reinforcement-learning

Here's the reproduction:

import os
import tempfile
from pathlib import Path
from ray._private.runtime_env.packaging import _zip_directory
from zipfile import ZipFile

with tempfile.TemporaryDirectory() as tmp_dir:
    # Prepare test directory
    path = Path(tmp_dir)
    subdir = path / "subdir"
    subdir.mkdir(parents=True)
    file1 = subdir / "file1.txt"
    with file

Continuation of issue #2474 as discussed here

Is there a way to train a bidirectional RNN (like LSTM or GRU) on trax nowadays?

The following applies to DDPG and TD3, and possibly other models. The following libraries were installed in a virtual environment:

numpy==1.16.4
stable-baselines==2.10.0
gym==0.14.0
tensorflow==1.14.0

Episode rewards do not seem to be updated in model.learn() before callback.on_step(). Depending on which callback.locals variable is used, this means that:

• episode rewards may n