


"""simple docstring"""

from collections.abc import Callable





class    lowerCamelCase__						:
      def __init__(		self	:	str      ,       A_	:	Callable | None = None							):






       '''simple docstring'''


       __lowercase									=	[]
       # Stores indexes of each item for supporting updates and deletion.
       __lowercase									=	{}
       # Stores current size of heap.
       __lowercase									=	0
       # Stores function used to evaluate the score of an item on which basis ordering
       # will be done.
       __lowercase									=	key or (lambda A_							: x)
      def SCREAMING_SNAKE_CASE_	(		self	:	List[Any]      ,       A_	:	int							):






       '''simple docstring'''


       return int((i - 1) / 2							) if i > 0 else None
      def SCREAMING_SNAKE_CASE_	(		self	:	Union[str, Any]      ,       A_	:	int							):






       '''simple docstring'''


       __lowercase									=	int(2 * i + 1							)
       return left if 0 < left < self.size else None
      def SCREAMING_SNAKE_CASE_	(		self	:	int      ,       A_	:	int							):






       '''simple docstring'''


       __lowercase									=	int(2 * i + 2							)
       return right if 0 < right < self.size else None
      def SCREAMING_SNAKE_CASE_	(		self	:	int      ,       A_	:	int      ,       A_	:	int							):






       '''simple docstring'''


       __lowercase							,		__lowercase									=	(
           self.pos_map[self.arr[j][0]],
           self.pos_map[self.arr[i][0]],
       )
       # Then swap the items in the list.
       __lowercase							,		__lowercase									=	self.arr[j], self.arr[i]
      def SCREAMING_SNAKE_CASE_	(		self	:	List[Any]      ,       A_	:	int      ,       A_	:	int							):






       '''simple docstring'''


       return self.arr[i][1] < self.arr[j][1]
      def SCREAMING_SNAKE_CASE_	(		self	:	Optional[Any]      ,       A_	:	int							):






       '''simple docstring'''


       __lowercase									=	self._left(A_							)
       __lowercase									=	self._right(A_							)
       __lowercase									=	i

       if left is not None and not self._cmp(A_      ,       A_							):
        __lowercase									=	left
       if right is not None and not self._cmp(A_      ,       A_							):
        __lowercase									=	right

       return valid_parent
      def SCREAMING_SNAKE_CASE_	(		self	:	List[str]      ,       A_	:	int							):






       '''simple docstring'''


       __lowercase									=	self._parent(A_							)
       while parent is not None and not self._cmp(A_      ,       A_							):
        self._swap(A_      ,       A_							)
        __lowercase							,		__lowercase									=	parent, self._parent(A_							)
      def SCREAMING_SNAKE_CASE_	(		self	:	Union[str, Any]      ,       A_	:	int							):






       '''simple docstring'''


       __lowercase									=	self._get_valid_parent(A_							)
       while valid_parent != index:
        self._swap(A_      ,       A_							)
        __lowercase							,		__lowercase									=	valid_parent, self._get_valid_parent(A_							)
      def SCREAMING_SNAKE_CASE_	(		self	:	Any      ,       A_	:	int      ,       A_	:	int							):






       '''simple docstring'''


       if item not in self.pos_map:
        return
       __lowercase									=	self.pos_map[item]
       __lowercase									=	[item, self.key(A_							)]
       # Make sure heap is right in both up and down direction.
       # Ideally only one of them will make any change.
       self._heapify_up(A_							)
       self._heapify_down(A_							)
      def SCREAMING_SNAKE_CASE_	(		self	:	str      ,       A_	:	int							):






       '''simple docstring'''


       if item not in self.pos_map:
        return
       __lowercase									=	self.pos_map[item]
       del self.pos_map[item]
       __lowercase									=	self.arr[self.size - 1]
       __lowercase									=	index
       self.size -= 1
       # Make sure heap is right in both up and down direction. Ideally only one
       # of them will make any change- so no performance loss in calling both.
       if self.size > index:
        self._heapify_up(A_							)
        self._heapify_down(A_							)
      def SCREAMING_SNAKE_CASE_	(		self	:	List[str]      ,       A_	:	int      ,       A_	:	int							):






