



import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib import Path
from urllib.parse import urlparse
from zipfile import ZipFile, is_zipfile

import cva
import numpy as np
import requests
import wget
from filelock import FileLock
from PIL import Image
from tqdm.auto import tqdm
from yaml import Loader, dump, load


try:
		import torch

		a_			=					True
except ImportError:
		a_			=					False


try:
		from torch.hub import _get_torch_home

		a_			=					_get_torch_home()
except ImportError:
		a_			=					os.path.expanduser(
		    os.getenv("""TORCH_HOME""", os.path.join(os.getenv("""XDG_CACHE_HOME""", """~/.cache"""), """torch"""))
		)

a_			=					os.path.join(torch_cache_home, """transformers""")

a_			=					"""https://cdn.huggingface.co"""
a_			=					"""https://s3.amazonaws.com/models.huggingface.co/bert"""
a_			=					"""/""".join(str(Path(__file__).resolve()).split("""/""")[:-1])
a_			=					os.path.join(PATH, """config.yaml""")
a_			=					os.path.join(PATH, """attributes.txt""")
a_			=					os.path.join(PATH, """objects.txt""")
a_			=					os.getenv("""PYTORCH_PRETRAINED_BERT_CACHE""", default_cache_path)
a_			=					os.getenv("""PYTORCH_TRANSFORMERS_CACHE""", PYTORCH_PRETRAINED_BERT_CACHE)
a_			=					os.getenv("""TRANSFORMERS_CACHE""", PYTORCH_TRANSFORMERS_CACHE)
a_			=					"""pytorch_model.bin"""
a_			=					"""config.yaml"""





def 		a__			(		_UpperCamelCase			: Dict=OBJECTS ,_UpperCamelCase			: Optional[int]=ATTRIBUTES							):
			__lowerCamelCase													=    []
			with open(_snake_case							) as f:
						for object in f.readlines():
									vg_classes.append(object.split(''','''							)[0].lower().strip()							)

			__lowerCamelCase													=    []
			with open(_snake_case							) as f:
						for object in f.readlines():
									vg_attrs.append(object.split(''','''							)[0].lower().strip()							)
			return vg_classes, vg_attrs





def 		a__			(		_UpperCamelCase			: Optional[int]							):
			__lowerCamelCase													=    OrderedDict()
			with open(_snake_case ,'''rb'''							) as f:
						__lowerCamelCase													=    pkl.load(_snake_case							)['''model''']
			for k in copy.deepcopy(list(ckp.keys()							)							):
						__lowerCamelCase													=    ckp.pop(_snake_case							)
						if isinstance(_snake_case ,np.ndarray							):
									__lowerCamelCase													=    torch.tensor(_snake_case							)
						else:
									assert isinstance(_snake_case ,torch.tensor							), type(_snake_case							)
						__lowerCamelCase													=    v
			return r



class  __lowerCAmelCase     :
	lowerCAmelCase__       					=  {}




	def __init__(						self	,				__UpperCAmelCase	,				__UpperCAmelCase = "root"	,				__UpperCAmelCase=0				):



				'''simple docstring'''
				__lowerCamelCase													=    name
				__lowerCamelCase													=    level
				__lowerCamelCase													=    {}
				for k, v in dictionary.items():
							if v is None:
										raise ValueError()
							__lowerCamelCase													=    copy.deepcopy(__UpperCAmelCase				)
							__lowerCamelCase													=    copy.deepcopy(__UpperCAmelCase				)
							if isinstance(__UpperCAmelCase	,				__UpperCAmelCase				):
										__lowerCamelCase													=    Config(__UpperCAmelCase	,				name=__UpperCAmelCase	,				level=level + 1				)
							__lowerCamelCase													=    v
							setattr(self	,				__UpperCAmelCase	,				__UpperCAmelCase				)

				__lowerCamelCase													=    d




	def __repr__(						self				):



				'''simple docstring'''
				return str(list((self._pointer.keys())				)				)




	def __setattr__(						self	,				__UpperCAmelCase	,				__UpperCAmelCase				):



