[cherry-pick] Variable, fusion_seqexpand_concat_fc, fusion_seqconv_eltadd_relu...

[cherry-pick] Variable, fusion_seqexpand_concat_fc, fusion_seqconv_eltadd_relu error message enhancement, test=develop (#24066)

paddle/fluid/framework/variable.h

@@ -30,11 +30,13 @@ class Variable {
     static_assert(
         IsRegisteredVarType<T>(),
         "Not registered type. Please register T inside var_type_traits.h");
-    PADDLE_ENFORCE(holder_ != nullptr, "Variable is not initialized.");
-    PADDLE_ENFORCE(holder_->Type() == VarTypeTrait<T>::kId,
+    PADDLE_ENFORCE_NOT_NULL(
+        holder_, platform::errors::NotFound("Variable is not initialized."));
+    PADDLE_ENFORCE_EQ(
+        holder_->Type(), VarTypeTrait<T>::kId,
+        platform::errors::InvalidArgument(
             "The Variable type must be %s, but the type it holds is %s.",
-                   ToTypeName(VarTypeTrait<T>::kId),
-                   ToTypeName(holder_->Type()));
+            ToTypeName(VarTypeTrait<T>::kId), ToTypeName(holder_->Type())));
     return *static_cast<const T*>(holder_->Ptr());
   }
 
@@ -45,10 +47,11 @@ class Variable {
     if (!holder_) {
       holder_.reset(new PlaceholderImpl<T>());
     } else {
-      PADDLE_ENFORCE(
-          holder_->Type() == VarTypeTrait<T>::kId,
+      PADDLE_ENFORCE_EQ(
+          holder_->Type(), VarTypeTrait<T>::kId,
+          platform::errors::InvalidArgument(
               "The Variable type must be %s, but the type it holds is %s.",
-          ToTypeName(VarTypeTrait<T>::kId), ToTypeName(holder_->Type()));
+              ToTypeName(VarTypeTrait<T>::kId), ToTypeName(holder_->Type())));
     }
     return static_cast<T*>(holder_->Ptr());
   }
@@ -61,7 +64,8 @@ class Variable {
   void Clear() { holder_.reset(); }
 
   int Type() const {
-    PADDLE_ENFORCE(holder_ != nullptr, "Variable is not initialized.");
+    PADDLE_ENFORCE_NOT_NULL(
+        holder_, platform::errors::NotFound("Variable is not initialized."));
     return holder_->Type();
   }
 

paddle/fluid/operators/fused/fusion_seqconv_eltadd_relu_op.cc

@@ -23,36 +23,53 @@ namespace operators {
 
 void FusionSeqConvEltAddReluOp::InferShape(
     framework::InferShapeContext* ctx) const {
-  PADDLE_ENFORCE(ctx->HasInput("X"),
-                 "Input(X) of FusionSeqConvEltAddReluOp should not be null.");
-  PADDLE_ENFORCE(
-      ctx->HasInput("Filter"),
-      "Input(Filter) of FusionSeqConvEltAddReluOp should not be null.");
-  PADDLE_ENFORCE(
-      ctx->HasInput("Bias"),
-      "Input(Bias) of FusionSeqConvEltAddReluOp should not be null.");
-  PADDLE_ENFORCE(
-      ctx->HasOutput("Out"),
-      "Output(Out) of FusionSeqConvEltAddReluOp should not be null.");
-  PADDLE_ENFORCE(
-      ctx->HasOutput("ColMat"),
-      "Output(ColMat) of FusionSeqConvEltAddReluOp should not be null.");
+  OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X",
+                 "fusion_seqconv_eltadd_relu");
+  OP_INOUT_CHECK(ctx->HasInput("Filter"), "Input", "Filter",
+                 "fusion_seqconv_eltadd_relu");
+  OP_INOUT_CHECK(ctx->HasInput("Bias"), "Input", "Bias",
+                 "fusion_seqconv_eltadd_relu");
+
+  OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out",
+                 "fusion_seqconv_eltadd_relu");
+  OP_INOUT_CHECK(ctx->HasOutput("ColMat"), "Output", "ColMat",
+                 "fusion_seqconv_eltadd_relu");
 
