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Diffstat (limited to 'src/core/CL/cl_kernels/im2col.cl')
| -rw-r--r-- | src/core/CL/cl_kernels/im2col.cl | 1360 |
1 files changed, 0 insertions, 1360 deletions
diff --git a/src/core/CL/cl_kernels/im2col.cl b/src/core/CL/cl_kernels/im2col.cl deleted file mode 100644 index a1467a0b36..0000000000 --- a/src/core/CL/cl_kernels/im2col.cl +++ /dev/null @@ -1,1360 +0,0 @@ -/* - * Copyright (c) 2018-2020 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" - -#if defined(DATA_TYPE) && defined(ELEMENT_SIZE) - -#if ELEMENT_SIZE == 1 -#define COND_DATA_TYPE char -#elif ELEMENT_SIZE == 2 -#define COND_DATA_TYPE short -#elif ELEMENT_SIZE == 4 -#define COND_DATA_TYPE int -#else // ELEMENT_SIZE -#error "Element size not support" -#endif // ELEMENT_SIZE - -#if defined(CONVOLVED_WIDTH) && defined(STRIDE_Y) && defined(SRC_DEPTH) -/** This opencl kernel performs im2col when the kernel size is 1x1, the stride_x = 1 and the data layout is NCHW - * - * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float - * @note The width of output tensor after matrix multiplication must be passed at compile time using -DCONVOLVED_WIDTH: e.g. -DCONVOLVED_WIDTH=34 - * @note The number of input channels must be passed at compile time using -DSRC_DEPTH: e.g. -DSRC_DEPTH=3 - * @note The stride along the Y direction must be passed at compile time using -DSTRIDE_Y: e.g. -DSTRIDE_Y=1 - * @note In case biases will be added to the convolution -DHAS_BIAS has to be passed to append the final matrix with 1 in each row. - * @note In case grouping is performed, the number of groups must be passed at compile time using -DNUM_GROUPS: e.g. -DNUM_GROUPS=4 - * - * @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8_SIGNED/QASYMM8/F16/F32 - * @param[in] src_stride_x Stride of the source tensor 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 tensor 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 tensor - * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr - * @param[in] dst_stride_x Stride of the destination tensor 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 tensor 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 destination 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 tensor - * @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes). - * @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes). - */ -__kernel void im2col1x1_stridex1_nchw( - TENSOR3D_DECLARATION(src), -#if defined(NUM_GROUPS) - TENSOR3D_DECLARATION(dst), -#else // defined(NUM_GROUPS) - IMAGE_DECLARATION(dst), -#endif // defined(NUM_GROUPS) - uint src_stride_w, - uint dst_stride_w) -{ - const uint xc = get_global_id(0) * 4; // x coordinate in the convolved tensor - const uint yc = get_global_id(1); // y coordinate in the convolved tensor - const uint ch = get_global_id(2) % SRC_DEPTH; // input feature map - const uint batch = get_global_id(2) / SRC_DEPTH; // batch size - - // Clamp xc - // The strategy clamps at "xc" as it will be a valid value for sure - uint4 xc_clamped = xc + (uint4)(0, 1, 2, 3); - - // Check which values are valid - const VEC_DATA_TYPE(COND_DATA_TYPE, 4) cond0 = CONVERT((xc_clamped < SRC_WIDTH), VEC_DATA_TYPE(COND_DATA_TYPE, 4)); - - xc_clamped = select((uint4)xc, xc_clamped, convert_int4(cond0)); - - // Calculate input indices - const uint xi = xc; - const uint yi = yc * STRIDE_Y; - - // Calculate output indices - -#if defined(NUM_GROUPS) - const uint xo = ch % (SRC_DEPTH / NUM_GROUPS); - const uint zo = ch / (SRC_DEPTH / NUM_GROUPS); -#else // defined(NUM_GROUPS) - const uint xo = ch; -#endif // defined(NUM_GROUPS) - const uint4 yo = xc_clamped + yc * CONVOLVED_WIDTH; // Index of the convolution - - // Get input and output address - __global uchar *input_ptr = src_ptr + src_offset_first_element_in_bytes + xi * src_stride_x + yi * src_stride_y + ch * src_stride_z + batch * src_stride_w; -#if defined(NUM_GROUPS) - __global uchar *output_ptr = dst_ptr + dst_offset_first_element_in_bytes + xo * dst_stride_x + zo * dst_stride_z + batch * dst_stride_w; -#else // defined(NUM_GROUPS) - __global uchar *output_ptr = dst_ptr + dst_offset_first_element_in_bytes + xo * dst_stride_x + batch * dst_stride_w; -#endif // defined(NUM_GROUPS) - - VEC_DATA_TYPE(DATA_TYPE, 4) - data = vload4(0, (__global DATA_TYPE *)input_ptr); - - // If out-of-bound, overwrite with the first element - data = select((VEC_DATA_TYPE(DATA_TYPE, 4))data.s0, data, cond0); - - *(__global DATA_TYPE *)(output_ptr + yo.s0 * dst_stride_y) = data.s0; - *(__global DATA_TYPE *)(output_ptr + yo.s1 * dst_stride_y) = data.s1; - *(__global DATA_TYPE *)(output_ptr + yo.s2 * dst_stride_y) = data.s2; - *(__global DATA_TYPE *)(output_ptr + yo.s3 * dst_stride_y) = data.s3; - -#ifdef HAS_BIAS -#if defined(NUM_GROUPS) - if(xo == (SRC_DEPTH / NUM_GROUPS - 1)) -#else // defined(NUM_GROUPS) - if(ch == (SRC_DEPTH - 1)) -#endif // defined(NUM_GROUPS) - { - *((__global DATA_TYPE *)(output_ptr + yo.s0 * dst_stride_y) + 1) = 1.0f; - *((__global DATA_TYPE *)(output_ptr + yo.s1 * dst_stride_y) + 1) = 1.0f; - *((__global DATA_TYPE *)(output_ptr + yo.s2 * dst_stride_y) + 1) = 1.0f; - *((__global DATA_TYPE *)(output_ptr + yo.s3 * dst_stride_y) + 1) = 1.0f; - } -#endif // HAS_BIAS -} -#endif // defined(CONVOLVED_WIDTH) && defined(STRIDE_Y) && defined(SRC_DEPTH) - -#if defined(CONVOLVED_WIDTH) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(STRIDE_X) && defined(STRIDE_Y) && defined(SRC_DEPTH) && defined(PAD_LEFT) && defined(PAD_RIGHT) && defined(PAD_TOP) && defined(PAD_BOTTOM) && defined(PAD_VALUE) -#if defined(DILATION_X) && defined(DILATION_Y) -/** This opencl kernel performs a generic im2col implementation when the data layout is NCHW - * - * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float - * @note The width and height of the input tensor must be passed at compile time using -DSRC_WIDTH and -DSRC_HEIGHT: e.g. -DSRC_WIDTH=128 and -DSRC_HEIGHT=128 - * @note The width of output tensor after matrix multiplication must be passed at compile time using -DCONVOLVED_WIDTH: e.g. -DCONVOLVED_WIDTH=34 - * @note The kernel width, height and depth must be passed at compile time using -DKERNEL_WIDTH, -DKERNEL_HEIGHT and -DSRC_DEPTH: e.g. -DKERNEL_WIDTH=3, -DKERNEL_HEIGHT=3 and -DSRC_DEPTH=64 - * @note The pad_left, pad_right, pad_top and pad_bottom must be passed at compile time using -DPAD_LEFT, -DPAD_RIGHT, -DPAD_TOP and -DPAD_BOTTOM: e.g. -DPAD_LEFT=1, -DPAD_RIGHT=2, -DPAD_TOP=3 and -DPAD_BOTTOM=2 - * @note The zero value to store in case we load values out-of-bounds must be passed at compile time using -DPAD_VALUE: e.g. -DPAD_VALUE=0.0 - * @note The stride along the X and Y directions must be passed at compile time using -DSTRIDE_X and -DSTRIDE_Y: e.g. -DSTRIDE_X=1 and -DSTRIDE_Y=1 - * @note The dilation_x and dilation_y must be passed at compile time using -DDILATION_X and -DDILATION_Y: e.g. -DDILATION_X=1, -DDILATION_Y=1 - * @note In case biases will be added to the convolution -DHAS_BIAS has to be passed to append the final matrix with 1 in each row. - * @note In case grouping is performed, the number of groups must be passed at compile time using -DNUM_GROUPS: e.g. -DNUM_GROUPS=4 - * - * @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8_SIGNED/QASYMM8/F16/F32 - * @param[in] src_stride_x Stride of the source tensor 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 tensor 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 tensor - * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr - * @param[in] dst_stride_x Stride of the destination tensor 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 tensor 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 destination 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 tensor - * @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes). - * @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes). - */ -__kernel void im2col_generic_nchw( - TENSOR3D_DECLARATION(src), -#if defined(NUM_GROUPS) - TENSOR3D_DECLARATION(dst), -#else // defined(NUM_GROUPS) - IMAGE_DECLARATION(dst), -#endif // defined(NUM_GROUPS) - uint src_stride_w, - uint dst_stride_w) -{ - const int xc = get_global_id(0); // x