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TheRock/rocm-libraries/projects/miopen/test/gtest/unit_SeqTensorDescriptor.cpp
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Flatten subprojects into a single base monorepo
2026-09-02 16:34:47 -07:00

104 lines
3.6 KiB
C++

/*******************************************************************************
*
* MIT License
*
* Copyright (c) 2025 Advanced Micro Devices, Inc.
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*
*******************************************************************************/
#include <gtest/gtest.h>
#include <miopen/logger.hpp>
#include <miopen/seq_tensor.hpp>
namespace {
struct SeqTensorDescriptorParams
{
SeqTensorDescriptorParams(miopenDataType_t datatype_in, std::vector<size_t>&& lens_in)
: datatype(datatype_in), lens(std::move(lens_in))
{
}
SeqTensorDescriptorParams(miopenDataType_t datatype_in,
std::vector<size_t>&& lens_in,
bool with_padded_seq_layout)
: datatype(datatype_in), lens(std::move(lens_in)), padded_seq_layout(with_padded_seq_layout)
{
}
miopen::SeqTensorDescriptor GetSeqTensorDescriptor() const
{
std::vector<unsigned int> layout_default(lens.size());
std::iota(layout_default.begin(), layout_default.end(), 0);
return {datatype, layout_default, lens, padded_seq_layout};
}
private:
miopenDataType_t datatype;
std::vector<size_t> lens;
bool padded_seq_layout;
};
struct TestCase
{
SeqTensorDescriptorParams tp;
size_t max_sequence_length;
size_t total_sequence_length;
size_t actual_count_of_sequence;
};
auto GetTestCases()
{
return std::vector{
// clang-format off
TestCase{{miopenHalf, {2, 2, 2}}, 2, 4, 2},
TestCase{{miopenHalf, {2, 2, 2}, true}, 2, 4, 2},
TestCase{{miopenHalf, {2, 2, 2, 2}}, 2, 4, 2},
TestCase{{miopenHalf, {2, 2, 2, 2}, true}, 2, 4, 2},
TestCase{{miopenHalf, {2, 8, 2, 2}}, 8, 16, 2},
TestCase{{miopenHalf, {2, 8, 2, 2}, true}, 8, 16, 2},
TestCase{{miopenHalf, {2, 16, 8, 2, 2}}, 16, 32, 2},
TestCase{{miopenHalf, {2, 16, 8, 2, 2}, true}, 16, 32, 2},
// clang-format on
};
}
struct TestTensorSequence : testing::TestWithParam<TestCase>
{
void RunTest()
{
const auto p = GetParam();
const auto td = p.tp.GetSeqTensorDescriptor();
ASSERT_EQ(td.GetTotalSequenceLen(), p.total_sequence_length);
ASSERT_EQ(td.GetMaxSequenceLength(), p.max_sequence_length);
ASSERT_EQ(td.GetMaxCountOfSequences(), p.actual_count_of_sequence);
}
};
using CPU_TestTensorSequence_FP16 = TestTensorSequence;
} // anonymous namespace
TEST_P(CPU_TestTensorSequence_FP16, SeqTensorDescriptor) { RunTest(); };
INSTANTIATE_TEST_SUITE_P(Full, CPU_TestTensorSequence_FP16, testing::ValuesIn(GetTestCases()));