class_docstr: Blueprint for a task that asks humans to compare conversational outputs.
class_docstr_tok: ["Blueprint","for","a","task","that","asks","humans","to","compare","conversational","outputs","."]
docstr: Return the InitializationData retrieved from the specified stream.
docstr_tok: ["Return","the","InitializationData","retrieved","from","the","specified","stream","."]
code: def get_initialization_data(self) -> Iterable["InitializationData"]:
      """
      Return the InitializationData retrieved from the specified stream.
      """
      # TODO(#99) once we can release HITs over time, configure this to
      # release as many as needed thusfar and top off when
      # onboardings fail
      num_conversations = math.ceil(
          self.args.blueprint.num_matchup_pairs
          / max((self.args.blueprint.subtasks_per_unit - 1), 1)
      )  # release enough hits to finish all annotations requested
      return [
          InitializationData(shared={}, unit_data=[{}])
          for _ in range(num_conversations)
      ]
  
file_path: ParlAI/parlai/crowdsourcing/tasks/acute_eval/acute_eval_blueprint.py
imports: import os
  import math
  from dataclasses import dataclass, field
  from typing import ClassVar, List, Type, Any, Dict, Iterable, TYPE_CHECKING
  from mephisto.abstractions.blueprint import Blueprint, BlueprintArgs, SharedTaskState
  from mephisto.data_model.assignment import InitializationData
  from mephisto.operations.registry import register_mephisto_abstraction
  from omegaconf import MISSING, DictConfig
  from parlai.crowdsourcing.tasks.acute_eval.acute_eval_agent_state import AcuteEvalAgentState
  from parlai.crowdsourcing.tasks.acute_eval.acute_eval_builder import AcuteEvalBuilder
  from parlai.crowdsourcing.tasks.acute_eval.acute_eval_runner import AcuteEvalRunner
  from parlai.utils.misc import warn_once
label_desc: Use image node_id 3 for calling the AcuteEvalBlueprint obj's underlying member method code with example usage: obj.get_initialization_data() and returns: unknown