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/*
* Copyright (c) 2017 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 "arm_compute/core/GLES_COMPUTE/kernels/GCIm2ColKernel.h"
#include "arm_compute/core/AccessWindowStatic.h"
#include "arm_compute/core/Error.h"
#include "arm_compute/core/GLES_COMPUTE/GCHelpers.h"
#include "arm_compute/core/GLES_COMPUTE/GCKernelLibrary.h"
#include "arm_compute/core/GLES_COMPUTE/IGCTensor.h"
#include "arm_compute/core/GLES_COMPUTE/OpenGLES.h"
#include "arm_compute/core/Helpers.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/core/Validate.h"
#include "support/ToolchainSupport.h"
#include <cmath>
#include <tuple>
using namespace arm_compute;
GCIm2ColKernel::GCIm2ColKernel()
: _input(nullptr), _output(nullptr), _convolved_dims(), _num_elems_processed_per_iteration(1), _run_func(nullptr)
{
}
void GCIm2ColKernel::configure(const IGCTensor *input, IGCTensor *output, std::pair<unsigned int, unsigned int> kernel_dims, const PadStrideInfo &conv_info, bool has_bias)
{
ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32);
ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
ARM_COMPUTE_UNUSED(kernel_dims);
_input = input;
_output = output;
std::set<std::string> build_opts;
std::string dt_name = (input->info()->data_type() == DataType::F32) ? "DATA_TYPE_FP32" : "DATA_TYPE_FP16";
build_opts.emplace("#define LOCAL_SIZE_X " + support::cpp11::to_string(1));
build_opts.emplace("#define LOCAL_SIZE_Y " + support::cpp11::to_string(1));
build_opts.emplace("#define LOCAL_SIZE_Z " + support::cpp11::to_string(1));
build_opts.insert("#define " + dt_name);
if(has_bias)
{
build_opts.emplace("#define HAS_BIAS");
}
int pad_x = 0;
int pad_y = 0;
int stride_x = 0;
int stride_y = 0;
std::tie(pad_x, pad_y) = conv_info.pad();
std::tie(stride_x, stride_y) = conv_info.stride();
const bool run_img2col_reduced = (output->info()->dimension(0) == (input->info()->dimension(0) * input->info()->dimension(1) * input->info()->dimension(2))) && (TensorShape::num_max_dimensions >= 4)
&& (std::equal(input->info()->tensor_shape().cbegin() + 3,
input->info()->tensor_shape().cend(),
output->info()->tensor_shape().cbegin() + 1))
&& ((stride_x == 1) && (stride_y == 1) && (pad_x == 0) && (pad_y == 0));
if(!run_img2col_reduced)
{
// this path is currently not used and not validated
build_opts.insert("#define IM2COL_GENERIC");
_convolved_dims = scaled_dimensions(input->info()->dimension(0), input->info()->dimension(1),
kernel_dims.first, kernel_dims.second,
conv_info);
_num_elems_processed_per_iteration = output->info()->dimension(0);
build_opts.emplace("#define KERNEL_WIDTH " + support::cpp11::to_string(kernel_dims.first));
build_opts.emplace("#define KERNEL_HEIGHT " + support::cpp11::to_string(kernel_dims.second));
build_opts.emplace("#define KERNEL_DEPTH " + support::cpp11::to_string(input->info()->dimension(2)));
build_opts.emplace("#define CONVOLVED_WIDTH " + support::cpp11::to_string(_convolved_dims.first));
build_opts.emplace("#define CONVOLVED_HEIGHT " + support::cpp11::to_string(_convolved_dims.second));
build_opts.emplace("#define STRIDE_X " + support::cpp11::to_string(conv_info.stride().first));
build_opts.emplace("#define STRIDE_Y " + support::cpp11::to_string(conv_info.stride().second));
build_opts.emplace("#define PAD_X " + support::cpp11::to_string(conv_info.pad().first));
build_opts.emplace("#define PAD_Y " + support::cpp11::to_string(conv_info.pad().second));
build_opts.emplace("#define SRC_WIDTH " + support::cpp11::to_string(input->info()->dimension(0)));
build_opts.emplace("#define SRC_HEIGHT " + support::cpp11::to_string(input->info()->dimension(1)));
// Create kernel
_kernel = static_cast<GCKernel>(GCKernelLibrary::get().create_kernel("im2col_generic", build_opts));
_run_func = &GCIm2ColKernel::run_generic;
}
else
{
build_opts.insert("#define IM2COL_REDUCED");
_num_elems_processed_per_iteration = 4 / input->info()->element_size();
// Create kernel
_kernel = static_cast<GCKernel>(GCKernelLibrary::get().create_kernel("im2col_reduced", build_opts));
