Update Agent_class.py

Agent_class.py

@@ -2,7 +2,7 @@ import torch
 
 class ParameterisedPolicy(torch.nn.Module):
     """
-    REINFORCE RL agent class. Returns action when the ParameterisedPolicy.act(observation) is used.
+    REINFORCE RL agent class. Returns action when the ParameterisedPolicy.act(observation) method is used.
     observation is a gym state vector.
     obs_len - length of the state vector
     act_space_len - length of the action vector
@@ -10,8 +10,6 @@ class ParameterisedPolicy(torch.nn.Module):
     """
     def __init__(self, obs_len=8, act_space_len=2):
         super().__init__()
-        self.deterministic = False
-        self.continuous = True
         self.obs_len = obs_len
         self.act_space_len = act_space_len
         self.lin_1 = torch.nn.Linear(self.obs_len, 256)
@@ -41,7 +39,9 @@ class ParameterisedPolicy(torch.nn.Module):
         return mu, sigma
     
     def act(self, observation):
-        
+        """
+        Method returns action when gym state vector is passed.
+        """
         (mus, sigmas) = self.forward(torch.tensor(observation, dtype=torch.float32))
         m = torch.distributions.normal.Normal(mus, sigmas)
         action = m.sample().detach().numpy()