

'''simple docstring'''
from typing import List, Optional, Union

import numpy as np

from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging


lowerCamelCase			:				Union[str, Any] 			=					logging.get_logger(__name__)







class 							A__   (	lowerCamelCase__  ):
		A__					=    ['input_values', 'padding_mask']





		def __init__(		self				:     str							, _a				:     Optional[Any] = 1							, _a				:     Union[str, Any] = 2_4000							, _a				:     Any = 0.0							, _a				:     Tuple = None							, _a				:     Optional[Any] = None							, **_a				:     Union[str, Any]							, )     ->   str:





							'''simple docstring'''






							super().__init__(feature_size=__lowerCamelCase							, sampling_rate=__lowerCamelCase							, padding_value=__lowerCamelCase							, **__lowerCamelCase			)
							_SCREAMING_SNAKE_CASE							   =chunk_length_s
							_SCREAMING_SNAKE_CASE							   =overlap





		@property
		def 						A  (		self				:     Optional[Any]			)     ->   Optional[int]:





							'''simple docstring'''






							if self.chunk_length_s is None:
												return None
							else:
												return int(self.chunk_length_s * self.sampling_rate			)





		@property
		def 						A  (		self				:     str			)     ->   Optional[int]:





							'''simple docstring'''






							if self.chunk_length_s is None or self.overlap is None:
												return None
							else:
												return max(1							, int((1.0 - self.overlap) * self.chunk_length			)			)





		def __call__(		self				:     Dict							, _a				:     Union[str, Any]							, _a				:     Dict = None							, _a				:     int = False							, _a				:     List[str] = None							, _a				:     int = None							, _a				:     Optional[int] = None							, )     ->   BatchFeature:





							'''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 audio 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.'			)

							if padding and truncation:
												raise ValueError('Both padding and truncation were set. Make sure you only set one.'			)
							elif padding is None:
												# by default let's pad the inputs
												_SCREAMING_SNAKE_CASE							   =True

							_SCREAMING_SNAKE_CASE							   =bool(
							    isinstance(__lowerCamelCase							, (list, tuple)			) and (isinstance(raw_audio[0]							, (np.ndarray, tuple, list)			))			)

							if is_batched:
												_SCREAMING_SNAKE_CASE							   =[np.asarray(__lowerCamelCase							, dtype=np.floataa			).T for audio in raw_audio]
							elif not is_batched and not isinstance(__lowerCamelCase							, np.ndarray			):
												_SCREAMING_SNAKE_CASE							   =np.asarray(__lowerCamelCase							, dtype=np.floataa			)
							elif isinstance(__lowerCamelCase							, np.ndarray			) and raw_audio.dtype is np.dtype(np.floataa			):
												_SCREAMING_SNAKE_CASE							   =raw_audio.astype(np.floataa			)

							# always return batch
							if not is_batched:
												_SCREAMING_SNAKE_CASE							   =[np.asarray(__lowerCamelCase			).T]

							# verify inputs are valid
							for idx, example in enumerate(__lowerCamelCase			):
												if example.ndim > 2:
																	raise ValueError(f"Expected input shape (channels, length) but got shape {example.shape}"			)
												if self.feature_size == 1 and example.ndim != 1:
																	raise ValueError(f"Expected mono audio but example has {example.shape[-1]} channels"			)
												if self.feature_size == 2 and example.shape[-1] != 2:
																	raise ValueError(f"Expected stereo audio but example has {example.shape[-1]} channels"			)

							_SCREAMING_SNAKE_CASE							   =None
							_SCREAMING_SNAKE_CASE							   =BatchFeature({'input_values': raw_audio}			)
							if self.chunk_stride is not None and self.chunk_length is not None and max_length is None:
												if truncation:
																	_SCREAMING_SNAKE_CASE							   =min(array.shape[0] for array in raw_audio			)
																	_SCREAMING_SNAKE_CASE							   =int(np.floor(max_length / self.chunk_stride			)			)
																	_SCREAMING_SNAKE_CASE							   =(nb_step - 1) * self.chunk_stride + self.chunk_length
												elif padding:
																	_SCREAMING_SNAKE_CASE							   =max(array.shape[0] for array in raw_audio			)
																	_SCREAMING_SNAKE_CASE							   =int(np.ceil(max_length / self.chunk_stride			)			)
																	_SCREAMING_SNAKE_CASE							   =(nb_step - 1) * self.chunk_stride + self.chunk_length
																	_SCREAMING_SNAKE_CASE							   ='''max_length'''
												else:
																	_SCREAMING_SNAKE_CASE							   =input_values

