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https://github.com/ROCm/composable_kernel.git
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76ec0089fb
* Expand the base class of pool2d, prepare to share base class with pool3d * Add pool3d device op * Add pool3d f16 example * Refactor the base class. implement generic pooling in the future * clang format * get original index in max pooling * Add outputindex to base class * Fix dimension * Add pooling instance * Use indexType instead * Remove useless header * Extract IndexDataType to template * Extract pooling reference code * clang format * clang format * Fix typo * Add tensor stride * Add missing header * Add index stride and output stride * Refine naming * Add type to base class * Rename file * Use proper size * Fix typo * Refine naming * Modify the argument into vector. * Add max pool profiler * Refine naming * Support f32 pool * Fix typo * Add avg pool2d fwd in profiler * clang format * Rename AccDatatype to ComputeDatatype * Fix init * test pool * Extract variable * Add client example * Check the pooling dim * clang format * Connect argv and arg_parser * Add found check * Remove useless header * Refine naming * Adjust the order of device_pool_fwd
76 lines
3.5 KiB
C++
76 lines
3.5 KiB
C++
// SPDX-License-Identifier: MIT
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// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
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#include "gtest/gtest.h"
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#include "profiler/profile_pool2d_fwd_impl.hpp"
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#include "test_pool_fwd_common.hpp"
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template <typename Tuple>
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class TestMaxPool2dFwd : public ::testing::Test
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{
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protected:
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using InDataType = std::tuple_element_t<0, Tuple>;
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using OutDataType = std::tuple_element_t<1, Tuple>;
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using ComputeDataType = std::tuple_element_t<2, Tuple>;
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using IndexDataType = std::tuple_element_t<3, Tuple>;
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std::vector<PoolingParam> params;
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void Run()
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{
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for(auto param : params)
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{
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// max pool
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bool success =
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ck::profiler::profile_pool2d_fwd_impl<InDataType,
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OutDataType,
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ComputeDataType,
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IndexDataType,
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ck::ReduceTensorOp::MAX,
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false,
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false>(true,
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2,
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false,
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false,
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param.length_,
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param.window_spatial_lengths_,
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param.window_strides_,
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param.input_left_pads_,
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param.input_right_pads_);
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EXPECT_TRUE(success);
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// max pool + index
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success = ck::profiler::profile_pool2d_fwd_impl<InDataType,
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OutDataType,
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ComputeDataType,
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IndexDataType,
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ck::ReduceTensorOp::MAX,
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false,
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true>(true,
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2,
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false,
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false,
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param.length_,
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param.window_spatial_lengths_,
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param.window_strides_,
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param.input_left_pads_,
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param.input_right_pads_);
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EXPECT_TRUE(success);
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}
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}
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};
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using KernelTypes =
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::testing::Types<std::tuple<F16, F16, F16, I32>, std::tuple<F32, F32, F32, I32>>;
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TYPED_TEST_SUITE(TestMaxPool2dFwd, KernelTypes);
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TYPED_TEST(TestMaxPool2dFwd, Test_Pool)
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{
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// length, window_length, window_stride, left_pad, right_pad
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this->params = {{{1, 1, 1, 1}, {1, 1}, {1, 1}, {0, 0}, {0, 0}},
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{{2, 16, 64, 64}, {64, 64}, {1, 1}, {0, 0}, {0, 0}},
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{{2, 32, 30, 30}, {2, 2}, {2, 2}, {1, 1}, {1, 1}}};
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this->Run();
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}
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