diff options
Diffstat (limited to 'src/cpu/kernels/CpuGemmLowpOffsetContributionKernel.cpp')
| -rw-r--r-- | src/cpu/kernels/CpuGemmLowpOffsetContributionKernel.cpp | 721 |
1 files changed, 721 insertions, 0 deletions
diff --git a/src/cpu/kernels/CpuGemmLowpOffsetContributionKernel.cpp b/src/cpu/kernels/CpuGemmLowpOffsetContributionKernel.cpp new file mode 100644 index 0000000000..2a76a5958d --- /dev/null +++ b/src/cpu/kernels/CpuGemmLowpOffsetContributionKernel.cpp @@ -0,0 +1,721 @@ +/* + * Copyright (c) 2017-2022,2024 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 "src/cpu/kernels/CpuGemmLowpOffsetContributionKernel.h" + +#include "arm_compute/core/Error.h" +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/ITensor.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/Utils.h" +#include "arm_compute/core/Validate.h" +#include "arm_compute/core/Window.h" + +#include "src/core/helpers/AutoConfiguration.h" +#include "src/core/helpers/WindowHelpers.h" + +#include <arm_neon.h> + +namespace arm_compute +{ +namespace cpu +{ +namespace kernels +{ +namespace +{ +Status validate_arguments(const ITensorInfo *mm_result, + const ITensorInfo *vector_sum_col, + const ITensorInfo *vector_sum_row, + int32_t a_offset, + int32_t b_offset) +{ + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(mm_result, 1, DataType::S32, DataType::F32); + + // We run if the offset is nonzero or a sum col has been provided, we need + // the second option in case the QuantizationInfo is dynamic + if (a_offset != 0 || vector_sum_col != nullptr) + { + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(vector_sum_col, 1, DataType::S32); + ARM_COMPUTE_RETURN_ERROR_ON(vector_sum_col->dimension(0) != mm_result->dimension(0)); + } + + // We run if the offset is nonzero or a sum row has been provided, we need + // the second option in case the QuantizationInfo is dynamic + if (b_offset != 0 || vector_sum_row != nullptr) + { + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(vector_sum_row, 1, DataType::S32); + + // Check if input is a 3D reinterpretation + const bool reinterpret_as_3d = + mm_result->num_dimensions() > 1 && mm_result->tensor_shape().y() != vector_sum_row->tensor_shape().x(); + + // Validate input + ARM_COMPUTE_RETURN_ERROR_ON(reinterpret_as_3d && vector_sum_row->dimension(0) != + (mm_result->dimension(1) * mm_result->dimension(2))); + ARM_COMPUTE_RETURN_ERROR_ON(!reinterpret_as_3d && vector_sum_row->dimension(0) != mm_result->dimension(1)); + + TensorShape output_shape = mm_result->tensor_shape(); + if (output_shape.num_dimensions() > 1) + { + const unsigned int output_batch_idx = reinterpret_as_3d ? 3 : 2; + + TensorShape vector_sum_row_shape = vector_sum_row->tensor_shape(); + vector_sum_row_shape.collapse_from(1); + output_shape.collapse_from(output_batch_idx); + + ARM_COMPUTE_RETURN_ERROR_ON_MSG(vector_sum_row_shape[1] != output_shape[output_batch_idx], + "mm_result tensor must have the same number of batches of output tensor"); + + if (vector_sum_col != nullptr) + { + TensorShape vector_sum_col_shape = vector_sum_col->tensor_shape(); + vector_sum_col_shape.collapse_from(1); + + ARM_COMPUTE_RETURN_ERROR_ON_MSG(vector_sum_col_shape[1] != 1 && + vector_sum_col_shape[1] != vector_sum_row_shape[1], + "vector_sum_col tensor must have the same number of batches of " + "vector_sum_row_shape or the number of batches must be set to 1"); + } + } + } + + return Status{}; +} + +void run_offset_contribution_float(const Window &window, + ITensor *mm_result, + const ITensor *vector_sum_col, + const ITensor *vector_sum_row, + int32_t a_offset, + int32_t b_offset, + int32_t k_offset, + float scale, + bool slide_vector_sum_col, + bool is_gemm3d) +{ + Window collapsed_window = window.collapse_if_possible(window, Window::DimZ); + collapsed_window.set(Window::DimX, Window::Dimension(0, 1, 1)); + + const int height_input = is_gemm3d ? mm_result->info()->dimension(1) : 0; + const int depth_input = is_gemm3d ? mm_result->info()->dimension(2) : 1; + + const int window_start_x = window.x().start(); + const int window_end_x = window.x().end(); + const int window_step_x = 16; + + // if vector_sum_col is nullptr then stride_y is 0, else get stride_y + const size_t sum_col_stride_y = (vector_sum_col != nullptr) ? (vector_sum_col->info()->strides_in_bytes().y()) : 0; + Iterator mm_result_it(mm_result, collapsed_window); + + if ((a_offset != 0) && (b_offset != 0) && (vector_sum_col != nullptr) && (vector_sum_row != nullptr)) // true, true + { + // Set window for vector_sum_col + Window win_vector_sum_col(collapsed_window); + win_vector_sum_col.set(Window::DimY, Window::Dimension(0, 0, 0)); + win_vector_sum_col.set(Window::DimZ, Window::Dimension(0, 0, 0)); + + // Set window for vector_sum_row + Window win_vector_sum_row(collapsed_window); + win_vector_sum_row.set(Window::DimX, Window::Dimension(0, 0, 0)); + win_vector_sum_row.set(Window::DimY, Window::Dimension(0, 0, 0)); + win_vector_sum_row.set(Window::DimZ, Window::Dimension(0, 0, 0)); + + Iterator vector_sum_col_it(vector_sum_col, win_vector_sum_col); + Iterator vector_sum_row_it(vector_sum_row, win_vector_sum_row); + + const size_t sum_row_stride_y = vector_sum_row->info()->strides_in_bytes().y(); + + // Offset in case vector_sum_col is batched + const int vector_sum_col_batch_offset = + slide_vector_sum_col ? vector_sum_col->info()->strides_in_bytes().z() : 0; + + execute_window_loop( + collapsed_window, + [&](const Coordinates &id) + { + const int batch_id = id.z() / depth_input; + const size_t batch_offset_col = batch_id * (sum_col_stride_y); + auto vector_sum_col_ptr = reinterpret_cast<const int32_t *>(vector_sum_col_it.ptr() + batch_offset_col + + batch_id * vector_sum_col_batch_offset); + auto mm_result_ptr = reinterpret_cast<float *>(mm_result_it.ptr()); + + // Compute the leftover term due to b_offset. + int32_t b_offset_term_s32 = + *(reinterpret_cast<const int32_t *>(vector_sum_row_it.ptr() + batch_id * sum_row_stride_y) + + id.y() + (id.z() % depth_input) * height_input); + b_offset_term_s32 *= b_offset; + + const int32x4_t b_offset_term_s32_vec = vdupq_n_s32(b_offset_term_s32); + + int x = window_start_x; + for (; x <= (window_end_x - window_step_x); x += window_step_x) + { + // Compute the leftover term due to a_offset. + int32x4x4_t a_offset_term_s32 = { + {vld1q_s32(vector_sum_col_ptr + x + 0), vld1q_s32(vector_sum_col_ptr + x + 4), + vld1q_s32(vector_sum_col_ptr + x + 8), vld1q_s32(vector_sum_col_ptr + x + 12)}}; + + a_offset_term_s32.val[0] = vmulq_n_s32(a_offset_term_s32.val[0], a_offset); + a_offset_term_s32.val[1] = vmulq_n_s32(a_offset_term_s32.val[1], a_offset); + a_offset_term_s32.val[2] = vmulq_n_s32(a_offset_term_s32.val[2], a_offset); + a_offset_term_s32.val[3] = vmulq_n_s32(a_offset_term_s32.val[3], a_offset); + + // Add a_offset_term_s32 and b_offset_term_s32 + int32x4x4_t offset_term_s32 = { + {vdupq_n_s32(k_offset), vdupq_n_s32(k_offset), vdupq_n_s32(k_offset), vdupq_n_s32(k_offset)}}; + + offset_term_s32.val[0] = + vaddq_s32(offset_term_s32.val[0], vaddq_s32(a_offset_term_s32.val[0], b_offset_term_s32_vec)); + offset_term_s32.val[1] = + vaddq_s32(offset_term_s32.val[1], vaddq_s32(a_offset_term_s32.val[1], b_offset_term_s32_vec)); + offset_term_s32.val[2] = + vaddq_s32(offset_term_s32.val[2], vaddq_s32(a_offset_term_s32.val[2], b_offset_term_s32_vec)); + offset_term_s32.val[3] = + vaddq_s32(offset_term_s32.val[3], vaddq_s32(a_offset_term_s32.val[3], b_offset_term_s32_vec)); + + float32x4x4_t in_f32 = {{vld1q_f32(mm_result_ptr + x + 0), vld1q_f32(mm_result_ptr + x + 4), + vld1q_f32(mm_result_ptr + x + 8), vld1q_f32(mm_result_ptr + x + 12)}}; + + // Convert and scale the S32 offsets to match the already scaled GEMM results + float32x4x4_t offset_terms_scaled = {{ + vmulq_n_f32(vcvtq_f32_s32(offset_term_s32.val[0]), scale), + vmulq_n_f32(vcvtq_f32_s32(offset_term_s32.val[1]), scale), + vmulq_n_f32(vcvtq_f32_s32(offset_term_s32.val[2]), scale), + vmulq_n_f32(vcvtq_f32_s32(offset_term_s32.val[3]), scale), + }}; + + // Add the offset terms to the GEMM result + in_f32.val[0] = vaddq_f32(in_f32.val[0], offset_terms_scaled.val[0]); + in_f32.val[1] = vaddq_f32(in_f32.val[1], offset_terms_scaled.val[1]); + in_f32.val[2] = vaddq_f32(in_f32.val[2], offset_terms_scaled.val[2]); + in_f32.val[3] = vaddq_f32(in_f32.val[3], offset_terms_scaled.val[3]); + + // Store the result with the offset contribution + vst1q_f32(mm_result_ptr + x + 0, in_f32.val[0]); + vst1q_f32(mm_result_ptr + x + 4, in_f32.val[1]); + vst1q_f32(mm_result_ptr + x + 8, in_f32.val[2]); + vst1q_f32(mm_result_ptr + x + 12, in_f32.val[3]); + } + + // Left-overs loop + for (; x < window_end_x; ++x) + { + // Compute the leftover term due to a_offset. + int32_t a_offset_term_s32 = *(vector_sum_col_ptr + x); + + a_offset_term_s32 *= a_offset; + + // Add the offset terms to GEMM's result + // Store the result with the offset contribution + mm_result_ptr[x] += (k_offset + a_offset_term_s32 + b_offset_term_s32) * scale; + } + }, + vector_sum_col_it, vector_sum_row_it, mm_result_it); + } + else if ((a_offset == 0) && (b_offset != 0) && (vector_sum_row != nullptr)) // false, true + { + ARM_COMPUTE_ERROR_ON_NULLPTR(vector_sum_row); + + // Set window for vector_sum_row + Window win_vector_sum_row(collapsed_window); + win_vector_sum_row.set(Window::DimX, Window::Dimension(0, 0, 0)); + win_vector_sum_row.set(Window::DimY, Window::Dimension(0, 0, 0)); + win_vector_sum_row.set(Window::DimZ, Window::Dimension(0, 0, 0)); + + Iterator vector_sum_row_it(vector_sum_row, win_vector_sum_row); + + const size_t sum_row_stride_y = vector_sum_row->info()->strides_in_bytes().y(); + + execute_window_loop( + collapsed_window, + [&](const Coordinates &id) + { + const int batch_id = id.z() / depth_input; + auto mm_result_ptr = reinterpret_cast<float *>(mm_result_it.ptr()); + + // Compute the leftover term due to b_offset. + int32_t row_sum = + *(reinterpret_cast<const int32_t *>(vector_sum_row_it.ptr() + batch_id * sum_row_stride_y) + + id.y() + (id.z() % depth_input) * height_input); + float scaled_b_offset_term_f32 = row_sum * b_offset * scale; + + const float32x4_t b_offset_term_f32_vec = vdupq_n_f32(scaled_b_offset_term_f32); + + int x = window_start_x; + for (; x <= (window_end_x - window_step_x); x += window_step_x) + { + float32x4x4_t in_f32 = {{vld1q_f32(mm_result_ptr + x + 0), vld1q_f32(mm_result_ptr + x + 4), + vld1q_f32(mm_result_ptr + x + 8), vld1q_f32(mm_result_ptr + x + 12)}}; + + // Add the offset