| commit | e80423f3417c5fb24ee8d2158db96efabe521dbb | [log] [tgz] |
|---|---|---|
| author | Aapo Kyrola <akyrola@fb.com> | Thu Dec 15 09:30:47 2016 -0800 |
| committer | Bram Wasti <bwasti@dev11999.prn1.facebook.com> | Thu Dec 15 12:01:31 2016 -0800 |
| tree | 1cb1f76e33582b69d46553b19a8406b1087f1b43 | |
| parent | cb918ac727c87e59d6f7caebdf9e2d2e282878c1 [diff] |
bug fix to distringuish train/test data Summary: We often use same net for training and testing, but we must distinguish their data. My yestterday's diff forgot to include that distinction (it was in the xray sampler before), and this diff adds it. Basically one provides a name for the input source for data_workers, and all the queues and scratch spaces are suffixed with that to separate them. Also specify the caffe2 queue's size to 4, which is empirically found to be sufficient. It was errorneously defined to be function of batch size, which does not make sense as each *element* in the queue is a batch, and led to out of memory issues on xray trainer. Differential Revision: D4329449 fbshipit-source-id: c994da1c8b0935b8eda2402c118d49b76caa7da8
Caffe2 is a deep learning framework made with expression, speed, and modularity in mind. It is an experimental refactoring of Caffe, and allows a more flexible way to organize computation.
Read the installation instructions for installation details.
Caffe2 is released under the BSD 2-Clause license.