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/*
* Copyright (c) 2017-2021 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"
#include "repeat.h"
#include "tile_helpers.h"
#if defined(POOL_AVG) || defined(POOL_L2)
#define POOL_OP(x, y) ((x) + (y))
#else /* defined(POOL_AVG) || defined(POOL_L2) */
#define POOL_OP(x, y) (fmax((x), (y)))
#endif /* defined(POOL_AVG) || defined(POOL_L2) */
#if defined(POOL_L2)
#define POW2_OP(x, vec_size) ((x) * (x))
#else /* defined(POOL_L2) */
#define POW2_OP(x, vec_size) (x)
#endif /* defined(POOL_L2) */
#define DIV_OP(x, y) (x * (1.f / y))
#define SQRT_OP(x) sqrt((x))
#if defined(FP_MIXED_PRECISION)
#define CONVERT_TO_ACC_DATA_TYPE(x, n) CONVERT(x, VEC_DATA_TYPE(ACC_DATA_TYPE, n))
#define VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(n, offset, ptr) \
CONVERT_TO_ACC_DATA_TYPE(vload##n(offset, ptr), n)
#else /* defined(FP_MIXED_PRECISION) */
#define VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(n, offset, ptr) vload##n(offset, ptr)
#endif /* defined(FP_MIXED_PRECISION) */
ACC_DATA_TYPE 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));
}
#if defined(POOL_SIZE_X) && defined(POOL_SIZE_Y)
/** Performs a pooling function of pool size equal to N (NCHW)
*
* @note Datatype must be passed using -DDATA_TYPE e.g. -DDATA_TYPE=float. Supported data types are F16/F32;
* @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
* @note The initial value for the pooling operation must be passed at compile time using -DINITIAL_VALUE e.g. -DINITIAL_VALUE=0
*
* @param[in] input_ptr Pointer to the source tensor. Supported data types: F16/F32
* @param[in] input_stride_x Stride of the 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 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 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 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 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 pooling_layer_MxN_nchw(
TENSOR3D_DECLARATION(input),
TENSOR3D_DECLARATION(output))
{
// Get pixels pointer
Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input);
Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output);
VEC_DATA_TYPE(ACC_DATA_TYPE, 8)
vdata = INITIAL_VALUE;
ACC_DATA_TYPE sdata = INITIAL_VALUE;
// Load data
for(int y = 0; y < POOL_SIZE_Y; y++)
{
int x = 0;
for(; x <= ((int)POOL_SIZE_X - 8); x += 8)
{
VEC_DATA_TYPE(ACC_DATA_TYPE, 8)
data0 = VLOAD_AND_CONVERT_TO_ACC_DATA_TYPE(8, 0, (__global DATA_TYPE *)tensor3D_offset(&input, x, y, 0));
#if defined(POOL_L2)
// Raise to power of 2 for L2 Pooling
data0 *= data0;
#endif /* defined(POOL_L2) */
vdata = POOL_OP(vdata, data0);
}
// Leftover
for(; x < (int)POOL_SIZE_X; ++x)
{
ACC_DATA_TYPE data0 = (ACC_DATA_TYPE)(*((__global DATA_TYPE *)tensor3D_offset(&input, x, y, 0)));
#if defined(POOL_L2)
// Raise to power of 2 for L2 Pooling
data0 *= data0;
#endif /* defined(POOL_L2) */
sdata = POOL_OP(sdata, data0);
}
}
// Reduce result
VEC_DATA_TYPE(ACC_DATA_TYPE, 4)
reduce4 = POOL_OP(vdata.s0123, vdata.s4567);
VEC_DATA_TYPE(ACC_DATA_TYPE, 2)
reduce2 = POOL_OP(reduce4.s01, reduce4.s23);
ACC_DATA_TYPE res = POOL_OP(reduce2.s0, reduce2.s1);
res = POOL_OP(res, sdata);
#if defined(POOL_AVG) || defined(POOL_L2)
// Divide by pool region in case of average pooling
res = 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) || defined(POOL_L2) */
#if defined(POOL_L2)
// Take square root of the result in L2 pooling
res = SQRT_OP(res);
#endif /* defined(POOL_L2) */
// Store result
*(__global DATA_TYPE *)output.ptr = (DATA_TYPE)res;
}
#endif // defined(POOL_SIZE_X) && defined(POOL_SIZE_Y)
#if defined(PAD_TENSOR_LEFT) && defined(PAD_TENSOR_RIGHT) && defined(PAD_TENSOR_TOP) && defined(PAD_TENSOR_BOTTOM)
inline void offset_no_padding_nchw(const Tensor3D *input, uint *offset_top, uint *offset_bottom)
{
const int pad_horiz = PAD_TENSOR_LEFT + PAD_TENSOR_RIGHT;
const int pad_vert = PAD_TENSOR_TOP + PAD_TENSOR_BOTTOM;
const int x = get_global_id(0) * STRIDE_X;
const int y = get_global_id(1) * STRIDE_Y;
const int z = get_global_id(2);
//x axis: width, y axis: height, z axis: component
const uint padded_offset = input->offset_first_element_in_bytes
+ x * input->stride_x
+ y * input->stride_y
