





'''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 :		str 			=				get_logger(__name__)



class 							__UpperCAmelCase     :







		'''simple docstring'''







		__lowerCAmelCase        =			'''dummy_data'''
		__lowerCAmelCase        =			'''datasets'''
		__lowerCAmelCase        =			False







		def __init__(self  :					Any					,					_lowerCAmelCase  :					str					,					_lowerCAmelCase  :					str					,					_lowerCAmelCase  :					Union[Version, str]					,					_lowerCAmelCase  :					Optional[str] = None					,					_lowerCAmelCase  :					bool = False					,					_lowerCAmelCase  :					bool = True					,					_lowerCAmelCase  :					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(_lowerCAmelCase					)
			# to be downloaded
			A							     =					None
			A							     =					None







		@property
		def 				A   (self  :					Union[str, Any]					):
			if self._dummy_file is None:
				A							     =					self.download_dummy_data()
			return self._dummy_file







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







		def 				A   (self  :					Tuple					):
			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(
			    _lowerCAmelCase					,					cache_dir=self.cache_dir					,					extract_compressed_file=_lowerCAmelCase					,					force_extract=_lowerCAmelCase					)

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







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







		@property
		def 				A   (self  :					Optional[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 				A   (self  :					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 				A   (self  :					Dict					,					_lowerCAmelCase  :					Any					,					*_lowerCAmelCase  :					Any					):
			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(_lowerCAmelCase					,					_lowerCAmelCase					):
				return self.create_dummy_data_dict(_lowerCAmelCase					,					_lowerCAmelCase					)
			elif isinstance(_lowerCAmelCase					,					(list, tuple)					):
				return self.create_dummy_data_list(_lowerCAmelCase					,					_lowerCAmelCase					)
			else:
				return self.create_dummy_data_single(_lowerCAmelCase					,					_lowerCAmelCase					)







		def 				A   (self  :					Dict					,					_lowerCAmelCase  :					Any					,					*_lowerCAmelCase  :					Any					):
			return self.download_and_extract(_lowerCAmelCase					)







		def 				A   (self  :					List[str]					,					_lowerCAmelCase  :					Union[str, Any]					,					_lowerCAmelCase  :					int					):
			return self.download_and_extract(_lowerCAmelCase					)







		def 				A   (self  :					Tuple					,					_lowerCAmelCase  :					List[Any]					,					*_lowerCAmelCase  :					Union[str, Any]					,					**_lowerCAmelCase  :					Optional[Any]					):
			return path







		def 				A   (self  :					Optional[int]					):
			return {}







		def 				A   (self  :					str					,					_lowerCAmelCase  :					List[str]					,					_lowerCAmelCase  :					Any					):
			A							     =					{}
			for key, single_urls in data_url.items():
				for download_callback in self.download_callbacks:
					if isinstance(_lowerCAmelCase					,					_lowerCAmelCase					):
						for single_url in single_urls:
							download_callback(_lowerCAmelCase					)
					else:
						A							     =					single_urls
						download_callback(_lowerCAmelCase					)
            # 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(_lowerCAmelCase					,					_lowerCAmelCase					):
					A							     =					[os.path.join(_lowerCAmelCase					,					urllib.parse.quote_plus(Path(_lowerCAmelCase					).name					)					) for x in single_urls]
				else:
					A							     =					single_urls
					A							     =					os.path.join(_lowerCAmelCase					,					urllib.parse.quote_plus(Path(_lowerCAmelCase					).name					)					)
				A							     =					value

			# make sure that values are unique
			if all(isinstance(_lowerCAmelCase					,					_lowerCAmelCase					) 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 				A   (self  :					Optional[int]					,					_lowerCAmelCase  :					str					,					_lowerCAmelCase  :					Dict					):
			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,}"""					,					_lowerCAmelCase					)					) 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(_lowerCAmelCase					)
			for single_url in data_url:
				for download_callback in self.download_callbacks:
					download_callback(_lowerCAmelCase					)
				# 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(_lowerCAmelCase					,					urllib.parse.quote_plus(single_url.split("""/"""					)[-1]					)					)
				dummy_data_list.append(_lowerCAmelCase					)
			return dummy_data_list







		def 				A   (self  :					Optional[Any]					,					_lowerCAmelCase  :					List[str]					,					_lowerCAmelCase  :					Optional[int]					):
			for download_callback in self.download_callbacks:
				download_callback(_lowerCAmelCase					)
			# 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(_lowerCAmelCase					,					urllib.parse.quote_plus(data_url.split("""/"""					)[-1]					)					)
			if os.path.exists(_lowerCAmelCase					) 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 				A   (self  :					Dict					):
			pass







		def 				A   (self  :					Union[str, Any]					):
			pass







		def 				A   (self  :					Optional[int]					,					_lowerCAmelCase  :					Dict					):
			def _iter_archive_members(_lowerCAmelCase  :					Tuple					):
				# this preserves the order of the members inside the ZIP archive
				A							     =					Path(self.dummy_file					).parent
				A							     =					path.relative_to(_lowerCAmelCase					)
				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(_lowerCAmelCase					)

