ContrastiveLocalLoss

class lightning_ir.loss.embedding.ContrastiveLocalLoss(temperature: float = 1.0)

Bases: EmbeddingLossFunction

Loss function that computes a contrastive loss between a query and multiple document embeddings, such that only one document embedding has a a high similarity to the query embedding, while all other document embeddings have a low similarity. Originally proposed in: Multi-View Document Representation Learning for Open-Domain Dense Retrieval

__init__(temperature: float = 1.0) → None

Methods

__init__([temperature])
compute_loss(output)	Compute the loss based on the embeddings in the output.

compute_loss(output: BiEncoderOutput) → torch.Tensor

Compute the loss based on the embeddings in the output.

Parameters:

output (BiEncoderOutput) – The output from the model containing query and document embeddings.

Returns:

The computed loss.

Return type:

torch.Tensor