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Diffstat (limited to 'src/core/CL/cl_kernels/gemmlowp.cl')
| -rw-r--r-- | src/core/CL/cl_kernels/gemmlowp.cl | 2316 |
1 files changed, 0 insertions, 2316 deletions
diff --git a/src/core/CL/cl_kernels/gemmlowp.cl b/src/core/CL/cl_kernels/gemmlowp.cl deleted file mode 100644 index d3eba89e76..0000000000 --- a/src/core/CL/cl_kernels/gemmlowp.cl +++ /dev/null @@ -1,2316 +0,0 @@ -/* - * Copyright (c) 2017-2021 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 "gemm_helpers.h" -#include "helpers_asymm.h" -#include "repeat.h" - -#if defined(DATA_TYPE) && defined(ACC_DATA_TYPE) - -#if defined(ARM_COMPUTE_OPENCL_DOT8_ENABLED) && defined(cl_arm_integer_dot_product_int8) -#if defined(ARM_COMPUTE_OPENCL_DOT8_ACC_ENABLED) && defined(cl_arm_integer_dot_product_accumulate_int8) -#define ARM_DOT(x, y, val) val = arm_dot_acc((x), (y), (val)); -#else // defined(ARM_COMPUTE_OPENCL_DOT8_ACC_ENABLED) && defined(cl_arm_integer_dot_product_accumulate_int8) -#define ARM_DOT(x, y, val) val += arm_dot((x), (y)); -#endif // defined(ARM_COMPUTE_OPENCL_DOT8_ACC_ENABLED) && defined(cl_arm_integer_dot_product_accumulate_int8) -#endif // defined(ARM_COMPUTE_OPENCL_DOT8_ENABLED) && defined(cl_arm_integer_dot_product_int8) - -#if defined(ARM_COMPUTE_OPENCL_DOT8_ENABLED) && defined(cl_arm_integer_dot_product_int8) - -#define ARM_DOT1(a, b, c) \ - ({ \ - ARM_DOT((VEC_DATA_TYPE(DATA_TYPE, 4))(a, (VEC_DATA_TYPE(DATA_TYPE, 3))0), (VEC_DATA_TYPE(DATA_TYPE, 4))(b, (VEC_DATA_TYPE(DATA_TYPE, 3))0), c); \ - }) -#define ARM_DOT2(a, b, c) \ - ({ \ - ARM_DOT((VEC_DATA_TYPE(DATA_TYPE, 4))(a, (VEC_DATA_TYPE(DATA_TYPE, 2))0), (VEC_DATA_TYPE(DATA_TYPE, 4))(b, (VEC_DATA_TYPE(DATA_TYPE, 2))0), c); \ - }) -#define ARM_DOT3(a, b, c) \ - ({ \ - ARM_DOT((VEC_DATA_TYPE(DATA_TYPE, 4))(a, (DATA_TYPE)0), (VEC_DATA_TYPE(DATA_TYPE, 4))(b, (DATA_TYPE)0), c); \ - }) -#define ARM_DOT4(a, b, c) \ - ({ \ - ARM_DOT(a, b, c); \ - }) -#define ARM_DOT8(a, b, c) \ - ({ \ - ARM_DOT4((a.lo), (b.lo), c); \ - ARM_DOT4((a.hi), (b.hi), c); \ - }) -#define ARM_DOT16(a, b, c) \ - ({ \ - ARM_DOT8((a.lo), (b.lo), c); \ - ARM_DOT8((a.hi), (b.hi), c); \ - }) - -#else // defined(ARM_COMPUTE_OPENCL_DOT8_ENABLED) && defined(cl_arm_integer_dot_product_int8) - -/** Specialized macros to perform the dot product instruction between two vectors of size K0 [1,16] without using the dot8 instruction. */ -#define ARM_DOT1(a, b, c) \ - ({ \ - c += (ACC_DATA_TYPE)a * b; \ - }) -#define ARM_DOT2(a, b, c) \ - ({ \ - c += (ACC_DATA_TYPE)a.s0 * b.s0; \ - c += (ACC_DATA_TYPE)a.s1 * b.s1; \ - }) -#define ARM_DOT3(a, b, c) \ - ({ \ - ARM_DOT2(a, b, c); \ - c += (ACC_DATA_TYPE)a.s2 * b.s2; \ - }) -#define ARM_DOT4(a, b, c) \ - ({ \ - ARM_DOT3(a, b, c); \ - c += (ACC_DATA_TYPE)a.s3 * b.s3; \ - }) -#define ARM_DOT8(a, b, c) \ - ({ \ - ARM_DOT4((a.lo), (b.lo), c); \ - ARM_DOT4((a.hi), (b.hi), c); \ - }) -#define ARM_DOT16(a, b, c) \ - ({ \ - ARM_DOT8((a.lo), (b.lo), c); \ - ARM_DOT8((a.hi), (b.hi), c); \ - }) -#endif // defined(ARM_COMPUTE_OPENCL_DOT8_ENABLED) && defined(cl_arm_integer_dot_product_int8) - -/** Specialized macros to perform a broadcast dot product operation between one vector "a" and N0 vectors "b" of size K0 [1,16] */ -#define ARM_DOT_K0X1(k0, a, b, c) \ - ({ \ - ARM_DOT_K0(k0, (a), (b##0), (c)); \ - }) -#define ARM_DOT_K0X2(k0, a, b, c) \ - ({ \ - ARM_DOT_K0(k0, (a), (b##0), (c.s0)); \ - ARM_DOT_K0(k0, (a), (b##1), (c.s1)); \ - }) -#define ARM_DOT_K0X3(k0, a, b, c) \ - ({ \ - ARM_DOT_K0X2(k0, a, b, c); \ - ARM_DOT_K0(k0, (a), (b##2), (c.s2)); \ - }) -#define ARM_DOT_K0X4(k0, a, b, c) \ - ({ \ - ARM_DOT_K0X3(k0, a, b, c); \ - ARM_DOT_K0(k0, (a), (b##3), (c.s3)); \ - }) -#define ARM_DOT_K0X8(k0, a, b, c) \ - ({ \ - ARM_DOT_K0X4(k0, a, b, c); \ - ARM_DOT_K0(k0, (a), (b##4), (c.s4)); \ - ARM_DOT_K0(k0, (a), (b##5), (c.s5)); \ - ARM_DOT_K0(k0, (a), (b##6), (c.s6)); \ - ARM_DOT_K0(k0, (a), (b##7), (c.s7)); \ - }) -#define ARM_DOT_K0X16(k0, a, b, c) \ - ({ \ - ARM_DOT_K0X8(k0, a, b, c); \ - ARM_DOT_K0(k0, (a), (b##8), (c.s8)); \ - ARM_DOT_K0(k0, (a), (b##9), (c.s9)); \ - ARM_DOT_K0(k0, (a), (b##A), (c.sA)); \ - ARM_DOT_K0(k0, (a), (b##B), (c.sB)); \ - ARM_DOT_K0(k0, (a), (b##C), (c.sC)); \ - ARM_DOT_K0(k0, (a), (b##D), (c.sD)); \ - ARM_DOT_K0(k0, (a), (b##E), (c.sE)); \ - ARM_DOT_K0(k0, (a), (b##F), (c.sF)); \ - }) - -/** Specialized macros to perform a partial matrix multiplication with dimensions M0,N0,K0 */ -#define ARM_MM_K0XN0X1(n0, k0, a, b, c) \ - ({ \ - ARM_DOT_K0XN0(n0, k0, (a##0), b, (c##0)); \ - }) -#define ARM_MM_K0XN0X2(n0, k0, a, b, c) \ - ({ \ - ARM_MM_K0XN0X1(n0, k0, a, b, c); \ - ARM_DOT_K0XN0(n0, k0, (a##1), b, (c##1)); \ - }) -#define ARM_MM_K0XN0X3(n0, k0, a, b, c) \ - ({ \ - ARM_MM_K0XN0X2(n0, k0, a, b, c); \ - ARM_DOT_K0XN0(n0, k0, (a##2), b, (c##2)); \ - }) -#define ARM_MM_K0XN0X4(n0, k0, a, b, c) \ - ({ \ - ARM_MM_K0XN0X3(n0, k0, a, b, c); \ - ARM_DOT_K0XN0(n0, k0, (a##3), b, (c##3)); \ - }) -#define ARM_MM_K0XN0X5(n0, k0, a, b, c) \ - ({ \ - ARM_MM_K0XN0X4(n0, k0, a, b, c); \ - ARM_DOT_K0XN0(n0, k0, (a##4), b, (c##4)); \ - }) -#define ARM_MM_K0XN0X6(n0, k0, a, b, c) \ - ({ \ - ARM_MM_K0XN0X5(n0, k0, a, b, c); \ - ARM_DOT_K0XN0(n0, k0, (a##5), b, (c##5)); \ - }) -#define ARM_MM_K0XN0X7(n0, k0, a, b, c) \ - ({ \ - ARM_MM_K0XN0X6(n0, k0, a, b, c); \ - ARM_DOT_K0XN0(n0, k0, (a##6), b, (c##6)); \ - }) -#define ARM_MM_K0XN0X8(n0, k0, a, b, c) \ - ({ \ - ARM_MM_K0XN0X7(n0, k0, a, b, c); \ - ARM_DOT_K0XN0(n0, k0, (a##7), b, (c##7)); \ - }) - -#define ARM_DOT_K0(k0, a, b, c) \ - ({ \ - CONCAT(ARM_DOT, k0) \ - ((a), (b), (c)); \ - }) - -#define ARM_DOT_K0XN0(n0, k0, a, b, c) \ - ({ \ - CONCAT(ARM_DOT_K0X, n0) \ - (k0, (a), b, (c)); \ - }) - -#define ARM_MM_K0XN0XM0(m0, n0, k0, a, b, c) \ - ({ \ - CONCAT(ARM_MM_K0XN0X, m0) \ - (n0, k0, a, b, c); \ - }) - -/** Specialized macros to perform a broadcast dot product operation between one vector "a" and N0 vectors "b" of size K0 [1,16] */ -#define ARM_MUL_N0X1(VECTOR_ACC_TYPE, a, b, c) \ - ({ \ - c += CONVERT(b##0, VECTOR_ACC_TYPE) * a; \ - }) -#define ARM_MUL_N0X2(VECTOR_ACC_TYPE, a, b, c) \ - ({ \ - c += CONVERT(b##0, VECTOR_ACC_TYPE) * a.s##0; \ - c += CONVERT(b##1, VECTOR_ACC_TYPE) * a.s##1; \ - }) -#define ARM_MUL_N0X3(VECTOR_ACC_TYPE, a, b, c) \ - ({ \ - ARM_MUL_N0X2(VECTOR_ACC_TYPE, a, b, c); \ - c += CONVERT(b##2, VECTOR_ACC_TYPE) * a.s##2; \ - }) -#define ARM_MUL_N0X4(VECTOR_ACC_TYPE, a, b, c) \ - ({ \ - ARM_MUL_N0X3(VECTOR_ACC_TYPE, a, b, c); \ - c += CONVERT(b##3, VECTOR_ACC_TYPE) * a.s##3; \ - }) -#define ARM_MUL_N0X8(VECTOR_ACC_TYPE, a, b, c) \ - ({ \ - ARM_MUL_N0X4(VECTOR_ACC_TYPE, a, b, c); \ - c += CONVERT(b##4, VECTOR_ACC_TYPE) * a.s##4; \ - c += CONVERT(b##5, VECTOR_ACC_TYPE) * a.s##5; \ - c += CONVERT(b##6, VECTOR_ACC_TYPE) * a.s##6; \ - c += CONVERT(b##7, VECTOR_ACC_TYPE) * a.s##7; \ - }) -#define ARM_MUL_N0X16(VECTOR_ACC_TYPE, a, b, c) \ - ({ \ - ARM_MUL_N0X8(VECTOR_ACC_TYPE, a, b, c); \ - c += CONVERT(b##8, VECTOR_ACC_TYPE) * a.s##8; \ - c += CONVERT(b##9, VECTOR_ACC_TYPE) * a.s##9; \ - c += CONVERT(b##A, VECTOR_ACC_TYPE) * a.s##A; \ - c += CONVERT(b##B, VECTOR_ACC_TYPE) * a.s##B; \ - c += CONVERT(b##C, VECTOR_ACC_TYPE) * a.s##C; \ - c += CONVERT(b##D, VECTOR_ACC_TYPE) * a.s##D; \ - c += CONVERT(b##E, VECTOR_ACC_TYPE) * a.s##E; \ - c += CONVERT(b##F, VECTOR_ACC_TYPE) * a.s##F; \ - }) -/** Specialized macros to perform a a partial matrix multiplication with dimensions M0,N0,K0 */ -#define ARM_MM_NATIVE_N0XK0X1(VECTOR_ACC_TYPE, k0, a, b, c) \ - ({ \ - ARM_MUL_N0XK0(VECTOR_ACC_TYPE, k0, (a##0), b, (c##0)); \ - }) -#define ARM_MM_NATIVE_N0XK0X2(VECTOR_ACC_TYPE, k0, a, b, c) \ - ({ \ - ARM_MM_NATIVE_N0XK0X1(VECTOR_ACC_TYPE, k0, a, b, c); \ - ARM_MUL_N0XK0(VECTOR_ACC_TYPE, k0, (a##1), b, (c##1)); \ - }) -#define ARM_MM_NATIVE_N0XK0X3(VECTOR_ACC_TYPE, k0, a, b, c) \ - ({ \ - ARM_MM_NATIVE_N0XK0X2(VECTOR_ACC_TYPE, k0, a, b, c); \ - ARM_MUL_N0XK0(VECTOR_ACC_TYPE, k0, (a##2), b, (c##2)); \ - }) -#define ARM_MM_NATIVE_N0XK0X4(VECTOR_ACC_TYPE, k0, a, b, c) \ - ({ \ - ARM_MM_NATIVE_N0XK0X3(VECTOR_ACC_TYPE, k0, a, b, c); \ - ARM_MUL_N0XK0(VECTOR_ACC_TYPE, k0, (a##3), b, (c##3)); \ - }) -#define ARM_MM_NATIVE_N0XK0X5(VECTOR_ACC_TYPE, k0, a, b, c) \ - ({ \ - ARM_MM_NATIVE_N0XK0X4(VECTOR_ACC_TYPE, k0, a, b, c); \ - ARM_MUL_N0XK0(VECTOR_ACC_TYPE, k0, (a##4), b, (c##4)); \ - }) -#define ARM_MM_NATIVE_N0XK0X6(VECTOR_ACC_TYPE, k0, a, b, c) \ - ({ \ - ARM_MM_NATIVE_N0XK0X5(VECTOR_ACC_TYPE, k0, a, b, c); \ - ARM_MUL_N0XK0(VECTOR_ACC_TYPE, k0, (a##5), b, (c##5)); \ - }) -#define ARM_MM_NATIVE_N0XK0X7(VECTOR_ACC_TYPE, k0, a, b, c) \ - ({ \ - ARM_MM_NATIVE_N0XK0X6(VECTOR_ACC_TYPE, k0, a, b, c); \ - ARM_MUL_N0XK0(VECTOR_ACC_TYPE, k0, (a##6), b, (c##6)); \ - }) -#define ARM_MM_NATIVE_N0XK0X8(VECTOR_ACC_TYPE, k0, a, b, c) \ - ({ \ - ARM_MM_NATIVE_N0XK0X7(VECTOR_ACC_TYPE, k0, a, b, c); \ - ARM_MUL_N0XK0(VECTOR_ACC_TYPE, k0, (a##7), b, (c##7)); \ - }) -#define ARM_MUL_N0XK0(VECTOR_ACC_TYPE, k0, a, b, c) \ - ({ \ - CONCAT(ARM_MUL_N0X, k0) \ - (VECTOR_ACC_TYPE, (a), b, (c)); \ - }) -#define ARM_MM_NATIVE_N0XK0XM0(VECTOR_ACC_TYPE, m0, k0, a, b, c) \ - ({ \ - CONCAT(ARM_MM_NATIVE_N0XK0X, m0) \ - (VECTOR_ACC_TYPE, k0, a, b, c); \ - }) - -#if defined(M0) && defined(N0) && defined(K0) && defined(V0) && defined(H0) && defined(M) && defined(N) && defined(PARTIAL_STORE_M0) && defined(PARTIAL_STORE_N0) -/** This OpenCL kernel computes the matrix multiplication between 2 matrices with QASYMM/QASYMM_SIGNED data type. - * The LHS matrix must be reshaped with @ref CLGEMMReshapeLHSMatrixKernel and the M0xK0 must be NOT transposed - * The RHS matrix must be reshaped with @ref CLGEMMReshapeRHSMatrixKernel and the K0xN0 must be transposed - * - * @note The input data type must be passed at compile time using -DDATA_TYPE (i.e. -DDATA_TYPE=uchar) - * @note The accumulator data type must be passed at compile time using -DACC_DATA_TYPE (i.e. -DACC_DATA_TYPE=uint) - * @note If the first two dimensions of NDRange have been dispatched with "dummy_work_items" support, the option -DDUMMY_WORK_ITEMS must be passed at compile time. - * @note The GEMM's dimensions M and N must be passed at compile time using -DM and -DN (i.e. -DM=52 and -DN=90). - * @note The block's dimensions used for reshaping the LHS matrix and the RHS matrix (M0, N0 and K0) must be passed at compile time using -DM0, -DN0 and -DK0 (i.e. -DM0=4, -DN0=8, -DK0=4). - * @note The number of M0xK0 vertical blocks stored on the same output row of the reshaped LHS matrix must be passed at compile time using -DV0 (i.e. -DV0=2) - * @note The number of K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (i.e. -DH0=2) - * @note If the M0xK0 blocks in the reshaped LHS matrix have been interleaved, the option -DLHS_INTERLEAVE must passed at compile time. - * @note If the K0xN0 blocks in the reshaped RHS matrix have been interleaved, the option -DRHS_INTERLEAVE must passed at compile time. - * @note Only the following configurations of M0, N0 and K0 are currently supported: - * - M0 = 2, 3, 4, 5, 6, 7, 8 - * - N0 = 2, 3, 4, 8, 16 - * - K0 = 2, 3, 4, 8, 16 - * - V0 >= 1 - * - H0 >= 1 - * - * @note In case the output has to be reinterpreted as a 3D tensor (i.e. output of convolution layer), the following information must be passed at compile time: - * -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D - * -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor. - * -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor - * (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns LHS matrix NOT reshaped - * - * @param[in] lhs_ptr Pointer to the LHS reshaped matrix. Supported data type: QASYMM8/QASYMM_SIGNED - * @param[in] lhs_stride_x Stride of the LHS reshaped matrix in X dimension (in bytes) - * @param[in] lhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] lhs_stride_y Stride of the LHS reshaped matrix in Y dimension (in bytes) - * @param[in] lhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS reshaped matrix - * @param[in] rhs_ptr Pointer to the RHS reshaped matrix. Supported data type: same as @p lhs_ptr - * @param[in] rhs_stride_x Stride of the RHS reshaped matrix in X dimension (in bytes) - * @param[in] rhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] rhs_stride_y Stride of the RHS reshaped matrix in Y dimension (in bytes) - * @param[in] rhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the RHS reshaped 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_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_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 - * @param[in] k Number of columns in LHS matrix and rows in RHS matrix not reshaped. - * @param[in] lhs_stride_z Stride of the LHS reshaped matrix in Z dimension (in bytes) - * @param[in] rhs_stride_z Stride of the RHS reshaped matrix in Z dimension (in bytes) - * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) - * @param[in] dst_cross_plane_pad (Optional) Bottom paddings in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D) - */ -__kernel void gemmlowp_mm_reshaped_lhs_nt_rhs_t(IMAGE_DECLARATION(lhs), - IMAGE_DECLARATION(rhs), - IMAGE_DECLARATION(dst), - uint k, - uint lhs_stride_z, - uint rhs_stride_z, - uint dst_stride_z -#if defined(REINTERPRET_OUTPUT_AS_3D) - , - uint dst_cross_plane_pad -#endif // REINTERPRET_OUTPUT_AS_3D - ) -{ - // Block size -#define LHS_BLOCK_SIZE ((K0) * (M0)) - -#if defined(LHS_INTERLEAVE) -#define LHS_OFFSET_X (K0) -#define LHS_STEP_X ((K0) * (V0)) -#define LHS_STEP_LOOP (1) -#else // defined(INTERLEAVE) -#define LHS_OFFSET_X (LHS_BLOCK_SIZE) -#define LHS_STEP_X (K0) -#define LHS_STEP_LOOP (V0) -#endif // defined(INTERLEAVE) - - // Block size -#define RHS_BLOCK_SIZE ((K0) * (N0)) - - // RHS offset and step X -#if defined(RHS_INTERLEAVE) -#define RHS_OFFSET_X (K0) -#define RHS_STEP_X ((K0) * (H0)) -#define RHS_STEP_LOOP (1) -#else // defined(RHS_INTERLEAVE) -#define RHS_OFFSET_X (RHS_BLOCK_SIZE) -#define RHS_STEP_X (K0) -#define RHS_STEP_LOOP (H0) -#endif // defined(RHS_INTERLEAVE) - - uint x = get_global_id(0); - uint y = get_global_id(1); - uint z = get_global_id(2); - -#if defined(DUMMY_WORK_ITEMS) - if((x * N0 >= N) || (y * M0 >= M)) - { - return; - } -#endif // defined(DUMMY_WORK_ITEMS) - - // Compute LHS matrix address - __global DATA_TYPE *lhs_addr = (__global DATA_TYPE *)(lhs_ptr + lhs_offset_first_element_in_bytes + (y % V0) * (uint)LHS_OFFSET_X + (y / V0) * (uint)lhs_stride_y + (z * lhs_stride_z)); - - // Compute RHS matrix address - __global DATA_TYPE *rhs_addr = (__global DATA_TYPE *)(rhs_ptr + rhs_offset_first_element_in_bytes + (x % H0) * (uint)RHS_OFFSET_X + (x / (uint)H0) * rhs_stride_y); - -#if defined(MATRIX_B_DEPTH) - // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3 - rhs_addr += (z % MATRIX_B_DEPTH) * rhs_stride_z; -#else // defined(MATRIX_B_DEPTH) - rhs_addr += z * rhs_stride_z; -#endif // defined(MATRIX_B_DEPTH) - - REPEAT_VAR_INIT_TO_CONST(8, uint, zlhs, 0); //uint zout0=0,zout1=0,zout2=0,... zout7=0; - REPEAT_VAR_INIT_TO_CONST(16, uint, zrhs, 0); - - // Initialize the accumulators - REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(ACC_DATA_TYPE, N0), c, 0); //VEC_DATA_TYPE(ACC_DATA_TYPE, N0) c0=0,c1=0,c2=0,... c(M0-1)=0; - - for(int i = 0; i < k; i += K0) - { - // Load values from LHS matrix - LOAD_BLOCK(M0, K0, DATA_TYPE, a, lhs_addr, 0, LHS_STEP_X, zlhs); - - // Load values from RHS matrix - LOAD_BLOCK(N0, K0, DATA_TYPE, b, rhs_addr, 0, RHS_STEP_X, zrhs); - - // Partial matrix multiplication M0,N0,K0 - ARM_MM_K0XN0XM0(M0, N0, K0, a, b, c); - - // Update address - lhs_addr += (M0 * LHS_STEP_X * LHS_STEP_LOOP); - rhs_addr += (N0 * RHS_STEP_X * RHS_STEP_LOOP); - } - - __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(int)) + (y * (uint)M0 * dst_stride_y); - - REPEAT_VAR_INIT_TO_CONST(8, uint, zout, 0); //uint zout0=0,zout1=0,zout2=0,... zout7=0; - -#if defined(REINTERPRET_OUTPUT_AS_3D) - // The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D - CALCULATE_Z_OFFSET(M0, uint, zout, y * M0, HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y); - - // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we - // multiply dst_stride_z by DEPTH_GEMM3D - dst_addr += z * dst_stride_z * DEPTH_GEMM3D; - -#else // defined(REINTERPRET_OUTPUT_AS_3D) - - // Add offset for batched GEMM - dst_addr += z * dst_stride_z; - -#endif // defined(REINTERPRET_OUTPUT_AS_3D) - - // Convert and store output block - const bool cond_y = ((get_global_id(1) + 1) * M0 >= M); - const bool cond_x = ((get_global_id(0) + 1) * N0 >= N); - - // Store output block - REPEAT_VAR_INIT_CONVERT_SAT(M0, VEC_DATA_TYPE(int, N0), c, c_lp); - STORE_BLOCK_BOUNDARY_AWARE(M0, N0, int, c_lp, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); - -#undef LHS_BLOCK_SIZE -#undef LHS_OFFSET_X -#undef LHS_STEP_X -#undef RHS_BLOCK_SIZE -#undef RHS_OFFSET_X -#undef RHS_STEP_X -} -#endif // defined(M0) && defined(N0) && defined(K0) && defined(V0) && defined(H0) && defined(M) && defined(N) && defined(PARTIAL_STORE_M0) && defined(PARTIAL_STORE_N0) - -#if defined(M0) && defined(N0) && defined(K0) && defined(H0) && defined(K) && defined(PARTIAL_STORE_M0) && defined(PARTIAL_STORE_N0) - -/** This OpenCL kernel computes the matrix multiplication between 2 matrices. - * The LHS matrix is NOT reshaped - * The RHS matrix is reshaped with @ref CLGEMMReshapeRHSMatrixKernel and the block K0xN0 is transposed - * - * @note The input data type must be passed at compile time using -DDATA_TYPE (i.e. -DDATA_TYPE=uchar) - * @note The accumulator data type must be passed at compile time using -DACC_DATA_TYPE (i.e. -DACC_DATA_TYPE=uint) - * @note The number of columns of LHS matrix must be passed at compile time using -DK (i.e. -DK=64) - * @note The block's dimensions used for reshaping the RHS matrix (N0 and K0) must be passed at compile time using -DN0 and -DK0 (i.e. -DN0=8, -DK0=4). - * @note The number of M0 rows to process must be passed at compile time using -DM0 (i.e. -DM0=2) - * @note The number of K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (i.e. -DH0=2) - * @note If the K0xN0 blocks in the reshaped RHS matrix have been interleaved, the option -DRHS_INTERLEAVE must passed at compile time. - * @note Only the following configurations of M0, N0 and K0 are currently supported: - * - M0 = 1, 2, 3, 4, 5, 6, 7, 8 - * - N0 = 2, 3, 4, 8, 16 - * - K0 = 2, 3, 4, 8, 16 - * - H0 >= 1 - * - * @note In case the input or output have to be reinterpreted as a 3D tensor, the following information must be passed at compile time: - * -# REINTERPRET_INPUT_AS_3D: To reinterpret the input as 3D - * -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D - * -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor. - * -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor - * (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns LHS matrix - * - * @param[in] lhs_ptr Pointer to the LHS reshaped matrix. Supported data type: QASYMM8/QASYMM8_SIGNED - * @param[in] lhs_stride_x Stride of the LHS reshaped matrix in X dimension (in bytes) - * @param[in] lhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] lhs_stride_y Stride of the LHS reshaped matrix in Y dimension (in bytes) - * @param[in] lhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS reshaped matrix - * @param[in] rhs_ptr Pointer to the RHS reshaped matrix. Supported data type: same as @p lhs_ptr - * @param[in] rhs_stride_x Stride of the RHS reshaped matrix in X dimension (in bytes) - * @param[in] rhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] rhs_stride_y Stride of the RHS reshaped matrix in Y dimension (in bytes) - * @param[in] rhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the RHS reshaped 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_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_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 - * @param[in] lhs_stride_z Stride of the LHS reshaped matrix in Z dimension (in bytes) - * @param[in] rhs_stride_z Stride of the RHS reshaped matrix in Z dimension (in bytes) - * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) - * @param[in] lhs_cross_plane_pad (Optional) Bottom paddings for LHS matrix in unit of elements (only if defined REINTERPRET_INPUT_AS_3D) - * @param[in] dst_cross_plane_pad (Optional) Bottom paddings for the output matrix in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D) - */ -__kernel void gemmlowp_mm_reshaped_only_rhs_t(IMAGE_DECLARATION(lhs), - IMAGE_DECLARATION(rhs), - IMAGE_DECLARATION(dst), - uint lhs_stride_z, - uint rhs_stride_z, - uint dst_stride_z -#if defined(REINTERPRET_INPUT_AS_3D) - , - uint lhs_cross_plane_pad -#endif // REINTERPRET_INPUT_AS_3D -#if defined(REINTERPRET_OUTPUT_AS_3D) - , - uint dst_cross_plane_pad -#endif // REINTERPRET_OUTPUT_AS_3D - ) -{ - // Block size -#define RHS_BLOCK_SIZE ((K0) * (N0)) - - // RHS offset and step X -#if defined(RHS_INTERLEAVE) -#define RHS_OFFSET_X (K0) -#define RHS_STEP_X ((K0) * (H0)) -#define RHS_STEP_LOOP (1) -#else // defined(RHS_INTERLEAVE) -#define RHS_OFFSET_X (RHS_BLOCK_SIZE) -#define RHS_STEP_X (K0) -#define RHS_STEP_LOOP (H0) -#endif // defined(RHS_INTERLEAVE) - - uint x = get_global_id(0); - uint y = get_global_id(1); - uint z = get_global_id(2); - -#if defined(DUMMY_WORK_ITEMS) - if((x * N0 >= N) || (y * M0 >= M)) - { - return; - } -#endif // defined(DUMMY_WORK_ITEMS) - - // Compute LHS matrix address - uint lhs_offset = lhs_offset_first_element_in_bytes + COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * (uint)lhs_stride_y; - - // Compute RHS matrix address - uint rhs_offset = rhs_offset_first_element_in_bytes + (x % H0) * (uint)RHS_OFFSET_X + (x / (uint)H0) * rhs_stride_y; - -#if defined(MATRIX_B_DEPTH) - // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3 - rhs_offset += (z % MATRIX_B_DEPTH) * rhs_stride_z; -#else // defined(MATRIX_B_DEPTH) - rhs_offset += z * rhs_stride_z; -#endif // defined(MATRIX_B_DEPTH) - - REPEAT_VAR_INIT_TO_CONST(8, uint, zlhs, 0); //uint zout0=0,zout1=0,zout2=0,... zout7=0; - REPEAT_VAR_INIT_TO_CONST(16, uint, zrhs, 0); - -#if defined(REINTERPRET_INPUT_AS_3D) - // The plane (zlhs) is calculated dividing M (y * M0) by HEIGHT_GEMM3D - CALCULATE_Z_OFFSET(M0, uint, zlhs, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y); - - // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we - // multiply lhs_stride_z by DEPTH_GEMM3D - lhs_offset += z * lhs_stride_z * DEPTH_GEMM3D; - -#else // defined(REINTERPRET_INPUT_AS_3D) - - // Add offset for batched GEMM - lhs_offset += z * lhs_stride_z; - -#endif // defined(REINTERPRET_INPUT_AS_3D) - - // Initialize the accumulators - REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(ACC_DATA_TYPE, N0), c, 0); //VEC_DATA_TYPE(ACC_DATA_TYPE, N0) c0=0,c1=0,c2=0,... c(N0-1)=0; - - int i = 0; - for(; i <= (K - K0); i += K0) - { - // Load values from LHS matrix - LOAD_BLOCK(M0, K0, DATA_TYPE, a, lhs_ptr, lhs_offset, lhs_stride_y, zlhs); - - // Load