def __init__(self, candidate_dataset):
super().__init__()
self.query_model = tf.keras.layers.Dense(16)
self.candidate_model = tf.keras.layers.Dense(16)
self.task = tasks.Retrieval(metrics=metrics.FactorizedTopK(
candidates=candidate_dataset.map(self.candidate_model),
ks=[5],
))
def __init__(self, candidate_dataset):
super().__init__()
self.query_model = tf.keras.layers.Dense(16)
self.candidate_model = tf.keras.layers.Dense(16)
self.ctr_model = tf.keras.layers.Dense(1, activation="sigmoid")
self.retrieval_task = tasks.Retrieval(
metrics=metrics.FactorizedTopK(
candidates=candidate_dataset.map(self.candidate_model),
ks=[5]))
self.ctr_task = tasks.Ranking(
metrics=[tf.keras.metrics.AUC(name="ctr_auc")])
def __init__(self, candidate_dataset):
super().__init__()
self.query_model = tf.keras.layers.Dense(16)
self.candidate_model = tf.keras.layers.Dense(16)
self.task = tasks.Retrieval(metrics=metrics.FactorizedTopK(
candidates=candidate_dataset.map(self.candidate_model),
k=5,
metrics=[
tf.keras.metrics.TopKCategoricalAccuracy(
k=5, name="factorized_categorical_accuracy_at_5")
]))