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config.json

@@ -1,4 +1,5 @@
 {
+  "_name_or_path": "/Users/andrewmayes/Dev/DaViT/models--amaye15--DaViT-Florence-2-large-ft/snapshots/4cc7068026aaeb388ba2b0826abae30d670de3fc",
   "architectures": [
     "DaViTModel"
   ],

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:16681ba87304886ec1ddac2a7bf40f127352bf5470fcc654da2199bc6776a775
-size 721311024
+oid sha256:a9e5478c88ead1963dca36b397c923b5e8c0a0c9897e94fff90c015f949fe4a4
+size 721319376

modeling_davit.py

@@ -597,11 +597,11 @@ class DaViTModel(PreTrainedModel):
         self.convs = nn.ModuleList(convs)
         self.blocks = nn.ModuleList(blocks)
 
-        # self.norms = (
-        #     nn.LayerNorm(self.embed_dims[-1])
-        #     if config.norm_layer == "layer_norm"
-        #     else nn.BatchNorm2d(self.embed_dims[-1])
-        # )
+        self.norms = (
+            nn.LayerNorm(self.embed_dims[-1])
+            if config.norm_layer == "layer_norm"
+            else nn.BatchNorm2d(self.embed_dims[-1])
+        )
         self.avgpool = nn.AdaptiveAvgPool1d(1)
         # self.head = (
         #     nn.Linear(self.embed_dims[-1], self.num_classes)
@@ -650,7 +650,7 @@ class DaViTModel(PreTrainedModel):
         x = self.avgpool(x.transpose(1, 2))
         # (batch_size, 1, num_tokens)
         x = torch.flatten(x, 1)
-        # x = self.norms(x)
+        x = self.norms(x)
 
         return x