





'''simple docstring'''


from dataclasses import dataclass
from enum import Enum
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
class  lowerCAmelCase_		(		__magic_name__		):
 __lowerCamelCase    :				Union[List[PIL.Image.Image], np.ndarray]
 __lowerCamelCase    :				Optional[List[bool]]


if is_transformers_available() and is_torch_available():
       from .pipeline_semantic_stable_diffusion import SemanticStableDiffusionPipeline



import enum
import os
from hashlib import shaaaa
from typing import Optional

from .. import config
from .logging import get_logger


SCREAMING_SNAKE_CASE			:						List[Any]				  =		get_logger(__name__)
class  A_			(							enum.Enum			):
  _SCREAMING_SNAKE_CASE     					=      """all_checks"""
  _SCREAMING_SNAKE_CASE     					=      """basic_checks"""
  _SCREAMING_SNAKE_CASE     					=      """no_checks"""
class  A_			(							a_			):
  pass
class  A_			(							a_			):
  pass
class  A_			(							a_			):
  pass
class  A_			(							a_			):
  pass



def 	__A		(      _A				,					_A				,					_A=None       ):



 """simple docstring"""


 if expected_checksums is None:
  logger.info("Unable to verify checksums."       )
  return
 if len(set(_A       ) - set(_A       )       ) > 0:
  raise ExpectedMoreDownloadedFiles(str(set(_A       ) - set(_A       )       )       )
 if len(set(_A       ) - set(_A       )       ) > 0:
  raise UnexpectedDownloadedFile(str(set(_A       ) - set(_A       )       )       )
 __a							=	[url for url in expected_checksums if expected_checksums[url] != recorded_checksums[url]]
 __a							=	" for " + verification_name if verification_name is not None else ""
 if len(_A       ) > 0:
  raise NonMatchingChecksumError(
      f"""Checksums didn't match{for_verification_name}:\n"""
      f"""{bad_urls}\n"""
      "Set `verification_mode='no_checks'` to skip checksums verification and ignore this error"       )
 logger.info("All the checksums matched successfully" + for_verification_name       )
class  A_			(							a_			):
  pass
class  A_			(							a_			):
  pass
class  A_			(							a_			):
  pass
class  A_			(							a_			):
  pass



def 	__A		(      _A				,					_A       ):



 """simple docstring"""


 if expected_splits is None:
  logger.info("Unable to verify splits sizes."       )
  return
 if len(set(_A       ) - set(_A       )       ) > 0:
  raise ExpectedMoreSplits(str(set(_A       ) - set(_A       )       )       )
 if len(set(_A       ) - set(_A       )       ) > 0:
  raise UnexpectedSplits(str(set(_A       ) - set(_A       )       )       )
 __a							=	[
     {"expected": expected_splits[name], "recorded": recorded_splits[name]}
     for name in expected_splits
     if expected_splits[name].num_examples != recorded_splits[name].num_examples
 ]
 if len(_A       ) > 0:
  raise NonMatchingSplitsSizesError(str(_A       )       )
 logger.info("All the splits matched successfully."       )



def 	__A		(      _A				,					_A = True       ):



 """simple docstring"""


 if record_checksum:
  __a							=	shaaaa()
  with open(_A				,					"rb"       ) as f:
   for chunk in iter(lambda: f.read(1 << 20       )				,					B""       ):
    m.update(_A       )
   __a							=	m.hexdigest()
 else:
  __a							=	None
 return {"num_bytes": os.path.getsize(_A       ), "checksum": checksum}






def 	__A		(      _A       ):



 """simple docstring"""


 if dataset_size and config.IN_MEMORY_MAX_SIZE:
  return dataset_size < config.IN_MEMORY_MAX_SIZE
 else:
  return False


