diff options
Diffstat (limited to 'src/core/CL/cl_kernels/instance_normalization.cl')
| -rw-r--r-- | src/core/CL/cl_kernels/instance_normalization.cl | 254 |
1 files changed, 0 insertions, 254 deletions
diff --git a/src/core/CL/cl_kernels/instance_normalization.cl b/src/core/CL/cl_kernels/instance_normalization.cl deleted file mode 100644 index adfbebd67d..0000000000 --- a/src/core/CL/cl_kernels/instance_normalization.cl +++ /dev/null @@ -1,254 +0,0 @@ -/* - * Copyright (c) 2019-2021 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(INTERNAL_DATA_TYPE) & defined(DIM_X) && defined(DIM_Y) && defined(DIM_Z) -/** This function computes the mean and variance of each plane of the input tensor and provides it as output. - * - * @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 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_stride_w Stride of the source tensor in W dimension (in bytes) - * @param[in] input_step_w input_stride_w * number of elements along W 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 compute_mean_var( - TENSOR4D_DECLARATION(input), - TENSOR3D_DECLARATION(output)) -{ - Tensor4D in = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(input, 0); - Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(output); - -#if defined(NHWC) - const int ch = get_global_id(0); // Current channel - const int batch = get_global_id(1); // Current batch - const int elements_plane = DIM_Y * DIM_Z; - INTERNAL_DATA_TYPE part_sum = 0.f; - INTERNAL_DATA_TYPE part_sum_sq = 0.f; - const int in_offset = input_offset_first_element_in_bytes + batch * input_stride_w + ch * sizeof(DATA_TYPE); - - for(int i_w = 0; i_w < DIM_Y; ++i_w) - { - for(int i_h = 0; i_h < DIM_Z; ++i_h) - { - INTERNAL_DATA_TYPE data = (INTERNAL_DATA_TYPE) * ((__global DATA_TYPE *)tensor4D_offset(&in, ch, i_w, i_h, batch)); - part_sum += data; - part_sum_sq += data * data; - } - } - - INTERNAL_DATA_TYPE mean = (part_sum / elements_plane); - INTERNAL_DATA_TYPE var = (part_sum_sq / elements_plane) - (mean * mean); - __global INTERNAL_DATA_TYPE *output_address0 = (__global INTERNAL_DATA_TYPE *)tensor3D_offset(&out, ch, 0, batch); - *output_address0 = mean; - __global INTERNAL_DATA_TYPE *output_address1 = (__global INTERNAL_DATA_TYPE *)tensor3D_offset(&out, ch, 1, batch); - *output_address1 = var; -#else // !defined(NHWC) - const int ch = get_global_id(2) % DIM_Z; // Current channel - const int batch = get_global_id(2) / DIM_Z; // Current batch - const int elements_plane = DIM_X * DIM_Y; - - VEC_DATA_TYPE(INTERNAL_DATA_TYPE, VEC_SIZE) - part_sum = 0.f; - VEC_DATA_TYPE(INTERNAL_DATA_TYPE, VEC_SIZE) - part_sum_sq = 0.f; - // Calculate partial sum - for(int y = 0; y < DIM_Y; ++y) - { - int x = 0; - for(; x <= (DIM_X - VEC_SIZE); x += VEC_SIZE) - { - // Load data - VEC_DATA_TYPE(INTERNAL_DATA_TYPE, VEC_SIZE) - data = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)tensor4D_offset(&in, x, y, ch, batch)), VEC_DATA_TYPE(INTERNAL_DATA_TYPE, VEC_SIZE)); - part_sum += data; - part_sum_sq += data * data; - } - // Left-overs loop - for(; x < DIM_X; ++x) - { - INTERNAL_DATA_TYPE data = (INTERNAL_DATA_TYPE)(*((__global DATA_TYPE *)tensor4D_offset(&in, x, y, ch, batch))); - part_sum.s0 += data; - part_sum_sq.s0 += 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; - - INTERNAL_DATA_TYPE sum = (INTERNAL_DATA_TYPE)part_sum.s0; - INTERNAL_DATA_TYPE sum_sq = (INTERNAL_DATA_TYPE)part_sum_sq.s0; - - const INTERNAL_DATA_TYPE mean = (sum / elements_plane); - const INTERNAL_DATA_TYPE var = (sum_sq / elements_plane) - (mean * mean); - - __global INTERNAL_DATA_TYPE *output_address0 = (__global INTERNAL_DATA_TYPE *)tensor3D_offset(&out, ch, 0, batch); - *output_address0 = mean; - __global INTERNAL_DATA_TYPE *output_address1 = (__global