feat: add dyanmic quant fuse pass

lite/core/mir/fusion/quant_dequant_fuse_pass.cc

@@ -27,10 +27,24 @@ namespace mir {
 void QuantDequantFusePass::Apply(const std::unique_ptr<SSAGraph>& graph) {
   // delete quant node
   std::vector<std::string> quant_op_types = {
-      "fake_quantize_range_abs_max", "fake_quantize_moving_average_abs_max"};
+      "fake_quantize_abs_max",
+      "fake_quantize_range_abs_max",
+      "fake_quantize_moving_average_abs_max"};
+  /*
+  for (auto& op_type : {"conv2d", "mul", "depthwise_conv2d"}) {
+    for (int i = 5; i >= 1; --i){
+      fusion::DynamicQuantDequantOpFuser fuser("fake_quantize_abs_max", op_type,
+  i);
+      fuser(graph.get());
+    }
+  }
+  */
+
   for (auto& op_type : quant_op_types) {
     fusion::DeleteQuantOpFuser fuser(op_type);
     fuser(graph.get());
+    fusion::DeleteDynamicQuantOpFuser dfuser(op_type);
+    dfuser(graph.get());
   }
 
   // fuse quantized node and dequant node

lite/core/mir/fusion/quant_dequant_op_fuser.cc

@@ -77,6 +77,55 @@ cpp::OpDesc DeleteQuantOpFuser::GenOpDesc(const key2nodes_t& matched) {
   return op_desc;
 }
 
+void DeleteDynamicQuantOpFuser::BuildPattern() {
+  auto* input_act_node =
+      VarNode("input_act_node")->assert_is_op_input(quant_op_type_, "X");
+  auto* quant_node =
+      OpNode("quant_node", quant_op_type_)->assert_is_op(quant_op_type_);
+  auto* output_scale_node =
+      VarNode("output_scale_node")
+          ->assert_is_op_output(quant_op_type_, "OutScale");
+  auto* output_act_node =
+      VarNode("output_act_node")->assert_is_op_output(quant_op_type_, "Out");
+
+  quant_node->LinksFrom({input_act_node});
+  output_scale_node->LinksFrom({quant_node});
+  output_act_node->LinksFrom({quant_node});
+  VLOG(4) << "DeleteQuantOpFuser BuildPattern quant_op_type:" << quant_op_type_;
+}
+
+void DeleteDynamicQuantOpFuser::InsertNewNode(SSAGraph* graph,
+                                              const key2nodes_t& matched) {
+  auto* input_act_node = matched.at("input_act_node");
+  auto* quant_node = matched.at("quant_node");
+  auto* output_scale_node = matched.at("output_scale_node");
+  auto* output_act_node = matched.at("output_act_node");
+
+  // obtain values, save values and relink node
+  int bit_length = quant_node->stmt()->op_info()->GetAttr<int>("bit_length");
+  int range = ((1 << (bit_length - 1)) - 1);
+  auto* scope = quant_node->stmt()->op()->scope();
+  auto* scale_tensor = scope->FindVar(output_scale_node->arg()->name)
+                           ->GetMutable<lite::Tensor>();
+  float scale_value = scale_tensor->data<float>()[0] / range;
+
+  auto outlinks = output_act_node->outlinks;
+  for (auto* quantized_node : outlinks) {
+    auto* op_desc = quantized_node->stmt()->mutable_op_info();
+    op_desc->SetAttr<int>("bit_length", bit_length);
+    IR_NODE_LINK_TO(input_act_node, quantized_node)
+  }
+
+  // delete nodes and edges
+  std::unordered_set<const Node*> nodes2rm = {
+      quant_node, output_scale_node, output_act_node};
+  GraphSafeRemoveNodes(graph, nodes2rm);
+}
+
+cpp::OpDesc DeleteDynamicQuantOpFuser::GenOpDesc(const key2nodes_t& matched) {
+  cpp::OpDesc op_desc;
+  return op_desc;
+}
 void DequantOpFuser::BuildPattern() {
   std::string weight_name = "";
   if (quantized_op_type_ == "conv2d" ||
@@ -130,8 +179,11 @@ void DequantOpFuser::InsertNewNode(SSAGraph* graph,
   auto& valid_places = quantized_op->stmt()->op()->valid_places();
   int bit_length = quantized_op->stmt()->op_info()->GetAttr<int>("bit_length");
   int range = ((1 << (bit_length - 1)) - 1);
-  float input_scale =
-      quantized_op->stmt()->op_info()->GetAttr<float>("input_scale");
+  float input_scale = 0;
+  if (quantized_op->stmt()->op_info()->HasAttr("input_scale")) {
+    input_scale =
+        quantized_op->stmt()->op_info()->GetAttr<float>("input_scale");
+  }
   float max_range = dequant_op->stmt()->op_info()->GetAttr<float>("max_range");
   float whole_weight_scale =
       static_cast<float>(range * range) / max_range / range;
@@ -163,7 +215,9 @@ void DequantOpFuser::InsertNewNode(SSAGraph* graph,
     weight_scale.push_back(whole_weight_scale);
   }
   op_desc.SetAttr("enable_int8", true);
-  op_desc.SetAttr("input_scale", input_scale);
+  if (quantized_op->stmt()->op_info()->HasAttr("input_scale")) {
+    op_desc.SetAttr("input_scale", input_scale);
+  }
   op_desc.SetAttr("weight_scale", weight_scale);
 
   // change the weight from the float type to int8 type.
@@ -464,6 +518,192 @@ cpp::OpDesc DeleteQuantDequantOpFuser::GenOpDesc(const key2nodes_t& matched) {
   cpp::OpDesc op_desc;
   return op_desc;
 }
+//  ================dynamic quant fuse==============
+// #define DYNAMIC_RANGE
+void DynamicQuantDequantOpFuser::BuildPattern() {
+  const int kNumFields = 5;
+  const int kQuantizedWeightOffset = 0;
+  const int kQuantizedOpOffset = 1;
+  const int kQuantizedOpOutOffset = 2;
+  const int kDequantOpOffset = 3;
+  const int kDequantOpOutOffset = 4;
+
+  std::string weight_name = "";
+  if (op_type_ == "conv2d" || op_type_ == "depthwise_conv2d") {
+    weight_name = "Filter";
+  } else {
+    weight_name = "Y";
+  }
+  auto* quant_op_input = VarNode("quant_op_input")
+                             ->assert_is_op_input(quant_type_, "X")
+                             ->AsInput();
+#ifdef DYNAMIC_RANGE
+  auto* quant_op_in_scale = VarNode("quant_op_in_scale")
+                                ->assert_is_op_input(quant_type_, "InScale")
+                                ->AsIntermediate();
+#endif
+  auto* quant_op = OpNode("quant_op", quant_type_)
+                       ->assert_is_op(quant_type_)
+                       ->AsIntermediate();
+
+  auto* quant_op_out_scale =
+      VarNode("quant_op_out_scale")
+          ->assert_is_op_output(quant_type_, "OutScale")
+          ->assert_is_op_input("fake_dequantize_max_abs", "Scale")
+          ->AsIntermediate();
+
+  auto* quant_op_out = VarNode("quant_op_out")
+                           ->assert_is_op_output(quant_type_, "Out")
+                           ->assert_is_op_input(op_type_)
+                           ->AsIntermediate();
+  std::vector<PMNode*> nodes;
+  for (int i = 0; i < times_; i++) {
+    nodes.push_back(VarNode(string_format("quantized_op_weight%d", i))
+                        ->assert_is_op_input(op_type_, weight_name)
+                        ->AsInput());
+
+    nodes.push_back(OpNode(string_format("quantized_op%d", i), op_type_)
+                        ->assert_is_op(op_type_)
+                        ->AsIntermediate());
+
+    nodes.push_back(VarNode(string_format("quantized_op_out%d", i))
+                        ->assert_is_op_output(op_type_)
+                        ->assert_is_op_input("fake_dequantize_max_abs", "X")
+                        ->AsIntermediate());
+
+    nodes.push_back(
+        OpNode(string_format("dequant_op%d", i), "fake_dequantize_max_abs")
+            ->assert_is_op("fake_dequantize_max_abs")
+            ->AsIntermediate());
+    nodes.push_back(VarNode(string_format("dequant_op_out%d", i))
+                        ->assert_is_op_output("fake_dequantize_max_abs", "Out")
+                        ->AsOutput());
+  }
+
+#ifdef DYNAMIC_RANGE
+  quant_op->LinksFrom({quant_op_input, quant_op_in_scale});
+#endif
+  quant_op->LinksFrom({quant_op_input});
+  quant_op_out->LinksFrom({quant_op});
+  quant_op_out_scale->LinksFrom({quant_op});
+  for (int i = 0; i < times_; i++) {
+    nodes[i * kNumFields + kQuantizedOpOffset]->LinksFrom(
+        {quant_op_out, nodes[i * kNumFields + kQuantizedWeightOffset]});
+    nodes[i * kNumFields + kQuantizedOpOutOffset]->LinksFrom(
+        {nodes[i * kNumFields + kQuantizedOpOffset]});
+    nodes[i * kNumFields + kDequantOpOffset]->LinksFrom(
+        {nodes[i * kNumFields + kQuantizedOpOutOffset], quant_op_out_scale});
+    nodes[i * kNumFields + kDequantOpOutOffset]->LinksFrom(
+        {nodes[i * kNumFields + kDequantOpOffset]});
+  }
+}
+
+void DynamicQuantDequantOpFuser::InsertNewNode(SSAGraph* graph,
+                                               const key2nodes_t& matched) {
+  const int kNumFields = 5;
+  const int kQuantizedWeightOffset = 0;
+  const int kQuantizedOpOffset = 1;
+  const int kDequantOpOffset = 3;
+  const int kDequantOpOutOffset = 4;
+
+  auto* quant_op_input = matched.at("quant_op_input");
+#ifdef DYNAMIC_RANGE
+  auto* quant_op_in_scale = matched.at("quant_op_in_scale");
+#endif
+  auto* quant_op = matched.at("quant_op");
+
+  std::vector<Node*> nodes;
