



"""simple docstring"""
from math import sqrt

def    _snake_case   (		UpperCamelCase		:	int		):
 assert isinstance(UpperCamelCase    ,	UpperCamelCase		) and (
     number >= 0
 ), "'number' must been an int and positive"

 UpperCAmelCase			:      List[str]			=			True

 # 0 and 1 are none primes.
 if number <= 1:
  UpperCAmelCase			:      Optional[Any]			=			False

 for divisor in range(2    ,	int(round(sqrt(UpperCamelCase		)		)		) + 1		):
  # if 'number' divisible by 'divisor' then sets 'status'
  # of false and break up the loop.
  if number % divisor == 0:
   UpperCAmelCase			:      int			=			False
   break

    # precondition
 assert isinstance(UpperCamelCase    ,	UpperCamelCase		), "'status' must been from type bool"

 return status

def    _snake_case   (		UpperCamelCase		:	Dict		):
 assert isinstance(UpperCamelCase    ,	UpperCamelCase		) and (n > 2), "'N' must been an int and > 2"

 # beginList: contains all natural numbers from 2 up to N
 UpperCAmelCase			:      List[Any]			=			list(range(2    ,	n + 1		)		)

 UpperCAmelCase			:      str			=			[]  # this list will be returns.

 # actual sieve of erathostenes
 for i in range(len(UpperCamelCase		)		):
  for j in range(i + 1    ,	len(UpperCamelCase		)		):
   if (begin_list[i] != 0) and (begin_list[j] % begin_list[i] == 0):
    UpperCAmelCase			:      List[Any]			=			0

    # filters actual prime numbers.
 UpperCAmelCase			:      Optional[int]			=			[x for x in begin_list if x != 0]

 # precondition
 assert isinstance(UpperCamelCase    ,	UpperCamelCase		), "'ans' must been from type list"

 return ans

def    _snake_case   (		UpperCamelCase		:	int		):
 assert isinstance(UpperCamelCase    ,	UpperCamelCase		) and (n > 2), "'N' must been an int and > 2"

 UpperCAmelCase			:      Optional[int]			=			[]

 # iterates over all numbers between 2 up to N+1
 # if a number is prime then appends to list 'ans'
 for number in range(2    ,	n + 1		):
  if is_prime(UpperCamelCase		):
   ans.append(UpperCamelCase		)

    # precondition
 assert isinstance(UpperCamelCase    ,	UpperCamelCase		), "'ans' must been from type list"

 return ans

def    _snake_case   (		UpperCamelCase		:	Any		):
 assert isinstance(UpperCamelCase    ,	UpperCamelCase		) and number >= 0, "'number' must been an int and >= 0"

 UpperCAmelCase			:      List[Any]			=			[]  # this list will be returns of the function.

 # potential prime number factors.

 UpperCAmelCase			:      Dict			=			2

 UpperCAmelCase			:      Union[str, Any]			=			number

 if number == 0 or number == 1:
  ans.append(UpperCamelCase		)

 # if 'number' not prime then builds the prime factorization of 'number'
 elif not is_prime(UpperCamelCase		):
  while quotient != 1:
   if is_prime(UpperCamelCase		) and (quotient % factor == 0):
    ans.append(UpperCamelCase		)
    quotient /= factor
   else:
    factor += 1

 else:
  ans.append(UpperCamelCase		)

 # precondition
 assert isinstance(UpperCamelCase    ,	UpperCamelCase		), "'ans' must been from type list"

 return ans

def    _snake_case   (		UpperCamelCase		:	int		):
 assert isinstance(UpperCamelCase    ,	UpperCamelCase		) and (
     number >= 0
 ), "'number' bust been an int and >= 0"

 UpperCAmelCase			:      Tuple			=			0

 # prime factorization of 'number'
 UpperCAmelCase			:      int			=			prime_factorization(UpperCamelCase		)

 UpperCAmelCase			:      Dict			=			max(UpperCamelCase		)

 # precondition
 assert isinstance(UpperCamelCase    ,	UpperCamelCase		), "'ans' must been from type int"

 return ans

def    _snake_case   (		UpperCamelCase		:	Optional[int]		):
 assert isinstance(UpperCamelCase    ,	UpperCamelCase		) and (
     number >= 0
 ), "'number' bust been an int and >= 0"

