diff options
Diffstat (limited to 'src/core/CL/cl_kernels/gemmlowp.cl')
| -rw-r--r-- | src/core/CL/cl_kernels/gemmlowp.cl | 202 |
1 files changed, 125 insertions, 77 deletions
diff --git a/src/core/CL/cl_kernels/gemmlowp.cl b/src/core/CL/cl_kernels/gemmlowp.cl index 214c7a4825..7a97fa6fa1 100644 --- a/src/core/CL/cl_kernels/gemmlowp.cl +++ b/src/core/CL/cl_kernels/gemmlowp.cl @@ -1160,9 +1160,9 @@ __kernel void gemmlowp_matrix_b_reduction(TENSOR3D_DECLARATION(src), #if defined(K_OFFSET) -/* Helper function used to calculate the offset contribution after @ref CLGEMMLowpMatrixMultiplyKernel. +/* Helper function used to calculate the offset contribution after matrix multiplication. * - * This kernel takes a final int32 accumulator value (the output of @CLGEMMLowpMatrixMultiplyKernel), + * 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) @@ -1254,9 +1254,9 @@ inline int4 offset_contribution( return (int4)K_OFFSET + a_offset_s32 + b_offset_s32; } -/* OpenCL kernel used to add the offset contribution after @ref CLGEMMLowpMatrixMultiplyKernel. The computation is performed in-place +/* 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 @CLGEMMLowpMatrixMultiplyKernel), + * 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) @@ -1389,38 +1389,46 @@ __kernel void gemmlowp_offset_contribution(TENSOR3D_DECLARATION(mm_result) * @note In case the clamping of the result is required, the min and max bounds can be passed at compile time using -DMIN_BOUND and -DMAX_BOUND. * These values can be used to implement "rectified linear unit" activation functions * - * @param[in] 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 - * @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] 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 + * @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) @@ -1435,7 +1443,13 @@ __kernel void gemmlowp_offset_contribution_quantize_down(TENSOR3D_DECLARATION(mm #if defined(ADD_BIAS) VECTOR_DECLARATION(biases), #endif // defined(ADD_BIAS) - TENSOR3D_DECLARATION(dst)) + TENSOR3D_DECLARATION(dst) +#if defined(PER_CHANNEL_QUANTIZATION) + , + VECTOR_DECLARATION(result_multipliers), + VECTOR_DECLARATION(result_shifts) +#endif // defined(PER_CHANNEL_QUANTIZATION) + ) { const int x = get_global_id(0) * 4; const int y = get_global_id(1); @@ -1486,9 +1500,19 @@ __kernel void gemmlowp_offset_contribution_quantize_down(TENSOR3D_DECLARATION(mm in_s32 += (int4)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); + int4 result_multipliers_values = vload4(0, (__global int *)result_multipliers_addr); + int4 result_shifts_values = vload4(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) uchar4 res = convert_uchar4_sat(in_s32); @@ -1503,9 +1527,9 @@ __kernel void gemmlowp_offset_contribution_quantize_down(TENSOR3D_DECLARATION(mm vstore4(res, 0, dst_addr); } -/* OpenCL kernel used to add the offset contribution after @ref CLGEMMLowpMatrixMultiplyKernel and it quantizes down to uint8. +/* 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 @CLGEMMLowpMatrixMultiplyKernel), adds to it the offset contribution of matrix A and matrix B and quantizes to uint8 through the output stage. + * 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) @@ -1535,38 +1559,46 @@ __kernel void gemmlowp_offset_contribution_quantize_down(TENSOR3D_DECLARATION(mm * @note In case the clamping of the result is required, the min and max bounds can be passed at compile time using -DMIN_BOUND and -DMAX_BOUND. * These values can be used to implement "rectified linear unit" activation functions * - * @param[in] 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 - * @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] 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 + * @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) @@ -1581,7 +1613,13 @@ __kernel void