{"action":"opened","issue":{"url":"https://api.github.com/repos/basveeling/wavenet/issues/14","repository_url":"https://api.github.com/repos/basveeling/wavenet","labels_url":"https://api.github.com/repos/basveeling/wavenet/issues/14/labels{/name}","comments_url":"https://api.github.com/repos/basveeling/wavenet/issues/14/comments","events_url":"https://api.github.com/repos/basveeling/wavenet/issues/14/events","html_url":"https://github.com/basveeling/wavenet/issues/14","id":180117608,"number":14,"title":"Performance benchmarks","user":{"login":"lelayf","id":1046340,"avatar_url":"https://avatars.githubusercontent.com/u/1046340?v=3","gravatar_id":"","url":"https://api.github.com/users/lelayf","html_url":"https://github.com/lelayf","followers_url":"https://api.github.com/users/lelayf/followers","following_url":"https://api.github.com/users/lelayf/following{/other_user}","gists_url":"https://api.github.com/users/lelayf/gists{/gist_id}","starred_url":"https://api.github.com/users/lelayf/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/lelayf/subscriptions","organizations_url":"https://api.github.com/users/lelayf/orgs","repos_url":"https://api.github.com/users/lelayf/repos","events_url":"https://api.github.com/users/lelayf/events{/privacy}","received_events_url":"https://api.github.com/users/lelayf/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2016-09-29T17:51:40Z","updated_at":"2016-09-29T17:51:40Z","closed_at":null,"body":"Hi ! I'm training a reasonably small network with 111888 parameters (2 stacks, dilation depth 10 and all other settings left untouched) on a single speaker dataset (77MB of 16 bit 44.1kHz WAV files = 32784 batches of 16). The ETA for one epoch is 42682s, so almost 12 hours. I'm using a Tesla K80, is that training time in line with your experience ? I know for sure I am processing 100K samples in half a second with a different implementation (based on TensorFlow).  When we say batch size is 16, are these 16 fragments of 4223 samples = 67528 samples ? If that's the case then I am processing 67K samples in about 30 seconds. Also is the stride a way to say our fragments should overlap by 128 samples when the input is split ?\r\ncheers"}}
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