






import math

from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase    							=      logging.get_logger(__name__)

UpperCamelCase    							=      {
    'facebook/data2vec-base-960h': 'https://huggingface.co/facebook/data2vec-audio-base-960h/resolve/main/config.json',
    # See all Data2VecAudio models at https://huggingface.co/models?filter=data2vec-audio
}







class 		_A						( UpperCAmelCase_ ):
  lowercase_						:			Optional[int]						=					'''data2vec-audio'''

  def __init__(    self						:	List[Any]   ,				lowerCamelCase__						:	List[Any]=32   ,				lowerCamelCase__						:	List[str]=7_68   ,				lowerCamelCase__						:	Union[str, Any]=12   ,				lowerCamelCase__						:	Dict=12   ,				lowerCamelCase__						:	List[Any]=30_72   ,				lowerCamelCase__						:	int="gelu"   ,				lowerCamelCase__						:	Optional[Any]=0.1   ,				lowerCamelCase__						:	int=0.1   ,				lowerCamelCase__						:	Optional[int]=0.1   ,				lowerCamelCase__						:	List[Any]=0.0   ,				lowerCamelCase__						:	Dict=0.1   ,				lowerCamelCase__						:	List[str]=0.1   ,				lowerCamelCase__						:	List[Any]=0.02   ,				lowerCamelCase__						:	List[str]=1e-5   ,				lowerCamelCase__						:	Tuple="gelu"   ,				lowerCamelCase__						:	Any=(5_12, 5_12, 5_12, 5_12, 5_12, 5_12, 5_12)   ,				lowerCamelCase__						:	Optional[Any]=(5, 2, 2, 2, 2, 2, 2)   ,				lowerCamelCase__						:	Optional[int]=(10, 3, 3, 3, 3, 2, 2)   ,				lowerCamelCase__						:	List[str]=False   ,				lowerCamelCase__						:	Dict=16   ,				lowerCamelCase__						:	str=19   ,				lowerCamelCase__						:	Union[str, Any]=5   ,				lowerCamelCase__						:	int=0.05   ,				lowerCamelCase__						:	Any=10   ,				lowerCamelCase__						:	str=2   ,				lowerCamelCase__						:	Optional[int]=0.0   ,				lowerCamelCase__						:	Optional[Any]=10   ,				lowerCamelCase__						:	List[Any]=0   ,				lowerCamelCase__						:	List[Any]="sum"   ,				lowerCamelCase__						:	List[Any]=False   ,				lowerCamelCase__						:	str=False   ,				lowerCamelCase__						:	Dict=2_56   ,				lowerCamelCase__						:	Any=(5_12, 5_12, 5_12, 5_12, 15_00)   ,				lowerCamelCase__						:	str=(5, 3, 3, 1, 1)   ,				lowerCamelCase__						:	List[str]=(1, 2, 3, 1, 1)   ,				lowerCamelCase__						:	str=5_12   ,				lowerCamelCase__						:	Optional[int]=0   ,				lowerCamelCase__						:	Tuple=1   ,				lowerCamelCase__						:	Dict=2   ,				lowerCamelCase__						:	int=False   ,				lowerCamelCase__						:	Tuple=3   ,				lowerCamelCase__						:	List[str]=2   ,				lowerCamelCase__						:	Union[str, Any]=3   ,				lowerCamelCase__						:	List[str]=None   ,				**lowerCamelCase__						:	str   ,				):
     """simple docstring"""

     super().__init__(**lowerCamelCase__   ,				pad_token_id=lowerCamelCase__   ,				bos_token_id=lowerCamelCase__   ,				eos_token_id=lowerCamelCase__			)
     __UpperCamelCase	:			int					=					hidden_size
     __UpperCamelCase	:			Any					=					feat_extract_activation
     __UpperCamelCase	:			str					=					list(lowerCamelCase__			)
     __UpperCamelCase	:			Union[str, Any]					=					list(lowerCamelCase__			)
     __UpperCamelCase	:			List[Any]					=					list(lowerCamelCase__			)
     __UpperCamelCase	:			Tuple					=					conv_bias
     __UpperCamelCase	:			Tuple					=					num_conv_pos_embeddings
     __UpperCamelCase	:			Dict					=					num_conv_pos_embedding_groups
     __UpperCamelCase	:			int					=					conv_pos_kernel_size
     __UpperCamelCase	:			int					=					len(self.conv_dim			)
     __UpperCamelCase	:			List[str]					=					num_hidden_layers
     __UpperCamelCase	:			List[Any]					=					intermediate_size
     __UpperCamelCase	:			Any					=					hidden_act
     __UpperCamelCase	:			List[Any]					=					num_attention_heads
     __UpperCamelCase	:			Dict					=					hidden_dropout
     __UpperCamelCase	:			List[str]					=					attention_dropout
     __UpperCamelCase	:			Tuple					=					activation_dropout
     __UpperCamelCase	:			Dict					=					feat_proj_dropout
     __UpperCamelCase	:			Dict					=					final_dropout
     __UpperCamelCase	:			int					=					layerdrop
     __UpperCamelCase	:			str					=					layer_norm_eps
     __UpperCamelCase	:			List[str]					=					initializer_range
     __UpperCamelCase	:			Optional[Any]					=					vocab_size
     __UpperCamelCase	:			Dict					=					use_weighted_layer_sum