				'''simple docstring'''
				__lowerCamelCase													=    val
				__lowerCamelCase													=    val
				__lowerCamelCase													=    key.split('''.'''				)
				__lowerCamelCase													=    len(__UpperCAmelCase				) - 1
				__lowerCamelCase													=    self._pointer
				if len(__UpperCAmelCase				) > 1:
							for i, l in enumerate(__UpperCAmelCase				):
										if hasattr(self	,				__UpperCAmelCase				) and isinstance(getattr(self	,				__UpperCAmelCase				)	,				__UpperCAmelCase				):
													setattr(getattr(self	,				__UpperCAmelCase				)	,				'''.'''.join(levels[i:]				)	,				__UpperCAmelCase				)
										if l == last_level:
													__lowerCamelCase													=    val
										else:
													__lowerCamelCase													=    pointer[l]




	def        lowerCamelCase      (						self				):



				'''simple docstring'''
				return self._pointer




	def        lowerCamelCase      (						self	,				__UpperCAmelCase	,				__UpperCAmelCase				):



				'''simple docstring'''
				with open(F"""{file_name}"""	,				'''w'''				) as stream:
							dump(__UpperCAmelCase	,				__UpperCAmelCase				)




	def        lowerCamelCase      (						self	,				__UpperCAmelCase	,				__UpperCAmelCase				):



				'''simple docstring'''
				with open(F"""{file_name}"""	,				'''w'''				) as stream:
							json.dump(__UpperCAmelCase	,				__UpperCAmelCase				)




	@staticmethod
	def        lowerCamelCase      (						__UpperCAmelCase				):



				'''simple docstring'''
				with open(__UpperCAmelCase				) as stream:
							__lowerCamelCase													=    load(__UpperCAmelCase	,				Loader=__UpperCAmelCase				)
				return data




	def __str__(						self				):



				'''simple docstring'''
				__lowerCamelCase													=    '''    '''
				if self._name != "root":
							__lowerCamelCase													=    F"""{t * (self._level-1)}{self._name}:\n"""
				else:
							__lowerCamelCase													=    ''''''
				__lowerCamelCase													=    self._level
				for i, (k, v) in enumerate(self._pointer.items()				):
							if isinstance(__UpperCAmelCase	,				__UpperCAmelCase				):
										r += F"""{t * (self._level)}{v}\n"""
										self._level += 1
							else:
										r += F"""{t * (self._level)}{k}: {v} ({type(__UpperCAmelCase				).__name__})\n"""
							__lowerCamelCase													=    level
				return r[:-1]




	@classmethod
	def        lowerCamelCase      (						cls	,				__UpperCAmelCase	,				**__UpperCAmelCase				):



				'''simple docstring'''
				__lowerCamelCase							,__lowerCamelCase													=    cls.get_config_dict(__UpperCAmelCase	,				**__UpperCAmelCase				)
				return cls(__UpperCAmelCase				)




	@classmethod
	def        lowerCamelCase      (						cls	,				__UpperCAmelCase	,				**__UpperCAmelCase				):



				'''simple docstring'''
				__lowerCamelCase													=    kwargs.pop('''cache_dir'''	,				__UpperCAmelCase				)
				__lowerCamelCase													=    kwargs.pop('''force_download'''	,				__UpperCAmelCase				)
				__lowerCamelCase													=    kwargs.pop('''resume_download'''	,				__UpperCAmelCase				)
				__lowerCamelCase													=    kwargs.pop('''proxies'''	,				__UpperCAmelCase				)
				__lowerCamelCase													=    kwargs.pop('''local_files_only'''	,				__UpperCAmelCase				)

				if os.path.isdir(__UpperCAmelCase				):
							__lowerCamelCase													=    os.path.join(__UpperCAmelCase	,				__UpperCAmelCase				)
				elif os.path.isfile(__UpperCAmelCase				) or is_remote_url(__UpperCAmelCase				):
							__lowerCamelCase													=    pretrained_model_name_or_path
				else:
							__lowerCamelCase													=    hf_bucket_url(__UpperCAmelCase	,				filename=__UpperCAmelCase	,				use_cdn=__UpperCAmelCase				)

				try:
							# Load from URL or cache if already cached
							__lowerCamelCase													=    cached_path(
							    __UpperCAmelCase	,				cache_dir=__UpperCAmelCase	,				force_download=__UpperCAmelCase	,				proxies=__UpperCAmelCase	,				resume_download=__UpperCAmelCase	,				local_files_only=__UpperCAmelCase	,				)
							# Load config dict
							if resolved_config_file is None:
										raise EnvironmentError

