mirror of https://github.com/coqui-ai/TTS.git
Fix vits args types
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@ -119,7 +119,7 @@ class VitsArgs(Coqpit):
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upsample_kernel_sizes_decoder (List[int]):
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Kernel sizes for each upsampling layer of the decoder network. Defaults to `[16, 16, 4, 4]`.
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use_sdp (int):
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use_sdp (bool):
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Use Stochastic Duration Predictor. Defaults to True.
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noise_scale (float):
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@ -128,7 +128,7 @@ class VitsArgs(Coqpit):
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inference_noise_scale (float):
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Noise scale used for the sample noise tensor in inference. Defaults to 0.667.
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length_scale (int):
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length_scale (float):
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Scale factor for the predicted duration values. Smaller values result faster speech. Defaults to 1.
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noise_scale_dp (float):
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@ -176,24 +176,24 @@ class VitsArgs(Coqpit):
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num_heads_text_encoder: int = 2
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num_layers_text_encoder: int = 6
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kernel_size_text_encoder: int = 3
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dropout_p_text_encoder: int = 0.1
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dropout_p_duration_predictor: int = 0.5
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dropout_p_text_encoder: float = 0.1
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dropout_p_duration_predictor: float = 0.5
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kernel_size_posterior_encoder: int = 5
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dilation_rate_posterior_encoder: int = 1
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num_layers_posterior_encoder: int = 16
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kernel_size_flow: int = 5
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dilation_rate_flow: int = 1
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num_layers_flow: int = 4
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resblock_type_decoder: int = "1"
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resblock_type_decoder: str = "1"
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resblock_kernel_sizes_decoder: List[int] = field(default_factory=lambda: [3, 7, 11])
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resblock_dilation_sizes_decoder: List[List[int]] = field(default_factory=lambda: [[1, 3, 5], [1, 3, 5], [1, 3, 5]])
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upsample_rates_decoder: List[int] = field(default_factory=lambda: [8, 8, 2, 2])
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upsample_initial_channel_decoder: int = 512
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upsample_kernel_sizes_decoder: List[int] = field(default_factory=lambda: [16, 16, 4, 4])
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use_sdp: int = True
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use_sdp: bool = True
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noise_scale: float = 1.0
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inference_noise_scale: float = 0.667
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length_scale: int = 1
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length_scale: float = 1
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noise_scale_dp: float = 1.0
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inference_noise_scale_dp: float = 1.0
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max_inference_len: int = None
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