





import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple

from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
					A    :					Tuple =      '''pt'''
elif is_tf_available():
					A    :					Union[str, Any] =      '''tf'''
else:
					A    :					List[str] =      '''jax'''


class   A			(SCREAMING_SNAKE_CASE   ,     unittest.TestCase    ):
			'''simple docstring'''




			__lowerCamelCase	:       Optional[int]							=    PerceiverTokenizer
			__lowerCamelCase	:       Optional[int]							=    False






			def    a_       (			self   :    Optional[int]   )	->	Optional[int]:







					"""simple docstring"""






					super().setUp()
					A__        =   PerceiverTokenizer()
					tokenizer.save_pretrained(self.tmpdirname   )






			@cached_property
			def    a_       (			self   :    Union[str, Any]   )	->	List[str]:







					"""simple docstring"""






					return PerceiverTokenizer.from_pretrained("""deepmind/language-perceiver"""   )






			def    a_       (			self   :    Dict							,	**__lowerCAmelCase   :    Union[str, Any]   )	->	PerceiverTokenizer:







					"""simple docstring"""






					return self.tokenizer_class.from_pretrained(self.tmpdirname							,	**__lowerCAmelCase   )






			def    a_       (			self   :    Union[str, Any]							,	__lowerCAmelCase   :    Union[str, Any]							,	__lowerCAmelCase   :    List[str]=False							,	__lowerCAmelCase   :    Optional[int]=20							,	__lowerCAmelCase   :    Optional[Any]=5   )	->	Tuple[str, list]:







					"""simple docstring"""






					A__        =   []
					for i in range(len(__lowerCAmelCase   )   ):
							try:
									A__        =   tokenizer.decode([i]							,	clean_up_tokenization_spaces=__lowerCAmelCase   )
							except UnicodeDecodeError:
									pass
							toks.append((i, tok)   )

					A__        =   list(filter(lambda __lowerCAmelCase   : re.match(R"""^[ a-zA-Z]+$"""							,	t[1]   )							,	__lowerCAmelCase   )   )
					A__        =   list(filter(lambda __lowerCAmelCase   : [t[0]] == tokenizer.encode(t[1]							,	add_special_tokens=__lowerCAmelCase   )							,	__lowerCAmelCase   )   )
					if max_length is not None and len(__lowerCAmelCase   ) > max_length:
							A__        =   toks[:max_length]
					if min_length is not None and len(__lowerCAmelCase   ) < min_length and len(__lowerCAmelCase   ) > 0:
							while len(__lowerCAmelCase   ) < min_length:
									A__        =   toks + toks
        # toks_str = [t[1] for t in toks]
					A__        =   [t[0] for t in toks]

					# Ensure consistency
					A__        =   tokenizer.decode(__lowerCAmelCase							,	clean_up_tokenization_spaces=__lowerCAmelCase   )
					if " " not in output_txt and len(__lowerCAmelCase   ) > 1:
							A__        =   (
							    tokenizer.decode([toks_ids[0]]							,	clean_up_tokenization_spaces=__lowerCAmelCase   )
							    + """ """
							    + tokenizer.decode(toks_ids[1:]							,	clean_up_tokenization_spaces=__lowerCAmelCase   )
							)
					if with_prefix_space:
							A__        =   """ """ + output_txt
					A__        =   tokenizer.encode(__lowerCAmelCase							,	add_special_tokens=__lowerCAmelCase   )
					return output_txt, output_ids






			def    a_       (			self   :    List[Any]   )	->	List[str]:







					"""simple docstring"""






					A__        =   self.perceiver_tokenizer
					A__        =   """Unicode €."""
					A__        =   tokenizer(__lowerCAmelCase   )
					A__        =   [4, 91, 1_16, 1_11, 1_05, 1_17, 1_06, 1_07, 38, 2_32, 1_36, 1_78, 52, 5]
					self.assertEqual(encoded["""input_ids"""]							,	__lowerCAmelCase   )

					# decoding
					A__        =   tokenizer.decode(__lowerCAmelCase   )
					self.assertEqual(__lowerCAmelCase							,	"""[CLS]Unicode €.[SEP]"""   )

