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