values from RHS matrix - LOAD_BLOCK(N0, K0, DATA_TYPE, b, rhs_ptr, rhs_offset, RHS_STEP_X, zrhs); - - // Partial matrix multiplication M0,N0,K0 - ARM_MM_K0XN0XM0(M0, N0, K0, a, b, c); - - lhs_offset += K0; - rhs_offset += N0 * RHS_STEP_X * RHS_STEP_LOOP; - } - // Left-over accumulations - for(; i < K; ++i) - { - // Load values from LHS matrix - LOAD_BLOCK(M0, 1, DATA_TYPE, a, lhs_ptr, lhs_offset, lhs_stride_y, zlhs); - - // Load values from RHS reshaped matrix - LOAD_BLOCK(N0, 1, DATA_TYPE, b, rhs_ptr, rhs_offset, RHS_STEP_X, zrhs); - - ARM_MM_K0XN0XM0(M0, N0, 1, a, b, c); - lhs_offset += 1; - rhs_offset += 1; - } - __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(int)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * dst_stride_y); - - REPEAT_VAR_INIT_TO_CONST(8, uint, zout, 0); //uint zout0=0,zout1=0,zout2=0,... zout7=0; - -#if defined(REINTERPRET_OUTPUT_AS_3D) - // The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D - CALCULATE_Z_OFFSET(M0, uint, zout, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y); - - // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we - // multiply dst_stride_z by DEPTH_GEMM3D - dst_addr += z * dst_stride_z * DEPTH_GEMM3D; - -#else // defined(REINTERPRET_OUTPUT_AS_3D) - - // Add offset for batched GEMM - dst_addr += z * dst_stride_z; - -#endif // defined(REINTERPRET_OUTPUT_AS_3D) - - // Convert and store output block - const bool cond_y = y == 0; - const bool cond_x = ((x + 1) * N0 >= N); - - // Store output block - REPEAT_VAR_INIT_CONVERT_SAT(M0, VEC_DATA_TYPE(int, N0), c, c_lp); - STORE_BLOCK_BOUNDARY_AWARE(M0, N0, int, c_lp, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); - -#undef RHS_BLOCK_SIZE -#undef RHS_OFFSET_X -#undef RHS_STEP_X -} - -#if defined(RESULT_OFFSET) && defined(RESULT_SHIFT) && defined(RESULT_MULTIPLIER) -/** This OpenCL kernel computes the matrix multiplication between 2 matrices with fused output stage using fixed-point arithmetic. - * The LHS matrix is NOT reshaped - * The RHS matrix is reshaped with @ref CLGEMMReshapeRHSMatrixKernel and the block K0xN0 is transposed - * - * @note The input data type must be passed at compile time using -DDATA_TYPE (i.e. -DDATA_TYPE=uchar) - * @note The accumulator data type must be passed at compile time using -DACC_DATA_TYPE (i.e. -DACC_DATA_TYPE=uint) - * @note The number of columns of LHS matrix must be passed at compile time using -DK (i.e. -DK=64) - * @note The block's dimensions used for reshaping the RHS matrix (N0 and K0) must be passed at compile time using -DN0 and -DK0 (i.e. -DN0=8, -DK0=4). - * @note The number of M0 rows to process must be passed at compile time using -DM0 (i.e. -DM0=2) - * @note The number of K0xN0 horizontal blocks stored on the same output row of the reshaped RHS matrix must be passed at compile time using -DH0 (i.e. -DH0=2) - * @note If the K0xN0 blocks in the reshaped RHS matrix have been interleaved, the option -DRHS_INTERLEAVE must passed at compile time. - * @note Only the following configurations of M0, N0 and K0 are currently supported: - * - M0 = 1, 2, 3, 4, 5, 6, 7, 8 - * - N0 = 2, 3, 4, 8, 16 - * - K0 = 2, 3, 4, 8, 16 - * - H0 >= 1 - * - * @note In case the input or output have to be reinterpreted as a 3D tensor, the following information must be passed at compile time: - * -# REINTERPRET_INPUT_AS_3D: To reinterpret the input as 3D - * -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D - * -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor. - * -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor - * (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns LHS matrix - * - * @note 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_MULTIPLIER and -DRESULT_SHIFT - * @note In case the addition of int32 biases is required, -DADD_BIAS should be passed at compile time - * @note The output datatype should be passed at compile time using -DOUTPUT_DATA_TYPE - * @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 - * @note In case of per-channel quantization of matrix B, -DPER_CHANNEL_QUANTIZATION must be passed at compile time. - * - * @param[in] lhs_ptr Pointer to the LHS reshaped matrix. Supported data type: QASYMM8/QASYMM8_SIGNED - * @param[in] lhs_stride_x Stride of the LHS reshaped matrix in X dimension (in bytes) - * @param[in] lhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] lhs_stride_y Stride of the LHS reshaped matrix in Y dimension (in bytes) - * @param[in] lhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS reshaped matrix - * @param[in] rhs_ptr Pointer to the RHS reshaped matrix. Supported data type: same as @p lhs_ptr - * @param[in] rhs_stride_x Stride of the RHS reshaped matrix in X dimension (in bytes) - * @param[in] rhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] rhs_stride_y Stride of the RHS reshaped matrix in Y dimension (in bytes) - * @param[in] rhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the RHS reshaped matrix - * @param[out] dst_ptr Pointer to the destination matrix Supported data type: same as @p lhs_ptr - * @param[in] dst_stride_x Stride of the destination matrix 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 matrix in Y dimension (in bytes) - * @param[in] dst_step_y dst_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 - * @param[in] lhs_stride_z Stride of the LHS reshaped matrix in Z dimension (in bytes) - * @param[in] rhs_stride_z Stride of the RHS reshaped matrix in Z dimension (in bytes) - * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) - * @param[in] lhs_cross_plane_pad (Optional) Bottom paddings for LHS matrix in unit of elements (only if defined REINTERPRET_INPUT_AS_3D) - * @param[in] dst_cross_plane_pad (Optional) Bottom paddings for the output matrix in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D) - * @param[in] sum_col_ptr (Optional) Pointer to the source tensor. Supported data type: S32 - * @param[in] sum_col_stride_x (Optional) Stride of the source tensor in X dimension (in bytes) - * @param[in] sum_col_step_x (Optional) sum_col_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] sum_col_stride_y (Optional) Stride of the source tensor in Y dimension (in bytes) - * @param[in] sum_col_step_y (Optional) sum_col_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] sum_col_offset_first_element_in_bytes (Optional) The offset of the first element in the source tensor - * @param[in] sum_row_ptr (Optional) Pointer to the source tensor. Supported data type: S32 - * @param[in] sum_row_stride_x (Optional) Stride of the source tensor in X dimension (in bytes) - * @param[in] sum_row_step_x (Optional) sum_row_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] sum_row_stride_y (Optional) Stride of the source tensor in Y dimension (in bytes) - * @param[in] sum_row_step_y (Optional) sum_row_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] sum_row_offset_first_element_in_bytes (Optional) The offset of the first element in the source tensor - * @param[in] biases_ptr (Optional) Pointer to the biases tensor. Supported data type: S32 - * @param[in] biases_stride_x (Optional) Stride of the biases tensor in X dimension (in bytes) - * @param[in] biases_step_x (Optional) biases_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] biases_offset_first_element_in_bytes (Optional) The offset of the first element in the biases tensor - * @param[in] result_multipliers_ptr (Optional) Pointer to the output multipliers vector for per-channel quantization. Supported data types: S32 - * @param[in] result_multipliers_stride_x (Optional) Stride of the output multipliers vector in X dimension (in bytes) - * @param[in] result_multipliers_step_x (Optional) output_multipliers_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] result_multipliers_offset_first_element_in_bytes (Optional) The offset of the first element in the output multipliers vector - * @param[in] result_shifts_ptr (Optional) Pointer to the output shifts vector for per-channel quantization. Supported data types: S32 - * @param[in] result_shifts_stride_x (Optional) Stride of the output shifts vector in X dimension (in bytes) - * @param[in] result_shifts_step_x (Optional) output_shifts_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] result_shifts_offset_first_element_in_bytes (Optional) The offset of the first element in the output shifts vector - */ -__kernel void gemmlowp_mm_reshaped_only_rhs_t_fused_output_stage_fixedpoint(IMAGE_DECLARATION(lhs), - IMAGE_DECLARATION(rhs), - IMAGE_DECLARATION(dst), - uint lhs_stride_z, - uint rhs_stride_z, - uint dst_stride_z -#if defined(REINTERPRET_INPUT_AS_3D) - , - uint lhs_cross_plane_pad -#endif // REINTERPRET_INPUT_AS_3D -#if defined(REINTERPRET_OUTPUT_AS_3D) - , - uint dst_cross_plane_pad -#endif // REINTERPRET_OUTPUT_AS_3D -#if defined(A_OFFSET) - , - IMAGE_DECLARATION(sum_col) -#endif // defined(A_OFFSET) -#if defined(B_OFFSET) - , - IMAGE_DECLARATION(sum_row) -#endif // defined(B_OFFSET) -#if defined(ADD_BIAS) - , - VECTOR_DECLARATION(biases) -#endif // defined(ADD_BIAS) -#if defined(PER_CHANNEL_QUANTIZATION) - , - VECTOR_DECLARATION(result_multipliers), - VECTOR_DECLARATION(result_shifts) -#endif // defined(PER_CHANNEL_QUANTIZATION) - ) -{ - // Block size -#define RHS_BLOCK_SIZE ((K0) * (N0)) - - // RHS offset and step X -#if defined(RHS_INTERLEAVE) -#define RHS_OFFSET_X (K0) -#define RHS_STEP_X ((K0) * (H0)) -#define RHS_STEP_LOOP (1) -#else // defined(RHS_INTERLEAVE) -#define RHS_OFFSET_X (RHS_BLOCK_SIZE) -#define RHS_STEP_X (K0) -#define RHS_STEP_LOOP (H0) -#endif // defined(RHS_INTERLEAVE) - - uint x = get_global_id(0); - uint y = get_global_id(1); - uint z = get_global_id(2); - -#if defined(DUMMY_WORK_ITEMS) - if((x * N0 >= N) || (y * M0 >= M)) - { - return; - } -#endif // defined(DUMMY_WORK_ITEMS) - - // Compute LHS matrix address - uint lhs_offset = lhs_offset_first_element_in_bytes + COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * (uint)lhs_stride_y; - - // Compute RHS matrix address - uint rhs_offset = rhs_offset_first_element_in_bytes + (x % H0) * (uint)RHS_OFFSET_X + (x / (uint)H0) * rhs_stride_y; - -#if defined(MATRIX_B_DEPTH) - // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3 - rhs_offset += (z % MATRIX_B_DEPTH) * rhs_stride_z; -#else // defined(MATRIX_B_DEPTH) - rhs_offset += z * rhs_stride_z; -#endif // defined(MATRIX_B_DEPTH) - - REPEAT_VAR_INIT_TO_CONST(8, uint, zlhs, 0); //uint zout0=0,zout1=0,zout2=0,... zout7=0; - REPEAT_VAR_INIT_TO_CONST(16, uint, zrhs, 0); - -#if defined(REINTERPRET_INPUT_AS_3D) - // The plane (zlhs) is calculated dividing M (y * M0) by HEIGHT_GEMM3D - CALCULATE_Z_OFFSET(M0, uint, zlhs, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y); - - // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we - // multiply lhs_stride_z by DEPTH_GEMM3D - lhs_offset += z * lhs_stride_z * DEPTH_GEMM3D; - -#else // defined(REINTERPRET_INPUT_AS_3D) - - // Add offset for batched GEMM - lhs_offset += z * lhs_stride_z; - -#endif // defined(REINTERPRET_INPUT_AS_3D) - - // Initialize the accumulators - REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(ACC_DATA_TYPE, N0), c, 0); //VEC_DATA_TYPE(ACC_DATA_TYPE, N0) c0=0,c1=0,c2=0,... c(N0-1)=0; - - int i = 0; - for(; i <= (K - K0); i += K0) - { - // Load values from LHS matrix - LOAD_BLOCK(M0, K0, DATA_TYPE, a, lhs_ptr, lhs_offset, lhs_stride_y, zlhs); - - // Load values from RHS matrix - LOAD_BLOCK(N0, K0, DATA_TYPE, b, rhs_ptr, rhs_offset, RHS_STEP_X, zrhs); - - // Partial