diff options
Diffstat (limited to 'src/core/NEON/kernels/NEGEMMLowpOffsetContributionKernel.cpp')
| -rw-r--r-- | src/core/NEON/kernels/NEGEMMLowpOffsetContributionKernel.cpp | 307 |
1 files changed, 175 insertions, 132 deletions
diff --git a/src/core/NEON/kernels/NEGEMMLowpOffsetContributionKernel.cpp b/src/core/NEON/kernels/NEGEMMLowpOffsetContributionKernel.cpp index af84d024d5..33a5b4ace3 100644 --- a/src/core/NEON/kernels/NEGEMMLowpOffsetContributionKernel.cpp +++ b/src/core/NEON/kernels/NEGEMMLowpOffsetContributionKernel.cpp @@ -62,16 +62,24 @@ Status validate_arguments(const ITensorInfo *mm_result, const ITensorInfo *vecto if(b_offset != 0) { ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(vector_sum_row, 1, DataType::S32); - ARM_COMPUTE_RETURN_ERROR_ON(vector_sum_row->dimension(0) != mm_result->dimension(1)); + + // 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(2); + output_shape.collapse_from(output_batch_idx); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(vector_sum_row_shape[1] != output_shape[2], + 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(a_offset != 0) @@ -117,77 +125,23 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *mm_result, Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; return std::make_pair(err, win); } -} // namespace - -NEGEMMLowpOffsetContributionKernel::NEGEMMLowpOffsetContributionKernel() - : _vector_sum_col(nullptr), _vector_sum_row(nullptr), _mm_result(nullptr), _a_offset(0), _b_offset(0), _k_offset(0), _slide_vector_sum_col(true) -{ -} - -void NEGEMMLowpOffsetContributionKernel::configure(ITensor *mm_result, const ITensor *vector_sum_col, const ITensor *vector_sum_row, int32_t k, int32_t a_offset, int32_t b_offset) -{ - // Perform validate step - ARM_COMPUTE_ERROR_ON_NULLPTR(mm_result); - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(mm_result->info(), - vector_sum_col != nullptr ? vector_sum_col->info() : nullptr, // NOLINT - vector_sum_row != nullptr ? vector_sum_row->info() : nullptr, // NOLINT - a_offset, b_offset)); // NOLINT - - _vector_sum_col = vector_sum_col; - _vector_sum_row = vector_sum_row; - _mm_result = mm_result; - _a_offset = a_offset; - _b_offset = b_offset; - _k_offset = a_offset * b_offset * k; - - // If a_offset == 0, vector_sum_col can be a nullptr - if(a_offset != 0) - { - // 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->info()->tensor_shape().num_dimensions() > 1; - } - - // Configure kernel window - auto win_config = validate_and_configure_window(mm_result->info(), - vector_sum_col != nullptr ? vector_sum_col->info() : nullptr, // NOLINT - vector_sum_row != nullptr ? vector_sum_row->info() : nullptr, // NOLINT - a_offset, b_offset); - ARM_COMPUTE_ERROR_THROW_ON(win_config.first); - INEKernel::configure(win_config.second); -} - -Status NEGEMMLowpOffsetContributionKernel::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)); - ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(mm_result->clone().get(), - vector_sum_col != nullptr ? vector_sum_col->clone().get() : nullptr, - vector_sum_row != nullptr ? vector_sum_row->clone().get() : nullptr, - a_offset, b_offset) - .first); // NOLINT - - return Status{}; -} -void NEGEMMLowpOffsetContributionKernel::run(const Window &window, const ThreadInfo &info) +template <bool is_gemm3d> +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) { - ARM_COMPUTE_UNUSED(info); - ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); - ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); + Window collapsed_window = window.collapse_if_possible(window, Window::DimZ); - Window collapsed_window = window.collapse_if_possible(IKernel::window(), Window::DimZ); + const int height_input = is_gemm3d ? mm_result->info()->dimension(1) : 0; + const int depth_input = is_gemm3d ? mm_result->info()->dimension(2) : 1; - if(_a_offset != 0 && _b_offset != 0) // true, true + 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)); - if(!