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Created Tensor::to functions (#8643)

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* Created Tensor::to functions

* Only have to(dtype) and to(device)

* Ignore requires_grad in TensorOptions(Tensor) constructor
This commit is contained in:
Peter Goldsborough
2018-06-20 09:28:08 -07:00
committed by GitHub
parent d97c9dd019
commit 065fdbd500
5 changed files with 159 additions and 26 deletions
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92
test/cpp/api/tensor.cpp
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@ -1,23 +1,85 @@
#include <catch.hpp>
#include <torch/functions.h>
#include <ATen/ATen.h>
TEST_CASE("tensor/device-placement") {
SECTION("DeviceGuard") {
// SECTION("On index zero by default") {
// auto tensor = at::ones({3, 3}, at::kCUDA);
// REQUIRE(tensor.get_device() == 0);
// }
#define REQUIRE_TENSOR_OPTIONS(device_, index_, type_, layout_) \
REQUIRE(tensor.device().type() == at::Device((device_), (index_)).type()); \
REQUIRE(tensor.device().index() == at::Device((device_), (index_)).index()); \
REQUIRE(tensor.dtype() == (type_)); \
REQUIRE(tensor.layout() == (layout_))
// // right hand side is TensorOptions
// torch::OptionGuard guard = torch::device(torch::kCUDA, 1);
// // convenience wrapper over OptionGuard
// torch::DeviceGuard guard(torch::kCUDA, 1);
// /// default device is CUDA
// torch::DeviceGuard guard(1);
TEST_CASE("Tensor/ToDtype") {
auto tensor = at::empty({3, 4});
REQUIRE_TENSOR_OPTIONS(at::kCPU, -1, at::kFloat, at::kStrided);
// note that this is separate from DeviceGuard. DeviceGuard should move into the
// detail namespace and do the actual thing. OptionGuard just modifies a
// global singleton of option defaults. It operates at a higher level.
tensor = tensor.to(at::kInt);
REQUIRE_TENSOR_OPTIONS(at::kCPU, -1, at::kInt, at::kStrided);
tensor = tensor.to(at::kChar);
REQUIRE_TENSOR_OPTIONS(at::kCPU, -1, at::kChar, at::kStrided);
tensor = tensor.to(at::kDouble);
REQUIRE_TENSOR_OPTIONS(at::kCPU, -1, at::kDouble, at::kStrided);
}
// Not currently supported.
// TEST_CASE("Tensor/ToLayout") {
// auto tensor = at::empty({3, 4});
// REQUIRE_TENSOR_OPTIONS(at::kCPU, -1, at::kFloat, at::kStrided);
//
// tensor = tensor.to(at::kSparse);
// REQUIRE_TENSOR_OPTIONS(at::kCPU, -1, at::kFloat, at::kSparse);
//
// tensor = tensor.to(at::kStrided);
// REQUIRE_TENSOR_OPTIONS(at::kCPU, -1, at::kFloat, at::kStrided);
// }
TEST_CASE("Tensor/ToDevice", "[cuda]") {
auto tensor = at::empty({3, 4});
REQUIRE_TENSOR_OPTIONS(at::kCPU, -1, at::kFloat, at::kStrided);
tensor = tensor.to({at::kCUDA, 1});
REQUIRE_TENSOR_OPTIONS(at::kCUDA, 1, at::kFloat, at::kStrided);
tensor = tensor.to({at::kCUDA, 0});
REQUIRE_TENSOR_OPTIONS(at::kCUDA, 0, at::kFloat, at::kStrided);
tensor = tensor.to({at::kCUDA, 1});
REQUIRE_TENSOR_OPTIONS(at::kCUDA, 1, at::kFloat, at::kStrided);
tensor = tensor.to(at::Device(at::kCPU));
REQUIRE_TENSOR_OPTIONS(at::kCPU, -1, at::kFloat, at::kStrided);
}
TEST_CASE("Tensor/ToDeviceAndDtype", "[cuda]") {
auto tensor = at::empty({3, 4});
REQUIRE_TENSOR_OPTIONS(at::kCPU, -1, at::kFloat, at::kStrided);
tensor = tensor.to({at::kCUDA, 1}, at::kInt);
REQUIRE_TENSOR_OPTIONS(at::kCUDA, 1, at::kInt, at::kStrided);
}
TEST_CASE("Tensor/ToOptionsRespectsRequiresGrad") {
{
auto tensor = torch::empty({3, 4}, at::requires_grad());
REQUIRE(tensor.requires_grad());
tensor = tensor.to(at::kDouble);
REQUIRE(tensor.requires_grad());
}
{
auto tensor = torch::empty({3, 4});
REQUIRE(!tensor.requires_grad());
tensor = tensor.to(at::kDouble);
REQUIRE(!tensor.requires_grad());
}
}
TEST_CASE("Tensor/ToDoesNotCopyWhenOptionsAreAllTheSame") {
auto tensor = at::empty({3, 4}, at::kFloat);
auto hopefully_not_copy = tensor.to(at::kFloat);
REQUIRE(hopefully_not_copy.data<float>() == tensor.data<float>());
}