| from transformers import PretrainedConfig | |
| class USADConfig(PretrainedConfig): | |
| model_type = "usad" | |
| def __init__( | |
| self, | |
| encoder_dim: int = 384, | |
| num_layers: int = 12, | |
| attention_type: str = "mhsa", | |
| num_attention_heads: int = 6, | |
| mamba_d_state: int = 16, | |
| mamba_d_conv: int = 4, | |
| mamba_expand: int = 2, | |
| mamba_bidirectional: bool = False, | |
| feed_forward_expansion_factor: int = 4, | |
| conv_expansion_factor: int = 2, | |
| feed_forward_dropout_p: float = 0.1, | |
| attention_dropout_p: float = 0.1, | |
| conv_dropout_p: float = 0.1, | |
| conv_kernel_size: int = 31, | |
| half_step_residual: bool = True, | |
| transformer_style: bool = True, | |
| use_framewise_subsample: bool = True, | |
| use_patchwise_subsample: bool = False, | |
| conv_subsample_channels: int = 64, | |
| conv_subsample_rate: int = 2, | |
| input_dim: int = 128, | |
| input_dropout_p: float = 0.0, | |
| conv_pos: bool = True, | |
| conv_pos_depth: int = 5, | |
| conv_pos_width: int = 95, | |
| conv_pos_groups: int = 16, | |
| subsample_normalization: bool = True, | |
| **kwargs, | |
| ): | |
| super().__init__(**kwargs) | |
| self.encoder_dim = encoder_dim | |
| self.num_layers = num_layers | |
| self.attention_type = attention_type | |
| self.num_attention_heads = num_attention_heads | |
| self.mamba_d_state = mamba_d_state | |
| self.mamba_d_conv = mamba_d_conv | |
| self.mamba_expand = mamba_expand | |
| self.mamba_bidirectional = mamba_bidirectional | |
| self.feed_forward_expansion_factor = feed_forward_expansion_factor | |
| self.conv_expansion_factor = conv_expansion_factor | |
| self.feed_forward_dropout_p = feed_forward_dropout_p | |
| self.attention_dropout_p = attention_dropout_p | |
| self.conv_dropout_p = conv_dropout_p | |
| self.conv_kernel_size = conv_kernel_size | |
| self.half_step_residual = half_step_residual | |
| self.transformer_style = transformer_style | |
| self.use_framewise_subsample = use_framewise_subsample | |
| self.use_patchwise_subsample = use_patchwise_subsample | |
| self.conv_subsample_channels = conv_subsample_channels | |
| self.conv_subsample_rate = conv_subsample_rate | |
| self.input_dim = input_dim | |
| self.input_dropout_p = input_dropout_p | |
| self.conv_pos = conv_pos | |
| self.conv_pos_depth = conv_pos_depth | |
| self.conv_pos_width = conv_pos_width | |
| self.conv_pos_groups = conv_pos_groups | |
| self.subsample_normalization = subsample_normalization | |