class_docstr: Abstract base class for representing constraints.
  
  The constraint class provides feasibility computation functionality for
  computing the probability of actions being feasible.
class_docstr_tok: ["Abstract","base","class","for","representing","constraints",".","The","constraint","class","provides","feasibility","computation","functionality","for","computing","the","probability","of","actions","being","feasible","."]
docstr: Returns the probability of input actions being feasible.
code: def __call__(
      self,
      observation: types.NestedTensor,
      actions: Optional[types.Tensor] = None,
  ) -> types.Tensor:
      """Returns the probability of input actions being feasible."""
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import abc
  import functools
  from typing import Callable, Iterable, Optional, Text
  import six
  import tensorflow
  import tensorflow_probability
  from tf_agents.bandits.policies import loss_utils
  from tf_agents.bandits.specs import utils
  from tf_agents.policies import utils
  from tf_agents.trajectories import time_step
  from tf_agents.typing import types
  from tf_agents.utils import common
  from tf_agents.utils import nest_utils
label_desc: Use image node_id 2 for calling the BaseConstraint obj's underlying member method code with example usage: obj.__call__(observation, actions) without return types