modify error message based on comments (#30189)

* modify error message based on comments

* edit code according to review.

* Correct spelling according to review.

paddle/fluid/inference/tensorrt/convert/pool2d_op.cc

@@ -197,9 +197,9 @@ class Pool2dOpConverter : public OpConverter {
             engine_, Padding, *const_cast<nvinfer1::ITensor *>(input1), pre_pad,
             post_pad);
         PADDLE_ENFORCE_NOT_NULL(
-            pad_layer,
-            platform::errors::Fatal(
-                "pad layer in poolOp converter could not be created."));
+            pad_layer, platform::errors::Fatal(
+                           "Pad layer in poolOp converter could not be "
+                           "created. The pointer to pad layer is `NULL`."));
         input1 = pad_layer->getOutput(0);
       }
       auto *pool_layer = TRT_ENGINE_ADD_LAYER(

paddle/fluid/operators/attention_lstm_op.cc

@@ -44,14 +44,18 @@ void AttentionLSTMOp::InferShape(framework::InferShapeContext* ctx) const {
 
   auto x_dims = ctx->GetInputDim("X");
   const int M = x_dims[1];
-  PADDLE_ENFORCE_EQ(x_dims.size(), 2, platform::errors::InvalidArgument(
-                                          "Input(X)'s rank must be 2."));
+  PADDLE_ENFORCE_EQ(x_dims.size(), 2,
+                    platform::errors::InvalidArgument(
+                        "Expected input(X)'s dimension is 2. But received %d.",
+                        x_dims.size()));
 
   auto w_dims = ctx->GetInputDim("LSTMWeight");
   const int D = w_dims[1] / 4;
   PADDLE_ENFORCE_EQ(
       w_dims.size(), 2,
-      platform::errors::InvalidArgument("Input(LSTMWeight)'s rank must be 2."));
+      platform::errors::InvalidArgument(
+          "Expected input(LSTMWeight)'s dimension is 2.But received %d.",
+          w_dims.size()));
   PADDLE_ENFORCE_EQ(
       w_dims[0], D + M,
       platform::errors::InvalidArgument(
@@ -77,8 +81,11 @@ void AttentionLSTMOp::InferShape(framework::InferShapeContext* ctx) const {
 
   if (ctx->HasInput("H0")) {
     auto h_dims = ctx->GetInputDim("H0");
-    PADDLE_ENFORCE_EQ(h_dims.size(), 2UL, platform::errors::InvalidArgument(
-                                              "Input(H0)'s rank must be 2."));
+    PADDLE_ENFORCE_EQ(
+        h_dims.size(), 2UL,
+        platform::errors::InvalidArgument(
+            "Expected input(H0)'s dimension is 2. But received %d.",
+            h_dims.size()));
     if (ctx->IsRuntime() ||
         (framework::product(c_dims) > 0 && framework::product(h_dims) > 0)) {
       PADDLE_ENFORCE_EQ(h_dims, c_dims,
@@ -94,7 +101,9 @@ void AttentionLSTMOp::InferShape(framework::InferShapeContext* ctx) const {
                         "Input(AttentionWeight)'s rank must be 2."));
   PADDLE_ENFORCE_EQ(atten_w_dims[0], M + D,
                     platform::errors::InvalidArgument(
-                        "AttentionWeight shapes must be (%d + %d) * 1.", M, D));
+                        "Expected `AttentionWeight` shape is [(%d + %d), 1]. "
+                        "But received shape = [%d, 1], shape[0] is not %d.",
+                        M, D, atten_w_dims[0], M + D));
   PADDLE_ENFORCE_EQ(atten_w_dims[1], 1,
                     platform::errors::InvalidArgument(
                         "AttentionWeight shapes must be (%d + %d) * 1.", M, D));

paddle/fluid/operators/bilinear_tensor_product_op.cc

@@ -50,9 +50,11 @@ class BilinearTensorProductOp : public framework::OperatorWithKernel {
     PADDLE_ENFORCE_EQ(
         y_dims.size(), 2UL,
         platform::errors::InvalidArgument("The input(Y) must be a 2D Tensor."));
-    PADDLE_ENFORCE_EQ(weight_dims.size(), 3UL,
-                      platform::errors::InvalidArgument(
-                          "The input(Weight) must be a 3D tensor."));
+    PADDLE_ENFORCE_EQ(
+        weight_dims.size(), 3UL,
+        platform::errors::InvalidArgument("Expected the input(Weight) is a 3D "
+                                          "tensor. But received %dD tensor.",
+                                          weight_dims.size()));
     if (ctx->IsRuntime() || (x_dims[0] > 0 && y_dims[0] > 0)) {
       PADDLE_ENFORCE_EQ(
           x_dims[0], y_dims[0],

