| /* |
| * Copyright (c) 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" |
| #include "helpers_asymm.h" |
| |
| #if defined(COLS_B) |
| /** This OpenCL kernel computes the matrix multiplication between matrix A (src0) and matrix B (src1) |
| * Matrix A and matrix B must be reshaped respectively with @ref gemm_interleave4x4_8bit and @ref gemm_transpose1x16 before running the matrix multiplication |
| * |
| * @attention The number of matrix B columns needs to be passed at compile time using -DCOLS_B |
| * |
| * @param[in] src0_ptr Pointer to the source matrix. Supported data type: QASYMM8 |
| * @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes) |
| * @param[in] src0_step_x src_stride_x * number of elements along X processed per workitem(in bytes) |
| * @param[in] src0_stride_y Stride of the source matrix in Y dimension (in bytes) |
| * @param[in] src0_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) |
| * @param[in] src0_offset_first_element_in_bytes The offset of the first element in the source matrix |
| * @param[in] src1_ptr Pointer to the source matrix. Supported data type: same as @p src0_ptr |
| * @param[in] src1_stride_x Stride of the source matrix in X dimension (in bytes) |
| * @param[in] src1_step_x src_stride_x * number of elements along X processed per workitem(in bytes) |
| * @param[in] src1_stride_y Stride of the source matrix in Y dimension (in bytes) |
| * @param[in] src1_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) |
| * @param[in] src1_offset_first_element_in_bytes The offset of the first element in the source matrix |
| * @param[out] dst_ptr Pointer to the destination matrix Supported data type: S32 |
| * @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes) |
| * @param[in] dst_step_x dst_gx_stride_x * number of elements along X processed per workitem(in bytes) |
| * @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes) |
| * @param[in] dst_step_y dst_gx_stride_y * number of elements along Y processed per workitem(in bytes) |
| * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix |
| */ |
| __kernel void gemmlowp_mm_interleaved_transposed(IMAGE_DECLARATION(src0), |
| IMAGE_DECLARATION(src1), |
| IMAGE_DECLARATION(dst)) |
| { |
| // src_addr.s0 = address of matrix A |
| // src_addr.s1 = address of matrix B |
| // Compute address for matrix A and B |
| int2 src_addr = (int2)(get_global_id(1), get_global_id(0)) * (int2)((src0_stride_y), |
| (src1_stride_y)); |
| |
| // Add offset_first_element_in_bytes |
| src_addr = src_addr + ((int2)(src0_offset_first_element_in_bytes, src1_offset_first_element_in_bytes)); |
| |
| // Compute end row address for matrix B |
| int end_row_mtx_b = src_addr.s1 + COLS_B; |
| |
| // Reset accumulators |
| int16 c00 = 0; |
| int16 c10 = 0; |
| int16 c20 = 0; |
| int16 c30 = 0; |
| |
| for(; src_addr.s1 <= (end_row_mtx_b - 32); src_addr += (int2)(8, 32)) |
| { |
| // Load values from matrix A (interleaved) and matrix B (transposed) |
| int8 a0 = convert_int8(vload8(0, ((__global uchar *)src0_ptr) + src_addr.s0)); |
| int16 b0 = convert_int16(vload16(0, ((__global uchar *)src1_ptr) + src_addr.s1)); |
| |
| c00 += (int16)a0.s0 * b0; |
| c10 += (int16)a0.s1 * b0; |
| c20 += (int16)a0.s2 * b0; |
| c30 += (int16)a0.s3 * b0; |
| |
| int16 b1 = convert_int16(vload16(0, ((__global uchar *)src1_ptr) + src_addr.s1 + 16)); |
| |
| c00 += (int16)a0.s4 * b1; |
| c10 += (int16)a0.s5 * b1; |
| c20 += (int16)a0.s6 * b1; |
| c30 += (int16)a0.s7 * b1; |
| } |
| |
| for(; src_addr.s1 < end_row_mtx_b; src_addr += (int2)(4, 16)) |
