



'''simple docstring'''

import os
from collections.abc import Iterator






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						str = "."							)      ->						Iterator[str]:







	"""simple docstring"""
	for dir_path, dir_names, filenames in os.walk(lowercase_							):
		lowerCAmelCase   =     [d for d in dir_names if d != """scripts""" and d[0] not in """._"""]
		for filename in filenames:
			if filename == "__init__.py":
				continue
			if os.path.splitext(lowercase_							)[1] in (".py", ".ipynb"):
				yield os.path.join(lowercase_							,		lowercase_							).lstrip("""./"""							)






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						Dict							)      ->						List[Any]:







	"""simple docstring"""
	return f'{i * "  "}*' if i else "\n##"






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						str							,		_SCREAMING_SNAKE_CASE					:						str							)      ->						str:







	"""simple docstring"""
	lowerCAmelCase   =     old_path.split(os.sep							)
	for i, new_part in enumerate(new_path.split(os.sep							)							):
		if (i + 1 > len(lowercase_							) or old_parts[i] != new_part) and new_part:
			print(f'{md_prefix(lowercase_							)} {new_part.replace("_"							,		" "							).title()}'							)
	return new_path






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						str = "."							)      ->						None:







	"""simple docstring"""
	lowerCAmelCase   =     """"""
	for filepath in sorted(good_file_paths(lowercase_							)							):
		lowerCAmelCase,       lowerCAmelCase   =     os.path.split(lowercase_							)
		if filepath != old_path:
			lowerCAmelCase   =     print_path(lowercase_							,		lowercase_							)
		lowerCAmelCase   =     (filepath.count(os.sep							) + 1) if filepath else 0
		lowerCAmelCase   =     f'{filepath}/{filename}'.replace(""" """							,		"""%20"""							)
		lowerCAmelCase   =     os.path.splitext(filename.replace("""_"""							,		""" """							).title()							)[0]
		print(f'{md_prefix(lowercase_							)} [{filename}]({url})'							)


if __name__ == "__main__":
				print_directory_md('.')




'''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 __snake_case(				_lowerCAmelCase ):


						'''simple docstring'''



						UpperCAmelCase							:   Union[str, Any]									=		["image_processor", "tokenizer"]
						UpperCAmelCase							:   Tuple									=		"BlipImageProcessor"
						UpperCAmelCase							:   Union[str, Any]									=		("BertTokenizer", "BertTokenizerFast")


						def __init__( self     ,	A_     ,	A_				)     ->     Dict:
							lowerCAmelCase   =     False
							super().__init__(A_     ,	A_				)
							lowerCAmelCase   =     self.image_processor


						def __call__( self     ,	A_ = None     ,	A_ = None     ,	A_ = True     ,	A_ = False     ,	A_ = None     ,	A_ = None     ,	A_ = 0     ,	A_ = None     ,	A_ = None     ,	A_ = False     ,	A_ = False     ,	A_ = False     ,	A_ = False     ,	A_ = False     ,	A_ = True     ,	A_ = None     ,	**A_     ,	)     ->     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:
								lowerCAmelCase   =     self.tokenizer
								lowerCAmelCase   =     self.tokenizer(
								    text=A_     ,	add_special_tokens=A_     ,	padding=A_     ,	truncation=A_     ,	max_length=A_     ,	stride=A_     ,	pad_to_multiple_of=A_     ,	return_attention_mask=A_     ,	return_overflowing_tokens=A_     ,	return_special_tokens_mask=A_     ,	return_offsets_mapping=A_     ,	return_token_type_ids=A_     ,	return_length=A_     ,	verbose=A_     ,	return_tensors=A_     ,	**A_     ,	)
								return text_encoding

							# add pixel_values
							lowerCAmelCase   =     self.image_processor(A_     ,	return_tensors=A_				)

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

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

							return encoding_image_processor


						def     __snake_case   ( self     ,	*A_     ,	**A_				)     ->     Union[str, Any]:
							return self.tokenizer.batch_decode(*A_     ,	**A_				)


						def     __snake_case   ( self     ,	*A_     ,	**A_				)     ->     Tuple:
							return self.tokenizer.decode(*A_     ,	**A_				)




						@property
						def     __snake_case   ( self				)     ->     str:
							lowerCAmelCase   =     self.tokenizer.model_input_names
							lowerCAmelCase   =     self.image_processor.model_input_names
							return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names				)				)