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GRU 和 LSTM，结论是两者可以做到差不多的 performance，又比较了 simple RNN 和 GRU，在 100M 参数的模型上前者还要好一点。最后似乎没写实际系统中用选择了哪一个。","created_at":"2016-11-30T05:45:04Z","updated_at":"2016-11-30T05:45:04Z","html_url":"https://github.com/unisound-ail/ds2-on-paddle/pull/1#discussion_r90172096","pull_request_url":"https://api.github.com/repos/unisound-ail/ds2-on-paddle/pulls/1","_links":{"self":{"href":"https://api.github.com/repos/unisound-ail/ds2-on-paddle/pulls/comments/90172096"},"html":{"href":"https://github.com/unisound-ail/ds2-on-paddle/pull/1#discussion_r90172096"},"pull_request":{"href":"https://api.github.com/repos/unisound-ail/ds2-on-paddle/pulls/1"}}},"pull_request":{"url":"https://api.github.com/repos/unisound-ail/ds2-on-paddle/pulls/1","id":95666095,"html_url":"https://github.com/unisound-ail/ds2-on-paddle/pull/1","diff_url":"https://github.com/unisound-ail/ds2-on-paddle/pull/1.diff","patch_url":"https://github.com/unisound-ail/ds2-on-paddle/pull/1.patch","issue_url":"https://api.github.com/repos/unisound-ail/ds2-on-paddle/issues/1","number":1,"state":"open","locked":false,"title":"[wip] 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