| { |
| // Load values from matrix A (interleaved) and matrix B (transposed) |
| int4 a0 = convert_int4(vload4(0, ((__global uchar *)src0_ptr) + src_addr.s0)); |
| int16 b0 = convert_int16(vload16(0, ((__global uchar *)src1_ptr) + src_addr.s1)); |
| |
| c00 += (int16)a0.s0 * b0; |
| c10 += (int16)a0.s1 * b0; |
| c20 += (int16)a0.s2 * b0; |
| c30 += (int16)a0.s3 * b0; |
| } |
| |
| // Compute destination address |
| Image dst = CONVERT_TO_IMAGE_STRUCT(dst); |
| |
| // Store 4x16 block |
| vstore16(c00, 0, (__global int *)(offset(&dst, 0, 0))); |
| vstore16(c10, 0, (__global int *)(offset(&dst, 0, 1))); |
| vstore16(c20, 0, (__global int *)(offset(&dst, 0, 2))); |
| vstore16(c30, 0, (__global int *)(offset(&dst, 0, 3))); |
| } |
| #endif // defined(COLS_B) |
| |
| #if defined(NUM_ELEMS_PROCESSED_PER_THREAD_X) && defined(NUM_ELEMS_PROCESSED_PER_THREAD_Y) && defined(COLS_A) |
| #define VECTOR_UCHAR VEC_DATA_TYPE(uchar, NUM_ELEMS_PROCESSED_PER_THREAD_X) |
| #define VECTOR_UINT VEC_DATA_TYPE(uint, NUM_ELEMS_PROCESSED_PER_THREAD_X) |
| #define VECTOR_INT VEC_DATA_TYPE(int, NUM_ELEMS_PROCESSED_PER_THREAD_X) |
| /** This OpenCL kernel computes the matrix multiplication between matrix A (src0) and matrix B (src1) in case both matrices have not beed reshaped |
| * |
| * @attention The number of matrix A columns needs to be passed at compile time using -DCOLS_A |
| * |
| * @param[in] src0_ptr Pointer to the source matrix. Supported data type: QASYMM8 |
| * @param[in] src0_stride_x Stride of the source matrix in X dimension (in bytes) |
| * @param[in] src0_step_x src_stride_x * number of elements along X processed per workitem(in bytes) |
| * @param[in] src0_stride_y Stride of the source matrix in Y dimension (in bytes) |
| * @param[in] src0_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) |
| * @param[in] src0_offset_first_element_in_bytes The offset of the first element in the source matrix |
| * @param[in] src1_ptr Pointer to the source matrix. Supported data type: same as @p src0_ptr |
| * @param[in] src1_stride_x Stride of the source matrix in X dimension (in bytes) |
| * @param[in] src1_step_x src_stride_x * number of elements along X processed per workitem(in bytes) |
| * @param[in] src1_stride_y Stride of the source matrix in Y dimension (in bytes) |
| * @param[in] src1_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) |
| * @param[in] src1_offset_first_element_in_bytes The offset of the first element in the source matrix |
| * @param[out] dst_ptr Pointer to the destination matrix Supported data type: S32 |
| * @param[in] dst_stride_x Stride of the destination matrix in X dimension (in bytes) |
| * @param[in] dst_step_x dst_gx_stride_x * number of elements along X processed per workitem(in bytes) |
| * @param[in] dst_stride_y Stride of the destination matrix in Y dimension (in bytes) |
| * @param[in] dst_step_y dst_gx_stride_y * number of elements along Y processed per workitem(in bytes) |
| * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination matrix |
| */ |
| __kernel void gemmlowp_mm(IMAGE_DECLARATION(src0), |
| IMAGE_DECLARATION(src1), |
| IMAGE_DECLARATION(dst)) |
| { |
| int idx = get_global_id(0) * NUM_ELEMS_PROCESSED_PER_THREAD_X; |
| |
| // Compute starting address for matrix A and Matrix B |
| int2 src_addr = ((int2)(src0_offset_first_element_in_bytes, src1_offset_first_element_in_bytes)); |
| |
| // Update address for the matrix A |
| src_addr.s0 += get_global_id(1) * src0_stride_y * NUM_ELEMS_PROCESSED_PER_THREAD_Y; |
