Allow multi-proc env to be rendered.

lib/RLTrader.py

@@ -213,23 +213,28 @@ def test(self, model_epoch: int = 0, should_render: bool = True):
 
         del train_provider
 
-        test_env = SubprocVecEnv([make_env(test_provider, i) for i in range(self.n_envs)])
+        test_env = DummyVecEnv([make_env(test_provider, i) for i in range(1)])
 
         model_path = path.join('data', 'agents', f'{self.study_name}__{model_epoch}.pkl')
         model = self.Model.load(model_path, env=test_env)
 
         self.logger.info(f'Testing model ({self.study_name}__{model_epoch})')
 
+        zero_completed_obs = np.zeros((self.n_envs,) + test_env.observation_space.shape)
+        zero_completed_obs[0, :] = test_env.reset()
+
         state = None
-        obs, rewards = test_env.reset(), []
+        rewards = []
 
         for _ in range(len(test_provider.data_frame)):
-            action, state = model.predict(obs, state=state)
+            action, state = model.predict(zero_completed_obs, state=state)
             obs, reward, _, __ = test_env.step(action)
 
+            zero_completed_obs[0, :] = obs
+
             rewards.append(reward)
 
-            if should_render and self.n_envs == 1:
+            if should_render:
                 test_env.render(mode='human')
 
         self.logger.info(

optimize.py

@@ -12,7 +12,7 @@ def optimize_code(params):
 
 
 if __name__ == '__main__':
-    n_process = multiprocessing.cpu_count() - 4
+    n_process = multiprocessing.cpu_count()
     params = {}
 
     processes = []