       '''simple docstring'''


       __lowercase									=	len(self.arr							)
       if arr_len == self.size:
        self.arr.append([item, self.key(A_							)]							)
       else:
        __lowercase									=	[item, self.key(A_							)]
       __lowercase									=	self.size
       self.size += 1
       self._heapify_up(self.size - 1							)
      def SCREAMING_SNAKE_CASE_	(		self	:	str							):






       '''simple docstring'''


       return self.arr[0] if self.size else None






      def SCREAMING_SNAKE_CASE_	(		self	:	int							):






       '''simple docstring'''


       __lowercase									=	self.get_top()
       if top_item_tuple:
        self.delete_item(top_item_tuple[0]							)
       return top_item_tuple






def lowerCAmelCase_      (				):






 """simple docstring"""









if __name__ == "__main__":
       import doctest

       doctest.testmod()




"""simple docstring"""

from collections import OrderedDict

from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES


UpperCAmelCase__  							=logging.get_logger(__name__)


UpperCAmelCase__  							=OrderedDict(
    [
        # Base model mapping
        ("albert", "FlaxAlbertModel"),
        ("bart", "FlaxBartModel"),
        ("beit", "FlaxBeitModel"),
        ("bert", "FlaxBertModel"),
        ("big_bird", "FlaxBigBirdModel"),
        ("blenderbot", "FlaxBlenderbotModel"),
        ("blenderbot-small", "FlaxBlenderbotSmallModel"),
        ("clip", "FlaxCLIPModel"),
        ("distilbert", "FlaxDistilBertModel"),
        ("electra", "FlaxElectraModel"),
        ("gpt-sw3", "FlaxGPT2Model"),
        ("gpt2", "FlaxGPT2Model"),
        ("gpt_neo", "FlaxGPTNeoModel"),
        ("gptj", "FlaxGPTJModel"),
        ("longt5", "FlaxLongT5Model"),
        ("marian", "FlaxMarianModel"),
        ("mbart", "FlaxMBartModel"),
        ("mt5", "FlaxMT5Model"),
        ("opt", "FlaxOPTModel"),
        ("pegasus", "FlaxPegasusModel"),
        ("regnet", "FlaxRegNetModel"),
        ("resnet", "FlaxResNetModel"),
        ("roberta", "FlaxRobertaModel"),
        ("roberta-prelayernorm", "FlaxRobertaPreLayerNormModel"),
        ("roformer", "FlaxRoFormerModel"),
        ("t5", "FlaxT5Model"),
        ("vision-text-dual-encoder", "FlaxVisionTextDualEncoderModel"),
        ("vit", "FlaxViTModel"),
        ("wav2vec2", "FlaxWav2Vec2Model"),
        ("whisper", "FlaxWhisperModel"),
        ("xglm", "FlaxXGLMModel"),
        ("xlm-roberta", "FlaxXLMRobertaModel"),
    ]
)

UpperCAmelCase__  							=OrderedDict(
    [
        # Model for pre-training mapping
        ("albert", "FlaxAlbertForPreTraining"),
        ("bart", "FlaxBartForConditionalGeneration"),
        ("bert", "FlaxBertForPreTraining"),
        ("big_bird", "FlaxBigBirdForPreTraining"),
        ("electra", "FlaxElectraForPreTraining"),
        ("longt5", "FlaxLongT5ForConditionalGeneration"),
        ("mbart", "FlaxMBartForConditionalGeneration"),
        ("mt5", "FlaxMT5ForConditionalGeneration"),
        ("roberta", "FlaxRobertaForMaskedLM"),
        ("roberta-prelayernorm", "FlaxRobertaPreLayerNormForMaskedLM"),
        ("roformer", "FlaxRoFormerForMaskedLM"),
        ("t5", "FlaxT5ForConditionalGeneration"),
        ("wav2vec2", "FlaxWav2Vec2ForPreTraining"),
        ("whisper", "FlaxWhisperForConditionalGeneration"),
        ("xlm-roberta", "FlaxXLMRobertaForMaskedLM"),
    ]
)

