






"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest

from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin



class      SCREAMING_SNAKE_CASE  (				_SCREAMING_SNAKE_CASE       ,       unittest.TestCase						):





	"""simple docstring"""




	_A       :				Optional[int]    =				CanineTokenizer
	_A       :				Any    =				False





	def    lowerCamelCase(self							):
		super().setUp()
		A_		:						Dict	    =   CanineTokenizer()
		tokenizer.save_pretrained(self.tmpdirname							)





	@cached_property
	def    lowerCamelCase(self							):
		return CanineTokenizer.from_pretrained("""google/canine-s"""							)





	def    lowerCamelCase(self     ,     **lowerCAmelCase_							):
		A_		:						List[Any]	    =   self.tokenizer_class.from_pretrained(self.tmpdirname     ,     **lowerCAmelCase_							)
		A_		:						Tuple	    =   1024
		return tokenizer





	@require_torch
	def    lowerCamelCase(self							):
		A_		:						List[Any]	    =   self.canine_tokenizer
		A_		:						int	    =   ["""Life is like a box of chocolates.""", """You never know what you're gonna get."""]
		# fmt: off
		A_		:						Optional[Any]	    =   [57344, 76, 105, 102, 101, 32, 105, 115, 32, 108, 105, 107, 101, 32, 97, 32, 98, 111, 120, 32, 111, 102, 32, 99, 104, 111, 99, 111, 108, 97, 116, 101, 115, 46, 57345, 0, 0, 0, 0]
		# fmt: on
		A_		:						Optional[Any]	    =   tokenizer(lowerCAmelCase_     ,     padding=lowerCAmelCase_     ,     return_tensors="""pt"""							)
		self.assertIsInstance(lowerCAmelCase_     ,     lowerCAmelCase_							)

		A_		:						Tuple	    =   list(batch.input_ids.numpy()[0]							)

		self.assertListEqual(lowerCAmelCase_     ,     lowerCAmelCase_							)

		self.assertEqual((2, 39)     ,     batch.input_ids.shape							)
		self.assertEqual((2, 39)     ,     batch.attention_mask.shape							)





	@require_torch
	def    lowerCamelCase(self							):
		A_		:						Dict	    =   self.canine_tokenizer
		A_		:						Tuple	    =   ["""Once there was a man.""", """He wrote a test in HuggingFace Tranformers."""]
		A_		:						int	    =   tokenizer(lowerCAmelCase_     ,     padding=lowerCAmelCase_     ,     return_tensors="""pt"""							)
		# check if input_ids, attention_mask and token_type_ids are returned
		self.assertIn("""input_ids"""     ,     lowerCAmelCase_							)
		self.assertIn("""attention_mask"""     ,     lowerCAmelCase_							)
		self.assertIn("""token_type_ids"""     ,     lowerCAmelCase_							)





	@require_torch
	def    lowerCamelCase(self							):
		A_		:						Any	    =   self.canine_tokenizer
		A_		:						int	    =   [
		    """What's the weater?""",
		    """It's about 25 degrees.""",
		]
		A_		:						Tuple	    =   tokenizer(
		    text_target=lowerCAmelCase_     ,     max_length=32     ,     padding="""max_length"""     ,     truncation=lowerCAmelCase_     ,     return_tensors="""pt"""							)
		self.assertEqual(32     ,     targets["""input_ids"""].shape[1]							)





	def    lowerCamelCase(self							):
		# safety check on max_len default value so we are sure the test works
		A_		:						List[Any]	    =   self.get_tokenizers()
		for tokenizer in tokenizers:
			with self.subTest(f"""{tokenizer.__class__.__name__}"""							):
				self.assertNotEqual(tokenizer.model_max_length     ,     42							)

        # Now let's start the test
		A_		:						Any	    =   self.get_tokenizers()
		for tokenizer in tokenizers:
			with self.subTest(f"""{tokenizer.__class__.__name__}"""							):
				# Isolate this from the other tests because we save additional tokens/etc
				A_		:						List[Any]	    =   tempfile.mkdtemp()

				A_		:						List[str]	    =   """ He is very happy, UNwant\u00E9d,running"""
				A_		:						List[str]	    =   tokenizer.encode(lowerCAmelCase_     ,     add_special_tokens=lowerCAmelCase_							)
				tokenizer.save_pretrained(lowerCAmelCase_							)

				A_		:						int	    =   tokenizer.__class__.from_pretrained(lowerCAmelCase_							)
				A_		:						Optional[int]	    =   after_tokenizer.encode(lowerCAmelCase_     ,     add_special_tokens=lowerCAmelCase_							)
				self.assertListEqual(lowerCAmelCase_     ,     lowerCAmelCase_							)

				shutil.rmtree(lowerCAmelCase_							)

