def test_init():
"""
Test initializations.
"""
b = msb.Invert(msb.ScalarAffine(scale=1.0))
assert isinstance(b, msb.Bijector)
b = msb.Invert(msb.Exp())
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(Net3, self).__init__()
self.origin = msb.ScalarAffine(scale=2.0, shift=1.0)
self.invert = msb.Invert(self.origin)
def __init__(self):
super(BackwardJacobian, self).__init__()
self.inv1 = msb.Invert(msb.Exp())
self.inv2 = msb.Invert(msb.ScalarAffine())
def __init__(self):
super(ForwardBackward, self).__init__()
self.inv1 = msb.Invert(msb.Exp())
self.inv2 = msb.Invert(msb.ScalarAffine())
def test_name():
b = msb.Invert(msb.ScalarAffine(scale=1.0))
assert b.name == 'InvertScalarAffine'
def test_type():
with pytest.raises(TypeError):
msb.Invert(msb.Exp(), name=0.1)
with pytest.raises(TypeError):
msb.Invert(0.1)
def __init__(self):
super(Net, self).__init__()
self.b1 = msb.ScalarAffine(2.0, 1.0)
self.inv = msb.Invert(self.b1)