UpperCAmelCase__  							=OrderedDict(
    [
        # Model for Masked LM mapping
        ("albert", "FlaxAlbertForMaskedLM"),
        ("bart", "FlaxBartForConditionalGeneration"),
        ("bert", "FlaxBertForMaskedLM"),
        ("big_bird", "FlaxBigBirdForMaskedLM"),
        ("distilbert", "FlaxDistilBertForMaskedLM"),
        ("electra", "FlaxElectraForMaskedLM"),
        ("mbart", "FlaxMBartForConditionalGeneration"),
        ("roberta", "FlaxRobertaForMaskedLM"),
        ("roberta-prelayernorm", "FlaxRobertaPreLayerNormForMaskedLM"),
        ("roformer", "FlaxRoFormerForMaskedLM"),
        ("xlm-roberta", "FlaxXLMRobertaForMaskedLM"),
    ]
)

UpperCAmelCase__  							=OrderedDict(
    [
        # Model for Seq2Seq Causal LM mapping
        ("bart", "FlaxBartForConditionalGeneration"),
        ("blenderbot", "FlaxBlenderbotForConditionalGeneration"),
        ("blenderbot-small", "FlaxBlenderbotSmallForConditionalGeneration"),
        ("encoder-decoder", "FlaxEncoderDecoderModel"),
        ("longt5", "FlaxLongT5ForConditionalGeneration"),
        ("marian", "FlaxMarianMTModel"),
        ("mbart", "FlaxMBartForConditionalGeneration"),
        ("mt5", "FlaxMT5ForConditionalGeneration"),
        ("pegasus", "FlaxPegasusForConditionalGeneration"),
        ("t5", "FlaxT5ForConditionalGeneration"),
    ]
)

UpperCAmelCase__  							=OrderedDict(
    [
        # Model for Image-classsification
        ("beit", "FlaxBeitForImageClassification"),
        ("regnet", "FlaxRegNetForImageClassification"),
        ("resnet", "FlaxResNetForImageClassification"),
        ("vit", "FlaxViTForImageClassification"),
    ]
)

UpperCAmelCase__  							=OrderedDict(
    [
        ("vision-encoder-decoder", "FlaxVisionEncoderDecoderModel"),
    ]
)

UpperCAmelCase__  							=OrderedDict(
    [
        # Model for Causal LM mapping
        ("bart", "FlaxBartForCausalLM"),
        ("bert", "FlaxBertForCausalLM"),
        ("big_bird", "FlaxBigBirdForCausalLM"),
        ("electra", "FlaxElectraForCausalLM"),
        ("gpt-sw3", "FlaxGPT2LMHeadModel"),
        ("gpt2", "FlaxGPT2LMHeadModel"),
        ("gpt_neo", "FlaxGPTNeoForCausalLM"),
        ("gptj", "FlaxGPTJForCausalLM"),
        ("opt", "FlaxOPTForCausalLM"),
        ("roberta", "FlaxRobertaForCausalLM"),
        ("roberta-prelayernorm", "FlaxRobertaPreLayerNormForCausalLM"),
        ("xglm", "FlaxXGLMForCausalLM"),
        ("xlm-roberta", "FlaxXLMRobertaForCausalLM"),
    ]
)

UpperCAmelCase__  							=OrderedDict(
    [
        # Model for Sequence Classification mapping
        ("albert", "FlaxAlbertForSequenceClassification"),
        ("bart", "FlaxBartForSequenceClassification"),
        ("bert", "FlaxBertForSequenceClassification"),
        ("big_bird", "FlaxBigBirdForSequenceClassification"),
        ("distilbert", "FlaxDistilBertForSequenceClassification"),
        ("electra", "FlaxElectraForSequenceClassification"),
        ("mbart", "FlaxMBartForSequenceClassification"),
        ("roberta", "FlaxRobertaForSequenceClassification"),
        ("roberta-prelayernorm", "FlaxRobertaPreLayerNormForSequenceClassification"),
        ("roformer", "FlaxRoFormerForSequenceClassification"),
        ("xlm-roberta", "FlaxXLMRobertaForSequenceClassification"),
    ]
)

