/* * Copyright (c) 2017-2019 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" /** This function applies upsample on an input image. * * @param[in] src_ptr Pointer to the source image. Supported data types: QASYMM8/F16/F32 * @param[in] src_stride_x Stride of the source image in X dimension (in bytes) * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] src_stride_y Stride of the source image in Y dimension (in bytes) * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes) * @param[in] src_step_z src_stride_z * number of elements along Z processed per workitem(in bytes) * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source image * @param[out] dst_ptr Pointer to the destination image. Supported data types: same as @p src_ptr * @param[in] dst_stride_x Stride of the destination image in X dimension (in bytes) * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] dst_stride_y Stride of the destination image in Y dimension (in bytes) * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] dst_stride_z Stride of the source tensor in Z dimension (in bytes) * @param[in] dst_step_z dst_stride_z * number of elements along Z processed per workitem(in bytes) * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination image */ __kernel void deconvolution_upsample( TENSOR3D_DECLARATION(src), TENSOR3D_DECLARATION(dst)) { Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src); Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst); // Store result *((__global DATA_TYPE *)dst.ptr) = *((__global DATA_TYPE *)src.ptr); } #if defined(FILTER_WIDTH) && defined(FILTER_HEIGHT) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(DATA_TYPE) /** This kernel reshapes the deconvolution output tensor before returning the result of the Deconvolution. The decovnolution output tensor * is the result of a @ref CLGEMM operation between the deconvolution input and the deconvolution filter * * @note Data type should be given as a preprocessor argument using -DDATA_TYPE=type, e.g., -DDATA_TYPE=F32 * @note The width of the filter should be given as a preprocessor argument using -DFILTER_WIDTH=width, e.g., -DFILTER_WIDTH=2 * @note The height of the filter should be given as a preprocessor argument using -DFILTER_HEIGHT=height, e.g., -DFILTER_HEIGHT=2 * @note The width of the input should be given as a preprocessor argument using -DSRC_WIDTH=width, e.g., -DSRC_WIDTH=10 * @note The height of the input should be given as a preprocessor argument using -DSRC_HEIGHT=width, e.g., -DSRC_HEIGHT=10 * @note The output data layout is NHWC if the preprocessor argument NUM_FILTERS is defined, NCHW if NUM_FILTERS is not defined * * @param[in] src_ptr Pointer to the source image. Supported data types: QASYMM8/F16/F32 * @param[in] src_stride_x Stride of the source image in X dimension (in bytes) * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] src_stride_y Stride of the source image in Y dimension (in bytes) * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes) * @param[in] src_step_z src_stride_z * number of elements along Z processed per workitem(in bytes) * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source image * @param[out] dst_ptr Pointer to the destination image. Supported data types: same as @p src_ptr * @param[in] dst_stride_x Stride of the destination image in X dimension (in bytes) * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] dst_stride_y Stride of the destination image in Y dimension (in bytes) * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] dst_stride_z Stride of the source tensor in Z dimension (in bytes) * @param[in] dst_step_z dst_stride_z * number of elements along Z processed per workitem(in bytes) * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination image * @param[in] bias_ptr (Optional) Pointer to the biases vector. Supported data types: F16/F32/S32 * @param[in] bias_stride_x (Optional) Stride of the biases vector in X dimension (in bytes) * @param[in] bias_step_x (Optional) biases_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the biases vector */ __kernel void deconvolution_reshape( TENSOR3D_DECLARATION(src), TENSOR3D_DECLARATION(dst) #if defined(ADD_BIAS) , VECTOR_DECLARATION(bias) #endif // defined(ADD_BIAS) ) { #define FILTER_AREA ((FILTER_WIDTH) * (FILTER_HEIGHT)) Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src); Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(dst); const DATA_TYPE data = *(__global DATA_TYPE *)src.ptr; // Store result const int x_in = get_global_id(0); const int y_in = get_global_id(1); const int z_in = get_global_id(2); #if defined(NUM_FILTERS) const int bias_index = x_in / (FILTER_AREA); const int z_out = bias_index + (NUM_FILTERS) * (z_in / (SRC_HEIGHT)); const int x_out = x_in % (FILTER_WIDTH) + y_in * (FILTER_WIDTH); const int y_out = (FILTER_HEIGHT) * (z_in % (SRC_HEIGHT)) + ((x_in % (FILTER_AREA)) / (FILTER_WIDTH)); #else // defined(NUM_FILTERS) const int x_out = x_in / (FILTER_AREA); const int y_out = x_in % (FILTER_WIDTH) + y_in * (FILTER_WIDTH); const int z_out = (FILTER_HEIGHT) * z_in + ((x_in % (FILTER_AREA)) / (FILTER_WIDTH)); const int bias_index = x_out; #endif // defined(NUM_FILTERS) #if defined(ADD_BIAS) Vector bias = CONVERT_TO_VECTOR_STRUCT_NO_STEP(bias); const DATA_TYPE bias_val = *(__global DATA_TYPE *)vector_offset(&bias, bias_index); *((__global DATA_TYPE *)tensor3D_offset(&dst, x_out, y_out, z_out)) = data + bias_val; #else // defined(ADD_BIAS) *((__global DATA_TYPE *)tensor3D_offset(&dst, x_out, y_out, z_out)) = data; #endif // defined(ADD_BIAS) #undef FILTER_AREA } #endif // defined(FILTER_WIDTH) && defined(FILTER_HEIGHT) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(DATA_TYPE)