


"""simple docstring"""




import argparse
import os
import re


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
__magic_name__						: Optional[int]    =				'src/diffusers'

# Matches is_xxx_available()
__magic_name__						: str    =				re.compile(R'is\_([a-z_]*)_available\(\)')
# Matches from xxx import bla
__magic_name__						: Any    =				re.compile(R'\s+from\s+\S*\s+import\s+([^\(\s].*)\n')


__magic_name__						: List[Any]    =				'\n{0} = None\n'

__magic_name__						: Tuple    =				'\nclass {0}(metaclass=DummyObject):\n    _backends = {1}\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, {1})\n\n    @classmethod\n    def from_config(cls, *args, **kwargs):\n        requires_backends(cls, {1})\n\n    @classmethod\n    def from_pretrained(cls, *args, **kwargs):\n        requires_backends(cls, {1})\n'


__magic_name__						: int    =				'\ndef {0}(*args, **kwargs):\n    requires_backends({0}, {1})\n'





def       a_ (	lowercase__ :Optional[Any]     ):
			__lowerCamelCase          =      _re_backend.findall(lowercase__     )
			if len(lowercase__     ) == 0:
						return None

			return "_and_".join(lowercase__     )





def       a_ (	):
			with open(os.path.join(lowercase__,			"""__init__.py"""     ),			"""r""",			encoding="""utf-8""",			newline="""\n"""     ) as f:
						__lowerCamelCase          =      f.readlines()

			# Get to the point we do the actual imports for type checking
			__lowerCamelCase          =      0
			__lowerCamelCase          =      {}
			# Go through the end of the file
			while line_index < len(lowercase__     ):
						# If the line contains is_backend_available, we grab all objects associated with the `else` block
						__lowerCamelCase          =      find_backend(lines[line_index]     )
						if backend is not None:
									while not lines[line_index].startswith("""else:"""     ):
												line_index += 1
									line_index += 1
									__lowerCamelCase          =      []
									# Until we unindent, add backend objects to the list
									while line_index < len(lowercase__     ) and len(lines[line_index]     ) > 1:
												__lowerCamelCase          =      lines[line_index]
												__lowerCamelCase          =      _re_single_line_import.search(lowercase__     )
												if single_line_import_search is not None:
															objects.extend(single_line_import_search.groups()[0].split(""", """     )     )
												elif line.startswith(""" """ * 8     ):
															objects.append(line[8:-2]     )
												line_index += 1

									if len(lowercase__     ) > 0:
												__lowerCamelCase          =      objects
						else:
									line_index += 1

			return backend_specific_objects





def       a_ (	lowercase__ :List[Any],			lowercase__ :List[str]     ):
			if name.isupper():
						return DUMMY_CONSTANT.format(lowercase__     )
			elif name.islower():
						return DUMMY_FUNCTION.format(lowercase__,			lowercase__     )
			else:
						return DUMMY_CLASS.format(lowercase__,			lowercase__     )





def       a_ (	lowercase__ :List[str]=None     ):
			if backend_specific_objects is None:
						__lowerCamelCase          =      read_init()
			# For special correspondence backend to module name as used in the function requires_modulename
			__lowerCamelCase          =      {}

			for backend, objects in backend_specific_objects.items():
						__lowerCamelCase          =      """[""" + """, """.join(f'"{b}"' for b in backend.split("""_and_"""     )     ) + """]"""
						__lowerCamelCase          =      """# This file is autogenerated by the command `make fix-copies`, do not edit.\n"""
						dummy_file += "from ..utils import DummyObject, requires_backends\n\n"
						dummy_file += "\n".join([create_dummy_object(lowercase__,			lowercase__     ) for o in objects]     )
						__lowerCamelCase          =      dummy_file

			return dummy_files





def       a_ (	lowercase__ :int=False     ):
			__lowerCamelCase          =      create_dummy_files()
			# For special correspondence backend to shortcut as used in utils/dummy_xxx_objects.py
			__lowerCamelCase          =      {"""torch""": """pt"""}

