


'''simple docstring'''

import logging
from dataclasses import dataclass, field
from typing import Optional

from seqaseq_trainer import arg_to_scheduler

from transformers import TrainingArguments


lowerCamelCase				:  Union[str, Any]    		=      logging.getLogger(__name__)
@dataclass
class     __lowerCAmelCase		(lowercase_	):





      '''simple docstring'''






      lowerCAmelCase__   :	Optional[float]       =				field(
          default=0.0    ,	metadata={"""help""": """The label smoothing epsilon to apply (if not zero)."""}	)
      lowerCAmelCase__   :	bool       =				field(default=lowercase_    ,	metadata={"""help""": """Whether to SortishSamler or not."""}	)
      lowerCAmelCase__   :	bool       =				field(
          default=lowercase_    ,	metadata={"""help""": """Whether to use generate to calculate generative metrics (ROUGE, BLEU)."""}	)
      lowerCAmelCase__   :	bool       =				field(default=lowercase_    ,	metadata={"""help""": """whether to use adafactor"""}	)
      lowerCAmelCase__   :	Optional[float]       =				field(
          default=lowercase_    ,	metadata={"""help""": """Encoder layer dropout probability. Goes into model.config."""}	)
      lowerCAmelCase__   :	Optional[float]       =				field(
          default=lowercase_    ,	metadata={"""help""": """Decoder layer dropout probability. Goes into model.config."""}	)
      lowerCAmelCase__   :	Optional[float]       =				field(default=lowercase_    ,	metadata={"""help""": """Dropout probability. Goes into model.config."""}	)
      lowerCAmelCase__   :	Optional[float]       =				field(
          default=lowercase_    ,	metadata={"""help""": """Attention dropout probability. Goes into model.config."""}	)
      lowerCAmelCase__   :	Optional[str]       =				field(
          default="""linear"""    ,	metadata={"""help""": f'Which lr scheduler to use. Selected in {sorted(arg_to_scheduler.keys()	)}'}    ,	)








'''simple docstring'''

import unittest

import numpy as np

def _SCREAMING_SNAKE_CASE (A    ,					A    ,					A    ,					A = None    ,					)			->			np.ndarray:






       """simple docstring"""







       lowercase__      =					np.shape(A			)
       lowercase__      =					np.shape(A			)
       lowercase__      =					np.shape(A			)

       if shape_a[0] != shape_b[0]:
              lowercase__      =					(
                  '''Expected the same number of rows for A and B. '''
                  f"Instead found A of size {shape_a} and B of size {shape_b}"
              )
              raise ValueError(A			)

       if shape_b[1] != shape_c[1]:
              lowercase__      =					(
                  '''Expected the same number of columns for B and C. '''
                  f"Instead found B of size {shape_b} and C of size {shape_c}"
              )
              raise ValueError(A			)

       lowercase__      =					pseudo_inv
       if a_inv is None:
              try:
                     lowercase__      =					np.linalg.inv(A			)
              except np.linalg.LinAlgError:
                     raise ValueError(
                         '''Input matrix A is not invertible. Cannot compute Schur complement.'''			)

       return mat_c - mat_b.T @ a_inv @ mat_b
class     __lowerCAmelCase		(unittest.TestCase	):





      '''simple docstring'''






      def  UpperCamelCase__						(self       :       Dict					):

             '''simple docstring'''







             lowercase__      =					np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]					)
             lowercase__      =					np.array([[0, 3], [3, 0], [2, 3]]					)
             lowercase__      =					np.array([[2, 1], [6, 3]]					)

             lowercase__      =					schur_complement(UpperCamelCase  ,		UpperCamelCase  ,		UpperCamelCase					)

             lowercase__      =					np.block([[a, b], [b.T, c]]					)

             lowercase__      =					np.linalg.det(UpperCamelCase					)
             lowercase__      =					np.linalg.det(UpperCamelCase					)
             lowercase__      =					np.linalg.det(UpperCamelCase					)

             self.assertAlmostEqual(UpperCamelCase  ,		det_a * det_s					)



      def  UpperCamelCase__						(self       :       Optional[int]					):

             '''simple docstring'''







             lowercase__      =					np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]					)
             lowercase__      =					np.array([[0, 3], [3, 0], [2, 3]]					)
             lowercase__      =					np.array([[2, 1], [6, 3]]					)

             with self.assertRaises(UpperCamelCase					):
                    schur_complement(UpperCamelCase  ,		UpperCamelCase  ,		UpperCamelCase					)






      def  UpperCamelCase__						(self       :       Union[str, Any]					):

             '''simple docstring'''







             lowercase__      =					np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]					)
             lowercase__      =					np.array([[0, 3], [3, 0], [2, 3]]					)
             lowercase__      =					np.array([[2, 1, 3], [6, 3, 5]]					)

             with self.assertRaises(UpperCamelCase					):
                    schur_complement(UpperCamelCase  ,		UpperCamelCase  ,		UpperCamelCase					)


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 unittest.main()