 UpperCAmelCase			:      Any			=			0

 # prime factorization of 'number'
 UpperCAmelCase			:      Dict			=			prime_factorization(UpperCamelCase		)

 UpperCAmelCase			:      Optional[int]			=			min(UpperCamelCase		)

 # precondition
 assert isinstance(UpperCamelCase    ,	UpperCamelCase		), "'ans' must been from type int"

 return ans

def    _snake_case   (		UpperCamelCase		:	str		):
 assert isinstance(UpperCamelCase    ,	UpperCamelCase		), "'number' must been an int"
 assert isinstance(number % 2 == 0    ,	UpperCamelCase		), "compare bust been from type bool"

 return number % 2 == 0

def    _snake_case   (		UpperCamelCase		:	Optional[Any]		):
 assert isinstance(UpperCamelCase    ,	UpperCamelCase		), "'number' must been an int"
 assert isinstance(number % 2 != 0    ,	UpperCamelCase		), "compare bust been from type bool"

 return number % 2 != 0

def    _snake_case   (		UpperCamelCase		:	Union[str, Any]		):
 assert (
     isinstance(UpperCamelCase    ,	UpperCamelCase		) and (number > 2) and is_even(UpperCamelCase		)
 ), "'number' must been an int, even and > 2"

 UpperCAmelCase			:      Any			=			[]  # this list will returned

 # creates a list of prime numbers between 2 up to 'number'
 UpperCAmelCase			:      Any			=			get_prime_numbers(UpperCamelCase		)
 UpperCAmelCase			:      Union[str, Any]			=			len(UpperCamelCase		)

 # run variable for while-loops.
 UpperCAmelCase			:      int			=			0
 UpperCAmelCase			:      str			=			None

 # exit variable. for break up the loops
 UpperCAmelCase			:      List[str]			=			True

 while i < len_pn and loop:
  UpperCAmelCase			:      Tuple			=			i + 1

  while j < len_pn and loop:
   if prime_numbers[i] + prime_numbers[j] == number:
    UpperCAmelCase			:      Optional[Any]			=			False
    ans.append(prime_numbers[i]		)
    ans.append(prime_numbers[j]		)

   j += 1

  i += 1

 # precondition
 assert (
     isinstance(UpperCamelCase    ,	UpperCamelCase		)
     and (len(UpperCamelCase		) == 2)
     and (ans[0] + ans[1] == number)
     and is_prime(ans[0]		)
     and is_prime(ans[1]		)
 ), "'ans' must contains two primes. And sum of elements must been eq 'number'"

 return ans

def    _snake_case   (		UpperCamelCase		:	List[str]    ,	UpperCamelCase		:	Union[str, Any]		):
 assert (
     isinstance(UpperCamelCase    ,	UpperCamelCase		)
     and isinstance(UpperCamelCase    ,	UpperCamelCase		)
     and (numbera >= 0)
     and (numbera >= 0)
 ), "'number1' and 'number2' must been positive integer."

 UpperCAmelCase			:      Optional[Any]			=			0

 while numbera != 0:
  UpperCAmelCase			:      Dict			=			numbera % numbera
  UpperCAmelCase			:      str			=			numbera
  UpperCAmelCase			:      List[str]			=			rest

 # precondition
 assert isinstance(UpperCamelCase    ,	UpperCamelCase		) and (
     numbera >= 0
 ), "'number' must been from type int and positive"

 return numbera

def    _snake_case   (		UpperCamelCase		:	Optional[Any]    ,	UpperCamelCase		:	Union[str, Any]		):
 assert (
     isinstance(UpperCamelCase    ,	UpperCamelCase		)
     and isinstance(UpperCamelCase    ,	UpperCamelCase		)
     and (numbera >= 1)
     and (numbera >= 1)
 ), "'number1' and 'number2' must been positive integer."

 UpperCAmelCase			:      Union[str, Any]			=			1  # actual answer that will be return.

