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/*
* Copyright (c) 2016, 2017 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 STRIDE_X == 1
#define CONVOLUTION1x3(acc, src_row_ptr, weights_row_ptr) CONVOLUTION1x3_STRIDE1(acc, src_row_ptr, weights_row_ptr)
#elif STRIDE_X == 2 /* STRIDE_X == 1 */
#define CONVOLUTION1x3(acc, src_row_ptr, weights_row_ptr) CONVOLUTION1x3_STRIDE2(acc, src_row_ptr, weights_row_ptr)
#else /* STRIDE_X not equals 1 or 2 */
#error "STRIDE_X larger than 2 is not supported"
#endif /* STRIDE_X == 2 */
#define CONVOLUTION1x3_STRIDE1(acc, src_row_ptr, weights_row_ptr) \
({ \
VEC_DATA_TYPE(DATA_TYPE, 4) \
weights_values0 = vload4(0, weights_row_ptr); \
VEC_DATA_TYPE(DATA_TYPE, 8) \
src0 = vload8(0, src_row_ptr); \
VEC_DATA_TYPE(DATA_TYPE, 2) \
src1 = vload2(0, src_row_ptr + 8); \
\
acc += src0 * (VEC_DATA_TYPE(DATA_TYPE, 8))weights_values0.s0; \
acc += (VEC_DATA_TYPE(DATA_TYPE, 8))(src0.s1234, src0.s567, src1.s0) * (VEC_DATA_TYPE(DATA_TYPE, 8))weights_values0.s1; \
acc += (VEC_DATA_TYPE(DATA_TYPE, 8))(src0.s234, src0.s567, src1.s01) * (VEC_DATA_TYPE(DATA_TYPE, 8))weights_values0.s2; \
})
#define CONVOLUTION1x3_STRIDE2(acc, src_row_ptr, weights_row_ptr) \
({ \
VEC_DATA_TYPE(DATA_TYPE, 4) \
weights_values0 = vload4(0, weights_row_ptr); \
VEC_DATA_TYPE(DATA_TYPE, 16) \
src0 = vload16(0, src_row_ptr); \
DATA_TYPE src1 = *(src_row_ptr + 16); \
\
acc += src0.even * (VEC_DATA_TYPE(DATA_TYPE, 8))weights_values0.s0; \
acc += (VEC_DATA_TYPE(DATA_TYPE, 8))(src0.s1357, src0.s9BDF) * (VEC_DATA_TYPE(DATA_TYPE, 8))weights_values0.s1; \
acc += (VEC_DATA_TYPE(DATA_TYPE, 8))(src0.s2468, src0.sACE, src1) * (VEC_DATA_TYPE(DATA_TYPE, 8))weights_values0.s2; \
})
/** This kernel performs a direct convolution to convolve the low three dimensions.
*
* @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float
* @note The third dimensions of the weights tensors must be passed at compile time using -DWEIGHTS_DEPTH
* @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: 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 Z 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[out] weights_ptr Pointer to the weights tensor. Supported data types: same as @p weights_ptr
* @param[in] weights_stride_x Stride of the weights tensor in X dimension (in bytes)
* @param[in] weights_step_x weights_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] weights_stride_y Stride of the weights tensor in Y dimension (in bytes)
* @param[in] weights_step_y weights_stride_y * number of elements along y processed per workitem(in bytes)
* @param[in] weights_stride_z Stride of the weights tensor in Z dimension (in bytes)
* @param[in] weights_step_z weights_stride_z * number of elements along Z processed per workitem(in bytes)
* @param[in] weights_offset_first_element_in_bytes The offset of the first element in the weights tensor
* @param[in] biases_ptr Pointer to the biases tensor. Same as @p src_ptr
* @param[in] biases_stride_x Stride of the biases tensor in X dimension (in bytes)
* @param[in] biases_step_x biases_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] biases_offset_first_element_in_bytes The offset of the first element in the biases tensor
* @param[in] weights_stride_w Stride of the weights tensor in the 4th dimension
*/
#if defined(DATA_TYPE) && defined(STRIDE_X) && defined(WEIGHTS_DEPTH)
__kernel void direct_convolution3x3(
TENSOR3D_DECLARATION(src),
TENSOR3D_DECLARATION(dst),
TENSOR3D_DECLARATION(weights),
#ifdef HAS_BIAS
VECTOR_DECLARATION(biases),
#endif /* defined(HAS_BIAS) */
unsigned int weights_stride_w)
{
Image src = CONVERT_TO_IMAGE_STRUCT(src);
Tensor3D weights = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(weights);
Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst);
VEC_DATA_TYPE(DATA_TYPE, 8)
pixels0 = 0;
__global uchar *weights_addr = (__global uchar *)tensor3D_offset(&weights, 0, 0, 0);
__global uchar *src_addr = (__global uchar *)offset(&src, 0, 0);
const int kernel_index = get_global_id(2);
weights_addr += kernel_index * weights_stride_w;
for(int d = 0; d < WEIGHTS_DEPTH; ++d)
{
CONVOLUTION1x3(pixels0, (__global DATA_TYPE *)(src_addr + 0 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 0 * weights_stride_y));
CONVOLUTION1x3(pixels0, (__global DATA_TYPE *)(src_addr + 1 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 1 * weights_stride_y));
CONVOLUTION1x3(pixels0, (__global DATA_TYPE *)(src_addr + 2 * src_stride_y), (__global DATA_TYPE *)(weights_addr + 2 * weights_stride_y));
src_addr += src_stride_z;
weights_addr += weights_stride_z;
}
#ifdef HAS_BIAS
Vector biases = CONVERT_TO_VECTOR_STRUCT_NO_STEP(biases);
pixels0 += (VEC_DATA_TYPE(DATA_TYPE, 8)) * ((__global DATA_TYPE *)(vector_offset(&biases, kernel_index)));
#endif /* defined(HAS_BIAS) */
vstore8(pixels0, 0, (__global DATA_TYPE *)dst.ptr);
}
#endif // defined(DATA_TYPE) && defined(STRIDE_X) && defined(WEIGHTS_DEPTH)