# BPR¶

Reference:

Steffen Rendle et al. “BPR: Bayesian Personalized Ranking from Implicit Feedback.” in UAI 2009.

class recbole.model.general_recommender.bpr.BPR(config, dataset)[source]

BPR is a basic matrix factorization model that be trained in the pairwise way.

calculate_loss(interaction)[source]

Calculate the training loss for a batch data.

Parameters

interaction (Interaction) – Interaction class of the batch.

Returns

Training loss, shape: []

Return type

torch.Tensor

forward(user, item)[source]

Defines the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

full_sort_predict(interaction)[source]

full sort prediction function. Given users, calculate the scores between users and all candidate items.

Parameters

interaction (Interaction) – Interaction class of the batch.

Returns

Predicted scores for given users and all candidate items, shape: [n_batch_users * n_candidate_items]

Return type

torch.Tensor

get_item_embedding(item)[source]

Get a batch of item embedding tensor according to input item’s id.

Parameters

item (torch.LongTensor) – The input tensor that contains item’s id, shape: [batch_size, ]

Returns

The embedding tensor of a batch of item, shape: [batch_size, embedding_size]

Return type

torch.FloatTensor

get_user_embedding(user)[source]

Get a batch of user embedding tensor according to input user’s id.

Parameters

user (torch.LongTensor) – The input tensor that contains user’s id, shape: [batch_size, ]

Returns

The embedding tensor of a batch of user, shape: [batch_size, embedding_size]

Return type

torch.FloatTensor

input_type = 2
predict(interaction)[source]

Predict the scores between users and items.

Parameters

interaction (Interaction) – Interaction class of the batch.

Returns

Predicted scores for given users and items, shape: [batch_size]

Return type

torch.Tensor

training: bool