






'''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


__UpperCAmelCase							:   List[str]							=  logging.get_logger(__name__)


__UpperCAmelCase							:   Tuple							=  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"),
    ]
)

__UpperCAmelCase							:   List[Any]							=  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"),
    ]
)

__UpperCAmelCase							:   Optional[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"),
    ]
)

__UpperCAmelCase							:   Union[str, Any]							=  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"),
    ]
)

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

__UpperCAmelCase							:   List[str]							=  OrderedDict(
    [
        ("vision-encoder-decoder", "FlaxVisionEncoderDecoderModel"),
    ]
)

__UpperCAmelCase							:   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"),
    ]
)

__UpperCAmelCase							:   Optional[int]							=  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"),
    ]
)

__UpperCAmelCase							:   Tuple							=  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"),
    ]
)

__UpperCAmelCase							:   Dict							=  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"),
    ]
)

__UpperCAmelCase							:   str							=  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"),
    ]
)

__UpperCAmelCase							:   int							=  OrderedDict(
    [
        ("bert", "FlaxBertForNextSentencePrediction"),
    ]
)

__UpperCAmelCase							:   Any							=  OrderedDict(
    [
        ("speech-encoder-decoder", "FlaxSpeechEncoderDecoderModel"),
        ("whisper", "FlaxWhisperForConditionalGeneration"),
    ]
)

__UpperCAmelCase							:   List[Any]							=  OrderedDict(
    [
        ("whisper", "FlaxWhisperForAudioClassification"),
    ]
)

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


class 					_snake_case						(			_BaseAutoModelClass ):
	_A          =   FLAX_MODEL_MAPPING




__UpperCAmelCase							:   int							=  auto_class_update(FlaxAutoModel)


class 					_snake_case						(			_BaseAutoModelClass ):
	_A          =   FLAX_MODEL_FOR_PRETRAINING_MAPPING




__UpperCAmelCase							:   Union[str, Any]							=  auto_class_update(FlaxAutoModelForPreTraining, head_doc="pretraining")


class 					_snake_case						(			_BaseAutoModelClass ):
	_A          =   FLAX_MODEL_FOR_CAUSAL_LM_MAPPING




__UpperCAmelCase							:   List[Any]							=  auto_class_update(FlaxAutoModelForCausalLM, head_doc="causal language modeling")


class 					_snake_case						(			_BaseAutoModelClass ):
	_A          =   FLAX_MODEL_FOR_MASKED_LM_MAPPING




__UpperCAmelCase							:   Union[str, Any]							=  auto_class_update(FlaxAutoModelForMaskedLM, head_doc="masked language modeling")


class 					_snake_case						(			_BaseAutoModelClass ):
	_A          =   FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING




__UpperCAmelCase							:   Union[str, Any]							=  auto_class_update(
    FlaxAutoModelForSeqaSeqLM, head_doc="sequence-to-sequence language modeling", checkpoint_for_example="t5-base"
)


class 					_snake_case						(			_BaseAutoModelClass ):
	_A          =   FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING




__UpperCAmelCase							:   int							=  auto_class_update(
    FlaxAutoModelForSequenceClassification, head_doc="sequence classification"
)


class 					_snake_case						(			_BaseAutoModelClass ):
	_A          =   FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING




__UpperCAmelCase							:   List[str]							=  auto_class_update(FlaxAutoModelForQuestionAnswering, head_doc="question answering")


class 					_snake_case						(			_BaseAutoModelClass ):
	_A          =   FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING




__UpperCAmelCase							:   Union[str, Any]							=  auto_class_update(
    FlaxAutoModelForTokenClassification, head_doc="token classification"
)


class 					_snake_case						(			_BaseAutoModelClass ):
	_A          =   FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING




__UpperCAmelCase							:   Optional[Any]							=  auto_class_update(FlaxAutoModelForMultipleChoice, head_doc="multiple choice")


class 					_snake_case						(			_BaseAutoModelClass ):
	_A          =   FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING




__UpperCAmelCase							:   Optional[Any]							=  auto_class_update(
    FlaxAutoModelForNextSentencePrediction, head_doc="next sentence prediction"
)


class 					_snake_case						(			_BaseAutoModelClass ):
	_A          =   FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING




__UpperCAmelCase							:   Optional[Any]							=  auto_class_update(
    FlaxAutoModelForImageClassification, head_doc="image classification"
)


class 					_snake_case						(			_BaseAutoModelClass ):
	_A          =   FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING




__UpperCAmelCase							:   Any							=  auto_class_update(FlaxAutoModelForVisionaSeq, head_doc="vision-to-text modeling")


class 					_snake_case						(			_BaseAutoModelClass ):
	_A          =   FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING




__UpperCAmelCase							:   Any							=  auto_class_update(
    FlaxAutoModelForSpeechSeqaSeq, head_doc="sequence-to-sequence speech-to-text modeling"
)







from typing import Any





def 					lowercase_ (    __snake_case     :							list	,	__snake_case     :							list	,	__snake_case     :							dict	,	__snake_case     :							dict	,	__snake_case     :							dict	,	)     -> list:





				'''simple docstring'''


				_validation(
				    __snake_case	,	__snake_case	,	__snake_case	,	__snake_case	,	__snake_case	,	)
				# Creates data structures and fill initial step
				snake_case__      :dict         =   {}
				snake_case__      :dict         =   {}
				for state in states_space:
								snake_case__      :List[Any]         =   observations_space[0]
								snake_case__      :str         =   (
								    initial_probabilities[state] * emission_probabilities[state][observation]
								)
								snake_case__      :str         =   None

