





# 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,
    is_vision_available,
)


UpperCAmelCase			:			str	  = {
    """configuration_tvlt""": ["""TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TvltConfig"""],
    """feature_extraction_tvlt""": ["""TvltFeatureExtractor"""],
    """processing_tvlt""": ["""TvltProcessor"""],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCAmelCase			:			Any	  = [
         """TVLT_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """TvltModel""",
         """TvltForPreTraining""",
         """TvltForAudioVisualClassification""",
         """TvltPreTrainedModel""",
     ]

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCAmelCase			:			Tuple	  = ["""TvltImageProcessor"""]


if TYPE_CHECKING:
     from .configuration_tvlt import TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP, TvltConfig
     from .processing_tvlt import TvltProcessor
     from .feature_extraction_tvlt import TvltFeatureExtractor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tvlt import (
              TVLT_PRETRAINED_MODEL_ARCHIVE_LIST,
              TvltForAudioVisualClassification,
              TvltForPreTraining,
              TvltModel,
              TvltPreTrainedModel,
          )

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .image_processing_tvlt import TvltImageProcessor


else:
     import sys

     UpperCAmelCase			:			List[str]	  = _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)












def   _A (	SCREAMING_SNAKE_CASE  :     int		):





  """simple docstring"""



  barcode //= 10  # exclude the last digit
  a__			:      int            =False
  a__			:      List[str]            =0

  # extract and check each digit
  while barcode != 0:
    a__			:      Optional[Any]            =1 if checker else 3
    s += mult * (barcode % 10)
    barcode //= 10
    a__			:      Union[str, Any]            =not checker

  return (10 - (s % 10)) % 10
def   _A (	SCREAMING_SNAKE_CASE  :     int		):





  """simple docstring"""



  return len(str(SCREAMING_SNAKE_CASE		)		) == 13 and get_check_digit(SCREAMING_SNAKE_CASE		) == barcode % 10
def   _A (	SCREAMING_SNAKE_CASE  :     str		):





  """simple docstring"""



  if str(SCREAMING_SNAKE_CASE		).isalpha():
    a__			:      Tuple            =f'''Barcode \'{barcode}\' has alphabetic characters.'''
    raise ValueError(SCREAMING_SNAKE_CASE		)
  elif int(SCREAMING_SNAKE_CASE		) < 0:
    raise ValueError("The entered barcode has a negative value. Try again."		)
  else:
    return int(SCREAMING_SNAKE_CASE		)


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     UpperCAmelCase			:			List[str]	  = get_barcode(input("""Barcode: """).strip())

     if is_valid(barcode):
          print(F"""'{barcode}' is a valid barcode.""")
     else:
          print(F"""'{barcode}' is NOT a valid barcode.""")






