Use the native Eigen round() method instead of std::function<float(float)>(round) which doesn't get vectorized and doesn't compile with gcc 6.2 (see #5419)

Change: 138575304

1 files changed, 3 insertions, 3 deletions

diff --git a/tensorflow/core/kernels/quantize_op.cc b/tensorflow/core/kernels/quantize_op.cc
index b8f0dd8642..2fdbe6ec8e 100644
--- a/tensorflow/core/kernels/quantize_op.cc
+++ b/tensorflow/core/kernels/quantize_op.cc
@@ -99,8 +99,8 @@ class QuantizeV2Op : public OpKernel {
       // Divide by (max_range - min_range) to get to [0, 1.0]
       // Multiply by range of T, after that shift left 1/2 range of T if
       // T is signed.
-      // Note that std::round is used to round the number before the cast.
-      // std::round implements "round-half-away-zero",
+      // Note that the number is rounded before the cast. Rounding follows the
+      // semantic of std::round, which implements "round-half-away-zero",
       // e.g., -5.5 gets rounded to -6, -5.4 goes to -5, 5.4 goes to 5,
       // and 5.5 goes to 6.
       auto o = output->template flat<T>();
@@ -113,7 +113,7 @@ class QuantizeV2Op : public OpKernel {
               min_range) *
                  scale_factor -
              half_range_)
-                .unaryExpr(std::function<float(float)>(round))
+                .round()
                 .template cast<T>();
       } else {
         // The fast path that avoids unaryExpr