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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:

def GaussianLogDensity(x, mu, log_var, name='GaussianLogDensity', EPSILON = 1e-6):
    '''GaussianLogDensity loss calculation for layer wise loss
    '''
    c = mx.sym.ones_like(log_var)*2.0 * 3.1416
    c = mx.symbol.log(c)
    var = mx.sym.exp(log_var)
    x_mu2 = mx.symbol.square(x - mu)   # [Issue] not sure the dim works or not?
    x_mu2_over_var = mx.symbol.broadcast_div(x_mu2, var + EPSILON)
    log_prob = -0.5 * (c + log_var + x_mu2_over_var)
    log_prob = mx.symbol.sum(log_prob, axis=1, name=name)   # keep_dims=True,
    return log_prob