class_docstr: A class containing all functions for auto-regressive text generation, to be used as a mixin in [`PreTrainedModel`].
  
  The class exposes [`~generation_utils.GenerationMixin.generate`], which can be used for:
      - *greedy decoding* by calling [`~generation_utils.GenerationMixin.greedy_search`] if `num_beams=1` and
        `do_sample=False`.
      - *contrastive search* by calling [`~generation_utils.GenerationMixin.contrastive_search`] if `penalty_alpha>0`
        and `top_k>1`
      - *multinomial sampling* by calling [`~generation_utils.GenerationMixin.sample`] if `num_beams=1` and
        `do_sample=True`.
      - *beam-search decoding* by calling [`~generation_utils.GenerationMixin.beam_search`] if `num_beams>1` and
        `do_sample=False`.
      - *beam-search multinomial sampling* by calling [`~generation_utils.GenerationMixin.beam_sample`] if
        `num_beams>1` and `do_sample=True`.
      - *diverse beam-search decoding* by calling [`~generation_utils.GenerationMixin.group_beam_search`], if
        `num_beams>1` and `num_beam_groups>1`.
      - *constrained beam-search decoding* by calling [`~generation_utils.GenerationMixin.constrained_beam_search`],
        if `constraints!=None` or `force_words_ids!=None`.
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docstr: Confirms that the model class is compatible with generation. If not, raises an exception that points to the
  right class to use.
docstr_tok: ["Confirms","that","the","model","class","is","compatible","with","generation",".","If","not",",","raises","an","exception","that","points","to","the","right","class","to","use","."]
code: def _validate_model_class(self):
      """
      Confirms that the model class is compatible with generation. If not, raises an exception that points to the
      right class to use.
      """
      if not hasattr(self, "prepare_inputs_for_generation"):
          generate_compatible_mappings = [
              MODEL_FOR_CAUSAL_LM_MAPPING,
              MODEL_FOR_CAUSAL_IMAGE_MODELING_MAPPING,
              MODEL_FOR_VISION_2_SEQ_MAPPING,
              MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
              MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING,
          ]
          generate_compatible_classes = set()
          for model_mapping in generate_compatible_mappings:
              supported_models = model_mapping.get(
                  type(self.config), default=None
              )
              if supported_models is not None:
                  generate_compatible_classes.add(
                      supported_models.__name__
                  )
          exception_message = (
              f"The current model class ({self.__class__.__name__}) is not compatible with `.generate()`, as "
              "it doesn't have a language model head."
          )
          if generate_compatible_classes:
              exception_message += f" Please use one of the following classes instead: {generate_compatible_classes}"
          raise TypeError(exception_message)
  
imports: import inspect
  import warnings
  from dataclasses import dataclass
  from typing import Any, Callable, Dict, Iterable, List, Optional, Tuple, Union
  import torch
  import torch.distributed
  from torch import nn
  from flexgen.timer import timers
  from .generation_beam_constraints import Constraint, DisjunctiveConstraint, PhrasalConstraint
  from .generation_beam_search import BeamScorer, BeamSearchScorer, ConstrainedBeamSearchScorer
  from .generation_logits_process import EncoderNoRepeatNGramLogitsProcessor, ExponentialDecayLengthPenalty, ForcedBOSTokenLogitsProcessor, ForcedEOSTokenLogitsProcessor, ForceTokensLogitsProcessor, HammingDiversityLogitsProcessor, InfNanRemoveLogitsProcessor, LogitNormalization, LogitsProcessorList, MinLengthLogitsProcessor, NoBadWordsLogitsProcessor, NoRepeatNGramLogitsProcessor, PrefixConstrainedLogitsProcessor, RepetitionPenaltyLogitsProcessor, SuppressTokensAtBeginLogitsProcessor, SuppressTokensLogitsProcessor, TemperatureLogitsWarper, TopKLogitsWarper, TopPLogitsWarper, TypicalLogitsWarper
  from .generation_stopping_criteria import MaxLengthCriteria, MaxTimeCriteria, StoppingCriteria, StoppingCriteriaList, validate_stopping_criteria
  from .modeling_outputs import CausalLMOutputWithPast, Seq2SeqLMOutput
  from .models.auto import MODEL_FOR_CAUSAL_IMAGE_MODELING_MAPPING, MODEL_FOR_CAUSAL_LM_MAPPING, MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING, MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING, MODEL_FOR_VISION_2_SEQ_MAPPING
  from .pytorch_utils import torch_int_div
  from .utils import ModelOutput, logging
label_desc: Use image node_id 17 for calling the GenerationMixin obj's underlying member method code with example usage: obj._validate_model_class() without return types