+ z * input->stride_z;
const uint offset_base = padded_offset
- y * pad_horiz * sizeof(DATA_TYPE) /* Horizontal padding for each row */
- PAD_TENSOR_TOP * input->stride_y /* top padding */
- z * MAX_HEIGHT * pad_horiz * sizeof(DATA_TYPE) - z * pad_vert * input->stride_y /* Z plane padding */
- PAD_TENSOR_LEFT * sizeof(DATA_TYPE);
#if defined(TENSOR_CHANNEL) && defined(TENSOR_WIDTH) && defined(TENSOR_HEIGHT)
*offset_top = (uint)((offset_base / sizeof(DATA_TYPE)) % (TENSOR_CHANNEL * TENSOR_WIDTH * TENSOR_HEIGHT));
#else /* defined(TENSOR_CHANNEL) && defined(TENSOR_WIDTH) && defined(TENSOR_HEIGHT) */
*offset_top = (uint)(offset_base / sizeof(DATA_TYPE));
#endif /* defined(TENSOR_CHANNEL) && defined(TENSOR_WIDTH) && defined(TENSOR_HEIGHT) */
*offset_bottom = *offset_top + input->stride_y / sizeof(DATA_TYPE) - pad_horiz;
return;
}
#endif //defined(PAD_TENSOR_LEFT) && defined(PAD_TENSOR_RIGHT) && defined(PAD_TENSOR_TOP) && defined(PAD_TENSOR_BOTTOM)
/** Performs a MAX pooling of pool size equal to 2, and record max value indices for NCHW.
*
* @note Datatype must be passed using -DDATA_TYPE e.g. -DDATA_TYPE=half. Supported data types are F32
* @note Pool sizes must be passed using -DPOOL_SIZE_X and -DPOOL_SIZE_Y e.g. -DPOOL_SIZE_X=13;
* @note Tensors width and height must be passed at compile time using -DMAX_WIDTH and -DMAX_HEIGHT
* @note Pool strides must be passed at compile time using -DSTRIDE_X and -DSTRIDE_Y which are the steps of the window along the x and y directions
* @note Tensor padding values must be passed at compile time using PAD_TENSOR_LEFT, PAD_TENSOR_RIGHT, PAD_TENSOR_TOP and PAD_TENSOR_BOTTOM
*
* @param[in] input_ptr Pointer to the source tensor. Supported data types: F32
* @param[in] input_stride_x Stride of the 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 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 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 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 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
* @param[in] indices_ptr Pointer to the indices tensor. Supported data types: U32
* @param[in] indices_stride_x Stride of the indices tensor in X dimension (in bytes)
* @param[in] indices_step_x indices_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] indices_stride_y Stride of the indices tensor in Y dimension (in bytes)
* @param[in] indices_step_y indices_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] indices_stride_z Stride of the indices tensor in Z dimension (in bytes)
* @param[in] indices_step_z indices_stride_z * number of elements along Z processed per workitem(in bytes)
* @param[in] indices_offset_first_element_in_bytes The offset of the first element in the indices tensor
*/
__kernel void pooling_layer_2_nchw_indices_fp32(
TENSOR3D_DECLARATION(input),
TENSOR3D_DECLARATION(output),
TENSOR3D_DECLARATION(indices))
{
// Get pixels pointer
Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input);
Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output);
Tensor3D indices = CONVERT_TO_TENSOR3D_STRUCT(indices);
// Load data
float2 data0 = VLOAD(2)(0, (__global float *)tensor3D_offset(&input, 0, 0, 0));
float2 data1 = VLOAD(2)(0, (__global float *)tensor3D_offset(&input, 0, 1, 0));
// Perform calculations
float data0_max = POOL_OP(data0.s0, data0.s1);
float data1_max = POOL_OP(data1.s0, data1.s1);
float res = POOL_OP(data0_max, data1_max);
// Store result
*(__global float *)output.ptr = res;
#if defined(PAD_TENSOR_LEFT) && defined(PAD_TENSOR_RIGHT) && defined(PAD_TENSOR_TOP) && defined(PAD_TENSOR_BOTTOM)
uint offset_top = 0;
uint offset_bottom = 0;
offset_no_padding_nchw(&input, &offset_top, &offset_bottom);
uint index0 = select(offset_top + 1, offset_top, isgreaterequal(data0.s0, data0.s1));
uint index1 = select(offset_bottom + 1, offset_bottom, isgreaterequal(data1.s0, data1.s1));
uint index = select(index1, index0, isgreaterequal(data0_max, data1_max));
*(__global uint *)indices.ptr = index;
#endif //defined(PAD_TENSOR_LEFT) && defined(PAD_TENSOR_RIGHT) && defined(PAD_TENSOR_TOP) && defined(PAD_TENSOR_BOTTOM)
}
/** Performs a MAX pooling of pool size equal to 2, and record max value indices for NCHW.