_slide_vector_sum_col) - { - win_vector_sum_col.set(Window::DimZ, 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); @@ -195,42 +149,49 @@ void NEGEMMLowpOffsetContributionKernel::run(const Window &window, const ThreadI 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(_vector_sum_col, win_vector_sum_col); - Iterator vector_sum_row(_vector_sum_row, win_vector_sum_row); - Iterator mm_result(_mm_result, window); + Iterator vector_sum_col_it(vector_sum_col, win_vector_sum_col); + Iterator vector_sum_row_it(vector_sum_row, win_vector_sum_row); + Iterator mm_result_it(mm_result, window); - const size_t sum_row_stride_y = _vector_sum_row->info()->strides_in_bytes().y(); + 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 auto vector_sum_col_ptr = reinterpret_cast<const int32_t *>(vector_sum_col_it.ptr() + batch_id * vector_sum_col_batch_offset); + // Compute the leftover term due to a_offset. int32x4x4_t a_offset_term_s32 = { { - vld1q_s32(reinterpret_cast<const int32_t *>(vector_sum_col.ptr()) + 0), - vld1q_s32(reinterpret_cast<const int32_t *>(vector_sum_col.ptr()) + 4), - vld1q_s32(reinterpret_cast<const int32_t *>(vector_sum_col.ptr()) + 8), - vld1q_s32(reinterpret_cast<const int32_t *>(vector_sum_col.ptr()) + 12) + vld1q_s32(vector_sum_col_ptr + 0), + vld1q_s32(vector_sum_col_ptr + 4), + vld1q_s32(vector_sum_col_ptr + 8), + vld1q_s32(vector_sum_col_ptr + 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); + 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); // Compute the leftover term due to b_offset. - int32x4_t b_offset_term_s32 = vld1q_dup_s32(reinterpret_cast<const int32_t *>(vector_sum_row.ptr() + id.z() * sum_row_stride_y) + id.y()); - b_offset_term_s32 = vmulq_n_s32(b_offset_term_s32, _b_offset); + int32x4_t b_offset_term_s32 = vld1q_dup_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 = vmulq_n_s32(b_offset_term_s32, b_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) + vdupq_n_s32(k_offset), + vdupq_n_s32(k_offset), + vdupq_n_s32(k_offset), + vdupq_n_s32(k_offset) } }; @@ -242,10 +203,10 @@ void NEGEMMLowpOffsetContributionKernel::run(const Window &window, const ThreadI int32x4x4_t in_s32 = { { - vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 0), - vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 4), - vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 8), - vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 12) + vld1q_s32(reinterpret_cast<const int32_t *>(mm_result_it.ptr()) + 0), + vld1q_s32(reinterpret_cast<const int32_t *>(mm_result_it.ptr()) + 4), + vld1q_s32(reinterpret_cast<const int32_t *>(mm_result_it.ptr()) + 8), + vld1q_s32(reinterpret_cast<const int32_t *>(mm_result_it.ptr()) + 12) } }; @@ -256,39 +217,44 @@ void NEGEMMLowpOffsetContributionKernel::run(const Window &window, const ThreadI in_s32.val[3] = vaddq_s32(in_s32.val[3], offset_term_s32.val[3]); // Store the result with the offset contribution - vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 0, in_s32.val[0]); - vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 4, in_s32.val[1]); - vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 8, in_s32.val[2]); - vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 12, in_s32.val[3]); + vst1q_s32(reinterpret_cast<int32_t *>(mm_result_it.ptr()) + 0, in_s32.val[0]); + vst1q_s32(reinterpret_cast<int32_t *>(mm_result_it.ptr()) + 4, in_s32.val[1]); + vst1q_s32(reinterpret_cast<int32_t *>(mm_result_it.ptr()) + 8, in_s32.val[2]); + vst1q_s32(reinterpret_cast<int32_t *>(mm_result_it.ptr()) + 12, in_s32.val[3]); }, - vector_sum_col, vector_sum_row, mm_result); + vector_sum_col_it, vector_sum_row_it, mm_result_it); } - else if((_a_offset == 0) && (_b_offset != 0)) // false, true + 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(_vector_sum_row, win_vector_sum_row); - Iterator