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/*
* Copyright (c) 2017-2018 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"
#define MUL_OP(x, y) ((x) * (y))
#define ADD_OP(x, y) ((x) + (y))
#define DIV_OP(x, y) ((x) / (y))
#define POW_OP(x, y) pow((x), (y))
#define SQCVT_SAT(a) (a)
#define LOAD_OP(offset, ptr) vload4(offset, ptr)
#define STORE_OP(data, offset, ptr) vstore4(data, offset, ptr)
#if defined(NUM_SLICES)
/** Apply cross-map normalization.
*
* @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short
* @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size, e.g. -DVEC_SIZE=16
* @note The radius should be given as a preprocessor argument using -DRADIUS=size. e.g. -DRADIUS=5
* @note The number of slices should be given as a preprocessor argument using -DNUM_SLICES=size. e.g. -DNUM_SLICES=192
* @note Scaling coefficient (= alpha/norm_size), beta and kappa need to be passed at compile time using -DCOEFF, -DALPHA and -DKAPPA
*
* @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 Pointer to the destination tensor. Supported data types: same as @p input_ptr
* @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes)
* @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes)
* @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] output_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] output_step_z output_stride_z * number of elements along Z processed per workitem(in bytes)
* @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination tensor
*/
__kernel void normalization_layer_cross_map(TENSOR3D_DECLARATION(input),
TENSOR3D_DECLARATION(output))
{
Tensor3D in = CONVERT_TO_TENSOR3D_STRUCT(input);
Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output);
VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
acc = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))0;
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
coeff_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(COEFF);
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
beta_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(BETA);
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
kappa_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(KAPPA);
const int current_slice = get_global_id(2);
const int left_slice = max(-(int)RADIUS, -current_slice);
const int right_slice = min((int)RADIUS, (int)NUM_SLICES - 1 - current_slice);
for(int i = left_slice; i <= right_slice; i++)
{
VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
values = LOAD_OP(0, (__global DATA_TYPE *)tensor3D_offset(&in, 0, 0, i));
acc = ADD_OP(acc, MUL_OP(values, values));
}
acc = ADD_OP(MUL_OP(acc, coeff_v), kappa_v);
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
normalized = POW_OP(acc, beta_v);
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
normalized_pixel = DIV_OP(LOAD_OP(0, (__global DATA_TYPE *)in.ptr), normalized);
STORE_OP(normalized_pixel, 0, (__global DATA_TYPE *)out.ptr);
}
#endif /* defined(NUM_SLICES) */
#if defined(WIDTH_SIZE)
/** Apply in-map normalization when tensors are in the NCHW data layout format.
*
* @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short
* @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size, e.g. -DVEC_SIZE=16
* @note The radius should be given as a preprocessor argument using -DRADIUS=size. e.g. -DRADIUS=5
* @note Scaling coefficient (= alpha/norm_size), beta and kappa need to be passed at compile time using -DCOEFF, -DALPHA and -DKAPPA
*
* @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 Pointer to the destination tensor. Supported data types: same as @p input_ptr
* @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes)
* @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] output_stride_y Stride of the first destination tensor in Y dimension (in bytes)
* @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] output_stride_z Stride of the first source tensor in Z dimension (in bytes)
* @param[in] output_step_z output_stride_z * number of elements along Z processed per workitem(in bytes)
* @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination tensor
*/
__kernel void normalization_layer_in_map_nchw(TENSOR3D_DECLARATION(input),
TENSOR3D_DECLARATION(output))
{
Tensor3D in = CONVERT_TO_TENSOR3D_STRUCT(input);
Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output);
VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
acc = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))0;
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
coeff_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(COEFF);
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
beta_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(BETA);
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
kappa_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(KAPPA);
