


"""simple docstring"""
from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE					:       str							   =							{
    """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:
			SCREAMING_SNAKE_CASE					:       Any							   =							[
			    """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:
			SCREAMING_SNAKE_CASE					:       List[str]							   =							[
			    """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:
			SCREAMING_SNAKE_CASE					:       str							   =							[
			    """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

			SCREAMING_SNAKE_CASE					:       Dict							   =							_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)












"""simple docstring"""






from typing import Callable, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase_      =				logging.get_logger(__name__)

lowerCAmelCase_      =				{
    '''microsoft/prophetnet-large-uncased''': (
        '''https://huggingface.co/microsoft/prophetnet-large-uncased/resolve/main/config.json'''
    ),
}



class 						lowerCAmelCase       (   snake_case				):
       lowerCAmelCase__    			=	"""prophetnet"""
       lowerCAmelCase__    			=	["""past_key_values"""]
       lowerCAmelCase__    			=	{
           """num_attention_heads""": """num_encoder_attention_heads""",
       }






       def __init__( self     ,	a__ = 0.1     ,	a__ = "gelu"     ,	a__ = 3_05_22     ,	a__ = 10_24     ,	a__ = 40_96     ,	a__ = 12     ,	a__ = 16     ,	a__ = 40_96     ,	a__ = 12     ,	a__ = 16     ,	a__ = 0.1     ,	a__ = 0.1     ,	a__ = 5_12     ,	a__ = 0.02     ,	a__ = True     ,	a__ = True     ,	a__ = 0     ,	a__ = 2     ,	a__ = 32     ,	a__ = 1_28     ,	a__ = False     ,	a__ = 0.0     ,	a__ = True     ,	a__ = 0     ,	a__ = 1     ,	a__ = 2     ,	**a__     ,	):
              _UpperCAmelCase			     =  vocab_size
              _UpperCAmelCase			     =  hidden_size
              _UpperCAmelCase			     =  encoder_ffn_dim
              _UpperCAmelCase			     =  num_encoder_layers
              _UpperCAmelCase			     =  num_encoder_attention_heads
              _UpperCAmelCase			     =  decoder_ffn_dim
              _UpperCAmelCase			     =  num_decoder_layers
              _UpperCAmelCase			     =  num_decoder_attention_heads
              _UpperCAmelCase			     =  max_position_embeddings
              _UpperCAmelCase			     =  init_std  # Normal(0, this parameter)
              _UpperCAmelCase			     =  activation_function

              # parameters for prophetnet
              _UpperCAmelCase			     =  ngram
              _UpperCAmelCase			     =  num_buckets
              _UpperCAmelCase			     =  relative_max_distance
              _UpperCAmelCase			     =  disable_ngram_loss
              _UpperCAmelCase			     =  eps

              # 3 Types of Dropout
              _UpperCAmelCase			     =  attention_dropout
              _UpperCAmelCase			     =  activation_dropout
              _UpperCAmelCase			     =  dropout

              _UpperCAmelCase			     =  use_cache

              super().__init__(
                  pad_token_id=a__     ,	bos_token_id=a__     ,	eos_token_id=a__     ,	is_encoder_decoder=a__     ,	add_cross_attention=a__     ,	decoder_start_token_id=a__     ,	**a__     ,	)






       @property
       def 				__A			( self  ):
              return self.num_encoder_layers + self.num_decoder_layers






       @num_hidden_layers.setter
       def 				__A			( self     ,	a__  ):
              raise NotImplementedError(
                  'This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and'
                  ' `num_decoder_layers`.'  )






