




'''simple docstring'''



from math import ceil
from typing import List, Optional, Union

import numpy as np

from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging


UpperCamelCase_    	=				logging.get_logger(__name__)






class 							_a				(			SCREAMING_SNAKE_CASE ):





       '''simple docstring'''






       A						:				str        =						['''audio_values''', '''audio_mask''']







       def __init__(      self,							A=2_048,							A=1,							A=[16, 16],							A=128,							A=44_100,							A=86,							A=2_048,							A=0.0,							**A,							):







             '''simple docstring'''







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

             SCREAMING_SNAKE_CASE   :      str    					=						spectrogram_length
             SCREAMING_SNAKE_CASE   :      Optional[Any]    					=						num_channels
             SCREAMING_SNAKE_CASE   :      List[str]    					=						patch_size
             SCREAMING_SNAKE_CASE   :      Optional[int]    					=						feature_size // self.patch_size[1]
             SCREAMING_SNAKE_CASE   :      Dict    					=						n_fft
             SCREAMING_SNAKE_CASE   :      Tuple    					=						sampling_rate // hop_length_to_sampling_rate
             SCREAMING_SNAKE_CASE   :      str    					=						sampling_rate
             SCREAMING_SNAKE_CASE   :      int    					=						padding_value
             SCREAMING_SNAKE_CASE   :      Any    					=						mel_filter_bank(
                 num_frequency_bins=1 + n_fft // 2,							num_mel_filters=A,							min_frequency=0.0,							max_frequency=2_20_50.0,							sampling_rate=A,							norm='slaney',							mel_scale='slaney',							).T







       def        UpperCamelCase_							(      self,							A  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      Optional[int]    					=						spectrogram(
                 A,							window_function(self.n_fft,							'hann'  ),							frame_length=self.n_fft,							hop_length=self.hop_length,							power=2.0,							mel_filters=self.mel_filters.T,							log_mel='dB',							db_range=80.0,							)
             SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						log_spec[:, :-1]
             SCREAMING_SNAKE_CASE   :      List[Any]    					=						log_spec - 20.0
             SCREAMING_SNAKE_CASE   :      Optional[Any]    					=						np.clip(log_spec / 40.0,							-2.0,							0.0  ) + 1.0
             return log_spec







       def __call__(      self,							A,							A = None,							A = True,							A = None,							A = False,							A = False,							**A,							):







             '''simple docstring'''







             if sampling_rate is not None:
                   if sampling_rate != self.sampling_rate:
                         raise ValueError(
                             'This feature extractor is set to support sampling rate'
                             F" of {self.sampling_rate}. Please make sure that the provided `raw_speech` input was sampled"
                             F" with {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   :      List[Any]    					=						isinstance(A,							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   :      int    					=						is_batched_numpy or (
                 isinstance(A,							(list, tuple)  ) and (isinstance(raw_speech[0],							(np.ndarray, tuple, list)  ))
             )
             if is_batched:
                   SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						[np.asarray([speech],							dtype=np.floataa  ).T for speech in raw_speech]
             elif not is_batched and not isinstance(A,							np.ndarray  ):
                   SCREAMING_SNAKE_CASE   :      Any    					=						np.asarray(A,							dtype=np.floataa  )
             elif isinstance(A,							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   :      Union[str, Any]    					=						[np.asarray([raw_speech]  ).T]

             # Convert audio signals to log mel spectrograms, truncate by time axis
             SCREAMING_SNAKE_CASE   :      int    					=						[
                 self._np_extract_fbank_features(waveform.squeeze()  ).T[: self.spectrogram_length] for waveform in raw_speech
             ]
             if isinstance(audio_features[0],							A  ):
                   SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						[np.asarray(A,							dtype=np.floataa  ) for feature in audio_features]

