class_docstr: Tests ActionDistribution classes.
code: def setUpClass(cls) -> None:
      # Set seeds for deterministic tests (make sure we don't fail
      # because of "bad" sampling).
      np.random.seed(42 + 1)
      torch.manual_seed(42 + 1)
  
imports: from functools import partial
  from gymnasium.spaces import Box, Dict, Tuple
  import numpy
  from scipy.stats import beta, norm
  import tree
  import unittest
  from ray.rllib.models.tf.tf_action_dist import Beta, Categorical, DiagGaussian, GumbelSoftmax, MultiActionDistribution, MultiCategorical, SquashedGaussian
  from ray.rllib.models.torch.torch_action_dist import TorchBeta, TorchCategorical, TorchDiagGaussian, TorchMultiActionDistribution, TorchMultiCategorical, TorchSquashedGaussian
  from ray.rllib.utils.framework import try_import_tf, try_import_torch
  from ray.rllib.utils.numpy import MIN_LOG_NN_OUTPUT, MAX_LOG_NN_OUTPUT, softmax, SMALL_NUMBER, LARGE_INTEGER
  from ray.rllib.utils.test_utils import check, framework_iterator
label_desc: Use image node_id 1 for calling the TestActionDistributions obj's underlying member method code with example usage: obj.setUpClass(cls) without return types