terms to GEMM's result + in_f32.val[0] = vaddq_f32(in_f32.val[0], b_offset_term_f32_vec); + in_f32.val[1] = vaddq_f32(in_f32.val[1], b_offset_term_f32_vec); + in_f32.val[2] = vaddq_f32(in_f32.val[2], b_offset_term_f32_vec); + in_f32.val[3] = vaddq_f32(in_f32.val[3], b_offset_term_f32_vec); + + // Store the result with the offset contribution + vst1q_f32(mm_result_ptr + x + 0, in_f32.val[0]); + vst1q_f32(mm_result_ptr + x + 4, in_f32.val[1]); + vst1q_f32(mm_result_ptr + x + 8, in_f32.val[2]); + vst1q_f32(mm_result_ptr + x + 12, in_f32.val[3]); + } + + // Left-overs loop + for (; x < window_end_x; ++x) + { + // Add the offset terms to GEMM's result + // Store the result with the offset contribution + mm_result_ptr[x] += scaled_b_offset_term_f32; + } + }, + vector_sum_row_it, mm_result_it); + } + else if ((a_offset != 0) && (b_offset == 0) && (vector_sum_col != nullptr)) // true, false + { + // Set window for vector_sum_col + Window win_vector_sum_col(collapsed_window); + win_vector_sum_col.set(Window::DimY, Window::Dimension(0, 0, 0)); + win_vector_sum_col.set(Window::DimZ, Window::Dimension(0, 0, 0)); + + Iterator vector_sum_col_it(vector_sum_col, win_vector_sum_col); + + // Offset in case vector_sum_col is batched + const int vector_sum_col_batch_offset = + slide_vector_sum_col ? vector_sum_col->info()->strides_in_bytes().z() : 0; + + execute_window_loop( + collapsed_window, + [&](const Coordinates &id) + { + const int batch_id = id.z() / depth_input; + const size_t batch_offset_col = + batch_id * + (sum_col_stride_y); // Value to offset vector_sum_col_ptr to allow for iteration of y values in tensor + auto vector_sum_col_ptr = reinterpret_cast<const int32_t *>(vector_sum_col_it.ptr() + batch_offset_col + + batch_id * vector_sum_col_batch_offset); + auto mm_result_ptr = reinterpret_cast<float *>(mm_result_it.ptr()); + + int x = window_start_x; + for (; x <= (window_end_x - window_step_x); x += window_step_x) + { + // Compute the leftover term due to a_offset. + int32x4x4_t a_offset_term_s32 = { + {vld1q_s32(vector_sum_col_ptr + x + 0), vld1q_s32(vector_sum_col_ptr + x + 4), + vld1q_s32(vector_sum_col_ptr + x + 8), vld1q_s32(vector_sum_col_ptr + x + 12)}}; + + a_offset_term_s32.val[0] = vmulq_n_s32(a_offset_term_s32.val[0], a_offset); + a_offset_term_s32.val[1] = vmulq_n_s32(a_offset_term_s32.val[1], a_offset); + a_offset_term_s32.val[2] = vmulq_n_s32(a_offset_term_s32.val[2], a_offset); + a_offset_term_s32.val[3] = vmulq_n_s32(a_offset_term_s32.val[3], a_offset); + + float32x4x4_t a_offset_term_scaled = {{ + vmulq_n_f32(vcvtq_f32_s32(a_offset_term_s32.val[0]), scale), + vmulq_n_f32(vcvtq_f32_s32(a_offset_term_s32.val[1]), scale), + vmulq_n_f32(vcvtq_f32_s32(a_offset_term_s32.val[2]), scale), + vmulq_n_f32(vcvtq_f32_s32(a_offset_term_s32.val[3]), scale), + }}; + + float32x4x4_t in_f32 = {{vld1q_f32(mm_result_ptr + x + 0), vld1q_f32(mm_result_ptr + x + 4), + vld1q_f32(mm_result_ptr + x + 8), vld1q_f32(mm_result_ptr + x + 12)}}; + + // Add the offset terms to GEMM's result + in_f32.val[0] = vaddq_f32(in_f32.val[0], a_offset_term_scaled.val[0]); + in_f32.val[1] = vaddq_f32(in_f32.val[1], a_offset_term_scaled.val[1]); + in_f32.val[2] = vaddq_f32(in_f32.val[2], a_offset_term_scaled.val[2]); + in_f32.val[3] = vaddq_f32(in_f32.val[3], a_offset_term_scaled.val[3]); + + // Store the result with the offset contribution + vst1q_f32(mm_result_ptr + x + 0, in_f32.val[0]); + vst1q_f32(mm_result_ptr + x + 4, in_f32.val[1]); + vst1q_f32(mm_result_ptr + x + 8, in_f32.val[2]); + vst1q_f32(mm_result_ptr + x + 12, in_f32.val[3]); + } + + // Left-overs loop + for (; x < window_end_x; ++x) + { + // Compute the leftover term due to a_offset. + const int32_t a_offset_term_s32 = *(vector_sum_col_ptr + x); + + // Add the offset terms to GEMM's result + // Store the result with the offset contribution + mm_result_ptr[x] += a_offset_term_s32 * a_offset * scale; + } + }, + vector_sum_col_it, mm_result_it); + } + else // false, false + { + // No offset contribution from matrix A and matrix B + return; + } +} + +void run_offset_contribution(const Window &window, + ITensor *mm_result, + const ITensor *vector_sum_col, + const ITensor *vector_sum_row, + int32_t a_offset, + int32_t b_offset, + int32_t k_offset, + bool slide_vector_sum_col, + bool is_gemm3d) +{ + Window collapsed_window = window.collapse_if_possible(window, Window::DimZ); + collapsed_window.set(Window::DimX, Window::Dimension(0, 1, 1)); + + const int height_input = is_gemm3d ? mm_result->info()->dimension(1) : 0; + const int depth_input = is_gemm3d ? mm_result->info()->dimension(2) : 1; + + const int window_start_x = window.x().start(); + const int window_end_x = window.x().end(); + const int window_step_x = 16; + + // if vector_sum_col is nullptr then stride_y is 0, else get stride_y + const size_t sum_col_stride_y = (vector_sum_col != nullptr) ? (vector_sum_col->info()->strides_in_bytes().y()) : 0; + Iterator mm_result_it(mm_result, collapsed_window); + + if ((a_offset != 0) && (b_offset != 0) && (vector_sum_col != nullptr) && (vector_sum_row != nullptr)) // true, true + { + // Set window for vector_sum_col + Window win_vector_sum_col(collapsed_window); + win_vector_sum_col.set(Window::DimY, Window::Dimension(0, 0, 0)); + win_vector_sum_col.set(Window::DimZ, Window::Dimension(0, 0, 0)); + + // Set window for vector_sum_row + Window win_vector_sum_row(collapsed_window); + win_vector_sum_row.set(Window::DimX, Window::Dimension(0, 0, 0)); + win_vector_sum_row.set(Window::DimY, Window::Dimension(0, 0, 0)); + win_vector_sum_row.set(Window::DimZ, Window::Dimension(0, 0, 0)); + + Iterator vector_sum_col_it(vector_sum_col, win_vector_sum_col); + Iterator vector_sum_row_it(vector_sum_row, win_vector_sum_row); + + const size_t sum_row_stride_y = vector_sum_row->info()->strides_in_bytes().y(); + + // Offset in case vector_sum_col is batched + const int vector_sum_col_batch_offset = + slide_vector_sum_col ? vector_sum_col->info()->strides_in_bytes().z() : 0; + + execute_window_loop( + collapsed_window, + [&](const Coordinates &id) + { + const int batch_id = id.z() / depth_input; + const size_t batch_offset_col = batch_id * (sum_col_stride_y); + auto vector_sum_col_ptr = reinterpret_cast<const int32_t *>(vector_sum_col_it.ptr() + batch_offset_col + + batch_id * vector_sum_col_batch_offset); + auto mm_result_ptr = reinterpret_cast<int32_t *>(mm_result_it.ptr()); + + // Compute the leftover term due to b_offset. + int32_t b_offset_term_s32 = + *(reinterpret_cast<const int32_t *>(vector_sum_row_it.ptr() + batch_id * sum_row_stride_y) + + id.y() + (id.z() % depth_input) * height_input); + b_offset_term_s32 *= b_offset; + + const int32x4_t b_offset_term_s32_vec = vdupq_n_s32(b_offset_term_s32); + + int x = window_start_x; + for (; x <= (window_end_x - window_step_x); x += window_step_x) + { + // Compute the leftover term due to a_offset. + int32x4x4_t a_offset_term_s32 = { + {vld1q_s32(vector_sum_col_ptr + x + 0), vld1q_s32(vector_sum_col_ptr + x + 4), + vld1q_s32(vector_sum_col_ptr + x + 8), vld1q_s32(vector_sum_col_ptr + x + 12)}}; + + a_offset_term_s32.val[0] = vmulq_n_s32(a_offset_term_s32.val[0], a_offset); + a_offset_term_s32.val[1] = vmulq_n_s32(a_offset_term_s32.val[1], a_offset); + a_offset_term_s32.val[2] = vmulq_n_s32(a_offset_term_s32.val[2], a_offset); + a_offset_term_s32.val[3] = vmulq_n_s32(a_offset_term_s32.val[3], a_offset); + + // Add a_offset_term_s32 and b_offset_term_s32 + int32x4x4_t offset_term_s32 = { + {vdupq_n_s32(k_offset), vdupq_n_s32(k_offset), vdupq_n_s32(k_offset), vdupq_n_s32(k_offset)}}; + + offset_term_s32.val[0] = + vaddq_s32(offset_term_s32.val[0], vaddq_s32(a_offset_term_s32.val[0], b_offset_term_s32_vec)); + offset_term_s32.val[1] = + vaddq_s32(offset_term_s32.val[1], vaddq_s32(a_offset_term_s32.val[1], b_offset_term_s32_vec)); + offset_term_s32.val[2] = + vaddq_s32(offset_term_s32.val[2], vaddq_s32(a_offset_term_s32.val[2], b_offset_term_s32_vec)); + offset_term_s32.val[3] = + vaddq_s32(offset_term_s32.val[3], vaddq_s32(a_offset_term_s32.val[3], b_offset_term_s32_vec)); + + int32x4x4_t in_s32 = {{vld1q_s32(mm_result_ptr + x + 0), vld1q_s32(mm_result_ptr + x + 4), + vld1q_s32(mm_result_ptr + x + 8), vld1q_s32(mm_result_ptr + x + 12)}}; + + // Add the offset terms to GEMM's result + in_s32.val[0] = vaddq_s32(in_s32.val[0], offset_term_s32.val[0]); + in_s32.val[1] = vaddq_s32(in_s32.val[1], offset_term_s32.val[1]); + in_s32.val[2] = vaddq_s32(in_s32.val[2], offset_term_s32.val[2]); + in_s32.val[3] = vaddq_s32(in_s32.val[3], offset_term_s32.val[3]); + + // Store the result with the offset contribution + vst1q_s32(mm_result_ptr + x + 0, in_s32.val[0]); + vst1q_s32(mm_result_ptr + x + 4, in_s32.val[1]); + vst1q_s32(mm_result_ptr + x + 8, in_s32.val[2]); + vst1q_s32(mm_result_ptr + x + 12, in_s32.val[3]); + } + + // Left-overs loop + for (; x < window_end_x; ++x) + { + // Compute the leftover term due to a_offset. + int32_t a_offset_term_s32 = *(vector_sum_col_ptr + x); + + a_offset_term_s32 *= a_offset; + + // Add the offset terms to GEMM's result + // Store the result with the offset contribution + mm_result_ptr[x] += k_offset + a_offset_term_s32 + b_offset_term_s32; + } + }, + vector_sum_col_it, vector_sum_row_it, mm_result_it); + } + else if ((a_offset == 0) && (b_offset != 0) && (vector_sum_row != nullptr)) // false, true + { + ARM_COMPUTE_ERROR_ON_NULLPTR(vector_sum_row); + + // Set window for vector_sum_row + Window win_vector_sum_row(collapsed_window); + win_vector_sum_row.set(Window::DimX, Window::Dimension(0, 0, 0)); + win_vector_sum_row.set(Window::DimY, Window::Dimension(0, 0, 0)); + win_vector_sum_row.set(Window::DimZ, Window::Dimension(0, 0, 0)); + + Iterator vector_sum_row_it(vector_sum_row, win_vector_sum_row); + + const size_t sum_row_stride_y = vector_sum_row->info()->strides_in_bytes().y(); + + execute_window_loop( + collapsed_window, + [&](const Coordinates &id) + { + const int batch_id = id.z() / depth_input; + auto mm_result_ptr = reinterpret_cast<int32_t *>(mm_result_it.ptr()); + + // Compute the leftover term due to b_offset. + int32_t b_offset_term_s32 = + *(reinterpret_cast<const int32_t *>(vector_sum_row_it.ptr() + batch_id * sum_row_stride_y) + + id.y() + (id.z() % depth_input) * height_input); + b_offset_term_s32 *= b_offset; + + const int32x4_t b_offset_term_s32_vec = vdupq_n_s32(b_offset_term_s32); + + int x = window_start_x; + for (; x <= (window_end_x - window_step_x); x += window_step_x) + { + int32x4x4_t