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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 "src/dynamic_fusion/sketch/gpu/template_writer/cl/ClTemplateLogits1DNorm.h"
#include "arm_compute/core/utils/helpers/AdjustVecSize.h"
#include "src/core/helpers/WindowHelpers.h"
#include "src/dynamic_fusion/sketch/gpu/GpuKernelComponentGroup.h"
#include "support/StringSupport.h"
namespace arm_compute
{
namespace experimental
{
namespace dynamic_fusion
{
ClTemplateLogits1DNorm::ClTemplateLogits1DNorm(ComponentId id,
const ArgumentPack<ITensorInfo> &tensors,
const Attributes &attributes)
: IGpuTemplateComponentWriter{id, tensors}, _src{}, _sum{}, _dst{}, _attributes{attributes}
{
_src = this->tensors().get_const_tensor(TensorType::ACL_SRC_0);
_sum = this->tensors().get_const_tensor(TensorType::ACL_SRC_1);
_dst = this->tensors().get_const_tensor(TensorType::ACL_DST_0);
ARM_COMPUTE_ERROR_ON_NULLPTR(_src);
ARM_COMPUTE_ERROR_ON_NULLPTR(_sum);
ARM_COMPUTE_ERROR_ON_NULLPTR(_dst);
}
std::string ClTemplateLogits1DNorm::get_name() const
{
return "logits_1d_norm";
}
std::string ClTemplateLogits1DNorm::get_component_code(const ComponentGroup &comp_group) const
{
ARM_COMPUTE_UNUSED(comp_group);
std::string code = R"_(
//------------------ START KERNEL {{meta_kernel_id}} ---------------------
{
const int x_offs = g_ind_0 * sizeof({{DATA_TYPE}});
__global uchar *src_addr = {{src}}_ptr + {{src}}_offset_first_element_in_bytes + x_offs + g_ind_1 * {{src}}_stride_y + g_ind_2 * {{src}}_stride_z;
__global uchar *dst_addr = {{dst}}_ptr + {{dst}}_offset_first_element_in_bytes + x_offs + g_ind_1 * {{dst}}_stride_y + g_ind_2 * {{dst}}_stride_z;
Image sum = CONVERT_TENSOR3D_TO_IMAGE_STRUCT_NO_STEP({{sum}});
)_";
// Load max value of 1D logits vector (row)
code += R"_(
{{DATA_TYPE}} sum_val = *((__global {{DATA_TYPE}} *)offset(&sum, 0, g_ind_1));
VEC_DATA_TYPE({{DATA_TYPE}}, N0)
data0 = VLOAD(N0)(0, (__global {{DATA_TYPE}} *)src_addr);
)_";
if (_attributes.is_log_softmax())
{
code += R"_(
sum_val = log(sum_val);
data0 -= sum_val;
)_";
}
else
{
code += R"_(
data0 /= sum_val;
)_";
}
code += R"_(
STORE_VECTOR_SELECT(data, {{DATA_TYPE}}, dst_addr, N0, PARTIAL_N0, PARTIAL_N0 != 0 && g_ind_0 == 0);
}
//------------------ END KERNEL {{meta_kernel_id}} ---------------------
)_";
return code;
}
void ClTemplateLogits1DNorm::declare_variables(GpuKernelVariableTable &vtable, const ComponentGroup &comp_group) const
{
vtable.declare_variable(comp_group, _src, GpuKernelArgumentInfo(GpuKernelArgumentInfo::Type::Tensor_3D), "src");
vtable.declare_variable(comp_group, _sum, GpuKernelArgumentInfo(GpuKernelArgumentInfo::Type::Tensor_3D), "sum");
vtable.declare_variable(comp_group, _dst, GpuKernelArgumentInfo(GpuKernelArgumentInfo::Type::Tensor_3D), "dst");
}
TagLUT ClTemplateLogits1DNorm::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["sum"] = vtable.get_variable(_sum);
lut["dst"] = vtable.get_variable(_dst);
// Local build options
lut["meta_kernel_id"] = id();
const DataType data_type = _src->data_type();
lut["DATA_TYPE"] = get_cl_type_from_data_type(data_type);
return lut;
}
CLBuildOptions ClTemplateLogits1DNorm::get_build_options(const ComponentGroup &comp_group) const
{
ARM_COMPUTE_UNUSED(comp_group);
CLBuildOptions build_opts{};
const auto root_window = comp_group.get_root_component()->template_writer()->get_window();
const unsigned int n0 = root_window.x().step();
build_opts.add_option("-DN0=" + support::cpp11::to_string(n0));
build_opts.add_option("-DPARTIAL_N0=" + support::cpp11::to_string((_src->dimension(0) % n0)));
return build_opts;
}
std::string ClTemplateLogits1DNorm::get_config_id() const
{
std::string config_id = get_name();
config_id += "_";
config_id += support::cpp11::to_string(_src->dimension(0));
config_id += "_";
config_id += string_from_data_type(_src->data_type());
return config_id;
}
std::set<std::string> ClTemplateLogits1DNorm::get_headers_list() const
{
return std::set<std::string>{"helpers.h", "tile_helpers.h"};
}
Window ClTemplateLogits1DNorm::get_window() const
{
ARM_COMPUTE_ERROR_ON_MSG(_dst->tensor_shape().total_size() == 0U, "Destination tensor is not initialized");
constexpr unsigned int serial_vector_size = 16;
const unsigned int vector_size = adjust_vec_size(serial_vector_size, _src->dimension(0));
Window win = calculate_max_window(*_src, Steps(vector_size));
return win.collapse(win, Window::DimZ);
}
} // namespace dynamic_fusion
} // namespace experimental
} // namespace arm_compute