import unittest
from pathlib import Path

from transformers import is_vision_available, load_tool
from transformers.testing_utils import get_tests_dir

from .test_tools_common import ToolTesterMixin


if is_vision_available():
		from PIL import Image




class 					UpperCamelCase	(     unittest.TestCase			,      snake_case__      ):




					def 							UpperCamelCase_						( self :					Any						):


							"""simple docstring"""




							__snake_case		       =     load_tool("image-segmentation"						)
							self.tool.setup()
							__snake_case		       =     load_tool("image-segmentation"      ,remote=_lowerCAmelCase						)




					def 							UpperCamelCase_						( self :					str						):


							"""simple docstring"""




							__snake_case		       =     Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"						)						) / "000000039769.png"						)
							__snake_case		       =     self.tool(_lowerCAmelCase      ,"cat"						)
							self.assertTrue(isinstance(_lowerCAmelCase      ,Image.Image						)						)




					def 							UpperCamelCase_						( self :					Dict						):


							"""simple docstring"""




							__snake_case		       =     Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"						)						) / "000000039769.png"						)
							__snake_case		       =     self.remote_tool(_lowerCAmelCase      ,"cat"						)
							self.assertTrue(isinstance(_lowerCAmelCase      ,Image.Image						)						)




					def 							UpperCamelCase_						( self :					List[Any]						):


							"""simple docstring"""




							__snake_case		       =     Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"						)						) / "000000039769.png"						)
							__snake_case		       =     self.tool(image=_lowerCAmelCase      ,label="cat"						)
							self.assertTrue(isinstance(_lowerCAmelCase      ,Image.Image						)						)







					def 							UpperCamelCase_						( self :					Optional[int]						):


							"""simple docstring"""




							__snake_case		       =     Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"						)						) / "000000039769.png"						)
							__snake_case		       =     self.remote_tool(image=_lowerCAmelCase      ,label="cat"						)
							self.assertTrue(isinstance(_lowerCAmelCase      ,Image.Image						)						)






import os
from shutil import copyfile
from typing import Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
		from .tokenization_reformer import ReformerTokenizer
else:
		lowerCamelCase__           =				None


lowerCamelCase__           =				logging.get_logger(__name__)


lowerCamelCase__           =				'▁'

lowerCamelCase__           =				{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

lowerCamelCase__           =				{
    'vocab_file': {
        'google/reformer-crime-and-punishment': (
            'https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model'
        )
    },
    'tokenizer_file': {
        'google/reformer-crime-and-punishment': (
            'https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/tokenizer.json'
        )
    },
}

lowerCamelCase__           =				{
    'google/reformer-crime-and-punishment': 52_42_88,
}




class 					UpperCamelCase	(     snake_case__      ):
					__UpperCamelCase						=   VOCAB_FILES_NAMES
					__UpperCamelCase						=   PRETRAINED_VOCAB_FILES_MAP
					__UpperCamelCase						=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					__UpperCamelCase						=   ["""input_ids""", """attention_mask"""]
					__UpperCamelCase						=   ReformerTokenizer




					def __init__( self :					Tuple      ,_lowerCAmelCase :					Dict=None      ,_lowerCAmelCase :					Union[str, Any]=None      ,_lowerCAmelCase :					int="</s>"      ,_lowerCAmelCase :					Dict="<unk>"      ,_lowerCAmelCase :					Dict=[]      ,**_lowerCAmelCase :					Optional[Any]      ,):


							"""simple docstring"""




							super().__init__(
							    _lowerCAmelCase      ,tokenizer_file=_lowerCAmelCase      ,eos_token=_lowerCAmelCase      ,unk_token=_lowerCAmelCase      ,additional_special_tokens=_lowerCAmelCase      ,**_lowerCAmelCase      ,)

							__snake_case		       =     vocab_file
							__snake_case		       =     False if not self.vocab_file else True







					def 							UpperCamelCase_						( self :					Dict      ,_lowerCAmelCase :					str      ,_lowerCAmelCase :					Optional[str] = None						):


							"""simple docstring"""




							if not self.can_save_slow_tokenizer:
									raise ValueError(
									    "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
									    "tokenizer."						)

							if not os.path.isdir(_lowerCAmelCase						):
									logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""						)
									return
							__snake_case		       =     os.path.join(
							    _lowerCAmelCase      ,(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]						)

							if os.path.abspath(self.vocab_file						) != os.path.abspath(_lowerCAmelCase						):
									copyfile(self.vocab_file      ,_lowerCAmelCase						)

							return (out_vocab_file,)