mm_result(_mm_result, window); + Iterator vector_sum_row_it(vector_sum_row, win_vector_sum_row); + Iterator mm_result_it(mm_result, window); - const size_t sum_row_stride_y = _vector_sum_row->info()->strides_in_bytes().y(); + const size_t sum_row_stride_y = vector_sum_row->info()->strides_in_bytes().y(); execute_window_loop(window, [&](const Coordinates & id) { + const int batch_id = id.z() / depth_input; + // Compute the leftover term due to b_offset. - int32x4_t b_offset_term_s32 = vld1q_dup_s32(reinterpret_cast<const int32_t *>(vector_sum_row.ptr() + id.z() * sum_row_stride_y) + id.y()); - b_offset_term_s32 = vmulq_n_s32(b_offset_term_s32, _b_offset); + int32x4_t b_offset_term_s32 = vld1q_dup_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 = vmulq_n_s32(b_offset_term_s32, b_offset); int32x4x4_t in_s32 = { { - vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 0), - vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 4), - vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 8), - vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 12) + vld1q_s32(reinterpret_cast<const int32_t *>(mm_result_it.ptr()) + 0), + vld1q_s32(reinterpret_cast<const int32_t *>(mm_result_it.ptr()) + 4), + vld1q_s32(reinterpret_cast<const int32_t *>(mm_result_it.ptr()) + 8), + vld1q_s32(reinterpret_cast<const int32_t *>(mm_result_it.ptr()) + 12) } }; @@ -299,51 +265,54 @@ void NEGEMMLowpOffsetContributionKernel::run(const Window &window, const ThreadI in_s32.val[3] = vaddq_s32(in_s32.val[3], b_offset_term_s32); // Store the result with the offset contribution - vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 0, in_s32.val[0]); - vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 4, in_s32.val[1]); - vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 8, in_s32.val[2]); - vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 12, in_s32.val[3]); + vst1q_s32(reinterpret_cast<int32_t *>(mm_result_it.ptr()) + 0, in_s32.val[0]); + vst1q_s32(reinterpret_cast<int32_t *>(mm_result_it.ptr()) + 4, in_s32.val[1]); + vst1q_s32(reinterpret_cast<int32_t *>(mm_result_it.ptr()) + 8, in_s32.val[2]); + vst1q_s32(reinterpret_cast<int32_t *>(mm_result_it.ptr()) + 12, in_s32.val[3]); }, - vector_sum_row, mm_result); + vector_sum_row_it, mm_result_it); } - else if((_a_offset != 0) && (_b_offset == 0)) // true, false + 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)); - if(!_slide_vector_sum_col) - { - win_vector_sum_col.set(Window::DimZ, Window::Dimension(0, 0, 0)); - } + win_vector_sum_col.set(Window::DimZ, Window::Dimension(0, 0, 0)); - Iterator vector_sum_col(_vector_sum_col, win_vector_sum_col); - Iterator mm_result(_mm_result, window); + Iterator vector_sum_col_it(vector_sum_col, win_vector_sum_col); + Iterator mm_result_it(mm_result, window); + + // 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(window, [&](const Coordinates & id) { + const int batch_id = id.z() / depth_input; + const auto vector_sum_col_ptr = reinterpret_cast<const int32_t *>(vector_sum_col_it.ptr() + batch_id * vector_sum_col_batch_offset); + // Compute the leftover term due to a_offset. int32x4x4_t a_offset_term_s32 = { { - vld1q_s32(reinterpret_cast<const int32_t *>(vector_sum_col.ptr()) + 0), - vld1q_s32(reinterpret_cast<const int32_t *>(vector_sum_col.ptr()) + 4), - vld1q_s32(reinterpret_cast<const int32_t *>(vector_sum_col.ptr()) + 8), - vld1q_s32(reinterpret_cast<const int32_t *>(vector_sum_col.ptr()) + 12) + vld1q_s32(vector_sum_col_ptr + 0), + vld1q_s32(vector_sum_col_ptr + 4), + vld1q_s32(vector_sum_col_ptr + 8), + vld1q_s32(vector_sum_col_ptr + 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); + 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(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 0), - vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 4), - vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 