diff --git a/ppcls/configs/ImageNet/CSPNet/CSPDarkNet53.yaml b/ppcls/configs/ImageNet/CSPNet/CSPDarkNet53.yaml
index cce4e3e591a1fad7ae8e78b1c523309ba7cec298..e512e5b32c79fb97909287d0d4f33b8d612dfc09 100644
--- a/ppcls/configs/ImageNet/CSPNet/CSPDarkNet53.yaml
+++ b/ppcls/configs/ImageNet/CSPNet/CSPDarkNet53.yaml
@@ -11,7 +11,7 @@ Global:
   print_batch_step: 10
   use_visualdl: False
   # used for static mode and model export
-  image_shape: [3, 224, 224]
+  image_shape: [3, 256, 256]
   save_inference_dir: ./inference
   # training model under @to_static
   to_static: False
diff --git a/ppcls/configs/ImageNet/DarkNet/DarkNet53.yaml b/ppcls/configs/ImageNet/DarkNet/DarkNet53.yaml
index 1a55e75d4661b1759dc46ac2203ad5f1e2ceb2fb..ba1478ffab6e3eca4c56af1cf59f3195f793b0f9 100644
--- a/ppcls/configs/ImageNet/DarkNet/DarkNet53.yaml
+++ b/ppcls/configs/ImageNet/DarkNet/DarkNet53.yaml
@@ -11,7 +11,7 @@ Global:
   print_batch_step: 10
   use_visualdl: False
   # used for static mode and model export
-  image_shape: [3, 224, 224]
+  image_shape: [3, 256, 256]
   save_inference_dir: ./inference
 
 # model architecture
@@ -53,7 +53,7 @@ DataLoader:
             to_rgb: True
             channel_first: False
         - RandCropImage:
-            size: 224
+            size: 256
         - RandFlipImage:
             flip_code: 1
         - NormalizeImage:
@@ -84,9 +84,9 @@ DataLoader:
             to_rgb: True
             channel_first: False
         - ResizeImage:
-            resize_short: 256
+            resize_short: 292
         - CropImage:
-            size: 224
+            size: 256
         - NormalizeImage:
             scale: 1.0/255.0
             mean: [0.485, 0.456, 0.406]
@@ -109,9 +109,9 @@ Infer:
         to_rgb: True
         channel_first: False
     - ResizeImage:
-        resize_short: 256
+        resize_short: 292
     - CropImage:
-        size: 224
+        size: 256
     - NormalizeImage:
         scale: 1.0/255.0
         mean: [0.485, 0.456, 0.406]
diff --git a/ppcls/configs/ImageNet/EfficientNet/EfficientNetB1.yaml b/ppcls/configs/ImageNet/EfficientNet/EfficientNetB1.yaml
index 502be5ead0ead05881dc0d1051d4aaee5023713f..92ec91b7ee941f6d61332100c9d9d49c034f6617 100644
--- a/ppcls/configs/ImageNet/EfficientNet/EfficientNetB1.yaml
+++ b/ppcls/configs/ImageNet/EfficientNet/EfficientNetB1.yaml
@@ -11,7 +11,7 @@ Global:
   print_batch_step: 10
   use_visualdl: False
   # used for static mode and model export
-  image_shape: [3, 224, 224]
+  image_shape: [3, 240, 240]
   save_inference_dir: ./inference
 
 # model architecture
@@ -110,9 +110,9 @@ Infer:
         to_rgb: True
         channel_first: False
     - ResizeImage:
-        resize_short: 256
+        resize_short: 272
     - CropImage:
-        size: 224
+        size: 240
     - NormalizeImage:
         scale: 1.0/255.0
         mean: [0.485, 0.456, 0.406]
diff --git a/ppcls/configs/ImageNet/EfficientNet/EfficientNetB2.yaml b/ppcls/configs/ImageNet/EfficientNet/EfficientNetB2.yaml
index 230d5604c25b0e87638d2b4c04c780dfd37f189b..16f2e2f11c918baef824b41d055cea387b855a44 100644
--- a/ppcls/configs/ImageNet/EfficientNet/EfficientNetB2.yaml
+++ b/ppcls/configs/ImageNet/EfficientNet/EfficientNetB2.yaml
@@ -11,7 +11,7 @@ Global:
   print_batch_step: 10
   use_visualdl: False
   # used for static mode and model export
-  image_shape: [3, 224, 224]
+  image_shape: [3, 260, 260]
   save_inference_dir: ./inference
 