coordinate in the convolved tensor - const int yc = get_global_id(1); // y coordinate in the convolved tensor - const int ch = get_global_id(2) % SRC_DEPTH; // input feature map - const int batch = get_global_id(2) / SRC_DEPTH; // batch size - - // Calculate input indices - const int xi = xc * STRIDE_X - PAD_LEFT; - const int yi = yc * STRIDE_Y - PAD_TOP; - - // Calculate output indices -#if defined(NUM_GROUPS) - const int xo = (ch % (SRC_DEPTH / NUM_GROUPS)) * KERNEL_WIDTH * KERNEL_HEIGHT; - const int zo = ch / (SRC_DEPTH / NUM_GROUPS); -#else // defined(NUM_GROUPS) - const int xo = ch * KERNEL_WIDTH * KERNEL_HEIGHT; -#endif // defined(NUM_GROUPS) - const int yo = xc + yc * CONVOLVED_WIDTH; // Index of the convolution - - __global uchar *input_ptr = src_ptr + src_offset_first_element_in_bytes + ch * src_stride_z + batch * src_stride_w; -#if defined(NUM_GROUPS) - __global DATA_TYPE *output_ptr = ((__global DATA_TYPE *)(dst_ptr + dst_offset_first_element_in_bytes + yo * dst_stride_y + zo * dst_stride_z + batch * dst_stride_w)) + xo; -#else // defined(NUM_GROUPS) - __global DATA_TYPE *output_ptr = ((__global DATA_TYPE *)(dst_ptr + dst_offset_first_element_in_bytes + yo * dst_stride_y + batch * dst_stride_w)) + xo; -#endif // defined(NUM_GROUPS) - - // Linearize convolution elements - for(int yk = 0; yk < KERNEL_HEIGHT; ++yk) - { - int y = yi + yk * DILATION_Y; - for(int xk = 0; xk < KERNEL_WIDTH; ++xk, ++output_ptr) - { - int x = xi + xk * DILATION_X; -#if PAD_LEFT == 0 && PAD_TOP == 0 && PAD_RIGHT == 0 && PAD_BOTTOM == 0 - *output_ptr = *((__global DATA_TYPE *)(input_ptr + x * src_stride_x + y * src_stride_y)); -#else // PAD_LEFT == 0 && PAD_TOP == 0 && PAD_RIGHT == 0 && PAD_BOTTOM == 0 - if(x < 0 || x >= SRC_WIDTH || y < 0 || y >= SRC_HEIGHT) - { - *output_ptr = PAD_VALUE; - } - else - { - *output_ptr = *((__global DATA_TYPE *)(input_ptr + x * src_stride_x + y * src_stride_y)); - } -#endif // PAD_LEFT == 0 && PAD_TOP == 0 && PAD_RIGHT == 0 && PAD_BOTTOM == 0 - } - } - -#ifdef HAS_BIAS -#if defined(NUM_GROUPS) - if((xo / (KERNEL_WIDTH * KERNEL_HEIGHT)) == (SRC_DEPTH / NUM_GROUPS - 1)) -#else // defined(NUM_GROUPS) - if(ch == (SRC_DEPTH - 1)) -#endif // defined(NUM_GROUPS) - { - *output_ptr = 1.0f; - } -#endif // HAS_BIAS -} -#endif // defined(DILATION_X) && defined(DILATION_Y) - -/** This opencl kernel performs im2col when the kernel size is 3x3 and the data layout is NCHW - * - * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float - * @note The width and height of the input tensor must be passed at compile time using -DSRC_WIDTH and -DSRC_HEIGHT: e.g. -DSRC_WIDTH=128 and -DSRC_HEIGHT=128 - * @note The width of output tensor after matrix multiplication must be passed at compile time using -DCONVOLVED_WIDTH: e.g. -DCONVOLVED_WIDTH=34 - * @note The number of input channels must be passed at compile time using -DSRC_DEPTH: e.g. -DSRC_DEPTH=3 - * @note The pad_left, pad_right, pad_top and pad_bottom must be passed at compile time using -DPAD_LEFT, -DPAD_RIGHT, -DPAD_TOP and -DPAD_BOTTOM: e.g. -DPAD_LEFT=1, -DPAD_RIGHT=2, -DPAD_TOP=3 and -DPAD_BOTTOM=2 - * @note The zero value to store in case we load values out-of-bounds must be passed at compile time using -DPAD_VALUE: e.g. -DPAD_VALUE=0.0 - * @note The stride along the X and Y directions must be passed at compile time using -DSTRIDE_X and -DSTRIDE_Y: e.g. -DSTRIDE_X=1 and -DSTRIDE_Y=1 - * @note In case biases will be added to the convolution -DHAS_BIAS has to be passed to append the final matrix with 1 in each row. - * - * @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8_SIGNED/QASYMM8/F16/F32 - * @param[in] src_stride_x Stride of the source tensor 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 tensor 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 tensor - * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr - * @param[in] dst_stride_x Stride of the destination tensor 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 tensor 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 destination 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 tensor - * @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes). - * @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes). - */ -__kernel void im2col3x3_nchw( - TENSOR3D_DECLARATION(src), -#if defined(NUM_GROUPS) - TENSOR3D_DECLARATION(dst), -#else // defined(NUM_GROUPS) - IMAGE_DECLARATION(dst), -#endif // defined(NUM_GROUPS) - uint src_stride_w, - uint dst_stride_w) -{ - const int xc = get_global_id(0); // x coordinate in the convolved tensor - const int yc = get_global_id(1); // y coordinate in the convolved tensor - const int ch = get_global_id(2) % SRC_DEPTH; // input feature map - const int batch = get_global_id(2) / SRC_DEPTH; // batch size - - // Calculate input indices - const int xi = xc * STRIDE_X - PAD_LEFT; - const int yi = yc * STRIDE_Y - PAD_TOP; - - // Calculate output indices -#if defined(NUM_GROUPS) - const int xo = (ch % (SRC_DEPTH / NUM_GROUPS)) * 9; // 3x3 - const int zo = ch / (SRC_DEPTH / NUM_GROUPS); -#else // defined(NUM_GROUPS) - const int xo = ch * 9; // 3x3 -#endif // defined(NUM_GROUPS) - const int yo = xc + yc * CONVOLVED_WIDTH; // Index of the convolution - - // Get input and output address - __global uchar *input_ptr = src_ptr + src_offset_first_element_in_bytes + xi * (int)src_stride_x + yi * (int)src_stride_y + ch * src_stride_z + batch * src_stride_w; -#if defined(NUM_GROUPS) - __global uchar *output_ptr = dst_ptr + dst_offset_first_element_in_bytes + xo * dst_stride_x + yo * dst_stride_y + zo * dst_stride_z + batch * dst_stride_w; -#else // defined(NUM_GROUPS) - __global uchar *output_ptr = dst_ptr + dst_offset_first_element_in_bytes + xo * dst_stride_x + yo * dst_stride_y + batch * dst_stride_w; -#endif // defined(NUM_GROUPS) - - VEC_DATA_TYPE(DATA_TYPE, 3) - row0 = vload3(0, (__global DATA_TYPE *)(input_ptr + 0 * src_stride_y)); - VEC_DATA_TYPE(DATA_TYPE, 3) - row1 = vload3(0, (__global DATA_TYPE *)(input_ptr + 1 * src_stride_y)); - VEC_DATA_TYPE(DATA_TYPE, 3) - row2 = vload3(0, (__global DATA_TYPE *)(input_ptr + 2 * src_stride_y)); - -#if PAD_LEFT != 0 || PAD_TOP != 0 || PAD_RIGHT != 0 || PAD_BOTTOM != 0 - // Put 0 if the value is out-of-bound - int3 x = (int3)xi + (int3)(0, 1, 2); - int3 y = (int3)yi + (int3)(0, 1, 2); - - VEC_DATA_TYPE(COND_DATA_TYPE, 3) - cond0 = CONVERT((x >= (int3)0 && x < (int3)SRC_WIDTH && (int3)(y.s0 >= 0 && y.s0 < SRC_HEIGHT)), VEC_DATA_TYPE(COND_DATA_TYPE, 3)); - VEC_DATA_TYPE(COND_DATA_TYPE, 3) - cond1 = CONVERT((x >= (int3)0 && x < (int3)SRC_WIDTH && (int3)(y.s1 >= 0 && y.s1 < SRC_HEIGHT)), VEC_DATA_TYPE(COND_DATA_TYPE, 3)); - VEC_DATA_TYPE(COND_DATA_TYPE, 3) - cond2 = CONVERT((x >= (int3)0 && x < (int3)SRC_WIDTH && (int3)(y.s2 >= 0 && y.s2 < SRC_HEIGHT)), VEC_DATA_TYPE(COND_DATA_TYPE, 3)); - - row0 = select((VEC_DATA_TYPE(DATA_TYPE, 3))PAD_VALUE, row0, cond0); - row1 = select((VEC_DATA_TYPE(DATA_TYPE, 3))PAD_VALUE, row1, cond1); - row2 = select((VEC_DATA_TYPE(DATA_TYPE, 3))PAD_VALUE, row2, cond2); -#endif // PAD_LEFT != 0 || PAD_TOP != 0 || PAD_RIGHT != 0 || PAD_BOTTOM != 0 - - vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row0.s012, row1.s012, row2.s01), 0, (__global DATA_TYPE *)output_ptr); - *((__global DATA_TYPE *)output_ptr + 8) = row2.s2; - -#ifdef HAS_BIAS -#if defined(NUM_GROUPS) - if((xo / 9) == (SRC_DEPTH / NUM_GROUPS - 1)) -#else // defined(NUM_GROUPS) - if(ch == (SRC_DEPTH - 1)) -#endif // defined(NUM_GROUPS) - { - *((__global DATA_TYPE *)output_ptr + 9) = 1.0f; - } -#endif // HAS_BIAS -} - -/** This opencl kernel performs im2col when the kernel size is 5x5 and the data layout is NCHW - * - * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float - * @note The width and height of the input tensor must be passed at compile time using -DSRC_WIDTH and -DSRC_HEIGHT: e.g. -DSRC_WIDTH=128 and -DSRC_HEIGHT=128 - * @note The width of output tensor after matrix multiplication must be passed at compile time using -DCONVOLVED_WIDTH: e.g. -DCONVOLVED_WIDTH=34 - * @note The number of input channels must be passed at compile time using -DSRC_DEPTH: e.g. -DSRC_DEPTH=3 - * @note The pad_left, pad_right, pad_top