Files
pytorch/test/cpp/api/tensor_options.cpp
Roy Li ab78449e8c Add ScalarType argument to Type::options() (#19270)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/19270
ghimport-source-id: a5ade6131f3260066c5750ea1fa9ed5c998bb791

Differential Revision: D14938707

Pulled By: li-roy

fbshipit-source-id: 018fb3f01706531a06515d6d861e5683a455a705
2019-04-21 21:16:07 -07:00

170 lines
5.2 KiB
C++

#include <gtest/gtest.h>
#include <torch/types.h>
#include <ATen/Context.h>
#include <ATen/Functions.h>
#include <c10/core/TensorOptions.h>
#include <string>
#include <vector>
using namespace at;
// 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.type().layout() == (layout_))
TEST(TensorOptionsTest, DefaultsToTheRightValues) {
TensorOptions options;
REQUIRE_OPTIONS(kCPU, -1, kFloat, kStrided);
}
TEST(TensorOptionsTest, ReturnsTheCorrectType) {
auto options = TensorOptions().device(kCPU).dtype(kInt).layout(kSparse);
ASSERT_TRUE(
at::getType(options) == getNonVariableType(Backend::SparseCPU, kInt));
}
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(getNonVariableDeprecatedTypeProperties(Backend::SparseCPU, kFloat));
REQUIRE_OPTIONS(kCPU, -1, kFloat, kSparse);
options = TensorOptions(getNonVariableDeprecatedTypeProperties(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, getNonVariableDeprecatedTypeProperties(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:321");
ASSERT_EQ(device, Device(DeviceType::HIP, 321));
std::vector<std::string> badnesses = {
"", "cud:1", "cuda:", "cpu::1", ":1", "3", "tpu:4", "??"};
for (const auto& badness : badnesses) {
ASSERT_ANY_THROW({ Device d(badness); });
}
}
struct DefaultDtypeTest : ::testing::Test {
DefaultDtypeTest() {
set_default_dtype(caffe2::TypeMeta::Make<float>());
}
~DefaultDtypeTest() override {
set_default_dtype(caffe2::TypeMeta::Make<float>());
}
};
TEST_F(DefaultDtypeTest, CanSetAndGetDefaultDtype) {
ASSERT_EQ(at::get_default_dtype(), kFloat);
set_default_dtype(caffe2::TypeMeta::Make<int>());
ASSERT_EQ(at::get_default_dtype(), kInt);
}
TEST_F(DefaultDtypeTest, NewTensorOptionsHasCorrectDefault) {
set_default_dtype(caffe2::TypeMeta::Make<int>());
ASSERT_EQ(at::get_default_dtype(), kInt);
TensorOptions options;
ASSERT_EQ(options.dtype(), kInt);
}
TEST_F(DefaultDtypeTest, NewTensorsHaveCorrectDefaultDtype) {
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);
}
}