 # model architecture
@@ -110,9 +110,9 @@ Infer:
         to_rgb: True
         channel_first: False
     - ResizeImage:
-        resize_short: 256
+        resize_short: 292
     - CropImage:
-        size: 224
+        size: 260
     - NormalizeImage:
         scale: 1.0/255.0
         mean: [0.485, 0.456, 0.406]
diff --git a/ppcls/configs/ImageNet/EfficientNet/EfficientNetB3.yaml b/ppcls/configs/ImageNet/EfficientNet/EfficientNetB3.yaml
index fcd8c013ff283e685b39a350e8b53b409be7d0d7..0847256f693c31590e502a9ecfe32b7477d0320f 100644
--- a/ppcls/configs/ImageNet/EfficientNet/EfficientNetB3.yaml
+++ b/ppcls/configs/ImageNet/EfficientNet/EfficientNetB3.yaml
@@ -11,7 +11,7 @@ Global:
   print_batch_step: 10
   use_visualdl: False
   # used for static mode and model export
-  image_shape: [3, 224, 224]
+  image_shape: [3, 300, 300]
   save_inference_dir: ./inference
 
 # model architecture
@@ -110,9 +110,9 @@ Infer:
         to_rgb: True
         channel_first: False
     - ResizeImage:
-        resize_short: 256
+        resize_short: 332
     - CropImage:
-        size: 224
+        size: 300
     - NormalizeImage:
         scale: 1.0/255.0
         mean: [0.485, 0.456, 0.406]
diff --git a/ppcls/configs/ImageNet/EfficientNet/EfficientNetB4.yaml b/ppcls/configs/ImageNet/EfficientNet/EfficientNetB4.yaml
index 1f97c7106a5898c14a64f0a735ec2de1f48efe69..c5396ff2bd92540eee6f857cdb1c06e7258eb756 100644
--- a/ppcls/configs/ImageNet/EfficientNet/EfficientNetB4.yaml
+++ b/ppcls/configs/ImageNet/EfficientNet/EfficientNetB4.yaml
@@ -11,7 +11,7 @@ Global:
   print_batch_step: 10
   use_visualdl: False
   # used for static mode and model export
-  image_shape: [3, 224, 224]
+  image_shape: [3, 380, 380]
   save_inference_dir: ./inference
 
 # model architecture
@@ -110,9 +110,9 @@ Infer:
         to_rgb: True
         channel_first: False
     - ResizeImage:
-        resize_short: 256
+        resize_short: 412
     - CropImage:
-        size: 224
+        size: 380
     - NormalizeImage:
         scale: 1.0/255.0
         mean: [0.485, 0.456, 0.406]
diff --git a/ppcls/configs/ImageNet/EfficientNet/EfficientNetB5.yaml b/ppcls/configs/ImageNet/EfficientNet/EfficientNetB5.yaml
index 94656dc8312ccbede247c63466ec7f7c9fb6ab6c..286971d4452325b13fb92d470e4844799c7ba918 100644
--- a/ppcls/configs/ImageNet/EfficientNet/EfficientNetB5.yaml
+++ b/ppcls/configs/ImageNet/EfficientNet/EfficientNetB5.yaml
@@ -11,7 +11,7 @@ Global:
   print_batch_step: 10
   use_visualdl: False
   # used for static mode and model export
-  image_shape: [3, 224, 224]
+  image_shape: [3, 456, 456]
   save_inference_dir: ./inference
 
