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https://github.com/pytorch/pytorch.git
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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
170 lines
5.2 KiB
C++
170 lines
5.2 KiB
C++
#include <gtest/gtest.h>
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#include <torch/types.h>
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#include <ATen/Context.h>
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#include <ATen/Functions.h>
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#include <c10/core/TensorOptions.h>
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#include <string>
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#include <vector>
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using namespace at;
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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.type().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, ReturnsTheCorrectType) {
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auto options = TensorOptions().device(kCPU).dtype(kInt).layout(kSparse);
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ASSERT_TRUE(
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at::getType(options) == getNonVariableType(Backend::SparseCPU, kInt));
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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 = TensorOptions(getNonVariableDeprecatedTypeProperties(Backend::SparseCPU, kFloat));
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REQUIRE_OPTIONS(kCPU, -1, kFloat, kSparse);
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options = TensorOptions(getNonVariableDeprecatedTypeProperties(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, getNonVariableDeprecatedTypeProperties(Backend::SparseCPU, kByte)).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:321");
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ASSERT_EQ(device, Device(DeviceType::HIP, 321));
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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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ASSERT_ANY_THROW({ Device d(badness); });
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}
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}
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struct DefaultDtypeTest : ::testing::Test {
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DefaultDtypeTest() {
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set_default_dtype(caffe2::TypeMeta::Make<float>());
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}
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~DefaultDtypeTest() override {
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set_default_dtype(caffe2::TypeMeta::Make<float>());
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}
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};
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TEST_F(DefaultDtypeTest, CanSetAndGetDefaultDtype) {
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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_F(DefaultDtypeTest, NewTensorOptionsHasCorrectDefault) {
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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_F(DefaultDtypeTest, NewTensorsHaveCorrectDefaultDtype) {
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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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