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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"
#if defined(POOL_AVG)
#define POOL_OP(x, y) ((x) + (y))
#else /* defined(POOL_AVG) */
#define POOL_OP(x, y) (max((x), (y)))
#endif /* defined(POOL_AVG) */
#define DIV_OP(x, y) (x * (1.f / y))
#if defined(POOL_L2)
#error "L2 pooling is not supported"
#endif /* defined(POOL_L2) */
int calculate_avg_scale(const int pool_size_x, const int pool_size_y, const int upper_bound_w, const int upper_bound_h,
const int pad_x, const int pad_y, const int stride_x, const int stride_y)
{
int start_x = get_global_id(0) * stride_x - pad_x;
int start_y = get_global_id(1) * stride_y - pad_y;
const int end_x = min(start_x + pool_size_x, upper_bound_w);
const int end_y = min(start_y + pool_size_y, upper_bound_h);
#if defined(EXCLUDE_PADDING)
start_x = max(0, start_x);
start_y = max(0, start_y);
#endif /* defined(EXCLUDE_PADDING) */
return ((end_y - start_y) * (end_x - start_x));
}
/** Performs a pooling function of pool size equal to N
*
* @note Pool sizes must be passed using -DPOOL_SIZE_X and -DPOOL_SIZE_Y e.g. -DPOOL_SIZE_X=13;
* @note In case of average pooling the following information must be passed at compile time:
* -DPOOL_AVG must be provided otherwise max pooling will be performed.
* -DMAX_WIDTH and -DMAX_HEIGHT which are the maximum accessible indeces in x and y dimensions (width + pad)
* -DSTRIDE_X and -DSTRIDE_Y which are the steps of the window along the x and y directions
* -DPAD_X and -DPAD_Y which are the pooling paddings in x and y dimension
*
* @param[in] input_ptr Pointer to the source image. Supported data types: QASYMM8
* @param[in] input_stride_x Stride of the source image 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 source image 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 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 source image
* @param[out] output_ptr Pointer to the destination image. Supported data types: same as @p input_ptr
* @param[in] output_stride_x Stride of the destination image 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 image 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 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 image
*/
__kernel void pooling_layer_MxN_quantized(
TENSOR3D_DECLARATION(input),
TENSOR3D_DECLARATION(output))
{
// Get pixels pointer
Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input);
Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output);
int8 vdata = 0;
int sdata = 0;
// Load data
for(int y = 0; y < POOL_SIZE_Y; y++)
{
int x = 0;
for(; x <= ((int)POOL_SIZE_X - 8); x += 8)
{
uchar8 data = vload8(0, (__global uchar *)tensor3D_offset(&input, x, y, 0));
int8 data0 = convert_int8(data);
vdata = POOL_OP(vdata, data0);
}
// Leftover
for(; x < (int)POOL_SIZE_X; ++x)
{
uchar data = *((__global uchar *)tensor3D_offset(&input, x, y, 0));
int data0 = convert_int(data);
sdata = POOL_OP(sdata, data0);
}
}
// Reduce result
int4 reduce4 = POOL_OP(vdata.s0123, vdata.s4567);
int2 reduce2 = POOL_OP(reduce4.s01, reduce4.s23);
int res = POOL_OP(reduce2.s0, reduce2.s1);
res = POOL_OP(res, sdata);
#if defined(POOL_AVG)
res = round(DIV_OP(res, calculate_avg_scale(POOL_SIZE_X, POOL_SIZE_Y, MAX_WIDTH, MAX_HEIGHT, PAD_X, PAD_Y, STRIDE_X, STRIDE_Y)));
#endif /* defined(POOL_AVG) */
// Store result
*(__global uchar *)output.ptr = convert_uchar(res);
}
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