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author | Pablo Tello <pablo.tello@arm.com> | 2018-06-21 15:13:17 +0100 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:54:54 +0000 |
commit | 3d319469e5f28066c507e4228dfeb6b9fdfb38a5 (patch) | |
tree | 430e7cfb332ce0c7788cedc2d01e03a21e560e86 /src/core/CL/cl_kernels/direct_convolution1x1.cl | |
parent | 069818d1a8379c3570919668e639d75cea2c1a9f (diff) | |
download | ComputeLibrary-3d319469e5f28066c507e4228dfeb6b9fdfb38a5.tar.gz |
COMPMID-807: NHWC support in CLDirectConvolution.
Change-Id: I8738aca2cc0104e4c4d7c9605762ab59fce10a33
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/137333
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/core/CL/cl_kernels/direct_convolution1x1.cl')
-rw-r--r-- | src/core/CL/cl_kernels/direct_convolution1x1.cl | 137 |
1 files changed, 126 insertions, 11 deletions
diff --git a/src/core/CL/cl_kernels/direct_convolution1x1.cl b/src/core/CL/cl_kernels/direct_convolution1x1.cl index 7a308c99e2..cceeb0f9c4 100644 --- a/src/core/CL/cl_kernels/direct_convolution1x1.cl +++ b/src/core/CL/cl_kernels/direct_convolution1x1.cl @@ -31,6 +31,122 @@ #if defined(DATA_TYPE) && defined(DATA_SIZE) && defined(STRIDE_X) && defined(WEIGHTS_DEPTH) +#if defined(DATA_LAYOUT_NHWC) + +#define PTR_TO_VALUE(PTR, DATA_TYPE) *((__global DATA_TYPE *)(PTR)) + +/** This kernel performs a direct convolution to convolve the low three dimensions of a tensor with data layout NHWC + * + * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float + * @note The data size must be passed at compile time using -DDATA_SIZE e.g. -DDATA_SIZE=32 + * @note The convolution stride x must be passed at compile time using -DSTRIDE_X e.g. -DSTRIDE_X=1 + * @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[in] weights_ptr Pointer to the weights tensor. Supported data types: same as @p src_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 + */ +__kernel void direct_convolution1x1_nhwc( + 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); + +#ifdef HAS_BIAS + Vector biases = CONVERT_TO_VECTOR_STRUCT_NO_STEP(biases); +#endif /* defined(HAS_BIAS) */ + + VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 8) + values = 0; + const int id0 = get_global_id(0); + const int id1 = get_global_id(1); + const int id2 = get_global_id(2); + weights.ptr += id0 * weights_stride_w; + __global uchar *src_addr = (__global uchar *)offset(&src, 0, 0) - src_stride_x * id0 + id2 * STRIDE_Y * (int)src_stride_z; + + for(volatile int d = 0; d < WEIGHTS_DEPTH; ++d) + { + DATA_TYPE weight = *(__global DATA_TYPE *)weights.ptr; +#if STRIDE_X == 1 + VEC_DATA_TYPE(DATA_TYPE, 8) + col0 = (VEC_DATA_TYPE(DATA_TYPE, 8))( + PTR_TO_VALUE(src_addr + 0 * src_stride_y, DATA_TYPE), + PTR_TO_VALUE(src_addr + 1 * src_stride_y, DATA_TYPE), + PTR_TO_VALUE(src_addr + 2 * src_stride_y, DATA_TYPE), + PTR_TO_VALUE(src_addr + 3 * src_stride_y, DATA_TYPE), + PTR_TO_VALUE(src_addr + 4 * src_stride_y, DATA_TYPE), + PTR_TO_VALUE(src_addr + 5 * src_stride_y, DATA_TYPE), + PTR_TO_VALUE(src_addr + 6 * src_stride_y, DATA_TYPE), + PTR_TO_VALUE(src_addr + 7 * src_stride_y, DATA_TYPE)); +#elif STRIDE_X == 2 /* STRIDE_X == 1 */ + VEC_DATA_TYPE(DATA_TYPE, 8) + col0 = (VEC_DATA_TYPE(DATA_TYPE, 8))( + PTR_TO_VALUE(src_addr + 0 * src_stride_y, DATA_TYPE), + PTR_TO_VALUE(src_addr + 2 * src_stride_y, DATA_TYPE), + PTR_TO_VALUE(src_addr + 4 * src_stride_y, DATA_TYPE), + PTR_TO_VALUE(src_addr + 6 * src_stride_y, DATA_TYPE), + PTR_TO_VALUE(src_addr + 8 * src_stride_y, DATA_TYPE), + PTR_TO_VALUE(src_addr + 10 * src_stride_y, DATA_TYPE), + PTR_TO_VALUE(src_addr + 12 * src_stride_y, DATA_TYPE), + PTR_TO_VALUE(src_addr + 14 * src_stride_y, DATA_TYPE)); +#else /* STRIDE_X not equals 1 or 2 */ +#error "STRIDE_X larger than 2 is not supported" +#endif /* STRIDE_X == 2 */ + values = ADD_OP(values, MUL_OP((VEC_DATA_TYPE(DATA_TYPE, 8))weight, col0)); + + src_addr += src_stride_x; + weights.ptr += weights_stride_x; + } + +#ifdef HAS_BIAS + values = ADD_OP(values, (VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 