


import functools
from math import sqrt
from time import time






def  _UpperCAmelCase						( __lowerCamelCase			,  *__lowerCamelCase			,  **__lowerCamelCase							)		->Any:


 '''simple docstring'''
 snake_case :			Tuple							=   time()
 snake_case :			Union[str, Any]							=   func(*__snake_case			,  **__snake_case							)
 snake_case :			Optional[int]							=   time()
 if int(end - start							) > 0:
  print(f'''{func.__name__} runtime: {(end - start):0.4f} s'''							)
 else:
  print(f'''{func.__name__} runtime: {(end - start) * 1000:0.4f} ms'''							)
 return output






def  _UpperCAmelCase						( __lowerCamelCase							)		->list[int]:


 '''simple docstring'''
 if n < 0:
  raise Exception('''n is negative'''							)
 if n == 0:
  return [0]
 snake_case :			Optional[Any]							=   [0, 1]
 for _ in range(n - 1							):
  fib.append(fib[-1] + fib[-2]							)
 return fib






def  _UpperCAmelCase						( __lowerCamelCase							)		->list[int]:


 '''simple docstring'''

 def fib_recursive_term(__lowerCamelCase							) -> int:
  if i < 0:
   raise Exception('''n is negative'''							)
  if i < 2:
   return i
  return fib_recursive_term(i - 1							) + fib_recursive_term(i - 2							)

 if n < 0:
  raise Exception('''n is negative'''							)
 return [fib_recursive_term(__snake_case							) for i in range(n + 1							)]






def  _UpperCAmelCase						( __lowerCamelCase							)		->list[int]:


 '''simple docstring'''

 @functools.cache
 def fib_recursive_term(__lowerCamelCase							) -> int:
  if i < 0:
   raise Exception('''n is negative'''							)
  if i < 2:
   return i
  return fib_recursive_term(i - 1							) + fib_recursive_term(i - 2							)

 if n < 0:
  raise Exception('''n is negative'''							)
 return [fib_recursive_term(__snake_case							) for i in range(n + 1							)]






def  _UpperCAmelCase						( __lowerCamelCase							)		->list[int]:


 '''simple docstring'''
 if n < 0:
  raise Exception('''n is negative'''							)
 # Cache must be outside recursuive function
 # other it will reset every time it calls itself.
 snake_case :			Optional[Any]							=   {0: 0, 1: 1, 2: 1}  # Prefilled cache

 def rec_fn_memoized(__lowerCamelCase							) -> int:
  if num in cache:
   return cache[num]

  snake_case :			int							=   rec_fn_memoized(num - 1							) + rec_fn_memoized(num - 2							)
  snake_case :			Dict							=   value
  return value

 return [rec_fn_memoized(__snake_case							) for i in range(n + 1							)]






def  _UpperCAmelCase						( __lowerCamelCase							)		->list[int]:


 '''simple docstring'''
 if n < 0:
  raise Exception('''n is negative'''							)
 if n >= 1475:
  raise Exception('''n is too large'''							)
 snake_case :			List[Any]							=   sqrt(5							)
 snake_case :			List[str]							=   (1 + sqrt_a) / 2
 return [round(phi**i / sqrt_a							) for i in range(n + 1							)]


if __name__ == "__main__":
  a					:				Optional[Any]       =      30
  time_func(fib_iterative, num)
  time_func(fib_recursive, num)  # Around 3s runtime
  time_func(fib_recursive_cached, num)  # Around 0ms runtime
  time_func(fib_memoization, num)
  time_func(fib_binet, num)








from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


if TYPE_CHECKING:
 from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, TensorType


lowerCamelCase_				:							Any       =    logging.get_logger(__name__)

lowerCamelCase_				:							Optional[Any]       =    {
    "microsoft/deberta-base": "https://huggingface.co/microsoft/deberta-base/resolve/main/config.json",
    "microsoft/deberta-large": "https://huggingface.co/microsoft/deberta-large/resolve/main/config.json",
    "microsoft/deberta-xlarge": "https://huggingface.co/microsoft/deberta-xlarge/resolve/main/config.json",
    "microsoft/deberta-base-mnli": "https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/config.json",
    "microsoft/deberta-large-mnli": "https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/config.json",
    "microsoft/deberta-xlarge-mnli": "https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/config.json",
}







