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Diffstat (limited to 'src/core/CL/cl_kernels/nchw/im2col.cl')
| -rw-r--r-- | src/core/CL/cl_kernels/nchw/im2col.cl | 863 |
1 files changed, 863 insertions, 0 deletions
diff --git a/src/core/CL/cl_kernels/nchw/im2col.cl b/src/core/CL/cl_kernels/nchw/im2col.cl new file mode 100644 index 0000000000..fddf918c63 --- /dev/null +++ b/src/core/CL/cl_kernels/nchw/im2col.cl @@ -0,0 +1,863 @@ +/* + * Copyright (c) 2018-2021 Arm Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#include "helpers.h" +#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) +#endif // defined(DATA_TYPE) && defined(ELEMENT_SIZE)
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