diff --git a/paddle/fluid/operators/distributed_ops/prefetch_op.cc b/paddle/fluid/operators/distributed_ops/prefetch_op.cc
index c6395289f8f77552f929222922f851b2db494f94..6037ab1523ec347574db4b18aa1de732acbd3336 100644
--- a/paddle/fluid/operators/distributed_ops/prefetch_op.cc
+++ b/paddle/fluid/operators/distributed_ops/prefetch_op.cc
@@ -57,7 +57,13 @@ class PrefetchOp : public framework::OperatorBase {
       }
     }
     for (size_t i = 0; i < rets.size(); i++) {
-      PADDLE_ENFORCE(rets[i]->Wait(), "internal error in RPCClient");
+      PADDLE_ENFORCE_EQ(
+          rets[i]->Wait(), true,
+          platform::errors::Fatal(
+              "It's a fatal error of RPCClient that RPCClient can't "
+              "get the wait result. It may happen when trainers or "
+              "parameter servers exit un normally or the network "
+              "issue!"));
     }
   }
 };
diff --git a/paddle/fluid/operators/optimizers/proximal_adagrad_op.cc b/paddle/fluid/operators/optimizers/proximal_adagrad_op.cc
index 3e2f12137afc2368aa12fa836c935f804f8c02d9..7fe2a9a94ac3c91dfe59c41ee0ccfe3efb27d088 100644
--- a/paddle/fluid/operators/optimizers/proximal_adagrad_op.cc
+++ b/paddle/fluid/operators/optimizers/proximal_adagrad_op.cc
@@ -24,34 +24,42 @@ class ProximalAdagradOp : public framework::OperatorWithKernel {
 
  protected:
   void InferShape(framework::InferShapeContext *ctx) const override {
-    PADDLE_ENFORCE(ctx->HasInput("Param"),
-                   "Input(Param) of ProximalAdagradOp should not be null.");
-    PADDLE_ENFORCE(ctx->HasInput("Moment"),
-                   "Input(Moment) of ProximalAdagradOp should not be null.");
-    PADDLE_ENFORCE(ctx->HasInput("Grad"),
-                   "Input(Grad) of ProximalAdagradOp should not be null.");
-    PADDLE_ENFORCE(
-        ctx->HasInput("LearningRate"),
-        "Input(LearningRate) of ProximalAdagradOp should not be null.");
-
-    PADDLE_ENFORCE(ctx->HasOutput("ParamOut"),
-                   "Output(ParamOut) of ProximalAdagradOp should not be null.");
-    PADDLE_ENFORCE(
-        ctx->HasOutput("MomentOut"),
-        "Output(MomentOut) of ProximalAdagradOp should not be null.");
+    OP_INOUT_CHECK(ctx->HasInput("Param"), "Input", "Param",
+                   "ProximalAdagradOp");
+    OP_INOUT_CHECK(ctx->HasInput("Moment"), "Input", "Moment",
+                   "ProximalAdagradOp");
+    OP_INOUT_CHECK(ctx->HasInput("Grad"), "Input", "Grad", "ProximalAdagradOp");
+    OP_INOUT_CHECK(ctx->HasInput("LearningRate"), "Input", "LearningRate",
+                   "ProximalAdagradOp");
+
+    OP_INOUT_CHECK(ctx->HasOutput("ParamOut"), "Output", "ParamOut",
+                   "ProximalAdagradOp");
+    OP_INOUT_CHECK(ctx->HasOutput("MomentOut"), "Output", "MomentOut",
+                   "ProximalAdagradOp");
 
