
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_					:						Optional[Any]				= logging.get_logger(__name__)


UpperCamelCase_					:						List[Any]				= 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_					:						Tuple				= 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_					:						List[str]				= 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_					:						List[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_					:						Dict				= OrderedDict(
    [
        # Model for Image-classsification
        ('''beit''', '''FlaxBeitForImageClassification'''),
        ('''regnet''', '''FlaxRegNetForImageClassification'''),
        ('''resnet''', '''FlaxResNetForImageClassification'''),
        ('''vit''', '''FlaxViTForImageClassification'''),
    ]
)

UpperCamelCase_					:						Union[str, Any]				= OrderedDict(
    [
        ('''vision-encoder-decoder''', '''FlaxVisionEncoderDecoderModel'''),
    ]
)

UpperCamelCase_					:						Optional[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_					:						Tuple				= 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_					:						Any				= 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_					:						Union[str, 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'''),
    ]
)

UpperCamelCase_					:						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'''),
    ]
)

UpperCamelCase_					:						Any				= OrderedDict(
    [
        ('''bert''', '''FlaxBertForNextSentencePrediction'''),
    ]
)

UpperCamelCase_					:						int				= OrderedDict(
    [
        ('''speech-encoder-decoder''', '''FlaxSpeechEncoderDecoderModel'''),
        ('''whisper''', '''FlaxWhisperForConditionalGeneration'''),
    ]
)

UpperCamelCase_					:						Optional[Any]				= OrderedDict(
    [
        ('''whisper''', '''FlaxWhisperForAudioClassification'''),
    ]
)

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



class __lowerCAmelCase				(					_BaseAutoModelClass      ):




			"""simple docstring"""







			snake_case	      =				FLAX_MODEL_MAPPING





UpperCamelCase_					:						List[Any]				= auto_class_update(FlaxAutoModel)



class __lowerCAmelCase				(					_BaseAutoModelClass      ):




			"""simple docstring"""







			snake_case	      =				FLAX_MODEL_FOR_PRETRAINING_MAPPING





UpperCamelCase_					:						int				= auto_class_update(FlaxAutoModelForPreTraining, head_doc='''pretraining''')



class __lowerCAmelCase				(					_BaseAutoModelClass      ):




			"""simple docstring"""







			snake_case	      =				FLAX_MODEL_FOR_CAUSAL_LM_MAPPING





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



class __lowerCAmelCase				(					_BaseAutoModelClass      ):




			"""simple docstring"""







			snake_case	      =				FLAX_MODEL_FOR_MASKED_LM_MAPPING





UpperCamelCase_					:						Optional[Any]				= auto_class_update(FlaxAutoModelForMaskedLM, head_doc='''masked language modeling''')



class __lowerCAmelCase				(					_BaseAutoModelClass      ):




			"""simple docstring"""







			snake_case	      =				FLAX_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING





UpperCamelCase_					:						List[Any]				= auto_class_update(
    FlaxAutoModelForSeqaSeqLM, head_doc='''sequence-to-sequence language modeling''', checkpoint_for_example='''t5-base'''
)



class __lowerCAmelCase				(					_BaseAutoModelClass      ):




			"""simple docstring"""







			snake_case	      =				FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING





UpperCamelCase_					:						Any				= auto_class_update(
    FlaxAutoModelForSequenceClassification, head_doc='''sequence classification'''
)



class __lowerCAmelCase				(					_BaseAutoModelClass      ):




			"""simple docstring"""







			snake_case	      =				FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING





UpperCamelCase_					:						Dict				= auto_class_update(FlaxAutoModelForQuestionAnswering, head_doc='''question answering''')



class __lowerCAmelCase				(					_BaseAutoModelClass      ):




			"""simple docstring"""







			snake_case	      =				FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING





UpperCamelCase_					:						Optional[Any]				= auto_class_update(
    FlaxAutoModelForTokenClassification, head_doc='''token classification'''
)



class __lowerCAmelCase				(					_BaseAutoModelClass      ):




