

'''simple docstring'''





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





class 		__SCREAMING_SNAKE_CASE       ( lowercase__			):
				lowerCamelCase_							=						['image_processor', 'tokenizer']
				lowerCamelCase_							=						'AutoImageProcessor'
				lowerCamelCase_							=						'AutoTokenizer'







				def __init__(					self    :		Tuple		,				UpperCAmelCase__    :		List[str]		,				UpperCAmelCase__    :		Any      ):
										'''simple docstring'''
										super().__init__(UpperCAmelCase__		,				UpperCAmelCase__      )
										lowercase   :       Optional[Any]								=self.image_processor







				def __call__(					self    :		Optional[Any]		,				UpperCAmelCase__    :		Optional[Any]=None		,				UpperCAmelCase__    :		Tuple=None		,				UpperCAmelCase__    :		List[str]=None		,				**UpperCAmelCase__    :		Any      ):
										'''simple docstring'''

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

										if text is not None:
																lowercase   :       Dict								=self.tokenizer(UpperCAmelCase__		,				return_tensors=UpperCAmelCase__		,				**UpperCAmelCase__      )

										if images is not None:
																lowercase   :       List[Any]								=self.image_processor(UpperCAmelCase__		,				return_tensors=UpperCAmelCase__		,				**UpperCAmelCase__      )

										if text is not None and images is not None:
																lowercase   :       str								=image_features.pixel_values
																return encoding
										elif text is not None:
																return encoding
										else:
																return BatchEncoding(data=dict(**UpperCAmelCase__      )		,				tensor_type=UpperCAmelCase__      )







				def    lowerCamelCase_  (					self    :		Union[str, Any]		,				*UpperCAmelCase__    :		Optional[Any]		,				**UpperCAmelCase__    :		Tuple      ):
										'''simple docstring'''
										return self.tokenizer.batch_decode(*UpperCAmelCase__		,				**UpperCAmelCase__      )







				def    lowerCamelCase_  (					self    :		List[Any]		,				*UpperCAmelCase__    :		Any		,				**UpperCAmelCase__    :		int      ):
										'''simple docstring'''
										return self.tokenizer.decode(*UpperCAmelCase__		,				**UpperCAmelCase__      )







				@property
				def    lowerCamelCase_  (					self    :		Optional[Any]      ):
										'''simple docstring'''
										return ["input_ids", "attention_mask", "pixel_values"]








'''simple docstring'''





import json
import os
import unittest

from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin





class 		__SCREAMING_SNAKE_CASE       ( lowercase__	,       unittest.TestCase			):
				lowerCamelCase_							=						BioGptTokenizer
				lowerCamelCase_							=						False







				def    lowerCamelCase_  (					self    :		Optional[Any]      ):
										'''simple docstring'''
										super().setUp()

										# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
										lowercase   :       List[str]								=[
										    '''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>''',
										    '''<unk>''',
										]
										lowercase   :       Any								=dict(zip(UpperCAmelCase__		,				range(len(UpperCAmelCase__      )      )      )      )
										lowercase   :       Union[str, Any]								=['''l o 123''', '''lo w 1456''', '''e r</w> 1789''', '''''']

										lowercase   :       Optional[int]								=os.path.join(self.tmpdirname		,				VOCAB_FILES_NAMES['''vocab_file''']      )
										lowercase   :       Union[str, Any]								=os.path.join(self.tmpdirname		,				VOCAB_FILES_NAMES['''merges_file''']      )
										with open(self.vocab_file		,				'''w'''      ) as fp:
																fp.write(json.dumps(UpperCAmelCase__      )      )
										with open(self.merges_file		,				'''w'''      ) as fp:
																fp.write('''\n'''.join(UpperCAmelCase__      )      )







				def    lowerCamelCase_  (					self    :		List[Any]		,				UpperCAmelCase__    :		Union[str, Any]      ):
										'''simple docstring'''
										lowercase   :       Dict								='''lower newer'''
										lowercase   :       str								='''lower newer'''
										return input_text, output_text







				def    lowerCamelCase_  (					self    :		List[Any]      ):
										'''simple docstring'''
										lowercase   :       List[Any]								=BioGptTokenizer(self.vocab_file		,				self.merges_file      )

										lowercase   :       Any								='''lower'''
										lowercase   :       int								=['''low''', '''er</w>''']
										lowercase   :       Optional[Any]								=tokenizer.tokenize(UpperCAmelCase__      )
										self.assertListEqual(UpperCAmelCase__		,				UpperCAmelCase__      )

										lowercase   :       Optional[int]								=tokens + ['''<unk>''']
										lowercase   :       Any								=[14, 15, 20]
										self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase__      )		,				UpperCAmelCase__      )







				@slow
				def    lowerCamelCase_  (					self    :		int      ):
										'''simple docstring'''
										lowercase   :       Dict								=BioGptTokenizer.from_pretrained('''microsoft/biogpt'''      )

										lowercase   :       List[str]								=tokenizer.encode('''sequence builders'''		,				add_special_tokens=UpperCAmelCase__      )
										lowercase   :       Optional[int]								=tokenizer.encode('''multi-sequence build'''		,				add_special_tokens=UpperCAmelCase__      )

										lowercase   :       str								=tokenizer.build_inputs_with_special_tokens(UpperCAmelCase__      )
										lowercase   :       Optional[Any]								=tokenizer.build_inputs_with_special_tokens(UpperCAmelCase__		,				UpperCAmelCase__      )

										self.assertTrue(encoded_sentence == [2] + text      )
										self.assertTrue(encoded_pair == [2] + text + [2] + text_a      )





