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https://github.com/zebrajr/pytorch.git
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8797bb1d30
Differential Revision: D10419671 Original commit changeset: 9cc8c5982fde fbshipit-source-id: c870ecdd3730cf695007ebb110d362996da05e5d
131 lines
4.1 KiB
C++
131 lines
4.1 KiB
C++
#include <gtest/gtest.h>
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#include <ATen/Context.h>
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#include <ATen/DeviceGuard.h>
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#include <ATen/Functions.h>
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#include <ATen/OptionsGuard.h>
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#include <ATen/core/TensorOptions.h>
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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.type().scalarType(), (type_)); \
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ASSERT_TRUE(tensor.type().layout() == (layout_))
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TEST(TensorOptionsTest, ConstructsWellFromCUDATypes_CUDA) {
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auto options = CUDA(kFloat).options();
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REQUIRE_OPTIONS(kCUDA, -1, kFloat, kStrided);
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options = CUDA(kInt).options();
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REQUIRE_OPTIONS(kCUDA, -1, kInt, kStrided);
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options = getNonVariableType(Backend::SparseCUDA, kFloat).options();
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REQUIRE_OPTIONS(kCUDA, -1, kFloat, kSparse);
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options = getNonVariableType(Backend::SparseCUDA, kByte).options();
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REQUIRE_OPTIONS(kCUDA, -1, kByte, kSparse);
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options = CUDA(kFloat).options(/*device=*/5);
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REQUIRE_OPTIONS(kCUDA, 5, kFloat, kStrided);
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options =
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getNonVariableType(Backend::SparseCUDA, kFloat).options(/*device=*/5);
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REQUIRE_OPTIONS(kCUDA, 5, kFloat, kSparse);
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}
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TEST(TensorOptionsTest, ConstructsWellFromCUDATensors_MultiCUDA) {
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auto options = empty(5, device(kCUDA).dtype(kDouble)).options();
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REQUIRE_OPTIONS(kCUDA, 0, kDouble, kStrided);
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options = empty(5, getNonVariableType(Backend::SparseCUDA, kByte)).options();
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REQUIRE_OPTIONS(kCUDA, 0, kByte, kSparse);
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if (at::globalContext().getNumGPUs() > 1) {
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Tensor tensor;
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{
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DeviceGuard guard(1);
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tensor = empty(5, device(kCUDA));
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}
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options = tensor.options();
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REQUIRE_OPTIONS(kCUDA, 1, kFloat, kStrided);
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{
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DeviceGuard guard(1);
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tensor = empty(5, device(kCUDA).layout(kSparse));
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}
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options = tensor.options();
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REQUIRE_OPTIONS(kCUDA, 1, kFloat, kSparse);
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}
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}
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TEST(OptionsGuardTest, TestFunctionality_CUDA) {
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Tensor tensor;
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{
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OptionsGuard guard(device(kCUDA));
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tensor = at::empty({10});
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}
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REQUIRE_TENSOR_OPTIONS(kCUDA, 0, kFloat, kStrided);
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{
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OptionsGuard guard(device({kCUDA, 1}));
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tensor = at::empty({10});
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}
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REQUIRE_TENSOR_OPTIONS(kCUDA, 1, kFloat, kStrided);
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{
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OptionsGuard guard(device(kCUDA).dtype(kInt));
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tensor = at::empty({10});
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}
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REQUIRE_TENSOR_OPTIONS(kCUDA, 0, kInt, kStrided);
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}
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TEST(OptionsGuardTest, DeviceGuardOptionsGuardInteraction_MultiCUDA) {
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Tensor tensor;
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{
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// Check that OptionsGuard respects any active device before construction.
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DeviceGuard guard(1);
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{
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OptionsGuard guard(device(kCUDA));
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tensor = at::empty({10});
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REQUIRE_TENSOR_OPTIONS(kCUDA, 1, kFloat, kStrided);
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{
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// Check that OptionsGuard respects any active device after
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// construction.
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DeviceGuard guard(0);
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tensor = at::empty({10});
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REQUIRE_TENSOR_OPTIONS(kCUDA, 0, kFloat, kStrided);
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{
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OptionsGuard guard(device({kCUDA, 1}));
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tensor = at::empty({10});
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REQUIRE_TENSOR_OPTIONS(kCUDA, 1, kFloat, kStrided);
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}
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}
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}
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}
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}
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TEST(DeviceGuardTest, IsMovable_CUDA) {
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DeviceGuard first(1);
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ASSERT_EQ(first.original_index(), 0);
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ASSERT_EQ(first.last_index(), 1);
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DeviceGuard second(std::move(first));
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ASSERT_EQ(second.original_index(), 0);
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ASSERT_EQ(second.last_index(), 1);
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ASSERT_EQ(first.original_index(), -1);
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DeviceGuard third;
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third = std::move(second);
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ASSERT_EQ(third.original_index(), 0);
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ASSERT_EQ(third.last_index(), 1);
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ASSERT_EQ(second.original_index(), -1);
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}
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