diff --git a/tensorflow_text/core/kernels/constrained_sequence_kernel.cc b/tensorflow_text/core/kernels/constrained_sequence_kernel.cc index ceb02fa09..160af2494 100644 --- a/tensorflow_text/core/kernels/constrained_sequence_kernel.cc +++ b/tensorflow_text/core/kernels/constrained_sequence_kernel.cc @@ -62,8 +62,7 @@ absl::Status ValidateConstraintTensor(const Tensor &tensor, const bool use_start_end_states, const string &name) { if (tensor.shape().dims() != 2) { - return InvalidArgument( - tensorflow::strings::StrCat(name, " must be of rank 2")); + return InvalidArgument(absl::StrCat(name, " must be of rank 2")); } int expected_size = use_start_end_states ? num_states + 1 : num_states; if (tensor.shape().dim_size(0) != expected_size) { @@ -110,7 +109,7 @@ class ConstrainedSequence : public OpKernel { const int num_scores = scores.num_scores(); OP_REQUIRES(context, lengths_tensor.NumElements() == batch_size, - InvalidArgument(tensorflow::strings::StrCat( + InvalidArgument(absl::StrCat( "There should be exactly one length for every batch " "element. Found ", lengths_tensor.NumElements(), diff --git a/tensorflow_text/core/kernels/sentencepiece_kernels.cc b/tensorflow_text/core/kernels/sentencepiece_kernels.cc index 4cc91495b..21b12fe32 100644 --- a/tensorflow_text/core/kernels/sentencepiece_kernels.cc +++ b/tensorflow_text/core/kernels/sentencepiece_kernels.cc @@ -68,14 +68,14 @@ struct SentencepieceResource : public ResourceBase { (reverse == this->reverse); } - Status AsGraphDef(GraphDefBuilder* builder, Node** out) const override { + sentencepiece::util::Status AsGraphDef(GraphDefBuilder* builder, Node** out) const override { absl::ReaderMutexLock l(&mu); // We set use_node_name_sharing with a unique node name so that the resource // can outlive the kernel. This means that the lifetime of the re-created // resource will be tied to the lifetime of the resource manager it is // created in. static std::atomic counter(0); - std::string unique_node_name = strings::StrCat( + std::string unique_node_name = absl::StrCat( "SentencepieceResourceFromGraphDef", "/", counter.fetch_add(1)); std::string model = processor.model_proto().SerializeAsString(); *out = ops::SourceOp( @@ -94,10 +94,10 @@ struct SentencepieceResource : public ResourceBase { // TODO(broken) Determine a medium cost of a call to the SentencePiece processor constexpr int64 kCostPerUnit = 10000; -::tensorflow::Status ToTFStatus(const sentencepiece::util::Status& s) { - if (s.ok()) return ::tensorflow::Status(); - return ::tensorflow::Status(static_cast<::absl::StatusCode>(s.code()), - ::tensorflow::string(s.message())); +absl::Status ToTFStatus(const sentencepiece::util::Status& s) { + if (s.ok()) return sentencepiece::util::Status(); + return sentencepiece::util::Status(static_cast<::absl::StatusCode>(s.code()), + ::tensorflow::string(s.message())); } template @@ -115,8 +115,8 @@ int32 GetPieceOrId( return sp.id(); } -tensorflow::Status HandleExtraOptions(OpKernelContext* ctx, - SentencepieceResource* sp) { +absl::Status HandleExtraOptions(OpKernelContext* ctx, + SentencepieceResource* sp) { const Tensor* add_bos_tensor = nullptr; TF_RETURN_IF_ERROR(ctx->input("add_bos", &add_bos_tensor)); const bool add_bos = add_bos_tensor->scalar()(); @@ -210,7 +210,7 @@ class SentencepieceOp : public OpKernel { GetNodeAttr(this->def(), "model", &model_proto_attr)); if (TF_PREDICT_FALSE(model_proto_attr.empty())) { - return Status(tensorflow::errors::InvalidArgument( + return sentencepiece::util::Status(tensorflow::errors::InvalidArgument( "Model argument must be specified.")); } // Loads serialized sentencepiece model proto to enable embedding