// 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. #include "pass_ncnn.h" namespace pnnx { namespace ncnn { class nn_Embedding : public GraphRewriterPass { public: const char* match_pattern_graph() const { return R"PNNXIR(7767517 3 2 pnnx.Input input 0 1 input nn.Embedding op_0 1 1 input out embedding_dim=%embedding_dim num_embeddings=%num_embeddings sparse=False @weight pnnx.Output output 1 0 out )PNNXIR"; } const char* type_str() const { return "Embed"; } const char* name_str() const { return "embed"; } void write(Operator* op, const std::map& captured_params, const std::map& captured_attrs) const { op->params["0"] = captured_params.at("embedding_dim"); op->params["1"] = captured_params.at("num_embeddings"); op->params["2"] = 0; op->params["3"] = (int)(captured_attrs.at("op_0.weight").data.size() / sizeof(float)); op->attrs["0"] = Attribute(); op->attrs["0"].data = {0, 0, 0, 0}; op->attrs["1"] = captured_attrs.at("op_0.weight"); } }; REGISTER_GLOBAL_PNNX_NCNN_GRAPH_REWRITER_PASS(nn_Embedding, 20) } // namespace ncnn } // namespace pnnx