Brute force retrieval.
Inherits From: TopK
tfrs.layers.factorized_top_k.BruteForce(
query_model: Optional[tf.keras.Model] = None,
k: int = 10,
name: Optional[Text] = None
)
Used in the notebooks
Args |
query_model
|
Optional Keras model for representing queries. If provided,
will be used to transform raw features into query embeddings when
querying the layer. If not provided, the layer will expect to be given
query embeddings as inputs.
|
k
|
Default k.
|
name
|
Name of the layer.
|
Methods
call
View source
call(
queries: Union[tf.Tensor, Dict[Text, tf.Tensor]],
k: Optional[int] = None
) -> Tuple[tf.Tensor, tf.Tensor]
Query the index.
Args |
queries
|
Query features. If query_model was provided in the constructor,
these can be raw query features that will be processed by the query
model before performing retrieval. If query_model was not provided,
these should be pre-computed query embeddings.
|
k
|
The number of candidates to retrieve. If not supplied, defaults to the
k value supplied in the constructor.
|
Returns |
Tuple of (top candidate scores, top candidate identifiers).
|
Raises |
ValueError if index has not been called.
|
index
View source
index(
candidates: Union[tf.Tensor, tf.data.Dataset],
identifiers: Optional[Union[tf.Tensor, tf.data.Dataset]] = None
) -> "BruteForce"
Builds the retrieval index.
When called multiple times the existing index will be dropped and a new one
created.
Args |
candidates
|
Matrix (or dataset) of candidate embeddings.
|
identifiers
|
Optional tensor (or dataset) of candidate identifiers. If
given, these will be used to as identifiers of top candidates returned
when performing searches. If not given, indices into the candidates
tensor will be given instead.
|
query_with_exclusions
View source
@tf.function
query_with_exclusions(
queries: Union[tf.Tensor, Dict[Text, tf.Tensor]],
exclusions: tf.Tensor,
k: Optional[int] = None
) -> Tuple[tf.Tensor, tf.Tensor]
Query the index.
Args |
queries
|
Query features. If query_model was provided in the constructor,
these can be raw query features that will be processed by the query
model before performing retrieval. If query_model was not provided,
these should be pre-computed query embeddings.
|
exclusions
|
[query_batch_size, num_to_exclude] tensor of identifiers to
be excluded from the top-k calculation. This is most commonly used to
exclude previously seen candidates from retrieval. For example, if a
user has already seen items with ids "42" and "43", you could set
exclude to [["42", "43"]] .
|
k
|
The number of candidates to retrieve. Defaults to constructor k
parameter if not supplied.
|
Returns |
Tuple of (top candidate scores, top candidate identifiers).
|
Raises |
ValueError if index has not been called.
ValueError if queries is not a tensor (after being passed through
the query model).
|