Function ConcatHelper

tensorflow/core/kernels/quantized_concat_op_test.cc:251–286

// quantized range; otherwise, they are set to different values.
template <typename T>
static void ConcatHelper(int iters, int concat_dimension, bool same_limits,
                         int dim2) {
  testing::StopTiming();
  Graph* g = new Graph(OpRegistry::Global());

  DataType dt = DataTypeToEnum<T>::v();
  const int kDim1 = 100;
  TensorShape shape({kDim1, dim2});

  Tensor concat_dim = test::AsScalar<int32>(concat_dimension);
  Tensor in0(dt, shape);
  in0.flat<T>().setRandom();
  Tensor in1(dt, shape);
  in1.flat<T>().setRandom();

  Tensor mins0 = test::AsScalar<float>(-1.0);
  Tensor maxes0 = test::AsScalar<float>(1.0);
  Tensor mins1 = test::AsScalar<float>(same_limits ? -1.0 : -255.0);
  Tensor maxes1 = test::AsScalar<float>(same_limits ? 1.0 : 255.0);

  Node* node;
  TF_CHECK_OK(NodeBuilder(g->NewName("n"), "QuantizedConcat")
                  .Input(Constant(g, concat_dim))
                  .Input({Constant(g, in0), Constant(g, in1)})
                  .Input({Constant(g, mins0), Constant(g, mins1)})
                  .Input({Constant(g, maxes0), Constant(g, maxes1)})
                  .Attr("N", 2)
                  .Attr("T", dt)
                  .Finalize(g, &node));

  testing::BytesProcessed(static_cast<int64>(iters) *
                          ((kDim1 * dim2) + (kDim1 * dim2)) * sizeof(T));
  testing::StartTiming();
  test::Benchmark("cpu", g).Run(iters);
  testing::UseRealTime();
}

static void BM_QConcatDim0SameLimitQInt32(int iters, int dim2) {
  ConcatHelper<qint32>(iters, 0 /* concat_dimension */, true /* same_limits */,