			# Locate actual dummy modules and read their content.
			__lowerCamelCase          =      os.path.join(lowercase__,			"""utils"""     )
			__lowerCamelCase          =      {
			    backend: os.path.join(lowercase__,			f'dummy_{short_names.get(lowercase__,			lowercase__     )}_objects.py'     )
			    for backend in dummy_files.keys()
			}

			__lowerCamelCase          =      {}
			for backend, file_path in dummy_file_paths.items():
						if os.path.isfile(lowercase__     ):
									with open(lowercase__,			"""r""",			encoding="""utf-8""",			newline="""\n"""     ) as f:
												__lowerCamelCase          =      f.read()
						else:
									__lowerCamelCase          =      """"""

			for backend in dummy_files.keys():
						if dummy_files[backend] != actual_dummies[backend]:
									if overwrite:
												print(
												    f'Updating diffusers.utils.dummy_{short_names.get(lowercase__,			lowercase__     )}_objects.py as the main '
												    """__init__ has new objects."""     )
												with open(dummy_file_paths[backend],			"""w""",			encoding="""utf-8""",			newline="""\n"""     ) as f:
															f.write(dummy_files[backend]     )
									else:
												raise ValueError(
												    """The main __init__ has objects that are not present in """
												    f'diffusers.utils.dummy_{short_names.get(lowercase__,			lowercase__     )}_objects.py. Run `make fix-copies` '
												    """to fix this."""     )


if __name__ == "__main__":
					__magic_name__						: Dict    =				argparse.ArgumentParser()
					parser.add_argument('--fix_and_overwrite', action='store_true', help='Whether to fix inconsistencies.')
					__magic_name__						: Optional[int]    =				parser.parse_args()

					check_dummies(args.fix_and_overwrite)








"""simple docstring"""




import unittest

from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


__magic_name__						: Dict    =				get_tests_dir('fixtures/test_sentencepiece.model')
__magic_name__						: int    =				get_tests_dir('fixtures/test_sentencepiece_bpe.model')

__magic_name__						: Any    =				'pt' if is_torch_available() else 'tf'




@require_sentencepiece
@require_tokenizers
class 			__snake_case   (lowerCamelCase			,		unittest.TestCase  ):
							__a					 =       CamembertTokenizer
							__a					 =       CamembertTokenizerFast
							__a					 =       True
							__a					 =       True




							def   __a   (     self:    List[Any]   ):
										super().setUp()

										# We have a SentencePiece fixture for testing
										__lowerCamelCase          =      CamembertTokenizer(A_   )
										tokenizer.save_pretrained(self.tmpdirname   )




							def   __a   (     self:    Union[str, Any]   ):
										__lowerCamelCase          =      """<pad>"""
										__lowerCamelCase          =      1

										self.assertEqual(self.get_tokenizer()._convert_token_to_id(A_   )     ,							A_   )
										self.assertEqual(self.get_tokenizer()._convert_id_to_token(A_   )     ,							A_   )




							def   __a   (     self:    Any   ):
										__lowerCamelCase          =      list(self.get_tokenizer().get_vocab().keys()   )

										self.assertEqual(vocab_keys[0]     ,							"""<s>NOTUSED"""   )
										self.assertEqual(vocab_keys[1]     ,							"""<pad>"""   )
										self.assertEqual(vocab_keys[-1]     ,							"""<mask>"""   )
										self.assertEqual(len(A_   )     ,							10_04   )




							def   __a   (     self:    Any   ):
										self.assertEqual(self.get_tokenizer().vocab_size     ,							10_05   )




							def   __a   (     self:    Optional[Any]   ):
										__lowerCamelCase          =      CamembertTokenizer(A_   )
										tokenizer.save_pretrained(self.tmpdirname   )
										__lowerCamelCase          =      CamembertTokenizerFast.from_pretrained(self.tmpdirname   )

