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/*
* Copyright (c) 2019-2021 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/core/CL/kernels/CLArgMinMaxLayerKernel.h"
#include "arm_compute/core/CL/CLHelpers.h"
#include "arm_compute/core/CL/CLKernelLibrary.h"
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/TensorInfo.h"
#include "arm_compute/core/Utils.h"
#include "arm_compute/core/Validate.h"
#include "src/core/CL/CLValidate.h"
#include "src/core/helpers/AutoConfiguration.h"
#include "src/core/helpers/WindowHelpers.h"
#include "support/StringSupport.h"
namespace arm_compute
{
namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *prev_output, const ITensorInfo *output, unsigned int axis, ReductionOperation op)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::S32, DataType::F16, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON_MSG(op != ReductionOperation::ARG_IDX_MAX && op != ReductionOperation::ARG_IDX_MIN, "Only ARG_IDX_MAX and ARG_IDX_MIN are supported");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis >= TensorShape::num_max_dimensions, "Reduction axis greater than max number of dimensions");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis > 3, "Unsupported reduction axis");
if(output->total_size() != 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U32, DataType::S32);
}
if(prev_output != nullptr && prev_output->total_size() != 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(prev_output, 1, DataType::U32, DataType::S32);
if(output->total_size() != 0)
{
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(prev_output, output);
}
}
return Status{};
}
} // namespace
CLArgMinMaxLayerKernel::CLArgMinMaxLayerKernel()
: _input(nullptr), _prev_output(nullptr), _output(nullptr), _reduction_axis(0), _op(ReductionOperation::ARG_IDX_MAX)
{
}
void CLArgMinMaxLayerKernel::configure(const ICLTensor *input, const ICLTensor *prev_output, ICLTensor *output, unsigned int axis, ReductionOperation op)
{
configure(CLKernelLibrary::get().get_compile_context(), input, prev_output, output, axis, op);
}
void CLArgMinMaxLayerKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *prev_output, ICLTensor *output, unsigned int axis, ReductionOperation op)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
TensorShape output_shape{ input->info()->tensor_shape() };
output_shape.set(axis, 1);
auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape).set_data_type(DataType::S32).reset_padding().set_is_resizable(true));
ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (prev_output != nullptr) ? prev_output->info() : nullptr, output->info(), axis, op));
auto padding_info = get_padding_info({ input, prev_output, output });
_input = input;
_prev_output = prev_output;
_output = output;
_reduction_axis = axis;
_op = op;
// Set build options
const auto vector_size = (axis == 0) ? 16U : adjust_vec_size(16U, input->info()->dimension(0));
CLBuildOptions build_opts;
build_opts.add_option_if(_prev_output != nullptr, "-DPREV_OUTPUT");
build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
build_opts.add_option("-DVEC_SIZE_LEFTOVER=" + support::cpp11::to_string(input->info()->dimension(0) % vector_size));
build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(vector_size));
build_opts.add_option_if(is_data_type_float(input->info()->data_type()), "-DFLOAT_DATA_TYPE");
build_opts.add_option_if_else(op == ReductionOperation::ARG_IDX_MAX, "-DARG_MAX", "-DARG_MIN");
build_opts.add_option("-DDATA_TYPE_OUTPUT=" + get_cl_type_from_data_type(output->info()->data_type()));
// Create kernel
cl::NDRange lws_hint = CLKernelLibrary::get().default_ndrange();
std::string kernel_axis_name;
switch(axis)
{
case 0:
{
const ICLTensor *input_for_width = prev_output != nullptr ? _prev_output : _input;
build_opts.add_option("-DWIDTH=" + support::cpp11::to_string(input_for_width->info()->dimension(0)));
kernel_axis_name = "x";
lws_hint = create_lws_hint_parallel_implementations(input_for_width->info()->dimension(0), vector_size);
