




import re
from pathlib import Path
from unittest import TestCase

import pytest


@pytest.mark.integration
class     UpperCamelCase_   (			UpperCAmelCase__					):

    '''simple docstring'''






    def 	SCREAMING_SNAKE_CASE							(      self				:     List[str] ,			UpperCAmelCase__				:     str)						->Optional[int]:





           '''simple docstring'''

           with open(UpperCAmelCase__ ,			encoding='''utf-8''') as input_file:
                  A__							=   re.compile(R'''(?!.*\b(?:encoding|rb|w|wb|w+|wb+|ab|ab+)\b)(?<=\s)(open)\((.*)\)''')
                  A__							=   input_file.read()
                  A__							=   regexp.search(UpperCAmelCase__)

           return match


    def 	SCREAMING_SNAKE_CASE							(      self				:     Optional[Any] ,			UpperCAmelCase__				:     str)						->Optional[int]:





           '''simple docstring'''

           with open(UpperCAmelCase__ ,			encoding='''utf-8''') as input_file:
                  A__							=   re.compile(R'''#[^\r\n]*print\(|\"[^\r\n]*print\(|\"\"\".*?print\(.*?\"\"\"|(print\()''' ,			re.DOTALL)
                  A__							=   input_file.read()
                  # use `re.finditer` to handle the case where the ignored groups would be matched first by `re.search`
                  A__							=   regexp.finditer(UpperCAmelCase__)

           A__							=   [match for match in matches if match is not None and match.group(1) is not None]
           return matches[0] if matches else None


    def 	SCREAMING_SNAKE_CASE							(      self				:     int)						->int:





           '''simple docstring'''

           A__							=   Path('''./datasets''')
           A__							=   list(dataset_paths.absolute().glob('''**/*.py'''))

           for dataset in dataset_files:
                  if self._no_encoding_on_file_open(str(UpperCAmelCase__)):
                         raise AssertionError(f"""open(...) must use utf-8 encoding in {dataset}""")





    def 	SCREAMING_SNAKE_CASE							(      self				:     Tuple)						->str:





           '''simple docstring'''

           A__							=   Path('''./datasets''')
           A__							=   list(dataset_paths.absolute().glob('''**/*.py'''))

           for dataset in dataset_files:
                  if self._no_print_statements(str(UpperCAmelCase__)):
                         raise AssertionError(f"""print statement found in {dataset}. Use datasets.logger/logging instead.""")








from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowerCamelCase     :		str								=       {"""configuration_focalnet""": ["""FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FocalNetConfig"""]}


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCamelCase     :		Dict								=       [
      """FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """FocalNetForImageClassification""",
      """FocalNetForMaskedImageModeling""",
      """FocalNetBackbone""",
      """FocalNetModel""",
      """FocalNetPreTrainedModel""",
  ]

if TYPE_CHECKING:
  from .configuration_focalnet import FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP, FocalNetConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_focalnet import (
        FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST,
        FocalNetBackbone,
        FocalNetForImageClassification,
        FocalNetForMaskedImageModeling,
        FocalNetModel,
        FocalNetPreTrainedModel,
    )

else:
  import sys

  _lowerCamelCase     :		Tuple								=       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


