Training neural networks in PyTorch
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Previously could crash when checking input sizes. See https://github.com/havakv/pycox/issues/92#issuecomment-908221306
Published by havakv about 3 years ago
Published by havakv almost 5 years ago
Some restructuring to make Model
more general. This means that some earlier code might break.
Main differences are:
model.predict
will use the model.net.predict
method if available. If not, it will use the old model.net.forward
.model.predict_net
will use model.net.forward
.predict
methods now works with dataloader input.predict_dataloader
as predict works with dataloaders.predict
methods take the optional argument func
which can be a torch
function that is applied to the output. E.g., func=torch.sigmoid
can be used for binary classification.target
is now an optional argument in fit
.compute_metrics
take the argument data
instead of input, target
.set_device
can be used to change the device of the model
. E.g., model.set_device('cpu')
will enable the model to work on cpu.DataLoaderSlice
to DataLoaderBatch
.Published by havakv almost 5 years ago
Only cosmetic changes from v0.1.1 to make it look nicer on pypi.
Published by havakv almost 5 years ago
First release to PyPI.