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| #!/usr/bin/python3 | |
| # -*- coding: utf-8 -*- | |
| from typing import Any, Dict, List, Tuple, Union | |
| from toolbox.torchaudio.configuration_utils import PretrainedConfig | |
| class DfNetConfig(PretrainedConfig): | |
| def __init__(self, | |
| sample_rate: int, | |
| fft_size: int, | |
| hop_size: int, | |
| df_bins: int, | |
| erb_bins: int, | |
| min_freq_bins_for_erb: int, | |
| df_order: int, | |
| df_lookahead: int, | |
| norm_tau: int, | |
| lsnr_max: int, | |
| lsnr_min: int, | |
| conv_channels: int, | |
| conv_kernel_size_input: Tuple[int, int], | |
| conv_kernel_size_inner: Tuple[int, int], | |
| convt_kernel_size_inner: Tuple[int, int], | |
| conv_lookahead: int, | |
| emb_hidden_dim: int, | |
| mask_post_filter: bool, | |
| df_hidden_dim: int, | |
| df_num_layers: int, | |
| df_pathway_kernel_size_t: int, | |
| df_gru_skip: str, | |
| post_filter_beta: float, | |
| df_n_iter: float, | |
| lsnr_dropout: bool, | |
| encoder_gru_skip_op: str, | |
| encoder_linear_groups: int, | |
| encoder_squeezed_gru_linear_groups: int, | |
| encoder_concat: bool, | |
| erb_decoder_gru_skip_op: str, | |
| erb_decoder_linear_groups: int, | |
| erb_decoder_emb_num_layers: int, | |
| df_decoder_linear_groups: int, | |
| **kwargs | |
| ): | |
| super(DfNetConfig, self).__init__(**kwargs) | |
| if df_gru_skip not in ("none", "identity", "grouped_linear"): | |
| raise AssertionError | |
| self.sample_rate = sample_rate | |
| self.fft_size = fft_size | |
| self.hop_size = hop_size | |
| self.df_bins = df_bins | |
| self.erb_bins = erb_bins | |
| self.min_freq_bins_for_erb = min_freq_bins_for_erb | |
| self.df_order = df_order | |
| self.df_lookahead = df_lookahead | |
| self.norm_tau = norm_tau | |
| self.lsnr_max = lsnr_max | |
| self.lsnr_min = lsnr_min | |
| self.conv_channels = conv_channels | |
| self.conv_kernel_size_input = conv_kernel_size_input | |
| self.conv_kernel_size_inner = conv_kernel_size_inner | |
| self.convt_kernel_size_inner = convt_kernel_size_inner | |
| self.conv_lookahead = conv_lookahead | |
| self.emb_hidden_dim = emb_hidden_dim | |
| self.mask_post_filter = mask_post_filter | |
| self.df_hidden_dim = df_hidden_dim | |
| self.df_num_layers = df_num_layers | |
| self.df_pathway_kernel_size_t = df_pathway_kernel_size_t | |
| self.df_gru_skip = df_gru_skip | |
| self.post_filter_beta = post_filter_beta | |
| self.df_n_iter = df_n_iter | |
| self.lsnr_dropout = lsnr_dropout | |
| self.encoder_gru_skip_op = encoder_gru_skip_op | |
| self.encoder_linear_groups = encoder_linear_groups | |
| self.encoder_squeezed_gru_linear_groups = encoder_squeezed_gru_linear_groups | |
| self.encoder_concat = encoder_concat | |
| self.erb_decoder_gru_skip_op = erb_decoder_gru_skip_op | |
| self.erb_decoder_linear_groups = erb_decoder_linear_groups | |
| self.erb_decoder_emb_num_layers = erb_decoder_emb_num_layers | |
| self.df_decoder_linear_groups = df_decoder_linear_groups | |
| if __name__ == "__main__": | |
| pass | |