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{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"id": "4effe69f",
"metadata": {},
"outputs": [],
"source": [
"from __future__ import print_function\n",
"\n",
"import argparse\n",
"import datetime\n",
"import os\n",
"from copy import deepcopy\n",
"\n",
"import deepspeed\n",
"import torch\n",
"import torch.distributed as dist\n",
"from hyperpyyaml import load_hyperpyyaml\n",
"from loguru import logger\n",
"from torch.distributed.elastic.multiprocessing.errors import record\n",
"\n",
"from comet_ml import Experiment\n",
"from cosyvoice.utils.executor import Executor\n",
"from cosyvoice.utils.losses import DPOLoss\n",
"from cosyvoice.utils.train_utils import (check_modify_and_save_config,\n",
" init_dataset_and_dataloader,\n",
" init_optimizer_and_scheduler,\n",
" save_model)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "0322c8f4",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/mas/anaconda3/envs/learnable/lib/python3.10/site-packages/diffusers/models/lora.py:393: FutureWarning: `LoRACompatibleLinear` is deprecated and will be removed in version 1.0.0. Use of `LoRACompatibleLinear` is deprecated. Please switch to PEFT backend by installing PEFT: `pip install peft`.\n",
" deprecate(\"LoRACompatibleLinear\", \"1.0.0\", deprecation_message)\n",
"2025-07-14 13:59:59,637 INFO input frame rate=25\n"
]
}
],
"source": [
"override_dict = {\n",
" k: None for k in [\"llm\", \"flow\", \"hift\", \"hifigan\"] if k != 'flow'\n",
"}\n",
"config = 'cosyvoice2.yaml'\n",
"qwen_pretrain_path = './pretrained_models/CosyVoice2-0.5B/CosyVoice-BlankEN'\n",
"try:\n",
" with open(config, \"r\", encoding=\"utf-8\") as f:\n",
" configs = load_hyperpyyaml(\n",
" f,\n",
" overrides={\n",
" **override_dict,\n",
" \"qwen_pretrain_path\": qwen_pretrain_path,\n",
" },\n",
" )\n",
"except Exception as e:\n",
" logger.error(f\"Error loading config: {e}\")\n",
" with open(config, \"r\", encoding=\"utf-8\") as f:\n",
" configs = load_hyperpyyaml(f, overrides=override_dict)\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "a0ba457c",
"metadata": {},
"outputs": [],
"source": [
"data_pipeline = configs['data_pipeline']\n",
"train_data = 'data/data.list'"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "03fe8925",
"metadata": {},
"outputs": [],
"source": [
"from cosyvoice.dataset.dataset import Dataset\n",
"train_dataset = Dataset(train_data, data_pipeline=data_pipeline, mode='train', gan=False, dpo=False, shuffle=True, partition=True)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "41bc6b44",
"metadata": {},
"outputs": [],
"source": [
"cnt = 0\n",
"for data in train_dataset:\n",
" if cnt==2:\n",
" break\n",
" cnt += 1"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "6f689e0b",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"dict_keys(['utts', 'speech_token', 'speech_token_len', 'speech_feat', 'speech_feat_len', 'text', 'text_token', 'text_token_len', 'utt_embedding', 'spk_embedding', 'embedding'])"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.keys()"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "cfbef316",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(tensor(47, dtype=torch.int32),\n",
" tensor([47, 50, 49, 49, 49, 48, 48, 48, 48, 47, 43, 47, 46, 46, 46, 45, 45, 45,\n",
" 45, 43], dtype=torch.int32))"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data['speech_token_len'][0], data['speech_token_len']"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "d0942196",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(20, 20, 20)"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(data['utts']), len(data['text']), len(data['speech_token_len'])"
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "622100eb",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(torch.Size([20]),\n",
" torch.Size([20]),\n",
" torch.Size([20, 192]),\n",
" torch.Size([20, 98, 80]),\n",
" torch.Size([20, 192]),\n",
" torch.Size([20]),\n",
" torch.Size([20, 192]))"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data['speech_token_len'].shape, data['speech_token_len'].shape, data['spk_embedding'].shape, data['speech_feat'].shape, data['embedding'].shape, data['speech_feat_len'].shape, data['embedding'].shape"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "0adc02f8",
"metadata": {},
"outputs": [],
"source": [
"token_len = data['speech_token_len']"
]
},
{
"cell_type": "code",
"execution_count": 38,
"id": "7aea884b",
"metadata": {},
"outputs": [],
"source": [
"from cosyvoice.utils.mask import make_pad_mask\n",
"mask = (~make_pad_mask(token_len)).float().unsqueeze(-1)"
]
},
{
"cell_type": "code",
"execution_count": 39,
"id": "45422efa",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"torch.Size([20, 50, 1])"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"mask.shape"
]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "0f2b0b77",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"tensor([47, 50, 49, 49, 49, 48, 48, 48, 48, 47, 43, 47, 46, 46, 46, 45, 45, 45,\n",
" 45, 43], dtype=torch.int32)"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"token_len"
]
},
{
"cell_type": "markdown",
"id": "fbf1de4d",
"metadata": {},
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "learnable",
"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": "3.10.18"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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