larroy commented on a change in pull request #15120: [bug] fix higher grad log
URL: https://github.com/apache/incubator-mxnet/pull/15120#discussion_r290526536
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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",
+ {n->inputs[1]}, nullptr, &n);
auto ggx_mid = MakeNode("elemwise_mul", n->attrs.name +
"_backward_mid_grad_grad",
- {gx, gx}, nullptr, &n);
+ {gx_mul_head_grads, nnvm::NodeEntry{g_lx}},
nullptr, &n);
auto ggx = MakeNode("negative", n->attrs.name + "_backward_grad_grad",
{nnvm::NodeEntry{ggx_mid}}, nullptr, &n);
std::vector<nnvm::NodeEntry> ret;
ret.emplace_back(MakeNode("elemwise_mul", n->attrs.name +
"_backward_grad_grad",
- {ograds[0], gx}, nullptr, &n));
+ {ograds[0], nnvm::NodeEntry{g_lx}}, nullptr, &n));
Review comment:
Hi. What do you mean by head_grads.grad? NodeEntry doesn't have a grad
field. Could you clarify? Are you referring to the python code below? The
gradient is always 0 when attach_grad() is called. The value is updated after
running backward on an output, or using autograd.grad.
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