add conv_transpose+bn fusion. test=develop

lite/core/mir/fusion/conv_bn_fuse_pass.cc

@@ -26,10 +26,12 @@ namespace mir {
 void ConvBNFusePass::Apply(const std::unique_ptr<SSAGraph>& graph) {
   // initialze fuser params
   std::vector<bool> conv_has_bias_cases{true, false};
-  std::vector<std::string> conv_type_cases{"conv2d", "depthwise_conv2d"};
+  std::vector<std::string> conv_type_cases{"conv2d", "depthwise_conv2d", "conv2d_transpose"};
   // start fuse using params
   for (auto conv_has_bias : conv_has_bias_cases) {
     for (auto conv_type : conv_type_cases) {
+      std::cout << "conv_has_bias:" << conv_has_bias
+              << " conv_type:" << conv_type << std::endl;
       VLOG(4) << "conv_has_bias:" << conv_has_bias
               << " conv_type:" << conv_type;
       fusion::ConvBNFuser fuser(conv_type, conv_has_bias);

lite/core/mir/fusion/conv_bn_fuser.cc

@@ -153,7 +153,7 @@ void ConvBNFuser::InsertNewNode(SSAGraph* graph, const key2nodes_t& matched) {
     // compute new conv_weight for int8
     auto weight_scale =
         conv_op_desc->GetAttr<std::vector<float>>("weight_scale");
-    for (unsigned int i = 0; i < h; ++i) {
+/*    for (unsigned int i = 0; i < h; ++i) {
       weight_scale[i] *= fabsf(alpha_data[i]);
       if (alpha_data[i] < 0.f) {
         auto ptr_row = conv_weight_d + i * w;
@@ -162,6 +162,33 @@ void ConvBNFuser::InsertNewNode(SSAGraph* graph, const key2nodes_t& matched) {
         }
       }
     }
+*/
+    if (conv_type_ == "conv2d_transpose") {
+      int c_size = conv_weight_t->dims()[1] * conv_weight_t->dims()[2] *
+                   conv_weight_t->dims()[3];
+      int hw = conv_weight_t->dims()[2] * conv_weight_t->dims()[3];
+      for (unsigned int k = 0; k < conv_weight_t->dims()[0]; ++k) {
+        for (unsigned int i = 0; i < h; ++i) {
+          weight_scale[i] *= fabsf(alpha_data[i]);
+          if (alpha_data[i] < 0.f) {
+            auto ptr_row = conv_weight_d + k * c_size + i * hw;
+            for (unsigned int j = 0; j < hw; ++j) {
+              ptr_row[j] *= -1;
+            }
+          }
+        }
+      }
+    } else {
+      for (unsigned int i = 0; i < h; ++i) {
+        weight_scale[i] *= fabsf(alpha_data[i]);
+        if (alpha_data[i] < 0.f) {
+          auto ptr_row = conv_weight_d + i * w;
+          for (unsigned int j = 0; j < w; ++j) {
+            ptr_row[j] *= -1;
+          }
+        }
+      }
+    }
     conv_op_desc->SetAttr("weight_scale", weight_scale);
   } else if (is_weight_quantization) {
     std::string scale_name = conv_weight_name + "_quant_scale";
@@ -176,10 +203,29 @@ void ConvBNFuser::InsertNewNode(SSAGraph* graph, const key2nodes_t& matched) {
   } else {
     // compute new conv_weight
     auto conv_weight_d = conv_weight_t->mutable_data<float>();
-    for (unsigned int i = 0; i < h; ++i) {    // n: conv2d output channels
+    /*for (unsigned int i = 0; i < h; ++i) {    // n: conv2d output channels
       for (unsigned int j = 0; j < w; ++j) {  // w: conv2d input channels
         conv_weight_d[i * w + j] *= alpha_data[i];
       }
+    }*/
+  if (conv_type_ == "conv2d_transpose") {
+      int c_size = conv_weight_t->dims()[1] * conv_weight_t->dims()[2] * 
+                   conv_weight_t->dims()[3];
+      int hw = conv_weight_t->dims()[2] * conv_weight_t->dims()[3];
+      for (unsigned int k = 0; k < conv_weight_t->dims()[0]; ++k) {
+        for (unsigned int i = 0; i < h; ++i) {
+            auto ptr_row = conv_weight_d + k * c_size + i * hw;
+            for (unsigned int j = 0; j < hw; ++j) {
+              ptr_row[j] *= alpha_data[i];
+            }
+        }
+      }
+    } else {
+      for (unsigned int i = 0; i < h; ++i) {    // n: conv2d output channels
+        for (unsigned int j = 0; j < w; ++j) {  // w: conv2d input channels
+          conv_weight_d[i * w + j] *= alpha_data[i];
+        }
+      }
     }
   }