def test(model, x_test):
return common_test(model, x_test)
'lstm_layers': lstm_layers,
'dropout': dropout,
})
model.apply(init_weights)
trainer = Trainer(
gpus=1,
min_epochs=12,
max_epochs=100,
progress_bar_refresh_rate=0,
)
trainer.fit(model)
xs = model.tds[:][0]
ys = model.tds[:][1]
y_hat = common_test(model, xs.cpu().numpy())
fig, ax = plt.subplots(1, 1)
cm_train = u_metrics.create_confusion_matrix(
classes, y_hat, ys)
u_plot.plot_confusion_matrix(cm_train, title=f'All', ax=ax)
plt.show()
print('Dist: ',
np.histogram(ys.cpu().numpy(), bins=classes)[0])
acc_train, recall_train, f1_train = u_metrics.get_metrics(
y_hat,
ys.cpu().numpy())
print(
f'layers: {lstm_layers:6} hidden: {hidden:6} dout: {dropout:6} LR: {lr:6} Acc: {acc_train:6.3f}, Rec: {recall_train:6.3f}, F1: {f1_train:6.3f}'
)
