code: 
  
  
  import functools
  from math import sqrt
  from time import time
  
  
  
  
  def 			__lowercase	(						_UpperCamelCase,    *_UpperCamelCase,    **_UpperCamelCase     )    ->List[Any]:
  
  
  
  
  
  
  
        """simple docstring"""
  
        lowercase			:   Union[str, Any]					   =		time()
        lowercase			:   int					   =		func(*_UpperCamelCase,    **_UpperCamelCase     )
        lowercase			:   Dict					   =		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 			__lowercase	(						_UpperCamelCase     )    ->list[int]:
  
  
  
  
  
  
  
        """simple docstring"""
  
        if n < 0:
              raise Exception('''n is negative'''     )
        if n == 0:
              return [0]
        lowercase			:   Any					   =		[0, 1]
        for _ in range(n - 1     ):
              fib.append(fib[-1] + fib[-2]     )
        return fib
  
  
  
  
  def 			__lowercase	(						_UpperCamelCase     )    ->list[int]:
  
  
  
  
  
  
  
        """simple docstring"""
  
        def fib_recursive_term(_UpperCamelCase     ) -> 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(_UpperCamelCase     ) for i in range(n + 1     )]
  
  
  
  
  def 			__lowercase	(						_UpperCamelCase     )    ->list[int]:
  
  
  
  
  
  
  
        """simple docstring"""
  
        @functools.cache
        def fib_recursive_term(_UpperCamelCase     ) -> 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(_UpperCamelCase     ) for i in range(n + 1     )]
  
  
  
  
  def 			__lowercase	(						_UpperCamelCase     )    ->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.
        lowercase			:   dict[int, int]					   =		{0: 0, 1: 1, 2: 1}  # Prefilled cache
  
        def rec_fn_memoized(_UpperCamelCase     ) -> int:
              if num in cache:
                    return cache[num]
  
              lowercase			:   Optional[int]					   =		rec_fn_memoized(num - 1     ) + rec_fn_memoized(num - 2     )
              lowercase			:   Union[str, Any]					   =		value
              return value
  
        return [rec_fn_memoized(_UpperCamelCase     ) for i in range(n + 1     )]
  
  
  
  
  def 			__lowercase	(						_UpperCamelCase     )    ->list[int]:
  
  
  
  
  
  
  
        """simple docstring"""
  
        if n < 0:
              raise Exception('''n is negative'''     )
        if n >= 1475:
              raise Exception('''n is too large'''     )
        lowercase			:   int					   =		sqrt(5     )
        lowercase			:   Tuple					   =		(1 + sqrt_a) / 2
        return [round(phi**i / sqrt_a     ) for i in range(n + 1     )]
  
  
  if __name__ == "__main__":
    __a     :   Tuple   				=      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)
  
  
style_context: 
  
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      is_torch_available,
      is_transformers_available,
      is_transformers_version,
  )
  
  
  try:
    if not (is_transformers_available() and is_torch_available() and is_transformers_version('''>=''', '''4.27.0''')):
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    from ...utils.dummy_torch_and_transformers_objects import (
        AudioLDMPipeline,
    )
  else:
    from .pipeline_audioldm import AudioLDMPipeline
  
  