refine/fc lstm fusion link (#13158)

paddle/fluid/framework/ir/fc_lstm_fuse_pass.cc

@@ -13,37 +13,37 @@
 // limitations under the License.
 
 #include "paddle/fluid/framework/ir/fc_lstm_fuse_pass.h"
+#include "paddle/fluid/framework/lod_tensor.h"
 
 namespace paddle {
 namespace framework {
 namespace ir {
 
-std::unique_ptr<ir::Graph> FCLstmFusePass::ApplyImpl(
-    std::unique_ptr<ir::Graph> graph) const {
-  GraphPatternDetector gpd;
-  auto* pattern = gpd.mutable_pattern();
-
-  std::unordered_set<int> fused_ops({// first lstm
-                                     13, 15, 16,
-                                     // second lstm
-                                     23, 25, 26});
-
-  pattern->NewNode([&](Node* x) { return fused_ops.count(x->id()); },
-                   "any_node");
+std::string GenNodeName(const std::string& prefix, const std::string& name) {
+  return prefix + "/" + name;
+}
 
-  std::unordered_set<Node*> marked_nodes;
+void BuildPattern(PDPattern* pattern, const std::string& name_scope,
+                  bool with_fc_bias) {
+  PDNode* x = pattern->NewNode(name_scope, "x")
+                  ->assert_is_op_input("mul")
+                  ->assert_var_not_persistable();
+  auto* fc_out = patterns::FC(pattern, name_scope, x, with_fc_bias);
+  fc_out->AsIntermediate();  // fc_out is a tmp var, will be removed after fuse.
+  patterns::LSTM(pattern, name_scope, fc_out);
+  // LOG(INFO) << "\n" << pattern->DotString();
+}
 
-  auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph,
-                     Graph* g) {
+int BuildFusion(Graph* graph, const std::string& name_scope, Scope* scope,
+                bool with_fc_bias) {
+  GraphPatternDetector gpd;
+  auto* pattern = gpd.mutable_pattern();
 
-    auto* id = subgraph.at(gpd.pattern().RetrieveNode("any_node"));
-    marked_nodes.insert(id);
-  };
-  gpd(graph.get(), handler);
+  BuildPattern(pattern, name_scope, with_fc_bias);
 
   // Create New OpDesc
   auto lstm_creator = [&](int lstm, int input, int weight_x, int weight_h,
-                          int bias, int hidden, int cell, int xx) {
+                          int bias, int hidden, int cell, int xx, int fc_bias) {
 #define GET_NODE(x) auto* x##_n = graph->RetriveNode(x);
     GET_NODE(input);
     GET_NODE(weight_x);
@@ -61,12 +61,33 @@ std::unique_ptr<ir::Graph> FCLstmFusePass::ApplyImpl(
     SET_IN(WeightX, weight_x);
     SET_IN(WeightH, weight_h);
     SET_IN(Bias, bias);
-#undef GET_NODE
 #undef SET_IN
+    if (with_fc_bias) {
+      // Add FC-bias with LSTM-bias and create a new weight
+      PADDLE_ENFORCE(scope);
+      const std::string& new_bias_var = name_scope + "_bias.new";
+      auto* bias_var = scope->Var(new_bias_var);
+      PADDLE_ENFORCE(bias_var);
+      auto* bias_tensor = bias_var->GetMutable<framework::LoDTensor>();
+      auto* lstm_bias_var = scope->FindVar(bias_n->Name());
+      PADDLE_ENFORCE(lstm_bias_var);
+      const auto& lstm_bias_tensor = lstm_bias_var->Get<framework::LoDTensor>();
+      bias_tensor->Resize(lstm_bias_tensor.dims());
+
+      GET_NODE(fc_bias);
+      auto* fc_bias_var = scope->FindVar(fc_bias_n->Name());
+      const auto& fc_bias_tensor = fc_bias_var->Get<framework::LoDTensor>();
+
+      auto* data = bias_tensor->mutable_data<float>(platform::CPUPlace());
+
+      for (int i = 0; i < bias_tensor->numel(); i++) {
+        data[i] =
+            fc_bias_tensor.data<float>()[i] + lstm_bias_tensor.data<float>()[i];
+      }
+      op_desc.SetInput("Bias", {new_bias_var});
+    }
 