| |
| // Update address for the matrix B |
| src_addr.s1 += idx; |
| |
| int end_row_vec_a = src_addr.s0 + COLS_A; |
| |
| VECTOR_UINT acc0 = 0; |
| #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 |
| VECTOR_UINT acc1 = 0; |
| #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 |
| #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 |
| VECTOR_UINT acc2 = 0; |
| #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 |
| #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 |
| VECTOR_UINT acc3 = 0; |
| #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 |
| |
| for(; src_addr.s0 <= (end_row_vec_a - 2); src_addr += (int2)(2, 2 * src1_stride_y)) |
| { |
| // Load values from matrix A |
| uchar2 a0 = vload2(0, src0_ptr + src_addr.s0 + 0 * src0_stride_y); |
| #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 |
| uchar2 a1 = vload2(0, src0_ptr + src_addr.s0 + 1 * src0_stride_y); |
| #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 |
| #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 |
| uchar2 a2 = vload2(0, src0_ptr + src_addr.s0 + 2 * src0_stride_y); |
| #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 |
| #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 |
| uchar2 a3 = vload2(0, src0_ptr + src_addr.s0 + 3 * src0_stride_y); |
| #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 |
| // Load values from matrix B |
| VECTOR_UCHAR b0 = VLOAD(NUM_ELEMS_PROCESSED_PER_THREAD_X)(0, src1_ptr + src_addr.s1); |
| VECTOR_UCHAR b1 = VLOAD(NUM_ELEMS_PROCESSED_PER_THREAD_X)(0, src1_ptr + src_addr.s1 + src1_stride_y); |
| |
| // Accumulate |
| acc0 += CONVERT(b0, VECTOR_UINT) * (VECTOR_UINT)a0.s0; |
| acc0 += CONVERT(b1, VECTOR_UINT) * (VECTOR_UINT)a0.s1; |
| #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 |
| acc1 += CONVERT(b0, VECTOR_UINT) * (VECTOR_UINT)a1.s0; |
| acc1 += CONVERT(b1, VECTOR_UINT) * (VECTOR_UINT)a1.s1; |
| #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 |
| #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 |
| acc2 += CONVERT(b0, VECTOR_UINT) * (VECTOR_UINT)a2.s0; |
| acc2 += CONVERT(b1, VECTOR_UINT) * (VECTOR_UINT)a2.s1; |
| #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 |
| #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 |
| acc3 += CONVERT(b0, VECTOR_UINT) * (VECTOR_UINT)a3.s0; |
| acc3 += CONVERT(b1, VECTOR_UINT) * (VECTOR_UINT)a3.s1; |
| #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 |
| } |
| |
| for(; src_addr.s0 < end_row_vec_a; src_addr += (int2)(1, src1_stride_y)) |
| { |
| // Load values from matrix A |
| uchar a0 = *(src0_ptr + src_addr.s0 + 0 * src0_stride_y); |
| #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 |
| uchar a1 = *(src0_ptr + src_addr.s0 + 1 * src0_stride_y); |
| #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 |
| #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 |
| uchar a2 = *(src0_ptr + src_addr.s0 + 2 * src0_stride_y); |
| #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 |
| #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 |
| uchar a3 = *(src0_ptr + src_addr.s0 + 3 * src0_stride_y); |
| #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 |
| // Load values from matrix B |
| VECTOR_UCHAR b0 = VLOAD(NUM_ELEMS_PROCESSED_PER_THREAD_X)(0, src1_ptr + src_addr.s1); |
| |
| // Accumulate |
| acc0 += CONVERT(b0, VECTOR_UINT) * (VECTOR_UINT)a0; |
| #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 |
| acc1 += CONVERT(b0, VECTOR_UINT) * (VECTOR_UINT)a1; |
| #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 |
