def __init__(self, lower: float = 1. / 8, upper: float = 1. / 3, seed=0):
super().__init__()
seed1, seed2 = _get_graph_seed(seed, 'uniform')
self.uniform = ops.UniformReal(seed1, seed2)
self.lower = Tensor(lower, mstype.float32)
self.upper = Tensor(upper, mstype.float32)
self.relu = ops.ReLU()
def __init__(self, keep_prob=0.5, dtype=mstype.float32):
super(Dropout, self).__init__()
if keep_prob <= 0 or keep_prob > 1:
raise ValueError("dropout probability should be a number in range (0, 1], but got {}".format(keep_prob))
Validator.check_subclass("dtype", dtype, mstype.number_type, self.cls_name)
Validator.check_value_type('keep_prob', keep_prob, [float], self.cls_name)
self.keep_prob = keep_prob
seed0, seed1 = _get_graph_seed(0, "dropout")
self.seed0 = seed0
self.seed1 = seed1
self.dropout = P.Dropout(keep_prob, seed0, seed1)
def __init__(self, keep_prob=0.5, dtype=mstype.float32):
super(Dropout, self).__init__()
if keep_prob <= 0 or keep_prob > 1:
raise ValueError("dropout probability should be a number in range (0, 1], but got {}".format(keep_prob))
Validator.check_subclass("dtype", dtype, mstype.number_type, self.cls_name)
Validator.check_value_type('keep_prob', keep_prob, [float], self.cls_name)
self.keep_prob = keep_prob
seed0, seed1 = _get_graph_seed(0, "dropout")
self.seed0 = seed0
self.seed1 = seed1
self.dtype = dtype
self.get_shape = P.Shape()
self.dropout_gen_mask = P.DropoutGenMask(Seed0=self.seed0, Seed1=self.seed1)
self.dropout_do_mask = P.DropoutDoMask()
self.cast = P.Cast()
self.is_gpu = context.get_context('device_target') in ["GPU"]
self.dropout = P.Dropout(keep_prob)
