cartpole/omd.py
def constraint_func(self, params_T, params_Q, replay, rng, target_params_Q):
    '''Parameterized by T function giving grad_Q (Bellman-error) = 0 constraint.
    '''
    replay_model, _ = self.batch_real_to_model(params_T, replay, rng)
    grads, aux_out = jax.grad(self.loss_Q, has_aux=True)(
      params_Q, target_params_Q, replay_model)
    return grads
Parameterized by T function giving grad_Q (Bellman-error) = 0 constraint.
    
Parameterized by T function giving grad_Q (Bellman-error) = 0 constraint.
Parameterized by T function giving grad_Q ( Bellman - error ) = 0 constraint .
def constraint_func(self, params_T, params_Q, replay, rng, target_params_Q):
    replay_model, _ = self.batch_real_to_model(params_T, replay, rng)
    grads, aux_out = jax.grad(self.loss_Q, has_aux=True)(
      params_Q, target_params_Q, replay_model)
    return grads
def constraint_func ( self , params_T , params_Q , replay , rng , target_params_Q ) : replay_model , _ = self . batch_real_to_model ( params_T , replay , rng ) grads , aux_out = jax . grad ( self . loss_Q , has_aux = True ) ( params_Q , target_params_Q , replay_model ) return grads
Parameterized by T function giving grad_Q (Bellman-error) = 0 constraint.
Parameterized by T function giving grad_Q ( Bellman - error ) = 0 constraint .
'''Parameterized by T function giving grad_Q (Bellman-error) = 0 constraint.
    '''
self
params_T
params_Q
replay
rng
target_params_Q