							__lowerCamelCase													=    Config.load_yaml(__UpperCAmelCase				)

				except EnvironmentError:
							__lowerCamelCase													=    '''Can\'t load config for'''
							raise EnvironmentError(__UpperCAmelCase				)

				if resolved_config_file == config_file:
							print('''loading configuration file from path'''				)
				else:
							print('''loading configuration file cache'''				)

				return Config.load_yaml(__UpperCAmelCase				), kwargs





def 		a__			(		_UpperCamelCase			: Dict							):
			__lowerCamelCase													=    torch.load('''dump.pt''' ,map_location=in_tensor.device							)
			__lowerCamelCase													=    in_tensor.numpy()
			__lowerCamelCase													=    out_tensor.numpy()[0]
			print(na.shape ,na[0, 0, :5]							)
			print(na.shape ,na[0, 0, :5]							)
			assert np.allclose(_snake_case ,_snake_case ,rtol=0.01 ,atol=0.1							), (
			    F"""{sum([1 for x in np.isclose(_snake_case ,_snake_case ,rtol=0.01 ,atol=0.1							).flatten() if x is False]							)/len(na.flatten()							)*1_00:.4f} %"""
			    " element-wise mismatch"
			)
			raise Exception('''tensors are all good'''							)

			# Hugging face functions below





def 		a__			(		_UpperCamelCase			: Optional[Any]							):
			__lowerCamelCase													=    urlparse(_snake_case							)
			return parsed.scheme in ("http", "https")





def 		a__			(		_UpperCamelCase			: int ,_UpperCamelCase			: List[str] ,_UpperCamelCase			: List[Any]=True							):
			__lowerCamelCase													=    CLOUDFRONT_DISTRIB_PREFIX if use_cdn else S3_BUCKET_PREFIX
			__lowerCamelCase													=    '''/''' not in model_id
			if legacy_format:
						return F"""{endpoint}/{model_id}-{filename}"""
			else:
						return F"""{endpoint}/{model_id}/{filename}"""





def 		a__			(		_UpperCamelCase			: str ,_UpperCamelCase			: Dict ,_UpperCamelCase			: Optional[Any]=None ,_UpperCamelCase			: Optional[Any]=0 ,_UpperCamelCase			: str=None ,):
			__lowerCamelCase													=    '''python/{}'''.format(sys.version.split()[0]							)
			if _torch_available:
						ua += "; torch/{}".format(torch.__version__							)
			if isinstance(_snake_case ,_snake_case							):
						ua += "; " + "; ".join('''{}/{}'''.format(_snake_case ,_snake_case							) for k, v in user_agent.items()							)
			elif isinstance(_snake_case ,_snake_case							):
						ua += "; " + user_agent
			__lowerCamelCase													=    {'''user-agent''': ua}
			if resume_size > 0:
						__lowerCamelCase													=    '''bytes=%d-''' % (resume_size,)
			__lowerCamelCase													=    requests.get(_snake_case ,stream=_snake_case ,proxies=_snake_case ,headers=_snake_case							)
			if response.status_code == 4_16:  # Range not satisfiable
						return
			__lowerCamelCase													=    response.headers.get('''Content-Length'''							)
			__lowerCamelCase													=    resume_size + int(_snake_case							) if content_length is not None else None
			__lowerCamelCase													=    tqdm(
			    unit='''B''' ,unit_scale=_snake_case ,total=_snake_case ,initial=_snake_case ,desc='''Downloading''' ,)
			for chunk in response.iter_content(chunk_size=10_24							):
						if chunk:  # filter out keep-alive new chunks
									progress.update(len(_snake_case							)							)
									temp_file.write(_snake_case							)
			progress.close()





def 		a__			(		_UpperCamelCase			: int ,_UpperCamelCase			: Tuple=None ,_UpperCamelCase			: Union[str, Any]=False ,_UpperCamelCase			: List[Any]=None ,_UpperCamelCase			: str=10 ,_UpperCamelCase			: List[Any]=False ,_UpperCamelCase			: str=None ,_UpperCamelCase			: int=False ,):






			if cache_dir is None:
						__lowerCamelCase													=    TRANSFORMERS_CACHE
			if isinstance(_snake_case ,_snake_case							):
						__lowerCamelCase													=    str(_snake_case							)

			os.makedirs(_snake_case ,exist_ok=_snake_case							)

