Made indepent of backend. Now only checks channel priority

(as suggested by @arodiss)

keras_contrib/callbacks/dead_relu_detector.py

@@ -63,14 +63,12 @@ class DeadReluDetector(Callback):
             act_len = len(shape_act)
 
             # should work for both Conv and Flat
-            if K.backend() == 'tensorflow':
+            if K.image_data_format() == 'channels_last':
                 # features in last axis
                 axis_filter = -1
-            elif K.backend() == 'theano':
+            else:
                 # features before the convolution axis, for weight_len the input and output have to be subtracted
                 axis_filter = -1 - (weight_len - 2)
-            else:
-                raise ValueError('Unknown backend: {}'.format(K.backend()))
 
             total_featuremaps = shape_act[axis_filter]
 

tests/keras_contrib/callbacks/dead_relu_detector_test.py

@@ -96,12 +96,10 @@ def test_DeadDeadReluDetector_conv():
     n_samples = 9
 
     # (5, 5) kernel, 4 input featuremaps and 10 output featuremaps
-    if K.backend() == 'tensorflow':
+    if K.image_data_format() == 'channels_last':
         input_shape = (n_samples, 5, 5, 4)
-    elif K.backend() == 'theano':
-        input_shape = (n_samples, 4, 5, 5)
     else:
-        raise ValueError('Unknown backend: {}'.format(K.backend()))
+        input_shape = (n_samples, 4, 5, 5)
 
     # ignore batch size
     input_shape_conv = tuple(input_shape[1:])