original_docstring: r"""Enforce the output of a neural network to satisfy the boundary condition.
  
          :param net: The neural network that approximates the ODE.
          :type net: `torch.nn.Module`
          :param t: The points where the neural network output is evaluated.
          :type t: `torch.tensor`
          :return: The modified output which now satisfies the boundary condition.
          :rtype: `torch.tensor`
  
  
          .. note::
              `enforce` is meant to be called by the function `solve` and `solve_system`.
          
docstring: r"""Enforce the output of a neural network to satisfy the boundary condition.
docstring_tokens: r " " " Enforce the output of a neural network to satisfy the boundary condition .
code: def enforce(self, net, t):
          r"""Enforce the output of a neural network to satisfy the boundary condition.
  
          :param net: The neural network that approximates the ODE.
          :type net: `torch.nn.Module`
          :param t: The points where the neural network output is evaluated.
          :type t: `torch.tensor`
          :return: The modified output which now satisfies the boundary condition.
          :rtype: `torch.tensor`
  
  
          .. note::
              `enforce` is meant to be called by the function `solve` and `solve_system`.
          """
          x = _network_output(net, t, self.ith_unit)
          t_tilde = (t-self.t_0) / (self.t_1-self.t_0)
          return self.x_0*(1-t_tilde) + self.x_1*t_tilde + (1-torch.exp((1-t_tilde)*t_tilde))*x
code_tokens: def enforce ( self , net , t ) : x = _network_output ( net , t , self . ith_unit ) t_tilde = ( t - self . t_0 ) / ( self . t_1 - self . t_0 ) return self . x_0 * ( 1 - t_tilde ) + self . x_1 * t_tilde + ( 1 - torch . exp ( ( 1 - t_tilde ) * t_tilde ) ) * x
short_docstring: r"""Enforce the output of a neural network to satisfy the boundary condition.
short_docstring_tokens: r " " " Enforce the output of a neural network to satisfy the boundary condition .
comment: r"""Enforce the output of a neural network to satisfy the boundary condition.
  
          :param net: The neural network that approximates the ODE.
          :type net: `torch.nn.Module`
          :param t: The points where the neural network output is evaluated.
          :type t: `torch.tensor`
          :return: The modified output which now satisfies the boundary condition.
          :rtype: `torch.tensor`
  
  
          .. note::
              `enforce` is meant to be called by the function `solve` and `solve_system`.
          """