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out.txt
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out.txt
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True
cuda:0
[]
[]
[]
['limit.npy', 'terminal.npy', 'observation.npy', 'action.npy', 'goal.npy', 'id_dict.npy', 'episode.npy', 'reward.npy']
/dev/shm/expert_3chan_beogym/expert_3chan_unionsquare/5/50
[]
[]
['limit.npy', 'terminal.npy', 'observation.npy', 'action.npy', 'goal.npy', 'id_dict.npy', 'episode.npy', 'reward.npy']
/dev/shm/expert_3chan_beogym/expert_3chan_hudsonriver/5/50
[]
[]
['limit.npy', 'terminal.npy', 'observation.npy', 'action.npy', 'goal.npy', 'id_dict.npy', 'episode.npy', 'reward.npy']
/dev/shm/expert_3chan_beogym/expert_3chan_alleghany/5/50
[]
[]
['limit.npy', 'terminal.npy', 'observation.npy', 'action.npy', 'goal.npy', 'id_dict.npy', 'episode.npy', 'reward.npy']
/dev/shm/expert_3chan_beogym/expert_3chan_wallstreet/5/50
[]
[]
['limit.npy', 'terminal.npy', 'observation.npy', 'action.npy', 'goal.npy', 'id_dict.npy', 'episode.npy', 'reward.npy']
/dev/shm/expert_3chan_beogym/expert_3chan_southshore/5/50
[]
[]
['limit.npy', 'terminal.npy', 'observation.npy', 'action.npy', 'goal.npy', 'id_dict.npy', 'episode.npy', 'reward.npy']
/dev/shm/expert_3chan_beogym/expert_3chan_cmu/5/50
each_len [1000000, 2000000, 3000000, 4000000, 5000000, 6000000]
blah blah
[]
[]
[]
['limit.npy', 'terminal.npy', 'observation.npy', 'action.npy', 'goal.npy', 'id_dict.npy', 'episode.npy', 'reward.npy']
/dev/shm/expert_3chan_beogym/expert_3chan_unionsquare/5/50
[]
[]
['limit.npy', 'terminal.npy', 'observation.npy', 'action.npy', 'goal.npy', 'id_dict.npy', 'episode.npy', 'reward.npy']
/dev/shm/expert_3chan_beogym/expert_3chan_hudsonriver/5/50
[]
[]
['limit.npy', 'terminal.npy', 'observation.npy', 'action.npy', 'goal.npy', 'id_dict.npy', 'episode.npy', 'reward.npy']
/dev/shm/expert_3chan_beogym/expert_3chan_alleghany/5/50
[]
[]
['limit.npy', 'terminal.npy', 'observation.npy', 'action.npy', 'goal.npy', 'id_dict.npy', 'episode.npy', 'reward.npy']
/dev/shm/expert_3chan_beogym/expert_3chan_wallstreet/5/50
[]
[]
['limit.npy', 'terminal.npy', 'observation.npy', 'action.npy', 'goal.npy', 'id_dict.npy', 'episode.npy', 'reward.npy']
/dev/shm/expert_3chan_beogym/expert_3chan_southshore/5/50
[]
[]
['limit.npy', 'terminal.npy', 'observation.npy', 'action.npy', 'goal.npy', 'id_dict.npy', 'episode.npy', 'reward.npy']
/dev/shm/expert_3chan_beogym/expert_3chan_cmu/5/50
each_len [1000000, 2000000, 3000000, 4000000, 5000000, 6000000]
blah blah
/dev/shm/expert_3chan_beogym
using resnet
/dev/shm/ expert_3chan_beogym
Loading trainset...
Loading testset...
Done!
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