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author | Michele Di Giorgio <michele.digiorgio@arm.com> | 2017-07-27 09:53:49 +0100 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:35:24 +0000 |
commit | 56dd726ee074cb145612d03240b710f8adb82ddd (patch) | |
tree | 35f3a18102ccaa8f21c8397470f3d63f835c890c /src/core/CL/kernels/CLMinMaxLayerKernel.cpp | |
parent | 1cd0d5247ed1be3f9e36eb3b39bb91de296e50dd (diff) | |
download | ComputeLibrary-56dd726ee074cb145612d03240b710f8adb82ddd.tar.gz |
COMPMID-448: Implement CL Quantization/Dequantization Layer.
Change-Id: Id002e23a2ac48af3d245416dc6411d9a04a1e513
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/81827
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Diffstat (limited to 'src/core/CL/kernels/CLMinMaxLayerKernel.cpp')
-rw-r--r-- | src/core/CL/kernels/CLMinMaxLayerKernel.cpp | 136 |
1 files changed, 136 insertions, 0 deletions
diff --git a/src/core/CL/kernels/CLMinMaxLayerKernel.cpp b/src/core/CL/kernels/CLMinMaxLayerKernel.cpp new file mode 100644 index 0000000000..9b4533bd8d --- /dev/null +++ b/src/core/CL/kernels/CLMinMaxLayerKernel.cpp @@ -0,0 +1,136 @@ +/* + * 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/CL/kernels/CLMinMaxLayerKernel.h" + +#include "arm_compute/core/AccessWindowStatic.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/Validate.h" +#include "arm_compute/core/Window.h" + +#include <climits> + +using namespace arm_compute; + +CLMinMaxLayerKernel::CLMinMaxLayerKernel() + : _input(nullptr), _output(nullptr) +{ +} + +void CLMinMaxLayerKernel::configure(const ICLTensor *input, ICLTensor *output) +{ + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32); + ARM_COMPUTE_ERROR_ON(input->info()->num_dimensions() < 3); + ARM_COMPUTE_ERROR_ON_NULLPTR(output); + + TensorShape output_shape{ input->info()->tensor_shape() }; + output_shape.set(Window::DimX, 2); + output_shape.remove_dimension(1); + output_shape.remove_dimension(1); + + // Output auto initialization if not yet initialized + auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), input->info()->fixed_point_position()); + + ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + ARM_COMPUTE_ERROR_ON_MISMATCHING_DIMENSIONS(output->info()->tensor_shape(), output_shape); + + _input = input; + _output = output; + + const unsigned int num_elems_processed_per_iteration = 1; + + std::set<std::string> build_opts; + build_opts.emplace("-DWIDTH=" + support::cpp11::to_string(input->info()->dimension(0))); + build_opts.emplace("-DHEIGHT=" + support::cpp11::to_string(input->info()->dimension(1))); + build_opts.emplace("-DDEPTH=" + support::cpp11::to_string(input->info()->dimension(2))); + + // Create kernel + _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("minmax_layer", build_opts)); + + // Configure kernel window + Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration)); + AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration); + AccessWindowStatic output_access(output->info(), 0, 0, 2, output->info()->dimension(1)); + + update_window_and_padding(win, input_access, output_access); + + output_access.set_valid_region(win, ValidRegion(Coordinates(), output->info()->tensor_shape())); + + ICLKernel::configure(win); +} + +void CLMinMaxLayerKernel::reset(cl::CommandQueue &queue) +{ + _output->map(queue, true); + + Window window_output; + window_output.use_tensor_dimensions(_output->info()->tensor_shape()); + window_output.set(Window::DimX, Window::Dimension(0, 1, 1)); + window_output.collapse_if_possible(ICLKernel::window(), 1); + + Iterator output(_output, window_output); + + // Reset output + execute_window_loop(window_output, [&](const Coordinates & id) + { + auto *ptr = reinterpret_cast<float *>(output.ptr()); + ptr[0] = std::numeric_limits<float>::max(); + ptr[1] = std::numeric_limits<float>::min(); + }, + output); + + _output->unmap(queue); +} + +void CLMinMaxLayerKernel::run(const Window &window, cl::CommandQueue &queue) +{ + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); + + // Collapse min/max batches + Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), 3); + Window slice = window_collapsed.first_slice_window_3D(); + slice.set(Window::DimX, Window::Dimension(0, 1, 1)); + slice.set(Window::DimY, Window::Dimension(0, 1, 1)); + slice.set(Window::DimZ, Window::Dimension(0, 1, 1)); + + Window window_output; + window_output.use_tensor_dimensions(_output->info()->tensor_shape()); + window_output.set(Window::DimX, Window::Dimension(0, 1, 1)); + window_output.collapse_if_possible(ICLKernel::window(), 1); + + Window output_slice = window_output.first_slice_window_1D(); + + do + { + unsigned int idx = 0; + // Set inputs + add_3D_tensor_argument(idx, _input, slice); + add_1D_tensor_argument(idx, _output, output_slice); + enqueue(queue, *this, slice); + } + while(window.slide_window_slice_3D(slice) && window_output.slide_window_slice_1D(output_slice)); +} |