diff options
Diffstat (limited to 'src/core/gpu/cl/kernels/ClPool2dKernel.cpp')
| -rw-r--r-- | src/core/gpu/cl/kernels/ClPool2dKernel.cpp | 509 |
1 files changed, 0 insertions, 509 deletions
diff --git a/src/core/gpu/cl/kernels/ClPool2dKernel.cpp b/src/core/gpu/cl/kernels/ClPool2dKernel.cpp deleted file mode 100644 index 0e15bffd14..0000000000 --- a/src/core/gpu/cl/kernels/ClPool2dKernel.cpp +++ /dev/null @@ -1,509 +0,0 @@ -/* - * Copyright (c) 2017-2021 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/core/gpu/cl/kernels/ClPool2dKernel.h" - -#include "arm_compute/core/CL/CLHelpers.h" -#include "arm_compute/core/CL/CLKernelLibrary.h" -#include "arm_compute/core/CL/ICLTensor.h" -#include "arm_compute/core/TensorInfo.h" -#include "arm_compute/core/Utils.h" -#include "arm_compute/core/Validate.h" -#include "arm_compute/core/utils/misc/ShapeCalculator.h" -#include "src/core/CL/CLValidate.h" -#include "src/core/helpers/AutoConfiguration.h" -#include "src/core/helpers/WindowHelpers.h" -#include "support/Cast.h" -#include "support/StringSupport.h" - -namespace arm_compute -{ -namespace opencl -{ -namespace kernels -{ -using namespace arm_compute::misc::shape_calculator; - -namespace -{ -// Internal window config info -using ClPoolingConfig = std::pair<unsigned int, BorderSize>; //num_elems_processed_per_iteration, border_size - -void auto_init(const ITensorInfo *src, ITensorInfo *dst, ITensorInfo *indices, PoolingLayerInfo pool_info) -{ - TensorShape out_shape = compute_pool_shape(*src, pool_info); - auto_init_if_empty(*dst, src->clone()->set_tensor_shape(out_shape)); - if(indices) - { - auto_init_if_empty(*indices, src->clone()->set_tensor_shape(out_shape).set_data_type(DataType::U32)); - } -} - -Status validate_arguments(const ITensorInfo *src, const ITensorInfo *dst, const PoolingLayerInfo &pool_info, const ITensorInfo *indices) -{ - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, dst); - ARM_COMPUTE_RETURN_ERROR_ON_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_MSG((is_data_type_quantized_asymmetric(src->data_type()) && pool_info.pool_type == PoolingType::L2), - "Unsupported combination of parameters!"); - - const auto data_layout = pool_info.data_layout == DataLayout::UNKNOWN ? src->data_layout() : pool_info.data_layout; - const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); - const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); - const bool is_global_pooling = pool_info.is_global_pooling; - unsigned int pool_size_x = is_global_pooling ? src->dimension(idx_width) : pool_info.pool_size.width; - unsigned int pool_size_y = is_global_pooling ? src->dimension(idx_height) : pool_info.pool_size.height; - int output_width = 0; - int output_height = 0; - std::tie(output_width, output_height) = scaled_dimensions_signed(src->tensor_shape()[idx_width], src->tensor_shape()[idx_height], - pool_size_x, pool_size_y, pool_info.pad_stride_info); - ARM_COMPUTE_RETURN_ERROR_ON_MSG((output_width < 1 || output_height < 1), "Calculated output dimension size is invalid"); - - // Check indices - if(indices) - { - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(pool_info.pool_type != PoolingType::MAX, "Pooling indices only supported for MAX pooling method"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG((pool_info.pool_size != Size2D(2, 2)), "Pooling indices only supported for pool size 2x2"); - - if(indices->total_size() != 0) - { - TensorInfo idx_info(TensorInfo(compute_pool_shape(*src, pool_info), 1, DataType::U32)); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(indices, &idx_info); - } - } - - // Checks performed when dst is configured - 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); - TensorInfo out_info(TensorInfo(compute_pool_shape(*src, pool_info), 1, dst->data_type())); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(dst, &out_info); - } - - return Status{}; -} - -std::tuple<Status, Window, ClPoolingConfig> validate_and_configure_window(ITensorInfo *src, ITensorInfo *dst, const PoolingLayerInfo &pool_info, ITensorInfo *indices = nullptr) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst); - - // Get data layout - const DataLayout data_layout = pool_info.data_layout == DataLayout::UNKNOWN ? src->data_layout() : pool_info.data_layout; - const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); - const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); - - int