



"""simple docstring"""





import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request

from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging import version

from .. import __version__
from . import DIFFUSERS_DYNAMIC_MODULE_NAME, HF_MODULES_CACHE, logging


lowercase  							=					(
    '''https://raw.githubusercontent.com/huggingface/diffusers/{revision}/examples/community/{pipeline}.py'''
)


lowercase  							=					logging.get_logger(__name__)  # pylint: disable=invalid-name




def 	UpperCAmelCase     (		):

		'''simple docstring'''


		_UpperCAmelCase							 =		'https://pypi.org/pypi/diffusers/json'
		_UpperCAmelCase							 =		json.loads(request.urlopen(A       ).read()       )['releases'].keys()
		return sorted(A     ,				key=lambda A       : version.Version(A       )       )




def 	UpperCAmelCase     (		):

		'''simple docstring'''


		if HF_MODULES_CACHE in sys.path:
				return

		sys.path.append(A       )
		os.makedirs(A     ,				exist_ok=A       )
		_UpperCAmelCase							 =		Path(A       ) / '__init__.py'
		if not init_path.exists():
				init_path.touch()




def 	UpperCAmelCase     (		A	:						Union[str, os.PathLike]       ):

		'''simple docstring'''


		init_hf_modules()
		_UpperCAmelCase							 =		Path(A       ) / name
		# If the parent module does not exist yet, recursively create it.
		if not dynamic_module_path.parent.exists():
				create_dynamic_module(dynamic_module_path.parent       )
		os.makedirs(A     ,				exist_ok=A       )
		_UpperCAmelCase							 =		dynamic_module_path / '__init__.py'
		if not init_path.exists():
				init_path.touch()




def 	UpperCAmelCase     (		A	:						List[Any]       ):

		'''simple docstring'''


		with open(A     ,				'r'     ,				encoding='utf-8'       ) as f:
				_UpperCAmelCase							 =		f.read()

		# Imports of the form `import .xxx`
		_UpperCAmelCase							 =		re.findall('^\s*import\s+\.(\S+)\s*$'     ,				A     ,				flags=re.MULTILINE       )
		# Imports of the form `from .xxx import yyy`
		relative_imports += re.findall('^\s*from\s+\.(\S+)\s+import'     ,				A     ,				flags=re.MULTILINE       )
		# Unique-ify
		return list(set(A       )       )




def 	UpperCAmelCase     (		A	:						List[str]       ):

		'''simple docstring'''


		_UpperCAmelCase							 =		False
		_UpperCAmelCase							 =		[module_file]
		_UpperCAmelCase							 =		[]

		# Let's recurse through all relative imports
		while not no_change:
				_UpperCAmelCase							 =		[]
				for f in files_to_check:
						new_imports.extend(get_relative_imports(A       )       )

				_UpperCAmelCase							 =		Path(A       ).parent
				_UpperCAmelCase							 =		[str(module_path / m       ) for m in new_imports]
				_UpperCAmelCase							 =		[f for f in new_import_files if f not in all_relative_imports]
				_UpperCAmelCase							 =		[f'{f}.py' for f in new_import_files]

				_UpperCAmelCase							 =		len(A       ) == 0
				all_relative_imports.extend(A       )

		return all_relative_imports




def 	UpperCAmelCase     (		A	:						str       ):

		'''simple docstring'''


		with open(A     ,				'r'     ,				encoding='utf-8'       ) as f:
				_UpperCAmelCase							 =		f.read()

		# Imports of the form `import xxx`
		_UpperCAmelCase							 =		re.findall('^\s*import\s+(\S+)\s*$'     ,				A     ,				flags=re.MULTILINE       )
		# Imports of the form `from xxx import yyy`
		imports += re.findall('^\s*from\s+(\S+)\s+import'     ,				A     ,				flags=re.MULTILINE       )
		# Only keep the top-level module
		_UpperCAmelCase							 =		[imp.split('.'       )[0] for imp in imports if not imp.startswith('.'       )]

