





'''simple docstring'''







# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile

from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version


lowerCAmelCase_					:    List[Any]      	=			get_logger(__name__)
class 				__SCREAMING_SNAKE_CASE  :






				"""simple docstring"""







				__a            ='dummy_data'
				__a            ='datasets'
				__a            =False




				def __init__(  self     :					Dict					,				__a     :					str					,				__a     :					str					,				__a     :					Union[Version, str]					,				__a     :					Optional[str] = None					,				__a     :					bool = False					,				__a     :					bool = True					,				__a     :					Optional[List[Callable]] = None					,				):
								_a								= 0
								_a								= dataset_name
								_a								= cache_dir
								_a								= use_local_dummy_data
								_a								= config
								# download_callbacks take a single url as input
								_a								= download_callbacks or []
								# if False, it doesn't load existing files and it returns the paths of the dummy files relative
								# to the dummy_data zip file root
								_a								= load_existing_dummy_data

								# TODO(PVP, QL) might need to make this more general
								_a								= str(__a					)
								# to be downloaded
								_a								= None
								_a								= None




				@property
				def   UpperCamelCase__   (  self     :					Dict					):
								if self._dummy_file is None:
												_a								= self.download_dummy_data()
								return self._dummy_file




				@property
				def   UpperCamelCase__   (  self     :					Dict					):
								if self.config is not None:
												# structure is dummy / config_name / version_name
												return os.path.join("dummy"					,				self.config.name					,				self.version_name					)
								# structure is dummy / version_name
								return os.path.join("dummy"					,				self.version_name					)




				@property
				def   UpperCamelCase__   (  self     :					Optional[int]					):
								return os.path.join(self.dummy_data_folder					,				"dummy_data.zip"					)




				def   UpperCamelCase__   (  self     :					int					):
								_a								= (
								    self.local_path_to_dummy_data if self.use_local_dummy_data is True else self.github_path_to_dummy_data
								)

								_a								= cached_path(
								    __a					,				cache_dir=self.cache_dir					,				extract_compressed_file=__a					,				force_extract=__a					)

								return os.path.join(__a					,				self.dummy_file_name					)




				@property
				def   UpperCamelCase__   (  self     :					Tuple					):
								return os.path.join(self.datasets_scripts_dir					,				self.dataset_name					,				self.dummy_zip_file					)




				@property
				def   UpperCamelCase__   (  self     :					Union[str, Any]					):
								if self._bucket_url is None:
												_a								= hf_github_url(self.dataset_name					,				self.dummy_zip_file.replace(os.sep					,				"/"					)					)
								return self._bucket_url




				@property
				def   UpperCamelCase__   (  self     :					Optional[int]					):
								# return full path if its a dir
								if os.path.isdir(self.dummy_file					):
												return self.dummy_file
								# else cut off path to file -> example `xsum`.
								return "/".join(self.dummy_file.replace(os.sep					,				"/"					).split("/"					)[:-1]					)




				def   UpperCamelCase__   (  self     :					Dict					,				__a     :					Tuple					,				*__a     :					Tuple					):
								if self.load_existing_dummy_data:
												# dummy data is downloaded and tested
												_a								= self.dummy_file
								else:
												# dummy data cannot be downloaded and only the path to dummy file is returned
												_a								= self.dummy_file_name

								# special case when data_url is a dict
								if isinstance(__a					,				__a					):
												return self.create_dummy_data_dict(__a					,				__a					)
								elif isinstance(__a					,				(list, tuple)					):
												return self.create_dummy_data_list(__a					,				__a					)
								else:
												return self.create_dummy_data_single(__a					,				__a					)




				def   UpperCamelCase__   (  self     :					Any					,				__a     :					int					,				*__a     :					int					):
								return self.download_and_extract(__a					)




				def   UpperCamelCase__   (  self     :					Union[str, Any]					,				__a     :					str					,				__a     :					int					):
								return self.download_and_extract(__a					)




				def   UpperCamelCase__   (  self     :					Tuple					,				__a     :					List[Any]					,				*__a     :					Tuple					,				**__a     :					int					):
								return path




				def   UpperCamelCase__   (  self     :					List[Any]					):
								return {}




				def   UpperCamelCase__   (  self     :					str					,				__a     :					List[str]					,				__a     :					Union[str, Any]					):
								_a								= {}
								for key, single_urls in data_url.items():
												for download_callback in self.download_callbacks:
																if isinstance(__a					,				__a					):
																				for single_url in single_urls:
																								download_callback(__a					)
																else:
																				_a								= single_urls
																				download_callback(__a					)
            # we force the name of each key to be the last file / folder name of the url path
            # if the url has arguments, we need to encode them with urllib.parse.quote_plus
												if isinstance(__a					,				__a					):
																_a								= [os.path.join(__a					,				urllib.parse.quote_plus(Path(__a					).name					)					) for x in single_urls]
												else:
																_a								= single_urls
																_a								= os.path.join(__a					,				urllib.parse.quote_plus(Path(__a					).name					)					)
												_a								= value

