"""simple docstring"""


import numpy as np

__UpperCamelCase										=     [
    ['''a''', '''b''', '''c''', '''d''', '''e'''],
    ['''f''', '''g''', '''h''', '''i''', '''k'''],
    ['''l''', '''m''', '''n''', '''o''', '''p'''],
    ['''q''', '''r''', '''s''', '''t''', '''u'''],
    ['''v''', '''w''', '''x''', '''y''', '''z'''],
]




class 					UpperCamelCase   :







       def __init__(					self) -> None:
            snake_case_   			=   np.array(lowerCAmelCase__)







       def 						a_		(					self,				lowerCAmelCase__) -> np.ndarray:
            snake_case_			,      snake_case_   			=   np.where(letter == self.SQUARE)
            snake_case_   			=   np.concatenate([indexa + 1, indexa + 1])
            return indexes







       def 						a_		(					self,				lowerCAmelCase__,				lowerCAmelCase__) -> str:
            return self.SQUARE[indexa - 1, indexa - 1]







       def 						a_		(					self,				lowerCAmelCase__) -> str:
            snake_case_   			=   message.lower()
            snake_case_   			=   message.replace('j',				'i')

            snake_case_   			=   ''
            for letter_index in range(len(lowerCAmelCase__)):
                 if message[letter_index] != " ":
                      snake_case_   			=   self.letter_to_numbers(message[letter_index])
                      snake_case_   			=   encoded_message + str(numbers[0]) + str(numbers[1])
                 elif message[letter_index] == " ":
                      snake_case_   			=   encoded_message + ' '

            return encoded_message







       def 						a_		(					self,				lowerCAmelCase__) -> str:
            snake_case_   			=   message.replace(' ',				'  ')
            snake_case_   			=   ''
            for numbers_index in range(int(len(lowerCAmelCase__) / 2)):
                 if message[numbers_index * 2] != " ":
                      snake_case_   			=   message[numbers_index * 2]
                      snake_case_   			=   message[numbers_index * 2 + 1]

                      snake_case_   			=   self.numbers_to_letter(int(lowerCAmelCase__),				int(lowerCAmelCase__))
                      snake_case_   			=   decoded_message + letter
                 elif message[numbers_index * 2] == " ":
                      snake_case_   			=   decoded_message + ' '

            return decoded_message


"""simple docstring"""


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


__UpperCamelCase										=     logging.get_logger(__name__)

__UpperCamelCase										=     {
    '''uw-madison/nystromformer-512''': '''https://huggingface.co/uw-madison/nystromformer-512/resolve/main/config.json''',
    # See all Nystromformer models at https://huggingface.co/models?filter=nystromformer
}




class 					UpperCamelCase   (							lowerCAmelCase__  ):
       SCREAMING_SNAKE_CASE_						      = "nystromformer"







       def __init__(					self,				lowerCAmelCase__=3_0000,				lowerCAmelCase__=768,				lowerCAmelCase__=12,				lowerCAmelCase__=12,				lowerCAmelCase__=3072,				lowerCAmelCase__="gelu_new",				lowerCAmelCase__=0.1,				lowerCAmelCase__=0.1,				lowerCAmelCase__=510,				lowerCAmelCase__=2,				lowerCAmelCase__=64,				lowerCAmelCase__=64,				lowerCAmelCase__=65,				lowerCAmelCase__=False,				lowerCAmelCase__=0.02,				lowerCAmelCase__=1e-5,				lowerCAmelCase__=1,				lowerCAmelCase__=0,				lowerCAmelCase__=2,				**lowerCAmelCase__,				) -> Optional[Any]:
            snake_case_   			=   vocab_size
            snake_case_   			=   max_position_embeddings
            snake_case_   			=   hidden_size
            snake_case_   			=   num_hidden_layers
            snake_case_   			=   num_attention_heads
            snake_case_   			=   intermediate_size
            snake_case_   			=   hidden_act
            snake_case_   			=   hidden_dropout_prob
            snake_case_   			=   attention_probs_dropout_prob
            snake_case_   			=   initializer_range
            snake_case_   			=   type_vocab_size
            snake_case_   			=   segment_means_seq_len
            snake_case_   			=   num_landmarks
            snake_case_   			=   conv_kernel_size
            snake_case_   			=   inv_coeff_init_option
            snake_case_   			=   layer_norm_eps
            super().__init__(pad_token_id=lowerCAmelCase__,				bos_token_id=lowerCAmelCase__,				eos_token_id=lowerCAmelCase__,				**lowerCAmelCase__)

