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)
