{"action":"closed","issue":{"url":"https://api.github.com/repos/Unity-Technologies/ml-agents/issues/907","repository_url":"https://api.github.com/repos/Unity-Technologies/ml-agents","labels_url":"https://api.github.com/repos/Unity-Technologies/ml-agents/issues/907/labels{/name}","comments_url":"https://api.github.com/repos/Unity-Technologies/ml-agents/issues/907/comments","events_url":"https://api.github.com/repos/Unity-Technologies/ml-agents/issues/907/events","html_url":"https://github.com/Unity-Technologies/ml-agents/issues/907","id":334983138,"node_id":"MDU6SXNzdWUzMzQ5ODMxMzg=","number":907,"title":"Is the code right in the sequence_length in Behavioral Cloning?","user":{"login":"icaro56","id":7433049,"node_id":"MDQ6VXNlcjc0MzMwNDk=","avatar_url":"https://avatars3.githubusercontent.com/u/7433049?v=4","gravatar_id":"","url":"https://api.github.com/users/icaro56","html_url":"https://github.com/icaro56","followers_url":"https://api.github.com/users/icaro56/followers","following_url":"https://api.github.com/users/icaro56/following{/other_user}","gists_url":"https://api.github.com/users/icaro56/gists{/gist_id}","starred_url":"https://api.github.com/users/icaro56/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/icaro56/subscriptions","organizations_url":"https://api.github.com/users/icaro56/orgs","repos_url":"https://api.github.com/users/icaro56/repos","events_url":"https://api.github.com/users/icaro56/events{/privacy}","received_events_url":"https://api.github.com/users/icaro56/received_events","type":"User","site_admin":false},"labels":[{"id":687381587,"node_id":"MDU6TGFiZWw2ODczODE1ODc=","url":"https://api.github.com/repos/Unity-Technologies/ml-agents/labels/help-wanted","name":"help-wanted","color":"33aa3f","default":false}],"state":"closed","locked":false,"assignee":{"login":"xiaomaogy","id":5985076,"node_id":"MDQ6VXNlcjU5ODUwNzY=","avatar_url":"https://avatars3.githubusercontent.com/u/5985076?v=4","gravatar_id":"","url":"https://api.github.com/users/xiaomaogy","html_url":"https://github.com/xiaomaogy","followers_url":"https://api.github.com/users/xiaomaogy/followers","following_url":"https://api.github.com/users/xiaomaogy/following{/other_user}","gists_url":"https://api.github.com/users/xiaomaogy/gists{/gist_id}","starred_url":"https://api.github.com/users/xiaomaogy/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/xiaomaogy/subscriptions","organizations_url":"https://api.github.com/users/xiaomaogy/orgs","repos_url":"https://api.github.com/users/xiaomaogy/repos","events_url":"https://api.github.com/users/xiaomaogy/events{/privacy}","received_events_url":"https://api.github.com/users/xiaomaogy/received_events","type":"User","site_admin":false},"assignees":[{"login":"xiaomaogy","id":5985076,"node_id":"MDQ6VXNlcjU5ODUwNzY=","avatar_url":"https://avatars3.githubusercontent.com/u/5985076?v=4","gravatar_id":"","url":"https://api.github.com/users/xiaomaogy","html_url":"https://github.com/xiaomaogy","followers_url":"https://api.github.com/users/xiaomaogy/followers","following_url":"https://api.github.com/users/xiaomaogy/following{/other_user}","gists_url":"https://api.github.com/users/xiaomaogy/gists{/gist_id}","starred_url":"https://api.github.com/users/xiaomaogy/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/xiaomaogy/subscriptions","organizations_url":"https://api.github.com/users/xiaomaogy/orgs","repos_url":"https://api.github.com/users/xiaomaogy/repos","events_url":"https://api.github.com/users/xiaomaogy/events{/privacy}","received_events_url":"https://api.github.com/users/xiaomaogy/received_events","type":"User","site_admin":false}],"milestone":null,"comments":1,"created_at":"2018-06-22T18:52:30Z","updated_at":"2018-08-14T17:52:36Z","closed_at":"2018-08-14T17:52:36Z","author_association":"NONE","body":"bc/trainer.py\r\nBehavioralCloningTrainer class\r\n\r\nIn the function take_action, the self.model.sequence_length is informed as 1, but if recurrent is set to True, this parameter mabe should b self.sequence_length.\r\n```\r\ndef take_action(self, all_brain_info: AllBrainInfo):\r\n        if len(all_brain_info[self.brain_name].agents) == 0:\r\n            return [], [], [], None\r\n\r\n        agent_brain = all_brain_info[self.brain_name]\r\n        feed_dict = {self.model.dropout_rate: 1.0, self.model.sequence_length: 1}\r\n...\r\n```\r\nPlease check this part of the code."}}
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