apeforest commented on a change in pull request #15413: [MXNET-978] Higher
Order Gradient Support `reciprocal`, `abs`.
URL: https://github.com/apache/incubator-mxnet/pull/15413#discussion_r300885216
##########
File path: src/operator/tensor/elemwise_unary_op_basic.cc
##########
@@ -717,7 +717,38 @@ Example::
MXNET_OPERATOR_REGISTER_BINARY(_backward_reciprocal)
.set_attr<FCompute>("FCompute<cpu>",
- ElemwiseBinaryOp::Compute<cpu, unary_bwd<mshadow_op::reciprocal_grad> >);
+ ElemwiseBinaryOp::Compute<cpu, unary_bwd<mshadow_op::reciprocal_grad> >)
+.set_attr<nnvm::FGradient>("FGradient",
+ [](const nnvm::NodePtr& n, const std::vector<nnvm::NodeEntry>& ograds) {
+ // ograds[0]: dL/dxgrad
+ // inputs[0]: dL/dy
+ // inputs[1]: x
+ // f(x) = y = 1/x
+ // f'(x) = -1/x^2
+ // f''(x) = 2/x^3 = -2 * (f'(x) * f(x))
+
+ const std::unordered_map<std::string, std::string> args = {{"scalar",
"-2.0"}};
+
+ auto dydx_mul_dldy = nnvm::NodeEntry{n}; // f'(x) * head_grads
+ auto dydx = MakeNode("elemwise_div", n->attrs.name + "_dydx",
+ {dydx_mul_dldy, n->inputs[0]}, nullptr, &n);
+ auto fx = MakeNode("reciprocal", n->attrs.name + "_fx",
+ {n->inputs[1]}, nullptr, &n);
+
+ auto d2ydx2_mid = MakeNode("elemwise_mul", n->attrs.name + "_d2ydx2_mid",
+ {dydx_mul_dldy, nnvm::NodeEntry{fx}}, nullptr,
&n);
+
+ auto d2ydx2 = MakeNode("_mul_scalar", n->attrs.name + "_d2ydx2",
+ {nnvm::NodeEntry{d2ydx2_mid}}, &args, &n);
+
+ std::vector<nnvm::NodeEntry> ret;
+
+ ret.emplace_back(MakeNode("elemwise_mul", n->attrs.name +
"_backward_grad_grad",
Review comment:
This term will be useful when you calculate the third order (and above)
gradient.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to 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
