docstr: Counts the total number of tokens using the suggestion here:
  https://community.openai.com/t/how-do-i-calculate-the-pricing-for-generation-of-text/11662/5
code: def count_tokens(
      self, request: Request, completions: List[Sequence]
  ) -> int:
      """
      Counts the total number of tokens using the suggestion here:
      https://community.openai.com/t/how-do-i-calculate-the-pricing-for-generation-of-text/11662/5
      """
      tokenized_prompt: TokenizationRequestResult = (
          self.huggingface_client.tokenize(
              TokenizationRequest(request.prompt)
          )
      )
      # Number of tokens in the prompt + number of tokens in all the completions
      return len(tokenized_prompt.tokens) + sum(
          [len(sequence.tokens) for sequence in completions]
      )
  
file_path: H2O/h2o_hf/helm/src/helm/proxy/token_counters/openai_token_counter.py
imports: from typing import List
  from helm.common.request import Request, Sequence
  from helm.common.tokenization_request import TokenizationRequest, TokenizationRequestResult
  from helm.proxy.clients.huggingface_client import HuggingFaceClient
  from .token_counter import TokenCounter
label_desc: Use image node_id 2 for calling the OpenAITokenCounter obj's underlying member method code with example usage: obj.count_tokens(request, completions) and returns: unknown