


"""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


snake_case__						:   int			 = logging.get_logger(__name__)


snake_case__						:   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'''),
    ]
)

snake_case__						:   Dict			 = 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'''),
    ]
)

snake_case__						:   Dict			 = 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'''),
    ]
)

snake_case__						:   Tuple			 = 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'''),
    ]
)

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

snake_case__						:   List[str]			 = OrderedDict(
    [
        ('''vision-encoder-decoder''', '''FlaxVisionEncoderDecoderModel'''),
    ]
)

snake_case__						:   Any			 = 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'''),
    ]
)

snake_case__						:   str			 = 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'''),
    ]
)

snake_case__						:   List[str]			 = 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'''),
    ]
)

snake_case__						:   Optional[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'''),
    ]
)

snake_case__						:   Union[str, 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'''),
    ]
)

snake_case__						:   str			 = OrderedDict(
    [
        ('''bert''', '''FlaxBertForNextSentencePrediction'''),
    ]
)

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

snake_case__						:   List[Any]			 = OrderedDict(
    [
        ('''whisper''', '''FlaxWhisperForAudioClassification'''),
    ]
)

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



class 						snake_case_(				_BaseAutoModelClass	):
     __UpperCamelCase     =    FLAX_MODEL_MAPPING



snake_case__						:   List[Any]			 = auto_class_update(FlaxAutoModel)



class 						snake_case_(				_BaseAutoModelClass	):
     __UpperCamelCase     =    FLAX_MODEL_FOR_PRETRAINING_MAPPING



snake_case__						:   List[Any]			 = auto_class_update(FlaxAutoModelForPreTraining, head_doc='''pretraining''')



class 						snake_case_(				_BaseAutoModelClass	):
     __UpperCamelCase     =    FLAX_MODEL_FOR_CAUSAL_LM_MAPPING



snake_case__						:   List[Any]			 = auto_class_update(FlaxAutoModelForCausalLM, head_doc='''causal language modeling''')



class 						snake_case_(				_BaseAutoModelClass	):
     __UpperCamelCase     =    FLAX_MODEL_FOR_MASKED_LM_MAPPING



snake_case__						:   Dict			 = auto_class_update(FlaxAutoModelForMaskedLM, head_doc='''masked language modeling''')



class 						snake_case_(				_BaseAutoModelClass	):
     __UpperCamelCase     =    FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING



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



class 						snake_case_(				_BaseAutoModelClass	):
     __UpperCamelCase     =    FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING



snake_case__						:   Dict			 = auto_class_update(
    FlaxAutoModelForSequenceClassification, head_doc='''sequence classification'''
)



class 						snake_case_(				_BaseAutoModelClass	):
     __UpperCamelCase     =    FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING



snake_case__						:   str			 = auto_class_update(FlaxAutoModelForQuestionAnswering, head_doc='''question answering''')



class 						snake_case_(				_BaseAutoModelClass	):
     __UpperCamelCase     =    FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING



snake_case__						:   int			 = auto_class_update(
    FlaxAutoModelForTokenClassification, head_doc='''token classification'''
)



class 						snake_case_(				_BaseAutoModelClass	):
     __UpperCamelCase     =    FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING



snake_case__						:   Dict			 = auto_class_update(FlaxAutoModelForMultipleChoice, head_doc='''multiple choice''')



class 						snake_case_(				_BaseAutoModelClass	):
     __UpperCamelCase     =    FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING



snake_case__						:   Tuple			 = auto_class_update(
    FlaxAutoModelForNextSentencePrediction, head_doc='''next sentence prediction'''
)



class 						snake_case_(				_BaseAutoModelClass	):
     __UpperCamelCase     =    FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING



snake_case__						:   List[Any]			 = auto_class_update(
    FlaxAutoModelForImageClassification, head_doc='''image classification'''
)



class 						snake_case_(				_BaseAutoModelClass	):
     __UpperCamelCase     =    FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING



snake_case__						:   Optional[Any]			 = auto_class_update(FlaxAutoModelForVisionaSeq, head_doc='''vision-to-text modeling''')



class 						snake_case_(				_BaseAutoModelClass	):
     __UpperCamelCase     =    FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING



snake_case__						:   List[str]			 = auto_class_update(
    FlaxAutoModelForSpeechSeqaSeq, head_doc='''sequence-to-sequence speech-to-text modeling'''
)






"""simple docstring"""
import pytest

import datasets


# Import fixture modules as plugins
SCREAMING_SNAKE_CASE :    List[Any]									=				["""tests.fixtures.files""", """tests.fixtures.hub""", """tests.fixtures.fsspec"""]






def 		lowercase							(     _snake_case						:      Optional[int]     ,   _snake_case						:      Optional[int]     )     ->Tuple:
	"""simple docstring"""





	for item in items:
		if any(marker in item.keywords for marker in ['''integration''', '''unit''']     ):
			continue
		item.add_marker(pytest.mark.unit     )






def 		lowercase							(     _snake_case						:      List[str]     )     ->Optional[int]:
	"""simple docstring"""





	config.addinivalue_line('''markers'''     ,   '''torchaudio_latest: mark test to run with torchaudio>=0.12'''     )






@pytest.fixture(autouse=_snake_case     )
def 		lowercase							(     _snake_case						:      Optional[Any]     ,   _snake_case						:      Dict     )     ->Any:
	"""simple docstring"""





	__snake_case	:						List[Any]						=				tmp_path_factory.getbasetemp() / '''cache'''
	__snake_case	:						int						=				test_hf_cache_home / '''datasets'''
	__snake_case	:						Tuple						=				test_hf_cache_home / '''metrics'''
	__snake_case	:						List[str]						=				test_hf_cache_home / '''modules'''
	monkeypatch.setattr('''datasets.config.HF_DATASETS_CACHE'''     ,   str(_snake_case     )     )
	monkeypatch.setattr('''datasets.config.HF_METRICS_CACHE'''     ,   str(_snake_case     )     )
	monkeypatch.setattr('''datasets.config.HF_MODULES_CACHE'''     ,   str(_snake_case     )     )
	__snake_case	:						Optional[int]						=				test_hf_datasets_cache / '''downloads'''
	monkeypatch.setattr('''datasets.config.DOWNLOADED_DATASETS_PATH'''     ,   str(_snake_case     )     )
	__snake_case	:						Tuple						=				test_hf_datasets_cache / '''downloads''' / '''extracted'''
	monkeypatch.setattr('''datasets.config.EXTRACTED_DATASETS_PATH'''     ,   str(_snake_case     )     )






@pytest.fixture(autouse=_snake_case     ,   scope='''session'''     )
def 		lowercase							(     )     ->Any:
	"""simple docstring"""





	datasets.disable_progress_bar()






@pytest.fixture(autouse=_snake_case     )
def 		lowercase							(     _snake_case						:      Tuple     )     ->Union[str, Any]:
	"""simple docstring"""





	monkeypatch.setattr('''datasets.config.HF_UPDATE_DOWNLOAD_COUNTS'''     ,   _snake_case     )






@pytest.fixture
def 		lowercase							(     _snake_case						:      Any     )     ->Optional[Any]:
	"""simple docstring"""





	monkeypatch.setattr('''sqlalchemy.util.deprecations.SILENCE_UBER_WARNING'''     ,   _snake_case     )





