Remove potentially misleading warning messages in `applications`.

keras/applications/inception_resnet_v2.py

@@ -352,16 +352,6 @@ def InceptionResNetV2(include_top=True,
 
     # Load weights
     if weights == 'imagenet':
-        if K.image_data_format() == 'channels_first':
-            if K.backend() == 'tensorflow':
-                warnings.warn('You are using the TensorFlow backend, yet you '
-                              'are using the Theano '
-                              'image data format convention '
-                              '(`image_data_format="channels_first"`). '
-                              'For best performance, set '
-                              '`image_data_format="channels_last"` in '
-                              'your Keras config '
-                              'at ~/.keras/keras.json.')
         if include_top:
             fname = 'inception_resnet_v2_weights_tf_dim_ordering_tf_kernels.h5'
             weights_path = get_file(fname,

keras/applications/inception_v3.py

@@ -366,16 +366,6 @@ def InceptionV3(include_top=True,
 
     # load weights
     if weights == 'imagenet':
-        if K.image_data_format() == 'channels_first':
-            if K.backend() == 'tensorflow':
-                warnings.warn('You are using the TensorFlow backend, yet you '
-                              'are using the Theano '
-                              'image data format convention '
-                              '(`image_data_format="channels_first"`). '
-                              'For best performance, set '
-                              '`image_data_format="channels_last"` in '
-                              'your Keras config '
-                              'at ~/.keras/keras.json.')
         if include_top:
             weights_path = get_file(
                 'inception_v3_weights_tf_dim_ordering_tf_kernels.h5',

keras/applications/resnet50.py

@@ -273,17 +273,6 @@ def ResNet50(include_top=True, weights='imagenet',
         model.load_weights(weights_path)
         if K.backend() == 'theano':
             layer_utils.convert_all_kernels_in_model(model)
-
-        if (K.image_data_format() == 'channels_first' and
-                K.backend() == 'tensorflow'):
-            warnings.warn('You are using the TensorFlow backend, yet you '
-                          'are using the Theano '
-                          'image data format convention '
-                          '(`image_data_format="channels_first"`). '
-                          'For best performance, set '
-                          '`image_data_format="channels_last"` in '
-                          'your Keras config '
-                          'at `~/.keras/keras.json`.')
     elif weights is not None:
         model.load_weights(weights)
 

keras/applications/vgg16.py

@@ -178,17 +178,6 @@ def VGG16(include_top=True, weights='imagenet',
         model.load_weights(weights_path)
         if K.backend() == 'theano':
             layer_utils.convert_all_kernels_in_model(model)
-
-        if (K.image_data_format() == 'channels_first' and
-                K.backend() == 'tensorflow'):
-            warnings.warn('You are using the TensorFlow backend, yet you '
-                          'are using the Theano '
-                          'image data format convention '
-                          '(`image_data_format="channels_first"`). '
-                          'For best performance, set '
-                          '`image_data_format="channels_last"` in '
-                          'your Keras config '
-                          'at `~/.keras/keras.json`.')
     elif weights is not None:
         model.load_weights(weights)
 

keras/applications/vgg19.py

@@ -181,17 +181,6 @@ def VGG19(include_top=True, weights='imagenet',
         model.load_weights(weights_path)
         if K.backend() == 'theano':
             layer_utils.convert_all_kernels_in_model(model)
-
-        if (K.image_data_format() == 'channels_first' and
-                K.backend() == 'tensorflow'):
-            warnings.warn('You are using the TensorFlow backend, yet you '
-                          'are using the Theano '
-                          'image data format convention '
-                          '(`image_data_format="channels_first"`). '
-                          'For best performance, set '
-                          '`image_data_format="channels_last"` in '
-                          'your Keras config '
-                          'at `~/.keras/keras.json`.')
     elif weights is not None:
         model.load_weights(weights)