
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__       =logging.get_logger(__name__)


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

lowercase__       =OrderedDict(
    [
        ('vision-encoder-decoder', 'FlaxVisionEncoderDecoderModel'),
    ]
)

lowercase__       =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__       =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__       =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__       =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__       =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__       =OrderedDict(
    [
        ('bert', 'FlaxBertForNextSentencePrediction'),
    ]
)

lowercase__       =OrderedDict(
    [
        ('speech-encoder-decoder', 'FlaxSpeechEncoderDecoderModel'),
        ('whisper', 'FlaxWhisperForConditionalGeneration'),
    ]
)

lowercase__       =OrderedDict(
    [
        ('whisper', 'FlaxWhisperForAudioClassification'),
    ]
)

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



class 		UpperCamelCase__  (       _BaseAutoModelClass    ):
   _SCREAMING_SNAKE_CASE      :							Optional[Any]	       =      FLAX_MODEL_MAPPING





lowercase__       =auto_class_update(FlaxAutoModel)



class 		UpperCamelCase__  (       _BaseAutoModelClass    ):
   _SCREAMING_SNAKE_CASE      :							Tuple	       =      FLAX_MODEL_FOR_PRETRAINING_MAPPING





lowercase__       =auto_class_update(FlaxAutoModelForPreTraining, head_doc='pretraining')



class 		UpperCamelCase__  (       _BaseAutoModelClass    ):
   _SCREAMING_SNAKE_CASE      :							Tuple	       =      FLAX_MODEL_FOR_CAUSAL_LM_MAPPING





lowercase__       =auto_class_update(FlaxAutoModelForCausalLM, head_doc='causal language modeling')



class 		UpperCamelCase__  (       _BaseAutoModelClass    ):
   _SCREAMING_SNAKE_CASE      :							Tuple	       =      FLAX_MODEL_FOR_MASKED_LM_MAPPING





lowercase__       =auto_class_update(FlaxAutoModelForMaskedLM, head_doc='masked language modeling')



class 		UpperCamelCase__  (       _BaseAutoModelClass    ):
   _SCREAMING_SNAKE_CASE      :							Dict	       =      FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING





lowercase__       =auto_class_update(
    FlaxAutoModelForSeqaSeqLM, head_doc='sequence-to-sequence language modeling', checkpoint_for_example='t5-base'
)



class 		UpperCamelCase__  (       _BaseAutoModelClass    ):
   _SCREAMING_SNAKE_CASE      :							str	       =      FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING





lowercase__       =auto_class_update(
    FlaxAutoModelForSequenceClassification, head_doc='sequence classification'
)



class 		UpperCamelCase__  (       _BaseAutoModelClass    ):
   _SCREAMING_SNAKE_CASE      :							Optional[Any]	       =      FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING





lowercase__       =auto_class_update(FlaxAutoModelForQuestionAnswering, head_doc='question answering')



class 		UpperCamelCase__  (       _BaseAutoModelClass    ):
   _SCREAMING_SNAKE_CASE      :							List[Any]	       =      FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING





lowercase__       =auto_class_update(
    FlaxAutoModelForTokenClassification, head_doc='token classification'
)



class 		UpperCamelCase__  (       _BaseAutoModelClass    ):
   _SCREAMING_SNAKE_CASE      :							Dict	       =      FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING





lowercase__       =auto_class_update(FlaxAutoModelForMultipleChoice, head_doc='multiple choice')



class 		UpperCamelCase__  (       _BaseAutoModelClass    ):
   _SCREAMING_SNAKE_CASE      :							List[Any]	       =      FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING





lowercase__       =auto_class_update(
    FlaxAutoModelForNextSentencePrediction, head_doc='next sentence prediction'
)



class 		UpperCamelCase__  (       _BaseAutoModelClass    ):
   _SCREAMING_SNAKE_CASE      :							str	       =      FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING





lowercase__       =auto_class_update(
    FlaxAutoModelForImageClassification, head_doc='image classification'
)



class 		UpperCamelCase__  (       _BaseAutoModelClass    ):
   _SCREAMING_SNAKE_CASE      :							Tuple	       =      FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING





lowercase__       =auto_class_update(FlaxAutoModelForVisionaSeq, head_doc='vision-to-text modeling')



class 		UpperCamelCase__  (       _BaseAutoModelClass    ):
   _SCREAMING_SNAKE_CASE      :							str	       =      FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING





lowercase__       =auto_class_update(
    FlaxAutoModelForSpeechSeqaSeq, head_doc='sequence-to-sequence speech-to-text modeling'
)


