pytorch/test/cpp/api/dispatch.cpp
Michael Ranieri 3567b881a5 make sure dispatch test works on windows (#36729)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/36729

setenv not available on windows

Test Plan: CI green in ovrsource

Reviewed By: stepancheg

Differential Revision: D21067835

fbshipit-source-id: ddbc3285ef88f123dc6a200b661c48cfafc6bf00
2020-04-16 11:36:56 -07:00

65 lines
1.8 KiB
C++

#include <gtest/gtest.h>
#include <torch/torch.h>
#include <ATen/native/Pow.h>
#include <torch/types.h>
#include <torch/utils.h>
#include <test/cpp/api/support.h>
#include <iostream>
#include <vector>
#include <type_traits>
#include <cstdlib>
using namespace at;
using namespace torch::test;
struct DispatchTest : torch::test::SeedingFixture {};
TEST_F(DispatchTest, TestAVX2) {
const std::vector<int> ints {1, 2, 3, 4};
const std::vector<int> result {1, 4, 27, 256};
const auto vals_tensor = torch::tensor(ints);
const auto pows_tensor = torch::tensor(ints);
#ifdef _WIN32
_putenv("ATEN_CPU_CAPABILITY=avx2");
#else
setenv("ATEN_CPU_CAPABILITY", "avx2", 1);
#endif
const auto actual_pow_avx2 = vals_tensor.pow(pows_tensor);
for (int i = 0; i < 4; i++) {
ASSERT_EQ(result[i], actual_pow_avx2[i].item<int>());
}
}
TEST_F(DispatchTest, TestAVX) {
const std::vector<int> ints {1, 2, 3, 4};
const std::vector<int> result {1, 4, 27, 256};
const auto vals_tensor = torch::tensor(ints);
const auto pows_tensor = torch::tensor(ints);
#ifdef _WIN32
_putenv("ATEN_CPU_CAPABILITY=avx");
#else
setenv("ATEN_CPU_CAPABILITY", "avx", 1);
#endif
const auto actual_pow_avx = vals_tensor.pow(pows_tensor);
for (int i = 0; i < 4; i++) {
ASSERT_EQ(result[i], actual_pow_avx[i].item<int>());
}
}
TEST_F(DispatchTest, TestDefault) {
const std::vector<int> ints {1, 2, 3, 4};
const std::vector<int> result {1, 4, 27, 256};
const auto vals_tensor = torch::tensor(ints);
const auto pows_tensor = torch::tensor(ints);
#ifdef _WIN32
_putenv("ATEN_CPU_CAPABILITY=default");
#else
setenv("ATEN_CPU_CAPABILITY", "default", 1);
#endif
const auto actual_pow_default = vals_tensor.pow(pows_tensor);
for (int i = 0; i < 4; i++) {
ASSERT_EQ(result[i], actual_pow_default[i].item<int>());
}
}