wkcn commented on a change in pull request #18492:
URL: https://github.com/apache/incubator-mxnet/pull/18492#discussion_r436195297
##########
File path: src/operator/nn/cudnn/cudnn_batch_norm-inl.h
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@@ -228,7 +228,7 @@ class CuDNNBatchNormOp {
&a,
&b,
&a,
- req[cudnnbatchnorm::kGamma] == kWriteTo ? &b: &b_add,
+ req[cudnnbatchnorm::kGamma] == kAddTo ? &b_add : &b,
Review comment:
The gradient of input, gamma and beta on CPU is wrong when `grad_req` is
True. The gradient of input is not accumulated. The gradient of gamma and beta
are both zero.
```python
import mxnet as mx
from mxnet.gluon import nn
N = 1
C = 3
H = W = 2
block = nn.BatchNorm()
block.collect_params().initialize()
block.collect_params().setattr('grad_req', 'add')
x = mx.nd.arange(N*C*H*W).reshape((N, C, H, W))
x.attach_grad()
for i in range(2):
with mx.autograd.record():
y = block(x)
loss = (y * y).sum()
loss.backward()
print(x.grad, block.gamma.grad(), block.beta.grad())
```
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