



'''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


__a          =		get_logger(__name__)







class     UpperCAmelCase_       :
    """simple docstring"""







    def __init__(    self					:     Any ,     snake_case_					:     Optional[str] = None						):
          snake_case__  :    List[Any]    						=      (
              os.path.join(snake_case_ ,     config.EXTRACTED_DATASETS_DIR						) if cache_dir else config.EXTRACTED_DATASETS_PATH
          )
          snake_case__  :    Any    						=      Extractor




    def lowerCamelCase       (    self					:     Optional[Any] ,     snake_case_					:     str						):
          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__  :    str    						=      os.path.abspath(snake_case_						)
          return os.path.join(self.extract_dir ,     hash_url_to_filename(snake_case_						)						)




    def lowerCamelCase       (    self					:     Optional[Any] ,     snake_case_					:     str ,     snake_case_					:     bool						):
          return force_extract or (
              not os.path.isfile(snake_case_						) and not (os.path.isdir(snake_case_						) and os.listdir(snake_case_						))
          )




    def lowerCamelCase       (    self					:     str ,     snake_case_					:     str ,     snake_case_					:     bool = False						):
          snake_case__  :    Dict    						=      self.extractor.infer_extractor_format(snake_case_						)
          if not extractor_format:
                return input_path
          snake_case__  :    List[Any]    						=      self._get_output_path(snake_case_						)
          if self._do_extract(snake_case_ ,     snake_case_						):
                self.extractor.extract(snake_case_ ,     snake_case_ ,     snake_case_						)
          return output_path







class     UpperCAmelCase_       (       _a	):
    """simple docstring"""







    @classmethod
    @abstractmethod
    def lowerCamelCase       (    cls					:     Optional[int] ,     snake_case_					:     Union[Path, str] ,     **snake_case_					:     Tuple						):
          ...




    @staticmethod
    @abstractmethod
    def lowerCamelCase       (    snake_case_					:     Union[Path, str] ,     snake_case_					:     Union[Path, str]						):
          ...







class     UpperCAmelCase_       (       _a		,		_a	):
    """simple docstring"""







    lowercase					=		[]




    @staticmethod
    def lowerCamelCase       (    snake_case_					:     Union[Path, str] ,     snake_case_					:     int						):
          with open(snake_case_ ,     """rb"""						) as f:
                return f.read(snake_case_						)




    @classmethod
    def lowerCamelCase       (    cls					:     Any ,     snake_case_					:     Union[Path, str] ,     snake_case_					:     bytes = b""						):
          if not magic_number:
                snake_case__  :    Optional[Any]    						=      max(len(snake_case_						) for cls_magic_number in cls.magic_numbers						)
                try:
                      snake_case__  :    List[str]    						=      cls.read_magic_number(snake_case_ ,     snake_case_						)
                except OSError:
                      return False
          return any(magic_number.startswith(snake_case_						) for cls_magic_number in cls.magic_numbers						)







class     UpperCAmelCase_       (       _a	):
    """simple docstring"""







    @classmethod
    def lowerCamelCase       (    cls					:     Union[str, Any] ,     snake_case_					:     Union[Path, str] ,     **snake_case_					:     Union[str, Any]						):
          return tarfile.is_tarfile(snake_case_						)




    @staticmethod
    def lowerCamelCase       (    snake_case_					:     List[str] ,     snake_case_					:     Optional[Any]						):

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

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

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

          snake_case__  :    Optional[int]    						=      resolved(snake_case_						)

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




    @staticmethod
    def lowerCamelCase       (    snake_case_					:     Union[Path, str] ,     snake_case_					:     Union[Path, str]						):
          os.makedirs(snake_case_ ,     exist_ok=snake_case_						)
          snake_case__  :    List[Any]    						=      tarfile.open(snake_case_						)
          tar_file.extractall(snake_case_ ,     members=TarExtractor.safemembers(snake_case_ ,     snake_case_						)						)
          tar_file.close()







class     UpperCAmelCase_       (       _a	):
    """simple docstring"""







    lowercase					=		[b"\x1F\x8B"]




    @staticmethod
    def lowerCamelCase       (    snake_case_					:     Union[Path, str] ,     snake_case_					:     Union[Path, str]						):
          with gzip.open(snake_case_ ,     """rb"""						) as gzip_file:
                with open(snake_case_ ,     """wb"""						) as extracted_file:
                      shutil.copyfileobj(snake_case_ ,     snake_case_						)







class     UpperCAmelCase_       (       _a	):
    """simple docstring"""







