






from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging


__lowerCamelCase						= logging.get_logger(__name__)

__lowerCamelCase						= {
    'uclanlp/plbart-base': 'https://huggingface.co/uclanlp/plbart-base/resolve/main/config.json',
    # See all PLBART models at https://huggingface.co/models?filter=plbart
}

class      UpperCamelCase_							(				UpperCamelCase       ):
						lowercase									=  '''plbart'''
						lowercase									=  ['''past_key_values''']
						lowercase									=  {'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}




						def __init__(    self		,	lowercase=50_005		,	lowercase=1_024		,	lowercase=6		,	lowercase=3_072		,	lowercase=12		,	lowercase=6		,	lowercase=3_072		,	lowercase=12		,	lowercase=0.0		,	lowercase=0.0		,	lowercase=True		,	lowercase=True		,	lowercase="gelu"		,	lowercase=768		,	lowercase=0.1		,	lowercase=0.1		,	lowercase=0.0		,	lowercase=0.02		,	lowercase=0.0		,	lowercase=True		,	lowercase=1		,	lowercase=0		,	lowercase=2		,	lowercase=2		,	**lowercase		,	)			->						Tuple:
													_a  :    int			=						vocab_size
													_a  :    Union[str, Any]			=						max_position_embeddings
													_a  :    Dict			=						d_model
													_a  :    Optional[Any]			=						encoder_ffn_dim
													_a  :    Dict			=						encoder_layers
													_a  :    Optional[Any]			=						encoder_attention_heads
													_a  :    Any			=						decoder_ffn_dim
													_a  :    int			=						decoder_layers
													_a  :    Dict			=						decoder_attention_heads
													_a  :    Optional[int]			=						dropout
													_a  :    List[Any]			=						attention_dropout
													_a  :    int			=						activation_dropout
													_a  :    List[str]			=						activation_function
													_a  :    Any			=						init_std
													_a  :    int			=						encoder_layerdrop
													_a  :    Any			=						decoder_layerdrop
													_a  :    Tuple			=						classifier_dropout
													_a  :    int			=						use_cache
													_a  :    str			=						encoder_layers
													_a  :    Any			=						scale_embedding  # scale factor will be sqrt(d_model) if True
													super().__init__(
													    pad_token_id=lowercase		,	bos_token_id=lowercase		,	eos_token_id=lowercase		,	is_encoder_decoder=lowercase		,	forced_eos_token_id=lowercase		,	**lowercase		,	)

class      UpperCamelCase_							(				UpperCamelCase       ):




						@property
						def      snake_case__(    self       )			->						Mapping[str, Mapping[int, str]]:
													return OrderedDict(
													    [
													        ('''input_ids''', {0: '''batch''', 1: '''sequence'''}),
													        ('''attention_mask''', {0: '''batch''', 1: '''sequence'''}),
													    ]       )







						@property
						def      snake_case__(    self       )			->						Mapping[str, Mapping[int, str]]:
													if self.use_past:
																				return OrderedDict(
																				    [
																				        ('''last_hidden_state''', {0: '''batch''', 1: '''sequence'''}),
																				        ('''past_keys''', {0: '''batch''', 2: '''sequence'''}),
																				        ('''encoder_last_hidden_state''', {0: '''batch''', 1: '''sequence'''}),
																				    ]       )
													else:
																				return OrderedDict(
																				    [
																				        ('''last_hidden_state''', {0: '''batch''', 1: '''sequence'''}),
																				        ('''encoder_last_hidden_state''', {0: '''batch''', 1: '''sequence'''}),
																				    ]       )







from typing import TYPE_CHECKING

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


__lowerCamelCase						= {
    'configuration_bart': ['BART_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BartConfig', 'BartOnnxConfig'],
    'tokenization_bart': ['BartTokenizer'],
}

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCamelCase						= ['BartTokenizerFast']

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCamelCase						= [
						    'BART_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'BartForCausalLM',
						    'BartForConditionalGeneration',
						    'BartForQuestionAnswering',
						    'BartForSequenceClassification',
						    'BartModel',
						    'BartPretrainedModel',
						    'PretrainedBartModel',
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCamelCase						= [
						    'TFBartForConditionalGeneration',
						    'TFBartForSequenceClassification',
						    'TFBartModel',
						    'TFBartPretrainedModel',
						]

try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowerCamelCase						= [
						    'FlaxBartDecoderPreTrainedModel',
						    'FlaxBartForCausalLM',
						    'FlaxBartForConditionalGeneration',
						    'FlaxBartForQuestionAnswering',
						    'FlaxBartForSequenceClassification',
						    'FlaxBartModel',
						    'FlaxBartPreTrainedModel',
						]

if TYPE_CHECKING:
						from .configuration_bart import BART_PRETRAINED_CONFIG_ARCHIVE_MAP, BartConfig, BartOnnxConfig
						from .tokenization_bart import BartTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_bart_fast import BartTokenizerFast

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_bart import (
												    BART_PRETRAINED_MODEL_ARCHIVE_LIST,
												    BartForCausalLM,
												    BartForConditionalGeneration,
												    BartForQuestionAnswering,
												    BartForSequenceClassification,
												    BartModel,
												    BartPretrainedModel,
												    PretrainedBartModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_bart import (
												    TFBartForConditionalGeneration,
												    TFBartForSequenceClassification,
												    TFBartModel,
												    TFBartPretrainedModel,
												)

						try:
												if not is_flax_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_flax_bart import (
												    FlaxBartDecoderPreTrainedModel,
												    FlaxBartForCausalLM,
												    FlaxBartForConditionalGeneration,
												    FlaxBartForQuestionAnswering,
												    FlaxBartForSequenceClassification,
												    FlaxBartModel,
												    FlaxBartPreTrainedModel,
												)

else:
						import sys

						__lowerCamelCase						= _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)