
"""simple docstring"""
import warnings
from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class       lowerCAmelCase_		(				_lowerCamelCase ):



							'''simple docstring'''





							_snake_case						      =		['image_processor', 'tokenizer']
							_snake_case						      =		'ViltImageProcessor'
							_snake_case						      =		('BertTokenizer', 'BertTokenizerFast')




							def __init__( self    ,				snake_case_=None    ,				snake_case_=None    ,				**snake_case_				)       ->  int:
													__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."""    ,				__UpperCamelCase    ,				)
																			__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__(__UpperCamelCase    ,				__UpperCamelCase				)
													__lowerCAmelCase     =  self.image_processor




							def __call__( self    ,				snake_case_    ,				snake_case_ = None    ,				snake_case_ = True    ,				snake_case_ = False    ,				snake_case_ = None    ,				snake_case_ = None    ,				snake_case_ = 0    ,				snake_case_ = None    ,				snake_case_ = None    ,				snake_case_ = None    ,				snake_case_ = False    ,				snake_case_ = False    ,				snake_case_ = False    ,				snake_case_ = False    ,				snake_case_ = True    ,				snake_case_ = None    ,				**snake_case_    ,				)       ->  BatchEncoding:
													__lowerCAmelCase     =  self.tokenizer(
													    text=__UpperCamelCase    ,				add_special_tokens=__UpperCamelCase    ,				padding=__UpperCamelCase    ,				truncation=__UpperCamelCase    ,				max_length=__UpperCamelCase    ,				stride=__UpperCamelCase    ,				pad_to_multiple_of=__UpperCamelCase    ,				return_token_type_ids=__UpperCamelCase    ,				return_attention_mask=__UpperCamelCase    ,				return_overflowing_tokens=__UpperCamelCase    ,				return_special_tokens_mask=__UpperCamelCase    ,				return_offsets_mapping=__UpperCamelCase    ,				return_length=__UpperCamelCase    ,				verbose=__UpperCamelCase    ,				return_tensors=__UpperCamelCase    ,				**__UpperCamelCase    ,				)
													# add pixel_values + pixel_mask
													__lowerCAmelCase     =  self.image_processor(__UpperCamelCase    ,				return_tensors=__UpperCamelCase				)
													encoding.update(__UpperCamelCase				)

													return encoding




							def    A__						( self    ,				*snake_case_    ,				**snake_case_				)       ->  Optional[int]:
													return self.tokenizer.batch_decode(*__UpperCamelCase    ,				**__UpperCamelCase				)




							def    A__						( self    ,				*snake_case_    ,				**snake_case_				)       ->  Optional[int]:
													return self.tokenizer.decode(*__UpperCamelCase    ,				**__UpperCamelCase				)




							@property
							def    A__						( self				)       ->  int:
													__lowerCAmelCase     =  self.tokenizer.model_input_names
													__lowerCAmelCase     =  self.image_processor.model_input_names
													return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names				)				)




							@property
							def    A__						( self				)       ->  str:
													warnings.warn(
													    """`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."""    ,				__UpperCamelCase    ,				)
													return self.image_processor_class




							@property
							def    A__						( self				)       ->  List[Any]:
													warnings.warn(
													    """`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead."""    ,				__UpperCamelCase    ,				)
													return self.image_processor





import json
import os
import unittest

from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer

from ...test_tokenization_common import TokenizerTesterMixin



class        lowerCAmelCase__					(  _lowerCamelCase ,				unittest.TestCase       ):
				A_   :     int								=     CTRLTokenizer
				A_   :     List[str]								=     False
				A_   :     str								=     False


				def __UpperCamelCase						(							self      :  Any       )		->     Tuple:
											super().setUp()

											# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
											A      						=    ['adapt', 're@@', 'a@@', 'apt', 'c@@', 't', '<unk>']
											A      						=    dict(zip(__UpperCamelCase						, range(len(__UpperCamelCase       )       )       )       )
											A      						=    ['#version: 0.2', 'a p', 'ap t</w>', 'r e', 'a d', 'ad apt</w>', '']
											A      						=    {'unk_token': '<unk>'}

											A      						=    os.path.join(self.tmpdirname						, VOCAB_FILES_NAMES['vocab_file']       )
											A      						=    os.path.join(self.tmpdirname						, VOCAB_FILES_NAMES['merges_file']       )
											with open(self.vocab_file						, 'w'						, encoding='utf-8'       ) as fp:
																		fp.write(json.dumps(__UpperCamelCase       ) + '\n'       )
											with open(self.merges_file						, 'w'						, encoding='utf-8'       ) as fp:
																		fp.write('\n'.join(__UpperCamelCase       )       )


				def __UpperCamelCase						(							self      :  Optional[Any]						, **__UpperCamelCase      :  List[str]       )		->     List[Any]:
											kwargs.update(self.special_tokens_map       )
											return CTRLTokenizer.from_pretrained(self.tmpdirname						, **__UpperCamelCase       )


				def __UpperCamelCase						(							self      :  int						, __UpperCamelCase      :  Optional[int]       )		->     Optional[Any]:
											A      						=    'adapt react readapt apt'
											A      						=    'adapt react readapt apt'
											return input_text, output_text


				def __UpperCamelCase						(							self      :  List[Any]       )		->     Optional[int]:
											A      						=    CTRLTokenizer(self.vocab_file						, self.merges_file						, **self.special_tokens_map       )
											A      						=    'adapt react readapt apt'
											A      						=    'adapt re@@ a@@ c@@ t re@@ adapt apt'.split()
											A      						=    tokenizer.tokenize(__UpperCamelCase       )
											self.assertListEqual(__UpperCamelCase						, __UpperCamelCase       )

											A      						=    tokens + [tokenizer.unk_token]

											A      						=    [0, 1, 2, 4, 5, 1, 0, 3, 6]
											self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCamelCase       )						, __UpperCamelCase       )