I have two classes and trying to build Tensorflow ranking model
when i run model.fit(cached_train, epochs=3), i get error
ValueError: The first argument to `Layer.call` must always be passed
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class ProdRankingModel(tf.keras.Model):
def __init__(self):
super().__init__()
embedding_dimension = 32
self.user_embeddings = tf.keras.Sequential([
tf.keras.layers.StringLookup(
vocabulary=unique_user_ids, mask_token=None),
tf.keras.layers.Embedding(len(unique_user_ids) + 1, embedding_dimension)])
self.prod_embeddings = tf.keras.Sequential([
tf.keras.layers.StringLookup(
vocabulary=unique_items, mask_token=None),
tf.keras.layers.Embedding(len(unique_items) + 1, embedding_dimension)
])
# Compute predictions.
self.ratings = tf.keras.Sequential([
tf.keras.layers.Dense(256, activation=”relu”),
tf.keras.layers.Dense(64, activation=”relu”),
tf.keras.layers.Dense(1)
])
def call(self, inputs):
user_id, products = inputs
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user_embedding = self.user_embeddings(user_id)
product_embedding = self.prod_embeddings(products)
return self.ratings(tf.concat([user_embedding, product_embedding], axis=1))
​
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class ProductModel(tfrs.models.Model):
def __init__(self):
super().__init__()
self.prodranking_model: tf.keras.Model = ProdRankingModel()
self.task: tf.keras.layers.Layer = tfrs.tasks.Ranking(
loss = tf.keras.losses.MeanSquaredError(),
metrics=[tf.keras.metrics.RootMeanSquaredError()]
)
​
def call(self, features: Dict[str, tf.Tensor]) -> tf.Tensor:
return self.prodranking_model(
(features[“user_id”], features[“prod_name”]))
​
def compute_loss(self, features: Dict[Text, tf.Tensor], training=False) -> tf.Tensor:
labels = features.pop(“prod_count”)
rating_predictions = self(features)
# The task computes the loss and the metrics.
return self.task(labels=labels, predictions=rating_predictions)