and pad_bottom must be passed at compile time using -DPAD_LEFT, -DPAD_RIGHT, -DPAD_TOP and -DPAD_BOTTOM: e.g. -DPAD_LEFT=1, -DPAD_RIGHT=2, -DPAD_TOP=3 and -DPAD_BOTTOM=2 - * @note The zero value to store in case we load values out-of-bounds must be passed at compile time using -DPAD_VALUE: e.g. -DPAD_VALUE=0.0 - * @note The stride along the X and Y directions must be passed at compile time using -DSTRIDE_X and -DSTRIDE_Y: e.g. -DSTRIDE_X=1 and -DSTRIDE_Y=1 - * @note In case biases will be added to the convolution -DHAS_BIAS has to be passed to append the final matrix with 1 in each row. - * @note In case grouping is performed, the number of groups must be passed at compile time using -DNUM_GROUPS: e.g. -DNUM_GROUPS=4 - * - * @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8_SIGNED/QASYMM8/F16/F32 - * @param[in] src_stride_x Stride of the source tensor 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 tensor 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 tensor - * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr - * @param[in] dst_stride_x Stride of the destination tensor 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 tensor 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 destination 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 tensor - * @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes). - * @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes). - */ -__kernel void im2col5x5_nchw( - TENSOR3D_DECLARATION(src), -#if defined(NUM_GROUPS) - TENSOR3D_DECLARATION(dst), -#else // defined(NUM_GROUPS) - IMAGE_DECLARATION(dst), -#endif // defined(NUM_GROUPS) - uint src_stride_w, - uint dst_stride_w) -{ - const int xc = get_global_id(0); // x coordinate in the convolved tensor - const int yc = get_global_id(1); // y coordinate in the convolved tensor - const int ch = get_global_id(2) % SRC_DEPTH; // input feature map - const int batch = get_global_id(2) / SRC_DEPTH; // batch size - - // Calculate input indices - const int xi = xc * STRIDE_X - PAD_LEFT; - const int yi = yc * STRIDE_Y - PAD_TOP; - - // Calculate output indices -#if defined(NUM_GROUPS) - const int xo = (ch % (SRC_DEPTH / NUM_GROUPS)) * 25; // 5x5 - const int zo = ch / (SRC_DEPTH / NUM_GROUPS); -#else // defined(NUM_GROUPS) - const int xo = ch * 25; // 5x5 -#endif // defined(NUM_GROUPS) - const int yo = xc + yc * CONVOLVED_WIDTH; // Index of the convolution - -#if PAD_LEFT != 0 || PAD_TOP != 0 || PAD_RIGHT != 0 || PAD_BOTTOM != 0 - // Put 0 if the value is out-of-bound - int4 x0 = (int4)xi + (int4)(0, 1, 2, 3); - int4 y0 = (int4)yi + (int4)(0, 1, 2, 3); - int x1 = xi + 4; - int y1 = yi + 4; - - // Check if we could have out-of-bounds elements in the x direction - VEC_DATA_TYPE(COND_DATA_TYPE, 4) - x0_condition = CONVERT((x0 >= (int4)0 && x0 < (int4)SRC_WIDTH), VEC_DATA_TYPE(COND_DATA_TYPE, 4)); - VEC_DATA_TYPE(COND_DATA_TYPE, 4) - y0_condition = CONVERT((y0 >= (int4)0 && y0 < (int4)SRC_HEIGHT), VEC_DATA_TYPE(COND_DATA_TYPE, 4)); - COND_DATA_TYPE x1_condition = (COND_DATA_TYPE)(x1 >= 0 && x1 < SRC_WIDTH); - COND_DATA_TYPE y1_condition = (COND_DATA_TYPE)(y1 >= 0 && y1 < SRC_HEIGHT); -#endif // PAD_LEFT != 0 || PAD_TOP != 0 || PAD_RIGHT != 0 || PAD_BOTTOM != 0 - - // Get input and output address - __global uchar *input_ptr = src_ptr + src_offset_first_element_in_bytes + xi * (int)src_stride_x + yi * (int)src_stride_y + ch * src_stride_z + batch * src_stride_w; -#if defined(NUM_GROUPS) - __global uchar *output_ptr = dst_ptr + dst_offset_first_element_in_bytes + xo * dst_stride_x + yo * dst_stride_y + zo * dst_stride_z + batch * dst_stride_w; -#else // defined(NUM_GROUPS) - __global uchar *output_ptr = dst_ptr + dst_offset_first_element_in_bytes + xo * dst_stride_x + yo * dst_stride_y + batch * dst_stride_w; -#endif // defined(NUM_GROUPS) - - { - VEC_DATA_TYPE(DATA_TYPE, 4) - row00 = vload4(0, (__global DATA_TYPE *)input_ptr); - DATA_TYPE - row01 = *((__global DATA_TYPE *)input_ptr + 4); - - input_ptr += src_stride_y; - - VEC_DATA_TYPE(DATA_TYPE, 4) - row10 = vload4(0, (__global DATA_TYPE *)input_ptr); - DATA_TYPE - row11 = *((__global DATA_TYPE *)input_ptr + 4); - -#if PAD_LEFT != 0 || PAD_TOP != 0 || PAD_RIGHT != 0 || PAD_BOTTOM != 0 - VEC_DATA_TYPE(COND_DATA_TYPE, 4) - cond00 = x0_condition && (VEC_DATA_TYPE(COND_DATA_TYPE, 4))y0_condition.s0; - VEC_DATA_TYPE(COND_DATA_TYPE, 4) - cond10 = x0_condition && (VEC_DATA_TYPE(COND_DATA_TYPE, 4))y0_condition.s1; - COND_DATA_TYPE cond01 = (COND_DATA_TYPE)(x1_condition && y0_condition.s0); - COND_DATA_TYPE cond11 = (COND_DATA_TYPE)(x1_condition && y0_condition.s1); - - // Replace with 0 if the value is not valid - row00 = select((VEC_DATA_TYPE(DATA_TYPE, 4))PAD_VALUE, row00, cond00); - row10 = select((VEC_DATA_TYPE(DATA_TYPE, 4))PAD_VALUE, row10, cond10); - row01 = select((DATA_TYPE)PAD_VALUE, row01, cond01); - row11 = select((DATA_TYPE)PAD_VALUE, row11, cond11); -#endif // PAD_LEFT != 0 || PAD_TOP != 0 || PAD_RIGHT != 0 || PAD_BOTTOM != 0 - - vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s0123, row01, - row10.s012), - 0, (__global DATA_TYPE *)output_ptr); - vstore2((VEC_DATA_TYPE(DATA_TYPE, 2))(row10.s3, row11), 0, (__global DATA_TYPE *)output_ptr + 8); - - input_ptr += src_stride_y; - output_ptr += 10 * dst_stride_x; - } - - { - VEC_DATA_TYPE(DATA_TYPE, 4) - row00 = vload4(0, (__global DATA_TYPE *)input_ptr); - DATA_TYPE - row01 = *((__global DATA_TYPE *)input_ptr + 4); - - input_ptr += src_stride_y; - - VEC_DATA_TYPE(DATA_TYPE, 4) - row10 = vload4(0, (__global DATA_TYPE *)input_ptr); - DATA_TYPE - row11 = *((__global DATA_TYPE *)input_ptr + 4); - -#if PAD_LEFT != 0 || PAD_TOP != 0 || PAD_RIGHT != 0 || PAD_BOTTOM != 0 - VEC_DATA_TYPE(COND_DATA_TYPE, 4) - cond00 = x0_condition && (VEC_DATA_TYPE(COND_DATA_TYPE, 4))y0_condition.s2; - VEC_DATA_TYPE(COND_DATA_TYPE, 4) - cond10 = x0_condition && (VEC_DATA_TYPE(COND_DATA_TYPE, 4))y0_condition.s3; - COND_DATA_TYPE cond01 = (COND_DATA_TYPE)(x1_condition && y0_condition.s2); - COND_DATA_TYPE cond11 = (COND_DATA_TYPE)(x1_condition && y0_condition.s3); - - // Replace with 0 if the value is not valid - row00 = select((VEC_DATA_TYPE(DATA_TYPE, 4))PAD_VALUE, row00, cond00); - row10 = select((VEC_DATA_TYPE(DATA_TYPE, 4))PAD_VALUE, row10, cond10); - row01 = select((DATA_TYPE)PAD_VALUE, row01, cond01); - row11 = select((DATA_TYPE)PAD_VALUE, row11, cond11); -#endif // PAD_LEFT != 0 || PAD_TOP != 0 || PAD_RIGHT != 0 || PAD_BOTTOM != 0 - - vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s0123, row01, - row10.s012), - 0, (__global DATA_TYPE *)output_ptr); - vstore2((VEC_DATA_TYPE(DATA_TYPE, 2))(row10.s3, row11), 0, (__global DATA_TYPE *)output_ptr + 8); - - input_ptr += src_stride_y; - output_ptr += 10 * dst_stride_x; - } - - { - VEC_DATA_TYPE(DATA_TYPE, 4) - row00 = vload4(0, (__global DATA_TYPE *)input_ptr); - DATA_TYPE - row01 = *((__global DATA_TYPE *)input_ptr + 4); - - input_ptr += src_stride_y; - -#if PAD_LEFT != 0 || PAD_TOP != 0 || PAD_RIGHT != 0 || PAD_BOTTOM != 0 - VEC_DATA_TYPE(COND_DATA_TYPE, 4) - cond00 = x0_condition && (VEC_DATA_TYPE(COND_DATA_TYPE, 4))y1_condition; - COND_DATA_TYPE cond01 = (COND_DATA_TYPE)(x1_condition && y1_condition); - - // Replace with 0 if the value is not valid - row00 = select((VEC_DATA_TYPE(DATA_TYPE, 4))PAD_VALUE, row00, cond00); - row01 = select((DATA_TYPE)PAD_VALUE, row01, cond01); -#endif // PAD_LEFT != 0 || PAD_TOP != 0 || PAD_RIGHT != 0 || PAD_BOTTOM != 0 - - vstore4(row00, 0, (__global DATA_TYPE *)output_ptr); - *((__global DATA_TYPE *)output_ptr + 4) = row01; - - output_ptr += 5 * dst_stride_x; - } - -#ifdef HAS_BIAS -#if defined(NUM_GROUPS) - if((xo / 25) == (SRC_DEPTH / NUM_GROUPS - 1)) -#else // defined(NUM_GROUPS) - if(ch == (SRC_DEPTH - 1)) -#endif // defined(NUM_GROUPS) - { - *((__global DATA_TYPE *)output_ptr) = 1.0f; - } -#endif // HAS_BIAS -} -#endif // defined(CONVOLVED_WIDTH) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(STRIDE_X) && defined(STRIDE_Y) && defined(SRC_DEPTH) && defined(PAD_LEFT) && defined(PAD_RIGHT) && defined(PAD_TOP) && defined(PAD_BOTTOM) && defined(PAD_VALUE) - -#if defined(CONVOLVED_WIDTH) && defined(STRIDE_X) && defined(STRIDE_Y) && defined(SRC_DEPTH) -/** This