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v0.1
GitHub
213cd68d
Split Buffer into processing and update buffers (#2964)
This is the first in a series of PRs that intend to move the agent processing logic (add_experiences and process_experiences) out of the trainer and into a separate class. The plan is to do so in steps: - Split the processing buffers (keeping track of agent trajectories and assembling trajectories) and update buffer (complete trajectories to be used for training) within the Trainer (this PR) - Move the processing buffer and add/process experiences into a separate, outside class - Change the data type of the update buffer to be a Trajectory - Place and read Trajectories from queues, add subscription mechanism for both AgentProcessor and Trainers |
5 年前 | |
|---|---|---|
| .. | ||
| __init__.py | Fix flake8 import warnings (#2584) | 5 年前 |
| models.py | Allow usage with tensorflow 2.0.0 (via tf.compat.v1) (#2665) | 5 年前 |
| offline_trainer.py | When checking for the compatibility of the expert brain with the policy brain, we will remove the action descriptions from the dictionary of things we need to compare. This is to prevent the case where a user has different descriptions for his actions but still wants to train a brain using expert demonstrations. (#2517) | 5 年前 |
| policy.py | check for numpy float64 (#2948) | 5 年前 |
| trainer.py | Split Buffer into processing and update buffers (#2964) | 5 年前 |