class_docstr: The policy action distribution of an agent.
  
  Attributes:
      inputs: input vector to compute samples from.
      model (ModelV2): reference to model producing the inputs.
docstr: Get the deterministic "sampling" output from the distribution.
  This is usually the max likelihood output, i.e. mean for Normal, argmax
  for Categorical, etc..
docstr_tok: ["Get","the","deterministic","``","sampling","''","output","from","the","distribution",".","This","is","usually","the","max","likelihood","output",",","i.e",".","mean","for","Normal",",","argmax","for","Categorical",",","etc",".."]
code: def deterministic_sample(self) -> TensorType:
      """
      Get the deterministic "sampling" output from the distribution.
      This is usually the max likelihood output, i.e. mean for Normal, argmax
      for Categorical, etc..
      """
      raise NotImplementedError
  
file_path: ray/rllib/models/action_dist.py
imports: import numpy
  import gymnasium
  from ray.rllib.models.modelv2 import ModelV2
  from ray.rllib.utils.annotations import DeveloperAPI
  from ray.rllib.utils.typing import TensorType, List, Union, ModelConfigDict
label_desc: Use image node_id 3 for calling the ActionDistribution obj's underlying member method code with example usage: obj.deterministic_sample() without return types