Update export doc (fixes + add torch jit)

[araffin]

Description

Related to #836 by @Gregwar

Motivation and Context

• I have raised an issue to propose this change (required for new features and bug fixes)

Types of changes

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to change)
• Documentation (update in the documentation)

Checklist:

• I've read the CONTRIBUTION guide (required)
• I have updated the changelog accordingly (required).
• My change requires a change to the documentation.
• I have updated the tests accordingly (required for a bug fix or a new feature).
• I have updated the documentation accordingly.
• I have reformatted the code using make format (required)
• I have checked the codestyle using make check-codestyle and make lint (required)
• I have ensured make pytest and make type both pass. (required)
• I have checked that the documentation builds using make doc (required)

Note: You can run most of the checks using make commit-checks.

Note: we are using a maximum length of 127 characters per line

[qgallouedec]

Here, it is not possible to copy and paste, because OnnxablePolicy is not defined. I understand that you don't want to rewrite the class to avoid overloading the example. So I would say to just delete everything that has been written before:

jit_path = "sac_traced.pt"

# Trace and optimize the module
traced_module = th.jit.trace(onnxable_model.eval(), dummy_input)
frozen_module = th.jit.freeze(traced_module)
frozen_module = th.jit.optimize_for_inference(frozen_module)
th.jit.save(frozen_module, jit_path)

##### Load and test with onnx

import torch as th

dummy_input = th.randn(1, *observation_size)
loaded_module = th.jit.load(jit_path)
action_jit = loaded_module(dummy_input)