

import unittest

import numpy as np
def     UpperCAmelCase_       (						_A				,		_A				,		_A				,		_A = None				,		):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__   =   np.shape(__a    )
     SCREAMING_SNAKE_CASE__   =   np.shape(__a    )
     SCREAMING_SNAKE_CASE__   =   np.shape(__a    )

     if shape_a[0] != shape_b[0]:
          SCREAMING_SNAKE_CASE__   =   (
              '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]:
          SCREAMING_SNAKE_CASE__   =   (
              '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    )

     SCREAMING_SNAKE_CASE__   =   pseudo_inv
     if a_inv is None:
          try:
               SCREAMING_SNAKE_CASE__   =   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 	UpperCAmelCase__		(	unittest.TestCase	):






  """simple docstring"""


  def 				lowercase_		(							self						:		Optional[int] )		->							None:
       SCREAMING_SNAKE_CASE__   =   np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]] )
       SCREAMING_SNAKE_CASE__   =   np.array([[0, 3], [3, 0], [2, 3]] )
       SCREAMING_SNAKE_CASE__   =   np.array([[2, 1], [6, 3]] )

       SCREAMING_SNAKE_CASE__   =   schur_complement(_A     ,       _A     ,       _A )

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

       SCREAMING_SNAKE_CASE__   =   np.linalg.det(_A )
       SCREAMING_SNAKE_CASE__   =   np.linalg.det(_A )
       SCREAMING_SNAKE_CASE__   =   np.linalg.det(_A )

       self.assertAlmostEqual(_A     ,       det_a * det_s )






  def 				lowercase_		(							self						:		Union[str, Any] )		->							None:
       SCREAMING_SNAKE_CASE__   =   np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]] )
       SCREAMING_SNAKE_CASE__   =   np.array([[0, 3], [3, 0], [2, 3]] )
       SCREAMING_SNAKE_CASE__   =   np.array([[2, 1], [6, 3]] )

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







  def 				lowercase_		(							self						:		Optional[int] )		->							None:
       SCREAMING_SNAKE_CASE__   =   np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]] )
       SCREAMING_SNAKE_CASE__   =   np.array([[0, 3], [3, 0], [2, 3]] )
       SCREAMING_SNAKE_CASE__   =   np.array([[2, 1, 3], [6, 3, 5]] )

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


if __name__ == "__main__":
       import doctest

       doctest.testmod()
       unittest.main()





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


_SCREAMING_SNAKE_CASE					:  Any             =      logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE					:  int             =      {
    '''edbeeching/decision-transformer-gym-hopper-medium''': (
        '''https://huggingface.co/edbeeching/decision-transformer-gym-hopper-medium/resolve/main/config.json'''
    ),
    # See all DecisionTransformer models at https://huggingface.co/models?filter=decision_transformer
}






class 	UpperCAmelCase__		(	A__	):






  """simple docstring"""


  a									= "decision_transformer"
  a									= ["past_key_values"]
  a									= {
      "max_position_embeddings": "n_positions",
      "num_attention_heads": "n_head",
      "num_hidden_layers": "n_layer",
  }






  def __init__(							self						:		Tuple     ,       __lowerCamelCase						:		Any=17     ,       __lowerCamelCase						:		Any=4     ,       __lowerCamelCase						:		List[Any]=128     ,       __lowerCamelCase						:		Union[str, Any]=4096     ,       __lowerCamelCase						:		Optional[Any]=True     ,       __lowerCamelCase						:		Any=1     ,       __lowerCamelCase						:		List[Any]=1024     ,       __lowerCamelCase						:		Any=3     ,       __lowerCamelCase						:		Dict=1     ,       __lowerCamelCase						:		List[Any]=None     ,       __lowerCamelCase						:		str="relu"     ,       __lowerCamelCase						:		Dict=0.1     ,       __lowerCamelCase						:		int=0.1     ,       __lowerCamelCase						:		List[str]=0.1     ,       __lowerCamelCase						:		str=1e-5     ,       __lowerCamelCase						:		Optional[Any]=0.02     ,       __lowerCamelCase						:		int=True     ,       __lowerCamelCase						:		Tuple=True     ,       __lowerCamelCase						:		Optional[int]=5_0256     ,       __lowerCamelCase						:		Tuple=5_0256     ,       __lowerCamelCase						:		int=False     ,       __lowerCamelCase						:		Optional[int]=False     ,       **__lowerCamelCase						:		Tuple     ,       )		->							Optional[Any]:
       SCREAMING_SNAKE_CASE__   =   state_dim
       SCREAMING_SNAKE_CASE__   =   act_dim
       SCREAMING_SNAKE_CASE__   =   hidden_size
       SCREAMING_SNAKE_CASE__   =   max_ep_len
       SCREAMING_SNAKE_CASE__   =   action_tanh
       SCREAMING_SNAKE_CASE__   =   vocab_size
       SCREAMING_SNAKE_CASE__   =   n_positions
       SCREAMING_SNAKE_CASE__   =   n_layer
       SCREAMING_SNAKE_CASE__   =   n_head
       SCREAMING_SNAKE_CASE__   =   n_inner
       SCREAMING_SNAKE_CASE__   =   activation_function
       SCREAMING_SNAKE_CASE__   =   resid_pdrop
       SCREAMING_SNAKE_CASE__   =   embd_pdrop
       SCREAMING_SNAKE_CASE__   =   attn_pdrop
       SCREAMING_SNAKE_CASE__   =   layer_norm_epsilon
       SCREAMING_SNAKE_CASE__   =   initializer_range
       SCREAMING_SNAKE_CASE__   =   scale_attn_weights
       SCREAMING_SNAKE_CASE__   =   use_cache
       SCREAMING_SNAKE_CASE__   =   scale_attn_by_inverse_layer_idx
       SCREAMING_SNAKE_CASE__   =   reorder_and_upcast_attn

       SCREAMING_SNAKE_CASE__   =   bos_token_id
       SCREAMING_SNAKE_CASE__   =   eos_token_id

       super().__init__(bos_token_id=__lowerCamelCase     ,       eos_token_id=__lowerCamelCase     ,       **__lowerCamelCase )