     if (
         (len(self.conv_stride			) != self.num_feat_extract_layers)
         or (len(self.conv_kernel			) != self.num_feat_extract_layers)
         or (len(self.conv_dim			) != self.num_feat_extract_layers)
     ):
        raise ValueError(
            """Configuration for convolutional layers is incorrect. It is required that `len(config.conv_dim)` =="""
            """ `len(config.conv_stride)` == `len(config.conv_kernel)`, but is `len(config.conv_dim) ="""
            f' {len(self.conv_dim			)}`, `len(config.conv_stride) = {len(self.conv_stride			)}`,'
            f' `len(config.conv_kernel) = {len(self.conv_kernel			)}`.'			)

     # fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
     __UpperCamelCase	:			int					=					mask_time_prob
     __UpperCamelCase	:			str					=					mask_time_length
     __UpperCamelCase	:			Union[str, Any]					=					mask_time_min_masks
     __UpperCamelCase	:			str					=					mask_feature_prob
     __UpperCamelCase	:			Optional[int]					=					mask_feature_length
     __UpperCamelCase	:			Tuple					=					mask_feature_min_masks

     # ctc loss
     __UpperCamelCase	:			str					=					ctc_loss_reduction
     __UpperCamelCase	:			Any					=					ctc_zero_infinity

     # adapter
     __UpperCamelCase	:			Optional[int]					=					add_adapter
     __UpperCamelCase	:			Optional[Any]					=					adapter_kernel_size
     __UpperCamelCase	:			Dict					=					adapter_stride
     __UpperCamelCase	:			List[str]					=					num_adapter_layers
     __UpperCamelCase	:			List[Any]					=					output_hidden_size or hidden_size

     # SequenceClassification-specific parameter. Feel free to ignore for other classes.
     __UpperCamelCase	:			Optional[Any]					=					classifier_proj_size

     # XVector-specific parameters. Feel free to ignore for other classes.
     __UpperCamelCase	:			List[Any]					=					list(lowerCamelCase__			)
     __UpperCamelCase	:			Any					=					list(lowerCamelCase__			)
     __UpperCamelCase	:			Optional[int]					=					list(lowerCamelCase__			)
     __UpperCamelCase	:			List[str]					=					xvector_output_dim

  @property
  def    a					(    self						:	str			):
     """simple docstring"""

     return math.prod(self.conv_stride			)











from __future__ import annotations

from typing import Any







class 		_A						:

  def __init__(    self						:	List[Any]   ,				lowerCamelCase__						:	int   ,				lowerCamelCase__						:	int   ,				lowerCamelCase__						:	float = 0			):
     """simple docstring"""

     __UpperCamelCase	,     __UpperCamelCase	:			Tuple					=					row, column
     __UpperCamelCase	:			Tuple					=					[[default_value for c in range(lowerCamelCase__			)] for r in range(lowerCamelCase__			)]

  def __str__(    self						:	List[Any]			):
     """simple docstring"""

     __UpperCamelCase	:			Dict					=					f'Matrix consist of {self.row} rows and {self.column} columns\n'

     # Make string identifier
     __UpperCamelCase	:			Optional[int]					=					0
     for row_vector in self.array:
        for obj in row_vector:
           __UpperCamelCase	:			int					=					max(lowerCamelCase__   ,				len(str(lowerCamelCase__			)			)			)
     __UpperCamelCase	:			Union[str, Any]					=					f'%{max_element_length}s'

     # Make string and return
     def single_line(lowerCamelCase__						:	list[float]			) -> str:
        nonlocal string_format_identifier
        __UpperCamelCase	:			List[Any]					=					"""["""
        line += ", ".join(string_format_identifier % (obj,) for obj in row_vector			)
        line += "]"
        return line

     s += "\n".join(single_line(lowerCamelCase__			) for row_vector in self.array			)
     return s

  def __repr__(    self						:	Any			):
     """simple docstring"""

     return str(self			)

  def    a					(    self						:	str   ,				lowerCamelCase__						:	tuple[int, int]			):
     """simple docstring"""

     if not (isinstance(lowerCamelCase__   ,				(list, tuple)			) and len(lowerCamelCase__			) == 2):
        return False
     elif not (0 <= loc[0] < self.row and 0 <= loc[1] < self.column):
        return False
     else:
        return True

