pytorch

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#include <gtest/gtest.h>
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#include <test/cpp/api/support.h>
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#include <torch/torch.h>
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#include <string>
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#include <vector>
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using namespace at;
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using namespace torch::test;
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// A macro so we don't lose location information when an assertion fails.
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#define REQUIRE_OPTIONS(device_, index_, type_, layout_)                  \
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  ASSERT_EQ(options.device().type(), Device((device_), (index_)).type()); \
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  ASSERT_TRUE(                                                            \
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      options.device().index() == Device((device_), (index_)).index());   \
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  ASSERT_EQ(options.dtype(), (type_));                                    \
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  ASSERT_TRUE(options.layout() == (layout_))
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#define REQUIRE_TENSOR_OPTIONS(device_, index_, type_, layout_)            \
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  ASSERT_EQ(tensor.device().type(), Device((device_), (index_)).type());   \
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  ASSERT_EQ(tensor.device().index(), Device((device_), (index_)).index()); \
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  ASSERT_EQ(tensor.scalar_type(), (type_));                                \
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  ASSERT_TRUE(tensor.options().layout() == (layout_))
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TEST(TensorOptionsTest, DefaultsToTheRightValues) {
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  TensorOptions options;
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  REQUIRE_OPTIONS(kCPU, -1, kFloat, kStrided);
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}
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TEST(TensorOptionsTest, UtilityFunctionsReturnTheRightTensorOptions) {
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  auto options = dtype(kInt);
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  REQUIRE_OPTIONS(kCPU, -1, kInt, kStrided);
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  options = layout(kSparse);
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  REQUIRE_OPTIONS(kCPU, -1, kFloat, kSparse);
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  options = device({kCUDA, 1});
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  REQUIRE_OPTIONS(kCUDA, 1, kFloat, kStrided);
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  options = device_index(1);
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  REQUIRE_OPTIONS(kCUDA, 1, kFloat, kStrided);
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  options = dtype(kByte).layout(kSparse).device(kCUDA, 2).device_index(3);
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  REQUIRE_OPTIONS(kCUDA, 3, kByte, kSparse);
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}
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TEST(TensorOptionsTest, ConstructsWellFromCPUTypes) {
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  TensorOptions options;
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  REQUIRE_OPTIONS(kCPU, -1, kFloat, kStrided);
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  options = TensorOptions({kCPU, 0});
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  REQUIRE_OPTIONS(kCPU, 0, kFloat, kStrided);
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  options = TensorOptions("cpu:0");
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  REQUIRE_OPTIONS(kCPU, 0, kFloat, kStrided);
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  options = TensorOptions(kInt);
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  REQUIRE_OPTIONS(kCPU, -1, kInt, kStrided);
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  options =
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      TensorOptions(getDeprecatedTypeProperties(Backend::SparseCPU, kFloat));
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  REQUIRE_OPTIONS(kCPU, -1, kFloat, kSparse);
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  options =
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      TensorOptions(getDeprecatedTypeProperties(Backend::SparseCPU, kByte));
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  REQUIRE_OPTIONS(kCPU, -1, kByte, kSparse);
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}
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TEST(TensorOptionsTest, ConstructsWellFromCPUTensors) {
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  auto options = empty(5, kDouble).options();
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  REQUIRE_OPTIONS(kCPU, -1, kDouble, kStrided);
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  options = empty(5, getDeprecatedTypeProperties(Backend::SparseCPU, kByte))
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                .options();
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  REQUIRE_OPTIONS(kCPU, -1, kByte, kSparse);
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}
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TEST(TensorOptionsTest, ConstructsWellFromVariables) {
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  auto options = torch::empty(5).options();
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  REQUIRE_OPTIONS(kCPU, -1, kFloat, kStrided);
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  ASSERT_FALSE(options.requires_grad());
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  options = torch::empty(5, at::requires_grad()).options();
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  REQUIRE_OPTIONS(kCPU, -1, kFloat, kStrided);
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  ASSERT_FALSE(options.requires_grad());
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}
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TEST(DeviceTest, ParsesCorrectlyFromString) {
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  Device device("cpu:0");
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  ASSERT_EQ(device, Device(DeviceType::CPU, 0));
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  device = Device("cpu");
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  ASSERT_EQ(device, Device(DeviceType::CPU));
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  device = Device("cuda:123");
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  ASSERT_EQ(device, Device(DeviceType::CUDA, 123));
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  device = Device("cuda");
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  ASSERT_EQ(device, Device(DeviceType::CUDA));
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  device = Device("mkldnn");
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  ASSERT_EQ(device, Device(DeviceType::MKLDNN));
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  device = Device("opengl");
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  ASSERT_EQ(device, Device(DeviceType::OPENGL));
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  device = Device("opencl");
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  ASSERT_EQ(device, Device(DeviceType::OPENCL));
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  device = Device("ideep");
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  ASSERT_EQ(device, Device(DeviceType::IDEEP));
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  device = Device("hip");
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  ASSERT_EQ(device, Device(DeviceType::HIP));
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  device = Device("hip:123");
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  ASSERT_EQ(device, Device(DeviceType::HIP, 123));
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  std::vector<std::string> badnesses = {
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      "", "cud:1", "cuda:", "cpu::1", ":1", "3", "tpu:4", "??"};
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  for (const auto& badness : badnesses) {
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    // NOLINTNEXTLINE(cppcoreguidelines-avoid-goto,hicpp-avoid-goto)
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    ASSERT_ANY_THROW({ Device d(badness); });
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  }
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}
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TEST(DefaultDtypeTest, CanSetAndGetDefaultDtype) {
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  AutoDefaultDtypeMode dtype_mode(kFloat);
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  ASSERT_EQ(at::get_default_dtype(), kFloat);
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  set_default_dtype(caffe2::TypeMeta::Make<int>());
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  ASSERT_EQ(at::get_default_dtype(), kInt);
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}
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TEST(DefaultDtypeTest, NewTensorOptionsHasCorrectDefault) {
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  AutoDefaultDtypeMode dtype_mode(kFloat);
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  set_default_dtype(caffe2::TypeMeta::Make<int>());
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  ASSERT_EQ(at::get_default_dtype(), kInt);
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  TensorOptions options;
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  ASSERT_EQ(options.dtype(), kInt);
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}
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TEST(DefaultDtypeTest, NewTensorsHaveCorrectDefaultDtype) {
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  AutoDefaultDtypeMode dtype_mode(kFloat);
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  set_default_dtype(caffe2::TypeMeta::Make<int>());
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  {
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    auto tensor = torch::ones(5);
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    ASSERT_EQ(tensor.dtype(), kInt);
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  }
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  set_default_dtype(caffe2::TypeMeta::Make<double>());
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  {
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    auto tensor = torch::ones(5);
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    ASSERT_EQ(tensor.dtype(), kDouble);
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  }
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  {
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    auto tensor = torch::ones(5, kFloat);
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    ASSERT_EQ(tensor.dtype(), kFloat);
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  }
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}
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