e+029.086707e+060.000000e+000.00.000000e+000.000000e+001.000000e+000.02.000000e+010.000000e+00
50%9.603652e+061.349772e+022.102608e+070.000000e+000.50.000000e+000.000000e+001.000000e+000.05.000000e+010.000000e+00
75%1.446836e+071.732394e+022.672823e+071.000000e+001.00.000000e+000.000000e+003.000000e+000.01.670000e+021.000000e+00
max1.951183e+075.313802e+022.947271e+071.340000e+021.08.000000e+001.001000e+031.819000e+040.06.110000e+031.000000e+00
\n", "
" ], "text/plain": [ " index time_used user_id upvote_count batch_index dislike_count flag_count play_count skip_count user_n_clips diff_preference\n", "count 1.712944e+06 1.712944e+06 1.712944e+06 1.712944e+06 1712944.0 1.712944e+06 1.712944e+06 1.712944e+06 1712944.0 1.712944e+06 1.712944e+06\n", "mean 9.656475e+06 1.395188e+02 1.784845e+07 3.597356e-01 0.5 1.052352e-01 1.019590e-02 2.609816e+00 0.0 1.448244e+02 3.147178e-01\n", "std 5.602627e+06 5.708663e+01 9.540311e+06 5.362078e-01 0.5 3.070541e-01 1.085210e+00 2.660276e+01 0.0 2.649325e+02 6.651682e-01\n", "min 4.000000e+00 2.271236e+00 2.000000e+01 -1.000000e+00 0.0 -1.000000e+00 0.000000e+00 0.000000e+00 0.0 2.000000e+00 -1.000000e+00\n", "25% 4.840176e+06 1.019368e+02 9.086707e+06 0.000000e+00 0.0 0.000000e+00 0.000000e+00 1.000000e+00 0.0 2.000000e+01 0.000000e+00\n", "50% 9.603652e+06 1.349772e+02 2.102608e+07 0.000000e+00 0.5 0.000000e+00 0.000000e+00 1.000000e+00 0.0 5.000000e+01 0.000000e+00\n", "75% 1.446836e+07 1.732394e+02 2.672823e+07 1.000000e+00 1.0 0.000000e+00 0.000000e+00 3.000000e+00 0.0 1.670000e+02 1.000000e+00\n", "max 1.951183e+07 5.313802e+02 2.947271e+07 1.340000e+02 1.0 8.000000e+00 1.001000e+03 1.819000e+04 0.0 6.110000e+03 1.000000e+00" ] }, "execution_count": 62, "metadata": {}, "output_type": "execute_result" } ], "source": [ "user_intersting_clips.describe()\n", "# 214202\n", "# 608730\n", "# 1376250\n", "# 4625842" ] }, { "cell_type": "code", "execution_count": 63, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:59.685498Z", "start_time": "2024-05-26T00:24:59.498024Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:29:05.876386Z", "iopub.status.busy": "2024-07-15T14:29:05.876221Z", "iopub.status.idle": "2024-07-15T14:29:05.906146Z", "shell.execute_reply": "2024-07-15T14:29:05.905645Z", "shell.execute_reply.started": "2024-07-15T14:29:05.876368Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "time validation 2024-07-10 19:35:00.176571+00:00 2024-07-15 13:27:17.904088+00:00\n" ] } ], "source": [ "print(\n", " \"time validation\",\n", " user_intersting_clips[\"created_at\"].min(),\n", " user_intersting_clips[\"created_at\"].max(),\n", ")" ] }, { "cell_type": "code", "execution_count": 64, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:24:59.900268Z", "start_time": "2024-05-26T00:24:59.686528Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:29:05.906992Z", "iopub.status.busy": "2024-07-15T14:29:05.906833Z", "iopub.status.idle": "2024-07-15T14:29:06.330129Z", "shell.execute_reply": "2024-07-15T14:29:06.329482Z", "shell.execute_reply.started": "2024-07-15T14:29:05.906975Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "time validation NaT\n" ] } ], "source": [ "print(\n", " \"time validation\",\n", " user_intersting_clips[\n", " user_intersting_clips[\"model_name\"] == \"chirp-v3p5-engine-ft\"\n", " ][\"created_at\"].max(),\n", ")" ] }, { "cell_type": "code", "execution_count": 65, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:00.171091Z", "start_time": "2024-05-26T00:24:59.901340Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:29:06.331092Z", "iopub.status.busy": "2024-07-15T14:29:06.330929Z", "iopub.status.idle": "2024-07-15T14:29:06.376906Z", "shell.execute_reply": "2024-07-15T14:29:06.376363Z", "shell.execute_reply.started": "2024-07-15T14:29:06.331075Z" } }, "outputs": [], "source": [ "# v3 launch test time # 2024-04-03 07:47:01.770988+00:00 t1\n", "# v3.5 launch time: 2024-05-19 05:21:54\n", "# latest exp time: '2024-05-29 04:01:39'\n", "date_cut = \"2024-06-04 15:21:36\"" ] }, { "cell_type": "code", "execution_count": 66, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:00.375833Z", "start_time": "2024-05-26T00:25:00.172648Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:29:06.377964Z", "iopub.status.busy": "2024-07-15T14:29:06.377803Z", "iopub.status.idle": "2024-07-15T14:29:06.508556Z", "shell.execute_reply": "2024-07-15T14:29:06.508001Z", "shell.execute_reply.started": "2024-07-15T14:29:06.377947Z" } }, "outputs": [], "source": [ "user_intersting_clips[\"is_pro_user\"] = user_intersting_clips[\"user_id\"].isin(pro_users)" ] }, { "cell_type": "code", "execution_count": 67, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:00.484734Z", "start_time": "2024-05-26T00:25:00.377280Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:29:06.509445Z", "iopub.status.busy": "2024-07-15T14:29:06.509291Z", "iopub.status.idle": "2024-07-15T14:29:06.526794Z", "shell.execute_reply": "2024-07-15T14:29:06.526270Z", "shell.execute_reply.started": "2024-07-15T14:29:06.509429Z" } }, "outputs": [], "source": [ "# def parse_for_tag(x):\n", "# if \"tags\" not in x:\n", "# return \"\"\n", "# out = x.get(\"tags\", \"\")\n", "# return out.lower() if out else \"\"\n", "\n", "# user_intersting_clips[\"tags\"] = user_intersting_clips[\"metadata\"].apply(parse_for_tag)" ] }, { "cell_type": "code", "execution_count": 68, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:00.893917Z", "start_time": "2024-05-26T00:25:00.485775Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:29:06.527772Z", "iopub.status.busy": "2024-07-15T14:29:06.527623Z", "iopub.status.idle": "2024-07-15T14:29:18.755348Z", "shell.execute_reply": "2024-07-15T14:29:18.754572Z", "shell.execute_reply.started": "2024-07-15T14:29:06.527756Z" } }, "outputs": [], "source": [ "# user_compare_mask = (\n", "# user_intersting_clips[\"created_at\"] >= date_cut\n", "# ) # & (user_intersting_clips[\"is_pro_user\"] == True)\n", "user_compare_mask = (\n", " (user_intersting_clips[\"created_at\"] >= date_cut)\n", " & (\n", " user_intersting_clips[\"model_name\"].isin(\n", " [\n", " # \"chirp-v3-engine-d\",\n", " # \"chirp-v3-engine-i\",\n", " # \"chirp-v3-engine-i-tp\",\n", " # \"chirp-v3-engine-s\",\n", " # \"chirp-v3p5-engine-d\",\n", " # \"chirp-v3p5-engine-s\",\n", " # \"chirp-v3p5-engine-s-2\",\n", " # \"chirp-v3p5-engine-s-3\",\n", " # \"chirp-v3p5-engine-s-4\",\n", " # \"chirp-v3p5-engine-s-5\",\n", " # \"chirp-v3p5-engine-s-6\",\n", " # \"chirp-v3p5-engine-s-7\",\n", " \"chirp-v3p5-engine-s-2\",\n", " \"chirp-v3p5-engine-s-8\",\n", " \"chirp-v3p5-engine-s-11\",\n", " \"chirp-v3p5-engine-s-12\",\n", " \"chirp-v3p5-engine-s-13\",\n", " \"chirp-v3p5-engine-s-14\",\n", " \"chirp-v3p5-engine-s-15\",\n", " \"chirp-v3p5-engine-upload\",\n", " \"chirp-v3p5-engine-upload-1\",\n", " \"chirp-v3p5-engine-upload-2\",\n", " \"chirp-v3p5-engine-upload-3\",\n", " \"chirp-v3p5-engine-upload-4\",\n", " \"chirp-v3p5-engine-ft\",\n", " \"chirp-v3p5-engine-ft-1\",\n", " ]\n", " )\n", " )\n", " # & (user_intersting_clips[\"is_pro_user\"] == False)\n", ")\n", "# user_compare_mask = (user_intersting_clips[\"created_at\"] >= date_cut) & (\n", "# user_intersting_clips[\"tags\"].apply(lambda x: \"metal\" in x.lower())\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\n", "\n", "# for _, row in user_intersting_clips[user_intersting_clips[\"request_id\"].astype(str) == \"87c45d24-68ae-45dd-b5b7-92cd70bd0ab5\"].iterrows():\n", "# print(row[\"metadata\"])\n", "\n", "# for _, row in user_intersting_clips[user_intersting_clips[\"request_id\"].astype(str) == \"fa86f07f-4476-406f-b756-7166e0b08679\"].iterrows():\n", "# print(row[\"metadata\"])" ] }, { "cell_type": "code", "execution_count": 69, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:01.140472Z", "start_time": "2024-05-26T00:25:00.895575Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:29:18.756488Z", "iopub.status.busy": "2024-07-15T14:29:18.756304Z", "iopub.status.idle": "2024-07-15T14:29:28.426745Z", "shell.execute_reply": "2024-07-15T14:29:28.425945Z", "shell.execute_reply.started": "2024-07-15T14:29:18.756469Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(1565558, 43)\n" ] } ], "source": [ "user_intersting_clips_3p5 = (\n", " user_intersting_clips[user_compare_mask].reset_index().copy()\n", ")\n", "\n", "\n", "def parse_inference_exp(x):\n", " # print(x)\n", " if \"param_experiment\" not in x:\n", " return \"\"\n", " out = x.get(\"param_experiment\", \"\")\n", " if out:\n", " return \"_\" + out\n", " return \"\"\n", "\n", "\n", "user_intersting_clips_3p5[\"model_name\"] = user_intersting_clips_3p5[\n", " \"model_name\"\n", "] + user_intersting_clips_3p5[\"metadata\"].apply(parse_inference_exp)\n", "user_intersting_clips_3p5 = user_intersting_clips_3p5.sort_values(\n", " by=[\"request_id\", \"preference\"]\n", ")\n", "print(user_intersting_clips_3p5.shape)" ] }, { "cell_type": "code", "execution_count": 70, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:01.522500Z", "start_time": "2024-05-26T00:25:01.521140Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:29:28.427888Z", "iopub.status.busy": "2024-07-15T14:29:28.427696Z", "iopub.status.idle": "2024-07-15T14:29:28.932348Z", "shell.execute_reply": "2024-07-15T14:29:28.931723Z", "shell.execute_reply.started": "2024-07-15T14:29:28.427869Z" } }, "outputs": [], "source": [ "# %load_ext autoreload\n", "# %autoreload 2" ] }, { "cell_type": "code", "execution_count": 71, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:02.009450Z", "start_time": "2024-05-26T00:25:01.523515Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:29:28.933280Z", "iopub.status.busy": "2024-07-15T14:29:28.933123Z", "iopub.status.idle": "2024-07-15T14:29:35.963940Z", "shell.execute_reply": "2024-07-15T14:29:35.963195Z", "shell.execute_reply.started": "2024-07-15T14:29:28.933262Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "chirp-v3p5-engine-ft-1_temp_semantic_70_win_over_chirp-v3p5-engine-ft-1, win ratio 0.489, counts 6392\n", "chirp-v3p5-engine-ft-1_temp_semantic_80_win_over_chirp-v3p5-engine-ft-1, win ratio 0.505, counts 6602\n", "chirp-v3p5-engine-ft-1_temp_semantic_95_win_over_chirp-v3p5-engine-ft-1, win ratio 0.493, counts 6461\n", "chirp-v3p5-engine-ft-1_text_cfg_11_win_over_chirp-v3p5-engine-ft-1, win ratio 0.504, counts 6722\n", "chirp-v3p5-engine-ft-1_win_over_chirp-v3p5-engine-ft-1, win ratio 1.000, counts 13337\n", "chirp-v3p5-engine-ft-1_win_over_chirp-v3p5-engine-ft-1_temp_semantic_70, win ratio 0.511, counts 6682\n", "chirp-v3p5-engine-ft-1_win_over_chirp-v3p5-engine-ft-1_temp_semantic_80, win ratio 0.495, counts 6464\n", "chirp-v3p5-engine-ft-1_win_over_chirp-v3p5-engine-ft-1_temp_semantic_95, win ratio 0.507, counts 6656\n", "chirp-v3p5-engine-ft-1_win_over_chirp-v3p5-engine-ft-1_text_cfg_11, win ratio 0.496, counts 6619\n", "chirp-v3p5-engine-s-8_temp_semantic_70_win_over_chirp-v3p5-engine-s-8, win ratio 0.667, counts 2\n", "chirp-v3p5-engine-s-8_temp_semantic_80_win_over_chirp-v3p5-engine-s-8, win ratio 0.500, counts 2\n", "chirp-v3p5-engine-s-8_text_cfg_11_win_over_chirp-v3p5-engine-s-8, win ratio 0.333, counts 1\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-8, win ratio 1.000, counts 651324\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-8_temp_semantic_70, win ratio 0.333, counts 1\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-8_temp_semantic_80, win ratio 0.500, counts 2\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-8_temp_semantic_95, win ratio 1.000, counts 2\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-8_text_cfg_11, win ratio 0.667, counts 2\n", "chirp-v3p5-engine-upload-4_temp_semantic_70_win_over_chirp-v3p5-engine-upload-4, win ratio 0.506, counts 11005\n", "chirp-v3p5-engine-upload-4_temp_semantic_70_win_over_chirp-v3p5-engine-upload-4_temp_semantic_70, win ratio 1.000, counts 1\n", "chirp-v3p5-engine-upload-4_win_over_chirp-v3p5-engine-upload-4, win ratio 1.000, counts 43760\n", "chirp-v3p5-engine-upload-4_win_over_chirp-v3p5-engine-upload-4_temp_semantic_70, win ratio 0.494, counts 10742\n" ] }, { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "get_preferfence_counts(user_intersting_clips_3p5)\n", "# user_intersting_clips[user_compare_mask]\n", "# )" ] }, { "cell_type": "code", "execution_count": 72, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:02.332947Z", "start_time": "2024-05-26T00:25:02.010694Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:29:35.965033Z", "iopub.status.busy": "2024-07-15T14:29:35.964856Z", "iopub.status.idle": "2024-07-15T14:29:43.117145Z", "shell.execute_reply": "2024-07-15T14:29:43.116387Z", "shell.execute_reply.started": "2024-07-15T14:29:35.965014Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "first gen\n", "chirp-v3p5-engine-ft-1_temp_semantic_70_win_over_chirp-v3p5-engine-ft-1, win ratio 0.490, counts 5426\n", "chirp-v3p5-engine-ft-1_temp_semantic_80_win_over_chirp-v3p5-engine-ft-1, win ratio 0.506, counts 5586\n", "chirp-v3p5-engine-ft-1_temp_semantic_95_win_over_chirp-v3p5-engine-ft-1, win ratio 0.488, counts 5400\n", "chirp-v3p5-engine-ft-1_text_cfg_11_win_over_chirp-v3p5-engine-ft-1, win ratio 0.505, counts 5685\n", "chirp-v3p5-engine-ft-1_win_over_chirp-v3p5-engine-ft-1, win ratio 1.000, counts 11294\n", "chirp-v3p5-engine-ft-1_win_over_chirp-v3p5-engine-ft-1_temp_semantic_70, win ratio 0.510, counts 5652\n", "chirp-v3p5-engine-ft-1_win_over_chirp-v3p5-engine-ft-1_temp_semantic_80, win ratio 0.494, counts 5462\n", "chirp-v3p5-engine-ft-1_win_over_chirp-v3p5-engine-ft-1_temp_semantic_95, win ratio 0.512, counts 5668\n", "chirp-v3p5-engine-ft-1_win_over_chirp-v3p5-engine-ft-1_text_cfg_11, win ratio 0.495, counts 5577\n", "chirp-v3p5-engine-s-8_temp_semantic_70_win_over_chirp-v3p5-engine-s-8, win ratio 0.667, counts 2\n", "chirp-v3p5-engine-s-8_temp_semantic_80_win_over_chirp-v3p5-engine-s-8, win ratio 0.500, counts 2\n", "chirp-v3p5-engine-s-8_text_cfg_11_win_over_chirp-v3p5-engine-s-8, win ratio 0.500, counts 1\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-8, win ratio 1.000, counts 564553\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-8_temp_semantic_70, win ratio 0.333, counts 1\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-8_temp_semantic_80, win ratio 0.500, counts 2\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-8_temp_semantic_95, win ratio 1.000, counts 2\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-8_text_cfg_11, win ratio 0.500, counts 1\n" ] }, { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "print(\"first gen\")\n", "first_gen_slice_df = user_intersting_clips_3p5[\n", " (user_intersting_clips_3p5[\"continued_parent\"].isna())\n", "].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": 73, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:02.574659Z", "start_time": "2024-05-26T00:25:02.334214Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:29:43.118235Z", "iopub.status.busy": "2024-07-15T14:29:43.118058Z", "iopub.status.idle": "2024-07-15T14:29:44.721102Z", "shell.execute_reply": "2024-07-15T14:29:44.720389Z", "shell.execute_reply.started": "2024-07-15T14:29:43.118216Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "chirp-v3p5-engine-ft-1_temp_semantic_70_win_over_chirp-v3p5-engine-ft-1, win ratio 0.484, counts 966\n", "chirp-v3p5-engine-ft-1_temp_semantic_80_win_over_chirp-v3p5-engine-ft-1, win ratio 0.503, counts 1016\n", "chirp-v3p5-engine-ft-1_temp_semantic_95_win_over_chirp-v3p5-engine-ft-1, win ratio 0.518, counts 1061\n", "chirp-v3p5-engine-ft-1_text_cfg_11_win_over_chirp-v3p5-engine-ft-1, win ratio 0.499, counts 1037\n", "chirp-v3p5-engine-ft-1_win_over_chirp-v3p5-engine-ft-1, win ratio 1.000, counts 2043\n", "chirp-v3p5-engine-ft-1_win_over_chirp-v3p5-engine-ft-1_temp_semantic_70, win ratio 0.516, counts 1030\n", "chirp-v3p5-engine-ft-1_win_over_chirp-v3p5-engine-ft-1_temp_semantic_80, win ratio 0.497, counts 1002\n", "chirp-v3p5-engine-ft-1_win_over_chirp-v3p5-engine-ft-1_temp_semantic_95, win ratio 0.482, counts 988\n", "chirp-v3p5-engine-ft-1_win_over_chirp-v3p5-engine-ft-1_text_cfg_11, win ratio 0.501, counts 1042\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-8, win ratio 1.000, counts 86771\n", "chirp-v3p5-engine-s-8_win_over_chirp-v3p5-engine-s-8_text_cfg_11, win ratio 1.000, counts 1\n", "chirp-v3p5-engine-upload-4_temp_semantic_70_win_over_chirp-v3p5-engine-upload-4, win ratio 0.506, counts 11005\n", "chirp-v3p5-engine-upload-4_temp_semantic_70_win_over_chirp-v3p5-engine-upload-4_temp_semantic_70, win ratio 1.000, counts 1\n", "chirp-v3p5-engine-upload-4_win_over_chirp-v3p5-engine-upload-4, win ratio 1.000, counts 43760\n", "chirp-v3p5-engine-upload-4_win_over_chirp-v3p5-engine-upload-4_temp_semantic_70, win ratio 0.494, counts 10742\n" ] }, { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "get_preferfence_counts(\n", " user_intersting_clips_3p5[(~user_intersting_clips_3p5[\"continued_parent\"].isna())],\n", " \"is continue\",\n", ")" ] }, { "cell_type": "code", "execution_count": 74, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:29:44.730498Z", "iopub.status.busy": "2024-07-15T14:29:44.726356Z", "iopub.status.idle": "2024-07-15T14:29:45.093079Z", "shell.execute_reply": "2024-07-15T14:29:45.092444Z", "shell.execute_reply.started": "2024-07-15T14:29:44.730463Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
