mirror of https://github.com/coqui-ai/TTS.git
55 lines
1.7 KiB
Python
55 lines
1.7 KiB
Python
import glob
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import os
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import shutil
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from tests import get_device_id, get_tests_output_path, run_cli
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from TTS.tts.configs import TacotronConfig
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config_path = os.path.join(get_tests_output_path(), "test_model_config.json")
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output_path = os.path.join(get_tests_output_path(), "train_outputs")
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config = TacotronConfig(
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batch_size=8,
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eval_batch_size=8,
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num_loader_workers=0,
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num_eval_loader_workers=0,
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text_cleaner="english_cleaners",
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use_phonemes=False,
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phoneme_language="en-us",
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phoneme_cache_path=os.path.join(get_tests_output_path(), "train_outputs/phoneme_cache/"),
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run_eval=True,
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test_delay_epochs=-1,
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epochs=1,
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print_step=1,
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test_sentences=[
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"Be a voice, not an echo.",
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],
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print_eval=True,
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r=5,
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max_decoder_steps=50,
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)
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config.audio.do_trim_silence = True
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config.audio.trim_db = 60
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config.save_json(config_path)
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# train the model for one epoch
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command_train = (
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f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_tts.py --config_path {config_path} "
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f"--coqpit.output_path {output_path} "
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"--coqpit.datasets.0.name ljspeech "
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"--coqpit.datasets.0.meta_file_train metadata.csv "
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"--coqpit.datasets.0.meta_file_val metadata.csv "
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"--coqpit.datasets.0.path tests/data/ljspeech "
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"--coqpit.test_delay_epochs 0"
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)
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run_cli(command_train)
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# Find latest folder
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continue_path = max(glob.glob(os.path.join(output_path, "*/")), key=os.path.getmtime)
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# restore the model and continue training for one more epoch
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command_train = f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_tts.py --continue_path {continue_path} "
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run_cli(command_train)
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shutil.rmtree(continue_path)
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