batch_norm trt converter error message, test=develop (#23620)

paddle/fluid/inference/tensorrt/convert/activation_op.cc

@@ -49,7 +49,6 @@ class ActivationOpConverter : public OpConverter {
       layer->setAlpha(0.);
       layer->setBeta(6.);
     }
-    g
 #endif
 
     auto output_name = op_desc.Output("Out")[0];

paddle/fluid/inference/tensorrt/convert/batch_norm_op.cc

@@ -26,13 +26,37 @@ class BatchNormOpConverter : public OpConverter {
     VLOG(3) << "convert a fluid batch norm op to tensorrt batch_norm";
 
     framework::OpDesc op_desc(op, nullptr);
-    PADDLE_ENFORCE_EQ(op_desc.Input("X").size(), 1);
-    PADDLE_ENFORCE_EQ(op_desc.Input("Bias").size(), 1);   // Bias is a weight
-    PADDLE_ENFORCE_EQ(op_desc.Input("Mean").size(), 1);   // Mean is a weight
-    PADDLE_ENFORCE_EQ(op_desc.Input("Scale").size(), 1);  // Scale is a weight
-    PADDLE_ENFORCE_EQ(op_desc.Input("Variance").size(),
-                      1);  // Variance is a weight
-    PADDLE_ENFORCE_EQ(op_desc.Output("Y").size(), 1);
+    PADDLE_ENFORCE_EQ(op_desc.Input("X").size(), 1,
+                      platform::errors::InvalidArgument(
+                          "Invalid input X's size of batch_norm TRT converter. "
+                          "Expected 1, received %d.",
+                          op_desc.Input("X").size()));
+    PADDLE_ENFORCE_EQ(op_desc.Input("Bias").size(), 1,
+                      platform::errors::InvalidArgument(
+                          "Invalid input Bias's size of batch_norm TRT "
+                          "converter. Expected 1, received %d.",
+                          op_desc.Input("Bias").size()));  // Bias is a weight
+    PADDLE_ENFORCE_EQ(op_desc.Input("Mean").size(), 1,
+                      platform::errors::InvalidArgument(
+                          "Invalid input Mean's size of batch_norm TRT "
+                          "converter. Expected 1, received %d.",
+                          op_desc.Input("Mean").size()));  // Mean is a weight
+    PADDLE_ENFORCE_EQ(op_desc.Input("Scale").size(), 1,
+                      platform::errors::InvalidArgument(
+                          "Invalid input Scale's size of batch_norm TRT "
+                          "converter. Expected 1, received %d.",
+                          op_desc.Input("Scale").size()));  // Scale is a weight
+    PADDLE_ENFORCE_EQ(
+        op_desc.Input("Variance").size(), 1,
+        platform::errors::InvalidArgument(
+            "Invalid input Variance's size of batch_norm TRT converter. "
+            "Expected 1, received %d.",
+            op_desc.Input("Variance").size()));  // Variance is a weight
+    PADDLE_ENFORCE_EQ(op_desc.Output("Y").size(), 1,
+                      platform::errors::InvalidArgument(
+                          "Invalid output Y's size of batch_norm TRT "
+                          "converter. Expected 1, received %d.",
+                          op_desc.Output("Y").size()));
 
     auto* X = engine_->GetITensor(op_desc.Input("X").front());
     // Declare weights
@@ -42,10 +66,22 @@ class BatchNormOpConverter : public OpConverter {
     auto* Variance_v = scope.FindVar(op_desc.Input("Variance").front());
     const float eps = boost::get<float>(op_desc.GetAttr("epsilon"));
 
-    PADDLE_ENFORCE_NOT_NULL(Bias_v);
-    PADDLE_ENFORCE_NOT_NULL(Mean_v);
-    PADDLE_ENFORCE_NOT_NULL(Scale_v);
-    PADDLE_ENFORCE_NOT_NULL(Variance_v);
+    PADDLE_ENFORCE_NOT_NULL(
+        Bias_v,
+        platform::errors::NotFound(
+            "Variable of Bias of batch_norm TRT converter is not found."));
+    PADDLE_ENFORCE_NOT_NULL(
+        Mean_v,
+        platform::errors::NotFound(
+            "Variable of Mean of batch_norm TRT converter is not found."));
+    PADDLE_ENFORCE_NOT_NULL(
+        Scale_v,
+        platform::errors::NotFound(
+            "Variable of Scale of batch_norm TRT converter is not found."));
+    PADDLE_ENFORCE_NOT_NULL(
+        Variance_v,
+        platform::errors::NotFound(
+            "Variable of Variance of batch_norm TRT converter is not found."));
 
     // get tensor
     auto* Bias_t = Bias_v->GetMutable<framework::LoDTensor>();