Function TEST

tests/cpp/test_tensor.cc:52–92

}

TEST(Tensor, Basic) {
  Tensor nd = Empty({1, 2, 3}, DLDataType({kDLFloat, 32, 1}), DLDevice({kDLCPU, 0}));
  Shape shape = nd.shape();
  Shape strides = nd.strides();
  EXPECT_EQ(shape.size(), 3);
  EXPECT_EQ(shape[0], 1);
  EXPECT_EQ(shape[1], 2);
  EXPECT_EQ(shape[2], 3);
  EXPECT_EQ(strides.size(), 3);
  EXPECT_EQ(strides[0], 6);
  EXPECT_EQ(strides[1], 3);
  EXPECT_EQ(strides[2], 1);
  EXPECT_EQ(nd.dtype(), DLDataType({kDLFloat, 32, 1}));
  for (int64_t i = 0; i < shape.Product(); ++i) {
    reinterpret_cast<float*>(nd.data_ptr())[i] = static_cast<float>(i);
  }

  EXPECT_EQ(nd.numel(), 6);
  EXPECT_EQ(nd.ndim(), 3);
  EXPECT_EQ(nd.data_ptr(), nd.GetDLTensorPtr()->data);

  Any any0 = nd;
  Tensor nd2 = any0.as<Tensor>().value();  // NOLINT(bugprone-unchecked-optional-access)
  EXPECT_EQ(nd2.dtype(), DLDataType({kDLFloat, 32, 1}));
  for (int64_t i = 0; i < shape.Product(); ++i) {
    EXPECT_EQ(reinterpret_cast<float*>(nd2.data_ptr())[i], i);
  }

  EXPECT_EQ(nd.IsContiguous(), true);
  EXPECT_EQ(nd2.use_count(), 3);

  Tensor nd3 = EmptyStrided({2, 3}, {1, 2}, DLDataType({kDLFloat, 32, 1}), DLDevice({kDLCPU, 0}));
  Shape shape3 = nd3.shape();
  Shape strides3 = nd3.strides();
  EXPECT_EQ(shape3.size(), 2);
  EXPECT_EQ(shape3[0], 2);
  EXPECT_EQ(shape3[1], 3);
  EXPECT_EQ(strides3.size(), 2);
  EXPECT_EQ(strides3[0], 1);
  EXPECT_EQ(strides3[1], 2);
}

TEST(Tensor, EmptyTensorIsContiguous) {
  // An empty tensor (any shape dim == 0) is trivially contiguous regardless of