 # model architecture
@@ -110,9 +110,9 @@ Infer:
         to_rgb: True
         channel_first: False
     - ResizeImage:
-        resize_short: 256
+        resize_short: 448
     - CropImage:
-        size: 224
+        size: 456
     - NormalizeImage:
         scale: 1.0/255.0
         mean: [0.485, 0.456, 0.406]
diff --git a/ppcls/configs/ImageNet/EfficientNet/EfficientNetB6.yaml b/ppcls/configs/ImageNet/EfficientNet/EfficientNetB6.yaml
index 8da4f005f0ac3ef6024aae6fe82070fb381bab64..edaab55460eb5f6e05abecdefe57c6bd5d13c7ca 100644
--- a/ppcls/configs/ImageNet/EfficientNet/EfficientNetB6.yaml
+++ b/ppcls/configs/ImageNet/EfficientNet/EfficientNetB6.yaml
@@ -11,7 +11,7 @@ Global:
   print_batch_step: 10
   use_visualdl: False
   # used for static mode and model export
-  image_shape: [3, 224, 224]
+  image_shape: [3, 528, 528]
   save_inference_dir: ./inference
 
 # model architecture
@@ -110,9 +110,9 @@ Infer:
         to_rgb: True
         channel_first: False
     - ResizeImage:
-        resize_short: 256
+        resize_short: 560
     - CropImage:
-        size: 224
+        size: 528
     - NormalizeImage:
         scale: 1.0/255.0
         mean: [0.485, 0.456, 0.406]
diff --git a/ppcls/configs/ImageNet/EfficientNet/EfficientNetB7.yaml b/ppcls/configs/ImageNet/EfficientNet/EfficientNetB7.yaml
index 2470cff1898db4cd1416bb35f1bed7a16fe4f097..1ced43d1d3bf5c688f0362615c683633d3dc74d1 100644
--- a/ppcls/configs/ImageNet/EfficientNet/EfficientNetB7.yaml
+++ b/ppcls/configs/ImageNet/EfficientNet/EfficientNetB7.yaml
@@ -11,7 +11,7 @@ Global:
   print_batch_step: 10
   use_visualdl: False
   # used for static mode and model export
-  image_shape: [3, 224, 224]
+  image_shape: [3, 600, 600]
   save_inference_dir: ./inference
 
 # model architecture
@@ -110,9 +110,9 @@ Infer:
         to_rgb: True
         channel_first: False
     - ResizeImage:
-        resize_short: 256
+        resize_short: 632
     - CropImage:
-        size: 224
+        size: 600
     - NormalizeImage:
         scale: 1.0/255.0
         mean: [0.485, 0.456, 0.406]
diff --git a/ppcls/configs/ImageNet/ResNeSt/ResNeSt101.yaml b/ppcls/configs/ImageNet/ResNeSt/ResNeSt101.yaml
index 7b3bc2bdb6fb4c6d32a1d95d972407f9cf58f4c7..724b56df430181f62cc24f53266e708a8812a8bc 100644
--- a/ppcls/configs/ImageNet/ResNeSt/ResNeSt101.yaml
+++ b/ppcls/configs/ImageNet/ResNeSt/ResNeSt101.yaml
@@ -11,7 +11,7 @@ Global:
   print_batch_step: 10
   use_visualdl: False
   # used for static mode and model export
-  image_shape: [3, 224, 224]
+  image_shape: [3, 256, 256]
   save_inference_dir: ./inference
 
 # model architecture
@@ -53,7 +53,7 @@ DataLoader:
             to_rgb: True
             channel_first: False
         - RandCropImage:
-            size: 224
+            size: 256
         - RandFlipImage:
             flip_code: 1
         - AutoAugment:
@@ -85,9 +85,9 @@ DataLoader:
             to_rgb: True
             channel_first: False
         - ResizeImage:
-            resize_short: 256
+            resize_short: 288
         - CropImage:
-            size: 224
+            size: 256
         - NormalizeImage:
             scale: 1.0/255.0
             mean: [0.485, 0.456, 0.406]
@@ -110,9 +110,9 @@ Infer:
         to_rgb: True
         channel_first: False
     - ResizeImage:
-        resize_short: 256
+        resize_short: 288
     - CropImage:
-        size: 224
+        size: 256
     - NormalizeImage:
         scale: 1.0/255.0
         mean: [0.485, 0.456, 0.406]