Source code for fairseq.modules.scalar_bias

# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.

import torch

[docs]class ScalarBias(torch.autograd.Function): """ Adds a vector of scalars, used in self-attention mechanism to allow the model to optionally attend to this vector instead of the past """
[docs] @staticmethod def forward(ctx, input, dim, bias_init): size = list(input.size()) size[dim] += 1 output =*size).fill_(bias_init) output.narrow(dim, 1, size[dim] - 1).copy_(input) ctx.dim = dim return output
[docs] @staticmethod def backward(ctx, grad): return grad.narrow(ctx.dim, 1, grad.size(ctx.dim) - 1), None, None
def scalar_bias(input, dim, bias_init=0): return ScalarBias.apply(input, dim, bias_init)