        # normal padding on batch
							if padded_inputs is None:
												_SCREAMING_SNAKE_CASE							   =self.pad(
												    __lowerCamelCase							, max_length=__lowerCamelCase							, truncation=__lowerCamelCase							, padding=__lowerCamelCase							, return_attention_mask=__lowerCamelCase							, )
												if padding:
																	_SCREAMING_SNAKE_CASE							   =padded_inputs.pop('attention_mask'			)

							_SCREAMING_SNAKE_CASE							   =[]
							for example in padded_inputs.pop('input_values'			):
												if self.feature_size == 1:
																	_SCREAMING_SNAKE_CASE							   =example[..., None]
												input_values.append(example.T			)

							_SCREAMING_SNAKE_CASE							   =input_values
							if return_tensors is not None:
												_SCREAMING_SNAKE_CASE							   =padded_inputs.convert_to_tensors(__lowerCamelCase			)

							return padded_inputs



'''simple docstring'''
from datasets.utils.patching import _PatchedModuleObj, patch_submodule

from . import _test_patching


def 	_lowerCAmelCase (						)				->      int:
     """simple docstring"""




     import os as original_os
     from os import path as original_path
     from os import rename as original_rename
     from os.path import dirname as original_dirname
     from os.path import join as original_join

     assert _test_patching.os is original_os
     assert _test_patching.path is original_path
     assert _test_patching.join is original_join

     assert _test_patching.renamed_os is original_os
     assert _test_patching.renamed_path is original_path
     assert _test_patching.renamed_join is original_join

     _SCREAMING_SNAKE_CASE							   ='__test_patch_submodule_mock__'
     with patch_submodule(_test_patching							,			'os.path.join'							,			_UpperCamelCase    ):
          # Every way to access os.path.join must be patched, and the rest must stay untouched

          # check os.path.join
          assert isinstance(_test_patching.os							,			_PatchedModuleObj    )
          assert isinstance(_test_patching.os.path							,			_PatchedModuleObj    )
          assert _test_patching.os.path.join is mock

          # check path.join
          assert isinstance(_test_patching.path							,			_PatchedModuleObj    )
          assert _test_patching.path.join is mock

          # check join
          assert _test_patching.join is mock

          # check that the other attributes are untouched
          assert _test_patching.os.rename is original_rename
          assert _test_patching.path.dirname is original_dirname
          assert _test_patching.os.path.dirname is original_dirname

          # Even renamed modules or objects must be patched

          # check renamed_os.path.join
          assert isinstance(_test_patching.renamed_os							,			_PatchedModuleObj    )
          assert isinstance(_test_patching.renamed_os.path							,			_PatchedModuleObj    )
          assert _test_patching.renamed_os.path.join is mock

          # check renamed_path.join
          assert isinstance(_test_patching.renamed_path							,			_PatchedModuleObj    )
          assert _test_patching.renamed_path.join is mock

          # check renamed_join
          assert _test_patching.renamed_join is mock

          # check that the other attributes are untouched
          assert _test_patching.renamed_os.rename is original_rename
          assert _test_patching.renamed_path.dirname is original_dirname
          assert _test_patching.renamed_os.path.dirname is original_dirname

