



'''simple docstring'''

import importlib
import shutil
import threading
import warnings
from typing import List

import fsspec
import fsspec.asyn

from . import compression
from .hffilesystem import HfFileSystem


UpperCAmelCase     		=   importlib.util.find_spec('s3fs') is not None

if _has_safs:
				from .safilesystem import SaFileSystem  # noqa: F401

UpperCAmelCase     		=   [
    compression.BzaFileSystem,
    compression.GzipFileSystem,
    compression.LzaFileSystem,
    compression.XzFileSystem,
    compression.ZstdFileSystem,
]

# Register custom filesystems
for fs_class in COMPRESSION_FILESYSTEMS + [HfFileSystem]:
				if fs_class.protocol in fsspec.registry and fsspec.registry[fs_class.protocol] is not fs_class:
								warnings.warn(F'''A filesystem protocol was already set for {fs_class.protocol} and will be overwritten.''')
				fsspec.register_implementation(fs_class.protocol, fs_class, clobber=True)






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						str							)      ->						str:







	"""simple docstring"""
	if "://" in dataset_path:
		lowerCAmelCase   =     dataset_path.split("""://"""							)[1]
	return dataset_path






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						fsspec.AbstractFileSystem							)      ->						bool:







	"""simple docstring"""
	if fs is not None and fs.protocol != "file":
		return True
	else:
		return False






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						fsspec.AbstractFileSystem							,		_SCREAMING_SNAKE_CASE					:						str							,		_SCREAMING_SNAKE_CASE					:						str							)      ->						str:







	"""simple docstring"""
	lowerCAmelCase   =     not is_remote_filesystem(_SCREAMING_SNAKE_CASE							)
	if is_local:
		# LocalFileSystem.mv does copy + rm, it is more efficient to simply move a local directory
		shutil.move(fs._strip_protocol(_SCREAMING_SNAKE_CASE							)							,		fs._strip_protocol(_SCREAMING_SNAKE_CASE							)							)
	else:
		fs.mv(_SCREAMING_SNAKE_CASE							,		_SCREAMING_SNAKE_CASE							,		recursive=_SCREAMING_SNAKE_CASE							)






def 		_snake_case		( )      ->						None:







	"""simple docstring"""
	if hasattr(fsspec.asyn							,		"""reset_lock"""							):
		# for future fsspec>2022.05.0
		fsspec.asyn.reset_lock()
	else:
		lowerCAmelCase   =     None
		lowerCAmelCase   =     None
		lowerCAmelCase   =     threading.Lock()




'''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				)				)