diff options
Diffstat (limited to 'src/dynamic_fusion/sketch/gpu/ckw_driver/components/GpuCkwPool2d.cpp')
| -rw-r--r-- | src/dynamic_fusion/sketch/gpu/ckw_driver/components/GpuCkwPool2d.cpp | 405 |
1 files changed, 405 insertions, 0 deletions
diff --git a/src/dynamic_fusion/sketch/gpu/ckw_driver/components/GpuCkwPool2d.cpp b/src/dynamic_fusion/sketch/gpu/ckw_driver/components/GpuCkwPool2d.cpp new file mode 100644 index 0000000000..d027f348ef --- /dev/null +++ b/src/dynamic_fusion/sketch/gpu/ckw_driver/components/GpuCkwPool2d.cpp @@ -0,0 +1,405 @@ +/* + * Copyright (c) 2023-2024 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/dynamic_fusion/sketch/gpu/ckw_driver/components/GpuCkwPool2d.h" + +#include "arm_compute/core/Error.h" +#include "arm_compute/core/utils/helpers/AdjustVecSize.h" +#include "arm_compute/core/Validate.h" + +#include "src/core/helpers/WindowHelpers.h" +#include "src/dynamic_fusion/sketch/gpu/ckw_driver/components/utils/CkwHelper.h" +#include "src/dynamic_fusion/sketch/gpu/ckw_driver/components/utils/type_converter/Common.h" +#include "src/dynamic_fusion/sketch/gpu/ckw_driver/GpuCkwScopedKernelWriter.h" +#include "src/dynamic_fusion/sketch/gpu/ckw_driver/GpuCkwVariableTable.h" +#include "src/dynamic_fusion/sketch/gpu/GpuKernelArgument.h" +#include "src/dynamic_fusion/sketch/gpu/GpuKernelComponentGroup.h" + +#include "compute_kernel_writer/include/ckw/KernelWriter.h" +#include <cstdint> + +namespace arm_compute +{ +namespace experimental +{ +namespace dynamic_fusion +{ +GpuCkwPool2d::GpuCkwPool2d(ComponentId id, + const ArgumentPack<ITensorInfo> &tensors, + const Attributes &attributes, + const Settings &settings) + : IGpuCkwComponentDriver{id, tensors}, _src{}, _dst{}, _attributes{attributes}, _settings{settings} + +{ + _src = this->tensors().get_const_tensor(TensorType::ACL_SRC_0); + _dst = this->tensors().get_const_tensor(TensorType::ACL_DST_0); + ARM_COMPUTE_ERROR_ON_NULLPTR(_src, _dst); +} + +void GpuCkwPool2d::write_component_code(const ComponentGroup &comp_group, + GpuCkwVariableTable &vtable, + GpuCkwScopedKernelWriter writer) const +{ + const uint32_t width_idx = get_data_layout_dimension_index(_src->data_layout(), DataLayoutDimension::WIDTH); + const uint32_t height_idx = get_data_layout_dimension_index(_src->data_layout(), DataLayoutDimension::HEIGHT); + + /******************************************************************************** + * 1 - Define tensors + ********************************************************************************/ + GpuCkwComponentArgument *src = vtable.declare_variable(comp_group, writer, _src, "src"); + GpuCkwComponentArgument *dst = vtable.declare_variable(comp_group, writer, _dst, "dst"); + + /******************************************************************************** + * 2 - Define CKW constants + ********************************************************************************/ + const auto dst_dt = to_ckw(_dst->data_type()); + const auto pool_sz_x = static_cast<int32_t>(_attributes.pool_size().x()); + const auto pool_sz_y = static_cast<int32_t>(_attributes.pool_size().y()); + const auto pad_x = static_cast<int32_t>(_attributes.pad().left); + const auto pad_y = static_cast<int32_t>(_attributes.pad().top); + const auto stride_x = static_cast<int32_t>(_attributes.stride().x()); + const auto stride_y = static_cast<int32_t>(_attributes.stride().y()); + const auto src_w = static_cast<int32_t>(_src->dimension(width_idx)); + const auto src_h = static_cast<int32_t>(_src->dimension(height_idx)); + const auto dst_h = static_cast<int32_t>(_dst->dimension(height_idx)); + + // CKW constants + auto