


'''simple docstring'''

import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union

from .. import config
from .filelock import FileLock
from .logging import get_logger


_UpperCAmelCase				: int							    =				get_logger(__name__)


class       a__				:







				"""simple docstring"""



				def __init__(self       ,			__lowercase = None		):
										__lowerCAmelCase							       =				(
										    os.path.join(__lowercase       ,			config.EXTRACTED_DATASETS_DIR		) if cache_dir else config.EXTRACTED_DATASETS_PATH
										)
										__lowerCAmelCase							       =				Extractor




				def 					_snake_case  (self       ,			__lowercase		):
										from .file_utils import hash_url_to_filename

										# Path where we extract compressed archives
										# We extract in the cache dir, and get the extracted path name by hashing the original path"
										__lowerCAmelCase							       =				os.path.abspath(__lowercase		)
										return os.path.join(self.extract_dir       ,			hash_url_to_filename(__lowercase		)		)




				def 					_snake_case  (self       ,			__lowercase       ,			__lowercase		):
										return force_extract or (
										    not os.path.isfile(__lowercase		) and not (os.path.isdir(__lowercase		) and os.listdir(__lowercase		))
										)




				def 					_snake_case  (self       ,			__lowercase       ,			__lowercase = False		):
										__lowerCAmelCase							       =				self.extractor.infer_extractor_format(__lowercase		)
										if not extractor_format:
																return input_path
										__lowerCAmelCase							       =				self._get_output_path(__lowercase		)
										if self._do_extract(__lowercase       ,			__lowercase		):
																self.extractor.extract(__lowercase       ,			__lowercase       ,			__lowercase		)
										return output_path


class       a__				( __A      ):







				"""simple docstring"""



				@classmethod
				@abstractmethod
				def 					_snake_case  (cls       ,			__lowercase       ,			**__lowercase		):
										...




				@staticmethod
				@abstractmethod
				def 					_snake_case  (__lowercase       ,			__lowercase		):
										...


class       a__				( __A							,						__A      ):







				"""simple docstring"""



				__UpperCamelCase    :		List[bytes]	=	[]




				@staticmethod
				def 					_snake_case  (__lowercase       ,			__lowercase		):
										with open(__lowercase       ,			'''rb'''		) as f:
																return f.read(__lowercase		)




				@classmethod
				def 					_snake_case  (cls       ,			__lowercase       ,			__lowercase = b""		):
										if not magic_number:
																__lowerCAmelCase							       =				max(len(__lowercase		) for cls_magic_number in cls.magic_numbers		)
																try:
																						__lowerCAmelCase							       =				cls.read_magic_number(__lowercase       ,			__lowercase		)
																except OSError:
																						return False
										return any(magic_number.startswith(__lowercase		) for cls_magic_number in cls.magic_numbers		)


class       a__				( __A      ):







				"""simple docstring"""



				@classmethod
				def 					_snake_case  (cls       ,			__lowercase       ,			**__lowercase		):
										return tarfile.is_tarfile(__lowercase		)




				@staticmethod
				def 					_snake_case  (__lowercase       ,			__lowercase		):

										def resolved(__lowercase		) -> str:
																return os.path.realpath(os.path.abspath(__lowercase		)		)

										def badpath(__lowercase       ,			__lowercase		) -> bool:
																# joinpath will ignore base if path is absolute
																return not resolved(os.path.join(__lowercase       ,			__lowercase		)		).startswith(__lowercase		)

										def badlink(__lowercase       ,			__lowercase		) -> bool:
																# Links are interpreted relative to the directory containing the link
																__lowerCAmelCase							       =				resolved(os.path.join(__lowercase       ,			os.path.dirname(info.name		)		)		)
																return badpath(info.linkname       ,			base=__lowercase		)

										__lowerCAmelCase							       =				resolved(__lowercase		)

										for finfo in members:
																if badpath(finfo.name       ,			__lowercase		):
																						logger.error(F"""Extraction of {finfo.name} is blocked (illegal path)"""		)
																elif finfo.issym() and badlink(__lowercase       ,			__lowercase		):
																						logger.error(F"""Extraction of {finfo.name} is blocked: Symlink to {finfo.linkname}"""		)
																elif finfo.islnk() and badlink(__lowercase       ,			__lowercase		):
																						logger.error(F"""Extraction of {finfo.name} is blocked: Hard link to {finfo.linkname}"""		)
																else:
																						yield finfo