								# make sure that values are unique
								if all(isinstance(__a					,				__a					) for i in dummy_data_dict.values()					) and len(set(dummy_data_dict.values()					)					) < len(
								    dummy_data_dict.values()					):
												# append key to value to make its name unique
												_a								= {key: value + key for key, value in dummy_data_dict.items()}

								return dummy_data_dict




				def   UpperCamelCase__   (  self     :					Optional[Any]					,				__a     :					List[str]					,				__a     :					str					):
								_a								= []
								# trick: if there are many shards named like `data.txt-000001-of-00300`, only use the first one
								_a								= all(bool(re.findall("[0-9]{3,}-of-[0-9]{3,}"					,				__a					)					) for url in data_url					)
								_a								= all(
								    url.startswith("https://ftp.ncbi.nlm.nih.gov/pubmed/baseline/pubmed"					) for url in data_url					)
								if data_url and (is_tf_records or is_pubmed_records):
												_a								= [data_url[0]] * len(__a					)
								for single_url in data_url:
												for download_callback in self.download_callbacks:
																download_callback(__a					)
												# we force the name of each key to be the last file / folder name of the url path
												# if the url has arguments, we need to encode them with urllib.parse.quote_plus
												_a								= os.path.join(__a					,				urllib.parse.quote_plus(single_url.split("/"					)[-1]					)					)
												dummy_data_list.append(__a					)
								return dummy_data_list




				def   UpperCamelCase__   (  self     :					Union[str, Any]					,				__a     :					Optional[int]					,				__a     :					List[Any]					):
								for download_callback in self.download_callbacks:
												download_callback(__a					)
								# we force the name of each key to be the last file / folder name of the url path
								# if the url has arguments, we need to encode them with urllib.parse.quote_plus
								_a								= os.path.join(__a					,				urllib.parse.quote_plus(data_url.split("/"					)[-1]					)					)
								if os.path.exists(__a					) or not self.load_existing_dummy_data:
												return value
								else:
												# Backward compatibility, maybe deprecate at one point.
												# For many datasets with single url calls to dl_manager.download_and_extract,
												# the dummy_data.zip file is actually the zipped downloaded file
												# while now we expected the dummy_data.zip file to be a directory containing
												# the downloaded file.
												return path_to_dummy_data




				def   UpperCamelCase__   (  self     :					Dict					):
								pass




				def   UpperCamelCase__   (  self     :					Dict					):
								pass




				def   UpperCamelCase__   (  self     :					Optional[int]					,				__a     :					Any					):
								def _iter_archive_members(__a     :					Tuple					):
												# this preserves the order of the members inside the ZIP archive
												_a								= Path(self.dummy_file					).parent
												_a								= path.relative_to(__a					)
												with ZipFile(self.local_path_to_dummy_data					) as zip_file:
																_a								= zip_file.namelist()
												for member in members:
																if member.startswith(relative_path.as_posix()					):
																				yield dummy_parent_path.joinpath(__a					)

								_a								= Path(__a					)
								_a								= _iter_archive_members(__a					) if self.use_local_dummy_data else path.rglob("*"					)
								for file_path in file_paths:
												if file_path.is_file() and not file_path.name.startswith((".", "__")					):
																yield file_path.relative_to(__a					).as_posix(), file_path.open("rb"					)




				def   UpperCamelCase__   (  self     :					Tuple					,				__a     :					Optional[int]					):
								if not isinstance(__a					,				__a					):
												_a								= [paths]
								for path in paths:
												if os.path.isfile(__a					):
																if os.path.basename(__a					).startswith((".", "__")					):
																				return
																yield path
												else:
																for dirpath, dirnames, filenames in os.walk(__a					):
																				if os.path.basename(__a					).startswith((".", "__")					):
																								continue
																				dirnames.sort()
																				for filename in sorted(__a					):
																								if filename.startswith((".", "__")					):
																												continue
																								yield os.path.join(__a					,				__a					)




from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class 	UpperCAmelCase_					(					UpperCamelCase    ):

   '''simple docstring'''




   __A :      Dict     		=		["image_processor", "tokenizer"]
   __A :      Dict     		=		"BridgeTowerImageProcessor"
   __A :      Optional[int]     		=		("RobertaTokenizer", "RobertaTokenizerFast")






   def __init__(		self						,				__A						,				__A ):






     """simple docstring"""





     super().__init__(__A						,				__A )






   def __call__(		self						,				__A						,				__A = None						,				__A = True						,				__A = False						,				__A = None						,				__A = None						,				__A = 0						,				__A = None						,				__A = None						,				__A = None						,				__A = False						,				__A = False						,				__A = False						,				__A = False						,				__A = True						,				__A = None						,				**__A						,				):






     """simple docstring"""





     lowerCamelCase :					str    =				self.tokenizer(
         text=__A						,				add_special_tokens=__A						,				padding=__A						,				truncation=__A						,				max_length=__A						,				stride=__A						,				pad_to_multiple_of=__A						,				return_token_type_ids=__A						,				return_attention_mask=__A						,				return_overflowing_tokens=__A						,				return_special_tokens_mask=__A						,				return_offsets_mapping=__A						,				return_length=__A						,				verbose=__A						,				return_tensors=__A						,				**__A						,				)
     # add pixel_values + pixel_mask
     lowerCamelCase :					int    =				self.image_processor(
         __A						,				return_tensors=__A						,				do_normalize=__A						,				do_center_crop=__A						,				**__A )
     encoding.update(__A )

     return encoding






   def _snake_case    (		self						,				*__A						,				**__A ):






     """simple docstring"""





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






   def _snake_case    (		self						,				*__A						,				**__A ):






     """simple docstring"""





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






   @property
   def _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					List[Any]    =				self.tokenizer.model_input_names
     lowerCamelCase :					int    =				self.image_processor.model_input_names
     return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names ) )



