feat(openvoice): add config classes

TTS/vc/configs/freevc_config.py

@@ -229,7 +229,7 @@ class FreeVCConfig(BaseVCConfig):
             If true, language embedding is used. Defaults to `False`.
 
     Note:
-        Check :class:`TTS.tts.configs.shared_configs.BaseTTSConfig` for the inherited parameters.
+        Check :class:`TTS.tts.configs.shared_configs.BaseVCConfig` for the inherited parameters.
 
     Example:
 

TTS/vc/configs/openvoice_config.py

@@ -0,0 +1,201 @@
+from dataclasses import dataclass, field
+from typing import Optional
+
+from coqpit import Coqpit
+
+from TTS.vc.configs.shared_configs import BaseVCConfig
+
+
+@dataclass
+class OpenVoiceAudioConfig(Coqpit):
+    """Audio configuration
+
+    Args:
+        input_sample_rate (int):
+            The sampling rate of the input waveform.
+
+        output_sample_rate (int):
+            The sampling rate of the output waveform.
+
+        fft_size (int):
+            The length of the filter.
+
+        hop_length (int):
+            The hop length.
+
+        win_length (int):
+            The window length.
+    """
+
+    input_sample_rate: int = field(default=22050)
+    output_sample_rate: int = field(default=22050)
+    fft_size: int = field(default=1024)
+    hop_length: int = field(default=256)
+    win_length: int = field(default=1024)
+
+
+@dataclass
+class OpenVoiceArgs(Coqpit):
+    """OpenVoice model arguments.
+
+    zero_g (bool):
+        Whether to zero the gradients.
+
+    inter_channels (int):
+        The number of channels in the intermediate layers.
+
+    hidden_channels (int):
+        The number of channels in the hidden layers.
+
+    filter_channels (int):
+        The number of channels in the filter layers.
+
+    n_heads (int):
+        The number of attention heads.
+
+    n_layers (int):
+        The number of layers.
+
+    kernel_size (int):
+        The size of the kernel.
+
+    p_dropout (float):
+        The dropout probability.
+
+    resblock (str):
+        The type of residual block.
+
+    resblock_kernel_sizes (List[int]):
+        The kernel sizes for the residual blocks.
+
+    resblock_dilation_sizes (List[List[int]]):
+        The dilation sizes for the residual blocks.
+
+    upsample_rates (List[int]):
+        The upsample rates.
+
+    upsample_initial_channel (int):
+        The number of channels in the initial upsample layer.
+
+    upsample_kernel_sizes (List[int]):
+        The kernel sizes for the upsample layers.
+
+    n_layers_q (int):
+        The number of layers in the quantization network.
+
+    use_spectral_norm (bool):
+        Whether to use spectral normalization.
+
+    gin_channels (int):
+        The number of channels in the global conditioning vector.
+
+    tau (float):
+        Tau parameter for the posterior encoder
+    """
+
+    zero_g: bool = field(default=True)
+    inter_channels: int = field(default=192)
+    hidden_channels: int = field(default=192)
+    filter_channels: int = field(default=768)
+    n_heads: int = field(default=2)
+    n_layers: int = field(default=6)
+    kernel_size: int = field(default=3)
+    p_dropout: float = field(default=0.1)
+    resblock: str = field(default="1")
+    resblock_kernel_sizes: list[int] = field(default_factory=lambda: [3, 7, 11])
+    resblock_dilation_sizes: list[list[int]] = field(default_factory=lambda: [[1, 3, 5], [1, 3, 5], [1, 3, 5]])
+    upsample_rates: list[int] = field(default_factory=lambda: [8, 8, 2, 2])
+    upsample_initial_channel: int = field(default=512)
+    upsample_kernel_sizes: list[int] = field(default_factory=lambda: [16, 16, 4, 4])
+    n_layers_q: int = field(default=3)
+    use_spectral_norm: bool = field(default=False)
+    gin_channels: int = field(default=256)
+    tau: float = field(default=0.3)
+
+
+@dataclass
+class OpenVoiceConfig(BaseVCConfig):
+    """Defines parameters for OpenVoice VC model.
+
+    Args:
+        model (str):
+            Model name. Do not change unless you know what you are doing.
+
+        model_args (OpenVoiceArgs):
+            Model architecture arguments. Defaults to `OpenVoiceArgs()`.
+
+        audio (OpenVoiceAudioConfig):
+            Audio processing configuration. Defaults to `OpenVoiceAudioConfig()`.
+
+        return_wav (bool):
+            If true, data loader returns the waveform as well as the other outputs. Do not change. Defaults to `True`.
+
+        compute_linear_spec (bool):
+            If true, the linear spectrogram is computed and returned alongside the mel output. Do not change. Defaults to `True`.
+
+        use_weighted_sampler (bool):
+            If true, use weighted sampler with bucketing for balancing samples between datasets used in training. Defaults to `False`.
+
+        weighted_sampler_attrs (dict):
+            Key retuned by the formatter to be used for weighted sampler. For example `{"root_path": 2.0, "speaker_name": 1.0}` sets sample probabilities
+            by overweighting `root_path` by 2.0. Defaults to `{}`.
+
+        weighted_sampler_multipliers (dict):
+            Weight each unique value of a key returned by the formatter for weighted sampling.
+            For example `{"root_path":{"/raid/datasets/libritts-clean-16khz-bwe-coqui_44khz/LibriTTS/train-clean-100/":1.0, "/raid/datasets/libritts-clean-16khz-bwe-coqui_44khz/LibriTTS/train-clean-360/": 0.5}`.
+            It will sample instances from `train-clean-100` 2 times more than `train-clean-360`. Defaults to `{}`.
+
+        r (int):
+            Number of spectrogram frames to be generated at a time. Do not change. Defaults to `1`.
+
+        add_blank (bool):
+            If true, a blank token is added in between every character. Defaults to `True`.
+
+    Note:
+        Check :class:`TTS.tts.configs.shared_configs.BaseVCConfig` for the inherited parameters.
+
+    Example:
+
+        >>> from TTS.vc.configs.openvoice_config import OpenVoiceConfig
+        >>> config = OpenVoiceConfig()
+    """
+
+    model: str = "openvoice"
+    # model specific params
+    model_args: OpenVoiceArgs = field(default_factory=OpenVoiceArgs)
+    audio: OpenVoiceAudioConfig = field(default_factory=OpenVoiceAudioConfig)
+
+    # optimizer
+    # TODO with training support
+
+    # loss params
+    # TODO with training support
+
+    # data loader params
+    return_wav: bool = True
+    compute_linear_spec: bool = True
+
+    # sampler params
+    use_weighted_sampler: bool = False  # TODO: move it to the base config
+    weighted_sampler_attrs: dict = field(default_factory=lambda: {})
+    weighted_sampler_multipliers: dict = field(default_factory=lambda: {})
+
+    # overrides
+    r: int = 1  # DO NOT CHANGE
+    add_blank: bool = True
+
+    # multi-speaker settings
+    # use speaker embedding layer
+    num_speakers: int = 0
+    speakers_file: Optional[str] = None
+    speaker_embedding_channels: int = 256
+
+    # use d-vectors
+    use_d_vector_file: bool = False
+    d_vector_file: Optional[list[str]] = None
+    d_vector_dim: Optional[int] = None
+
+    def __post_init__(self) -> None:
+        for key, val in self.model_args.items():
+            if hasattr(self, key):
+                self[key] = val