				@staticmethod
				def 					_snake_case  (__lowercase       ,			__lowercase		):
										os.makedirs(__lowercase       ,			exist_ok=__lowercase		)
										__lowerCAmelCase							       =				tarfile.open(__lowercase		)
										tar_file.extractall(__lowercase       ,			members=TarExtractor.safemembers(__lowercase       ,			__lowercase		)		)
										tar_file.close()


class       a__				( __A      ):







				"""simple docstring"""



				__UpperCamelCase    :		List[Any]	=	[B'\x1F\x8B']




				@staticmethod
				def 					_snake_case  (__lowercase       ,			__lowercase		):
										with gzip.open(__lowercase       ,			'''rb'''		) as gzip_file:
																with open(__lowercase       ,			'''wb'''		) as extracted_file:
																						shutil.copyfileobj(__lowercase       ,			__lowercase		)


class       a__				( __A      ):







				"""simple docstring"""



				__UpperCamelCase    :		Union[str, Any]	=	[
				    B'PK\x03\x04',
				    B'PK\x05\x06',  # empty archive
				    B'PK\x07\x08',  # spanned archive
				]




				@classmethod
				def 					_snake_case  (cls       ,			__lowercase       ,			__lowercase = b""		):
										if super().is_extractable(__lowercase       ,			magic_number=__lowercase		):
																return True
										try:
																# Alternative version of zipfile.is_zipfile that has less false positives, but misses executable zip archives.
																# From: https://github.com/python/cpython/pull/5053
																from zipfile import (
																    _CD_SIGNATURE,
																    _ECD_DISK_NUMBER,
																    _ECD_DISK_START,
																    _ECD_ENTRIES_TOTAL,
																    _ECD_OFFSET,
																    _ECD_SIZE,
																    _EndRecData,
																    sizeCentralDir,
																    stringCentralDir,
																    structCentralDir,
																)

																with open(__lowercase       ,			'''rb'''		) as fp:
																						__lowerCAmelCase							       =				_EndRecData(__lowercase		)
																						if endrec:
																												if endrec[_ECD_ENTRIES_TOTAL] == 0 and endrec[_ECD_SIZE] == 0 and endrec[_ECD_OFFSET] == 0:
																																		return True  # Empty zipfiles are still zipfiles
																												elif endrec[_ECD_DISK_NUMBER] == endrec[_ECD_DISK_START]:
																																		fp.seek(endrec[_ECD_OFFSET]		)  # Central directory is on the same disk
																																		if fp.tell() == endrec[_ECD_OFFSET] and endrec[_ECD_SIZE] >= sizeCentralDir:
																																								__lowerCAmelCase							       =				fp.read(__lowercase		)  # CD is where we expect it to be
																																								if len(__lowercase		) == sizeCentralDir:
																																														__lowerCAmelCase							       =				struct.unpack(__lowercase       ,			__lowercase		)  # CD is the right size
																																														if centdir[_CD_SIGNATURE] == stringCentralDir:
																																																				return True  # First central directory entry  has correct magic number
																return False
										except Exception:  # catch all errors in case future python versions change the zipfile internals
																return False




				@staticmethod
				def 					_snake_case  (__lowercase       ,			__lowercase		):
										os.makedirs(__lowercase       ,			exist_ok=__lowercase		)
										with zipfile.ZipFile(__lowercase       ,			'''r'''		) as zip_file:
																zip_file.extractall(__lowercase		)
																zip_file.close()


class       a__				( __A      ):







				"""simple docstring"""



				__UpperCamelCase    :		Optional[int]	=	[B'\xFD\x37\x7A\x58\x5A\x00']




				@staticmethod
				def 					_snake_case  (__lowercase       ,			__lowercase		):
										with lzma.open(__lowercase		) as compressed_file:
																with open(__lowercase       ,			'''wb'''		) as extracted_file:
																						shutil.copyfileobj(__lowercase       ,			__lowercase		)


class       a__				( __A      ):







				"""simple docstring"""



