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/*
* 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 "ClTemplateReshape.h"
#include "arm_compute/core/utils/helpers/AdjustVecSize.h"
#include "arm_compute/core/utils/StringUtils.h"
#include "src/core/helpers/WindowHelpers.h"
#include "src/dynamic_fusion/sketch/gpu/GpuKernelComponentGroup.h"
namespace arm_compute
{
namespace experimental
{
namespace dynamic_fusion
{
constexpr unsigned int vector_size_byte_opencl = 16;
ClTemplateReshape::ClTemplateReshape(ComponentId id, const ArgumentPack<ITensorInfo> &tensors)
: IGpuTemplateComponentWriter{id, tensors}, _src{}, _dst{}
{
_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);
}
std::string ClTemplateReshape::get_name() const
{
return "reshape";
}
std::string ClTemplateReshape::get_component_code(const ComponentGroup &comp_group) const
{
ARM_COMPUTE_UNUSED(comp_group);
std::string code;
code = R"_(
//------------------ START KERNEL {{meta_kernel_id}} ---------------------
// IN(src) {{src}}
// OUT(dst, accum) {{dst}}
TILE(uint, M0, 1, g_dst_indirect_y);
{
__global uchar * base_src_ptr = {{src}}_ptr + {{src}}_offset_first_element_in_bytes;
const int tile_vertical_idx = g_ind_1 * {{arg_dst}}_c + g_ind_2 * {{arg_dst}}_c * {{arg_dst}}_w;
LOOP_UNROLLING(int, _m0, 0, 1, M0,
{
const int row_idx = _m0 * {{arg_dst}}_c + tile_vertical_idx;
const int tile_horizontal_idx = g_ind_0 + row_idx;
LOOP_UNROLLING(int, _n0, 0, 1, N0,
{
{{src}}_ptr = base_src_ptr;
const int linear_idx = tile_horizontal_idx + _n0;
const int in_id_x = linear_idx % {{src}}_c;
const int in_id_y = (linear_idx / {{src}}_c) % {{src}}_w;
const int in_id_z = linear_idx / ({{src}}_c * {{src}}_w);
{{src}}_ptr += in_id_x * sizeof({{DATA_TYPE}}) + in_id_y * {{src}}_stride_y + in_id_z * {{src}}_stride_z;
{{dst}}[_m0].s[_n0] = *((__global {{DATA_TYPE}} *){{src}}_ptr);
})
})
LOOP_UNROLLING(int, i, 0, 1, M0,
{
g_dst_indirect_y[i].v = (uint)min((int)(g_ind_1 + i), (int)({{arg_dst}}_w) - 1);
g_dst_indirect_y[i].v += (int)(g_ind_2 % {{arg_dst}}_h) * (int)({{arg_dst}}_w);
g_dst_indirect_y[i].v += (int)(g_ind_2 / {{arg_dst}}_h) * (int)({{arg_dst}}_w * {{arg_dst}}_h);
})
}
//------------------ END KERNEL {{meta_kernel_id}} ---------------------
)_";
return code;
}
void ClTemplateReshape::declare_variables(GpuKernelVariableTable &vtable, const ComponentGroup &comp_group) const
{
vtable.declare_variable(comp_group, _src,
GpuKernelArgumentInfo(common_tensor_type), // GpuKernelArgumentInfo::Type::Image_3D
"src");
vtable.declare_variable(comp_group, _dst, GpuKernelArgumentInfo(common_tensor_type), "dst");
}
TagLUT ClTemplateReshape::get_tag_lut(const GpuKernelVariableTable &vtable, const ComponentGroup &comp_group) const
{
ARM_COMPUTE_UNUSED(comp_group);
TagLUT lut{};
// Arguments and global shared variables
lut["src"] = vtable.get_variable(_src);
lut["dst"] = vtable.get_variable(_dst);
lut["arg_dst"] = vtable.get_variable(comp_group.get_any_dst_tensor());
lut["meta_kernel_id"] = id();
lut["DATA_TYPE"] = get_cl_type_from_data_type(_dst->data_type());
return lut;
}
CLBuildOptions ClTemplateReshape::get_build_options(const ComponentGroup &comp_group) const
{
CLBuildOptions build_opts{};
const auto root_window = comp_group.get_root_component()->template_writer()->get_window();
const unsigned int n0 = root_window.x().step();
const unsigned int m0 = root_window.y().step();
const unsigned int partial_store_n0 = _dst->dimension(0) % n0;
build_opts.add_option("-DN0=" + support::cpp11::to_string(n0));
build_opts.add_option("-DM0=" + support::cpp11::to_string(m0));
build_opts.add_option("-DPARTIAL_N0=" + support::cpp11::to_string(partial_store_n0));
return build_opts;
}
std::string ClTemplateReshape::get_config_id() const
{
std::string config_id{};
config_id += lower_string(string_from_data_type(_dst->data_type()));
config_id += "_";
config_id += support::cpp11::to_string(_dst->dimension(0));
config_id += "_";
config_id += support::cpp11::to_string(_dst->dimension(1));
return config_id;
}
std::set<std::string> ClTemplateReshape::get_headers_list() const
{
return std::set<std::string>{"helpers.h", "tile_helpers.h"};
}
Window ClTemplateReshape::get_window() const
{
ARM_COMPUTE_ERROR_ON_MSG(_dst->tensor_shape().total_size() == 0U, "Destination tensor is not initialized");
const unsigned int n0 = adjust_vec_size(vector_size_byte_opencl / _dst->element_size(), _dst->dimension(0));
Window win = calculate_max_window(*_dst, Steps(n0));
return win.collapse(win, Window::DimZ);
}
} // namespace dynamic_fusion
} // namespace experimental
} // namespace arm_compute
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