			__lowerCamelCase													=    None
			if not local_files_only:
						try:
									__lowerCamelCase													=    requests.head(_snake_case ,allow_redirects=_snake_case ,proxies=_snake_case ,timeout=_snake_case							)
									if response.status_code == 2_00:
												__lowerCamelCase													=    response.headers.get('''ETag'''							)
						except (EnvironmentError, requests.exceptions.Timeout):
									# etag is already None
									pass

			__lowerCamelCase													=    url_to_filename(_snake_case ,_snake_case							)

			# get cache path to put the file
			__lowerCamelCase													=    os.path.join(_snake_case ,_snake_case							)

			# etag is None = we don't have a connection, or url doesn't exist, or is otherwise inaccessible.
			# try to get the last downloaded one
			if etag is None:
						if os.path.exists(_snake_case							):
									return cache_path
						else:
									__lowerCamelCase													=    [
									    file
									    for file in fnmatch.filter(os.listdir(_snake_case							) ,filename + '''.*'''							)
									    if not file.endswith('''.json'''							) and not file.endswith('''.lock'''							)
									]
									if len(_snake_case							) > 0:
												return os.path.join(_snake_case ,matching_files[-1]							)
									else:
												# If files cannot be found and local_files_only=True,
												# the models might've been found if local_files_only=False
												# Notify the user about that
												if local_files_only:
															raise ValueError(
															    '''Cannot find the requested files in the cached path and outgoing traffic has been'''
															    ''' disabled. To enable model look-ups and downloads online, set \'local_files_only\''''
															    ''' to False.'''							)
												return None

    # From now on, etag is not None.
			if os.path.exists(_snake_case							) and not force_download:
						return cache_path

			# Prevent parallel downloads of the same file with a lock.
			__lowerCamelCase													=    cache_path + '''.lock'''
			with FileLock(_snake_case							):
						# If the download just completed while the lock was activated.
						if os.path.exists(_snake_case							) and not force_download:
									# Even if returning early like here, the lock will be released.
									return cache_path

						if resume_download:
									__lowerCamelCase													=    cache_path + '''.incomplete'''

									@contextmanager
									def _resumable_file_manager():
												with open(_snake_case ,'''a+b'''							) as f:
															yield f

									__lowerCamelCase													=    _resumable_file_manager
									if os.path.exists(_snake_case							):
												__lowerCamelCase													=    os.stat(_snake_case							).st_size
									else:
												__lowerCamelCase													=    0
						else:
									__lowerCamelCase													=    partial(tempfile.NamedTemporaryFile ,dir=_snake_case ,delete=_snake_case							)
									__lowerCamelCase													=    0

						# Download to temporary file, then copy to cache dir once finished.
						# Otherwise you get corrupt cache entries if the download gets interrupted.
						with temp_file_manager() as temp_file:
									print(
									    '''%s not found in cache or force_download set to True, downloading to %s''' ,_snake_case ,temp_file.name ,)

									http_get(
									    _snake_case ,_snake_case ,proxies=_snake_case ,resume_size=_snake_case ,user_agent=_snake_case ,)

						os.replace(temp_file.name ,_snake_case							)

						__lowerCamelCase													=    {'''url''': url, '''etag''': etag}
						__lowerCamelCase													=    cache_path + '''.json'''
						with open(_snake_case ,'''w'''							) as meta_file:
									json.dump(_snake_case ,_snake_case							)

			return cache_path





def 		a__			(		_UpperCamelCase			: List[Any] ,_UpperCamelCase			: List[str]=None							):
			__lowerCamelCase													=    url.encode('''utf-8'''							)
			__lowerCamelCase													=    shaaaa(_snake_case							)
			__lowerCamelCase													=    url_hash.hexdigest()

			if etag:
						__lowerCamelCase													=    etag.encode('''utf-8'''							)
						__lowerCamelCase													=    shaaaa(_snake_case							)
						filename += "." + etag_hash.hexdigest()