INTERNAL_DATA_TYPE *)tensor3D_offset(&out, ch, 1, batch); - *output_address1 = var; - -#endif // defined(NHWC) -} -#endif /* defined(VEC_SIZE) && defined(DATA_TYPE) && defined(DIM_X) && defined(DIM_Y) && defined(DIM_Z) */ - -#if defined(VEC_SIZE) && defined(DATA_TYPE) && defined(INTERNAL_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), - TENSOR3D_DECLARATION(mean_var) -#ifndef IN_PLACE - , - TENSOR4D_DECLARATION(output) -#endif /* IN_PLACE */ -) -{ - Tensor4D in = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(input, 0); - Tensor3D mean_var = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(mean_var); -#ifndef IN_PLACE - Tensor4D out = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(output, 0); -#endif /* IN_PLACE */ - -#if defined(NHWC) - const int ch = get_global_id(0); // Current channel - const int batch = get_global_id(2); // Current batch -#else /* defined(NHWC) */ - const int ch = get_global_id(2) % DIM_Z; // Current channel - const int batch = get_global_id(2) / DIM_Z; // Current batch -#endif /* defined(NHWC) */ - - const __global INTERNAL_DATA_TYPE *mean_ptr = (__global INTERNAL_DATA_TYPE *)tensor3D_offset(&mean_var, ch, 0, batch); - const __global INTERNAL_DATA_TYPE *var_ptr = (__global INTERNAL_DATA_TYPE *)tensor3D_offset(&mean_var, ch, 1, batch); - const INTERNAL_DATA_TYPE mean = (INTERNAL_DATA_TYPE) * mean_ptr; - const INTERNAL_DATA_TYPE var = (INTERNAL_DATA_TYPE) * var_ptr; - const INTERNAL_DATA_TYPE multip = GAMMA / sqrt(var + EPSILON); - const INTERNAL_DATA_TYPE beta = (INTERNAL_DATA_TYPE)BETA; - -#if defined(NHWC) - const int in_offset = input_offset_first_element_in_bytes + batch * input_stride_w + ch * sizeof(DATA_TYPE); -#ifndef IN_PLACE - const int out_offset = output_offset_first_element_in_bytes + batch * input_stride_w + ch * sizeof(DATA_TYPE); -#endif /* IN_PLACE */ - - 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 *)tensor4D_offset(&in, ch, i_w, i_h, batch); -#ifdef IN_PLACE - __global DATA_TYPE *output_address = input_address; -#else /* !IN_PLACE */ - __global DATA_TYPE *output_address = (__global DATA_TYPE *)tensor4D_offset(&out, ch, i_w, i_h, batch); -#endif /* IN_PLACE */ - *(output_address) = (*(input_address) - mean) * multip + (INTERNAL_DATA_TYPE)BETA; - } - } -#else // !defined(NHWC) - for(int y = 0; y < DIM_Y; ++y) - { - int x = 0; - for(; x <= (DIM_X - VEC_SIZE); x += VEC_SIZE) - { - __global DATA_TYPE *input_address = (__global DATA_TYPE *)tensor4D_offset(&in, x, y, ch, batch); -#ifdef IN_PLACE - __global DATA_TYPE *output_address = input_address; -#else /* !IN_PLACE */ - __global DATA_TYPE *output_address = (__global DATA_TYPE *)tensor4D_offset(&out, x, y, ch, batch); -#endif /* IN_PLACE */ - - VEC_DATA_TYPE(INTERNAL_DATA_TYPE, VEC_SIZE) - data = CONVERT(VLOAD(VEC_SIZE)(0, input_address), VEC_DATA_TYPE(INTERNAL_DATA_TYPE, VEC_SIZE)); - - VEC_DATA_TYPE(INTERNAL_DATA_TYPE, VEC_SIZE) - res = (data - mean) * multip + (INTERNAL_DATA_TYPE)BETA; - VSTORE(VEC_SIZE) - (CONVERT(res, VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)), 0, output_address); - } - // Left-overs loop - for(; x < DIM_X; ++x) - { - __global DATA_TYPE *input_address = (__global DATA_TYPE *)tensor4D_offset(&in, x, y, ch, batch); -#ifdef IN_PLACE - __global DATA_TYPE *output_address = input_address; -#else /* !IN_PLACE */ - __global DATA_TYPE *output_address = (__global DATA_TYPE *)tensor4D_offset(&out, x, y, ch, batch); -#endif /* IN_PLACE */ - *(output_address) = (*(input_address) - mean) * multip + (INTERNAL_DATA_TYPE)BETA; - } - } -#endif // defined(NHWC) -} -#endif /* defined(VEC_SIZE) && defined(DATA_TYPE) && defined(INTERNAL_DATA_TYPE) && defined(GAMMA) && defined(BETA) && defined(EPSILON) && defined(DIM_X) && defined(DIM_Y) && defined(DIM_Z) */ |