				__UpperCamelCase    :		List[Any]	=	[B'Rar!\x1a\x07\x00', B'Rar!\x1a\x07\x01\x00']  # RAR_ID  # RAR5_ID




				@staticmethod
				def 					_snake_case  (__lowercase       ,			__lowercase		):
										if not config.RARFILE_AVAILABLE:
																raise ImportError('''Please pip install rarfile'''		)
										import rarfile

										os.makedirs(__lowercase       ,			exist_ok=__lowercase		)
										__lowerCAmelCase							       =				rarfile.RarFile(__lowercase		)
										rf.extractall(__lowercase		)
										rf.close()


class       a__				( __A      ):







				"""simple docstring"""



				__UpperCamelCase    :		Any	=	[B'\x28\xb5\x2F\xFD']




				@staticmethod
				def 					_snake_case  (__lowercase       ,			__lowercase		):
										if not config.ZSTANDARD_AVAILABLE:
																raise ImportError('''Please pip install zstandard'''		)
										import zstandard as zstd

										__lowerCAmelCase							       =				zstd.ZstdDecompressor()
										with open(__lowercase       ,			'''rb'''		) as ifh, open(__lowercase       ,			'''wb'''		) as ofh:
																dctx.copy_stream(__lowercase       ,			__lowercase		)


class       a__				( __A      ):







				"""simple docstring"""



				__UpperCamelCase    :		Union[str, Any]	=	[B'\x42\x5A\x68']




				@staticmethod
				def 					_snake_case  (__lowercase       ,			__lowercase		):
										with bza.open(__lowercase       ,			'''rb'''		) as compressed_file:
																with open(__lowercase       ,			'''wb'''		) as extracted_file:
																						shutil.copyfileobj(__lowercase       ,			__lowercase		)


class       a__				( __A      ):







				"""simple docstring"""



				__UpperCamelCase    :		Optional[int]	=	[B'\x37\x7A\xBC\xAF\x27\x1C']




				@staticmethod
				def 					_snake_case  (__lowercase       ,			__lowercase		):
										if not config.PY7ZR_AVAILABLE:
																raise ImportError('''Please pip install py7zr'''		)
										import pyazr

										os.makedirs(__lowercase       ,			exist_ok=__lowercase		)
										with pyazr.SevenZipFile(__lowercase       ,			'''r'''		) as archive:
																archive.extractall(__lowercase		)


class       a__				( __A      ):







				"""simple docstring"""



				__UpperCamelCase    :		List[str]	=	[B'\x04\x22\x4D\x18']




				@staticmethod
				def 					_snake_case  (__lowercase       ,			__lowercase		):
										if not config.LZ4_AVAILABLE:
																raise ImportError('''Please pip install lz4'''		)
										import lza.frame

										with lza.frame.open(__lowercase       ,			'''rb'''		) as compressed_file:
																with open(__lowercase       ,			'''wb'''		) as extracted_file:
																						shutil.copyfileobj(__lowercase       ,			__lowercase		)


class       a__				:







				"""simple docstring"""



				__UpperCamelCase    :		Dict[str, Type[BaseExtractor]]	=	{
				    "tar": TarExtractor,
				    "gzip": GzipExtractor,
				    "zip": ZipExtractor,
				    "xz": XzExtractor,
				    "rar": RarExtractor,
				    "zstd": ZstdExtractor,
				    "bz2": BzipaExtractor,
				    "7z": SevenZipExtractor,  # <Added version="2.4.0"/>
				    "lz4": LzaExtractor,  # <Added version="2.4.0"/>
				}




				@classmethod
				def 					_snake_case  (cls		):
										return max(
										    len(__lowercase		)
										    for extractor in cls.extractors.values()
										    if issubclass(__lowercase       ,			__lowercase		)
										    for extractor_magic_number in extractor.magic_numbers		)




				@staticmethod
				def 					_snake_case  (__lowercase       ,			__lowercase		):
										try:
																return MagicNumberBaseExtractor.read_magic_number(__lowercase       ,			magic_number_length=__lowercase		)
										except OSError:
																return b""




				@classmethod
				def 					_snake_case  (cls       ,			__lowercase       ,			__lowercase = False		):
										warnings.warn(
										    '''Method \'is_extractable\' was deprecated in version 2.4.0 and will be removed in 3.0.0. '''
										    '''Use \'infer_extractor_format\' instead.'''       ,			category=__lowercase       ,			)
										__lowerCAmelCase							       =				cls.infer_extractor_format(__lowercase		)
										if extractor_format:
																return True if not return_extractor else (True, cls.extractors[extractor_format])
										return False if not return_extractor else (False, None)




