[cherry-pick] map matmul/squeeze2+matmul/reshape2+matmul to mul #29911 (#29980)

paddle/fluid/framework/ir/CMakeLists.txt

@@ -60,6 +60,7 @@ pass_library(graph_to_program_pass base)
 pass_library(graph_viz_pass base)
 pass_library(lock_free_optimize_pass base)
 pass_library(fc_fuse_pass inference)
+pass_library(map_matmul_to_mul_pass inference)
 pass_library(attention_lstm_fuse_pass inference)
 pass_library(fc_lstm_fuse_pass inference)
 pass_library(embedding_fc_lstm_fuse_pass inference)

paddle/fluid/framework/ir/graph_pattern_detector.cc

@@ -1555,6 +1555,65 @@ PDNode *patterns::Reshape::operator()() {
 }
 
 PDNode *patterns::Matmul::operator()() {
+  auto matmul_op = pattern->NewNode(matmul_op_repr())->assert_is_op("matmul");
+
+  auto matmul_in_x = pattern->NewNode(matmul_in_x_repr())
+                         ->AsInput()
+                         ->assert_is_op_input("matmul", "X");
+  auto matmul_in_y = pattern->NewNode(matmul_in_y_repr())
+                         ->AsInput()
+                         ->assert_is_op_input("matmul", "Y");
+  auto matmul_out = pattern->NewNode(matmul_out_repr())
+                        ->AsOutput()
+                        ->assert_is_op_output("matmul", "Out");
+
+  matmul_op->LinksFrom({matmul_in_x, matmul_in_y}).LinksTo({matmul_out});
+  return matmul_out;
+}
+
+PDNode *patterns::Squeeze2Matmul::operator()() {
+  auto squeeze2_in_x = pattern->NewNode(squeeze2_in_x_repr())
+                           ->assert_is_op_input("squeeze2", "X")
+                           ->AsInput();
+  auto squeeze2_op =
+      pattern->NewNode(squeeze2_op_repr())->assert_is_op("squeeze2");
+  auto matmul_in_x = pattern->NewNode(matmul_in_x_repr())
+                         ->assert_is_op_output("squeeze2", "Out")
+                         ->assert_is_op_input("matmul", "X");
+  auto matmul_in_y =
+      pattern->NewNode(matmul_in_y_repr())->assert_is_op_input("matmul", "Y");
+  auto matmul_op = pattern->NewNode(matmul_op_repr())->assert_is_op("matmul");
+  auto matmul_out = pattern->NewNode(matmul_out_repr())
+                        ->AsOutput()
+                        ->assert_is_op_output("matmul", "Out");
+
+  squeeze2_op->LinksFrom({squeeze2_in_x}).LinksTo({matmul_in_x});
+  matmul_op->LinksFrom({matmul_in_x, matmul_in_y}).LinksTo({matmul_out});
+  return matmul_out;
+}
+
+PDNode *patterns::Reshape2Matmul::operator()() {
+  auto reshape2_in_x = pattern->NewNode(reshape2_in_x_repr())
+                           ->assert_is_op_input("reshape2", "X")
+                           ->AsInput();
+  auto reshape2_op =
+      pattern->NewNode(reshape2_op_repr())->assert_is_op("reshape2");
+  auto matmul_in_x = pattern->NewNode(matmul_in_x_repr())
+                         ->assert_is_op_output("reshape2", "Out")
+                         ->assert_is_op_input("matmul", "X");
+  auto matmul_in_y =
+      pattern->NewNode(matmul_in_y_repr())->assert_is_op_input("matmul", "Y");
+  auto matmul_op = pattern->NewNode(matmul_op_repr())->assert_is_op("matmul");
+  auto matmul_out = pattern->NewNode(matmul_out_repr())
+                        ->AsOutput()
+                        ->assert_is_op_output("matmul", "Out");
+
+  reshape2_op->LinksFrom({reshape2_in_x}).LinksTo({matmul_in_x});
+  matmul_op->LinksFrom({matmul_in_x, matmul_in_y}).LinksTo({matmul_out});
+  return matmul_out;
+}
+
+PDNode *patterns::MatmulWithInputOps::operator()() {
   auto prev_op_x = pattern->NewNode(prev_op_x_repr())->assert_is_op();
   auto prev_op_y = pattern->NewNode(prev_op_y_repr())->assert_is_op();
 