             # Create audio attention mask
             SCREAMING_SNAKE_CASE   :      Tuple    					=						max(
                 [ceil(feature.shape[0] / self.patch_size[0]  ) * self.freq_len for feature in audio_features]  )  # The maximum number of audio patches in a batch
             if return_attention_mask:
                   SCREAMING_SNAKE_CASE   :      List[Any]    					=						[
                       (ceil(feature.shape[0] / self.patch_size[0]  ) * self.freq_len) * [1]
                       + (max_patch_len - ceil(feature.shape[0] / self.patch_size[0]  ) * self.freq_len) * [0]
                       for feature in audio_features
                   ]
                   SCREAMING_SNAKE_CASE   :      Tuple    					=						np.array(A  ).astype(np.floataa  )

             # convert into correct format for padding
             SCREAMING_SNAKE_CASE   :      Tuple    					=						max_patch_len // self.freq_len * self.patch_size[0]  # The maximum audio size in a batch
             SCREAMING_SNAKE_CASE   :      Optional[Any]    					=						np.ones([len(A  ), 1, max_time_len, self.feature_size]  ).astype(np.floataa  )
             SCREAMING_SNAKE_CASE   :      Optional[int]    					=						padded_audio_features * self.padding_value
             for i in range(len(A  )  ):
                   SCREAMING_SNAKE_CASE   :      Optional[int]    					=						audio_features[i]
                   SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						feature

             # return as BatchFeature
             if return_attention_mask:
                   SCREAMING_SNAKE_CASE   :      Any    					=						{'audio_values': padded_audio_features, 'audio_mask': audio_mask}
             else:
                   SCREAMING_SNAKE_CASE   :      Dict    					=						{'audio_values': padded_audio_features}

             SCREAMING_SNAKE_CASE   :      str    					=						BatchFeature(data=A,							tensor_type=A  )
             return encoded_inputs








'''simple docstring'''



from typing import Any






class 							_a				:





       '''simple docstring'''






       def __init__(      self,							A  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      str    					=						data
             SCREAMING_SNAKE_CASE   :      Any    					=						None







       def __repr__(      self  ):







             '''simple docstring'''







             return F"Node({self.data})"






class 							_a				:





       '''simple docstring'''






       def __init__(      self  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      List[str]    					=						None







       def __iter__(      self  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      Optional[Any]    					=						self.head
             while node:
                   yield node.data
                   SCREAMING_SNAKE_CASE   :      List[str]    					=						node.next







       def __len__(      self  ):







             '''simple docstring'''







             return sum(1 for _ in self  )







       def __repr__(      self  ):







             '''simple docstring'''







             return "->".join([str(A  ) for item in self]  )







       def __getitem__(      self,							A  ):







             '''simple docstring'''







             if not 0 <= index < len(self  ):
                   raise ValueError('list index out of range.'  )
             for i, node in enumerate(self  ):
                   if i == index:
                         return node
             return None







       def __setitem__(      self,							A,							A  ):







             '''simple docstring'''







             if not 0 <= index < len(self  ):
                   raise ValueError('list index out of range.'  )
             SCREAMING_SNAKE_CASE   :      Optional[Any]    					=						self.head
             for _ in range(A  ):
                   SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						current.next
             SCREAMING_SNAKE_CASE   :      Any    					=						data







       def        UpperCamelCase_							(      self,							A  ):







             '''simple docstring'''







             self.insert_nth(len(self  ),							A  )







       def        UpperCamelCase_							(      self,							A  ):







             '''simple docstring'''







             self.insert_nth(0,							A  )







       def        UpperCamelCase_							(      self,							A,							A  ):







             '''simple docstring'''







             if not 0 <= index <= len(self  ):
                   raise IndexError('list index out of range'  )
             SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						Node(A  )
             if self.head is None:
                   SCREAMING_SNAKE_CASE   :      Optional[int]    					=						new_node
             elif index == 0:
                   SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						self.head  # link new_node to head
                   SCREAMING_SNAKE_CASE   :      Tuple    					=						new_node
             else:
                   SCREAMING_SNAKE_CASE   :      Optional[int]    					=						self.head
                   for _ in range(index - 1  ):
                         SCREAMING_SNAKE_CASE   :      str    					=						temp.next
                   SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						temp.next
                   SCREAMING_SNAKE_CASE   :      List[str]    					=						new_node







       def        UpperCamelCase_							(      self  ):  # print every node data







             '''simple docstring'''







             print(self  )







       def        UpperCamelCase_							(      self  ):