| #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 |
| acc2 += CONVERT(b0, VECTOR_UINT) * (VECTOR_UINT)a2; |
| #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 |
| #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 |
| acc3 += CONVERT(b0, VECTOR_UINT) * (VECTOR_UINT)a3; |
| #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 |
| } |
| |
| // Compute destination address |
| Image dst = CONVERT_TO_IMAGE_STRUCT(dst); |
| |
| // Store the result |
| VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X) |
| (CONVERT(acc0, VECTOR_INT), 0, (__global int *)(offset(&dst, 0, 0))); |
| #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 |
| VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X) |
| (CONVERT(acc1, VECTOR_INT), 0, (__global int *)(offset(&dst, 0, 1))); |
| #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 1 |
| #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 |
| VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X) |
| (CONVERT(acc2, VECTOR_INT), 0, (__global int *)(offset(&dst, 0, 2))); |
| #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 2 |
| #if NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 |
| VSTORE(NUM_ELEMS_PROCESSED_PER_THREAD_X) |
| (CONVERT(acc3, VECTOR_INT), 0, (__global int *)(offset(&dst, 0, 3))); |
| #endif // NUM_ELEMS_PROCESSED_PER_THREAD_Y > 3 |
| } |
| #endif // defined(NUM_ELEMS_PROCESSED_PER_THREAD_X) && defined(NUM_ELEMS_PROCESSED_PER_THREAD_Y) && defined(COLS_A) |
| |
| #if defined(COLS_A) |
| /** OpenCL kernel used to compute the row-vectors of sums of all the entries in each row of Matrix A. |
| * |
| * @note This stage is needed to handle the offset of matrix product |
| * https://github.com/google/gemmlowp/blob/master/doc/low-precision.md |
| * |
| * @attention The number of matrix A columns needs to be passed at compile time using -DCOLS_A |
| * |
| * @param[in] src_ptr Pointer to the source tensor. Supported data type: QASYMM8 |
| * @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 type: S32 |
| * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) |
| * @param[in] dst_step_x dst_gx_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_gx_stride_y * number of elements along Y processed per workitem(in bytes) |
| * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor |
| */ |
| __kernel void gemmlowp_matrix_a_reduction(TENSOR3D_DECLARATION(src), |
| IMAGE_DECLARATION(dst)) |
| { |
| // Compute source and destination addresses |
| Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src); |
| Image dst = CONVERT_TO_IMAGE_STRUCT(dst); |
| |
| uint4 sum_row_u32 = (uint4)0; |
| uint sum_row = 0; |
| |
| __global const uchar *matrix_a = (__global const uchar *)(src.ptr + get_global_id(0) * src_stride_y + get_global_id(1) * src_stride_z); |
| |
| int i = 0; |
| |
| // This for loop performs 16 accumulations |
| for(; i <= ((int)COLS_A - 16); i += 16) |
| { |
| const uchar16 a0_u8 = vload16(0, matrix_a + i); |
| |
| sum_row_u32 += convert_uint4(a0_u8.s0123) + convert_uint4(a0_u8.s4567) + convert_uint4(a0_u8.s89AB) + convert_uint4(a0_u8.sCDEF); |
| } |
| |
| // This for loop performs the leftover accumulations |
| for(; i < COLS_A; ++i) |
| { |
| sum_row += matrix_a[i]; |
| } |
| |
| sum_row += sum_row_u32.s0 + sum_row_u32.s1 + sum_row_u32.s2 + sum_row_u32.s3; |
| |
| *((__global int *)dst.ptr) = (int)sum_row; |
| } |
| #endif // defined(COLS_A) |
| |
| #if defined(COLS_B) && defined(ROWS_B) |
| /** OpenCL kernel used to compute the row-vectors of sums of all the entries in each column of Matrix B. |