+  for (int i = 0; i < times_; i++) {
+    nodes.push_back(matched.at(string_format("quantized_op_weight%d", i)));
+    nodes.push_back(matched.at(string_format("quantized_op%d", i)));
+    nodes.push_back(matched.at(string_format("quantized_op_out%d", i)));
+    nodes.push_back(matched.at(string_format("dequant_op%d", i)));
+    nodes.push_back(matched.at(string_format("dequant_op_out%d", i)));
+  }
+  int bit_length = quant_op->stmt()->op_info()->GetAttr<int>("bit_length");
+  auto* scope = quant_op->stmt()->op()->scope();
+  auto& valid_places = quant_op->stmt()->op()->valid_places();
+  int range = ((1 << (bit_length - 1)) - 1);
+
+#ifdef DYNAMIC_RANGE
+  auto input_scale_t = scope->FindVar(quant_op_in_scale->arg()->name)
+                           ->GetMutable<lite::Tensor>();
+  float input_scale = input_scale_t->data<float>()[0] / range;
+  VLOG(4) << "range: " << range << " input_scale: " << input_scale;
+#endif
+  for (int i = 0; i < times_; i++) {
+    float max_range = nodes[i * kNumFields + kDequantOpOffset]
+                          ->stmt()
+                          ->op_info()
+                          ->GetAttr<float>("max_range");
+    // weight_scale = max(abs(weight))
+    float whole_weight_scale =
+        static_cast<float>(range * range) / max_range / range;
+
+    cpp::OpDesc op_desc =
+        *nodes[i * kNumFields + kQuantizedOpOffset]->stmt()->op_info();
+
+    auto quantized_weight_var_name =
+        nodes[i * kNumFields + kQuantizedWeightOffset]->arg()->name;
+    auto quantized_weight_t =
+        scope->FindVar(quantized_weight_var_name)->GetMutable<lite::Tensor>();
+    std::vector<float> weight_scale;
+    int weight_scale_size;
+
+    if (op_type_ == "conv2d" || op_type_ == "depthwise_conv2d") {
+      op_desc.SetInput("Input", {matched.at("quant_op_input")->arg()->name});
+      op_desc.SetOutput(
+          "Output", {nodes[i * kNumFields + kDequantOpOutOffset]->arg()->name});
+      // Conv weight shape: Cout * Cin * kh * hw, the weight_scale_size should
+      // be Cout.
+      weight_scale_size = quantized_weight_t->dims()[0];
+    } else if (op_type_ == "mul") {
+      op_desc.SetInput("X", {matched.at("quant_op_input")->arg()->name});
+      op_desc.SetOutput(
+          "Out", {nodes[i * kNumFields + kDequantOpOutOffset]->arg()->name});
+      // Fc weight: Cin * Cout, the weight_scale_size should be Cout.
+      weight_scale_size = quantized_weight_t->dims()[1];
+    }
+    for (int i = 0; i < weight_scale_size; i++) {
+      weight_scale.push_back(whole_weight_scale);
+    }
+    // op_desc.SetAttr("enable_int8", true);
+    // op_desc.SetAttr("input_scale", input_scale);
+    op_desc.SetAttr("weight_scale", weight_scale);
+
+    Tensor temp_tensor;
+    temp_tensor.CopyDataFrom(*quantized_weight_t);
+    float* temp_data = temp_tensor.mutable_data<float>();
+    size_t weight_num = quantized_weight_t->data_size();
+    quantized_weight_t->set_persistable(true);
+#ifdef LITE_WITH_FPGA
+    float* quantized_weight_data = quantized_weight_t->mutable_data<float>();
+    for (size_t i = 0; i < weight_num; i++) {
+      quantized_weight_data[i] = temp_data[i] * whole_weight_scale;
+    }
+    quantized_weight_t->set_precision(PRECISION(kFloat));
+#else
+    int8_t* quantized_weight_data = quantized_weight_t->mutable_data<int8_t>();
+    for (size_t i = 0; i < weight_num; i++) {
+      quantized_weight_data[i] = static_cast<int8_t>(temp_data[i]);
+    }
+    quantized_weight_t->set_precision(PRECISION(kInt8));
+#endif
+    auto quantized_op = LiteOpRegistry::Global().Create(op_type_);
+    quantized_op->Attach(op_desc, scope);
+    auto* new_op_node =
+        graph->GraphCreateInstructNode(quantized_op, valid_places);
+    IR_NODE_LINK_TO(quant_op_input, new_op_node);
+    IR_NODE_LINK_TO(nodes[i * kNumFields + kQuantizedWeightOffset],
+                    new_op_node);
+    IR_NODE_LINK_TO(new_op_node, nodes[i * kNumFields + kDequantOpOutOffset]);
+  }
+}
+
+cpp::OpDesc DynamicQuantDequantOpFuser::GenOpDesc(const key2nodes_t& matched) {
+  cpp::OpDesc op_desc;
+  return op_desc;
+}
 
