code: def retrace_continuous(
      q_tm1: Array,
      q_t: Array,
      v_t: Array,
      r_t: Array,
      discount_t: Array,
      log_rhos: Array,
      lambda_: Union[Array, float],
      stop_target_gradients: bool = True,
  ) -> Array:
      """Retrace continuous.
  
      See "Safe and Efficient Off-Policy Reinforcement Learning" by Munos et al.
      (https://arxiv.org/abs/1606.02647).
  
      Args:
        q_tm1: Q-values at times [0, ..., K - 1].
        q_t: Q-values evaluated at actions collected using behavior
          policy at times [1, ..., K - 1].
        v_t: Value estimates of the target policy at times [1, ..., K].
        r_t: reward at times [1, ..., K].
        discount_t: discount at times [1, ..., K].
        log_rhos: Log importance weight pi_target/pi_behavior evaluated at actions
          collected using behavior policy [1, ..., K - 1].
        lambda_: scalar or a vector of mixing parameter lambda.
        stop_target_gradients: bool indicating whether or not to apply stop gradient
          to targets.
  
      Returns:
        Retrace error.
      """
  
      chex.assert_rank(
          [q_tm1, q_t, r_t, discount_t, log_rhos, lambda_],
          [1, 1, 1, 1, 1, {0, 1}],
      )
      chex.assert_type(
          [q_tm1, q_t, r_t, discount_t, log_rhos],
          [float, float, float, float, float],
      )
  
      c_t = jnp.minimum(1.0, jnp.exp(log_rhos)) * lambda_
  
      # The generalized returns are independent of Q-values and cs at the final
      # state.
      target_tm1 = multistep.general_off_policy_returns_from_q_and_v(
          q_t, v_t, r_t, discount_t, c_t
      )
  
      target_tm1 = jax.lax.select(
          stop_target_gradients,
          jax.lax.stop_gradient(target_tm1),
          target_tm1,
      )
      return target_tm1 - q_tm1
  
imports: from typing import Union
  import chex
  import jax
  import jax.numpy
  from rlax._src import base
  from rlax._src import clipping
  from rlax._src import distributions
  from rlax._src import multistep
label_desc: Use image node_id 13 for calling a global function with example usage: retrace_continuous(q_tm1, q_t, v_t, r_t, discount_t, log_rhos, lambda_, stop_target_gradients) and returns: unknown