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