41 lines
1000 B
Python
41 lines
1000 B
Python
import tqdm
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import expert
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import copy
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import sys, os
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def process_all_experts(env_args={}, policy_args={}):
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"""
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Process all experts in the Interaction Dataset
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For now, using NormalizedIntersimpleExpert with NRasterizedIncrementingAgent environment
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Args:
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env_args (dict): default environment kwargs
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policy_args (dict): default policy kwargs
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"""
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for loc in LOCATIONS:
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for track in TRACKS:
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it_env_args = copy.deepcopy(env_args)
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it_env_args.update({
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'loc':loc,
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'track':track,
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})
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it_path = 'newpathname'
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expert.demonstrations(
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expert='NormalizedIntersimpleExpert',
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env='NRasterizedIncrementingAgent',
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path=it_path,
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env_args=it_env_args,
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policy_args=policy_args,
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)
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if __name__=='__main__':
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import fire
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fire.Fire(process_all_experts)
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