					A__        =   tokenizer("""e è é ê ë"""   )
					A__        =   [4, 1_07, 38, 2_01, 1_74, 38, 2_01, 1_75, 38, 2_01, 1_76, 38, 2_01, 1_77, 5]
					self.assertEqual(encoded["""input_ids"""]							,	__lowerCAmelCase   )
					# decoding
					A__        =   tokenizer.decode(__lowerCAmelCase   )
					self.assertEqual(__lowerCAmelCase							,	"""[CLS]e è é ê ë[SEP]"""   )

					# encode/decode, but with `encode` instead of `__call__`
					self.assertEqual(tokenizer.decode(tokenizer.encode("""e è é ê ë"""   )   )							,	"""[CLS]e è é ê ë[SEP]"""   )






			def    a_       (			self   :    Tuple   )	->	Tuple:







					"""simple docstring"""






					A__        =   self.perceiver_tokenizer
					A__        =   ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
					# fmt: off
					A__        =   [4, 71, 38, 1_14, 1_17, 1_16, 1_09, 38, 1_18, 1_03, 1_20, 1_03, 1_09, 1_20, 1_03, 1_18, 1_10, 38, 1_08, 1_17, 1_20, 38, 1_21, 1_23, 1_15, 1_15, 1_03, 1_20, 1_11, 1_28, 1_03, 1_22, 1_11, 1_17, 1_16, 52, 5, 0]
					# fmt: on
					A__        =   tokenizer(__lowerCAmelCase							,	padding=__lowerCAmelCase							,	return_tensors=__lowerCAmelCase   )
					self.assertIsInstance(__lowerCAmelCase							,	__lowerCAmelCase   )

					if FRAMEWORK != "jax":
							A__        =   list(batch.input_ids.numpy()[0]   )
					else:
							A__        =   list(batch.input_ids.tolist()[0]   )

					self.assertListEqual(__lowerCAmelCase							,	__lowerCAmelCase   )

					self.assertEqual((2, 38)							,	batch.input_ids.shape   )
					self.assertEqual((2, 38)							,	batch.attention_mask.shape   )






			def    a_       (			self   :    Union[str, Any]   )	->	Tuple:







					"""simple docstring"""






					A__        =   self.perceiver_tokenizer
					A__        =   ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
					A__        =   tokenizer(__lowerCAmelCase							,	padding=__lowerCAmelCase							,	return_tensors=__lowerCAmelCase   )
					# check if input_ids are returned and no decoder_input_ids
					self.assertIn("""input_ids"""							,	__lowerCAmelCase   )
					self.assertIn("""attention_mask"""							,	__lowerCAmelCase   )
					self.assertNotIn("""decoder_input_ids"""							,	__lowerCAmelCase   )
					self.assertNotIn("""decoder_attention_mask"""							,	__lowerCAmelCase   )






			def    a_       (			self   :    Optional[Any]   )	->	Optional[Any]:







					"""simple docstring"""






					A__        =   self.perceiver_tokenizer
					A__        =   [
					    """Summary of the text.""",
					    """Another summary.""",
					]
					A__        =   tokenizer(
					    text_target=__lowerCAmelCase							,	max_length=32							,	padding="""max_length"""							,	truncation=__lowerCAmelCase							,	return_tensors=__lowerCAmelCase   )
					self.assertEqual(32							,	targets["""input_ids"""].shape[1]   )






			def    a_       (			self   :    int   )	->	Optional[int]:







					"""simple docstring"""






					A__        =   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__        =   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__        =   tempfile.mkdtemp()

									A__        =   """ He is very happy, UNwant\u00E9d,running"""
									A__        =   tokenizer.encode(__lowerCAmelCase							,	add_special_tokens=__lowerCAmelCase   )
									tokenizer.save_pretrained(__lowerCAmelCase   )

									A__        =   tokenizer.__class__.from_pretrained(__lowerCAmelCase   )
									A__        =   after_tokenizer.encode(__lowerCAmelCase							,	add_special_tokens=__lowerCAmelCase   )
									self.assertListEqual(__lowerCAmelCase							,	__lowerCAmelCase   )

									shutil.rmtree(__lowerCAmelCase   )

					A__        =   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__        =   tempfile.mkdtemp()