matrix multiplication M0,N0,K0 - ARM_MM_K0XN0XM0(M0, N0, K0, a, b, c); - - lhs_offset += K0; - rhs_offset += N0 * RHS_STEP_X * RHS_STEP_LOOP; - } - // Left-over accumulations - for(; i < K; ++i) - { - // Load values from LHS matrix - LOAD_BLOCK(M0, 1, DATA_TYPE, a, lhs_ptr, lhs_offset, lhs_stride_y, zlhs); - - // Load values from RHS reshaped matrix - LOAD_BLOCK(N0, 1, DATA_TYPE, b, rhs_ptr, rhs_offset, RHS_STEP_X, zrhs); - - ARM_MM_K0XN0XM0(M0, N0, 1, a, b, c); - lhs_offset += 1; - rhs_offset += 1; - } - // Result of MM is of type DATA_TYPE - __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(DATA_TYPE)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * dst_stride_y); - - REPEAT_VAR_INIT_TO_CONST(8, uint, zout, 0); //uint zout0=0,zout1=0,zout2=0,... zout7=0; - -#if defined(REINTERPRET_OUTPUT_AS_3D) - // The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D - CALCULATE_Z_OFFSET(M0, uint, zout, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y); - - // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we - // multiply dst_stride_z by DEPTH_GEMM3D - dst_addr += z * dst_stride_z * DEPTH_GEMM3D; - -#else // defined(REINTERPRET_OUTPUT_AS_3D) - - // Add offset for batched GEMM - dst_addr += z * dst_stride_z; - -#endif // defined(REINTERPRET_OUTPUT_AS_3D) - - // Convert result of matrix multiplication to S32 - REPEAT_VAR_INIT_CONVERT_SAT(M0, VEC_DATA_TYPE(int, N0), c, c_int); - - // Offset contribution: c += (A_OFFSET * sum_col) + (B_OFFSET * sum_row) + K_OFFSET; - REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(int, N0), offset_s32_, K_OFFSET); - -#if defined(A_OFFSET) - // Compute the offset contribution due to A_OFFSET - __global uchar *sum_col_addr = sum_col_ptr + sum_col_offset_first_element_in_bytes + (x * (uint)N0) * sizeof(int); - -#if defined(SUM_COL_HAS_BATCHES) - sum_col_addr += z * sum_col_stride_y; -#endif // defined(SUM_COL_HAS_BATCHES) - VEC_DATA_TYPE(int, N0) - a_offset_s32 = VLOAD(N0)(0, (__global int *)sum_col_addr); - a_offset_s32 *= (VEC_DATA_TYPE(int, N0))A_OFFSET; - - REPEAT_ADD_VECTOR_TO_VAR(M0, offset_s32_, a_offset_s32); -#endif // defined(A_OFFSET) - -#if defined(B_OFFSET) - // Compute the offset contribution due to B_OFFSET - // Note: The sum_row tensor is generated through CLGEMMLowpMatrixAReductionKernel which - // does not introduce paddings. For this reason is safe to access the tensor in this manner - // without considering that the coordinate "y" could come from an input 3D tensor - __global uchar *sum_row_addr = sum_row_ptr + sum_row_offset_first_element_in_bytes + (COMPUTE_M0_START_ROW(y, (uint)M0, PARTIAL_STORE_M0)) * sizeof(int) + z * sum_row_stride_y; - - LOAD_SCALAR_AS_VECTOR(M0, N0, int, b_offset_s32_, sum_row_addr, 0, sum_row_stride_x); - - REPEAT_MLA_VAR_WITH_CONST_VEC(M0, offset_s32_, b_offset_s32_, (VEC_DATA_TYPE(int, N0))B_OFFSET); -#endif // defined(B_OFFSET) - -#if defined(ADD_BIAS) - // Add bias - __global uchar *bias_addr = biases_ptr + biases_offset_first_element_in_bytes + (x * (uint)N0) * sizeof(int); - - VEC_DATA_TYPE(int, N0) - bias_values = VLOAD(N0)(0, (__global int *)bias_addr); - REPEAT_ADD_VECTOR_TO_VAR(M0, offset_s32_, bias_values); -#endif // defined(ADD_BIAS) - - REPEAT_ADD_TWO_VARS(M0, c_int, offset_s32_); - - // Multiply by result_mult_int and shift -#if defined(PER_CHANNEL_QUANTIZATION) - __global uchar *result_multipliers_addr = result_multipliers_ptr + result_multipliers_offset_first_element_in_bytes + (x * (uint)N0) * sizeof(int); - __global uchar *result_shifts_addr = result_shifts_ptr + result_shifts_offset_first_element_in_bytes + (x * (uint)N0) * sizeof(int); - - VEC_DATA_TYPE(int, N0) - res_mul = VLOAD(N0)(0, (__global int *)result_multipliers_addr); - VEC_DATA_TYPE(int, N0) - res_shift = VLOAD(N0)(0, (__global int *)result_shifts_addr); - - REPEAT_ASYMM_MULT_BY_QUANT_MULTIPLIER_PER_CHANNEL(M0, N0, c_int, res_mul, res_shift); -#else // defined(PER_CHANNEL_QUANTIZATION) - -#if RESULT_SHIFT < 0 - REPEAT_ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(M0, N0, c_int, RESULT_MULTIPLIER, RESULT_SHIFT); -#else // RESULT_SHIFT >= 0 - REPEAT_ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(M0, N0, c_int, RESULT_MULTIPLIER, RESULT_SHIFT); -#endif // RESULT_SHIFT < 0 - -#endif // defined(PER_CHANNEL_QUANTIZATION) - - // Add the offset terms to GEMM's result - REPEAT_ADD_CONST_TO_VAR(M0, VEC_DATA_TYPE(int, N0), c_int, RESULT_OFFSET); - -#if defined(MIN_BOUND) - REPEAT_MAX_CONST_VAR(M0, VEC_DATA_TYPE(int, N0), c_int, MIN_BOUND); -#endif // defined(MIN_BOUND) -#if defined(MAX_BOUND) - REPEAT_MIN_CONST_VAR(M0, VEC_DATA_TYPE(int, N0), c_int, MAX_BOUND); -#endif // defined(MAX_BOUND) - - // Convert and store output block - const bool cond_y = y == 0; - const bool cond_x = ((x + 1) * N0 >= N); - - // Store output block - REPEAT_VAR_INIT_CONVERT_SAT(M0, VEC_DATA_TYPE(DATA_TYPE, N0), c_int, c_lp); - STORE_BLOCK_BOUNDARY_AWARE(M0, N0, DATA_TYPE, c_lp, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); - -#undef RHS_BLOCK_SIZE -#undef RHS_OFFSET_X -#undef RHS_STEP_X -} -#endif // defined(RESULT_OFFSET) && defined(RESULT_SHIFT) && defined(RESULT_MULTIPLIER) -#endif // defined(M0) && defined(N0) && defined(K0) && defined(H0) && defined(K) && defined(PARTIAL_STORE_M0) && defined(PARTIAL_STORE_N0) - -#if defined(M0) && defined(N0) && defined(K0) && defined(K) && defined(PARTIAL_STORE_M0) && defined(PARTIAL_STORE_N0) - -/** This OpenCL kernel computes the matrix multiplication between 2 matrices. - * The LHS matrix is NOT reshaped - * The RHS matrix is NOT reshaped - * - * @note The input data type must be passed at compile time using -DDATA_TYPE (i.e. -DDATA_TYPE=uchar) - * @note The accumulator data type must be passed at compile time using -DACC_DATA_TYPE (i.e. -DACC_DATA_TYPE=uint) - * @note The number of columns of LHS matrix must be passed at compile time using -DK (i.e. -DK=64) - * @note The number of M0 rows to process must be passed at compile time using -DM0 (i.e. -DM0=2) - * @note The number of N0 columns to process must be passed at compile time using -DN0 (i.e. -DN0=2) - * @note The number of K0 partial accumulations must be passed at compile time using -DK0 (i.e., -DK0=2) - * @note Only the following configurations of M0, N0 and K0 are currently supported: - * - M0 = 1, 2, 3, 4, 5, 6, 7, 8 - * - N0 = 2, 3, 4, 8, 16 - * - K0 = 2, 3, 4, 8, 16 - * - * @note In case the input or output have to be reinterpreted as a 3D tensor, the following information must be passed at compile time: - * -# REINTERPRET_INPUT_AS_3D: To reinterpret the input as 3D - * -# REINTERPRET_OUTPUT_AS_3D: To reinterpret the output as 3D - * -# HEIGHT_GEMM3D: The height of the output in case it has to be reinterpreted as a 3D tensor. - * -# DEPTH_GEMM3D: The depth of the output in case it has to be reinterpreted as a 3D tensor - * (HEIGHT_GEMM3D * DEPTH_GEMM3D) = columns LHS matrix - * - * @param[in] lhs_ptr Pointer to the LHS reshaped matrix. Supported data type: QASYMM8 - * @param[in] lhs_stride_x Stride of the LHS reshaped matrix in X dimension (in bytes) - * @param[in] lhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] lhs_stride_y Stride of the LHS reshaped matrix in Y dimension (in bytes) - * @param[in] lhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] lhs_offset_first_element_in_bytes The offset of the first element in the LHS reshaped matrix - * @param[in] rhs_ptr Pointer to the RHS reshaped matrix. Supported data type: same as @p lhs_ptr - * @param[in] rhs_stride_x Stride of the RHS reshaped matrix in X dimension (in bytes) - * @param[in] rhs_step_x src_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] rhs_stride_y Stride of the RHS reshaped matrix in Y dimension (in bytes) - * @param[in] rhs_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] rhs_offset_first_element_in_bytes The offset of the first element in the RHS reshaped 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_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_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 - * @param[in] lhs_stride_z Stride of the LHS reshaped matrix in Z dimension (in bytes) - * @param[in] rhs_stride_z Stride of the RHS reshaped matrix in Z dimension (in bytes) - * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) - * @param[in] lhs_cross_plane_pad (Optional) Bottom paddings for LHS matrix in unit of elements (only if defined REINTERPRET_INPUT_AS_3D) - * @param[in] dst_cross_plane_pad (Optional) Bottom paddings for the output matrix in unit of elements (only if defined REINTERPRET_OUTPUT_AS_3D) - */ -__kernel void gemmlowp_mm_native(IMAGE_DECLARATION(lhs), - IMAGE_DECLARATION(rhs), - IMAGE_DECLARATION(dst), - uint lhs_stride_z, - uint rhs_stride_z, - uint dst_stride_z -#if defined(REINTERPRET_INPUT_AS_3D) - , - uint lhs_cross_plane_pad -#endif // REINTERPRET_INPUT_AS_3D -#if defined(REINTERPRET_OUTPUT_AS_3D) - , - uint dst_cross_plane_pad -#endif // REINTERPRET_OUTPUT_AS_3D - ) -{ - uint x = get_global_id(0); - uint y = get_global_id(1); - uint z = get_global_id(2); - -#if defined(DUMMY_WORK_ITEMS) - if((x * N0 >= N) || (y * M0 >= M)) - { - return; - } -#endif // defined(DUMMY_WORK_ITEMS) - - // Compute LHS matrix address - uint lhs_offset = lhs_offset_first_element_in_bytes + COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * (uint)lhs_stride_y; - - // Compute RHS matrix address - uint rhs_offset = rhs_offset_first_element_in_bytes + x * N0 * sizeof(DATA_TYPE); - -#if defined(MATRIX_B_DEPTH) - // Do not slide matrix B if the matrix B has 3 dimensions and matrix A more than 3 - rhs_offset += (z % MATRIX_B_DEPTH) * rhs_stride_z; -#else // defined(MATRIX_B_DEPTH) - rhs_offset += z * rhs_stride_z; -#endif // defined(MATRIX_B_DEPTH) - - REPEAT_VAR_INIT_TO_CONST(8, uint, zlhs, 0); - REPEAT_VAR_INIT_TO_CONST(16, uint, zrhs, 0); - -#if defined(REINTERPRET_INPUT_AS_3D) - // The plane (zlhs) is calculated dividing M (y * M0) by HEIGHT_GEMM3D - CALCULATE_Z_OFFSET(M0, uint, zlhs, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, lhs_cross_plane_pad, lhs_stride_y); - - // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we - // multiply lhs_stride_z by DEPTH_GEMM3D - lhs_offset += z * lhs_stride_z * DEPTH_GEMM3D; - -#else // defined(REINTERPRET_INPUT_AS_3D) - - // Add offset for batched GEMM - lhs_offset += z * lhs_stride_z; - -#endif // defined(REINTERPRET_INPUT_AS_3D) - - // Initialize the accumulators - REPEAT_VAR_INIT_TO_CONST(M0, VEC_DATA_TYPE(ACC_DATA_TYPE, N0), c, 0); //VEC_DATA_TYPE(ACC_DATA_TYPE, N0) c0=0,c1=0,c2=0,... c(M0-1)=0; - - int i = 0; - - for(; i <= (K - K0); i += K0) - { - // Load values from LHS matrix - LOAD_BLOCK(M0, K0, DATA_TYPE, a, lhs_ptr, lhs_offset, lhs_stride_y, zlhs); - - // Load values from RHS matrix - LOAD_BLOCK(K0, N0, DATA_TYPE, b, rhs_ptr, rhs_offset, rhs_stride_y, zrhs); - - // Partial matrix multiplication M0,N0,K0 -#if(GPU_ARCH == GPU_ARCH_MIDGARD) - ARM_MM_NATIVE_N0XK0XM0(VEC_DATA_TYPE(ACC_DATA_TYPE, N0), M0, K0, a, b, c); -#else // GPU_ARCH == GPU_ARCH_MIDGARD - // Transpose the values from RHS matrix - TRANSPOSE_K0XN0(K0, N0, b_t, b, DATA_TYPE); - - ARM_MM_K0XN0XM0(M0, N0, K0, a, b_t, c); -#endif // GPU_ARCH == GPU_ARCH_MIDGARD - - // Update the offset - lhs_offset += K0; - rhs_offset += K0 * rhs_stride_y; - } - - // Left-over for loop - for(; i < K; ++i) - { - // Load values from LHS matrix - LOAD_BLOCK(M0, 1, DATA_TYPE, a, lhs_ptr, lhs_offset, lhs_stride_y, zlhs); - - // Load