



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


a__    =	get_logger(__name__)







class 		snake_case						:



   '''simple docstring'''






   def __init__(					self							:			Union[str, Any]				,		lowerCAmelCase							:			Optional[str] = None)				->				Any:

    """simple docstring"""







    _snake_case    :  Any					=					(
        os.path.join(lowerCAmelCase				,		config.EXTRACTED_DATASETS_DIR) if cache_dir else config.EXTRACTED_DATASETS_PATH
    )
    _snake_case    :  Dict					=					Extractor

   def      UpperCamelCase_  (					self							:			Dict				,		lowerCAmelCase							:			str)				->				str:

    """simple docstring"""







    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"
    _snake_case    :  Dict					=					os.path.abspath(lowerCAmelCase)
    return os.path.join(self.extract_dir				,		hash_url_to_filename(lowerCAmelCase))

   def      UpperCamelCase_  (					self							:			str				,		lowerCAmelCase							:			str				,		lowerCAmelCase							:			bool)				->				bool:

    """simple docstring"""







    return force_extract or (
        not os.path.isfile(lowerCAmelCase) and not (os.path.isdir(lowerCAmelCase) and os.listdir(lowerCAmelCase))
    )


   def      UpperCamelCase_  (					self							:			int				,		lowerCAmelCase							:			str				,		lowerCAmelCase							:			bool = False)				->				str:

    """simple docstring"""







    _snake_case    :  Optional[int]					=					self.extractor.infer_extractor_format(lowerCAmelCase)
    if not extractor_format:
     return input_path
    _snake_case    :  Optional[int]					=					self._get_output_path(lowerCAmelCase)
    if self._do_extract(lowerCAmelCase				,		lowerCAmelCase):
     self.extractor.extract(lowerCAmelCase				,		lowerCAmelCase				,		lowerCAmelCase)
    return output_path







class 		snake_case						(	SCREAMING_SNAKE_CASE_  ):



   '''simple docstring'''






   @classmethod
   @abstractmethod
   def      UpperCamelCase_  (					cls							:			Union[str, Any]				,		lowerCAmelCase							:			Union[Path, str]				,		**lowerCAmelCase							:			Tuple)				->				bool:

    """simple docstring"""







    ...


   @staticmethod
   @abstractmethod
   def      UpperCamelCase_  (					lowerCAmelCase							:			Union[Path, str]				,		lowerCAmelCase							:			Union[Path, str])				->				None:

    """simple docstring"""







    ...







class 		snake_case						(	SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_  ):



   '''simple docstring'''






   snake_case_					: List[bytes]          =		[]

   @staticmethod
   def      UpperCamelCase_  (					lowerCAmelCase							:			Union[Path, str]				,		lowerCAmelCase							:			int)				->				Dict:

    """simple docstring"""







    with open(lowerCAmelCase				,		"""rb""") as f:
     return f.read(lowerCAmelCase)


   @classmethod
   def      UpperCamelCase_  (					cls							:			Optional[int]				,		lowerCAmelCase							:			Union[Path, str]				,		lowerCAmelCase							:			bytes = b"")				->				bool:

    """simple docstring"""







    if not magic_number:
     _snake_case    :  Optional[Any]					=					max(len(lowerCAmelCase) for cls_magic_number in cls.magic_numbers)
     try:
      _snake_case    :  Dict					=					cls.read_magic_number(lowerCAmelCase				,		lowerCAmelCase)
     except OSError:
      return False
    return any(magic_number.startswith(lowerCAmelCase) for cls_magic_number in cls.magic_numbers)







class 		snake_case						(	SCREAMING_SNAKE_CASE_  ):



   '''simple docstring'''






   @classmethod
   def      UpperCamelCase_  (					cls							:			Optional[int]				,		lowerCAmelCase							:			Union[Path, str]				,		**lowerCAmelCase							:			List[str])				->				bool:

    """simple docstring"""







    return tarfile.is_tarfile(lowerCAmelCase)

