"""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


__lowercase		:		Optional[Any]														=							logging.get_logger(__name__)


__lowercase		:		Any														=							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"),
    ]
)

__lowercase		:		Optional[int]														=							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"),
    ]
)

__lowercase		:		Union[str, Any]														=							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"),
    ]
)

__lowercase		:		Union[str, Any]														=							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"),
    ]
)

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

__lowercase		:		Optional[int]														=							OrderedDict(
    [
        ("vision-encoder-decoder", "FlaxVisionEncoderDecoderModel"),
    ]
)

__lowercase		:		str														=							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"),
    ]
)

__lowercase		:		Any														=							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"),
    ]
)

__lowercase		:		int														=							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"),
    ]
)

__lowercase		:		List[str]														=							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"),
    ]
)

__lowercase		:		Any														=							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"),
    ]
)

__lowercase		:		Optional[int]														=							OrderedDict(
    [
        ("bert", "FlaxBertForNextSentencePrediction"),
    ]
)

__lowercase		:		List[Any]														=							OrderedDict(
    [
        ("speech-encoder-decoder", "FlaxSpeechEncoderDecoderModel"),
        ("whisper", "FlaxWhisperForConditionalGeneration"),
    ]
)

__lowercase		:		List[Any]														=							OrderedDict(
    [
        ("whisper", "FlaxWhisperForAudioClassification"),
    ]
)

__lowercase		:		Optional[int]														=							_LazyAutoMapping(CONFIG_MAPPING_NAMES, FLAX_MODEL_MAPPING_NAMES)
__lowercase		:		List[Any]														=							_LazyAutoMapping(CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_PRETRAINING_MAPPING_NAMES)
__lowercase		:		str														=							_LazyAutoMapping(CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_MASKED_LM_MAPPING_NAMES)
__lowercase		:		Optional[int]														=							_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES
)
__lowercase		:		List[Any]														=							_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES
)
__lowercase		:		Tuple														=							_LazyAutoMapping(CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES)
__lowercase		:		List[str]														=							_LazyAutoMapping(CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_CAUSAL_LM_MAPPING_NAMES)
__lowercase		:		Any														=							_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES
)
__lowercase		:		Dict														=							_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES
)
__lowercase		:		Optional[int]														=							_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES
)
__lowercase		:		Any														=							_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING_NAMES
)
__lowercase		:		Any														=							_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING_NAMES
)
__lowercase		:		str														=							_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES
)
__lowercase		:		Optional[Any]														=							_LazyAutoMapping(
    CONFIG_MAPPING_NAMES, FLAX_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES
)



class      _A	(						_BaseAutoModelClass					):




    """simple docstring"""




    UpperCamelCase_	:					Tuple							=					FLAX_MODEL_MAPPING






__lowercase		:		Union[str, Any]														=							auto_class_update(FlaxAutoModel)



class      _A	(						_BaseAutoModelClass					):




    """simple docstring"""




    UpperCamelCase_	:					List[str]							=					FLAX_MODEL_FOR_PRETRAINING_MAPPING






__lowercase		:		Dict														=							auto_class_update(FlaxAutoModelForPreTraining, head_doc="pretraining")



class      _A	(						_BaseAutoModelClass					):




    """simple docstring"""




    UpperCamelCase_	:					Optional[Any]							=					FLAX_MODEL_FOR_CAUSAL_LM_MAPPING






__lowercase		:		List[str]														=							auto_class_update(FlaxAutoModelForCausalLM, head_doc="causal language modeling")



class      _A	(						_BaseAutoModelClass					):




    """simple docstring"""




    UpperCamelCase_	:					List[Any]							=					FLAX_MODEL_FOR_MASKED_LM_MAPPING






__lowercase		:		Union[str, Any]														=							auto_class_update(FlaxAutoModelForMaskedLM, head_doc="masked language modeling")



class      _A	(						_BaseAutoModelClass					):




    """simple docstring"""




    UpperCamelCase_	:					Optional[Any]							=					FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING






__lowercase		:		Optional[int]														=							auto_class_update(
    FlaxAutoModelForSeqaSeqLM, head_doc="sequence-to-sequence language modeling", checkpoint_for_example="t5-base"
)



class      _A	(						_BaseAutoModelClass					):




    """simple docstring"""




    UpperCamelCase_	:					Union[str, Any]							=					FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING






__lowercase		:		str														=							auto_class_update(
    FlaxAutoModelForSequenceClassification, head_doc="sequence classification"
)



class      _A	(						_BaseAutoModelClass					):




    """simple docstring"""




    UpperCamelCase_	:					int							=					FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING






__lowercase		:		Optional[int]														=							auto_class_update(FlaxAutoModelForQuestionAnswering, head_doc="question answering")



class      _A	(						_BaseAutoModelClass					):




    """simple docstring"""




    UpperCamelCase_	:					Optional[Any]							=					FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING






__lowercase		:		str														=							auto_class_update(
    FlaxAutoModelForTokenClassification, head_doc="token classification"
)



class      _A	(						_BaseAutoModelClass					):




    """simple docstring"""




    UpperCamelCase_	:					List[str]							=					FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING






__lowercase		:		List[str]														=							auto_class_update(FlaxAutoModelForMultipleChoice, head_doc="multiple choice")



class      _A	(						_BaseAutoModelClass					):




    """simple docstring"""




    UpperCamelCase_	:					str							=					FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING






__lowercase		:		Tuple														=							auto_class_update(
    FlaxAutoModelForNextSentencePrediction, head_doc="next sentence prediction"
)



class      _A	(						_BaseAutoModelClass					):