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




    @classmethod
    def lowerCamelCase       (    cls					:     int ,     snake_case_					:     Union[Path, str] ,     snake_case_					:     bytes = b""						):
          if super().is_extractable(snake_case_ ,     magic_number=snake_case_						):
                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(snake_case_ ,     """rb"""						) as fp:
                      snake_case__  :    Any    						=      _EndRecData(snake_case_						)
                      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__  :    List[str]    						=      fp.read(snake_case_						)  # CD is where we expect it to be
                                        if len(snake_case_						) == sizeCentralDir:
                                              snake_case__  :    Dict    						=      struct.unpack(snake_case_ ,     snake_case_						)  # 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 lowerCamelCase       (    snake_case_					:     Union[Path, str] ,     snake_case_					:     Union[Path, str]						):
          os.makedirs(snake_case_ ,     exist_ok=snake_case_						)
          with zipfile.ZipFile(snake_case_ ,     """r"""						) as zip_file:
                zip_file.extractall(snake_case_						)
                zip_file.close()







class     UpperCAmelCase_       (       _a	):
    """simple docstring"""







    lowercase					=		[b"\xFD\x37\x7A\x58\x5A\x00"]




    @staticmethod
    def lowerCamelCase       (    snake_case_					:     Union[Path, str] ,     snake_case_					:     Union[Path, str]						):
          with lzma.open(snake_case_						) as compressed_file:
                with open(snake_case_ ,     """wb"""						) as extracted_file:
                      shutil.copyfileobj(snake_case_ ,     snake_case_						)







class     UpperCAmelCase_       (       _a	):
    """simple docstring"""







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




    @staticmethod
    def lowerCamelCase       (    snake_case_					:     Union[Path, str] ,     snake_case_					:     Union[Path, str]						):
          if not config.RARFILE_AVAILABLE:
                raise ImportError("""Please pip install rarfile"""						)
          import rarfile

          os.makedirs(snake_case_ ,     exist_ok=snake_case_						)
          snake_case__  :    Tuple    						=      rarfile.RarFile(snake_case_						)
          rf.extractall(snake_case_						)
          rf.close()







class     UpperCAmelCase_       (       _a	):
    """simple docstring"""







    lowercase					=		[b"\x28\xb5\x2F\xFD"]




    @staticmethod
    def lowerCamelCase       (    snake_case_					:     Union[Path, str] ,     snake_case_					:     Union[Path, str]						):
          if not config.ZSTANDARD_AVAILABLE:
                raise ImportError("""Please pip install zstandard"""						)
          import zstandard as zstd

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







class     UpperCAmelCase_       (       _a	):
    """simple docstring"""







    lowercase					=		[b"\x42\x5A\x68"]




    @staticmethod
    def lowerCamelCase       (    snake_case_					:     Union[Path, str] ,     snake_case_					:     Union[Path, str]						):
          with bza.open(snake_case_ ,     """rb"""						) as compressed_file:
                with open(snake_case_ ,     """wb"""						) as extracted_file:
                      shutil.copyfileobj(snake_case_ ,     snake_case_						)







class     UpperCAmelCase_       (       _a	):
    """simple docstring"""







    lowercase					=		[b"\x37\x7A\xBC\xAF\x27\x1C"]




    @staticmethod
    def lowerCamelCase       (    snake_case_					:     Union[Path, str] ,     snake_case_					:     Union[Path, str]						):
          if not config.PY7ZR_AVAILABLE:
                raise ImportError("""Please pip install py7zr"""						)
          import pyazr

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







class     UpperCAmelCase_       (       _a	):
    """simple docstring"""







    lowercase					=		[b"\x04\x22\x4D\x18"]




    @staticmethod
    def lowerCamelCase       (    snake_case_					:     Union[Path, str] ,     snake_case_					:     Union[Path, str]						):
          if not config.LZ4_AVAILABLE:
                raise ImportError("""Please pip install lz4"""						)
          import lza.frame

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







class     UpperCAmelCase_       :
    """simple docstring"""







    lowercase					=		{
        "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 lowerCamelCase       (    cls					:     List[str]						):
          return max(
              len(snake_case_						)
              for extractor in cls.extractors.values()
              if issubclass(snake_case_ ,     snake_case_						)
              for extractor_magic_number in extractor.magic_numbers						)