level_0indexidcreated_atupdated_attime_usedmetadatauser_idstatusdiscord_message_idprompt_idrequest_idis_generateds3_idupvote_countbatch_indexmodel_nameprompt_textdaily_theme_idis_deletedimage_s3_idis_publicdislike_countflag_countplay_countskip_counttitleslugis_in_playlistcontinued_parentis_pro_useruser_n_clipsupvoteddeletedhas_continuedpart_of_concathas_actionflaggeddownvotedpos_preferenceneg_preferencediff_preferencepreference
\n", "
" ], "text/plain": [ "Empty DataFrame\n", "Columns: [level_0, index, id, created_at, updated_at, time_used, metadata, user_id, status, discord_message_id, prompt_id, request_id, is_generated, s3_id, upvote_count, batch_index, model_name, prompt_text, daily_theme_id, is_deleted, image_s3_id, is_public, dislike_count, flag_count, play_count, skip_count, title, slug, is_in_playlist, continued_parent, is_pro_user, user_n_clips, upvoted, deleted, has_continued, part_of_concat, has_action, flagged, downvoted, pos_preference, neg_preference, diff_preference, preference]\n", "Index: []" ] }, "execution_count": 74, "metadata": {}, "output_type": "execute_result" } ], "source": [ "user_intersting_clips_3p5[\n", " user_intersting_clips_3p5[\"model_name\"]\n", " == \"chirp-v3p5-engine-s_cfg_tags_max_steps_none\"\n", "]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Clean up SHIT" ] }, { "cell_type": "code", "execution_count": 75, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:02.592376Z", "start_time": "2024-05-26T00:25:02.575733Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:29:45.094108Z", "iopub.status.busy": "2024-07-15T14:29:45.093934Z", "iopub.status.idle": "2024-07-15T14:29:45.139208Z", "shell.execute_reply": "2024-07-15T14:29:45.138638Z", "shell.execute_reply.started": "2024-07-15T14:29:45.094089Z" } }, "outputs": [], "source": [ "# to get the right play conts, we need the right df..." ] }, { "cell_type": "code", "execution_count": 76, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:07.682737Z", "start_time": "2024-05-26T00:25:02.593456Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:29:45.140110Z", "iopub.status.busy": "2024-07-15T14:29:45.139955Z", "iopub.status.idle": "2024-07-15T14:30:17.827829Z", "shell.execute_reply": "2024-07-15T14:30:17.827060Z", "shell.execute_reply.started": "2024-07-15T14:29:45.140094Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(1851952, 11)\n" ] } ], "source": [ "# ~ only 1 min :)\n", "partial_reaction_df = reaction_df[\n", " reaction_df[\"clip_id\"].isin(user_intersting_clips[\"id\"])\n", "].copy()\n", "print(partial_reaction_df.shape)\n", "total_play_reaction_df_sum = partial_reaction_df.groupby(\"clip_id\")[\"play_count\"].sum()\n", "total_play_reaction_df_sum_df = total_play_reaction_df_sum.reset_index().rename(\n", " columns={\"clip_id\": \"id\", \"play_count\": \"reaction_play_count\"}\n", ")\n", "user_intersting_clips = user_intersting_clips.merge(\n", " total_play_reaction_df_sum_df, on=\"id\", how=\"left\"\n", ")" ] }, { "cell_type": "code", "execution_count": 77, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:07.781022Z", "start_time": "2024-05-26T00:25:07.684000Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:30:17.829003Z", "iopub.status.busy": "2024-07-15T14:30:17.828818Z", "iopub.status.idle": "2024-07-15T14:30:41.242226Z", "shell.execute_reply": "2024-07-15T14:30:41.241608Z", "shell.execute_reply.started": "2024-07-15T14:30:17.828985Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(931938, 11)\n" ] } ], "source": [ "partial_reaction_df_pro = reaction_df[\n", " (reaction_df[\"clip_id\"].isin(user_intersting_clips[\"id\"]))\n", " & (reaction_df[\"is_pro_user\"] == True)\n", "].copy()\n", "print(partial_reaction_df_pro.shape)\n", "total_play_reaction_df_sum_pro = partial_reaction_df_pro.groupby(\"clip_id\")[\n", " \"play_count\"\n", "].sum()\n", "total_play_reaction_df_sum_pro_df = total_play_reaction_df_sum_pro.reset_index().rename(\n", " columns={\"clip_id\": \"id\", \"play_count\": \"reaction_pro_play_count\"}\n", ")\n", "user_intersting_clips = user_intersting_clips.merge(\n", " total_play_reaction_df_sum_pro_df, on=\"id\", how=\"left\"\n", ")" ] }, { "cell_type": "code", "execution_count": 78, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:30:41.243163Z", "iopub.status.busy": "2024-07-15T14:30:41.243006Z", "iopub.status.idle": "2024-07-15T14:30:41.877267Z", "shell.execute_reply": "2024-07-15T14:30:41.876642Z", "shell.execute_reply.started": "2024-07-15T14:30:41.243146Z" } }, "outputs": [ { "data": { "text/plain": [ "count 898323.000000\n", "mean 0.209111\n", "std 15.696875\n", "min 0.000000\n", "25% 0.000000\n", "50% 0.000000\n", "75% 0.000000\n", "max 11108.000000\n", "dtype: float64" ] }, "execution_count": 78, "metadata": {}, "output_type": "execute_result" } ], "source": [ "(\n", " user_intersting_clips[\"reaction_play_count\"]\n", " - user_intersting_clips[\"reaction_pro_play_count\"]\n", ").describe()" ] }, { "cell_type": "code", "execution_count": 79, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:30:41.878305Z", "iopub.status.busy": "2024-07-15T14:30:41.878132Z", "iopub.status.idle": "2024-07-15T14:30:41.900046Z", "shell.execute_reply": "2024-07-15T14:30:41.899486Z", "shell.execute_reply.started": "2024-07-15T14:30:41.878287Z" } }, "outputs": [], "source": [ "# user_intersting_clips[\n", "# (\n", "# user_intersting_clips[\"reaction_play_count\"]\n", "# - user_intersting_clips[\"reaction_pro_play_count\"]\n", "# )\n", "# >= 5\n", "# ][\"user_id\"].value_counts()" ] }, { "cell_type": "code", "execution_count": 80, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:08.095035Z", "start_time": "2024-05-26T00:25:07.782738Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:30:41.900876Z", "iopub.status.busy": "2024-07-15T14:30:41.900724Z", "iopub.status.idle": "2024-07-15T14:30:45.898091Z", "shell.execute_reply": "2024-07-15T14:30:45.897337Z", "shell.execute_reply.started": "2024-07-15T14:30:41.900859Z" } }, "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": 81, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:08.361849Z", "start_time": "2024-05-26T00:25:08.199583Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:30:45.899219Z", "iopub.status.busy": "2024-07-15T14:30:45.899042Z", "iopub.status.idle": "2024-07-15T14:30:45.935946Z", "shell.execute_reply": "2024-07-15T14:30:45.935405Z", "shell.execute_reply.started": "2024-07-15T14:30:45.899200Z" } }, "outputs": [ { "data": { "text/plain": [ "0.49880790031664785" ] }, "execution_count": 81, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# too_much_data_mask = (\n", "# (user_intersting_clips[\"preference\"] == False)\n", "# & (\n", "# (user_intersting_clips[\"dislike_count\"] >= 1) # single play is super catchy\n", "# | (user_intersting_clips[\"flag_count\"] >= 1) # or the concat play is super catchy\n", "# )\n", "# )\n", "# too_much_data_mask.sum() / ((user_intersting_clips[\"preference\"] == True).sum())\n", "too_much_data_mask = (\n", " (user_intersting_clips[\"preference\"] == True)\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\"] >= 20)\n", " # & (user_intersting_clips[\"continued_parent\"].isna())\n", ")\n", "too_much_data_mask.sum() / ((user_intersting_clips[\"preference\"] == True).sum())" ] }, { "cell_type": "code", "execution_count": 82, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:08.523643Z", "start_time": "2024-05-26T00:25:08.367348Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:30:45.936813Z", "iopub.status.busy": "2024-07-15T14:30:45.936660Z", "iopub.status.idle": "2024-07-15T14:30:46.704678Z", "shell.execute_reply": "2024-07-15T14:30:46.704074Z", "shell.execute_reply.started": "2024-07-15T14:30:45.936796Z" } }, "outputs": [], "source": [ "final_good_enough_requests = user_intersting_clips[too_much_data_mask][\n", " \"request_id\"\n", "].unique()" ] }, { "cell_type": "code", "execution_count": 83, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:08.703927Z", "start_time": "2024-05-26T00:25:08.525193Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:30:46.705602Z", "iopub.status.busy": "2024-07-15T14:30:46.705446Z", "iopub.status.idle": "2024-07-15T14:30:51.273904Z", "shell.execute_reply": "2024-07-15T14:30:51.273296Z", "shell.execute_reply.started": "2024-07-15T14:30:46.705585Z" } }, "outputs": [], "source": [ "final_interesting_clips = user_intersting_clips[\n", " user_intersting_clips[\"request_id\"].isin(set(final_good_enough_requests))\n", "].copy()" ] }, { "cell_type": "code", "execution_count": 84, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:30:51.274813Z", "iopub.status.busy": "2024-07-15T14:30:51.274659Z", "iopub.status.idle": "2024-07-15T14:30:51.680544Z", "shell.execute_reply": "2024-07-15T14:30:51.680031Z", "shell.execute_reply.started": "2024-07-15T14:30:51.274796Z" } }, "outputs": [ { "data": { "text/plain": [ "model_name\n", "chirp-v3p5-engine-s-8 339524\n", "chirp-v3p5-engine-upload-4 37855\n", "chirp-v3p5-engine-ft-1 32585\n", "chirp-v3p5-engine-s-8-no-top-p 9551\n", "chirp-v3p5-engine-s-19 2190\n", "chirp-v3p5-engine-s-18 2131\n", "chirp-v3p5-engine-t 2067\n", "chirp-v3p5-engine-ft-2 1312\n", "Name: count, dtype: int64" ] }, "execution_count": 84, "metadata": {}, "output_type": "execute_result" } ], "source": [ "final_interesting_clips[final_interesting_clips[\"preference\"] == True][\n", " \"model_name\"\n", "].value_counts()" ] }, { "cell_type": "code", "execution_count": 85, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:08.884389Z", "start_time": "2024-05-26T00:25:08.705530Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:30:51.681364Z", "iopub.status.busy": "2024-07-15T14:30:51.681214Z", "iopub.status.idle": "2024-07-15T14:30:51.731486Z", "shell.execute_reply": "2024-07-15T14:30:51.730932Z", "shell.execute_reply.started": "2024-07-15T14:30:51.681348Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "batch_index preference\n", "0 True 220443\n", " False 206772\n", "1 False 220443\n", " True 206772\n", "Name: count, dtype: int64\n" ] } ], "source": [ "print(final_interesting_clips.groupby(\"batch_index\")[\"preference\"].value_counts())" ] }, { "cell_type": "code", "execution_count": 86, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:09.198504Z", "start_time": "2024-05-26T00:25:08.885507Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:30:51.732350Z", "iopub.status.busy": "2024-07-15T14:30:51.732199Z", "iopub.status.idle": "2024-07-15T14:30:54.620168Z", "shell.execute_reply": "2024-07-15T14:30:54.619579Z", "shell.execute_reply.started": "2024-07-15T14:30:51.732334Z" } }, "outputs": [], "source": [ "assert (\n", " final_interesting_clips[final_interesting_clips[\"request_id\"].isna()].shape[0] == 0\n", ")\n", "check_df = final_interesting_clips.groupby(\"request_id\")[\"id\"].nunique()\n", "check_df[check_df.values != 2]\n", "assert check_df[check_df.values != 2].shape[0] == 0" ] }, { "cell_type": "code", "execution_count": 87, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:30:54.621074Z", "iopub.status.busy": "2024-07-15T14:30:54.620911Z", "iopub.status.idle": "2024-07-15T14:30:54.901361Z", "shell.execute_reply": "2024-07-15T14:30:54.900873Z", "shell.execute_reply.started": "2024-07-15T14:30:54.621057Z" } }, "outputs": [ { "data": { "text/plain": [ "(65170, 50)" ] }, "execution_count": 87, "metadata": {}, "output_type": "execute_result" } ], "source": [ "final_interesting_clips[\n", " final_interesting_clips[\"model_name\"] == \"chirp-v3p5-engine-ft-1\"\n", "].shape" ] }, { "cell_type": "code", "execution_count": 88, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:36:45.167690Z", "start_time": "2024-05-26T00:36:45.164768Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:30:54.902138Z", "iopub.status.busy": "2024-07-15T14:30:54.901991Z", "iopub.status.idle": "2024-07-15T14:30:54.934278Z", "shell.execute_reply": "2024-07-15T14:30:54.933823Z", "shell.execute_reply.started": "2024-07-15T14:30:54.902122Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "done (854430, 50)\n" ] } ], "source": [ "# final_interesting_clips[final_interesting_clips[\"model_name\"] == \"chirp-v3p5-engine-ft-1\"].to_csv(\n", "# \"/home/tony/Data/Preference/13b_v0/interesting_clips_ft1_20240715.csv\", index=False\n", "# )\n", "# final_interesting_clips[final_interesting_clips[\"model_name\"] == \"chirp-v3p5-engine-s-8\"].to_csv(\n", "# \"/home/tony/Data/Preference/13b_v0/interesting_clips_20240712_s8.csv\", index=False\n", "# )\n", "print(\"done\", final_interesting_clips.shape)" ] }, { "cell_type": "code", "execution_count": 89, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:09.681554Z", "start_time": "2024-05-26T00:25:09.441803Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:30:54.935009Z", "iopub.status.busy": "2024-07-15T14:30:54.934865Z", "iopub.status.idle": "2024-07-15T14:30:54.981871Z", "shell.execute_reply": "2024-07-15T14:30:54.981435Z", "shell.execute_reply.started": "2024-07-15T14:30:54.934994Z" } }, "outputs": [], "source": [ "# smaller_mask = final_interesting_clips[\"model_name\"].isin([\"chirp-v3-engine-d\", \"chirp-v3-engine-v0\"])" ] }, { "cell_type": "code", "execution_count": 90, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:09.933748Z", "start_time": "2024-05-26T00:25:09.683018Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:30:54.982729Z", "iopub.status.busy": "2024-07-15T14:30:54.982586Z", "iopub.status.idle": "2024-07-15T14:30:55.039608Z", "shell.execute_reply": "2024-07-15T14:30:55.039180Z", "shell.execute_reply.started": "2024-07-15T14:30:54.982713Z" } }, "outputs": [], "source": [ "# final_interesting_clips[smaller_mask].to_csv(\n", "# \"/home/tony/Data/Preference/7b_v2/interesting_clips_20240421_prev_model.csv\", index=False\n", "# )" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# For faster processing once" ] }, { "cell_type": "code", "execution_count": 91, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:25:10.265241Z", "start_time": "2024-05-26T00:25:09.934743Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:30:55.040420Z", "iopub.status.busy": "2024-07-15T14:30:55.040280Z", "iopub.status.idle": "2024-07-15T14:30:55.277114Z", "shell.execute_reply": "2024-07-15T14:30:55.276391Z", "shell.execute_reply.started": "2024-07-15T14:30:55.040404Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "total unique users 1117723\n" ] } ], "source": [ "print(\"total unique users\", clip_df[\"user_id\"].nunique())" ] }, { "cell_type": "code", "execution_count": 92, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:26:43.409660Z", "start_time": "2024-05-26T00:25:10.266379Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:30:55.278199Z", "iopub.status.busy": "2024-07-15T14:30:55.278022Z", "iopub.status.idle": "2024-07-15T14:30:55.299125Z", "shell.execute_reply": "2024-07-15T14:30:55.298569Z", "shell.execute_reply.started": "2024-07-15T14:30:55.278179Z" } }, "outputs": [], "source": [ "# 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()" ] }, { "cell_type": "code", "execution_count": 93, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:26:43.423857Z", "start_time": "2024-05-26T00:26:43.411248Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:30:55.299962Z", "iopub.status.busy": "2024-07-15T14:30:55.299812Z", "iopub.status.idle": "2024-07-15T14:30:55.400200Z", "shell.execute_reply": "2024-07-15T14:30:55.399596Z", "shell.execute_reply.started": "2024-07-15T14:30:55.299946Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Series([], Name: count, dtype: int64)\n", "(0, 40)\n" ] } ], "source": [ "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)" ] }, { "cell_type": "code", "execution_count": 94, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:26:43.803559Z", "start_time": "2024-05-26T00:26:43.622922Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:30:55.401098Z", "iopub.status.busy": "2024-07-15T14:30:55.400937Z", "iopub.status.idle": "2024-07-15T14:30:55.422416Z", "shell.execute_reply": "2024-07-15T14:30:55.421897Z", "shell.execute_reply.started": "2024-07-15T14:30:55.401081Z" } }, "outputs": [ { "data": { "text/plain": [ "array([], dtype=int64)" ] }, "execution_count": 94, "metadata": {}, "output_type": "execute_result" } ], "source": [ "user_intersting_clips[user_intersting_clips[\"user_n_clips\"] > 10000][\"user_id\"].unique()" ] }, { "cell_type": "code", "execution_count": 95, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:26:45.770044Z", "start_time": "2024-05-26T00:26:44.912085Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:30:55.423494Z", "iopub.status.busy": "2024-07-15T14:30:55.423100Z", "iopub.status.idle": "2024-07-15T14:30:55.471265Z", "shell.execute_reply": "2024-07-15T14:30:55.470746Z", "shell.execute_reply.started": "2024-07-15T14:30:55.423476Z" } }, "outputs": [], "source": [ "# # wtf is going on with these requests\n", "# print(total_clip_df[total_clip_df[\"model_name\"] == \"chirp-v3-0\"].shape)\n", "# print(\n", "# total_clip_df[total_clip_df[\"model_name\"] == \"chirp-v3-0\"][\"user_id\"].value_counts()\n", "# )" ] }, { "cell_type": "code", "execution_count": 96, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:26:46.088296Z", "start_time": "2024-05-26T00:26:45.772102Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:30:55.472270Z", "iopub.status.busy": "2024-07-15T14:30:55.472116Z", "iopub.status.idle": "2024-07-15T14:30:55.559118Z", "shell.execute_reply": "2024-07-15T14:30:55.558646Z", "shell.execute_reply.started": "2024-07-15T14:30:55.472254Z" } }, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