| * |
| * @note This stage is needed to handle the offset of matrix product |
| * https://github.com/google/gemmlowp/blob/master/doc/low-precision.md |
| * |
| * @attention The number of matrix B columns and rows needs to be passed at compile time using -DCOLS_B and -DROWS_B |
| * |
| * @param[in] src_ptr Pointer to the source tensor. Supported data type: QASYMM8 |
| * @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 type: S32 |
| * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) |
| * @param[in] dst_step_x dst_gx_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_gx_stride_y * number of elements along Y processed per workitem(in bytes) |
| * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor |
| */ |
| __kernel void gemmlowp_matrix_b_reduction(TENSOR3D_DECLARATION(src), |
| IMAGE_DECLARATION(dst)) |
| { |
| // Compute source and destination addresses |
| Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src); |
| Image dst = CONVERT_TO_IMAGE_STRUCT(dst); |
| |
| uint16 sum_col_u32 = (uint16)0; |
| |
| __global const uchar *matrix_b = (__global const uchar *)(src.ptr + get_global_id(1) * src_stride_z); |
| |
| int i = 0; |
| // This for loop performs 4 accumulations |
| for(; i <= ((int)ROWS_B - 4); i += 4) |
| { |
| const uchar16 b0_u8 = vload16(0, matrix_b + 0 * src_stride_y); |
| const uchar16 b1_u8 = vload16(0, matrix_b + 1 * src_stride_y); |
| const uchar16 b2_u8 = vload16(0, matrix_b + 2 * src_stride_y); |
| const uchar16 b3_u8 = vload16(0, matrix_b + 3 * src_stride_y); |
| |
| sum_col_u32 += convert_uint16(b0_u8) + convert_uint16(b1_u8) + convert_uint16(b2_u8) + convert_uint16(b3_u8); |
| |
| matrix_b += 4 * src_stride_y; |
| } |
| |
| // This for loop perfoms the leftover accumulations |
| for(; i < (int)ROWS_B; ++i) |
| { |
| const uchar16 b0_u8 = vload16(0, matrix_b); |
| |
| sum_col_u32 += convert_uint16(b0_u8); |
| |
| matrix_b += src_stride_y; |
| } |
| |
| vstore16(convert_int16(sum_col_u32), 0, (__global int *)dst.ptr); |
| } |
| #endif // defined(COLS_B) && defined(ROWS_B) |
| |
| #if defined(K_OFFSET) |
| /* OpenCL kernel used to add the offset contribution after @ref CLGEMMLowpMatrixMultiplyKernel. The computation is performed in-place |
| * |
| * This kernel takes a final int32 accumulator value (the output of @CLGEMMLowpMatrixMultiplyKernel), |
| * and adds to it the offset contribution of matrix A and matrix B in-place. |
| * |
| * @attention The k_offset = a_offset * b_offset * k (where k is the number of matrix A columns) needs to be passed at compile time using -DK_OFFSET (i.e. -DK_OFFSET=1200) |
| * @note In case the offset contribution due to a_offset is required, a_offset needs to be passed at compile time using -DA_OFFSET (i.e. -DA_OFFSET=1) |
| * @note In case the offset contribution due to b_offset is required, b_offset needs to be passed at compile time using -DB_OFFSET (i.e. -DB_OFFSET=6) |
| * @note In case sum_col has batches, -DSUM_COL_HAS_BATCHES must be passed at compile time. Usually if gemmlowp is used to accelerate convolution layer, sum_col will not have batches |
| * |
| * The final result is: |
| * |
| * mm_result[i][k] = mm_result[i][k] + |
| * (sum_col[k] * A_OFFSET) + |
| * (sum_row[i] * B_OFFSET) + |
| * (K_OFFSET) |
| * |
| * @param[in] mm_result_ptr Pointer to the source tensor. Supported data type: S32 |
| * @param[in] mm_result_stride_x Stride of the source tensor in X dimension (in bytes) |
| * @param[in] mm_result_step_x mm_result_stride_x * number of elements along X processed per workitem(in bytes) |