     # check that everthing is back to normal when the patch is over

     assert _test_patching.os is original_os
     assert _test_patching.path is original_path
     assert _test_patching.join is original_join

     assert _test_patching.renamed_os is original_os
     assert _test_patching.renamed_path is original_path
     assert _test_patching.renamed_join is original_join


def 	_lowerCAmelCase (						)				->      Optional[Any]:
     """simple docstring"""




     assert _test_patching.open is open

     _SCREAMING_SNAKE_CASE							   ='__test_patch_submodule_builtin_mock__'
     # _test_patching has "open" in its globals
     assert _test_patching.open is open
     with patch_submodule(_test_patching							,			'open'							,			_UpperCamelCase    ):
          assert _test_patching.open is mock

     # check that everthing is back to normal when the patch is over

     assert _test_patching.open is open


def 	_lowerCAmelCase (						)				->      str:
     """simple docstring"""




     _SCREAMING_SNAKE_CASE							   ='__test_patch_submodule_missing_mock__'
     with patch_submodule(_test_patching							,			'pandas.read_csv'							,			_UpperCamelCase    ):
          pass


def 	_lowerCAmelCase (						)				->      Optional[Any]:
     """simple docstring"""




     _SCREAMING_SNAKE_CASE							   ='__test_patch_submodule_missing_builtin_mock__'
     # _test_patching doesn't have "len" in its globals
     assert getattr(_test_patching							,			'len'							,			_UpperCamelCase    ) is None
     with patch_submodule(_test_patching							,			'len'							,			_UpperCamelCase    ):
          assert _test_patching.len is mock
     assert _test_patching.len is len


def 	_lowerCAmelCase (						)				->      str:
     """simple docstring"""




     _SCREAMING_SNAKE_CASE							   ='__test_patch_submodule_start_and_stop_mock__'
     _SCREAMING_SNAKE_CASE							   =patch_submodule(_test_patching							,			'open'							,			_UpperCamelCase    )
     assert _test_patching.open is open
     patch.start()
     assert _test_patching.open is mock
     patch.stop()
     assert _test_patching.open is open


def 	_lowerCAmelCase (						)				->      Optional[Any]:
     """simple docstring"""




     from os import rename as original_rename
     from os.path import dirname as original_dirname
     from os.path import join as original_join

     _SCREAMING_SNAKE_CASE							   ='__test_patch_submodule_successive_join__'
     _SCREAMING_SNAKE_CASE							   ='__test_patch_submodule_successive_dirname__'
     _SCREAMING_SNAKE_CASE							   ='__test_patch_submodule_successive_rename__'
     assert _test_patching.os.path.join is original_join
     assert _test_patching.os.path.dirname is original_dirname
     assert _test_patching.os.rename is original_rename

     with patch_submodule(_test_patching							,			'os.path.join'							,			_UpperCamelCase    ):
          with patch_submodule(_test_patching							,			'os.rename'							,			_UpperCamelCase    ):
               with patch_submodule(_test_patching							,			'os.path.dirname'							,			_UpperCamelCase    ):
                    assert _test_patching.os.path.join is mock_join
                    assert _test_patching.os.path.dirname is mock_dirname
                    assert _test_patching.os.rename is mock_rename

    # try another order
     with patch_submodule(_test_patching							,			'os.rename'							,			_UpperCamelCase    ):
          with patch_submodule(_test_patching							,			'os.path.join'							,			_UpperCamelCase    ):
               with patch_submodule(_test_patching							,			'os.path.dirname'							,			_UpperCamelCase    ):
                    assert _test_patching.os.path.join is mock_join
                    assert _test_patching.os.path.dirname is mock_dirname
                    assert _test_patching.os.rename is mock_rename

     assert _test_patching.os.path.join is original_join
     assert _test_patching.os.path.dirname is original_dirname
     assert _test_patching.os.rename is original_rename







def 	_lowerCAmelCase (						)				->      Optional[Any]:
     """simple docstring"""




     _SCREAMING_SNAKE_CASE							   ='__test_patch_submodule_doesnt_exist_mock__'
     with patch_submodule(_test_patching							,			'__module_that_doesn_exist__.__attribute_that_doesn_exist__'							,			_UpperCamelCase    ):
          pass
     with patch_submodule(_test_patching							,			'os.__attribute_that_doesn_exist__'							,			_UpperCamelCase    ):
          pass
