Hello, I have read the code carefully, and I have some doubts about num_env.
1: If this parameter equal to 4, is it equivalent to training four models? Or is it something like accelerated training?
2: I used openai baseline and get one summary when using 8 num_envs to train one model but I get 4 summaries when the num envs is 4 and using your code . I read the loger code of openAI and your code , I found that openAI add all infos of all envs to one summary but your code add info to its own FileWriter summary . is it right ? If I only want one summary , can i simply add all infos ? is this right ? if not , How can i get only one summry when i use multiply envs to train one model ?
3: when I test pong using A2C , it cost about 8k to coverage , but when I use openAI baseline ,it only costs about 500 steps to coverage , this makes me very confused .
DongChen06
commented
4 years ago
Hello, I have read the code carefully, and I have some doubts about num_env.
1: If this parameter equal to 4, is it equivalent to training four models? Or is it something like accelerated training?
2: I used openai baseline and get one summary when using 8 num_envs to train one model but I get 4 summaries when the num envs is 4 and using your code . I read the loger code of openAI and your code , I found that openAI add all infos of all envs to one summary but your code add info to its own FileWriter summary . is it right ? If I only want one summary , can i simply add all infos ? is this right ? if not , How can i get only one summry when i use multiply envs to train one model ?
3: when I test pong using A2C , it cost about 8k to coverage , but when I use openAI baseline ,it only costs about 500 steps to coverage , this makes me very confused .
Any suggestions ?
Bests.