 # for kgV (x,1)
 if numbera > 1 and numbera > 1:
  # builds the prime factorization of 'number1' and 'number2'
  UpperCAmelCase			:      int			=			prime_factorization(UpperCamelCase		)
  UpperCAmelCase			:      List[Any]			=			prime_factorization(UpperCamelCase		)

 elif numbera == 1 or numbera == 1:
  UpperCAmelCase			:      List[Any]			=			[]
  UpperCAmelCase			:      Any			=			[]
  UpperCAmelCase			:      Optional[int]			=			max(UpperCamelCase    ,	UpperCamelCase		)

 UpperCAmelCase			:      Tuple			=			0
 UpperCAmelCase			:      Union[str, Any]			=			0

 UpperCAmelCase			:      Union[str, Any]			=			[]  # captured numbers int both 'primeFac1' and 'primeFac2'

 # iterates through primeFac1
 for n in prime_fac_a:
  if n not in done:
   if n in prime_fac_a:
    UpperCAmelCase			:      Dict			=			prime_fac_a.count(UpperCamelCase		)
    UpperCAmelCase			:      Dict			=			prime_fac_a.count(UpperCamelCase		)

    for _ in range(max(UpperCamelCase    ,	UpperCamelCase		)		):
     ans *= n

   else:
    UpperCAmelCase			:      Optional[int]			=			prime_fac_a.count(UpperCamelCase		)

    for _ in range(UpperCamelCase		):
     ans *= n

   done.append(UpperCamelCase		)

    # iterates through primeFac2
 for n in prime_fac_a:
  if n not in done:
   UpperCAmelCase			:      Tuple			=			prime_fac_a.count(UpperCamelCase		)

   for _ in range(UpperCamelCase		):
    ans *= n

   done.append(UpperCamelCase		)

    # precondition
 assert isinstance(UpperCamelCase    ,	UpperCamelCase		) and (
     ans >= 0
 ), "'ans' must been from type int and positive"

 return ans

def    _snake_case   (		UpperCamelCase		:	List[str]		):
 assert isinstance(UpperCamelCase    ,	UpperCamelCase		) and (n >= 0), "'number' must been a positive int"

 UpperCAmelCase			:      Any			=			0
 UpperCAmelCase			:      int			=			2  # this variable holds the answer

 while index < n:
  index += 1

  ans += 1  # counts to the next number

  # if ans not prime then
  # runs to the next prime number.
  while not is_prime(UpperCamelCase		):
   ans += 1

    # precondition
 assert isinstance(UpperCamelCase    ,	UpperCamelCase		) and is_prime(
     UpperCamelCase		), "'ans' must been a prime number and from type int"

 return ans

def    _snake_case   (		UpperCamelCase		:	str    ,	UpperCamelCase		:	int		):
 assert (
     is_prime(UpperCamelCase		) and is_prime(UpperCamelCase		) and (p_number_a < p_number_a)
 ), "The arguments must been prime numbers and 'pNumber1' < 'pNumber2'"

 UpperCAmelCase			:      Any			=			p_number_a + 1  # jump to the next number

 UpperCAmelCase			:      Dict			=			[]  # this list will be returns.

 # if number is not prime then
 # fetch the next prime number.
 while not is_prime(UpperCamelCase		):
  number += 1

 while number < p_number_a:
  ans.append(UpperCamelCase		)

  number += 1

  # fetch the next prime number.
  while not is_prime(UpperCamelCase		):
   number += 1

    # precondition
 assert (
     isinstance(UpperCamelCase    ,	UpperCamelCase		)
     and ans[0] != p_number_a
     and ans[len(UpperCamelCase		) - 1] != p_number_a
 ), "'ans' must been a list without the arguments"

 # 'ans' contains not 'pNumber1' and 'pNumber2' !
 return ans

def    _snake_case   (		UpperCamelCase		:	List[str]		):
 assert isinstance(UpperCamelCase    ,	UpperCamelCase		) and (n >= 1), "'n' must been int and >= 1"

 UpperCAmelCase			:      Union[str, Any]			=			[]  # will be returned.

 for divisor in range(1    ,	n + 1		):
  if n % divisor == 0:
   ans.append(UpperCamelCase		)

    # precondition
 assert ans[0] == 1 and ans[len(UpperCamelCase		) - 1] == n, "Error in function getDivisiors(...)"

 return ans

def    _snake_case   (		UpperCamelCase		:	Optional[int]		):
 assert isinstance(UpperCamelCase    ,	UpperCamelCase		) and (
     number > 1
 ), "'number' must been an int and >= 1"

 UpperCAmelCase			:      Tuple			=			get_divisors(UpperCamelCase		)

 # precondition
 assert (
     isinstance(UpperCamelCase    ,	UpperCamelCase		)
     and (divisors[0] == 1)
     and (divisors[len(UpperCamelCase		) - 1] == number)
 ), "Error in help-function getDivisiors(...)"