UpperCAmelCase__  							=OrderedDict(
    [
        # Model for Question Answering mapping
        ("albert", "FlaxAlbertForQuestionAnswering"),
        ("bart", "FlaxBartForQuestionAnswering"),
        ("bert", "FlaxBertForQuestionAnswering"),
        ("big_bird", "FlaxBigBirdForQuestionAnswering"),
        ("distilbert", "FlaxDistilBertForQuestionAnswering"),
        ("electra", "FlaxElectraForQuestionAnswering"),
        ("mbart", "FlaxMBartForQuestionAnswering"),
        ("roberta", "FlaxRobertaForQuestionAnswering"),
        ("roberta-prelayernorm", "FlaxRobertaPreLayerNormForQuestionAnswering"),
        ("roformer", "FlaxRoFormerForQuestionAnswering"),
        ("xlm-roberta", "FlaxXLMRobertaForQuestionAnswering"),
    ]
)

UpperCAmelCase__  							=OrderedDict(
    [
        # Model for Token Classification mapping
        ("albert", "FlaxAlbertForTokenClassification"),
        ("bert", "FlaxBertForTokenClassification"),
        ("big_bird", "FlaxBigBirdForTokenClassification"),
        ("distilbert", "FlaxDistilBertForTokenClassification"),
        ("electra", "FlaxElectraForTokenClassification"),
        ("roberta", "FlaxRobertaForTokenClassification"),
        ("roberta-prelayernorm", "FlaxRobertaPreLayerNormForTokenClassification"),
        ("roformer", "FlaxRoFormerForTokenClassification"),
        ("xlm-roberta", "FlaxXLMRobertaForTokenClassification"),
    ]
)

UpperCAmelCase__  							=OrderedDict(
    [
        # Model for Multiple Choice mapping
        ("albert", "FlaxAlbertForMultipleChoice"),
        ("bert", "FlaxBertForMultipleChoice"),
        ("big_bird", "FlaxBigBirdForMultipleChoice"),
        ("distilbert", "FlaxDistilBertForMultipleChoice"),
        ("electra", "FlaxElectraForMultipleChoice"),
        ("roberta", "FlaxRobertaForMultipleChoice"),
        ("roberta-prelayernorm", "FlaxRobertaPreLayerNormForMultipleChoice"),
        ("roformer", "FlaxRoFormerForMultipleChoice"),
        ("xlm-roberta", "FlaxXLMRobertaForMultipleChoice"),
    ]
)

UpperCAmelCase__  							=OrderedDict(
    [
        ("bert", "FlaxBertForNextSentencePrediction"),
    ]
)

UpperCAmelCase__  							=OrderedDict(
    [
        ("speech-encoder-decoder", "FlaxSpeechEncoderDecoderModel"),
        ("whisper", "FlaxWhisperForConditionalGeneration"),
    ]
)

UpperCAmelCase__  							=OrderedDict(
    [
        ("whisper", "FlaxWhisperForAudioClassification"),
    ]
)