		A_		:						Any	    =   self.get_tokenizers(model_max_length=42							)
		for tokenizer in tokenizers:
			with self.subTest(f"""{tokenizer.__class__.__name__}"""							):
				# Isolate this from the other tests because we save additional tokens/etc
				A_		:						Union[str, Any]	    =   tempfile.mkdtemp()

				A_		:						Tuple	    =   """ He is very happy, UNwant\u00E9d,running"""

				A_		:						str	    =   tokenizer.additional_special_tokens

				# We can add a new special token for Canine as follows:
				A_		:						Optional[Any]	    =   chr(0xE007							)
				additional_special_tokens.append(lowerCAmelCase_							)
				tokenizer.add_special_tokens({"""additional_special_tokens""": additional_special_tokens}							)
				A_		:						Union[str, Any]	    =   tokenizer.encode(lowerCAmelCase_     ,     add_special_tokens=lowerCAmelCase_							)
				tokenizer.save_pretrained(lowerCAmelCase_							)

				A_		:						int	    =   tokenizer.__class__.from_pretrained(lowerCAmelCase_							)
				A_		:						Union[str, Any]	    =   after_tokenizer.encode(lowerCAmelCase_     ,     add_special_tokens=lowerCAmelCase_							)
				self.assertListEqual(lowerCAmelCase_     ,     lowerCAmelCase_							)
				self.assertIn(lowerCAmelCase_     ,     after_tokenizer.additional_special_tokens							)
				self.assertEqual(after_tokenizer.model_max_length     ,     42							)

				A_		:						Any	    =   tokenizer.__class__.from_pretrained(lowerCAmelCase_     ,     model_max_length=43							)
				self.assertEqual(tokenizer.model_max_length     ,     43							)

				shutil.rmtree(lowerCAmelCase_							)





	def    lowerCamelCase(self							):
		A_		:						List[str]	    =   self.get_tokenizers(do_lower_case=lowerCAmelCase_							)
		for tokenizer in tokenizers:
			with self.subTest(f"""{tokenizer.__class__.__name__}"""							):
				A_		:						List[str]	    =   self.get_clean_sequence(lowerCAmelCase_							)

				# a special token for Canine can be defined as follows:
				A_		:						List[str]	    =   0xE005
				A_		:						Dict	    =   chr(lowerCAmelCase_							)

				tokenizer.add_special_tokens({"""cls_token""": special_token}							)
				A_		:						List[Any]	    =   tokenizer.encode(lowerCAmelCase_     ,     add_special_tokens=lowerCAmelCase_							)
				self.assertEqual(len(lowerCAmelCase_							)     ,     1							)

				A_		:						str	    =   tokenizer.decode(ids + encoded_special_token     ,     clean_up_tokenization_spaces=lowerCAmelCase_							)
				A_		:						Union[str, Any]	    =   tokenizer.encode(lowerCAmelCase_     ,     add_special_tokens=lowerCAmelCase_							)

				A_		:						str	    =   tokenizer.encode(lowerCAmelCase_     ,     add_special_tokens=lowerCAmelCase_							)
				A_		:						Any	    =   tokenizer.encode(lowerCAmelCase_     ,     add_special_tokens=lowerCAmelCase_							)
				self.assertEqual(lowerCAmelCase_     ,     input_encoded + special_token_id							)

				A_		:						str	    =   tokenizer.decode(lowerCAmelCase_     ,     skip_special_tokens=lowerCAmelCase_							)
				self.assertTrue(special_token not in decoded							)





	def    lowerCamelCase(self							):
		A_		:						Any	    =   self.get_tokenizers(do_lower_case=lowerCAmelCase_							)
		for tokenizer in tokenizers:
			with self.subTest(f"""{tokenizer.__class__.__name__}"""							):
				A_		:						Union[str, Any]	    =   chr(0xE005							)
				A_		:						int	    =   chr(0xE006							)

				# `add_tokens` method stores special tokens only in `tokenizer.unique_no_split_tokens`. (in tokenization_utils.py)
				tokenizer.add_tokens([SPECIAL_TOKEN_1]     ,     special_tokens=lowerCAmelCase_							)
				# `add_special_tokens` method stores special tokens in `tokenizer.additional_special_tokens`,
				# which also occur in `tokenizer.all_special_tokens`. (in tokenization_utils_base.py)
				tokenizer.add_special_tokens({"""additional_special_tokens""": [SPECIAL_TOKEN_2]}							)

