| /* |
| * 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 defined(FIXED_POINT_POSITION) |
| #include "fixed_point.h" |
| |
| #define ADD_OP(a, b) ADD_SAT_OP_EXPAND((a), (b), DATA_TYPE_PROMOTED, 8) |
| #define MUL_OP(a, b) MUL_SAT_OP_EXPAND(CONVERT((a), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 8)), CONVERT((b), VEC_DATA_TYPE(DATA_TYPE_PROMOTED, 8)), DATA_TYPE_PROMOTED, 8, FIXED_POINT_POSITION) |
| |
| // There is no need to have a larger intermediate type for qs32 because all the arguments are already promoted |
| MULQ_SAT_IMPL(qs32x8, qs32x8) |
| |
| #else /* FIXED_POINT_POSITION */ |
| #undef CONVERT_SAT |
| |
| #define ADD_OP(a, b) ((a) + (b)) |
| #define MUL_OP(a, b) ((a) * (b)) |
| #define CONVERT_SAT(a, b) ((a)) |
| |
| #endif /* FIXED_POINT_POSITION */ |
| |
| #if defined(DATA_TYPE) && defined(DATA_SIZE) && defined(STRIDE_X) && defined(WEIGHTS_DEPTH) |
| |
| #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) |
| #elif STRIDE_X == 2 |
| #define INPUT_PIXEL(data_size) extract_input_stride2 |
| #elif STRIDE_X == 1 |
| #define INPUT_PIXEL(data_size) extract_input_stride1 |
| #else /* STRIDE_X not equals 1, 2 or 3 */ |
| #error "Only support strides 1, 2 and 3" |
| #endif /* STRIDE_X == 3 */ |
| |
| /** Extracts a 1D horizontal vector from the input tensor with stride as 1. |
| * |
| * @param[in] input_pixel Pointer to the first pixel. |
| * |
| * @return extracted input pixels. |
| */ |
| inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride1(__global const DATA_TYPE *input_pixel) |
| { |
| return vload8(0, input_pixel); |
| } |
| |
| /** Extracts a 1D horizontal vector from the input tensor with stride as 2. |
| * |
| * @param[in] input_pixel Pointer to the first pixel. |
| * |
| * @return extracted input pixels. |
| */ |
| inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride2(__global const DATA_TYPE *input_pixel) |
| { |
| VEC_DATA_TYPE(DATA_TYPE, 16) |
| temp = vload16(0, input_pixel); |
| return temp.s02468ace; |
| } |
| |
| /** Extracts a 1D horizontal vector from the input tensor with stride as 3 and 32-bit data size. |
| * |
| * @param[in] input_pixel Pointer to the first pixel. |
| * |
| * @return extracted input pixels. |
| */ |
| inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride3_32(__global const DATA_TYPE *input_pixel) |
| { |
| VEC_DATA_TYPE(DATA_TYPE, 4) |
| temp1 = vload4(0, input_pixel); |
| VEC_DATA_TYPE(DATA_TYPE, 4) |
| temp2 = vload4(0, input_pixel + 6); |
| VEC_DATA_TYPE(DATA_TYPE, 4) |
| temp3 = vload4(0, input_pixel + 12); |
| VEC_DATA_TYPE(DATA_TYPE, 4) |
| temp4 = vload4(0, input_pixel + 18); |
| return (VEC_DATA_TYPE(DATA_TYPE, 8))(temp1.s03, temp2.s03, temp3.s03, temp4.s03); |
| } |
| |
| /** Extracts a 1D horizontal vector from the input tensor with stride as 3 and 16-bit data size. |
| * |
| * @param[in] input_pixel Pointer to the first pixel. |
| * |
| * @return extracted input pixels. |
| */ |
| inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride3_16(__global const DATA_TYPE *input_pixel) |
| { |
| VEC_DATA_TYPE(DATA_TYPE, 8) |
| temp1 = vload8(0, input_pixel); |
| VEC_DATA_TYPE(DATA_TYPE, 8) |
| temp2 = vload8(0, input_pixel + 8); |
| VEC_DATA_TYPE(DATA_TYPE, 8) |
| temp3 = vload8(0, input_pixel + 16); |
| return (VEC_DATA_TYPE(DATA_TYPE, 8))(temp1.s036, temp2.s147, temp3.s25); |
| } |
| |
| /** Extracts a 1D horizontal vector from the input tensor with stride as 3 and 8-bit data size. |
| * |
| * @param[in] input_pixel Pointer to the first pixel. |
| * |
| * @return extracted input pixels. |
| */ |
| inline VEC_DATA_TYPE(DATA_TYPE, 8) extract_input_stride3_8(__global const DATA_TYPE *input_pixel) |
| { |
| VEC_DATA_TYPE(DATA_TYPE, 16) |
| temp1 = vload16(0, input_pixel); |
| VEC_DATA_TYPE(DATA_TYPE, 16) |
| temp2 = vload16(0, input_pixel + 12); |
| return (VEC_DATA_TYPE(DATA_TYPE, 8))(temp1.s0369, temp2.s0369); |
