def test_arguments(): """ args passing during initialization. """ n = msd.LogNormal() assert isinstance(n, msd.Distribution) n = msd.LogNormal([3.0], [4.0], dtype=dtype.float32) assert isinstance(n, msd.Distribution)
def __init__(self, shape, seed=0): super(Sampling, self).__init__() self.ln = msd.LogNormal(np.array([0.3]), np.array([[0.2], [0.4]]), seed=seed, dtype=dtype.float32) self.shape = shape
def __init__(self): super(KL, self).__init__() self.ln = msd.LogNormal(np.array([0.3]), np.array([0.4]), dtype=dtype.float32)
def __init__(self): super(LogProb, self).__init__() self.ln = msd.LogNormal(np.array([0.3]), np.array([[0.2], [0.4]]), dtype=dtype.float32)
def __init__(self): super(Net, self).__init__() self.LogNormal = msd.LogNormal(0., 1., dtype=dtype.float32)
def __init__(self): super(LogNormalProb1, self).__init__() self.lognormal = msd.LogNormal()
def __init__(self): super(LogNormalProb, self).__init__() self.lognormal = msd.LogNormal(3.0, 4.0, dtype=dtype.float32)
def test_sd(): with pytest.raises(ValueError): msd.LogNormal(0., 0.) with pytest.raises(ValueError): msd.LogNormal(0., -1.)
def test_name(): with pytest.raises(TypeError): msd.LogNormal(0., 1., name=1.0)
def test_seed(): with pytest.raises(TypeError): msd.LogNormal(0., 1., seed='seed')
def test_type(): with pytest.raises(TypeError): msd.LogNormal(0., 1., dtype=dtype.int32)
def test_lognormal_shape_errpr(): """ Invalid shapes. """ with pytest.raises(ValueError): msd.LogNormal([[2.], [1.]], [[2.], [3.], [4.]], dtype=dtype.float32)
def __init__(self): super(LogNormalConstruct, self).__init__() self.lognormal = msd.LogNormal(3.0, 4.0) self.lognormal1 = msd.LogNormal()
def __init__(self): super(LogNormalBasics, self).__init__() self.n = msd.LogNormal(3.0, 4.0, dtype=dtype.float32)
def __init__(self): super(LogNormalCrossEntropy, self).__init__() self.n1 = msd.LogNormal(np.array([3.0]), np.array([4.0]), dtype=dtype.float32) self.n2 = msd.LogNormal(dtype=dtype.float32)