| * @param[in] mm_result_stride_y Stride of the source tensor in Y dimension (in bytes) |
| * @param[in] mm_result_step_y mm_result_stride_y * number of elements along Y processed per workitem(in bytes) |
| * @param[in] mm_result_stride_z Stride of the source tensor in Z dimension (in bytes) |
| * @param[in] mm_result_step_z mm_result_stride_z * number of elements along Z processed per workitem(in bytes) |
| * @param[in] mm_result_offset_first_element_in_bytes The offset of the first element in the source tensor |
| * @param[in] sum_col_result_ptr Pointer to the source tensor. Supported data type: same as @p mm_result_ptr |
| * @param[in] sum_col_result_stride_x Stride of the source tensor in X dimension (in bytes) |
| * @param[in] sum_col_result_step_x sum_col_stride_x * number of elements along X processed per workitem(in bytes) |
| * @param[in] sum_col_result_stride_y Stride of the source tensor in Y dimension (in bytes) |
| * @param[in] sum_col_result_step_y sum_col_stride_y * number of elements along Y processed per workitem(in bytes) |
| * @param[in] sum_col_result_offset_first_element_in_bytes The offset of the first element in the source tensor |
| * @param[in] sum_row_result_ptr Pointer to the source tensor. Supported data type: same as @p mm_result_ptr |
| * @param[in] sum_row_result_stride_x Stride of the source tensor in X dimension (in bytes) |
| * @param[in] sum_row_result_step_x sum_row_stride_x * number of elements along X processed per workitem(in bytes) |
| * @param[in] sum_row_result_stride_y Stride of the source tensor in Y dimension (in bytes) |
| * @param[in] sum_row_result_step_y sum_row_stride_y * number of elements along Y processed per workitem(in bytes) |
| * @param[in] sum_row_result_offset_first_element_in_bytes The offset of the first element in the source tensor |
| */ |
| __kernel void gemmlowp_offset_contribution(TENSOR3D_DECLARATION(mm_result) |
| #if defined(A_OFFSET) |
| , |
| IMAGE_DECLARATION(sum_col) |
| #endif // defined(A_OFFSET) |
| #if defined(B_OFFSET) |
| , |
| IMAGE_DECLARATION(sum_row) |
| #endif // defined(B_OFFSET) |
| ) |
| { |
| Tensor3D mm_result = CONVERT_TO_TENSOR3D_STRUCT(mm_result); |
| |
| int16 a_offset_s32 = (int16)0; |
| int16 b_offset_s32 = (int16)0; |
| |
| #if defined(A_OFFSET) |
| Image sum_col = CONVERT_TO_IMAGE_STRUCT(sum_col); |
| |
| // Compute the offset contribution due to A_OFFSET |
| #if defined(SUM_COL_HAS_BATCHES) |
| a_offset_s32 = vload16(0, (__global int *)(sum_col.ptr + get_global_id(2) * sum_col_stride_y)); |
| #else // defined(MATRIX_B_HAS_BATCHES) |
| a_offset_s32 = vload16(0, (__global int *)(sum_col.ptr)); |
| #endif // defined(MATRIX_B_HAS_BATCHES) |
| |
| a_offset_s32 *= (int16)A_OFFSET; |
| #endif // defined(A_OFFSET) |
| |
| #if defined(B_OFFSET) |
| Image sum_row = CONVERT_TO_IMAGE_STRUCT(sum_row); |
| |
| // Compute the offset contribution due to B_OFFSET |
| b_offset_s32 = (int16) * (((__global int *)(sum_row.ptr + get_global_id(2) * sum_row_stride_y)) + get_global_id(1)); |
| b_offset_s32 *= (int16)B_OFFSET; |
| #endif // defined(B_OFFSET) |
| |
| const int16 offset_term_s32 = (int16)K_OFFSET + a_offset_s32 + b_offset_s32; |
| |
| int16 in_s32 = vload16(0, (__global int *)mm_result.ptr); |
| |
| // Add the offset terms to GEMM's result |
| in_s32 += offset_term_s32; |
| |
| // Store the result with the offset contribution |
| vstore16(in_s32, 0, (__global int *)mm_result.ptr); |
| } |
| #endif // defined(K_OFFSET) |
| |
| #if defined(RESULT_OFFSET) && defined(RESULT_MULT_INT) && defined(RESULT_SHIFT) |