   @staticmethod
   def      UpperCamelCase_  (					lowerCAmelCase							:			List[str]				,		lowerCAmelCase							:			Optional[int])				->				int:

    """simple docstring"""







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

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

    def badlink(lowerCAmelCase							:			Optional[int]				,		lowerCAmelCase							:			str) -> bool:
     # Links are interpreted relative to the directory containing the link
     _snake_case    :  List[str]					=					resolved(os.path.join(lowerCAmelCase				,		os.path.dirname(info.name)))
     return badpath(info.linkname				,		base=lowerCAmelCase)

    _snake_case    :  List[str]					=					resolved(lowerCAmelCase)

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


   @staticmethod
   def      UpperCamelCase_  (					lowerCAmelCase							:			Union[Path, str]				,		lowerCAmelCase							:			Union[Path, str])				->				None:

    """simple docstring"""







    os.makedirs(lowerCAmelCase				,		exist_ok=lowerCAmelCase)
    _snake_case    :  Union[str, Any]					=					tarfile.open(lowerCAmelCase)
    tar_file.extractall(lowerCAmelCase				,		members=TarExtractor.safemembers(lowerCAmelCase				,		lowerCAmelCase))
    tar_file.close()







class 		snake_case						(	SCREAMING_SNAKE_CASE_  ):



   '''simple docstring'''






   snake_case_					: Tuple          =		[b"""\x1F\x8B"""]

   @staticmethod
   def      UpperCamelCase_  (					lowerCAmelCase							:			Union[Path, str]				,		lowerCAmelCase							:			Union[Path, str])				->				None:

    """simple docstring"""







    with gzip.open(lowerCAmelCase				,		"""rb""") as gzip_file:
     with open(lowerCAmelCase				,		"""wb""") as extracted_file:
      shutil.copyfileobj(lowerCAmelCase				,		lowerCAmelCase)







class 		snake_case						(	SCREAMING_SNAKE_CASE_  ):



   '''simple docstring'''






   snake_case_					: Dict          =		[
       b"""PK\x03\x04""",
       b"""PK\x05\x06""",  # empty archive
       b"""PK\x07\x08""",  # spanned archive
   ]

   @classmethod
   def      UpperCamelCase_  (					cls							:			Any				,		lowerCAmelCase							:			Union[Path, str]				,		lowerCAmelCase							:			bytes = b"")				->				bool:

    """simple docstring"""







    if super().is_extractable(lowerCAmelCase				,		magic_number=lowerCAmelCase):
     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(lowerCAmelCase				,		"""rb""") as fp:
      _snake_case    :  Optional[Any]					=					_EndRecData(lowerCAmelCase)
      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:
         _snake_case    :  Optional[int]					=					fp.read(lowerCAmelCase)  # CD is where we expect it to be
         if len(lowerCAmelCase) == sizeCentralDir:
          _snake_case    :  str					=					struct.unpack(lowerCAmelCase				,		lowerCAmelCase)  # 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      UpperCamelCase_  (					lowerCAmelCase							:			Union[Path, str]				,		lowerCAmelCase							:			Union[Path, str])				->				None:

    """simple docstring"""







    os.makedirs(lowerCAmelCase				,		exist_ok=lowerCAmelCase)
    with zipfile.ZipFile(lowerCAmelCase				,		"""r""") as zip_file:
     zip_file.extractall(lowerCAmelCase)
     zip_file.close()







class 		snake_case						(	SCREAMING_SNAKE_CASE_  ):



   '''simple docstring'''






   snake_case_					: Optional[Any]          =		[b"""\xFD\x37\x7A\x58\x5A\x00"""]

   @staticmethod
   def      UpperCamelCase_  (					lowerCAmelCase							:			Union[Path, str]				,		lowerCAmelCase							:			Union[Path, str])				->				None:

    """simple docstring"""







    with lzma.open(lowerCAmelCase) as compressed_file:
     with open(lowerCAmelCase				,		"""wb""") as extracted_file:
      shutil.copyfileobj(lowerCAmelCase				,		lowerCAmelCase)







class 		snake_case						(	SCREAMING_SNAKE_CASE_  ):



   '''simple docstring'''






   snake_case_					: str          =		[b"""Rar!\x1a\x07\x00""", b"""Rar!\x1a\x07\x01\x00"""]  # RAR_ID  # RAR5_ID

   @staticmethod
   def      UpperCamelCase_  (					lowerCAmelCase							:			Union[Path, str]				,		lowerCAmelCase							:			Union[Path, str])				->				None:

    """simple docstring"""







    if not config.RARFILE_AVAILABLE:
     raise ImportError("""Please pip install rarfile""")
    import rarfile

    os.makedirs(lowerCAmelCase				,		exist_ok=lowerCAmelCase)
    _snake_case    :  Any					=					rarfile.RarFile(lowerCAmelCase)
    rf.extractall(lowerCAmelCase)
    rf.close()







class 		snake_case						(	SCREAMING_SNAKE_CASE_  ):



   '''simple docstring'''






   snake_case_					: List[Any]          =		[b"""\x28\xb5\x2F\xFD"""]

   @staticmethod
   def      UpperCamelCase_  (					lowerCAmelCase							:			Union[Path, str]				,		lowerCAmelCase							:			Union[Path, str])				->				None:

    """simple docstring"""







    if not config.ZSTANDARD_AVAILABLE:
     raise ImportError("""Please pip install zstandard""")
    import zstandard as zstd

    _snake_case    :  Dict					=					zstd.ZstdDecompressor()
    with open(lowerCAmelCase				,		"""rb""") as ifh, open(lowerCAmelCase				,		"""wb""") as ofh:
     dctx.copy_stream(lowerCAmelCase				,		lowerCAmelCase)







class 		snake_case						(	SCREAMING_SNAKE_CASE_  ):



   '''simple docstring'''






   snake_case_					: List[Any]          =		[b"""\x42\x5A\x68"""]

   @staticmethod
   def      UpperCamelCase_  (					lowerCAmelCase							:			Union[Path, str]				,		lowerCAmelCase							:			Union[Path, str])				->				None:

    """simple docstring"""







    with bza.open(lowerCAmelCase				,		"""rb""") as compressed_file:
     with open(lowerCAmelCase				,		"""wb""") as extracted_file:
      shutil.copyfileobj(lowerCAmelCase				,		lowerCAmelCase)







class 		snake_case						(	SCREAMING_SNAKE_CASE_  ):



   '''simple docstring'''






   snake_case_					: Tuple          =		[b"""\x37\x7A\xBC\xAF\x27\x1C"""]

   @staticmethod
   def      UpperCamelCase_  (					lowerCAmelCase							:			Union[Path, str]				,		lowerCAmelCase							:			Union[Path, str])				->				None:

    """simple docstring"""







    if not config.PY7ZR_AVAILABLE:
     raise ImportError("""Please pip install py7zr""")
    import pyazr

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







class 		snake_case						(	SCREAMING_SNAKE_CASE_  ):



   '''simple docstring'''






   snake_case_					: Union[str, Any]          =		[b"""\x04\x22\x4D\x18"""]

   @staticmethod
   def      UpperCamelCase_  (					lowerCAmelCase							:			Union[Path, str]				,		lowerCAmelCase							:			Union[Path, str])				->				None:

    """simple docstring"""







    if not config.LZ4_AVAILABLE:
     raise ImportError("""Please pip install lz4""")
    import lza.frame

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







class 		snake_case						:



   '''simple docstring'''






   snake_case_					: 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      UpperCamelCase_  (					cls							:			Any)				->				List[str]:

    """simple docstring"""







    return max(
        len(lowerCAmelCase)
        for extractor in cls.extractors.values()
        if issubclass(lowerCAmelCase				,		lowerCAmelCase)
        for extractor_magic_number in extractor.magic_numbers)