   auto x_dims = ctx->GetInputDim("X");
   auto w_dims = ctx->GetInputDim("Filter");
   int context_length = ctx->Attrs().Get<int>("contextLength");
-  PADDLE_ENFORCE(
-      ctx->Attrs().Get<int>("contextStride") == 1,
-      "Currently, FusionSeqConvEltAddReluOp only supports contextStride=1.");
-  PADDLE_ENFORCE(x_dims.size() == 2 && w_dims.size() == 2,
-                 "Input(X, Filter) should be 2-D tensor.");
-  PADDLE_ENFORCE(x_dims.size() == 2 && w_dims.size() == 2,
-                 "Input(X, Filter) should be 2-D tensor.");
-  PADDLE_ENFORCE(w_dims[0] == context_length * x_dims[1],
-                 "Filter's height should be context_length * "
-                 "input_hidden_size .");
-  PADDLE_ENFORCE_GT(context_length + ctx->Attrs().Get<int>("contextStart"), 0,
-                    "contextStart size should be smaller than contextLength.");
+  PADDLE_ENFORCE_EQ(ctx->Attrs().Get<int>("contextStride"), 1,
+                    platform::errors::InvalidArgument(
+                        "Currently, FusionSeqConvEltAddReluOp only supports "
+                        "contextStride=1, but received value is: %d.",
+                        ctx->Attrs().Get<int>("contextStride")));
+
+  PADDLE_ENFORCE_EQ(
+      x_dims.size(), 2,
+      platform::errors::InvalidArgument(
+          "Input(X) should be 2-D tensor, but reveiced value is: %d.",
+          x_dims.size()));
+
+  PADDLE_ENFORCE_EQ(
+      w_dims.size(), 2,
+      platform::errors::InvalidArgument(
+          "Filter should be 2-D tensor, but reveiced value is: %d.",
+          w_dims.size()));
+
+  PADDLE_ENFORCE_EQ(w_dims[0], context_length * x_dims[1],
+                    platform::errors::InvalidArgument(
+                        "Filter's height should be equal to context_length * "
+                        "input_hidden_size, but received Filter height is: %d,"
+                        "context_length is: %d, input_hidden_size is: %d.",
+                        w_dims[0], context_length, x_dims[1]));
+
+  PADDLE_ENFORCE_GT(
+      context_length + ctx->Attrs().Get<int>("contextStart"), 0,
+      platform::errors::InvalidArgument(
+          "contextStart size should be smaller than contextLength, "
+          "but received context_length is: %d, contextStart is: "
+          "%d.",
+          context_length, ctx->Attrs().Get<int>("contextStart")));
 
   ctx->SetOutputDim("Out", {x_dims[0], w_dims[1]});
   ctx->SetOutputDim("ColMat", {x_dims[0], w_dims[0]});
@@ -130,10 +147,17 @@ class FusionSeqConvEltAddReluKernel : public framework::OpKernel<T> {
     auto x_lod = x->lod();
     auto x_dims = x->dims();
     auto w_dims = w->dims();
-    PADDLE_ENFORCE_EQ(b->numel(), w_dims[1],
-                      "bias size should be equal to output feature size.");
-    PADDLE_ENFORCE_EQ(x_lod.size(), 1UL,
-                      "Only support one level sequence now.");
+    PADDLE_ENFORCE_EQ(
+        b->numel(), w_dims[1],
+        platform::errors::InvalidArgument(
+            "bias size should be equal to weights feature size, but received "
+            "bias size is: %d, weights feature size is: %d.",
+            b->numel(), w_dims[1]));
+    PADDLE_ENFORCE_EQ(
+        x_lod.size(), 1UL,
+        platform::errors::InvalidArgument(
+            "Only support one level sequence now, but received value is: %d.",
+            x_lod.size()));
 
