diff options
Diffstat (limited to 'src')
6 files changed, 447 insertions, 26 deletions
diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp index 0cc6e320bf..4af2b09530 100644 --- a/src/core/CL/CLKernelLibrary.cpp +++ b/src/core/CL/CLKernelLibrary.cpp @@ -308,6 +308,8 @@ const std::map<std::string, std::string> CLKernelLibrary::_kernel_program_map = { "non_max_suppression", "nonmax.cl" }, { "normalization_layer_cross_map", "normalization_layer.cl" }, { "normalization_layer_in_map", "normalization_layer.cl" }, + { "normalize_planar_yuv_layer_nchw", "normalize_planar_yuv_layer.cl" }, + { "normalize_planar_yuv_layer_nhwc", "normalize_planar_yuv_layer.cl" }, { "NV12_to_IYUV_bt709", "color_convert.cl" }, { "NV12_to_RGB888_bt709", "color_convert.cl" }, { "NV12_to_RGBA8888_bt709", "color_convert.cl" }, @@ -674,6 +676,10 @@ const std::map<std::string, std::string> CLKernelLibrary::_program_source_map = #include "./cl_kernels/normalization_layer.clembed" }, { + "normalize_planar_yuv_layer.cl", +#include "./cl_kernels/normalize_planar_yuv_layer.clembed" + }, + { "batchnormalization_layer.cl", #include "./cl_kernels/batchnormalization_layer.clembed" }, diff --git a/src/core/CL/cl_kernels/normalize_planar_yuv_layer.cl b/src/core/CL/cl_kernels/normalize_planar_yuv_layer.cl new file mode 100644 index 0000000000..dc6652449e --- /dev/null +++ b/src/core/CL/cl_kernels/normalize_planar_yuv_layer.cl @@ -0,0 +1,134 @@ +/* + * Copyright (c) 2018 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 "helpers.h" + +#if defined(DATA_TYPE) && defined(VEC_SIZE) + +#define TYPE VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + +/** Apply normalize_planar_yuv layer on tensors with NCHW format. + * + * @note Data type should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float + * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE e.g. -DVEC_SIZE=8 + * @note The depth of the input tensor should be given as a preprocessor argument using -DNUM_CHANNELS e.g. -DNUM_CHANNELS=8 + * + * @param[in] src_ptr Pointer to the first source tensor. Supported data types: F16/F32 + * @param[in] src_stride_x Stride of the first source tensor in X dimension (in bytes) + * @param[in] src_step_x input_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] src_stride_y Stride of the first source tensor in Y dimension (in bytes) + * @param[in] src_step_y input_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] src_stride_z Stride of the first source tensor in Z dimension (in bytes) + * @param[in] src_step_z input_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] src_offset_first_element_in_bytes The offset of the first element in the first source tensor + * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr + * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] dst_step_x output_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] dst_step_y output_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) + * @param[in] dst_step_z output_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor + * @param[in] mean_ptr Pointer to the mean source tensor. Supported data types: same as @p src_ptr + * @param[in] mean_stride_x Stride of the mean source tensor in X dimension (in bytes) + * @param[in] mean_step_x mean_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] mean_offset_first_element_in_bytes The offset of the first element in the mean source tensor + * @param[in] std_ptr Pointer to the std tensor. Supported data types: same as @p src_ptr + * @param[in] std_stride_x Stride of the std tensor in X dimension (in bytes) + * @param[in] std_step_x std_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] std_offset_first_element_in_bytes The offset of the first element in the var source tensor + */ +__kernel void normalize_planar_yuv_layer_nchw(TENSOR3D_DECLARATION(src), + TENSOR3D_DECLARATION(dst), + VECTOR_DECLARATION(mean), + VECTOR_DECLARATION(std)) +{ + Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src); + Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst); + Vector mean = CONVERT_TO_VECTOR_STRUCT(mean); + Vector std = CONVERT_TO_VECTOR_STRUCT(std); + + const uint current_slice = get_global_id(2) % NUM_CHANNELS; + + const DATA_TYPE curr_mean = *((__global DATA_TYPE *)(mean.ptr + current_slice * mean.stride_x)); + const DATA_TYPE curr_std = *((__global