Comments (4)
Hello,
Thank you very much for your interest in our work. We are currently organizing the relevant code for rendering and saving replay, and we plan to submit a Pull Request within the next few days. We appreciate your patience.
Best wishes.
from lightzero.
Hello,
The example code for loading a trained model and saving the replay is now available in this Pull Request. To store the replay, you can set main_config.env.save_video = True
in this file, and specify the path to your trained model's checkpoint file in model_path
.
Best wishes.
from lightzero.
Hello ! Thanks a lot :D I'll be testing ASAP ! Thank you for your work
from lightzero.
Hello,
The Pull Request related to real-time video rendering and saving replay has been merged into the main branch. Please refer to the instructions in this file for visualizing the agent.
Best regards.
from lightzero.
Related Issues (16)
- Low resource utilization with default gomoku_alphazero_sp_mode_config.py HOT 3
- cannot import name 'ez_tree' from 'lzero.mcts.ctree.ctree_efficientzero' (D:\LightZero-main\LightZero-main\lzero\mcts\ctree\ctree_efficientzero\__init__.py) HOT 5
- How to draw train curve HOT 3
- Bugs caused by some interface adjustments. HOT 2
- I dream of agent playing 2048 using this library~ HOT 3
- Unrelated Records During EfficientZero in TensorBoard HOT 2
- Clang Issue - `pip install -e .` HOT 2
- Get a error when "pip install -e ." HOT 5
- Can't get mujoco example working on colab HOT 2
- requirement torch<=1.12.1,>=1.1.0 (from di-engine[common-env]) (from versions: 2.0.0, 2.0.1) HOT 1
- Inhomogeneous Shape of GameSegment.child_visit_segment HOT 6
- Lacking inference script HOT 4
- What is the easiest way to run experiments on colored Atari environments? HOT 1
- Errors on new install HOT 1
- A few questions about starting out and the Chess environment? HOT 3
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from lightzero.