     const T* x_data = x->data<T>();
     const T* w_data = w->data<T>();
@@ -183,7 +207,12 @@ class FusionSeqConvEltAddReluKernel : public framework::OpKernel<T> {
           copy_size -= src_mat_w_sz;
         }
       } else {
-        PADDLE_ENFORCE_GE(context_length, up_pad + down_pad + 1);
+        PADDLE_ENFORCE_GE(context_length, up_pad + down_pad + 1,
+                          platform::errors::InvalidArgument(
+                              "context length must be bigger or equal than "
+                              "up_pad + down_pad + 1, but received context "
+                              "length is: %d, up_pad is: %d, down_pad is: %d.",
+                              context_length, up_pad, down_pad));
         std::memset(dst_data, 0, seq_len * col_mat_w_sz);
         dst_data = dst_data + up_pad * src_mat_w;
         int zero_sz = up_pad * src_mat_w_sz;

paddle/fluid/operators/fused/fusion_seqexpand_concat_fc_op.cc

@@ -24,38 +24,59 @@ namespace operators {
 
 void FusionSeqExpandConcatFCOp::InferShape(
     framework::InferShapeContext* ctx) const {
-  PADDLE_ENFORCE_GT(
-      ctx->Inputs("X").size(), 1UL,
-      "Inputs(X) of FusionSeqExpandConcatFCOp should larger than 1.");
-  PADDLE_ENFORCE(
-      ctx->HasInput("FCWeight"),
-      "Input(FCWeight) of FusionSeqExpandConcatFCOp should not be null.");
-  PADDLE_ENFORCE(
-      ctx->HasOutput("Out"),
-      "Output(Out) of FusionSeqExpandConcatFCOp should not be null.");
-  PADDLE_ENFORCE(
-      ctx->HasOutput("FCOut"),
-      "Output(FCOut) of FusionSeqExpandConcatFCOp should not be null.");
+  PADDLE_ENFORCE_GT(ctx->Inputs("X").size(), 1UL,
+                    platform::errors::InvalidArgument(
+                        "Inputs(X) of FusionSeqExpandConcatFCOp should larger "
+                        "than 1, but received value is: %d.",
+                        ctx->Inputs("X").size()));
+  OP_INOUT_CHECK(ctx->HasInput("FCWeight"), "Input", "FCWeight",
+                 "fusion_seqexpand_concat_fc");
+  OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out",
+                 "fusion_seqexpand_concat_fc");
+  OP_INOUT_CHECK(ctx->HasOutput("FCOut"), "Output", "FCOut",
+                 "fusion_seqexpand_concat_fc");
 
   auto ins_dims = ctx->GetInputsDim("X");
   auto w_dims = ctx->GetInputDim("FCWeight");  // (M0+M1+M2+..) x D
-  PADDLE_ENFORCE_EQ(w_dims.size(), 2, "Input(FCWeight)'s rank must be 2.");
+  PADDLE_ENFORCE_EQ(
+      w_dims.size(), 2,
+      platform::errors::InvalidArgument(
+          "Input(FCWeight)'s rank must be 2, but received value is: %d.",
+          w_dims.size()));
   const int D = w_dims[1];
   int sum = ins_dims[0][1];
   for (size_t i = 1; i < ins_dims.size(); ++i) {
     sum += ins_dims[i][1];
   }
-  PADDLE_ENFORCE_EQ(sum, w_dims[0],
-                    "FC height should be sum of all inputs width.");
+  PADDLE_ENFORCE_EQ(sum, w_dims[0], platform::errors::InvalidArgument(
+                                        "FC height should be sum of all inputs "
+                                        "width, but received FC height is: %d, "
+                                        "sum of all inputs width is: %d.",
+                                        w_dims[0], sum));
   if (ctx->HasInput("FCBias")) {
     auto b_dims = ctx->GetInputDim("FCBias");
-    PADDLE_ENFORCE(b_dims.size() == 1 || b_dims.size() == 2,
-                   "b_dims should be 1 or 2, get %d", b_dims.size());
+    PADDLE_ENFORCE_EQ(
+        b_dims.size() == 1 || b_dims.size() == 2, true,
+        platform::errors::InvalidArgument(
+            "FCBias dim should be 1 or 2, but received value is: %d.",
+            b_dims.size()));
     if (b_dims.size() == 1) {
-      PADDLE_ENFORCE_EQ(b_dims[0], D, "FCBias shapes must be %d.", D);
+      PADDLE_ENFORCE_EQ(b_dims[0], D,
+                        platform::errors::InvalidArgument(
+                            "FCBias shapes must be %d when FCBias dim = 1, but "
+                            "received value is: %d.",
+                            D, b_dims[0]));
     } else {
-      PADDLE_ENFORCE_EQ(b_dims[0], 1, "FCBias shapes must be 1x%d.", D);
-      PADDLE_ENFORCE_EQ(b_dims[1], D, "FCBias shapes must be 1x%d.", D);
+      PADDLE_ENFORCE_EQ(b_dims[0], 1,
+                        platform::errors::InvalidArgument(
+                            "FCBias shapes must be 1x%d, when FCBias dim = 2, "
+                            "but received dim[0] is: %d.",
+                            D, b_dims[0]));
+      PADDLE_ENFORCE_EQ(b_dims[1], D,
+                        platform::errors::InvalidArgument(
+                            "FCBias shapes must be 1x%d, when FCBias dim = 2, "
+                            "but received dim[1] is: %d.",
+                            D, b_dims[1]));
     }
   }
 