import logging
import os
from logging import (
    CRITICAL,  # NOQA
    DEBUG,  # NOQA
    ERROR,  # NOQA
    FATAL,  # NOQA
    INFO,  # NOQA
    NOTSET,  # NOQA
    WARN,  # NOQA
    WARNING,  # NOQA
)
from typing import Optional

from tqdm import auto as tqdm_lib


lowercase__       ={
    'debug': logging.DEBUG,
    'info': logging.INFO,
    'warning': logging.WARNING,
    'error': logging.ERROR,
    'critical': logging.CRITICAL,
}

lowercase__       =logging.WARNING




def    __UpperCamelCase     (				):
 __a :  Optional[Any]						=  os.getenv('''DATASETS_VERBOSITY'''  ,   lowerCAmelCase__  )
 if env_level_str:
  if env_level_str in log_levels:
   return log_levels[env_level_str]
  else:
   logging.getLogger().warning(
       f"Unknown option DATASETS_VERBOSITY={env_level_str}, "
       f"has to be one of: { ', '.join(log_levels.keys()  ) }"  )
 return _default_log_level




def    __UpperCamelCase     (				):
 return __name__.split('''.'''  )[0]




def    __UpperCamelCase     (				):
 return logging.getLogger(_get_library_name()  )




def    __UpperCamelCase     (				):
 # Apply our default configuration to the library root logger.
 __a :  str						=  _get_library_root_logger()
 library_root_logger.setLevel(_get_default_logging_level()  )




def    __UpperCamelCase     (				):
 __a :  Any						=  _get_library_root_logger()
 library_root_logger.setLevel(logging.NOTSET  )




def    __UpperCamelCase     (				lowerCAmelCase__							:				Optional[str] = None  ):
 if name is None:
  __a :  Union[str, Any]						=  _get_library_name()
 return logging.getLogger(lowerCAmelCase__  )




def    __UpperCamelCase     (				):
 return _get_library_root_logger().getEffectiveLevel()




def    __UpperCamelCase     (				lowerCAmelCase__							:				int  ):
 _get_library_root_logger().setLevel(lowerCAmelCase__  )




def    __UpperCamelCase     (				):
 return set_verbosity(lowerCAmelCase__  )




def    __UpperCamelCase     (				):
 return set_verbosity(lowerCAmelCase__  )




def    __UpperCamelCase     (				):
 return set_verbosity(lowerCAmelCase__  )




def    __UpperCamelCase     (				):
 return set_verbosity(lowerCAmelCase__  )




def    __UpperCamelCase     (				):
 __a :  Union[str, Any]						=  False




def    __UpperCamelCase     (				):
 __a :  Tuple						=  True


# Configure the library root logger at the module level (singleton-like)
_configure_library_root_logger()



class 		UpperCamelCase__  :
   def __init__(self :					str					,				*snake_case_ :					str					,				**snake_case_ :					Union[str, Any]   ):  # pylint: disable=unused-argument
    __a :  Optional[Any]						=  args[0] if args else None
   def __iter__(self :					List[str]   ):
    return iter(self._iterator   )
   def __getattr__(self :					str					,				snake_case_ :					Optional[Any]   ):

    def empty_fn(*snake_case_ :					int					,				**snake_case_ :					int   ):  # pylint: disable=unused-argument
     return

    return empty_fn
   def __enter__(self :					Union[str, Any]   ):
    return self







   def __exit__(self :					str					,				snake_case_ :					List[str]					,				snake_case_ :					int					,				snake_case_ :					Optional[Any]   ):
    return





lowercase__       =True



class 		UpperCamelCase__  :
   def __call__(self :					Tuple					,				*snake_case_ :					str					,				snake_case_ :					str=False					,				**snake_case_ :					Dict   ):
    if _tqdm_active and not disable:
     return tqdm_lib.tqdm(*snake_case_					,				**snake_case_   )
    else:
     return EmptyTqdm(*snake_case_					,				**snake_case_   )
   def       lowerCAmelCase			(self :					Optional[Any]					,				*snake_case_ :					Union[str, Any]					,				**snake_case_ :					Optional[Any]   ):
    __a :  List[Any]						=  None
    if _tqdm_active:
     return tqdm_lib.tqdm.set_lock(*snake_case_					,				**snake_case_   )







   def       lowerCAmelCase			(self :					str   ):
    if _tqdm_active:
     return tqdm_lib.tqdm.get_lock()





lowercase__       =_tqdm_cls()




def    __UpperCamelCase     (				):
 global _tqdm_active
 return bool(_tqdm_active  )




def    __UpperCamelCase     (				):
 global _tqdm_active
 __a :  Dict						=  True




def    __UpperCamelCase     (				):
 global _tqdm_active
 __a :  Union[str, Any]						=  False