| /** This OpenCL kernel is used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8 |
| * |
| * This kernel takes a final int32 accumulator value and processes it to obtain the final QASYMM8 value. |
| * The following computations will be performed by the kernel: |
| * |
| * -# Add offset terms to final result |
| * -# Multiply each entry of result by result_mult_int |
| * -# Add bias to final result (if -DADD_BIAS is passed at compile time) |
| * -# Shift the int32 accumulator by result_shift |
| * -# Clamp the value between the specified min and max bounds (if -DMIN_BOUND and/or -DMAX_BOUND are passed at compile time) |
| * -# Clamp the resulting int32 values to the [0..255] range and cast to QASYMM8. |
| * |
| * @attention The offset, scalar scale factor and number of bits to shift right of output tensor must be passed at compile time using -DRESULT_OFFSET, -RESULT_MULT_INT and -DRESULT_SHIFT |
| * |
| * @note In case the addition of int32 biases is required, -DADD_BIAS should be passed at compile time |
| * @note In case the clamping of the result is required, the min and max bounds can be passed at compile time using -DMIN_BOUND and -DMAX_BOUND. |
| * These values can be used to implement "rectified linear unit" activation functions |
| * |
| * @param[in] src_ptr Pointer to the source tensor. Supported data type: S32 |
| * @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[in] biases_ptr Pointer to the biases tensor. Supported data type: 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[out] dst_ptr Pointer to the destination tensor Supported data type: QASYMM8 |
| * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) |
| * @param[in] dst_step_x dst_gx_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_gx_stride_y * number of elements along Y processed per workitem(in bytes) |
| * @param[in] dst_stride_z Stride of the source tensor in Z dimension (in bytes) |
| * @param[in] dst_step_z src_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 |
| */ |
| __kernel void gemmlowp_output_stage_quantize_down(TENSOR3D_DECLARATION(src), |
| #if defined(ADD_BIAS) |
| VECTOR_DECLARATION(biases), |
| #endif // defined(ADD_BIAS) |
| TENSOR3D_DECLARATION(dst)) |
| { |
| // Compute source and destination addresses |
| Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src); |
| Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst); |
| #if defined(ADD_BIAS) |
| Vector biases = CONVERT_TO_VECTOR_STRUCT(biases); |
| #endif // defined(ADD_BIAS) |
| |
| int16 input_values = vload16(0, (__global int *)src.ptr); |
| |
| // Add the offset terms to GEMM's result |
| input_values += (int16)RESULT_OFFSET; |
| |
| #if defined(ADD_BIAS) |
| // Add bias |
| const int16 biases_values = vload16(0, (__global int *)biases.ptr); |
| input_values += (int16)biases_values; |
| #endif // defined(ADD_BIAS) |
| |
| // Multiply by result_mult_int and shift |
| input_values *= RESULT_MULT_INT; |
| |
| input_values >>= RESULT_SHIFT; |
| |
| uchar16 res = convert_uchar16_sat(input_values); |
| |
| #if defined(MIN_BOUND) |
| res = max(res, (uchar16)MIN_BOUND); |
| #endif // defined(MIN_BOUND) |
| #if defined(MAX_BOUND) |
| res = min(res, (uchar16)MAX_BOUND); |
| #endif // defined(MAX_BOUND) |
| |
| // Store the result |
| vstore16(res, 0, dst.ptr); |
| } |
| #endif // defined(RESULT_OFFSET) && defined(RESULT_MULT_INT) && defined(RESULT_SHIFT) |
| |
| #if defined(RESULT_OFFSET_AFTER_SHIFT) && defined(RESULT_FIXEDPOINT_MULTIPLIER) && defined(RESULT_SHIFT) |
