| // Tencent is pleased to support the open source community by making ncnn available. | |
| // | |
| // Copyright (C) 2021 THL A29 Limited, a Tencent company. All rights reserved. | |
| // | |
| // Licensed under the BSD 3-Clause License (the "License"); you may not use this file except | |
| // in compliance with the License. You may obtain a copy of the License at | |
| // | |
| // https://opensource.org/licenses/BSD-3-Clause | |
| // | |
| // 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. | |
| namespace pnnx { | |
| class Embedding : public FuseModulePass | |
| { | |
| public: | |
| const char* match_type_str() const | |
| { | |
| return "__torch__.torch.nn.modules.sparse.Embedding"; | |
| } | |
| const char* type_str() const | |
| { | |
| return "nn.Embedding"; | |
| } | |
| void write(Operator* op, const std::shared_ptr<torch::jit::Graph>& graph, const torch::jit::Module& mod) const | |
| { | |
| const torch::jit::Node* embedding = find_node_by_kind(graph, "aten::embedding"); | |
| const auto& weight = mod.attr("weight").toTensor(); | |
| op->params["num_embeddings"] = weight.size(0); | |
| op->params["embedding_dim"] = weight.size(1); | |
| // op->params["padding_idx"] = embedding->namedInput("padding_idx"); | |
| // op->params["scale_grad_by_freq"] = embedding->namedInput("scale_grad_by_freq"); | |
| op->params["sparse"] = embedding->namedInput("sparse"); | |
| op->attrs["weight"] = weight; | |
| } | |
| }; | |
| REGISTER_GLOBAL_PNNX_FUSE_MODULE_PASS(Embedding) | |
| } // namespace pnnx | |