_run_func = &GCIm2ColKernel::run_reduced;
}
// Configure kernel window
Window win = calculate_max_window(*input->info(), Steps(_num_elems_processed_per_iteration));
if(input->info()->data_type() == DataType::F16)
{
// Calculate input right and bottom border
AccessWindowHorizontal input_access(input->info(), 0, _num_elems_processed_per_iteration);
// Calculate output right and bottom border
const int output_width = output->info()->dimension(0);
const int output_height = output->info()->dimension(1);
const int output_padding_right = ceil_to_multiple(output_width, _num_elems_processed_per_iteration) - output_width;
AccessWindowStatic output_access(output->info(), 0, 0, output_width + output_padding_right, output_height);
update_window_and_padding(win, input_access, output_access);
}
output->info()->set_valid_region(ValidRegion(Coordinates(), output->info()->tensor_shape()));
if(!run_img2col_reduced)
{
// set the Z dimension's step same size as the whole dimension so that one can't split across the Z dimension
win.set_dimension_step(Window::DimZ, win[Window::DimZ].end() - win[Window::DimZ].start());
}
IGCKernel::configure(win);
}
void GCIm2ColKernel::run(const Window &window)
{
ARM_COMPUTE_ERROR_ON(_run_func == nullptr);
(this->*_run_func)(window);
}
void GCIm2ColKernel::run_generic(const Window &window)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(IGCKernel::window(), window);
// Get initial windows
Window window_collapsed = window.collapse_if_possible(IGCKernel::window(), Window::DimZ);
// Change the Z dimension's step back to 1
window_collapsed.set_dimension_step(Window::DimZ, 1);
Window slice = window_collapsed.first_slice_window_3D();
Window slice_in = window_collapsed.first_slice_window_3D();
Window slice_out = window_collapsed.first_slice_window_3D();
// Setup slice
slice.set(Window::DimX, Window::Dimension(0, static_cast<int>(_convolved_dims.first), 1));
slice.set(Window::DimY, Window::Dimension(0, static_cast<int>(_convolved_dims.second), 1));
// Setup input slice
// The first three dimensions of the input are increased by the inner loops
slice_in.set(Window::DimX, Window::Dimension(0, 0, 0));
slice_in.set(Window::DimY, Window::Dimension(0, 0, 0));
slice_in.set(Window::DimZ, Window::Dimension(0, 0, 0));
// Setup output slice
slice_out.set(Window::DimX, Window::Dimension(0, _output->info()->dimension(0), _num_elems_processed_per_iteration));
slice_out.set(Window::DimY, Window::Dimension(0, _output->info()->dimension(1), 1));
slice_out.set(Window::DimZ, Window::Dimension(0, 1, 1));
_kernel.use();
do
{
unsigned int idx = 0;
add_3D_tensor_argument(idx, _input, 1, slice_in);
add_2D_tensor_argument(idx, _output, 2, slice_out);
_kernel.set_argument(idx++, static_cast<unsigned int>(_input->info()->dimension(2)));
_kernel.set_argument(idx++, static_cast<unsigned int>(_input->info()->strides_in_bytes()[3]));
_kernel.set_argument(idx++, static_cast<unsigned int>(_output->info()->strides_in_bytes()[3]));
_kernel.update_shader_params();
enqueue(*this, slice);
}
while(window_collapsed.slide_window_slice_3D(slice) && window_collapsed.slide_window_slice_3D(slice_out) && window_collapsed.slide_window_slice_3D(slice_in));
}
void GCIm2ColKernel::run_reduced(const Window &window)
{
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(IGCKernel::window(), window);
Window out_window;
out_window.use_tensor_dimensions(_output->info()->tensor_shape());
Window out_slice = out_window.first_slice_window_1D();
Window in_slice = window.first_slice_window_3D();
_kernel.use();
// Run kernel
do
{
// Set arguments
unsigned int idx = 0;
add_3D_tensor_argument(idx, _input, 1, in_slice);
add_1D_tensor_argument(idx, _output, 2, out_slice);
_kernel.set_argument(idx++, _input->info()->dimension(0));
_kernel.set_argument(idx++, _input->info()->dimension(1));
_kernel.update_shader_params();
enqueue(*this, in_slice);
}
while(window.slide_window_slice_3D(in_slice) && out_window.slide_window_slice_1D(out_slice));
}
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