in_s32 = {{vld1q_s32(mm_result_ptr + x + 0), vld1q_s32(mm_result_ptr + x + 4), + vld1q_s32(mm_result_ptr + x + 8), vld1q_s32(mm_result_ptr + x + 12)}}; + + // Add the offset terms to GEMM's result + in_s32.val[0] = vaddq_s32(in_s32.val[0], b_offset_term_s32_vec); + in_s32.val[1] = vaddq_s32(in_s32.val[1], b_offset_term_s32_vec); + in_s32.val[2] = vaddq_s32(in_s32.val[2], b_offset_term_s32_vec); + in_s32.val[3] = vaddq_s32(in_s32.val[3], b_offset_term_s32_vec); + + // Store the result with the offset contribution + vst1q_s32(mm_result_ptr + x + 0, in_s32.val[0]); + vst1q_s32(mm_result_ptr + x + 4, in_s32.val[1]); + vst1q_s32(mm_result_ptr + x + 8, in_s32.val[2]); + vst1q_s32(mm_result_ptr + x + 12, in_s32.val[3]); + } + + // Left-overs loop + for (; x < window_end_x; ++x) + { + // Add the offset terms to GEMM's result + // Store the result with the offset contribution + mm_result_ptr[x] += b_offset_term_s32; + } + }, + vector_sum_row_it, mm_result_it); + } + else if ((a_offset != 0) && (b_offset == 0) && (vector_sum_col != nullptr)) // true, false + { + // Set window for vector_sum_col + Window win_vector_sum_col(collapsed_window); + win_vector_sum_col.set(Window::DimY, Window::Dimension(0, 0, 0)); + win_vector_sum_col.set(Window::DimZ, Window::Dimension(0, 0, 0)); + + Iterator vector_sum_col_it(vector_sum_col, win_vector_sum_col); + + // Offset in case vector_sum_col is batched + const int vector_sum_col_batch_offset = + slide_vector_sum_col ? vector_sum_col->info()->strides_in_bytes().z() : 0; + + execute_window_loop( + collapsed_window, + [&](const Coordinates &id) + { + const int batch_id = id.z() / depth_input; + const size_t batch_offset_col = + batch_id * + (sum_col_stride_y); // Value to offset vector_sum_col_ptr to allow for iteration of y values in tensor + auto vector_sum_col_ptr = reinterpret_cast<const int32_t *>(vector_sum_col_it.ptr() + batch_offset_col + + batch_id * vector_sum_col_batch_offset); + auto mm_result_ptr = reinterpret_cast<int32_t *>(mm_result_it.ptr()); + + int x = window_start_x; + for (; x <= (window_end_x - window_step_x); x += window_step_x) + { + // Compute the leftover term due to a_offset. + int32x4x4_t a_offset_term_s32 = { + {vld1q_s32(vector_sum_col_ptr + x + 0), vld1q_s32(vector_sum_col_ptr + x + 4), + vld1q_s32(vector_sum_col_ptr + x + 8), vld1q_s32(vector_sum_col_ptr + x + 12)}}; + + a_offset_term_s32.val[0] = vmulq_n_s32(a_offset_term_s32.val[0], a_offset); + a_offset_term_s32.val[1] = vmulq_n_s32(a_offset_term_s32.val[1], a_offset); + a_offset_term_s32.val[2] = vmulq_n_s32(a_offset_term_s32.val[2], a_offset); + a_offset_term_s32.val[3] = vmulq_n_s32(a_offset_term_s32.val[3], a_offset); + + int32x4x4_t in_s32 = {{vld1q_s32(mm_result_ptr + x + 0), vld1q_s32(mm_result_ptr + x + 4), + vld1q_s32(mm_result_ptr + x + 8), vld1q_s32(mm_result_ptr + x + 12)}}; + + // Add the offset terms to GEMM's result + in_s32.val[0] = vaddq_s32(in_s32.val[0], a_offset_term_s32.val[0]); + in_s32.val[1] = vaddq_s32(in_s32.val[1], a_offset_term_s32.val[1]); + in_s32.val[2] = vaddq_s32(in_s32.val[2], a_offset_term_s32.val[2]); + in_s32.val[3] = vaddq_s32(in_s32.val[3], a_offset_term_s32.val[3]); + + // Store the result with the offset contribution + vst1q_s32(mm_result_ptr + x + 0, in_s32.val[0]); + vst1q_s32(mm_result_ptr + x + 4, in_s32.val[1]); + vst1q_s32(mm_result_ptr + x + 8, in_s32.val[2]); + vst1q_s32(mm_result_ptr + x + 12, in_s32.val[3]); + } + + // Left-overs loop + for (; x < window_end_x; ++x) + { + // Compute