paddle/fluid/framework/ir/graph_pattern_detector.h

@@ -940,10 +940,52 @@ struct Reshape : public PatternBase {
 
 // Matmul op
 // Forward pass for matmul.
-// matmul_out is a result of the operator.
 struct Matmul : public PatternBase {
   Matmul(PDPattern* pattern, const std::string& name_scope)
-      : PatternBase(pattern, name_scope, "reshape2") {}
+      : PatternBase(pattern, name_scope, "matmul") {}
+
+  PDNode* operator()();
+  PATTERN_DECL_NODE(matmul_in_x);
+  PATTERN_DECL_NODE(matmul_in_y);
+  PATTERN_DECL_NODE(matmul_op);
+  PATTERN_DECL_NODE(matmul_out);
+};
+
+// Squeeze2 + Matmul
+// Forward pass.
+struct Squeeze2Matmul : public PatternBase {
+  Squeeze2Matmul(PDPattern* pattern, const std::string& name_scope)
+      : PatternBase(pattern, name_scope, "squeeze2_matmul") {}
+
+  PDNode* operator()();
+  PATTERN_DECL_NODE(squeeze2_in_x);
+  PATTERN_DECL_NODE(squeeze2_op);
+  PATTERN_DECL_NODE(matmul_in_x);
+  PATTERN_DECL_NODE(matmul_in_y);
+  PATTERN_DECL_NODE(matmul_op);
+  PATTERN_DECL_NODE(matmul_out);
+};
+
+// Reshape2 + Matmul
+// Forward pass.
+struct Reshape2Matmul : public PatternBase {
+  Reshape2Matmul(PDPattern* pattern, const std::string& name_scope)
+      : PatternBase(pattern, name_scope, "reshape2_matmul") {}
+
+  PDNode* operator()();
+  PATTERN_DECL_NODE(reshape2_in_x);
+  PATTERN_DECL_NODE(reshape2_op);
+  PATTERN_DECL_NODE(matmul_in_x);
+  PATTERN_DECL_NODE(matmul_in_y);
+  PATTERN_DECL_NODE(matmul_op);
+  PATTERN_DECL_NODE(matmul_out);
+};
+
+// Forward pass for two input ops and matmul op.
+// matmul_out is a result of the operator.
+struct MatmulWithInputOps : public PatternBase {
+  MatmulWithInputOps(PDPattern* pattern, const std::string& name_scope)
+      : PatternBase(pattern, name_scope, "matmul_with_input_ops") {}
 
   PDNode* operator()();
   PATTERN_DECL_NODE(prev_op_x);

