





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


A_        =  logging.get_logger(__name__)

A_        =  {
    "google/pegasus-x-base": "https://huggingface.co/google/pegasus-x-base/resolve/main/config.json",
    "google/pegasus-x-large": "https://huggingface.co/google/pegasus-x-large/resolve/main/config.json",
    # See all PEGASUS-X models at https://huggingface.co/models?filter=pegasus-x
}

class SCREAMING_SNAKE_CASE_			(       lowercase_ ):





					"""simple docstring"""


					A__								=     "pegasus_x"
					A__								=     ["past_key_values"]
					A__								=     {"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}





					def __init__(			self						,	_lowerCAmelCase=9_6103						,	_lowerCAmelCase=1_6384						,	_lowerCAmelCase=16						,	_lowerCAmelCase=4096						,	_lowerCAmelCase=16						,	_lowerCAmelCase=16						,	_lowerCAmelCase=4096						,	_lowerCAmelCase=16						,	_lowerCAmelCase=0.0						,	_lowerCAmelCase=0.0						,	_lowerCAmelCase=True						,	_lowerCAmelCase=True						,	_lowerCAmelCase="gelu"						,	_lowerCAmelCase=1024						,	_lowerCAmelCase=0.1						,	_lowerCAmelCase=0.0						,	_lowerCAmelCase=0.0						,	_lowerCAmelCase=0.02						,	_lowerCAmelCase=0						,	_lowerCAmelCase=True						,	_lowerCAmelCase=0						,	_lowerCAmelCase=1						,	_lowerCAmelCase=1						,	_lowerCAmelCase=32						,	_lowerCAmelCase=512						,	_lowerCAmelCase=True						,	**_lowerCAmelCase						,	):
										lowerCamelCase__      =							vocab_size
										lowerCamelCase__      =							max_position_embeddings
										lowerCamelCase__      =							d_model
										lowerCamelCase__      =							encoder_ffn_dim
										lowerCamelCase__      =							encoder_layers
										lowerCamelCase__      =							encoder_attention_heads
										lowerCamelCase__      =							decoder_ffn_dim
										lowerCamelCase__      =							decoder_layers
										lowerCamelCase__      =							decoder_attention_heads
										lowerCamelCase__      =							dropout
										lowerCamelCase__      =							attention_dropout
										lowerCamelCase__      =							activation_dropout
										lowerCamelCase__      =							activation_function
										lowerCamelCase__      =							init_std
										lowerCamelCase__      =							encoder_layerdrop
										lowerCamelCase__      =							decoder_layerdrop
										lowerCamelCase__      =							use_cache
										lowerCamelCase__      =							encoder_layers
										lowerCamelCase__      =							scale_embedding  # scale factor will be sqrt(d_model) if True

										lowerCamelCase__      =							num_global_tokens
										lowerCamelCase__      =							block_size
										lowerCamelCase__      =							stagger_local_blocks

										super().__init__(
										    pad_token_id=_lowerCAmelCase						,	eos_token_id=_lowerCAmelCase						,	is_encoder_decoder=_lowerCAmelCase						,	decoder_start_token_id=_lowerCAmelCase						,	forced_eos_token_id=_lowerCAmelCase						,	**_lowerCAmelCase						,	)





					@property
					def        __magic_name__			(			self						):
										return self.encoder_attention_heads






					@property
					def        __magic_name__			(			self						):
										return self.d_model








def  __UpperCamelCase   (     a = 998001)			->int:

					# fetches the next number
					for number in range(n - 1,  9999,  -1):
										lowerCamelCase__      =							str(a)

										# checks whether 'str_number' is a palindrome.
										if str_number == str_number[::-1]:
															lowerCamelCase__      =							999

															# if 'number' is a product of two 3-digit numbers
															# then number is the answer otherwise fetch next number.
															while divisor != 99:
																				if (number % divisor == 0) and (len(str(number // divisor)) == 3.0):
																									return number
																				divisor -= 1
					raise ValueError("That number is larger than our acceptable range.")


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