DATA_TYPE *)(std.ptr + current_slice * std.stride_x)); + + TYPE data = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)src.ptr); + TYPE res = (data - curr_mean) / curr_std; + + VSTORE(VEC_SIZE) + (res, 0, (__global DATA_TYPE *)dst.ptr); +} + +/** Apply normalize_planar_yuv layer on tensors with NHWC format. + * + * @note Data type should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float + * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE e.g. -DVEC_SIZE=8 + * + * @param[in] src_ptr Pointer to the first source tensor. Supported data types: F16/F32 + * @param[in] src_stride_x Stride of the first source tensor in X dimension (in bytes) + * @param[in] src_step_x input_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] src_stride_y Stride of the first source tensor in Y dimension (in bytes) + * @param[in] src_step_y input_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] src_stride_z Stride of the first source tensor in Z dimension (in bytes) + * @param[in] src_step_z input_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] src_offset_first_element_in_bytes The offset of the first element in the first source tensor + * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr + * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) + * @param[in] dst_step_x output_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) + * @param[in] dst_step_y output_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) + * @param[in] dst_step_z output_stride_z * number of elements along Z processed per workitem(in bytes) + * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor + * @param[in] mean_ptr Pointer to the mean source tensor. Supported data types: same as @p src_ptr + * @param[in] mean_stride_x Stride of the mean source tensor in X dimension (in bytes) + * @param[in] mean_step_x mean_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] mean_offset_first_element_in_bytes The offset of the first element in the mean source tensor + * @param[in] std_ptr Pointer to the std tensor. Supported data types: same as @p src_ptr + * @param[in] std_stride_x Stride of the std tensor in X dimension (in bytes) + * @param[in] std_step_x std_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] std_offset_first_element_in_bytes The offset of the first element in the var source tensor + */ +__kernel void normalize_planar_yuv_layer_nhwc(TENSOR3D_DECLARATION(src), + TENSOR3D_DECLARATION(dst), + VECTOR_DECLARATION(mean), + VECTOR_DECLARATION(std)) +{ + Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src); + Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst); + Vector mean = CONVERT_TO_VECTOR_STRUCT(mean); + Vector std = CONVERT_TO_VECTOR_STRUCT(std); + + const uint current_slice = get_global_id(0); + + const TYPE curr_mean = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(mean.ptr + current_slice * VEC_SIZE * mean.stride_x)); + const TYPE curr_std = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(std.ptr + current_slice * VEC_SIZE * std.stride_x)); + + TYPE data = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)src.ptr); + TYPE res = (data - curr_mean) / curr_std; + + VSTORE(VEC_SIZE) + (res, 0, (__global DATA_TYPE *)dst.ptr); +} +#endif // defined(DATA_TYPE) && defined(VEC_SIZE) diff --git a/src/core/CL/kernels/CLNormalizePlanarYUVLayerKernel.cpp b/src/core/CL/kernels/CLNormalizePlanarYUVLayerKernel.cpp new file mode 100644 index 0000000000..31451ef422 --- /dev/null +++ b/src/core/CL/kernels/CLNormalizePlanarYUVLayerKernel.cpp @@ -0,0 +1,173 @@ +/* + * Copyright (c) 2018 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/CLNormalizePlanarYUVLayerKernel.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/CLValidate.