										__lowerCamelCase          =      """I was born in 92000, and this is falsé."""

										__lowerCamelCase          =      tokenizer.encode(A_   )
										__lowerCamelCase          =      rust_tokenizer.encode(A_   )
										self.assertListEqual(A_     ,							A_   )

										__lowerCamelCase          =      tokenizer.encode(A_     ,							add_special_tokens=A_   )
										__lowerCamelCase          =      rust_tokenizer.encode(A_     ,							add_special_tokens=A_   )
										self.assertListEqual(A_     ,							A_   )

										# <unk> tokens are not the same for `rust` than for `slow`.
										# Because spm gives back raw token instead of `unk` in EncodeAsPieces
										# tokens = tokenizer.tokenize(sequence)
										__lowerCamelCase          =      tokenizer.convert_ids_to_tokens(A_   )
										__lowerCamelCase          =      rust_tokenizer.tokenize(A_   )
										self.assertListEqual(A_     ,							A_   )




							def   __a   (     self:    List[str]   ):
										if not self.test_rust_tokenizer:
													return

										__lowerCamelCase          =      self.get_tokenizer()
										__lowerCamelCase          =      self.get_rust_tokenizer()

										__lowerCamelCase          =      """I was born in 92000, and this is falsé."""

										__lowerCamelCase          =      tokenizer.tokenize(A_   )
										__lowerCamelCase          =      rust_tokenizer.tokenize(A_   )
										self.assertListEqual(A_     ,							A_   )

										__lowerCamelCase          =      tokenizer.encode(A_     ,							add_special_tokens=A_   )
										__lowerCamelCase          =      rust_tokenizer.encode(A_     ,							add_special_tokens=A_   )
										self.assertListEqual(A_     ,							A_   )

										__lowerCamelCase          =      self.get_rust_tokenizer()
										__lowerCamelCase          =      tokenizer.encode(A_   )
										__lowerCamelCase          =      rust_tokenizer.encode(A_   )
										self.assertListEqual(A_     ,							A_   )




							@slow
							def   __a   (     self:    Optional[Any]   ):
										# fmt: off
										__lowerCamelCase          =      {"""input_ids""": [[5, 54, 71_96, 2_97, 30, 23, 7_76, 18, 11, 32_15, 37_05, 82_52, 22, 31_64, 11_81, 21_16, 29, 16, 8_13, 25, 7_91, 33_14, 20, 34_46, 38, 2_75_75, 1_20, 6, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [5, 4_68, 17, 11, 90_88, 20, 15_17, 8, 2_28_04, 1_88_18, 10, 38, 6_29, 6_07, 6_07, 1_42, 19, 71_96, 8_67, 56, 1_03_26, 24, 22_67, 20, 4_16, 50_72, 1_56_12, 2_33, 7_34, 7, 23_99, 27, 16, 30_15, 16_49, 7, 24, 20, 43_38, 23_99, 27, 13, 34_00, 14, 13, 61_89, 8, 9_30, 9, 6]], """attention_mask""": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
										# fmt: on

										# camembert is a french model. So we also use french texts.
										__lowerCamelCase          =      [
										    """Le transformeur est un modèle d'apprentissage profond introduit en 2017, """
										    """utilisé principalement dans le domaine du traitement automatique des langues (TAL).""",
										    """À l'instar des réseaux de neurones récurrents (RNN), les transformeurs sont conçus """
										    """pour gérer des données séquentielles, telles que le langage naturel, pour des tâches """
										    """telles que la traduction et la synthèse de texte.""",
										]

										self.tokenizer_integration_test_util(
										    expected_encoding=A_     ,							model_name="""camembert-base"""     ,							revision="""3a0641d9a1aeb7e848a74299e7e4c4bca216b4cf"""     ,							sequences=A_     ,							)




