I have defined databunch as
data = (TabularList.from_df(train_df, path='./', cont_names=cont_names, procs=procs) .split_by_idx(list(range(500,3000))) .label_from_df(cols=dep_var) .add_test(test, label=0) .databunch())
After training i am
p = learn3.get_preds() len(p)
o/p is 2500 which is correct as
this is 2500 numbers
But now i have other data of around few thousand inputs and if i do
for index in range(len(test_df)): predictions = learn3.predict(test_df.iloc[index]) predictions = predictions.tolist() print(index)
It will take really huge amount of time. I want to pass test_df and get the predictions as was as
p = learn3.get_preds()
How can i do that ?
Do we have way to replace this and pass data from other file ?