{"action":"created","issue":{"url":"https://api.github.com/repos/lukemelas/EfficientNet-PyTorch/issues/5","repository_url":"https://api.github.com/repos/lukemelas/EfficientNet-PyTorch","labels_url":"https://api.github.com/repos/lukemelas/EfficientNet-PyTorch/issues/5/labels{/name}","comments_url":"https://api.github.com/repos/lukemelas/EfficientNet-PyTorch/issues/5/comments","events_url":"https://api.github.com/repos/lukemelas/EfficientNet-PyTorch/issues/5/events","html_url":"https://github.com/lukemelas/EfficientNet-PyTorch/issues/5","id":451168424,"node_id":"MDU6SXNzdWU0NTExNjg0MjQ=","number":5,"title":"Testing result ","user":{"login":"Oktai15","id":17337773,"node_id":"MDQ6VXNlcjE3MzM3Nzcz","avatar_url":"https://avatars1.githubusercontent.com/u/17337773?v=4","gravatar_id":"","url":"https://api.github.com/users/Oktai15","html_url":"https://github.com/Oktai15","followers_url":"https://api.github.com/users/Oktai15/followers","following_url":"https://api.github.com/users/Oktai15/following{/other_user}","gists_url":"https://api.github.com/users/Oktai15/gists{/gist_id}","starred_url":"https://api.github.com/users/Oktai15/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/Oktai15/subscriptions","organizations_url":"https://api.github.com/users/Oktai15/orgs","repos_url":"https://api.github.com/users/Oktai15/repos","events_url":"https://api.github.com/users/Oktai15/events{/privacy}","received_events_url":"https://api.github.com/users/Oktai15/received_events","type":"User","site_admin":false},"labels":[{"id":1383055877,"node_id":"MDU6TGFiZWwxMzgzMDU1ODc3","url":"https://api.github.com/repos/lukemelas/EfficientNet-PyTorch/labels/enhancement","name":"enhancement","color":"a2eeef","default":true}],"state":"open","locked":false,"assignee":{"login":"lukemelas","id":13307440,"node_id":"MDQ6VXNlcjEzMzA3NDQw","avatar_url":"https://avatars1.githubusercontent.com/u/13307440?v=4","gravatar_id":"","url":"https://api.github.com/users/lukemelas","html_url":"https://github.com/lukemelas","followers_url":"https://api.github.com/users/lukemelas/followers","following_url":"https://api.github.com/users/lukemelas/following{/other_user}","gists_url":"https://api.github.com/users/lukemelas/gists{/gist_id}","starred_url":"https://api.github.com/users/lukemelas/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/lukemelas/subscriptions","organizations_url":"https://api.github.com/users/lukemelas/orgs","repos_url":"https://api.github.com/users/lukemelas/repos","events_url":"https://api.github.com/users/lukemelas/events{/privacy}","received_events_url":"https://api.github.com/users/lukemelas/received_events","type":"User","site_admin":false},"assignees":[{"login":"lukemelas","id":13307440,"node_id":"MDQ6VXNlcjEzMzA3NDQw","avatar_url":"https://avatars1.githubusercontent.com/u/13307440?v=4","gravatar_id":"","url":"https://api.github.com/users/lukemelas","html_url":"https://github.com/lukemelas","followers_url":"https://api.github.com/users/lukemelas/followers","following_url":"https://api.github.com/users/lukemelas/following{/other_user}","gists_url":"https://api.github.com/users/lukemelas/gists{/gist_id}","starred_url":"https://api.github.com/users/lukemelas/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/lukemelas/subscriptions","organizations_url":"https://api.github.com/users/lukemelas/orgs","repos_url":"https://api.github.com/users/lukemelas/repos","events_url":"https://api.github.com/users/lukemelas/events{/privacy}","received_events_url":"https://api.github.com/users/lukemelas/received_events","type":"User","site_admin":false}],"milestone":null,"comments":1,"created_at":"2019-06-02T08:43:39Z","updated_at":"2019-06-03T05:44:35Z","closed_at":null,"author_association":"NONE","body":"Will you check your reimplementation except for accuracy? The same speed & memory?"},"comment":{"url":"https://api.github.com/repos/lukemelas/EfficientNet-PyTorch/issues/comments/498120336","html_url":"https://github.com/lukemelas/EfficientNet-PyTorch/issues/5#issuecomment-498120336","issue_url":"https://api.github.com/repos/lukemelas/EfficientNet-PyTorch/issues/5","id":498120336,"node_id":"MDEyOklzc3VlQ29tbWVudDQ5ODEyMDMzNg==","user":{"login":"alantwm","id":10906401,"node_id":"MDQ6VXNlcjEwOTA2NDAx","avatar_url":"https://avatars1.githubusercontent.com/u/10906401?v=4","gravatar_id":"","url":"https://api.github.com/users/alantwm","html_url":"https://github.com/alantwm","followers_url":"https://api.github.com/users/alantwm/followers","following_url":"https://api.github.com/users/alantwm/following{/other_user}","gists_url":"https://api.github.com/users/alantwm/gists{/gist_id}","starred_url":"https://api.github.com/users/alantwm/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/alantwm/subscriptions","organizations_url":"https://api.github.com/users/alantwm/orgs","repos_url":"https://api.github.com/users/alantwm/repos","events_url":"https://api.github.com/users/alantwm/events{/privacy}","received_events_url":"https://api.github.com/users/alantwm/received_events","type":"User","site_admin":false},"created_at":"2019-06-03T05:44:35Z","updated_at":"2019-06-03T05:44:35Z","author_association":"NONE","body":"Hello Luke,\r\n\r\nThanks for this great piece of work! I'm testing the inference time for efficientnet-B1 vs. Resnet152 on the panda image you provided. And on my CPU I get 150ms for efficientnet-B1 and 314ms for Resnet152 (using torchvision's resnet152 model). I got the timing using the %%timeit feature of jupyter notebooks. Considering the difference in the number of parameters, the inference time seems too similar. Do you know what might cause this? Do you experience something similar?"}}
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