diff --git a/paddle/fluid/inference/capi/pd_predictor.cc b/paddle/fluid/inference/capi/pd_predictor.cc index 0509a6190211c25b6461c1d683daa6b33110b4e0..31915496893e6242dc7cd10ffd48af278d124245 100644 --- a/paddle/fluid/inference/capi/pd_predictor.cc +++ b/paddle/fluid/inference/capi/pd_predictor.cc @@ -130,7 +130,8 @@ bool PD_PredictorZeroCopyRun(const PD_AnalysisConfig* config, VLOG(3) << "The inputs' size is " << input_names.size(); PADDLE_ENFORCE_EQ( input_names.size(), in_size, - "The number of input and the number of model's input must match. "); + paddle::platform::errors::InvalidArgument( + "The number of input and the number of model's input must match.")); for (int i = 0; i < in_size; ++i) { auto input_t = predictor->GetInputTensor(inputs[i].name); std::vector tensor_shape; diff --git a/paddle/fluid/operators/fused/fusion_seqpool_cvm_concat_op.cc b/paddle/fluid/operators/fused/fusion_seqpool_cvm_concat_op.cc index f64e4f134d62f125e3e781ebf43163a566587d58..ecb7db46a9d8159b8da124e941cc69522f64cd57 100644 --- a/paddle/fluid/operators/fused/fusion_seqpool_cvm_concat_op.cc +++ b/paddle/fluid/operators/fused/fusion_seqpool_cvm_concat_op.cc @@ -24,20 +24,27 @@ void FusionSeqPoolCVMConcatOp::InferShape( framework::InferShapeContext* ctx) const { PADDLE_ENFORCE_GE( ctx->Inputs("X").size(), 1UL, - "Inputs(X) of FusionSeqPoolCVMConcatOp should not be empty."); - PADDLE_ENFORCE(ctx->HasOutput("Out"), - "Output(Out) of FusionSeqPoolCVMConcatOp should not be null."); + paddle::platform::errors::InvalidArgument( + "Inputs(X) of FusionSeqPoolCVMConcatOp should not be empty.")); + PADDLE_ENFORCE( + ctx->HasOutput("Out"), + paddle::platform::errors::InvalidArgument( + "Output(Out) of FusionSeqPoolCVMConcatOp should not be null.")); int axis = ctx->Attrs().Get("axis"); PADDLE_ENFORCE_EQ( - axis, 1, "FusionSeqPoolCVMConcatOp only supports concat axis=1 yet."); + axis, 1, + paddle::platform::errors::InvalidArgument( + "FusionSeqPoolCVMConcatOp only supports concat axis=1 yet.")); bool use_cvm = ctx->Attrs().Get("use_cvm"); PADDLE_ENFORCE_EQ( use_cvm, true, - "FusionSeqPoolCVMConcatOp only supports use_cvm is true yet."); + paddle::platform::errors::InvalidArgument( + "FusionSeqPoolCVMConcatOp only supports use_cvm is true yet.")); auto ins_dims = ctx->GetInputsDim("X"); const size_t n = ins_dims.size(); - PADDLE_ENFORCE_GT(n, 0UL, "Input tensors count should > 0."); + PADDLE_ENFORCE_GT(n, 0UL, paddle::platform::errors::InvalidArgument( + "Input tensors count should > 0.")); if (n == 1) { LOG(WARNING) << "Only have one input, may waste memory"; } @@ -45,7 +52,8 @@ void FusionSeqPoolCVMConcatOp::InferShape( // The output height should be confirmed in Compute, // since input lod is not accessible here. PADDLE_ENFORCE_EQ(ins_dims[0].size(), 2, - "The dims size of first input should be 2."); + paddle::platform::errors::InvalidArgument( + "The dims size of first input should be 2.")); ctx->SetOutputDim("Out", {-1, ins_dims[0][axis] * static_cast(n)}); } @@ -99,7 +107,8 @@ class FusionSeqPoolCVMConcatKernel : public framework::OpKernel { int w = ins[0]->numel() / x0_dims[0]; PADDLE_ENFORCE_EQ(y_dims[1] % w, 0, - "The output of dims[1] should be dividable of w"); + paddle::platform::errors::InvalidArgument( + "The output of dims[1] should be dividable of w")); jit::seq_pool_attr_t attr(w, jit::SeqPoolType::kSum); if (pooltype == "AVERAGE") { attr.type = jit::SeqPoolType::kAvg; @@ -117,9 +126,11 @@ class FusionSeqPoolCVMConcatKernel : public framework::OpKernel { const T* src = ins[i]->data(); T* dst = y_data + i * w; PADDLE_ENFORCE_EQ(static_cast(ins[i]->numel() / x_dims[0]), w, - "Width of all inputs should be equal."); + paddle::platform::errors::InvalidArgument( + "Width of all inputs should be equal.")); PADDLE_ENFORCE_EQ(x_lod.size(), bs + 1, - "Batchsize of all inputs should be equal."); + paddle::platform::errors::InvalidArgument( + "Batchsize of all inputs should be equal.")); for (size_t j = 0; j < bs; ++j) { attr.h = static_cast(x_lod[j + 1] - x_lod[j]); seqpool(src, dst, &attr);