






import json
import os
import unittest

from transformers import HerbertTokenizer, HerbertTokenizerFast
from transformers.models.herbert.tokenization_herbert import VOCAB_FILES_NAMES
from transformers.testing_utils import get_tests_dir, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class 							a_				(		a_			,			unittest.TestCase	):


							'''simple docstring'''






							__a:			Optional[int]									=					HerbertTokenizer
							__a:			Any									=					HerbertTokenizerFast
							__a:			Any									=					True

							def   _lowercase (	self     )      ->      Optional[Any]:
														'''simple docstring'''

														super().setUp()

														# Use a simpler test file without japanese/chinese characters
														with open(f'''{get_tests_dir()}/fixtures/sample_text_no_unicode.txt'''    ,    encoding='utf-8'     ) as f_data:
																					lowerCAmelCase_       		=  f_data.read().replace('\n\n'    ,    '\n'     ).strip()

														lowerCAmelCase_       		=  [
														    '<s>',
														    '</s>',
														    'l',
														    'o',
														    'w',
														    'e',
														    'r',
														    's',
														    't',
														    'i',
														    'd',
														    'n',
														    'w</w>',
														    'r</w>',
														    't</w>',
														    'lo',
														    'low',
														    'er</w>',
														    'low</w>',
														    'lowest</w>',
														    'newer</w>',
														    'wider</w>',
														    ',</w>',
														    '<unk>',
														]
														lowerCAmelCase_       		=  dict(zip(lowercase_    ,    range(len(lowercase_     )     )     )     )
														lowerCAmelCase_       		=  ['l o 123', 'lo w 1456', 'e r</w> 1789', '']

														lowerCAmelCase_       		=  os.path.join(self.tmpdirname    ,    VOCAB_FILES_NAMES['vocab_file']     )
														lowerCAmelCase_       		=  os.path.join(self.tmpdirname    ,    VOCAB_FILES_NAMES['merges_file']     )
														with open(self.vocab_file    ,    'w'     ) as fp:
																					fp.write(json.dumps(lowercase_     )     )
														with open(self.merges_file    ,    'w'     ) as fp:
																					fp.write('\n'.join(lowercase_     )     )

							def   _lowercase (	self    ,    lowercase_     )      ->      Optional[Any]:
														'''simple docstring'''

														lowerCAmelCase_       		=  'lower newer'
														lowerCAmelCase_       		=  'lower newer'
														return input_text, output_text

							def   _lowercase (	self     )      ->      Tuple:
														'''simple docstring'''

														lowerCAmelCase_       		=  self.tokenizer_class(vocab_file=self.vocab_file    ,    merges_file=self.merges_file     )

														lowerCAmelCase_       		=  'lower'
														lowerCAmelCase_       		=  ['low', 'er</w>']
														lowerCAmelCase_       		=  tokenizer.tokenize(lowercase_     )
														self.assertListEqual(lowercase_    ,    lowercase_     )

														lowerCAmelCase_       		=  tokens + ['<unk>']
														lowerCAmelCase_       		=  [1_6, 1_7, 2_3]
														self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase_     )    ,    lowercase_     )

							def   _lowercase (	self     )      ->      Union[str, Any]:
														'''simple docstring'''

														if not self.test_rust_tokenizer:
																					return

														lowerCAmelCase_       		=  self.get_tokenizer()
														lowerCAmelCase_       		=  self.get_rust_tokenizer()

														lowerCAmelCase_       		=  'lower,newer'

														lowerCAmelCase_       		=  tokenizer.tokenize(lowercase_     )
														lowerCAmelCase_       		=  rust_tokenizer.tokenize(lowercase_     )
														self.assertListEqual(lowercase_    ,    lowercase_     )

														lowerCAmelCase_       		=  tokenizer.encode(lowercase_    ,    add_special_tokens=lowercase_     )
														lowerCAmelCase_       		=  rust_tokenizer.encode(lowercase_    ,    add_special_tokens=lowercase_     )
														self.assertListEqual(lowercase_    ,    lowercase_     )

														lowerCAmelCase_       		=  self.get_rust_tokenizer()
														lowerCAmelCase_       		=  tokenizer.encode(lowercase_     )
														lowerCAmelCase_       		=  rust_tokenizer.encode(lowercase_     )
														self.assertListEqual(lowercase_    ,    lowercase_     )