pool_stride_x = 0; - int pool_stride_y = 0; - unsigned int pooled_w = 0; - unsigned int pooled_h = 0; - int pool_size_x = pool_info.is_global_pooling ? src->dimension(idx_width) : pool_info.pool_size.width; - int pool_size_y = pool_info.is_global_pooling ? src->dimension(idx_height) : pool_info.pool_size.height; - 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_pad_right = pad_stride_info.pad_right(); - const int pool_pad_top = pad_stride_info.pad_top(); - const int pool_pad_left = pad_stride_info.pad_left(); - const int pool_pad_bottom = pad_stride_info.pad_bottom(); - BorderSize border_size = BorderSize(); - - auto_init(src, dst, indices, pool_info); - pooled_w = dst->tensor_shape()[idx_width]; - pooled_h = dst->tensor_shape()[idx_height]; - - const DataType data_type = src->data_type(); - - const int src_width = src->dimension(idx_width); - const int src_height = src->dimension(idx_height); - - unsigned int num_elems_processed_per_iteration = 0; - bool window_changed = false; - Window win{}; - switch(data_layout) - { - case DataLayout::NCHW: - { - // Initialize border size - border_size = BorderSize(pool_pad_top, pool_pad_right, pool_pad_bottom, pool_pad_left); - // Change the number of elements processed per iteration - // for pooling 3x3 with stride less equal than 3 - const bool can_optimize = (pool_size_x == 3) && (pool_size_y == 3) && (pool_stride_x <= 3) && !is_data_type_quantized(data_type); - num_elems_processed_per_iteration = can_optimize ? 4 : 1; - const unsigned int num_elems_read_per_iteration = (num_elems_processed_per_iteration - 1) * pool_stride_x + pool_size_x; - - // Number of iterations in X dimension - const int num_iterations_x = (pooled_w + num_elems_processed_per_iteration - 1) / num_elems_processed_per_iteration; - - // Upper limit for the number of right/bottom border elements that are accessed - const int upper_bound_w = ((num_iterations_x - 1) * num_elems_processed_per_iteration * pool_stride_x - pool_pad_left + num_elems_read_per_iteration) - src_width; - const int upper_bound_h = ((pooled_h - 1) * pool_stride_y - pool_pad_top + pool_size_y) - src_height; - - border_size.right = std::max(upper_bound_w, pool_pad_right); - border_size.bottom = std::max(upper_bound_h, pool_pad_bottom); - - win = calculate_max_window(*dst, Steps(num_elems_processed_per_iteration)); - - AccessWindowRectangle src_access(src, -pool_pad_left, -pool_pad_top, num_elems_read_per_iteration, pool_size_y, - pool_stride_x, pool_stride_y); - AccessWindowHorizontal dst_access(dst, 0, num_elems_processed_per_iteration); - - // Update indices window - if(indices) - { - AccessWindowHorizontal indices_access(indices, 0, num_elems_processed_per_iteration); - window_changed = update_window_and_padding(win, src_access, dst_access, indices_access); - indices_access.set_valid_region(win, ValidRegion(Coordinates(), indices->tensor_shape())); - } - else - { - window_changed = update_window_and_padding(win, src_access, dst_access); - } - - dst_access.set_valid_region(win, ValidRegion(Coordinates(), dst->tensor_shape())); - break; - } - case DataLayout::NHWC: - { - const size_t vec_size = dst->data_type() == DataType::F32 ? 2 : 4; - - // Initialize border size - border_size = BorderSize(); - num_elems_processed_per_iteration = adjust_vec_size(vec_size, dst->dimension(0)); - win = calculate_max_window(*dst, Steps(num_elems_processed_per_iteration)); - break; - } - default: - ARM_COMPUTE_ERROR("Not implemented"); - } - - Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; - return std::make_tuple(err, win, ClPoolingConfig(num_elems_processed_per_iteration, border_size)); -} -} // namespace - -ClPool2dKernel::ClPool2dKernel() - : _pool_info(), _data_layout(DataLayout::UNKNOWN), _border_size(0), _num_elems_processed_per_iteration(1) -{ -} - -BorderSize ClPool2dKernel::border_size() const -{ - return _border_size; -} - -void ClPool2dKernel::configure(const ClCompileContext &compile_context, ITensorInfo *src, ITensorInfo *dst, const PoolingLayerInfo &pool_info, ITensorInfo *indices) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst); - - auto padding_info = get_padding_info({ src, dst, indices }); - - // Set instance variables - _pool_info = pool_info; - _data_layout = pool_info.data_layout == DataLayout::UNKNOWN ? src->data_layout() : pool_info.data_layout; - int pool_stride_x = 0; - int pool_stride_y = 0; - const PoolingType pool_type = pool_info.pool_type; - const int idx_width = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH); - const int idx_height = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT); - const int idx_channel = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::CHANNEL); - const int idx_batch_size = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::BATCHES); - const int pool_size_x = pool_info.is_global_pooling ? src->dimension(idx_width) : pool_info.pool_size.width; - const int pool_size_y = pool_info.is_global_pooling ? src->dimension(idx_height) : pool_info.pool_size.height; - const PadStrideInfo pad_stride_info = pool_info.pad_stride_info; - const bool exclude_padding = pool_info.exclude_padding; - std::tie(pool_stride_x, pool_stride_y) = pad_stride_info.stride(); - const int pool_pad_top = pad_stride_info.pad_top(); - const int pool_pad_left = pad_stride_info.pad_left(); - - // Set build options - CLBuildOptions build_opts; - const DataType data_type = src->data_type(); - - // Configure kernel window - auto win_config = validate_and_configure_window(src, dst, pool_info, indices); - - ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config)); - ICLKernel::configure_internal(std::get<1>(win_config)); - - ClPoolingConfig pooling_config = std::get<2>(win_config); - _num_elems_processed_per_iteration = pooling_config.first; - _border_size = pooling_config.second; - - build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(_num_elems_processed_per_iteration)); - - // Tensor paddings are used to calculate the indicies for MAX pooling - if(pool_info.pool_size == Size2D(2, 2) && pool_type == PoolingType::MAX && indices && is_data_type_float(data_type)) - { - build_opts.add_option("-DPAD_TENSOR_LEFT=" + support::cpp11::to_string(src->padding().left)); - build_opts.add_option("-DPAD_TENSOR_RIGHT=" + support::cpp11::to_string(src->padding().right)); - build_opts.add_option("-DPAD_TENSOR_TOP=" + support::cpp11::to_string(src->padding().top)); - build_opts.add_option("-DPAD_TENSOR_BOTTOM=" + support::cpp11::to_string(src->padding().bottom)); - build_opts.add_option("-DTENSOR_CHANNEL=" + support::cpp11::to_string(src->dimension(idx_channel))); - build_opts.add_option("-DTENSOR_WIDTH=" + support::cpp11::to_string(src->dimension(idx_width))); - build_opts.add_option("-DTENSOR_HEIGHT=" + support::cpp11::to_string(src->dimension(idx_height))); - } - - if(is_data_type_quantized_asymmetric(data_type) && src->quantization_info() != dst->quantization_info()) - { - const UniformQuantizationInfo iq_info = src->quantization_info().uniform(); - const UniformQuantizationInfo oq_info = dst->quantization_info().uniform(); - - build_opts.add_option("-DOFFSET_IN1=" + float_to_string_with_full_precision(iq_info.offset)); - build_opts.add_option("-DOFFSET_OUT=" + float_to_string_with_full_precision(oq_info.offset)); - build_opts.add_option("-DSCALE_IN1=" + float_to_string_with_full_precision(iq_info.scale)); - build_opts.add_option("-DSCALE_OUT=" + float_to_string_with_full_precision(oq_info.scale)); - } - - // Check dst dimensions - auto_init(src, dst, indices, pool_info); - - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, dst, pool_info, indices)); - - build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type)); - build_opts.add_option("-DPOOL_" + string_from_pooling_type(pool_type)); - build_opts.add_option("-DSTRIDE_X=" + support::cpp11::to_string(pool_stride_x)); - build_opts.add_option("-DSTRIDE_Y=" + support::cpp11::to_string(pool_stride_y)); - build_opts.add_option("-DPAD_X=" + support::cpp11::to_string(pool_pad_left)); - build_opts.add_option("-DPAD_Y=" + support::cpp11::to_string(pool_pad_top)); - build_opts.add_option("-DPOOL_SIZE_X=" + support::cpp11::to_string(pool_size_x)); - build_opts.add_option("-DPOOL_SIZE_Y=" + support::cpp11::to_string(pool_size_y)); - - // Set the initial value for the pooling operation accordingly with the data type - if(pool_type == PoolingType::MAX) - { - if(is_data_type_quantized(data_type)) - { - PixelValue type_min{}; - std::tie(type_min, std::ignore) = get_min_max(data_type); - build_opts.add_option("-DINITIAL_VALUE=" + support::cpp11::to_string(type_min.get<int32_t>())); - } - else - { - build_opts.add_option("-DINITIAL_VALUE=" + float_to_string_with_full_precision(std::numeric_limits<float>::lowest())); - } - } - else - { - // Pool AVG and Pool L2 initial value - build_opts.add_option("-DINITIAL_VALUE=0"); - } - - build_opts.add_option("-DMAX_WIDTH=" + support::cpp11::to_string(src->dimension(idx_width) + (exclude_padding ? 