-    VLOG(4) << "hidden_n: " << hidden_n->Name();
-    VLOG(4) << "cell: " << cell_n->Name();
-    VLOG(4) << "xx: " << xx_n->Name();
+#undef GET_NODE
 
     op_desc.SetInput("H0", {});
     op_desc.SetInput("C0", {});
@@ -76,7 +97,7 @@ std::unique_ptr<ir::Graph> FCLstmFusePass::ApplyImpl(
     op_desc.SetOutput("BatchedGate", {"blstm_0.tmp_2"});
     op_desc.SetOutput("BatchCellPreAct", {"blstm_1.tmp_2"});
     op_desc.SetAttr("is_reverse", lstm_n->Op()->GetAttr("is_reverse"));
-    op_desc.SetAttr("use_peepholes", false);
+    op_desc.SetAttr("use_peepholes", lstm_n->Op()->GetAttr("use_peepholes"));
     auto* op = graph->CreateOpNode(&op_desc);
 
 #define LINK_TO(a, b)      \
@@ -89,33 +110,71 @@ std::unique_ptr<ir::Graph> FCLstmFusePass::ApplyImpl(
     LINK_TO(op, hidden_n);
 #undef LINK_TO
     return op;
-
   };
 
-  lstm_creator(16, 12, 14, 18, 17, 22, 21, 19);
-  lstm_creator(26, 12, 24, 28, 27, 32, 31, 29);
+  int fusion_count{0};
 
-  // remove all the nodes
+  auto fc_no_bias_handler = [&](
+      const GraphPatternDetector::subgraph_t& subgraph, Graph* g) {
 
-  for (auto* node : marked_nodes) {
-    graph->RemoveNode(const_cast<Node*>(node));
-  }
+#define GET_NODE(name__)                                \
+  std::string name__##key = name_scope + "/" + #name__; \
+  auto* name__##n = pattern->RetrieveNode(name__##key); \
+  PADDLE_ENFORCE(name__##n);                            \
+  PADDLE_ENFORCE(subgraph.count(name__##n));            \
+  Node* name__##_n = subgraph.at(name__##n);            \
+  int name__ __attribute__((unused)) = name__##_n->id();
 
-  for (auto* node : graph->Nodes()) {
-    for (auto it = node->inputs.begin(); it != node->inputs.end();) {
-      if (marked_nodes.count(*it)) {
-        it = const_cast<Node*>(node)->inputs.erase(it);
-      } else
-        it++;
-    }
-    for (auto it = node->outputs.begin(); it != node->outputs.end();) {
-      if (marked_nodes.count(*it)) {
-        it = const_cast<Node*>(node)->outputs.erase(it);
-      } else
-        it++;
+    GET_NODE(x);
+    GET_NODE(w);
+    GET_NODE(mul);
+    GET_NODE(fc_out);
+    GET_NODE(Weight);
+    GET_NODE(lstm);
+    GET_NODE(Bias);
+    GET_NODE(Hidden);
+    GET_NODE(Cell);
+
+    if (with_fc_bias) {
+      GET_NODE(fc_bias);
+      lstm_creator(lstm, x, w, Weight, Bias, Hidden, Cell, fc_out, fc_bias);
+    } else {
+      lstm_creator(lstm, x, w, Weight, Bias, Hidden, Cell, fc_out, -1);
     }
-  }
+#undef GET_NODE
+
+    // Remove unneeded nodes.
+    std::unordered_set<const Node*> marked_nodes({mul_n, lstm_n});
+
+    GraphSafeRemoveNodes(graph, marked_nodes);
+
+    ++fusion_count;
+  };
+
+  gpd(graph, fc_no_bias_handler);
+
+  return fusion_count;
+}
+
+std::unique_ptr<ir::Graph> MulLstmFusePass::ApplyImpl(
+    std::unique_ptr<ir::Graph> graph) const {
+  FusePassBase::Init(name_scope_, graph.get());
+
+  int fusion_count = BuildFusion(graph.get(), name_scope_, param_scope(),
+                                 false /*with_fc_bias*/);
+
+  AddStatis(fusion_count);
+  return graph;
+}
+
+std::unique_ptr<ir::Graph> FCLstmFusePass::ApplyImpl(
+    std::unique_ptr<ir::Graph> graph) const {
+  FusePassBase::Init(name_scope_, graph.get());
+
+  int fusion_count = BuildFusion(graph.get(), name_scope_, param_scope(),
+                                 true /*with_fc_bias*/);
 
