| from transformers import PretrainedConfig | |
| class MySegformerConfig(PretrainedConfig): | |
| model_type = "my_segformer" | |
| def __init__( | |
| self, | |
| embed_dims=[64, 128, 320, 512], | |
| num_stages=4, | |
| num_layers=[3, 4, 6, 3], | |
| num_heads=[1, 2, 4, 8], | |
| patch_sizes=[7, 3, 3, 3], | |
| strides=[4, 2, 2, 2], | |
| sr_ratios=[8, 4, 2, 1], | |
| mlp_ratio=4, | |
| qkv_bias=True, | |
| drop_rate=0.0, | |
| attn_drop_rate=0.0, | |
| drop_path_rate=0.0, | |
| out_indices=(0, 1, 2, 3), | |
| **kwargs | |
| ): | |
| super().__init__(**kwargs) | |
| # Absicherung, falls embed_dims als int übergeben wird | |
| if isinstance(embed_dims, int): | |
| embed_dims = [embed_dims] | |
| self.embed_dims = embed_dims | |
| self.num_stages = num_stages | |
| self.num_layers = num_layers | |
| self.num_heads = num_heads | |
| self.patch_sizes = patch_sizes | |
| self.strides = strides | |
| self.sr_ratios = sr_ratios | |
| self.mlp_ratio = mlp_ratio | |
| self.qkv_bias = qkv_bias | |
| self.drop_rate = drop_rate | |
| self.attn_drop_rate = attn_drop_rate | |
| self.drop_path_rate = drop_path_rate | |
| self.out_indices = out_indices | |