docstr: This method calls choose_action to get action based on obs
docstr_tok: ["This","method","calls","choose_action","to","get","action","based","on","obs"]
code: def act(
      self,
      obs: CBInput,
  ) -> Tuple[torch.Tensor, torch.Tensor]:
      """
      This method calls choose_action to get action based on obs
      """
      chosen_action, log_prob = self.choose_action(
          features_all_arms=obs.context_arm_features
      )
      return chosen_action, log_prob
  
imports: import random
  from dataclasses import replace
  from typing import Any, Optional, Tuple
  import reagent.core.types
  import torch
  from reagent.core.types import CBInput
  from reagent.gym.policies.policy import Policy
  from reagent.gym.policies.samplers.discrete_sampler import GreedyActionSampler
  from reagent.gym.types import Sampler, Scorer
  from reagent.models.linear_regression import LinearRegressionUCB
  from reagent.training.cb.base_trainer import BaseCBTrainerWithEval
  from reagent.training.cb.linucb_trainer import LinUCBTrainer
  from reagent.training.parameters import LinUCBTrainerParameters
label_desc: Use image node_id 5 for calling the DynamicBanditAgent obj's underlying member method code with example usage: obj.act(obs) and returns: chosen_action,  log_prob