| from transformers import PretrainedConfig | |
| class SatDINOConfig(PretrainedConfig): | |
| model_type = "satdino" | |
| def __init__( | |
| self, | |
| img_size=[224], | |
| patch_size=16, | |
| in_chans=3, | |
| num_classes=0, | |
| embed_dim=768, | |
| depth=12, | |
| num_heads=12, | |
| mlp_ratio=4., | |
| qkv_bias=False, | |
| qk_scale=None, | |
| drop_rate=0., | |
| attn_drop_rate=0., | |
| drop_path_rate=0., | |
| norm_layer=1e-6, | |
| use_xformers=False, | |
| pos_encoding_method="learnable", | |
| **kwargs | |
| ): | |
| self.img_size = img_size | |
| self.patch_size = patch_size | |
| self.in_chans = in_chans | |
| self.num_classes = num_classes | |
| self.embed_dim = embed_dim | |
| self.depth = depth | |
| self.num_heads = num_heads | |
| self.mlp_ratio = mlp_ratio | |
| self.qkv_bias = qkv_bias | |
| self.qk_scale = qk_scale | |
| self.drop_rate = drop_rate | |
| self.attn_drop_rate = attn_drop_rate | |
| self.drop_path_rate = drop_path_rate | |
| self.norm_layer = norm_layer | |
| self.use_xformers = use_xformers | |
| self.pos_encoding_method = pos_encoding_method | |
| super().__init__(**kwargs) | |