		# Unique-ify and test we got them all
		_UpperCAmelCase							 =		list(set(A       )       )
		_UpperCAmelCase							 =		[]
		for imp in imports:
				try:
						importlib.import_module(A       )
				except ImportError:
						missing_packages.append(A       )

		if len(A       ) > 0:
				raise ImportError(
				    'This modeling file requires the following packages that were not found in your environment: '
				    f'{", ".join(A       )}. Run `pip install {" ".join(A       )}`'       )

		return get_relative_imports(A       )




def 	UpperCAmelCase     (		A	:						Dict     ,				A	:						Tuple       ):

		'''simple docstring'''


		_UpperCAmelCase							 =		module_path.replace(os.path.sep     ,				'.'       )
		_UpperCAmelCase							 =		importlib.import_module(A       )

		if class_name is None:
				return find_pipeline_class(A       )
		return getattr(A     ,				A       )




def 	UpperCAmelCase     (		A	:						Tuple       ):

		'''simple docstring'''


		from ..pipelines import DiffusionPipeline

		_UpperCAmelCase							 =		dict(inspect.getmembers(A     ,				inspect.isclass       )       )

		_UpperCAmelCase							 =		None
		for cls_name, cls in cls_members.items():
				if (
				    cls_name != DiffusionPipeline.__name__
				    and issubclass(cls     ,				A       )
				    and cls.__module__.split('.'       )[0] != "diffusers"
				):
						if pipeline_class is not None:
								raise ValueError(
								    f'Multiple classes that inherit from {DiffusionPipeline.__name__} have been found:'
								    f' {pipeline_class.__name__}, and {cls_name}. Please make sure to define only one in'
								    f' {loaded_module}.'       )
						_UpperCAmelCase							 =		cls

		return pipeline_class




def 	UpperCAmelCase     (		A	:						Union[str, os.PathLike]     ,				A	:						str     ,				A	:						Optional[Union[str, os.PathLike]] = None     ,				A	:						bool = False     ,				A	:						bool = False     ,				A	:						Optional[Dict[str, str]] = None     ,				A	:						Optional[Union[bool, str]] = None     ,				A	:						Optional[str] = None     ,				A	:						bool = False     ,				):

		'''simple docstring'''


		_UpperCAmelCase							 =		str(A       )

		_UpperCAmelCase							 =		os.path.join(A     ,				A       )

		if os.path.isfile(A       ):
				_UpperCAmelCase							 =		module_file_or_url
				_UpperCAmelCase							 =		'local'
		elif pretrained_model_name_or_path.count('/'       ) == 0:
				_UpperCAmelCase							 =		get_diffusers_versions()
				# cut ".dev0"
				_UpperCAmelCase							 =		'v' + '.'.join(__version__.split('.'       )[:3]       )

				# retrieve github version that matches
				if revision is None:
						_UpperCAmelCase							 =		latest_version if latest_version[1:] in available_versions else 'main'
						logger.info(f'Defaulting to latest_version: {revision}.'       )
				elif revision in available_versions:
						_UpperCAmelCase							 =		f'v{revision}'
				elif revision == "main":
						_UpperCAmelCase							 =		revision
				else:
						raise ValueError(
						    f'`custom_revision`: {revision} does not exist. Please make sure to choose one of'
						    f' {", ".join(available_versions + ["main"]       )}.'       )

				# community pipeline on GitHub
				_UpperCAmelCase							 =		COMMUNITY_PIPELINES_URL.format(revision=A     ,				pipeline=A       )
				try:
						_UpperCAmelCase							 =		cached_download(
						    A     ,				cache_dir=A     ,				force_download=A     ,				proxies=A     ,				resume_download=A     ,				local_files_only=A     ,				use_auth_token=A     ,				)
						_UpperCAmelCase							 =		'git'
						_UpperCAmelCase							 =		pretrained_model_name_or_path + '.py'
				except EnvironmentError:
						logger.error(f'Could not locate the {module_file} inside {pretrained_model_name_or_path}.'       )
						raise
		else:
				try:
						# Load from URL or cache if already cached
						_UpperCAmelCase							 =		hf_hub_download(
						    A     ,				A     ,				cache_dir=A     ,				force_download=A     ,				proxies=A     ,				resume_download=A     ,				local_files_only=A     ,				use_auth_token=A     ,				)
						_UpperCAmelCase							 =		os.path.join('local'     ,				'--'.join(pretrained_model_name_or_path.split('/'       )       )       )
				except EnvironmentError:
						logger.error(f'Could not locate the {module_file} inside {pretrained_model_name_or_path}.'       )
						raise