8)) * ((__global DATA_TYPE *)(vector_offset(&biases, id0)))); +#endif /* defined(HAS_BIAS) */ + + *((__global DATA_TYPE *)dst.ptr) = values.s0; + *((__global DATA_TYPE *)(dst.ptr + 1 * dst_stride_y)) = values.s1; + *((__global DATA_TYPE *)(dst.ptr + 2 * dst_stride_y)) = values.s2; + *((__global DATA_TYPE *)(dst.ptr + 3 * dst_stride_y)) = values.s3; + *((__global DATA_TYPE *)(dst.ptr + 4 * dst_stride_y)) = values.s4; + *((__global DATA_TYPE *)(dst.ptr + 5 * dst_stride_y)) = values.s5; + *((__global DATA_TYPE *)(dst.ptr + 6 * dst_stride_y)) = values.s6; + *((__global DATA_TYPE *)(dst.ptr + 7 * dst_stride_y)) = values.s7; +} +#endif // defined(DATA_LAYOUT_NHWC) + #if STRIDE_X == 3 #define INPUT_PIXEL_STR(data_size) extract_input_stride3_##data_size #define INPUT_PIXEL(data_size) INPUT_PIXEL_STR(data_size) @@ -46,7 +162,7 @@ * * @param[in] input_pixel Pointer to the first pixel. * - * @return extracted input pixels. + * @return extracted input values. */ inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride1(__global const DATA_TYPE *input_pixel) { @@ -57,7 +173,7 @@ inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride1(__global const DATA_TYP * * @param[in] input_pixel Pointer to the first pixel. * - * @return extracted input pixels. + * @return extracted input values. */ inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride2(__global const DATA_TYPE *input_pixel) { @@ -70,7 +186,7 @@ inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride2(__global const DATA_TYP * * @param[in] input_pixel Pointer to the first pixel. * - * @return extracted input pixels. + * @return extracted input values. */ inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride3_32(__global const DATA_TYPE *input_pixel) { @@ -89,7 +205,7 @@ inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride3_32(__global const DATA_ * * @param[in] input_pixel Pointer to the first pixel. * - * @return extracted input pixels. + * @return extracted input values. */ inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride3_16(__global const DATA_TYPE *input_pixel) { @@ -106,7 +222,7 @@ inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride3_16(__global const DATA_ * * @param[in] input_pixel Pointer to the first pixel. * - * @return extracted input pixels. + * @return extracted input values. */ inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride3_8(__global const DATA_TYPE *input_pixel) { @@ -173,27 +289,26 @@ __kernel void direct_convolution1x1( #endif /* defined(HAS_BIAS) */ VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 8) - pixels = 0; + values = 0; const uint z_index = get_global_id(2); weights.ptr += z_index * weights_stride_w; - for(volatile int d = 0; d < WEIGHTS_DEPTH; ++d) { DATA_TYPE weight = *(__global DATA_TYPE *)weights.ptr; VEC_DATA_TYPE(DATA_TYPE, 8) input_pixel = INPUT_PIXEL(DATA_SIZE)((__global DATA_TYPE *)src.ptr); - pixels = ADD_OP(pixels, MUL_OP((VEC_DATA_TYPE(DATA_TYPE, 8))weight, input_pixel)); + values = ADD_OP(values, MUL_OP((VEC_DATA_TYPE(DATA_TYPE, 8))weight, input_pixel)); src.ptr += src_stride_z; weights.ptr += weights_stride_z; } #ifdef HAS_BIAS - pixels = ADD_OP(pixels, (VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 8)) * ((__global DATA_TYPE *)(vector_offset(&biases, z_index)))); + values = ADD_OP(values, (VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 8)) * ((__global DATA_TYPE *)(vector_offset(&biases, z_index)))); #endif /* defined(HAS_BIAS) */ - vstore8(CONVERT_SAT(pixels, VEC_DATA_TYPE(DATA_TYPE, 8)), 0, (__global DATA_TYPE *)dst.ptr); + vstore8(CONVERT_SAT(values, VEC_DATA_TYPE(DATA_TYPE, 8)), 0, (__global DATA_TYPE *)dst.ptr); } #endif // defined(DATA_TYPE) && defined(DATA_SIZE) && defined(STRIDE_X) && defined(WEIGHTS_DEPTH) @@ -314,4 +429,4 @@ __kernel void direct_convolution1x1_f32_bifrost( vstore4(acc2, 0, (__global float *)(dst.ptr + 2 * dst_stride_y)); vstore4(acc3, 0, (__global float *)(dst.ptr + 3 * dst_stride_y)); } -#endif // defined(WEIGHTS_DEPTH)
\ No newline at end of file +#endif // defined(WEIGHTS_DEPTH) |