/* Copyright 2016 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 "tensorflow/core/common_runtime/kernel_benchmark_testlib.h"
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#include "tensorflow/core/framework/allocator.h"
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#include "tensorflow/core/framework/fake_input.h"
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#include "tensorflow/core/framework/node_def_builder.h"
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#include "tensorflow/core/framework/op_kernel.h"
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#include "tensorflow/core/framework/tensor.h"
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#include "tensorflow/core/framework/tensor_testutil.h"
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#include "tensorflow/core/framework/types.h"
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#include "tensorflow/core/framework/types.pb.h"
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#include "tensorflow/core/graph/node_builder.h"
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#include "tensorflow/core/kernels/ops_testutil.h"
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#include "tensorflow/core/kernels/ops_util.h"
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#include "tensorflow/core/lib/core/status_test_util.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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// Test data from the TensorFlow README.md.
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const char* lines[] = {
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"**TensorFlow** is an open source software library for numerical "
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"computation using data flow graphs.",
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"The graph nodes represent mathematical operations, while the graph edges "
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"represent the multidimensional data arrays (tensors) that flow between "
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"them.",
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"This flexible architecture enables you to deploy computation to one or "
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"more CPUs or GPUs in a desktop, server, or mobile device without "
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"rewriting code.",
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"TensorFlow also includes "
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"[TensorBoard](https://www.tensorflow.org/guide/"
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"summaries_and_tensorboard), a data visualization toolkit.",
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"TensorFlow was originally developed by researchers and engineers working "
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"on the Google Brain team within Google's Machine Intelligence Research "
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"organization for the purposes of conducting machine learning and deep "
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"neural networks research.",
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"The system is general enough to be applicable in a wide variety of other "
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"domains, as well.",
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"TensorFlow provides stable Python API and C APIs as well as without API "
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"backwards compatibility guarantee like C++, Go, Java, JavaScript and "
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"Swift."};
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const char kRegExPattern[] = "\\p{P}";
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const char kRewrite[] = " ";
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Tensor GetTestTensor(int batch) {
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const int sz = TF_ARRAYSIZE(lines);
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Tensor t(DT_STRING, {batch});
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auto s = t.flat<string>();
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for (int i = 0; i < batch; ++i) {
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s(i) = lines[i % sz];
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}
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return t;
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}
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Graph* SetupRegexReplaceGraph(const Tensor& input, const string& input_pattern,
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const string& input_rewrite) {
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Graph* g = new Graph(OpRegistry::Global());
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Tensor pattern(DT_STRING, TensorShape({}));
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pattern.flat<string>().setConstant(input_pattern);
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Tensor rewrite(DT_STRING, TensorShape({}));
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rewrite.flat<string>().setConstant(input_rewrite);
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TF_CHECK_OK(NodeBuilder("regex_replace_op", "RegexReplace")
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.Input(test::graph::Constant(g, input))
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.Input(test::graph::Constant(g, pattern))
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.Input(test::graph::Constant(g, rewrite))
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.Attr("replace_global", true)
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.Finalize(g, nullptr /* node */));
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return g;
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}
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void BM_RegexReplace(int iters, int batch_size) {
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testing::StopTiming();
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testing::ItemsProcessed(static_cast<int64>(iters));
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testing::UseRealTime();
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Tensor input = GetTestTensor(batch_size);
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Graph* g = SetupRegexReplaceGraph(input, kRegExPattern, kRewrite);
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testing::StartTiming();
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test::Benchmark("cpu", g).Run(iters);
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}
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BENCHMARK(BM_RegexReplace)
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->Arg(1)
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->Arg(8)
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->Arg(16)
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->Arg(32)
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->Arg(64)
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->Arg(128)
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->Arg(256);
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Graph* SetupStaticGraph(const Tensor& input, const string& input_pattern,
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const string& rewrite) {
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Graph* g = new Graph(OpRegistry::Global());
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TF_CHECK_OK(NodeBuilder("static_regex_replace_op", "StaticRegexReplace")
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.Attr("pattern", input_pattern)
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.Attr("rewrite", rewrite)
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.Input(test::graph::Constant(g, input))
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.Attr("replace_global", true)
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.Finalize(g, nullptr /* node */));
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return g;
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}
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void BM_StaticRegexReplace(int iters, int batch_size) {
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testing::StopTiming();
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testing::ItemsProcessed(static_cast<int64>(iters));
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testing::UseRealTime();
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Tensor input = GetTestTensor(batch_size);
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Graph* g = SetupStaticGraph(input, kRegExPattern, kRewrite);
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testing::StartTiming();
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test::Benchmark("cpu", g).Run(iters);
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}
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BENCHMARK(BM_StaticRegexReplace)
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->Arg(1)
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->Arg(8)
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->Arg(16)
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->Arg(32)
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->Arg(64)
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->Arg(128)
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->Arg(256);
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} // end namespace tensorflow
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