class_docstr: Each `Instance` in a `Scenario` looks like this:
  
      <input> -> <reference1>
                 <reference2>
                 <reference3> [correct]
                 <reference4>
  
  For generation, the language model will generate the output.
  
      <instructions>
  
      Input: <input>                  # train
      Output: <reference>
  
      Input: <input>                  # test
      Output:
  
  In general, each example is:
  
      <input_prefix><input><output_prefix><output>
code: def generate_requests(
      self, eval_instance: Instance
  ) -> List[RequestState]:
      prompt: Prompt = self.construct_prompt(
          self.train_instances,
          eval_instance,
          include_output=False,
          reference_index=None,
      )
      request = Request(
          model=self.adapter_spec.model,
          prompt=prompt.text,
          num_completions=self.adapter_spec.num_outputs,
          temperature=self.adapter_spec.temperature,
          max_tokens=self.adapter_spec.max_tokens,
          stop_sequences=self.adapter_spec.stop_sequences,
          random=self.adapter_spec.random,
      )
      request_state = RequestState(
          instance=eval_instance,
          reference_index=None,
          request_mode=None,
          train_trial_index=self.train_trial_index,
          output_mapping=None,
          request=request,
          result=None,
          num_train_instances=prompt.num_train_instances,
          prompt_truncated=prompt.truncated,
      )
      return [request_state]
  
file_path: H2O/h2o_hf/helm/src/helm/benchmark/adaptation/adapters/generation_adapter.py
imports: from typing import List
  from helm.benchmark.adaptation.prompt import Prompt
  from helm.benchmark.adaptation.request_state import RequestState
  from helm.benchmark.scenarios.scenario import Instance
  from helm.common.request import Request
  from .in_context_learning_adapter import InContextLearningAdapter
label_desc: Use image node_id 1 for calling the GenerationAdapter obj's underlying member method code with example usage: obj.generate_requests(eval_instance) and returns: list