Python

I’m trying to set up a Functions class that will handle functions for my NN projects. I’ve figured out I’d like the list of functions to be somewhat flexible (easily add, or remove functions used).

I’ve created a list of functions, defined a bunch of lambda functions, added a method that adds all the functions in the body to the list. When I try to check the length of the list it shows the correct number, but when I try to retrieve a function into a variable and pass it an argument I get an information that lambda takes 1 argument and I gave it 2. I don’t understand what is the second argument.

import numpy as np

class Functions():
    f0 = identity = lambda x: x
    f1 = linear_step = lambda x: 1 if x > 0 else 0
    f2 = sigmoid = lambda x: 1/(1+np.exp(-x))
    f3 = tanh = lambda x: np.tanh(x)
    f4 = swish = lambda x: x/(1+np.exp(-x))
    f5 = absolute = lambda x: abs(x)
    f6 = cubic = lambda x: x**3
    f7 = square = lambda x: x**2
    f8 = sinusoid = lambda x: np.sin(x)
    f9 = square_root = lambda x: np.sqrt(x)
    f10 = cubic_root = lambda x: np.cbrt(x)
    f11 = opposite = lambda x: -x
    f12 = inverse = lambda x: 1/x
    f13 = exponential = lambda x: np.exp(x)
    
    def __init__(self): #constructor
        self._functions = []
        self.add_functions(self.f0, self.f1, self.f2, self.f3, self.f4, self.f5, self.f6, self.f7, self.f8, self.f9, self.f10, self.f11, self.f12, self.f13)

    #add a fyunction to the list, if it is not already there
    def _add_function(self, function):
        if function not in self._functions:
            self._functions.append(function)
            #print(f"Added function: {function.__name__}")
            return True
        else:
            #print(f"Function: {function.__name__} already exists at index: {functions.index(function)}")
            return False
        
    #add multiple functions to the list
    def add_functions(self, *args):
        for function in args:
            self._add_function(function)
            
    #get the number of functions in the list
    def number_of_functions(self):
        return len(self._functions)


    #return the function at the given index
    def get_function(self, index):
        try:
            return self._functions[index]
        except IndexError:
            print("Index out of range");
            return None
    
    def get_all_functions(self):
        return self._functions
        
        

functs = Functions()

print(f"number of functions {functs.number_of_functions()}")

iden = functs.get_function(0)
print(f"identity of one is {iden(1)}")

What’s causing the issue? Alternatively what would be a better way to have an enumerable data structure to store and load the activation functions?

Answer

All these functions behave the same as add_function, __init__, and number_of_functions. They are secretly being passed self. I have shown two fixes below:

class Functions:
    f0 = identity = lambda self, x: x
    f1 = linear_step = lambda self, x: 1 if x > 0 else 0
    f2 = sigmoid = lambda self, x: 1 / (1 + np.exp(-x))
    f3 = tanh = lambda self, x: np.tanh(x)
    # ...

class Functions:
    f0 = identity = staticmethod(lambda x: x)
    f1 = linear_step = staticmethod(lambda x: 1 if x > 0 else 0)
    f2 = sigmoid = staticmethod(lambda x: 1 / (1 + np.exp(-x)))
    f3 = tanh = staticmethod(lambda x: np.tanh(x))
    # ...

Python – Using a lambda function stored in a list of functions inside a class

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Answer