| } |
| |
| /** 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 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[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 |
| */ |
| __kernel void direct_convolution1x1( |
| 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) |
| pixels = 0; |
| |
| const uint z_index = get_global_id(2); |
| |
| weights.ptr += z_index * weights_stride_w; |
| |
| for(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)); |
| 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)))); |
| #endif /* defined(HAS_BIAS) */ |
| |
| vstore8(CONVERT_SAT(pixels, 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) |
| |
| #if defined(WEIGHTS_DEPTH) |
| |
| #define CONVOLUTION1x1_BIFROST(acc, src, weight_value) \ |
| ({ \ |
| acc.s0 = mad(src.s0, weight_value, acc.s0); \ |
| acc.s1 = mad(src.s1, weight_value, acc.s1); \ |
| acc.s2 = mad(src.s2, weight_value, acc.s2); \ |
| acc.s3 = mad(src.s3, weight_value, acc.s3); \ |
| }) |
| |
| /** An optimized direct convolution 1x1 OpenCL kernel for Bifrost architectures when the data type is F32 |
| * |
| * @note This OpenCL kernel works only with stride_x and stride_y equal to 1 |
| * @note The third dimensions of the weights tensors must be passed at compile time using -DWEIGHTS_DEPTH |
| * @note In case biases, -DHAS_BIAS must to be passed at compile |
| * |
| * @param[in] src_ptr Pointer to the source tensor. Supported data types: 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 |
| */ |
| __kernel void direct_convolution1x1_f32_bifrost( |
| TENSOR3D_DECLARATION(src), |
| TENSOR3D_DECLARATION(dst), |
| TENSOR3D_DECLARATION(weights), |
| #ifdef HAS_BIAS |
| VECTOR_DECLARATION(biases), |
| #endif /* defined(HAS_BIAS) */ |
| unsigned int weights_stride_w) |
| { |
| // Get the kernel index |
| const int kernel_index = get_global_id(2); |
| |
| Image src = CONVERT_TO_IMAGE_STRUCT(src); |
| Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst); |
| |
| float4 acc0 = 0.0f; |
| float4 acc1 = 0.0f; |
| float4 acc2 = 0.0f; |
| float4 acc3 = 0.0f; |
| |
| __global uchar *weights_addr = (__global uchar *)(weights_ptr + weights_offset_first_element_in_bytes + kernel_index * weights_stride_w); |
| __global uchar *src_addr = (__global uchar *)offset(&src, 0, 0); |
| |
| for(ushort d = 0; d < (ushort)WEIGHTS_DEPTH; ++d) |
| { |
| // Load the weights |
| float weight = *((__global float *)weights_addr); |
| |
| // Load values from row0 of input tensor |
| float4 src0 = vload4(0, (__global float *)(src_addr + 0 * src_stride_y)); |
| float4 src1 = vload4(0, (__global float *)(src_addr + 1 * src_stride_y)); |
| float4 src2 = vload4(0, (__global float *)(src_addr + 2 * src_stride_y)); |
| float4 src3 = vload4(0, (__global float *)(src_addr + 3 * src_stride_y)); |
| |
| CONVOLUTION1x1_BIFROST(acc0, src0, weight); |
| CONVOLUTION1x1_BIFROST(acc1, src1, weight); |
| CONVOLUTION1x1_BIFROST(acc2, src2, weight); |
| CONVOLUTION1x1_BIFROST(acc3, src3, weight); |
| |
| src_addr += src_stride_z; |
| weights_addr += weights_stride_z; |
| } |
| |
| #ifdef HAS_BIAS |
| Vector biases = CONVERT_TO_VECTOR_STRUCT_NO_STEP(biases); |
| |
| float bias = (float) * ((__global float *)(vector_offset(&biases, kernel_index))); |
| |
| acc0.s0 += bias; |
| acc0.s1 += bias; |
| acc0.s2 += bias; |
| acc0.s3 += bias; |
| acc1.s0 += bias; |
| acc1.s1 += bias; |
| acc1.s2 += bias; |
| acc1.s3 += bias; |
| acc2.s0 += bias; |
| acc2.s1 += bias; |
| acc2.s2 += bias; |
| acc2.s3 += bias; |
| acc3.s0 += bias; |
| acc3.s1 += bias; |
| acc3.s2 += bias; |
| acc3.s3 += bias; |
| #endif /* defined(HAS_BIAS) */ |
| |
| vstore4(acc0, 0, (__global float *)(dst.ptr + 0 * dst_stride_y)); |
| vstore4(acc1, 0, (__global float *)(dst.ptr + 1 * dst_stride_y)); |
| 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) |
