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In deepracer/rl_coach/data/bucket, create new folder called rl-deepracer-pretrained. Within rl-deepracer-pretrained, create new folder called model.
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From deepracer/rl_coach/data/bucket/rl-deepracer-sagemaker/model, copy the following five files into rl-deepracer-pretrained/model (where X_Step is the most recently completed):
- X_Step-Y.ckpt.index
- X_Step-Y.ckpt.meta
- X_Step-Y.ckpt.data-00000-of-00001
- model_metadata.json
- checkpoint
- In deepracer/rl_coach, edit rl_deepracer_coach_robomaker.py, uncomment the two pretrained lines and save the file:
- "pretrained_s3_bucket": "{}".format(s3_bucket),
- "pretrained_s3_prefix": "rl-deepracer-pretrained"
- Train as normal.