				A_		:						Dict	    =   tokenizer.tokenize(lowerCAmelCase_							)
				A_		:						List[str]	    =   tokenizer.tokenize(lowerCAmelCase_							)

				self.assertEqual(len(lowerCAmelCase_							)     ,     1							)
				self.assertEqual(len(lowerCAmelCase_							)     ,     1							)
				self.assertEqual(token_a[0]     ,     lowerCAmelCase_							)
				self.assertEqual(token_a[0]     ,     lowerCAmelCase_							)





	@require_tokenizers
	def    lowerCamelCase(self							):
		A_		:						str	    =   self.get_tokenizers(do_lower_case=lowerCAmelCase_							)
		for tokenizer in tokenizers:
			with self.subTest(f"""{tokenizer.__class__.__name__}"""							):
				# a special token for Canine can be defined as follows:
				A_		:						Tuple	    =   0xE006
				A_		:						int	    =   chr(lowerCAmelCase_							)

				A_		:						str	    =   AddedToken(lowerCAmelCase_     ,     lstrip=lowerCAmelCase_							)
				tokenizer.add_special_tokens({"""additional_special_tokens""": [new_token]}							)

				with tempfile.TemporaryDirectory() as tmp_dir_name:
					tokenizer.save_pretrained(lowerCAmelCase_							)
					tokenizer.from_pretrained(lowerCAmelCase_							)





	def    lowerCamelCase(self							):
		A_		:						Any	    =   []
		if self.test_slow_tokenizer:
			tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())							)

		if self.test_rust_tokenizer:
			tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())							)

		for tokenizer_class, tokenizer_utils in tokenizer_list:
			with tempfile.TemporaryDirectory() as tmp_dir:
				tokenizer_utils.save_pretrained(lowerCAmelCase_							)

				with open(os.path.join(lowerCAmelCase_     ,     """special_tokens_map.json"""							)     ,     encoding="""utf-8"""							) as json_file:
					A_		:						List[Any]	    =   json.load(lowerCAmelCase_							)

				with open(os.path.join(lowerCAmelCase_     ,     """tokenizer_config.json"""							)     ,     encoding="""utf-8"""							) as json_file:
					A_		:						Any	    =   json.load(lowerCAmelCase_							)

				# a special token for Canine can be defined as follows:
				A_		:						str	    =   0xE006
				A_		:						Dict	    =   chr(lowerCAmelCase_							)

				A_		:						Tuple	    =   [new_token_a]
				A_		:						List[Any]	    =   [new_token_a]

				with open(os.path.join(lowerCAmelCase_     ,     """special_tokens_map.json"""							)     ,     """w"""     ,     encoding="""utf-8"""							) as outfile:
					json.dump(lowerCAmelCase_     ,     lowerCAmelCase_							)
				with open(os.path.join(lowerCAmelCase_     ,     """tokenizer_config.json"""							)     ,     """w"""     ,     encoding="""utf-8"""							) as outfile:
					json.dump(lowerCAmelCase_     ,     lowerCAmelCase_							)

				# the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
				# into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
				# "special_tokens_map.json" files
				A_		:						Dict	    =   tokenizer_class.from_pretrained(lowerCAmelCase_     ,     extra_ids=0							)
				self.assertIn(lowerCAmelCase_     ,     tokenizer_without_change_in_init.additional_special_tokens							)
				# self.assertIn("an_additional_special_token",tokenizer_without_change_in_init.get_vocab()) # ByT5Tokenization no vocab
				self.assertEqual(
				    [new_token_a]     ,     tokenizer_without_change_in_init.convert_ids_to_tokens(
				        tokenizer_without_change_in_init.convert_tokens_to_ids([new_token_a]							)							)     ,     )

				A_		:						Union[str, Any]	    =   0xE007
				A_		:						Optional[Any]	    =   chr(lowerCAmelCase_							)
				# Now we test that we can change the value of additional_special_tokens in the from_pretrained
				A_		:						List[str]	    =   [AddedToken(lowerCAmelCase_     ,     lstrip=lowerCAmelCase_							)]
				A_		:						Union[str, Any]	    =   tokenizer_class.from_pretrained(
				    lowerCAmelCase_     ,     additional_special_tokens=lowerCAmelCase_     ,     extra_ids=0							)

				self.assertIn(lowerCAmelCase_     ,     tokenizer.additional_special_tokens							)
				# self.assertIn(new_token_2,tokenizer.get_vocab()) # ByT5Tokenization no vocab
				self.assertEqual(
				    [new_token_a]     ,     tokenizer.convert_ids_to_tokens(tokenizer.convert_tokens_to_ids([new_token_a]							)							)							)





