


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


lowerCAmelCase							=						logging.get_logger(__name__)

lowerCAmelCase							=						{
    """unc-nlp/lxmert-base-uncased""": """https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json""",
}




class        lowerCamelCase      (     _UpperCamelCase   ):
	_lowerCAmelCase    :		List[Any]        =	'''lxmert'''
	_lowerCAmelCase    :		Optional[int]        =	{}


	def __init__(						self							,    lowercase__=3_0_5_2_2							,    lowercase__=7_6_8							,    lowercase__=1_2							,    lowercase__=9_5_0_0							,    lowercase__=1_6_0_0							,    lowercase__=4_0_0							,    lowercase__=3_0_7_2							,    lowercase__="gelu"							,    lowercase__=0.1							,    lowercase__=0.1							,    lowercase__=5_1_2							,    lowercase__=2							,    lowercase__=0.0_2							,    lowercase__=1e-12							,    lowercase__=9							,    lowercase__=5							,    lowercase__=5							,    lowercase__=2_0_4_8							,    lowercase__=4							,    lowercase__=6.6_7							,    lowercase__=True							,    lowercase__=True							,    lowercase__=True							,    lowercase__=True							,    lowercase__=True							,    lowercase__=True							,    lowercase__=True							,    **lowercase__							,    ):
							__UpperCAmelCase :       int  						=  vocab_size
							__UpperCAmelCase :       str  						=  hidden_size
							__UpperCAmelCase :       List[Any]  						=  num_attention_heads
							__UpperCAmelCase :       str  						=  hidden_act
							__UpperCAmelCase :       Union[str, Any]  						=  intermediate_size
							__UpperCAmelCase :       Any  						=  hidden_dropout_prob
							__UpperCAmelCase :       Tuple  						=  attention_probs_dropout_prob
							__UpperCAmelCase :       Any  						=  max_position_embeddings
							__UpperCAmelCase :       Tuple  						=  type_vocab_size
							__UpperCAmelCase :       int  						=  initializer_range
							__UpperCAmelCase :       Optional[int]  						=  layer_norm_eps
							__UpperCAmelCase :       Optional[Any]  						=  num_qa_labels
							__UpperCAmelCase :       List[Any]  						=  num_object_labels
							__UpperCAmelCase :       Optional[Any]  						=  num_attr_labels
							__UpperCAmelCase :       Union[str, Any]  						=  l_layers
							__UpperCAmelCase :       Any  						=  x_layers
							__UpperCAmelCase :       Optional[int]  						=  r_layers
							__UpperCAmelCase :       int  						=  visual_feat_dim
							__UpperCAmelCase :       int  						=  visual_pos_dim
							__UpperCAmelCase :       int  						=  visual_loss_normalizer
							__UpperCAmelCase :       int  						=  task_matched
							__UpperCAmelCase :       str  						=  task_mask_lm
							__UpperCAmelCase :       Tuple  						=  task_obj_predict
							__UpperCAmelCase :       Tuple  						=  task_qa
							__UpperCAmelCase :       List[str]  						=  visual_obj_loss
							__UpperCAmelCase :       Optional[Any]  						=  visual_attr_loss
							__UpperCAmelCase :       Union[str, Any]  						=  visual_feat_loss
							__UpperCAmelCase :       int  						=  {'''vision''': r_layers, '''cross_encoder''': x_layers, '''language''': l_layers}
							super().__init__(**lowercase__)





def 						__SCREAMING_SNAKE_CASE       (					lowercase_			)		->    list:




						'''simple docstring'''







						__UpperCAmelCase :       Optional[Any]  						=  int(lowercase_			)
						if n_element < 1:
												__UpperCAmelCase :       str  						=  ValueError('''a should be a positive number'''			)
												raise my_error

						__UpperCAmelCase :       Any  						=  [1]
						__UpperCAmelCase						,			__UpperCAmelCase						,			__UpperCAmelCase :       Any  						=  (0, 0, 0)
						__UpperCAmelCase :       int  						=  1
						while index < n_element:
												while hamming_list[i] * 2 <= hamming_list[-1]:
																		i += 1
												while hamming_list[j] * 3 <= hamming_list[-1]:
																		j += 1
												while hamming_list[k] * 5 <= hamming_list[-1]:
																		k += 1
												hamming_list.append(
												    min(hamming_list[i] * 2			,					hamming_list[j] * 3			,					hamming_list[k] * 5			)			)
												index += 1
						return hamming_list


if __name__ == "__main__":
				lowerCAmelCase							=						input("""Enter the last number (nth term) of the Hamming Number Series: """)
				print("""Formula of Hamming Number Series => 2^i * 3^j * 5^k""")
				lowerCAmelCase							=						hamming(int(n))
				print("""-----------------------------------------------------""")
				print(F'The list with nth numbers is: {hamming_numbers}')
				print("""-----------------------------------------------------""")

