


'''simple docstring'''
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():
		__snake_case							   =  '''pt'''
elif is_tf_available():
		__snake_case							   =  '''tf'''
else:
		__snake_case							   =  '''jax'''
class      lowercase			(							A__			,	unittest.TestCase      ):

		"""simple docstring"""

		_a									=       PerceiverTokenizer
		_a									=       False




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							super().setUp()
							UpperCamelCase__     :Any							      =				PerceiverTokenizer()
							tokenizer.save_pretrained(self.tmpdirname							)




		@cached_property
		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


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




		def 					lowerCAmelCase__       (	self					,     **UpperCamelCase_							):

							'''simple docstring'''


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




		def 					lowerCAmelCase__       (	self					,     UpperCamelCase_					,     UpperCamelCase_=False					,     UpperCamelCase_=20					,     UpperCamelCase_=5							):

							'''simple docstring'''


							UpperCamelCase__     :Optional[Any]							      =				[]
							for i in range(len(UpperCamelCase_							)							):
												try:
																	UpperCamelCase__     :Tuple							      =				tokenizer.decode([i]					,     clean_up_tokenization_spaces=UpperCamelCase_							)
												except UnicodeDecodeError:
																	pass
												toks.append((i, tok)							)

							UpperCamelCase__     :Optional[int]							      =				list(filter(lambda UpperCamelCase_							: re.match(r'''^[ a-zA-Z]+$'''					,     t[1]							)					,     UpperCamelCase_							)							)
							UpperCamelCase__     :Optional[Any]							      =				list(filter(lambda UpperCamelCase_							: [t[0]] == tokenizer.encode(t[1]					,     add_special_tokens=UpperCamelCase_							)					,     UpperCamelCase_							)							)
							if max_length is not None and len(UpperCamelCase_							) > max_length:
												UpperCamelCase__     :int							      =				toks[:max_length]
							if min_length is not None and len(UpperCamelCase_							) < min_length and len(UpperCamelCase_							) > 0:
												while len(UpperCamelCase_							) < min_length:
																	UpperCamelCase__     :Optional[int]							      =				toks + toks
        # toks_str = [t[1] for t in toks]
							UpperCamelCase__     :List[str]							      =				[t[0] for t in toks]

							# Ensure consistency
							UpperCamelCase__     :List[str]							      =				tokenizer.decode(UpperCamelCase_					,     clean_up_tokenization_spaces=UpperCamelCase_							)
							if " " not in output_txt and len(UpperCamelCase_							) > 1:
												UpperCamelCase__     :int							      =				(
												    tokenizer.decode([toks_ids[0]]					,     clean_up_tokenization_spaces=UpperCamelCase_							)
												    + ''' '''
												    + tokenizer.decode(toks_ids[1:]					,     clean_up_tokenization_spaces=UpperCamelCase_							)
												)
							if with_prefix_space:
												UpperCamelCase__     :List[Any]							      =				''' ''' + output_txt
							UpperCamelCase__     :Union[str, Any]							      =				tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)
							return output_txt, output_ids




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :int							      =				self.perceiver_tokenizer
							UpperCamelCase__     :int							      =				'''Unicode €.'''
							UpperCamelCase__     :Union[str, Any]							      =				tokenizer(UpperCamelCase_							)
							UpperCamelCase__     :List[str]							      =				[4, 91, 116, 111, 105, 117, 106, 107, 38, 232, 136, 178, 52, 5]
							self.assertEqual(encoded['''input_ids''']					,     UpperCamelCase_							)

							# decoding
							UpperCamelCase__     :Optional[Any]							      =				tokenizer.decode(UpperCamelCase_							)
							self.assertEqual(UpperCamelCase_					,     '''[CLS]Unicode €.[SEP]'''							)

