


from typing import List, Optional, Union

from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType



class 							A   (	UpperCAmelCase__							):
					'''simple docstring'''






					A__      =			['''image_processor''', '''tokenizer''']
					A__      =			'''BlipImageProcessor'''
					A__      =			('''BertTokenizer''', '''BertTokenizerFast''')

					def __init__(self   :						Tuple				, _UpperCAmelCase   :						Any				, _UpperCAmelCase   :						str		)						->       int:




							"""simple docstring"""


							lowercase__					      =		False
							super().__init__(_UpperCAmelCase				, _UpperCAmelCase		)
							lowercase__					      =		self.image_processor

					def __call__(self   :						List[str]				, _UpperCAmelCase   :						ImageInput = None				, _UpperCAmelCase   :						Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None				, _UpperCAmelCase   :						bool = True				, _UpperCAmelCase   :						Union[bool, str, PaddingStrategy] = False				, _UpperCAmelCase   :						Union[bool, str, TruncationStrategy] = None				, _UpperCAmelCase   :						Optional[int] = None				, _UpperCAmelCase   :						int = 0				, _UpperCAmelCase   :						Optional[int] = None				, _UpperCAmelCase   :						Optional[bool] = None				, _UpperCAmelCase   :						bool = False				, _UpperCAmelCase   :						bool = False				, _UpperCAmelCase   :						bool = False				, _UpperCAmelCase   :						bool = False				, _UpperCAmelCase   :						bool = False				, _UpperCAmelCase   :						bool = True				, _UpperCAmelCase   :						Optional[Union[str, TensorType]] = None				, **_UpperCAmelCase   :						List[str]				, )						->       BatchEncoding:




							"""simple docstring"""


							if images is None and text is None:
									raise ValueError("""You have to specify either images or text."""		)

							# Get only text
							if images is None:
									lowercase__					      =		self.tokenizer
									lowercase__					      =		self.tokenizer(
									    text=_UpperCAmelCase				, add_special_tokens=_UpperCAmelCase				, padding=_UpperCAmelCase				, truncation=_UpperCAmelCase				, max_length=_UpperCAmelCase				, stride=_UpperCAmelCase				, pad_to_multiple_of=_UpperCAmelCase				, return_attention_mask=_UpperCAmelCase				, return_overflowing_tokens=_UpperCAmelCase				, return_special_tokens_mask=_UpperCAmelCase				, return_offsets_mapping=_UpperCAmelCase				, return_token_type_ids=_UpperCAmelCase				, return_length=_UpperCAmelCase				, verbose=_UpperCAmelCase				, return_tensors=_UpperCAmelCase				, **_UpperCAmelCase				, )
									return text_encoding

							# add pixel_values
							lowercase__					      =		self.image_processor(_UpperCAmelCase				, return_tensors=_UpperCAmelCase		)

							if text is not None:
									lowercase__					      =		self.tokenizer(
									    text=_UpperCAmelCase				, add_special_tokens=_UpperCAmelCase				, padding=_UpperCAmelCase				, truncation=_UpperCAmelCase				, max_length=_UpperCAmelCase				, stride=_UpperCAmelCase				, pad_to_multiple_of=_UpperCAmelCase				, return_attention_mask=_UpperCAmelCase				, return_overflowing_tokens=_UpperCAmelCase				, return_special_tokens_mask=_UpperCAmelCase				, return_offsets_mapping=_UpperCAmelCase				, return_token_type_ids=_UpperCAmelCase				, return_length=_UpperCAmelCase				, verbose=_UpperCAmelCase				, return_tensors=_UpperCAmelCase				, **_UpperCAmelCase				, )
							else:
									lowercase__					      =		None

							if text_encoding is not None:
									encoding_image_processor.update(_UpperCAmelCase		)

							return encoding_image_processor

					def   lowerCamelCase__					(self   :						Optional[int]				, *_UpperCAmelCase   :						Union[str, Any]				, **_UpperCAmelCase   :						Dict		)						->       List[Any]:




							"""simple docstring"""


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

					def   lowerCamelCase__					(self   :						int				, *_UpperCAmelCase   :						List[Any]				, **_UpperCAmelCase   :						Optional[Any]		)						->       str:




							"""simple docstring"""


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


					@property
					def   lowerCamelCase__					(self   :						int		)						->       Optional[Any]:




							"""simple docstring"""


							lowercase__					      =		self.tokenizer.model_input_names
							lowercase__					      =		self.image_processor.model_input_names
							return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names		)		)





import json
import os
import unittest

from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
class 							A   (	UpperCAmelCase__			,  unittest.TestCase							):
					'''simple docstring'''






					A__      =			OpenAIGPTTokenizer
					A__      =			OpenAIGPTTokenizerFast
					A__      =			True
					A__      =			False

					def   lowerCamelCase__					(self   :						List[str]		)						->       int:




							"""simple docstring"""


							super().setUp()

							# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
							lowercase__					      =		[
							    """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__					      =		dict(zip(_UpperCAmelCase				, range(len(_UpperCAmelCase		)		)		)		)
							lowercase__					      =		["""#version: 0.2""", """l o""", """lo w""", """e r</w>""", """"""]

							lowercase__					      =		os.path.join(self.tmpdirname				, VOCAB_FILES_NAMES["""vocab_file"""]		)
							lowercase__					      =		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   :						Dict				, _UpperCAmelCase   :						List[Any]		)						->       Any:




							"""simple docstring"""


							return "lower newer", "lower newer"

					def   lowerCamelCase__					(self   :						Dict		)						->       Tuple:




							"""simple docstring"""


							lowercase__					      =		OpenAIGPTTokenizer(self.vocab_file				, self.merges_file		)

							lowercase__					      =		"""lower"""
							lowercase__					      =		["""low""", """er</w>"""]
							lowercase__					      =		tokenizer.tokenize(_UpperCAmelCase		)
							self.assertListEqual(_UpperCAmelCase				, _UpperCAmelCase		)

							lowercase__					      =		tokens + ["""<unk>"""]
							lowercase__					      =		[14, 15, 20]
							self.assertListEqual(tokenizer.convert_tokens_to_ids(_UpperCAmelCase		)				, _UpperCAmelCase		)

					def   lowerCamelCase__					(self   :						Optional[int]				, _UpperCAmelCase   :						Union[str, Any]=15		)						->       Optional[int]:




							"""simple docstring"""


							for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
									with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''		):
											lowercase__					      =		self.rust_tokenizer_class.from_pretrained(_UpperCAmelCase				, **_UpperCAmelCase		)

											# Simple input
											lowercase__					      =		"""This is a simple input"""
											lowercase__					      =		["""This is a simple input 1""", """This is a simple input 2"""]
											lowercase__					      =		("""This is a simple input""", """This is a pair""")
											lowercase__					      =		[
											    ("""This is a simple input 1""", """This is a simple input 2"""),
											    ("""This is a simple pair 1""", """This is a simple pair 2"""),
											]

											# Simple input tests
											self.assertRaises(_UpperCAmelCase				, tokenizer_r.encode				, _UpperCAmelCase				, max_length=_UpperCAmelCase				, padding="""max_length"""		)

											# Simple input
											self.assertRaises(_UpperCAmelCase				, tokenizer_r.encode_plus				, _UpperCAmelCase				, max_length=_UpperCAmelCase				, padding="""max_length"""		)

											# Simple input
											self.assertRaises(
											    _UpperCAmelCase				, tokenizer_r.batch_encode_plus				, _UpperCAmelCase				, max_length=_UpperCAmelCase				, padding="""max_length"""				, )

											# Pair input
											self.assertRaises(_UpperCAmelCase				, tokenizer_r.encode				, _UpperCAmelCase				, max_length=_UpperCAmelCase				, padding="""max_length"""		)

											# Pair input
											self.assertRaises(_UpperCAmelCase				, tokenizer_r.encode_plus				, _UpperCAmelCase				, max_length=_UpperCAmelCase				, padding="""max_length"""		)

											# Pair input
											self.assertRaises(
											    _UpperCAmelCase				, tokenizer_r.batch_encode_plus				, _UpperCAmelCase				, max_length=_UpperCAmelCase				, padding="""max_length"""				, )


					def   lowerCamelCase__					(self   :						Tuple		)						->       Any:




							"""simple docstring"""


							pass






@require_ftfy
@require_spacy
@require_tokenizers
class 							A   (	UpperCAmelCase__							):
					'''simple docstring'''






					pass

