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From GitBox <...@apache.org>
Subject [GitHub] ZhennanQin commented on a change in pull request #12530: Implement mkldnn convolution fusion and quantization.
Date Wed, 26 Sep 2018 04:14:07 GMT
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 &param = 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 &param = 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.

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