
'''simple docstring'''



import argparse
import datetime
def    lowerCAmelCase_	(				SCREAMING_SNAKE_CASE_						)     ->     str:




   """simple docstring"""
   _SCREAMING_SNAKE_CASE      =				{
       """0""": """Sunday""",
       """1""": """Monday""",
       """2""": """Tuesday""",
       """3""": """Wednesday""",
       """4""": """Thursday""",
       """5""": """Friday""",
       """6""": """Saturday""",
   }

   _SCREAMING_SNAKE_CASE      =				{0: 1, 1: 2, 2: 3, 3: 4, 4: 5, 5: 6, 6: 0}

   # Validate
   if not 0 < len(SCREAMING_SNAKE_CASE_						) < 11:
      raise ValueError("""Must be 10 characters long"""						)

   # Get month
   _SCREAMING_SNAKE_CASE      =				int(date_input[0] + date_input[1]						)
   # Validate
   if not 0 < m < 13:
      raise ValueError("""Month must be between 1 - 12"""						)

   _SCREAMING_SNAKE_CASE      =				date_input[2]
   # Validate
   if sep_a not in ["-", "/"]:
      raise ValueError("""Date separator must be '-' or '/'"""						)

   # Get day
   _SCREAMING_SNAKE_CASE      =				int(date_input[3] + date_input[4]						)
   # Validate
   if not 0 < d < 32:
      raise ValueError("""Date must be between 1 - 31"""						)

   # Get second separator
   _SCREAMING_SNAKE_CASE      =				date_input[5]
   # Validate
   if sep_a not in ["-", "/"]:
      raise ValueError("""Date separator must be '-' or '/'"""						)

   # Get year
   _SCREAMING_SNAKE_CASE      =				int(date_input[6] + date_input[7] + date_input[8] + date_input[9]						)
   # Arbitrary year range
   if not 45 < y < 85_00:
      raise ValueError(
          """Year out of range. There has to be some sort of limit...right?"""						)

   # Get datetime obj for validation
   _SCREAMING_SNAKE_CASE      =				datetime.date(int(SCREAMING_SNAKE_CASE_						)    ,      int(SCREAMING_SNAKE_CASE_						)    ,      int(SCREAMING_SNAKE_CASE_						)						)

   # Start math
   if m <= 2:
      _SCREAMING_SNAKE_CASE      =				y - 1
      _SCREAMING_SNAKE_CASE      =				m + 12
   # maths var
   _SCREAMING_SNAKE_CASE      =				int(str(SCREAMING_SNAKE_CASE_						)[:2]						)
   _SCREAMING_SNAKE_CASE      =				int(str(SCREAMING_SNAKE_CASE_						)[2:]						)
   _SCREAMING_SNAKE_CASE      =				int(2.6 * m - 5.39						)
   _SCREAMING_SNAKE_CASE      =				int(c / 4						)
   _SCREAMING_SNAKE_CASE      =				int(k / 4						)
   _SCREAMING_SNAKE_CASE      =				int(d + k						)
   _SCREAMING_SNAKE_CASE      =				int(t + u + v + x						)
   _SCREAMING_SNAKE_CASE      =				int(z - (2 * c)						)
   _SCREAMING_SNAKE_CASE      =				round(w % 7						)
   # End math

   # Validate math
   if f != convert_datetime_days[dt_ck.weekday()]:
      raise AssertionError("""The date was evaluated incorrectly. Contact developer."""						)

   # Response
   _SCREAMING_SNAKE_CASE      =				F"Your date {date_input}, is a {days[str(SCREAMING_SNAKE_CASE_						)]}!"
   return response


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     UpperCamelCase__      :		Dict       							=  argparse.ArgumentParser(
         description=(
             "Find out what day of the week nearly any date is or was. Enter "
             "date as a string in the mm-dd-yyyy or mm/dd/yyyy format"
         )
     )
     parser.add_argument(
         "date_input", type=str, help="Date as a string (mm-dd-yyyy or mm/dd/yyyy)"
     )
     UpperCamelCase__      :		int       							=  parser.parse_args()
     zeller(args.date_input)








'''simple docstring'''



import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding

class    _a				(_lowerCamelCase):





       """simple docstring"""




       SCREAMING_SNAKE_CASE      =  ['image_processor', 'tokenizer']
       SCREAMING_SNAKE_CASE      =  'ChineseCLIPImageProcessor'
       SCREAMING_SNAKE_CASE      =  ('BertTokenizer', 'BertTokenizerFast')






       def __init__(							self       ,							A__=None       ,							A__=None       ,							**A__      )    ->			int:
          _SCREAMING_SNAKE_CASE      =				None
          if "feature_extractor" in kwargs:
             warnings.warn(
                 """The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"""
                 """ instead."""       ,							A__       ,							)
             _SCREAMING_SNAKE_CASE      =				kwargs.pop("""feature_extractor"""      )

          _SCREAMING_SNAKE_CASE      =				image_processor if image_processor is not None else feature_extractor
          if image_processor is None:
             raise ValueError("""You need to specify an `image_processor`."""      )
          if tokenizer is None:
             raise ValueError("""You need to specify a `tokenizer`."""      )

          super().__init__(A__       ,							A__      )
          _SCREAMING_SNAKE_CASE      =				self.image_processor






       def __call__(							self       ,							A__=None       ,							A__=None       ,							A__=None       ,							**A__      )    ->			Optional[int]:

          if text is None and images is None:
             raise ValueError("""You have to specify either text or images. Both cannot be none."""      )

          if text is not None:
             _SCREAMING_SNAKE_CASE      =				self.tokenizer(A__       ,							return_tensors=A__       ,							**A__      )

          if images is not None:
             _SCREAMING_SNAKE_CASE      =				self.image_processor(A__       ,							return_tensors=A__       ,							**A__      )

          if text is not None and images is not None:
             _SCREAMING_SNAKE_CASE      =				image_features.pixel_values
             return encoding
          elif text is not None:
             return encoding
          else:
             return BatchEncoding(data=dict(**A__      )       ,							tensor_type=A__      )






       def        UpperCamelCase				(							self       ,							*A__       ,							**A__      )    ->			Dict:
          return self.tokenizer.batch_decode(*A__       ,							**A__      )






       def        UpperCamelCase				(							self       ,							*A__       ,							**A__      )    ->			Optional[Any]:
          return self.tokenizer.decode(*A__       ,							**A__      )






       @property
       def        UpperCamelCase				(							self      )    ->			List[Any]:
          _SCREAMING_SNAKE_CASE      =				self.tokenizer.model_input_names
          _SCREAMING_SNAKE_CASE      =				self.image_processor.model_input_names
          return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names      )      )






       @property
       def        UpperCamelCase				(							self      )    ->			Optional[int]:
          warnings.warn(
              """`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."""       ,							A__       ,							)
          return self.image_processor_class






