Weights-only saving & loading
save_weights method
Model.save_weights(filepath, overwrite=True)
Saves all layer weights to a .weights.h5 file.
Arguments
- filepath:
strorpathlib.Pathobject. Path where to save the model. Must end in.weights.h5. - overwrite: Whether we should overwrite any existing model at the target location, or instead ask the user via an interactive prompt.
load_weights method
Model.load_weights(filepath, skip_mismatch=False, **kwargs)
Load weights from a file saved via save_weights().
Weights are loaded based on the network's topology. This means the architecture should be the same as when the weights were saved. Note that layers that don't have weights are not taken into account in the topological ordering, so adding or removing layers is fine as long as they don't have weights.
Partial weight loading
If you have modified your model, for instance by adding a new layer
(with weights) or by changing the shape of the weights of a layer,
you can choose to ignore errors and continue loading
by setting skip_mismatch=True. In this case any layer with
mismatching weights will be skipped. A warning will be displayed
for each skipped layer.
Arguments
- filepath: String, path to the weights file to load.
It can either be a
.weights.h5file or a legacy.h5weights file. - skip_mismatch: Boolean, whether to skip loading of layers where there is a mismatch in the number of weights, or a mismatch in the shape of the weights.