			A							     =					Path(_lowerCAmelCase					)
			A							     =					_iter_archive_members(_lowerCAmelCase					) 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(_lowerCAmelCase					).as_posix(), file_path.open("""rb"""					)







		def 				A   (self  :					str					,					_lowerCAmelCase  :					List[Any]					):
			if not isinstance(_lowerCAmelCase					,					_lowerCAmelCase					):
				A							     =					[paths]
			for path in paths:
				if os.path.isfile(_lowerCAmelCase					):
					if os.path.basename(_lowerCAmelCase					).startswith((""".""", """__""")					):
						return
					yield path
				else:
					for dirpath, dirnames, filenames in os.walk(_lowerCAmelCase					):
						if os.path.basename(_lowerCAmelCase					).startswith((""".""", """__""")					):
							continue
						dirnames.sort()
						for filename in sorted(_lowerCAmelCase					):
							if filename.startswith((""".""", """__""")					):
								continue
							yield os.path.join(_lowerCAmelCase					,					_lowerCAmelCase					)



from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase  :					List[Any]													=       logging.get_logger(__name__)

lowercase  :					Any													=       {
    'google/pegasus-large': 'https://huggingface.co/google/pegasus-large/resolve/main/config.json',
    # See all PEGASUS models at https://huggingface.co/models?filter=pegasus
}




class  lowerCamelCase__							(				__lowercase):




	'''simple docstring'''




	_A								=     'pegasus'
	_A								=     ['past_key_values']
	_A								=     {'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}







	def __init__(					self		:Dict     ,   a		:Dict=5_0_2_6_5     ,   a		:Dict=1_0_2_4     ,   a		:Union[str, Any]=1_2     ,   a		:Any=4_0_9_6     ,   a		:str=1_6     ,   a		:str=1_2     ,   a		:Optional[Any]=4_0_9_6     ,   a		:int=1_6     ,   a		:Optional[int]=0.0     ,   a		:Optional[int]=0.0     ,   a		:List[Any]=True     ,   a		:Union[str, Any]=True     ,   a		:int="gelu"     ,   a		:Dict=1_0_2_4     ,   a		:List[Any]=0.1     ,   a		:List[str]=0.0     ,   a		:List[Any]=0.0     ,   a		:str=0.02     ,   a		:int=0     ,   a		:Any=False     ,   a		:Dict=0     ,   a		:int=1     ,   a		:Optional[Any]=1     ,   **a		:Optional[int]     ,   )		-> str:
								__UpperCamelCase	:   List[Any]			   =					vocab_size
								__UpperCamelCase	:   Union[str, Any]			   =					max_position_embeddings
								__UpperCamelCase	:   str			   =					d_model
								__UpperCamelCase	:   Dict			   =					encoder_ffn_dim
								__UpperCamelCase	:   int			   =					encoder_layers
								__UpperCamelCase	:   int			   =					encoder_attention_heads
								__UpperCamelCase	:   List[Any]			   =					decoder_ffn_dim
								__UpperCamelCase	:   List[Any]			   =					decoder_layers
								__UpperCamelCase	:   List[str]			   =					decoder_attention_heads
								__UpperCamelCase	:   str			   =					dropout
								__UpperCamelCase	:   Union[str, Any]			   =					attention_dropout
								__UpperCamelCase	:   List[str]			   =					activation_dropout
								__UpperCamelCase	:   Optional[Any]			   =					activation_function
								__UpperCamelCase	:   Tuple			   =					init_std
								__UpperCamelCase	:   Optional[int]			   =					encoder_layerdrop
								__UpperCamelCase	:   Union[str, Any]			   =					decoder_layerdrop
								__UpperCamelCase	:   Optional[Any]			   =					use_cache
								__UpperCamelCase	:   Union[str, Any]			   =					encoder_layers
								__UpperCamelCase	:   int			   =					scale_embedding  # scale factor will be sqrt(d_model) if True
								super().__init__(
								    pad_token_id=a     ,   eos_token_id=a     ,   is_encoder_decoder=a     ,   decoder_start_token_id=a     ,   forced_eos_token_id=a     ,   **a     ,   )







	@property
	def    _lowerCamelCase				(					self		:Dict						)		-> int:
								return self.encoder_attention_heads







	@property
	def    _lowerCamelCase				(					self		:Optional[Any]						)		-> int:
								return self.d_model