





"""simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import PIL
from PIL import Image

from ...utils import BaseOutput, is_torch_available, is_transformers_available






@dataclass
# Copied from diffusers.pipelines.stable_diffusion.__init__.StableDiffusionPipelineOutput with Stable->Alt
class       _SCREAMING_SNAKE_CASE(     A						):
       SCREAMING_SNAKE_CASE_     :   Union[List[PIL.Image.Image], np.ndarray]
       SCREAMING_SNAKE_CASE_     :   Optional[List[bool]]


if is_transformers_available() and is_torch_available():
  from .modeling_roberta_series import RobertaSeriesModelWithTransformation
  from .pipeline_alt_diffusion import AltDiffusionPipeline
  from .pipeline_alt_diffusion_imgaimg import AltDiffusionImgaImgPipeline






"""simple docstring"""
# Lint as: python3

import hashlib
from typing import Union



def   __lowerCamelCase     (							a_  :	Union[str, int, bytes]							)    ->   bytes:
      if isinstance(a_				,     a_							):
            # Data already in bytes, returns as it as
            return hash_data
      elif isinstance(a_				,     a_							):
            # We keep the data as it as for it ot be later encoded to UTF-8
            # However replace `\\` with `/` for Windows compatibility
            __SCREAMING_SNAKE_CASE     :str	       =						hash_data.replace('''\\'''				,     '''/'''							)
      elif isinstance(a_				,     a_							):
            __SCREAMING_SNAKE_CASE     :Union[str, Any]	       =						str(a_							)
      else:
            # If data is not of the required type, raise error
            raise InvalidKeyError(a_							)

      return hash_data.encode('''utf-8'''							)






class       _SCREAMING_SNAKE_CASE(     A						):




       def __init__(		self	,SCREAMING_SNAKE_CASE__							)    ->   Optional[int]:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE     :Tuple	       =						'''\nFAILURE TO GENERATE DATASET: Invalid key type detected'''
             __SCREAMING_SNAKE_CASE     :int	       =						f'''\nFound Key {hash_data} of type {type(SCREAMING_SNAKE_CASE__							)}'''
             __SCREAMING_SNAKE_CASE     :Optional[int]	       =						'''\nKeys should be either str, int or bytes type'''
             super().__init__(f'''{self.prefix}{self.err_msg}{self.suffix}'''							)






class       _SCREAMING_SNAKE_CASE(     A						):




       def __init__(		self	,SCREAMING_SNAKE_CASE__	,SCREAMING_SNAKE_CASE__	,SCREAMING_SNAKE_CASE__=""							)    ->   List[str]:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE     :str	       =						key
             __SCREAMING_SNAKE_CASE     :str	       =						duplicate_key_indices
             __SCREAMING_SNAKE_CASE     :Union[str, Any]	       =						fix_msg
             __SCREAMING_SNAKE_CASE     :int	       =						'''Found multiple examples generated with the same key'''
             if len(SCREAMING_SNAKE_CASE__							) <= 20:
                   __SCREAMING_SNAKE_CASE     :Dict	       =						f'''\nThe examples at index {", ".join(SCREAMING_SNAKE_CASE__							)} have the key {key}'''
             else:
                   __SCREAMING_SNAKE_CASE     :List[str]	       =						f'''\nThe examples at index {", ".join(duplicate_key_indices[:20]							)}... ({len(SCREAMING_SNAKE_CASE__							) - 20} more) have the key {key}'''
             __SCREAMING_SNAKE_CASE     :Union[str, Any]	       =						'''\n''' + fix_msg if fix_msg else ''''''
             super().__init__(f'''{self.prefix}{self.err_msg}{self.suffix}'''							)






class       _SCREAMING_SNAKE_CASE:




       def __init__(		self	,SCREAMING_SNAKE_CASE__							)    ->   Union[str, Any]:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE     :Dict	       =						hashlib.mda(_as_bytes(SCREAMING_SNAKE_CASE__							)							)




       def 					_UpperCamelCase  (		self	,SCREAMING_SNAKE_CASE__							)    ->   int:





             """simple docstring"""






             __SCREAMING_SNAKE_CASE     :Tuple	       =						self._split_mda.copy()
             __SCREAMING_SNAKE_CASE     :Optional[Any]	       =						_as_bytes(SCREAMING_SNAKE_CASE__							)
             mda.update(SCREAMING_SNAKE_CASE__							)
             # Convert to integer with hexadecimal conversion
             return int(mda.hexdigest()	,16							)