			"""simple docstring"""







			snake_case	      =				FLAX_MODEL_FOR_MULTIPLE_CHOICE_MAPPING





UpperCamelCase_					:						str				= auto_class_update(FlaxAutoModelForMultipleChoice, head_doc='''multiple choice''')



class __lowerCAmelCase				(					_BaseAutoModelClass      ):




			"""simple docstring"""







			snake_case	      =				FLAX_MODEL_FOR_NEXT_SENTENCE_PREDICTION_MAPPING





UpperCamelCase_					:						Optional[int]				= auto_class_update(
    FlaxAutoModelForNextSentencePrediction, head_doc='''next sentence prediction'''
)



class __lowerCAmelCase				(					_BaseAutoModelClass      ):




			"""simple docstring"""







			snake_case	      =				FLAX_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING





UpperCamelCase_					:						Union[str, Any]				= auto_class_update(
    FlaxAutoModelForImageClassification, head_doc='''image classification'''
)



class __lowerCAmelCase				(					_BaseAutoModelClass      ):




			"""simple docstring"""







			snake_case	      =				FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING





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



class __lowerCAmelCase				(					_BaseAutoModelClass      ):




			"""simple docstring"""







			snake_case	      =				FLAX_MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING





UpperCamelCase_					:						Optional[int]				= auto_class_update(
    FlaxAutoModelForSpeechSeqaSeq, head_doc='''sequence-to-sequence speech-to-text modeling'''
)






"""simple docstring"""





import os

import pytest
from attr import dataclass


UpperCamelCase_					:						str				= '''us-east-1'''  # defaults region



@dataclass
class __lowerCAmelCase				:




			"""simple docstring"""







			snake_case	      =				42
			snake_case	      =				"arn:aws:iam::558105141721:role/sagemaker_execution_role"
			snake_case	      =				{
			    "task_name": "mnli",
			    "per_device_train_batch_size": 16,
			    "per_device_eval_batch_size": 16,
			    "do_train": True,
			    "do_eval": True,
			    "do_predict": True,
			    "output_dir": "/opt/ml/model",
			    "overwrite_output_dir": True,
			    "max_steps": 5_00,
			    "save_steps": 55_00,
			}
			snake_case	      =				{**hyperparameters, "max_steps": 10_00}




			@property
			def      lowerCamelCase__     (				self						:					int	)      -> str:







								"""simple docstring"""
								if self.framework == "pytorch":
													return [
													    {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
													    {"Name": "eval_accuracy", "Regex": r"eval_accuracy.*=\D*(.*?)$"},
													    {"Name": "eval_loss", "Regex": r"eval_loss.*=\D*(.*?)$"},
													]
								else:
													return [
													    {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
													    {"Name": "eval_accuracy", "Regex": r"loss.*=\D*(.*?)]?$"},
													    {"Name": "eval_loss", "Regex": r"sparse_categorical_accuracy.*=\D*(.*?)]?$"},
													]




			@property
			def      lowerCamelCase__     (				self						:					Any	)      -> str:







								"""simple docstring"""
								return F'{self.framework}-transfromers-test'




			@property
			def      lowerCamelCase__     (				self						:					List[Any]	)      -> str:







								"""simple docstring"""
								return F'./tests/sagemaker/scripts/{self.framework}'






			@property
			def      lowerCamelCase__     (				self						:					Any	)      -> str:







								"""simple docstring"""
								if self.framework == "pytorch":
													return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:1.7.1-transformers4.6.1-gpu-py36-cu110-ubuntu18.04"
								else:
													return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-training:2.4.1-transformers4.6.1-gpu-py37-cu110-ubuntu18.04"





@pytest.fixture(scope="class"				)
def 							A_     (__a				):

					'''simple docstring'''





					A_				 =						SageMakerTestEnvironment(framework=request.cls.framework				)