paddle/fluid/framework/ir/map_matmul_to_mul_pass.cc

+// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed 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.
+
+#include "paddle/fluid/framework/ir/map_matmul_to_mul_pass.h"
+
+#include <cmath>
+#include <string>
+#include <vector>
+
+#include "paddle/fluid/framework/ir/graph_helper.h"
+#include "paddle/fluid/framework/op_version_registry.h"
+#include "paddle/fluid/platform/enforce.h"
+
+namespace paddle {
+namespace framework {
+namespace ir {
+
+void MapMatmul2MulPass::ApplyImpl(ir::Graph* graph) const {
+  PADDLE_ENFORCE_NOT_NULL(
+      graph, platform::errors::InvalidArgument("Graph cannot be nullptr."));
+  std::string name_scope = "map_matmul_to_mul_pass";
+  FusePassBase::Init(name_scope, graph);
+
+  GraphPatternDetector gpd;
+  patterns::Matmul matmul_pattern(gpd.mutable_pattern(), name_scope);
+  matmul_pattern();
+
+  int found_count = 0;
+  auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph,
+                     Graph* g) {
+    VLOG(4) << "map matmul to mul";
+    GET_IR_NODE_FROM_SUBGRAPH(matmul_in_x, matmul_in_x, matmul_pattern);
+    GET_IR_NODE_FROM_SUBGRAPH(matmul_in_y, matmul_in_y, matmul_pattern);
+    GET_IR_NODE_FROM_SUBGRAPH(matmul_op, matmul_op, matmul_pattern);
+    GET_IR_NODE_FROM_SUBGRAPH(matmul_out, matmul_out, matmul_pattern);
+    bool flag = true;
+
+    bool transpose_X =
+        BOOST_GET_CONST(bool, matmul_op->Op()->GetAttr("transpose_X"));
+    bool transpose_Y =
+        BOOST_GET_CONST(bool, matmul_op->Op()->GetAttr("transpose_Y"));
+    float alpha = BOOST_GET_CONST(float, matmul_op->Op()->GetAttr("alpha"));
+    flag = flag && !transpose_X && !transpose_Y && std::abs(alpha - 1.0) < 1e-5;
+
+    std::vector<int64_t> x_shape = matmul_in_x->Var()->GetShape();
+    std::vector<int64_t> y_shape = matmul_in_y->Var()->GetShape();
+    size_t x_rank = x_shape.size();
+    size_t y_rank = y_shape.size();
+    flag = flag && x_rank == 2 && y_rank == 2;
+
+    std::vector<Node*>& next_ops = matmul_out->outputs;
+    flag = flag && next_ops.size() == 1 &&
+           next_ops[0]->Name() == "elementwise_add";
+
+    if (flag) {
+      OpDesc desc;
+      desc.SetType("mul");
+      desc.SetInput("X", {matmul_in_x->Name()});
+      desc.SetInput("Y", {matmul_in_y->Name()});
+      desc.SetOutput("Out", {matmul_out->Name()});
+      desc.SetAttr("x_num_col_dims", 1);
+      desc.SetAttr("y_num_col_dims", 1);
+
+      auto mul_node = g->CreateOpNode(&desc);
+      IR_NODE_LINK_TO(matmul_in_x, mul_node);
+      IR_NODE_LINK_TO(matmul_in_y, mul_node);
+      IR_NODE_LINK_TO(mul_node, matmul_out);
+      GraphSafeRemoveNodes(graph, {matmul_op});
+      ++found_count;
+    }
+  };
+
+  gpd(graph, handler);
+  AddStatis(found_count);
+}
+
+void Squeeze2MatmulFusePass::ApplyImpl(ir::Graph* graph) const {
+  PADDLE_ENFORCE_NOT_NULL(
+      graph, platform::errors::InvalidArgument("Graph cannot be nullptr."));
+  std::string name_scope = "squeeze2_matmul_fuse_pass";
+  FusePassBase::Init(name_scope, graph);
+
+  GraphPatternDetector gpd;
+  patterns::Squeeze2Matmul fuse_pattern(gpd.mutable_pattern(), name_scope);
+  fuse_pattern();
+
+  int found_count = 0;
+  auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph,
+                     Graph* g) {
+    VLOG(4) << "fuse squeeze2+matmul to mul";
+    GET_IR_NODE_FROM_SUBGRAPH(squeeze2_in_x, squeeze2_in_x, fuse_pattern);
+    GET_IR_NODE_FROM_SUBGRAPH(squeeze2_op, squeeze2_op, fuse_pattern);
+    GET_IR_NODE_FROM_SUBGRAPH(matmul_in_x, matmul_in_x, fuse_pattern);
+    GET_IR_NODE_FROM_SUBGRAPH(matmul_in_y, matmul_in_y, fuse_pattern);
+    GET_IR_NODE_FROM_SUBGRAPH(matmul_op, matmul_op, fuse_pattern);
+    GET_IR_NODE_FROM_SUBGRAPH(matmul_out, matmul_out, fuse_pattern);
+    bool flag = true;
+
+    size_t squeeze2_in_x_rank = (squeeze2_in_x->Var()->GetShape()).size();
+    std::vector<int> squeeze2_op_axes =
+        BOOST_GET_CONST(std::vector<int>, squeeze2_op->Op()->GetAttr("axes"));
+    flag = flag && squeeze2_in_x_rank == 4 &&
+           squeeze2_op_axes == std::vector<int>{2, 3} &&
+           (matmul_in_x->outputs).size() == 1;
+
+    bool transpose_X =
+        BOOST_GET_CONST(bool, matmul_op->Op()->GetAttr("transpose_X"));
+    bool transpose_Y =
+        BOOST_GET_CONST(bool, matmul_op->Op()->GetAttr("transpose_Y"));
+    float alpha = BOOST_GET_CONST(float, matmul_op->Op()->GetAttr("alpha"));
+    size_t matmul_in_x_rank = (matmul_in_x->Var()->GetShape()).size();
+    size_t matmul_in_y_rank = (matmul_in_y->Var()->GetShape()).size();
+    flag = flag && !transpose_X && !transpose_Y &&
+           std::abs(alpha - 1.0) < 1e-5 && matmul_in_x_rank == 2 &&
+           matmul_in_y_rank == 2;
