47 lines
1.2 KiB
Python
47 lines
1.2 KiB
Python
import os
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from operator import itemgetter
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import joblib
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import numpy as np
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from keras.models import load_model as load_keras_model
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from sklearn.utils import class_weight
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def exists_or_make_path(p):
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if not os.path.exists(p):
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os.makedirs(p)
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def get_custom_class_weights(client, server):
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return {
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"client": class_weight.compute_class_weight('balanced', np.unique(client), client),
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"server": class_weight.compute_class_weight('balanced', np.unique(server), server)
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}
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def get_custom_sample_weights(client, server):
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return {
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"client": class_weight.compute_sample_weight("balanced", client),
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"server": class_weight.compute_sample_weight("balanced", server)
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}
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def load_ordered_hyperband_results(path):
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results = joblib.load(path)
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return sorted(results, itemgetter("loss"))
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def load_model(path, custom_objects=None):
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clf = load_keras_model(path, custom_objects)
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try:
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embd = clf.get_layer("domain_cnn").layer
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except Exception:
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# in some version i forgot to specify domain_cnn
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# this bug fix is for certain compatibility
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try:
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embd = clf.layers[1].layer
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except Exception:
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embd = clf.get_layer("domain_cnn")
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return embd, clf
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