gemmlowp_offset_contribution_quantize_down_fixedpoint(TENSOR3D_DEC #if defined(ADD_BIAS) VECTOR_DECLARATION(biases), #endif // defined(ADD_BIAS) - TENSOR3D_DECLARATION(dst)) + TENSOR3D_DECLARATION(dst) +#if defined(PER_CHANNEL_QUANTIZATION) + , + VECTOR_DECLARATION(result_multipliers), + VECTOR_DECLARATION(result_shifts) +#endif // defined(PER_CHANNEL_QUANTIZATION) + ) { const int x = get_global_id(0) * 4; const int y = get_global_id(1); @@ -1629,7 +1667,16 @@ __kernel void gemmlowp_offset_contribution_quantize_down_fixedpoint(TENSOR3D_DEC // -------------- 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); + int4 result_multipliers_values = vload4(0, (__global int *)result_multipliers_addr); + int4 result_shifts_values = vload4(0, (__global int *)result_shifts_addr); + + in_s32 = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(in_s32, result_multipliers_values, result_shifts_values, 4); +#else // !defined(PER_CHANNEL_QUANTIZATION) in_s32 = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(in_s32, RESULT_MULTIPLIER, RESULT_SHIFT, 4); +#endif // defined(PER_CHANNEL_QUANTIZATION) // Add the offset terms to GEMM's result in_s32 += (int4)RESULT_OFFSET; @@ -1646,7 +1693,8 @@ __kernel void gemmlowp_offset_contribution_quantize_down_fixedpoint(TENSOR3D_DEC // Store the result vstore4(res, 0, dst_addr); } -#endif // defined(K_OFFSET) && defined(RESULT_OFFSET) && defined(RESULT_MULTIPLIER) && defined(RESULT_SHIFT) +#endif // defined(RESULT_OFFSET) && defined(RESULT_MULTIPLIER) && defined(RESULT_SHIFT) + #endif // defined(K_OFFSET) #if defined(RESULT_OFFSET) && defined(RESULT_MULT_INT) && defined(RESULT_SHIFT) @@ -1739,7 +1787,7 @@ __kernel void gemmlowp_output_stage_quantize_down(TENSOR3D_DECLARATION(src), #if defined(RESULT_OFFSET_AFTER_SHIFT) && defined(RESULT_FIXEDPOINT_MULTIPLIER) && defined(RESULT_SHIFT) /** This OpenCL kernel is used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8 * - * This kernel takes a final int32 accumulator value (the output of @ref CLGEMMLowpMatrixMultiplyKernel), and processes it to obtain the final QASYMM8 value. + * This kernel takes a final int32 accumulator value (the output of matrix multiplication), and processes it to obtain the final QASYMM8 value. * The following computations will be performed by the kernel: * * -# Compute fixed point multiplication between each entry of input by result_fixedpoint_multiplier @@ -1825,7 +1873,7 @@ __kernel void gemmlowp_output_stage_quantize_down_fixedpoint(TENSOR3D_DECLARATIO /** 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 @ref CLGEMMLowpMatrixMultiplyKernel), and processes it to obtain the final QSYMM16 value. + * 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 @@ -1890,7 +1938,7 @@ __kernel void gemmlowp_output_stage_quantize_down_fixedpoint_qsymm16(TENSOR3D_DE // Multiply by result_mult_int and shift #if RESULT_SHIFT < 0 input_values = ASYMM_MULT(input_values * (1 << (-RESULT_SHIFT)), RESULT_FIXEDPOINT_MULTIPLIER, 4); -#else // RESULT_SHIFT >= 0 +#else // RESULT_SHIFT >= 0 input_values = ASYMM_MULT_BY_QUANT_MULTIPLIER_LESS_THAN_ONE(input_values, RESULT_FIXEDPOINT_MULTIPLIER, RESULT_SHIFT, 4); #endif // RESULT_SHIFT < 0 @@ -1911,7 +1959,7 @@ __kernel void gemmlowp_output_stage_quantize_down_fixedpoint_qsymm16(TENSOR3D_DE #if defined(REAL_MULTIPLIER) && defined(OUTPUT_OFFSET) /** This OpenCL kernel is used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8 * - * This kernel takes a final int32 accumulator value (the output of @ref CLGEMMLowpMatrixMultiplyKernel), and processes it to obtain the final QASYMM8 value. + * This kernel takes a final int32 accumulator value (the output of matrix multiplication), and processes it to obtain the final QASYMM8 value. * The following computations will be performed by the kernel: * * -# Compute fixed point multiplication between each entry of input by result_fixedpoint_multiplier |