ZhennanQin commented on a change in pull request #12530: Implement mkldnn convolution fusion and quantization. URL: https://github.com/apache/incubator-mxnet/pull/12530#discussion_r220422029
########## File path: src/operator/subgraph/mkldnn/mkldnn_conv_post_quantize_property.cc ########## @@ -0,0 +1,163 @@ +/* + * 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. + */ + +#if MXNET_USE_MKLDNN == 1 + +#include "../common.h" +#include "../subgraph_property.h" +#include "../../nn/mkldnn/mkldnn_convolution-inl.h" +#include "mkldnn_conv-inl.h" +#include "../../quantization/requantize-inl.h" + +namespace mxnet { +namespace op { + +class SgMKLDNNConvPostQuantizeSelector : public SubgraphSelector { + public: + /*! \brief pattern match status */ + enum SelectStatus { + kFail = 0, + kStart, + kSuccess, + }; + + private: + bool disable_all; + SelectStatus status; + std::vector<const nnvm::Node *> matched_list; + + public: + explicit SgMKLDNNConvPostQuantizeSelector(int dis_all) + : disable_all(dis_all) {} + + bool Select(const nnvm::Node &n) override { + if ((!disable_all) && n.op() && n.op()->name == "_sg_mkldnn_conv") { + auto const ¶m = nnvm::get<MKLDNNConvFusionParam>(n.attrs.parsed); + if (param.full_conv_param.mkldnn_param.quantized) { + status = kStart; + matched_list.clear(); + matched_list.push_back(&n); + return true; + } + } + return false; + } + + bool SelectInput(const nnvm::Node &n, const nnvm::Node &new_node) override { + return false; + } + + bool SelectOutput(const nnvm::Node &n, const nnvm::Node &new_node) override { + if (status == kFail || status == kSuccess || new_node.is_variable()) + return false; + // If n isn't the last matched node, then we encoutered a internal + // branch, we should pop out the node behind n and stop fusion. + if (matched_list.back() != &n) { + status = kFail; + return false; + } + if (new_node.op()->name == "_contrib_requantize") { + auto const ¶m = nnvm::get<RequantizeParam>(new_node.attrs.parsed); + if (param.min_calib_range.has_value() && + param.max_calib_range.has_value()) { + matched_list.push_back(&new_node); + status = kSuccess; + return true; + } else { + status = kFail; + } + } + return false; + } + + std::vector<nnvm::Node *> Filter( + const std::vector<nnvm::Node *> &candidates) override { + if (status != kSuccess) { + return std::vector<nnvm::Node *>(0); + } else { + return candidates; + } + } +}; + +class SgMKLDNNConvPostQuantizeProperty : public SubgraphProperty { + public: + SgMKLDNNConvPostQuantizeProperty() { + disable_all = dmlc::GetEnv("MXNET_DISABLE_MKLDNN_OPT", 0); + if (disable_all) { + LOG(INFO) << "MKLDNN Convolution post-quantization optimization pass is disabled."; + } else { + LOG(INFO) << "Start to execute MKLDNN Convolution post-quantization optimization pass."; + } + } + static SubgraphPropertyPtr Create() { + return std::make_shared<SgMKLDNNConvPostQuantizeProperty>(); + } + nnvm::NodePtr CreateSubgraphNode(const nnvm::Symbol &sym, + const int subgraph_id = 0) const override { + nnvm::NodePtr conv_node = nullptr; + nnvm::NodePtr requantize_node = nullptr; + DFSVisit(sym.outputs, [&](const nnvm::NodePtr &node) { + if (node->is_variable()) return; + auto &op_name = node->op()->name; + if (op_name == "_sg_mkldnn_conv") { + conv_node = node; + } else if (op_name == "_contrib_requantize") { + requantize_node = node; + } + }); + CHECK_NOTNULL(conv_node); + CHECK_NOTNULL(requantize_node); + auto const &requantize_param = + nnvm::get<RequantizeParam>(requantize_node->attrs.parsed); + CHECK(requantize_param.min_calib_range.has_value()); + CHECK(requantize_param.max_calib_range.has_value()); + conv_node->attrs.dict["min_calib_range"] = + std::to_string(requantize_param.min_calib_range.value()); + conv_node->attrs.dict["max_calib_range"] = + std::to_string(requantize_param.max_calib_range.value()); + conv_node->op()->attr_parser(&(conv_node->attrs)); + return conv_node; + } + + SubgraphSelectorPtr CreateSubgraphSelector() const override { + auto selector = + std::make_shared<SgMKLDNNConvPostQuantizeSelector>(disable_all); + return selector; + } + + void ConnectSubgraphOutput( + const nnvm::NodePtr n, + std::vector<nnvm::NodeEntry *> *output_entries) const override { + for (size_t i = 0; i < output_entries->size(); ++i) { + auto entry_ptr = output_entries->at(i); + *entry_ptr = nnvm::NodeEntry{n, entry_ptr->index, 0}; Review comment: For this case, n is _sg_mkldnn_conv, and entry_ptr->node is the followed requantize op. This is a customized version for this certain fusion pass, as _sg_mkldnn_conv has same output sequence(output, output_min, output_max) as requantize. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
