





'''simple docstring'''



from collections import OrderedDict
from typing import Mapping

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


_SCREAMING_SNAKE_CASE    =			logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE    =			{
    '''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 							__lowercase				(					lowerCAmelCase__  ):







	'''simple docstring'''

	a			: Any      =				"plbart"
	a			: str      =				["past_key_values"]
	a			: Union[str, Any]      =				{"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}


	def __init__(self   ,_lowerCamelCase=50005   ,_lowerCamelCase=1024   ,_lowerCamelCase=6   ,_lowerCamelCase=3072   ,_lowerCamelCase=12   ,_lowerCamelCase=6   ,_lowerCamelCase=3072   ,_lowerCamelCase=12   ,_lowerCamelCase=0.0   ,_lowerCamelCase=0.0   ,_lowerCamelCase=True   ,_lowerCamelCase=True   ,_lowerCamelCase="gelu"   ,_lowerCamelCase=768   ,_lowerCamelCase=0.1   ,_lowerCamelCase=0.1   ,_lowerCamelCase=0.0   ,_lowerCamelCase=0.0_2   ,_lowerCamelCase=0.0   ,_lowerCamelCase=True   ,_lowerCamelCase=1   ,_lowerCamelCase=0   ,_lowerCamelCase=2   ,_lowerCamelCase=2   ,**_lowerCamelCase   ,)							->							Any:







				'''simple docstring'''





				__lowercase   =							vocab_size
				__lowercase   =							max_position_embeddings
				__lowercase   =							d_model
				__lowercase   =							encoder_ffn_dim
				__lowercase   =							encoder_layers
				__lowercase   =							encoder_attention_heads
				__lowercase   =							decoder_ffn_dim
				__lowercase   =							decoder_layers
				__lowercase   =							decoder_attention_heads
				__lowercase   =							dropout
				__lowercase   =							attention_dropout
				__lowercase   =							activation_dropout
				__lowercase   =							activation_function
				__lowercase   =							init_std
				__lowercase   =							encoder_layerdrop
				__lowercase   =							decoder_layerdrop
				__lowercase   =							classifier_dropout
				__lowercase   =							use_cache
				__lowercase   =							encoder_layers
				__lowercase   =							scale_embedding  # scale factor will be sqrt(d_model) if True
				super().__init__(
				    pad_token_id=_lowerCamelCase   ,bos_token_id=_lowerCamelCase   ,eos_token_id=_lowerCamelCase   ,is_encoder_decoder=_lowerCamelCase   ,forced_eos_token_id=_lowerCamelCase   ,**_lowerCamelCase   ,)






class 							__lowercase				(					lowerCAmelCase__  ):







	'''simple docstring'''

	@property
	def   _UpperCAmelCase   (self       )							->							Mapping[str, Mapping[int, str]]:







				'''simple docstring'''





				return OrderedDict(
				    [
				        ('''input_ids''', {0: '''batch''', 1: '''sequence'''}),
				        ('''attention_mask''', {0: '''batch''', 1: '''sequence'''}),
				    ]       )


	@property
	def   _UpperCAmelCase   (self       )							->							Mapping[str, Mapping[int, str]]:







				'''simple docstring'''





				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'''}),
							    ]       )












'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


_SCREAMING_SNAKE_CASE    =			{
    '''configuration_deformable_detr''': ['''DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DeformableDetrConfig'''],
}

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_SCREAMING_SNAKE_CASE    =			['''DeformableDetrFeatureExtractor''']
	_SCREAMING_SNAKE_CASE    =			['''DeformableDetrImageProcessor''']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_SCREAMING_SNAKE_CASE    =			[
	    '''DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''DeformableDetrForObjectDetection''',
	    '''DeformableDetrModel''',
	    '''DeformableDetrPreTrainedModel''',
	]


if TYPE_CHECKING:
	from .configuration_deformable_detr import DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, DeformableDetrConfig

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .feature_extraction_deformable_detr import DeformableDetrFeatureExtractor
		from .image_processing_deformable_detr import DeformableDetrImageProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_deformable_detr import (
		    DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
		    DeformableDetrForObjectDetection,
		    DeformableDetrModel,
		    DeformableDetrPreTrainedModel,
		)

else:
	import sys

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





