
from collections import OrderedDict
from typing import Mapping

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


snake_case__  							=							logging.get_logger(__name__)

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 							UpperCAmelCase	(   lowerCAmelCase_					):
					a__: Tuple			  =				"""plbart"""
					a__: Tuple			  =				["""past_key_values"""]
					a__: Optional[int]			  =				{"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}

					def __init__(			self      :					Tuple ,      lowerCAmelCase      :					Any=5_0005 ,      lowerCAmelCase      :					Union[str, Any]=1024 ,      lowerCAmelCase      :					Tuple=6 ,      lowerCAmelCase      :					Any=3072 ,      lowerCAmelCase      :					Dict=12 ,      lowerCAmelCase      :					int=6 ,      lowerCAmelCase      :					Any=3072 ,      lowerCAmelCase      :					str=12 ,      lowerCAmelCase      :					Optional[int]=0.0 ,      lowerCAmelCase      :					Dict=0.0 ,      lowerCAmelCase      :					Union[str, Any]=True ,      lowerCAmelCase      :					Tuple=True ,      lowerCAmelCase      :					Union[str, Any]="gelu" ,      lowerCAmelCase      :					Dict=768 ,      lowerCAmelCase      :					Optional[int]=0.1 ,      lowerCAmelCase      :					Dict=0.1 ,      lowerCAmelCase      :					Optional[Any]=0.0 ,      lowerCAmelCase      :					Optional[Any]=0.02 ,      lowerCAmelCase      :					Tuple=0.0 ,      lowerCAmelCase      :					Tuple=True ,      lowerCAmelCase      :					Any=1 ,      lowerCAmelCase      :					Dict=0 ,      lowerCAmelCase      :					List[Any]=2 ,      lowerCAmelCase      :					Optional[Any]=2 ,      **lowerCAmelCase      :					Dict ,      ):
											lowercase       :    Optional[Any]											=  vocab_size
											lowercase       :    int											=  max_position_embeddings
											lowercase       :    Tuple											=  d_model
											lowercase       :    Optional[Any]											=  encoder_ffn_dim
											lowercase       :    Any											=  encoder_layers
											lowercase       :    int											=  encoder_attention_heads
											lowercase       :    Any											=  decoder_ffn_dim
											lowercase       :    Optional[int]											=  decoder_layers
											lowercase       :    int											=  decoder_attention_heads
											lowercase       :    List[Any]											=  dropout
											lowercase       :    Any											=  attention_dropout
											lowercase       :    Optional[int]											=  activation_dropout
											lowercase       :    List[Any]											=  activation_function
											lowercase       :    Optional[int]											=  init_std
											lowercase       :    Optional[int]											=  encoder_layerdrop
											lowercase       :    List[str]											=  decoder_layerdrop
											lowercase       :    List[Any]											=  classifier_dropout
											lowercase       :    Any											=  use_cache
											lowercase       :    Dict											=  encoder_layers
											lowercase       :    Tuple											=  scale_embedding  # scale factor will be sqrt(d_model) if True
											super().__init__(
											    pad_token_id=__SCREAMING_SNAKE_CASE ,      bos_token_id=__SCREAMING_SNAKE_CASE ,      eos_token_id=__SCREAMING_SNAKE_CASE ,      is_encoder_decoder=__SCREAMING_SNAKE_CASE ,      forced_eos_token_id=__SCREAMING_SNAKE_CASE ,      **__SCREAMING_SNAKE_CASE ,      )







class 							UpperCAmelCase	(   lowerCAmelCase_					):

					@property
					def        _lowerCAmelCase	(			self      :					str					):
											return OrderedDict(
											    [
											        ('''input_ids''', {0: '''batch''', 1: '''sequence'''}),
											        ('''attention_mask''', {0: '''batch''', 1: '''sequence'''}),
											    ]					)




					@property
					def        _lowerCAmelCase	(			self      :					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 itertools import combinations_with_replacement

def        lowerCamelCase_      (			UpperCAmelCase_							:				int = 1_00       ):
						lowercase       :    list[int]											=  [*list(range(1							,			21       )       ), 25]
						lowercase       :    list[int]											=  [2 * x for x in range(1							,			21       )] + [50]
						lowercase       :    list[int]											=  [3 * x for x in range(1							,			21       )]
						lowercase       :    list[int]											=  singles + doubles + triples + [0]

						lowercase       :    int											=  0
						lowercase       :    int
						lowercase       :    int
						lowercase       :    int
						lowercase       :    int

						for double in doubles:
												for throwa, throwa in combinations_with_replacement(UpperCAmelCase_							,			2       ):
																		lowercase       :    Union[str, Any]											=  double + throwa + throwa
																		if checkout_total < limit:
																								num_checkouts += 1

						return num_checkouts


if __name__ == "__main__":
				print(F'{solution() = }')


