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/* Copyright 2015 Google Inc. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#include "tensorflow/core/public/tensor.h"
#include <gtest/gtest.h>
#include "tensorflow/core/common_runtime/kernel_benchmark_testlib.h"
#include "tensorflow/core/platform/test_benchmark.h"
namespace tensorflow {
// Creates a Graph which "reduce"s a 3D float tensor of "num" elements
// into a scalar.
static Graph* ToScalar(const string& reduce, int num) {
Graph* g = new Graph(OpRegistry::Global());
Tensor data(DT_FLOAT, TensorShape({64, 64, num / (64 * 64)}));
data.flat<float>().setRandom();
Tensor axes(DT_INT32, TensorShape({3}));
axes.flat<int32>()(0) = 0;
axes.flat<int32>()(1) = 1;
axes.flat<int32>()(2) = 2;
test::graph::Reduce(g, reduce, test::graph::Constant(g, data),
test::graph::Constant(g, axes));
return g;
}
// Creates a bench which reduces a 3D tensor with total "num" floats
// into a scalar on a "device". Runs the bench for "iters" times.
static void ReduceToScalar(int iters, const string& device,
const string& reduce, int num) {
testing::ItemsProcessed(static_cast<int64>(iters) * num);
testing::BytesProcessed(static_cast<int64>(iters) * num * sizeof(float));
test::Benchmark(device, ToScalar(reduce, num)).Run(iters);
}
static void BM_Sum3DToScalarCPU(int iters, int num) {
ReduceToScalar(iters, "cpu", "Sum", num);
}
BENCHMARK(BM_Sum3DToScalarCPU)->Range(1 << 13, 1 << 20);
static void BM_Max3DToScalarCPU(int iters, int num) {
ReduceToScalar(iters, "cpu", "Max", num);
}
BENCHMARK(BM_Max3DToScalarCPU)->Range(1 << 13, 1 << 20);
static void BM_Prod3DToScalarCPU(int iters, int num) {
ReduceToScalar(iters, "cpu", "Prod", num);
}
BENCHMARK(BM_Prod3DToScalarCPU)->Range(1 << 13, 1 << 20);
static void BM_Mean3DToScalarCPU(int iters, int num) {
ReduceToScalar(iters, "cpu", "Mean", num);
}
BENCHMARK(BM_Mean3DToScalarCPU)->Range(1 << 13, 1 << 20);
static void BM_Sum3DToScalarGPU(int iters, int num) {
ReduceToScalar(iters, "gpu", "Sum", num);
}
BENCHMARK(BM_Sum3DToScalarGPU)->Range(1 << 13, 1 << 20);
static void BM_Max3DToScalarGPU(int iters, int num) {
ReduceToScalar(iters, "gpu", "Max", num);
}
BENCHMARK(BM_Max3DToScalarGPU)->Range(1 << 13, 1 << 20);
static void BM_Prod3DToScalarGPU(int iters, int num) {
ReduceToScalar(iters, "gpu", "Prod", num);
}
BENCHMARK(BM_Prod3DToScalarGPU)->Range(1 << 13, 1 << 20);
// Once Mean is available on GPU, enable this.
// static void BM_Mean3DToScalarGPU(int iters, int num) {
// ReduceToScalar(iters, "gpu", "Mean", num);
// }
// BENCHMARK(BM_Mean3DToScalarGPU)->Range(1 << 13, 1 << 20);
} // end namespace tensorflow
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