Merge pull request #573 from Unity-Technologies/hotfix-multiple-visual

[Multiple observations] Addresses issue #571

Author: Marwan Mattar

python/unitytrainers/models.py

@@ -80,15 +80,16 @@ def create_continuous_state_encoder(self, h_size, activation, num_layers):
                                      kernel_initializer=c_layers.variance_scaling_initializer(1.0))
         return hidden
 
-    def create_visual_encoder(self, h_size, activation, num_layers):
+    def create_visual_encoder(self, image_input, h_size, activation, num_layers):
         """
         Builds a set of visual (CNN) encoders.
+        :param image_input: The placeholder for the image input to use.
         :param h_size: Hidden layer size.
         :param activation: What type of activation function to use for layers.
         :param num_layers: number of hidden layers to create.
         :return: List of hidden layer tensors.
         """
-        conv1 = tf.layers.conv2d(self.visual_in[-1], 16, kernel_size=[8, 8], strides=[4, 4],
+        conv1 = tf.layers.conv2d(image_input, 16, kernel_size=[8, 8], strides=[4, 4],
                                  activation=tf.nn.elu)
         conv2 = tf.layers.conv2d(conv1, 32, kernel_size=[4, 4], strides=[2, 2],
                                  activation=tf.nn.elu)
@@ -136,7 +137,7 @@ def create_new_obs(self, num_streams, h_size, num_layers):
             hidden_state, hidden_visual = None, None
             if brain.number_visual_observations > 0:
                 for j in range(brain.number_visual_observations):
-                    encoded_visual = self.create_visual_encoder(h_size, activation_fn, num_layers)
+                    encoded_visual = self.create_visual_encoder(self.visual_in[j], h_size, activation_fn, num_layers)
                     visual_encoders.append(encoded_visual)
                 hidden_visual = tf.concat(visual_encoders, axis=1)
             if brain.vector_observation_space_size > 0: