mirror of https://github.com/coqui-ai/TTS.git
parent
c8b9ca3d71
commit
39004484b9
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@ -103,8 +103,8 @@ synthesizer = Synthesizer(
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model_path, config_path, speakers_file_path, vocoder_path, vocoder_config_path, use_cuda=args.use_cuda
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model_path, config_path, speakers_file_path, vocoder_path, vocoder_config_path, use_cuda=args.use_cuda
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)
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)
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use_multi_speaker = synthesizer.tts_model.speaker_manager is not None and synthesizer.tts_model.num_speakers > 1
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use_multi_speaker = hasattr(synthesizer.tts_model, "speaker_manager") and synthesizer.tts_model.num_speakers > 1
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speaker_manager = synthesizer.tts_model.speaker_manager if hasattr(synthesizer.tts_model, "speaker_manager") else None
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speaker_manager = getattr(synthesizer.tts_model, "speaker_manager", None)
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# TODO: set this from SpeakerManager
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# TODO: set this from SpeakerManager
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use_gst = synthesizer.tts_config.get("use_gst", False)
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use_gst = synthesizer.tts_config.get("use_gst", False)
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app = Flask(__name__)
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app = Flask(__name__)
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@ -820,7 +820,7 @@ class Trainer:
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"""🏃 train -> evaluate -> test for the number of epochs."""
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"""🏃 train -> evaluate -> test for the number of epochs."""
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if self.restore_step != 0 or self.args.best_path:
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if self.restore_step != 0 or self.args.best_path:
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print(" > Restoring best loss from " f"{os.path.basename(self.args.best_path)} ...")
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print(" > Restoring best loss from " f"{os.path.basename(self.args.best_path)} ...")
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self.best_loss = load_fsspec(self.args.best_path, map_location="cpu")["model_loss"]
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self.best_loss = load_fsspec(self.args.restore_path, map_location="cpu")["model_loss"]
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print(f" > Starting with loaded last best loss {self.best_loss}.")
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print(f" > Starting with loaded last best loss {self.best_loss}.")
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self.total_steps_done = self.restore_step
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self.total_steps_done = self.restore_step
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