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)