Support quantizing conv2d_transpose, test=develop (#3893)

lite/core/mir/fusion/quant_dequant_fuse_pass.cc

@@ -34,12 +34,13 @@ void QuantDequantFusePass::Apply(const std::unique_ptr<SSAGraph>& graph) {
   }
 
   // fuse quantized node and dequant node
-  for (auto& op_type : {"conv2d", "mul", "depthwise_conv2d"}) {
+  for (auto& op_type :
+       {"conv2d", "mul", "depthwise_conv2d", "conv2d_transpose"}) {
     fusion::DequantOpFuser fuser(op_type);
     fuser(graph.get());
   }
 
-  for (auto& op_type : {"conv2d", "depthwise_conv2d"}) {
+  for (auto& op_type : {"conv2d", "depthwise_conv2d", "conv2d_transpose"}) {
     fusion::ChannelWiseDequantOpFuser fuser(op_type);
     fuser(graph.get());
   }

lite/core/mir/fusion/quant_dequant_op_fuser.cc

@@ -23,6 +23,20 @@ namespace lite {
 namespace mir {
 namespace fusion {
 
+static std::string GetWeightArgname(const std::string& op_type) {
+  std::string weight_argname{};
+  std::vector<std::string> conv_ops = {
+      "conv2d", "depthwise_conv2d", "conv2d_transpose"};
+  std::vector<std::string> mul_ops = {"mul", "matmul"};
+  if (std::find(conv_ops.begin(), conv_ops.end(), op_type) != conv_ops.end()) {
+    weight_argname = "Filter";
+  } else if (std::find(mul_ops.begin(), mul_ops.end(), op_type) !=
+             mul_ops.end()) {
+    weight_argname = "Y";
+  }
+  return weight_argname;
+}
+
 void DeleteQuantOpFuser::BuildPattern() {
   auto* input_scale_node = VarNode("input_scale_node")
                                ->assert_is_op_input(quant_op_type_, "InScale");
@@ -83,20 +97,13 @@ cpp::OpDesc DeleteQuantOpFuser::GenOpDesc(const key2nodes_t& matched) {
 }
 
 void DequantOpFuser::BuildPattern() {
-  std::string weight_name = "";
-  if (quantized_op_type_ == "conv2d" ||
-      quantized_op_type_ == "depthwise_conv2d") {
-    weight_name = "Filter";
-  } else {
-    weight_name = "Y";
-  }
-
+  std::string weight_argname = GetWeightArgname(quantized_op_type_);
   auto* quantized_op_input = VarNode("quantized_op_input")
                                  ->assert_is_op_input(quantized_op_type_)
                                  ->AsInput();
   auto* quantized_op_weight =
       VarNode("quantized_op_weight")
-          ->assert_is_op_input(quantized_op_type_, weight_name)
+          ->assert_is_op_input(quantized_op_type_, weight_argname)
           ->AsInput();
   auto* quantized_op = OpNode("quantized_op", quantized_op_type_)
                            ->assert_is_op(quantized_op_type_)
@@ -152,7 +159,8 @@ void DequantOpFuser::InsertNewNode(SSAGraph* graph,
   std::vector<float> weight_scale;
   int weight_scale_size = 0;
   if (quantized_op_type_ == "conv2d" ||
-      quantized_op_type_ == "depthwise_conv2d") {
+      quantized_op_type_ == "depthwise_conv2d" ||
+      quantized_op_type_ == "conv2d_transpose") {
     op_desc.SetInput("Input", {quantized_op_input->arg()->name});
     op_desc.SetOutput("Output", {dequant_op_out->arg()->name});
     // Conv weight shape: Cout * Cin * kh * hw, the weight_scale_size should
@@ -199,12 +207,13 @@ cpp::OpDesc DequantOpFuser::GenOpDesc(const key2nodes_t& matched) {
 
 void ChannelWiseDequantOpFuser::BuildPattern() {
   std::string dequant_op_type = "fake_channel_wise_dequantize_max_abs";
+  std::string weight_argname = GetWeightArgname(quantized_op_type_);
   auto* quantized_op_input = VarNode("quantized_op_input")
                                  ->assert_is_op_input(quantized_op_type_)
                                  ->AsInput();
   auto* quantized_op_weight =
       VarNode("quantized_op_weight")
-          ->assert_is_op_input(quantized_op_type_, "Filter")
+          ->assert_is_op_input(quantized_op_type_, weight_argname)
           ->AsInput();
   auto* quantized_op = OpNode("quantized_op", quantized_op_type_)
                            ->assert_is_op(quantized_op_type_)
@@ -263,14 +272,17 @@ void ChannelWiseDequantOpFuser::InsertNewNode(SSAGraph* graph,
   // set op desc
   auto op_desc = *quantized_op->stmt()->op_info();
   if (quantized_op_type_ == "conv2d" ||
-      quantized_op_type_ == "depthwise_conv2d") {
+      quantized_op_type_ == "depthwise_conv2d" ||
+      quantized_op_type_ == "conv2d_transpose") {
     op_desc.SetInput("Input", {quantized_op_input->arg()->name});
     op_desc.SetOutput("Output", {dequant_op_out->arg()->name});
   } else if (quantized_op_type_ == "mul" || quantized_op_type_ == "matmul") {
     op_desc.SetInput("X", {quantized_op_input->arg()->name});
     op_desc.SetOutput("Out", {dequant_op_out->arg()->name});
   }
-  op_desc.SetAttr("enable_int8", true);
+  if (quantized_op_type_ != "conv2d_transpose") {
+    op_desc.SetAttr("enable_int8", true);
+  }
   op_desc.SetInputScale(weight_name, weight_scale);
 
   // change the weight from the float type to int8 type.