code: 
  
  """simple docstring"""
  
  
  
  
  from typing import List, Optional, Tuple, Union
  
  from . import logging
  from .import_utils import is_torch_available, is_torch_version
  
  
  if is_torch_available():
  	import torch
  
  __A												=	logging.get_logger(__name__)  # pylint: disable=invalid-name
  
  try:
  	from torch._dynamo import allow_in_graph as maybe_allow_in_graph
  except (ImportError, ModuleNotFoundError):
  	def      __SCREAMING_SNAKE_CASE		(		cls   ):
  						"""simple docstring"""
  						return cls
  def      __SCREAMING_SNAKE_CASE		(		lowercase__    ,							lowercase__ = None    ,							lowercase__ = None    ,							lowercase__ = None    ,							lowercase__ = None    ,							):
  					"""simple docstring"""
  					A    =      device
  					A    =      shape[0]
  
  					A    =      layout or torch.strided
  					A    =      device or torch.device("cpu"   )
  
  					if generator is not None:
  										A    =      generator.device.type if not isinstance(lowercase__    ,							lowercase__   ) else generator[0].device.type
  										if gen_device_type != device.type and gen_device_type == "cpu":
  															A    =      "cpu"
  															if device != "mps":
  																				logger.info(
  																				    F"""The passed generator was created on 'cpu' even though a tensor on {device} was expected."""
  																				    F""" Tensors will be created on 'cpu' and then moved to {device}. Note that one can probably"""
  																				    F""" slighly speed up this function by passing a generator that was created on the {device} device."""   )
  										elif gen_device_type != device.type and gen_device_type == "cuda":
  															raise ValueError(F"""Cannot generate a {device} tensor from a generator of type {gen_device_type}."""   )
  
  					if isinstance(lowercase__    ,							lowercase__   ):
  										A    =      (1,) + shape[1:]
  										A    =      [
  										    torch.randn(lowercase__    ,							generator=generator[i]    ,							device=lowercase__    ,							dtype=lowercase__    ,							layout=lowercase__   )
  										    for i in range(lowercase__   )
  										]
  										A    =      torch.cat(lowercase__    ,							dim=0   ).to(lowercase__   )
  					else:
  										A    =      torch.randn(lowercase__    ,							generator=lowercase__    ,							device=lowercase__    ,							dtype=lowercase__    ,							layout=lowercase__   ).to(lowercase__   )
  
  					return latents
  def      __SCREAMING_SNAKE_CASE		(		lowercase__   ):
  					"""simple docstring"""
  					if is_torch_version("<"    ,							"2.0.0"   ) or not hasattr(lowercase__    ,							"_dynamo"   ):
  										return False
  					return isinstance(lowercase__    ,							torch._dynamo.eval_frame.OptimizedModule   )
  
  
  
  
  
  
style_context: 
  
  """simple docstring"""
  
  
  
  
  def      __SCREAMING_SNAKE_CASE		(		lowercase__   ):
  					"""simple docstring"""
  					if not isinstance(lowercase__    ,							lowercase__   ):
  										A    =      (
  										    "operation can not be conducted on a object of type "
  										    F"""{type(lowercase__   ).__name__}"""
  										)
  										raise TypeError(lowercase__   )
  					A    =      ""
  					for _ in range(0    ,							32   ):
  										bit_string += str(number % 2   )
  										A    =      number >> 1
  					return bit_string
  def      __SCREAMING_SNAKE_CASE		(		lowercase__   ):
  					"""simple docstring"""
  					if number < 0:
  										raise ValueError("the value of input must be positive"   )
  					elif isinstance(lowercase__    ,							lowercase__   ):
  										raise TypeError("Input value must be a 'int' type"   )
  					elif isinstance(lowercase__    ,							lowercase__   ):
  										raise TypeError("'<' not supported between instances of 'str' and 'int'"   )
  					A    =      0
  					# iterator over [1 to 32],since we are dealing with 32 bit integer
  					for _ in range(1    ,							33   ):
  										# left shift the bits by unity
  										A    =      result << 1
  										# get the end bit
  										A    =      number % 2
  										# right shift the bits by unity
  										A    =      number >> 1
  										# add that bit to our ans
  										A    =      result | end_bit
  					return get_reverse_bit_string(lowercase__   )
  
  
  if __name__ == "__main__":
  	import doctest
  
  	doctest.testmod()
  
  
  
  
  
  