8), - vld1q_s32(reinterpret_cast<const int32_t *>(mm_result.ptr()) + 12) + vld1q_s32(reinterpret_cast<const int32_t *>(mm_result_it.ptr()) + 0), + vld1q_s32(reinterpret_cast<const int32_t *>(mm_result_it.ptr()) + 4), + vld1q_s32(reinterpret_cast<const int32_t *>(mm_result_it.ptr()) + 8), + vld1q_s32(reinterpret_cast<const int32_t *>(mm_result_it.ptr()) + 12) } }; @@ -354,12 +323,12 @@ void NEGEMMLowpOffsetContributionKernel::run(const Window &window, const ThreadI 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(reinterpret_cast<int32_t *>(mm_result.ptr()) + 0, in_s32.val[0]); - vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 4, in_s32.val[1]); - vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 8, in_s32.val[2]); - vst1q_s32(reinterpret_cast<int32_t *>(mm_result.ptr()) + 12, in_s32.val[3]); + vst1q_s32(reinterpret_cast<int32_t *>(mm_result_it.ptr()) + 0, in_s32.val[0]); + vst1q_s32(reinterpret_cast<int32_t *>(mm_result_it.ptr()) + 4, in_s32.val[1]); + vst1q_s32(reinterpret_cast<int32_t *>(mm_result_it.ptr()) + 8, in_s32.val[2]); + vst1q_s32(reinterpret_cast<int32_t *>(mm_result_it.ptr()) + 12, in_s32.val[3]); }, - vector_sum_col, mm_result); + vector_sum_col_it, mm_result_it); } else // false, false { @@ -367,3 +336,77 @@ void NEGEMMLowpOffsetContributionKernel::run(const Window &window, const ThreadI return; } } +} // namespace + +NEGEMMLowpOffsetContributionKernel::NEGEMMLowpOffsetContributionKernel() + : _vector_sum_col(nullptr), _vector_sum_row(nullptr), _mm_result(nullptr), _a_offset(0), _b_offset(0), _k_offset(0), _slide_vector_sum_col(true) +{ +} + +void NEGEMMLowpOffsetContributionKernel::configure(ITensor *mm_result, const ITensor *vector_sum_col, const ITensor *vector_sum_row, int32_t k, int32_t a_offset, int32_t b_offset) +{ + // Perform validate step + ARM_COMPUTE_ERROR_ON_NULLPTR(mm_result); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(mm_result->info(), + vector_sum_col != nullptr ? vector_sum_col->info() : nullptr, // NOLINT + vector_sum_row != nullptr ? vector_sum_row->info() : nullptr, // NOLINT + a_offset, b_offset)); // NOLINT + + _vector_sum_col = vector_sum_col; + _vector_sum_row = vector_sum_row; + _mm_result = mm_result; + _a_offset = a_offset; + _b_offset = b_offset; + _k_offset = a_offset * b_offset * k; + + // If a_offset == 0, vector_sum_col can be a nullptr + if(a_offset != 0) + { + // 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->info()->tensor_shape().num_dimensions() > 1; + } + + // Configure kernel window + auto win_config = validate_and_configure_window(mm_result->info(), + vector_sum_col != nullptr ? vector_sum_col->info() : nullptr, // NOLINT + vector_sum_row != nullptr ? vector_sum_row->info() : nullptr, // NOLINT + a_offset, b_offset); + ARM_COMPUTE_ERROR_THROW_ON(win_config.first); + INEKernel::configure(win_config.second); +} + +Status NEGEMMLowpOffsetContributionKernel::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)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(mm_result->clone().get(), + vector_sum_col != nullptr ? vector_sum_col->clone().get() : nullptr, + vector_sum_row != nullptr ? vector_sum_row->clone().get() : nullptr, + a_offset, b_offset) + .first); // NOLINT + + return Status{}; +} + +void NEGEMMLowpOffsetContributionKernel::run(const Window &window, const ThreadInfo &info) +{ + ARM_COMPUTE_UNUSED(info); + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); + + // 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(); + + if(reinterpret_as_3d) + { + run_offset_contribution<true>(window, _mm_result, _vector_sum_col, _vector_sum_row, _a_offset, _b_offset, _k_offset, _slide_vector_sum_col); + } + else + { + run_offset_contribution<false>(window, _mm_result, _vector_sum_col, _vector_sum_row, _a_offset, _b_offset, _k_offset, _slide_vector_sum_col); + } +}
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