+  AddStatis(fusion_count);
   return graph;
 }
 
@@ -123,4 +182,5 @@ std::unique_ptr<ir::Graph> FCLstmFusePass::ApplyImpl(
 }  // namespace framework
 }  // namespace paddle
 
+REGISTER_PASS(mul_lstm_fuse_pass, paddle::framework::ir::MulLstmFusePass);
 REGISTER_PASS(fc_lstm_fuse_pass, paddle::framework::ir::FCLstmFusePass);

paddle/fluid/framework/ir/fc_lstm_fuse_pass.h

@@ -12,20 +12,34 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
+#include "paddle/fluid/framework/ir/fuse_pass_base.h"
 #include "paddle/fluid/framework/ir/graph.h"
 #include "paddle/fluid/framework/ir/graph_pattern_detector.h"
-#include "paddle/fluid/framework/ir/pass.h"
 
 namespace paddle {
 namespace framework {
 namespace ir {
 
-class FCLstmFusePass : public Pass {
+// The MulLstmFusePass and MulLstmFusePass will fuse to the same FusionLstm op.
+
+// Just FC without bias
+class FCLstmFusePass : public FusePassBase {
  public:
   virtual ~FCLstmFusePass() {}
 
  protected:
   std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
+
+  const std::string name_scope_{"fc_lstm_fuse"};
+};
+
+class MulLstmFusePass : public FusePassBase {
+ public:
+  virtual ~MulLstmFusePass() {}
+
+ protected:
+  std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
+  const std::string name_scope_{"fc_nobias_lstm_fuse"};
 };
 
 }  // namespace ir

paddle/fluid/framework/ir/graph_pattern_detector.cc

@@ -19,6 +19,7 @@
 #include "paddle/fluid/framework/ir/graph_helper.h"
 #include "paddle/fluid/framework/ir/graph_pattern_detector.h"
 #include "paddle/fluid/framework/ir/graph_traits.h"
+#include "paddle/fluid/framework/ir/graph_viz_pass.h"
 #include "paddle/fluid/platform/enforce.h"
 
 namespace paddle {
@@ -71,7 +72,11 @@ void PDPattern::AddEdge(PDNode* a, PDNode* b) {
 
 void GraphPatternDetector::operator()(Graph* graph,
                                       GraphPatternDetector::handle_t handler) {
-  if (!MarkPDNodesInGraph(*graph)) return;
+  if (!MarkPDNodesInGraph(*graph)) {
+    LOG(INFO) << "Mark failed";
+    return;
+  }
+
   auto subgraphs = DetectPatterns();
   UniquePatterns(&subgraphs);
   RemoveOverlappedMatch(&subgraphs);
@@ -87,7 +92,7 @@ void GraphPatternDetector::operator()(Graph* graph,
 }
 
 bool GraphPatternDetector::MarkPDNodesInGraph(const ir::Graph& graph) {
-  VLOG(4) << "mark pdnodes in graph";
+  VLOG(3) << "mark pdnodes in graph";
   if (graph.Nodes().empty()) return false;
 
   for (auto& node : GraphTraits::DFS(graph)) {
@@ -107,6 +112,7 @@ bool GraphPatternDetector::MarkPDNodesInGraph(const ir::Graph& graph) {
     }
   }
   VLOG(3) << pdnodes2nodes_.size() << " nodes marked";
+
   return !pdnodes2nodes_.empty();
 }
 
