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Update README.md

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@@ -255,7 +255,7 @@ The objective of RealFormer is to attain the maximum level of detail to the real
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  ```python
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  RealFormerAGA(
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  (patch_embed): DynamicPatchEmbedding(
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- (proj): Conv2d(2048, 768, kernel_size=(1, 1), stride=(1, 1))
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  )
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  (encoder_layers): ModuleList(
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  (0-15): 16 x TransformerEncoderBlock(
@@ -330,9 +330,9 @@ RealFormerAGA(
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  (bn): BatchNorm2d(3, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
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  (relu): ReLU(inplace=True)
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  )
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- (final_layer): Conv2d(3, 2048, kernel_size=(1, 1), stride=(1, 1))
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  (style_encoder): Sequential(
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- (0): Conv2d(2048, 768, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))
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  (1): ReLU()
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  (2): AdaptiveAvgPool2d(output_size=1)
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  (3): Flatten(start_dim=1, end_dim=-1)
 
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  ```python
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  RealFormerAGA(
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  (patch_embed): DynamicPatchEmbedding(
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+ (proj): Conv2d(3, 768, kernel_size=(1, 1), stride=(1, 1))
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  )
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  (encoder_layers): ModuleList(
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  (0-15): 16 x TransformerEncoderBlock(
 
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  (bn): BatchNorm2d(3, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
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  (relu): ReLU(inplace=True)
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  )
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+ (final_layer): Conv2d(3, 3, kernel_size=(1, 1), stride=(1, 1))
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  (style_encoder): Sequential(
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+ (0): Conv2d(3, 768, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))
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  (1): ReLU()
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  (2): AdaptiveAvgPool2d(output_size=1)
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  (3): Flatten(start_dim=1, end_dim=-1)