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/*
* Copyright (c) 2016-2023 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 "tile_helpers.h"
#if defined(SCALE_NEAREST_NEIGHBOUR)
//! @cond Doxygen_Suppress
/** Performs scale on a tensor by interpolating with the NEAREAST NEIGHBOUR method. (NHWC)
*
* @note Sampling policy to used is passed as -DSAMPLING_POLICY_(TYPE) e.g. -DSAMPLING_POLICY_TOP_LEFT
* @note The tensor type ("BUFFER" only is supported) of the source tensor must be passed at compile time using -DSRC_TENSOR_TYPE (e.g. -DSRC_TENSOR_TYPE=BUFFER)
* @note The tensor type ("BUFFER" only is supported) of the destination tensor must be passed at compile time using -DDST_TENSOR_TYPE (e.g. -DDST_TENSOR_TYPE=BUFFER)
* @note The data type of the source tensor must be passed at compile time using -DSRC_DATA_TYPE (e.g. -DSRC_DATA_TYPE=float)
* @note The data type of the destination tensor must be passed at compile time using -DDST_DATA_TYPE (e.g. -DDST_DATA_TYPE=float)
* @note The number of N0 output channels to process must be passed at compile time using -DN0 (e.g. -DN0=2)
* @note The border value value must be passed at compile time using -DCONSTANT_VALUE (e.g. -DCONSTANT_VALUE=0)
* @note In case of F32/F16, -DIS_FLOATING_POINT must be passed at compile time
* @note If the source tensor has more than 3 dimensions, -DBATCHED_EXECUTION must be passed at compile time
*
* @param[in] src_ptr Pointer to the source tensor. Supported data types: U8/S16/F16/F32.
* @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes)
* @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes)
* @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes)
* @param[in] src_c The size of the channels dimension of the source tensor
* @param[in] src_w The size of the width dimension of the source tensor
* @param[in] src_h The size of the height dimension of the source tensor
* @param[in] src_n The size of the batches dimension of the source tensor
* @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor
* @param[in] dst_ptr Pointer to the destination tensor. Supported data types: U8/S16/F16/F32.
* @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes)
* @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes)
* @param[in] dst_c The size of the channels dimension of the destination tensor
* @param[in] dst_w The size of the width dimension of the destination tensor
* @param[in] dst_h The size of the height dimension of the destination tensor
* @param[in] dst_n The size of the batches dimension of the destination tensor
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor
* @param[in] scale_x The scale value to apply on the source width
* @param[in] scale_y The scale value to apply on the source height
*/
//! @endcond
__kernel void scale_nearest_neighbour_nhwc(
TENSOR4D_RO_T(src, SRC_TENSOR_TYPE),
TENSOR4D_WO_T(dst, DST_TENSOR_TYPE),
const float scale_x,
const float scale_y)
{
const int cout = GET_SPATIAL_IDX(0, N0, PARTIAL_N0); // OFM
const int xo = GET_SPATIAL_IDX(1, 1, 0); // WIDTH
#if defined(BATCHED_EXECUTION)
const int yo = GET_SPATIAL_IDX(2, 1, 0) % dst_h; // HEIGHT
const int bout = GET_SPATIAL_IDX(2, 1, 0) / dst_h; // BATCH SIZE IDX
#else // defined(BATCHED_EXECUTION)
const int yo = GET_SPATIAL_IDX(2, 1, 0); // HEIGHT
const int bout = 0; // BATCH SIZE IDX
#endif // defined(BATCHED_EXECUTION)
#ifdef SAMPLING_POLICY_TOP_LEFT
float xi_f = (xo * scale_x);
float yi_f = (yo * scale_y);
#elif SAMPLING_POLICY_CENTER
float xi_f = ((xo + 0.5f) * scale_x);
float yi_f = ((yo + 0.5f) * scale_y);
#else // SAMPLING_POLICY
#error("Unsupported sampling policy");
#endif // SAMPLING_POLICY
#ifdef ALIGN_CORNERS
xi_f = round(xi_f);
yi_f = round(yi_f);
#endif // ALIGN_CORNERS
const int xi0 = clamp((int)xi_f, 0, (int)src_w - 1);
const int yi0 = clamp((int)yi_f, 0, (int)src_h - 1);
