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Add unittests for cuSub
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‎tests/gpu/CMakeLists.txt‎

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linalg_test/Abs_test.cpp
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linalg_test/Add_test.cpp
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linalg_test/Mul_test.cpp
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linalg_test/Sub_test.cpp
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linalg_test/Det_test.cpp
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linalg_test/Directsum_test.cpp
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linalg_test/ExpH_test.cpp

‎tests/gpu/linalg_test/Sub_test.cpp‎

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#include "gtest/gtest.h"
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#include "gpu_test_tools.h"
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#include "cytnx.hpp"
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namespace SubTest {
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::testing::AssertionResult CheckSubResult(const cytnx::Tensor& gpu_result,
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const cytnx::Tensor& left_tensor,
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const cytnx::Tensor& right_tensor);
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::testing::AssertionResult CheckSubScalarResult(const cytnx::Tensor& gpu_result,
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const cytnx::Tensor& tensor,
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const cytnx::cytnx_double& scalar,
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bool scalar_left = false);
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std::vector<std::vector<cytnx::cytnx_uint64>> GetTestShapes();
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cytnx::cytnx_double GetTolerance(const unsigned int& dtype);
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class SubTestAllShapes : public ::testing::TestWithParam<std::vector<cytnx::cytnx_uint64>> {};
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// Test tensor-to-tensor subtraction
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TEST_P(SubTestAllShapes, gpu_tensor_sub_tensor_all_types) {
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const std::vector<cytnx::cytnx_uint64>& shape = GetParam();
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for (auto dtype : cytnx::TestTools::dtype_list) {
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if (dtype == cytnx::Type.Bool) {
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continue;
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}
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SCOPED_TRACE("Testing Sub(tensor, tensor) with shape: " + ::testing::PrintToString(shape) +
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" and dtype: " + std::to_string(dtype));
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cytnx::Tensor gpu_tensor1 = cytnx::Tensor(shape, dtype).to(cytnx::Device.cuda);
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cytnx::Tensor gpu_tensor2 = cytnx::Tensor(shape, dtype).to(cytnx::Device.cuda);
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cytnx::TestTools::InitTensorUniform(gpu_tensor1);
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cytnx::TestTools::InitTensorUniform(gpu_tensor2);
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cytnx::Tensor gpu_result = cytnx::linalg::Sub(gpu_tensor1, gpu_tensor2);
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EXPECT_TRUE(CheckSubResult(gpu_result, gpu_tensor1, gpu_tensor2));
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cytnx::Tensor gpu_result_member = gpu_tensor1.Sub(gpu_tensor2);
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EXPECT_TRUE(CheckSubResult(gpu_result_member, gpu_tensor1, gpu_tensor2));
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cytnx::Tensor gpu_result_operator = gpu_tensor1 - gpu_tensor2;
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EXPECT_TRUE(CheckSubResult(gpu_result_operator, gpu_tensor1, gpu_tensor2));
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}
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}
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// Test scalar-to-tensor subtraction
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TEST_P(SubTestAllShapes, gpu_scalar_sub_tensor_all_types) {
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const std::vector<cytnx::cytnx_uint64>& shape = GetParam();
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for (auto dtype : cytnx::TestTools::dtype_list) {
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if (dtype == cytnx::Type.Bool) {
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continue;
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}
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SCOPED_TRACE("Testing Sub(scalar, tensor) with shape: " + ::testing::PrintToString(shape) +
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" and dtype: " + std::to_string(dtype));
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cytnx::Tensor gpu_tensor = cytnx::Tensor(shape, dtype).to(cytnx::Device.cuda);
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cytnx::TestTools::InitTensorUniform(gpu_tensor);
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cytnx::cytnx_double scalar = 2.3;
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cytnx::Tensor gpu_result = cytnx::linalg::Sub(scalar, gpu_tensor);
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EXPECT_TRUE(CheckSubScalarResult(gpu_result, gpu_tensor, scalar, true));
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cytnx::Tensor gpu_result_operator = scalar - gpu_tensor;
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EXPECT_TRUE(CheckSubScalarResult(gpu_result_operator, gpu_tensor, scalar, true));
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}
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}
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// Test tensor-to-scalar subtraction
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TEST_P(SubTestAllShapes, gpu_tensor_sub_scalar_all_types) {
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const std::vector<cytnx::cytnx_uint64>& shape = GetParam();
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for (auto dtype : cytnx::TestTools::dtype_list) {
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if (dtype == cytnx::Type.Bool) {
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continue;
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}
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SCOPED_TRACE("Testing Sub(tensor, scalar) with shape: " + ::testing::PrintToString(shape) +
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" and dtype: " + std::to_string(dtype));
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cytnx::Tensor gpu_tensor = cytnx::Tensor(shape, dtype).to(cytnx::Device.cuda);
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cytnx::TestTools::InitTensorUniform(gpu_tensor);
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cytnx::cytnx_double scalar = 2.3;
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cytnx::Tensor gpu_result = cytnx::linalg::Sub(gpu_tensor, scalar);
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EXPECT_TRUE(CheckSubScalarResult(gpu_result, gpu_tensor, scalar, false));
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cytnx::Tensor gpu_result_member = gpu_tensor.Sub(scalar);
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EXPECT_TRUE(CheckSubScalarResult(gpu_result_member, gpu_tensor, scalar, false));
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cytnx::Tensor gpu_result_operator = gpu_tensor - scalar;
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EXPECT_TRUE(CheckSubScalarResult(gpu_result_operator, gpu_tensor, scalar, false));
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}
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}