+
+    std::vector<Node*>& next_ops = matmul_out->outputs;
+    flag = flag && next_ops.size() == 1 &&
+           next_ops[0]->Name() == "elementwise_add";
+
+    if (flag) {
+      OpDesc desc;
+      desc.SetType("mul");
+      desc.SetInput("X", {squeeze2_in_x->Name()});
+      desc.SetInput("Y", {matmul_in_y->Name()});
+      desc.SetOutput("Out", {matmul_out->Name()});
+      desc.SetAttr("x_num_col_dims", 1);
+      desc.SetAttr("y_num_col_dims", 1);
+
+      auto mul_node = g->CreateOpNode(&desc);
+      IR_NODE_LINK_TO(squeeze2_in_x, mul_node);
+      IR_NODE_LINK_TO(matmul_in_y, mul_node);
+      IR_NODE_LINK_TO(mul_node, matmul_out);
+      GraphSafeRemoveNodes(graph, {squeeze2_op, matmul_in_x, matmul_op});
+      ++found_count;
+    }
+  };
+
+  gpd(graph, handler);
+  AddStatis(found_count);
+}
+
+void Reshape2MatmulFusePass::ApplyImpl(ir::Graph* graph) const {
+  PADDLE_ENFORCE_NOT_NULL(
+      graph, platform::errors::InvalidArgument("Graph cannot be nullptr."));
+  std::string name_scope = "reshape2_matmul_fuse_pass";
+  FusePassBase::Init(name_scope, graph);
+
+  GraphPatternDetector gpd;
+  patterns::Reshape2Matmul fuse_pattern(gpd.mutable_pattern(), name_scope);
+  fuse_pattern();
+
+  int found_count = 0;
+  auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph,
+                     Graph* g) {
+    VLOG(4) << "fuse reshape2+matmul to mul";
+    GET_IR_NODE_FROM_SUBGRAPH(reshape2_in_x, reshape2_in_x, fuse_pattern);
+    GET_IR_NODE_FROM_SUBGRAPH(reshape2_op, reshape2_op, fuse_pattern);
+    GET_IR_NODE_FROM_SUBGRAPH(matmul_in_x, matmul_in_x, fuse_pattern);
+    GET_IR_NODE_FROM_SUBGRAPH(matmul_in_y, matmul_in_y, fuse_pattern);
+    GET_IR_NODE_FROM_SUBGRAPH(matmul_op, matmul_op, fuse_pattern);
+    GET_IR_NODE_FROM_SUBGRAPH(matmul_out, matmul_out, fuse_pattern);
+    bool flag = true;
+
+    size_t reshape2_in_nums = reshape2_op->inputs.size();
+    auto reshape2_in_x_shape = reshape2_in_x->Var()->GetShape();
+    size_t reshape2_in_x_rank = reshape2_in_x_shape.size();
+    std::vector<int> reshape2_op_shape =
+        BOOST_GET_CONST(std::vector<int>, reshape2_op->Op()->GetAttr("shape"));
+    flag = flag && reshape2_in_nums == 1 && reshape2_in_x_rank == 4 &&
+           reshape2_in_x_shape[2] == 1 && reshape2_in_x_shape[3] == 1 &&
+           reshape2_op_shape.size() == 2 && (matmul_in_x->outputs).size() == 1;
+
+    bool transpose_X =
+        BOOST_GET_CONST(bool, matmul_op->Op()->GetAttr("transpose_X"));
+    bool transpose_Y =
+        BOOST_GET_CONST(bool, matmul_op->Op()->GetAttr("transpose_Y"));
+    float alpha = BOOST_GET_CONST(float, matmul_op->Op()->GetAttr("alpha"));
+    size_t matmul_in_x_rank = (matmul_in_x->Var()->GetShape()).size();
+    size_t matmul_in_y_rank = (matmul_in_y->Var()->GetShape()).size();
+    flag = flag && !transpose_X && !transpose_Y &&
+           std::abs(alpha - 1.0) < 1e-5 && matmul_in_x_rank == 2 &&
+           matmul_in_y_rank == 2;
+
+    std::vector<Node*>& next_ops = matmul_out->outputs;
+    flag = flag && next_ops.size() == 1 &&
+           next_ops[0]->Name() == "elementwise_add";
+
+    if (flag) {
+      OpDesc desc;
+      desc.SetType("mul");
+      desc.SetInput("X", {reshape2_in_x->Name()});
+      desc.SetInput("Y", {matmul_in_y->Name()});
+      desc.SetOutput("Out", {matmul_out->Name()});
+      desc.SetAttr("x_num_col_dims", 1);
+      desc.SetAttr("y_num_col_dims", 1);
+
+      auto mul_node = g->CreateOpNode(&desc);
+      IR_NODE_LINK_TO(reshape2_in_x, mul_node);
+      IR_NODE_LINK_TO(matmul_in_y, mul_node);
+      IR_NODE_LINK_TO(mul_node, matmul_out);
+      GraphSafeRemoveNodes(graph, {reshape2_op, matmul_in_x, matmul_op});
+      ++found_count;
+    }
+  };
+
+  gpd(graph, handler);
+  AddStatis(found_count);
+}
+
+}  // namespace ir
+}  // namespace framework
+}  // namespace paddle
+
+REGISTER_PASS(map_matmul_to_mul_pass, paddle::framework::ir::MapMatmul2MulPass);
+REGISTER_PASS_CAPABILITY(map_matmul_to_mul_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("matmul", 0)
+            .EQ("mul", 0));
+
+REGISTER_PASS(squeeze2_matmul_fuse_pass,
+              paddle::framework::ir::Squeeze2MatmulFusePass);
+REGISTER_PASS_CAPABILITY(squeeze2_matmul_fuse_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("matmul", 0)
+            .EQ("squeeze2", 0)
+            .EQ("mul", 0));
+
+REGISTER_PASS(reshape2_matmul_fuse_pass,
+              paddle::framework::ir::Reshape2MatmulFusePass);
+REGISTER_PASS_CAPABILITY(reshape2_matmul_fuse_pass)
+    .AddCombination(
+        paddle::framework::compatible::OpVersionComparatorCombination()
+            .EQ("matmul", 0)
+            .EQ("reshape2", 0)
+            .EQ("mul", 0));