}
break;
case 1:
build_opts.add_option("-DHEIGHT=" + support::cpp11::to_string(input->info()->dimension(1)));
kernel_axis_name = "y";
break;
case 2:
build_opts.add_option("-DDEPTH=" + support::cpp11::to_string(input->info()->dimension(2)));
kernel_axis_name = "z";
break;
case 3:
build_opts.add_option("-DDEPTH=" + support::cpp11::to_string(input->info()->dimension(2)));
build_opts.add_option("-DBATCH=" + support::cpp11::to_string(input->info()->dimension(3)));
kernel_axis_name = "w";
break;
default:
ARM_COMPUTE_ERROR("Not supported");
}
_kernel = create_kernel(compile_context, "arg_min_max_" + kernel_axis_name, build_opts.options());
// Configure kernel window
Window win = calculate_max_window((prev_output != nullptr) ? (*prev_output->info()) : (*input->info()), Steps(vector_size));
ICLKernel::configure_internal(win, lws_hint);
ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info));
}
Status CLArgMinMaxLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *prev_output, const ITensorInfo *output, unsigned int axis, ReductionOperation op)
{
ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, prev_output, output, axis, op));
return Status{};
}
void CLArgMinMaxLayerKernel::run(const Window &window, cl::CommandQueue &queue)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
switch(_reduction_axis)
{
case 0:
{
// Set out window
Window out_window(window);
out_window.set(Window::DimX, Window::Dimension(0, 0, 0));
// Get first input and output slices
Window in_slice = window.first_slice_window_2D();
Window out_slice = out_window.first_slice_window_2D();
// Reshape window
const unsigned int num_tensors = _prev_output != nullptr ? 3 : 2;
// Set local sums buffer
unsigned int local_res_size = lws_hint()[0] * _output->info()->element_size();
_kernel.setArg(num_arguments_per_2D_tensor() * num_tensors, local_res_size, nullptr);
do
{
unsigned int idx = 0;
add_2D_tensor_argument(idx, _input, in_slice);
if(_prev_output != nullptr)
{
add_2D_tensor_argument(idx, _prev_output, in_slice);
}
add_2D_tensor_argument(idx, _output, out_slice);
enqueue(queue, *this, in_slice, lws_hint());
}
while(window.slide_window_slice_2D(in_slice) && window.slide_window_slice_2D(out_slice));
}
break;
case 1:
{
// Get first input and output slices
Window window_in{ window };
window_in.set(Window::DimY, Window::Dimension(0, _input->info()->dimension(1), _input->info()->dimension(1)));
Window in_slice = window_in.first_slice_window_2D();
Window out_slice = window.first_slice_window_2D();
do
{
unsigned int idx = 0;
add_2D_tensor_argument(idx, _input, in_slice);
add_2D_tensor_argument(idx, _output, out_slice);
enqueue(queue, *this, in_slice, lws_hint());
}
while(window_in.slide_window_slice_2D(in_slice) && window.slide_window_slice_2D(out_slice));
}
break;
case 2:
{
// Get first input and output slices
Window window_in{ window };
window_in.set(Window::DimZ, Window::Dimension(0, _input->info()->dimension(2), _input->info()->dimension(2)));
Window in_slice = window_in.first_slice_window_3D();
Window out_slice = window.first_slice_window_3D();
do
{
unsigned int idx = 0;
add_3D_tensor_argument(idx, _input, in_slice);
add_3D_tensor_argument(idx, _output, out_slice);
enqueue(queue, *this, in_slice, lws_hint());
}
while(window_in.slide_window_slice_3D(in_slice) && window.slide_window_slice_3D(out_slice));
}
break;
case 3:
{
// Get first input and output slices
Window window_in{ window };
window_in.set(3, Window::Dimension(0, 1, 1));
Window in_slice = window_in.first_slice_window_4D();
Window out_slice = window.first_slice_window_4D();
do
{
unsigned int idx = 0;
add_4D_tensor_argument(idx, _input, in_slice);
add_4D_tensor_argument(idx, _output, out_slice);
enqueue(queue, *this, in_slice, lws_hint());
}
while(window_in.slide_window_slice_4D(in_slice) && window.slide_window_slice_4D(out_slice));
}
break;
default:
ARM_COMPUTE_ERROR("Not supported");
}
}
} // namespace arm_compute
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