diff options
Diffstat (limited to 'src/dynamic_fusion/sketch/gpu/ckw_driver/components/GpuCkwActivation.cpp')
| -rw-r--r-- | src/dynamic_fusion/sketch/gpu/ckw_driver/components/GpuCkwActivation.cpp | 259 |
1 files changed, 182 insertions, 77 deletions
diff --git a/src/dynamic_fusion/sketch/gpu/ckw_driver/components/GpuCkwActivation.cpp b/src/dynamic_fusion/sketch/gpu/ckw_driver/components/GpuCkwActivation.cpp index c3b1b3c8bc..68f478a7ce 100644 --- a/src/dynamic_fusion/sketch/gpu/ckw_driver/components/GpuCkwActivation.cpp +++ b/src/dynamic_fusion/sketch/gpu/ckw_driver/components/GpuCkwActivation.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2023 Arm Limited. + * Copyright (c) 2023-2024 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -26,69 +26,29 @@ #include "arm_compute/core/Error.h" #include "arm_compute/core/utils/helpers/AdjustVecSize.h" #include "arm_compute/core/Validate.h" -#include "ckw/TensorTileSampler.h" #include "src/core/helpers/WindowHelpers.h" -#include "src/dynamic_fusion/sketch/gpu/ckw_driver/components/utils/WriterHelper.h" -#include "src/dynamic_fusion/sketch/gpu/ckw_driver/GpuCkwKernelWriter.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> #include <string> -using namespace ckw; namespace arm_compute { namespace experimental { namespace dynamic_fusion { -namespace -{ -/** Create a simple sampler from tile of dimension [m0, n0] - */ -inline TensorTileSampler create_sampler(GpuCkwScopedKernelWriter &writer, int32_t m0, int32_t n0) -{ - TensorTileSampler sampler; - - auto &gid_0 = writer->declare_tile("gid_0", ckw::DataType::Int32); - auto &gid_1 = writer->declare_tile("gid_1", ckw::DataType::Int32); - auto &gid_2 = writer->declare_tile("gid_2", ckw::DataType::Int32); - - auto &const_0 = writer->declare_tile("0", 0); - writer->op_get_global_id(gid_0, 0); - writer->op_get_global_id(gid_1, 1); - writer->op_get_global_id(gid_2, 2); - - auto &x_coord = writer->declare_tile("x_coord", ckw::DataType::Int32); - auto &y_coord = writer->declare_tile("y_coord", ckw::DataType::Int32); - auto &m0_t = writer->declare_tile("m0", m0); - auto &n0_t = writer->declare_tile("n0", n0); - writer->op_binary_expression(x_coord, gid_0, BinaryOp::Mul, n0_t); - writer->op_binary_expression(y_coord, gid_1, BinaryOp::Mul, m0_t); - - sampler.x(x_coord); - sampler.y(y_coord); - sampler.z(const_0); // 3rd dimension collapsed with 2nd dimension - sampler.b(gid_2); - - sampler.width(n0); - sampler.height(m0); - - sampler.format(TensorSamplerFormat::C_WH_1); // 3rd dimension collapsed with 2nd dimension - sampler.address_mode_x(TensorSamplerAddressModeX::None); - sampler.address_mode_y(TensorSamplerAddressModeY::ClampToBorder); - sampler.address_mode_z(TensorSamplerAddressModeZ::Skip); // Dimensions higher than 3 not supported yet - - return sampler; -} -} // namespace GpuCkwActivation::GpuCkwActivation(ComponentId id, const ArgumentPack<ITensorInfo> &tensors, - const Attributes &attributes) + const Attributes &attributes) // NOLINT : IGpuCkwComponentDriver{id, tensors}, _src{}, _dst{}, _attributes{attributes} { _src = this->tensors().get_const_tensor(TensorType::ACL_SRC_0); @@ -100,78 +60,223 @@ void GpuCkwActivation::write_component_code(const ComponentGroup &comp_group, GpuCkwVariableTable &vtable, GpuCkwScopedKernelWriter writer) const { - const auto root_window = comp_group.get_root_component()->ckw_component_driver()->get_window(); - const unsigned int n0 = root_window.x().step(); - const