class_docstr: Client for the Microsoft's Megatron-Turing NLG models (https://arxiv.org/abs/2201.11990).
  
  According to the internal documentation: https://github.com/microsoft/turing-academic-TNLG,
  "the model will generate roughly 3 tokens per second. The response will be returned once
  all tokens have been generated."
code: def decode(self, request: DecodeRequest) -> DecodeRequestResult:
      raise NotImplementedError("Use the HuggingFaceClient to decode.")
  
file_path: H2O/h2o_hf/helm/src/helm/proxy/clients/microsoft_client.py
imports: from typing import List, Optional, Dict
  from filelock import FileLock
  from openai.api_resources.abstract import engine_api_resource
  import openai
  from helm.common.cache import Cache, CacheConfig
  from helm.common.request import EMBEDDING_UNAVAILABLE_REQUEST_RESULT, Request, RequestResult, Sequence, Token
  from helm.common.tokenization_request import TokenizationRequest, TokenizationRequestResult, DecodeRequest, DecodeRequestResult
  from .client import Client, wrap_request_time, truncate_sequence
  from .openai_client import ORIGINAL_COMPLETION_ATTRIBUTES
label_desc: Use image node_id 5 for calling the MicrosoftClient obj's underlying member method code with example usage: obj.decode(request) without return types