56 lines
2.0 KiB
Python
56 lines
2.0 KiB
Python
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from coqpit import Coqpit
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from TTS.model import BaseTrainerModel
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# pylint: skip-file
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class BaseVocoder(BaseTrainerModel):
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"""Base `vocoder` class. Every new `vocoder` model must inherit this.
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It defines `vocoder` specific functions on top of `Model`.
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Notes on input/output tensor shapes:
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Any input or output tensor of the model must be shaped as
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- 3D tensors `batch x time x channels`
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- 2D tensors `batch x channels`
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- 1D tensors `batch x 1`
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"""
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MODEL_TYPE = "vocoder"
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def __init__(self, config):
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super().__init__()
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self._set_model_args(config)
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def _set_model_args(self, config: Coqpit):
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"""Setup model args based on the config type.
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If the config is for training with a name like "*Config", then the model args are embeded in the
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config.model_args
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If the config is for the model with a name like "*Args", then we assign the directly.
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"""
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# don't use isintance not to import recursively
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if "Config" in config.__class__.__name__:
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if "characters" in config:
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_, self.config, num_chars = self.get_characters(config)
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self.config.num_chars = num_chars
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if hasattr(self.config, "model_args"):
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config.model_args.num_chars = num_chars
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if "model_args" in config:
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self.args = self.config.model_args
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# This is for backward compatibility
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if "model_params" in config:
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self.args = self.config.model_params
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else:
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self.config = config
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if "model_args" in config:
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self.args = self.config.model_args
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# This is for backward compatibility
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if "model_params" in config:
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self.args = self.config.model_params
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else:
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raise ValueError("config must be either a *Config or *Args")
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