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
\n", "
" ], "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": 96, "metadata": {}, "output_type": "execute_result" } ], "source": [ "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": 97, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:27:00.130778Z", "start_time": "2024-05-26T00:26:46.089923Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:30:55.559929Z", "iopub.status.busy": "2024-07-15T14:30:55.559770Z", "iopub.status.idle": "2024-07-15T14:31:22.863475Z", "shell.execute_reply": "2024-07-15T14:31:22.862890Z", "shell.execute_reply.started": "2024-07-15T14:30:55.559912Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(3726331, 26)\n", "0.1909722921563228\n" ] } ], "source": [ "no_reaction_clip_df = total_clip_df[\n", " ~total_clip_df[\"id\"].isin(reaction_df[\"clip_id\"])\n", "].copy()\n", "print(no_reaction_clip_df.shape)\n", "print(no_reaction_clip_df.shape[0] / total_clip_df.shape[0])" ] }, { "cell_type": "code", "execution_count": 98, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:27:01.185878Z", "start_time": "2024-05-26T00:27:00.132882Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:31:22.864353Z", "iopub.status.busy": "2024-07-15T14:31:22.864199Z", "iopub.status.idle": "2024-07-15T14:31:28.004094Z", "shell.execute_reply": "2024-07-15T14:31:28.003568Z", "shell.execute_reply.started": "2024-07-15T14:31:22.864336Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.6684459255301171\n" ] } ], "source": [ "min_generations_for_no_reaction = 20\n", "inspection_date_cut = \"2024-05-10\"\n", "# inspection_date_cut = \"2024-06-18\"\n", "no_reaction_clip_df[\"no_reaction_count\"] = no_reaction_clip_df.groupby(\"user_id\")[\n", " \"user_id\"\n", "].transform(\"count\")\n", "no_reaction_clip_df[\"is_pro_user\"] = no_reaction_clip_df[\"user_id\"].isin(pro_users)\n", "no_reaction_clip_df[\"user_id\"].nunique()\n", "bot_user_mask = (\n", " (no_reaction_clip_df[\"no_reaction_count\"] >= min_generations_for_no_reaction)\n", " & (no_reaction_clip_df[\"created_at\"] >= inspection_date_cut)\n", " # & (no_reaction_clip_df[\"is_pro_user\"] == True)\n", ")\n", "sub_total_clip_df = total_clip_df[\n", " total_clip_df[\"user_id\"].isin(\n", " no_reaction_clip_df[bot_user_mask][\"user_id\"].unique()\n", " )\n", "].copy()\n", "sub_total_clip_df[\"is_pro_user\"] = sub_total_clip_df[\"user_id\"].isin(pro_users)\n", "print(no_reaction_clip_df[bot_user_mask].shape[0] / sub_total_clip_df.shape[0])" ] }, { "cell_type": "code", "execution_count": 99, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:27:02.022423Z", "start_time": "2024-05-26T00:27:01.187814Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:31:28.004985Z", "iopub.status.busy": "2024-07-15T14:31:28.004829Z", "iopub.status.idle": "2024-07-15T14:31:33.416677Z", "shell.execute_reply": "2024-07-15T14:31:33.416078Z", "shell.execute_reply.started": "2024-07-15T14:31:28.004968Z" } }, "outputs": [], "source": [ "sub_total_clip_df[\"gen_count\"] = sub_total_clip_df.groupby(\"user_id\")[\n", " \"user_id\"\n", "].transform(\"count\")\n", "user_id_no_reaction_dict = no_reaction_clip_df.set_index(\"user_id\")[\n", " \"no_reaction_count\"\n", "].to_dict()\n", "user_id_total_dict = (\n", " sub_total_clip_df[sub_total_clip_df[\"is_pro_user\"] == False]\n", " .set_index(\"user_id\")[\"gen_count\"]\n", " .to_dict()\n", ")\n", "pro_user_id_total_dict = (\n", " sub_total_clip_df[sub_total_clip_df[\"is_pro_user\"] == True]\n", " .set_index(\"user_id\")[\"gen_count\"]\n", " .to_dict()\n", ")\n", "\n", "user_ratio_dict = {}\n", "pro_user_ratio_dict = {}\n", "for user_id, total_gen in user_id_total_dict.items():\n", " user_ratio = user_id_no_reaction_dict.get(user_id, 0) / total_gen\n", " user_ratio_dict[user_id] = user_ratio\n", "for user_id, total_gen in pro_user_id_total_dict.items():\n", " user_ratio = user_id_no_reaction_dict.get(user_id, 0) / total_gen\n", " pro_user_ratio_dict[user_id] = user_ratio" ] }, { "cell_type": "code", "execution_count": 100, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:27:02.191083Z", "start_time": "2024-05-26T00:27:02.024409Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:31:33.418585Z", "iopub.status.busy": "2024-07-15T14:31:33.417448Z", "iopub.status.idle": "2024-07-15T14:31:33.872776Z", "shell.execute_reply": "2024-07-15T14:31:33.872279Z", "shell.execute_reply.started": "2024-07-15T14:31:33.418552Z" } }, "outputs": [ { "data": { "image/png": "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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.hist(\n", " user_ratio_dict.values(), bins=np.linspace(0, 1, 50), alpha=0.5, label=\"free user\"\n", ")\n", "plt.hist(\n", " pro_user_ratio_dict.values(),\n", " bins=np.linspace(0, 1, 50),\n", " alpha=0.5,\n", " label=\"pro user\",\n", ")\n", "plt.xlabel(\n", " f\"fraction of generations (min {min_generations_for_no_reaction}) that have no actions\"\n", ")\n", "plt.ylabel(\"number of users\")\n", "plt.yscale(\"log\")\n", "plt.legend()\n", "plt.title(f\"Potential bots since {max(cutoff_date, inspection_date_cut)}\")\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 101, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:27:02.229332Z", "start_time": "2024-05-26T00:27:02.192457Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:31:33.873654Z", "iopub.status.busy": "2024-07-15T14:31:33.873493Z", "iopub.status.idle": "2024-07-15T14:31:33.897828Z", "shell.execute_reply": "2024-07-15T14:31:33.897355Z", "shell.execute_reply.started": "2024-07-15T14:31:33.873637Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "10107\n", "1642\n" ] } ], "source": [ "super_bad_user_id = set()\n", "for user_id, user_ratio in user_ratio_dict.items():\n", " if user_ratio >= 0.99:\n", " super_bad_user_id.add(user_id)\n", "print(len(super_bad_user_id))\n", "super_bad_pro_user_id = set()\n", "for user_id, user_ratio in pro_user_ratio_dict.items():\n", " if user_ratio >= 0.99:\n", " super_bad_pro_user_id.add(user_id)\n", "print(len(super_bad_pro_user_id))" ] }, { "cell_type": "code", "execution_count": 102, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:31:33.898562Z", "iopub.status.busy": "2024-07-15T14:31:33.898420Z", "iopub.status.idle": "2024-07-15T14:31:33.948240Z", "shell.execute_reply": "2024-07-15T14:31:33.947577Z", "shell.execute_reply.started": "2024-07-15T14:31:33.898546Z" } }, "outputs": [], "source": [ "from datetime import datetime\n", "\n", "curr_date = datetime.today().strftime(\"%Y_%m_%d\")" ] }, { "cell_type": "code", "execution_count": 103, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:31:33.949551Z", "iopub.status.busy": "2024-07-15T14:31:33.948803Z", "iopub.status.idle": "2024-07-15T14:31:34.024876Z", "shell.execute_reply": "2024-07-15T14:31:34.024182Z", "shell.execute_reply.started": "2024-07-15T14:31:33.949522Z" } }, "outputs": [], "source": [ "with open(f\"/home/tony/Data/bots/bad_user_{curr_date}.json\", \"w\") as fp:\n", " json.dump(list(super_bad_user_id), fp)\n", "with open(f\"/home/tony/Data/bots/bad_pro_user_{curr_date}.json\", \"w\") as fp:\n", " json.dump(list(super_bad_pro_user_id), fp)" ] }, { "cell_type": "code", "execution_count": 104, "metadata": { "ExecuteTime": { "end_time": "2024-05-26T00:27:02.725735Z", "start_time": "2024-05-26T00:27:02.230988Z" }, "execution": { "iopub.execute_input": "2024-07-15T14:31:34.029490Z", "iopub.status.busy": "2024-07-15T14:31:34.025724Z", "iopub.status.idle": "2024-07-15T14:31:36.967648Z", "shell.execute_reply": "2024-07-15T14:31:36.967059Z", "shell.execute_reply.started": "2024-07-15T14:31:34.029457Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "free frac 0.019857457945881334\n", "pro frac 0.08441768131544135\n", "total frac 0.10427513926132267\n" ] } ], "source": [ "print(\n", " f\"free frac {total_clip_df[total_clip_df['user_id'].isin(super_bad_user_id)].shape[0] / total_clip_df.shape[0]}\"\n", ")\n", "print(\n", " f\"pro frac {total_clip_df[total_clip_df['user_id'].isin(super_bad_pro_user_id)].shape[0] / total_clip_df.shape[0]}\"\n", ")\n", "print(\n", " f\"total frac {total_clip_df[total_clip_df['user_id'].isin(super_bad_user_id.union(super_bad_pro_user_id))].shape[0] / total_clip_df.shape[0]}\"\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Alpha