    @staticmethod
    def lowerCamelCase       (    snake_case_					:     Union[Path, str] ,     snake_case_					:     int						):
          try:
                return MagicNumberBaseExtractor.read_magic_number(snake_case_ ,     magic_number_length=snake_case_						)
          except OSError:
                return b""




    @classmethod
    def lowerCamelCase       (    cls					:     int ,     snake_case_					:     Union[Path, str] ,     snake_case_					:     bool = 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=snake_case_ ,     )
          snake_case__  :    str    						=      cls.infer_extractor_format(snake_case_						)
          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 lowerCamelCase       (    cls					:     Optional[int] ,     snake_case_					:     Union[Path, str]						):  # <Added version="2.4.0"/>
          snake_case__  :    str    						=      cls._get_magic_number_max_length()
          snake_case__  :    Dict    						=      cls._read_magic_number(snake_case_ ,     snake_case_						)
          for extractor_format, extractor in cls.extractors.items():
                if extractor.is_extractable(snake_case_ ,     magic_number=snake_case_						):
                      return extractor_format




    @classmethod
    def lowerCamelCase       (    cls					:     Any ,     snake_case_					:     Union[Path, str] ,     snake_case_					:     Union[Path, str] ,     snake_case_					:     Optional[str] = None ,     snake_case_					:     Optional[BaseExtractor] = "deprecated" ,     ):
          os.makedirs(os.path.dirname(snake_case_						) ,     exist_ok=snake_case_						)
          # Prevent parallel extractions
          snake_case__  :    str    						=      str(Path(snake_case_						).with_suffix(""".lock"""						)						)
          with FileLock(snake_case_						):
                shutil.rmtree(snake_case_ ,     ignore_errors=snake_case_						)
                if extractor_format or extractor != "deprecated":
                      if extractor != "deprecated" or not isinstance(snake_case_ ,     snake_case_						):  # 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=snake_case_ ,     )
                            snake_case__  :    int    						=      extractor if extractor != """deprecated""" else extractor_format
                      else:
                            snake_case__  :    str    						=      cls.extractors[extractor_format]
                      return extractor.extract(snake_case_ ,     snake_case_						)
                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=snake_case_ ,     )
                      for extractor in cls.extractors.values():
                            if extractor.is_extractable(snake_case_						):
                                  return extractor.extract(snake_case_ ,     snake_case_						)

from typing import List, Optional, Union

import numpy as np

from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import BatchFeature
from ....file_utils import PaddingStrategy, TensorType
from ....utils import logging


__UpperCamelCase		:       Optional[Any]									=     logging.get_logger(__name__)





class 					lowercase__						(   UpperCamelCase_):
						UpperCamelCase_     =		["""input_features""", """attention_mask"""]


						def __init__(       self	:				Any    ,		UpperCamelCase__	:				List[str]=80    ,		UpperCamelCase__	:				Tuple=1_6000    ,		UpperCamelCase__	:				Dict=0.0    ,		UpperCamelCase__	:				Tuple=10    ,		UpperCamelCase__	:				int=25    ,		UpperCamelCase__	:				Optional[Any]="hamming_window"    ,		UpperCamelCase__	:				Tuple=3_2768.0    ,		UpperCamelCase__	:				str=0.97    ,		UpperCamelCase__	:				List[str]=1.0    ,		UpperCamelCase__	:				Optional[int]=True    ,		UpperCamelCase__	:				Dict=True    ,		UpperCamelCase__	:				List[str]=False    ,		**UpperCamelCase__	:				List[str]    ,		):





												'''simple docstring'''





												super().__init__(feature_size=UpperCamelCase__    ,		sampling_rate=UpperCamelCase__    ,		padding_value=UpperCamelCase__    ,		**UpperCamelCase__						)

												SCREAMING_SNAKE_CASE							:    Dict							=							feature_size
												SCREAMING_SNAKE_CASE							:    Union[str, Any]							=							sampling_rate
												SCREAMING_SNAKE_CASE							:    int							=							padding_value
												SCREAMING_SNAKE_CASE							:    Optional[Any]							=							hop_length
												SCREAMING_SNAKE_CASE							:    Tuple							=							win_length
												SCREAMING_SNAKE_CASE							:    Union[str, Any]							=							frame_signal_scale
												SCREAMING_SNAKE_CASE							:    int							=							preemphasis_coeff
												SCREAMING_SNAKE_CASE							:    List[Any]							=							mel_floor
												SCREAMING_SNAKE_CASE							:    int							=							normalize_means
												SCREAMING_SNAKE_CASE							:    List[str]							=							normalize_vars
												SCREAMING_SNAKE_CASE							:    Any							=							win_function
												SCREAMING_SNAKE_CASE							:    Union[str, Any]							=							return_attention_mask

