mirror of https://github.com/coqui-ai/TTS.git
137 lines
4.8 KiB
Python
137 lines
4.8 KiB
Python
from dataclasses import dataclass, field
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from typing import List
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from TTS.tts.configs.shared_configs import BaseTTSConfig
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from TTS.tts.models.vits import VitsArgs
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@dataclass
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class VitsConfig(BaseTTSConfig):
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"""Defines parameters for VITS End2End TTS model.
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Args:
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model (str):
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Model name. Do not change unless you know what you are doing.
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model_args (VitsArgs):
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Model architecture arguments. Defaults to `VitsArgs()`.
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grad_clip (List):
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Gradient clipping thresholds for each optimizer. Defaults to `[5.0, 5.0]`.
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lr_gen (float):
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Initial learning rate for the generator. Defaults to 0.0002.
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lr_disc (float):
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Initial learning rate for the discriminator. Defaults to 0.0002.
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lr_scheduler_gen (str):
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Name of the learning rate scheduler for the generator. One of the `torch.optim.lr_scheduler.*`. Defaults to
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`ExponentialLR`.
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lr_scheduler_gen_params (dict):
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Parameters for the learning rate scheduler of the generator. Defaults to `{'gamma': 0.999875, "last_epoch":-1}`.
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lr_scheduler_disc (str):
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Name of the learning rate scheduler for the discriminator. One of the `torch.optim.lr_scheduler.*`. Defaults to
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`ExponentialLR`.
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lr_scheduler_disc_params (dict):
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Parameters for the learning rate scheduler of the discriminator. Defaults to `{'gamma': 0.999875, "last_epoch":-1}`.
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scheduler_after_epoch (bool):
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If true, step the schedulers after each epoch else after each step. Defaults to `False`.
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optimizer (str):
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Name of the optimizer to use with both the generator and the discriminator networks. One of the
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`torch.optim.*`. Defaults to `AdamW`.
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kl_loss_alpha (float):
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Loss weight for KL loss. Defaults to 1.0.
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disc_loss_alpha (float):
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Loss weight for the discriminator loss. Defaults to 1.0.
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gen_loss_alpha (float):
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Loss weight for the generator loss. Defaults to 1.0.
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feat_loss_alpha (float):
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Loss weight for the feature matching loss. Defaults to 1.0.
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mel_loss_alpha (float):
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Loss weight for the mel loss. Defaults to 45.0.
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return_wav (bool):
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If true, data loader returns the waveform as well as the other outputs. Do not change. Defaults to `True`.
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compute_linear_spec (bool):
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If true, the linear spectrogram is computed and returned alongside the mel output. Do not change. Defaults to `True`.
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min_seq_len (int):
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Minimum text length to be considered for training. Defaults to `13`.
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max_seq_len (int):
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Maximum text length to be considered for training. Defaults to `500`.
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r (int):
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Number of spectrogram frames to be generated at a time. Do not change. Defaults to `1`.
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add_blank (bool):
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If true, a blank token is added in between every character. Defaults to `True`.
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test_sentences (List[str]):
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List of sentences to be used for testing.
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Note:
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Check :class:`TTS.tts.configs.shared_configs.BaseTTSConfig` for the inherited parameters.
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Example:
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>>> from TTS.tts.configs import VitsConfig
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>>> config = VitsConfig()
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"""
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model: str = "vits"
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# model specific params
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model_args: VitsArgs = field(default_factory=VitsArgs)
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# optimizer
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grad_clip: List[float] = field(default_factory=lambda: [5, 5])
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lr_gen: float = 0.0002
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lr_disc: float = 0.0002
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lr_scheduler_gen: str = "ExponentialLR"
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lr_scheduler_gen_params: dict = field(default_factory=lambda: {"gamma": 0.999875, "last_epoch": -1})
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lr_scheduler_disc: str = "ExponentialLR"
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lr_scheduler_disc_params: dict = field(default_factory=lambda: {"gamma": 0.999875, "last_epoch": -1})
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scheduler_after_epoch: bool = True
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optimizer: str = "AdamW"
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optimizer_params: dict = field(default_factory=lambda: {"betas": [0.8, 0.99], "eps": 1e-9, "weight_decay": 0.01})
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# loss params
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kl_loss_alpha: float = 1.0
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disc_loss_alpha: float = 1.0
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gen_loss_alpha: float = 1.0
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feat_loss_alpha: float = 1.0
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mel_loss_alpha: float = 45.0
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# data loader params
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return_wav: bool = True
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compute_linear_spec: bool = True
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# overrides
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min_seq_len: int = 32
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max_seq_len: int = 1000
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r: int = 1 # DO NOT CHANGE
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add_blank: bool = True
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# testing
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test_sentences: List[str] = field(
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default_factory=lambda: [
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"It took me quite a long time to develop a voice, and now that I have it I'm not going to be silent.",
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"Be a voice, not an echo.",
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"I'm sorry Dave. I'm afraid I can't do that.",
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"This cake is great. It's so delicious and moist.",
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"Prior to November 22, 1963.",
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]
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)
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