opencl kernel performs im2col when the kernel size is 11x11, we do not have paddings and the data layout is NCHW - * - * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float - * @note The width of output tensor after matrix multiplication must be passed at compile time using -DCONVOLVED_WIDTH: e.g. -DCONVOLVED_WIDTH=34 - * @note The number of input channels must be passed at compile time using -DSRC_DEPTH: e.g. -DSRC_DEPTH=3 - * @note The stride along the X and Y directions must be passed at compile time using -DSTRIDE_X and -DSTRIDE_Y: e.g. -DSTRIDE_X=1 and -DSTRIDE_Y=1 - * @note In case biases will be added to the convolution -DHAS_BIAS has to be passed to append the final matrix with 1 in each row. - * @note In case grouping is performed, the number of groups must be passed at compile time using -DNUM_GROUPS: e.g. -DNUM_GROUPS=4 - * - * @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8_SIGNED/QASYMM8/F16/F32 - * @param[in] src_stride_x Stride of the source tensor 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 tensor 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 tensor - * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr - * @param[in] dst_stride_x Stride of the destination tensor 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 tensor 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 destination 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 tensor - * @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes). - * @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes). - */ -__kernel void im2col11x11_padx0_pady0_nchw( - TENSOR3D_DECLARATION(src), -#if defined(NUM_GROUPS) - TENSOR3D_DECLARATION(dst), -#else // defined(NUM_GROUPS) - IMAGE_DECLARATION(dst), -#endif // defined(NUM_GROUPS) - uint src_stride_w, - uint dst_stride_w) -{ - const int xc = get_global_id(0); // x coordinate in the convolved tensor - const int yc = get_global_id(1); // y coordinate in the convolved tensor - const int ch = get_global_id(2) % SRC_DEPTH; // input feature map - const int batch = get_global_id(2) / SRC_DEPTH; // batch size - - // Calculate input indices - const int xi = xc * STRIDE_X; - const int yi = yc * STRIDE_Y; - - // Calculate output indices -#if defined(NUM_GROUPS) - const int xo = (ch % (SRC_DEPTH / NUM_GROUPS)) * 121; // 11x11 - const int zo = ch / (SRC_DEPTH / NUM_GROUPS); -#else // defined(NUM_GROUPS) - const int xo = ch * 121; // 11x11 -#endif // defined(NUM_GROUPS) - const int yo = xc + yc * CONVOLVED_WIDTH; // Index of the convolution - - // Get input and output address - __global uchar *input_ptr = src_ptr + src_offset_first_element_in_bytes + xi * src_stride_x + yi * src_stride_y + ch * src_stride_z + batch * src_stride_w; -#if defined(NUM_GROUPS) - __global uchar *output_ptr = dst_ptr + dst_offset_first_element_in_bytes + xo * dst_stride_x + yo * dst_stride_y + zo * dst_stride_z + batch * dst_stride_w; -#else // defined(NUM_GROUPS) - __global uchar *output_ptr = dst_ptr + dst_offset_first_element_in_bytes + xo * dst_stride_x + yo * dst_stride_y + batch * dst_stride_w; -#endif // defined(NUM_GROUPS) - - { - VEC_DATA_TYPE(DATA_TYPE, 8) - row00 = vload8(0, (__global DATA_TYPE *)(input_ptr)); - VEC_DATA_TYPE(DATA_TYPE, 3) - row01 = vload3(0, (__global DATA_TYPE *)(input_ptr) + 8); - - vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s01234567), 0, (__global DATA_TYPE *)output_ptr); - vstore3((VEC_DATA_TYPE(DATA_TYPE, 3))(row01.s012), 0, (__global DATA_TYPE *)output_ptr + 8); - - input_ptr += src_stride_y; - output_ptr += 11 * src_stride_x; - } - - { - VEC_DATA_TYPE(DATA_TYPE, 8) - row00 = vload8(0, (__global DATA_TYPE *)(input_ptr)); - VEC_DATA_TYPE(DATA_TYPE, 3) - row01 = vload3(0, (__global DATA_TYPE *)(input_ptr) + 8); - - vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s01234567), 0, (__global DATA_TYPE *)output_ptr); - vstore3((VEC_DATA_TYPE(DATA_TYPE, 3))(row01.s012), 0, (__global DATA_TYPE *)output_ptr + 8); - - input_ptr += src_stride_y; - output_ptr += 11 * src_stride_x; - } - - { - VEC_DATA_TYPE(DATA_TYPE, 8) - row00 = vload8(0, (__global DATA_TYPE *)(input_ptr)); - VEC_DATA_TYPE(DATA_TYPE, 3) - row01 = vload3(0, (__global DATA_TYPE *)(input_ptr) + 8); - - vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s01234567), 0, (__global DATA_TYPE *)output_ptr); - vstore3((VEC_DATA_TYPE(DATA_TYPE, 3))(row01.s012), 0, (__global DATA_TYPE *)output_ptr + 8); - - input_ptr += src_stride_y; - output_ptr += 11 * src_stride_x; - } - - { - VEC_DATA_TYPE(DATA_TYPE, 8) - row00 = vload8(0, (__global DATA_TYPE *)(input_ptr)); - VEC_DATA_TYPE(DATA_TYPE, 3) - row01 = vload3(0, (__global DATA_TYPE *)(input_ptr) + 8); - - vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s01234567), 0, (__global DATA_TYPE *)output_ptr); - vstore3((VEC_DATA_TYPE(DATA_TYPE, 3))(row01.s012), 0, (__global DATA_TYPE *)output_ptr + 8); - - input_ptr += src_stride_y; - output_ptr += 11 * src_stride_x; - } - - { - VEC_DATA_TYPE(DATA_TYPE, 8) - row00 = vload8(0, (__global DATA_TYPE *)(input_ptr)); - VEC_DATA_TYPE(DATA_TYPE, 3) - row01 = vload3(0, (__global DATA_TYPE *)(input_ptr) + 8); - - vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s01234567), 0, (__global DATA_TYPE *)output_ptr); - vstore3((VEC_DATA_TYPE(DATA_TYPE, 3))(row01.s012), 0, (__global DATA_TYPE *)output_ptr + 8); - - input_ptr += src_stride_y; - output_ptr += 11 * src_stride_x; - } - - { - VEC_DATA_TYPE(DATA_TYPE, 8) - row00 = vload8(0, (__global DATA_TYPE *)(input_ptr)); - VEC_DATA_TYPE(DATA_TYPE, 3) - row01 = vload3(0, (__global DATA_TYPE *)(input_ptr) + 8); - - vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s01234567), 0, (__global DATA_TYPE *)output_ptr); - vstore3((VEC_DATA_TYPE(DATA_TYPE, 3))(row01.s012), 0, (__global DATA_TYPE *)output_ptr + 8); - - input_ptr += src_stride_y; - output_ptr += 11 * src_stride_x; - } - - { - VEC_DATA_TYPE(DATA_TYPE, 8) - row00 = vload8(0, (__global DATA_TYPE *)(input_ptr)); - VEC_DATA_TYPE(DATA_TYPE, 3) - row01 = vload3(0, (__global DATA_TYPE *)(input_ptr) + 8); - - vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s01234567), 0, (__global DATA_TYPE *)output_ptr); - vstore3((VEC_DATA_TYPE(DATA_TYPE, 3))(row01.s012), 0, (__global DATA_TYPE *)output_ptr + 8); - - input_ptr += src_stride_y; - output_ptr += 11 * src_stride_x; - } - - { - VEC_DATA_TYPE(DATA_TYPE, 8) - row00 = vload8(0, (__global DATA_TYPE *)(input_ptr)); - VEC_DATA_TYPE(DATA_TYPE, 3) - row01 = vload3(0, (__global DATA_TYPE *)(input_ptr) + 8); - - vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s01234567), 0, (__global DATA_TYPE *)output_ptr); - vstore3((VEC_DATA_TYPE(DATA_TYPE, 3))(row01.s012), 0, (__global DATA_TYPE *)output_ptr + 8); - - input_ptr += src_stride_y; - output_ptr += 11 * src_stride_x; - } - - { - VEC_DATA_TYPE(DATA_TYPE, 8) - row00 = vload8(0, (__global DATA_TYPE *)(input_ptr)); - VEC_DATA_TYPE(DATA_TYPE, 3) - row01 = vload3(0, (__global DATA_TYPE *)(input_ptr) + 8); - - vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s01234567), 0, (__global DATA_TYPE *)output_ptr); - vstore3((VEC_DATA_TYPE(DATA_TYPE, 3))(row01.s012), 0, (__global DATA_TYPE *)output_ptr + 8); - - input_ptr += src_stride_y; - output_ptr += 11 * src_stride_x; - } - - { - VEC_DATA_TYPE(DATA_TYPE, 8) - row00 = vload8(0, (__global DATA_TYPE *)(input_ptr)); - VEC_DATA_TYPE(DATA_TYPE, 3) - row01 = vload3(0, (__global DATA_TYPE *)(input_ptr) + 8); - - vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s01234567), 0, (__global DATA_TYPE *)output_ptr); - vstore3((VEC_DATA_TYPE(DATA_TYPE, 3))(row01.s012), 0, (__global DATA_TYPE *)output_ptr + 8); - - input_ptr += src_stride_y; - output_ptr += 11 * src_stride_x; - } - - { - VEC_DATA_TYPE(DATA_TYPE, 8) - row00 = vload8(0, (__global DATA_TYPE *)(input_ptr)); - VEC_DATA_TYPE(DATA_TYPE, 3) - row01 = vload3(0, (__global DATA_TYPE *)(input_ptr) + 8); - - vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s01234567), 0, (__global DATA_TYPE *)output_ptr); - vstore3((VEC_DATA_TYPE(DATA_TYPE, 3))(row01.s012), 0, (__global DATA_TYPE *)output_ptr + 8); - - output_ptr += 11 * src_stride_x; - } - -#ifdef HAS_BIAS -#if defined(NUM_GROUPS) - if((xo / 121) == (SRC_DEPTH / NUM_GROUPS - 1)) -#else // defined(NUM_GROUPS) - if(ch == (SRC_DEPTH - 1)) -#endif // defined(NUM_GROUPS) - { - *((__global DATA_TYPE *)output_ptr) = 1.0f; - } -#endif // HAS_BIAS -} -#endif // defined(CONVOLVED_WIDTH) && defined(STRIDE_X) && defined(STRIDE_Y) && defined(SRC_DEPTH) - -#if defined(CONVOLVED_WIDTH) && defined(STRIDE_X) && defined(STRIDE_Y) && defined(KERNEL_WIDTH) && defined(KERNEL_HEIGHT) && defined(SRC_DEPTH) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(VECTOR_SIZE) && defined(WIDTH_MOD_VECTOR_SIZE) -/** This opencl kernel performs im2col when the kernel size is greater than 1x1, we do not have paddings and the data layout is NCHW - * - * @note The data type must be passed at compile time using -DDATA_TYPE e.g. -DDATA_TYPE=float. - * @note The vector size must be passed at compile time using -DVECTOR_SIZE e.g. -DVECTOR_SIZE=4. - * @note The width modulo vector size must be passed at compile time using -DWIDTH_MOD_VECTOR_SIZE e.g. -DWIDTH_MOD_VECTOR_SIZE=3. - * @note The stride along the X and Y directions must be passed at compile time using -DSTRIDE_X and -DSTRIDE_Y: e.g. -DSTRIDE_X=1 and -DSTRIDE_Y=1 - * @note In case biases will be added to the convolution -DHAS_BIAS has to be passed to append the final matrix with 1 in each row. - * @note In case grouping is performed, the number of groups must be passed at compile time using -DNUM_GROUPS: e.g. -DNUM_GROUPS=4 - * - * @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8_SIGNED/QASYMM8/F16/F32 - * @param[in] src_stride_x Stride of the source tensor 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 tensor 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 tensor - * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr - * @param[in] dst_stride_x Stride of the destination tensor 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 tensor 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 destination 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 tensor - * @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes). - * @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes). - */ -__kernel void im2col_generic_padx0_pady0_nchw( - TENSOR3D_DECLARATION(src), -#if defined(NUM_GROUPS) - TENSOR3D_DECLARATION(dst), -#else // defined(NUM_GROUPS) - IMAGE_DECLARATION(dst), -#endif // defined(NUM_GROUPS) - uint src_stride_w, - uint dst_stride_w) -{ - const int xc = get_global_id(0); // x coordinate in the convolved tensor - const int yc = get_global_id(1); // y coordinate in the convolved tensor - const int ch = get_global_id(2) % SRC_DEPTH; // input feature map - const int batch = get_global_id(2) / SRC_DEPTH; // batch size - - // Calculate input indices - const int xi = xc * STRIDE_X; - const int yi = yc * STRIDE_Y; - - // Calculate output indices -#if defined(NUM_GROUPS) - const int xo = (ch % (SRC_DEPTH / NUM_GROUPS)) * KERNEL_WIDTH * KERNEL_HEIGHT; - const int zo = ch / (SRC_DEPTH / NUM_GROUPS); -#else // defined(NUM_GROUPS) - const int xo = ch * KERNEL_WIDTH * KERNEL_HEIGHT; -#endif // defined(NUM_GROUPS) - const int yo = xc + yc * CONVOLVED_WIDTH; // Index of the convolution - - __global uchar *input_ptr = src_ptr + src_offset_first_element_in_bytes + ch * src_stride_z + batch * src_stride_w; -#if defined(NUM_GROUPS) - __global DATA_TYPE *output_ptr = ((__global DATA_TYPE *)(dst_ptr + dst_offset_first_element_in_bytes + yo * dst_stride_y + zo * dst_stride_z + batch * dst_stride_w)) + xo; -#else // defined(NUM_GROUPS) - __global DATA_TYPE *output_ptr = ((__global DATA_TYPE *)(dst_ptr + dst_offset_first_element_in_bytes + yo * dst_stride_y + batch * dst_stride_w)) + xo; -#endif // defined(NUM_GROUPS) - - // Linearize convolution elements - for(int y = yi, y_e = yi + KERNEL_HEIGHT; y < y_e; ++y) - { - int last_x = 0; - for(int x = xi, x_e = xi + KERNEL_WIDTH; x + VECTOR_SIZE <= x_e; x += VECTOR_SIZE, output_ptr += VECTOR_SIZE) - { - VEC_DATA_TYPE(DATA_TYPE, VECTOR_SIZE) - row = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + x * src_stride_x + y * src_stride_y)); - VSTORE(VECTOR_SIZE) - (row, 0, output_ptr); - last_x = x; - } - // Copy the remainder of the row by doing VLOAD(WIDTH_MOD_VECTOR_SIZE) and VSTORE(WIDTH_MOD_VECTOR_SIZE). - // Note that x and output_ptr have already been incremented by VECTOR_SIZE by the loop just before exit. -#if WIDTH_MOD_VECTOR_SIZE == 1 - *output_ptr = *((__global DATA_TYPE *)(input_ptr + (last_x + VECTOR_SIZE) * src_stride_x + y * src_stride_y)); -#elif WIDTH_MOD_VECTOR_SIZE > 1 - VEC_DATA_TYPE(DATA_TYPE, WIDTH_MOD_VECTOR_SIZE) - row = VLOAD(WIDTH_MOD_VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + (last_x + VECTOR_SIZE) * src_stride_x + y * src_stride_y)); - VSTORE(WIDTH_MOD_VECTOR_SIZE) - (row, 0, output_ptr); -#endif /* WIDTH_MOD_VECTOR_SIZE */ - output_ptr += WIDTH_MOD_VECTOR_SIZE; - } /* End of loop over KERNEL_HEIGHT */ - -#ifdef HAS_BIAS -#if defined(NUM_GROUPS) - if((xo / (KERNEL_WIDTH * KERNEL_HEIGHT)) == (SRC_DEPTH / NUM_GROUPS - 1)) -#else // defined(NUM_GROUPS) - if(ch == (SRC_DEPTH - 1)) -#endif // defined(NUM_GROUPS) - { - *output_ptr = 1.0f; - } -#endif // HAS_BIAS -} -#endif //defined(CONVOLVED_WIDTH) && defined(STRIDE_X) && defined(STRIDE_Y) && defined(PAD_LEFT) && defined(PAD_TOP) && defined(PAD_RIGHT) && defined(PAD_BOTTOM) && defined(KERNEL_WIDTH) && defined(KERNEL_HEIGHT) && defined(SRC_DEPTH) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(VECTOR_SIZE) && defined(WIDTH_MOD_VECTOR_SIZE) - -#if defined(CONVOLVED_WIDTH) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(STRIDE_X) && defined(STRIDE_Y) && defined(KERNEL_WIDTH) && defined(KERNEL_HEIGHT) && defined(SRC_DEPTH) && defined(PAD_LEFT) && defined(PAD_RIGHT) && defined(PAD_TOP) && defined(PAD_BOTTOM) && defined(PAD_VALUE) && defined(VECTOR_SIZE) && defined(BOUNDARY_VECTOR_SIZE) - -#define VECTOR_N VEC_DATA_TYPE(DATA_TYPE, VECTOR_SIZE) -#define COND_N VEC_DATA_TYPE(COND_DATA_TYPE, VECTOR_SIZE) - -/** Store a 1x9 row or a 3x3 block in a boundary-aware manner to avoid paddings in the channel dimension - * @name IM2COL1X9_NHWC_STORE - * - * @note To use this macro for a 3x3 block, @p ROW has to be 0 - * - * @param[in] VECTOR_SIZE The non-boundary vector width of @p DATA. Supported: 1(scalar), 2, 3, 4, 8, 16 - * @param[in] BOUNDARY_VECTOR_SIZE The boundary vector width of @p DATA. Supported: 1-16, but has to be <= @p size - * @param[in] DATA_TYPE Data type of @p DATA - * @param[in] SRC_DEPTH Input channel size / depth - * @param[in] DATA Value variable base name - * @param[in] ROW The row number to store. Supported: 0-8 - * @param[in] OUTPUT_PTR Output pointer - * @{ - */ -#if defined(VECTOR_SIZE) && defined(BOUNDARY_VECTOR_SIZE) && BOUNDARY_VECTOR_SIZE < VECTOR_SIZE -#define IM2COL1X9_NHWC_STORE(VECTOR_SIZE, BOUNDARY_VECTOR_SIZE, DATA_TYPE, SRC_DEPTH, DATA, ROW, OUTPUT_PTR) \ - const bool at_channel_boundary = get_global_id(0) == 0; \ - if(at_channel_boundary) \ - { \ - IM2COL1X9_NHWC_STORE_PARTIAL(VECTOR_SIZE, BOUNDARY_VECTOR_SIZE, DATA_TYPE, SRC_DEPTH, DATA, ROW, OUTPUT_PTR) \ - } \ - else \ - { \ - IM2COL1X9_NHWC_STORE_NONPARTIAL(VECTOR_SIZE, DATA_TYPE, SRC_DEPTH, DATA, ROW, OUTPUT_PTR) \ - } -#else // defined(VECTOR_SIZE) && defined(BOUNDARY_VECTOR_SIZE) && BOUNDARY_VECTOR_SIZE < VECTOR_SIZE -#define IM2COL1X9_NHWC_STORE(VECTOR_SIZE, BOUNDARY_VECTOR_SIZE, DATA_TYPE, SRC_DEPTH, DATA, ROW, OUTPUT_PTR) \ - IM2COL1X9_NHWC_STORE_NONPARTIAL(VECTOR_SIZE, DATA_TYPE, SRC_DEPTH, DATA, ROW, OUTPUT_PTR) -#endif // defined(VECTOR_SIZE) && defined(BOUNDARY_VECTOR_SIZE) && BOUNDARY_VECTOR_SIZE < VECTOR_SIZE - -#define IM2COL1X9_NHWC_STORE_NONPARTIAL(VECTOR_SIZE, DATA_TYPE, SRC_DEPTH, DATA, ROW, OUTPUT_PTR) \ - VSTORE(VECTOR_SIZE) \ - (DATA##0, 0, (__global DATA_TYPE *)(OUTPUT_PTR) + (0 + ROW * 9) * SRC_DEPTH); \ - VSTORE(VECTOR_SIZE) \ - (DATA##1, 0, (__global DATA_TYPE *)(OUTPUT_PTR) + (1 + ROW * 9) * SRC_DEPTH); \ - VSTORE(VECTOR_SIZE) \ - (DATA##2, 0, (__global DATA_TYPE *)(OUTPUT_PTR) + (2 + ROW * 9) * SRC_DEPTH); \ - VSTORE(VECTOR_SIZE) \ - (DATA##3, 0, (__global DATA_TYPE *)(OUTPUT_PTR) + (3 + ROW * 9) * SRC_DEPTH); \ - VSTORE(VECTOR_SIZE) \ - (DATA##4, 0, (__global DATA_TYPE *)(OUTPUT_PTR) + (4 + ROW * 