mirror of https://github.com/coqui-ai/TTS.git
56 lines
1.7 KiB
Python
56 lines
1.7 KiB
Python
from dataclasses import asdict, dataclass, field
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from .shared_configs import BaseGANVocoderConfig
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@dataclass
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class HifiganConfig(BaseGANVocoderConfig):
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"""Defines parameters for HifiGAN vocoder."""
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model: str = "hifigan"
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# model specific params
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discriminator_model: str = "hifigan_discriminator"
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generator_model: str = "hifigan_generator"
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generator_model_params: dict = field(
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default_factory=lambda: {
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"upsample_factors": [8, 8, 2, 2],
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"upsample_kernel_sizes": [16, 16, 4, 4],
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"upsample_initial_channel": 512,
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"resblock_kernel_sizes": [3, 7, 11],
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"resblock_dilation_sizes": [[1, 3, 5], [1, 3, 5], [1, 3, 5]],
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"resblock_type": "1",
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}
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)
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# LOSS PARAMETERS - overrides
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use_stft_loss: bool = False
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use_subband_stft_loss: bool = False
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use_mse_gan_loss: bool = True
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use_hinge_gan_loss: bool = False
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use_feat_match_loss: bool = True # requires MelGAN Discriminators (MelGAN and HifiGAN)
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use_l1_spec_loss: bool = True
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# loss weights - overrides
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stft_loss_weight: float = 0
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subband_stft_loss_weight: float = 0
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mse_G_loss_weight: float = 1
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hinge_G_loss_weight: float = 0
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feat_match_loss_weight: float = 108
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l1_spec_loss_weight: float = 45
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l1_spec_loss_params: dict = field(
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default_factory=lambda: {
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"use_mel": True,
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"sample_rate": 22050,
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"n_fft": 1024,
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"hop_length": 256,
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"win_length": 1024,
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"n_mels": 80,
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"mel_fmin": 0.0,
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"mel_fmax": None,
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}
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)
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# optimizer parameters
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lr: float = 1e-4
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wd: float = 1e-6
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