docstr: take greedy actions
  Args:
      obs (np.ndarray):               (n_agents, obs_shape)
      available_actions (np.ndarray): (n_agents, n_actions)
  Returns:
      actions (np.ndarray):           (n_agents, )
docstr_tok: ["take","greedy","actions","Args",":","obs","(","np.ndarray",")",":","(","n_agents",",","obs_shape",")","available_actions","(","np.ndarray",")",":","(","n_agents",",","n_actions",")","Returns",":","actions","(","np.ndarray",")",":","(","n_agents",",",")"]
code: def predict(self, obs, available_actions):
      """take greedy actions
      Args:
          obs (np.ndarray):               (n_agents, obs_shape)
          available_actions (np.ndarray): (n_agents, n_actions)
      Returns:
          actions (np.ndarray):           (n_agents, )
      """
      obs = torch.tensor(obs, dtype=torch.float32, device=self.device)
      available_actions = torch.tensor(
          available_actions, dtype=torch.long, device=self.device
      )
      agents_q, self.alg.hidden_states = self.alg.predict_local_q(
          obs, self.alg.hidden_states
      )
      # mask unavailable actions
      agents_q[available_actions == 0] = -1e10
      actions = agents_q.max(dim=1)[1].detach().cpu().numpy()
      return actions
  
file_path: PARL/benchmark/torch/qmix/qmix_agent.py
imports: import parl
  import torch
  import numpy
  import os
  import torch
label_desc: Use image node_id 6 for calling the QMixAgent obj's underlying member method code with example usage: obj.predict(obs, available_actions) and returns: actions