const int current_col = get_global_id(0) << 2;
const int left_pos = max(-(int)RADIUS, -3 - current_col);
const int right_pos = min((int)RADIUS, (int)WIDTH_SIZE - 1 - current_col);
#if defined(IN_MAP_2D)
const int current_row = get_global_id(1);
const int first_row = max(-(int)RADIUS, -current_row);
const int last_row = min((int)RADIUS, (int)get_global_size(1) - 1 - current_row);
#endif /* defined(IN_MAP_2D) */
#if defined(IN_MAP_2D)
for(int j = first_row; j <= last_row; ++j)
{
#endif /* defined(IN_MAP_2D) */
for(int i = left_pos; i <= right_pos; ++i)
{
#if defined(IN_MAP_2D)
VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
values = LOAD_OP(0, (__global DATA_TYPE *)tensor3D_offset(&in, i, j, 0));
#else /* defined(IN_MAP_2D) */
VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
values = LOAD_OP(0, (__global DATA_TYPE *)tensor3D_offset(&in, i, 0, 0));
#endif /* defined(IN_MAP_2D) */
acc = ADD_OP(acc, MUL_OP(values, values));
}
#if defined(IN_MAP_2D)
}
#endif /* defined(IN_MAP_2D) */
acc = ADD_OP(MUL_OP(acc, coeff_v), kappa_v);
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
normalized = POW_OP(acc, beta_v);
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
normalized_pixel = DIV_OP(LOAD_OP(0, (__global DATA_TYPE *)in.ptr), normalized);
STORE_OP(normalized_pixel, 0, (__global DATA_TYPE *)out.ptr);
}
#endif // defined(WIDTH_SIZE)
#if defined(NUM_SLICES)
/** Apply in-map normalization when tensors are in the NHWC data layout format.
*
* @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short
* @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size, e.g. -DVEC_SIZE=16
* @note The radius should be given as a preprocessor argument using -DRADIUS=size. e.g. -DRADIUS=5
* @note The number of slices should be given as a preprocessor argument using -DNUM_SLICES=size. e.g. -DNUM_SLICES=192
* @note Scaling coefficient (= alpha/norm_size), beta and kappa need to be passed at compile time using -DCOEFF, -DALPHA and -DKAPPA
*
* @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 Pointer to the destination tensor. Supported data types: same as @p input_ptr
* @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes)
* @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] output_stride_y Stride of the first destination tensor in Y dimension (in bytes)
* @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] output_stride_z Stride of the first source tensor in Z dimension (in bytes)
* @param[in] output_step_z output_stride_z * number of elements along Z processed per workitem(in bytes)
* @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination tensor
*/
__kernel void normalization_layer_in_map_nhwc(TENSOR3D_DECLARATION(input),
TENSOR3D_DECLARATION(output))
{
Tensor3D in = CONVERT_TO_TENSOR3D_STRUCT(input);
Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output);
VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
acc = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))0;
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
coeff_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(COEFF);
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
beta_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(BETA);
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
kappa_v = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))SQCVT_SAT(KAPPA);
const int current_cols = get_global_id(1);
const int first_col = max(-(int)RADIUS, -current_cols);
const int last_col = min((int)RADIUS, (int)get_global_size(1) - 1 - current_cols);
#if defined(IN_MAP_2D)
const int current_rows = get_global_id(2);
const int first_row = max(-(int)RADIUS, -current_rows);
const int last_row = min((int)RADIUS, (int)NUM_SLICES - 1 - current_rows);
#endif /* defined(IN_MAP_2D) */
#if defined(IN_MAP_2D)
for(int j = first_row; j <= last_row; ++j)
{
#endif /* defined(IN_MAP_2D) */
for(int i = first_col; i <= last_col; ++i)
{
#if defined(IN_MAP_2D)
VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
values = LOAD_OP(0, (__global DATA_TYPE *)tensor3D_offset(&in, 0, i, j));
#else /* defined(IN_MAP_2D) */
VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
values = LOAD_OP(0, (__global DATA_TYPE *)tensor3D_offset(&in, 0, i, 0));
#endif /* defined(IN_MAP_2D) */
acc = ADD_OP(acc, MUL_OP(values, values));
}
#if defined(IN_MAP_2D)
}
#endif /* defined(IN_MAP_2D) */
acc = ADD_OP(MUL_OP(acc, coeff_v), kappa_v);
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
normalized = POW_OP(acc, beta_v);
const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
normalized_pixel = DIV_OP(LOAD_OP(0, (__global DATA_TYPE *)in.ptr), normalized);
STORE_OP(normalized_pixel, 0, (__global DATA_TYPE *)out.ptr);
}
#endif /* defined(NUM_SLICES) */
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