unsigned int m0 = root_window.y().step(); + /******************************************************************************** + * 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_h = static_cast<int32_t>(_dst->dimension(1)); + const auto dst_dt = to_ckw(_dst->data_type()); + + // CKW constants + auto const_dst_h_i32 = writer->declare_constant_tile(ckw::ConstantData({{dst_h}}, ckw::DataType::Int32)); + auto const_pos_1_i32 = writer->declare_constant_tile(ckw::ConstantData({{1}}, ckw::DataType::Int32)); + auto const_0_i32 = writer->declare_constant_tile(ckw::ConstantData({{0}}, ckw::DataType::Int32)); + auto const_neg_1_fp = writer->declare_constant_tile(ckw::ConstantData({{-1.0f}}, dst_dt)); + auto const_pos_1_fp = writer->declare_constant_tile(ckw::ConstantData({{1.0f}}, dst_dt)); + auto const_0_fp = writer->declare_constant_tile(ckw::ConstantData({{0.0f}}, dst_dt)); + auto const_A_fp = writer->declare_constant_tile(ckw::ConstantData({{_attributes.a()}}, dst_dt)); + auto const_B_fp = writer->declare_constant_tile(ckw::ConstantData({{_attributes.b()}}, dst_dt)); + + /******************************************************************************** + * 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 compute block parameters depend on the employed tensor format + + // Destination compute block size + int32_t dst_n0 = -1; + int32_t dst_m0 = -1; + + // Destination compute block size left-over + int32_t dst_n0_partial = -1; + int32_t dst_m0_partial = -1; + + // Shift-back for the overlapping-min strategy + int32_t dst_shift_back = -1; + + if (!dst->has_tile()) + { + // If ROOT component, we use ckw::TensorSamplerFormat::Dim0_Dim1xDim2_1 + // as tensor format + const auto root_window = comp_group.get_root_component()->ckw_component_driver()->get_window(); + + dst_n0 = root_window.x().step(); + dst_m0 = root_window.y().step(); + dst_n0_partial = _dst->dimension(0) % dst_n0; + dst_m0_partial = (_dst->dimension(1) * _dst->dimension(2)) % dst_m0; + dst_shift_back = (dst_n0 - dst_n0_partial) % dst_n0; - GpuCkwComponentArgument *src = - vtable.declare_variable(comp_group, writer, _src, TensorStorageType::ClBufferUint8Ptr, "src"); - GpuCkwComponentArgument *dst = - vtable.declare_variable(comp_group, writer, _dst, TensorStorageType::ClBufferUint8Ptr, "dst"); + ckw::TensorSampler sampler_dst; + sampler_dst.format(ckw::TensorSamplerFormat::Dim0_Dim1xDim2_1); - load_src_dst_tiles_and_prepare_sampler(writer, src, dst, m0, n0, create_sampler); + if (dst_n0_partial == 0) + { + sampler_dst.address_mode_x(ckw::TensorSamplerAddressModeX::None); + } + else + { + sampler_dst.address_mode_x(ckw::TensorSamplerAddressModeX::OverlappingMin); + } - auto &src_tile = src->tile(); - auto &dst_tile = dst->tile(); + 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)); + + // Bind tile to the tensor + dst->init_virtual_tensor(tile_dst, sampler_dst); + } + else + { + // dst_m0_partial depends on the TensorSamplerFormat + dst_n0 = dst->tile().tile_info().width(); + dst_m0 = dst->tile().tile_info().height(); + dst_n0_partial = _dst->dimension(0) % dst_n0; + + ckw::TensorSampler sampler_dst = dst->tensor_sampler(); + + if (sampler_dst.format() == ckw::TensorSamplerFormat::Dim0_Dim1xDim2_1) + { + dst_m0_partial = (_dst->dimension(1) * _dst->dimension(2)) % dst_m0; + } + else if (sampler_dst.format() == ckw::TensorSamplerFormat::Dim0_Dim1_Dim2) + { + dst_m0_partial = _dst->dimension(1) % dst_m0; + } + + // Shift-back for the overlapping-min strategy + dst_shift_back = (dst_n0 - dst_n0_partial) % dst_n0; + } + + const auto &tile_dst = dst->tile(); + + /******************************************************************************** + * 4 - Define the compute block parameters CKW constants + ********************************************************************************/ + // Only now we can declare the N0 and M0 as constant + auto const_dst_n0 = writer->declare_constant_tile(ckw::ConstantData({{dst_n0}}, ckw::DataType::Int32)); + auto const_dst_m0 = writer->declare_constant_tile(ckw::ConstantData({{dst_m0}}, ckw::DataType::Int32)); + auto const_dst_shift_back_n0 = + writer->declare_constant_tile(ckw::ConstantData({{dst_shift_back}}, ckw::DataType::Int32)); + + /******************************************************************************** + * 5 - Define the sampler for the input tensor + ********************************************************************************/ + if (!src->has_tile()) + { + // Sampler + ckw::TensorSampler sampler_src = dst->tensor_sampler(); + + auto tile_gid_0 = writer->declare_tile("gid_0_src", ckw::TileInfo(ckw::DataType::Int32)); + auto tile_gid_1 = writer->declare_tile("gid_1_src", ckw::TileInfo(ckw::DataType::Int32)); + auto tile_gid_2 = writer->declare_tile("gid_2_src", 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_nout0 = writer->declare_tile("nout0_src", ckw::TileInfo(ckw::DataType::Int32)); // OFM + auto tile_mout0 = + writer->declare_tile("mout0_src", ckw::TileInfo(ckw::DataType::Int32)); // WIDTH or WIDTH x HEIGHT + auto tile_mout1 = writer->declare_tile("mout1_src", ckw::TileInfo(ckw::DataType::Int32)); // HEIGHT or 0 + auto tile_bout0 = writer->declare_tile("bout0_src", ckw::TileInfo(ckw::DataType::Int32)); // BATCH SIZE IDX + + get_coordinate_from_gws_overlapping_min(writer, tile_nout0, tile_gid_0, const_dst_n0, const_dst_shift_back_n0, + const_0_i32); + get_coordinate_from_gws(writer, tile_mout0, tile_gid_1, const_dst_m0); + + // Get the boundary aware coordinates at each global dimension index + if (sampler_src.format() == ckw::TensorSamplerFormat::Dim0_Dim1xDim2_1) + { + writer->op_assign(tile_mout1, const_0_i32); + get_coordinate_from_gws(writer, tile_bout0, tile_gid_2, const_pos_1_i32); + } + else if (sampler_src.format() == ckw::TensorSamplerFormat::Dim0_Dim1_Dim2) + { + 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); + } + + auto tile_src = writer->declare_tile("src", ckw::TileInfo(dst_dt, dst_m0, dst_n0)); + + writer->op_load(tile_src, src->tensor(), sampler_src, tile_nout0, tile_mout0, tile_mout1, tile_bout0); + + // Here, init_virtual_tensor() it is used to bring the tile_src outside the compound statement + src->init_virtual_tensor(tile_src, sampler_src); + } - // Constants - const auto &constant_minus_1 = writer->declare_tile("minus_1", -1); - const auto &constant_pos_1 = writer->declare_tile("one", 1); - const auto &constant_zero = writer->declare_tile("zero", 0); - const auto &constant_A = writer->declare_tile("A_VAL", _attributes.a()); - const auto &constant_B = writer->declare_tile("B_VAL", _attributes.b()); + const auto &tile_src = src->tile(); - // Perform the operation. + /******************************************************************************** + * 7 - Write the rest of the code + ********************************************************************************/ switch (_attributes.activation()) { case ActivationLayerInfo::ActivationFunction::LOGISTIC: { // dst = src * -1 - writer->op_binary_expression(dst_tile, src_tile, BinaryOp::Mul, constant_minus_1); + writer->op_binary(tile_dst, ckw::BinaryOp::Mul, tile_src, const_neg_1_fp); // dst = exp(src * -1) - writer->op_unary_elementwise_function(dst_tile, UnaryFunction::Exp, dst_tile); + writer->op_unary(tile_dst, ckw::UnaryOp::Exp, tile_dst); // dst = 1 + (exp(src * -1)) - writer->op_binary_expression(dst_tile, dst_tile, BinaryOp::Add, constant_pos_1); + writer->op_binary(tile_dst, ckw::BinaryOp::Add, tile_dst, const_pos_1_fp); // dst = 1 / 1 + (exp(src * -1)) - writer->op_binary_expression(dst_tile, constant_pos_1, BinaryOp::Div, dst_tile); + writer->op_binary(tile_dst, ckw::BinaryOp::Div, const_pos_1_fp, tile_dst); break; } case ActivationLayerInfo::ActivationFunction::TANH: { // dst = B_VAL * src - writer->op_binary_expression(dst_tile, src_tile, BinaryOp::Mul, constant_B); + writer->op_binary(tile_dst, ckw::BinaryOp::Mul, tile_src, const_B_fp); // dst = tanh(B_VAL * src) - writer->op_unary_elementwise_function(dst_tile, UnaryFunction::Tanh, dst_tile); + writer->op_unary(tile_dst, ckw::UnaryOp::Tanh, tile_dst); // dst = A_VAL * tanh(B_VAL * src) - writer->op_binary_expression(dst_tile, dst_tile, BinaryOp::Mul, constant_A); + writer->op_binary(tile_dst, ckw::BinaryOp::Mul, tile_dst, const_A_fp); break; } case ActivationLayerInfo::ActivationFunction::RELU: { // dst = max(src, 0) - writer->op_binary_elementwise_function(dst_tile, ckw::BinaryFunction::Max, src_tile, constant_zero); + writer->op_binary(tile_dst, ckw::BinaryOp::Max, tile_src, const_0_fp); break; } case ActivationLayerInfo::ActivationFunction::BOUNDED_RELU: { //dst = max(src, 0) - writer->op_binary_elementwise_function(dst_tile, ckw::BinaryFunction::Max, src_tile, constant_zero); + writer->op_binary(tile_dst, ckw::BinaryOp::Max, tile_src, const_0_fp); //dst = min(max(src, 0), A_VAL) - writer->op_binary_elementwise_function(dst_tile, ckw::BinaryFunction::Min, dst_tile, constant_A); + writer->op_binary(tile_dst, ckw::BinaryOp::Min, tile_dst, const_A_fp); break; } case ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU: { //dst = max(src, B_VAL) - writer->op_binary_elementwise_function(dst_tile, ckw::BinaryFunction::Max, src_tile, constant_B); + writer->op_binary(tile_dst, ckw::BinaryOp::Max, tile_src, const_B_fp); //dst = min(max(src, B_VAL), A_VAL) - writer->op_binary_elementwise_function(dst_tile, ckw::BinaryFunction::Min, dst_tile, constant_A); + writer->op_binary(tile_dst, ckw::BinaryOp::Min, tile_dst, const_A_fp); break; } default: CKW_ASSERT(false); break; } + ARM_COMPUTE_ERROR_ON_MSG(dst->has_tile() == false, "You must bind a tile before appending another component"); } Window GpuCkwActivation::get_window() const @@ -182,8 +287,8 @@ Window GpuCkwActivation::get_window() const // Collapse Dim 1 (W) and Dim 2 (H) together, leave Dim 0 (C) unchanged // This is in line with the collapsing convention used by operators like Conv2d output_shape.collapse(2U, 1U); - constexpr unsigned int vector_size_byte_opencl = 16; - const unsigned int num_elems_processed_per_iteration = + constexpr uint32_t vector_size_byte_opencl = 16; + const uint32_t num_elems_processed_per_iteration = adjust_vec_size(vector_size_byte_opencl / _dst->element_size(), _dst->dimension(0)); Window win = calculate_max_window(output_shape, Steps(num_elems_processed_per_iteration)); |