mirror of
https://github.com/zebrajr/pytorch.git
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9fac0a5093
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/11096 To discourage willy-nilly use, and make it clearer that it is not a Variable Reviewed By: cpuhrsch Differential Revision: D9583699 fbshipit-source-id: 4fbde0c01ae3deb2c7ef8c125a9028f089b203ae
129 lines
4.1 KiB
C++
129 lines
4.1 KiB
C++
#include "catch.hpp"
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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/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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REQUIRE(options.device().type() == Device((device_), (index_)).type()); \
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REQUIRE(options.device().index() == Device((device_), (index_)).index()); \
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REQUIRE(options.dtype() == (type_)); \
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REQUIRE(options.layout() == (layout_))
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#define REQUIRE_TENSOR_OPTIONS(device_, index_, type_, layout_) \
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REQUIRE(tensor.device().type() == Device((device_), (index_)).type()); \
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REQUIRE(tensor.device().index() == Device((device_), (index_)).index()); \
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REQUIRE(tensor.type().scalarType() == (type_)); \
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REQUIRE(tensor.type().layout() == (layout_))
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TEST_CASE("TensorOptions/ConstructsWellFromCUDATypes", "[cuda]") {
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auto options = TensorOptions(CUDA(kFloat));
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REQUIRE_OPTIONS(kCUDA, -1, kFloat, kStrided);
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options = TensorOptions(CUDA(kInt));
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REQUIRE_OPTIONS(kCUDA, -1, kInt, kStrided);
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options = TensorOptions(getNonVariableType(Backend::SparseCUDA, kFloat));
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REQUIRE_OPTIONS(kCUDA, -1, kFloat, kSparse);
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options = TensorOptions(getNonVariableType(Backend::SparseCUDA, kByte));
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REQUIRE_OPTIONS(kCUDA, -1, kByte, kSparse);
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options = TensorOptions(CUDA(kFloat), /*device=*/5);
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REQUIRE_OPTIONS(kCUDA, 5, kFloat, kStrided);
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options = TensorOptions(getNonVariableType(Backend::SparseCUDA, kFloat), /*device=*/5);
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REQUIRE_OPTIONS(kCUDA, 5, kFloat, kSparse);
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}
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TEST_CASE("TensorOptions/ConstructsWellFromCUDATensors", "[multi-cuda]") {
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auto options = TensorOptions(empty(5, device(kCUDA).dtype(kDouble)));
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REQUIRE_OPTIONS(kCUDA, 0, kDouble, kStrided);
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options = TensorOptions(empty(5, getNonVariableType(Backend::SparseCUDA, kByte)));
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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 = TensorOptions(tensor);
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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 = TensorOptions(tensor);
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REQUIRE_OPTIONS(kCUDA, 1, kFloat, kSparse);
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}
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}
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TEST_CASE("OptionsGuardCUDA", "[multi-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_CASE("DeviceGuardOptionsGuardInteraction", "[multi-cuda]") {
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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_CASE("DeviceGuardIsMovable", "[cuda]") {
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DeviceGuard first(1);
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REQUIRE(first.original_index() == 0);
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REQUIRE(first.last_index() == 1);
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DeviceGuard second(std::move(first));
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REQUIRE(second.original_index() == 0);
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REQUIRE(second.last_index() == 1);
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REQUIRE(first.original_index() == -1);
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DeviceGuard third;
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third = std::move(second);
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REQUIRE(third.original_index() == 0);
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REQUIRE(third.last_index() == 1);
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REQUIRE(second.original_index() == -1);
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}
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