code: def compute_priority(errors: tf.Tensor, alpha: float):
      """Compute priority as mixture of max and mean sequence errors."""
      abs_errors = tf.abs(errors)
      mean_priority = tf.reduce_mean(abs_errors, axis=0)
      max_priority = tf.reduce_max(abs_errors, axis=0)
  
      return alpha * max_priority + (1 - alpha) * mean_priority
  
imports: import functools
  import time
  from typing import Dict, Iterator, List, Mapping, Union, Optional
  import acme
  from acme import specs
  from acme.adders import reverb
  from acme.tf import losses
  from acme.tf import networks
  from acme.tf import savers
  from acme.tf import utils
  from acme.utils import counting
  from acme.utils import loggers
  import numpy
  import reverb
  import sonnet
  import tensorflow
  import tree
label_desc: Use image node_id 1 for calling a global function with example usage: compute_priority(errors, alpha) and returns: unknown