/* * Copyright (c) 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 withoutput restriction, including withoutput 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(DATA_TYPE) && defined(BATCH_SIZE) /** Batch to space transformation. (NCHW) * * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float * @note The input tensor batch size must be passed at compile time using -DBATCH_SIZE. e.g. -DBATCH_SIZE=2 * * @param[in] input_ptr Pointer to the source tensor. Supported data types: U8/S8/QASYMM8/U16/S16/F16/U32/S32/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 first source tensor * @param[in] batch_id The input tensor batch id * @param[in] block_shape_ptr Pointer to the source tensor. Supported data types: S32 * @param[in] block_shape_stride_x Stride of the source tensor in X dimension (in bytes) * @param[in] block_shape_step_x block_shape_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] block_shape_stride_y Stride of the source tensor in Y dimension (in bytes) * @param[in] block_shape_step_y block_shape_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] input_offset_first_element_in_bytes The offset of the first element in the first 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 batch_to_space_nchw( TENSOR3D_DECLARATION(input), const int batch_id, VECTOR_DECLARATION(block_shape), TENSOR4D_DECLARATION(output)) { Tensor3D in = CONVERT_TO_TENSOR3D_STRUCT(input); Tensor4D out = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(output, 0); Vector block = CONVERT_TO_VECTOR_STRUCT_NO_STEP(block_shape); const int block_x = *((__global int *)vector_offset(&block, 0)); const int block_y = *((__global int *)vector_offset(&block, 1)); const int r = (BATCH_SIZE / (block_x * block_y)); const int x = get_global_id(0); const int y = get_global_id(1); const int z = get_global_id(2); const int w = batch_id % r; const int out_x = x * block_x + (batch_id / r) % block_x; const int out_y = y * block_y + (batch_id / r) / block_x; *((__global DATA_TYPE *)tensor4D_offset(&out, out_x, out_y, z, w)) = *((__global DATA_TYPE *)in.ptr); } /** Batch to space transformation. (NHWC) * * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float * @note The input tensor batch size must be passed at compile time using -DBATCH_SIZE. e.g. -DBATCH_SIZE=2 * * @param[in] input_ptr Pointer to the source tensor. Supported data types: U8/S8/QASYMM8/U16/S16/F16/U32/S32/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 first source tensor * @param[in] batch_id The input tensor batch id * @param[in] block_shape_ptr Pointer to the source tensor. Supported data types: S32 * @param[in] block_shape_stride_x Stride of the source tensor in X dimension (in bytes) * @param[in] block_shape_step_x block_shape_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] block_shape_stride_y Stride of the source tensor in Y dimension (in bytes) * @param[in] block_shape_step_y block_shape_stride_y * number of elements along Y processed per workitem(in bytes) * @param[in] input_offset_first_element_in_bytes The offset of the first element in the first 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 batch_to_space_nhwc( TENSOR3D_DECLARATION(input), const int batch_id, VECTOR_DECLARATION(block_shape), TENSOR4D_DECLARATION(output)) { Tensor3D in = CONVERT_TO_TENSOR3D_STRUCT(input); Tensor4D out = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(output, 0); Vector block = CONVERT_TO_VECTOR_STRUCT_NO_STEP(block_shape); const int block_x = *((__global int *)vector_offset(&block, 0)); const int block_y = *((__global int *)vector_offset(&block, 1)); const int r = (BATCH_SIZE / (block_x * block_y)); const int x = get_global_id(1); const int y = get_global_id(2); const int z = get_global_id(0); const int w = batch_id % r; const int out_x = x * block_x + (batch_id / r) % block_x; const int out_y = y * block_y + (batch_id / r) / block_x; *((__global DATA_TYPE *)tensor4D_offset(&out, z, out_x, out_y, w)) = *((__global DATA_TYPE *)in.ptr); } #endif // defined(DATA_TYPE) && defined(BATCH_SIZE) #if defined(DATA_TYPE) && defined(BATCH_SIZE) && defined(BLOCK_SHAPE_X) && defined(BLOCK_SHAPE_Y) /** Batch to space transformation. (NCHW) * * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float * @note The input tensor batch size must be passed at compile time using -DBATCH_SIZE. e.g. -DBATCH_SIZE=2 * @note The block shape x must be passed at compile time using -DBLOCK_SHAPE_X. e.g. -DBLOCK_SHAPE_X=2 * @note The block shape y must be passed at compile time using -DBLOCK_SHAPE_Y. e.g. -DBLOCK_SHAPE_Y=2 * * @param[in] input_ptr Pointer to the source tensor. Supported data types: U8/S8/QASYMM8/U16/S16/F16/U32/S32/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 first source tensor * @param[in] batch_id The input tensor batch id * @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 batch_to_space_static_nchw( TENSOR3D_DECLARATION(input), const int batch_id, TENSOR4D_DECLARATION(output)) { Tensor3D in = CONVERT_TO_TENSOR3D_STRUCT(input); Tensor4D out = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(output, 0); const int block_x = BLOCK_SHAPE_X; const int block_y = BLOCK_SHAPE_Y; const int r = (BATCH_SIZE / (block_x * block_y)); const int x = get_global_id(0); const int y = get_global_id(1); const int z = get_global_id(2); const int w = batch_id % r; const int out_x = x * block_x + (batch_id / r) % block_x; const int out_y = y * block_y + (batch_id / r) / block_x; *((__global DATA_TYPE *)tensor4D_offset(&out, out_x, out_y, z, w)) = *((__global DATA_TYPE *)in.ptr); } /** Batch to space transformation. (NHWC) * * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float * @note The input tensor batch size must be passed at compile time using -DBATCH_SIZE. e.g. -DBATCH_SIZE=2 * @note The block shape x must be passed at compile time using -DBLOCK_SHAPE_X. e.g. -DBLOCK_SHAPE_X=2 * @note The block shape y must be passed at compile time using -DBLOCK_SHAPE_Y. e.g. -DBLOCK_SHAPE_Y=2 * * @param[in] input_ptr Pointer to the source tensor. Supported data types: U8/S8/QASYMM8/U16/S16/F16/U32/S32/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 first source tensor * @param[in] batch_id The input tensor batch id * @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 batch_to_space_static_nhwc( TENSOR3D_DECLARATION(input), const int batch_id, TENSOR4D_DECLARATION(output)) { Tensor3D in = CONVERT_TO_TENSOR3D_STRUCT(input); Tensor4D out = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(output, 0); const int block_x = BLOCK_SHAPE_X; const int block_y = BLOCK_SHAPE_Y; const int r = (BATCH_SIZE / (block_x * block_y)); const int x = get_global_id(1); const int y = get_global_id(2); const int z = get_global_id(0); const int w = batch_id % r; const int out_x = x * block_x + (batch_id / r) % block_x; const int out_y = y * block_y + (batch_id / r) / block_x; *((__global DATA_TYPE *)tensor4D_offset(&out, z, out_x, out_y, w)) = *((__global DATA_TYPE *)in.ptr); } #endif // defined(DATA_TYPE) && defined(BATCH_SIZE) && defined(BLOCK_SHAPE_X) && defined(BLOCK_SHAPE_Y)