class  _lowerCamelCase			(lowerCamelCase					):
     lowercase__				  =			"""deberta"""

     def __init__(  self							,       SCREAMING_SNAKE_CASE_=50_265							,       SCREAMING_SNAKE_CASE_=768							,       SCREAMING_SNAKE_CASE_=12							,       SCREAMING_SNAKE_CASE_=12							,       SCREAMING_SNAKE_CASE_=3_072							,       SCREAMING_SNAKE_CASE_="gelu"							,       SCREAMING_SNAKE_CASE_=0.1							,       SCREAMING_SNAKE_CASE_=0.1							,       SCREAMING_SNAKE_CASE_=512							,       SCREAMING_SNAKE_CASE_=0							,       SCREAMING_SNAKE_CASE_=0.0_2							,       SCREAMING_SNAKE_CASE_=1E-7							,       SCREAMING_SNAKE_CASE_=False							,       SCREAMING_SNAKE_CASE_=-1							,       SCREAMING_SNAKE_CASE_=0							,       SCREAMING_SNAKE_CASE_=True							,       SCREAMING_SNAKE_CASE_=None							,       SCREAMING_SNAKE_CASE_=0							,       SCREAMING_SNAKE_CASE_="gelu"							,       **SCREAMING_SNAKE_CASE_							,       ):
            super().__init__(**SCREAMING_SNAKE_CASE_    )

            __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						       =   max_position_embeddings
            __snake_case						       =   type_vocab_size
            __snake_case						       =   initializer_range
            __snake_case						       =   relative_attention
            __snake_case						       =   max_relative_positions
            __snake_case						       =   pad_token_id
            __snake_case						       =   position_biased_input

            # Backwards compatibility
            if type(SCREAMING_SNAKE_CASE_    ) == str:
                   __snake_case						       =   [x.strip() for x in pos_att_type.lower().split('|'    )]

            __snake_case						       =   pos_att_type
            __snake_case						       =   vocab_size
            __snake_case						       =   layer_norm_eps

            __snake_case						       =   kwargs.get('pooler_hidden_size'							,       SCREAMING_SNAKE_CASE_    )
            __snake_case						       =   pooler_dropout
            __snake_case						       =   pooler_hidden_act







class  _lowerCamelCase			(lowerCamelCase					):

     @property
     def 						__lowerCamelCase				(  self    ):
            if self.task == "multiple-choice":
                   __snake_case						       =   {0: 'batch', 1: 'choice', 2: 'sequence'}
            else:
                   __snake_case						       =   {0: 'batch', 1: 'sequence'}
            if self._config.type_vocab_size > 0:
                   return OrderedDict(
                       [('input_ids', dynamic_axis), ('attention_mask', dynamic_axis), ('token_type_ids', dynamic_axis)]    )
            else:
                   return OrderedDict([('input_ids', dynamic_axis), ('attention_mask', dynamic_axis)]    )

     @property
     def 						__lowerCamelCase				(  self    ):
            return 12

     def 						__lowerCamelCase				(  self							,       SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_ = -1							,       SCREAMING_SNAKE_CASE_ = -1							,       SCREAMING_SNAKE_CASE_ = -1							,       SCREAMING_SNAKE_CASE_ = False							,       SCREAMING_SNAKE_CASE_ = None							,       SCREAMING_SNAKE_CASE_ = 3							,       SCREAMING_SNAKE_CASE_ = 40							,       SCREAMING_SNAKE_CASE_ = 40							,       SCREAMING_SNAKE_CASE_ = None							,       ):
            __snake_case						       =   super().generate_dummy_inputs(preprocessor=SCREAMING_SNAKE_CASE_							,       framework=SCREAMING_SNAKE_CASE_    )
            if self._config.type_vocab_size == 0 and "token_type_ids" in dummy_inputs:
                   del dummy_inputs["token_type_ids"]
            return dummy_inputs
