From 79f88e6d825402388bb79fc123ee2dfe01985bda Mon Sep 17 00:00:00 2001 From: Manuel Bottini Date: Wed, 18 Sep 2019 15:02:53 +0100 Subject: COMPMID-2313: Implement CL INSTANCE_NORMALIZATION function Change-Id: If11799bef1bbb973d4287ffc1c6eb4c2a28bbf5f Signed-off-by: Manuel Bottini Reviewed-on: https://review.mlplatform.org/c/1989 Comments-Addressed: Arm Jenkins Tested-by: Arm Jenkins Reviewed-by: Michele Di Giorgio --- src/core/CL/CLKernelLibrary.cpp | 5 + src/core/CL/cl_kernels/instance_normalization.cl | 181 +++++++++++++++++++++ .../kernels/CLInstanceNormalizationLayerKernel.cpp | 150 +++++++++++++++++ 3 files changed, 336 insertions(+) create mode 100644 src/core/CL/cl_kernels/instance_normalization.cl create mode 100644 src/core/CL/kernels/CLInstanceNormalizationLayerKernel.cpp (limited to 'src/core') diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp index 978e35fef6..fa5193fde2 100644 --- a/src/core/CL/CLKernelLibrary.cpp +++ b/src/core/CL/CLKernelLibrary.cpp @@ -371,6 +371,7 @@ const std::map CLKernelLibrary::_kernel_program_map = { "init_level", "optical_flow_pyramid_lk.cl" }, { "init_level_max", "optical_flow_pyramid_lk.cl" }, { "init_level_max_initial_estimate", "optical_flow_pyramid_lk.cl" }, + { "instance_normalization", "instance_normalization.cl" }, { "integral_horizontal", "integral_image.cl" }, { "integral_vertical", "integral_image.cl" }, { "IYUV_to_NV12_bt709", "color_convert.cl" }, @@ -821,6 +822,10 @@ const std::map CLKernelLibrary::_program_source_map = { "im2col.cl", #include "./cl_kernels/im2col.clembed" + }, + { + "instance_normalization.cl", +#include "./cl_kernels/instance_normalization.clembed" }, { "integral_image.cl", diff --git a/src/core/CL/cl_kernels/instance_normalization.cl b/src/core/CL/cl_kernels/instance_normalization.cl new file mode 100644 index 0000000000..699597e8a8 --- /dev/null +++ b/src/core/CL/cl_kernels/instance_normalization.cl @@ -0,0 +1,181 @@ +/* + * 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(GAMMA) && defined(BETA) && defined(EPSILON) && defined(DIM_X) && defined(DIM_Y) && defined(DIM_Z) +/** 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=data_type compile flag, e.g. -DDATA_TYPE=float + * @attention The scale scalar value applied to the normalized tensor should be passed using the -DGAMMA=value compile flag, e.g. -DGAMMA=1.3 + * @attention The offset scalar value applied to the normalized tensor should be passed using the -DBETA=value compile flag, e.g. -DBETA=2.4 + * @attention Normalization epsilon parameter should be given as a preprocessor argument with -DEPSILON=value. e.g. -DEPSILON=0.001f + * @attention Dimensions X, Y, and Z should be given as a preprocessor argument with -DDIM_X=value, -DDIM_Y=value, -DDIM_Z=value. e.g. -DDIM_X=6, -DDIM_Y=2, -DDIM_Z=7 + * + * @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_stride_z Stride of the first source tensor in Z dimension (in bytes) + * @param[in] input_step_z input_stride_z * number of elements along Z 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_stride_z (Optional) Stride of the destination tensor in Z dimension (in bytes) + * @param[in] output_step_z (Optional) output_stride_z * number of elements along Z 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 instance_normalization( + TENSOR4D_DECLARATION(input) +#ifndef IN_PLACE + , + TENSOR4D_DECLARATION(output) +#endif /* IN_PLACE */ +) +{ + DATA_TYPE sum = 0.f; + DATA_TYPE sum_sq = 0.f; + +#if defined(NHWC) + + const int pc = get_global_id(0); + const int pn = get_global_id(2); + const int elements_plane = DIM_Y * DIM_Z; + const int elements_x_y = DIM_X * DIM_Y; + const int elements_x_y_z = DIM_X * DIM_Y * DIM_Z; + + for(int i_w = 0; i_w < DIM_Y; ++i_w) + { + for(int i_h = 0; i_h < DIM_Z; ++i_h) + { + DATA_TYPE data = *((__global DATA_TYPE *)input_ptr + pc + i_w * DIM_X + i_h * elements_x_y + pn * elements_x_y_z); + sum += data; + sum_sq += data * data; + } + } + +#else // !defined(NHWC) + const int elements_plane = DIM_X * DIM_Y; + const int plane_address = get_global_id(2) * elements_plane; + int i = 0; + + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + part_sum = 0.f; + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + part_sum_sq = 0.f; + // Calculate partial sum + for(; i <= (elements_plane - VEC_SIZE); i += VEC_SIZE) + { + // Load data + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + data = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)input_ptr + i + plane_address); + part_sum += data; + part_sum_sq += data * data; + } + // Perform reduction +#if VEC_SIZE > 8 + part_sum.s01234567 += part_sum.s89abcdef; + part_sum_sq.s01234567 += part_sum_sq.s89abcdef; +#endif // VEC_SIZE > 8 +#if VEC_SIZE > 4 + part_sum.s0123 += part_sum.s4567; + part_sum_sq.s0123 += part_sum_sq.s4567; +#endif // VEC_SIZE > 4 +#if VEC_SIZE > 2 + part_sum.s01 += part_sum.s23; + part_sum_sq.s01 += part_sum_sq.s23; +#endif // VEC_SIZE > 2 + part_sum.s0 += part_sum.s1; + part_sum_sq.s0 += part_sum_sq.s1; + // Left-overs loop + for(; i < elements_plane; ++i) + { + DATA_TYPE data = *((__global DATA_TYPE *)input_ptr + i + plane_address); + part_sum.s0 += data; + part_sum_sq.s0 += data * data; + } + + sum = part_sum.s0; + sum_sq = part_sum_sq.s0; + +#endif // defined(NHWC) + + const DATA_TYPE mean_float = ((float)sum / elements_plane); + const DATA_TYPE mean = (DATA_TYPE)mean_float; + const float var_float = ((float)sum_sq / elements_plane) - (mean_float * mean_float); + const float multip_float = GAMMA / sqrt(var_float + EPSILON); + const DATA_TYPE multip = (DATA_TYPE)multip_float; + +#if defined(NHWC) + + for(int i_w = 0; i_w < DIM_Y; ++i_w) + { + for(int i_h = 0; i_h < DIM_Z; ++i_h) + { + __global DATA_TYPE *input_address = (__global DATA_TYPE *)input_ptr + pc + i_w * DIM_X + i_h * elements_x_y + pn * elements_x_y_z; +#ifdef IN_PLACE + __global DATA_TYPE *output_address = input_address; +#else /* !IN_PLACE */ + __global DATA_TYPE *output_address = (__global DATA_TYPE *)output_ptr + pc + i_w * DIM_X + i_h * elements_x_y + pn * elements_x_y_z; +#endif /* IN_PLACE */ + *(output_address) = (*(input_address) - mean) * multip + (DATA_TYPE)BETA; + } + } + +#else // !defined(NHWC) + i = 0; + for(; i <= (elements_plane - VEC_SIZE); i += VEC_SIZE) + { + __global DATA_TYPE *input_address = (__global DATA_TYPE *)input_ptr + i + plane_address; +#ifdef IN_PLACE + __global DATA_TYPE *output_address = input_address; +#else /* !IN_PLACE */ + __global DATA_TYPE *output_address = (__global DATA_TYPE *)output_ptr + i + plane_address; +#endif /* IN_PLACE */ + + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + data = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)input_address); + + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + res = (data - mean) * multip + (DATA_TYPE)BETA; + VSTORE(VEC_SIZE) + (res, 0, (__global DATA_TYPE *)output_address); + } + for(; i < elements_plane; ++i) + { + __global DATA_TYPE *input_address = (__global DATA_TYPE *)input_ptr + i + plane_address; +#ifdef IN_PLACE + __global DATA_TYPE *output_address = input_address; +#else /* !IN_PLACE */ + __global DATA_TYPE *output_address = (__global DATA_TYPE *)output_ptr + i + plane_address; +#endif /* IN_PLACE */ + *(output_address) = (*(input_address) - mean) * multip + (DATA_TYPE)BETA; + } +#endif // defined(NHWC) +} +#endif /* defined(VEC_SIZE) && defined(DATA_TYPE) && defined(GAMMA) && defined(BETA) && defined(EPSILON) && defined(DIM_X) && defined(DIM_Y) && defined(DIM_Z) */ diff --git a/src/core/CL/kernels/CLInstanceNormalizationLayerKernel.cpp b/src/core/CL/kernels/CLInstanceNormalizationLayerKernel.cpp new file mode 100644 index 0000000000..a03322b61d --- /dev/null +++ b/src/core/CL/kernels/CLInstanceNormalizationLayerKernel.cpp @@ -0,0 +1,150 @@ +/* + * 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/CLInstanceNormalizationLayerKernel.