             '''simple docstring'''







             return self.delete_nth(0  )







       def        UpperCamelCase_							(      self  ):  # delete from tail







             '''simple docstring'''







             return self.delete_nth(len(self  ) - 1  )







       def        UpperCamelCase_							(      self,							A = 0  ):







             '''simple docstring'''







             if not 0 <= index <= len(self  ) - 1:  # test if index is valid
                   raise IndexError('List index out of range.'  )
             SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						self.head  # default first node
             if index == 0:
                   SCREAMING_SNAKE_CASE   :      List[str]    					=						self.head.next
             else:
                   SCREAMING_SNAKE_CASE   :      Union[str, Any]    					=						self.head
                   for _ in range(index - 1  ):
                         SCREAMING_SNAKE_CASE   :      Any    					=						temp.next
                   SCREAMING_SNAKE_CASE   :      List[str]    					=						temp.next
                   SCREAMING_SNAKE_CASE   :      Optional[int]    					=						temp.next.next
             return delete_node.data







       def        UpperCamelCase_							(      self  ):







             '''simple docstring'''







             return self.head is None







       def        UpperCamelCase_							(      self  ):







             '''simple docstring'''







             SCREAMING_SNAKE_CASE   :      int    					=						None
             SCREAMING_SNAKE_CASE   :      Any    					=						self.head

             while current:
                   # Store the current node's next node.
                   SCREAMING_SNAKE_CASE   :      Optional[int]    					=						current.next
                   # Make the current node's next point backwards
                   SCREAMING_SNAKE_CASE   :      int    					=						prev
                   # Make the previous node be the current node
                   SCREAMING_SNAKE_CASE   :      int    					=						current
                   # Make the current node the next node (to progress iteration)
                   SCREAMING_SNAKE_CASE   :      List[Any]    					=						next_node
             # Return prev in order to put the head at the end
             SCREAMING_SNAKE_CASE   :      List[Any]    					=						prev




def   lowercase__(			):

      """simple docstring"""






      SCREAMING_SNAKE_CASE   :      Dict    					=						LinkedList()
      assert linked_list.is_empty() is True
      assert str(__UpperCamelCase    ) == ""

      try:
            linked_list.delete_head()
            raise AssertionError  # This should not happen.
      except IndexError:
            assert True  # This should happen.

      try:
            linked_list.delete_tail()
            raise AssertionError  # This should not happen.
      except IndexError:
            assert True  # This should happen.

      for i in range(10    ):
            assert len(__UpperCamelCase    ) == i
            linked_list.insert_nth(__UpperCamelCase      ,i + 1    )
      assert str(__UpperCamelCase    ) == "->".join(str(__UpperCamelCase    ) for i in range(1      ,11    )    )

      linked_list.insert_head(0    )
      linked_list.insert_tail(11    )
      assert str(__UpperCamelCase    ) == "->".join(str(__UpperCamelCase    ) for i in range(0      ,12    )    )

      assert linked_list.delete_head() == 0
      assert linked_list.delete_nth(9    ) == 10
      assert linked_list.delete_tail() == 11
      assert len(__UpperCamelCase    ) == 9
      assert str(__UpperCamelCase    ) == "->".join(str(__UpperCamelCase    ) for i in range(1      ,10    )    )

      assert all(linked_list[i] == i + 1 for i in range(0      ,9    )    ) is True

      for i in range(0      ,9    ):
            SCREAMING_SNAKE_CASE   :      Any    					=						-i
      assert all(linked_list[i] == -i for i in range(0      ,9    )    ) is True

      linked_list.reverse()
      assert str(__UpperCamelCase    ) == "->".join(str(__UpperCamelCase    ) for i in range(-8      ,1    )    )




def   lowercase__(			):

      """simple docstring"""






