Bug fix multiple observations

Unity-Technologies · Jan 19, 2018 · ecdbbd7 · ecdbbd7
1 parent a1d35bf
commit ecdbbd7
Showing 1 changed file with 13 additions and 11 deletions.
diff --git a/python/ppo/models.py b/python/ppo/models.py
@@ -215,11 +215,12 @@ def __init__(self, lr, brain, h_size, epsilon, max_step, normalize, num_layers):
 
  hidden_state, hidden_visual, hidden_policy, hidden_value = None, None, None, None
  encoders = []
- for i in range(brain.number_observations):
- height_size, width_size = brain.camera_resolutions[i]['height'], brain.camera_resolutions[i]['width']
- bw = brain.camera_resolutions[i]['blackAndWhite']
- encoders.append(self.create_visual_encoder(height_size, width_size, bw, h_size, 2, tf.nn.tanh, num_layers))
- hidden_visual = tf.concat(encoders, axis=2)
+ if brain.number_observations > 0:
+ for i in range(brain.number_observations):
+ height_size, width_size = brain.camera_resolutions[i]['height'], brain.camera_resolutions[i]['width']
+ bw = brain.camera_resolutions[i]['blackAndWhite']
+ encoders.append(self.create_visual_encoder(height_size, width_size, bw, h_size, 2, tf.nn.tanh, num_layers))
+ hidden_visual = tf.concat(encoders, axis=2)
  if brain.state_space_size > 0:
  s_size = brain.state_space_size
  if brain.state_space_type == "continuous":
@@ -278,12 +279,13 @@ def __init__(self, lr, brain, h_size, epsilon, beta, max_step, normalize, num_la
  self.normalize = normalize
 
  hidden_state, hidden_visual, hidden = None, None, None
- encoders = []
- for i in range(brain.number_observations):
- height_size, width_size = brain.camera_resolutions[i]['height'], brain.camera_resolutions[i]['width']
- bw = brain.camera_resolutions[i]['blackAndWhite']
- encoders.append(self.create_visual_encoder(height_size, width_size, bw, h_size, 1, tf.nn.elu, num_layers)[0])
- hidden_visual = tf.concat(encoders, axis=1)
+ if brain.number_observations > 0:
+ encoders = []
+ for i in range(brain.number_observations):
+ height_size, width_size = brain.camera_resolutions[i]['height'], brain.camera_resolutions[i]['width']
+ bw = brain.camera_resolutions[i]['blackAndWhite']
+ encoders.append(self.create_visual_encoder(height_size, width_size, bw, h_size, 1, tf.nn.elu, num_layers)[0])
+ hidden_visual = tf.concat(encoders, axis=1)
  if brain.state_space_size > 0:
  s_size = brain.state_space_size
  if brain.state_space_type == "continuous":