
"""simple docstring"""


import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
		from .tokenization_xglm import XGLMTokenizer
else:
		_lowercase											=			None


_lowercase											=			logging.get_logger(__name__)

_lowercase											=			{'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

_lowercase											=			{
    '''vocab_file''': {
        '''facebook/xglm-564M''': '''https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model''',
    },
    '''tokenizer_file''': {
        '''facebook/xglm-564M''': '''https://huggingface.co/facebook/xglm-564M/resolve/main/tokenizer.json''',
    },
}

_lowercase											=			{
    '''facebook/xglm-564M''': 20_48,
}







class 			lowerCAmelCase_			( _lowercase      ):



						'''simple docstring'''


						_lowerCamelCase:      Optional[int] =      VOCAB_FILES_NAMES
						_lowerCamelCase:      Optional[Any] =      PRETRAINED_VOCAB_FILES_MAP
						_lowerCamelCase:      Any =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						_lowerCamelCase:      Union[str, Any] =      ['''input_ids''', '''attention_mask''']
						_lowerCamelCase:      Optional[int] =      XGLMTokenizer


						def __init__(	self       : int					,A_       : Union[str, Any]=None					,A_       : Optional[int]=None					,A_       : Optional[Any]="<s>"					,A_       : Any="</s>"					,A_       : Union[str, Any]="</s>"					,A_       : int="<s>"					,A_       : Tuple="<unk>"					,A_       : str="<pad>"					,**A_       : str					,)       ->				Any:
							# Compatibility with the original tokenizer
							A  				=				7
							A  				=				[F'<madeupword{i}>' for i in range(self.num_madeup_words )]

							A  				=				kwargs.get('additional_special_tokens'					,[] )
							kwargs["additional_special_tokens"] += [
							    word for word in madeup_words if word not in kwargs["additional_special_tokens"]
							]

							super().__init__(
							    A_					,tokenizer_file=A_					,bos_token=A_					,eos_token=A_					,sep_token=A_					,cls_token=A_					,unk_token=A_					,pad_token=A_					,**A_					,)

							A  				=				vocab_file
							A  				=				False if not self.vocab_file else True


						def   _SCREAMING_SNAKE_CASE (	self       : int					,A_       : List[int]					,A_       : Optional[List[int]] = None )       ->				List[int]:

							if token_ids_a is None:
								return [self.sep_token_id] + token_ids_a
							A  				=				[self.sep_token_id]
							return sep + token_ids_a + sep + sep + token_ids_a


						def   _SCREAMING_SNAKE_CASE (	self       : Any					,A_       : List[int]					,A_       : Optional[List[int]] = None )       ->				List[int]:
							A  				=				[self.sep_token_id]

							if token_ids_a is None:
								return len(sep + token_ids_a ) * [0]
							return len(sep + token_ids_a + sep + sep + token_ids_a ) * [0]




						def   _SCREAMING_SNAKE_CASE (	self       : List[Any]					,A_       : str					,A_       : Optional[str] = None )       ->				Tuple[str]:
							if not self.can_save_slow_tokenizer:
								raise ValueError(
								    'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
								    'tokenizer.' )

							if not os.path.isdir(A_ ):
								logger.error(F'Vocabulary path ({save_directory}) should be a directory.' )
								return
							A  				=				os.path.join(
							    A_					,(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'] )

							if os.path.abspath(self.vocab_file ) != os.path.abspath(A_ ):
								copyfile(self.vocab_file					,A_ )

							return (out_vocab_file,)