 }  // namespace fusion
 }  // namespace mir

lite/core/mir/fusion/quant_dequant_op_fuser.h

@@ -52,6 +52,19 @@ class DeleteQuantOpFuser : public FuseBase {
  private:
   std::string quant_op_type_{};
 };
+class DeleteDynamicQuantOpFuser : public FuseBase {
+ public:
+  explicit DeleteDynamicQuantOpFuser(const std::string& quant_op_type)
+      : quant_op_type_(quant_op_type) {}
+  void BuildPattern() override;
+  void InsertNewNode(SSAGraph* graph, const key2nodes_t& matched) override;
+
+ private:
+  cpp::OpDesc GenOpDesc(const key2nodes_t& matched) override;
+
+ private:
+  std::string quant_op_type_{};
+};
 
 /* DequantOpFuser process conv2d/depthwise_conv2d/mul + fake_dequantize_max_abs.
 */
@@ -106,6 +119,24 @@ class DeleteQuantDequantOpFuser : public FuseBase {
  private:
   std::string quantized_op_type_{};
 };
+// dynamic quantdequant op fuser
+class DynamicQuantDequantOpFuser : public FuseBase {
+ public:
+  explicit DynamicQuantDequantOpFuser(const std::string& quantized_op_type,
+                                      const std::string& op_type,
+                                      int i)
+      : op_type_(op_type), quant_type_(quantized_op_type), times_(i) {}
+  void BuildPattern() override;
+  void InsertNewNode(SSAGraph* graph, const key2nodes_t& matched) override;
+
+ private:
+  cpp::OpDesc GenOpDesc(const key2nodes_t& matched) override;
+
+ private:
+  std::string op_type_{};
+  std::string quant_type_{};
+  int times_{1};
+};
 
 }  // namespace fusion
 }  // namespace mir

lite/operators/fake_quantize_range_abs_max.cc

@@ -23,3 +23,5 @@ namespace operators {}  // namespace operators
 
 REGISTER_LITE_OP(fake_quantize_range_abs_max,
                  paddle::lite::operators::FakeQuantizeRangeMaxAbsOpLite);
+REGISTER_LITE_OP(fake_quantize_abs_max,
+                 paddle::lite::operators::FakeQuantizeRangeMaxAbsOpLite);

lite/operators/fake_quantize_range_abs_max.h

@@ -40,13 +40,15 @@ class FakeQuantizeRangeMaxAbsOpLite : public OpLite {
 
   bool AttachImpl(const cpp::OpDesc &op_desc, lite::Scope *scope) override {
     auto x = op_desc.Input("X").front();
-    auto in_scale = op_desc.Input("InScale").front();
+    if (op_desc.HasInput("InScale")) {
+      auto in_scale = op_desc.Input("InScale").front();
+      param_.in_scale = scope->FindVar(in_scale)->GetMutable<lite::Tensor>();
+    }
 
     auto out = op_desc.Output("Out").front();
     auto out_scale = op_desc.Output("OutScale").front();
 
     param_.x = scope->FindVar(x)->GetMutable<lite::Tensor>();
-    param_.in_scale = scope->FindVar(in_scale)->GetMutable<lite::Tensor>();
 
     param_.out = scope->FindVar(out)->GetMutable<lite::Tensor>();
     param_.out_scale = scope->FindVar(out_scale)->GetMutable<lite::Tensor>();