@@ -357,7 +363,9 @@ PDNode* PDNode::assert_is_op_nth_input(const std::string& op_type,
   assert_is_op_input(op_type);
   asserts_.emplace_back([=](Node* x) {
     for (auto* op : x->outputs) {
-      if (IsNthInput(x, op, argument, nth)) return true;
+      if (op->IsOp() && op->Op()->Type() == op_type &&
+          IsNthInput(x, op, argument, nth))
+        return true;
     }
     return false;
   });
@@ -368,7 +376,9 @@ PDNode* PDNode::assert_is_op_nth_output(const std::string& op_type,
   assert_is_var();
   asserts_.emplace_back([=](Node* x) {
     for (auto* op : x->inputs) {
-      if (IsNthOutput(x, op, argument, nth)) return true;
+      if (op->IsOp() && op->Op()->Type() == op_type &&
+          IsNthOutput(x, op, argument, nth))
+        return true;
     }
     return false;
   });
@@ -412,6 +422,12 @@ PDNode* PDNode::assert_is_op_output(const std::string& op_type) {
   });
   return this;
 }
+PDNode* PDNode::assert_is_op_output(const std::string& op_type,
+                                    const std::string& argument) {
+  assert_is_var();
+  assert_is_op_nth_output(op_type, argument, 0);
+  return this;
+}
 PDNode* PDNode::assert_is_op_input(const std::string& op_type) {
   assert_is_var();
   asserts_.emplace_back([=](Node* x) {
@@ -424,6 +440,12 @@ PDNode* PDNode::assert_is_op_input(const std::string& op_type) {
   });
   return this;
 }
+PDNode* PDNode::assert_is_op_input(const std::string& op_type,
+                                   const std::string& argument) {
+  assert_is_var();
+  assert_is_op_nth_input(op_type, argument, 0);
+  return this;
+}
 PDNode* PDNode::assert_op_has_n_inputs(const std::string& op_type, size_t n) {
   assert_is_op(op_type);
   asserts_.emplace_back([=](Node* x) { return x->inputs.size() == n; });
@@ -439,6 +461,128 @@ PDNode* PDNode::assert_more(PDNode::teller_t&& teller) {
   return this;
 }
 
+bool VarLinksToOp(Node* node, const std::string& op_type) {
+  for (auto* out : node->outputs) {
+    if (out->IsOp() && out->Op()->Type() == op_type) {
+      return true;
+    }
+  }
+  return false;
+}
+bool IsNthInput(Node* var, Node* op, const std::string& argument, size_t nth) {
+  PADDLE_ENFORCE(var->IsVar());
+  PADDLE_ENFORCE(op->IsOp());
+  if (op->Op()->Input(argument).size() <= nth) return false;
+  return var->Name() == op->Op()->Input(argument)[nth];
+}
+bool IsNthOutput(Node* var, Node* op, const std::string& argument, size_t nth) {
+  PADDLE_ENFORCE(var->IsVar());
+  PADDLE_ENFORCE(op->IsOp());
+  if (op->Op()->Output(argument).size() <= nth) return false;
+  return var->Name() == op->Op()->Output(argument)[nth];
+}
+void GraphSafeRemoveNodes(Graph* graph,
+                          const std::unordered_set<const Node*>& nodes) {
+  for (auto* node : nodes) {
+    graph->RemoveNode(const_cast<Node*>(node));
+  }
+
+  for (auto* node : graph->Nodes()) {
+    for (auto it = node->inputs.begin(); it != node->inputs.end();) {
+      if (nodes.count(*it)) {
+        it = const_cast<Node*>(node)->inputs.erase(it);
+      } else
+        it++;
+    }
+    for (auto it = node->outputs.begin(); it != node->outputs.end();) {
+      if (nodes.count(*it)) {
+        it = const_cast<Node*>(node)->outputs.erase(it);
+      } else
+        it++;
+    }
+  }
+}
+bool VarLinksFromOp(Node* node, const std::string& op_type) {
+  for (auto* out : node->inputs) {
+    if (out->IsOp() && out->Op()->Type() == op_type) {
+      return true;
+    }
+  }
+  return false;
+}
+
+PDNode* patterns::FC(PDPattern* pattern, const std::string& name_scope,
+                     PDNode* x, bool with_bias) {
+  // Create Operators
+  PDNode* elementwise_add_op{nullptr};
+  auto* mul_op = pattern->NewNode(name_scope, "mul")->assert_is_op("mul");
+  if (with_bias) {
+    elementwise_add_op = pattern->NewNode(name_scope, "elementwise_add")
+                             ->assert_is_op("elementwise_add");
+  }
+  // Create variables
+  // w
+  auto* mul_weight_var = pattern->NewNode(name_scope, "w")
+                             ->AsInput()
+                             ->assert_is_persistable_var()
+                             ->assert_is_op_nth_input("mul", "Y", 0);
+  PDNode* mul_out_var{nullptr};
+  if (with_bias) {
+    // intermediate variable, will be removed in the IR after fuse.
+    mul_out_var = pattern->NewNode(name_scope, "mul_out")
+                      ->AsIntermediate()
+                      ->assert_is_only_output_of_op("mul")
+                      ->assert_is_op_input("elementwise_add");
+  }
+  PDNode *bias{nullptr}, *fc_out{nullptr};
+  if (with_bias) {
+    // bias
+    bias = pattern->NewNode(name_scope, "fc_bias")
+               ->assert_is_op_input("elementwise_add")
+               ->AsInput();
+    // output
+    fc_out = pattern->NewNode(name_scope, "fc_out")
+                 ->AsOutput()
+                 ->assert_is_op_output("elementwise_add");
+  } else {
+    fc_out = pattern->NewNode(name_scope, "fc_out")
+                 ->AsOutput()
+                 ->assert_is_op_output("mul");
+  }
+
+  if (with_bias) {
+    mul_op->LinksFrom({mul_weight_var, x}).LinksTo({mul_out_var});
+    elementwise_add_op->LinksFrom({mul_out_var, bias}).LinksTo({fc_out});
+  } else {
+    mul_op->LinksFrom({mul_weight_var, x}).LinksTo({fc_out});
+  }
+
+  return fc_out;
+}
+PDNode* patterns::LSTM(PDPattern* pattern, const std::string& name_scope,
+                       PDNode* x) {
+  x->assert_is_op_input("lstm", "Input");
+  auto* lstm_op = pattern->NewNode(name_scope, "lstm")->assert_is_op("lstm");
+#define NEW_NODE(arg__, io__)                        \
+  auto* arg__ = pattern->NewNode(name_scope, #arg__) \
+                    ->assert_is_op_##io__("lstm", #arg__);
+
+  // Currently, the H0 and C0 are optional
+  // TODO(Superjomn) upgrade the fuse framework to support optional.
+  // NEW_NODE(H0, input);
+  // NEW_NODE(C0, input);
+  NEW_NODE(Weight, input);
+  NEW_NODE(Bias, input);
+
+  NEW_NODE(Hidden, output);
+  NEW_NODE(Cell, output);
+  NEW_NODE(BatchGate, output);
+  NEW_NODE(BatchCellPreAct, output);
+
+  lstm_op->LinksFrom({x, Weight, Bias});
+  lstm_op->LinksTo({Hidden, Cell, BatchGate, BatchCellPreAct});
+  return Hidden;
+}
 }  // namespace ir
 }  // namespace framework
 }  // namespace paddle

