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_     :   Tuple 				=				logging.get_logger(__name__)


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

lowercase_     :   List[Any] 				=				OrderedDict(
    [
        ('vision-encoder-decoder', 'FlaxVisionEncoderDecoderModel'),
    ]
)

lowercase_     :   Optional[int] 				=				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_     :   Dict 				=				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_     :   Optional[Any] 				=				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_     :   Union[str, Any] 				=				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_     :   int 				=				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_     :   List[str] 				=				OrderedDict(
    [
        ('bert', 'FlaxBertForNextSentencePrediction'),
    ]
)

lowercase_     :   Tuple 				=				OrderedDict(
    [
        ('speech-encoder-decoder', 'FlaxSpeechEncoderDecoderModel'),
        ('whisper', 'FlaxWhisperForConditionalGeneration'),
    ]
)

lowercase_     :   List[str] 				=				OrderedDict(
    [
        ('whisper', 'FlaxWhisperForAudioClassification'),
    ]
)

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






class 		_lowerCamelCase		(   _BaseAutoModelClass    ):
    __a  =      FLAX_MODEL_MAPPING
lowercase_     :   Dict 				=				auto_class_update(FlaxAutoModel)






class 		_lowerCamelCase		(   _BaseAutoModelClass    ):
    __a  =      FLAX_MODEL_FOR_PRETRAINING_MAPPING
lowercase_     :   List[Any] 				=				auto_class_update(FlaxAutoModelForPreTraining, head_doc='pretraining')






class 		_lowerCamelCase		(   _BaseAutoModelClass    ):
    __a  =      FLAX_MODEL_FOR_CAUSAL_LM_MAPPING
lowercase_     :   List[Any] 				=				auto_class_update(FlaxAutoModelForCausalLM, head_doc='causal language modeling')






class 		_lowerCamelCase		(   _BaseAutoModelClass    ):
    __a  =      FLAX_MODEL_FOR_MASKED_LM_MAPPING
lowercase_     :   str 				=				auto_class_update(FlaxAutoModelForMaskedLM, head_doc='masked language modeling')






class 		_lowerCamelCase		(   _BaseAutoModelClass    ):
    __a  =      FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING
lowercase_     :   Dict 				=				auto_class_update(
    FlaxAutoModelForSeqaSeqLM, head_doc='sequence-to-sequence language modeling', checkpoint_for_example='t5-base'
)






class 		_lowerCamelCase		(   _BaseAutoModelClass    ):
    __a  =      FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING
lowercase_     :   Dict 				=				auto_class_update(
    FlaxAutoModelForSequenceClassification, head_doc='sequence classification'
)






class 		_lowerCamelCase		(   _BaseAutoModelClass    ):
    __a  =      FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING
lowercase_     :   Dict 				=				auto_class_update(FlaxAutoModelForQuestionAnswering, head_doc='question answering')






class 		_lowerCamelCase		(   _BaseAutoModelClass    ):
    __a  =      FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING
lowercase_     :   int 				=				auto_class_update(
    FlaxAutoModelForTokenClassification, head_doc='token classification'
)






class 		_lowerCamelCase		(   _BaseAutoModelClass    ):
    __a  =      FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING
lowercase_     :   Optional[int] 				=				auto_class_update(FlaxAutoModelForMultipleChoice, head_doc='multiple choice')






class 		_lowerCamelCase		(   _BaseAutoModelClass    ):
    __a  =      FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING
lowercase_     :   Tuple 				=				auto_class_update(
    FlaxAutoModelForNextSentencePrediction, head_doc='next sentence prediction'
)






class 		_lowerCamelCase		(   _BaseAutoModelClass    ):
    __a  =      FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING
lowercase_     :   Optional[Any] 				=				auto_class_update(
    FlaxAutoModelForImageClassification, head_doc='image classification'
)






class 		_lowerCamelCase		(   _BaseAutoModelClass    ):
    __a  =      FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING
lowercase_     :   str 				=				auto_class_update(FlaxAutoModelForVisionaSeq, head_doc='vision-to-text modeling')






class 		_lowerCamelCase		(   _BaseAutoModelClass    ):
    __a  =      FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING
lowercase_     :   Tuple 				=				auto_class_update(
    FlaxAutoModelForSpeechSeqaSeq, head_doc='sequence-to-sequence speech-to-text modeling'
)


# Lint as: python3
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union


lowercase_     :   str 				=				re.compile(R'^(?P<major>\d+)' R'\.(?P<minor>\d+)' R'\.(?P<patch>\d+)$')






@total_ordering
@dataclass
class 		_lowerCamelCase		:
    __a  =      42
    __a  =      None
    __a  =      None
    __a  =      None
    __a  =      None
    def 						UpperCamelCase_				(  self   )       ->					str:
     SCREAMING_SNAKE_CASE__,	SCREAMING_SNAKE_CASE__,	SCREAMING_SNAKE_CASE__:   int=      _str_to_version_tuple(self.version_str   )
    def __repr__(  self   )       ->					Dict:
     return f'{self.tuple[0]}.{self.tuple[1]}.{self.tuple[2]}'
    @property
    def 						UpperCamelCase_				(  self   )       ->					List[str]:
     return self.major, self.minor, self.patch
    def 						UpperCamelCase_				(  self , lowerCAmelCase   )       ->					Dict:
     if isinstance(lowerCAmelCase , lowerCAmelCase   ):
      return Version(lowerCAmelCase   )
     elif isinstance(lowerCAmelCase , lowerCAmelCase   ):
      return other
     raise TypeError(f'{other} (type {type(lowerCAmelCase   )}) cannot be compared to version.'   )
    def __eq__(  self , lowerCAmelCase   )       ->					Optional[int]:
     try:
      SCREAMING_SNAKE_CASE__:   List[str]=      self._validate_operand(lowerCAmelCase   )
     except (TypeError, ValueError):
      return False
     else:
      return self.tuple == other.tuple
    def __lt__(  self , lowerCAmelCase   )       ->					List[str]:
     SCREAMING_SNAKE_CASE__:   Optional[Any]=      self._validate_operand(lowerCAmelCase   )
     return self.tuple < other.tuple
    def __hash__(  self   )       ->					List[Any]:
     return hash(_version_tuple_to_str(self.tuple   )   )
    @classmethod
    def 						UpperCamelCase_				(  cls , lowerCAmelCase   )       ->					Tuple:
     SCREAMING_SNAKE_CASE__:   Dict=      {f.name for f in dataclasses.fields(cls   )}
     return cls(**{k: v for k, v in dic.items() if k in field_names}   )



    def 						UpperCamelCase_				(  self   )       ->					str:
     return self.version_str







def 			A__      (	snake_case_ :		int      ):
 SCREAMING_SNAKE_CASE__:   List[Any]=      _VERSION_REG.match(snake_case_      )
 if not res:
  raise ValueError(F'Invalid version \'{version_str}\'. Format should be x.y.z with {{x,y,z}} being digits.'      )
 return tuple(int(snake_case_      ) for v in [res.group('''major'''      ), res.group('''minor'''      ), res.group('''patch'''      )]      )







def 			A__      (	snake_case_ :		Union[str, Any]      ):
 return ".".join(str(snake_case_      ) for v in version_tuple      )