UpperCAmelCase__  							=_LazyAutoMapping(CONFIG_MAPPING_NAMES, FLAX_MODEL_MAPPING_NAMES)
UpperCAmelCase__  							=_LazyAutoMapping(CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_PRETRAINING_MAPPING_NAMES)
UpperCAmelCase__  							=_LazyAutoMapping(CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_MASKED_LM_MAPPING_NAMES)
UpperCAmelCase__  							=_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES
)
UpperCAmelCase__  							=_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES
)
UpperCAmelCase__  							=_LazyAutoMapping(CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES)
UpperCAmelCase__  							=_LazyAutoMapping(CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_CAUSAL_LM_MAPPING_NAMES)
UpperCAmelCase__  							=_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES
)
UpperCAmelCase__  							=_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES
)
UpperCAmelCase__  							=_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES
)
UpperCAmelCase__  							=_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING_NAMES
)
UpperCAmelCase__  							=_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING_NAMES
)
UpperCAmelCase__  							=_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES
)
UpperCAmelCase__  							=_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES
)





class    lowerCamelCase__						(		_BaseAutoModelClass    ):
      a :     List[Any]											=		FLAX_MODEL_MAPPING






UpperCAmelCase__  							=auto_class_update(FlaxAutoModel)





class    lowerCamelCase__						(		_BaseAutoModelClass    ):
      a :     int											=		FLAX_MODEL_FOR_PRETRAINING_MAPPING






UpperCAmelCase__  							=auto_class_update(FlaxAutoModelForPreTraining, head_doc="pretraining")





class    lowerCamelCase__						(		_BaseAutoModelClass    ):
      a :     Tuple											=		FLAX_MODEL_FOR_CAUSAL_LM_MAPPING






UpperCAmelCase__  							=auto_class_update(FlaxAutoModelForCausalLM, head_doc="causal language modeling")





class    lowerCamelCase__						(		_BaseAutoModelClass    ):
      a :     List[str]											=		FLAX_MODEL_FOR_MASKED_LM_MAPPING






UpperCAmelCase__  							=auto_class_update(FlaxAutoModelForMaskedLM, head_doc="masked language modeling")





class    lowerCamelCase__						(		_BaseAutoModelClass    ):
      a :     str											=		FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING






UpperCAmelCase__  							=auto_class_update(
    FlaxAutoModelForSeqaSeqLM, head_doc="sequence-to-sequence language modeling", checkpoint_for_example="t5-base"
)





class    lowerCamelCase__						(		_BaseAutoModelClass    ):
      a :     str											=		FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING






UpperCAmelCase__  							=auto_class_update(
    FlaxAutoModelForSequenceClassification, head_doc="sequence classification"
)





class    lowerCamelCase__						(		_BaseAutoModelClass    ):
      a :     Tuple											=		FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING






UpperCAmelCase__  							=auto_class_update(FlaxAutoModelForQuestionAnswering, head_doc="question answering")





class    lowerCamelCase__						(		_BaseAutoModelClass    ):
      a :     Union[str, Any]											=		FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING






UpperCAmelCase__  							=auto_class_update(
    FlaxAutoModelForTokenClassification, head_doc="token classification"
)





class    lowerCamelCase__						(		_BaseAutoModelClass    ):
      a :     Optional[Any]											=		FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING






UpperCAmelCase__  							=auto_class_update(FlaxAutoModelForMultipleChoice, head_doc="multiple choice")





class    lowerCamelCase__						(		_BaseAutoModelClass    ):
      a :     Optional[int]											=		FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING






UpperCAmelCase__  							=auto_class_update(
    FlaxAutoModelForNextSentencePrediction, head_doc="next sentence prediction"
)





class    lowerCamelCase__						(		_BaseAutoModelClass    ):
      a :     Union[str, Any]											=		FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING






UpperCAmelCase__  							=auto_class_update(
    FlaxAutoModelForImageClassification, head_doc="image classification"
)





class    lowerCamelCase__						(		_BaseAutoModelClass    ):
      a :     Dict											=		FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING






UpperCAmelCase__  							=auto_class_update(FlaxAutoModelForVisionaSeq, head_doc="vision-to-text modeling")





class    lowerCamelCase__						(		_BaseAutoModelClass    ):
      a :     List[str]											=		FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING






UpperCAmelCase__  							=auto_class_update(
    FlaxAutoModelForSpeechSeqaSeq, head_doc="sequence-to-sequence speech-to-text modeling"
)
