Increase test coverages by factorizing CNTK pads (#10259)

keras/backend/cntk_backend.py

@@ -2025,20 +2025,8 @@ def function(inputs, outputs, updates=[], **kwargs):
 def temporal_padding(x, padding=(1, 1)):
     assert len(padding) == 2
     num_dynamic_axis = _get_dynamic_axis_num(x)
-    base_shape = x.shape
-    if num_dynamic_axis > 0:
-        assert len(base_shape) == 2
-        if hasattr(C, 'pad'):
-            x = C.pad(x, pattern=[padding, (0, 0)])
-        else:
-            x = _padding(x, padding, 0)
-    else:
-        assert len(base_shape) == 3
-        if hasattr(C, 'pad'):
-            x = C.pad(x, pattern=[(0, 0), padding, (0, 0)])
-        else:
-            x = _padding(x, padding, 1)
-    return x
+    assert len(x.shape) == 3 - (1 if num_dynamic_axis > 0 else 0)
+    return pad(x, [padding], 'channels_last', num_dynamic_axis)
 
 
 def _padding(x, pattern, axis):
@@ -2062,6 +2050,24 @@ def _padding(x, pattern, axis):
     return x
 
 
+def pad(x, pad_info, data_format, num_dynamic_axis):
+    if hasattr(C, 'pad'):
+        pattern = [list(p) for p in pad_info]
+        if data_format == 'channels_first':
+            pattern = [[0, 0]] + pattern
+        else:
+            pattern = pattern + [[0, 0]]
+        if num_dynamic_axis == 0:
+            pattern = [[0, 0]] + pattern
+        return C.pad(x, pattern=pattern)
+    else:
+        for (a, p) in enumerate(pad_info):
+            x = _padding(x, p,
+                         a + (1 if num_dynamic_axis == 0 else 0) +
+                         (1 if data_format == 'channels_first' else 0))
+        return x
+
+
 def spatial_2d_padding(x, padding=((1, 1), (1, 1)), data_format=None):
     assert len(padding) == 2
     assert len(padding[0]) == 2
@@ -2072,38 +2078,8 @@ def spatial_2d_padding(x, padding=((1, 1), (1, 1)), data_format=None):
         raise ValueError('Unknown data_format ' + str(data_format))
 
     num_dynamic_axis = _get_dynamic_axis_num(x)
-    base_shape = x.shape
-    if data_format == 'channels_first':
-        if num_dynamic_axis > 0:
-            assert len(base_shape) == 3
-            if hasattr(C, 'pad'):
-                x = C.pad(x, pattern=[[0, 0], list(padding[0]), list(padding[1])])
-            else:
-                x = _padding(x, padding[0], 1)
-                x = _padding(x, padding[1], 2)
-        else:
-            assert len(base_shape) == 4
-            if hasattr(C, 'pad'):
-                x = C.pad(x, pattern=[[0, 0], [0, 0], list(padding[0]), list(padding[1])])
-            else:
-                x = _padding(x, padding[0], 2)
-                x = _padding(x, padding[1], 3)
-    else:
-        if num_dynamic_axis > 0:
-            assert len(base_shape) == 3
-            if hasattr(C, 'pad'):
-                x = C.pad(x, pattern=[list(padding[0]), list(padding[1]), [0, 0]])
-            else:
-                x = _padding(x, padding[0], 0)
-                x = _padding(x, padding[1], 1)
-        else:
-            assert len(base_shape) == 4
-            if hasattr(C, 'pad'):
-                x = C.pad(x, pattern=[[0, 0], list(padding[0]), list(padding[1]), [0, 0]])
-            else:
-                x = _padding(x, padding[0], 1)
-                x = _padding(x, padding[1], 2)
-    return x
+    assert len(x.shape) == 4 - (1 if num_dynamic_axis > 0 else 0)
+    return pad(x, padding, data_format, num_dynamic_axis)
 
 
 def spatial_3d_padding(x, padding=((1, 1), (1, 1), (1, 1)), data_format=None):
@@ -2117,42 +2093,8 @@ def spatial_3d_padding(x, padding=((1, 1), (1, 1), (1, 1)), data_format=None):
         raise ValueError('Unknown data_format ' + str(data_format))
 
     num_dynamic_axis = _get_dynamic_axis_num(x)
-    base_shape = x.shape
-    if data_format == 'channels_first':
-        if num_dynamic_axis > 0:
-            assert len(base_shape) == 4
-            if hasattr(C, 'pad'):
-                x = C.pad(x, pattern=[[0, 0], list(padding[0]), list(padding[1]), list(padding[2])])
-            else:
-                x = _padding(x, padding[0], 1)
-                x = _padding(x, padding[1], 2)
-                x = _padding(x, padding[2], 3)
-        else:
-            assert len(base_shape) == 5
-            if hasattr(C, 'pad'):
-                x = C.pad(x, pattern=[[0, 0], [0, 0], list(padding[0]), list(padding[1]), list(padding[2])])
-            else:
-                x = _padding(x, padding[0], 2)
-                x = _padding(x, padding[1], 3)
-                x = _padding(x, padding[2], 4)
-    else:
-        if num_dynamic_axis > 0:
-            assert len(base_shape) == 4
-            if hasattr(C, 'pad'):
-                x = C.pad(x, pattern=[list(padding[0]), list(padding[1]), list(padding[2]), [0, 0]])
-            else:
-                x = _padding(x, padding[0], 0)
-                x = _padding(x, padding[1], 1)
-                x = _padding(x, padding[2], 2)
-        else:
-            assert len(base_shape) == 5
-            if hasattr(C, 'pad'):
-                x = C.pad(x, pattern=[[0, 0], list(padding[0]), list(padding[1]), list(padding[2]), [0, 0]])
-            else:
-                x = _padding(x, padding[0], 1)
-                x = _padding(x, padding[1], 2)
-                x = _padding(x, padding[2], 3)
-    return x
+    assert len(x.shape) == 5 - (1 if num_dynamic_axis > 0 else 0)
+    return pad(x, padding, data_format, num_dynamic_axis)
 
 
 def one_hot(indices, num_classes):