												SCREAMING_SNAKE_CASE							:    int							=							win_length * sampling_rate // 1000
												SCREAMING_SNAKE_CASE							:    Optional[int]							=							hop_length * sampling_rate // 1000

												SCREAMING_SNAKE_CASE							:    int							=							optimal_fft_length(self.sample_size						)
												SCREAMING_SNAKE_CASE							:    Tuple							=							(self.n_fft // 2) + 1


						def        __A       (       self	:				str    ,		UpperCamelCase__	:				np.array						):





												'''simple docstring'''





												if self.win_function == "hamming_window":
																		SCREAMING_SNAKE_CASE							:    List[str]							=							window_function(window_length=self.sample_size    ,		name=self.win_function    ,		periodic=UpperCamelCase__						)
												else:
																		SCREAMING_SNAKE_CASE							:    Tuple							=							window_function(window_length=self.sample_size    ,		name=self.win_function						)

												SCREAMING_SNAKE_CASE							:    Optional[Any]							=							mel_filter_bank(
												    num_frequency_bins=self.n_freqs    ,		num_mel_filters=self.feature_size    ,		min_frequency=0.0    ,		max_frequency=self.sampling_rate / 2.0    ,		sampling_rate=self.sampling_rate    ,		)

												SCREAMING_SNAKE_CASE							:    Tuple							=							spectrogram(
												    one_waveform * self.frame_signal_scale    ,		window=UpperCamelCase__    ,		frame_length=self.sample_size    ,		hop_length=self.sample_stride    ,		fft_length=self.n_fft    ,		center=UpperCamelCase__    ,		preemphasis=self.preemphasis_coeff    ,		mel_filters=UpperCamelCase__    ,		mel_floor=self.mel_floor    ,		log_mel='''log'''    ,		)
												return msfc_features.T


						def        __A       (       self	:				int    ,		UpperCamelCase__	:				Optional[Any]    ,		UpperCamelCase__	:				List[Any]    ,		UpperCamelCase__	:				Optional[int]						):





												'''simple docstring'''





												if self.normalize_means:
																		SCREAMING_SNAKE_CASE							:    str							=							x[:input_length].mean(axis=0						)
																		SCREAMING_SNAKE_CASE							:    List[str]							=							np.subtract(UpperCamelCase__    ,		UpperCamelCase__						)
												if self.normalize_vars:
																		SCREAMING_SNAKE_CASE							:    str							=							x[:input_length].std(axis=0						)
																		SCREAMING_SNAKE_CASE							:    Optional[int]							=							np.divide(UpperCamelCase__    ,		UpperCamelCase__						)

												if input_length < x.shape[0]:
																		SCREAMING_SNAKE_CASE							:    List[str]							=							padding_value

												# make sure array is in float32
												SCREAMING_SNAKE_CASE							:    str							=							x.astype(np.floataa						)

												return x


						def        __A       (       self	:				Union[str, Any]    ,		UpperCamelCase__	:				List[np.ndarray]    ,		UpperCamelCase__	:				Optional[np.ndarray] = None						):





												'''simple docstring'''





												SCREAMING_SNAKE_CASE							:    Tuple							=							attention_mask.sum(-1						) if attention_mask is not None else [x.shape[0] for x in input_features]
												return [self._normalize_one(UpperCamelCase__    ,		UpperCamelCase__    ,		self.padding_value						) for x, n in zip(UpperCamelCase__    ,		UpperCamelCase__						)]



						def __call__(       self	:				Dict    ,		UpperCamelCase__	:				Union[np.ndarray, List[float], List[np.ndarray], List[List[float]]]    ,		UpperCamelCase__	:				Union[bool, str, PaddingStrategy] = False    ,		UpperCamelCase__	:				Optional[int] = None    ,		UpperCamelCase__	:				bool = False    ,		UpperCamelCase__	:				Optional[int] = None    ,		UpperCamelCase__	:				Optional[bool] = None    ,		UpperCamelCase__	:				Optional[Union[str, TensorType]] = None    ,		UpperCamelCase__	:				Optional[int] = None    ,		**UpperCamelCase__	:				Optional[int]    ,		):





