Comments (2)
Hi Paul,
thanks for raising this, I need to clarify this in the documentation. The signature of your __call__
function expects a train
variable. This is useful for models with dropout, for example.
You can solve the issue by simply changing def __call__(self, x):
into def __call__(self, x, **kwargs):
.
Notice that the model also checks whether the number of classes in the data corresponds to the number of logits. If you want to run this just as an example, you my want to redefine y
to something like y = jnp.arange(10)[None].repeat(5, axis=0)
.
from fortuna.
@gianlucadetommaso thanks! Sounds good, it works now with your suggestion of adding **kwargs
in the __call__
arguments.
from fortuna.
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