the leftover term due to a_offset. + const int32_t a_offset_term_s32 = *(vector_sum_col_ptr + x); + + // Add the offset terms to GEMM's result + // Store the result with the offset contribution + mm_result_ptr[x] += a_offset_term_s32 * a_offset; + } + }, + vector_sum_col_it, mm_result_it); + } + else // false, false + { + // No offset contribution from matrix A and matrix B + return; + } +} +} // namespace + +void CpuGemmLowpOffsetContributionKernel::configure(ITensorInfo *mm_result, + ITensorInfo *vector_sum_col, + ITensorInfo *vector_sum_row, + int32_t k, + int32_t a_offset, + int32_t b_offset, + float scale) +{ + // Perform validate step + ARM_COMPUTE_UNUSED(vector_sum_row); + ARM_COMPUTE_ERROR_ON_NULLPTR(mm_result); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(mm_result, vector_sum_col, vector_sum_row, a_offset, b_offset)); + + _a_offset = a_offset; + _b_offset = b_offset; + _k = k; + + _scale = scale; + + if (vector_sum_col != nullptr) + { + // Check if vector_sum_col_shape should be slidden or not + // Don't slide vector_sum_col_shape along the y dimension if vector_sum_col_shape has just 1 dimension and vector_sum_row_shape more than 1 + // This scenario can happen when the the matrix multiplication is used to perform a convolution operation + _slide_vector_sum_col = vector_sum_col->tensor_shape().num_dimensions() > 1; + } + + // Configure kernel window + Window win = calculate_max_window(*mm_result, Steps()); + ICpuKernel::configure(win); +} + +void CpuGemmLowpOffsetContributionKernel::set_a_offset(int32_t a_offset) +{ + _a_offset = a_offset; +} + +void CpuGemmLowpOffsetContributionKernel::set_b_offset(int32_t b_offset) +{ + _b_offset = b_offset; +} + +void CpuGemmLowpOffsetContributionKernel::set_scale(float scale) +{ + _scale = scale; +} + +Status CpuGemmLowpOffsetContributionKernel::validate(const ITensorInfo *mm_result, + const ITensorInfo *vector_sum_col, + const ITensorInfo *vector_sum_row, + int32_t a_offset, + int32_t b_offset) +{ + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(mm_result, vector_sum_col, vector_sum_row, a_offset, b_offset)); + return Status{}; +} + +void CpuGemmLowpOffsetContributionKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) +{ + ARM_COMPUTE_UNUSED(info); + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICpuKernel::window(), window); + + auto vector_sum_col = tensors.get_const_tensor(TensorType::ACL_SRC_0); + auto vector_sum_row = tensors.get_const_tensor(TensorType::ACL_SRC_1); + auto mm_result = tensors.get_tensor(TensorType::ACL_DST); + + // Check if input is a 3D reinterpretation + const bool reinterpret_as_3d = vector_sum_row != nullptr && mm_result->info()->num_dimensions() > 1 && + mm_result->info()->tensor_shape().y() != vector_sum_row->info()->tensor_shape().x(); + + // check to see what is the output type of result + auto k_offset = _a_offset * _b_offset * _k; + if (mm_result->info()->data_type() == DataType::F32) + { + run_offset_contribution_float(window, mm_result, vector_sum_col, vector_sum_row, _a_offset, _b_offset, k_offset, + _scale, _slide_vector_sum_col, reinterpret_as_3d); + } + else + { + run_offset_contribution(window, mm_result, vector_sum_col, vector_sum_row, _a_offset, _b_offset, k_offset, + _slide_vector_sum_col, reinterpret_as_3d); + } +} + +const char *CpuGemmLowpOffsetContributionKernel::name() const +{ + return "CpuGemmLowpOffsetContributionKernel"; +} +} // namespace kernels +} // namespace cpu +} // namespace arm_compute |