/* * Licensed to the Apache Software Foundation (ASF) under one * or more contributor license agreements. See the NOTICE file * distributed with this work for additional information * regarding copyright ownership. The ASF licenses this file * to you 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. */ /*! * Copyright (c) 2018 by Contributors * \file yolo.cc * \brief Yolo related operators */ #include <tvm/relay/op.h> #include <tvm/relay/attrs/vision.h> #include <topi/vision/reorg.h> #include <vector> #include "../op_common.h" #include "../type_relations.h" namespace tvm { namespace relay { TVM_REGISTER_NODE_TYPE(YoloReorgAttrs); /*! * \brief YoloReorgRel Output type and shape relation evaluation function. * \param num_inputs Number of input types in the args. * \param attrs The additional attributes of the operator. * \param reporter The reporter to report solution to. * \return false if This relation cannot be resolved. true if this relation has been resolved. */ bool YoloReorgRel(const Array<Type>& types, int num_inputs, const Attrs& attrs, const TypeReporter& reporter) { CHECK_EQ(types.size(), 2); const auto* data = types[0].as<TensorTypeNode>(); if (data == nullptr) return false; const YoloReorgAttrs* param = attrs.as<YoloReorgAttrs>(); CHECK(param != nullptr); CHECK(data->shape.size() == 4) << "Yolo reorg supports only 4 dimension."; std::vector<IndexExpr> oshape(data->shape.begin(), data->shape.end()); oshape[1] = oshape[1] * param->stride * param->stride; oshape[2] = indexdiv(oshape[2], param->stride); oshape[3] = indexdiv(oshape[3], param->stride); reporter->Assign(types[1], TensorTypeNode::make(oshape, data->dtype)); return true; } Expr MakeYoloReorg(Expr data, Integer stride) { auto attrs = make_node<YoloReorgAttrs>(); attrs->stride = stride; static const Op& op = Op::Get("vision.yolo_reorg"); return CallNode::make(op, {data}, Attrs(attrs), {}); } TVM_REGISTER_API("relay.op.vision._make.yolo_reorg") .set_body_typed(MakeYoloReorg); RELAY_REGISTER_OP("vision.yolo_reorg") .describe(R"doc("Yolo reorg operation. This layer reorganize the output. Its function is mostly shape transform.")doc" TVM_ADD_FILELINE) .add_argument("data", "Tensor", "The input tensor.") .set_num_inputs(1) .set_support_level(5) .set_attrs_type_key("relay.attrs.YoloReorgAttrs") .add_type_rel("YoloReorg", YoloReorgRel) .set_attr<FTVMCompute>("FTVMCompute", [](const Attrs& attrs, const Array<Tensor>& inputs, const Type& out_type, const Target& target) { const auto* params = attrs.as<YoloReorgAttrs>(); CHECK(params != nullptr); return Array<Tensor>{ topi::vision::reorg(inputs[0], params->stride) }; }); } // namespace relay } // namespace tvm