  def __getitem__(    self						:	Union[str, Any]   ,				lowerCamelCase__						:	tuple[int, int]			):
     """simple docstring"""

     assert self.validate_indicies(lowerCamelCase__			)
     return self.array[loc[0]][loc[1]]

  def __setitem__(    self						:	Union[str, Any]   ,				lowerCamelCase__						:	tuple[int, int]   ,				lowerCamelCase__						:	float			):
     """simple docstring"""

     assert self.validate_indicies(lowerCamelCase__			)
     __UpperCamelCase	:			str					=					value

  def __add__(    self						:	int   ,				lowerCamelCase__						:	Matrix			):
     """simple docstring"""

     assert isinstance(lowerCamelCase__   ,				lowerCamelCase__			)
     assert self.row == another.row and self.column == another.column

     # Add
     __UpperCamelCase	:			Tuple					=					Matrix(self.row   ,				self.column			)
     for r in range(self.row			):
        for c in range(self.column			):
           __UpperCamelCase	:			Optional[int]					=					self[r, c] + another[r, c]
     return result

  def __neg__(    self						:	Optional[int]			):
     """simple docstring"""

     __UpperCamelCase	:			str					=					Matrix(self.row   ,				self.column			)
     for r in range(self.row			):
        for c in range(self.column			):
           __UpperCamelCase	:			Any					=					-self[r, c]
     return result

  def __sub__(    self						:	Tuple   ,				lowerCamelCase__						:	Matrix			):
     """simple docstring"""

     return self + (-another)

  def __mul__(    self						:	Tuple   ,				lowerCamelCase__						:	int | float | Matrix			):
     """simple docstring"""

     if isinstance(lowerCamelCase__   ,				(int, float)			):  # Scalar multiplication
        __UpperCamelCase	:			List[str]					=					Matrix(self.row   ,				self.column			)
        for r in range(self.row			):
           for c in range(self.column			):
              __UpperCamelCase	:			Tuple					=					self[r, c] * another
        return result
     elif isinstance(lowerCamelCase__   ,				lowerCamelCase__			):  # Matrix multiplication
        assert self.column == another.row
        __UpperCamelCase	:			List[Any]					=					Matrix(self.row   ,				another.column			)
        for r in range(self.row			):
           for c in range(another.column			):
              for i in range(self.column			):
                 result[r, c] += self[r, i] * another[i, c]
        return result
     else:
        __UpperCamelCase	:			Any					=					f'Unsupported type given for another ({type(lowerCamelCase__			)})'
        raise TypeError(lowerCamelCase__			)

  def    a					(    self						:	Union[str, Any]			):
     """simple docstring"""

     __UpperCamelCase	:			Dict					=					Matrix(self.column   ,				self.row			)
     for r in range(self.row			):
        for c in range(self.column			):
           __UpperCamelCase	:			str					=					self[r, c]
     return result

  def    a					(    self						:	Any   ,				lowerCamelCase__						:	Matrix   ,				lowerCamelCase__						:	Matrix			):
     """simple docstring"""

     assert isinstance(lowerCamelCase__   ,				lowerCamelCase__			) and isinstance(lowerCamelCase__   ,				lowerCamelCase__			)
     assert self.row == self.column == u.row == v.row  # u, v should be column vector
     assert u.column == v.column == 1  # u, v should be column vector

     # Calculate
     __UpperCamelCase	:			Optional[int]					=					v.transpose()
     __UpperCamelCase	:			Tuple					=					(v_t * self * u)[0, 0] + 1
     if numerator_factor == 0:
        return None  # It's not invertable
     return self - ((self * u) * (v_t * self) * (1.0 / numerator_factor))


# Testing
if __name__ == "__main__":


       def 				__lowerCamelCase     (							)     ->  None:
          # a^(-1)
          __UpperCamelCase	:			str					=					Matrix(3					,							3					,							0							)
          for i in range(3							):
             __UpperCamelCase	:			List[str]					=					1
          print(f'a^(-1) is {ainv}'							)
          # u, v
          __UpperCamelCase	:			Any					=					Matrix(3					,							1					,							0							)
          __UpperCamelCase	,     __UpperCamelCase	,     __UpperCamelCase	:			Any					=					1, 2, -3
          __UpperCamelCase	:			int					=					Matrix(3					,							1					,							0							)
          __UpperCamelCase	,     __UpperCamelCase	,     __UpperCamelCase	:			Dict					=					4, -2, 5
          print(f'u is {u}'							)
          print(f'v is {v}'							)
          print(f'uv^T is {u * v.transpose()}'							)
          # Sherman Morrison
          print(f'(a + uv^T)^(-1) is {ainv.sherman_morrison(__lowerCAmelCase					,							__lowerCAmelCase							)}'							)


       def 				__lowerCamelCase     (							)     ->  None:
          import doctest

          doctest.testmod()



       testa()