				@classmethod
				def 					_snake_case  (cls       ,			__lowercase		):  # <Added version="2.4.0"/>
										__lowerCAmelCase							       =				cls._get_magic_number_max_length()
										__lowerCAmelCase							       =				cls._read_magic_number(__lowercase       ,			__lowercase		)
										for extractor_format, extractor in cls.extractors.items():
																if extractor.is_extractable(__lowercase       ,			magic_number=__lowercase		):
																						return extractor_format




				@classmethod
				def 					_snake_case  (cls       ,			__lowercase       ,			__lowercase       ,			__lowercase = None       ,			__lowercase = "deprecated"       ,			):
										os.makedirs(os.path.dirname(__lowercase		)       ,			exist_ok=__lowercase		)
										# Prevent parallel extractions
										__lowerCAmelCase							       =				str(Path(__lowercase		).with_suffix('''.lock'''		)		)
										with FileLock(__lowercase		):
																shutil.rmtree(__lowercase       ,			ignore_errors=__lowercase		)
																if extractor_format or extractor != "deprecated":
																						if extractor != "deprecated" or not isinstance(__lowercase       ,			__lowercase		):  # passed as positional arg
																												warnings.warn(
																												    '''Parameter \'extractor\' was deprecated in version 2.4.0 and will be removed in 3.0.0. '''
																												    '''Use \'extractor_format\' instead.'''       ,			category=__lowercase       ,			)
																												__lowerCAmelCase							       =				extractor if extractor != '''deprecated''' else extractor_format
																						else:
																												__lowerCAmelCase							       =				cls.extractors[extractor_format]
																						return extractor.extract(__lowercase       ,			__lowercase		)
																else:
																						warnings.warn(
																						    '''Parameter \'extractor_format\' was made required in version 2.4.0 and not passing it will raise an '''
																						    '''exception in 3.0.0.'''       ,			category=__lowercase       ,			)
																						for extractor in cls.extractors.values():
																												if extractor.is_extractable(__lowercase		):
																																		return extractor.extract(__lowercase       ,			__lowercase		)





'''simple docstring'''

import unittest
from pathlib import Path
from tempfile import TemporaryDirectory

from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available
from transformers.models.gpta.tokenization_gpta import GPTaTokenizer
from transformers.testing_utils import require_keras_nlp, require_tf, slow


if is_tf_available():
	import tensorflow as tf

if is_keras_nlp_available():
	from transformers.models.gpta import TFGPTaTokenizer


_UpperCAmelCase				: str							    =				["""gpt2"""]
_UpperCAmelCase				: Optional[int]							    =				"""gpt2"""

if is_tf_available():


	class       a__				( tf.Module      ):







					"""simple docstring"""



					def __init__(self       ,			__lowercase		):
											super().__init__()
											__lowerCAmelCase							       =				tokenizer
											__lowerCAmelCase							       =				AutoConfig.from_pretrained(__lowercase		)
											__lowerCAmelCase							       =				TFGPTaLMHeadModel.from_config(__lowercase		)




					@tf.function(input_signature=(tf.TensorSpec((None,)       ,			tf.string       ,			name='''text'''		),)		)
					def 					_snake_case  (self       ,			__lowercase		):
											__lowerCAmelCase							       =				self.tokenizer(__lowercase		)
											__lowerCAmelCase							       =				tokenized['''input_ids'''].to_tensor()

											__lowerCAmelCase							       =				tf.cast(input_ids_dense > 0       ,			tf.intaa		)
											# input_mask = tf.reshape(input_mask, [-1, MAX_SEQ_LEN])

											__lowerCAmelCase							       =				self.model(input_ids=__lowercase       ,			attention_mask=__lowercase		)['''logits''']

											return outputs


@require_tf
@require_keras_nlp
class       a__				( unittest.TestCase      ):







				"""simple docstring"""



				def 					_snake_case  (self		):
										super().setUp()

										__lowerCAmelCase							       =				[GPTaTokenizer.from_pretrained(__lowercase		) for checkpoint in (TOKENIZER_CHECKPOINTS)]
										__lowerCAmelCase							       =				[TFGPTaTokenizer.from_pretrained(__lowercase		) for checkpoint in TOKENIZER_CHECKPOINTS]
										assert len(self.tokenizers		) == len(self.tf_tokenizers		)

