enable relu fuse in arm conv kernel

test=develop

paddle/fluid/lite/kernels/arm/conv_compute_test.cc

@@ -45,7 +45,7 @@ void conv_compute_ref(const operators::ConvParam& param) {
     bias_data = param.bias->mutable_data<float>();
   }
   bool flag_bias = bias_data != nullptr;
-  bool flag_relu = false;  // TODO(hong19860320) param.relu
+  bool flag_relu = param.fuse_relu;
 
   int num = input_dims[0];
   int chout = output_dims[1];
@@ -183,7 +183,8 @@ TEST(conv_arm, compute) {
                           auto* filter_data = filter.mutable_data<float>();
                           auto* output_data = output.mutable_data<float>();
                           for (int i = 0; i < input.dims().production(); i++) {
-                            input_data[i] = static_cast<float>(i % 128);
+                            float sign = i % 3 == 0 ? -1.0f : 1.0f;
+                            input_data[i] = sign * static_cast<float>(i % 128);
                           }
                           for (int i = 0; i < filter.dims().production(); i++) {
                             filter_data[i] =
@@ -208,7 +209,7 @@ TEST(conv_arm, compute) {
                             }
                             param.bias = &bias;
                           }
-                          // TODO(hong19860320) param.relu = flag_relu;
+                          param.fuse_relu = flag_relu;
                           param.paddings = std::vector<int>({padding, padding});
                           param.strides = std::vector<int>({stride, stride});
                           param.dilations =

paddle/fluid/lite/operators/conv_op.h

@@ -73,6 +73,7 @@ class ConvOpLite : public OpLite {
         }
       }
     }
+    param_.fuse_relu = op_desc.GetAttr<bool>("fuse_relu");
     return true;
   }