							UpperCamelCase__     :Optional[Any]							      =				tokenizer('''e è é ê ë'''							)
							UpperCamelCase__     :Dict							      =				[4, 107, 38, 201, 174, 38, 201, 175, 38, 201, 176, 38, 201, 177, 5]
							self.assertEqual(encoded['''input_ids''']					,     UpperCamelCase_							)
							# decoding
							UpperCamelCase__     :Tuple							      =				tokenizer.decode(UpperCamelCase_							)
							self.assertEqual(UpperCamelCase_					,     '''[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 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :List[Any]							      =				self.perceiver_tokenizer
							UpperCamelCase__     :Union[str, Any]							      =				['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
							# fmt: off
							UpperCamelCase__     :Tuple							      =				[4, 71, 38, 114, 117, 116, 109, 38, 118, 103, 120, 103, 109, 120, 103, 118, 110, 38, 108, 117, 120, 38, 121, 123, 115, 115, 103, 120, 111, 128, 103, 122, 111, 117, 116, 52, 5, 0]
							# fmt: on
							UpperCamelCase__     :Any							      =				tokenizer(UpperCamelCase_					,     padding=UpperCamelCase_					,     return_tensors=UpperCamelCase_							)
							self.assertIsInstance(UpperCamelCase_					,     UpperCamelCase_							)

							if FRAMEWORK != "jax":
												UpperCamelCase__     :Dict							      =				list(batch.input_ids.numpy()[0]							)
							else:
												UpperCamelCase__     :Optional[Any]							      =				list(batch.input_ids.tolist()[0]							)

							self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)

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




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :int							      =				self.perceiver_tokenizer
							UpperCamelCase__     :List[str]							      =				['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
							UpperCamelCase__     :int							      =				tokenizer(UpperCamelCase_					,     padding=UpperCamelCase_					,     return_tensors=UpperCamelCase_							)
							# check if input_ids are returned and no decoder_input_ids
							self.assertIn('''input_ids'''					,     UpperCamelCase_							)
							self.assertIn('''attention_mask'''					,     UpperCamelCase_							)
							self.assertNotIn('''decoder_input_ids'''					,     UpperCamelCase_							)
							self.assertNotIn('''decoder_attention_mask'''					,     UpperCamelCase_							)




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :Optional[Any]							      =				self.perceiver_tokenizer
							UpperCamelCase__     :Tuple							      =				[
							    '''Summary of the text.''',
							    '''Another summary.''',
							]
							UpperCamelCase__     :Union[str, Any]							      =				tokenizer(
							    text_target=UpperCamelCase_					,     max_length=32					,     padding='''max_length'''					,     truncation=UpperCamelCase_					,     return_tensors=UpperCamelCase_							)
							self.assertEqual(32					,     targets['''input_ids'''].shape[1]							)




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :Optional[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
							UpperCamelCase__     :List[str]							      =				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
																	UpperCamelCase__     :str							      =				tempfile.mkdtemp()

																	UpperCamelCase__     :List[Any]							      =				''' He is very happy, UNwant\u00E9d,running'''
																	UpperCamelCase__     :Any							      =				tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)
																	tokenizer.save_pretrained(UpperCamelCase_							)

																	UpperCamelCase__     :List[str]							      =				tokenizer.__class__.from_pretrained(UpperCamelCase_							)
																	UpperCamelCase__     :int							      =				after_tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)
																	self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)

																	shutil.rmtree(UpperCamelCase_							)

							UpperCamelCase__     :Tuple							      =				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
																	UpperCamelCase__     :Optional[int]							      =				tempfile.mkdtemp()

																	UpperCamelCase__     :Union[str, Any]							      =				''' He is very happy, UNwant\u00E9d,running'''
																	tokenizer.add_tokens(['''bim''', '''bambam''']							)
																	UpperCamelCase__     :str							      =				tokenizer.additional_special_tokens
																	additional_special_tokens.append('''new_additional_special_token'''							)
																	tokenizer.add_special_tokens({'''additional_special_tokens''': additional_special_tokens}							)
																	UpperCamelCase__     :Optional[int]							      =				tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)
																	tokenizer.save_pretrained(UpperCamelCase_							)

																	UpperCamelCase__     :List[Any]							      =				tokenizer.__class__.from_pretrained(UpperCamelCase_							)
																	UpperCamelCase__     :Union[str, Any]							      =				after_tokenizer.encode(UpperCamelCase_					,     add_special_tokens=UpperCamelCase_							)
																	self.assertListEqual(UpperCamelCase_					,     UpperCamelCase_							)
																	self.assertIn('''new_additional_special_token'''					,     after_tokenizer.additional_special_tokens							)
																	self.assertEqual(after_tokenizer.model_max_length					,     42							)