												'''simple docstring'''





												if sampling_rate is not None:
																		if sampling_rate != self.sampling_rate:
																								raise ValueError(
																								    f"""The model corresponding to this feature extractor: {self} was trained using a sampling rate of"""
																								    f""" {self.sampling_rate}. Please make sure that the provided `raw_speech` input was sampled with"""
																								    f""" {self.sampling_rate} and not {sampling_rate}."""						)
												else:
																		logger.warning(
																		    '''It is strongly recommended to pass the ``sampling_rate`` argument to this function. '''
																		    '''Failing to do so can result in silent errors that might be hard to debug.'''						)

												SCREAMING_SNAKE_CASE							:    Any							=							isinstance(UpperCamelCase__    ,		np.ndarray						) and len(raw_speech.shape						) > 1
												if is_batched_numpy and len(raw_speech.shape						) > 2:
																		raise ValueError(f"""Only mono-channel audio is supported for input to {self}"""						)
												SCREAMING_SNAKE_CASE							:    str							=							is_batched_numpy or (
												    isinstance(UpperCamelCase__    ,		(list, tuple)						) and (isinstance(raw_speech[0]    ,		(np.ndarray, tuple, list)						))
												)

												if is_batched:
																		SCREAMING_SNAKE_CASE							:    int							=							[np.asarray(UpperCamelCase__    ,		dtype=np.floataa						) for speech in raw_speech]
												elif not is_batched and not isinstance(UpperCamelCase__    ,		np.ndarray						):
																		SCREAMING_SNAKE_CASE							:    Dict							=							np.asarray(UpperCamelCase__    ,		dtype=np.floataa						)
												elif isinstance(UpperCamelCase__    ,		np.ndarray						) and raw_speech.dtype is np.dtype(np.floataa						):
																		SCREAMING_SNAKE_CASE							:    Optional[Any]							=							raw_speech.astype(np.floataa						)

												# always return batch
												if not is_batched:
																		SCREAMING_SNAKE_CASE							:    List[str]							=							[raw_speech]

												# extract fbank features
												SCREAMING_SNAKE_CASE							:    Optional[Any]							=							[self._extract_mfsc_features(UpperCamelCase__						) for one_waveform in raw_speech]

												# convert into correct format for padding
												SCREAMING_SNAKE_CASE							:    Tuple							=							BatchFeature({'''input_features''': features}						)

												SCREAMING_SNAKE_CASE							:    Optional[Any]							=							self.pad(
												    UpperCamelCase__    ,		padding=UpperCamelCase__    ,		max_length=UpperCamelCase__    ,		truncation=UpperCamelCase__    ,		pad_to_multiple_of=UpperCamelCase__    ,		return_attention_mask=UpperCamelCase__    ,		**UpperCamelCase__    ,		)
												# make sure list is in array format
												SCREAMING_SNAKE_CASE							:    Union[str, Any]							=							padded_inputs.get('''input_features'''						)
												if isinstance(input_features[0]    ,		UpperCamelCase__						):
																		SCREAMING_SNAKE_CASE							:    Any							=							[np.asarray(UpperCamelCase__    ,		dtype=np.floataa						) for feature in input_features]

												SCREAMING_SNAKE_CASE							:    Union[str, Any]							=							padded_inputs.get('''attention_mask'''						)
												if attention_mask is not None:
																		SCREAMING_SNAKE_CASE							:    Optional[int]							=							[np.asarray(UpperCamelCase__    ,		dtype=np.intaa						) for array in attention_mask]

												if self.normalize_means or self.normalize_vars:
																		SCREAMING_SNAKE_CASE							:    Optional[Any]							=							(
																		    np.array(UpperCamelCase__    ,		dtype=np.intaa						)
																		    if self._get_padding_strategies(UpperCamelCase__    ,		max_length=UpperCamelCase__						) is not PaddingStrategy.DO_NOT_PAD
																		    and padding
																		    else None
																		)
																		SCREAMING_SNAKE_CASE							:    List[Any]							=							self.normalize(
																		    padded_inputs['''input_features''']    ,		attention_mask=UpperCamelCase__						)

												if return_tensors is not None:
																		SCREAMING_SNAKE_CASE							:    Union[str, Any]							=							padded_inputs.convert_to_tensors(UpperCamelCase__						)

												return padded_inputs





