Add some names to inception v3 model

inception_v3.py

@@ -125,7 +125,7 @@ def InceptionV3(include_top=True, weights='imagenet',
     x = conv2d_bn(x, 192, 3, 3, border_mode='valid')
     x = MaxPooling2D((3, 3), strides=(2, 2))(x)
 
-    # mixed: 35 x 35 x 256
+    # mixed 0, 1, 2: 35 x 35 x 256
     for i in range(3):
         branch1x1 = conv2d_bn(x, 64, 1, 1)
 
@@ -140,9 +140,10 @@ def InceptionV3(include_top=True, weights='imagenet',
             (3, 3), strides=(1, 1), border_mode='same')(x)
         branch_pool = conv2d_bn(branch_pool, 32, 1, 1)
         x = merge([branch1x1, branch5x5, branch3x3dbl, branch_pool],
-                  mode='concat', concat_axis=channel_axis)
+                  mode='concat', concat_axis=channel_axis,
+                  name='mixed' + str(i))
 
-    # mixed3: 17 x 17 x 768
+    # mixed 3: 17 x 17 x 768
     branch3x3 = conv2d_bn(x, 384, 3, 3, subsample=(2, 2), border_mode='valid')
 
     branch3x3dbl = conv2d_bn(x, 64, 1, 1)
@@ -152,9 +153,10 @@ def InceptionV3(include_top=True, weights='imagenet',
 
     branch_pool = MaxPooling2D((3, 3), strides=(2, 2))(x)
     x = merge([branch3x3, branch3x3dbl, branch_pool],
-              mode='concat', concat_axis=channel_axis)
+              mode='concat', concat_axis=channel_axis,
+              name='mixed3')
 
-    # mixed4: 17 x 17 x 768
+    # mixed 4: 17 x 17 x 768
     branch1x1 = conv2d_bn(x, 192, 1, 1)
 
     branch7x7 = conv2d_bn(x, 128, 1, 1)
@@ -170,10 +172,11 @@ def InceptionV3(include_top=True, weights='imagenet',
     branch_pool = AveragePooling2D((3, 3), strides=(1, 1), border_mode='same')(x)
     branch_pool = conv2d_bn(branch_pool, 192, 1, 1)
     x = merge([branch1x1, branch7x7, branch7x7dbl, branch_pool],
-              mode='concat', concat_axis=channel_axis)
+              mode='concat', concat_axis=channel_axis,
+              name='mixed4')
 
-    # mixed5: 17 x 17 x 768
-    for _ in range(2):
+    # mixed 5, 6: 17 x 17 x 768
+    for i in range(2):
         branch1x1 = conv2d_bn(x, 192, 1, 1)
 
         branch7x7 = conv2d_bn(x, 160, 1, 1)
@@ -190,9 +193,10 @@ def InceptionV3(include_top=True, weights='imagenet',
             (3, 3), strides=(1, 1), border_mode='same')(x)
         branch_pool = conv2d_bn(branch_pool, 192, 1, 1)
         x = merge([branch1x1, branch7x7, branch7x7dbl, branch_pool],
-                  mode='concat', concat_axis=channel_axis)
+                  mode='concat', concat_axis=channel_axis,
+                  name='mixed' + str(5 + i))
 
-    # mixed7: 17 x 17 x 768
+    # mixed 7: 17 x 17 x 768
     branch1x1 = conv2d_bn(x, 192, 1, 1)
 
     branch7x7 = conv2d_bn(x, 192, 1, 1)
@@ -208,9 +212,10 @@ def InceptionV3(include_top=True, weights='imagenet',
     branch_pool = AveragePooling2D((3, 3), strides=(1, 1), border_mode='same')(x)
     branch_pool = conv2d_bn(branch_pool, 192, 1, 1)
     x = merge([branch1x1, branch7x7, branch7x7dbl, branch_pool],
-              mode='concat', concat_axis=channel_axis)
+              mode='concat', concat_axis=channel_axis,
+              name='mixed7')
 
-    # mixed8: 8 x 8 x 1280
+    # mixed 8: 8 x 8 x 1280
     branch3x3 = conv2d_bn(x, 192, 1, 1)
     branch3x3 = conv2d_bn(branch3x3, 320, 3, 3,
                           subsample=(2, 2), border_mode='valid')
@@ -223,17 +228,19 @@ def InceptionV3(include_top=True, weights='imagenet',
 
     branch_pool = AveragePooling2D((3, 3), strides=(2, 2))(x)
     x = merge([branch3x3, branch7x7x3, branch_pool],
-              mode='concat', concat_axis=channel_axis)
+              mode='concat', concat_axis=channel_axis,
+              name='mixed8')
 
-    # mixed9: 8 x 8 x 2048
-    for _ in range(2):
+    # mixed 9: 8 x 8 x 2048
+    for i in range(2):
         branch1x1 = conv2d_bn(x, 320, 1, 1)
 
         branch3x3 = conv2d_bn(x, 384, 1, 1)
         branch3x3_1 = conv2d_bn(branch3x3, 384, 1, 3)
         branch3x3_2 = conv2d_bn(branch3x3, 384, 3, 1)
         branch3x3 = merge([branch3x3_1, branch3x3_2],
-                          mode='concat', concat_axis=channel_axis)
+                          mode='concat', concat_axis=channel_axis,
+                          name='mixed9_' + str(i))
 
         branch3x3dbl = conv2d_bn(x, 448, 1, 1)
         branch3x3dbl = conv2d_bn(branch3x3dbl, 384, 3, 3)
@@ -246,7 +253,8 @@ def InceptionV3(include_top=True, weights='imagenet',
             (3, 3), strides=(1, 1), border_mode='same')(x)
         branch_pool = conv2d_bn(branch_pool, 192, 1, 1)
         x = merge([branch1x1, branch3x3, branch3x3dbl, branch_pool],
-                  mode='concat', concat_axis=channel_axis)
+                  mode='concat', concat_axis=channel_axis,
+                  name='mixed' + str(9 + i))
 
     if include_top:
         # Classification block
@@ -259,7 +267,6 @@ def InceptionV3(include_top=True, weights='imagenet',
 
     # load weights
     if weights == 'imagenet':
-        print('K.image_dim_ordering:', K.image_dim_ordering())
         if K.image_dim_ordering() == 'th':
             if include_top:
                 weights_path = get_file('inception_v3_weights_th_dim_ordering_th_kernels.h5',