[BE] Make coding_ddpg.py runnable outside of Colab env (#2750)

* [BE] Make coding_ddpg.py runnable outside of Colab env

By setting spawn method to fork

Also, add missing parenthesis

---------

Co-authored-by: Vincent Moens <[email protected]>
Co-authored-by: Svetlana Karslioglu <[email protected]>

Author: 3 people

advanced_source/coding_ddpg.py

@@ -63,16 +63,25 @@
 #      %%bash
 #      pip3 install torchrl mujoco glfw
 
-import torchrl
-import torch
-import tqdm
-from typing import Tuple
-
 # sphinx_gallery_start_ignore
 import warnings
 warnings.filterwarnings("ignore")
+import multiprocessing
+# TorchRL prefers spawn method, that restricts creation of  ``~torchrl.envs.ParallelEnv`` inside
+# `__main__` method call, but for the easy of reading the code switch to fork
+# which is also a default spawn method in Google's Colaboratory
+try:
+    multiprocessing.set_start_method("fork")
+except RuntimeError:
+    assert multiprocessing.get_start_method() == "fork"
 # sphinx_gallery_end_ignore
 
+
+import torchrl
+import torch
+import tqdm
+from typing import Tuple
+
 ###############################################################################
 # We will execute the policy on CUDA if available
 device =  torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
@@ -1219,6 +1228,6 @@ def ceil_div(x, y):
 # 
 # To iterate further on this loss module we might consider:
 # 
-# - Using `@dispatch` (see `[Feature] Distpatch IQL loss module <https://github.com/pytorch/rl/pull/1230>`_.
+# - Using `@dispatch` (see `[Feature] Distpatch IQL loss module <https://github.com/pytorch/rl/pull/1230>`_.)
 # - Allowing flexible TensorDict keys.
 #