| /** This OpenCL kernel is used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8 |
| * |
| * This kernel takes a final int32 accumulator value (the output of @ref CLGEMMLowpMatrixMultiplyKernel), and processes it to obtain the final QASYMM8 value. |
| * The following computations will be performed by the kernel: |
| * |
| * -# Compute fixed point multiplication between each entry of input by result_fixedpoint_multiplier |
| * -# Add bias to final result if bias tensor is not a nullptr |
| * -# Round to nearest division by a power-of-two using result_shift |
| * -# Add offset to each result |
| * -# Clamp the value between the specified min and max bounds |
| * -# Clamp the resulting int32 values to the [0..255] range and cast to QASYMM8. |
| * |
| * @attention The offset, scalar scale factor and number of bits to shift right of output tensor must be passed at compile time using -DRESULT_OFFSET, -RESULT_MULT_INT and -DRESULT_SHIFT |
| * |
| * @note In case the addition of int32 biases is required, -DADD_BIAS should be passed at compile time |
| * @note In case the clamping of the result is required, the min and max bounds can be passed at compile time using -DMIN_BOUND and -DMAX_BOUND. |
| * These values can be used to implement "rectified linear unit" activation functions |
| * |
| * @param[in] src_ptr Pointer to the source tensor. Supported data type: S32 |
| * @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[in] biases_ptr Pointer to the biases tensor. Supported data type: 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[out] dst_ptr Pointer to the destination tensor Supported data type: QASYMM8 |
| * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) |
| * @param[in] dst_step_x dst_gx_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_gx_stride_y * number of elements along Y processed per workitem(in bytes) |
| * @param[in] dst_stride_z Stride of the source tensor in Z dimension (in bytes) |
| * @param[in] dst_step_z src_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 |
| */ |
| __kernel void gemmlowp_output_stage_quantize_down_fixedpoint(TENSOR3D_DECLARATION(src), |
| #if defined(ADD_BIAS) |
| VECTOR_DECLARATION(biases), |
| #endif // defined(ADD_BIAS) |
| TENSOR3D_DECLARATION(dst)) |
| { |
| // Compute source and destination addresses |
| Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src); |
| Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst); |
| #if defined(ADD_BIAS) |
| Vector biases = CONVERT_TO_VECTOR_STRUCT(biases); |
| #endif // defined(ADD_BIAS) |
| |
| int16 input_values = vload16(0, (__global int *)src.ptr); |
| |
| #if defined(ADD_BIAS) |
| // Add bias |
| const int16 biases_values = vload16(0, (__global int *)biases.ptr); |
| input_values += (int16)biases_values; |
| #endif // defined(ADD_BIAS) |
| |
| // Multiply by result_mult_int and shift |
| input_values = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(input_values, RESULT_FIXEDPOINT_MULTIPLIER, RESULT_SHIFT, 16); |
| |
| // Add the offset terms to GEMM's result |
| input_values += (int16)RESULT_OFFSET_AFTER_SHIFT; |
| |
| uchar16 res = convert_uchar16_sat(input_values); |
| |
| #if defined(MIN_BOUND) |
| res = max(res, (uchar16)MIN_BOUND); |
| #endif // defined(MIN_BOUND) |
| #if defined(MAX_BOUND) |
| res = min(res, (uchar16)MAX_BOUND); |
| #endif // defined(MAX_BOUND) |
| |
| // Store the result |
| vstore16(res, 0, dst.ptr); |
| } |
| #endif // defined(RESULT_OFFSET_AFTER_SHIFT) && defined(RESULT_FIXEDPOINT_MULTIPLIER) && defined(RESULT_SHIFT) |