*
* @note Datatype must be passed using -DDATA_TYPE e.g. -DDATA_TYPE=half. Supported data types are F16
* @note Pool sizes must be passed using -DPOOL_SIZE_X and -DPOOL_SIZE_Y e.g. -DPOOL_SIZE_X=13;
* @note Tensors width and height must be passed at compile time using -DMAX_WIDTH and -DMAX_HEIGHT
* @note Pool strides must be passed at compile time using -DSTRIDE_X and -DSTRIDE_Y which are the steps of the window along the x and y directions
* @note Tensor padding values must be passed at compile time using PAD_TENSOR_LEFT, PAD_TENSOR_RIGHT, PAD_TENSOR_TOP and PAD_TENSOR_BOTTOM
*
* @param[in] input_ptr Pointer to the source tensor. Supported data types: F16
* @param[in] input_stride_x Stride of the 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 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 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 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 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
* @param[in] indices_ptr Pointer to the indices tensor. Supported data types: U32
* @param[in] indices_stride_x Stride of the indices tensor in X dimension (in bytes)
* @param[in] indices_step_x indices_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] indices_stride_y Stride of the indices tensor in Y dimension (in bytes)
* @param[in] indices_step_y indices_stride_y * number of elements along Y processed per workitem(in bytes)
* @param[in] indices_stride_z Stride of the indices tensor in Z dimension (in bytes)
* @param[in] indices_step_z indices_stride_z * number of elements along Z processed per workitem(in bytes)
* @param[in] indices_offset_first_element_in_bytes The offset of the first element in the indices tensor
*/
__kernel void pooling_layer_2_nchw_indices_fp16(
TENSOR3D_DECLARATION(input),
TENSOR3D_DECLARATION(output),
TENSOR3D_DECLARATION(indices))
{
// Get pixels pointer
Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT(input);
Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT(output);
Tensor3D indices = CONVERT_TO_TENSOR3D_STRUCT(indices);
// Load data
half2 data0 = VLOAD(2)(0, (__global half *)tensor3D_offset(&input, 0, 0, 0));
half2 data1 = VLOAD(2)(0, (__global half *)tensor3D_offset(&input, 0, 1, 0));
// Perform calculations
half data0_max = POOL_OP(data0.s0, data0.s1);
half data1_max = POOL_OP(data1.s0, data1.s1);
half res = POOL_OP(data0_max, data1_max);
// Store result
*(__global half *)output.ptr = res;
#if defined(PAD_TENSOR_LEFT) && defined(PAD_TENSOR_RIGHT) && defined(PAD_TENSOR_TOP) && defined(PAD_TENSOR_BOTTOM)
uint offset_top = 0;
uint offset_bottom = 0;
offset_no_padding_nchw(&input, &offset_top, &offset_bottom);
uint index0 = select(offset_top + 1, offset_top, isgreaterequal(data0.s0, data0.s1));
uint index1 = select(offset_bottom + 1, offset_bottom, isgreaterequal(data1.s0, data1.s1));
uint index = select(index1, index0, isgreaterequal(data0_max, data1_max));
*(__global uint *)indices.ptr = index;
#endif //defined(PAD_TENSOR_LEFT) && defined(PAD_TENSOR_RIGHT) && defined(PAD_TENSOR_TOP) && defined(PAD_TENSOR_BOTTOM)
}
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