human
What is a the Python program you requested given the following:
I am working on the file "2.Backpropagation.ipynb".
The first task is:
Thus we need to add the gradient terms to the model and the loss.
Can you write Python program for it?
assistant
#Here is the Python program you requested.

import numpy as np
class model:
    def __init__(self,d):
        self.w = np.zeros((1,d+1))
    def forward(self,x):
        #Takes a data point and evaluates f(x,w)
        return np.dot(self.w[0,:-1],x.T)+self.w[0,-1]
    def gradient(self,x):
        return np.concatenate((x,np.array([1])))
    def gradient_x(self,x):
        return self.w[0,:-1]

class loss:
    def __init__(self):
        self.y = 0
        
    def evaluate(self,model,x,t):
        #Evaluates the loss function L(y,t)
        self.y = model.forward(x)
        return (t-self.y)*(t-self.y)
    
    def gradient(self,model,x,t):
        self.y = model.forward(x)
        return -2.*(t-self.y)