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MaxPool & AvgPool bwd instances, test, ckProfiler, client example (#861)

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* Add maxpool instances

* Rename index pool to max pool.

* Add maxpool bwd bf16 instances

* Add avg pool bwd instances

* Rename avgpool and maxpool to avg_pool3d and max_pool

* Add bf16 pool fwd instances

* Add max pool bwd to ckProfiler

* Add avg pool3d bwd to ckProfiler

* Add avg pool bwd test

* Fix bug of reference pool fwd (dilation)

* Fix bug of max pool bwd  (dilation and initZero)

* Support bf16 compute data type

* Force compute type be f32. Because atomicAdd only support f32

* Add max pool bwd test

* Rename folder

* Rename pool

* Add max pool bwd client example

* Add avg pool bwd client example

* Add missing workspace

* clang format

* Rename macro

* remove useless header

* remove useless layout
This commit is contained in:
rocking
2023-08-31 21:01:50 +08:00
committed by GitHub
parent bf1912ed3d
commit 866377de18
45 changed files with 2174 additions and 40 deletions
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86
test/pool/test_max_pool3d_fwd.cpp Normal file
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// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
#include "gtest/gtest.h"
#include "profiler/profile_pool3d_fwd_impl.hpp"
#include "test_pool_fwd_common.hpp"
template <typename Tuple>
class TestMaxPool3dFwd : public ::testing::Test
{
protected:
using InDataType = std::tuple_element_t<0, Tuple>;
using OutDataType = std::tuple_element_t<1, Tuple>;
using ComputeDataType = std::tuple_element_t<2, Tuple>;
using IndexDataType = std::tuple_element_t<3, Tuple>;
std::vector<PoolingParam> params;
void Run()
{
for(auto param : params)
{
// max pool
bool success =
ck::profiler::profile_pool3d_fwd_impl<InDataType,
OutDataType,
ComputeDataType,
IndexDataType,
ck::tensor_layout::convolution::NDHWC,
ck::tensor_layout::convolution::NDHWC,
ck::ReduceTensorOp::MAX,
false,
false>(true,
2,
false,
false,
param.length_,
param.window_spatial_lengths_,
param.window_strides_,
param.window_dilations_,
param.input_left_pads_,
param.input_right_pads_);
EXPECT_TRUE(success);
// max pool + index
success = ck::profiler::profile_pool3d_fwd_impl<InDataType,
OutDataType,
ComputeDataType,
IndexDataType,
ck::tensor_layout::convolution::NDHWC,
ck::tensor_layout::convolution::NDHWC,
ck::ReduceTensorOp::MAX,
false,
true>(true,
2,
false,
false,
param.length_,
param.window_spatial_lengths_,
param.window_strides_,
param.window_dilations_,
param.input_left_pads_,
param.input_right_pads_);
EXPECT_TRUE(success);
}
}
};
#ifdef CK_ENABLE_FP16
using KernelTypes =
::testing::Types<std::tuple<F16, F16, F32, I32>, std::tuple<F32, F32, F32, I32>>;
#else
using KernelTypes = ::testing::Types<std::tuple<F32, F32, F32, I32>>;
#endif
TYPED_TEST_SUITE(TestMaxPool3dFwd, KernelTypes);
TYPED_TEST(TestMaxPool3dFwd, Test_Pool)
{
// length, window_length, window_stride, window_dilation, left_pad, right_pad
this->params = {{{1, 1, 1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}},
{{2, 16, 64, 64, 64}, {64, 64, 64}, {1, 1, 1}, {1, 1, 1}, {0, 0, 0}, {0, 0, 0}},
{{2, 16, 64, 64, 64}, {4, 4, 4}, {4, 4, 4}, {2, 2, 2}, {0, 0, 0}, {0, 0, 0}},
{{2, 32, 30, 30, 30}, {2, 2, 2}, {2, 2, 2}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}}};
this->Run();
}