| /* |
| * Copyright (c) 2023 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 "GpuCkwCast.h" |
| |
| #include "arm_compute/core/Error.h" |
| #include "arm_compute/core/Validate.h" |
| #include "arm_compute/core/utils/helpers/AdjustVecSize.h" |
| #include "ckw/TensorTileSampler.h" |
| #include "src/core/helpers/WindowHelpers.h" |
| #include "src/dynamic_fusion/sketch/gpu/GpuKernelArgument.h" |
| #include "src/dynamic_fusion/sketch/gpu/GpuKernelComponentGroup.h" |
| #include "src/dynamic_fusion/sketch/gpu/ckw_driver/GpuCkwKernelWriter.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/ckw_driver/components/utils/TypeConverter.h" |
| #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 |
| |
| GpuCkwCast::GpuCkwCast(ComponentId id, |
| const ArgumentPack<ITensorInfo> &tensors, |
| const Attributes &attributes) |
| : IGpuCkwComponentDriver{ id, tensors }, |
| _src{}, |
| _dst{}, |
| _attributes{ attributes } |
| { |
| _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 GpuCkwCast::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(); |
| |
| GpuCkwComponentArgument *src = vtable.declare_variable(comp_group, writer, _src, TensorStorageType::ClBufferUint8Ptr, "src"); |
| GpuCkwComponentArgument *dst = vtable.declare_variable(comp_group, writer, _dst, TensorStorageType::ClBufferUint8Ptr, "dst"); |
| |
| // Load the source tile and prepare the sampler. |
| if(!src->has_tile()) |
| { |
| const auto sampler = create_sampler(writer, m0, n0); |
| writer->op_load_once(src, sampler); |
| } |
| else |
| { |
| const auto &sampler = src->tile_sampler(); |
| writer->op_load_once(src, sampler); |
| } |
| |
| const auto &src_tile = src->tile(); |
| const auto &sampler = src->tile_sampler(); |
| |
| // Prepare the output tile. |
| if(!dst->has_tile()) |
| { |
| // Get Target datatype and convert it to ckw::DataType. |
| ckw::DataType target_dt = dynamic_fusion::to_ckw(_attributes.data_type()); |
| |
| // Create dst_tile based on src_tile dimensions and with target DataType. |
| const TileInfo src_tile_info = src_tile.tile_info(); |
| const TileInfo dst_tile_info = TileInfo(target_dt, src_tile_info.height(), src_tile_info.width()); |
| |
| // Declare dst_tile |
| auto &tile = writer->declare_tile("dst_tile", dst_tile_info); |
| dst->init_virtual_tensor(tile, sampler); |
| } |
| |
| const auto &dst_tile = dst->tile(); |
| |
| // Check if this op is cast-down or cast-up |
| const size_t src_size = data_size_from_type(_src->data_type()); |
| const size_t dst_size = data_size_from_type(_dst->data_type()); |
| const bool cast_down = (src_size >= dst_size); |
| |
| if(cast_down && is_data_type_quantized(_src->data_type())) |
| { |
| const auto &constant_x80 = writer->declare_tile("0x80", 0x80); |
| writer->op_binary_expression(src_tile, src_tile, BinaryOp::BitwiseXOR, constant_x80); |
| } |
| |
| ckw::ConvertPolicy convert_policy = ckw::ConvertPolicy::None; |
| |
| if(cast_down && (is_data_type_float(_src->data_type()) || _attributes.convert_policy() == ConvertPolicy::SATURATE)) |
| { |
| convert_policy = ckw::ConvertPolicy::Saturate; |
| } |
| |
| writer->op_cast_expression(dst_tile, src_tile, convert_policy); |
| } |
| |
| Window GpuCkwCast::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(); |
| // 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 = 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)); |
| |
| return win; |
| } |
| |
| } // namespace dynamic_fusion |
| } // namespace experimental |
| } // namespace arm_compute |