"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


_lowercase											=			{
    '''auto_factory''': ['''get_values'''],
    '''configuration_auto''': ['''ALL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CONFIG_MAPPING''', '''MODEL_NAMES_MAPPING''', '''AutoConfig'''],
    '''feature_extraction_auto''': ['''FEATURE_EXTRACTOR_MAPPING''', '''AutoFeatureExtractor'''],
    '''image_processing_auto''': ['''IMAGE_PROCESSOR_MAPPING''', '''AutoImageProcessor'''],
    '''processing_auto''': ['''PROCESSOR_MAPPING''', '''AutoProcessor'''],
    '''tokenization_auto''': ['''TOKENIZER_MAPPING''', '''AutoTokenizer'''],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowercase											=			[
		    '''MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING''',
		    '''MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING''',
		    '''MODEL_FOR_AUDIO_XVECTOR_MAPPING''',
		    '''MODEL_FOR_BACKBONE_MAPPING''',
		    '''MODEL_FOR_CAUSAL_IMAGE_MODELING_MAPPING''',
		    '''MODEL_FOR_CAUSAL_LM_MAPPING''',
		    '''MODEL_FOR_CTC_MAPPING''',
		    '''MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING''',
		    '''MODEL_FOR_DEPTH_ESTIMATION_MAPPING''',
		    '''MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING''',
		    '''MODEL_FOR_IMAGE_SEGMENTATION_MAPPING''',
		    '''MODEL_FOR_INSTANCE_SEGMENTATION_MAPPING''',
		    '''MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING''',
		    '''MODEL_FOR_MASKED_LM_MAPPING''',
		    '''MODEL_FOR_MASK_GENERATION_MAPPING''',
		    '''MODEL_FOR_MULTIPLE_CHOICE_MAPPING''',
		    '''MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING''',
		    '''MODEL_FOR_OBJECT_DETECTION_MAPPING''',
		    '''MODEL_FOR_PRETRAINING_MAPPING''',
		    '''MODEL_FOR_QUESTION_ANSWERING_MAPPING''',
		    '''MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING''',
		    '''MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING''',
		    '''MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING''',
		    '''MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING''',
		    '''MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING''',
		    '''MODEL_FOR_TEXT_ENCODING_MAPPING''',
		    '''MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING''',
		    '''MODEL_FOR_UNIVERSAL_SEGMENTATION_MAPPING''',
		    '''MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING''',
		    '''MODEL_FOR_VISION_2_SEQ_MAPPING''',
		    '''MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING''',
		    '''MODEL_MAPPING''',
		    '''MODEL_WITH_LM_HEAD_MAPPING''',
		    '''MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING''',
		    '''MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING''',
		    '''AutoModel''',
		    '''AutoBackbone''',
		    '''AutoModelForAudioClassification''',
		    '''AutoModelForAudioFrameClassification''',
		    '''AutoModelForAudioXVector''',
		    '''AutoModelForCausalLM''',
		    '''AutoModelForCTC''',
		    '''AutoModelForDepthEstimation''',
		    '''AutoModelForImageClassification''',
		    '''AutoModelForImageSegmentation''',
		    '''AutoModelForInstanceSegmentation''',
		    '''AutoModelForMaskGeneration''',
		    '''AutoModelForTextEncoding''',
		    '''AutoModelForMaskedImageModeling''',
		    '''AutoModelForMaskedLM''',
		    '''AutoModelForMultipleChoice''',
		    '''AutoModelForNextSentencePrediction''',
		    '''AutoModelForObjectDetection''',
		    '''AutoModelForPreTraining''',
		    '''AutoModelForQuestionAnswering''',
		    '''AutoModelForSemanticSegmentation''',
		    '''AutoModelForSeq2SeqLM''',
		    '''AutoModelForSequenceClassification''',
		    '''AutoModelForSpeechSeq2Seq''',
		    '''AutoModelForTableQuestionAnswering''',
		    '''AutoModelForTokenClassification''',
		    '''AutoModelForUniversalSegmentation''',
		    '''AutoModelForVideoClassification''',
		    '''AutoModelForVision2Seq''',
		    '''AutoModelForVisualQuestionAnswering''',
		    '''AutoModelForDocumentQuestionAnswering''',
		    '''AutoModelWithLMHead''',
		    '''AutoModelForZeroShotImageClassification''',
		    '''AutoModelForZeroShotObjectDetection''',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowercase											=			[
		    '''TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING''',
		    '''TF_MODEL_FOR_CAUSAL_LM_MAPPING''',
		    '''TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING''',
		    '''TF_MODEL_FOR_MASK_GENERATION_MAPPING''',
		    '''TF_MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING''',
		    '''TF_MODEL_FOR_MASKED_LM_MAPPING''',
		    '''TF_MODEL_FOR_MULTIPLE_CHOICE_MAPPING''',
		    '''TF_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING''',
		    '''TF_MODEL_FOR_PRETRAINING_MAPPING''',
		    '''TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING''',
		    '''TF_MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING''',
		    '''TF_MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING''',
		    '''TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING''',
		    '''TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING''',
		    '''TF_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING''',
		    '''TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING''',
		    '''TF_MODEL_FOR_TEXT_ENCODING_MAPPING''',
		    '''TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING''',
		    '''TF_MODEL_FOR_VISION_2_SEQ_MAPPING''',
		    '''TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING''',
		    '''TF_MODEL_MAPPING''',
		    '''TF_MODEL_WITH_LM_HEAD_MAPPING''',
		    '''TFAutoModel''',
		    '''TFAutoModelForAudioClassification''',
		    '''TFAutoModelForCausalLM''',
		    '''TFAutoModelForImageClassification''',
		    '''TFAutoModelForMaskedImageModeling''',
		    '''TFAutoModelForMaskedLM''',
		    '''TFAutoModelForMaskGeneration''',
		    '''TFAutoModelForMultipleChoice''',
		    '''TFAutoModelForNextSentencePrediction''',
		    '''TFAutoModelForPreTraining''',
		    '''TFAutoModelForDocumentQuestionAnswering''',
		    '''TFAutoModelForQuestionAnswering''',
		    '''TFAutoModelForSemanticSegmentation''',
		    '''TFAutoModelForSeq2SeqLM''',
		    '''TFAutoModelForSequenceClassification''',
		    '''TFAutoModelForSpeechSeq2Seq''',
		    '''TFAutoModelForTableQuestionAnswering''',
		    '''TFAutoModelForTextEncoding''',
		    '''TFAutoModelForTokenClassification''',
		    '''TFAutoModelForVision2Seq''',
		    '''TFAutoModelForZeroShotImageClassification''',
		    '''TFAutoModelWithLMHead''',
		]