			if url.endswith('''.h5'''							):
						filename += ".h5"

			return filename





def 		a__			(		_UpperCamelCase			: Optional[Any] ,_UpperCamelCase			: int=None ,_UpperCamelCase			: Optional[Any]=False ,_UpperCamelCase			: int=None ,_UpperCamelCase			: Any=False ,_UpperCamelCase			: Any=None ,_UpperCamelCase			: List[str]=False ,_UpperCamelCase			: List[Any]=False ,_UpperCamelCase			: Any=False ,):






			if cache_dir is None:
						__lowerCamelCase													=    TRANSFORMERS_CACHE
			if isinstance(_snake_case ,_snake_case							):
						__lowerCamelCase													=    str(_snake_case							)
			if isinstance(_snake_case ,_snake_case							):
						__lowerCamelCase													=    str(_snake_case							)

			if is_remote_url(_snake_case							):
						# URL, so get it from the cache (downloading if necessary)
						__lowerCamelCase													=    get_from_cache(
						    _snake_case ,cache_dir=_snake_case ,force_download=_snake_case ,proxies=_snake_case ,resume_download=_snake_case ,user_agent=_snake_case ,local_files_only=_snake_case ,)
			elif os.path.exists(_snake_case							):
						# File, and it exists.
						__lowerCamelCase													=    url_or_filename
			elif urlparse(_snake_case							).scheme == "":
						# File, but it doesn't exist.
						raise EnvironmentError('''file {} not found'''.format(_snake_case							)							)
			else:
						# Something unknown
						raise ValueError('''unable to parse {} as a URL or as a local path'''.format(_snake_case							)							)

			if extract_compressed_file:
						if not is_zipfile(_snake_case							) and not tarfile.is_tarfile(_snake_case							):
									return output_path

						# Path where we extract compressed archives
						# We avoid '.' in dir name and add "-extracted" at the end: "./model.zip" => "./model-zip-extracted/"
						__lowerCamelCase							,__lowerCamelCase													=    os.path.split(_snake_case							)
						__lowerCamelCase													=    output_file.replace('''.''' ,'''-'''							) + '''-extracted'''
						__lowerCamelCase													=    os.path.join(_snake_case ,_snake_case							)

						if os.path.isdir(_snake_case							) and os.listdir(_snake_case							) and not force_extract:
									return output_path_extracted

						# Prevent parallel extractions
						__lowerCamelCase													=    output_path + '''.lock'''
						with FileLock(_snake_case							):
									shutil.rmtree(_snake_case ,ignore_errors=_snake_case							)
									os.makedirs(_snake_case							)
									if is_zipfile(_snake_case							):
												with ZipFile(_snake_case ,'''r'''							) as zip_file:
															zip_file.extractall(_snake_case							)
															zip_file.close()
									elif tarfile.is_tarfile(_snake_case							):
												__lowerCamelCase													=    tarfile.open(_snake_case							)
												tar_file.extractall(_snake_case							)
												tar_file.close()
									else:
												raise EnvironmentError('''Archive format of {} could not be identified'''.format(_snake_case							)							)

						return output_path_extracted

			return output_path





def 		a__			(		_UpperCamelCase			: Any ,_UpperCamelCase			: int=","							):
			assert isinstance(_snake_case ,_snake_case							)
			if os.path.isfile(_snake_case							):
						with open(_snake_case							) as f:
									__lowerCamelCase													=    eval(f.read()							)
			else:
						__lowerCamelCase													=    requests.get(_snake_case							)
						try:
									__lowerCamelCase													=    requests.json()
						except Exception:
									__lowerCamelCase													=    req.content.decode()
									assert data is not None, "could not connect"
									try:
												__lowerCamelCase													=    eval(_snake_case							)
									except Exception:
												__lowerCamelCase													=    data.split('''\n'''							)
						req.close()
			return data





def 		a__			(		_UpperCamelCase			: List[Any]							):
			__lowerCamelCase													=    requests.get(_snake_case							)
			__lowerCamelCase													=    np.array(Image.open(BytesIO(response.content							)							)							)
			return img





