| /* |
| * Copyright (c) 2016-2021 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 "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_T(src, SRC_TENSOR_TYPE), |
| TENSOR4D_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_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_bilinear_nhwc( |
| TENSOR4D_T(src, SRC_TENSOR_TYPE), |
| TENSOR4D_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) |
| TILE(float, 1, N0, out_f); |
| TILE(float, 1, N0, in00_f); |
| TILE(float, 1, N0, in01_f); |
| TILE(float, 1, N0, in10_f); |
| TILE(float, 1, N0, in11_f); |
| |
| 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); |
| |
| // Dequantize |
| LOOP_UNROLLING(int, n0, 0, 1, N0, |
| { |
| in00_f[0].s[n0] = ((float)in00[0].s[n0] - (float)OFFSET) * (float)SCALE; |
| in01_f[0].s[n0] = ((float)in01[0].s[n0] - (float)OFFSET) * (float)SCALE; |
| in10_f[0].s[n0] = ((float)in10[0].s[n0] - (float)OFFSET) * (float)SCALE; |
| in11_f[0].s[n0] = ((float)in11[0].s[n0] - (float)OFFSET) * (float)SCALE; |
| }) |
| |
| // Calculate the output in the floating-point domain |
| out_f[0].v = ((in00_f[0].v * b * b1) + (in01_f[0].v * a * b1) + (in10_f[0].v * b * a1) + (in11_f[0].v * a * a1)); |
| |
| // Quantize |
| LOOP_UNROLLING(int, n0, 0, 1, N0, |
| { |
| out[0].s[n0] = CONVERT_SAT(out_f[0].s[n0] / (float)SCALE + (float)OFFSET, DST_DATA_TYPE); |
| }) |
| #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 */ |
