code: def minimize_and_clip(
      optimizer: LocalOptimizer,
      objective: TensorType,
      var_list: List["tf.Variable"],
      clip_val: float = 10.0,
  ) -> ModelGradients:
      """Computes, then clips gradients using objective, optimizer and var list.
  
      Ensures the norm of the gradients for each variable is clipped to
      `clip_val`.
  
      Args:
          optimizer: Either a shim optimizer (tf eager) containing a
              tf.GradientTape under `self.tape` or a tf1 local optimizer
              object.
          objective: The loss tensor to calculate gradients on.
          var_list: The list of tf.Variables to compute gradients over.
          clip_val: The global norm clip value. Will clip around -clip_val and
              +clip_val.
  
      Returns:
          The resulting model gradients (list or tuples of grads + vars)
          corresponding to the input `var_list`.
      """
      # Accidentally passing values < 0.0 will break all gradients.
      assert clip_val is None or clip_val > 0.0, clip_val
  
      if tf.executing_eagerly():
          tape = optimizer.tape
          grads_and_vars = list(
              zip(list(tape.gradient(objective, var_list)), var_list)
          )
      else:
          grads_and_vars = optimizer.compute_gradients(
              objective, var_list=var_list
          )
  
      return [
          (
              tf.clip_by_norm(g, clip_val)
              if clip_val is not None
              else g,
              v,
          )
          for (g, v) in grads_and_vars
          if g is not None
      ]
  
imports: import logging
  from typing import Any, Callable, List, Optional, Type, TYPE_CHECKING, Union
  import gymnasium
  import numpy
  import tree
  from gymnasium.spaces import Discrete, MultiDiscrete
  from ray.rllib.utils.annotations import PublicAPI, DeveloperAPI
  from ray.rllib.utils.framework import try_import_tf
  from ray.rllib.utils.spaces.space_utils import get_base_struct_from_space
  from ray.rllib.utils.typing import LocalOptimizer, ModelGradients, PartialAlgorithmConfigDict, SpaceStruct, TensorStructType, TensorType
label_desc: Use image node_id 10 for calling a global function with example usage: minimize_and_clip(optimizer, objective, var_list, clip_val) and returns: unknown