write an equivalent lines of code that does the same job as the following code $($ function should remain the same$)$:

import numpy as $np$

def forward$\_$propagation$($x$,$ weights$)$:

# Calculating the weighted sum including bias

weighted$\_$sum $,$ weights$[1$:$])+$ weights$[0]$

print $($weighted$\_$sum$)$

# Applying activation function $($step function$)$

$y=1$ if weighted$\_$sum $0$ else $0$

return y