Fixes for recurrent

ml-agents/mlagents/trainers/ppo/policy.py

     def get_batched_value_estimates(self, batch: AgentBuffer) -> Dict[str, np.ndarray]:
         feed_dict: Dict[tf.Tensor, Any] = {
             self.model.batch_size: batch.num_experiences,
-            self.model.sequence_length: self.sequence_length,
+            self.model.sequence_length: 1,  # We want to feed data in batch-wise, not time-wise.
         }
 
         if self.use_vec_obs:

ml-agents/mlagents/trainers/trajectory.py

         agent_buffer_trajectory["next_vector_in"].append(
             next_vec_vis_obs.vector_observations
         )
-        if exp.memory:
+        if exp.memory is not None:
             agent_buffer_trajectory["memory"].append(exp.memory)
 
         agent_buffer_trajectory["masks"].append(1.0)