| from transformers import PretrainedConfig |
|
|
|
|
| |
| class DaViTConfig(PretrainedConfig): |
| model_type = "davit" |
|
|
| def __init__( |
| self, |
| in_chans=3, |
| |
| depths=(1, 1, 9, 1), |
| patch_size=(7, 3, 3, 3), |
| patch_stride=(4, 2, 2, 2), |
| patch_padding=(3, 1, 1, 1), |
| patch_prenorm=(False, True, True, True), |
| embed_dims=(256, 512, 1024, 2048), |
| num_heads=(8, 16, 32, 64), |
| num_groups=(8, 16, 32, 64), |
| window_size=12, |
| mlp_ratio=4.0, |
| qkv_bias=True, |
| drop_path_rate=0.1, |
| norm_layer="layer_norm", |
| enable_checkpoint=False, |
| conv_at_attn=True, |
| conv_at_ffn=True, |
| projection_dim=1024, |
| **kwargs |
| ): |
| super().__init__(**kwargs) |
| self.in_chans = in_chans |
| |
| self.depths = depths |
| self.patch_size = patch_size |
| self.patch_stride = patch_stride |
| self.patch_padding = patch_padding |
| self.patch_prenorm = patch_prenorm |
| self.embed_dims = embed_dims |
| self.num_heads = num_heads |
| self.num_groups = num_groups |
| self.window_size = window_size |
| self.mlp_ratio = mlp_ratio |
| self.qkv_bias = qkv_bias |
| self.drop_path_rate = drop_path_rate |
| self.norm_layer = norm_layer |
| self.enable_checkpoint = enable_checkpoint |
| self.conv_at_attn = conv_at_attn |
| self.conv_at_ffn = conv_at_ffn |
| self.projection_dim = projection_dim |
|
|
