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README.md
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---
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library_name: gia
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tags:
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- deep-reinforcement-learning
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- reinforcement-learning
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- gia
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- multi-task
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- multi-modal
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- imitation-learning
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- offline-reinforcement-learning
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---
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An imitation learning environment for the plate-slide-back-v2 environment, sample for the policy plate-slide-back-v2
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This environment was created as part of the Generally Intelligent Agents project gia: https://github.com/huggingface/gia
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## Load dataset
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First, clone it with
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```sh
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git clone https://huggingface.co/datasets/qgallouedec/prj_gia_dataset_metaworld_plate_slide_back_v2_1111
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```
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Then, load it with
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```python
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import numpy as np
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dataset = np.load("prj_gia_dataset_metaworld_plate_slide_back_v2_1111/dataset.npy", allow_pickle=True).item()
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print(dataset.keys()) # dict_keys(['observations', 'actions', 'dones', 'rewards'])
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```
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dataset.npy
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version https://git-lfs.github.com/spec/v1
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oid sha256:9c926b5b391c1dda408a96631232b77d6db7ecf5cd39d72cb3d69760b815e9fe
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size 17700601
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