																	UpperCamelCase__     :Union[str, Any]							      =				tokenizer.__class__.from_pretrained(UpperCamelCase_					,     model_max_length=43							)
																	self.assertEqual(tokenizer.model_max_length					,     43							)

																	shutil.rmtree(UpperCamelCase_							)




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :List[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(UpperCamelCase_							)

																	with open(os.path.join(UpperCamelCase_					,     '''special_tokens_map.json'''							)					,     encoding='''utf-8'''							) as json_file:
																						UpperCamelCase__     :str							      =				json.load(UpperCamelCase_							)

																	with open(os.path.join(UpperCamelCase_					,     '''tokenizer_config.json'''							)					,     encoding='''utf-8'''							) as json_file:
																						UpperCamelCase__     :List[Any]							      =				json.load(UpperCamelCase_							)

																	UpperCamelCase__     :Dict							      =				[F'''<extra_id_{i}>''' for i in range(125							)]

																	UpperCamelCase__     :int							      =				added_tokens_extra_ids + [
																	    '''an_additional_special_token'''
																	]
																	UpperCamelCase__     :Union[str, Any]							      =				added_tokens_extra_ids + [
																	    '''an_additional_special_token'''
																	]

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

																	# 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
																	UpperCamelCase__     :Any							      =				tokenizer_class.from_pretrained(
																	    UpperCamelCase_					,     )
																	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
																	UpperCamelCase__     :str							      =				added_tokens_extra_ids + [AddedToken('''a_new_additional_special_token'''					,     lstrip=UpperCamelCase_							)]
																	UpperCamelCase__     :Tuple							      =				tokenizer_class.from_pretrained(
																	    UpperCamelCase_					,     additional_special_tokens=UpperCamelCase_					,     )

																	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 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :Any							      =				self.perceiver_tokenizer
							self.assertEqual(tokenizer.decode([178]							)					,     '''�'''							)




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							pass




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							pass




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							pass




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							pass




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :Any							      =				self.get_tokenizers(fast=UpperCamelCase_					,     do_lower_case=UpperCamelCase_							)
							for tokenizer in tokenizers:
												with self.subTest(F'''{tokenizer.__class__.__name__}'''							):
																	UpperCamelCase__     :Dict							      =				['''[CLS]''', '''t''', '''h''', '''i''', '''s''', ''' ''', '''i''', '''s''', ''' ''', '''a''', ''' ''', '''t''', '''e''', '''s''', '''t''', '''[SEP]''']
																	UpperCamelCase__     :Optional[int]							      =				tokenizer.convert_tokens_to_string(UpperCamelCase_							)

																	self.assertIsInstance(UpperCamelCase_					,     UpperCamelCase_							)



'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


__snake_case							   =  {'''configuration_reformer''': ['''REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ReformerConfig''']}

try:
		if not is_sentencepiece_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__snake_case							   =  ['''ReformerTokenizer''']

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__snake_case							   =  ['''ReformerTokenizerFast''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__snake_case							   =  [
		    '''REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''ReformerAttention''',
		    '''ReformerForMaskedLM''',
		    '''ReformerForQuestionAnswering''',
		    '''ReformerForSequenceClassification''',
		    '''ReformerLayer''',
		    '''ReformerModel''',
		    '''ReformerModelWithLMHead''',
		    '''ReformerPreTrainedModel''',
		]


if TYPE_CHECKING:
		from .configuration_reformer import REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, ReformerConfig

		try:
				if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_reformer import ReformerTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_reformer_fast import ReformerTokenizerFast

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_reformer import (
				    REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ReformerAttention,
				    ReformerForMaskedLM,
				    ReformerForQuestionAnswering,
				    ReformerForSequenceClassification,
				    ReformerLayer,
				    ReformerModel,
				    ReformerModelWithLMHead,
				    ReformerPreTrainedModel,
				)

else:
		import sys

		__snake_case							   =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)