zhanghang1989 commented on a change in pull request #9931: Add axes support to
Dropout for variational dropout in NLP
URL: https://github.com/apache/incubator-mxnet/pull/9931#discussion_r172389676
##########
File path: src/operator/nn/dropout-inl.h
##########
@@ -228,11 +301,27 @@ class DropoutOp {
if (!MKLForward(s, pgen, this->pkeep_, in_data, out_data)) {
const TBlob &mask = out_data[dropout::kMask];
CHECK(req[dropout::kOut] != kAddTo);
- LaunchRNG<DropoutKernel, xpu>(s, pgen, out.Size(),
- out.dptr<DType>(),
- mask.dptr<DType>(),
- in_data[dropout::kData].dptr<DType>(),
- this->pkeep_);
+ // initialize the mask
+ LaunchRNG<BernoulliKernel, xpu>(s, pgen, out.Size(),
+ mask.dptr<DType>(),
+ this->pkeep_);
+ if (req[0] != kNullOp) {
+ // broardcast mul
+ TShape new_lshape, new_rshape, new_oshape;
+ int ndim =
BinaryBroadcastShapeCompact(in_data[dropout::kData].shape_,
+ mask.shape_, out.shape_,
+ &new_lshape, &new_rshape,
&new_oshape);
+ BROADCAST_NDIM_SWITCH(ndim, NDim, {
+ mshadow::Shape<NDim> oshape = new_oshape.get<NDim>();
+ mshadow::Shape<NDim> lstride =
mxnet_op::calc_stride(new_lshape.get<NDim>());
+ mshadow::Shape<NDim> rstride =
mxnet_op::calc_stride(new_rshape.get<NDim>());
+ mxnet_op::Kernel<mxnet_op::binary_broadcast_kernel<NDim, DType,
+ mshadow_op::mul>, xpu>::
+ template LaunchEx(s, new_oshape.Size(), req[0], lstride,
rstride, oshape,
+ in_data[dropout::kData].dptr<DType>(),
+ mask.dptr<DType>(), out.dptr<DType>());
+ });
+ }
}
Review comment:
Thx @cjolivier01 . I added the condition check here
https://github.com/apache/incubator-mxnet/pull/9931/files#diff-4aea2cc24c0bb4e8e48face9faf4aa26R249
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
us...@infra.apache.org
With regards,
Apache Git Services