   @staticmethod
   def      UpperCamelCase_  (					lowerCAmelCase							:			Union[Path, str]				,		lowerCAmelCase							:			int)				->				List[Any]:

    """simple docstring"""







    try:
     return MagicNumberBaseExtractor.read_magic_number(lowerCAmelCase				,		magic_number_length=lowerCAmelCase)
    except OSError:
     return b""

   @classmethod
   def      UpperCamelCase_  (					cls							:			List[Any]				,		lowerCAmelCase							:			Union[Path, str]				,		lowerCAmelCase							:			bool = False)				->				bool:

    """simple docstring"""







    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=lowerCAmelCase				,		)
    _snake_case    :  str					=					cls.infer_extractor_format(lowerCAmelCase)
    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      UpperCamelCase_  (					cls							:			Tuple				,		lowerCAmelCase							:			Union[Path, str])				->				str:  # <Added version="2.4.0"/>

    """simple docstring"""







    _snake_case    :  List[str]					=					cls._get_magic_number_max_length()
    _snake_case    :  Union[str, Any]					=					cls._read_magic_number(lowerCAmelCase				,		lowerCAmelCase)
    for extractor_format, extractor in cls.extractors.items():
     if extractor.is_extractable(lowerCAmelCase				,		magic_number=lowerCAmelCase):
      return extractor_format


   @classmethod
   def      UpperCamelCase_  (					cls							:			List[Any]				,		lowerCAmelCase							:			Union[Path, str]				,		lowerCAmelCase							:			Union[Path, str]				,		lowerCAmelCase							:			Optional[str] = None				,		lowerCAmelCase							:			Optional[BaseExtractor] = "deprecated"				,		)				->				None:

    """simple docstring"""







    os.makedirs(os.path.dirname(lowerCAmelCase)				,		exist_ok=lowerCAmelCase)
    # Prevent parallel extractions
    _snake_case    :  str					=					str(Path(lowerCAmelCase).with_suffix(""".lock"""))
    with FileLock(lowerCAmelCase):
     shutil.rmtree(lowerCAmelCase				,		ignore_errors=lowerCAmelCase)
     if extractor_format or extractor != "deprecated":
      if extractor != "deprecated" or not isinstance(lowerCAmelCase				,		lowerCAmelCase):  # 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=lowerCAmelCase				,		)
       _snake_case    :  str					=					extractor if extractor != """deprecated""" else extractor_format
      else:
       _snake_case    :  List[Any]					=					cls.extractors[extractor_format]
      return extractor.extract(lowerCAmelCase				,		lowerCAmelCase)
     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=lowerCAmelCase				,		)
      for extractor in cls.extractors.values():
       if extractor.is_extractable(lowerCAmelCase):
        return extractor.extract(lowerCAmelCase				,		lowerCAmelCase)





from __future__ import annotations

import unittest

from transformers import is_tf_available
from transformers.testing_utils import require_tf, slow

from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipeline_mixin import PipelineTesterMixin


if is_tf_available():
  import numpy
  import tensorflow as tf

  from transformers import (
      TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
      TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
      TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
      BertConfig,
      DPRConfig,
      TFDPRContextEncoder,
      TFDPRQuestionEncoder,
      TFDPRReader,
  )







class 		snake_case						:



   '''simple docstring'''






