/* Copyright 2015 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include <random>
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#include "tensorflow/core/common_runtime/kernel_benchmark_testlib.h"
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#include "tensorflow/core/framework/tensor.h"
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#include "tensorflow/core/platform/test.h"
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#include "tensorflow/core/platform/test_benchmark.h"
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namespace tensorflow {
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namespace {
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Tensor VecShape(int64 v) {
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if (v >= std::numeric_limits<int32>::max()) {
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Tensor shape(DT_INT64, TensorShape({1}));
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shape.vec<int64>()(0) = v;
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return shape;
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} else {
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Tensor shape(DT_INT32, TensorShape({1}));
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shape.vec<int32>()(0) = v;
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return shape;
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}
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}
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Tensor VecLam32(int64 n, int magnitude) {
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std::mt19937 gen(0x12345);
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std::uniform_real_distribution<float> dist(0.0, 1.0);
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Tensor lams(DT_FLOAT, TensorShape({n}));
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for (int i = 0; i < n; i++) {
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// Generate in range (magnitude, 2 * magnitude)
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lams.vec<float>()(i) = magnitude * (1 + dist(gen));
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}
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return lams;
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}
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Tensor VecLam64(int64 n, int magnitude) {
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std::mt19937 gen(0x12345);
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std::uniform_real_distribution<double> dist(0.0, 1.0);
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Tensor lams(DT_DOUBLE, TensorShape({n}));
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for (int i = 0; i < n; i++) {
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// Generate in range (magnitude, 2 * magnitude)
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lams.vec<double>()(i) = magnitude * (1 + dist(gen));
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}
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return lams;
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}
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#define BM_Poisson(DEVICE, BITS, MAGNITUDE) \
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static void BM_##DEVICE##_RandomPoisson_lam_##MAGNITUDE##_##BITS( \
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int iters, int nsamp, int nlam) { \
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testing::ItemsProcessed(static_cast<int64>(iters) * nsamp * nlam); \
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Graph* g = new Graph(OpRegistry::Global()); \
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test::graph::RandomPoisson( \
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g, test::graph::Constant(g, VecShape(nsamp)), \
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test::graph::Constant(g, VecLam##BITS(nlam, MAGNITUDE))); \
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test::Benchmark(#DEVICE, g).Run(iters); \
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} \
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BENCHMARK(BM_##DEVICE##_RandomPoisson_lam_##MAGNITUDE##_##BITS) \
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->RangePair(1, 64, 2, 50);
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BM_Poisson(cpu, 32, 1);
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BM_Poisson(cpu, 32, 8);
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BM_Poisson(cpu, 32, 32);
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BM_Poisson(cpu, 64, 1);
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BM_Poisson(cpu, 64, 8);
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BM_Poisson(cpu, 64, 32);
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} // namespace
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} // namespace tensorflow
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