tfrs.metrics.FactorizedTopK

Computes metrics for across top K candidates surfaced by a retrieval model.

Used in the notebooks

Used in the tutorials

The default metric is top K categorical accuracy: how often the true candidate is in the top K candidates for a given query.

candidates A layer for retrieving top candidates in response to a query, or a dataset of candidate embeddings from which candidates should be retrieved.
metrics The metrics to compute. If not supplied, will compute top-K categorical accuracy metrics.
k The number of top scoring candidates to retrieve for metric evaluation.
name Optional name.

Methods

call

This is where the layer's logic lives.

Note here that call() method in tf.keras is little bit different from keras API. In keras API, you can pass support masking for layers as additional arguments. Whereas tf.keras has compute_mask() method to support masking.

Args
inputs Input tensor, or dict/list/tuple of input tensors. The first positional inputs argument is subject to special rules:

  • inputs must be explicitly passed. A layer cannot have zero arguments, and inputs cannot be provided via the default value of a keyword argument.
  • NumPy array or Python scalar values in inputs get cast as tensors.
  • Keras mask metadata is only collected from inputs.
  • Layers are built (build(input_shape) method) using shape info from inputs only.
  • input_spec compatibility is only checked against inputs.
  • Mixed precision input casting is only applied to inputs. If a layer has tensor arguments in *args or **kwargs, their casting behavior in mixed precision should be handled manually.
  • The SavedModel input specification is generated using inputs only.
  • Integration with various ecosystem packages like TFMOT, TFLite, TF.js, etc is only supported for inputs and not for tensors in positional and keyword arguments.
*args Additional positional arguments. May contain tensors, although this is not recommended, for the reasons above.
**kwargs Additional keyword arguments. May contain tensors, although this is not recommended, for the reasons above. The following optional keyword arguments are reserved:
  • training: Boolean scalar tensor of Python boolean indicating whether the call is meant for training or inference.
  • mask: Boolean input mask. If the layer's call() method takes a mask argument, its default value will be set to the mask generated for inputs by the previous layer (if input did come from a layer that generated a corresponding mask, i.e. if it came from a Keras layer with masking support).
  • Returns
    A tensor or list/tuple of tensors.

    reset_states

    View source

    Resets the metrics.

    result

    View source

    Returns a list of metric results.

    update_state

    View source

    Updates the metrics.

    Args
    query_embeddings [num_queries, embedding_dim] tensor of query embeddings.
    true_candidate_embeddings [num_queries, embedding_dim] tensor of embeddings for candidates that were selected for the query.

    Returns
    Update op. Only used in graph mode.