How to modify the positional encoding in torch.nn.Transformer?

#1

I am doing some experiments on positional encoding, and would like to use torch.nn.Transformer for my experiments.

But it seems there is no argument for me to change the positional encoding. I also cannot seem to find in the source code where the torch.nn.Transformer is handling tthe positional encoding.

How to change the default sin cos encoding to some of my custom-made encoding?

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#2

Hi, i’m not expert about pytorch or transformers but i think nn.Transformer doesn’t have positional encoding, you have to code yourself then to add token embeddings.

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#3

if you are looking for a positional encoder see this:

class PositionalEncoding(nn.Module):

    def __init__(self, d_model, dropout=0.1, max_len=5000):
        super(PositionalEncoding, self).__init__()
        self.dropout = nn.Dropout(p=dropout)

        pe = torch.zeros(max_len, d_model)
        position = torch.arange(0, max_len, dtype=torch.float).unsqueeze(1)
        div_term = torch.exp(torch.arange(0, d_model, 2).float() * (-math.log(10000.0) / d_model))
        pe[:, 0::2] = torch.sin(position * div_term)
        pe[:, 1::2] = torch.cos(position * div_term)
        pe = pe.unsqueeze(0).transpose(0, 1)
        self.register_buffer('pe', pe)

    def forward(self, x):
        x = x + self.pe[:x.size(0), :]
        return self.dropout(x)

https://pytorch.org/tutorials/beginner/transformer_tutorial.html