





# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCAmelCase_     							= {
    'configuration_mgp_str': ['MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MgpstrConfig'],
    'processing_mgp_str': ['MgpstrProcessor'],
    'tokenization_mgp_str': ['MgpstrTokenizer'],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase_     							= [
      'MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST',
      'MgpstrModel',
      'MgpstrPreTrainedModel',
      'MgpstrForSceneTextRecognition',
  ]

if TYPE_CHECKING:
  from .configuration_mgp_str import MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP, MgpstrConfig
  from .processing_mgp_str import MgpstrProcessor
  from .tokenization_mgp_str import MgpstrTokenizer

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_mgp_str import (
        MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST,
        MgpstrForSceneTextRecognition,
        MgpstrModel,
        MgpstrPreTrainedModel,
    )
else:
  import sys

  UpperCAmelCase_     							= _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)








import re
from pathlib import Path
from unittest import TestCase

import pytest






@pytest.mark.integration
class     lowercase__       (	__lowerCamelCase				):

   '''simple docstring'''


   def       UpperCamelCase__  (    self,		__magic_name__							) ->      Union[str, Any]:






       """simple docstring"""

       with open(__magic_name__,		encoding='''utf-8'''							) as input_file:
           UpperCamelCase__							:				Tuple          =      re.compile(R'''(?!.*\b(?:encoding|rb|w|wb|w+|wb+|ab|ab+)\b)(?<=\s)(open)\((.*)\)'''							)
           UpperCamelCase__							:				str          =      input_file.read()
           UpperCamelCase__							:				List[Any]          =      regexp.search(__magic_name__							)

       return match




   def       UpperCamelCase__  (    self,		__magic_name__							) ->      Any:






       """simple docstring"""

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

       UpperCamelCase__							:				Dict          =      [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       UpperCamelCase__  (    self							) ->      List[Any]:






       """simple docstring"""
       UpperCamelCase__							:				int          =      Path('''./datasets'''							)
       UpperCamelCase__							:				Any          =      list(dataset_paths.absolute().glob('''**/*.py'''							)							)

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




   def       UpperCamelCase__  (    self							) ->      Dict:






       """simple docstring"""
       UpperCamelCase__							:				Optional[int]          =      Path('''./datasets'''							)
       UpperCamelCase__							:				Optional[Any]          =      list(dataset_paths.absolute().glob('''**/*.py'''							)							)

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

