





'''simple docstring'''

import os

from packaging import version

from .. import __version__
from .accelerate_utils import apply_forward_hook
from .constants import (
    CONFIG_NAME,
    DEPRECATED_REVISION_ARGS,
    DIFFUSERS_CACHE,
    DIFFUSERS_DYNAMIC_MODULE_NAME,
    FLAX_WEIGHTS_NAME,
    HF_MODULES_CACHE,
    HUGGINGFACE_CO_RESOLVE_ENDPOINT,
    ONNX_EXTERNAL_WEIGHTS_NAME,
    ONNX_WEIGHTS_NAME,
    SAFETENSORS_WEIGHTS_NAME,
    TEXT_ENCODER_ATTN_MODULE,
    WEIGHTS_NAME,
)
from .deprecation_utils import deprecate
from .doc_utils import replace_example_docstring
from .dynamic_modules_utils import get_class_from_dynamic_module
from .hub_utils import (
    HF_HUB_OFFLINE,
    _add_variant,
    _get_model_file,
    extract_commit_hash,
    http_user_agent,
)
from .import_utils import (
    BACKENDS_MAPPING,
    ENV_VARS_TRUE_AND_AUTO_VALUES,
    ENV_VARS_TRUE_VALUES,
    USE_JAX,
    USE_TF,
    USE_TORCH,
    DummyObject,
    OptionalDependencyNotAvailable,
    is_accelerate_available,
    is_accelerate_version,
    is_bsa_available,
    is_flax_available,
    is_ftfy_available,
    is_inflect_available,
    is_invisible_watermark_available,
    is_k_diffusion_available,
    is_k_diffusion_version,
    is_librosa_available,
    is_note_seq_available,
    is_omegaconf_available,
    is_onnx_available,
    is_safetensors_available,
    is_scipy_available,
    is_tensorboard_available,
    is_tf_available,
    is_torch_available,
    is_torch_version,
    is_torchsde_available,
    is_transformers_available,
    is_transformers_version,
    is_unidecode_available,
    is_wandb_available,
    is_xformers_available,
    requires_backends,
)
from .logging import get_logger
from .outputs import BaseOutput
from .pil_utils import PIL_INTERPOLATION, numpy_to_pil, pt_to_pil
from .torch_utils import is_compiled_module, randn_tensor


if is_torch_available():
      from .testing_utils import (
          floats_tensor,
          load_hf_numpy,
          load_image,
          load_numpy,
          load_pt,
          nightly,
          parse_flag_from_env,
          print_tensor_test,
          require_torch_a,
          require_torch_gpu,
          skip_mps,
          slow,
          torch_all_close,
          torch_device,
      )
      from .torch_utils import maybe_allow_in_graph

from .testing_utils import export_to_gif, export_to_video


lowercase_         =			get_logger(__name__)





def lowerCamelCase						(					__lowerCamelCase			:   List[Any]   )						->Union[str, Any]:
    if version.parse(_lowerCamelCase   ) < version.parse(_lowerCamelCase   ):
        if "dev" in min_version:
            _SCREAMING_SNAKE_CASE     =      (
                """This example requires a source install from HuggingFace diffusers (see """
                """`https://huggingface.co/docs/diffusers/installation#install-from-source`),"""
            )
        else:
            _SCREAMING_SNAKE_CASE     =      F'This example requires a minimum version of {min_version},'
        error_message += F' but the version found is {__version__}.\n'
        raise ImportError(_lowerCamelCase   )










'''simple docstring'''

def lowerCamelCase						(					__lowerCamelCase			:   int   )						->int:
    barcode //= 10  # exclude the last digit
    _SCREAMING_SNAKE_CASE     =      False
    _SCREAMING_SNAKE_CASE     =      0

    # extract and check each digit
    while barcode != 0:
        _SCREAMING_SNAKE_CASE     =      1 if checker else 3
        s += mult * (barcode % 10)
        barcode //= 10
        _SCREAMING_SNAKE_CASE     =      not checker

    return (10 - (s % 10)) % 10





def lowerCamelCase						(					__lowerCamelCase			:   int   )						->bool:
    return len(str(__lowerCamelCase   )   ) == 13 and get_check_digit(__lowerCamelCase   ) == barcode % 10





def lowerCamelCase						(					__lowerCamelCase			:   str   )						->int:
    if str(__lowerCamelCase   ).isalpha():
        _SCREAMING_SNAKE_CASE     =      F'Barcode \'{barcode}\' has alphabetic characters.'
        raise ValueError(__lowerCamelCase   )
    elif int(__lowerCamelCase   ) < 0:
        raise ValueError("""The entered barcode has a negative value. Try again."""   )
    else:
        return int(__lowerCamelCase   )


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      lowercase_         =			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.""")



