def __init__(self,
loc=None,
scale=None,
seed=None,
dtype=mstype.float32,
name="Cauchy"):
"""
Constructor of Cauchy.
"""
param = dict(locals())
param['param_dict'] = {'loc': loc, 'scale': scale}
valid_dtype = mstype.float_type
Validator.check_type_name("dtype", dtype, valid_dtype,
type(self).__name__)
super(Cauchy, self).__init__(seed, dtype, name, param)
self._loc = self._add_parameter(loc, 'loc')
self._scale = self._add_parameter(scale, 'scale')
if self._scale is not None:
check_greater_zero(self._scale, "scale")
# ops needed for the class
self.atan = P.Atan()
self.cast = P.Cast()
self.const = P.ScalarToArray()
self.dtypeop = P.DType()
self.exp = exp_generic
self.fill = P.Fill()
self.less = P.Less()
self.log = log_generic
self.log1p = log1p_generic
self.squeeze = P.Squeeze(0)
self.shape = P.Shape()
self.sq = P.Square()
self.sqrt = P.Sqrt()
self.tan = P.Tan()
self.uniform = C.uniform
self.entropy_const = np.log(4 * np.pi)
def __init__(self, strategy1, strategy2):
super().__init__()
self.matmul = P.MatMul().set_strategy(strategy1)
self.atan = P.Atan().set_strategy(strategy2)
self.matmul2 = P.MatMul().set_strategy(strategy1)
def __init__(self):
super(NetAtan, self).__init__()
self.atan = P.Atan()