Tripletloss, TripletCNN and further Tensorflow 2 support #2
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added 20 commits
June 30, 2020 12:57
del_mse_nodes() fails with TF2. This functionality should achieve the same end.
This is no guarantee that everything will work with TF2
triplet loss can be switched on or off with command line arguments
add shell script collecting invariance scores of different models for certain epochs
add shell script to collect test scores for specified models and epochs
add shell script to train the tripletcnn architecture as classifier without triplet loss on Cifar10
alexhernandezgarcia
previously approved these changes
Nov 4, 2020
edit paths for more generality
Comment on lines
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| # Ensure the model has no MSE nodes and outputs | ||
| model = del_mse_nodes(model) | ||
| # Ensure the model has no MSE nodes and outputs by building a new model | ||
| # with the old models weights and only the softmax output | ||
| softmax_layers = [layer for layer in model.layers if layer.name=='softmax'] | ||
| assert len(softmax_layers) == 1, 'Model has multiple softmax layers' | ||
| softmax_layer = softmax_layers[0] | ||
| model = Model(model.input, softmax_layer.output) |
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This is a partial fix, since it may not work with models with more complex connectivity.
In any case these lines should go on surgery.py
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Amongst others, this pull request adds