def _check_param_value(beta1, beta2, eps, prim_name):
validator.check_value_type("beta1", beta1, [float], prim_name)
validator.check_value_type("beta2", beta2, [float], prim_name)
validator.check_value_type("eps", eps, [float], prim_name)
validator.check_float_range(beta1, 0.0, 1.0, Rel.INC_NEITHER, "beta1", prim_name)
validator.check_float_range(beta2, 0.0, 1.0, Rel.INC_NEITHER, "beta2", prim_name)
validator.check_positive_float(eps, "eps", prim_name)
def __init__(self, central_fraction):
super(CentralCrop, self).__init__()
validator.check_value_type("central_fraction", central_fraction,
[float], self.cls_name)
validator.check_float_range(central_fraction, 0.0, 1.0, Rel.INC_RIGHT,
'central_fraction', self.cls_name)
self.central_fraction = central_fraction
self.slice = P.Slice()
def _check_param_value(beta1, beta2, eps, weight_decay, prim_name):
"""Check the type of inputs."""
validator.check_value_type("beta1", beta1, [float], prim_name)
validator.check_value_type("beta2", beta2, [float], prim_name)
validator.check_value_type("eps", eps, [float], prim_name)
validator.check_value_type("weight_dacay", weight_decay, [float], prim_name)
validator.check_float_range(beta1, 0.0, 1.0, Rel.INC_NEITHER, "beta1", prim_name)
validator.check_float_range(beta2, 0.0, 1.0, Rel.INC_NEITHER, "beta2", prim_name)
validator.check_positive_float(eps, "eps", prim_name)
validator.check_non_negative_float(weight_decay, "weight_decay", prim_name)
def __init__(self, margin=0.0, reduction="mean"):
super(CosineEmbeddingLoss, self).__init__(reduction)
self.reduce_sum = P.ReduceSum()
self.maximum = P.Maximum()
validator.check_value_type("margin", margin, [float], self.cls_name)
self.margin = validator.check_float_range(margin, -1.0, 1.0,
Rel.INC_BOTH, "margin",
self.cls_name)
