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- pyproject.toml +1 -1
- src/f5_tts/model/trainer.py +0 -2
pyproject.toml
CHANGED
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
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[project]
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name = "f5-tts"
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version = "1.0.
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description = "F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matching"
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readme = "README.md"
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license = {text = "MIT License"}
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[project]
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name = "f5-tts"
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+
version = "1.0.7"
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description = "F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matching"
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readme = "README.md"
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license = {text = "MIT License"}
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src/f5_tts/model/trainer.py
CHANGED
@@ -357,7 +357,6 @@ class Trainer:
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)
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for batch in current_dataloader:
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-
print("shitttttttttttttttt", self.model.training)
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with self.accelerator.accumulate(self.model):
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text_inputs = batch["text"]
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mel_spec = batch["mel"].permute(0, 2, 1)
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@@ -429,7 +428,6 @@ class Trainer:
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torchaudio.save(
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f"{log_samples_path}/update_{global_update}_ref.wav", ref_audio, target_sample_rate
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)
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-
self.model.train()
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if global_update % self.last_per_updates == 0 and self.accelerator.sync_gradients:
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self.save_checkpoint(global_update, last=True)
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)
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for batch in current_dataloader:
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with self.accelerator.accumulate(self.model):
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text_inputs = batch["text"]
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mel_spec = batch["mel"].permute(0, 2, 1)
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torchaudio.save(
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f"{log_samples_path}/update_{global_update}_ref.wav", ref_audio, target_sample_rate
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)
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if global_update % self.last_per_updates == 0 and self.accelerator.sync_gradients:
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self.save_checkpoint(global_update, last=True)
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