data parsing row major

contrib/Python/cntk/context.py

@@ -571,7 +571,7 @@ class LocalExecutionContext(AbstractContext):
                 continue
             else:
                 data = LocalExecutionContext._sanitized_asarray(
-                    data).reshape(shape, order='F')
+                    data).reshape(shape, order='C')
 
             tensor_seq.append(data)
 
@@ -755,12 +755,12 @@ class LocalExecutionContext(AbstractContext):
                         action_name = action_name)
 
         out_name = os.path.join(self.directory, CNTK_OUTPUT_FILENAME + '.')
+        node.tag = orig_node_tag
         if backward_pass:
-            n = input_name.name if isinstance(
-                input_name, ComputationNode) else input_name
+            n = input_name.name if isinstance(input_name, ComputationNode)\
+                    else input_name
             out_name += n + '.grad'
-        else:
-            node.tag = orig_node_tag
+        else:            
             out_name += node.name
 
         result_content = open(out_name).read()

contrib/Python/cntk/ops/__init__.py

@@ -959,8 +959,6 @@ def input_numpy(value, alias=None, dynamic_axis='', name=None):
         if len(cntk_shape) == 0:
             raise ValueError('value should be an array of input samples')
             
-        # cntk uses column major, thus we reverse the shape
-        cntk_shape = tuple(reversed(cntk_shape))
         node = input(cntk_shape, dynamic_axis=dynamic_axis, name=name)
         from ..reader import LazyInputReader
         node.reader = LazyInputReader(

contrib/Python/cntk/utils/__init__.py

@@ -38,7 +38,8 @@ def cntk_to_numpy_shape(shape):
     if not shape:
         shape = (1,)
 
-    return shape
+    # cntk uses column major, thus we reverse the axes
+    return tuple(reversed(shape))
 
 
 def aggregate_readers(readers):