MKLDNN conv + elementwise_add fusion: UT for missing bias added. UTs refactored. Some minor changes in the pass

paddle/fluid/framework/ir/conv_elementwise_add_mkldnn_fuse_pass.cc

@@ -68,8 +68,7 @@ graph_ptr ConvElementwiseAddMKLDNNFusePass::ApplyImpl(graph_ptr graph) const {
 
   conv_output->AsIntermediate();
 
-  auto conv_op_has_bias = [](const Node& conv_op,
-                             const Scope& scope) -> std::pair<bool, Node*> {
+  auto conv_op_has_bias = [](const Node& conv_op) -> std::pair<bool, Node*> {
     auto bias_input_names = conv_op.Op()->Inputs();
     auto bias_it = bias_input_names.find("Bias");
 
@@ -116,7 +115,7 @@ graph_ptr ConvElementwiseAddMKLDNNFusePass::ApplyImpl(graph_ptr graph) const {
     bool has_bias;
     Node* conv_bias;
 
-    std::tie(has_bias, conv_bias) = conv_op_has_bias(*conv_op, *param_scope());
+    std::tie(has_bias, conv_bias) = conv_op_has_bias(*conv_op);
 
     if (has_bias) {
       op_desc.SetInput("Bias", {conv_bias->Name()});

paddle/fluid/framework/ir/graph_pattern_detector.cc

@@ -1014,7 +1014,7 @@ PDNode *patterns::Conv::operator()() {
                         ->AsOutput()
                         ->assert_is_op_output("conv2d", "Output");
 
-  conv_op->LinksFrom({input_var, /*bias_var,*/ filter_var});
+  conv_op->LinksFrom({input_var, filter_var});
   conv_op->LinksTo({output_var});
 
   return output_var;

paddle/fluid/framework/ir/graph_pattern_detector.h

@@ -617,7 +617,6 @@ struct Conv : public PatternBase {
 
   PATTERN_DECL_NODE(conv_op);
   PATTERN_DECL_NODE(conv_input);
-  PATTERN_DECL_NODE(conv_bias);
   PATTERN_DECL_NODE(conv_filter);
   PATTERN_DECL_NODE(conv_residual_data);
   PATTERN_DECL_NODE(conv_output);