   def __init__(					self							:			Optional[Any]				,		lowerCAmelCase							:			str				,		lowerCAmelCase							:			Optional[Any]=13				,		lowerCAmelCase							:			int=7				,		lowerCAmelCase							:			Optional[int]=True				,		lowerCAmelCase							:			Optional[Any]=True				,		lowerCAmelCase							:			List[str]=True				,		lowerCAmelCase							:			str=True				,		lowerCAmelCase							:			Any=99				,		lowerCAmelCase							:			Dict=32				,		lowerCAmelCase							:			List[str]=2				,		lowerCAmelCase							:			str=4				,		lowerCAmelCase							:			List[str]=37				,		lowerCAmelCase							:			Dict="gelu"				,		lowerCAmelCase							:			Optional[int]=0.1				,		lowerCAmelCase							:			Any=0.1				,		lowerCAmelCase							:			List[Any]=512				,		lowerCAmelCase							:			Optional[int]=16				,		lowerCAmelCase							:			Dict=2				,		lowerCAmelCase							:			str=0.02				,		lowerCAmelCase							:			Optional[Any]=3				,		lowerCAmelCase							:			Optional[Any]=4				,		lowerCAmelCase							:			Tuple=None				,		lowerCAmelCase							:			List[Any]=0				,		)				->				int:

    """simple docstring"""







    _snake_case    :  Dict					=					parent
    _snake_case    :  int					=					batch_size
    _snake_case    :  str					=					seq_length
    _snake_case    :  List[str]					=					is_training
    _snake_case    :  Tuple					=					use_input_mask
    _snake_case    :  Optional[Any]					=					use_token_type_ids
    _snake_case    :  Any					=					use_labels
    _snake_case    :  str					=					vocab_size
    _snake_case    :  List[str]					=					hidden_size
    _snake_case    :  List[str]					=					num_hidden_layers
    _snake_case    :  Dict					=					num_attention_heads
    _snake_case    :  int					=					intermediate_size
    _snake_case    :  Any					=					hidden_act
    _snake_case    :  List[Any]					=					hidden_dropout_prob
    _snake_case    :  Tuple					=					attention_probs_dropout_prob
    _snake_case    :  List[Any]					=					max_position_embeddings
    _snake_case    :  int					=					type_vocab_size
    _snake_case    :  Dict					=					type_sequence_label_size
    _snake_case    :  List[str]					=					initializer_range
    _snake_case    :  Dict					=					num_labels
    _snake_case    :  Optional[Any]					=					num_choices
    _snake_case    :  Dict					=					scope
    _snake_case    :  List[Any]					=					projection_dim

   def      UpperCamelCase_  (					self							:			Dict)				->				List[str]:

    """simple docstring"""







    _snake_case    :  Optional[int]					=					ids_tensor([self.batch_size, self.seq_length]				,		self.vocab_size)

    _snake_case    :  List[str]					=					None
    if self.use_input_mask:
     # follow test_modeling_tf_ctrl.py
     _snake_case    :  List[Any]					=					random_attention_mask([self.batch_size, self.seq_length])

    _snake_case    :  str					=					None
    if self.use_token_type_ids:
     _snake_case    :  Optional[Any]					=					ids_tensor([self.batch_size, self.seq_length]				,		self.type_vocab_size)

    _snake_case    :  Tuple					=					None
    _snake_case    :  Any					=					None
    _snake_case    :  str					=					None
    if self.use_labels:
     _snake_case    :  Optional[Any]					=					ids_tensor([self.batch_size]				,		self.type_sequence_label_size)
     _snake_case    :  Union[str, Any]					=					ids_tensor([self.batch_size, self.seq_length]				,		self.num_labels)
     _snake_case    :  Optional[Any]					=					ids_tensor([self.batch_size]				,		self.num_choices)

    _snake_case    :  Union[str, Any]					=					BertConfig(
        vocab_size=self.vocab_size				,		hidden_size=self.hidden_size				,		num_hidden_layers=self.num_hidden_layers				,		num_attention_heads=self.num_attention_heads				,		intermediate_size=self.intermediate_size				,		hidden_act=self.hidden_act				,		hidden_dropout_prob=self.hidden_dropout_prob				,		attention_probs_dropout_prob=self.attention_probs_dropout_prob				,		max_position_embeddings=self.max_position_embeddings				,		type_vocab_size=self.type_vocab_size				,		is_decoder=lowerCAmelCase				,		initializer_range=self.initializer_range				,		)
    _snake_case    :  Optional[int]					=					DPRConfig(projection_dim=self.projection_dim				,		**config.to_dict())

    return config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels

   def      UpperCamelCase_  (					self							:			Optional[int]				,		lowerCAmelCase							:			Optional[Any]				,		lowerCAmelCase							:			Optional[Any]				,		lowerCAmelCase							:			List[str]				,		lowerCAmelCase							:			Optional[Any]				,		lowerCAmelCase							:			Tuple				,		lowerCAmelCase							:			Tuple				,		lowerCAmelCase							:			List[str])				->				List[Any]:

    """simple docstring"""







    _snake_case    :  Dict					=					TFDPRContextEncoder(config=lowerCAmelCase)
    _snake_case    :  Union[str, Any]					=					model(lowerCAmelCase				,		attention_mask=lowerCAmelCase				,		token_type_ids=lowerCAmelCase)
    _snake_case    :  Optional[int]					=					model(lowerCAmelCase				,		token_type_ids=lowerCAmelCase)
    _snake_case    :  List[str]					=					model(lowerCAmelCase)
    self.parent.assertEqual(result.pooler_output.shape				,		(self.batch_size, self.projection_dim or self.hidden_size))

   def      UpperCamelCase_  (					self							:			List[Any]				,		lowerCAmelCase							:			int				,		lowerCAmelCase							:			List[str]				,		lowerCAmelCase							:			Optional[Any]				,		lowerCAmelCase							:			Any				,		lowerCAmelCase							:			Any				,		lowerCAmelCase							:			Union[str, Any]				,		lowerCAmelCase							:			Optional[int])				->				int:

    """simple docstring"""







    _snake_case    :  Optional[int]					=					TFDPRQuestionEncoder(config=lowerCAmelCase)
    _snake_case    :  List[Any]					=					model(lowerCAmelCase				,		attention_mask=lowerCAmelCase				,		token_type_ids=lowerCAmelCase)
    _snake_case    :  List[Any]					=					model(lowerCAmelCase				,		token_type_ids=lowerCAmelCase)
    _snake_case    :  Tuple					=					model(lowerCAmelCase)
    self.parent.assertEqual(result.pooler_output.shape				,		(self.batch_size, self.projection_dim or self.hidden_size))

   def      UpperCamelCase_  (					self							:			List[str]				,		lowerCAmelCase							:			List[str]				,		lowerCAmelCase							:			Union[str, Any]				,		lowerCAmelCase							:			Dict				,		lowerCAmelCase							:			Optional[int]				,		lowerCAmelCase							:			str				,		lowerCAmelCase							:			Tuple				,		lowerCAmelCase							:			str)				->				Tuple:

    """simple docstring"""







    _snake_case    :  Optional[Any]					=					TFDPRReader(config=lowerCAmelCase)
    _snake_case    :  Any					=					model(lowerCAmelCase				,		attention_mask=lowerCAmelCase)

    self.parent.assertEqual(result.start_logits.shape				,		(self.batch_size, self.seq_length))
    self.parent.assertEqual(result.end_logits.shape				,		(self.batch_size, self.seq_length))
    self.parent.assertEqual(result.relevance_logits.shape				,		(self.batch_size,))


   def      UpperCamelCase_  (					self							:			str)				->				Any:

    """simple docstring"""







    _snake_case    :  List[Any]					=					self.prepare_config_and_inputs()
    (
        (
        _snake_case
    )	,    (
        _snake_case
    )	,    (
        _snake_case
    )	,    (
        _snake_case
    )	,    (
        _snake_case
    )	,    (
        _snake_case
    )	,    (
        _snake_case
    )	,    
    )    :  Union[str, Any]					=					config_and_inputs
    _snake_case    :  Union[str, Any]					=					{"""input_ids""": input_ids}
    return config, inputs_dict







@require_tf
class 		snake_case						(	SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_					,unittest.TestCase  ):



