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Diffstat (limited to 'src/core/CL/cl_kernels/nchw/direct_convolution1x1.cl')
-rw-r--r-- | src/core/CL/cl_kernels/nchw/direct_convolution1x1.cl | 316 |
1 files changed, 0 insertions, 316 deletions
diff --git a/src/core/CL/cl_kernels/nchw/direct_convolution1x1.cl b/src/core/CL/cl_kernels/nchw/direct_convolution1x1.cl deleted file mode 100644 index 8ab2d1d4ea..0000000000 --- a/src/core/CL/cl_kernels/nchw/direct_convolution1x1.cl +++ /dev/null @@ -1,316 +0,0 @@ -/* - * Copyright (c) 2016-2021 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" - -#undef CONVERT_SAT - -#define ADD_OP(a, b) ((a) + (b)) -#define MUL_OP(a, b) ((a) * (b)) -#define CONVERT_SAT(a, b) ((a)) - -#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 values. - */ -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 values. - */ -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 values. - */ -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 values. - */ -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 values. - */ -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[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( - 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 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); - 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 - 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(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) - -#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[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_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) |