def test_type():
with pytest.raises(TypeError):
msb.GumbelCDF(scale='scale')
with pytest.raises(TypeError):
msb.GumbelCDF(loc='loc')
with pytest.raises(TypeError):
msb.GumbelCDF(name=0.1)
def test_invalid_scale():
"""
Test invalid scale.
"""
with pytest.raises(ValueError):
msb.GumbelCDF(scale=0.0)
with pytest.raises(ValueError):
msb.GumbelCDF(scale=-1.0)
def test_init():
"""
Test initializations.
"""
b = msb.GumbelCDF()
assert isinstance(b, msb.Bijector)
b = msb.GumbelCDF(scale=1.0)
assert isinstance(b, msb.Bijector)
b = msb.GumbelCDF(loc=0.0)
assert isinstance(b, msb.Bijector)
b = msb.GumbelCDF(3.0, 4.0)
assert isinstance(b, msb.Bijector)
def __init__(self,
loc,
scale,
seed=0,
dtype=mstype.float32,
name="Gumbel"):
"""
Constructor of Gumbel distribution.
"""
valid_dtype = mstype.float_type
Validator.check_type_name("dtype", dtype, valid_dtype, type(self).__name__)
gumbel_cdf = msb.GumbelCDF(loc, scale)
super(Gumbel, self).__init__(
distribution=msd.Uniform(0.0, 1.0, dtype=dtype),
bijector=msb.Invert(gumbel_cdf),
seed=seed, name=name)
# overwrite default_parameters and parameter_names
self._reset_parameters()
self._loc = self._add_parameter(loc, 'loc')
self._scale = self._add_parameter(scale, 'scale')
self._gumbel_bijector = gumbel_cdf
# ops needed for the class
self.cast = P.Cast()
self.const = P.ScalarToArray()
self.exp = exp_generic
self.expm1 = expm1_generic
self.fill = P.Fill()
self.lgamma = nn.LGamma()
self.log = log_generic
self.shape = P.Shape()
self.sqrt = P.Sqrt()
def __init__(self):
super(ForwardJacobian, self).__init__()
self.b1 = msb.GumbelCDF(1.0, 2.0)
self.b2 = msb.GumbelCDF()
def __init__(self):
super(ForwardBackward, self).__init__()
self.b1 = msb.GumbelCDF(1.0, 2.0)
self.b2 = msb.GumbelCDF()
def __init__(self):
super(Net, self).__init__()
self.b1 = msb.GumbelCDF(1.0, 2.0)
self.b2 = msb.GumbelCDF()
def __init__(self, loc, scale):
super(Net3, self).__init__()
self.bijector = msb.GumbelCDF(loc, scale)