							@slow
							def   _lowercase (	self     )      ->      Optional[int]:
														'''simple docstring'''

														lowerCAmelCase_       		=  self.tokenizer_class.from_pretrained('allegro/herbert-base-cased'     )

														lowerCAmelCase_       		=  tokenizer.encode('konstruowanie sekwencji'    ,    add_special_tokens=lowercase_     )
														lowerCAmelCase_       		=  tokenizer.encode('konstruowanie wielu sekwencji'    ,    add_special_tokens=lowercase_     )

														lowerCAmelCase_       		=  tokenizer.build_inputs_with_special_tokens(lowercase_     )
														lowerCAmelCase_       		=  tokenizer.build_inputs_with_special_tokens(lowercase_    ,    lowercase_     )

														assert encoded_sentence == [0] + text + [2]
														assert encoded_pair == [0] + text + [2] + text_a + [2]














import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding




class 							a_				(		a_	):


							'''simple docstring'''






							__a:			int									=					['''image_processor''', '''tokenizer''']
							__a:			int									=					'''VideoMAEImageProcessor'''
							__a:			Dict									=					('''CLIPTokenizer''', '''CLIPTokenizerFast''')

							def __init__(	self    ,    lowercase_=None    ,    lowercase_=None    ,    **lowercase_     )      ->      Optional[Any]:
														'''simple docstring'''

														lowerCAmelCase_       		=  None
														if "feature_extractor" in kwargs:
																					warnings.warn(
																					    'The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'
																					    ' instead.'    ,    lowercase_    ,    )
																					lowerCAmelCase_       		=  kwargs.pop('feature_extractor'     )

														lowerCAmelCase_       		=  image_processor if image_processor is not None else feature_extractor
														if image_processor is None:
																					raise ValueError('You need to specify an `image_processor`.'     )
														if tokenizer is None:
																					raise ValueError('You need to specify a `tokenizer`.'     )

														super().__init__(lowercase_    ,    lowercase_     )
														lowerCAmelCase_       		=  self.image_processor

							def __call__(	self    ,    lowercase_=None    ,    lowercase_=None    ,    lowercase_=None    ,    **lowercase_     )      ->      Optional[int]:
														'''simple docstring'''

														if text is None and videos is None:
																					raise ValueError('You have to specify either text or videos. Both cannot be none.'     )

														if text is not None:
																					lowerCAmelCase_       		=  self.tokenizer(lowercase_    ,    return_tensors=lowercase_    ,    **lowercase_     )

														if videos is not None:
																					lowerCAmelCase_       		=  self.image_processor(lowercase_    ,    return_tensors=lowercase_    ,    **lowercase_     )

														if text is not None and videos is not None:
																					lowerCAmelCase_       		=  image_features.pixel_values
																					return encoding
														elif text is not None:
																					return encoding
														else:
																					return BatchEncoding(data=dict(**lowercase_     )    ,    tensor_type=lowercase_     )

							def   _lowercase (	self    ,    *lowercase_    ,    **lowercase_     )      ->      Union[str, Any]:
														'''simple docstring'''

														return self.tokenizer.batch_decode(*lowercase_    ,    **lowercase_     )

							def   _lowercase (	self    ,    *lowercase_    ,    **lowercase_     )      ->      str:
														'''simple docstring'''

														return self.tokenizer.decode(*lowercase_    ,    **lowercase_     )

							@property
							def   _lowercase (	self     )      ->      Any:
														'''simple docstring'''

														return ["input_ids", "attention_mask", "position_ids", "pixel_values"]

							@property
							def   _lowercase (	self     )      ->      List[str]:
														'''simple docstring'''

														warnings.warn(
														    '`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'    ,    lowercase_    ,    )
														return self.image_processor_class






							@property
							def   _lowercase (	self     )      ->      int:
														'''simple docstring'''

														warnings.warn(
														    '`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'    ,    lowercase_    ,    )
														return self.image_processor



