update hello.py.

hello.py

@@ -51,17 +51,27 @@ def net():
 #     masking_ratio = 0.5  # they found 50% to yield the best results
 # )
 
-   
     model = NesT(
     image_size = 600,
     patch_size = 30,
     dim = 256,
     heads = 18,#16
     num_hierarchies = 3,        # number of hierarchies
-    block_repeats = (3, 3, 16),  # (2,2,12) the number of transformer blocks at each heirarchy, starting from the bottom
+    block_repeats = (2, 4, 18),  # (2,4,16)(2,4,12)(2,2,12) the number of transformer blocks at each heirarchy, starting from the bottom
     num_classes = 5
 )
 
+   
+#     model = NesT(
+#     image_size = 600,
+#     patch_size = 30,
+#     dim = 256,
+#     heads = 16,#16
+#     num_hierarchies = 3,        # number of hierarchies
+#     block_repeats = (2, 3, 16),  # (2,2,12) the number of transformer blocks at each heirarchy, starting from the bottom
+#     num_classes = 5
+# )
+
 #     model = CrossFormer( #图片尺寸要是7的倍数，如448
 #     num_classes = 5,                # number of output classes
 #     dim = (64, 128, 256, 512),         # dimension at each stage
@@ -404,8 +414,4 @@ if __name__ == "__main__":
     LEARNING_RATE = 3e-2
     WEIGHT_DECAY = 0
     WARMUP_STEPS = 500
-    train(model,train_loader,device,train_NUM_STEPS,LEARNING_RATE,WEIGHT_DECAY,WARMUP_STEPS,test_loader)
-
-
-
-    
+    train(model,train_loader,device,train_NUM_STEPS,LEARNING_RATE,WEIGHT_DECAY,WARMUP_STEPS,test_loader)