def 		a__			(		_UpperCamelCase			: Any							):
			__lowerCamelCase													=    url.split('''/'''							)[-1]
			if fn not in os.listdir(os.getcwd()							):
						wget.download(_snake_case							)
			with open(_snake_case ,'''rb'''							) as stream:
						__lowerCamelCase													=    pkl.load(_snake_case							)
			__lowerCamelCase													=    weights.pop('''model'''							)
			__lowerCamelCase													=    {}
			for k, v in model.items():
						__lowerCamelCase													=    torch.from_numpy(_snake_case							)
						if "running_var" in k:
									__lowerCamelCase													=    torch.tensor([0]							)
									__lowerCamelCase													=    k.replace('''running_var''' ,'''num_batches_tracked'''							)
									__lowerCamelCase													=    zero
			return new





def 		a__			(		):
			print(F"""{os.path.abspath(os.path.join(_snake_case ,os.pardir							)							)}/demo.ipynb"""							)





def 		a__			(		_UpperCamelCase			: List[Any] ,_UpperCamelCase			: str="RGB"							):
			assert isinstance(_snake_case ,_snake_case							)
			if os.path.isfile(_snake_case							):
						__lowerCamelCase													=    cva.imread(_snake_case							)
			else:
						__lowerCamelCase													=    get_image_from_url(_snake_case							)
						assert img is not None, F"""could not connect to: {im}"""
			__lowerCamelCase													=    cva.cvtColor(_snake_case ,cva.COLOR_BGR2RGB							)
			if input_format == "RGB":
						__lowerCamelCase													=    img[:, :, ::-1]
			return img





def 		a__			(		_UpperCamelCase			: List[Any] ,_UpperCamelCase			: Tuple=1							):
			return (images[i : i + batch] for i in range(0 ,len(_snake_case							) ,_snake_case							))











import unittest

from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin



@require_rjieba
@require_tokenizers
class  __lowerCAmelCase     (	lowerCAmelCase__  ,	unittest.TestCase   ):
 lowerCAmelCase__       					=  RoFormerTokenizer
 lowerCAmelCase__       					=  RoFormerTokenizerFast
 lowerCAmelCase__       					=  True
 lowerCAmelCase__       					=  True




 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    super().setUp()




 def        lowerCamelCase      (						self	,				**__UpperCAmelCase				):



    '''simple docstring'''
    return self.tokenizer_class.from_pretrained('''junnyu/roformer_chinese_base'''	,				**__UpperCAmelCase				)




 def        lowerCamelCase      (						self	,				**__UpperCAmelCase				):



    '''simple docstring'''
    return self.rust_tokenizer_class.from_pretrained('''junnyu/roformer_chinese_base'''	,				**__UpperCAmelCase				)




 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    __lowerCamelCase													=    '''永和服装饰品有限公司,今天天气非常好'''
    __lowerCamelCase													=    '''永和 服装 饰品 有限公司 , 今 天 天 气 非常 好'''
    return input_text, output_text




 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    __lowerCamelCase													=    self.get_tokenizer()
    __lowerCamelCase							,__lowerCamelCase													=    self.get_chinese_input_output_texts()
    __lowerCamelCase													=    tokenizer.tokenize(__UpperCAmelCase				)

    self.assertListEqual(__UpperCAmelCase	,				output_text.split()				)

    __lowerCamelCase													=    tokens + [tokenizer.unk_token]
    __lowerCamelCase													=    [22943, 21332, 34431, 45904, 117, 306, 1231, 1231, 2653, 33994, 1266, 100]
    self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCAmelCase				)	,				__UpperCAmelCase				)




 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    __lowerCamelCase													=    self.get_rust_tokenizer()
    __lowerCamelCase							,__lowerCamelCase													=    self.get_chinese_input_output_texts()
    __lowerCamelCase													=    tokenizer.tokenize(__UpperCAmelCase				)
    self.assertListEqual(__UpperCAmelCase	,				output_text.split()				)
    __lowerCamelCase													=    tokens + [tokenizer.unk_token]
    __lowerCamelCase													=    [22943, 21332, 34431, 45904, 117, 306, 1231, 1231, 2653, 33994, 1266, 100]
    self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCAmelCase				)	,				__UpperCAmelCase				)




 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    pass




 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    pass




 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    pass






