New GraphDef version 4: TensorFlow is now scalar strict

The kAllowLegacyScalars flag is now gone.  Instead, scalar strictness now
depends on the GraphDef version: we are lenient below 4 and strict with 4
and above.  All new graphs should use version >= 4.

The internal Google version of tensorflow is now as scalar strict as the
open source release.  Note that outside of PLATFORM_GOOGLE, this change has no
effect, since the code was already scalar strict.
Change: 111467133

1 files changed, 2 insertions, 2 deletions

diff --git a/tensorflow/core/kernels/segment_reduction_ops.cc b/tensorflow/core/kernels/segment_reduction_ops.cc
index 7ddb7f474f..96cde639c1 100644
--- a/tensorflow/core/kernels/segment_reduction_ops.cc
+++ b/tensorflow/core/kernels/segment_reduction_ops.cc
@@ -184,7 +184,7 @@ class UnsortedSegmentSumOp : public OpKernel {
     const Tensor& num_segments = context->input(2);
 
     OP_REQUIRES(
-        context, TensorShapeUtils::IsLegacyScalar(num_segments.shape()),
+        context, IsLegacyScalar(num_segments.shape()),
         errors::InvalidArgument("num_segments should be a scalar, not shape ",
                                 num_segments.shape().ShortDebugString()));
 
@@ -406,7 +406,7 @@ class SparseSegmentMeanGradOp : public OpKernel {
                 errors::InvalidArgument("indices should be a vector."));
     OP_REQUIRES(context, TensorShapeUtils::IsVector(segment_ids.shape()),
                 errors::InvalidArgument("segment_ids should be a vector."));
-    OP_REQUIRES(context, TensorShapeUtils::IsLegacyScalar(output_dim0.shape()),
+    OP_REQUIRES(context, IsLegacyScalar(output_dim0.shape()),
                 errors::InvalidArgument("output_dim0 should be a scalar."));
 
     const int64 N = indices.NumElements();