From: A. Unique TensorFlower <gardener@tensorflow.org>
Date: Thu, 17 May 2018 18:13:00 +0000 (-0700)
Subject: Use integral power function rather than floating point version. The integral version... 
X-Git-Tag: upstream/v1.9.0_rc1~94^2^2~70
X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=9e2ce8f4c483e68309a60dc89739bb1b79b4a12e;p=platform%2Fupstream%2Ftensorflow.git

Use integral power function rather than floating point version. The integral version is faster.

PiperOrigin-RevId: 197021020
---

diff --git a/tensorflow/core/grappler/optimizers/memory_optimizer.cc b/tensorflow/core/grappler/optimizers/memory_optimizer.cc
index 7c6468b..1be5f8d 100644
--- a/tensorflow/core/grappler/optimizers/memory_optimizer.cc
+++ b/tensorflow/core/grappler/optimizers/memory_optimizer.cc
@@ -36,6 +36,7 @@ limitations under the License.
 #include "tensorflow/core/grappler/utils.h"
 #include "tensorflow/core/grappler/utils/topological_sort.h"
 #include "tensorflow/core/grappler/utils/traversal.h"
+#include "tensorflow/core/lib/math/math_util.h"
 #include "tensorflow/core/protobuf/rewriter_config.pb.h"
 
 namespace tensorflow {
@@ -1069,9 +1070,11 @@ static bool IdentifySwappingCandidates(
         // ensure that swapping the tensor back in won't recreate the memory
         // bottleneck. Last but not least, we want the tensor to have as few
         // remaining uses as possible.
-        mem_info.fitness = std::pow((earliest_use - peak_time).count(), 2);
-        mem_info.fitness /= std::pow(mem_info.uses_left.size(), 2);
-        mem_info.fitness += std::pow((allocation_time - peak_time).count(), 2);
+        mem_info.fitness =
+            MathUtil::IPow((earliest_use - peak_time).count(), 2);
+        mem_info.fitness /= MathUtil::IPow(mem_info.uses_left.size(), 2);
+        mem_info.fitness +=
+            MathUtil::IPow((allocation_time - peak_time).count(), 2);
         mem_info.fitness = -mem_info.fitness;
         mem_state.push_back(mem_info);
       }