xidulu commented on a change in pull request #15495: [Numpy] Added operator
logaddexp; added support for zero-size tensor in BinaryBroadcastBackwardUseIn
URL: https://github.com/apache/incubator-mxnet/pull/15495#discussion_r302343715
##########
File path: src/operator/numpy/np_elemwise_broadcast_op.cc
##########
@@ -186,6 +212,21 @@
MXNET_OPERATOR_REGISTER_NP_BINARY_SCALAR(_npi_power_scalar)
.set_attr<FCompute>("FCompute<cpu>", BinaryScalarOp::Compute<cpu,
mshadow_op::power>)
.set_attr<nnvm::FGradient>("FGradient",
ElemwiseGradUseIn{"_backward_power_scalar"});
+MXNET_OPERATOR_REGISTER_NP_BINARY_SCALAR(_npi_logaddexp_scalar)
+.set_attr<FCompute>("FCompute<cpu>", BinaryScalarOp::Compute<cpu,
mshadow_op::logaddexp>)
+.set_attr<nnvm::FGradient>("Fgradient",
ElemwiseGradUseIn{"_backward_logaddexp_scalar"});
+
+
+MXNET_OPERATOR_REGISTER_BINARY(_backward_logaddexp_scalar)
+.add_argument("scalar", "float", "scalar value")
+.set_attr_parser([](NodeAttrs *attrs) { attrs->parsed =
std::stod(attrs->dict["scalar"]); })
+.set_attr<FCompute>("FCompute<cpu>", BinaryScalarOp::Backward<
+ cpu, mshadow_op::logadd_left>);
+
+
+
+
+
Review comment:
blank lines removed, thanks for reviewing
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