    # Check we have all the requirements in our environment
		_UpperCAmelCase							 =		check_imports(A       )

		# Now we move the module inside our cached dynamic modules.
		_UpperCAmelCase							 =		DIFFUSERS_DYNAMIC_MODULE_NAME + os.path.sep + submodule
		create_dynamic_module(A       )
		_UpperCAmelCase							 =		Path(A       ) / full_submodule
		if submodule == "local" or submodule == "git":
				# We always copy local files (we could hash the file to see if there was a change, and give them the name of
				# that hash, to only copy when there is a modification but it seems overkill for now).
				# The only reason we do the copy is to avoid putting too many folders in sys.path.
				shutil.copy(A     ,				submodule_path / module_file       )
				for module_needed in modules_needed:
						_UpperCAmelCase							 =		f'{module_needed}.py'
						shutil.copy(os.path.join(A     ,				A       )     ,				submodule_path / module_needed       )
		else:
				# Get the commit hash
				# TODO: we will get this info in the etag soon, so retrieve it from there and not here.
				if isinstance(A     ,				A       ):
						_UpperCAmelCase							 =		use_auth_token
				elif use_auth_token is True:
						_UpperCAmelCase							 =		HfFolder.get_token()
				else:
						_UpperCAmelCase							 =		None

				_UpperCAmelCase							 =		model_info(A     ,				revision=A     ,				token=A       ).sha

				# The module file will end up being placed in a subfolder with the git hash of the repo. This way we get the
				# benefit of versioning.
				_UpperCAmelCase							 =		submodule_path / commit_hash
				_UpperCAmelCase							 =		full_submodule + os.path.sep + commit_hash
				create_dynamic_module(A       )

				if not (submodule_path / module_file).exists():
						shutil.copy(A     ,				submodule_path / module_file       )
				# Make sure we also have every file with relative
				for module_needed in modules_needed:
						if not (submodule_path / module_needed).exists():
								get_cached_module_file(
								    A     ,				f'{module_needed}.py'     ,				cache_dir=A     ,				force_download=A     ,				resume_download=A     ,				proxies=A     ,				use_auth_token=A     ,				revision=A     ,				local_files_only=A     ,				)
		return os.path.join(A     ,				A       )






def 	UpperCAmelCase     (		A	:						Union[str, os.PathLike]     ,				A	:						str     ,				A	:						Optional[str] = None     ,				A	:						Optional[Union[str, os.PathLike]] = None     ,				A	:						bool = False     ,				A	:						bool = False     ,				A	:						Optional[Dict[str, str]] = None     ,				A	:						Optional[Union[bool, str]] = None     ,				A	:						Optional[str] = None     ,				A	:						bool = False     ,				**A	:						Dict     ,				):

		'''simple docstring'''


		_UpperCAmelCase							 =		get_cached_module_file(
		    A     ,				A     ,				cache_dir=A     ,				force_download=A     ,				resume_download=A     ,				proxies=A     ,				use_auth_token=A     ,				revision=A     ,				local_files_only=A     ,				)
		return get_class_in_module(A     ,				final_module.replace('.py'     ,				''       )       )







"""simple docstring"""





import unittest

from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
@require_sentencepiece
@slow  # see https://github.com/huggingface/transformers/issues/11457
class 			lowercase__			(      A,					unittest.TestCase    ):
							'''simple docstring'''







							_UpperCAmelCase      				=					BarthezTokenizer
							_UpperCAmelCase      				=					BarthezTokenizerFast
							_UpperCAmelCase      				=					True
							_UpperCAmelCase      				=					True






							def        lowerCamelCase_   (  self						)			->							Optional[int]:
									super().setUp()

									_UpperCAmelCase							 =		BarthezTokenizerFast.from_pretrained('moussaKam/mbarthez'						)
									tokenizer.save_pretrained(self.tmpdirname						)
									tokenizer.save_pretrained(self.tmpdirname	,       legacy_format=snake_case						)
									_UpperCAmelCase							 =		tokenizer






							def        lowerCamelCase_   (  self						)			->							Dict:
									_UpperCAmelCase							 =		'<pad>'
									_UpperCAmelCase							 =		1