    """simple docstring"""




    UpperCamelCase_	:					Optional[int]							=					FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING






__lowercase		:		Dict														=							auto_class_update(
    FlaxAutoModelForImageClassification, head_doc="image classification"
)



class      _A	(						_BaseAutoModelClass					):




    """simple docstring"""




    UpperCamelCase_	:					Optional[Any]							=					FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING






__lowercase		:		Optional[int]														=							auto_class_update(FlaxAutoModelForVisionaSeq, head_doc="vision-to-text modeling")



class      _A	(						_BaseAutoModelClass					):




    """simple docstring"""




    UpperCamelCase_	:					Optional[int]							=					FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING






__lowercase		:		Optional[Any]														=							auto_class_update(
    FlaxAutoModelForSpeechSeqaSeq, head_doc="sequence-to-sequence speech-to-text modeling"
)
"""simple docstring"""



from __future__ import annotations

from collections.abc import Iterator
from typing import Any



class      _A	:




    """simple docstring"""




    def __init__(		self							:     Tuple	,      A_							:     Any    )    ->       Union[str, Any]:
         __snake_case				=							data
         __snake_case				=							None






class      _A	:




    """simple docstring"""




    def __init__(		self							:     Union[str, Any]    )    ->       List[Any]:
         __snake_case				=							None
         __snake_case				=							None
    def __iter__(		self							:     Optional[Any]    )    ->       Iterator[Any]:
         __snake_case				=							self.head
         while self.head:
              yield node.data
              __snake_case				=							node.next
              if node == self.head:
                   break
    def __len__(		self							:     List[Any]    )    ->       int:
         return sum(1 for _ in self    )
    def __repr__(		self							:     Optional[int]    )    ->       Union[str, Any]:
         return "->".join(str(A_    ) for item in iter(self    )    )
    def  lowercase					(		self							:     int	,      A_							:     Any    )    ->       None:
         self.insert_nth(len(self    )	,      A_    )
    def  lowercase					(		self							:     List[str]	,      A_							:     Any    )    ->       None:
         self.insert_nth(0	,      A_    )
    def  lowercase					(		self							:     List[Any]	,      A_							:     int	,      A_							:     Any    )    ->       None:
         if index < 0 or index > len(self    ):
              raise IndexError('''list index out of range.'''    )
         __snake_case				=							Node(A_    )
         if self.head is None:
              __snake_case				=							new_node  # first node points itself
              __snake_case				=							__snake_case				=							new_node
         elif index == 0:  # insert at head
              __snake_case				=							self.head
              __snake_case				=							__snake_case				=							new_node
         else:
              __snake_case				=							self.head
              for _ in range(index - 1    ):
                   __snake_case				=							temp.next
              __snake_case				=							temp.next
              __snake_case				=							new_node
              if index == len(self    ) - 1:  # insert at tail
                   __snake_case				=							new_node
    def  lowercase					(		self							:     int    )    ->       str:
         return self.delete_nth(0    )
    def  lowercase					(		self							:     List[Any]    )    ->       Any:
         return self.delete_nth(len(self    ) - 1    )
    def  lowercase					(		self							:     List[str]	,      A_							:     int = 0    )    ->       Any:
         if not 0 <= index < len(self    ):
              raise IndexError('''list index out of range.'''    )
         __snake_case				=							self.head
         if self.head == self.tail:  # just one node
              __snake_case				=							__snake_case				=							None
         elif index == 0:  # delete head node
              __snake_case				=							self.tail.next.next
              __snake_case				=							self.head.next
         else:
              __snake_case				=							self.head
              for _ in range(index - 1    ):
                   __snake_case				=							temp.next
              __snake_case				=							temp.next
              __snake_case				=							temp.next.next
              if index == len(self    ) - 1:  # delete at tail
                   __snake_case				=							temp
         return delete_node.data







    def  lowercase					(		self							:     Dict    )    ->       bool:
         return len(self    ) == 0






def    SCREAMING_SNAKE_CASE       (     ):
     __snake_case				=							CircularLinkedList()
     assert len(snake_case) == 0
     assert circular_linked_list.is_empty() is True
     assert str(snake_case) == ""

     try:
          circular_linked_list.delete_front()
          raise AssertionError  # This should not happen
     except IndexError:
          assert True  # This should happen

     try:
          circular_linked_list.delete_tail()
          raise AssertionError  # This should not happen
     except IndexError:
          assert True  # This should happen

     try:
          circular_linked_list.delete_nth(-1)
          raise AssertionError
     except IndexError:
          assert True

     try:
          circular_linked_list.delete_nth(0)
          raise AssertionError
     except IndexError:
          assert True

     assert circular_linked_list.is_empty() is True
     for i in range(5):
          assert len(snake_case) == i
          circular_linked_list.insert_nth(snake_case,      i + 1)
     assert str(snake_case) == "->".join(str(snake_case) for i in range(1,      6))

     circular_linked_list.insert_tail(6)
     assert str(snake_case) == "->".join(str(snake_case) for i in range(1,      7))
     circular_linked_list.insert_head(0)
     assert str(snake_case) == "->".join(str(snake_case) for i in range(0,      7))

     assert circular_linked_list.delete_front() == 0
     assert circular_linked_list.delete_tail() == 6
     assert str(snake_case) == "->".join(str(snake_case) for i in range(1,      6))
     assert circular_linked_list.delete_nth(2) == 3

     circular_linked_list.insert_nth(2,      3)
     assert str(snake_case) == "->".join(str(snake_case) for i in range(1,      6))

     assert circular_linked_list.is_empty() is False


if __name__ == "__main__":
       import doctest

       doctest.testmod()