Creates a Functional Keras ranking model.
tfr.keras.model.create_keras_model(
network, loss, metrics, optimizer, size_feature_name, list_size=None
)
A mask is inferred from size_feature_name and passed to the network, along
with feature dictionary as inputs.
Args |
|---|
network
|
(tfr.keras.network.RankingNetwork) A ranking network which
generates a list of scores.
|
loss
|
(tfr.keras.losses._RankingLoss) A ranking loss.
|
metrics
|
(list) List of ranking metrics, tfr.keras.metrics._RankingMetric
instances.
|
optimizer
|
(tf.keras.optimizer.Optimizer) Optimizer to minimize ranking
loss.
|
size_feature_name
|
(str) Name of feature for example list sizes. If not
None, this feature name corresponds to a tf.int32 Tensor of size
[batch_size] corresponding to sizes of example lists. If None, all
examples are treated as valid.
|
list_size
|
(int) The list size for example features. If None, use dynamic
list size. A fixed list size is required for TPU training.
|
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