testing user selection" ] }, { "cell_type": "code", "execution_count": 105, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:31:36.968541Z", "iopub.status.busy": "2024-07-15T14:31:36.968385Z", "iopub.status.idle": "2024-07-15T14:31:36.989704Z", "shell.execute_reply": "2024-07-15T14:31:36.989319Z", "shell.execute_reply.started": "2024-07-15T14:31:36.968524Z" } }, "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))" ] }, { "cell_type": "code", "execution_count": 106, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:31:36.990582Z", "iopub.status.busy": "2024-07-15T14:31:36.990232Z", "iopub.status.idle": "2024-07-15T14:31:37.040773Z", "shell.execute_reply": "2024-07-15T14:31:37.040324Z", "shell.execute_reply.started": "2024-07-15T14:31:36.990565Z" } }, "outputs": [], "source": [ "# 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": 107, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:31:37.041490Z", "iopub.status.busy": "2024-07-15T14:31:37.041343Z", "iopub.status.idle": "2024-07-15T14:31:37.086407Z", "shell.execute_reply": "2024-07-15T14:31:37.085974Z", "shell.execute_reply.started": "2024-07-15T14:31:37.041475Z" } }, "outputs": [], "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": 108, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:31:37.087338Z", "iopub.status.busy": "2024-07-15T14:31:37.086997Z", "iopub.status.idle": "2024-07-15T14:31:37.129943Z", "shell.execute_reply": "2024-07-15T14:31:37.129506Z", "shell.execute_reply.started": "2024-07-15T14:31:37.087322Z" } }, "outputs": [], "source": [ "# session_query = snow_session.sql(f\"\"\" select *\n", "# from ML_SONG_SUMMARY_INFO\n", "# where song_id in ('7e7da06b-5d1f-4cc9-8e7c-54bb7c9bd3f1')\n", "# and p_date = DATE(SYSDATE() - INTERVAL '1 HOUR')\n", "# order by p_hour desc\n", "# limit 1;\"\"\")\n", "# df_snow_test = pd.DataFrame(session_query.collect())" ] }, { "cell_type": "code", "execution_count": 109, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:31:37.130780Z", "iopub.status.busy": "2024-07-15T14:31:37.130521Z", "iopub.status.idle": "2024-07-15T14:31:37.179177Z", "shell.execute_reply": "2024-07-15T14:31:37.178736Z", "shell.execute_reply.started": "2024-07-15T14:31:37.130764Z" } }, "outputs": [], "source": [ "# df_snow_test" ] }, { "cell_type": "code", "execution_count": 110, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:31:37.179902Z", "iopub.status.busy": "2024-07-15T14:31:37.179758Z", "iopub.status.idle": "2024-07-15T14:31:37.224005Z", "shell.execute_reply": "2024-07-15T14:31:37.223580Z", "shell.execute_reply.started": "2024-07-15T14:31:37.179887Z" } }, "outputs": [], "source": [ "# user_intersting_clips_3p5[\"prompt_text\"]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Express Feedback dataset" ] }, { "cell_type": "code", "execution_count": 111, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:31:37.224701Z", "iopub.status.busy": "2024-07-15T14:31:37.224564Z", "iopub.status.idle": "2024-07-15T14:32:01.933451Z", "shell.execute_reply": "2024-07-15T14:32:01.932869Z", "shell.execute_reply.started": "2024-07-15T14:31:37.224686Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "37,887 rows\n" ] } ], "source": [ "query = f\"\"\"\n", "SELECT * FROM bots_userreaction\n", "WHERE feedback_reason IS NOT NULL\n", "\"\"\"\n", "feedback_reaction_df = pd.read_sql_query(query, engine)\n", "print(f\"{feedback_reaction_df.shape[0]:,} rows\")" ] }, { "cell_type": "code", "execution_count": 112, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:01.934318Z", "iopub.status.busy": "2024-07-15T14:32:01.934162Z", "iopub.status.idle": "2024-07-15T14:32:02.419388Z", "shell.execute_reply": "2024-07-15T14:32:02.418879Z", "shell.execute_reply.started": "2024-07-15T14:32:01.934301Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(37887, 10)\n", "after reemoving no feedback parts (37076, 10)\n" ] } ], "source": [ "print(feedback_reaction_df.shape)\n", "feedback_reaction_df = feedback_reaction_df[\n", " feedback_reaction_df[\"feedback_reason\"] != \"\"\n", "]\n", "print(\"after reemoving no feedback parts\", feedback_reaction_df.shape)" ] }, { "cell_type": "code", "execution_count": 113, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:02.420154Z", "iopub.status.busy": "2024-07-15T14:32:02.420003Z", "iopub.status.idle": "2024-07-15T14:32:02.493547Z", "shell.execute_reply": "2024-07-15T14:32:02.493093Z", "shell.execute_reply.started": "2024-07-15T14:32:02.420137Z" } }, "outputs": [], "source": [ "bad_audio_quality_ids = list(\n", " str(s)\n", " for s in feedback_reaction_df[\n", " feedback_reaction_df[\"feedback_reason\"].str.contains(\"bad_poor_audio_quality\")\n", " ][\"clip_id\"].unique()\n", ")\n", "# with open(\n", "# \"/home/tony/Data/Preference/13b_v0/interesting_clips_20240627_feedback_bad_audio_quality_ids.json\",\n", "# \"w\",\n", "# ) as fp:\n", "# json.dump(bad_audio_quality_ids, fp)" ] }, { "cell_type": "code", "execution_count": 114, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:02.494296Z", "iopub.status.busy": "2024-07-15T14:32:02.494145Z", "iopub.status.idle": "2024-07-15T14:32:02.523062Z", "shell.execute_reply": "2024-07-15T14:32:02.522634Z", "shell.execute_reply.started": "2024-07-15T14:32:02.494280Z" } }, "outputs": [], "source": [ "# id_query_str = \",\".join(\"'\" + x + \"'\" for x in bad_audio_quality_ids)\n", "\n", "# query = f\"\"\"\n", "# SELECT * FROM bots_generatedclip\n", "# WHERE status='complete' AND id IN ({id_query_str})\n", "# \"\"\"\n", "# sub_feedback_clip_df = pd.read_sql_query(query, engine)\n", "\n", "# sub_feedback_request_ids = list(str(s) for s in sub_feedback_clip_df[\"request_id\"].unique())\n", "\n", "# id_value_counts = sub_feedback_clip_df[\"request_id\"].value_counts()\n", "# # Filter to keep only values with a count of 1\n", "# unique_request_values = id_value_counts[id_value_counts == 1].reset_index()[\"request_id\"].unique()\n", "# print(len(unique_request_values))" ] }, { "cell_type": "code", "execution_count": 115, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:02.523868Z", "iopub.status.busy": "2024-07-15T14:32:02.523731Z", "iopub.status.idle": "2024-07-15T14:32:11.337765Z", "shell.execute_reply": "2024-07-15T14:32:11.337190Z", "shell.execute_reply.started": "2024-07-15T14:32:02.523853Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "unique_feedback_clip_ids 37076\n", "(1563, 26)\n" ] } ], "source": [ "feedback_clip_ids = feedback_reaction_df[\"clip_id\"].unique()\n", "print(\"unique_feedback_clip_ids\", len(feedback_clip_ids))\n", "subset_of_clips_df = total_clip_df[total_clip_df[\"id\"].isin(feedback_clip_ids)].copy()\n", "print(subset_of_clips_df.shape)" ] }, { "cell_type": "code", "execution_count": 116, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:11.338583Z", "iopub.status.busy": "2024-07-15T14:32:11.338432Z", "iopub.status.idle": "2024-07-15T14:32:17.626072Z", "shell.execute_reply": "2024-07-15T14:32:17.625498Z", "shell.execute_reply.started": "2024-07-15T14:32:11.338566Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "total feedback requets, 1027\n", "(2051, 40)\n" ] } ], "source": [ "feedback_requests = subset_of_clips_df[\"request_id\"].unique()\n", "print(f\"total feedback requets, {len(feedback_requests)}\")\n", "feedback_clip_df = clip_df[clip_df[\"request_id\"].isin(feedback_requests)].copy()\n", "print(feedback_clip_df.shape)" ] }, { "cell_type": "code", "execution_count": 117, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:17.626943Z", "iopub.status.busy": "2024-07-15T14:32:17.626787Z", "iopub.status.idle": "2024-07-15T14:32:17.647878Z", "shell.execute_reply": "2024-07-15T14:32:17.647437Z", "shell.execute_reply.started": "2024-07-15T14:32:17.626926Z" } }, "outputs": [], "source": [ "# missing_requests = set(feedback_requests).difference(clip_df[\"request_id\"].unique())\n", "# print(\"missing requests\", len(missing_requests))" ] }, { "cell_type": "code", "execution_count": 118, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:17.648736Z", "iopub.status.busy": "2024-07-15T14:32:17.648593Z", "iopub.status.idle": "2024-07-15T14:32:17.734467Z", "shell.execute_reply": "2024-07-15T14:32:17.733981Z", "shell.execute_reply.started": "2024-07-15T14:32:17.648720Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "postive feedbacks 19339, negative feedbacks 17737\n" ] } ], "source": [ "positive_feedback_ids = feedback_reaction_df[\n", " feedback_reaction_df[\"feedback_reason\"] == \"good_quality\"\n", "][\"clip_id\"].unique()\n", "negative_feedback_ids = feedback_reaction_df[\n", " feedback_reaction_df[\"feedback_reason\"] != \"good_quality\"\n", "][\"clip_id\"].unique()\n", "print(\n", " f\"postive feedbacks {len(positive_feedback_ids)}, negative feedbacks {len(negative_feedback_ids)}\"\n", ")" ] }, { "cell_type": "code", "execution_count": 119, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:17.735330Z", "iopub.status.busy": "2024-07-15T14:32:17.735183Z", "iopub.status.idle": "2024-07-15T14:32:17.761663Z", "shell.execute_reply": "2024-07-15T14:32:17.761212Z", "shell.execute_reply.started": "2024-07-15T14:32:17.735312Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "pos_preference\n", "False 1238\n", "True 813\n", "Name: count, dtype: int64 neg_preference\n", "False 1664\n", "True 387\n", "Name: count, dtype: int64\n" ] } ], "source": [ "print(\n", " feedback_clip_df[\"pos_preference\"].value_counts(),\n", " feedback_clip_df[\"neg_preference\"].value_counts(),\n", ")" ] }, { "cell_type": "code", "execution_count": 120, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:17.762366Z", "iopub.status.busy": "2024-07-15T14:32:17.762221Z", "iopub.status.idle": "2024-07-15T14:32:17.826834Z", "shell.execute_reply": "2024-07-15T14:32:17.826385Z", "shell.execute_reply.started": "2024-07-15T14:32:17.762350Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1038 475\n" ] } ], "source": [ "# request has a positive\n", "# postive_feedback_mask = feedback_clip_df[\"id\"].isin(positive_feedback_ids) & (\n", "# ~feedback_clip_df[\"id\"].isin(negative_feedback_ids)\n", "# )\n", "postive_feedback_mask = feedback_clip_df[\"id\"].isin(positive_feedback_ids)\n", "negative_feedback_mask = feedback_clip_df[\"id\"].isin(negative_feedback_ids)\n", "print(sum(postive_feedback_mask), sum(negative_feedback_mask))" ] }, { "cell_type": "code", "execution_count": 121, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:17.827563Z", "iopub.status.busy": "2024-07-15T14:32:17.827421Z", "iopub.status.idle": "2024-07-15T14:32:17.883326Z", "shell.execute_reply": "2024-07-15T14:32:17.882826Z", "shell.execute_reply.started": "2024-07-15T14:32:17.827548Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "total unique requets 1026, \n", "postive feedbacks requests 748,non-positive feedback requets 735, \n", "non-negative feedback requets 917,negative feedbacks requests 366\n", "positive pairs 457 negative pairs 257 total pairs 626\n" ] } ], "source": [ "positive_feedback_requests = set(\n", " feedback_clip_df[postive_feedback_mask][\"request_id\"].unique()\n", ")\n", "non_positive_feedback_requests = set(\n", " feedback_clip_df[~postive_feedback_mask][\"request_id\"].unique()\n", ")\n", "non_negative_feedback_requests = set(\n", " feedback_clip_df[~negative_feedback_mask][\"request_id\"].unique()\n", ")\n", "negative_feedback_requests = set(\n", " feedback_clip_df[negative_feedback_mask][\"request_id\"].unique()\n", ")\n", "print(\n", " f\"total unique requets {feedback_clip_df['request_id'].nunique()}, \\n\"\n", " f\"postive feedbacks requests {len(positive_feedback_requests)},\"\n", " f\"non-positive feedback requets {len(non_positive_feedback_requests)}, \\n\"\n", " f\"non-negative feedback requets {len(non_negative_feedback_requests)},\"\n", " f\"negative feedbacks requests {len(negative_feedback_requests)}\"\n", ")\n", "positive_request_pairs = positive_feedback_requests.intersection(\n", " non_positive_feedback_requests\n", ")\n", "negative_request_pairs = negative_feedback_requests.intersection(\n", " non_negative_feedback_requests\n", ")\n", "total_feedback_requests = positive_request_pairs.union(negative_request_pairs)\n", "print(\n", " f\"positive pairs {len(positive_request_pairs)}\",\n", " f\"negative pairs {len(negative_request_pairs)}\",\n", " f\"total pairs {len(total_feedback_requests)}\",\n", ")" ] }, { "cell_type": "code", "execution_count": 122, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:17.894669Z", "iopub.status.busy": "2024-07-15T14:32:17.894348Z", "iopub.status.idle": "2024-07-15T14:32:17.932955Z", "shell.execute_reply": "2024-07-15T14:32:17.932323Z", "shell.execute_reply.started": "2024-07-15T14:32:17.894650Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(1252, 40)\n" ] } ], "source": [ "paired_feedback_clip_df = feedback_clip_df[\n", " feedback_clip_df[\"request_id\"].isin(total_feedback_requests)\n", "].copy()\n", "print(paired_feedback_clip_df.shape)" ] }, { "cell_type": "code", "execution_count": 123, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:17.933961Z", "iopub.status.busy": "2024-07-15T14:32:17.933787Z", "iopub.status.idle": "2024-07-15T14:32:18.005042Z", "shell.execute_reply": "2024-07-15T14:32:18.004492Z", "shell.execute_reply.started": "2024-07-15T14:32:17.933944Z" } }, "outputs": [], "source": [ "paired_feedback_clip_df[\"pos_feedback\"] = paired_feedback_clip_df[\"id\"].isin(\n", " positive_feedback_ids\n", ") & (~paired_feedback_clip_df[\"id\"].isin(negative_feedback_ids))\n", "paired_feedback_clip_df[\"neg_feedback\"] = paired_feedback_clip_df[\"id\"].isin(\n", " negative_feedback_ids\n", ") & (~paired_feedback_clip_df[\"id\"].isin(positive_feedback_ids))" ] }, { "cell_type": "code", "execution_count": 124, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:18.005921Z", "iopub.status.busy": "2024-07-15T14:32:18.005769Z", "iopub.status.idle": "2024-07-15T14:32:18.040069Z", "shell.execute_reply": "2024-07-15T14:32:18.039554Z", "shell.execute_reply.started": "2024-07-15T14:32:18.005905Z" } }, "outputs": [ { "data": { "text/plain": [ "(pos_feedback\n", " False 795\n", " True 457\n", " Name: count, dtype: int64,\n", " neg_feedback\n", " False 995\n", " True 257\n", " Name: count, dtype: int64)" ] }, "execution_count": 124, "metadata": {}, "output_type": "execute_result" } ], "source": [ "paired_feedback_clip_df[\"pos_feedback\"].value_counts(), paired_feedback_clip_df[\n", " \"neg_feedback\"\n", "].value_counts()" ] }, { "cell_type": "code", "execution_count": 125, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:18.040873Z", "iopub.status.busy": "2024-07-15T14:32:18.040723Z", "iopub.status.idle": "2024-07-15T14:32:18.087977Z", "shell.execute_reply": "2024-07-15T14:32:18.087450Z", "shell.execute_reply.started": "2024-07-15T14:32:18.040858Z" } }, "outputs": [], "source": [ "paired_feedback_clip_df = paired_feedback_clip_df.sort_values(\n", " by=[\"request_id\"]\n", ").reset_index(drop=True)\n", "paired_feedback_clip_df[\"diff_preference\"] = paired_feedback_clip_df[\n", " \"pos_preference\"\n", "].astype(int) - paired_feedback_clip_df[\"neg_preference\"].astype(int)" ] }, { "cell_type": "code", "execution_count": 126, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:18.088976Z", "iopub.status.busy": "2024-07-15T14:32:18.088652Z", "iopub.status.idle": "2024-07-15T14:32:18.143371Z", "shell.execute_reply": "2024-07-15T14:32:18.142860Z", "shell.execute_reply.started": "2024-07-15T14:32:18.088957Z" } }, "outputs": [ { "data": { "text/plain": [ "diff_preference\n", " 0 614\n", " 1 441\n", "-1 197\n", "Name: count, dtype: int64" ] }, "execution_count": 126, "metadata": {}, "output_type": "execute_result" } ], "source": [ "paired_feedback_clip_df[\"diff_preference\"].value_counts()" ] }, { "cell_type": "code", "execution_count": 127, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:18.144325Z", "iopub.status.busy": "2024-07-15T14:32:18.144177Z", "iopub.status.idle": "2024-07-15T14:32:18.206437Z", "shell.execute_reply": "2024-07-15T14:32:18.205839Z", "shell.execute_reply.started": "2024-07-15T14:32:18.144308Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "diff_preference\n", " 0.0 260\n", " 1.0 150\n", "-1.0 142\n", " 2.0 40\n", "-2.0 34\n", "Name: count, dtype: int64\n" ] } ], "source": [ "feedback_diff_series = paired_feedback_clip_df[\"diff_preference\"].diff()\n", "print(\n", " feedback_diff_series[1::2].value_counts()\n", ") # 1 is pos, not neg pair or nothing, neg; 2 is pos / neg (hence the larger difference)\n", "# but this can be wilder...as we didn't filter on requests!" ] }, { "cell_type": "code", "execution_count": 128, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:18.207337Z", "iopub.status.busy": "2024-07-15T14:32:18.207175Z", "iopub.status.idle": "2024-07-15T14:32:18.258200Z", "shell.execute_reply": "2024-07-15T14:32:18.257673Z", "shell.execute_reply.started": "2024-07-15T14:32:18.207320Z" } }, "outputs": [], "source": [ "paired_feedback_clip_df = paired_feedback_clip_df.sort_values(\n", " by=[\"request_id\", \"diff_preference\"]\n", ").reset_index(drop=True)" ] }, { "cell_type": "code", "execution_count": 129, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:18.259012Z", "iopub.status.busy": "2024-07-15T14:32:18.258863Z", "iopub.status.idle": "2024-07-15T14:32:18.312961Z", "shell.execute_reply": "2024-07-15T14:32:18.312427Z", "shell.execute_reply.started": "2024-07-15T14:32:18.258996Z" } }, "outputs": [ { "data": { "text/plain": [ "preference\n", "False 626\n", "True 626\n", "Name: count, dtype: int64" ] }, "execution_count": 129, "metadata": {}, "output_type": "execute_result" } ], "source": [ "paired_feedback_clip_df[\"preference\"] = paired_feedback_clip_df.index % 2 == 1\n", "paired_feedback_clip_df[\"preference\"].value_counts()" ] }, { "cell_type": "code", "execution_count": 130, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:18.313769Z", "iopub.status.busy": "2024-07-15T14:32:18.313619Z", "iopub.status.idle": "2024-07-15T14:32:18.357977Z", "shell.execute_reply": "2024-07-15T14:32:18.357526Z", "shell.execute_reply.started": "2024-07-15T14:32:18.313752Z" } }, "outputs": [], "source": [ "paired_feedback_clip_df[\"diff_feedback\"] = paired_feedback_clip_df[\n", " \"pos_feedback\"\n", "].astype(int) - paired_feedback_clip_df[\"neg_feedback\"].astype(int)" ] }, { "cell_type": "code", "execution_count": 131, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:18.358682Z", "iopub.status.busy": "2024-07-15T14:32:18.358540Z", "iopub.status.idle": "2024-07-15T14:32:18.415622Z", "shell.execute_reply": "2024-07-15T14:32:18.415091Z", "shell.execute_reply.started": "2024-07-15T14:32:18.358666Z" } }, "outputs": [ { "data": { "text/plain": [ "diff_feedback\n", " 0 538\n", " 1 457\n", "-1 257\n", "Name: count, dtype: int64" ] }, "execution_count": 131, "metadata": {}, "output_type": "execute_result" } ], "source": [ "paired_feedback_clip_df[\"diff_feedback\"].value_counts()" ] }, { "cell_type": "code", "execution_count": 132, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:18.416523Z", "iopub.status.busy": "2024-07-15T14:32:18.416369Z", "iopub.status.idle": "2024-07-15T14:32:18.479743Z", "shell.execute_reply": "2024-07-15T14:32:18.479201Z", "shell.execute_reply.started": "2024-07-15T14:32:18.416507Z" } }, "outputs": [], "source": [ "paired_feedback_clip_df = paired_feedback_clip_df.sort_values(\n", " by=[\"request_id\", \"diff_feedback\"]\n", ").reset_index(drop=True)" ] }, { "cell_type": "code", "execution_count": 133, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:18.480608Z", "iopub.status.busy": "2024-07-15T14:32:18.480455Z", "iopub.status.idle": "2024-07-15T14:32:18.520884Z", "shell.execute_reply": "2024-07-15T14:32:18.520322Z", "shell.execute_reply.started": "2024-07-15T14:32:18.480592Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "diff_feedback\n", "1.0 538\n", "2.0 88\n", "Name: count, dtype: int64\n" ] } ], "source": [ "feedback_diff_feedback_series = paired_feedback_clip_df[\"diff_feedback\"].diff()\n", "\n", "print(\n", " feedback_diff_feedback_series[1::2].value_counts()\n", ") # 1 is pos, not neg pair or nothing, neg; 2 is pos / neg (hence the larger difference)\n", "# but this can be wilder...as we didn't filter on requests!" ] }, { "cell_type": "code", "execution_count": 134, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:18.521691Z", "iopub.status.busy": "2024-07-15T14:32:18.521540Z", "iopub.status.idle": "2024-07-15T14:32:18.568087Z", "shell.execute_reply": "2024-07-15T14:32:18.567564Z", "shell.execute_reply.started": "2024-07-15T14:32:18.521674Z" } }, "outputs": [], "source": [ "paired_feedback_clip_df[\"feedback_preference\"] = paired_feedback_clip_df.index % 2 == 1" ] }, { "cell_type": "code", "execution_count": 135, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:18.569042Z", "iopub.status.busy": "2024-07-15T14:32:18.568891Z", "iopub.status.idle": "2024-07-15T14:32:18.619360Z", "shell.execute_reply": "2024-07-15T14:32:18.618849Z", "shell.execute_reply.started": "2024-07-15T14:32:18.569026Z" } }, "outputs": [ { "data": { "text/plain": [ "True 0.744409\n", "False 0.255591\n", "Name: proportion, dtype: float64" ] }, "execution_count": 135, "metadata": {}, "output_type": "execute_result" } ], "source": [ "(\n", " paired_feedback_clip_df[\"feedback_preference\"]\n", " == paired_feedback_clip_df[\"preference\"]\n", ").value_counts(normalize=True)" ] }, { "cell_type": "code", "execution_count": 136, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:18.620196Z", "iopub.status.busy": "2024-07-15T14:32:18.620039Z", "iopub.status.idle": "2024-07-15T14:32:18.666320Z", "shell.execute_reply": "2024-07-15T14:32:18.665811Z", "shell.execute_reply.started": "2024-07-15T14:32:18.620179Z" } }, "outputs": [ { "data": { "text/plain": [ "True 0.813099\n", "False 0.186901\n", "Name: proportion, dtype: float64" ] }, "execution_count": 136, "metadata": {}, "output_type": "execute_result" } ], "source": [ "(\n", " paired_feedback_clip_df[\"pos_feedback\"] == paired_feedback_clip_df[\"pos_preference\"]\n", ").value_counts(normalize=True)" ] }, { "cell_type": "code", "execution_count": 137, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:18.667138Z", "iopub.status.busy": "2024-07-15T14:32:18.666990Z", "iopub.status.idle": "2024-07-15T14:32:18.719006Z", "shell.execute_reply": "2024-07-15T14:32:18.718490Z", "shell.execute_reply.started": "2024-07-15T14:32:18.667123Z" } }, "outputs": [ { "data": { "text/plain": [ "True 0.782748\n", "False 0.217252\n", "Name: proportion, dtype: float64" ] }, "execution_count": 137, "metadata": {}, "output_type": "execute_result" } ], "source": [ "(\n", " paired_feedback_clip_df[\"neg_feedback\"] == paired_feedback_clip_df[\"neg_preference\"]\n", ").value_counts(normalize=True)" ] }, { "cell_type": "code", "execution_count": 138, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:18.719819Z", "iopub.status.busy": "2024-07-15T14:32:18.719673Z", "iopub.status.idle": "2024-07-15T14:32:19.308463Z", "shell.execute_reply": "2024-07-15T14:32:19.307892Z", "shell.execute_reply.started": "2024-07-15T14:32:18.719804Z" } }, "outputs": [ { "data": { "text/plain": [ "221" ] }, "execution_count": 138, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# overlapping with existing?\n", "paired_feedback_clip_df[\"request_id\"].isin(\n", " final_interesting_clips[\"request_id\"]\n", ").sum() // 2" ] }, { "cell_type": "code", "execution_count": 139, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:19.309353Z", "iopub.status.busy": "2024-07-15T14:32:19.309197Z", "iopub.status.idle": "2024-07-15T14:32:19.328786Z", "shell.execute_reply": "2024-07-15T14:32:19.328233Z", "shell.execute_reply.started": "2024-07-15T14:32:19.309336Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(1252, 45)\n" ] } ], "source": [ "# paired_feedback_clip_df.to_csv(\"/home/tony/Data/Preference/13b_v0/interesting_clips_20240712_feedback.csv\", index=False)\n", "print(paired_feedback_clip_df.shape)" ] }, { "cell_type": "code", "execution_count": 140, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:19.329599Z", "iopub.status.busy": "2024-07-15T14:32:19.329451Z", "iopub.status.idle": "2024-07-15T14:32:19.385139Z", "shell.execute_reply": "2024-07-15T14:32:19.384591Z", "shell.execute_reply.started": "2024-07-15T14:32:19.329583Z" } }, "outputs": [], "source": [ "weird_feedback_mask = (paired_feedback_clip_df[\"pos_feedback\"] == True) & (\n", " paired_feedback_clip_df[\"dislike_count\"] > 0\n", ")" ] }, { "cell_type": "code", "execution_count": 141, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:19.385959Z", "iopub.status.busy": "2024-07-15T14:32:19.385802Z", "iopub.status.idle": "2024-07-15T14:32:19.438451Z", "shell.execute_reply": "2024-07-15T14:32:19.437931Z", "shell.execute_reply.started": "2024-07-15T14:32:19.385943Z" } }, "outputs": [ { "data": { "text/plain": [ "user_id\n", "5388914 3\n", "4951235 3\n", "1514454 2\n", "4540475 2\n", "171120 1\n", "3562155 1\n", "20799 1\n", "4848914 1\n", "5462432 1\n", "5241603 1\n", "4174763 1\n", "4841498 1\n", "Name: count, dtype: int64" ] }, "execution_count": 141, "metadata": {}, "output_type": "execute_result" } ], "source": [ "paired_feedback_clip_df[weird_feedback_mask][\"user_id\"].value_counts()" ] }, { "cell_type": "code", "execution_count": 142, "metadata": { "execution": { "iopub.execute_input": "2024-07-15T14:32:19.439277Z", "iopub.status.busy": "2024-07-15T14:32:19.439122Z", "iopub.status.idle": "2024-07-15T14:32:19.493268Z", "shell.execute_reply": "2024-07-15T14:32:19.492772Z", "shell.execute_reply.started": "2024-07-15T14:32:19.439261Z" } }, "outputs": [], "source": [ "# feedback_reaction_df[feedback_reaction_df[\"clip_id\"].isin(paired_feedback_clip_df[weird_feedback_mask][\"id\"].unique())]" ] }, { "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 }