				# Fills the data structure with the probabilities of
				# different transitions and pointers to previous states
				for o in range(1	,	len(__snake_case      )      ):
								snake_case__      :Any         =   observations_space[o]
								snake_case__      :Tuple         =   observations_space[o - 1]
								for state in states_space:
												# Calculates the argmax for probability function
												snake_case__      :Tuple         =   ""
												snake_case__      :Union[str, Any]         =   -1
												for k_state in states_space:
																snake_case__      :int         =   (
																    probabilities[(k_state, prior_observation)]
																    * transition_probabilities[k_state][state]
																    * emission_probabilities[state][observation]
																)
																if probability > max_probability:
																				snake_case__      :str         =   probability
																				snake_case__      :Tuple         =   k_state

            # Update probabilities and pointers dicts
												snake_case__      :List[str]         =   (
												    probabilities[(arg_max, prior_observation)]
												    * transition_probabilities[arg_max][state]
												    * emission_probabilities[state][observation]
												)

												snake_case__      :List[str]         =   arg_max

    # The final observation
				snake_case__      :str         =   observations_space[len(__snake_case      ) - 1]

				# argmax for given final observation
				snake_case__      :Optional[int]         =   ""
				snake_case__      :List[str]         =   -1
				for k_state in states_space:
								snake_case__      :List[str]         =   probabilities[(k_state, final_observation)]
								if probability > max_probability:
												snake_case__      :List[str]         =   probability
												snake_case__      :int         =   k_state
				snake_case__      :Any         =   arg_max

				# Process pointers backwards
				snake_case__      :int         =   last_state
				snake_case__      :List[str]         =   []
				for o in range(len(__snake_case      ) - 1	,	-1	,	-1      ):
								result.append(__snake_case      )
								snake_case__      :List[str]         =   pointers[previous, observations_space[o]]
				result.reverse()

				return result





def 					lowercase_ (    __snake_case     :							Any	,	__snake_case     :							Any	,	__snake_case     :							Any	,	__snake_case     :							Any	,	__snake_case     :							Any	,	)     -> None:





				'''simple docstring'''


				_validate_not_empty(
				    __snake_case	,	__snake_case	,	__snake_case	,	__snake_case	,	__snake_case	,	)
				_validate_lists(__snake_case	,	__snake_case      )
				_validate_dicts(
				    __snake_case	,	__snake_case	,	__snake_case      )





def 					lowercase_ (    __snake_case     :							Any	,	__snake_case     :							Any	,	__snake_case     :							Any	,	__snake_case     :							Any	,	__snake_case     :							Any	,	)     -> None:





				'''simple docstring'''


				if not all(
				    [
				        observations_space,
				        states_space,
				        initial_probabilities,
				        transition_probabilities,
				        emission_probabilities,
				    ]      ):
								raise ValueError("There's an empty parameter"      )





def 					lowercase_ (    __snake_case     :							Any	,	__snake_case     :							Any      )     -> None:





				'''simple docstring'''


				_validate_list(__snake_case	,	"observations_space"      )
				_validate_list(__snake_case	,	"states_space"      )





def 					lowercase_ (    __snake_case     :							Any	,	__snake_case     :							str      )     -> None:





				'''simple docstring'''


				if not isinstance(_object	,	__snake_case      ):
								snake_case__      :Optional[int]         =   F'{var_name} must be a list'
								raise ValueError(__snake_case      )
				else:
								for x in _object:
												if not isinstance(__snake_case	,	__snake_case      ):
																snake_case__      :Any         =   F'{var_name} must be a list of strings'
																raise ValueError(__snake_case      )





def 					lowercase_ (    __snake_case     :							Any	,	__snake_case     :							Any	,	__snake_case     :							Any	,	)     -> None:





				'''simple docstring'''


				_validate_dict(__snake_case	,	"initial_probabilities"	,	__snake_case      )
				_validate_nested_dict(__snake_case	,	"transition_probabilities"      )
				_validate_nested_dict(__snake_case	,	"emission_probabilities"      )





def 					lowercase_ (    __snake_case     :							Any	,	__snake_case     :							str      )     -> None:





				'''simple docstring'''


				_validate_dict(_object	,	__snake_case	,	__snake_case      )
				for x in _object.values():
								_validate_dict(__snake_case	,	__snake_case	,	__snake_case	,	__snake_case      )





def 					lowercase_ (    __snake_case     :							Any	,	__snake_case     :							str	,	__snake_case     :							type	,	__snake_case     :							bool = False      )     -> None:





				'''simple docstring'''


				if not isinstance(_object	,	__snake_case      ):
								snake_case__      :str         =   F'{var_name} must be a dict'
								raise ValueError(__snake_case      )
				if not all(isinstance(__snake_case	,	__snake_case      ) for x in _object      ):
								snake_case__      :List[Any]         =   F'{var_name} all keys must be strings'
								raise ValueError(__snake_case      )
				if not all(isinstance(__snake_case	,	__snake_case      ) for x in _object.values()      ):
								snake_case__      :Optional[int]         =   "nested dictionary " if nested else ""
								snake_case__      :int         =   F'{var_name} {nested_text}all values must be {value_type.__name__}'
								raise ValueError(__snake_case      )


if __name__ == "__main__":
	from doctest import testmod

	testmod()