9) * SRC_DEPTH); \ - VSTORE(VECTOR_SIZE) \ - (DATA##5, 0, (__global DATA_TYPE *)(OUTPUT_PTR) + (5 + ROW * 9) * SRC_DEPTH); \ - VSTORE(VECTOR_SIZE) \ - (DATA##6, 0, (__global DATA_TYPE *)(OUTPUT_PTR) + (6 + ROW * 9) * SRC_DEPTH); \ - VSTORE(VECTOR_SIZE) \ - (DATA##7, 0, (__global DATA_TYPE *)(OUTPUT_PTR) + (7 + ROW * 9) * SRC_DEPTH); \ - VSTORE(VECTOR_SIZE) \ - (DATA##8, 0, (__global DATA_TYPE *)(OUTPUT_PTR) + (8 + ROW * 9) * SRC_DEPTH); - -#define IM2COL1X9_NHWC_STORE_PARTIAL(VECTOR_SIZE, BOUNDARY_VECTOR_SIZE, DATA_TYPE, SRC_DEPTH, DATA, ROW, OUTPUT_PTR) \ - VSTORE_PARTIAL(VECTOR_SIZE, BOUNDARY_VECTOR_SIZE) \ - (DATA##0, 0, (__global DATA_TYPE *)(OUTPUT_PTR) + (0 + ROW * 9) * SRC_DEPTH); \ - VSTORE_PARTIAL(VECTOR_SIZE, BOUNDARY_VECTOR_SIZE) \ - (DATA##1, 0, (__global DATA_TYPE *)(OUTPUT_PTR) + (1 + ROW * 9) * SRC_DEPTH); \ - VSTORE_PARTIAL(VECTOR_SIZE, BOUNDARY_VECTOR_SIZE) \ - (DATA##2, 0, (__global DATA_TYPE *)(OUTPUT_PTR) + (2 + ROW * 9) * SRC_DEPTH); \ - VSTORE_PARTIAL(VECTOR_SIZE, BOUNDARY_VECTOR_SIZE) \ - (DATA##3, 0, (__global DATA_TYPE *)(OUTPUT_PTR) + (3 + ROW * 9) * SRC_DEPTH); \ - VSTORE_PARTIAL(VECTOR_SIZE, BOUNDARY_VECTOR_SIZE) \ - (DATA##4, 0, (__global DATA_TYPE *)(OUTPUT_PTR) + (4 + ROW * 9) * SRC_DEPTH); \ - VSTORE_PARTIAL(VECTOR_SIZE, BOUNDARY_VECTOR_SIZE) \ - (DATA##5, 0, (__global DATA_TYPE *)(OUTPUT_PTR) + (5 + ROW * 9) * SRC_DEPTH); \ - VSTORE_PARTIAL(VECTOR_SIZE, BOUNDARY_VECTOR_SIZE) \ - (DATA##6, 0, (__global DATA_TYPE *)(OUTPUT_PTR) + (6 + ROW * 9) * SRC_DEPTH); \ - VSTORE_PARTIAL(VECTOR_SIZE, BOUNDARY_VECTOR_SIZE) \ - (DATA##7, 0, (__global DATA_TYPE *)(OUTPUT_PTR) + (7 + ROW * 9) * SRC_DEPTH); \ - VSTORE_PARTIAL(VECTOR_SIZE, BOUNDARY_VECTOR_SIZE) \ - (DATA##8, 0, (__global DATA_TYPE *)(OUTPUT_PTR) + (8 + ROW * 9) * SRC_DEPTH); -/** @}*/ - -/** This kernel performs im2col when the kernel size is 3x3 and the data layout is NHWC - * - * @note This kernel computes VECTOR_SIZE elements - * @note This kernel stores VECTOR_SIZE or BOUNDARY_VECTOR_SIZE (if at boundary) elements - * @note The vector size must be passed at compile time using -DVECTOR_SIZE: e.g. -DVECTOR_SIZE=2 - * @note The boundary vector size must be passed at compile time using -DBOUNDARY_VECTOR_SIZE: e.g. -DBOUNDARY_VECTOR_SIZE=1 - * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float - * @note The width of output tensor after matrix multiplication must be passed at compile time using -DCONVOLVED_WIDTH: e.g. -DCONVOLVED_WIDTH=34 - * @note The kernel depth must be passed at compile time using -DSRC_DEPTH: e.g. -DSRC_DEPTH=3 - * @note The stride along the Y direction must be passed at compile time using -DSTRIDE_Y: e.g. -DSTRIDE_Y=1 - * @note In case biases will be added to the convolution -DHAS_BIAS has to be passed to append the final matrix with 1 in each row. - * - * @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8_SIGNED/QASYMM8/F16/F32 - * @param[in] src_stride_x Stride of the source tensor 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 tensor 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 tensor - * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr - * @param[in] dst_stride_x Stride of the destination tensor 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 tensor 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_offset_first_element_in_bytes The offset of the first element in the destination tensor - * @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes). - * @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes). - */ -__kernel void im2col3x3_nhwc( - TENSOR3D_DECLARATION(src), - IMAGE_DECLARATION(dst), - uint src_stride_w, - uint dst_stride_w) -{ - // input feature map, boundary-corrected (shift all non-boundary vectors by shift_amount) to avoid padding - const int shift_amount = (int)VECTOR_SIZE - (int)BOUNDARY_VECTOR_SIZE; - const int ch = max((int)(get_global_id(0) * VECTOR_SIZE) - shift_amount, 0); - const int yo = get_global_id(1); - const int batch = get_global_id(2); // batch size - - // Calculate input indices - const int xi = (get_global_id(1) % CONVOLVED_WIDTH) * STRIDE_X; - const int yi = (get_global_id(1) / (int)CONVOLVED_WIDTH) * STRIDE_Y; - - // Get input and output address - __global uchar *input_ptr = src_ptr + src_offset_first_element_in_bytes + ch * sizeof(DATA_TYPE) + batch * (int)src_stride_w; - __global uchar *output_ptr = dst_ptr + dst_offset_first_element_in_bytes + ch * sizeof(DATA_TYPE) + yo * (int)dst_stride_y + batch * (int)dst_stride_w; - - int yi_coord = 0; - int3 offset = 0; - - // Clamp xi - int3 xi_offset = ((int3)xi + (int3)(0, 1, 2) * DILATION_X - (int3)PAD_LEFT); -#if PAD_LEFT != 0 || PAD_RIGHT != 0 -#define CLAMP(x, min_val, max_val) min(max(x, min_val), max_val) - xi_offset = CLAMP(xi_offset, (int3)0, (int3)(SRC_WIDTH - 1)); -#endif // PAD_LEFT != 0 || PAD_RIGHT != 0 - // Multiply by src_stride_y as the width (X) dimension here is the second (y) dimension in src NHWC tensor - xi_offset *= (int3)src_stride_y; - - // Out-of-bound condition for X - int3 x_cond = (((int3)xi + (int3)(0, 1, 2) * DILATION_X - (int3)PAD_LEFT) < (int3)0) || (((int3)xi + (int3)(0, 1, 2) * DILATION_X - (int3)PAD_LEFT) >= (int3)SRC_WIDTH); - - // yi == 0 - // Clamp yi - // yi_coord is casted to unsigned int in order to use just a min() operation - // A "-1" 32 bit signed variable converted to unsigned gives 4294967295 - // This is a trick so that the values loaded in the padding areas are always from the last row (SRC_HEIGHT - 1), - // because of the negative yi_coord wrap-around, but it gets overwritten by PAD_VALUE immediately as the wrap-around - // also causes y_cond (y padding condition) to be satisfied - yi_coord = yi - (int)PAD_TOP; - - // Clamp only if PAD_TOP or PAD_BOTTOM is not equal to 0 -#if PAD_TOP != 0 || PAD_BOTTOM != 0 - yi_coord = min((uint)yi_coord, (uint)(SRC_HEIGHT - 1)); -#endif // PAD_TOP != 0 || PAD_BOTTOM != 0 - - // Compute offset - offset = xi_offset + (yi_coord * (int)src_stride_z); - - // Load input values - VECTOR_N values0 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset.s0)); - VECTOR_N values1 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset.s1)); - VECTOR_N values2 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset.s2)); - -#if PAD_TOP != 0 || PAD_LEFT != 0 || PAD_BOTTOM != 0 || PAD_RIGHT != 0 - // Replace invalid values with PAD_VALUE - int y_cond = (int)((uint)(yi - (int)PAD_TOP) >= (uint)(SRC_HEIGHT)); - values0 = select(values0, (VECTOR_N)PAD_VALUE, (COND_N)((COND_N)y_cond || (COND_N)(x_cond.s0))); - values1 = select(values1, (VECTOR_N)PAD_VALUE, (COND_N)((COND_N)y_cond || (COND_N)(x_cond.s1))); - values2 = select(values2, (VECTOR_N)PAD_VALUE, (COND_N)((COND_N)y_cond || (COND_N)(x_cond.s2))); -#endif // PAD_TOP != 0 || PAD_LEFT != 0 || PAD_BOTTOM != 0 || PAD_RIGHT != 0 - - // yi == 1 - // Clamp yi_coord (it can be negative if PAD_TOP > 1) - yi_coord = yi - (int)PAD_TOP + 1 * DILATION_Y; - - // Clamp only if PAD_TOP or PAD_BOTTOM is not equal to 0 -#if PAD_TOP != 0 || PAD_BOTTOM != 0 - yi_coord = min((uint)yi_coord, (uint)(SRC_HEIGHT - 1)); -#endif // PAD_TOP != 0 || PAD_BOTTOM != 0 - - // Compute offset - offset = xi_offset + (yi_coord * (int)src_stride_z); - - // Load input values - VECTOR_N values3 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset.s0)); - VECTOR_N values4 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset.s1)); - VECTOR_N values5 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset.s2)); - -#if PAD_TOP != 0 || PAD_LEFT != 0 || PAD_BOTTOM != 0 || PAD_RIGHT != 0 - // Replace invalid values with zeros - y_cond = (int)((uint)(yi - (int)PAD_TOP + 1 * DILATION_Y) >= (uint)(SRC_HEIGHT)); - values3 = select(values3, (VECTOR_N)PAD_VALUE, (COND_N)((COND_N)y_cond || (COND_N)(x_cond.s0))); - values4 = select(values4, (VECTOR_N)PAD_VALUE, (COND_N)((COND_N)y_cond || (COND_N)(x_cond.s1))); - values5 = select(values5, (VECTOR_N)PAD_VALUE, (COND_N)((COND_N)y_cond || (COND_N)(x_cond.s2))); -#endif // PAD_TOP != 0 || PAD_LEFT != 0 || PAD_BOTTOM != 0 || PAD_RIGHT != 0 - - // yi == 2 - // Clamp yi_coord - yi_coord = yi - (int)PAD_TOP + 2 * DILATION_Y; - - // Clamp only if PAD_TOP or PAD_BOTTOM is not