try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowercase											=			[
		    '''FLAX_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING''',
		    '''FLAX_MODEL_FOR_CAUSAL_LM_MAPPING''',
		    '''FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING''',
		    '''FLAX_MODEL_FOR_MASKED_LM_MAPPING''',
		    '''FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING''',
		    '''FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING''',
		    '''FLAX_MODEL_FOR_PRETRAINING_MAPPING''',
		    '''FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING''',
		    '''FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING''',
		    '''FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING''',
		    '''FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING''',
		    '''FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING''',
		    '''FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING''',
		    '''FLAX_MODEL_MAPPING''',
		    '''FlaxAutoModel''',
		    '''FlaxAutoModelForCausalLM''',
		    '''FlaxAutoModelForImageClassification''',
		    '''FlaxAutoModelForMaskedLM''',
		    '''FlaxAutoModelForMultipleChoice''',
		    '''FlaxAutoModelForNextSentencePrediction''',
		    '''FlaxAutoModelForPreTraining''',
		    '''FlaxAutoModelForQuestionAnswering''',
		    '''FlaxAutoModelForSeq2SeqLM''',
		    '''FlaxAutoModelForSequenceClassification''',
		    '''FlaxAutoModelForSpeechSeq2Seq''',
		    '''FlaxAutoModelForTokenClassification''',
		    '''FlaxAutoModelForVision2Seq''',
		]


