Yes, you should be able to just call theano.function(...) before the loops.
On Wednesday, July 12, 2017 at 4:13:33 AM UTC-7, Kelvin Chiu wrote: > > for x in range(x_range): > for y in range(y_range): > t_test_set_x = theano_translation(test_set_x, x, y, borrow=True) > predict_model = theano.function(inputs=[index], > outputs=layer3.errors(y), > givens={layer0.input: > t_test_set_x[index * 500: (index + 1) * 500], > y: test_set_y[index * 500: > (index + 1) * 500]}) > for batch_value in range(0, 20, 1): > temp_predicted_values = predict_model(batch_value) > predicted_values = temp_predicted_values + predicted_values > > > This is part of my source code. Now, the theano function is put inside 2 for > loops. And my test set is updated in every loop. Is there anyway to put the > theano function outside the for loop so that i can speed up the > computational process ? > > -- --- You received this message because you are subscribed to the Google Groups "theano-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to theano-users+unsubscr...@googlegroups.com. For more options, visit https://groups.google.com/d/optout.