paddle/fluid/framework/ir/graph_pattern_detector.h

@@ -95,7 +95,11 @@ struct PDNode {
   PDNode* assert_var_not_persistable();
   PDNode* assert_is_persistable_var();
   PDNode* assert_is_op_output(const std::string& op_type);
+  PDNode* assert_is_op_output(const std::string& op_type,
+                              const std::string& argument);
   PDNode* assert_is_op_input(const std::string& op_type);
+  PDNode* assert_is_op_input(const std::string& op_type,
+                             const std::string& argument);
   PDNode* assert_is_op_nth_input(const std::string& op_type,
                                  const std::string& argument, int nth);
   PDNode* assert_is_op_nth_output(const std::string& op_type,
@@ -167,6 +171,9 @@ class PDPattern {
 
   PDNode* NewNode(PDNode::teller_t&& teller, const std::string& name = NewID());
   PDNode* NewNode(const std::string& name = NewID());
+  PDNode* NewNode(const std::string& prefix, const std::string& name) {
+    return NewNode(prefix + "/" + name);
+  }
   PDNode* RetrieveNode(const std::string& id) const;
 
   const std::vector<std::unique_ptr<PDNode>>& nodes() const { return nodes_; }
@@ -257,64 +264,36 @@ class GraphPatternDetector {
 
 // some helper methods.
 
-// Op's input.
-static bool VarLinksToOp(Node* node, const std::string& op_type) {
-  for (auto* out : node->outputs) {
-    if (out->IsOp() && out->Op()->Type() == op_type) {
-      return true;
-    }
-  }
-  return false;
-}
-
-// Op's output.
-static bool VarLinksFromOp(Node* node, const std::string& op_type) {
-  for (auto* out : node->inputs) {
-    if (out->IsOp() && out->Op()->Type() == op_type) {
-      return true;
-    }
-  }
-  return false;
-}
+// Tell if a var links to an Op
+bool VarLinksToOp(Node* node, const std::string& op_type);
+
+// Tell if an op links to a var
+bool VarLinksFromOp(Node* node, const std::string& op_type);
 
