Refine `squared_l2_distance_grad` error message (#24418)

test=develop

paddle/fluid/operators/squared_l2_distance_op.h

@@ -77,8 +77,16 @@ class SquaredL2DistanceGradKernel : public framework::OpKernel<T> {
     auto* x_g = context.Output<Tensor>(framework::GradVarName("X"));
     auto* y_g = context.Output<Tensor>(framework::GradVarName("Y"));
 
-    PADDLE_ENFORCE_NOT_NULL(x_g);
-    PADDLE_ENFORCE_NOT_NULL(y_g);
+    PADDLE_ENFORCE_NOT_NULL(
+        x_g, platform::errors::NotFound(
+                 "variable(%s) cannot be found "
+                 "in scope for operator 'squared_l2_distance_grad'.",
+                 framework::GradVarName("X")));
+    PADDLE_ENFORCE_NOT_NULL(
+        y_g, platform::errors::NotFound(
+                 "variable(%s) cannot be found "
+                 "in scope for operator 'squared_l2_distance_grad'.",
+                 framework::GradVarName("Y")));
 
     auto sub_result = EigenMatrix<T>::From(*in0);
     auto out_grad = EigenMatrix<T>::From(*in1);
@@ -106,8 +114,11 @@ class SquaredL2DistanceGradKernel : public framework::OpKernel<T> {
     y_g->mutable_data<T>(context.GetPlace());
 
     PADDLE_ENFORCE_GE(sub_result.dimensions()[0], y_dims[0],
+                      platform::errors::InvalidArgument(
                           "First dimension of gradient must be greater or "
-                      "equal than first dimension of target.");
+                          "equal than first dimension of target. But received "
+                          "gradient dimension = %d and target dimension is %d.",
+                          sub_result.dimensions()[0], y_dims[0]));
 
     if (sub_result.dimensions()[0] == y_dims[0]) {
       auto y_grad =