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olasaadi 2022-05-30 12:52:32 +03:00
parent 8de77f9afd
commit a3fb68fb56
2 changed files with 141 additions and 26 deletions
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16
tests/test_pytorch.py
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@ -48,16 +48,20 @@ def test_nursery_pytorch():
out = self.fc4(out)
return self.classifier(out)
mlp_model = pytorch_model(4, 24)
mlp_model = torch.nn.DataParallel(mlp_model)
model = pytorch_model(4, 24)
model = torch.nn.DataParallel(model)
criterion = nn.CrossEntropyLoss()
optimizer = optim.Adam(mlp_model.parameters(), lr=0.01)
optimizer = optim.Adam(model.parameters(), lr=0.01)
mlp_art_model = PyTorchClassifier(model=mlp_model, output_type=ModelOutputType.CLASSIFIER_VECTOR, loss=criterion,
art_model = PyTorchClassifier(model=model, output_type=ModelOutputType.CLASSIFIER_VECTOR, loss=criterion,
optimizer=optimizer, input_shape=(24,),
nb_classes=4)
mlp_art_model.fit(ArrayDataset(x_train.astype(np.float32), y_train))
art_model.fit(ArrayDataset(x_train.astype(np.float32), y_train))
pred = np.array([np.argmax(arr) for arr in mlp_art_model.predict(ArrayDataset(x_test.astype(np.float32)))])
pred = np.array([np.argmax(arr) for arr in art_model.predict(ArrayDataset(x_test.astype(np.float32)))])
print('Base model accuracy: ', np.sum(pred == y_test) / len(y_test))
art_model.load_best_state_dict_checkpoint()