1 files changed, 12 insertions, 16 deletions

diff --git a/tensorflow/compiler/xla/service/shape_inference.cc b/tensorflow/compiler/xla/service/shape_inference.cc
index 5e4df9ddd6..b332709995 100644
--- a/tensorflow/compiler/xla/service/shape_inference.cc
+++ b/tensorflow/compiler/xla/service/shape_inference.cc
@@ -1135,8 +1135,7 @@ ShapeInference::InferDegenerateDimensionBroadcastShape(
 
 /* static */ StatusOr<Shape> ShapeInference::InferSliceShape(
     const Shape& arg, tensorflow::gtl::ArraySlice<int64> starts,
-    tensorflow::gtl::ArraySlice<int64> limits,
-    tensorflow::gtl::ArraySlice<int64> strides) {
+    tensorflow::gtl::ArraySlice<int64> limits) {
   TF_RETURN_IF_ERROR(ExpectNotTupleOrOpaque(arg, "operand of slice"));
   VLOG(2) << tensorflow::strings::Printf(
       "slicing shape %s starts={%s} limits={%s}",
@@ -1159,13 +1158,13 @@ ShapeInference::InferDegenerateDimensionBroadcastShape(
   for (int64 dimension = 0; dimension < starts.size(); ++dimension) {
     int64 start_index = starts[dimension];
     int64 limit_index = limits[dimension];
-    int64 stride = strides[dimension];
     if (start_index < 0) {
       return InvalidArgument("negative start index to slice: %lld",
                              start_index);
     }
-    if (stride == 0) {
-      return InvalidArgument("Zero stride");
+    if (limit_index < 0) {
+      return InvalidArgument("negative limit index to slice: %lld",
+                             limit_index);
     }
     if (limit_index > arg.dimensions(dimension)) {
       return InvalidArgument(
@@ -1173,21 +1172,18 @@ ShapeInference::InferDegenerateDimensionBroadcastShape(
           "size (%lld)",
           limit_index, arg.dimensions(dimension));
     }
+    if (start_index > limit_index) {
+      return InvalidArgument(
+          "limit index (%lld) must be greater or equal to "
+          "start index (%lld) in slice",
+          limit_index, start_index);
+    }
     VLOG(2) << tensorflow::strings::Printf("starts[%lld] = %lld", dimension,
                                            start_index);
     VLOG(2) << tensorflow::strings::Printf("limits[%lld] = %lld", dimension,
                                            limit_index);
-    if (stride > 0) {
-      if (start_index > limit_index) {
-        return InvalidArgument(
-            "limit index (%lld) must be greater or equal to "
-            "start index (%lld) in slice with positive stride",
-            limit_index, start_index);
-      }
-      sizes.push_back((limit_index - start_index + stride - 1) / stride);
-    } else {
-      return InvalidArgument("Negative strides not supported");
-    }
+
+    sizes.push_back(limits[dimension] - starts[dimension]);
   }
 
   return ShapeUtil::MakeShape(arg.element_type(), sizes);