

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():
				_UpperCAmelCase	:     Any		       = 'pt'
elif is_tf_available():
				_UpperCAmelCase	:     str		       = 'tf'
else:
				_UpperCAmelCase	:     Optional[int]		       = 'jax'







class 				lowercase       ( UpperCamelCase_			,						unittest.TestCase    ):
				__SCREAMING_SNAKE_CASE      :				Optional[Any]     =    PerceiverTokenizer
				__SCREAMING_SNAKE_CASE      :				int     =    False




				def 					a							(      self ):
											super().setUp()
											snake_case_           =					PerceiverTokenizer()
											tokenizer.save_pretrained(self.tmpdirname )




				@cached_property
				def 					a							(      self ):
											return PerceiverTokenizer.from_pretrained('deepmind/language-perceiver' )




				def 					a							(      self   ,     **snake_case ):
											return self.tokenizer_class.from_pretrained(self.tmpdirname   ,     **UpperCamelCase__ )




				def 					a							(      self   ,     snake_case   ,     snake_case=False   ,     snake_case=20   ,     snake_case=5 ):
											snake_case_           =					[]
											for i in range(len(UpperCamelCase__ ) ):
																		try:
																									snake_case_           =					tokenizer.decode([i]   ,     clean_up_tokenization_spaces=UpperCamelCase__ )
																		except UnicodeDecodeError:
																									pass
																		toks.append((i, tok) )

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

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




				def 					a							(      self ):
											snake_case_           =					self.perceiver_tokenizer
											snake_case_           =					'''Unicode €.'''
											snake_case_           =					tokenizer(UpperCamelCase__ )
											snake_case_           =					[4, 91, 116, 111, 105, 117, 106, 107, 38, 232, 136, 178, 52, 5]
											self.assertEqual(encoded['input_ids']   ,     UpperCamelCase__ )

											# decoding
											snake_case_           =					tokenizer.decode(UpperCamelCase__ )
											self.assertEqual(UpperCamelCase__   ,     '[CLS]Unicode €.[SEP]' )

											snake_case_           =					tokenizer('e è é ê ë' )
											snake_case_           =					[4, 107, 38, 201, 174, 38, 201, 175, 38, 201, 176, 38, 201, 177, 5]
											self.assertEqual(encoded['input_ids']   ,     UpperCamelCase__ )
											# decoding
											snake_case_           =					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 					a							(      self ):
											snake_case_           =					self.perceiver_tokenizer
											snake_case_           =					['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
											# fmt: off
											snake_case_           =					[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
											snake_case_           =					tokenizer(UpperCamelCase__   ,     padding=UpperCamelCase__   ,     return_tensors=UpperCamelCase__ )
											self.assertIsInstance(UpperCamelCase__   ,     UpperCamelCase__ )

											if FRAMEWORK != "jax":
																		snake_case_           =					list(batch.input_ids.numpy()[0] )
											else:
																		snake_case_           =					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 					a							(      self ):
											snake_case_           =					self.perceiver_tokenizer
											snake_case_           =					['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
											snake_case_           =					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 					a							(      self ):
											snake_case_           =					self.perceiver_tokenizer
											snake_case_           =					[
											    '''Summary of the text.''',
											    '''Another summary.''',
											]
											snake_case_           =					tokenizer(
											    text_target=UpperCamelCase__   ,     max_length=32   ,     padding='max_length'   ,     truncation=UpperCamelCase__   ,     return_tensors=UpperCamelCase__ )
											self.assertEqual(32   ,     targets['input_ids'].shape[1] )




				def 					a							(      self ):
											snake_case_           =					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
											snake_case_           =					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
																									snake_case_           =					tempfile.mkdtemp()

																									snake_case_           =					''' He is very happy, UNwant\u00E9d,running'''
																									snake_case_           =					tokenizer.encode(UpperCamelCase__   ,     add_special_tokens=UpperCamelCase__ )
																									tokenizer.save_pretrained(UpperCamelCase__ )

																									snake_case_           =					tokenizer.__class__.from_pretrained(UpperCamelCase__ )
																									snake_case_           =					after_tokenizer.encode(UpperCamelCase__   ,     add_special_tokens=UpperCamelCase__ )
																									self.assertListEqual(UpperCamelCase__   ,     UpperCamelCase__ )

																									shutil.rmtree(UpperCamelCase__ )

											snake_case_           =					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
																									snake_case_           =					tempfile.mkdtemp()

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

																									snake_case_           =					tokenizer.__class__.from_pretrained(UpperCamelCase__ )
																									snake_case_           =					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 )

																									snake_case_           =					tokenizer.__class__.from_pretrained(UpperCamelCase__   ,     model_max_length=43 )
																									self.assertEqual(tokenizer.model_max_length   ,     43 )

																									shutil.rmtree(UpperCamelCase__ )




				def 					a							(      self ):
											snake_case_           =					[]
											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:
																																snake_case_           =					json.load(UpperCamelCase__ )

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

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

																									snake_case_           =					added_tokens_extra_ids + [
																									    '''an_additional_special_token'''
																									]
																									snake_case_           =					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
																									snake_case_           =					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
																									snake_case_           =					added_tokens_extra_ids + [AddedToken('a_new_additional_special_token'   ,     lstrip=UpperCamelCase__ )]
																									snake_case_           =					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 					a							(      self ):
											snake_case_           =					self.perceiver_tokenizer
											self.assertEqual(tokenizer.decode([178] )   ,     '�' )




				def 					a							(      self ):
											pass




				def 					a							(      self ):
											pass




				def 					a							(      self ):
											pass




				def 					a							(      self ):
											pass




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

																									self.assertIsInstance(UpperCamelCase__   ,     UpperCamelCase__ )







def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__   ):







							'''simple docstring'''






							snake_case_           =					len(UpperCamelCase__   )
							snake_case_           =					len(UpperCamelCase__   )
							snake_case_           =					(
							    first_str_length if first_str_length > second_str_length else second_str_length
							)
							snake_case_           =					[]
							for char_count in range(UpperCamelCase__   ):
														if char_count < first_str_length:
																					output_list.append(first_str[char_count]   )
														if char_count < second_str_length:
																					output_list.append(second_str[char_count]   )
							return "".join(UpperCamelCase__   )


if __name__ == "__main__":
					print(alternative_string_arrange("""AB""", """XYZ"""), end=""" """)