values from RHS matrix - LOAD_BLOCK(1, N0, DATA_TYPE, b, rhs_ptr, rhs_offset, rhs_stride_y, zrhs); - - // Partial matrix multiplication M0,N0,1 -#if(GPU_ARCH == GPU_ARCH_MIDGARD) - ARM_MM_NATIVE_N0XK0XM0(VEC_DATA_TYPE(ACC_DATA_TYPE, N0), M0, 1, a, b, c); -#else // GPU_ARCH == GPU_ARCH_MIDGARD - // Transpose the values from RHS matrix - TRANSPOSE_K0XN0(1, N0, b_t, b, DATA_TYPE); - - ARM_MM_K0XN0XM0(M0, N0, 1, a, b_t, c); -#endif // GPU_ARCH == GPU_ARCH_MIDGARD - - // Update the offset - lhs_offset += 1; - rhs_offset += rhs_stride_y; - } - - __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + (x * (uint)N0 * sizeof(int)) + (COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0) * dst_stride_y); - - REPEAT_VAR_INIT_TO_CONST(M0, uint, zout, 0); //uint zout0=0,zout1=0,zout2=0,... zout7=0; - -#if defined(REINTERPRET_OUTPUT_AS_3D) - // The plane (zout) is calculated dividing M (y * M0) by HEIGHT_GEMM3D - CALCULATE_Z_OFFSET(M0, uint, zout, COMPUTE_M0_START_ROW(y, M0, PARTIAL_STORE_M0), HEIGHT_GEMM3D, DEPTH_GEMM3D, dst_cross_plane_pad, dst_stride_y); - - // Add offset for batched GEMM. The batches will be in the fourth dimension and for this reason we - // multiply dst_stride_z by DEPTH_GEMM3D - dst_addr += z * dst_stride_z * DEPTH_GEMM3D; - -#else // defined(REINTERPRET_OUTPUT_AS_3D) - - // Add offset for batched GEMM - dst_addr += z * dst_stride_z; - -#endif // defined(REINTERPRET_OUTPUT_AS_3D) - const bool cond_y = y == 0; - const bool cond_x = ((x + 1) * N0 >= N); - - // Convert and store output block - REPEAT_VAR_INIT_CONVERT(M0, VEC_DATA_TYPE(int, N0), c, res); // resN = CONVERT(cN, VEC_DATA_TYPE(int, N0)); - STORE_BLOCK_BOUNDARY_AWARE(M0, N0, int, res, dst_addr, dst_stride_y, zout, PARTIAL_STORE_M0, PARTIAL_STORE_N0, cond_y, cond_x); -} -#endif // defined(M0) && defined(N0) && defined(K0) && defined(K) && defined(PARTIAL_STORE_M0) && defined(PARTIAL_STORE_N0) - -#if defined(COLS_A) -/** OpenCL kernel used to compute the row-vectors of sums of all the entries in each row of Matrix A. - * It is also possible to multiply each reduced row by a scalar value, if SCALAR is passed at compile time. - * - * @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 - * @note The input data type must be passed at compile time using -DDATA_TYPE (i.e. -DDATA_TYPE=uchar) - * @note The data type for the accumulation must be passed at compile time using -DACC_DATA_TYPE (i.e. -DACC_DATA_TYPE=uint) - * @note In case of scaling the scalar value must be passed at compile time using -DSCALAR (e.g. -DSCALAR=3) - * - * @param[in] src_ptr Pointer to the source tensor. Supported data type: QASYMM8/QASYMM8_SIGNED/QSYMM8 - * @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); - - VEC_DATA_TYPE(ACC_DATA_TYPE, 4) - sum_row_32 = (VEC_DATA_TYPE(ACC_DATA_TYPE, 4))0; - ACC_DATA_TYPE sum_row = 0; - - __global const DATA_TYPE *matrix_a = (__global const DATA_TYPE *)(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 VEC_DATA_TYPE(DATA_TYPE, 16) a0 = vload16(0, matrix_a + i); - - sum_row_32 += CONVERT(a0.s0123, VEC_DATA_TYPE(ACC_DATA_TYPE, 4)) + CONVERT(a0.s4567, VEC_DATA_TYPE(ACC_DATA_TYPE, 4)) + CONVERT(a0.s89AB, VEC_DATA_TYPE(ACC_DATA_TYPE, 4)) + CONVERT(a0.sCDEF, - VEC_DATA_TYPE(ACC_DATA_TYPE, 4)); - } - - // This for loop performs the leftover accumulations - for(; i < COLS_A; ++i) - { - sum_row += (ACC_DATA_TYPE)matrix_a[i]; - } - - sum_row += sum_row_32.s0 + sum_row_32.s1 + sum_row_32.s2 + sum_row_32.s3; - -#if defined(SCALAR) - sum_row *= (int)SCALAR; -#endif // defined(SCALAR) - *((__global int *)dst.ptr) = (int)sum_row; -} - -#if defined(ARM_COMPUTE_OPENCL_DOT8_ENABLED) && defined(cl_arm_integer_dot_product_int8) -/** OpenCL kernel used to compute the row-vectors of sums of all the entries in each row of Matrix A using the arm dot product instruction. - * It is also possible to multiply each reduced row by a scalar value, if SCALAR is passed at compile time. - * - * @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 - * @note The input data type must be passed at compile time using -DDATA_TYPE (i.e. -DDATA_TYPE=uchar) - * @note The data type for the accumulation must be passed at compile time using -DACC_DATA_TYPE (i.e. -DACC_DATA_TYPE=uint) - * @note In case of scaling the scalar value must be passed at compile time using -DSCALAR (e.g. -DSCALAR=3) - * - * @param[in] src_ptr Pointer to the source tensor. Supported data type: QASYMM8/QASYMM8_SIGNED/QSYMM8 - * @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_dot8(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); - - ACC_DATA_TYPE sum_row = 0; - - __global const DATA_TYPE *matrix_a = (__global const DATA_TYPE *)(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 - 32); i += 32) - { - VEC_DATA_TYPE(DATA_TYPE, 16) - a0 = vload16(0, matrix_a + i); - - sum_row += arm_dot(a0.s0123, (VEC_DATA_TYPE(DATA_TYPE, 4))(1)); - sum_row += arm_dot(a0.s4567, (VEC_DATA_TYPE(DATA_TYPE, 4))(1)); - sum_row += arm_dot(a0.s89AB, (VEC_DATA_TYPE(DATA_TYPE, 4))(1)); - sum_row += arm_dot(a0.sCDEF, (VEC_DATA_TYPE(DATA_TYPE, 4))(1)); - - a0 = vload16(1, matrix_a + i); - - sum_row += arm_dot(a0.s0123, (VEC_DATA_TYPE(DATA_TYPE, 4))(1)); - sum_row += arm_dot(a0.s4567, (VEC_DATA_TYPE(DATA_TYPE, 4))(1)); - sum_row += arm_dot(a0.s89AB, (VEC_DATA_TYPE(DATA_TYPE, 4))(1)); - sum_row += arm_dot(a0.sCDEF, (VEC_DATA_TYPE(DATA_TYPE, 4))(1)); - } - - // This for loop performs the leftover accumulations - for(; i < COLS_A; ++i) - { - sum_row += (ACC_DATA_TYPE)matrix_a[i]; - } - -#if defined(SCALAR) - sum_row *= (int)SCALAR; -#endif // defined(SCALAR) - *((__global int *)dst.ptr) = (int)sum_row; -} -#endif // defined(ARM_COMPUTE_OPENCL_DOT8_ENABLED) && defined(cl_arm_integer_dot_product_int8) -#endif // defined(COLS_A) - -#if defined(COLS_B) && defined(ROWS_B) && defined(VEC_SIZE) && defined(VEC_SIZE_LEFTOVER) -/** OpenCL kernel used to compute the row-vectors of sums of all the entries in each column of Matrix B. - * It is also possible to multiply each reduced column by a scalar value, if SCALAR is passed at compile time. - * - * @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 - * @note The input data type must be passed at compile time using -DDATA_TYPE (i.e. -DDATA_TYPE=uchar) - * @note The data type for the accumulation must be passed at compile time using -DACC_DATA_TYPE (i.e. -DACC_DATA_TYPE=uint) - * @note In case of scaling the scalar value must be passed at compile time using -DSCALAR (i.e. -DSCALAR=3) - * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16 - * @note Leftover vector size has to be passed at compile time using -DVEC_SIZE_LEFTOVER. e.g. -DVEC_SIZE_LEFTOVER=3. It is defined as the remainder between the input's first dimension and VEC_SIZE - * - * @param[in] src_ptr Pointer to the source tensor. Supported data type: QASYMM8/QASYMM8_SIGNED/QSYMM8/QSYMM8_PER_CHANNEL - * @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 - const uint x_offs = max((int)(get_global_id(0) * VEC_SIZE - (VEC_SIZE - VEC_SIZE_LEFTOVER) % VEC_SIZE), 0); - const uint y = get_global_id(1); - - __global const DATA_TYPE *matrix_b = (__global const DATA_TYPE *)(src_ptr + src_offset_first_element_in_bytes + x_offs * sizeof(DATA_TYPE) + y * src_step_y + y * src_stride_z); - __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + x_offs * sizeof(int) + y * dst_stride_y; - - VEC_DATA_TYPE(ACC_DATA_TYPE, VEC_SIZE) - sum_col_32 = (VEC_DATA_TYPE(ACC_DATA_TYPE, VEC_SIZE))0; - - int i = 0; - // This for loop performs 4 accumulations - for(; i <= ((int)ROWS_B - 4); i += 4) - { - const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) - b0 = VLOAD(VEC_SIZE)(0, matrix_b + 0 * src_stride_y); - const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) - b1 = VLOAD(VEC_SIZE)(0, matrix_b + 1 * src_stride_y); - const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) - b2 = VLOAD(VEC_SIZE)(0, matrix_b + 2 * src_stride_y); - const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) - b3 = VLOAD(VEC_SIZE)(0, matrix_b + 3 * src_stride_y); - - sum_col_32 += CONVERT(b0, VEC_DATA_TYPE(ACC_DATA_TYPE, VEC_SIZE)) + CONVERT(b1, VEC_DATA_TYPE(ACC_DATA_TYPE, VEC_SIZE)) + CONVERT(b2, VEC_DATA_TYPE(ACC_DATA_TYPE, VEC_SIZE)) + CONVERT(b3, - VEC_DATA_TYPE(ACC_DATA_TYPE, VEC_SIZE)); - - matrix_b += 4 * src_stride_y; - } - - // This for loop perfoms the leftover accumulations - for(; i < (int)ROWS_B; ++i) - { - const VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) - b0 = VLOAD(VEC_SIZE)(0, matrix_b); - - sum_col_32 += CONVERT(b0, VEC_DATA_TYPE(ACC_DATA_TYPE, VEC_SIZE)); - - matrix_b += src_stride_y; - } - -#if defined(SCALAR) - sum_col_32 *= (VEC_DATA_TYPE(ACC_DATA_TYPE, VEC_SIZE))SCALAR; -#endif // defined(SCALAR) - VEC_DATA_TYPE(int, VEC_SIZE) - res0 = CONVERT(sum_col_32, VEC_DATA_TYPE(int, VEC_SIZE)); - - STORE_VECTOR_SELECT(res, int, dst_addr, VEC_SIZE, VEC_SIZE_LEFTOVER, VEC_SIZE_LEFTOVER != 0 && get_global_id(0) == 0) -} -#endif // defined(COLS_B) && defined(ROWS_B) && defined(VEC_SIZE) && defined(VEC_SIZE_LEFTOVER) - -#endif // defined(DATA_TYPE) && defined(ACC_DATA_TYPE) - -#if defined(K_OFFSET) && defined(VEC_SIZE) && defined(VEC_SIZE_LEFTOVER) - -#define VEC_INT VEC_DATA_TYPE(int, VEC_SIZE) - -/* Helper function used to calculate the offset contribution after matrix multiplication. - * - * This kernel takes a final int32 accumulator value (the output of matrix multiplication), - * and calculates the offset contribution of matrix A and matrix B. - * - * @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 - * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16 - * @note Leftover vector size has to be passed at compile time using -DVEC_SIZE_LEFTOVER. e.g. -DVEC_SIZE_LEFTOVER=3. It is defined as the remainder between the input's first dimension and VEC_SIZE - * - * @param[in] x max((int)(get_global_id(0) * VEC_SIZE - (VEC_SIZE - VEC_SIZE_LEFTOVER) % VEC_SIZE), 0) - * @param[in] y get_global_id(1) - * @param[in] z get_global_id(2) - * @param[in] sum_col_ptr (Optional) Pointer to the source tensor. Supported data type: same as @p mm_result_ptr - * @param[in] sum_col_stride_x (Optional) Stride of the source tensor in X dimension (in bytes) - * @param[in] sum_col_step_x (Optional) sum_col_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] sum_col_stride_y (Optional) Stride of the source tensor in Y dimension (in bytes) - * @param[in] sum_col_step_y (Optional) sum_col_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] sum_col_offset_first_element_in_bytes (Optional) The offset of the first element in the source tensor - * @param[in] sum_row_ptr (Optional) Pointer to the source tensor. Supported data type: same as @p mm_result_ptr - * @param[in] sum_row_stride_x (Optional) Stride of the source tensor in X dimension (in bytes) - * @param[in] sum_row_step_x (Optional) sum_row_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] sum_row_stride_y (Optional) Stride of the source tensor in Y dimension (in bytes) - * @param[in] sum_row_step_y (Optional) sum_row_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] sum_row_offset_first_element_in_bytes (Optional) The offset of the first element in the source tensor - * @param[in] biases_ptr (Optional) Pointer to the biases tensor. Supported data type: same as @p src_ptr - * @param[in] biases_stride_x (Optional) Stride of the biases tensor in X dimension (in bytes) - * @param[in] biases_step_x (Optional) biases_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] biases_offset_first_element_in_bytes (Optional) The offset of the first element in the biases tensor - */ -inline VEC_INT offset_contribution( - int x, - int y, - int z -#if defined(A_OFFSET) - , - IMAGE_DECLARATION(sum_col) -#endif // defined(A_OFFSET) -#if defined(B_OFFSET) - , - IMAGE_DECLARATION(sum_row) -#endif // defined(B_OFFSET) -#if defined(ADD_BIAS) - , - VECTOR_DECLARATION(biases) -#endif // defined(ADD_BIAS) -) -{ - VEC_INT a_offset_s32 = (VEC_INT)0; - VEC_INT b_offset_s32 = (VEC_INT)0; - - int batch_id = z; -#if defined(DEPTH_INPUT3D) - batch_id /= (int)DEPTH_INPUT3D; -#endif // defined(DEPTH_INPUT3D) - -#if defined(A_OFFSET) - // Compute the offset contribution due to A_OFFSET - __global uchar *sum_col_addr = sum_col_ptr + sum_col_offset_first_element_in_bytes + x * sizeof(int); - - // Compute the offset contribution due to A_OFFSET -#if defined(SUM_COL_HAS_BATCHES) - a_offset_s32 = VLOAD(VEC_SIZE)(0, (__global int *)(sum_col_addr + batch_id * sum_col_stride_y)); -#else // defined(SUM_COL_HAS_BATCHES) - a_offset_s32 = VLOAD(VEC_SIZE)(0, (__global int *)sum_col_addr); -#endif // defined(SUM_COL_HAS_BATCHES) - - a_offset_s32 *= (VEC_INT)A_OFFSET; -#endif // defined(A_OFFSET) - -#if defined(B_OFFSET) - // Compute the offset contribution due to A_OFFSET - __global uchar *sum_row_addr = sum_row_ptr + sum_row_offset_first_element_in_bytes + y * sizeof(int); - - // Compute the offset contribution due to B_OFFSET -#if defined(HEIGHT_INPUT3D) && defined(DEPTH_INPUT3D) - b_offset_s32 = (VEC_INT) * (((__global int *)(sum_row_addr + batch_id * sum_row_stride_y)) + (z % (int)DEPTH_INPUT3D) * (int)HEIGHT_INPUT3D); -#else // defined(HEIGHT_INPUT3D) && defined(DEPTH_INPUT3D) - b_offset_s32 = (VEC_INT) * (((__global int *)(sum_row_addr + batch_id * sum_row_stride_y))); -#endif // defined(HEIGHT_INPUT3D) && defined(DEPTH_INPUT3D) - b_offset_s32 *= (VEC_INT)B_OFFSET; -#endif // defined(B_OFFSET) - -#if defined(ADD_BIAS) - // Add bias - __global uchar *bias_addr = biases_ptr + biases_offset_first_element_in_bytes + x * sizeof(int); - - VEC_INT biases_values = VLOAD(VEC_SIZE)(0, (__global int *)bias_addr); - b_offset_s32 += (VEC_INT)biases_values; -#endif // defined(ADD_BIAS) - - return (VEC_INT)K_OFFSET + a_offset_s32 + b_offset_s32; -} - -/* OpenCL kernel used to add the offset contribution after matrix multiplication. The computation is performed in-place - * - * This kernel takes a final int32 accumulator value (the output of matrix multiplication), - * 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 - * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16 - * @note Leftover vector size has to be passed at compile time using -DVEC_SIZE_LEFTOVER. e.g. -DVEC_SIZE_LEFTOVER=3. It is defined as the remainder between the input's first dimension and VEC_SIZE - * - * 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_ptr (Optional) Pointer to the source tensor. Supported data type: same as @p mm_result_ptr - * @param[in] sum_col_stride_x (Optional) Stride of the source tensor in X dimension (in bytes) - * @param[in] sum_col_step_x (Optional) sum_col_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] sum_col_stride_y (Optional) Stride of the source tensor in Y dimension (in bytes) - * @param[in] sum_col_step_y (Optional) sum_col_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] sum_col_offset_first_element_in_bytes (Optional) The offset of the first element in the source tensor - * @param[in] sum_row_ptr (Optional) Pointer to the source tensor. Supported data type: same as @p mm_result_ptr - * @param[in] sum_row_stride_x (Optional) Stride of the source tensor in X dimension (in bytes) - * @param[in] sum_row_step_x (Optional) sum_row_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] sum_row_stride_y (Optional) Stride of the source tensor in Y dimension (in bytes) - * @param[in] sum_row_step_y (Optional) sum_row_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] sum_row_offset_first_element_in_bytes (Optional) The offset of the first element in the source tensor - * @param[in] biases_ptr (Optional) Pointer to the biases tensor. Supported data type: same as @p src_ptr - * @param[in] biases_stride_x (Optional) Stride of the biases tensor in X dimension (in bytes) - * @param[in] biases_step_x (Optional) biases_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] biases_offset_first_element_in_bytes (Optional) The offset of the first element in the biases 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) -#if defined(ADD_BIAS) - , - VECTOR_DECLARATION(biases) -#endif // defined(ADD_BIAS)) - ) -{ - const int x = max((int)(get_global_id(0) * VEC_SIZE - (VEC_SIZE - VEC_SIZE_LEFTOVER) % VEC_SIZE), 0); - const int y = get_global_id(1); - const int z = get_global_id(2); - - // Compute offset contribution - VEC_INT offset_term_s32 = offset_contribution( - x, y, z -#if defined(A_OFFSET) - , - sum_col_ptr, - sum_col_stride_x, - sum_col_step_x, - sum_col_stride_y, - sum_col_step_y, - sum_col_offset_first_element_in_bytes -#endif // defined(A_OFFSET) -#if defined(B_OFFSET) - , - sum_row_ptr, - sum_row_stride_x, - sum_row_step_x, - sum_row_stride_y, - sum_row_step_y, - sum_row_offset_first_element_in_bytes -#endif // defined(B_OFFSET) -#if defined(ADD_BIAS) - , - biases_ptr, - biases_stride_x, - biases_step_x, - biases_offset_first_element_in_bytes -#endif // defined(ADD_BIAS) - ); - - __global uchar *mm_result_addr = mm_result_ptr + mm_result_offset_first_element_in_bytes + x * sizeof(int) + y * mm_result_stride_y + z * mm_result_stride_z; - - VEC_INT in_s32_0 = VLOAD(VEC_SIZE)(0, (__global int *)mm_result_addr); - - // Add the offset terms to GEMM's result - in_s32_0 += offset_term_s32; - - // Store the result with the offset contribution - STORE_VECTOR_SELECT(in_s32_, int, mm_result_addr, VEC_SIZE, VEC_SIZE_LEFTOVER, VEC_SIZE_LEFTOVER != 0 && get_global_id(0) == 0) -} - -#if defined(RESULT_OFFSET) && defined(RESULT_MULTIPLIER) && defined(RESULT_SHIFT) && defined(OUTPUT_DATA_TYPE) -/* OpenCL kernel used to add the offset contribution after @ref CLGEMMLowpMatrixMultiplyKernel and it quantizes down to uint8. - * - * This kernel takes a final int32 accumulator value (the output of @CLGEMMLowpMatrixMultiplyKernel), adds to it the offset contribution of matrix A and matrix B and quantizes to uint8 through the output stage. - * - * - * @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 result before the output stage is: - * - * mm_result[i][k] = mm_result[i][k] + - * (sum_col[k] * A_OFFSET) + - * (sum_row[i] * B_OFFSET) + - * (K_OFFSET) - * - * This result is quantized down to uint8/int8 using the output stage. The output stage computes the following operations: - * - * -# 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. - * - to the [-128..127] range and cast to QASYMM8_SIGNED. - * - * @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 The output datatype should be passed at compile time using -DOUTPUT_DATA_TYPE - * @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 - * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16 - * @note Leftover vector size has to be passed at compile time using -DVEC_SIZE_LEFTOVER. e.g. -DVEC_SIZE_LEFTOVER=3. It is defined as the remainder between the input's first dimension and VEC_SIZE - * - * @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_ptr (Optional) Pointer to the source tensor. Supported data type: same as @p mm_result_ptr - * @param[in] sum_col_stride_x (Optional) Stride of the source tensor in X dimension (in bytes) - * @param[in] sum_col_step_x (Optional) sum_col_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] sum_col_stride_y (Optional) Stride of the source tensor in Y dimension (in bytes) - * @param[in] sum_col_step_y (Optional) sum_col_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] sum_col_offset_first_element_in_bytes (Optional) The offset of the first element in the source tensor - * @param[in] sum_row_ptr (Optional) Pointer to the source tensor. Supported data type: same as @p mm_result_ptr - * @param[in] sum_row_stride_x (Optional) Stride of the source tensor in X dimension (in bytes) - * @param[in] sum_row_step_x (Optional) sum_row_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] sum_row_stride_y (Optional) Stride of the source tensor in Y dimension (in bytes) - * @param[in] sum_row_step_y (Optional) sum_row_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] sum_row_offset_first_element_in_bytes (Optional) The offset of the first element in the source tensor - * @param[in] biases_ptr (Optional) Pointer to the biases tensor. Supported data type: same as @p src_ptr - * @param[in] biases_stride_x (Optional) Stride of the biases tensor in X dimension (in bytes) - * @param[in] biases_step_x (Optional) biases_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] biases_offset_first_element_in_bytes (Optional) The offset of the first element in the biases tensor - * @param[out] dst_ptr Pointer to the destination tensor Supported data type: QASYMM8/QASYMM8_SIGNED - * @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 - * @param[in] result_multipliers_ptr (Optional) Pointer to the output multipliers vector for per-channel quantization. Supported data types: S32 - * @param[in] result_multipliers_stride_x (Optional) Stride of the output multipliers vector in X dimension (in bytes) - * @param[in] result_multipliers_step_x (Optional) output_multipliers_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] result_multipliers_offset_first_element_in_bytes (Optional) The offset of the first element in the output multipliers vector - * @param[in] result_shifts_ptr (Optional) Pointer to the output shifts vector for per-channel quantization. Supported data types: S32 - * @param[in] result_shifts_stride_x (Optional) Stride of the output shifts vector in X dimension (in bytes) - * @param[in] result_shifts_step_x (Optional) output_shifts_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] result_shifts_offset_first_element_in_bytes (Optional) The offset of the first element in the output shifts vector - */ -__kernel void gemmlowp_offset_contribution_quantize_down(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) - , -#if defined(ADD_BIAS) - VECTOR_DECLARATION(biases), -#endif // defined(ADD_BIAS) - TENSOR3D_DECLARATION(dst) -#if defined(PER_CHANNEL_QUANTIZATION) - , - VECTOR_DECLARATION(result_multipliers), - VECTOR_DECLARATION(result_shifts) -#endif // defined(PER_CHANNEL_QUANTIZATION) - ) -{ - const int x = max((int)(get_global_id(0) * VEC_SIZE - (VEC_SIZE - VEC_SIZE_LEFTOVER) % VEC_SIZE), 0); - const int y = get_global_id(1); - const int z = get_global_id(2); - - __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + x + y * dst_stride_y + z * dst_stride_z; - - // Compute offset contribution - VEC_INT offset_term_s32 = offset_contribution( - x, y, z -#if defined(A_OFFSET) - , - sum_col_ptr, - sum_col_stride_x, - sum_col_step_x, - sum_col_stride_y, - sum_col_step_y, - sum_col_offset_first_element_in_bytes -#endif // defined(A_OFFSET) -#if defined(B_OFFSET) - , - sum_row_ptr, - sum_row_stride_x, - sum_row_step_x, - sum_row_stride_y, - sum_row_step_y, - sum_row_offset_first_element_in_bytes -#endif // defined(B_OFFSET) -#if defined(ADD_BIAS) - , - biases_ptr, - biases_stride_x, - biases_step_x, - biases_offset_first_element_in_bytes -#endif // defined(ADD_BIAS) - ); - - __global uchar *mm_result_addr = mm_result_ptr + mm_result_offset_first_element_in_bytes + x * sizeof(int) + y * mm_result_stride_y + z * mm_result_stride_z; - - VEC_INT in_s32 = VLOAD(VEC_SIZE)(0, (__global int *)mm_result_addr); - - // Add the offset terms to GEMM's result - in_s32 += offset_term_s32; - - // -------------- OUTPUT STAGE - - // Add the offset terms to GEMM's result - in_s32 += (VEC_INT)RESULT_OFFSET; - - // Multiply by result_mult_int and shift -#if defined(PER_CHANNEL_QUANTIZATION) - __global uchar *result_multipliers_addr = result_multipliers_ptr + result_multipliers_offset_first_element_in_bytes + x * sizeof(int); - __global uchar *result_shifts_addr = result_shifts_ptr + result_shifts_offset_first_element_in_bytes + x * sizeof(int); - VEC_INT result_multipliers_values = VLOAD(VEC_SIZE)(0, (__global int *)result_multipliers_addr); - VEC_INT result_shifts_values = VLOAD(VEC_SIZE)(0, (__global int *)result_shifts_addr); - - in_s32 *= result_multipliers_values; - in_s32 >>= result_shifts_values; -#else // defined(PER_CHANNEL_QUANTIZATION) - in_s32 *= RESULT_MULTIPLIER; - - in_s32 >>= RESULT_SHIFT; -#endif // defined(PER_CHANNEL_QUANTIZATION) - - VEC_DATA_TYPE(OUTPUT_DATA_TYPE, VEC_SIZE) - res0 = CONVERT_SAT(in_s32, VEC_DATA_TYPE(OUTPUT_DATA_TYPE, VEC_SIZE)); - -#if defined(MIN_BOUND) - res0 = max(res0, (VEC_DATA_TYPE(OUTPUT_DATA_TYPE, VEC_SIZE))MIN_BOUND); -#endif // defined(MIN_BOUND) -#if defined(MAX_BOUND) - res0 = min(res0, (VEC_DATA_TYPE(OUTPUT_DATA_TYPE, VEC_SIZE))MAX_BOUND); -#endif // defined(MAX_BOUND) - - // Store the result - STORE_VECTOR_SELECT(res, OUTPUT_DATA_TYPE, dst_addr, VEC_SIZE, VEC_SIZE_LEFTOVER, VEC_SIZE_LEFTOVER != 0 && get_global_id(0) == 0) -} - -/* OpenCL kernel used to add the offset contribution after matrix multiplication and it quantizes down to uint8. - * - * This kernel takes a final int32 accumulator value (the output of matrix multiplication), adds to it the offset contribution of matrix A and matrix B and quantizes to uint8 through the output stage. - * - * - * @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 result before the output stage is: - * - * mm_result[i][k] = mm_result[i][k] + - * (sum_col[k] * A_OFFSET) + - * (sum_row[i] * B_OFFSET) + - * (K_OFFSET) - * - * This result is quantized down to uint8/int8 using the output stage. The output stage computes the following operations: - * - * -# 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. - * - to the [-128..127] range and cast to QASYMM8_SIGNED. - * - * @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 The output datatype should be passed at compile time using -DOUTPUT_DATA_TYPE - * @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 - * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16 - * @note Leftover vector size has to be passed at compile time using -DVEC_SIZE_LEFTOVER. e.g. -DVEC_SIZE_LEFTOVER=3. It is defined as the remainder between the input's first dimension and VEC_SIZE - * - * @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_ptr (Optional) Pointer to the source tensor. Supported data type: same as @p mm_result_ptr - * @param[in] sum_col_stride_x (Optional) Stride of the source tensor in X dimension (in bytes) - * @param[in] sum_col_step_x (Optional) sum_col_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] sum_col_stride_y (Optional) Stride of the source tensor in Y dimension (in bytes) - * @param[in] sum_col_step_y (Optional) sum_col_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] sum_col_offset_first_element_in_bytes (Optional) The offset of the first element in the source tensor - * @param[in] sum_row_ptr (Optional) Pointer to the source tensor. Supported data type: same as @p mm_result_ptr - * @param[in] sum_row_stride_x (Optional) Stride of the source tensor in X dimension (in bytes) - * @param[in] sum_row_step_x (Optional) sum_row_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] sum_row_stride_y (Optional) Stride of the source tensor in Y dimension (in bytes) - * @param[in] sum_row_step_y (Optional) sum_row_stride_y * number of elements along Y processed per workitem(in bytes) - * @param[in] sum_row_offset_first_element_in_bytes (Optional) The offset of the first element in the source tensor - * @param[in] biases_ptr (Optional) Pointer to the biases tensor. Supported data type: same as @p src_ptr - * @param[in] biases_stride_x (Optional) Stride of the biases tensor in X dimension (in bytes) - * @param[in] biases_step_x (Optional) biases_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] biases_offset_first_element_in_bytes (Optional) The offset of the first element in the biases tensor - * @param[out] dst_ptr Pointer to the destination tensor Supported data type: QASYMM8/QASYMM8_SIGNED - * @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 - * @param[in] result_multipliers_ptr (Optional) Pointer to the output multipliers vector for per-channel quantization. Supported data types: S32 - * @param[in] result_multipliers_stride_x (Optional) Stride of the output multipliers vector in X dimension (in bytes) - * @param[in] result_multipliers_step_x (Optional) output_multipliers_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] result_multipliers_offset_first_element_in_bytes (Optional) The offset of the first element in the output multipliers vector - * @param[in] result_shifts_ptr (Optional) Pointer to the output shifts vector for per-channel quantization. Supported data types: S32 - * @param[in] result_shifts_stride_x (Optional) Stride of the output shifts vector in X dimension (in bytes) - * @param[in] result_shifts_step_x (Optional) output_shifts_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] result_shifts_offset_first_element_in_bytes (Optional) The offset of the first element in the output shifts vector - */ -__kernel void gemmlowp_offset_contribution_quantize_down_fixedpoint(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) - , -#if defined(ADD_BIAS) - VECTOR_DECLARATION(biases), -#endif // defined(ADD_BIAS) - TENSOR3D_DECLARATION(dst) -#if defined(PER_CHANNEL_QUANTIZATION) - , - VECTOR_DECLARATION(result_multipliers), - VECTOR_DECLARATION(result_shifts) -#endif // defined(PER_CHANNEL_QUANTIZATION) - ) -{ - const int x = max((int)(get_global_id(0) * VEC_SIZE - (VEC_SIZE - VEC_SIZE_LEFTOVER) % VEC_SIZE), 0); - const int y = get_global_id(1); - const int z = get_global_id(2); - - // Compute offset contribution - VEC_INT offset_term_s32 = offset_contribution( - x, y, z -#if defined(A_OFFSET) - , - sum_col_ptr, - sum_col_stride_x, - sum_col_step_x, - sum_col_stride_y, - sum_col_step_y, - sum_col_offset_first_element_in_bytes -#endif // defined(A_OFFSET) -#if defined(B_OFFSET) - , - sum_row_ptr, - sum_row_stride_x, - sum_row_step_x, - sum_row_stride_y, - sum_row_step_y, - sum_row_offset_first_element_in_bytes -#endif // defined(B_OFFSET) -#if defined(ADD_BIAS) - , - biases_ptr, - biases_stride_x, - biases_step_x, - biases_offset_first_element_in_bytes -#endif // defined(ADD_BIAS) - ); - - __global uchar *mm_result_addr = mm_result_ptr + mm_result_offset_first_element_in_bytes + x * sizeof(int) + y * mm_result_stride_y + z * mm_result_stride_z; - - __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + x + y * dst_stride_y + z * dst_stride_z; - - VEC_INT in_s32 = VLOAD(VEC_SIZE)(0, (__global int *)mm_result_addr); - - // Add the offset terms to GEMM's result - in_s32 += offset_term_s32; - - // -------------- OUTPUT STAGE - - // Multiply by result_mult_int and shift -#if defined(PER_CHANNEL_QUANTIZATION) - __global uchar *result_multipliers_addr = result_multipliers_ptr + result_multipliers_offset_first_element_in_bytes + x * sizeof(int); - __global uchar *result_shifts_addr = result_shifts_ptr + result_shifts_offset_first_element_in_bytes + x * sizeof(int); - VEC_INT result_multipliers_values = VLOAD(VEC_SIZE)(0, (__global int *)result_multipliers_addr); - VEC_INT result_shifts_values = VLOAD(VEC_SIZE)(0, (__global int *)result_shifts_addr); - - VEC_INT in_s32_shift_lt0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(in_s32, result_multipliers_values, result_shifts_values, VEC_SIZE); - VEC_INT in_s32_shift_gt0 = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(in_s32, result_multipliers_values, result_shifts_values, VEC_SIZE); - in_s32 = select(in_s32_shift_lt0, in_s32_shift_gt0, result_shifts_values >= 0); -#else // defined(PER_CHANNEL_QUANTIZATION) - -#if RESULT_SHIFT < 0 - in_s32 = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(in_s32, RESULT_MULTIPLIER, RESULT_SHIFT, VEC_SIZE); -#else // RESULT_SHIFT >= 0 - in_s32 = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(in_s32, RESULT_MULTIPLIER, RESULT_SHIFT, VEC_SIZE); -#endif // RESULT_SHIFT < 0 - -#endif // defined(PER_CHANNEL_QUANTIZATION) - - // Add the offset terms to GEMM's result - in_s32 += (VEC_INT)RESULT_OFFSET; - - VEC_DATA_TYPE(OUTPUT_DATA_TYPE, VEC_SIZE) - res0 = CONVERT_SAT(in_s32, VEC_DATA_TYPE(OUTPUT_DATA_TYPE, VEC_SIZE)); - -#if defined(MIN_BOUND) - res0 = max(res0, (VEC_DATA_TYPE(OUTPUT_DATA_TYPE, VEC_SIZE))MIN_BOUND); -#endif // defined(MIN_BOUND) -#if defined(MAX_BOUND) - res0 = min(res0, (VEC_DATA_TYPE(OUTPUT_DATA_TYPE, VEC_SIZE))MAX_BOUND); -#endif // defined(MAX_BOUND) - - // Store the result - STORE_VECTOR_SELECT(res, OUTPUT_DATA_TYPE, dst_addr, VEC_SIZE, VEC_SIZE_LEFTOVER, VEC_SIZE_LEFTOVER != 0 && get_global_id(0) == 0) -} -#endif // defined(RESULT_OFFSET) && defined(RESULT_MULTIPLIER) && defined(RESULT_SHIFT) && defined(OUTPUT_DATA_TYPE) - -#undef VEC_INT - -#endif // defined(K_OFFSET) && defined(VEC_SIZE) && defined(VEC_SIZE_LEFTOVER) - -#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/QASYMM8_SIGNED - * - * This kernel takes a final int32 accumulator value and processes it to obtain the final QASYMM8/QASYMM8_SIGNED 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. - * -# - to the [-128..127] range and cast to QASYMM8_SIGNED. - * - * @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 The output datatype should be passed at compile time using -DOUTPUT_DATA_TYPE - * @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 - * @note Leftover vector size has to be passed at compile time using -DVEC_SIZE_LEFTOVER. e.g. -DVEC_SIZE_LEFTOVER=3. It is defined as the remainder between the input's first dimension and VEC_SIZE - * - * @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 (Optional) Pointer to the biases tensor. Supported data type: same as @p src_ptr - * @param[in] biases_stride_x (Optional) Stride of the biases tensor in X dimension (in bytes) - * @param[in] biases_step_x (Optional) biases_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] biases_offset_first_element_in_bytes (Optional) The offset of the first element in the biases tensor - * @param[out] dst_ptr Pointer to the destination tensor Supported data type: QASYMM8/QASYMM8_SIGNED - * @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 - int x = max((int)(get_global_id(0) * VEC_SIZE - (VEC_SIZE - VEC_SIZE_LEFTOVER) % VEC_SIZE), 0); - int y = get_global_id(1); - int z = get_global_id(2); - - __global uchar *src_addr = src_ptr + src_offset_first_element_in_bytes + x * sizeof(int) + y * src_stride_y + z * src_stride_z; - - __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + x + y * dst_stride_y + z * dst_stride_z; - - VEC_DATA_TYPE(int, VEC_SIZE) - input_values = VLOAD(VEC_SIZE)(0, (__global int *)src_addr); - -#if defined(ADD_BIAS) - // Add bias - __global uchar *bias_addr = biases_ptr + biases_offset_first_element_in_bytes + x * sizeof(int); - - VEC_DATA_TYPE(int, VEC_SIZE) - biases_values = VLOAD(VEC_SIZE)(0, (__global int *)bias_addr); - input_values += biases_values; -#endif // defined(ADD_BIAS) - - // Add the offset terms to GEMM's result - input_values += (VEC_DATA_TYPE(int, VEC_SIZE))RESULT_OFFSET; - - // Multiply by result_mult_int and shift - input_values *= RESULT_MULT_INT; - -#if RESULT_SHIFT < 0 - input_values >>= -RESULT_SHIFT; -#else // RESULT_SHIFT >= 0 - input_values >>= RESULT_SHIFT; -#endif // RESULT_SHIFT < 0 - - VEC_DATA_TYPE(OUTPUT_DATA_TYPE, VEC_SIZE) - res0 = CONVERT_SAT(input_values, VEC_DATA_TYPE(OUTPUT_DATA_TYPE, VEC_SIZE)); - -#if defined(MIN_BOUND) - res0 = max(res0, (VEC_DATA_TYPE(OUTPUT_DATA_TYPE, VEC_SIZE))MIN_BOUND); -#endif // defined(MIN_BOUND) -#if defined(MAX_BOUND) - res0 = min(res0, (VEC_DATA_TYPE(OUTPUT_DATA_TYPE, VEC_SIZE))MAX_BOUND); -#endif // defined(MAX_BOUND) - - // Store the result - STORE_VECTOR_SELECT(res, OUTPUT_DATA_TYPE, dst_addr, VEC_SIZE, VEC_SIZE_LEFTOVER, VEC_SIZE_LEFTOVER != 0 && get_global_id(0) == 0) -} -#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/QASYMM8_SIGNED - * - * This kernel takes a final int32 accumulator value (the output of matrix multiplication), and processes it to obtain the final QASYMM8/QASYMM8_SIGNED 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. - * - to the [-128..127] range and cast to QASYMM8_SIGNED. - * - * @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_AFTER_SHIFT, -DRESULT_FIXEDPOINT_MULTIPLIER and -DRESULT_SHIFT - * - * @note In case the addition of int32 biases is required, -DADD_BIAS should be passed at compile time - * @note The output datatype should be passed at compile time using -DOUTPUT_DATA_TYPE - * @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 - * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16 - * @note Leftover vector size has to be passed at compile time using -DVEC_SIZE_LEFTOVER. e.g. -DVEC_SIZE_LEFTOVER=3. It is defined as the remainder between the input's first dimension and VEC_SIZE - * - * @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 (Optional) Pointer to the biases tensor. Supported data type: same as @p src_ptr - * @param[in] biases_stride_x (Optional) Stride of the biases tensor in X dimension (in bytes) - * @param[in] biases_step_x (Optional) biases_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] biases_offset_first_element_in_bytes (Optional) The offset of the first element in the biases tensor - * @param[out] dst_ptr Pointer to the destination tensor Supported data type: QASYMM8/QASYMM8_SIGNED - * @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 - int x = max((int)(get_global_id(0) * VEC_SIZE - (VEC_SIZE - VEC_SIZE_LEFTOVER) % VEC_SIZE), 0); - int y = get_global_id(1); - int z = get_global_id(2); - - __global uchar *src_addr = src_ptr + src_offset_first_element_in_bytes + x * sizeof(int) + y * src_stride_y + z * src_stride_z; - - __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + x + y * dst_stride_y + z * dst_stride_z; - - VEC_DATA_TYPE(int, VEC_SIZE) - input_values = VLOAD(VEC_SIZE)(0, (__global int *)src_addr); - -#if defined(ADD_BIAS) - // Add bias - __global uchar *bias_addr = biases_ptr + biases_offset_first_element_in_bytes + x * sizeof(int); - - VEC_DATA_TYPE(int, VEC_SIZE) - biases_values = VLOAD(VEC_SIZE)(0, (__global int *)bias_addr); - input_values += biases_values; -#endif // defined(ADD_BIAS) - - // Multiply by result_mult_int and shift -#if RESULT_SHIFT < 0 - input_values = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(input_values, RESULT_FIXEDPOINT_MULTIPLIER, RESULT_SHIFT, VEC_SIZE); -#else // RESULT_SHIFT >= 0 - input_values = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(input_values, RESULT_FIXEDPOINT_MULTIPLIER, RESULT_SHIFT, VEC_SIZE); -#endif // RESULT_SHIFT < 0 - - // Add the offset terms to GEMM's result - input_values += (VEC_DATA_TYPE(int, VEC_SIZE))RESULT_OFFSET_AFTER_SHIFT; - - VEC_DATA_TYPE(OUTPUT_DATA_TYPE, VEC_SIZE) - res0 = CONVERT_SAT(input_values, VEC_DATA_TYPE(OUTPUT_DATA_TYPE, VEC_SIZE)); - -#if defined(MIN_BOUND) - res0 = max(res0, (VEC_DATA_TYPE(OUTPUT_DATA_TYPE, VEC_SIZE))MIN_BOUND); -#endif // defined(MIN_BOUND) -#if defined(MAX_BOUND) - res0 = min(res0, (VEC_DATA_TYPE(OUTPUT_DATA_TYPE, VEC_SIZE))MAX_BOUND); -#endif // defined(MAX_BOUND) - - // Store the result - STORE_VECTOR_SELECT(res, OUTPUT_DATA_TYPE, dst_addr, VEC_SIZE, VEC_SIZE_LEFTOVER, VEC_SIZE_LEFTOVER != 0 && get_global_id(0) == 0) -} -#endif // defined(RESULT_OFFSET_AFTER_SHIFT) && defined(RESULT_FIXEDPOINT_MULTIPLIER) && defined(RESULT_SHIFT) - -#if defined(RESULT_FIXEDPOINT_MULTIPLIER) && defined(RESULT_SHIFT) - -/** This OpenCL kernel is used to quantize down the int32 accumulator values of GEMMLowp to QSYMM16 - * - * This kernel takes a final int32 accumulator value (the output of matrix multiplication), and processes it to obtain the final QSYMM16 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 [-32768..32767] range and cast to QSYMM16. - * - * @attention The offset, scalar scale factor and number of bits to shift right of output tensor must be passed at compile time using -DRESULT_FIXEDPOINT_MULTIPLIER 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 - * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16 - * @note Leftover vector size has to be passed at compile time using -DVEC_SIZE_LEFTOVER. e.g. -DVEC_SIZE_LEFTOVER=3. It is defined as the remainder between the input's first dimension and VEC_SIZE - * - * @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 (Optional) Pointer to the biases tensor. Supported data type: same as @p src_ptr - * @param[in] biases_stride_x (Optional) Stride of the biases tensor in X dimension (in bytes) - * @param[in] biases_step_x (Optional) biases_stride_x * number of elements along X processed per workitem(in bytes) - * @param[in] biases_offset_first_element_in_bytes (Optional) The offset of the first element in the biases tensor - * @param[out] dst_ptr Pointer to the destination tensor Supported data type: QSYMM16 - * @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_qsymm16(TENSOR3D_DECLARATION(src), -#if defined(ADD_BIAS) - VECTOR_DECLARATION(biases), -#endif // defined(ADD_BIAS) - TENSOR3D_DECLARATION(dst)) -{ - // Compute source and destination addresses - int x = max((int)(get_global_id(0) * VEC_SIZE - (VEC_SIZE - VEC_SIZE_LEFTOVER) % VEC_SIZE), 0); - int y = get_global_id(1); - int z = get_global_id(2); - - __global uchar *src_addr = src_ptr + src_offset_first_element_in_bytes + x * sizeof(int) + y * src_stride_y + z * src_stride_z; - - __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + x * sizeof(short) + y * dst_stride_y + z * dst_stride_z; - - VEC_DATA_TYPE(int, VEC_SIZE) - input_values = VLOAD(VEC_SIZE)(0, (__global int *)src_addr); - -#if defined(ADD_BIAS) - // Add bias - __global uchar *bias_addr = biases_ptr + biases_offset_first_element_in_bytes + x * sizeof(int); - - VEC_DATA_TYPE(int, VEC_SIZE) - biases_values = VLOAD(VEC_SIZE)(0, (__global int *)bias_addr); - input_values += biases_values; -#endif // defined(ADD_BIAS) - - // Multiply by result_mult_int and shift -#if RESULT_SHIFT < 0 - input_values = ASYMM_MULT_BY_QUANT_MULTIPLIER_GREATER_THAN_ONE(input_values, RESULT_FIXEDPOINT_MULTIPLIER, RESULT_SHIFT, VEC_SIZE); -#else // RESULT_SHIFT >= 0 - input_values = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(input_values, RESULT_FIXEDPOINT_MULTIPLIER, RESULT_SHIFT, VEC_SIZE); -#endif // RESULT_SHIFT < 0 - - VEC_DATA_TYPE(short, VEC_SIZE) - res0 = CONVERT_SAT(input_values, VEC_DATA_TYPE(short, VEC_SIZE)); - -#if defined(MIN_BOUND) - res0 = max(res0, (VEC_DATA_TYPE(short, VEC_SIZE))MIN_BOUND); -#endif // defined(MIN_BOUND) -#if defined(MAX_BOUND) - res0 = min(res0, (VEC_DATA_TYPE(short, VEC_SIZE))MAX_BOUND); -#endif // defined(MAX_BOUND) - - // Store the result - STORE_VECTOR_SELECT(res, short, dst_addr, VEC_SIZE, VEC_SIZE_LEFTOVER, VEC_SIZE_LEFTOVER != 0 && get_global_id(0) == 0) -} -#endif // defined(RESULT_FIXEDPOINT_MULTIPLIER) && defined(RESULT_SHIFT) - -#if defined(REAL_MULTIPLIER) && defined(OUTPUT_OFFSET) -/** This OpenCL kernel is used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8/QASYMM8_SIGNED - * - * This kernel takes a final int32 accumulator value (the output of matrix multiplication), and processes it to obtain the final QASYMM8/QASYMM8_SIGNED 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 - * -# Requantize - * -# 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. - * - to the [-128..127] range and cast to QASYMM8_SIGNED. - * - * @attention The offset and scalar scale factor must be passed at compile time using -DRESULT_OFFSET, -DREAL_MULTIPLIER - * - * @note In case the addition of int32 biases is required, -DADD_BIAS should be passed at compile time - * @note The output datatype should be passed at compile time using -DOUTPUT_DATA_TYPE - * @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 - * @note Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16 - * @note Leftover vector size has to be passed at compile time using -DVEC_SIZE_LEFTOVER. e.g. -DVEC_SIZE_LEFTOVER=3. It is defined as the remainder between the input's first dimension and VEC_SIZE - * - * @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_stride_w Stride of the source tensor in W dimension (in bytes) - * @param[in] dst_step_w src_stride_w * number of elements along W 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_float(TENSOR3D_DECLARATION(src), -#if defined(ADD_BIAS) - VECTOR_DECLARATION(biases), -#endif // defined(ADD_BIAS) -#if defined(DST_HEIGHT) - TENSOR4D_DECLARATION(dst)) -#else // defined(DST_HEIGHT) - TENSOR3D_DECLARATION(dst)) -#endif // defined(DST_HEIGHT) -{ - // Compute source and destination addresses - int x = max((int)(get_global_id(0) * VEC_SIZE - (VEC_SIZE - VEC_SIZE_LEFTOVER) % VEC_SIZE), 0); - int y = get_global_id(1); - int z = get_global_id(2); - - __global uchar *src_addr = src_ptr + src_offset_first_element_in_bytes + x * sizeof(int) + y * src_stride_y + z * src_stride_z; - - __global uchar *dst_addr = dst_ptr + dst_offset_first_element_in_bytes + x + y * dst_stride_y + z * dst_stride_z; - - VEC_DATA_TYPE(int, VEC_SIZE) - input_values = VLOAD(VEC_SIZE)(0, (__global int *)src_addr); - -#if defined(ADD_BIAS) - // Add bias - __global uchar *bias_addr = biases_ptr + biases_offset_first_element_in_bytes + x * sizeof(int); - - VEC_DATA_TYPE(int, VEC_SIZE) - biases_values = VLOAD(VEC_SIZE)(0, (__global int *)bias_addr); - input_values += (VEC_DATA_TYPE(int, VEC_SIZE))biases_values; -#endif // defined(ADD_BIAS) - - // Convert to float - VEC_DATA_TYPE(float, VEC_SIZE) - input_values_f = CONVERT(input_values, VEC_DATA_TYPE(float, VEC_SIZE)); - input_values_f = round(input_values_f * (float)REAL_MULTIPLIER + (float)OUTPUT_OFFSET); - - VEC_DATA_TYPE(OUTPUT_DATA_TYPE, VEC_SIZE) - res0 = CONVERT_SAT(input_values_f, VEC_DATA_TYPE(OUTPUT_DATA_TYPE, VEC_SIZE)); - -#if defined(MIN_BOUND) - res0 = max(res0, (VEC_DATA_TYPE(OUTPUT_DATA_TYPE, VEC_SIZE))MIN_BOUND); -#endif // defined(MIN_BOUND) -#if defined(MAX_BOUND) - res0 = min(res0, (VEC_DATA_TYPE(OUTPUT_DATA_TYPE, VEC_SIZE))MAX_BOUND); -#endif // defined(MAX_BOUND) - - // Store the result - STORE_VECTOR_SELECT(res, OUTPUT_DATA_TYPE, dst_addr, VEC_SIZE, VEC_SIZE_LEFTOVER, VEC_SIZE_LEFTOVER != 0 && get_global_id(0) == 0) -} -#endif // defined(REAL_MULTIPLIER) && defined(OUTPUT_OFFSET) |