if TYPE_CHECKING:
		from .auto_factory import get_values
		from .configuration_auto import ALL_PRETRAINED_CONFIG_ARCHIVE_MAP, CONFIG_MAPPING, MODEL_NAMES_MAPPING, AutoConfig
		from .feature_extraction_auto import FEATURE_EXTRACTOR_MAPPING, AutoFeatureExtractor
		from .image_processing_auto import IMAGE_PROCESSOR_MAPPING, AutoImageProcessor
		from .processing_auto import PROCESSOR_MAPPING, AutoProcessor
		from .tokenization_auto import TOKENIZER_MAPPING, AutoTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_auto import (
				    MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING,
				    MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING,
				    MODEL_FOR_AUDIO_XVECTOR_MAPPING,
				    MODEL_FOR_BACKBONE_MAPPING,
				    MODEL_FOR_CAUSAL_IMAGE_MODELING_MAPPING,
				    MODEL_FOR_CAUSAL_LM_MAPPING,
				    MODEL_FOR_CTC_MAPPING,
				    MODEL_FOR_DEPTH_ESTIMATION_MAPPING,
				    MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING,
				    MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING,
				    MODEL_FOR_IMAGE_SEGMENTATION_MAPPING,
				    MODEL_FOR_INSTANCE_SEGMENTATION_MAPPING,
				    MODEL_FOR_MASK_GENERATION_MAPPING,
				    MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING,
				    MODEL_FOR_MASKED_LM_MAPPING,
				    MODEL_FOR_MULTIPLE_CHOICE_MAPPING,
				    MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING,
				    MODEL_FOR_OBJECT_DETECTION_MAPPING,
				    MODEL_FOR_PRETRAINING_MAPPING,
				    MODEL_FOR_QUESTION_ANSWERING_MAPPING,
				    MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING,
				    MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
				    MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
				    MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING,
				    MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING,
				    MODEL_FOR_TEXT_ENCODING_MAPPING,
				    MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
				    MODEL_FOR_UNIVERSAL_SEGMENTATION_MAPPING,
				    MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING,
				    MODEL_FOR_VISION_2_SEQ_MAPPING,
				    MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING,
				    MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING,
				    MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING,
				    MODEL_MAPPING,
				    MODEL_WITH_LM_HEAD_MAPPING,
				    AutoBackbone,
				    AutoModel,
				    AutoModelForAudioClassification,
				    AutoModelForAudioFrameClassification,
				    AutoModelForAudioXVector,
				    AutoModelForCausalLM,
				    AutoModelForCTC,
				    AutoModelForDepthEstimation,
				    AutoModelForDocumentQuestionAnswering,
				    AutoModelForImageClassification,
				    AutoModelForImageSegmentation,
				    AutoModelForInstanceSegmentation,
				    AutoModelForMaskedImageModeling,
				    AutoModelForMaskedLM,
				    AutoModelForMaskGeneration,
				    AutoModelForMultipleChoice,
				    AutoModelForNextSentencePrediction,
				    AutoModelForObjectDetection,
				    AutoModelForPreTraining,
				    AutoModelForQuestionAnswering,
				    AutoModelForSemanticSegmentation,
				    AutoModelForSeqaSeqLM,
				    AutoModelForSequenceClassification,
				    AutoModelForSpeechSeqaSeq,
				    AutoModelForTableQuestionAnswering,
				    AutoModelForTextEncoding,
				    AutoModelForTokenClassification,
				    AutoModelForUniversalSegmentation,
				    AutoModelForVideoClassification,
				    AutoModelForVisionaSeq,
				    AutoModelForVisualQuestionAnswering,
				    AutoModelForZeroShotImageClassification,
				    AutoModelForZeroShotObjectDetection,
				    AutoModelWithLMHead,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_auto import (
				    TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING,
				    TF_MODEL_FOR_CAUSAL_LM_MAPPING,
				    TF_MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING,
				    TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING,
				    TF_MODEL_FOR_MASK_GENERATION_MAPPING,
				    TF_MODEL_FOR_MASKED_IMAGE_MODELING_MAPPING,
				    TF_MODEL_FOR_MASKED_LM_MAPPING,
				    TF_MODEL_FOR_MULTIPLE_CHOICE_MAPPING,
				    TF_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING,
				    TF_MODEL_FOR_PRETRAINING_MAPPING,
				    TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING,
				    TF_MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING,
				    TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
				    TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
				    TF_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING,
				    TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING,
				    TF_MODEL_FOR_TEXT_ENCODING_MAPPING,
				    TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
				    TF_MODEL_FOR_VISION_2_SEQ_MAPPING,
				    TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING,
				    TF_MODEL_MAPPING,
				    TF_MODEL_WITH_LM_HEAD_MAPPING,
				    TFAutoModel,
				    TFAutoModelForAudioClassification,
				    TFAutoModelForCausalLM,
				    TFAutoModelForDocumentQuestionAnswering,
				    TFAutoModelForImageClassification,
				    TFAutoModelForMaskedImageModeling,
				    TFAutoModelForMaskedLM,
				    TFAutoModelForMaskGeneration,
				    TFAutoModelForMultipleChoice,
				    TFAutoModelForNextSentencePrediction,
				    TFAutoModelForPreTraining,
				    TFAutoModelForQuestionAnswering,
				    TFAutoModelForSemanticSegmentation,
				    TFAutoModelForSeqaSeqLM,
				    TFAutoModelForSequenceClassification,
				    TFAutoModelForSpeechSeqaSeq,
				    TFAutoModelForTableQuestionAnswering,
				    TFAutoModelForTextEncoding,
				    TFAutoModelForTokenClassification,
				    TFAutoModelForVisionaSeq,
				    TFAutoModelForZeroShotImageClassification,
				    TFAutoModelWithLMHead,
				)

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_auto import (
				    FLAX_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING,
				    FLAX_MODEL_FOR_CAUSAL_LM_MAPPING,
				    FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING,
				    FLAX_MODEL_FOR_MASKED_LM_MAPPING,
				    FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING,
				    FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING,
				    FLAX_MODEL_FOR_PRETRAINING_MAPPING,
				    FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING,
				    FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
				    FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
				    FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING,
				    FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
				    FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING,
				    FLAX_MODEL_MAPPING,
				    FlaxAutoModel,
				    FlaxAutoModelForCausalLM,
				    FlaxAutoModelForImageClassification,
				    FlaxAutoModelForMaskedLM,
				    FlaxAutoModelForMultipleChoice,
				    FlaxAutoModelForNextSentencePrediction,
				    FlaxAutoModelForPreTraining,
				    FlaxAutoModelForQuestionAnswering,
				    FlaxAutoModelForSeqaSeqLM,
				    FlaxAutoModelForSequenceClassification,
				    FlaxAutoModelForSpeechSeqaSeq,
				    FlaxAutoModelForTokenClassification,
				    FlaxAutoModelForVisionaSeq,
				)

else:
		import sys

		_lowercase											=			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)