Python torch.nn.Hardshrink() Examples

The following are 2 code examples of torch.nn.Hardshrink(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module torch.nn , or try the search function .
Example #1
Source File: Base_Network.py    From nn_builder with MIT License 5 votes vote down vote up 
def create_str_to_activations_converter(self):
        """Creates a dictionary which converts strings to activations"""
        str_to_activations_converter = {"elu": nn.ELU(), "hardshrink": nn.Hardshrink(), "hardtanh": nn.Hardtanh(),
                                        "leakyrelu": nn.LeakyReLU(), "logsigmoid": nn.LogSigmoid(), "prelu": nn.PReLU(),
                                        "relu": nn.ReLU(), "relu6": nn.ReLU6(), "rrelu": nn.RReLU(), "selu": nn.SELU(),
                                        "sigmoid": nn.Sigmoid(), "softplus": nn.Softplus(), "logsoftmax": nn.LogSoftmax(),
                                        "softshrink": nn.Softshrink(), "softsign": nn.Softsign(), "tanh": nn.Tanh(),
                                        "tanhshrink": nn.Tanhshrink(), "softmin": nn.Softmin(), "softmax": nn.Softmax(dim=1),
                                         "none": None}
        return str_to_activations_converter
Example #2
Source File: memory_module.py    From memae-anomaly-detection with MIT License 5 votes vote down vote up 
def __init__(self, mem_dim, fea_dim, shrink_thres=0.0025):
        super(MemoryUnit, self).__init__()
        self.mem_dim = mem_dim
        self.fea_dim = fea_dim
        self.weight = Parameter(torch.Tensor(self.mem_dim, self.fea_dim))  # M x C
        self.bias = None
        self.shrink_thres= shrink_thres
        # self.hard_sparse_shrink_opt = nn.Hardshrink(lambd=shrink_thres)

        self.reset_parameters()