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" + +namespace arm_compute +{ +namespace +{ +Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, float gamma, float beta, float epsilon) +{ + ARM_COMPUTE_UNUSED(gamma); + ARM_COMPUTE_UNUSED(beta); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(epsilon == 0.f, "Epsilon must be different than 0"); + + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32); + + 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); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output); + } + + return Status{}; +} + +std::tuple validate_and_configure_window(ITensorInfo *input, ITensorInfo *output) +{ + // We handle the planes manually + Window win = calculate_max_window(*input, Steps(1)); + + // Output auto initialization if not yet initialized + auto_init_if_empty(*output, input->tensor_shape(), 1, input->data_type()); + + // CLInstanceNormalizationLayerKernel doesn't need padding so update_window_and_padding() can be skipped + Coordinates coord; + coord.set_num_dimensions(output->num_dimensions()); + output->set_valid_region(ValidRegion(coord, output->tensor_shape())); + return std::make_pair(Status{}, win); +} +} // namespace + +CLInstanceNormalizationLayerKernel::CLInstanceNormalizationLayerKernel() + : _input(nullptr), _output(nullptr), _gamma(1), _beta(0), _epsilon(1e-12), _run_in_place(false) +{ +} + +void CLInstanceNormalizationLayerKernel::configure(ICLTensor *input, ICLTensor *output, float gamma, float beta, float epsilon) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input); + + _input = input; + _output = output == nullptr ? input : output; + _gamma = gamma; + _beta = beta; + _epsilon = epsilon; + + _run_in_place = (output == nullptr) || (output == input); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(_input->info(), _output->info(), gamma, beta, epsilon)); + const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size(); + + 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("-DDIM_X=" + support::cpp11::to_string(input->info()->dimension(0))); + build_opts.add_option("-DDIM_Y=" + support::cpp11::to_string(input->info()->dimension(1))); + build_opts.add_option("-DDIM_Z=" + support::cpp11::to_string(input->info()->dimension(2))); + build_opts.add_option("-DGAMMA=" + float_to_string_with_full_precision(gamma)); + build_opts.add_option("-DBETA=" + float_to_string_with_full_precision(beta)); + build_opts.add_option("-DEPSILON=" + float_to_string_with_full_precision(epsilon)); + build_opts.add_option_if(_run_in_place, "-DIN_PLACE"); + build_opts.add_option_if(_input->info()->data_layout() == DataLayout::NHWC, "-DNHWC"); + + // Create kernel + _kernel = static_cast(CLKernelLibrary::get().create_kernel("instance_normalization", build_opts.options())); + + // Configure kernel window + auto win_config = validate_and_configure_window(_input->info(), _output->info()); + ARM_COMPUTE_ERROR_THROW_ON(std::get<0>(win_config)); + ICLKernel::configure_internal(std::get<1>(win_config)); +} + +Status CLInstanceNormalizationLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, float gamma, float beta, float epsilon) +{ + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, gamma, beta, epsilon)); + ARM_COMPUTE_RETURN_ON_ERROR(std::get<0>(validate_and_configure_window(input->clone().get(), (output == nullptr ? input->clone().get() : output->clone().get())))); + return Status{}; +} + +void CLInstanceNormalizationLayerKernel::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 = window.collapse(window, Window::DimZ); + + // We will process the planes together + if(_input->info()->data_layout() == DataLayout::NCHW) + { + collapsed_window.set(Window::DimX, Window::Dimension(0, 1, 1)); + collapsed_window.set(Window::DimY, Window::Dimension(0, 1, 1)); + } + else + { + collapsed_window.set(Window::DimY, Window::Dimension(0, 1, 1)); + collapsed_window.set(Window::DimZ, Window::Dimension(0, _input->info()->dimension(3), 1)); + } + + unsigned int idx = 0; + add_4D_tensor_argument(idx, _input, collapsed_window); + if(!_run_in_place) + { + add_4D_tensor_argument(idx, _output, collapsed_window); + } + + enqueue(queue, *this, collapsed_window, lws_hint()); +} +} // namespace arm_compute \ No newline at end of file -- cgit v1.2.1