mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-06 12:20:52 +01:00
a5df8ec841
* Created DefaultTensorOptions * Fix TensorOptions() call which was interpreted as function decl * Fix empty OptionsGuard * Make options_ and mutex_ in DefaultTensorOptions class static because of dynamic linker issues * Make DefaultOptions thread local
114 lines
3.5 KiB
C++
114 lines
3.5 KiB
C++
#include "catch.hpp"
|
|
|
|
#include <ATen/Context.h>
|
|
#include <ATen/DeviceGuard.h>
|
|
#include <ATen/Functions.h>
|
|
#include <ATen/OptionsGuard.h>
|
|
#include <ATen/TensorOptions.h>
|
|
|
|
using namespace at;
|
|
|
|
// A macro so we don't lose location information when an assertion fails.
|
|
#define REQUIRE_OPTIONS(device_, index_, type_, layout_) \
|
|
REQUIRE(options.device().type() == Device((device_), (index_)).type()); \
|
|
REQUIRE(options.device().index() == Device((device_), (index_)).index()); \
|
|
REQUIRE(options.dtype() == (type_)); \
|
|
REQUIRE(options.layout() == (layout_))
|
|
|
|
#define REQUIRE_TENSOR_OPTIONS(device_, index_, type_, layout_) \
|
|
REQUIRE(tensor.device().type() == Device((device_), (index_)).type()); \
|
|
REQUIRE(tensor.device().index() == Device((device_), (index_)).index()); \
|
|
REQUIRE(tensor.type().scalarType() == (type_)); \
|
|
REQUIRE(tensor.type().layout() == (layout_))
|
|
|
|
TEST_CASE("TensorOptions/ConstructsWellFromCUDATypes", "[cuda]") {
|
|
auto options = TensorOptions(CUDA(kFloat));
|
|
REQUIRE_OPTIONS(kCUDA, -1, kFloat, kStrided);
|
|
|
|
options = TensorOptions(CUDA(kInt));
|
|
REQUIRE_OPTIONS(kCUDA, -1, kInt, kStrided);
|
|
|
|
options = TensorOptions(getType(kSparseCUDA, kFloat));
|
|
REQUIRE_OPTIONS(kCUDA, -1, kFloat, kSparse);
|
|
|
|
options = TensorOptions(getType(kSparseCUDA, kByte));
|
|
REQUIRE_OPTIONS(kCUDA, -1, kByte, kSparse);
|
|
|
|
options = TensorOptions(CUDA(kFloat), /*device=*/5);
|
|
REQUIRE_OPTIONS(kCUDA, 5, kFloat, kStrided);
|
|
|
|
options = TensorOptions(getType(kSparseCUDA, kFloat), /*device=*/5);
|
|
REQUIRE_OPTIONS(kCUDA, 5, kFloat, kSparse);
|
|
}
|
|
|
|
TEST_CASE("TensorOptions/ConstructsWellFromCUDATensors", "[cuda]") {
|
|
auto options = TensorOptions(empty(5, device(kCUDA).dtype(kDouble)));
|
|
REQUIRE_OPTIONS(kCUDA, 0, kDouble, kStrided);
|
|
|
|
options = TensorOptions(empty(5, getType(kSparseCUDA, kByte)));
|
|
REQUIRE_OPTIONS(kCUDA, 0, kByte, kSparse);
|
|
|
|
if (at::globalContext().getNumGPUs() > 1) {
|
|
Tensor tensor;
|
|
{
|
|
DeviceGuard guard(1);
|
|
tensor = empty(5, device(kCUDA));
|
|
}
|
|
options = TensorOptions(tensor);
|
|
REQUIRE_OPTIONS(kCUDA, 1, kFloat, kStrided);
|
|
|
|
{
|
|
DeviceGuard guard(1);
|
|
tensor = empty(5, device(kCUDA).layout(kSparse));
|
|
}
|
|
options = TensorOptions(tensor);
|
|
REQUIRE_OPTIONS(kCUDA, 1, kFloat, kSparse);
|
|
}
|
|
}
|
|
|
|
TEST_CASE("OptionsGuardCUDA", "[cuda]") {
|
|
Tensor tensor;
|
|
{
|
|
OptionsGuard guard(device(kCUDA));
|
|
tensor = at::empty({10});
|
|
}
|
|
REQUIRE_TENSOR_OPTIONS(kCUDA, 0, kFloat, kStrided);
|
|
|
|
{
|
|
OptionsGuard guard(device({kCUDA, 1}));
|
|
tensor = at::empty({10});
|
|
}
|
|
REQUIRE_TENSOR_OPTIONS(kCUDA, 1, kFloat, kStrided);
|
|
|
|
{
|
|
OptionsGuard guard(device(kCUDA).dtype(kInt));
|
|
tensor = at::empty({10});
|
|
}
|
|
REQUIRE_TENSOR_OPTIONS(kCUDA, 0, kInt, kStrided);
|
|
}
|
|
|
|
TEST_CASE("DeviceGuardOptionsGuardInteraction", "[cuda]") {
|
|
Tensor tensor;
|
|
{
|
|
// Check that OptionsGuard respects any active device before construction.
|
|
DeviceGuard guard(1);
|
|
{
|
|
OptionsGuard guard(device(kCUDA));
|
|
tensor = at::empty({10});
|
|
REQUIRE_TENSOR_OPTIONS(kCUDA, 1, kFloat, kStrided);
|
|
{
|
|
// Check that OptionsGuard respects any active device after
|
|
// construction.
|
|
DeviceGuard guard(0);
|
|
tensor = at::empty({10});
|
|
REQUIRE_TENSOR_OPTIONS(kCUDA, 0, kFloat, kStrided);
|
|
{
|
|
OptionsGuard guard(device({kCUDA, 1}));
|
|
tensor = at::empty({10});
|
|
REQUIRE_TENSOR_OPTIONS(kCUDA, 1, kFloat, kStrided);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|