Merge changes from github.

Change: 134721831

1 files changed, 33 insertions, 15 deletions

diff --git a/tensorflow/python/ops/nn_ops.py b/tensorflow/python/ops/nn_ops.py
index 6486463b2c..b70cf83d91 100644
--- a/tensorflow/python/ops/nn_ops.py
+++ b/tensorflow/python/ops/nn_ops.py
@@ -1429,28 +1429,34 @@ ops.RegisterShape("AvgPool")(common_shapes.call_cpp_shape_fn)
 ops.RegisterShape("MaxPool")(common_shapes.call_cpp_shape_fn)
 
 
-@ops.RegisterShape("FusedResizeAndPadConv2D")
-def _FusedResizeAndPadConv2DShape(op):
-  """Shape function for FusedResizeAndPadConv2D op."""
+def _CommonFusedConvCalculations(op, has_resize):
+  """Shape function for Fused*Conv2D ops."""
   # The bilinear resize shape calculation.
   input_shape = op.inputs[0].get_shape().with_rank(4)
-  unused_size_shape = op.inputs[1].get_shape().merge_with([2])
-  size = tensor_util.constant_value(op.inputs[1])
-  if size is not None:
-    height = size[0]
-    width = size[1]
+  if has_resize:
+    unused_size_shape = op.inputs[1].get_shape().merge_with([2])
+    size = tensor_util.constant_value(op.inputs[1])
+    if size is not None:
+      height = size[0]
+      width = size[1]
+    else:
+      height = None
+      width = None
+    resized_shape = tensor_shape.TensorShape(
+        [input_shape[0], height, width, input_shape[3]])
+    paddings_index = 2
+    filter_index = 3
   else:
-    height = None
-    width = None
-  resized_shape = tensor_shape.TensorShape(
-      [input_shape[0], height, width, input_shape[3]])
+    resized_shape = input_shape
+    paddings_index = 1
+    filter_index = 2
 
   # Calculates the effect of the padding.
-  paddings_shape = op.inputs[2].get_shape().with_rank(2)
+  paddings_shape = op.inputs[paddings_index].get_shape().with_rank(2)
   resized_shape = resized_shape.with_rank(paddings_shape[0].value)
   paddings_shape = paddings_shape.merge_with(
       tensor_shape.matrix(resized_shape.ndims, 2))
-  paddings = tensor_util.constant_value(op.inputs[2])
+  paddings = tensor_util.constant_value(op.inputs[paddings_index])
   if paddings is None:
     padded_shape = tensor_shape.unknown_shape(ndims=resized_shape.ndims)
   else:
@@ -1462,7 +1468,7 @@ def _FusedResizeAndPadConv2DShape(op):
     padded_shape = tensor_shape.TensorShape(output_dims)
 
   # Finally work out the convolution's effect.
-  filter_shape = op.inputs[3].get_shape().with_rank(4)
+  filter_shape = op.inputs[filter_index].get_shape().with_rank(4)
 
   batch_size = padded_shape[0]
   in_rows = padded_shape[1]
@@ -1494,6 +1500,18 @@ def _FusedResizeAndPadConv2DShape(op):
   return [tensor_shape.TensorShape(output_shape)]
 
 
+@ops.RegisterShape("FusedResizeAndPadConv2D")
+def _FusedResizeAndPadConv2DShape(op):
+  """Shape function for FusedResizeAndPadConv2D op."""
+  return _CommonFusedConvCalculations(op, True)
+
+
+@ops.RegisterShape("FusedPadConv2D")
+def _FusedPadConv2DShape(op):
+  """Shape function for FusedResizeAndPadConv2D op."""
+  return _CommonFusedConvCalculations(op, False)
+
+
 ops.RegisterShape("MaxPoolWithArgmax")(common_shapes.call_cpp_shape_fn)