									A__        =   """ He is very happy, UNwant\u00E9d,running"""
									tokenizer.add_tokens(["""bim""", """bambam"""]   )
									A__        =   tokenizer.additional_special_tokens
									additional_special_tokens.append("""new_additional_special_token"""   )
									tokenizer.add_special_tokens({"""additional_special_tokens""": additional_special_tokens}   )
									A__        =   tokenizer.encode(__lowerCAmelCase							,	add_special_tokens=__lowerCAmelCase   )
									tokenizer.save_pretrained(__lowerCAmelCase   )

									A__        =   tokenizer.__class__.from_pretrained(__lowerCAmelCase   )
									A__        =   after_tokenizer.encode(__lowerCAmelCase							,	add_special_tokens=__lowerCAmelCase   )
									self.assertListEqual(__lowerCAmelCase							,	__lowerCAmelCase   )
									self.assertIn("""new_additional_special_token"""							,	after_tokenizer.additional_special_tokens   )
									self.assertEqual(after_tokenizer.model_max_length							,	42   )

									A__        =   tokenizer.__class__.from_pretrained(__lowerCAmelCase							,	model_max_length=43   )
									self.assertEqual(tokenizer.model_max_length							,	43   )

									shutil.rmtree(__lowerCAmelCase   )






			def    a_       (			self   :    Optional[int]   )	->	Any:







					"""simple docstring"""






					A__        =   []
					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__        =   json.load(__lowerCAmelCase   )

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

									A__        =   [f'<extra_id_{i}>' for i in range(1_25   )]

									A__        =   added_tokens_extra_ids + [
									    """an_additional_special_token"""
									]
									A__        =   added_tokens_extra_ids + [
									    """an_additional_special_token"""
									]

									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__        =   tokenizer_class.from_pretrained(
									    __lowerCAmelCase							,	)
									self.assertIn(
									    """an_additional_special_token"""							,	tokenizer_without_change_in_init.additional_special_tokens   )
									self.assertEqual(
									    ["""an_additional_special_token"""]							,	tokenizer_without_change_in_init.convert_ids_to_tokens(
									        tokenizer_without_change_in_init.convert_tokens_to_ids(["""an_additional_special_token"""]   )   )							,	)

									# Now we test that we can change the value of additional_special_tokens in the from_pretrained
									A__        =   added_tokens_extra_ids + [AddedToken("""a_new_additional_special_token"""							,	lstrip=__lowerCAmelCase   )]
									A__        =   tokenizer_class.from_pretrained(
									    __lowerCAmelCase							,	additional_special_tokens=__lowerCAmelCase							,	)

									self.assertIn("""a_new_additional_special_token"""							,	tokenizer.additional_special_tokens   )
									self.assertEqual(
									    ["""a_new_additional_special_token"""]							,	tokenizer.convert_ids_to_tokens(
									        tokenizer.convert_tokens_to_ids(["""a_new_additional_special_token"""]   )   )							,	)






			def    a_       (			self   :    int   )	->	int:







					"""simple docstring"""






					A__        =   self.perceiver_tokenizer
					self.assertEqual(tokenizer.decode([1_78]   )							,	"""�"""   )






			def    a_       (			self   :    str   )	->	Optional[Any]:







					"""simple docstring"""






					pass






			def    a_       (			self   :    str   )	->	str:







					"""simple docstring"""






					pass






			def    a_       (			self   :    Tuple   )	->	Tuple:







					"""simple docstring"""






					pass






			def    a_       (			self   :    List[Any]   )	->	str:







					"""simple docstring"""






					pass







			def    a_       (			self   :    Tuple   )	->	str:







					"""simple docstring"""






					A__        =   self.get_tokenizers(fast=__lowerCAmelCase							,	do_lower_case=__lowerCAmelCase   )
					for tokenizer in tokenizers:
							with self.subTest(f'{tokenizer.__class__.__name__}'   ):
									A__        =   ["""[CLS]""", """t""", """h""", """i""", """s""", """ """, """i""", """s""", """ """, """a""", """ """, """t""", """e""", """s""", """t""", """[SEP]"""]
									A__        =   tokenizer.convert_tokens_to_string(__lowerCAmelCase   )

									self.assertIsInstance(__lowerCAmelCase							,	__lowerCAmelCase   )










class   A			(SCREAMING_SNAKE_CASE    ):
			'''simple docstring'''




			pass


class   A			(SCREAMING_SNAKE_CASE    ):
			'''simple docstring'''




			pass


class   A			:
			'''simple docstring'''




			def __init__(			self   :    List[Any]   )	->	str:







					"""simple docstring"""






					A__        =   [
					    [],
					    [],
					    [],
					]






			def    a_       (			self   :    Dict							,	__lowerCAmelCase   :    int							,	__lowerCAmelCase   :    int   )	->	None:







					"""simple docstring"""






					try:
							if len(self.queues[priority]   ) >= 1_00:
									raise OverflowError("""Maximum queue size is 100"""   )
							self.queues[priority].append(__lowerCAmelCase   )
					except IndexError:
							raise ValueError("""Valid priorities are 0, 1, and 2"""   )






			def    a_       (			self   :    Optional[Any]   )	->	int:







					"""simple docstring"""






					for queue in self.queues:
							if queue:
									return queue.pop(0   )
					raise UnderFlowError("""All queues are empty"""   )







			def __str__(			self   :    Tuple   )	->	str:







					"""simple docstring"""






					return "\n".join(f'Priority {i}: {q}' for i, q in enumerate(self.queues   )   )


class   A			:
			'''simple docstring'''




			def __init__(			self   :    int   )	->	str:







					"""simple docstring"""






					A__        =   []






			def    a_       (			self   :    int							,	__lowerCAmelCase   :    int   )	->	None:







					"""simple docstring"""






					if len(self.queue   ) == 1_00:
							raise OverFlowError("""Maximum queue size is 100"""   )
					self.queue.append(__lowerCAmelCase   )






			def    a_       (			self   :    List[str]   )	->	int:







					"""simple docstring"""






					if not self.queue:
							raise UnderFlowError("""The queue is empty"""   )
					else:
							A__        =   min(self.queue   )
							self.queue.remove(__lowerCAmelCase   )
							return data







			def __str__(			self   :    List[Any]   )	->	str:







					"""simple docstring"""






					return str(self.queue   )







def    __lowerCamelCase					(							)		->				Optional[Any]:






		"""simple docstring"""

		A__        =   FixedPriorityQueue()
		fpq.enqueue(0    ,     1_0    )
		fpq.enqueue(1    ,     7_0    )
		fpq.enqueue(0    ,     1_0_0    )
		fpq.enqueue(2    ,     1    )
		fpq.enqueue(2    ,     5    )
		fpq.enqueue(1    ,     7    )
		fpq.enqueue(2    ,     4    )
		fpq.enqueue(1    ,     6_4    )
		fpq.enqueue(0    ,     1_2_8    )
		print(__a    )
		print(fpq.dequeue()    )
		print(fpq.dequeue()    )
		print(fpq.dequeue()    )
		print(fpq.dequeue()    )
		print(fpq.dequeue()    )
		print(__a    )
		print(fpq.dequeue()    )
		print(fpq.dequeue()    )
		print(fpq.dequeue()    )
		print(fpq.dequeue()    )
		print(fpq.dequeue()    )







def    __lowerCamelCase					(							)		->				int:






		"""simple docstring"""

		A__        =   ElementPriorityQueue()
		epq.enqueue(1_0    )
		epq.enqueue(7_0    )
		epq.enqueue(1_0_0    )
		epq.enqueue(1    )
		epq.enqueue(5    )
		epq.enqueue(7    )
		epq.enqueue(4    )
		epq.enqueue(6_4    )
		epq.enqueue(1_2_8    )
		print(__a    )
		print(epq.dequeue()    )
		print(epq.dequeue()    )
		print(epq.dequeue()    )
		print(epq.dequeue()    )
		print(epq.dequeue()    )
		print(__a    )
		print(epq.dequeue()    )
		print(epq.dequeue()    )
		print(epq.dequeue()    )
		print(epq.dequeue()    )
		print(epq.dequeue()    )


if __name__ == "__main__":
					fixed_priority_queue()
					element_priority_queue()



