From 5b48ad7d43c3d1c2fdbae64beac3f37bc6697338 Mon Sep 17 00:00:00 2001 From: Michele Di Giorgio Date: Tue, 4 Jun 2019 18:43:35 +0100 Subject: COMPMID-2386: Add support for CLMeanStdNormalizationLayer Change-Id: I0323b2410b222fd08933da22de455e798a60a0b1 Signed-off-by: Michele Di Giorgio Reviewed-on: https://review.mlplatform.org/c/1297 Comments-Addressed: Arm Jenkins Reviewed-by: Gian Marco Iodice Tested-by: Arm Jenkins --- src/core/CL/CLKernelLibrary.cpp | 5 + .../CL/cl_kernels/mean_stddev_normalization.cl | 124 +++++++++++++++++ .../CL/kernels/CLMeanStdDevNormalizationKernel.cpp | 151 +++++++++++++++++++++ 3 files changed, 280 insertions(+) create mode 100644 src/core/CL/cl_kernels/mean_stddev_normalization.cl create mode 100644 src/core/CL/kernels/CLMeanStdDevNormalizationKernel.cpp (limited to 'src/core') diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp index b734fd291c..51acd9f339 100644 --- a/src/core/CL/CLKernelLibrary.cpp +++ b/src/core/CL/CLKernelLibrary.cpp @@ -379,6 +379,7 @@ const std::map CLKernelLibrary::_kernel_program_map = { "lktracker_stage1", "optical_flow_pyramid_lk.cl" }, { "magnitude_phase", "magnitude_phase.cl" }, { "mean_stddev_accumulate", "mean_stddev.cl" }, + { "mean_stddev_normalization", "mean_stddev_normalization.cl" }, { "memset", "memset.cl" }, { "minmax", "minmaxloc.cl" }, { "minmax_border", "minmaxloc.cl" }, @@ -816,6 +817,10 @@ const std::map CLKernelLibrary::_program_source_map = { "mean_stddev.cl", #include "./cl_kernels/mean_stddev.clembed" + }, + { + "mean_stddev_normalization.cl", +#include "./cl_kernels/mean_stddev_normalization.clembed" }, { "memset.cl", diff --git a/src/core/CL/cl_kernels/mean_stddev_normalization.cl b/src/core/CL/cl_kernels/mean_stddev_normalization.cl new file mode 100644 index 0000000000..9667737c65 --- /dev/null +++ b/src/core/CL/cl_kernels/mean_stddev_normalization.cl @@ -0,0 +1,124 @@ +/* + * Copyright (c) 2019 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(VEC_SIZE) && defined(DATA_TYPE) && defined(EPSILON) && defined(WIDTH) +/** This function normalizes the input 2D tensor across the first dimension with respect to mean and standard deviation of the same dimension. + * + * @attention Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16 + * @attention Data type should be passed using the -DDATA_TYPE compile flag, e.g. -DDATA_TYPE=float + * @attention Width of the input tensor should be passed using the -DWIDTH compile flag, e.g. -DWIDTH=16 + * @attention Normalization epsilon parameter should be given as a preprocessor argument with -DEPSILON=value. e.g. -DEPSILON=0.001f + * + * @param[in] input_ptr Pointer to the first source tensor. Supported data types: F16/F32 + * @param[in] input_stride_x Stride of the first source tensor in X dimension (in bytes) + * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] input_stride_y Stride of the first source tensor in Y dimension (in bytes) + * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] input_offset_first_element_in_bytes The offset of the first element in the first source tensor + * @param[out] output_ptr (Optional) Pointer to the destination tensor. Supported data types: same as @p input_ptr + * @param[in] output_stride_x (Optional) Stride of the destination tensor in X dimension (in bytes) + * @param[in] output_step_x (Optional) output_stride_x * number of elements along X processed per workitem(in bytes) + * @param[in] output_stride_y (Optional) Stride of the destination tensor in Y dimension (in bytes) + * @param[in] output_step_y (Optional) output_stride_y * number of elements along Y processed per workitem(in bytes) + * @param[in] output_offset_first_element_in_bytes (Optional) The offset of the first element in the destination tensor + */ +__kernel void mean_stddev_normalization( + IMAGE_DECLARATION(input) +#ifndef IN_PLACE + , + IMAGE_DECLARATION(output) +#endif /* IN_PLACE */ +) +{ + // Get pixels pointer + Image in = CONVERT_TO_IMAGE_STRUCT(input); +#ifdef IN_PLACE + Image out = in; +#else /* IN_PLACE */ + Image out = CONVERT_TO_IMAGE_STRUCT(output); +#endif /* IN_PLACE */ + + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + sum = 0.f; + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + sum_sq = 0.f; + // Calculate partial sum + int i = 0; + for(; i <= (WIDTH - VEC_SIZE); i += VEC_SIZE) + { + // Load data + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + data = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)offset(&in, i, 0)); + + sum += data; + sum_sq += data * data; + } + // Perform reduction +#if VEC_SIZE > 8 + sum.s01234567 += sum.s89abcdef; + sum_sq.s01234567 += sum_sq.s89abcdef; +#endif // VEC_SIZE > 8 +#if VEC_SIZE > 4 + sum.s0123 += sum.s4567; + sum_sq.s0123 += sum_sq.s4567; +#endif // VEC_SIZE > 4 +#if VEC_SIZE > 2 + sum.s01 += sum.s23; + sum_sq.s01 += sum_sq.s23; +#endif // VEC_SIZE > 2 + sum.s0 += sum.s1; + sum_sq.s0 += sum_sq.s1; + // Left-overs loop + for(; i < WIDTH; ++i) + { + DATA_TYPE data = *((__global DATA_TYPE *)offset(&in, i, 0)); + + sum.s0 += data; + sum_sq.s0 += data * data; + } + + DATA_TYPE mean = sum.s0 / WIDTH; + DATA_TYPE var = (sum_sq.s0 / WIDTH) - (mean * mean); + DATA_TYPE stddev_inv = 1.f / sqrt(var + EPSILON); + + i = 0; + for(; i <= (WIDTH - VEC_SIZE); i += VEC_SIZE) + { + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + data = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)offset(&in, i, 0)); + + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + res = (data - mean) * stddev_inv; + VSTORE(VEC_SIZE) + (res, 0, (__global DATA_TYPE *)offset(&out, i, 0)); + } + for(; i < WIDTH; ++i) + { + DATA_TYPE data = *((__global DATA_TYPE *)offset(&in, i, 0)); + + *((__global DATA_TYPE *)offset(&out, i, 0)) = (data - mean) * stddev_inv; + } +} +#endif /* defined(VEC_SIZE) && defined(DATA_TYPE) && defined(EPSILON) && defined(WIDTH) */ diff --git a/src/core/CL/kernels/CLMeanStdDevNormalizationKernel.cpp b/src/core/CL/kernels/CLMeanStdDevNormalizationKernel.cpp new file mode 100644 index 0000000000..a9baf24fa6 --- /dev/null +++ b/src/core/CL/kernels/CLMeanStdDevNormalizationKernel.cpp @@ -0,0 +1,151 @@ +/* + * Copyright (c) 2019 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/CLMeanStdDevNormalizationKernel.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/CL/OpenCL.h" +#include "arm_compute/core/Error.h" +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/Window.h" + +namespace arm_compute +{ +namespace +{ +Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, float epsilon) +{ + ARM_COMPUTE_UNUSED(epsilon); + ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_dimensions() > 2, "Input tensor cannot have more than 2 dimensions"); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32); + + // Checks performed when output is configured + if((output != nullptr) && (output->total_size() != 0)) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + } + return Status{}; +} + +std::pair validate_and_configure_window(ITensorInfo *input, ITensorInfo *output) +{ + if(output != nullptr) + { + ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); + // Output auto inizialitation if not yet initialized + auto_init_if_empty(*output, *input); + } + + const unsigned int num_elems_processed_per_iteration = 16 / input->element_size(); + + // This kernel doesn't need padding + Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration)); + if(output != nullptr) + { + output->set_valid_region(ValidRegion(Coordinates(), output->tensor_shape())); + } + + return std::make_pair(Status{}, win); +} +} // namespace + +CLMeanStdDevNormalizationKernel::CLMeanStdDevNormalizationKernel() + : _input(nullptr), _output(nullptr), _run_in_place(false) +{ +} + +void CLMeanStdDevNormalizationKernel::configure(ICLTensor *input, ICLTensor *output, float epsilon) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input); + + _run_in_place = (output == nullptr) || (output == input); + + ARM_COMPUTE_ERROR_THROW_ON(CLMeanStdDevNormalizationKernel::validate(input->info(), (output != nullptr) ? output->info() : nullptr, epsilon)); + + _input = input; + _output = output; + + const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size(); + + // 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("-DEPSILON=" + float_to_string_with_full_precision(epsilon)); + build_opts.add_option("-DWIDTH=" + support::cpp11::to_string(input->info()->dimension(0))); + build_opts.add_option_if(_run_in_place, "-DIN_PLACE"); + + // Create kernel + _kernel = static_cast(CLKernelLibrary::get().create_kernel("mean_stddev_normalization", build_opts.options())); + + // Configure kernel window + auto win_config = validate_and_configure_window(input->info(), (_run_in_place) ? nullptr : output->info()); + ARM_COMPUTE_ERROR_THROW_ON(win_config.first); + ICLKernel::configure_internal(win_config.second); + + // Set config_id for enabling LWS tuning + _config_id = "mean_stddev_normalization_layer_"; + _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)); +} + +Status CLMeanStdDevNormalizationKernel::validate(const ITensorInfo *input, const ITensorInfo *output, float epsilon) +{ + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, epsilon)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), (output != nullptr) ? output->clone().get() : nullptr).first); + return Status{}; +} + +void CLMeanStdDevNormalizationKernel::run(const Window &window, cl::CommandQueue &queue) +{ + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); + + Window slice = window.first_slice_window_2D(); + // Set slice step equal to width to force gws[0] to 1, as each thread normalizes across all rows + slice.set_dimension_step(Window::DimX, _input->info()->dimension(0)); + + do + { + unsigned int idx = 0; + add_2D_tensor_argument(idx, _input, slice); + if(!_run_in_place) + { + add_2D_tensor_argument(idx, _output, slice); + } + enqueue(queue, *this, slice, lws_hint()); + } + while(window.slide_window_slice_2D(slice)); +} +} // namespace arm_compute -- cgit v1.2.1