mirror of https://github.com/coqui-ai/TTS.git
52 lines
1.6 KiB
Python
52 lines
1.6 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 MelganConfig(BaseGANVocoderConfig):
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"""Defines parameters for MelGAN vocoder."""
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model: str = "melgan"
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# Model specific params
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discriminator_model: str = "melgan_multiscale_discriminator"
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discriminator_model_params: dict = field(
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default_factory=lambda: {"base_channels": 16, "max_channels": 1024, "downsample_factors": [4, 4, 4, 4]}
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)
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generator_model: str = "melgan_generator"
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generator_model_params: dict = field(
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default_factory=lambda: {"upsample_factors": [8, 8, 2, 2], "num_res_blocks": 3}
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)
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# Training - overrides
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batch_size: int = 16
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seq_len: int = 8192
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pad_short: int = 2000
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use_noise_augment: bool = True
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use_cache: bool = True
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# LOSS PARAMETERS - overrides
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use_stft_loss: bool = True
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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 = False
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stft_loss_params: dict = field(
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default_factory=lambda: {
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"n_ffts": [1024, 2048, 512],
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"hop_lengths": [120, 240, 50],
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"win_lengths": [600, 1200, 240],
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}
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)
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# loss weights - overrides
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stft_loss_weight: float = 0.5
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subband_stft_loss_weight: float = 0
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mse_G_loss_weight: float = 2.5
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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 = 0
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