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+/* Copyright 2016 The TensorFlow Authors. 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 <string>
+
+#include "tensorflow/core/common_runtime/kernel_benchmark_testlib.h"
+#include "tensorflow/core/framework/allocator.h"
+#include "tensorflow/core/framework/fake_input.h"
+#include "tensorflow/core/framework/node_def_builder.h"
+#include "tensorflow/core/framework/op.h"
+#include "tensorflow/core/framework/op_kernel.h"
+#include "tensorflow/core/framework/tensor.h"
+#include "tensorflow/core/framework/tensor_shape.h"
+#include "tensorflow/core/framework/tensor_testutil.h"
+#include "tensorflow/core/framework/tensor_types.h"
+#include "tensorflow/core/framework/types.h"
+#include "tensorflow/core/framework/types.pb.h"
+#include "tensorflow/core/graph/graph.h"
+#include "tensorflow/core/graph/node_builder.h"
+#include "tensorflow/core/graph/testlib.h"
+#include "tensorflow/core/kernels/ops_testutil.h"
+#include "tensorflow/core/kernels/ops_util.h"
+#include "tensorflow/core/lib/core/status.h"
+#include "tensorflow/core/lib/core/status_test_util.h"
+#include "tensorflow/core/platform/macros.h"
+#include "tensorflow/core/platform/test.h"
+#include "tensorflow/core/platform/test_benchmark.h"
+#include "tensorflow/core/platform/types.h"
+
+namespace tensorflow {
+
+// Test data from the TensorFlow README.md.
+const char* lines[] = {
+ "**TensorFlow** is an open source software library for numerical "
+ "computation using data flow graphs.",
+ "The graph nodes represent mathematical operations, while the graph edges "
+ "represent the multidimensional data arrays (tensors) that flow between "
+ "them.",
+ "This flexible architecture enables you to deploy computation to one or "
+ "more CPUs or GPUs in a desktop, server, or mobile device without "
+ "rewriting code.",
+ "TensorFlow also includes "
+ "[TensorBoard](https://www.tensorflow.org/guide/"
+ "summaries_and_tensorboard), a data visualization toolkit.",
+ "TensorFlow was originally developed by researchers and engineers working "
+ "on the Google Brain team within Google's Machine Intelligence Research "
+ "organization for the purposes of conducting machine learning and deep "
+ "neural networks research.",
+ "The system is general enough to be applicable in a wide variety of other "
+ "domains, as well.",
+ "TensorFlow provides stable Python API and C APIs as well as without API "
+ "backwards compatibility guarantee like C++, Go, Java, JavaScript and "
+ "Swift."};
+
+Tensor GetTestTensor(int batch) {
+ const int sz = TF_ARRAYSIZE(lines);
+ Tensor t(DT_STRING, {batch});
+ auto s = t.flat<string>();
+ for (int i = 0; i < batch; ++i) {
+ s(i) = lines[i % sz];
+ }
+ return t;
+}
+
+Graph* SetupSubstrGraph(const Tensor& input, const int32 pos, const int32 len) {
+ Graph* g = new Graph(OpRegistry::Global());
+ Tensor position(DT_INT32, TensorShape({}));
+ position.flat<int32>().setConstant(pos);
+ Tensor length(DT_INT32, TensorShape({}));
+ length.flat<int32>().setConstant(len);
+
+ TF_CHECK_OK(NodeBuilder("substr_op", "Substr")
+ .Input(test::graph::Constant(g, input))
+ .Input(test::graph::Constant(g, position))
+ .Input(test::graph::Constant(g, length))
+ .Finalize(g, nullptr /* node */));
+ return g;
+}
+
+void BM_Substr(int iters, int batch_size) {
+ testing::StopTiming();
+ testing::ItemsProcessed(static_cast<int64>(iters));
+ testing::UseRealTime();
+ Tensor input = GetTestTensor(batch_size);
+ Graph* g = SetupSubstrGraph(input, 3, 30);
+ testing::StartTiming();
+ test::Benchmark("cpu", g).Run(iters);
+}
+
+BENCHMARK(BM_Substr)->Arg(1)->Arg(8)->Arg(16)->Arg(32)->Arg(64)->Arg(128)->Arg(
+ 256);
+
+} // end namespace tensorflow