@@ -133,18 +154,42 @@ class FusionSeqExpandConcatFCOpKernel : public framework::OpKernel<T> {
 
     // some check and fcout should be reshape here
     // since infershape can not get lod info
-    PADDLE_ENFORCE_EQ(ref_lod.size(), 1UL, "Only support input lod size is 1.");
-    PADDLE_ENFORCE_EQ(in1_lod.size(), 1UL, "Only support input lod size is 1.");
+    PADDLE_ENFORCE_EQ(
+        ref_lod.size(), 1UL,
+        platform::errors::InvalidArgument(
+            "Only support input lod size is 1, but received value is: %d.",
+            ref_lod.size()));
+    PADDLE_ENFORCE_EQ(
+        in1_lod.size(), 1UL,
+        platform::errors::InvalidArgument(
+            "Only support input lod size is 1, but received value is: %d.",
+            in1_lod.size()));
     PADDLE_ENFORCE_EQ(static_cast<int>(in1_lod[0].size() - 1), N,
-                      "Batch size of all inputs should be equal.");
-    PADDLE_ENFORCE_EQ(static_cast<int>(in1_lod[0][N]), N,
-                      "Seq_length of other inputs should be 1.");
-    PADDLE_ENFORCE_EQ(in1_dims[0], N, "input height should be batch size.");
+                      platform::errors::InvalidArgument(
+                          "Batch size of all inputs should be equal to %d, but "
+                          "received value is: %d.",
+                          N, static_cast<int>(in1_lod[0].size() - 1)));
+    PADDLE_ENFORCE_EQ(
+        static_cast<int>(in1_lod[0][N]), N,
+        platform::errors::InvalidArgument("Seq_length of other inputs should "
+                                          "be %d, but received value is: %d.",
+                                          N, static_cast<int>(in1_lod[0][N])));
+    PADDLE_ENFORCE_EQ(
+        in1_dims[0], N,
+        platform::errors::InvalidArgument(
+            "input height should be batch size: %d, but received value is %d.",
+            N, in1_dims[0]));
     for (size_t i = 2; i < ins.size(); ++i) {
       PADDLE_ENFORCE_EQ(ins[i]->dims()[0], N,
-                        "All other inputs height should be equal");
+                        platform::errors::InvalidArgument(
+                            "All other inputs height should be equal to %d, "
+                            "but received value is: %d.",
+                            N, ins[i]->dims()[0]));
       PADDLE_ENFORCE_EQ(ins[i]->lod(), in1_lod,
-                        "All other inputs should have same lod");
+                        platform::errors::InvalidArgument(
+                            "All other inputs should have same lod: %d, but "
+                            "received value is: %d.",
+                            in1_lod, ins[i]->lod()));
     }
     fc_out->Resize({N, D});