const_pool_sz_x_i32 = writer->declare_constant_tile(ckw::ConstantData({{pool_sz_x}}, ckw::DataType::Int32)); + auto const_pool_sz_y_i32 = writer->declare_constant_tile(ckw::ConstantData({{pool_sz_y}}, ckw::DataType::Int32)); + auto const_pad_x_i32 = writer->declare_constant_tile(ckw::ConstantData({{pad_x}}, ckw::DataType::Int32)); + auto const_pad_y_i32 = writer->declare_constant_tile(ckw::ConstantData({{pad_y}}, ckw::DataType::Int32)); + auto const_stride_x_i32 = writer->declare_constant_tile(ckw::ConstantData({{stride_x}}, ckw::DataType::Int32)); + auto const_stride_y_i32 = writer->declare_constant_tile(ckw::ConstantData({{stride_y}}, ckw::DataType::Int32)); + auto const_src_w_i32 = writer->declare_constant_tile(ckw::ConstantData({{src_w}}, ckw::DataType::Int32)); + auto const_src_h_i32 = writer->declare_constant_tile(ckw::ConstantData({{src_h}}, ckw::DataType::Int32)); + auto const_dst_h_i32 = writer->declare_constant_tile(ckw::ConstantData({{dst_h}}, ckw::DataType::Int32)); + auto const_0_i32 = writer->declare_constant_tile(ckw::ConstantData({{0}}, ckw::DataType::Int32)); + auto const_pos_1_i32 = writer->declare_constant_tile(ckw::ConstantData({{1}}, ckw::DataType::Int32)); + auto const_0_fp = writer->declare_constant_tile(ckw::ConstantData({{0.0f}}, dst_dt)); + auto const_lowest_val_fp = + writer->declare_constant_tile(ckw::ConstantData({{std::numeric_limits<float>::lowest()}}, ckw::DataType::Fp32)); + auto const_neg_inf_val_fp = writer->declare_constant_tile(ckw::ConstantData({{-1.0f / 0.0f}}, ckw::DataType::Fp32)); + + /******************************************************************************** + * 3 - Define the compute block parameters and destination tile (if not root component) + * Bind the tile to the tensor to share it among different components and + * initialize the compute block parameters + ********************************************************************************/ + // The n0 and m0 parameters from root_window only refers to the output + const auto root_window = comp_group.get_root_component()->ckw_component_driver()->get_window(); + + // Destination compute block size + const int32_t dst_n0 = root_window.x().step(); + const int32_t dst_m0 = root_window.y().step(); + + // Destination compute block size left-over + const int32_t dst_n0_partial = _dst->dimension(0) % dst_n0; + const int32_t dst_m0_partial = _dst->dimension(1) % dst_m0; + + // Shift-back for the overlapping-min strategy + const int32_t dst_shift_back = (dst_n0 - dst_n0_partial) % dst_n0; + + ckw::TensorSampler sampler_dst; + sampler_dst.format(ckw::TensorSamplerFormat::Dim0_Dim1_Dim2); + if (dst_n0_partial == 0) + { + sampler_dst.address_mode_x(ckw::TensorSamplerAddressModeX::None); + } + else + { + sampler_dst.address_mode_x(ckw::TensorSamplerAddressModeX::OverlappingMin); + } + + if (dst_m0_partial == 0) + { + sampler_dst.address_mode_y(ckw::TensorSamplerAddressModeY::None); + } + else + { + sampler_dst.address_mode_y(ckw::TensorSamplerAddressModeY::ClampToBorderMaxOnly); + } + + sampler_dst.address_mode_z(ckw::TensorSamplerAddressModeZ::None); + sampler_dst.storage(ckw::TensorStorageType::BufferUint8Ptr); + + // Declare destination tile + auto tile_dst = writer->declare_tile("dst", ckw::TileInfo(dst_dt, dst_m0, dst_n0)); + + // Initialize destination tile + writer->op_assign(tile_dst, const_0_fp); + + // Bind tile to the tensor + dst->init_virtual_tensor(tile_dst, sampler_dst); + + /******************************************************************************** + * 4 - Define the compute block parameters CKW constants + ********************************************************************************/ + // Only now we can declare the N0 and M0 as constant + auto const_dst_n0_i32 = writer->declare_constant_tile(ckw::ConstantData({{dst_n0}}, ckw::DataType::Int32)); + auto const_dst_m0_i32 = writer->declare_constant_tile(ckw::ConstantData({{dst_m0}}, ckw::DataType::Int32)); + auto const_shift_back_dst_n0_i32 = + writer->declare_constant_tile(ckw::ConstantData({{dst_shift_back}}, ckw::DataType::Int32)); + + /******************************************************************************** + * 5 - Define the sampler for the input tensor + ********************************************************************************/ + ckw::TensorSampler sampler_src; + sampler_src.format(ckw::TensorSamplerFormat::Dim0_Dim1_Dim2); + sampler_src.address_mode_x(ckw::TensorSamplerAddressModeX::None); + sampler_src.address_mode_y(ckw::TensorSamplerAddressModeY::None); + sampler_src.address_mode_z(ckw::TensorSamplerAddressModeZ::None); + + /******************************************************************************** + * 6 - Extra operations required before writing the main code + ********************************************************************************/ + // Check if it is global pooling + const bool is_global_pooling = (pool_sz_x == src_w) && (pool_sz_y == src_h) && (pad_x == 0) && (pad_y == 0); + + // Accumulate always in F32 if the pool type is not MAX + const bool acc_f32 = (dst_dt == ckw::DataType::Fp32) || + ((dst_dt == ckw::DataType::Fp16) && _attributes.pool_type() != PoolingType::MAX); + + const auto acc_dt = acc_f32 ? ckw::DataType::Fp32 : ckw::DataType::Fp16; + + const bool is_wider_acc = dst_dt != acc_dt; + + /******************************************************************************** + * 7 - Get the coordinates of the destination tile + ********************************************************************************/ + auto tile_gid_0 = writer->declare_tile("gid_0", ckw::TileInfo(ckw::DataType::Int32)); + auto tile_gid_1 = writer->declare_tile("gid_1", ckw::TileInfo(ckw::DataType::Int32)); + auto tile_gid_2 = writer->declare_tile("gid_2", ckw::TileInfo(ckw::DataType::Int32)); + + writer->op_get_global_id(tile_gid_0, 0); + writer->op_get_global_id(tile_gid_1, 1); + writer->op_get_global_id(tile_gid_2, 2); + + auto tile_cout0 = writer->declare_tile("cout0", ckw::TileInfo(ckw::DataType::Int32)); // OFM + auto tile_mout0 = writer->declare_tile("mout0", ckw::TileInfo(ckw::DataType::Int32)); // WIDTH + auto tile_mout1 = writer->declare_tile("mout1", ckw::TileInfo(ckw::DataType::Int32)); // HEIGHT + auto tile_bout0 = writer->declare_tile("bout0", ckw::TileInfo(ckw::DataType::Int32)); // BATCH SIZE IDX + + // Calculate coordinates + get_coordinate_from_gws_overlapping_min(writer, tile_cout0, tile_gid_0, const_dst_n0_i32, + const_shift_back_dst_n0_i32, const_0_i32); + get_coordinate_from_gws(writer, tile_mout0, tile_gid_1, const_dst_m0_i32); + writer->op_binary(tile_mout1, ckw::BinaryOp::Mod, tile_gid_2, const_dst_h_i32); + writer->op_binary(tile_bout0, ckw::BinaryOp::Div, tile_gid_2, const_dst_h_i32); + + /******************************************************************************** + * 8 - Write the rest of the code + ********************************************************************************/ + // A tile used to temporarily store results or as an accumulator in case of AVG and L2 pooling. + auto tile_res = writer->declare_tile("tile_res", ckw::TileInfo(acc_dt, dst_m0, dst_n0)); + + // Initialise result tile with appropriate value + if (_attributes.pool_type() == PoolingType::MAX) + { + if (_settings.use_inf_as_limit()) + { + writer->op_cast(tile_res, const_neg_inf_val_fp, ckw::ConvertPolicy::None); + } + else + { + writer->op_cast(tile_res, const_lowest_val_fp, ckw::ConvertPolicy::None); + } + } + else + { + writer->op_cast(tile_res, const_0_fp, ckw::ConvertPolicy::None); + } + + // tile_idx_in_w = tile_mout0 * STRIDE_X - PAD_X + auto tile_src_coord_x_start = writer->declare_tile("idx_in_w", ckw::DataType::Int32); + writer->op_binary(tile_src_coord_x_start, ckw::BinaryOp::Mul, tile_mout0, const_stride_x_i32); + writer->op_binary(tile_src_coord_x_start, ckw::BinaryOp::Sub, tile_src_coord_x_start, const_pad_x_i32); + + // tile_idx_in_h = tile_mout1 * STRIDE_Y - PAD_Y + auto tile_src_coord_y_start = writer->declare_tile("idx_in_h", ckw::DataType::Int32); + writer->op_binary(tile_src_coord_y_start, ckw::BinaryOp::Mul, tile_mout1, const_stride_y_i32); + writer->op_binary(tile_src_coord_y_start, ckw::BinaryOp::Sub, tile_src_coord_y_start, const_pad_y_i32); + + auto tile_neg_src_coord_x_start = writer->declare_tile("neg_src_coord_x_start", ckw::DataType::Int32); + auto tile_neg_src_coord_y_start = writer->declare_tile("neg_src_coord_y_start", ckw::DataType::Int32); + + writer->op_binary(tile_neg_src_coord_x_start, ckw::BinaryOp::Sub, const_0_i32, tile_src_coord_x_start); + writer->op_binary(tile_neg_src_coord_y_start, ckw::BinaryOp::Sub, const_0_i32, tile_src_coord_y_start); + + // int pool_x_s = max((int)0, -idx_in_w); + // int pool_x_e = min((int)POOL_SIZE_X, (int)SRC_WIDTH - idx_in_w); + // int pool_y_s = max((int)0, -idx_in_h); + // int pool_y_e = min((int)POOL_SIZE_Y, (int)SRC_HEIGHT - idx_in_h); + auto tile_pool_x_s = writer->declare_tile("pool_x_s", ckw::DataType::Int32); + auto tile_pool_y_s = writer->declare_tile("pool_y_s", ckw::DataType::Int32); + auto tile_pool_x_e = writer->declare_tile("pool_x_e", ckw::DataType::Int32); + auto tile_pool_y_e = writer->declare_tile("pool_y_e", ckw::DataType::Int32); + + writer->op_binary(tile_pool_x_s, ckw::BinaryOp::Max, const_0_i32, tile_neg_src_coord_x_start); + writer->op_binary(tile_pool_x_e, ckw::BinaryOp::Add, const_src_w_i32, tile_neg_src_coord_x_start); + writer->op_binary(tile_pool_x_e, ckw::BinaryOp::Min, const_pool_sz_x_i32, tile_pool_x_e); + writer->op_binary(tile_pool_y_s, ckw::BinaryOp::Max, const_0_i32, tile_neg_src_coord_y_start); + writer->op_binary(tile_pool_y_e, ckw::BinaryOp::Add, const_src_h_i32, tile_neg_src_coord_y_start); + writer->op_binary(tile_pool_y_e, ckw::BinaryOp::Min, const_pool_sz_y_i32, tile_pool_y_e); + + // #if defined(EXCLUDE_PADDING) + // int filter_size = (pool_y_e - pool_y_s) * (pool_x_e - pool_x_s); + // #else // defined(EXCLUDE_PADDING) + // int filter_size = POOL_SIZE_X * POOL_SIZE_Y; + // #endif // defined(EXCLUDE_PADDING) + auto tile_filter_size = writer->declare_tile("filter_size", ckw::DataType::Int32); + if (_attributes.exclude_padding()) + { + auto tile_x_diff = writer->declare_tile("x_diff", ckw::DataType::Int32); + auto tile_y_diff = writer->declare_tile("y_diff", ckw::DataType::Int32); + + writer->op_binary(tile_x_diff, ckw::BinaryOp::Sub, tile_pool_x_e, tile_pool_x_s); + writer->op_binary(tile_y_diff, ckw::BinaryOp::Sub, tile_pool_y_e, tile_pool_y_s); + writer->op_binary(tile_filter_size, ckw::BinaryOp::Mul, tile_x_diff, tile_y_diff); + } + else + { + writer->op_binary(tile_filter_size, ckw::BinaryOp::Mul, const_pool_sz_x_i32, const_pool_sz_y_i32); + } + + auto tile_x = writer->declare_tile("x", ckw::DataType::Int32); + auto tile_y = writer->declare_tile("y", ckw::DataType::Int32); + + if (is_global_pooling) + { + writer->op_assign(tile_y, const_0_i32); + writer->op_assign(tile_pool_y_e, const_pool_sz_y_i32); + } + else + { + writer->op_assign(tile_y, tile_pool_y_s); + } + + // Y dim for-loop + writer->op_for_loop( + tile_y, ckw::BinaryOp::Less, tile_pool_y_e, tile_y, ckw::AssignmentOp::Increment, const_pos_1_i32, + [&]() + { + // Reset the iterator for the inner loop + if (is_global_pooling) + { + writer->op_assign(tile_x, const_0_i32); + writer->op_assign(tile_pool_x_e, const_pool_sz_x_i32); + } + else + { + writer->op_assign(tile_x, tile_pool_x_s); + } + + auto tile_src_coord_y = writer->declare_tile("src_coord_y", ckw::DataType::Int32); + writer->op_binary(tile_src_coord_y, ckw::BinaryOp::Add, tile_src_coord_y_start, tile_y); + + // X dim for-loop + writer->op_for_loop( + tile_x, ckw::BinaryOp::Less, tile_pool_x_e, tile_x, ckw::AssignmentOp::Increment, const_pos_1_i32, + [&]() + { + auto tile_src_coord_x = writer->declare_tile("src_coord_x", ckw::DataType::Int32); + writer->op_binary(tile_src_coord_x, ckw::BinaryOp::Add, tile_src_coord_x_start, tile_x); + + ckw::DataType src_dt = to_ckw(_src->data_type()); + auto tile_src = writer->declare_tile("tile_src", ckw::TileInfo(acc_dt, dst_m0, dst_n0)); + + // Load src tile + if (is_wider_acc) + { + auto tile_src0 = writer->declare_tile("src_tile0", ckw::TileInfo(src_dt, dst_m0, dst_n0)); + writer->op_load(tile_src0, src->tensor(), sampler_src, tile_cout0, tile_src_coord_x, + tile_src_coord_y, tile_bout0); + writer->op_cast(tile_src, tile_src0, ckw::ConvertPolicy::None); + } + else + { + writer->op_load(tile_src, src->tensor(), sampler_src, tile_cout0, tile_src_coord_x, + tile_src_coord_y, tile_bout0); + } + + // Take the square of the input, for L2 Pooling + if (_attributes.pool_type() == PoolingType::L2) + { + writer->op_binary(tile_src, ckw::BinaryOp::Mul, tile_src, tile_src); + } + + // Perfom Pooling op + if (_attributes.pool_type() == PoolingType::MAX) + { + writer->op_binary(tile_res, ckw::BinaryOp::Max, tile_res, tile_src); + } + else + { + writer->op_binary(tile_res, ckw::BinaryOp::Add, tile_res, tile_src); + } + }); + }); + + if ((_attributes.pool_type() == PoolingType::AVG) || (_attributes.pool_type() == PoolingType::L2)) + { + // Filter_size is automatically broadcasted in the operation + auto tile_filter_size_fp = writer->declare_tile("filter_size_fp", ckw::TileInfo(acc_dt)); + writer->op_cast(tile_filter_size_fp, tile_filter_size, ckw::ConvertPolicy::None); + writer->op_binary(tile_res, ckw::BinaryOp::Div, tile_res, tile_filter_size_fp); + } + + // Take square root of the result in L2 pooling + if (_attributes.pool_type() == PoolingType::L2) + { + writer->op_unary(tile_res, ckw::UnaryOp::Sqrt, tile_res); + } + + // Store the results and do casting if mixed precision + if (is_wider_acc) + { + writer->op_cast(tile_dst, tile_res, ckw::ConvertPolicy::None); + } + else + { + writer->op_assign(tile_dst, tile_res); + } +} + +Window GpuCkwPool2d::get_window() const +{ + ARM_COMPUTE_ERROR_ON_MSG(_dst->tensor_shape().total_size() == 0U, "Destination tensor is not initialized"); + + TensorShape output_shape = _dst->tensor_shape(); + const uint32_t vec_size = adjust_vec_size(((_dst->data_type() == DataType::F32) ? 2 : 4), _dst->dimension(0)); + // Create and configure kernel window + auto win = calculate_max_window(output_shape, Steps(vec_size)); + win = win.collapse_if_possible(win, Window::DimZ); // collapse window on batch size. + return win; +} + +std::string GpuCkwPool2d::get_name(const ComponentGroup &comp_group) const +{ + ARM_COMPUTE_UNUSED(comp_group); + + return "pool2dMxN"; +} + +} // namespace dynamic_fusion +} // namespace experimental +} // namespace arm_compute |