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author | Dana Zlotnik <dana.zlotnik@arm.com> | 2022-01-26 12:38:03 +0200 |
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committer | Dana Zlotnik <dana.zlotnik@arm.com> | 2022-02-14 12:50:03 +0000 |
commit | 149203bc23d5c84fe1326d9dea4730750fab6710 (patch) | |
tree | 5e3450a5a4e5ed8421fe45688b2cfdeef9b2ef59 /src/cpu/kernels/CpuMaxUnpoolingLayerKernel.cpp | |
parent | 6a2df886f32dcf7af4258163b0652f0fab07ecc5 (diff) | |
download | ComputeLibrary-149203bc23d5c84fe1326d9dea4730750fab6710.tar.gz |
Port MaxUnpoolingLayer kernel and add KernelSelect vaidation test
Resolves COMPMID-4958
Change-Id: Ibed5155f2e3ece46635f6ea9617bf11cefc402b1
Signed-off-by: Dana Zlotnik <dana.zlotnik@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7028
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/cpu/kernels/CpuMaxUnpoolingLayerKernel.cpp')
-rw-r--r-- | src/cpu/kernels/CpuMaxUnpoolingLayerKernel.cpp | 148 |
1 files changed, 148 insertions, 0 deletions
diff --git a/src/cpu/kernels/CpuMaxUnpoolingLayerKernel.cpp b/src/cpu/kernels/CpuMaxUnpoolingLayerKernel.cpp new file mode 100644 index 0000000000..604f22f6cc --- /dev/null +++ b/src/cpu/kernels/CpuMaxUnpoolingLayerKernel.cpp @@ -0,0 +1,148 @@ +/* + * Copyright (c) 2020-2022 Arm Limited. + * + * SPDX-License-Identifier: MIT + * + * 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 "src/cpu/kernels/CpuMaxUnpoolingLayerKernel.h" + +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/Validate.h" +#include "arm_compute/core/Window.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" +#include "src/core/CPP/Validate.h" +#include "src/core/common/Registrars.h" +#include "src/core/helpers/AutoConfiguration.h" +#include "src/core/helpers/WindowHelpers.h" +#include "src/cpu/kernels/maxunpool/list.h" +#include "support/ToolchainSupport.h" + +namespace arm_compute +{ +namespace cpu +{ +namespace kernels +{ +using namespace misc::shape_calculator; + +namespace +{ +static const std::vector<CpuMaxUnpoolingLayerKernel::MaxUnpoolingKernel> available_kernels = +{ + { + "neon_fp32_maxunpooling", + [](const DataTypeISASelectorData & data) { return data.dt == DataType::F32; }, + REGISTER_FP32_NEON(neon_fp32_maxunpooling) + }, + { + "neon_fp16_maxunpooling", + [](const DataTypeISASelectorData & data) { return data.dt == DataType::F16 && data.isa.fp16; }, + REGISTER_FP16_NEON(neon_fp16_maxunpooling) + }, + { + "neon_qu8_maxunpooling", + [](const DataTypeISASelectorData & data) { return data.dt == DataType::QASYMM8; }, + REGISTER_QASYMM8_NEON(neon_qs8_maxunpooling) + }, + { + "neon_qs8_maxunpooling", + [](const DataTypeISASelectorData & data) { return data.dt == DataType::QASYMM8_SIGNED; }, + REGISTER_QASYMM8_SIGNED_NEON(neon_qu8_maxunpooling) + }, +}; + +Status validate_arguments(const ITensorInfo *src, const ITensorInfo *indices, const ITensorInfo *dst, const PoolingLayerInfo &pool_info) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, indices, dst); + ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(src); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(indices, 1, DataType::U32); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(src, indices); + + int pool_stride_x = 0; + int pool_stride_y = 0; + PoolingType pool_type = pool_info.pool_type; + const PadStrideInfo pad_stride_info = pool_info.pad_stride_info; + std::tie(pool_stride_x, pool_stride_y) = pad_stride_info.stride(); + const int pool_size_x = pool_info.pool_size.width; + const int pool_size_y = pool_info.pool_size.height; + const Size2D pool_size(pool_size_x, pool_size_y); + + ARM_COMPUTE_RETURN_ERROR_ON_MSG(pool_type != PoolingType::MAX, "Pooling indices only supported for MAX pooling method"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG((pool_size != Size2D(2, 2)), "Pooling indices only supported for pool size 2x2"); + if(dst->total_size() != 0) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, dst); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(src, dst); + } + + return Status{}; +} +} // namespace + +void CpuMaxUnpoolingLayerKernel::configure(const ITensorInfo *src, const ITensorInfo *indices, ITensorInfo *dst, const PoolingLayerInfo &pool_info) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst, indices); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, indices, dst, pool_info)); + ARM_COMPUTE_UNUSED(indices); + + const auto uk = CpuMaxUnpoolingLayerKernel::get_implementation(DataTypeISASelectorData{ src->data_type(), CPUInfo::get().get_isa() }); + ARM_COMPUTE_ERROR_ON_NULLPTR(uk); + _run_method = uk->ukernel; + + const TensorShape output_shape = compute_unpool_shape(*src, pool_info); + auto_init_if_empty(*dst, src->clone()->set_tensor_shape(output_shape)); + + auto window = calculate_max_window(*src, Steps()); + ICpuKernel::configure(window); +} + +Status CpuMaxUnpoolingLayerKernel::validate(const ITensorInfo *src, const ITensorInfo *indices, const ITensorInfo *dst, const PoolingLayerInfo &pool_info) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, indices, dst); + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, indices, dst, pool_info)); + return Status{}; +} + +void CpuMaxUnpoolingLayerKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) +{ + ARM_COMPUTE_UNUSED(info); + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICpuKernel::window(), window); + + const auto src = tensors.get_const_tensor(TensorType::ACL_SRC_0); + const auto indices = tensors.get_const_tensor(TensorType::ACL_SRC_1); + const auto dst = tensors.get_tensor(TensorType::ACL_DST); + + _run_method(src, indices, dst, window); +} + +const char *CpuMaxUnpoolingLayerKernel::name() const +{ + return "CpuMaxUnpoolingLayerKernel"; +} + +const std::vector<CpuMaxUnpoolingLayerKernel::MaxUnpoolingKernel> &CpuMaxUnpoolingLayerKernel::get_available_kernels() +{ + return available_kernels; +} +} // namespace kernels +} // namespace cpu +} // namespace arm_compute
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