 # summed all divisors up to 'number' (exclusive), hence [:-1]
 return sum(divisors[:-1]		) == number

def    _snake_case   (		UpperCamelCase		:	List[str]    ,	UpperCamelCase		:	Optional[int]		):
 assert (
     isinstance(UpperCamelCase    ,	UpperCamelCase		)
     and isinstance(UpperCamelCase    ,	UpperCamelCase		)
     and (denominator != 0)
 ), "The arguments must been from type int and 'denominator' != 0"

 # build the greatest common divisor of numerator and denominator.
 UpperCAmelCase			:      Optional[int]			=			gcd(abs(UpperCamelCase		)    ,	abs(UpperCamelCase		)		)

 # precondition
 assert (
     isinstance(UpperCamelCase    ,	UpperCamelCase		)
     and (numerator % gcd_of_fraction == 0)
     and (denominator % gcd_of_fraction == 0)
 ), "Error in function gcd(...,...)"

 return (numerator // gcd_of_fraction, denominator // gcd_of_fraction)

def    _snake_case   (		UpperCamelCase		:	List[str]		):
 assert isinstance(UpperCamelCase    ,	UpperCamelCase		) and (n >= 0), "'n' must been a int and >= 0"

 UpperCAmelCase			:      Dict			=			1  # this will be return.

 for factor in range(1    ,	n + 1		):
  ans *= factor

 return ans

def    _snake_case   (		UpperCamelCase		:	Union[str, Any]		):
 assert isinstance(UpperCamelCase    ,	UpperCamelCase		) and (n >= 0), "'n' must been an int and >= 0"

 UpperCAmelCase			:      List[Any]			=			0
 UpperCAmelCase			:      Any			=			1
 UpperCAmelCase			:      List[Any]			=			1  # this will be return

 for _ in range(n - 1		):
  UpperCAmelCase			:      str			=			ans
  ans += fiba
  UpperCAmelCase			:      Optional[int]			=			tmp

 return ans





"""simple docstring"""
from collections import OrderedDict
from typing import Any, Mapping, Optional

from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging


A:     Optional[int]										=	logging.get_logger(__name__)

A:     Union[str, Any]										=	{
    "EleutherAI/gpt-neo-1.3B": "https://huggingface.co/EleutherAI/gpt-neo-1.3B/resolve/main/config.json",
    # See all GPTNeo models at https://huggingface.co/models?filter=gpt_neo
}



class    SCREAMING_SNAKE_CASE__						(      UpperCAmelCase__				):
   __lowerCAmelCase						:     List[str]		=		'gpt_neo'
   __lowerCAmelCase						:     Any		=		['past_key_values']
   __lowerCAmelCase						:     int		=		{'num_attention_heads': 'num_heads', 'num_hidden_layers': 'num_layers'}

   def __init__(     self   ,  _SCREAMING_SNAKE_CASE=50257   ,  _SCREAMING_SNAKE_CASE=2048   ,  _SCREAMING_SNAKE_CASE=2048   ,  _SCREAMING_SNAKE_CASE=24   ,  _SCREAMING_SNAKE_CASE=[[["global", "local"], 12]]   ,  _SCREAMING_SNAKE_CASE=16   ,  _SCREAMING_SNAKE_CASE=None   ,  _SCREAMING_SNAKE_CASE=256   ,  _SCREAMING_SNAKE_CASE="gelu_new"   ,  _SCREAMING_SNAKE_CASE=0.0   ,  _SCREAMING_SNAKE_CASE=0.0   ,  _SCREAMING_SNAKE_CASE=0.0   ,  _SCREAMING_SNAKE_CASE=0.1   ,  _SCREAMING_SNAKE_CASE=1E-5   ,  _SCREAMING_SNAKE_CASE=0.02   ,  _SCREAMING_SNAKE_CASE=True   ,  _SCREAMING_SNAKE_CASE=50256   ,  _SCREAMING_SNAKE_CASE=50256   ,  **_SCREAMING_SNAKE_CASE   ,  )						->   str:





