larroy commented on a change in pull request #15120: [bug] fix higher grad log
URL: https://github.com/apache/incubator-mxnet/pull/15120#discussion_r290528016
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File path: src/operator/tensor/elemwise_unary_op_basic.cc
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@@ -1074,16 +1074,19 @@
MXNET_OPERATOR_REGISTER_BINARY_WITH_SPARSE_CPU_DR(_backward_log,
[](const nnvm::NodePtr& n, const std::vector<nnvm::NodeEntry>& ograds) {
// For f(x) -> f = log
// f''(x) = -1 * (f'(x) * f'(x))
- auto gx = nnvm::NodeEntry{n};
+ auto gx_mul_head_grads = nnvm::NodeEntry{n}; // f'(x) * head_grads
+ auto head_grads = nnvm::NodeEntry{n->inputs[0]};
+ auto g_lx = MakeNode("reciprocal", n->attrs.name + "_backward_log_grad",
Review comment:
can we add a comment about the inputs and what is g_lx? it would help
reason about the code. Are the inputs of n (backward_log)
- 0: input gradient
- 1: x
?
So g_lx is a node having 1/x ? or the derivative of the log right? can we
rename to g_logx ?
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