* Fix Batch to_torch method not updating dtype/device of already converted data.
* Fix dtype/device to forwarded by to_tensor for Batch over Batch.
* Add Unit test to check to_torch dtype/device recursive forwarding.
* Batch UT check accessing data using both dict and class style.
* Fix utils to_tensor dtype/device forwarding. Add Unit tests.
* Fix UT.
Co-authored-by: Alexis Duburcq <alexis.duburcq@wandercraft.eu>
Co-authored-by: n+e <463003665@qq.com>
* Enable to convert Batch data back to torch.
* Add torch converter to collector.
* Fix
* Move to_numpy/to_torch convert in dedicated utils.py.
* Use to_numpy/to_torch to convert arrays.
* fix lint
* fix
* Add unit test to check Batch from/to numpy.
* Fix Batch over Batch.
Co-authored-by: Alexis Duburcq <alexis.duburcq@wandercraft.eu>
* add sum_tree.py
* add prioritized replay buffer
* del sum_tree.py
* fix some format issues
* fix weight_update bug
* simply replace replaybuffer in test_dqn without weight update
* weight default set to 1
* fix sampling bug when buffer is not full
* rename parameter
* fix formula error, add accuracy check
* add PrioritizedDQN test
* add test_pdqn.py
* add update_weight() doc
* add ref of prio dqn in readme.md and index.rst
* restore test_dqn.py, fix args of test_pdqn.py
* update atari.py
* fix setup.py
pass the pytest
* fix setup.py
pass the pytest
* add args "render"
* change the tensorboard writter
* change the tensorboard writter
* change device, render, tensorboard log location
* change device, render, tensorboard log location
* remove some wrong local files
* fix some tab mistakes and the envs name in continuous/test_xx.py
* add examples and point robot maze environment
* fix some bugs during testing examples
* add dqn network and fix some args
* change back the tensorboard writter's frequency to ensure ppo and a2c can write things normally
* add a warning to collector
* rm some unrelated files
* reformat
* fix a bug in test_dqn due to the model wrong selection