    '''simple docstring'''




    UpperCAmelCase			:      int			=			vocab_size
    UpperCAmelCase			:      List[Any]			=			max_position_embeddings
    UpperCAmelCase			:      str			=			hidden_size
    UpperCAmelCase			:      Dict			=			num_layers
    UpperCAmelCase			:      List[Any]			=			num_heads
    UpperCAmelCase			:      Optional[Any]			=			intermediate_size
    UpperCAmelCase			:      Dict			=			window_size
    UpperCAmelCase			:      int			=			activation_function
    UpperCAmelCase			:      Tuple			=			resid_dropout
    UpperCAmelCase			:      int			=			embed_dropout
    UpperCAmelCase			:      Optional[int]			=			attention_dropout
    UpperCAmelCase			:      Optional[int]			=			classifier_dropout
    UpperCAmelCase			:      Any			=			layer_norm_epsilon
    UpperCAmelCase			:      Union[str, Any]			=			initializer_range
    UpperCAmelCase			:      List[str]			=			use_cache

    UpperCAmelCase			:      Union[str, Any]			=			bos_token_id
    UpperCAmelCase			:      str			=			eos_token_id

    UpperCAmelCase			:      Union[str, Any]			=			attention_types
    UpperCAmelCase			:      int			=			self.expand_attention_types_params(_SCREAMING_SNAKE_CASE		)

    if len(self.attention_layers		) != self.num_layers:
     raise ValueError(
         """Configuration for convolutional module is incorrect. """
         """It is required that `len(config.attention_layers)` == `config.num_layers` """
         F"but is `len(config.attention_layers) = {len(self.attention_layers		)}`, "
         F"`config.num_layers = {self.num_layers}`. "
         """`config.attention_layers` is prepared using `config.attention_types`. """
         """Please verify the value of `config.attention_types` argument."""		)

    super().__init__(bos_token_id=_SCREAMING_SNAKE_CASE   ,  eos_token_id=_SCREAMING_SNAKE_CASE   ,  **_SCREAMING_SNAKE_CASE		)




   @staticmethod
   def 			SCREAMING_SNAKE_CASE  (     _SCREAMING_SNAKE_CASE		)						->   Union[str, Any]:





    '''simple docstring'''




    UpperCAmelCase			:      List[str]			=			[]
    for item in attention_types:
     for _ in range(item[1]		):
      attentions.extend(item[0]		)
    return attentions

def    _snake_case		(		UpperCamelCase		:	Union[str, Any]    ,	UpperCamelCase		:	Union[str, Any]    ,	UpperCamelCase		:	Optional[Any]    ,	UpperCamelCase		:	Dict		):
 import torch

 UpperCAmelCase			:      Optional[Any]			=			input.size()
 UpperCAmelCase			:      int			=			len(UpperCamelCase		)
 UpperCAmelCase			:      Optional[Any]			=			shape[dimension]

 UpperCAmelCase			:      Union[str, Any]			=			torch.arange(0    ,	UpperCamelCase    ,	UpperCamelCase		)
 UpperCAmelCase			:      List[Any]			=			torch.div(sizedim - size    ,	UpperCamelCase    ,	rounding_mode="""floor"""		) + 1
 UpperCAmelCase			:      Optional[Any]			=			torch.arange(UpperCamelCase		) + low_indices[:min_length][:, None]

 UpperCAmelCase			:      List[Any]			=			[slice(UpperCamelCase		)] * rank
 UpperCAmelCase			:      Optional[Any]			=			indices
 UpperCAmelCase			:      Optional[Any]			=			input[s]

 UpperCAmelCase			:      List[Any]			=			list(range(0    ,	rank + 1		)		)
 perm.append(perm.pop(dimension + 1		)		)

 return sliced.permute(UpperCamelCase		)

def    _snake_case		(		UpperCamelCase		:	Tuple    ,	UpperCamelCase		:	Dict		):
 import torch

 UpperCAmelCase			:      List[str]			=			torch.arange(1    ,	UpperCamelCase		)
 UpperCAmelCase			:      Any			=			torch.remainder(UpperCamelCase    ,	UpperCamelCase		)
 UpperCAmelCase			:      Union[str, Any]			=			remainders == 0
 UpperCAmelCase			:      str			=			candidates[divisor_indices]
 UpperCAmelCase			:      Optional[int]			=			torch.max(UpperCamelCase		)
 return largest_divisor, torch.div(UpperCamelCase    ,	UpperCamelCase    ,	rounding_mode="""floor"""		)



class    SCREAMING_SNAKE_CASE__						(      UpperCAmelCase__				):

   @property
   def 			SCREAMING_SNAKE_CASE  (     self		)						->   Mapping[str, Mapping[int, str]]:





    '''simple docstring'''




    UpperCAmelCase			:      Any			=			OrderedDict({"""input_ids""": {0: """batch""", 1: """sequence"""}}		)
    if self.use_past:
     self.fill_with_past_key_values_(_SCREAMING_SNAKE_CASE   ,  direction="""inputs"""		)
     UpperCAmelCase			:      str			=			{0: """batch""", 1: """past_sequence + sequence"""}
    else:
     UpperCAmelCase			:      List[str]			=			{0: """batch""", 1: """sequence"""}

    return common_inputs

   @property
   def 			SCREAMING_SNAKE_CASE  (     self		)						->   int:





    '''simple docstring'''




    return self._config.num_heads

   def 			SCREAMING_SNAKE_CASE  (     self   ,  _SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE = -1   ,  _SCREAMING_SNAKE_CASE = -1   ,  _SCREAMING_SNAKE_CASE = False   ,  _SCREAMING_SNAKE_CASE = None   ,  )						->   Mapping[str, Any]:





    '''simple docstring'''




    UpperCAmelCase			:      List[str]			=			super(_SCREAMING_SNAKE_CASE   ,  self		).generate_dummy_inputs(
        _SCREAMING_SNAKE_CASE   ,  batch_size=_SCREAMING_SNAKE_CASE   ,  seq_length=_SCREAMING_SNAKE_CASE   ,  is_pair=_SCREAMING_SNAKE_CASE   ,  framework=_SCREAMING_SNAKE_CASE		)

    # We need to order the input in the way they appears in the forward()
    UpperCAmelCase			:      Dict			=			OrderedDict({"""input_ids""": common_inputs["""input_ids"""]}		)

    # Need to add the past_keys
    if self.use_past:
     if not is_torch_available():
      raise ValueError("""Cannot generate dummy past_keys inputs without PyTorch installed."""		)
     else:
      import torch

      UpperCAmelCase			,	UpperCAmelCase			:      List[Any]			=			common_inputs["""input_ids"""].shape
      # Not using the same length for past_key_values
      UpperCAmelCase			:      Any			=			seqlen + 2
      UpperCAmelCase			:      str			=			(
          batch,
          self.num_attention_heads,
          past_key_values_length,
          self._config.hidden_size // self.num_attention_heads,
      )
      UpperCAmelCase			:      Optional[int]			=			[
          (torch.zeros(_SCREAMING_SNAKE_CASE		), torch.zeros(_SCREAMING_SNAKE_CASE		)) for _ in range(self.num_layers		)
      ]

    UpperCAmelCase			:      List[str]			=			common_inputs["""attention_mask"""]
    if self.use_past:
     UpperCAmelCase			:      str			=			ordered_inputs["""attention_mask"""].dtype
     UpperCAmelCase			:      int			=			torch.cat(
         [ordered_inputs["""attention_mask"""], torch.ones(_SCREAMING_SNAKE_CASE   ,  _SCREAMING_SNAKE_CASE   ,  dtype=_SCREAMING_SNAKE_CASE		)]   ,  dim=1		)

    return ordered_inputs




   @property
   def 			SCREAMING_SNAKE_CASE  (     self		)						->   int:





    '''simple docstring'''




    return 13
