Fix DQN w RNN tutorial

Author: svekars

intermediate_source/dqn_with_rnn_tutorial.py

@@ -342,7 +342,10 @@
 # will return a new instance of the LSTM (with shared weights) that will
 # assume that the input data is sequential in nature.
 #
-policy = Seq(feature, lstm.set_recurrent_mode(True), mlp, qval)
+from torchrl.modules import set_recurrent_mode
+
+with set_recurrent_mode(True):
+    policy = Seq(feature, lstm, mlp, qval)
 
 ######################################################################
 # Because we still have a couple of uninitialized parameters we should
@@ -389,7 +392,9 @@
 #   For the sake of efficiency, we're only running a few thousands iterations
 #   here. In a real setting, the total number of frames should be set to 1M.
 #
-collector = SyncDataCollector(env, stoch_policy, frames_per_batch=50, total_frames=200, device=device)
+collector = SyncDataCollector(
+    env, stoch_policy, frames_per_batch=50, total_frames=200, device=device
+)
 rb = TensorDictReplayBuffer(
     storage=LazyMemmapStorage(20_000), batch_size=4, prefetch=10
 )
@@ -464,5 +469,5 @@
 #
 # Further Reading
 # ---------------
-# 
+#
 # - The TorchRL documentation can be found `here <https://pytorch.org/rl/>`_.