






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


lowerCamelCase      :       str    =						logging.get_logger(__name__)

lowerCamelCase      :       Optional[Any]    =						{
    '''EleutherAI/gpt-neox-20b''': '''https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json''',
    # See all GPTNeoX models at https://huggingface.co/models?filter=gpt_neox
}



class 				_UpperCamelCase      (a_      ):
      snake_case_	=				"""gpt_neox"""


      def __init__(						self       ,    __UpperCamelCase=5_0_4_3_2       ,    __UpperCamelCase=6_1_4_4       ,    __UpperCamelCase=4_4       ,    __UpperCamelCase=6_4       ,    __UpperCamelCase=2_4_5_7_6       ,    __UpperCamelCase="gelu"       ,    __UpperCamelCase=0.2_5       ,    __UpperCamelCase=1_0_0_0_0       ,    __UpperCamelCase=0.0       ,    __UpperCamelCase=0.0       ,    __UpperCamelCase=0.1       ,    __UpperCamelCase=2_0_4_8       ,    __UpperCamelCase=0.0_2       ,    __UpperCamelCase=1e-5       ,    __UpperCamelCase=True       ,    __UpperCamelCase=0       ,    __UpperCamelCase=2       ,    __UpperCamelCase=False       ,    __UpperCamelCase=True       ,    __UpperCamelCase=None       ,    **__UpperCamelCase       ,    )->						Union[str, Any]:
           super().__init__(bos_token_id=__UpperCamelCase       ,    eos_token_id=__UpperCamelCase       ,    **__UpperCamelCase						)
           __lowerCAmelCase             =       vocab_size
           __lowerCAmelCase             =       max_position_embeddings
           __lowerCAmelCase             =       hidden_size
           __lowerCAmelCase             =       num_hidden_layers
           __lowerCAmelCase             =       num_attention_heads
           __lowerCAmelCase             =       intermediate_size
           __lowerCAmelCase             =       hidden_act
           __lowerCAmelCase             =       rotary_pct
           __lowerCAmelCase             =       rotary_emb_base
           __lowerCAmelCase             =       attention_dropout
           __lowerCAmelCase             =       hidden_dropout
           __lowerCAmelCase             =       classifier_dropout
           __lowerCAmelCase             =       initializer_range
           __lowerCAmelCase             =       layer_norm_eps
           __lowerCAmelCase             =       use_cache
           __lowerCAmelCase             =       tie_word_embeddings
           __lowerCAmelCase             =       use_parallel_residual
           __lowerCAmelCase             =       rope_scaling
           self._rope_scaling_validation()

           if self.hidden_size % self.num_attention_heads != 0:
                raise ValueError(
                    "The hidden size is not divisble by the number of attention heads! Make sure to update them!"						)


      def 			__UpperCAmelCase		(						self						)->						Optional[int]:
           if self.rope_scaling is None:
                return

           if not isinstance(self.rope_scaling       ,    __UpperCamelCase						) or len(self.rope_scaling						) != 2:
                raise ValueError(
                    "`rope_scaling` must be a dictionary with with two fields, `name` and `factor`, "
                    F"""got {self.rope_scaling}"""						)
           __lowerCAmelCase             =       self.rope_scaling.get("type"       ,    __UpperCamelCase						)
           __lowerCAmelCase             =       self.rope_scaling.get("factor"       ,    __UpperCamelCase						)
           if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
                raise ValueError(
                    F"""`rope_scaling`'s name field must be one of ['linear', 'dynamic'], got {rope_scaling_type}"""						)
           if rope_scaling_factor is None or not isinstance(__UpperCamelCase       ,    __UpperCamelCase						) or rope_scaling_factor <= 1.0:
                raise ValueError(F"""`rope_scaling`'s factor field must be an float > 1, got {rope_scaling_factor}"""						)














import itertools
import string
from collections.abc import Generator, Iterable





def    __lowerCAmelCase   (    __snake_case       ,			__snake_case							):
     __lowerCAmelCase             =       iter(__snake_case							)
     while True:
          __lowerCAmelCase             =       tuple(itertools.islice(__snake_case       ,			__snake_case							)							)
          if not chunk:
               return
          yield chunk





def    __lowerCAmelCase   (    __snake_case							):
     __lowerCAmelCase             =       "".join([c.upper() for c in dirty if c in string.ascii_letters]							)
     __lowerCAmelCase             =       ""

     if len(__snake_case							) < 2:
          return dirty

     for i in range(len(__snake_case							) - 1							):
          clean += dirty[i]

          if dirty[i] == dirty[i + 1]:
               clean += "X"

     clean += dirty[-1]

     if len(__snake_case							) & 1:
          clean += "X"

     return clean





def    __lowerCAmelCase   (    __snake_case							):
     # I and J are used interchangeably to allow
     # us to use a 5x5 table (25 letters)
     __lowerCAmelCase             =       "ABCDEFGHIKLMNOPQRSTUVWXYZ"
     # we're using a list instead of a '2d' array because it makes the math
     # for setting up the table and doing the actual encoding/decoding simpler
     __lowerCAmelCase             =       []

     # copy key chars into the table if they are in `alphabet` ignoring duplicates
     for char in key.upper():
          if char not in table and char in alphabet:
               table.append(__snake_case							)

    # fill the rest of the table in with the remaining alphabet chars
     for char in alphabet:
          if char not in table:
               table.append(__snake_case							)

     return table





def    __lowerCAmelCase   (    __snake_case       ,			__snake_case							):
     __lowerCAmelCase             =       generate_table(__snake_case							)
     __lowerCAmelCase             =       prepare_input(__snake_case							)
     __lowerCAmelCase             =       ""

     # https://en.wikipedia.org/wiki/Playfair_cipher#Description
     for chara, chara in chunker(__snake_case       ,			2							):
          __lowerCAmelCase      ,			__lowerCAmelCase             =       divmod(table.index(__snake_case							)       ,			5							)
          __lowerCAmelCase      ,			__lowerCAmelCase             =       divmod(table.index(__snake_case							)       ,			5							)

          if rowa == rowa:
               ciphertext += table[rowa * 5 + (cola + 1) % 5]
               ciphertext += table[rowa * 5 + (cola + 1) % 5]
          elif cola == cola:
               ciphertext += table[((rowa + 1) % 5) * 5 + cola]
               ciphertext += table[((rowa + 1) % 5) * 5 + cola]
          else:  # rectangle
               ciphertext += table[rowa * 5 + cola]
               ciphertext += table[rowa * 5 + cola]

     return ciphertext





def    __lowerCAmelCase   (    __snake_case       ,			__snake_case							):
     __lowerCAmelCase             =       generate_table(__snake_case							)
     __lowerCAmelCase             =       ""

     # https://en.wikipedia.org/wiki/Playfair_cipher#Description
     for chara, chara in chunker(__snake_case       ,			2							):
          __lowerCAmelCase      ,			__lowerCAmelCase             =       divmod(table.index(__snake_case							)       ,			5							)
          __lowerCAmelCase      ,			__lowerCAmelCase             =       divmod(table.index(__snake_case							)       ,			5							)

          if rowa == rowa:
               plaintext += table[rowa * 5 + (cola - 1) % 5]
               plaintext += table[rowa * 5 + (cola - 1) % 5]
          elif cola == cola:
               plaintext += table[((rowa - 1) % 5) * 5 + cola]
               plaintext += table[((rowa - 1) % 5) * 5 + cola]
          else:  # rectangle
               plaintext += table[rowa * 5 + cola]
               plaintext += table[rowa * 5 + cola]

     return plaintext






