Benchmark crop and resize op.

PiperOrigin-RevId: 206829040

1 files changed, 72 insertions, 0 deletions

diff --git a/tensorflow/core/kernels/crop_and_resize_op_benchmark_test.cc b/tensorflow/core/kernels/crop_and_resize_op_benchmark_test.cc
new file mode 100644
index 0000000000..d7ca64bea0
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+++ b/tensorflow/core/kernels/crop_and_resize_op_benchmark_test.cc
@@ -0,0 +1,72 @@
+/* Copyright 2015 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 "tensorflow/core/common_runtime/kernel_benchmark_testlib.h"
+#include "tensorflow/core/framework/tensor.h"
+#include "tensorflow/core/graph/node_builder.h"
+#include "tensorflow/core/platform/test.h"
+#include "tensorflow/core/platform/test_benchmark.h"
+
+namespace tensorflow {
+
+static Graph* BM_CropAndResize(int batches, int width, int height, int depth,
+                               int crop_height, int crop_width) {
+  Graph* g = new Graph(OpRegistry::Global());
+  Tensor in(DT_FLOAT, TensorShape({batches, height, width, depth}));
+  in.flat<float>().setRandom();
+  Tensor boxes(DT_FLOAT, TensorShape({batches, 4}));
+  auto boxes_tensor = boxes.matrix<float>();
+  Tensor box_ind(DT_INT32, TensorShape({batches}));
+  auto box_ind_flat = box_ind.flat<int32>();
+  for (int i = 0; i < batches; ++i) {
+    boxes_tensor(i, 0) = 0.2;
+    boxes_tensor(i, 1) = 0.2;
+    boxes_tensor(i, 2) = 0.8;
+    boxes_tensor(i, 3) = 0.7;
+    box_ind_flat(i) = i;
+  }
+  Tensor crop_size(DT_INT32, TensorShape({2}));
+  auto crop_size_flat = crop_size.flat<int32>();
+  crop_size_flat(0) = crop_height;
+  crop_size_flat(1) = crop_width;
+  Node* ret;
+  TF_CHECK_OK(NodeBuilder(g->NewName("n"), "CropAndResize")
+                  .Input(test::graph::Constant(g, in))
+                  .Input(test::graph::Constant(g, boxes))
+                  .Input(test::graph::Constant(g, box_ind))
+                  .Input(test::graph::Constant(g, crop_size))
+                  .Finalize(g, &ret));
+  return g;
+}
+
+#define BM_CropAndResizeDev(DEVICE, B, W, H, D, CH, CW)                        \
+  static void BM_CropAndResize_##DEVICE##_##B##_##W##_##H##_##D##_##CH##_##CW( \
+      int iters) {                                                             \
+    testing::ItemsProcessed(iters* B* W* H* D);                                \
+    test::Benchmark(#DEVICE, BM_CropAndResize(B, W, H, D, CH, CW)).Run(iters); \
+  }                                                                            \
+  BENCHMARK(BM_CropAndResize_##DEVICE##_##B##_##W##_##H##_##D##_##CH##_##CW);
+
+// Benchmark results using CPU:Intel Haswell with HyperThreading (6 cores)
+// Benchmark                                Time(ns) CPU(ns)  Iterations
+// BM_CropAndResize_cpu_1_640_640_3_512_512 7078765 7173520 100 163.361M items/s
+// BM_CropAndResize_cpu_1_640_640_1_512_512 3801232 3914692 185  99.784M items/s
+// BM_CropAndResize_cpu_1_80_80_512_7_7      182470  241767 2941  1.372G items/s
+
+BM_CropAndResizeDev(cpu, 1, 640, 640, 3, 512, 512);
+BM_CropAndResizeDev(cpu, 1, 640, 640, 1, 512, 512);
+BM_CropAndResizeDev(cpu, 1, 80, 80, 512, 7, 7);
+
+}  // namespace tensorflow