


"""simple docstring"""







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  UpperCamelCase_	( UpperCamelCase):

	"""simple docstring"""





	snake_case__				:  List[str]    					=			["image_processor", "tokenizer"]
	snake_case__				:  Any    					=			"BlipImageProcessor"
	snake_case__				:  Any    					=			("BertTokenizer", "BertTokenizerFast")




	def __init__( self			:				str			,			UpperCAmelCase__			:				Dict			,			UpperCAmelCase__			:				Any   )       ->	Any:
						__SCREAMING_SNAKE_CASE						   =				False
						super().__init__(UpperCAmelCase__			,			UpperCAmelCase__   )
						__SCREAMING_SNAKE_CASE						   =				self.image_processor




	def __call__( self			:				Union[str, Any]			,			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__			:				Union[str, Any]			,			)       ->	BatchEncoding:
						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:
											__SCREAMING_SNAKE_CASE						   =				self.tokenizer
											__SCREAMING_SNAKE_CASE						   =				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
						__SCREAMING_SNAKE_CASE						   =				self.image_processor(UpperCAmelCase__			,			return_tensors=UpperCAmelCase__   )

						if text is not None:
											__SCREAMING_SNAKE_CASE						   =				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:
											__SCREAMING_SNAKE_CASE						   =				None

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

						return encoding_image_processor




	def   UpperCAmelCase_      ( self			:				str			,			*UpperCAmelCase__			:				str			,			**UpperCAmelCase__			:				List[Any]   )       ->	List[str]:
						return self.tokenizer.batch_decode(*UpperCAmelCase__			,			**UpperCAmelCase__   )




	def   UpperCAmelCase_      ( self			:				str			,			*UpperCAmelCase__			:				Tuple			,			**UpperCAmelCase__			:				Tuple   )       ->	List[str]:
						return self.tokenizer.decode(*UpperCAmelCase__			,			**UpperCAmelCase__   )




	@property
	def   UpperCAmelCase_      ( self			:				Dict   )       ->	Union[str, Any]:
						__SCREAMING_SNAKE_CASE						   =				self.tokenizer.model_input_names
						__SCREAMING_SNAKE_CASE						   =				self.image_processor.model_input_names
						return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names   )   )




"""simple docstring"""







import pytest

from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs




@pytest.mark.parametrize(
    "kwargs, expected"  ,						[
        ({"num_shards": 0, "max_num_jobs": 1}, []),
        ({"num_shards": 10, "max_num_jobs": 1}, [range(10   )]),
        ({"num_shards": 10, "max_num_jobs": 10}, [range(lowerCAmelCase_  ,						i + 1   ) for i in range(10   )]),
        ({"num_shards": 1, "max_num_jobs": 10}, [range(1   )]),
        ({"num_shards": 10, "max_num_jobs": 3}, [range(0  ,						4   ), range(4  ,						7   ), range(7  ,						10   )]),
        ({"num_shards": 3, "max_num_jobs": 10}, [range(0  ,						1   ), range(1  ,						2   ), range(2  ,						3   )]),
    ]  ,						)
def    UpperCAmelCase__       (lowerCAmelCase_  ,						lowerCAmelCase_   ):




					'''simple docstring'''


					__SCREAMING_SNAKE_CASE						   =				_distribute_shards(**lowerCAmelCase_   )
					assert out == expected




@pytest.mark.parametrize(
    "gen_kwargs, max_num_jobs, expected"  ,						[
        ({"foo": 0}, 10, [{"foo": 0}]),
        ({"shards": [0, 1, 2, 3]}, 1, [{"shards": [0, 1, 2, 3]}]),
        ({"shards": [0, 1, 2, 3]}, 4, [{"shards": [0]}, {"shards": [1]}, {"shards": [2]}, {"shards": [3]}]),
        ({"shards": [0, 1]}, 4, [{"shards": [0]}, {"shards": [1]}]),
        ({"shards": [0, 1, 2, 3]}, 2, [{"shards": [0, 1]}, {"shards": [2, 3]}]),
    ]  ,						)
def    UpperCAmelCase__       (lowerCAmelCase_  ,						lowerCAmelCase_  ,						lowerCAmelCase_   ):




					'''simple docstring'''


					__SCREAMING_SNAKE_CASE						   =				_split_gen_kwargs(lowerCAmelCase_  ,						lowerCAmelCase_   )
					assert out == expected




@pytest.mark.parametrize(
    "gen_kwargs, expected"  ,						[
        ({"foo": 0}, 1),
        ({"shards": [0]}, 1),
        ({"shards": [0, 1, 2, 3]}, 4),
        ({"shards": [0, 1, 2, 3], "foo": 0}, 4),
        ({"shards": [0, 1, 2, 3], "other": (0, 1)}, 4),
        ({"shards": [0, 1, 2, 3], "shards2": [0, 1]}, RuntimeError),
    ]  ,						)
def    UpperCAmelCase__       (lowerCAmelCase_  ,						lowerCAmelCase_   ):




					'''simple docstring'''


					if expected is RuntimeError:
										with pytest.raises(lowerCAmelCase_   ):
															_number_of_shards_in_gen_kwargs(lowerCAmelCase_   )
					else:
										__SCREAMING_SNAKE_CASE						   =				_number_of_shards_in_gen_kwargs(lowerCAmelCase_   )
										assert out == expected
