image_dim_ordering to image_data_format, Keras with Tensorflow backend, Tensorflow 2.1 compatible

Author: jiapei100

resnet_152.py

@@ -111,10 +111,10 @@ def resnet152_model(img_rows, img_cols, color_type=1, num_classes=None):
 
     # Handle Dimension Ordering for different backends
     global bn_axis
-    if K.image_dim_ordering() == 'tf':
+    if K.image_data_format() == 'channels_last':
       bn_axis = 3
       img_input = Input(shape=(img_rows, img_cols, color_type), name='data')
-    else:
+    else:	# Must be channels_first
       bn_axis = 1
       img_input = Input(shape=(color_type, img_rows, img_cols), name='data')
 
@@ -147,7 +147,7 @@ def resnet152_model(img_rows, img_cols, color_type=1, num_classes=None):
 
     model = Model(img_input, x_fc)
 
-    if K.image_dim_ordering() == 'th':
+    if K.image_data_format() == 'channels_first':
       # Use pre-trained weights for Theano backend
       weights_path = 'models/resnet152_weights_th.h5'
     else: