Python torch.nn.CELU Examples

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Example #1
Source File: base_utils.py    From pt-ranking.github.io with MIT License 4 votes vote down vote up 
def get_AF(af_str):
    """
    Given the string identifier, get PyTorch-supported activation function.

    """
    if af_str == 'R':
        return nn.ReLU()         # ReLU(x)=max(0,x)

    elif af_str == 'LR':
        return nn.LeakyReLU()    # LeakyReLU(x)=max(0,x)+negative_slope∗min(0,x)

    elif af_str == 'RR':
        return nn.RReLU()        # the randomized leaky rectified liner unit function

    elif af_str == 'E':          # ELU(x)=max(0,x)+min(0,α∗(exp(x)−1))
        return nn.ELU()

    elif af_str == 'SE':         # SELU(x)=scale∗(max(0,x)+min(0,α∗(exp(x)−1)))
        return nn.SELU()

    elif af_str == 'CE':         # CELU(x)=max(0,x)+min(0,α∗(exp(x/α)−1))
        return nn.CELU()

    elif af_str == 'S':
        return nn.Sigmoid()

    elif af_str == 'SW':
        #return SWISH()
        raise NotImplementedError

    elif af_str == 'T':
        return nn.Tanh()

    elif af_str == 'ST':         # a kind of normalization
        return F.softmax()      # Applies the Softmax function to an n-dimensional input Tensor rescaling them so that the elements of the n-dimensional output Tensor lie in the range (0,1) and sum to 1

    elif af_str == 'EP':
        #return Exp()
        raise NotImplementedError

    else:
        raise NotImplementedError