mirror of https://github.com/coqui-ai/TTS.git
101 lines
3.6 KiB
Python
101 lines
3.6 KiB
Python
import glob
|
|
import json
|
|
import os
|
|
import shutil
|
|
|
|
from trainer import get_last_checkpoint
|
|
|
|
from tests import get_device_id, get_tests_output_path, run_cli
|
|
from TTS.tts.configs.delightful_tts_config import DelightfulTtsAudioConfig, DelightfulTTSConfig
|
|
from TTS.tts.models.delightful_tts import DelightfulTtsArgs, VocoderConfig
|
|
|
|
config_path = os.path.join(get_tests_output_path(), "test_model_config.json")
|
|
output_path = os.path.join(get_tests_output_path(), "train_outputs")
|
|
|
|
|
|
audio_config = DelightfulTtsAudioConfig()
|
|
model_args = DelightfulTtsArgs(
|
|
use_speaker_embedding=False, d_vector_dim=256, use_d_vector_file=True, speaker_embedding_channels=256
|
|
)
|
|
|
|
vocoder_config = VocoderConfig()
|
|
|
|
config = DelightfulTTSConfig(
|
|
model_args=model_args,
|
|
audio=audio_config,
|
|
vocoder=vocoder_config,
|
|
batch_size=2,
|
|
eval_batch_size=8,
|
|
compute_f0=True,
|
|
run_eval=True,
|
|
test_delay_epochs=-1,
|
|
text_cleaner="english_cleaners",
|
|
use_phonemes=True,
|
|
phoneme_language="en-us",
|
|
phoneme_cache_path="tests/data/ljspeech/phoneme_cache/",
|
|
f0_cache_path="tests/data/ljspeech/f0_cache_delightful/", ## delightful f0 cache is incompatible with other models
|
|
epochs=1,
|
|
print_step=1,
|
|
print_eval=True,
|
|
binary_align_loss_alpha=0.0,
|
|
use_attn_priors=False,
|
|
test_sentences=[
|
|
["Be a voice, not an echo.", "ljspeech-0"],
|
|
],
|
|
output_path=output_path,
|
|
use_speaker_embedding=False,
|
|
use_d_vector_file=True,
|
|
d_vector_file="tests/data/ljspeech/speakers.json",
|
|
d_vector_dim=256,
|
|
speaker_embedding_channels=256,
|
|
)
|
|
|
|
# active multispeaker d-vec mode
|
|
config.model_args.use_speaker_embedding = False
|
|
config.model_args.use_d_vector_file = True
|
|
config.model_args.d_vector_file = "tests/data/ljspeech/speakers.json"
|
|
config.model_args.d_vector_dim = 256
|
|
|
|
|
|
config.save_json(config_path)
|
|
|
|
command_train = (
|
|
f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_tts.py --config_path {config_path} "
|
|
f"--coqpit.output_path {output_path} "
|
|
"--coqpit.datasets.0.formatter ljspeech "
|
|
"--coqpit.datasets.0.meta_file_train metadata.csv "
|
|
"--coqpit.datasets.0.meta_file_val metadata.csv "
|
|
"--coqpit.datasets.0.path tests/data/ljspeech "
|
|
"--coqpit.datasets.0.meta_file_attn_mask tests/data/ljspeech/metadata_attn_mask.txt "
|
|
"--coqpit.test_delay_epochs 0"
|
|
)
|
|
|
|
run_cli(command_train)
|
|
|
|
# Find latest folder
|
|
continue_path = max(glob.glob(os.path.join(output_path, "*/")), key=os.path.getmtime)
|
|
|
|
# Inference using TTS API
|
|
continue_config_path = os.path.join(continue_path, "config.json")
|
|
continue_restore_path, _ = get_last_checkpoint(continue_path)
|
|
speaker_id = "ljspeech-1"
|
|
continue_speakers_path = config.d_vector_file
|
|
|
|
out_wav_path = os.path.join(get_tests_output_path(), "output.wav")
|
|
# Check integrity of the config
|
|
with open(continue_config_path, "r", encoding="utf-8") as f:
|
|
config_loaded = json.load(f)
|
|
assert config_loaded["characters"] is not None
|
|
assert config_loaded["output_path"] in continue_path
|
|
assert config_loaded["test_delay_epochs"] == 0
|
|
|
|
# Load the model and run inference
|
|
inference_command = f"CUDA_VISIBLE_DEVICES='{get_device_id()}' tts --text 'This is an example.' --speaker_idx {speaker_id} --config_path {continue_config_path} --speakers_file_path {continue_speakers_path} --model_path {continue_restore_path} --out_path {out_wav_path}"
|
|
run_cli(inference_command)
|
|
|
|
# restore the model and continue training for one more epoch
|
|
command_train = f"CUDA_VISIBLE_DEVICES='{get_device_id()}' python TTS/bin/train_tts.py --continue_path {continue_path} "
|
|
run_cli(command_train)
|
|
shutil.rmtree(continue_path)
|
|
shutil.rmtree("tests/data/ljspeech/f0_cache_delightful/")
|