	@require_tokenizers
	def    lowerCamelCase(self							):
		A_		:						List[Any]	    =   self.get_tokenizers(do_lower_case=lowerCAmelCase_							)
		for tokenizer in tokenizers:
			with self.subTest(f"""{tokenizer.__class__.__name__}"""							):
				A_		:						Tuple	    =   """hello world"""
				if self.space_between_special_tokens:
					A_		:						List[str]	    =   """[CLS] hello world [SEP]"""
				else:
					A_		:						int	    =   input
				A_		:						Optional[int]	    =   tokenizer.encode(lowerCAmelCase_     ,     add_special_tokens=lowerCAmelCase_							)
				A_		:						Optional[Any]	    =   tokenizer.decode(lowerCAmelCase_     ,     spaces_between_special_tokens=self.space_between_special_tokens							)
				self.assertIn(lowerCAmelCase_     ,     [output, output.lower()]							)





	def    lowerCamelCase(self							):
		A_		:						Any	    =   self.get_tokenizers()
		for tokenizer in tokenizers:
			with self.subTest(f"""{tokenizer.__class__.__name__}"""							):
				A_		:						List[Any]	    =   [
				    """bos_token""",
				    """eos_token""",
				    """unk_token""",
				    """sep_token""",
				    """pad_token""",
				    """cls_token""",
				    """mask_token""",
				]

		A_		:						Any	    =   """a"""
		A_		:						Union[str, Any]	    =   ord(lowerCAmelCase_							)

		for attr in attributes_list:
			setattr(lowerCAmelCase_     ,     attr + """_id"""     ,     lowerCAmelCase_							)
			self.assertEqual(getattr(lowerCAmelCase_     ,     lowerCAmelCase_							)     ,     lowerCAmelCase_							)
			self.assertEqual(getattr(lowerCAmelCase_     ,     attr + """_id"""							)     ,     lowerCAmelCase_							)

			setattr(lowerCAmelCase_     ,     attr + """_id"""     ,     lowerCAmelCase_							)
			self.assertEqual(getattr(lowerCAmelCase_     ,     lowerCAmelCase_							)     ,     lowerCAmelCase_							)
			self.assertEqual(getattr(lowerCAmelCase_     ,     attr + """_id"""							)     ,     lowerCAmelCase_							)

		setattr(lowerCAmelCase_     ,     """additional_special_tokens_ids"""     ,     []							)
		self.assertListEqual(getattr(lowerCAmelCase_     ,     """additional_special_tokens"""							)     ,     []							)
		self.assertListEqual(getattr(lowerCAmelCase_     ,     """additional_special_tokens_ids"""							)     ,     []							)

		A_		:						Union[str, Any]	    =   0xE006
		A_		:						int	    =   chr(lowerCAmelCase_							)
		setattr(lowerCAmelCase_     ,     """additional_special_tokens_ids"""     ,     [additional_special_token_id]							)
		self.assertListEqual(getattr(lowerCAmelCase_     ,     """additional_special_tokens"""							)     ,     [additional_special_token]							)
		self.assertListEqual(getattr(lowerCAmelCase_     ,     """additional_special_tokens_ids"""							)     ,     [additional_special_token_id]							)





	def    lowerCamelCase(self							):
		pass





	def    lowerCamelCase(self							):
		pass





	def    lowerCamelCase(self							):
		pass





	def    lowerCamelCase(self							):
		pass





	def    lowerCamelCase(self							):
		pass





	def    lowerCamelCase(self							):
		pass





	def    lowerCamelCase(self							):
		pass





	def    lowerCamelCase(self							):
		pass









"""simple docstring"""
_lowerCAmelCase         =							{"a": ["c", "b"], "b": ["d", "e"], "c": [], "d": [], "e": []}
_lowerCAmelCase         =							["a", "b", "c", "d", "e"]






def 			__UpperCamelCase	(		snake_case__   ,   snake_case__   ,   snake_case__					):
	A_		:						int	    =   start
	# add current to visited
	visited.append(snake_case__					)
	A_		:						Any	    =   edges[current]
	for neighbor in neighbors:
		# if neighbor not in visited, visit
		if neighbor not in visited:
			A_		:						Optional[Any]	    =   topological_sort(snake_case__   ,   snake_case__   ,   snake_case__					)
    # if all neighbors visited add current to sort
	sort.append(snake_case__					)
	# if all vertices haven't been visited select a new one to visit
	if len(snake_case__					) != len(snake_case__					):
		for vertice in vertices:
			if vertice not in visited:
				A_		:						Optional[Any]	    =   topological_sort(snake_case__   ,   snake_case__   ,   snake_case__					)
    # return sort
	return sort


if __name__ == "__main__":
							_lowerCAmelCase         =							topological_sort("a", [], [])
							print(sort)