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// Test in-place tensor subtraction
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TEST_P(SubTestAllShapes, gpu_tensor_isub_all_types) {
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const std::vector<cytnx::cytnx_uint64>& shape = GetParam();
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for (auto dtype : cytnx::TestTools::dtype_list) {
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if (dtype == cytnx::Type.Bool) {
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continue;
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}
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SCOPED_TRACE("Testing iSub(tensor, tensor) with shape: " + ::testing::PrintToString(shape) +
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" and dtype: " + std::to_string(dtype));
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cytnx::Tensor gpu_tensor1 = cytnx::Tensor(shape, dtype).to(cytnx::Device.cuda);
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cytnx::Tensor gpu_tensor2 = cytnx::Tensor(shape, dtype).to(cytnx::Device.cuda);
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cytnx::TestTools::InitTensorUniform(gpu_tensor1);
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cytnx::TestTools::InitTensorUniform(gpu_tensor2);
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cytnx::Tensor original_gpu_tensor1 = gpu_tensor1.clone();
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cytnx::Tensor original_gpu_tensor2 = gpu_tensor2.clone();
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cytnx::linalg::iSub(gpu_tensor1, gpu_tensor2);
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EXPECT_TRUE(CheckSubResult(gpu_tensor1, original_gpu_tensor1, original_gpu_tensor2));
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cytnx::Tensor gpu_tensor1_op = original_gpu_tensor1.clone();
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gpu_tensor1_op -= original_gpu_tensor2;
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EXPECT_TRUE(CheckSubResult(gpu_tensor1_op, original_gpu_tensor1, original_gpu_tensor2));
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}
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}
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INSTANTIATE_TEST_SUITE_P(SubTests, SubTestAllShapes, ::testing::ValuesIn(GetTestShapes()));
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::testing::AssertionResult CheckSubResult(const cytnx::Tensor& gpu_result,
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const cytnx::Tensor& left_tensor,
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const cytnx::Tensor& right_tensor) {
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// Compare CUDA Sub result against CPU Sub result
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cytnx::Tensor left_cpu = left_tensor.to(cytnx::Device.cpu);
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cytnx::Tensor right_cpu = right_tensor.to(cytnx::Device.cpu);
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cytnx::Tensor expected_cpu = cytnx::linalg::Sub(left_cpu, right_cpu);
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cytnx::Tensor gpu_result_cpu = gpu_result.to(cytnx::Device.cpu);
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cytnx::cytnx_double tolerance = GetTolerance(gpu_result.dtype());
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if (!cytnx::TestTools::AreNearlyEqTensor(gpu_result_cpu, expected_cpu, tolerance)) {
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return ::testing::AssertionFailure()
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<< "Sub result mismatch: CUDA Sub result differs from CPU Sub result. "
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<< "Left dtype: " << left_tensor.dtype() << ", Right dtype: " << right_tensor.dtype()
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<< ", tolerance used: " << tolerance;
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}
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return ::testing::AssertionSuccess();
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}
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::testing::AssertionResult CheckSubScalarResult(const cytnx::Tensor& gpu_result,
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const cytnx::Tensor& tensor,
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const cytnx::cytnx_double& scalar,
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bool scalar_left) {
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// Compare CUDA Sub result against CPU Sub result
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cytnx::Tensor tensor_cpu = tensor.to(cytnx::Device.cpu);
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cytnx::Tensor expected_cpu;
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if (scalar_left) {
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expected_cpu = cytnx::linalg::Sub(scalar, tensor_cpu);
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} else {
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expected_cpu = cytnx::linalg::Sub(tensor_cpu, scalar);
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}
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cytnx::Tensor gpu_result_cpu = gpu_result.to(cytnx::Device.cpu);
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cytnx::cytnx_double tolerance = GetTolerance(gpu_result.dtype());
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if (!cytnx::TestTools::AreNearlyEqTensor(gpu_result_cpu, expected_cpu, tolerance)) {
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return ::testing::AssertionFailure()
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<< "Sub scalar result mismatch: CUDA Sub result differs from CPU Sub result. "
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<< "Tensor dtype: " << tensor.dtype() << ", scalar: " << scalar
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<< ", scalar_left: " << scalar_left << ", tolerance used: " << tolerance;
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}
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return ::testing::AssertionSuccess();
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}
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std::vector<std::vector<cytnx::cytnx_uint64>> GetTestShapes() {
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std::vector<std::vector<cytnx::cytnx_uint64>> all_shapes;
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auto shapes_1d = cytnx::TestTools::GenerateTestShapes(1, 1, 1024, 4);
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auto shapes_2d = cytnx::TestTools::GenerateTestShapes(2, 1, 512, 4);
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auto shapes_3d = cytnx::TestTools::GenerateTestShapes(3, 1, 64, 4);
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auto shapes_4d = cytnx::TestTools::GenerateTestShapes(4, 1, 32, 4);
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all_shapes.insert(all_shapes.end(), shapes_1d.begin(), shapes_1d.end());
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all_shapes.insert(all_shapes.end(), shapes_2d.begin(), shapes_2d.end());
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all_shapes.insert(all_shapes.end(), shapes_3d.begin(), shapes_3d.end());
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all_shapes.insert(all_shapes.end(), shapes_4d.begin(), shapes_4d.end());
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return all_shapes;
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}
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cytnx::cytnx_double GetTolerance(const unsigned int& dtype) {
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cytnx::cytnx_double tolerance = 1e-6;
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return tolerance;
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}
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} // namespace SubTest

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