cedricconol

def train(self, X, y, learning_rate=0.01, epochs=5):
        
        if len(X.shape)==1:
            X=tf.reshape(X,[X.shape[0],1])
        
        self.m.assign([self.var]*X.shape[-1])
        
        for i in range(epochs):
            print("Epoch: ", i)
            

cedricconol

class SimpleLinearRegression:
    def __init__(self, initializer='random'):
        if initializer=='ones':
            self.var = 1.
        elif initializer=='zeros':
            self.var = 0.
        elif initializer=='random':
            selfx.var = tf.random.uniform(shape=[], minval=0., maxval=1.)
            
        self.m = tf.Variable(1., shape=tf.TensorShape(None))