0 : pool_pad_left))); - build_opts.add_option("-DMAX_HEIGHT=" + support::cpp11::to_string(src->dimension(idx_height) + (exclude_padding ? 0 : pool_pad_top))); - - // Create kernel - switch(_data_layout) - { - case DataLayout::NCHW: - { - const auto use_fp_mixed_precision = (data_type == DataType::F16) && pool_info.fp_mixed_precision; - const auto use_wider_accumulator = use_fp_mixed_precision && (pool_type != PoolingType::MAX); - const auto acc_data_type = get_cl_type_from_data_type(use_wider_accumulator ? DataType::F32 : data_type); - build_opts.add_option("-DACC_DATA_TYPE=" + acc_data_type); - build_opts.add_option_if(use_wider_accumulator, "-DFP_MIXED_PRECISION"); - - if(pool_type != PoolingType::MAX) - { - build_opts.add_option_if(exclude_padding, "-DEXCLUDE_PADDING"); - } - - if((pool_size_x == 3) && (pool_size_y == 3) && !is_data_type_quantized_asymmetric(data_type)) - { - // Check if we have pool3x3 with stride_x less equal than 3. In these cases, run an optimized OpenCL kernel where - // each thread computes 4 dst elements - const bool is_pool3x3_stride_le3 = (pool_size_x == 3) && (pool_size_y == 3) && (pool_stride_x <= 3); - - std::string kernel_name = ((is_pool3x3_stride_le3) ? "pooling_layer_optimized_" : "pooling_layer_") - + support::cpp11::to_string(pool_size_x); - _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); - } - else if(pool_info.pool_size == Size2D(2, 2) && pool_type == PoolingType::MAX && indices && is_data_type_float(data_type)) - { - // For max pooling with pool2x2, store indicies which will be used in max unpooling - if(data_type == DataType::F32) - { - std::string kernel_name = "pooling_layer_2_nchw_indices_fp32"; - _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); - } - else if(data_type == DataType::F16) - { - std::string kernel_name = "pooling_layer_2_nchw_indices_fp16"; - _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); - } - } - else // Run general case - { - std::string kernel_name = is_data_type_quantized_asymmetric(data_type) ? "pooling_layer_MxN_quantized_nchw" : "pooling_layer_MxN_nchw"; - _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); - } - break; - } - case DataLayout::NHWC: - { - // Floating point mixed precision is support on F16 only - const auto use_fp_mixed_precision = (data_type == DataType::F16) && pool_info.fp_mixed_precision && pool_type != PoolingType::MAX; - - // Wider accumulation is required to avoid accuracy loss - // Case 1: Floating point mixed precision (fp16 src data and fp32 accumulation) - // Cast 2: Quantized (int8/uint8 src data and int32 accumulation ) - DataType acc_data_type = data_type; - - if(use_fp_mixed_precision) - { - acc_data_type = DataType::F32; - } - else if(is_data_type_quantized(data_type) && pool_type != PoolingType::MAX) - { - acc_data_type = DataType::S32; - } - - build_opts.add_option("-DACC_DATA_TYPE=" + get_cl_type_from_data_type(acc_data_type)); - build_opts.add_option_if(use_fp_mixed_precision, "-DFP_MIXED_PRECISION"); - build_opts.add_option_if(exclude_padding, "-DEXCLUDE_PADDING"); - build_opts.add_option("-DSRC_WIDTH=" + support::cpp11::to_string(src->dimension(idx_width))); - build_opts.add_option("-DSRC_HEIGHT=" + support::cpp11::to_string(src->dimension(idx_height))); - build_opts.add_option("-DDST_HEIGHT=" + support::cpp11::to_string(dst->dimension(idx_height))); - build_opts.add_option("-DDST_CHANNELS=" + support::cpp11::to_string(dst->dimension(idx_channel))); - build_opts.add_option("-DDST_BATCH_SIZE=" + support::cpp11::to_string(dst->dimension(idx_batch_size))); - build_opts.add_option("-DVEC_SIZE_LEFTOVER=" + support::cpp11::to_string(src->dimension(0) % _num_elems_processed_per_iteration)); - if(pool_info.pool_size == Size2D(2, 2) && is_data_type_float(data_type)) - { - build_opts.add_option_if(indices != nullptr && pool_type == PoolingType::MAX, "-DEXTRACT_MAX_INDEX"); - - std::string kernel_name = "pooling_layer_2x2_nhwc"; - _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); - } - else - { - std::string kernel_name = is_data_type_quantized_asymmetric(data_type) ? "pooling_layer_MxN_quantized_nhwc" : "pooling_layer_MxN_nhwc"; - _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); - } - break; - } - default: - ARM_COMPUTE_ERROR("Not implemented"); - } - - // Set config_id for enabling LWS tuning - _config_id = "pooling_layer_"; - _config_id += lower_string(string_from_data_type(data_type)); - _config_id += "_"; - _config_id += lower_string(string_from_data_layout(_data_layout)); - _config_id += "_"; - _config_id += support::cpp11::to_string(dst->dimension(idx_width)); - _config_id += "_"; - _config_id += support::cpp11::to_string(dst->dimension(idx_height)); - _config_id += "_"; - _config_id += support::cpp11::to_string(dst->dimension(idx_channel)); - _config_id += "_"; - _config_id += lower_string(string_from_data_layout(src->data_layout())); - - ARM_COMPUTE_ERROR_ON(src->data_layout() == DataLayout::NHWC && has_padding_changed(padding_info)); -} - -Status ClPool2dKernel::validate(const ITensorInfo *src, const ITensorInfo *dst, const PoolingLayerInfo &pool_info, const ITensorInfo *indices) -{ - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, dst, pool_info, indices)); - ARM_COMPUTE_RETURN_ON_ERROR(std::get<0>(validate_and_configure_window(src->clone().get(), dst->clone().get(), pool_info))); - - return Status{}; -} - -void ClPool2dKernel::run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue) -{ - ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); - ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); - - unsigned int pool_stride_x = 0; - unsigned int pool_stride_y = 0; - std::tie(pool_stride_x, pool_stride_y) = _pool_info.pad_stride_info.stride(); - - const auto src = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC)); - auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST_0)); - auto indices = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST_1)); - - // Collapse window - Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); - - switch(_data_layout) - { - case DataLayout::NCHW: - { - Window slice = window_collapsed.first_slice_window_3D(); - do - { - // Upsample src by pool size - Window in_slice(slice); - in_slice.set(Window::DimX, Window::Dimension(in_slice.x().start() - _pool_info.pad_stride_info.pad_left(), - (in_slice.x().end() - _pool_info.pad_stride_info.pad_left()) * pool_stride_x, - pool_stride_x * _num_elems_processed_per_iteration)); - in_slice.set(Window::DimY, Window::Dimension(in_slice.y().start() - _pool_info.pad_stride_info.pad_top(), - (in_slice.y().end() - _pool_info.pad_stride_info.pad_top()) * pool_stride_y, - pool_stride_y)); - - // Set srcs - unsigned int idx = 0; - add_3D_tensor_argument(idx, src, in_slice); - add_3D_tensor_argument(idx, dst, slice); - if(indices && is_data_type_float(src->info()->data_type()) && (_pool_info.pool_size == Size2D(2, 2))) - { - add_3D_tensor_argument(idx, indices, slice); - } - enqueue(queue, *this, slice, lws_hint()); - } - while(window_collapsed.slide_window_slice_3D(slice)); - break; - } - case DataLayout::NHWC: - { - const size_t batch_size = dst->info()->tensor_shape().total_size_upper(3); - - Window slice = window_collapsed.first_slice_window_4D(); - Window in_slice = window_collapsed.first_slice_window_4D(); - in_slice.set(Window::DimX, Window::Dimension(0, src->info()->dimension(0), _num_elems_processed_per_iteration)); - in_slice.set(Window::DimY, Window::Dimension(0, src->info()->dimension(1), pool_stride_x)); - in_slice.set(Window::DimZ, Window::Dimension(0, src->info()->dimension(2), pool_stride_y)); - in_slice.set(3, Window::Dimension(0, batch_size, 1)); - do - { - // Set srcs - unsigned int idx = 0; - add_4D_tensor_argument(idx, src, in_slice); - add_4D_tensor_argument(idx, dst, slice); - if(indices && is_data_type_float(src->info()->data_type()) && (_pool_info.pool_type == PoolingType::MAX) && (_pool_info.pool_size == Size2D(2, 2))) - { - add_4D_tensor_argument(idx, indices, slice); - } - enqueue(queue, *this, slice, lws_hint()); - } - while(window.slide_window_slice_4D(slice) && window.slide_window_slice_4D(in_slice)); - break; - } - default: - ARM_COMPUTE_ERROR("Not implemented"); - } -} -} // namespace kernels -} // namespace opencl -} // namespace arm_compute |