what will the equivalent code be for

```
z_loss = 0.5 * tf.reduce_sum(tf.square(z_mean) + tf.exp(z_logvar) - z_logvar - 1, axis = [1,2,3])
```

What are the pytorch equivalent for reduce_mean and reduce_sum

Thanks

what will the equivalent code be for

```
z_loss = 0.5 * tf.reduce_sum(tf.square(z_mean) + tf.exp(z_logvar) - z_logvar - 1, axis = [1,2,3])
```

What are the pytorch equivalent for reduce_mean and reduce_sum

Thanks

`torch.mean`

and `torch.sum`

would be the replacements (or call `.mean()`

or `.sum()`

on a tensor directly).

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