def __init__(self, input_size, hidden_layers, out_size):
    super(MLP_drop, self).__init__()
    self.sizes = (([input_size] + hidden_layers) + [out_size])
    self.linears = [nn.Sequential(nn.Linear(in_dim, out_dim, True), nn.Dropout(0.5)) for (in_dim, out_dim) in zip(self.sizes[:(- 1)], self.sizes[1:])]
    self.linears = nn.ModuleList(self.linears)
    self.weight_init()
def __init__(self, input_size, hidden_layers, out_size):
    super(MLP_drop, self).__init__()
    self.sizes = (([input_size] + hidden_layers) + [out_size])
    self.linears = [nn.Sequential(nn.Linear(in_dim, out_dim, True), nn.Dropout(0.5)) for (in_dim, out_dim) in zip(self.sizes[:(- 1)], self.sizes[1:])]
    self.linears = nn.ModuleList(self.linears)
    self.weight_init()