kromskii2/alltalk_tts
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add warmup

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bmalaski committed 2024-07-02 00:14:54 -04:00
1 parent 797a4b996a
commit e347f15046
3 files changed
+63 -7
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finetune.py
+15 -7
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@@ -704,7 +704,7 @@ def basemodel_or_finetunedmodel_choice(value):
elif value == "Existing finetuned model":
basemodel_or_finetunedmodel = False
def train_gpt(language, num_epochs, batch_size, grad_acumm, train_csv, eval_csv, learning_rate, model_to_train, continue_run, disable_shared_memory, learning_rate_scheduler, optimizer, max_audio_length=255995, progress=gr.Progress()):
def train_gpt(language, num_epochs, batch_size, grad_acumm, train_csv, eval_csv, learning_rate, model_to_train, continue_run, disable_shared_memory, learning_rate_scheduler, optimizer, warm_up, max_audio_length=255995, progress=gr.Progress()):
pfc_check_fail()
if "No Models Available" in model_to_train:
@@ -983,6 +983,8 @@ def train_gpt(language, num_epochs, batch_size, grad_acumm, train_csv, eval_csv,
eval_samples=eval_samples,
training_assets=training_assets,
c_logger=c_logger,
warmup=warm_up,
)
if(disable_shared_memory):
@@ -1789,6 +1791,11 @@ if __name__ == "__main__":
label="Disable Shared Memory Use",
scale=1,
)
warm_up = gr.Checkbox(
value=False,
label="Perform Small a Warmup Learning",
scale=1,
)
train_csv = gr.Textbox(
label="Train CSV:",
scale=2,
@@ -1875,7 +1882,7 @@ if __name__ == "__main__":
grad_acumm = gr.Slider(
label="Grad accumulation steps:",
minimum=1,
maximum=32,
maximum=128,
step=1,
value=args.grad_acumm,
)
@@ -1906,7 +1913,7 @@ if __name__ == "__main__":
demo.load(load_metrics, None, [model_data, train_time], every=1)
demo.load(read_logs, None, logs_tts_train, every=1)
def train_model(language, train_csv, eval_csv, learning_rates, model_to_train, num_epochs, batch_size, grad_acumm, max_audio_length, speaker_name_input_training, continue_run, disable_shared_memory, learning_rate_scheduler, optimizer, progress=gr.Progress()):
def train_model(language, train_csv, eval_csv, learning_rates, model_to_train, num_epochs, batch_size, grad_acumm, max_audio_length, speaker_name_input_training, continue_run, disable_shared_memory, learning_rate_scheduler, optimizer, warm_up, progress=gr.Progress()):
clear_gpu_cache()
global out_path
if speaker_name_input_training and speaker_name_input_training != 'personsname':
@@ -1914,8 +1921,8 @@ if __name__ == "__main__":
if not train_csv or not eval_csv:
if (out_path / "metadata_eval.csv").exists() and (out_path / "metadata_train.csv").exists():
train_csv = out_path / "metadata_eval.csv"
eval_csv = out_path / "metadata_train.csv"
train_csv = out_path / "metadata_train.csv"
eval_csv = out_path / "metadata_eval.csv"
print("Using existing metadata and training csv.")
else:
return "You need to run the data processing step or manually set `Train CSV` and `Eval CSV` fields !", "", "", "", ""
@@ -1924,7 +1931,7 @@ if __name__ == "__main__":
max_audio_length = int(max_audio_length * 22050)
learning_rate = float(learning_rates) # Convert the learning rate value to a float
progress(0, "Initializing training...")
config_path, original_xtts_checkpoint, vocab_file, exp_path, speaker_wav = train_gpt(language, num_epochs, batch_size, grad_acumm, train_csv, eval_csv, learning_rate, model_to_train, continue_run, disable_shared_memory, learning_rate_scheduler, optimizer, max_audio_length=max_audio_length, progress=gr.Progress())
config_path, original_xtts_checkpoint, vocab_file, exp_path, speaker_wav = train_gpt(language, num_epochs, batch_size, grad_acumm, train_csv, eval_csv, learning_rate, model_to_train, continue_run, disable_shared_memory, learning_rate_scheduler, optimizer, warm_up, max_audio_length=max_audio_length, progress=gr.Progress())
# copy original files to avoid parameters changes issues
shutil.copy(config_path, exp_path)
@@ -2304,7 +2311,8 @@ if __name__ == "__main__":
continue_run,
disable_shared_memory,
learning_rate_scheduler,
optimizer
optimizer,
warm_up
],
outputs=[progress_train, xtts_config, xtts_vocab, xtts_checkpoint, speaker_reference_audio, speaker_name_input_testing],
)