      SCREAMING_SNAKE_CASE   :      List[str]    					=						[
          -9,
          1_00,
          Node(77_34_51_12    ),
          'dlrow olleH',
          7,
          55_55,
          0,
          -1_9_2.5_5_5_5_5,
          'Hello, world!',
          7_7.9,
          Node(10    ),
          None,
          None,
          1_2.2_0,
      ]
      SCREAMING_SNAKE_CASE   :      Optional[int]    					=						LinkedList()

      for i in test_input:
            linked_list.insert_tail(__UpperCamelCase    )

      # Check if it's empty or not
      assert linked_list.is_empty() is False
      assert (
          str(__UpperCamelCase    ) == "-9->100->Node(77345112)->dlrow olleH->7->5555->0->"
          "-192.55555->Hello, world!->77.9->Node(10)->None->None->12.2"
      )

      # Delete the head
      SCREAMING_SNAKE_CASE   :      str    					=						linked_list.delete_head()
      assert result == -9
      assert (
          str(__UpperCamelCase    ) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
          "Hello, world!->77.9->Node(10)->None->None->12.2"
      )

      # Delete the tail
      SCREAMING_SNAKE_CASE   :      Dict    					=						linked_list.delete_tail()
      assert result == 1_2.2
      assert (
          str(__UpperCamelCase    ) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
          "Hello, world!->77.9->Node(10)->None->None"
      )

      # Delete a node in specific location in linked list
      SCREAMING_SNAKE_CASE   :      str    					=						linked_list.delete_nth(10    )
      assert result is None
      assert (
          str(__UpperCamelCase    ) == "100->Node(77345112)->dlrow olleH->7->5555->0->-192.55555->"
          "Hello, world!->77.9->Node(10)->None"
      )

      # Add a Node instance to its head
      linked_list.insert_head(Node('Hello again, world!'    )    )
      assert (
          str(__UpperCamelCase    )
          == "Node(Hello again, world!)->100->Node(77345112)->dlrow olleH->"
          "7->5555->0->-192.55555->Hello, world!->77.9->Node(10)->None"
      )

      # Add None to its tail
      linked_list.insert_tail(__UpperCamelCase    )
      assert (
          str(__UpperCamelCase    )
          == "Node(Hello again, world!)->100->Node(77345112)->dlrow olleH->"
          "7->5555->0->-192.55555->Hello, world!->77.9->Node(10)->None->None"
      )

      # Reverse the linked list
      linked_list.reverse()
      assert (
          str(__UpperCamelCase    )
          == "None->None->Node(10)->77.9->Hello, world!->-192.55555->0->5555->"
          "7->dlrow olleH->Node(77345112)->100->Node(Hello again, world!)"
      )




def   lowercase__(			):

      """simple docstring"""






      from doctest import testmod

      testmod()

      SCREAMING_SNAKE_CASE   :      Dict    					=						LinkedList()
      linked_list.insert_head(input('Inserting 1st at head '    ).strip()    )
      linked_list.insert_head(input('Inserting 2nd at head '    ).strip()    )
      print('\nPrint list:'    )
      linked_list.print_list()
      linked_list.insert_tail(input('\nInserting 1st at tail '    ).strip()    )
      linked_list.insert_tail(input('Inserting 2nd at tail '    ).strip()    )
      print('\nPrint list:'    )
      linked_list.print_list()
      print('\nDelete head'    )
      linked_list.delete_head()
      print('Delete tail'    )
      linked_list.delete_tail()
      print('\nPrint list:'    )
      linked_list.print_list()
      print('\nReverse linked list'    )
      linked_list.reverse()
      print('\nPrint list:'    )
      linked_list.print_list()
      print('\nString representation of linked list:'    )
      print(__UpperCamelCase    )
      print('\nReading/changing Node data using indexing:'    )
      print(f"Element at Position 1: {linked_list[1]}"    )
      SCREAMING_SNAKE_CASE   :      str    					=						input('Enter New Value: '    ).strip()
      print('New list:'    )
      print(__UpperCamelCase    )
      print(f"length of linked_list is : {len(__UpperCamelCase    )}"    )


if __name__ == "__main__":
      main()


