Op (FusedEmbeddingSeqPool) error message enhancement. (#23454)

paddle/fluid/operators/fused/fused_embedding_seq_pool_op.cc

@@ -24,30 +24,47 @@ class FusedEmbeddingSeqPoolOp : public framework::OperatorWithKernel {
   using framework::OperatorWithKernel::OperatorWithKernel;
 
   void InferShape(framework::InferShapeContext* ctx) const override {
-    PADDLE_ENFORCE(ctx->HasInput("W"),
-                   "Input W of FusedEmbeddingSeqPoolOp should not be null.");
-    PADDLE_ENFORCE(ctx->HasInput("Ids"),
-                   "Input Ids of FusedEmbeddingSeqPoolOp should not be null.");
-    PADDLE_ENFORCE(ctx->HasOutput("Out"),
-                   "Output of FusedEmbeddingSeqPoolOp should not be null.");
-
+    OP_INOUT_CHECK(ctx->HasInput("W"), "Input", "W", "FusedEmbeddingSeqPool");
+    OP_INOUT_CHECK(ctx->HasInput("Ids"), "Input", "Ids",
+                   "FusedEmbeddingSeqPool");
+    OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out",
+                   "FusedEmbeddingSeqPool");
     auto table_dims = ctx->GetInputDim("W");
     auto ids_dims = ctx->GetInputDim("Ids");
     const std::string& combiner = ctx->Attrs().Get<std::string>("combiner");
 
-    PADDLE_ENFORCE_EQ(table_dims.size(), 2);
-    PADDLE_ENFORCE_GE(ids_dims.size(), 1,
-                      "The dim size of the 'Ids' tensor must greater than 1.");
-    PADDLE_ENFORCE_EQ(ids_dims[ids_dims.size() - 1], 1,
-                      "The last dimension of the 'Ids' tensor must be 1.");
+    PADDLE_ENFORCE_EQ(table_dims.size(), 2,
+                      platform::errors::InvalidArgument(
+                          "The dim size of the input tensor 'W' should be 2. "
+                          "But received W's size = %d.",
+                          table_dims.size()));
+    PADDLE_ENFORCE_GE(
+        ids_dims.size(), 1,
+        platform::errors::InvalidArgument(
+            "The dim size of the input tensor 'Ids' should be greater "
+            "than or equal to 1. But received Ids's size = %d.",
+            ids_dims.size()));
+    PADDLE_ENFORCE_EQ(
+        ids_dims[ids_dims.size() - 1], 1,
+        platform::errors::InvalidArgument(
+            "The last dimension of the input tensor 'Ids' should be 1. "
+            "But received Ids's size in the last dimension = %d.",
+            ids_dims[ids_dims.size() - 1]));
     // we only support sum now
-    PADDLE_ENFORCE_EQ(combiner, "sum");
+    PADDLE_ENFORCE_EQ(combiner, "sum",
+                      platform::errors::Unimplemented(
+                          "The pooling type of sequence_pool only support sum "
+                          "now. So the 'combiner' must be 'sum'."));
 
     int64_t last_dim = FusedEmbeddingSeqPoolLastDim(table_dims, ids_dims);
     // in compile time, the lod level of ids must be 1
     framework::VarDesc* ids_desc =
         boost::get<framework::VarDesc*>(ctx->GetInputVarPtrs("Ids")[0]);
-    PADDLE_ENFORCE_EQ(ids_desc->GetLoDLevel(), 1);
+    PADDLE_ENFORCE_EQ(ids_desc->GetLoDLevel(), 1,
+                      platform::errors::InvalidArgument(
+                          "In compile time, the LoD Level of Ids should be 1. "
+                          "But received the LoD Level of Ids = %d.",
+                          ids_desc->GetLoDLevel()));
 
     // in compile time, the shape from Ids -> output
     // should be [-1, 1] -> [-1, embedding_size]

paddle/fluid/operators/fused/fused_embedding_seq_pool_op.h

@@ -90,8 +90,17 @@ struct EmbeddingVSumFunctor {
     int64_t idx_width = ids_t->numel() / ids_lod.back();
     auto *output = output_t->mutable_data<T>(context.GetPlace());
 
-    PADDLE_ENFORCE_LE(table_width * idx_width, out_width);
-    PADDLE_ENFORCE_GT(ids_lod.size(), 1UL, "The LoD[0] could NOT be empty");
+    PADDLE_ENFORCE_LE(table_width * idx_width, out_width,
+                      platform::errors::InvalidArgument(
+                          "table_width * idx_width should be less than or "
+                          "equal to out_width. But received "
+                          "table_width * idx_width = %s, out_width = %d.",
+                          table_width * idx_width, out_width));
+    PADDLE_ENFORCE_GT(ids_lod.size(), 1UL,
+                      platform::errors::InvalidArgument(
+                          "The tensor ids's LoD[0] should be greater than 1. "
+                          "But received the ids's LoD[0] = %d.",
+                          ids_lod.size()));
 
     jit::emb_seq_pool_attr_t attr(table_height, table_width, 0, idx_width,
                                   out_width, jit::SeqPoolType::kSum);
@@ -130,7 +139,10 @@ class FusedEmbeddingSeqPoolKernel : public framework::OpKernel<T> {
     const auto &ids_lod = ids_t->lod();
     // in run time, the LoD of ids must be 1
     PADDLE_ENFORCE_EQ(ids_lod.size(), 1UL,
-                      "The LoD level of Input(Ids) must be 1");
+                      platform::errors::InvalidArgument(
+                          "The LoD level of Input(Ids) should be 1. But "
+                          "received Ids's LoD level = %d.",
+                          ids_lod.size()));
     int64_t batch_size = ids_lod[0].size() - 1;
     // in run time, the shape from Ids -> output
     // should be [seq_length, 1] -> [batch_size, last_dim]
@@ -244,7 +256,10 @@ class FusedEmbeddingSeqPoolGradKernel : public framework::OpKernel<T> {
 
       const auto &ids_lod = ids->lod();
       PADDLE_ENFORCE_EQ(ids_lod.size(), 1UL,
-                        "The LoD level of Input(Ids) must be 1");
+                        platform::errors::InvalidArgument(
+                            "The LoD level of Input(Ids) should be 1. But "
+                            "received Ids's LoD level = %d.",
+                            ids_lod.size()));
       const std::vector<uint64_t> offset = ids_lod[0];
       auto len = ids->numel();
       int idx_width = len / offset.back();