






"""simple docstring"""




import os
import unittest

from transformers import LxmertTokenizer, LxmertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class        UpperCamelCase			(	lowerCAmelCase__		,     unittest.TestCase      ):
 UpperCamelCase					:       Any			=					LxmertTokenizer
 UpperCamelCase					:       Optional[int]			=					LxmertTokenizerFast
 UpperCamelCase					:       int			=					True
 UpperCamelCase					:       Dict			=					True


 def _lowercase	(     self		:						Optional[Any]							)					->       Dict:
   super().setUp()

   _a  :       List[str]             =	[
       """[UNK]""",
       """[CLS]""",
       """[SEP]""",
       """want""",
       """##want""",
       """##ed""",
       """wa""",
       """un""",
       """runn""",
       """##ing""",
       """,""",
       """low""",
       """lowest""",
   ]
   _a  :       Tuple             =	os.path.join(self.tmpdirname							,						VOCAB_FILES_NAMES["""vocab_file"""]							)
   with open(self.vocab_file							,						"""w"""							,						encoding="""utf-8"""							) as vocab_writer:
     vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]							)							)


 def _lowercase	(     self		:						int							,						UpperCAmelCase__		:						Tuple							)					->       List[Any]:
   _a  :       Union[str, Any]             =	"""UNwant\u00E9d,running"""
   _a  :       int             =	"""unwanted, running"""
   return input_text, output_text


 def _lowercase	(     self		:						Tuple							)					->       Dict:
   _a  :       Union[str, Any]             =	self.tokenizer_class(self.vocab_file							)

   _a  :       int             =	tokenizer.tokenize("""UNwant\u00E9d,running"""							)
   self.assertListEqual(__a							,						["""un""", """##want""", """##ed""", """,""", """runn""", """##ing"""]							)
   self.assertListEqual(tokenizer.convert_tokens_to_ids(__a							)							,						[7, 4, 5, 10, 8, 9]							)







 def _lowercase	(     self		:						Dict							)					->       Any:
   if not self.test_rust_tokenizer:
     return

   _a  :       Dict             =	self.get_tokenizer()
   _a  :       Tuple             =	self.get_rust_tokenizer()

   _a  :       int             =	"""I was born in 92000, and this is falsé."""

   _a  :       str             =	tokenizer.tokenize(__a							)
   _a  :       Optional[Any]             =	rust_tokenizer.tokenize(__a							)
   self.assertListEqual(__a							,						__a							)

   _a  :       Union[str, Any]             =	tokenizer.encode(__a							,						add_special_tokens=__a							)
   _a  :       Optional[int]             =	rust_tokenizer.encode(__a							,						add_special_tokens=__a							)
   self.assertListEqual(__a							,						__a							)

   _a  :       int             =	self.get_rust_tokenizer()
   _a  :       Union[str, Any]             =	tokenizer.encode(__a							)
   _a  :       Optional[int]             =	rust_tokenizer.encode(__a							)
   self.assertListEqual(__a							,						__a							)





"""simple docstring"""


A     :   int			    =			{
    "Pillow": "Pillow",
    "accelerate": "accelerate>=0.11.0",
    "compel": "compel==0.1.8",
    "black": "black~=23.1",
    "datasets": "datasets",
    "filelock": "filelock",
    "flax": "flax>=0.4.1",
    "hf-doc-builder": "hf-doc-builder>=0.3.0",
    "huggingface-hub": "huggingface-hub>=0.13.2",
    "requests-mock": "requests-mock==1.10.0",
    "importlib_metadata": "importlib_metadata",
    "invisible-watermark": "invisible-watermark",
    "isort": "isort>=5.5.4",
    "jax": "jax>=0.2.8,!=0.3.2",
    "jaxlib": "jaxlib>=0.1.65",
    "Jinja2": "Jinja2",
    "k-diffusion": "k-diffusion>=0.0.12",
    "torchsde": "torchsde",
    "note_seq": "note_seq",
    "librosa": "librosa",
    "numpy": "numpy",
    "omegaconf": "omegaconf",
    "parameterized": "parameterized",
    "protobuf": "protobuf>=3.20.3,<4",
    "pytest": "pytest",
    "pytest-timeout": "pytest-timeout",
    "pytest-xdist": "pytest-xdist",
    "ruff": "ruff>=0.0.241",
    "safetensors": "safetensors",
    "sentencepiece": "sentencepiece>=0.1.91,!=0.1.92",
    "scipy": "scipy",
    "onnx": "onnx",
    "regex": "regex!=2019.12.17",
    "requests": "requests",
    "tensorboard": "tensorboard",
    "torch": "torch>=1.4",
    "torchvision": "torchvision",
    "transformers": "transformers>=4.25.1",
    "urllib3": "urllib3<=2.0.0",
}




