{"push_id":845809047,"size":1,"distinct_size":1,"ref":"refs/heads/tensor_notype","head":"e546d135ea08d16bb8dd360ef3c03b63d8169202","before":"71a31bcfc1ee979672c16c2c14f6d66c1d342b17","commits":[{"sha":"e546d135ea08d16bb8dd360ef3c03b63d8169202","author":{"email":"d468ff703b23435fce3e870638a3446bcdbc607b@gmail.com","name":"Yangqing Jia"},"message":"Two main changes:\n\n(1) Loss: do not coerce a gradient output. Although it may be numerically more efficient to do so, it makes the definition of a loss kind of funny if one does not really want to run backward pass.\n(2) Autodifferentiation: allow more explicit in-place check, in-place is now opt-in, and implemented a simple SSA/IR gradient generation scheme. Also added some core gradient tests.\n\nMisc bugfixes as well.","distinct":true,"url":"https://api.github.com/repos/Yangqing/caffe2/commits/e546d135ea08d16bb8dd360ef3c03b63d8169202"}]}