   '''simple docstring'''






   snake_case_					: Any          =		(
       (
           TFDPRContextEncoder,
           TFDPRQuestionEncoder,
           TFDPRReader,
       )
       if is_tf_available()
       else ()
   )
   snake_case_					: List[str]          =		{"""feature-extraction""": TFDPRQuestionEncoder} if is_tf_available() else {}

   snake_case_					: Tuple          =		False
   snake_case_					: str          =		False
   snake_case_					: Tuple          =		False
   snake_case_					: int          =		False
   snake_case_					: List[Any]          =		False

   def      UpperCamelCase_  (					self							:			Tuple)				->				str:

    """simple docstring"""







    _snake_case    :  List[str]					=					TFDPRModelTester(self)
    _snake_case    :  Dict					=					ConfigTester(self				,		config_class=lowerCAmelCase				,		hidden_size=37)

   def      UpperCamelCase_  (					self							:			List[Any])				->				Optional[Any]:

    """simple docstring"""







    self.config_tester.run_common_tests()

   def      UpperCamelCase_  (					self							:			List[str])				->				Optional[int]:

    """simple docstring"""







    _snake_case    :  Any					=					self.model_tester.prepare_config_and_inputs()
    self.model_tester.create_and_check_dpr_context_encoder(*lowerCAmelCase)

   def      UpperCamelCase_  (					self							:			List[str])				->				Optional[Any]:

    """simple docstring"""







    _snake_case    :  str					=					self.model_tester.prepare_config_and_inputs()
    self.model_tester.create_and_check_dpr_question_encoder(*lowerCAmelCase)

   def      UpperCamelCase_  (					self							:			List[str])				->				Tuple:

    """simple docstring"""







    _snake_case    :  str					=					self.model_tester.prepare_config_and_inputs()
    self.model_tester.create_and_check_dpr_reader(*lowerCAmelCase)


   @slow
   def      UpperCamelCase_  (					self							:			List[str])				->				Any:

    """simple docstring"""







    for model_name in TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
     _snake_case    :  List[Any]					=					TFDPRContextEncoder.from_pretrained(lowerCAmelCase)
     self.assertIsNotNone(lowerCAmelCase)

    for model_name in TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
     _snake_case    :  List[str]					=					TFDPRContextEncoder.from_pretrained(lowerCAmelCase)
     self.assertIsNotNone(lowerCAmelCase)

    for model_name in TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
     _snake_case    :  Any					=					TFDPRQuestionEncoder.from_pretrained(lowerCAmelCase)
     self.assertIsNotNone(lowerCAmelCase)

    for model_name in TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
     _snake_case    :  Union[str, Any]					=					TFDPRReader.from_pretrained(lowerCAmelCase)
     self.assertIsNotNone(lowerCAmelCase)







@require_tf
class 		snake_case						(	unittest.TestCase  ):



   '''simple docstring'''






   @slow
   def      UpperCamelCase_  (					self							:			List[str])				->				Optional[int]:

    """simple docstring"""







    _snake_case    :  List[str]					=					TFDPRQuestionEncoder.from_pretrained("""facebook/dpr-question_encoder-single-nq-base""")

    _snake_case    :  str					=					tf.constant(
        [[101, 7592, 1010, 2003, 2026, 3899, 1_0140, 1029, 102]])  # [CLS] hello, is my dog cute? [SEP]
    _snake_case    :  Optional[int]					=					model(lowerCAmelCase)[0]  # embedding shape = (1, 768)
    # compare the actual values for a slice.
    _snake_case    :  Union[str, Any]					=					tf.constant(
        [
            [
                0.03_236_253,
                0.12_753_335,
                0.16_818_509,
                0.00_279_786,
                0.3_896_933,
                0.24_264_945,
                0.2_178_971,
                -0.02_335_227,
                -0.08_481_959,
                -0.14_324_117,
            ]
        ])
    self.assertTrue(numpy.allclose(output[:, :10].numpy()				,		expected_slice.numpy()				,		atol=1E-4))
