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samuelkim314 avatar samuelkim314 commented on June 18, 2024

Yes, one way is to do it the way you suggested. Note that you'll also have to modify the pretty_print functions accordingly as well.

Another way (which is what we did in our experiments) is to simply have a separate EQL network for each output.

from deepsymreg.

D-Hsueh avatar D-Hsueh commented on June 18, 2024

I guess the expr in pretty_print.py is the last layers functions, so if I want to see all functions, just change

expr = sym_pp(weights[:-1], funcs, var_names, threshold=threshold, n_double=n_double)
expr = last_pp(expr, weights[-1])
expr = expr[0, 0]
return expr

to

expr = sym_pp(weights[:-1], funcs, var_names, threshold=threshold, n_double=n_double)
expr = last_pp(expr, weights[-1])
# expr = expr[0, 0]
return expr

in pretty_print.py's def network ?

from deepsymreg.

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