// Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. #include "lite/kernels/huawei_ascend_npu/bridges/graph.h" #include "lite/kernels/huawei_ascend_npu/bridges/utility.h" #include "lite/kernels/npu/bridges/registry.h" namespace paddle { namespace lite { namespace subgraph { namespace huawei_ascend_npu { int MatMulConverter(void* ctx, OpLite* op, KernelBase* kernel) { CHECK(ctx != nullptr); CHECK(op != nullptr); auto graph = static_cast(ctx); auto op_info = op->op_info(); auto op_type = op_info->Type(); auto scope = op->scope(); VLOG(3) << "[HUAWEI_ASCEND_NPU] Converting " + op_type + "..."; // Get input and output vars and op attributes auto x_name = op_info->Input("X").front(); auto x = scope->FindTensor(x_name); auto x_dims = x->dims(); if (x_dims.size() < 2) { LOG(WARNING) << "[HUAWEI_ASCEND_NPU] Input dims should be equal or large " "than 2 in Huawei Ascend NPU DDK."; return FAILED; } auto y_name = op_info->Input("Y").front(); auto y = scope->FindTensor(y_name); auto y_dims = y->dims(); if (y_dims.size() < 2) { LOG(WARNING) << "[HUAWEI_ASCEND_NPU] Input dims should be equal or large " "than 2 in Huawei Ascend NPU DDK."; return FAILED; } if (x_dims.size() != y_dims.size()) { LOG(WARNING) << "[HUAWEI_ASCEND_NPU] dims size of input x1 and x2 must be " "same in Huawei Ascend NPU DDK."; return FAILED; } auto out_name = op_info->Output("Out").front(); auto out = scope->FindTensor(out_name); auto out_dims = out->dims(); bool transpose_x = op_info->GetAttr("transpose_X"); bool transpose_y = op_info->GetAttr("transpose_Y"); float alpha = op_info->GetAttr("alpha"); std::shared_ptr x_node = nullptr; if (graph->Has(x_name)) { x_node = graph->Get(x_name); } else { x_node = graph->Add(x_name, *x); } std::shared_ptr y_node = nullptr; if (graph->Has(y_name)) { y_node = graph->Get(y_name); } else { y_node = graph->Add(y_name, *y); } // Matmul node std::shared_ptr matmul_node = nullptr; if (x_dims.size() == 2) { matmul_node = graph->Add(out_name); auto matmul_op = matmul_node->data(); matmul_op->set_input_x1(*x_node->data()); matmul_op->set_input_x2(*y_node->data()); matmul_op->set_attr_transpose_x1(transpose_x); matmul_op->set_attr_transpose_x2(transpose_y); INPUT_UPDATE(matmul_op, x1, x_node); INPUT_UPDATE(matmul_op, x2, y_node); OUTPUT_UPDATE(matmul_op, y, matmul_node); } else { matmul_node = graph->Add(out_name); auto matmul_op = matmul_node->data(); matmul_op->set_input_x1(*x_node->data()); matmul_op->set_input_x2(*y_node->data()); matmul_op->set_attr_adj_x1(transpose_x); matmul_op->set_attr_adj_x2(transpose_y); INPUT_UPDATE(matmul_op, x1, x_node); INPUT_UPDATE(matmul_op, x2, y_node); OUTPUT_UPDATE(matmul_op, y, matmul_node); } if (fabs(alpha - 1.f) > 1e-6f) { auto scale_node = graph->Add(out_name); auto scale_op = scale_node->data(); scale_op->set_input_x(*matmul_node->data()); scale_op->set_attr_value(alpha); INPUT_UPDATE(scale_op, x, matmul_node); OUTPUT_UPDATE(scale_op, y, scale_node); } return REBUILD_WHEN_SHAPE_CHANGED; } } // namespace huawei_ascend_npu } // namespace subgraph } // namespace lite } // namespace paddle REGISTER_SUBGRAPH_BRIDGE( matmul, kHuaweiAscendNPU, paddle::lite::subgraph::huawei_ascend_npu::MatMulConverter);