equal to 0 -#if PAD_TOP != 0 || PAD_BOTTOM != 0 - yi_coord = min((uint)yi_coord, (uint)(SRC_HEIGHT - 1)); -#endif // PAD_TOP != 0 || PAD_BOTTOM != 0 - - // Compute offset - offset = xi_offset + (yi_coord * (int)src_stride_z); - - // Load input values - VECTOR_N values6 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset.s0)); - VECTOR_N values7 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset.s1)); - VECTOR_N values8 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset.s2)); - -#if PAD_TOP != 0 || PAD_LEFT != 0 || PAD_BOTTOM != 0 || PAD_RIGHT != 0 - // Replace invalid values with PAD_VALUE - y_cond = (int)((uint)(yi - (int)PAD_TOP + 2 * DILATION_Y) >= (uint)(SRC_HEIGHT)); - values6 = select(values6, (VECTOR_N)PAD_VALUE, (COND_N)((COND_N)y_cond || (COND_N)(x_cond.s0))); - values7 = select(values7, (VECTOR_N)PAD_VALUE, (COND_N)((COND_N)y_cond || (COND_N)(x_cond.s1))); - values8 = select(values8, (VECTOR_N)PAD_VALUE, (COND_N)((COND_N)y_cond || (COND_N)(x_cond.s2))); -#endif // PAD_TOP != 0 || PAD_LEFT != 0 || PAD_BOTTOM != 0 || PAD_RIGHT != 0 - - // Store in a boundary-aware way to avoid padding - IM2COL1X9_NHWC_STORE(VECTOR_SIZE, BOUNDARY_VECTOR_SIZE, DATA_TYPE, SRC_DEPTH, values, 0, output_ptr) - -#ifdef HAS_BIAS - // We can use VECTOR_SIZE instead of BOUNDARY_VECTOR_SIZE even if it's at the boundary. This is because the bias is - // added at the end of the channel, while the boundary vec is at the beginning of the channel. - // The only case where the boundary vec is at the end of the channel is when there's only a single boundary vec in - // the whole channel dimension, but in that case VECTOR_SIZE is also equal to BOUNDARY_VECTOR_SIZE - // See the value of num_elems_processed_per_iteration in configure_opencl_kernel method in CLIm2ColKernel.cpp - if((ch + VECTOR_SIZE) >= SRC_DEPTH) - { - *((__global DATA_TYPE *)(output_ptr) - ch + SRC_DEPTH * 9) = 1.0f; - } -#endif // HAS_BIAS -} - -#if PAD_TOP != 0 || PAD_LEFT != 0 || PAD_BOTTOM != 0 || PAD_RIGHT != 0 -#define IM2COL1x9(i) \ - ({ \ - yi_coord = yi - (int)PAD_TOP + i * DILATION_Y; \ - yi_coord = min((uint)yi_coord, (uint)(SRC_HEIGHT - 1)); \ - \ - offset0 = xi_offset0 + (yi_coord * (int)src_stride_z); \ - offset1 = xi_offset1 + (yi_coord * (int)src_stride_z); \ - \ - VECTOR_N values0 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset0.s0)); \ - VECTOR_N values1 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset0.s1)); \ - VECTOR_N values2 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset0.s2)); \ - VECTOR_N values3 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset0.s3)); \ - VECTOR_N values4 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset0.s4)); \ - VECTOR_N values5 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset0.s5)); \ - VECTOR_N values6 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset0.s6)); \ - VECTOR_N values7 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset0.s7)); \ - VECTOR_N values8 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset1)); \ - \ - int y_cond = (int)((uint)(yi - (int)PAD_TOP + i * DILATION_Y) >= (uint)(SRC_HEIGHT)); \ - values0 = select(values0, (VECTOR_N)PAD_VALUE, (COND_N)((COND_N)y_cond || (COND_N)(x_cond0.s0))); \ - values1 = select(values1, (VECTOR_N)PAD_VALUE, (COND_N)((COND_N)y_cond || (COND_N)(x_cond0.s1))); \ - values2 = select(values2, (VECTOR_N)PAD_VALUE, (COND_N)((COND_N)y_cond || (COND_N)(x_cond0.s2))); \ - values3 = select(values3, (VECTOR_N)PAD_VALUE, (COND_N)((COND_N)y_cond || (COND_N)(x_cond0.s3))); \ - values4 = select(values4, (VECTOR_N)PAD_VALUE, (COND_N)((COND_N)y_cond || (COND_N)(x_cond0.s4))); \ - values5 = select(values5, (VECTOR_N)PAD_VALUE, (COND_N)((COND_N)y_cond || (COND_N)(x_cond0.s5))); \ - values6 = select(values6, (VECTOR_N)PAD_VALUE, (COND_N)((COND_N)y_cond || (COND_N)(x_cond0.s6))); \ - values7 = select(values7, (VECTOR_N)PAD_VALUE, (COND_N)((COND_N)y_cond || (COND_N)(x_cond0.s7))); \ - values8 = select(values8, (VECTOR_N)PAD_VALUE, (COND_N)((COND_N)y_cond || (COND_N)(x_cond1))); \ - \ - IM2COL1X9_NHWC_STORE(VECTOR_SIZE, BOUNDARY_VECTOR_SIZE, DATA_TYPE, SRC_DEPTH, values, i, output_ptr) \ - }) -#else // PAD_TOP != 0 || PAD_LEFT != 0 || PAD_BOTTOM != 0 || PAD_RIGHT != 0 -#define IM2COL1x9(i) \ - ({ \ - yi_coord = yi - (int)PAD_TOP + i * DILATION_Y; \ - yi_coord = min((uint)yi_coord, (uint)(SRC_HEIGHT - 1)); \ - \ - offset0 = xi_offset0 + (yi_coord * (int)src_stride_z); \ - offset1 = xi_offset1 + (yi_coord * (int)src_stride_z); \ - \ - VECTOR_N values0 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset0.s0)); \ - VECTOR_N values1 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset0.s1)); \ - VECTOR_N values2 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset0.s2)); \ - VECTOR_N values3 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset0.s3)); \ - VECTOR_N values4 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset0.s4)); \ - VECTOR_N values5 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset0.s5)); \ - VECTOR_N values6 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset0.s6)); \ - VECTOR_N values7 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset0.s7)); \ - VECTOR_N values8 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset1)); \ - \ - IM2COL1X9_NHWC_STORE(VECTOR_SIZE, BOUNDARY_VECTOR_SIZE, DATA_TYPE, SRC_DEPTH, values, i, output_ptr) \ - }) -#endif // PAD_TOP != 0 || PAD_LEFT != 0 || PAD_BOTTOM != 0 || PAD_RIGHT != 0 - -/** This kernel performs im2col when the kernel size is 9x9 and the data layout is NHWC - * - * @note This kernel computes VECTOR_SIZE elements - * @note This kernel stores VECTOR_SIZE or BOUNDARY_VECTOR_SIZE (if at boundary) elements - * @note The vector size must be passed at compile time using -DVECTOR_SIZE: e.g. -DVECTOR_SIZE=2 - * @note The boundary vector size must be passed at compile time using -DBOUNDARY_VECTOR_SIZE: e.g. -DBOUNDARY_VECTOR_SIZE=1 - * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float - * @note The width of output tensor after matrix multiplication must be passed at compile time using -DCONVOLVED_WIDTH: e.g. -DCONVOLVED_WIDTH=34 - * @note The kernel depth must be passed at compile time using -DSRC_DEPTH: e.g. -DSRC_DEPTH=3 - * @note The stride along the Y direction must be passed at compile time using -DSTRIDE_Y: e.g. -DSTRIDE_Y=1 - * @note In case biases will be added to the convolution -DHAS_BIAS has to be passed to append the final matrix with 1 in each row. - * - * @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8_SIGNED/QASYMM8/F16/F32 - * @param[in] src_stride_x Stride of the source tensor 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 tensor 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 tensor - * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr - * @param[in] dst_stride_x Stride of the destination tensor 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 tensor 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_offset_first_element_in_bytes The offset of the first element in the destination tensor - * @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes). - * @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes). - */ -__kernel void im2col9x9_nhwc( - TENSOR3D_DECLARATION(src), - IMAGE_DECLARATION(dst), - uint src_stride_w, - uint dst_stride_w) -{ - // input feature map, boundary-corrected (shift all non-boundary vectors by shift_amount) to avoid padding - const int shift_amount = (int)VECTOR_SIZE - (int)BOUNDARY_VECTOR_SIZE; - const int ch = max((int)(get_global_id(0) * VECTOR_SIZE) - shift_amount, 0); - const int yo = get_global_id(1); - const int batch = get_global_id(2); // batch size - - // Calculate input indices - const int xi = (get_global_id(1) % CONVOLVED_WIDTH) * STRIDE_X; - const int yi = (get_global_id(1) / (int)CONVOLVED_WIDTH) * STRIDE_Y; - - // Get input and output address - __global uchar *input_ptr = src_ptr + src_offset_first_element_in_bytes + ch * sizeof(DATA_TYPE) + batch * (int)src_stride_w; - __global uchar *output_ptr = dst_ptr + dst_offset_first_element_in_bytes + ch * sizeof(DATA_TYPE) + yo * (int)dst_stride_y + batch * (int)dst_stride_w; - - int yi_coord = 0; - int8 