1 files changed, 4 insertions, 48 deletions

diff --git a/tensorflow/contrib/image/ops/image_ops.cc b/tensorflow/contrib/image/ops/image_ops.cc
index 4c6d8c0d19..68771b3d05 100644
--- a/tensorflow/contrib/image/ops/image_ops.cc
+++ b/tensorflow/contrib/image/ops/image_ops.cc
@@ -19,55 +19,9 @@ limitations under the License.
 
 namespace tensorflow {
 
-using shape_inference::DimensionHandle;
 using shape_inference::InferenceContext;
 using shape_inference::ShapeHandle;
 
-namespace {
-
-// Sets output[0] to shape [batch_dim,height,width,channel_dim], where
-// height and width come from the size_tensor.
-Status SetOutputToSizedImage(InferenceContext* c, DimensionHandle batch_dim,
-                             int size_input_idx, DimensionHandle channel_dim) {
-  // Verify shape of size input.
-  ShapeHandle size;
-  TF_RETURN_IF_ERROR(c->WithRank(c->input(size_input_idx), 1, &size));
-  DimensionHandle unused;
-  TF_RETURN_IF_ERROR(c->WithValue(c->Dim(size, 0), 2, &unused));
-
-  // Get size values from the size tensor.
-  const Tensor* size_tensor = c->input_tensor(size_input_idx);
-  DimensionHandle width;
-  DimensionHandle height;
-  if (size_tensor == nullptr) {
-    width = c->UnknownDim();
-    height = c->UnknownDim();
-  } else {
-    // TODO(petewarden) - Remove once we have constant evaluation in C++ only.
-    if (size_tensor->dtype() != DT_INT32) {
-      return errors::InvalidArgument(
-          "Bad size input type for SetOutputToSizedImage: Expected DT_INT32 "
-          "but got ",
-          DataTypeString(size_tensor->dtype()), " for input #", size_input_idx,
-          " in ", c->DebugString());
-    }
-    auto vec = size_tensor->vec<int32>();
-    height = c->MakeDim(vec(0));
-    width = c->MakeDim(vec(1));
-  }
-  c->set_output(0, c->MakeShape({batch_dim, height, width, channel_dim}));
-  return Status::OK();
-}
-
-Status ResizeShapeFn(InferenceContext* c) {
-  ShapeHandle input;
-  TF_RETURN_IF_ERROR(c->WithRank(c->input(0), 4, &input));
-  return SetOutputToSizedImage(c, c->Dim(input, 0), 2 /* size_input_idx */,
-                               c->Dim(input, 3));
-}
-
-}  // namespace
-
 // TODO(ringwalt): Add a "fill_mode" argument with "constant", "mirror", etc.
 // TODO(ringwalt): Add a "fill_constant" argument for constant mode (default 0).
 // TODO(ringwalt): Add an "output_shape" argument. This is sufficient to
@@ -75,11 +29,13 @@ Status ResizeShapeFn(InferenceContext* c) {
 REGISTER_OP("ImageProjectiveTransform")
     .Input("images: dtype")
     .Input("transforms: float32")
-    .Input("output_shape: int32")
     .Attr("dtype: {uint8, int32, int64, float32, float64}")
     .Attr("interpolation: string")
     .Output("transformed_images: dtype")
-    .SetShapeFn(ResizeShapeFn)
+    .SetShapeFn([](InferenceContext* c) {
+      c->set_output(0, c->input(0));
+      return Status::OK();
+    })
     .Doc(R"doc(
 Applies the given transform to each of the images.