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      1 /* Copyright 2015 The TensorFlow Authors. All Rights Reserved.
      2 
      3 Licensed under the Apache License, Version 2.0 (the "License");
      4 you may not use this file except in compliance with the License.
      5 You may obtain a copy of the License at
      6 
      7     http://www.apache.org/licenses/LICENSE-2.0
      8 
      9 Unless required by applicable law or agreed to in writing, software
     10 distributed under the License is distributed on an "AS IS" BASIS,
     11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
     12 See the License for the specific language governing permissions and
     13 limitations under the License.
     14 ==============================================================================*/
     15 
     16 #include <functional>
     17 #include <memory>
     18 #include <vector>
     19 
     20 #include "tensorflow/core/common_runtime/kernel_benchmark_testlib.h"
     21 #include "tensorflow/core/framework/allocator.h"
     22 #include "tensorflow/core/framework/fake_input.h"
     23 #include "tensorflow/core/framework/node_def_builder.h"
     24 #include "tensorflow/core/framework/op_kernel.h"
     25 #include "tensorflow/core/framework/tensor.h"
     26 #include "tensorflow/core/framework/types.h"
     27 #include "tensorflow/core/framework/types.pb.h"
     28 #include "tensorflow/core/graph/graph.h"
     29 #include "tensorflow/core/graph/node_builder.h"
     30 #include "tensorflow/core/graph/testlib.h"
     31 #include "tensorflow/core/kernels/ops_testutil.h"
     32 #include "tensorflow/core/kernels/ops_util.h"
     33 #include "tensorflow/core/lib/core/status_test_util.h"
     34 #include "tensorflow/core/lib/gtl/array_slice.h"
     35 #include "tensorflow/core/lib/random/simple_philox.h"
     36 #include "tensorflow/core/platform/test.h"
     37 #include "tensorflow/core/platform/test_benchmark.h"
     38 
     39 namespace tensorflow {
     40 
     41 namespace test {
     42 namespace graph {
     43 
     44 class Node* GatherNd(Graph* g, class Node* in0, class Node* in1) {
     45   class Node* ret;
     46   TF_CHECK_OK(NodeBuilder(g->NewName("n"), "GatherNd")
     47                   .Input(in0)
     48                   .Input(in1)
     49                   .Finalize(g, &ret));
     50   return ret;
     51 }
     52 
     53 }  // namespace graph
     54 }  // namespace test
     55 
     56 namespace {
     57 
     58 class GatherNdOpTest : public OpsTestBase {
     59  protected:
     60   void MakeOp(DataType index_type) {
     61     TF_ASSERT_OK(NodeDefBuilder("myop", "GatherNd")
     62                      .Input(FakeInput(DT_FLOAT))
     63                      .Input(FakeInput(index_type))
     64                      .Finalize(node_def()));
     65     TF_ASSERT_OK(InitOp());
     66   }
     67 };
     68 
     69 TEST_F(GatherNdOpTest, Simple) {
     70   MakeOp(DT_INT32);
     71 
     72   // Feed and run
     73   AddInputFromArray<float>(TensorShape({5}), {0, 1, 2, 8, 4});
     74   AddInputFromArray<int32>(TensorShape({2, 1}), {3, 4});
     75   TF_ASSERT_OK(RunOpKernel());
     76 
     77   // Check the output.
     78   Tensor expected(allocator(), DT_FLOAT, TensorShape({2}));
     79   test::FillValues<float>(&expected, {8, 4});
     80   test::ExpectTensorEqual<float>(expected, *GetOutput(0));
     81 }
     82 
     83 constexpr int kLookups = 2000;
     84 
     85 template <typename Index>
     86 static Graph* GatherNd(int dim) {
     87   Graph* g = new Graph(OpRegistry::Global());
     88   // Always use a 512MB buffer.
     89   // const int kRows = ((512 << 20) / sizeof(float)) / dim;
     90   Tensor params(DT_FLOAT, TensorShape({dim, 8, 16, 32}));
     91   params.flat<float>().setRandom();
     92 
     93   random::PhiloxRandom philox(301, 17);
     94   random::SimplePhilox rnd(&philox);
     95   Tensor indices(DataTypeToEnum<Index>::value, TensorShape({kLookups, 4}));
     96   auto indices_mat = indices.matrix<Index>();
     97   for (int i = 0; i < kLookups; i++) {
     98     indices_mat(i, 0) = rnd.Uniform(dim);
     99     indices_mat(i, 1) = rnd.Uniform(8);
    100     indices_mat(i, 2) = rnd.Uniform(16);
    101     indices_mat(i, 3) = rnd.Uniform(32);
    102   }
    103 
    104   test::graph::GatherNd(g, test::graph::Constant(g, params),
    105                         test::graph::Constant(g, indices));
    106   return g;
    107 }
    108 
    109 #define BM_GATHER_ND(DEVICE, INDEX)                                 \
    110   static void BM_##DEVICE##_gather_nd_##INDEX(int iters, int dim) { \
    111     const int64 tot = static_cast<int64>(iters) * kLookups * 4;     \
    112     testing::ItemsProcessed(tot);                                   \
    113     testing::BytesProcessed(tot * sizeof(float));                   \
    114     testing::UseRealTime();                                         \
    115     test::Benchmark(#DEVICE, GatherNd<INDEX>(dim)).Run(iters);      \
    116   }                                                                 \
    117   BENCHMARK(BM_##DEVICE##_gather_nd_##INDEX)                        \
    118       ->Arg(10)                                                     \
    119       ->Arg(100)                                                    \
    120       ->Arg(1000)                                                   \
    121       ->Arg(10000)
    122 
    123 BM_GATHER_ND(cpu, int32);
    124 BM_GATHER_ND(gpu, int32);
    125 BM_GATHER_ND(cpu, int64);
    126 BM_GATHER_ND(gpu, int64);
    127 
    128 }  // namespace
    129 }  // namespace tensorflow
    130