paddle/fluid/operators/detection/target_assign_op.cc

@@ -43,7 +43,9 @@ class TargetAssignOp : public framework::OperatorWithKernel {
 
     PADDLE_ENFORCE_EQ(
         in_dims.size(), 3,
-        platform::errors::InvalidArgument("The rank of Input(X) must be 3."));
+        platform::errors::InvalidArgument(
+            "Expected the rank of Input(X) is 3. But received %d.",
+            in_dims.size()));
     PADDLE_ENFORCE_EQ(mi_dims.size(), 2,
                       platform::errors::InvalidArgument(
                           "The rank of Input(MatchIndices) must be 2."));

paddle/fluid/operators/mkldnn/batch_norm_mkldnn_op.cc

@@ -54,9 +54,14 @@ class BatchNormMKLDNNHandler
       const float epsilon = ctx.Attr<float>("epsilon");
       const bool fuse_with_relu = ctx.Attr<bool>("fuse_with_relu");
 
+      std::vector<std::string> DataLayout_error_msg = {"kNHWC", "kNCHW",
+                                                       "kAnyLayout", "kMKLDNN"};
       PADDLE_ENFORCE_EQ(
           x->layout(), DataLayout::kMKLDNN,
-          platform::errors::InvalidArgument("Wrong layout set for X tensor"));
+          platform::errors::InvalidArgument(
+              "Wrong layout set for X tensor. Expected layout is `kMKLDNN`, "
+              "But received %s.",
+              DataLayout_error_msg[static_cast<int>(DataLayout::kMKLDNN)]));
       PADDLE_ENFORCE_NE(
           x->format(), MKLDNNMemoryFormat::undef,
           platform::errors::InvalidArgument("Wrong format set for X tensor"));

paddle/fluid/operators/mkldnn/matmul_mkldnn_op.cc

@@ -374,9 +374,12 @@ class DNNLMatMulKernel : public framework::OpKernel<T> {
  public:
   void Compute(const framework::ExecutionContext& ctx) const override {
     if (ctx.HasAttr("head_number")) {
-      PADDLE_ENFORCE_EQ(ctx.Attr<int>("head_number"), 1,
-                        platform::errors::Unimplemented(
-                            "DNNL matmul doesn't support multiple heads."));
+      PADDLE_ENFORCE_EQ(
+          ctx.Attr<int>("head_number"), 1,
+          platform::errors::Unimplemented(
+              "DNNL matmul doesn't support multiple heads. Expected "
+              "head_number=1. But received `head_number` is %d",
+              ctx.Attr<int>("head_number")));
     }
     platform::MKLDNNDeviceContext::tls().log_lib_version();
     ExecuteMatMul<T, T>(ctx);

paddle/fluid/operators/reader/blocking_queue.h

@@ -54,7 +54,9 @@ class BlockingQueue {
     PADDLE_ENFORCE_LT(
         queue_.size(), capacity_,
         platform::errors::PermissionDenied(
-            "The queue size cannot exceed the set queue capacity."));
+            "The queue size cannot exceed the set queue capacity. Expected "
+            "queue size is less than %d. But received %d",
+            capacity_, queue_.size()));
     queue_.push_back(elem);
     receive_cv_.notify_one();
     return true;
@@ -73,7 +75,9 @@ class BlockingQueue {
     PADDLE_ENFORCE_LT(
         queue_.size(), capacity_,
         platform::errors::PermissionDenied(
-            "The queue size cannot exceed the set queue capacity."));
+            "The queue size cannot exceed the set queue capacity. Expected "
+            "queue size is less than %d. But received %d",
+            capacity_, queue_.size()));
     queue_.emplace_back(std::move(elem));
     receive_cv_.notify_one();
     return true;

paddle/fluid/operators/reader/read_op.cc

@@ -122,10 +122,13 @@ class ReadOp : public framework::OperatorBase {
     const std::vector<framework::proto::VarType::Type>& var_types =
         reader->VarTypes();
     const std::vector<bool>& need_check_feed = reader->NeedCheckFeed();
-    PADDLE_ENFORCE_EQ(out_arg_names.size(), need_check_feed.size(),
-                      platform::errors::InvalidArgument(
-                          "output size of read_op and the number of fed "
-                          "variables of reader do not match"));
+    PADDLE_ENFORCE_EQ(
+        out_arg_names.size(), need_check_feed.size(),
+        platform::errors::InvalidArgument(
+            "Output size of read_op and the number of fed "
+            "variables of reader do not match. Received size of output is %d, "
+            "number of fed variables of reader is %d",
+            out_arg_names.size(), need_check_feed.size()));
 
     for (size_t i = 0; i < out_arg_names.size(); ++i) {
       auto* out =