class_docstr: Sample negative spot and asoc to construct SSI
class_docstr_tok: ["Sample","negative","spot","and","asoc","to","construct","SSI"]
code: def full_spot(self, shuffle=False):
      # Random Prompt + Shuffle
      if not self.ordered_prompt and shuffle:
          ordered_prompt = False
      else:
          ordered_prompt = True
      return self.convert_prefix(
          candidates=self.spot_list,
          prompt=self.spot_prompt,
          mapper=self.spot_dict,
          ordered_prompt=ordered_prompt,
      )
  
imports: import os
  from dataclasses import dataclass
  import torch
  import logging
  import random
  import math
  from typing import Optional, Union
  from collections import OrderedDict
  from transformers import PreTrainedTokenizerBase, PreTrainedModel
  from transformers.file_utils import PaddingStrategy
  from ...extraction.record_schema import RecordSchema
  from ...extraction.dataset_processer import spot_prompt, asoc_prompt
  from ...extraction.constants import BaseStructureMarker, text_start
  from ...extraction.utils import convert_to_record_function
  from ...extraction.noiser.spot_asoc_noiser import SpotAsocNoiser
label_desc: Use image node_id 6 for calling the DynamicSSIGenerator obj's underlying member method code with example usage: obj.full_spot(shuffle) and returns: self