										__lowerCAmelCase							       =				[
										    '''This is a straightforward English test sentence.''',
										    '''This one has some weird characters\rto\nsee\r\nif  those\u00E9break things.''',
										    '''Now we\'re going to add some Chinese: 一 二 三 一二三''',
										    '''And some much more rare Chinese: 齉 堃 齉堃''',
										    '''Je vais aussi écrire en français pour tester les accents''',
										    '''Classical Irish also has some unusual characters, so in they go: Gaelaċ, ꝼ''',
										]
										__lowerCAmelCase							       =				list(zip(self.test_sentences       ,			self.test_sentences[::-1]		)		)




				def 					_snake_case  (self		):
										for tokenizer, tf_tokenizer in zip(self.tokenizers       ,			self.tf_tokenizers		):
																for test_inputs in self.test_sentences:
																						__lowerCAmelCase							       =				tokenizer([test_inputs]       ,			return_tensors='''tf'''		)
																						__lowerCAmelCase							       =				tf_tokenizer([test_inputs]		)

																						for key in python_outputs.keys():
																												# convert them to numpy to avoid messing with ragged tensors
																												__lowerCAmelCase							       =				python_outputs[key].numpy()
																												__lowerCAmelCase							       =				tf_outputs[key].numpy()

																												self.assertTrue(tf.reduce_all(python_outputs_values.shape == tf_outputs_values.shape		)		)
																												self.assertTrue(tf.reduce_all(tf.cast(__lowercase       ,			tf.intaa		) == tf_outputs_values		)		)




				@slow
				def 					_snake_case  (self		):
										for tf_tokenizer in self.tf_tokenizers:
																__lowerCAmelCase							       =				tf.function(__lowercase		)
																for test_inputs in self.test_sentences:
																						__lowerCAmelCase							       =				tf.constant(__lowercase		)
																						__lowerCAmelCase							       =				compiled_tokenizer(__lowercase		)
																						__lowerCAmelCase							       =				tf_tokenizer(__lowercase		)

																						for key in eager_outputs.keys():
																												self.assertTrue(tf.reduce_all(eager_outputs[key] == compiled_outputs[key]		)		)




				@slow
				def 					_snake_case  (self		):
										for tf_tokenizer in self.tf_tokenizers:
																__lowerCAmelCase							       =				ModelToSave(tokenizer=__lowercase		)
																__lowerCAmelCase							       =				tf.convert_to_tensor([self.test_sentences[0]]		)
																__lowerCAmelCase							       =				model.serving(__lowercase		)  # Build model with some sample inputs
																with TemporaryDirectory() as tempdir:
																						__lowerCAmelCase							       =				Path(__lowercase		) / '''saved.model'''
																						tf.saved_model.save(__lowercase       ,			__lowercase       ,			signatures={'''serving_default''': model.serving}		)
																						__lowerCAmelCase							       =				tf.saved_model.load(__lowercase		)
																__lowerCAmelCase							       =				loaded_model.signatures['''serving_default'''](__lowercase		)['''output_0''']
																# We may see small differences because the loaded model is compiled, so we need an epsilon for the test
																self.assertTrue(tf.reduce_all(out == loaded_output		)		)




				@slow
				def 					_snake_case  (self		):
										for tf_tokenizer in self.tf_tokenizers:
																__lowerCAmelCase							       =				tf.convert_to_tensor([self.test_sentences[0]]		)
																__lowerCAmelCase							       =				tf_tokenizer(__lowercase		)  # Build model with some sample inputs

																__lowerCAmelCase							       =				tf_tokenizer.get_config()
																__lowerCAmelCase							       =				TFGPTaTokenizer.from_config(__lowercase		)
																__lowerCAmelCase							       =				model_from_config(__lowercase		)

																for key in from_config_output.keys():
																						self.assertTrue(tf.reduce_all(from_config_output[key] == out[key]		)		)




				@slow
				def 					_snake_case  (self		):
										for tf_tokenizer in self.tf_tokenizers:
																# for the test to run
																__lowerCAmelCase							       =				12_31_23

																for max_length in [3, 5, 10_24]:
																						__lowerCAmelCase							       =				tf.convert_to_tensor([self.test_sentences[0]]		)
																						__lowerCAmelCase							       =				tf_tokenizer(__lowercase       ,			max_length=__lowercase		)

																						__lowerCAmelCase							       =				out['''input_ids'''].numpy().shape[1]

																						assert out_length == max_length