paddle/fluid/framework/ir/map_matmul_to_mul_pass.h

+// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed 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.
+
+#pragma once
+
+#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 {
+
+/*
+ * Map matmul to mul, so the optimization can use fc_fuse_pass.
+ * The mul op must satisfy the following conditions:
+ * 1. the transpose_X and transpose_Y attrs are false
+ * 2. the alpha attr is 1.0
+ * 3. the rank of input X and Y is 2
+ * 4. the next op of matmul is only elementwise_add
+ *
+ * Notice:
+ *  the rank of input activation is obtained from var_desc,
+ *  it maybe change in runtime.
+ */
+class Graph;
+
+class MapMatmul2MulPass : public FusePassBase {
+ public:
+  virtual ~MapMatmul2MulPass() {}
+
+ protected:
+  void ApplyImpl(Graph* graph) const override;
+};
+
+/*
+ * Fuse squeeze2+matmul to mul, so the optimization can use fc_fuse_pass.
+ * The squeeze2 op must satisfy the following conditions:
+ * 1. the rank of input X is 4
+ * 2. the axis attr is [2, 3]
+ * 3. the next op is only matmul
+ *
+ * The matmul op must satisfy the following conditions:
+ * 1. the transpose_X and transpose_Y attrs are false
+ * 2. the alpha attr is 1.0
+ * 3. the rank of input X and Y is 2
+ * 4. the next op of matmul is only elementwise_add
+ *
+ * Notice:
+ *  the rank of input activation is obtained from var_desc,
+ *  it maybe change in runtime. Therefore, the pass considers
+ *  the above passes to reduce the impact on other models.
+ */
+
+class Squeeze2MatmulFusePass : public FusePassBase {
+ public:
+  virtual ~Squeeze2MatmulFusePass() {}
+
+ protected:
+  void ApplyImpl(Graph* graph) const override;
+};
+
+/*
+ * Fuse reshape2+matmul to mul, so the optimization can use fc_fuse_pass.
+ * The reshape2 op must satisfy the following conditions:
+ * 1. reshape2 has one input node, which means it don't
+ *    have Shape or ShapeTensor input
+ * 2. the rank of input X is 4 and the last two dims of input X is 1
+ * 3. the rank of shape attr is 2
+ * 4. the next op is only matmul
+ *
+ * The matmul op must satisfy the following conditions:
+ * 1. the transpose_X and transpose_Y attrs are false
+ * 2. the alpha attr is 1.0
+ * 3. the rank of input X and Y is 2
+ * 4. the next op of matmul is only elementwise_add
+ *
+ * Notice:
+ *  the shape and rank of input activation is obtained from var_desc,
+ *  they maybe change in runtime. Therefore, the pass considers
+ *  the above passes to reduce the impact on other models.
+ */
+
+class Reshape2MatmulFusePass : public FusePassBase {
+ public:
+  virtual ~Reshape2MatmulFusePass() {}
+
+ protected:
+  void ApplyImpl(Graph* graph) const override;
+};
+
+}  // namespace ir
+}  // namespace framework
+}  // namespace paddle

