allennlp.modules.similarity_functions.dot_product#

DotProductSimilarity#

DotProductSimilarity(self, scale_output:bool=False) -> None

This similarity function simply computes the dot product between each pair of vectors, with an optional scaling to reduce the variance of the output elements.

Parameters

  • scale_output : bool, optional If True, we will scale the output by math.sqrt(tensor.size(-1)), to reduce the variance in the result.

forward#

DotProductSimilarity.forward(self, tensor_1:torch.Tensor, tensor_2:torch.Tensor) -> torch.Tensor

Takes two tensors of the same shape, such as (batch_size, length_1, length_2, embedding_dim). Computes a (possibly parameterized) similarity on the final dimension and returns a tensor with one less dimension, such as (batch_size, length_1, length_2).