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/Window.h" + +#include "support/ToolchainSupport.h" + +using namespace arm_compute; + +namespace +{ +Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const ITensorInfo *mean, const ITensorInfo *std) +{ + ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output); + + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, mean, std); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, std); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(mean->num_dimensions() > 1, "mean and std must be vectors"); + + const unsigned int channel_idx = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::CHANNEL); + ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(channel_idx) != mean->dimension(0)); + + // Checks performed when output is configured + if(output->total_size() != 0) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); + } + + return Status{}; +} + +std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, ITensorInfo *mean, ITensorInfo *std) +{ + // Output tensor auto initialization if not yet initialized + auto_init_if_empty(*output, *input->clone()); + + const unsigned int num_elems_processed_per_iteration = 16 / input->element_size(); + + Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration)); + + AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration); + AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration); + + bool window_changed = update_window_and_padding(win, input_access, output_access); + output_access.set_valid_region(win, input->valid_region()); + + if(input->data_layout() == DataLayout::NHWC) + { + AccessWindowHorizontal mean_access(mean, 0, num_elems_processed_per_iteration); + AccessWindowHorizontal std_access(std, 0, num_elems_processed_per_iteration); + window_changed = window_changed || update_window_and_padding(win, mean_access, std_access); + } + + Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; + return std::make_pair(err, win); +} +} // namespace + +CLNormalizePlanarYUVLayerKernel::CLNormalizePlanarYUVLayerKernel() + : _input(nullptr), _output(nullptr), _mean(nullptr), _std(nullptr) +{ +} + +void CLNormalizePlanarYUVLayerKernel::configure(const ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *std) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, mean, std); + + // Output tensor auto initialization if not yet initialized + auto_init_if_empty(*output->info(), *input->info()->clone()); + + // Perform validation step + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), mean->info(), std->info())); + + _input = input; + _output = output; + _mean = mean; + _std = std; + + const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size(); + const unsigned int channel_idx = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::CHANNEL); + + // Set build options + CLBuildOptions build_opts; + build_opts.add_option(("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()))); + build_opts.add_option(("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration))); + build_opts.add_option(("-DNUM_CHANNELS=" + support::cpp11::to_string(input->info()->dimension(channel_idx)))); + + // Create kernel + _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("normalize_planar_yuv_layer_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options())); + + // Configure kernel window + auto win_config = validate_and_configure_window(input->info(), output->info(), mean->info(), std->info()); + ARM_COMPUTE_ERROR_THROW_ON(win_config.first); + ICLKernel::configure_internal(win_config.second); + + // Set config_id for enabling LWS tuning + _config_id = "normalize_planar_yuv_layer_"; + _config_id += lower_string(string_from_data_layout(input->info()->data_layout())); + _config_id += "_"; + _config_id += lower_string(string_from_data_type(input->info()->data_type())); + _config_id += "_"; + _config_id += support::cpp11::to_string(input->info()->dimension(0)); + _config_id += "_"; + _config_id += support::cpp11::to_string(input->info()->dimension(1)); + _config_id += "_"; + _config_id += support::cpp11::to_string(input->info()->dimension(2)); +} + +Status CLNormalizePlanarYUVLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const ITensorInfo *mean, const ITensorInfo *std) +{ + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, mean, std)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get(), mean->clone().get(), std->clone().get()).first); + + return Status{}; +} + +void CLNormalizePlanarYUVLayerKernel::run(const Window &window, cl::CommandQueue &queue) +{ + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); + + Window collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); + Window slice = collapsed.first_slice_window_3D(); + + Window slice_in = collapsed.first_slice_window_1D(); + slice_in.set(Window::DimX, Window::Dimension(0, 0, 0)); + + unsigned int idx = 2 * num_arguments_per_3D_tensor(); + add_1D_tensor_argument(idx, _mean, slice_in); + add_1D_tensor_argument(idx, _std, slice_in); + + do + { + idx = 0; + add_3D_tensor_argument(idx, _input, slice); + add_3D_tensor_argument(idx, _output, slice); + enqueue(queue, *this, slice, lws_hint()); + } + while(collapsed.slide_window_slice_3D(slice)); +} diff --git a/src/core/GLES_COMPUTE/kernels/GCNormalizePlanarYUVLayerKernel.cpp b/src/core/GLES_COMPUTE/kernels/GCNormalizePlanarYUVLayerKernel.cpp index fac29024e3..03463b2552 100644 --- a/src/core/GLES_COMPUTE/kernels/GCNormalizePlanarYUVLayerKernel.cpp +++ b/src/core/GLES_COMPUTE/kernels/GCNormalizePlanarYUVLayerKernel.cpp @@ -36,26 +36,75 @@ using namespace arm_compute; +namespace +{ +Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const ITensorInfo *mean, const ITensorInfo *std) +{ + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16); + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output); + ARM_COMPUTE_RETURN_ERROR_ON(input->data_layout() != DataLayout::NCHW); + + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, mean, std); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, std); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(mean->num_dimensions() > 1, "mean and std must be vectors"); + + const unsigned int channel_idx = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::CHANNEL); + ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(channel_idx) != mean->dimension(0)); + + // Checks performed when output is configured + if(output->total_size() != 0) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); + } + + return Status{}; +} + +std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output, ITensorInfo *mean, ITensorInfo *std) +{ + // Output tensor auto initialization if not yet initialized + auto_init_if_empty(*output, *input->clone()); + + const unsigned int num_elems_processed_per_iteration = 4; + + // Configure kernel window + Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration)); + + AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration); + AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration); + const int mean_padding = ceil_to_multiple(mean->dimension(0), num_elems_processed_per_iteration) - mean->dimension(0); + const int std_padding = ceil_to_multiple(std->dimension(0), num_elems_processed_per_iteration) - std->dimension(0); + AccessWindowStatic mean_access(mean, 0, 0, mean->dimension(0) + mean_padding, mean->dimension(1)); + AccessWindowStatic std_access(std, 0, 0, std->dimension(0) + std_padding, std->dimension(1)); + + const bool window_changed = update_window_and_padding(win, input_access, output_access, mean_access, std_access); + output_access.set_valid_region(win, input->valid_region()); + + Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; + return std::make_pair(err, win); +} +} // namespace + GCNormalizePlanarYUVLayerKernel::GCNormalizePlanarYUVLayerKernel() - : _input(nullptr), _output(nullptr), _mean(nullptr), _sd(nullptr) + : _input(nullptr), _output(nullptr), _mean(nullptr), _std(nullptr) { } -void GCNormalizePlanarYUVLayerKernel::configure(const IGCTensor *input, IGCTensor *output, const IGCTensor *mean, const IGCTensor *sd) +void GCNormalizePlanarYUVLayerKernel::configure(const IGCTensor *input, IGCTensor *output, const IGCTensor *mean, const IGCTensor *std) { - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16); - ARM_COMPUTE_ERROR_ON_NULLPTR(output); - ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output, mean, sd); - ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output); - ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(mean, sd); - ARM_COMPUTE_ERROR_ON(input->info()->dimension(2) != mean->info()->dimension(0)); + ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, mean, std); + + // Output tensor auto initialization if not yet initialized + auto_init_if_empty(*output->info(), *input->info()->clone()); + + // Perform validation step + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), mean->info(), std->info())); _input = input; _output = output; _mean = mean; - _sd = sd; - - const unsigned int num_elems_processed_per_iteration = 4; + _std = std; // Set build options std::set<std::string> build_opts; @@ -67,19 +116,17 @@ void GCNormalizePlanarYUVLayerKernel::configure(const IGCTensor *input, IGCTenso _kernel = static_cast<GCKernel>(GCKernelLibrary::get().create_kernel("normalize_planar_yuv_layer", build_opts)); // Configure kernel window - Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration)); + auto win_config = validate_and_configure_window(input->info(), output->info(), mean->info(), std->info()); + ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config)); - AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration); - AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration); - const int mean_padding = ceil_to_multiple(mean->info()->dimension(0), num_elems_processed_per_iteration) - mean->info()->dimension(0); - const int sd_padding = ceil_to_multiple(sd->info()->dimension(0), num_elems_processed_per_iteration) - sd->info()->dimension(0); - AccessWindowStatic mean_access(mean->info(), 0, 0, mean->info()->dimension(0) + mean_padding, mean->info()->dimension(1)); - AccessWindowStatic sd_access(sd->info(), 0, 0, sd->info()->dimension(0) + sd_padding, sd->info()->dimension(1)); - - update_window_and_padding(win, input_access, output_access, mean_access, sd_access); - output_access.set_valid_region(win, input->info()->valid_region()); + IGCKernel::configure(std::get<1>(win_config)); +} - IGCKernel::configure(win); +Status GCNormalizePlanarYUVLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const ITensorInfo *mean, const ITensorInfo *std) +{ + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, mean, std)); + ARM_COMPUTE_RETURN_ON_ERROR(std::get<0>(validate_and_configure_window(input->clone().get(), output->clone().get(), mean->clone().get(), std->clone().get()))); + return Status{}; } void GCNormalizePlanarYUVLayerKernel::run(const Window &window) @@ -100,7 +147,7 @@ void GCNormalizePlanarYUVLayerKernel::run(const Window &window) unsigned int idx = 2 * num_arguments_per_3D_tensor(); add_1D_tensor_argument(idx, _mean, 3, slice_in); - add_1D_tensor_argument(idx, _sd, 4, slice_in); + add_1D_tensor_argument(idx, _std, 4, slice_in); slice_in = window.first_slice_window_3D(); diff --git a/src/runtime/CL/functions/CLNormalizePlanarYUVLayer.cpp b/src/runtime/CL/functions/CLNormalizePlanarYUVLayer.cpp new file mode 100644 index 0000000000..11d70e31fb --- /dev/null +++ b/src/runtime/CL/functions/CLNormalizePlanarYUVLayer.cpp @@ -0,0 +1,55 @@ +/* + * Copyright (c) 2018 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/runtime/CL/functions/CLNormalizePlanarYUVLayer.h" + +#include "arm_compute/core/Error.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/Validate.h" +#include "arm_compute/runtime/CL/CLScheduler.h" + +namespace arm_compute +{ +CLNormalizePlanarYUVLayer::CLNormalizePlanarYUVLayer() + : _norm_kernel() +{ +} + +void CLNormalizePlanarYUVLayer::configure(const ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *std) +{ + _norm_kernel.configure(input, output, mean, std); +} + +Status CLNormalizePlanarYUVLayer::validate(const ITensorInfo *input, const ITensorInfo *output, + const ITensorInfo *mean, const ITensorInfo *std) +{ + return CLNormalizePlanarYUVLayerKernel::validate(input, output, mean, std); +} + +void CLNormalizePlanarYUVLayer::run() +{ + CLScheduler::get().enqueue(_norm_kernel, true); +} +} // namespace arm_compute diff --git a/src/runtime/GLES_COMPUTE/functions/GCNormalizePlanarYUVLayer.cpp b/src/runtime/GLES_COMPUTE/functions/GCNormalizePlanarYUVLayer.cpp index 5fb971c154..19fdc3d7c0 100755 --- a/src/runtime/GLES_COMPUTE/functions/GCNormalizePlanarYUVLayer.cpp +++ b/src/runtime/GLES_COMPUTE/functions/GCNormalizePlanarYUVLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017 ARM Limited. + * Copyright (c) 2017-2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -37,9 +37,15 @@ GCNormalizePlanarYUVLayer::GCNormalizePlanarYUVLayer() { } -void GCNormalizePlanarYUVLayer::configure(const IGCTensor *input, IGCTensor *output, const IGCTensor *mean, const IGCTensor *sd) +void GCNormalizePlanarYUVLayer::configure(const IGCTensor *input, IGCTensor *output, const IGCTensor *mean, const IGCTensor *std) { - _norm_kernel.configure(input, output, mean, sd); + _norm_kernel.configure(input, output, mean, std); +} + +Status GCNormalizePlanarYUVLayer::validate(const ITensorInfo *input, const ITensorInfo *output, + const ITensorInfo *mean, const ITensorInfo *std) +{ + return GCNormalizePlanarYUVLayerKernel::validate(input, output, mean, std); } void GCNormalizePlanarYUVLayer::run() |