paddle/fluid/framework/ir/mkldnn/cpu_quantize_pass.cc

@@ -679,7 +679,7 @@ void CPUQuantizePass::QuantizeReshape(Graph* graph) const {
 void CPUQuantizePass::QuantizeMatmul(Graph* graph) const {
   GraphPatternDetector gpd;
   auto pattern = gpd.mutable_pattern();
-  patterns::Matmul matmul_pattern{pattern, name_scope_};
+  patterns::MatmulWithInputOps matmul_pattern{pattern, name_scope_};
   matmul_pattern();
 
   int quantize_matmul_count = 0;

paddle/fluid/inference/api/paddle_pass_builder.cc

@@ -82,11 +82,14 @@ const std::vector<std::string> kTRTSubgraphPasses({
       "embedding_eltwise_layernorm_fuse_pass",  //
       "multihead_matmul_fuse_pass_v2",          //
       "skip_layernorm_fuse_pass",               //
-      "unsqueeze2_eltwise_fuse_pass",
-      "conv_bn_fuse_pass",       //
-      "fc_fuse_pass",            //
-      "tensorrt_subgraph_pass",  //
-      "conv_bn_fuse_pass",       //
+      "unsqueeze2_eltwise_fuse_pass",           //
+      "conv_bn_fuse_pass",                      //
+      "squeeze2_matmul_fuse_pass",              //
+      "reshape2_matmul_fuse_pass",              //
+      "map_matmul_to_mul_pass",                 //
+      "fc_fuse_pass",                           //
+      "tensorrt_subgraph_pass",                 //
+      "conv_bn_fuse_pass",                      //
 #if CUDNN_VERSION >= 7100  // To run conv_fusion, the version of cudnn must be
                            // guaranteed at least v7
       "conv_elementwise_add_act_fuse_pass",   //
@@ -113,6 +116,9 @@ GpuPassStrategy::GpuPassStrategy() : PassStrategy({}) {
         "conv_eltwiseadd_bn_fuse_pass",              //
         "embedding_eltwise_layernorm_fuse_pass",     //
         "multihead_matmul_fuse_pass_v2",             //
+        "squeeze2_matmul_fuse_pass",                 //
+        "reshape2_matmul_fuse_pass",                 //
+        "map_matmul_to_mul_pass",                    //
         "fc_fuse_pass",                              //
         "fc_elementwise_layernorm_fuse_pass",        //
 #if CUDNN_VERSION >= 7100  // To run conv_fusion, the version of cudnn must be
@@ -164,6 +170,9 @@ CpuPassStrategy::CpuPassStrategy() : PassStrategy({}) {
                   "fc_gru_fuse_pass",                        //
                   "mul_gru_fuse_pass",                       //
                   "seq_concat_fc_fuse_pass",                 //
+                  "squeeze2_matmul_fuse_pass",               //
+                  "reshape2_matmul_fuse_pass",               //
+                  "map_matmul_to_mul_pass",                  //
                   "fc_fuse_pass",                            //
                   "repeated_fc_relu_fuse_pass",              //
                   "squared_mat_sub_fuse_pass",               //