class_docstr: Riva NLP Services implement task-specific APIs for popular NLP tasks including
  intent recognition (as well as slot filling), and entity extraction.
class_docstr_tok: ["Riva","NLP","Services","implement","task-specific","APIs","for","popular","NLP","tasks","including","intent","recognition","(","as","well","as","slot","filling",")",",","and","entity","extraction","."]
code: def TranslateText(
      request,
      target,
      options=(),
      channel_credentials=None,
      call_credentials=None,
      insecure=False,
      compression=None,
      wait_for_ready=None,
      timeout=None,
      metadata=None,
  ):
      return grpc.experimental.unary_unary(
          request,
          target,
          "/nvidia.riva.nmt.RivaTranslate/TranslateText",
          nmt__pb2.TranslateTextRequest.SerializeToString,
          nmt__pb2.TranslateTextResponse.FromString,
          options,
          channel_credentials,
          insecure,
          call_credentials,
          compression,
          wait_for_ready,
          timeout,
          metadata,
      )
  
file_path: NeMo/tools/nmt_grpc_service/api/nmt_pb2_grpc.py
imports: import grpc
  from .None import nmt_pb2
label_desc: Use image node_id 1 for calling the RivaTranslate obj's underlying member method code with example usage: obj.TranslateText(request, target, options, channel_credentials, call_credentials, insecure, compression, wait_for_ready, timeout, metadata) and returns: grpc