Implement Dropout Layer in Deep Neural Network

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import numpy as np

class Dropout():
    def __init__(self, p):
        self.mask = None
        self.p = p
    
    def __call__(self, X, mode):
        return self.forward(X, mode)
    
    def forward(self, X, mode):
        if mode == 'train':
            self.mask = np.random.binomial(1, self.p, X.shape)
            self.mask = np.true_divide(self.mask, self.p)
            out =  self.mask * X
        else:
            out = X
     
        return out
    
    def backward(self, d_out):
        return d_out * self.mask