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






							def        lowerCamelCase_   (  self						)			->							List[str]:
									_UpperCAmelCase							 =		list(self.get_tokenizer().get_vocab().keys()						)

									self.assertEqual(vocab_keys[0]	,       '<s>'						)
									self.assertEqual(vocab_keys[1]	,       '<pad>'						)
									self.assertEqual(vocab_keys[-1]	,       '<mask>'						)
									self.assertEqual(len(snake_case						)	,       101122						)






							def        lowerCamelCase_   (  self						)			->							List[Any]:
									self.assertEqual(self.get_tokenizer().vocab_size	,       101122						)






							@require_torch
							def        lowerCamelCase_   (  self						)			->							List[str]:
									_UpperCAmelCase							 =		['A long paragraph for summarization.', 'Another paragraph for summarization.']
									_UpperCAmelCase							 =		[0, 57, 3018, 70307, 91, 2]

									_UpperCAmelCase							 =		self.tokenizer(
									    snake_case	,       max_length=len(snake_case						)	,       padding=snake_case	,       truncation=snake_case	,       return_tensors='pt'						)
									self.assertIsInstance(snake_case	,       snake_case						)

									self.assertEqual((2, 6)	,       batch.input_ids.shape						)
									self.assertEqual((2, 6)	,       batch.attention_mask.shape						)
									_UpperCAmelCase							 =		batch.input_ids.tolist()[0]
									self.assertListEqual(snake_case	,       snake_case						)






							def        lowerCamelCase_   (  self						)			->							Optional[Any]:
									if not self.test_rust_tokenizer:
											return

									_UpperCAmelCase							 =		self.get_tokenizer()
									_UpperCAmelCase							 =		self.get_rust_tokenizer()

									_UpperCAmelCase							 =		'I was born in 92000, and this is falsé.'

									_UpperCAmelCase							 =		tokenizer.tokenize(snake_case						)
									_UpperCAmelCase							 =		rust_tokenizer.tokenize(snake_case						)
									self.assertListEqual(snake_case	,       snake_case						)

									_UpperCAmelCase							 =		tokenizer.encode(snake_case	,       add_special_tokens=snake_case						)
									_UpperCAmelCase							 =		rust_tokenizer.encode(snake_case	,       add_special_tokens=snake_case						)
									self.assertListEqual(snake_case	,       snake_case						)

									_UpperCAmelCase							 =		self.get_rust_tokenizer()
									_UpperCAmelCase							 =		tokenizer.encode(snake_case						)
									_UpperCAmelCase							 =		rust_tokenizer.encode(snake_case						)
									self.assertListEqual(snake_case	,       snake_case						)






							@slow
							def        lowerCamelCase_   (  self						)			->							Optional[int]:
									# fmt: off
									_UpperCAmelCase							 =		{'input_ids': [[0, 490, 14328, 4507, 354, 47, 43669, 95, 25, 78117, 20215, 19779, 190, 22, 400, 4, 35343, 80310, 603, 86, 24937, 105, 33438, 94762, 196, 39642, 7, 15, 15933, 173, 2, 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, 10534, 87, 25, 66, 3358, 196, 55289, 8, 82961, 81, 2204, 75203, 7, 15, 763, 12956, 216, 178, 14328, 9595, 1377, 69693, 7, 448, 71021, 196, 18106, 1437, 13974, 108, 9083, 4, 49315, 7, 39, 86, 1326, 2793, 46333, 4, 448, 196, 74588, 7, 49315, 7, 39, 21, 822, 38470, 74, 21, 66723, 62480, 8, 22050, 5, 2]], '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, 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, 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, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
									# fmt: on

									# moussaKam/mbarthez is a french model. So we also use french texts.
									_UpperCAmelCase							 =		[
									    '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=snake_case	,       model_name='moussaKam/mbarthez'	,       revision='c2e4ecbca5e3cd2c37fe1ac285ca4fbdf1366fb6'	,       sequences=snake_case	,       )