TILE(SRC_DATA_TYPE, 1, N0, in00);
T_LOAD_NHWC_WITH_DILATION(SRC_DATA_TYPE, 1, 1, N0, SRC_TENSOR_TYPE, src, bout, yi0, xi0, cout, src_w, src_h, 1, 1, false, in00);
TILE(uint, 1, 1, dst_indirect_y);
// Calculate the destination indirect Y
dst_indirect_y[0].v = xo + (yo * (int)(dst_w)) + bout * (int)(dst_w * dst_h);
bool x_cond = PARTIAL_N0 != 0 && get_global_id(0) == 0;
T_STORE_INDIRECT_WIDTH_SELECT(DST_DATA_TYPE, 1, N0, PARTIAL_N0, DST_TENSOR_TYPE, dst, cout, dst_stride_y, x_cond, in00, dst_indirect_y);
}
#endif /* SCALE_NEAREST_NEIGHBOUR */
#if defined(SCALE_BILINEAR)
//! @cond Doxygen_Suppress
/** Performs scale on a tensor by interpolating with the BILINEAR method. (NHWC)
*
* @note If border mode replicate is used, is should be passed as -DBORDER_MODE_REPLICATE
* @note Sampling policy to used is passed as -DSAMPLING_POLICY_(TYPE) e.g. -DSAMPLING_POLICY_TOP_LEFT
* @note The tensor type ("BUFFER" only is supported) of the source tensor must be passed at compile time using -DSRC_TENSOR_TYPE (e.g. -DSRC_TENSOR_TYPE=BUFFER)
* @note The tensor type ("BUFFER" only is supported) of the destination tensor must be passed at compile time using -DDST_TENSOR_TYPE (e.g. -DDST_TENSOR_TYPE=BUFFER)
* @note The data type of the source tensor must be passed at compile time using -DSRC_DATA_TYPE (e.g. -DSRC_DATA_TYPE=float)
* @note The data type of the destination tensor must be passed at compile time using -DDST_DATA_TYPE (e.g. -DDST_DATA_TYPE=float)
* @note The number of N0 output channels to process must be passed at compile time using -DN0 (e.g. -DN0=2)
* @note The border value value must be passed at compile time using -DCONSTANT_VALUE (e.g. -DCONSTANT_VALUE=0)
* @note In case of F32/F16, -DIS_FLOATING_POINT must be passed at compile time
* @note If the source tensor has more than 3 dimensions, -DBATCHED_EXECUTION must be passed at compile time
*
* @note In case of QASYMM8, the following extra information must be passed at compile time:
* - The source offset e.g. -DOFFSET=4
* - The source scale e.g. -DSCALE=4
*
* @param[in] src_img (Not supported) Read only cl_image object for the source tensor. Included when SRC_TENSOR_TYPE=IMAGE
* @param[in] src_ptr Pointer to the source tensor. Supported data types: U8/S16/F16/F32.
* @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes)
* @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes)
* @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes)
* @param[in] src_c The size of the channels dimension of the source tensor
* @param[in] src_w The size of the width dimension of the source tensor
* @param[in] src_h The size of the height dimension of the source tensor
* @param[in] src_n The size of the batches dimension of the source tensor
* @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor
* @param[out] dst_img (Not supported) Write only cl_image object for the destination tensor. Included when DST_TENSOR_TYPE=IMAGE
* @param[out] dst_ptr Pointer to the destination tensor. Supported data types: U8/S16/F16/F32.
* @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes)
* @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes)
* @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes)
* @param[in] dst_c The size of the channels dimension of the destination tensor
* @param[in] dst_w The size of the width dimension of the destination tensor
* @param[in] dst_h The size of the height dimension of the destination tensor
* @param[in] dst_n The size of the batches dimension of the destination tensor
* @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor
* @param[in] scale_x The scale value to apply on the source width
* @param[in] scale_y The scale value to apply on the source height
*/
//! @endcond
__kernel void scale_bilinear_nhwc(
TENSOR4D_RO_T(src, SRC_TENSOR_TYPE),