 // Check whether a var node is a op node's nth input.
-static bool IsNthInput(Node* var, Node* op, const std::string& argument,
-                       size_t nth) {
-  PADDLE_ENFORCE(var->IsVar());
-  PADDLE_ENFORCE(op->IsOp());
-  if (op->inputs.size() <= nth) return false;
-  return var->Name() == op->Op()->Input(argument)[nth];
-}
-
-static bool IsNthOutput(Node* var, Node* op, const std::string& argument,
-                        size_t nth) {
-  PADDLE_ENFORCE(var->IsVar());
-  PADDLE_ENFORCE(op->IsOp());
-  if (op->inputs.size() <= nth) return false;
-  return var->Name() == op->Op()->Output(argument)[nth];
-}
-
-static void GraphSafeRemoveNodes(Graph* graph,
-                                 const std::unordered_set<const Node*>& nodes) {
-  for (auto* node : nodes) {
-    graph->RemoveNode(const_cast<Node*>(node));
-  }
+bool IsNthInput(Node* var, Node* op, const std::string& argument, size_t nth);
 
-  for (auto* node : graph->Nodes()) {
-    for (auto it = node->inputs.begin(); it != node->inputs.end();) {
-      if (nodes.count(*it)) {
-        it = const_cast<Node*>(node)->inputs.erase(it);
-      } else
-        it++;
-    }
-    for (auto it = node->outputs.begin(); it != node->outputs.end();) {
-      if (nodes.count(*it)) {
-        it = const_cast<Node*>(node)->outputs.erase(it);
-      } else
-        it++;
-    }
-  }
-}
+// Tell whether a var node is a op node's nth output.
+bool IsNthOutput(Node* var, Node* op, const std::string& argument, size_t nth);
+
+// Graph safely remove some nodes, will automatically clean up the edges.
+void GraphSafeRemoveNodes(Graph* graph,
+                          const std::unordered_set<const Node*>& nodes);
+
+// Some pre-defined patterns those can be reused in multiple passes.
+namespace patterns {
+
+// FC with bias
+// op: mul + elementwise_add
+// named nodes:
+// mul, elementwise_add
+// w, mul_out, bias, fc_out
+PDNode* FC(PDPattern* pattern, const std::string& name_scope, PDNode* x,
+           bool with_bias);
+
+PDNode* LSTM(PDPattern* pattern, const std::string& name_scope, PDNode* x);
+
+}  // namespace patterns
 
 }  // namespace ir
 }  // namespace framework

paddle/fluid/framework/ir/graph_viz_pass.h

@@ -42,6 +42,13 @@ class GraphVizPass : public Pass {
   marked_nodes_t ConsumeMarkedNodes(Graph* graph) const;
 };
 
+static GraphVizPass::marked_nodes_t& GetMarkedNodes(Graph* graph) {
+  if (!graph->Has(kGraphvizMarkedNodeAttr)) {
+    graph->Set(kGraphvizMarkedNodeAttr, new GraphVizPass::marked_nodes_t);
+  }
+  return graph->Get<GraphVizPass::marked_nodes_t>(kGraphvizMarkedNodeAttr);
+}
+
 }  // namespace ir
 }  // namespace framework
 }  // namespace paddle

paddle/fluid/inference/analysis/analyzer.cc

@@ -109,6 +109,7 @@ void Analyzer::Run(Argument* argument) {
                     "infer_clean_graph_pass", "graph_viz_pass",    //
                     "attention_lstm_fuse_pass", "graph_viz_pass",  //
                     "fc_lstm_fuse_pass", "graph_viz_pass",         //
+                    "mul_lstm_fuse_pass", "graph_viz_pass",        //
                     "seq_concat_fc_fuse_pass", "graph_viz_pass",   //
                     "fc_fuse_pass", "graph_viz_pass"               //
 

paddle/fluid/inference/analysis/analyzer_tester.cc

@@ -329,6 +329,7 @@ void TestDituRNNPrediction(const std::string &model_path,
 
     ASSERT_TRUE(fuse_statis.count("fc"));
     EXPECT_EQ(fuse_statis.at("fc"), 1);
+    EXPECT_EQ(fuse_statis.at("fc_nobias_lstm_fuse"), 1);
   }
 }