offset0 = 0; - int offset1 = 0; - - // Clamp xi - int8 xi_offset0 = ((int8)xi + (int8)(0, 1, 2, 3, 4, 5, 6, 7) * DILATION_X - (int8)PAD_LEFT); - int xi_offset1 = ((int)xi + (int)(8) * DILATION_X - (int)PAD_LEFT); - -#if PAD_LEFT != 0 || PAD_RIGHT != 0 -#define CLAMP(x, min_val, max_val) min(max(x, min_val), max_val) - xi_offset0 = CLAMP(xi_offset0, (int8)0, (int8)(SRC_WIDTH - 1)); - xi_offset1 = CLAMP(xi_offset1, (int)0, (int)(SRC_WIDTH - 1)); -#endif // PAD_LEFT != 0 || PAD_RIGHT != 0 - xi_offset0 *= (int8)src_stride_y; - xi_offset1 *= (int)src_stride_y; - - // Out-of-bound condition for X - int8 x_cond0 = (((int8)xi + (int8)(0, 1, 2, 3, 4, 5, 6, 7) * DILATION_X - (int8)PAD_LEFT) < (int8)0) || (((int8)xi + (int8)(0, 1, 2, 3, 4, 5, 6, 7) * DILATION_X - (int8)PAD_LEFT) >= (int8)SRC_WIDTH); - int x_cond1 = (((int)xi + (int)(8) * DILATION_X - (int)PAD_LEFT) < (int)0) || (((int)xi + (int)(8) * DILATION_X - (int)PAD_LEFT) >= (int)SRC_WIDTH); - - IM2COL1x9(0); - IM2COL1x9(1); - IM2COL1x9(2); - IM2COL1x9(3); - IM2COL1x9(4); - IM2COL1x9(5); - IM2COL1x9(6); - IM2COL1x9(7); - IM2COL1x9(8); - -#ifdef HAS_BIAS - // We can use VECTOR_SIZE instead of BOUNDARY_VECTOR_SIZE even if it's at the boundary. This is because the bias is - // added at the end of the channel, while the boundary vec is at the beginning of the channel. - // The only case where the boundary vec is at the end of the channel is when there's only a single boundary vec in - // the whole channel dimension, but in that case VECTOR_SIZE is also equal to BOUNDARY_VECTOR_SIZE - // See the value of num_elems_processed_per_iteration in configure_opencl_kernel method in CLIm2ColKernel.cpp - if((ch + VECTOR_SIZE) >= SRC_DEPTH) - { - *((__global DATA_TYPE *)(output_ptr) - ch + SRC_DEPTH * 81) = 1.0f; - } -#endif // HAS_BIAS -} - -/** This opencl kernel performs a generic im2col implementation when the data layout is NHWC - * - * @note This kernel computes VECTOR_SIZE elements - * @note This kernel stores VECTOR_SIZE or BOUNDARY_VECTOR_SIZE (if at boundary) elements - * @note The vector size must be passed at compile time using -DVECTOR_SIZE: e.g. -DVECTOR_SIZE=2 - * @note The boundary vector size must be passed at compile time using -DBOUNDARY_VECTOR_SIZE: e.g. -DBOUNDARY_VECTOR_SIZE=1 - * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float - * @note The width and height of the input tensor must be passed at compile time using -DSRC_WIDTH and -DSRC_HEIGHT: e.g. -DSRC_WIDTH=128 and -DSRC_HEIGHT=128 - * @note The width of output tensor after matrix multiplication must be passed at compile time using -DCONVOLVED_WIDTH: e.g. -DCONVOLVED_WIDTH=34 - * @note The kernel width, height and depth must be passed at compile time using -DKERNEL_WIDTH, -DKERNEL_HEIGHT and -DSRC_DEPTH: e.g. -DKERNEL_WIDTH=3, -DKERNEL_HEIGHT=3 and -DSRC_DEPTH=64 - * @note The pad_left, pad_right, pad_top and pad_bottom must be passed at compile time using -DPAD_LEFT, -DPAD_RIGHT, -DPAD_TOP and -DPAD_BOTTOM: e.g. -DPAD_LEFT=1, -DPAD_RIGHT=2, -DPAD_TOP=3 and -DPAD_BOTTOM=2 - * @note The zero value to store in case we load values out-of-bounds must be passed at compile time using -DPAD_VALUE: e.g. -DPAD_VALUE=0.0 - * @note The stride along the X and Y directions must be passed at compile time using -DSTRIDE_X and -DSTRIDE_Y: e.g. -DSTRIDE_X=1 and -DSTRIDE_Y=1 - * @note The dilation_x and dilation_y must be passed at compile time using -DDILATION_X and -DDILATION_Y: e.g. -DDILATION_X=1, -DDILATION_Y=1 - * @note In case biases will be added to the convolution -DHAS_BIAS has to be passed to append the final matrix with 1 in each row. - * - * @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8_SIGNED/QASYMM8/F16/F32 - * @param[in] src_stride_x Stride of the source tensor 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 tensor 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 tensor - * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr - * @param[in] dst_stride_x Stride of the destination tensor 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 tensor 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_offset_first_element_in_bytes The offset of the first element in the destination tensor - * @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes). - * @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes). - */ -__kernel void im2col_generic_nhwc( - TENSOR3D_DECLARATION(src), - IMAGE_DECLARATION(dst), - uint src_stride_w, - uint dst_stride_w) -{ - // input feature map, boundary-corrected (shift all non-boundary vectors by shift_amount) to avoid padding - const int shift_amount = (int)VECTOR_SIZE - (int)BOUNDARY_VECTOR_SIZE; - const int ch = max((int)(get_global_id(0) * VECTOR_SIZE) - shift_amount, 0); - const int yo = get_global_id(1); - const int batch = get_global_id(2); // batch size - - // Calculate input indices - const int xi = (get_global_id(1) % CONVOLVED_WIDTH) * STRIDE_X; - const int yi = (get_global_id(1) / (int)CONVOLVED_WIDTH) * STRIDE_Y; - - // Get input and output address - __global uchar *input_ptr = src_ptr + src_offset_first_element_in_bytes + ch * sizeof(DATA_TYPE) + batch * (int)src_stride_w; - __global uchar *output_ptr = dst_ptr + dst_offset_first_element_in_bytes + ch * sizeof(DATA_TYPE) + yo * (int)dst_stride_y + batch * (int)dst_stride_w; - - int i = 0; - for(int yk = 0; yk < KERNEL_HEIGHT; ++yk) - { - // Clamp yi_coord - int yi_coord = yi + yk * DILATION_Y - (int)PAD_TOP; - yi_coord = CLAMP(yi_coord, (int)0, (int)(SRC_HEIGHT - 1)); - - // Out-of-bound condition for Y - int y_border_condition = ((yi + yk * DILATION_Y - (int)PAD_TOP) < (int)0) || ((yi + yk * DILATION_Y - (int)PAD_TOP) >= (int)SRC_HEIGHT); - - for(int xk = 0; xk < KERNEL_WIDTH; ++xk) - { - // Clamp xi_coord - int xi_coord = (xi + xk * DILATION_X - (int)PAD_LEFT); - xi_coord = CLAMP(xi_coord, (int)0, (int)(SRC_WIDTH - 1)); - - // Out-of-bound condition for X - int x_border_condition = ((xi + xk * DILATION_X - (int)PAD_LEFT) < (int)0) || ((xi + xk * DILATION_X - (int)PAD_LEFT) >= (int)SRC_WIDTH); - - int offset = xi_coord * (int)src_stride_y + (yi_coord * (int)src_stride_z); - - VECTOR_N values0 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset)); - -#if PAD_LEFT != 0 || PAD_TOP != 0 || PAD_RIGHT != 0 || PAD_BOTTOM != 0 - // Replace with PAD_VALUE if the value is out-of-bound - values0 = select(values0, (VECTOR_N)PAD_VALUE, (COND_N)((COND_N)x_border_condition || (COND_N)(y_border_condition))); -#endif // PAD_LEFT != 0 || PAD_TOP != 0 || PAD_RIGHT != 0 || PAD_BOTTOM != 0 - - // Store in a boundary-aware way to avoid padding -#if BOUNDARY_VECTOR_SIZE != VECTOR_SIZE - const bool at_channel_boundary = get_global_id(0) == 0; - if(at_channel_boundary) - { - VSTORE_PARTIAL(VECTOR_SIZE, BOUNDARY_VECTOR_SIZE) - (values0, 0, (__global DATA_TYPE *)(output_ptr) + i * (int)SRC_DEPTH); - } - else // at_channel_boundary -#endif // BOUNDARY_VECTOR_SIZE != VECTOR_SIZE - { - VSTORE(VECTOR_SIZE) - (values0, 0, (__global DATA_TYPE *)(output_ptr) + i * (int)SRC_DEPTH); - } - i++; - } - } - -#ifdef HAS_BIAS - // We can use VECTOR_SIZE instead of BOUNDARY_VECTOR_SIZE even if it's at the boundary. This is because the bias is - // added at the end of the channel, while the boundary vec is at the beginning of the channel. - // The only case where the boundary vec is at the end of the channel is when there's only a single boundary vec in - // the whole channel dimension, but in that case VECTOR_SIZE is also equal to BOUNDARY_VECTOR_SIZE - // See the value of num_elems_processed_per_iteration in configure_opencl_kernel method in CLIm2ColKernel.cpp - if((ch + VECTOR_SIZE) >= SRC_DEPTH) - { - *((__global DATA_TYPE *)(output_ptr) - ch + SRC_DEPTH * KERNEL_WIDTH * KERNEL_HEIGHT) = 1.0f; - } -#endif // HAS_BIAS -} -#endif // defined(CONVOLVED_WIDTH) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(STRIDE_X) && defined(STRIDE_Y) && defined(KERNEL_WIDTH) && defined(KERNEL_HEIGHT) && defined(SRC_DEPTH) && defined(PAD_LEFT) && defined(PAD_RIGHT) && defined(PAD_TOP) && defined(PAD_BOTTOM) && defined(PAD_VALUE) && defined(VECTOR_SIZE) && defined(BOUNDARY_VECTOR_SIZE) -#endif // defined(DATA_TYPE) && defined(ELEMENT_SIZE) |