TENSOR4D_WO_T(dst, DST_TENSOR_TYPE),
const float scale_x,
const float scale_y)
{
const int cout = GET_SPATIAL_IDX(0, N0, PARTIAL_N0); // OFM
const int xo = GET_SPATIAL_IDX(1, 1, 0); // WIDTH
#if defined(BATCHED_EXECUTION)
const int yo = GET_SPATIAL_IDX(2, 1, 0) % dst_h; // HEIGHT
const int bout = GET_SPATIAL_IDX(2, 1, 0) / dst_h; // BATCH SIZE IDX
#else // defined(BATCHED_EXECUTION)
const int yo = GET_SPATIAL_IDX(2, 1, 0); // HEIGHT
const int bout = 0; // BATCH SIZE IDX
#endif // defined(BATCHED_EXECUTION)
#ifdef SAMPLING_POLICY_TOP_LEFT
float xi_f = (xo * scale_x);
float yi_f = (yo * scale_y);
#elif SAMPLING_POLICY_CENTER
float xi_f = ((xo + 0.5f) * scale_x - 0.5f);
float yi_f = ((yo + 0.5f) * scale_y - 0.5f);
#else // SAMPLING_POLICY
#error("Unsupported sampling policy");
#endif // SAMPLING_POLICY
const int xi = (int)floor(xi_f);
const int yi = (int)floor(yi_f);
TILE(SRC_DATA_TYPE, 1, N0, in00);
TILE(SRC_DATA_TYPE, 1, N0, in01);
TILE(SRC_DATA_TYPE, 1, N0, in10);
TILE(SRC_DATA_TYPE, 1, N0, in11);
// Initialize the tiles to CONSTANT_VALUE
in00[0].v = CONSTANT_VALUE;
in01[0].v = CONSTANT_VALUE;
in10[0].v = CONSTANT_VALUE;
in11[0].v = CONSTANT_VALUE;
#ifndef BORDER_MODE_REPLICATE
T_LOAD_NHWC_WITH_DILATION(SRC_DATA_TYPE, 1, 1, N0, SRC_TENSOR_TYPE, src, bout, yi, xi, cout, src_w, src_h, 1, 1, true, in00);
T_LOAD_NHWC_WITH_DILATION(SRC_DATA_TYPE, 1, 1, N0, SRC_TENSOR_TYPE, src, bout, yi, xi + 1, cout, src_w, src_h, 1, 1, true, in01);
T_LOAD_NHWC_WITH_DILATION(SRC_DATA_TYPE, 1, 1, N0, SRC_TENSOR_TYPE, src, bout, yi + 1, xi, cout, src_w, src_h, 1, 1, true, in10);
T_LOAD_NHWC_WITH_DILATION(SRC_DATA_TYPE, 1, 1, N0, SRC_TENSOR_TYPE, src, bout, yi + 1, xi + 1, cout, src_w, src_h, 1, 1, true, in11);
#else // BORDER_MODE_REPLICATE
const int xi0 = clamp(xi, 0, (int)src_w - 1);
const int yi0 = clamp(yi, 0, (int)src_h - 1);
const int xi1 = clamp(xi + 1, 0, (int)src_w - 1);
const int yi1 = clamp(yi + 1, 0, (int)src_h - 1);
T_LOAD_NHWC_WITH_DILATION(SRC_DATA_TYPE, 1, 1, N0, SRC_TENSOR_TYPE, src, bout, yi0, xi0, cout, src_w, src_h, 1, 1, false, in00);
T_LOAD_NHWC_WITH_DILATION(SRC_DATA_TYPE, 1, 1, N0, SRC_TENSOR_TYPE, src, bout, yi0, xi1, cout, src_w, src_h, 1, 1, false, in01);
T_LOAD_NHWC_WITH_DILATION(SRC_DATA_TYPE, 1, 1, N0, SRC_TENSOR_TYPE, src, bout, yi1, xi0, cout, src_w, src_h, 1, 1, false, in10);
T_LOAD_NHWC_WITH_DILATION(SRC_DATA_TYPE, 1, 1, N0, SRC_TENSOR_TYPE, src, bout, yi1, xi1, cout, src_w, src_h, 1, 1, false, in11);
#endif // BORDER_MODE_REPLICATE
TILE(DST_DATA_TYPE, 1, N0, out);
#if defined(IS_FLOATING_POINT)
const SRC_DATA_TYPE a = (SRC_DATA_TYPE)(xi_f - (float)xi);
const SRC_DATA_TYPE b = (SRC_DATA_TYPE)(1.f - a);
const SRC_DATA_TYPE a1 = (SRC_DATA_TYPE)(yi_f - (float)yi);
const SRC_DATA_TYPE b1 = (SRC_DATA_TYPE)(1.f - a1);
// Calculate the output
out[0].v = ((in00[0].v * b * b1) + (in01[0].v * a * b1) + (in10[0].v * b * a1) + (in11[0].v * a * a1));
#else // defined(IS_FLOATING_POINT)
const float a = (xi_f - (float)xi);
const float b = (1.f - a);
const float a1 = (yi_f - (float)yi);
const float b1 = (1.f - a1);
out[0].v = CONVERT_SAT((CONVERT(in00[0].v, VEC_DATA_TYPE(float, N0)) * b * b1) +
(CONVERT(in01[0].v, VEC_DATA_TYPE(float, N0)) * a * b1) +
(CONVERT(in10[0].v, VEC_DATA_TYPE(float, N0)) * b * a1) +
(CONVERT(in11[0].v, VEC_DATA_TYPE(float, N0)) * a * a1),
VEC_DATA_TYPE(DST_DATA_TYPE, N0));
#endif // defined(IS_FLOATING_POINT)
TILE(uint, 1, 1, dst_indirect_y);
// Calculate the destination indirect Y
dst_indirect_y[0].v = xo + (yo * (int)(dst_w)) + bout * (int)(dst_w * dst_h);
bool x_cond = PARTIAL_N0 != 0 && get_global_id(0) == 0;
T_STORE_INDIRECT_WIDTH_SELECT(DST_DATA_TYPE, 1, N0, PARTIAL_N0, DST_TENSOR_TYPE, dst, cout, dst_stride_y, x_cond, out, dst_indirect_y);
}
#endif /* SCALE_BILINEAR */
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