monkey patched timm swintransformer model

app.py

@@ -106,7 +106,7 @@ def Final_Compute_regression_results_Sample(Model, batch_sampler,num_head=2):
             if ratios.vcdr < 0.6:
                 glaucoma = 'None (Rule of thumb ~0.6 or greater is suspicious)'
             else:
-                glaucoma = 'May be thre is a risk of Glaucoma (Rule of thumb ~0.6 or greater is suspicious)'
+                glaucoma = 'May be there is a risk of Glaucoma (Rule of thumb ~0.6 or greater is suspicious)'
 
             # print('Galucoma:')
 

pipline.py

@@ -11,12 +11,38 @@ from collections import namedtuple
 
 # check you have the right version of timm
 # assert timm.__version__ == "0.3.2"
-from timm.models.swin_transformer import swin_base_patch4_window12_384_in22k
+from timm.models.swin_transformer import swin_base_patch4_window12_384_in22k, SwinTransformer
 
 torch.manual_seed(0)
 device = "cuda" if torch.cuda.is_available() else "cpu"
 pad_value = 10
 
+def forward_features(self, x):
+    x = self.patch_embed(x)
+    if self.absolute_pos_embed is not None:
+        x = x + self.absolute_pos_embed
+    x = self.pos_drop(x)
+
+    hide=[]
+    for layer in self.layers:
+        x = layer(x)
+        #print(x.shape)
+        hide.append(x)
+
+    #x = self.layers(x)
+    x = self.norm(x)  # B L C
+    return hide
+
+def forward(self, x):
+        x = self.forward_features(x)
+        #x = self.forward_head(x)
+        return x
+
+SwinTransformer.forward_features = forward_features
+SwinTransformer.forward = forward
+
+
+
 
 def extract_regions_Last(img_test, ytruth, pad1=pad_value, pad2=pad_value, pad3=pad_value, pad4=pad_value):