add I-JEPA pretrained weight for ViT

timm/models/vision_transformer.py

@@ -879,6 +879,17 @@ def _convert_dinov2(state_dict, model):
     return out_dict
 
 
+def _convert_ijepa(state_dict, model):
+    out_dict = {}
+    for k, v in state_dict['encoder'].items():
+        if k.startswith('module.'):
+            k = k[7:]
+        if k.startswith('norm.'):
+            k = 'fc_norm.' + k[5:]
+        out_dict[k] = v
+    return out_dict
+
+
 def checkpoint_filter_fn(
         state_dict,
         model,
@@ -896,7 +907,10 @@ def checkpoint_filter_fn(
         return _convert_openai_clip(state_dict, model)
 
     if "mask_token" in state_dict:
-        return _convert_dinov2(state_dict, model)
+        state_dict = _convert_dinov2(state_dict, model)
+
+    if "encoder" in state_dict:
+        state_dict = _convert_ijepa(state_dict, model)
 
     for k, v in state_dict.items():
         if 'patch_embed.proj.weight' in k:
@@ -1437,6 +1451,27 @@ def _cfg(url='', **kwargs):
         hf_hub_id='timm/',
         license='cc-by-nc-4.0',
         mean=IMAGENET_DEFAULT_MEAN, std=IMAGENET_DEFAULT_STD, num_classes=0),
+
+    'vit_huge_patch14_224_ijepa.in1k': _cfg(
+        url='https://dl.fbaipublicfiles.com/ijepa/IN1K-vit.h.14-300e.pth.tar',
+        # hf_hub_id='timm/',
+        license='cc-by-nc-4.0',
+        mean=IMAGENET_DEFAULT_MEAN, std=IMAGENET_DEFAULT_STD, num_classes=0),
+    'vit_huge_patch14_224_ijepa.in22k': _cfg(
+        url='https://dl.fbaipublicfiles.com/ijepa/IN22K-vit.h.14-900e.pth.tar',
+        # hf_hub_id='timm/',
+        license='cc-by-nc-4.0',
+        mean=IMAGENET_DEFAULT_MEAN, std=IMAGENET_DEFAULT_STD, num_classes=0),
+    'vit_huge_patch16_448_ijepa.in1k': _cfg(
+        url='https://dl.fbaipublicfiles.com/ijepa/IN1K-vit.h.16-448px-300e.pth.tar',
+        # hf_hub_id='timm/',
+        license='cc-by-nc-4.0',
+        mean=IMAGENET_DEFAULT_MEAN, std=IMAGENET_DEFAULT_STD, num_classes=0),
+    'vit_gigantic_patch16_224_ijepa.in22k': _cfg(
+        url='https://dl.fbaipublicfiles.com/ijepa/IN22K-vit.g.16-600e.pth.tar',
+        # hf_hub_id='timm/',
+        license='cc-by-nc-4.0',
+        mean=IMAGENET_DEFAULT_MEAN, std=IMAGENET_DEFAULT_STD, num_classes=0),
 })
 
 
@@ -2031,6 +2066,30 @@ def vit_giant_patch14_dinov2(pretrained=False, **kwargs) -> VisionTransformer:
         'vit_giant_patch14_dinov2', pretrained=pretrained, **dict(model_args, **kwargs))
     return model
 
+@register_model
+def vit_huge_patch14_224_ijepa(pretrained=False, **kwargs) -> VisionTransformer:
+    """ ViT-Huge model (ViT-H/14) from `I-JEPA` - https://arxiv.org/abs/2301.08243
+    """
+    model_args = dict(patch_size=14, embed_dim=1280, depth=32, num_heads=16, class_token=False, global_pool='avg')
+    model = _create_vision_transformer('vit_huge_patch14_224_ijepa', pretrained=pretrained, **dict(model_args, **kwargs))
+    return model
+
+@register_model
+def vit_huge_patch16_448_ijepa(pretrained=False, **kwargs) -> VisionTransformer:
+    """ ViT-Huge model (ViT-H/16) from `I-JEPA` - https://arxiv.org/abs/2301.08243
+    """
+    model_args = dict(patch_size=16, embed_dim=1280, depth=32, num_heads=16, class_token=False, global_pool='avg', img_size=448)
+    model = _create_vision_transformer('vit_huge_patch16_448_ijepa', pretrained=pretrained, **dict(model_args, **kwargs))
+    return model
+
+@register_model
+def vit_gigantic_patch16_224_ijepa(pretrained=False, **kwargs) -> VisionTransformer:
+    """ ViT-Gigantic (big-G) model (ViT-G/16) from `I-JEPA - https://arxiv.org/abs/2301.08243
+    """
+    model_args = dict(patch_size=16, embed_dim=1664, mlp_ratio=64/13, depth=48, num_heads=16)
+    model = _create_vision_transformer(
+        'vit_gigantic_patch16_224_ijepa', pretrained=pretrained, **dict(model_args, **kwargs))
+    return model
 
 register_model_deprecations(__name__, {
     'vit_tiny_patch16_224_in21k': 'vit_tiny_patch16_224.augreg_in21k',

timm/models/vision_transformer_sam.py

@@ -605,6 +605,3 @@ def samvit_huge_patch16(pretrained=False, **kwargs) -> VisionTransformerSAM:
     model = _create_vision_transformer(
         'samvit_huge_patch16', pretrained=pretrained, **dict(model_args, **kwargs))
     return model
-
-# TODO:
-# support any input size, now only 1024 x 1024 (pretrained)