INNER CODE UNIT · Python

w2

drawbridge/keras-mmoe · synthetic_demo.py:49

    w2 = c * (rho * mu1 + np.sqrt(1. - rho ** 2) * mu2)

    # Feature and label generation
    alpha = np.random.normal(size=m)
    beta = np.random.normal(size=m)
    y0 = []
    y1 = []
    X = []

    for i in range(num_row):
        x = np.random.normal(size=num_dimension)
        X.append(x)
        num1 = w1.dot(x)
        num2 = w2.dot(x)
        comp1, comp2 = 0.0, 0.0

        for j in range(m):
            comp1 += np.sin(alpha[j] * num1 + beta[j])

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