     auto param_dim = ctx->GetInputDim("Param");
-    PADDLE_ENFORCE_EQ(
-        param_dim, ctx->GetInputDim("Grad"),
-        "Param and Grad of ProximalAdagrad Op must have same dimension.");
-
-    PADDLE_ENFORCE_EQ(
-        param_dim, ctx->GetInputDim("Moment"),
-        "Param and Moment of ProximalAdagrad Op must have same dimension.");
+    PADDLE_ENFORCE_EQ(param_dim, ctx->GetInputDim("Grad"),
+                      platform::errors::InvalidArgument(
+                          "The shape of Intput(Param) should be equal to the "
+                          "Input(Grad) of ProximalAdagrad Op. But received "
+                          "Input(Param).dimensions=[%s], "
+                          "Input(Grad).dimensions=[%s]",
+                          param_dim, ctx->GetInputDim("Grad")));
+
+    PADDLE_ENFORCE_EQ(param_dim, ctx->GetInputDim("Moment"),
+                      platform::errors::InvalidArgument(
+                          "The shape of Intput(Param) should be equal to the "
+                          "Input(Moment) of ProximalAdagrad Op. But received "
+                          "Input(Param).dimensions=[%s], "
+                          "Input(Moment).dimensions=[%s]",
+                          param_dim, ctx->GetInputDim("Moment")));
 
     auto lr_dim = ctx->GetInputDim("LearningRate");
-    PADDLE_ENFORCE_EQ(framework::product(lr_dim), 1,
-                      "Learning Rate should be a scalar.");
+    PADDLE_ENFORCE_EQ(
+        framework::product(lr_dim), 1,
+        platform::errors::InvalidArgument(
+            "Learning Rate should be a scalar. But received dimension[%s]",
+            lr_dim));
 
     ctx->SetOutputDim("ParamOut", param_dim);
     ctx->SetOutputDim("MomentOut", param_dim);
diff --git a/paddle/fluid/operators/optimizers/proximal_gd_op.cc b/paddle/fluid/operators/optimizers/proximal_gd_op.cc
index cf3c3e2ccb92cd588edea6468b61e6d2e5678be5..edaf55129ad229c5cfc6b5448cf16ec98a08169d 100644
--- a/paddle/fluid/operators/optimizers/proximal_gd_op.cc
+++ b/paddle/fluid/operators/optimizers/proximal_gd_op.cc
@@ -24,23 +24,29 @@ class ProximalGDOp : public framework::OperatorWithKernel {
 
  protected:
   void InferShape(framework::InferShapeContext *ctx) const override {
-    PADDLE_ENFORCE(ctx->HasInput("Param"),
-                   "Input(Param) of ProximalGDOp should not be null.");
-    PADDLE_ENFORCE(ctx->HasInput("Grad"),
-                   "Input(Grad) of ProximalGDOp should not be null.");
-    PADDLE_ENFORCE(ctx->HasInput("LearningRate"),
-                   "Input(LearningRate) of ProximalGDOp should not be null.");
+    OP_INOUT_CHECK(ctx->HasInput("Param"), "Input", "Param", "ProximalGDOp");
+    OP_INOUT_CHECK(ctx->HasInput("Grad"), "Input", "Grad", "ProximalGDOp");
+    OP_INOUT_CHECK(ctx->HasInput("LearningRate"), "Input", "LearningRate",
+                   "ProximalGDOp");
 
-    PADDLE_ENFORCE(ctx->HasOutput("ParamOut"),
-                   "Output(ParamOut) of ProximalGDOp should not be null.");
+    OP_INOUT_CHECK(ctx->HasOutput("ParamOut"), "Output", "Paramout",
+                   "ProximalGDOp");
 
     auto param_dim = ctx->GetInputDim("Param");
     PADDLE_ENFORCE_EQ(param_dim, ctx->GetInputDim("Grad"),
-                      "Two input of ProximalGD Op's dimension must be same.");
+                      platform::errors::InvalidArgument(
+                          "The shape of Intput(Param) should be equal to the "
+                          "Input(Grad) of ProximalGD Op. But received "
+                          "Input(Param).dimensions=[%s], "
+                          "Input(Grad).dimensions=[%s]",
+                          param_dim, ctx->GetInputDim("Grad")));
 
     auto lr_dim = ctx->GetInputDim("LearningRate");
-    PADDLE_ENFORCE_EQ(framework::product(lr_dim), 1,
-                      "Learning Rate should be a scalar.");
+    PADDLE_ENFORCE_EQ(
+        framework::product(lr_dim), 1,
+        platform::errors::InvalidArgument(
+            "Learning Rate should be a scalar. But received dimmensions:[%s]",
+            lr_dim));
 
     ctx->SetOutputDim("ParamOut", param_dim);
   }