



"""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  							=					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 			lowercase__			(      _BaseAutoModelClass    ):
							'''simple docstring'''







							_UpperCAmelCase      				=					FLAX_MODEL_MAPPING







lowercase  							=					auto_class_update(FlaxAutoModel)




class 			lowercase__			(      _BaseAutoModelClass    ):
							'''simple docstring'''







							_UpperCAmelCase      				=					FLAX_MODEL_FOR_PRETRAINING_MAPPING







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




class 			lowercase__			(      _BaseAutoModelClass    ):
							'''simple docstring'''







							_UpperCAmelCase      				=					FLAX_MODEL_FOR_CAUSAL_LM_MAPPING







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




class 			lowercase__			(      _BaseAutoModelClass    ):
							'''simple docstring'''







							_UpperCAmelCase      				=					FLAX_MODEL_FOR_MASKED_LM_MAPPING







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




class 			lowercase__			(      _BaseAutoModelClass    ):
							'''simple docstring'''







							_UpperCAmelCase      				=					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 			lowercase__			(      _BaseAutoModelClass    ):
							'''simple docstring'''







							_UpperCAmelCase      				=					FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING







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




class 			lowercase__			(      _BaseAutoModelClass    ):
							'''simple docstring'''







							_UpperCAmelCase      				=					FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING







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




class 			lowercase__			(      _BaseAutoModelClass    ):
							'''simple docstring'''







							_UpperCAmelCase      				=					FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING







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




class 			lowercase__			(      _BaseAutoModelClass    ):
							'''simple docstring'''







							_UpperCAmelCase      				=					FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING







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




class 			lowercase__			(      _BaseAutoModelClass    ):
							'''simple docstring'''







							_UpperCAmelCase      				=					FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING







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




class 			lowercase__			(      _BaseAutoModelClass    ):
							'''simple docstring'''







							_UpperCAmelCase      				=					FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING







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




class 			lowercase__			(      _BaseAutoModelClass    ):
							'''simple docstring'''







							_UpperCAmelCase      				=					FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING







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




class 			lowercase__			(      _BaseAutoModelClass    ):
							'''simple docstring'''







							_UpperCAmelCase      				=					FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING







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







"""simple docstring"""





from typing import List, Optional, TypeVar

from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _interleave_iterable_datasets
from .splits import NamedSplit
from .utils import logging
from .utils.py_utils import Literal


lowercase  							=					logging.get_logger(__name__)


lowercase  							=					TypeVar('''DatasetType''', Dataset, IterableDataset)




def 	UpperCAmelCase     (		A	:						List[DatasetType]     ,				A	:						Optional[List[float]] = None     ,				A	:						Optional[int] = None     ,				A	:						Optional[DatasetInfo] = None     ,				A	:						Optional[NamedSplit] = None     ,				A	:						Literal["first_exhausted", "all_exhausted"] = "first_exhausted"     ,				):

		'''simple docstring'''


		from .arrow_dataset import Dataset
		from .iterable_dataset import IterableDataset

		if not datasets:
				raise ValueError('Unable to interleave an empty list of datasets.'       )
		for i, dataset in enumerate(A       ):
				if not isinstance(A     ,				(Dataset, IterableDataset)       ):
						if isinstance(A     ,				(DatasetDict, IterableDatasetDict)       ):
								if not dataset:
										raise ValueError(
										    f'Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} '
										    'is an empty dataset dictionary.'       )
								raise ValueError(
								    f'Dataset at position {i} has at least one split: {list(A       )}\n'
								    f'Please pick one to interleave with the other datasets, for example: dataset[\'{next(iter(A       )       )}\']'       )
						raise ValueError(
						    f'Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(A       ).__name__}.'       )
				if i == 0:
						_UpperCAmelCase ,					_UpperCAmelCase							 =		(
						    (Dataset, IterableDataset) if isinstance(A     ,				A       ) else (IterableDataset, Dataset)
						)
				elif not isinstance(A     ,				A       ):
						raise ValueError(
						    f'Unable to interleave a {dataset_type.__name__} (at position 0) with a {other_type.__name__} (at position {i}). Expected a list of Dataset objects or a list of IterableDataset objects.'       )
		if stopping_strategy not in ["first_exhausted", "all_exhausted"]:
				raise ValueError(f'{stopping_strategy} is not supported. Please enter a valid stopping_strategy.'       )
		if dataset_type is Dataset:
				return _interleave_map_style_datasets(
				    A     ,				A     ,				A     ,				info=A     ,				split=A     ,				stopping_strategy=A       )
		else:
				return _interleave_iterable_datasets(
				    A     ,				A     ,				A     ,				info=A     ,				split=A     ,				stopping_strategy=A       )






def 	UpperCAmelCase     (		A	:						List[DatasetType]     ,				A	:						Optional[DatasetInfo] = None     ,				A	:						Optional[NamedSplit] = None     ,				A	:						int = 0     ,				):

		'''simple docstring'''


		if not dsets:
				raise ValueError('Unable to concatenate an empty list of datasets.'       )
		for i, dataset in enumerate(A       ):
				if not isinstance(A     ,				(Dataset, IterableDataset)       ):
						if isinstance(A     ,				(DatasetDict, IterableDatasetDict)       ):
								if not dataset:
										raise ValueError(
										    f'Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} '
										    'is an empty dataset dictionary.'       )
								raise ValueError(
								    f'Dataset at position {i} has at least one split: {list(A       )}\n'
								    f'Please pick one to interleave with the other datasets, for example: dataset[\'{next(iter(A       )       )}\']'       )
						raise ValueError(
						    f'Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(A       ).__name__}.'       )
				if i == 0:
						_UpperCAmelCase ,					_UpperCAmelCase							 =		(
						    (Dataset, IterableDataset) if isinstance(A     ,				A       ) else (IterableDataset, Dataset)
						)
				elif not isinstance(A     ,				A       ):
						raise ValueError(
						    f'Unable to interleave a {dataset_type.__name__} (at position 0) with a {other_type.__name__} (at position {i}). Expected a list of Dataset objects or a list of IterableDataset objects.'       )
		if dataset_type is Dataset:
				return _concatenate_map_style_datasets(A     ,				info=A     ,				split=A     ,				axis=A       )
		else:
				return _concatenate_iterable_datasets(A     ,				info=A     ,				split=A     ,				axis=A       )


