Thank you very much for your reply.
I also tried the way you suggested. But still got wrong result.
```
def _mx_logistic_regression_output(inputs, attrs):
label = inputs[1]
pred = _op.sigmoid(inputs[0])
# We use the stable formula: max(pred, 0) - pred * label + log(1 +
exp(-abs(pred)))
one = _expr.const(1, dtype="float32")
exp_neg_abs_x = _op.exp(_op.negative(_op.abs(pred))) # exp(-abs(pred))
soft_relu = _op.add(_op.log(_op.add(one, exp_neg_abs_x)), _op.nn.relu(pred))
loss = _op.nn.relu(pred) - pred * label + soft_relu
return loss
```
```
TVM result:
[[1.8551042 1.8551042 1.8551042 1.8551042]
[1.8551042 1.8551042 1.8551042 1.8551042]
[1.8551042 1.8551042 1.8551042 1.8551042]]
MXNet result:
[[0.7310586 0.7310586 0.7310586 0.7310586]
[0.7310586 0.7310586 0.7310586 0.7310586]
[0.7310586 0.7310586 0.7310586 0.7310586]]
```
---
[Visit
Topic](https://discuss.tvm.ai/t/unsupported-op-logisticregressionoutput-when-import-ncf-model-from-mxnet/6863/3)
to respond.
You are receiving this because you enabled mailing list mode.
To unsubscribe from these emails, [click
here](https://discuss.tvm.ai/email/unsubscribe/78415d10290dc36d87edfb48cd189db325c4fea9f359f676a7d09a34b72b3cf8).
