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Dot interaction layer.
tfrs.layers.feature_interaction.DotInteraction( self_interaction: bool = False, skip_gather: bool = False, name: Optional[str] = None, **kwargs ) -> None
See theory in the DLRM paper: https://arxiv.org/pdf/1906.00091.pdf, section 2.1.3. Sparse activations and dense activations are combined. Dot interaction is applied to a batch of input Tensors [e1,...,e_k] of the same dimension and the output is a batch of Tensors with all distinct pairwise dot products of the form dot(e_i, e_j) for i <= j if self self_interaction is True, otherwise dot(e_i, e_j) i < j.
call( inputs: List[tf.Tensor] ) -> tf.Tensor
Performs the interaction operation on the tensors in the list.
The tensors represent as transformed dense features and embedded categorical features. Pre-condition: The tensors should all have the same shape.
||List of features with shapes [batch_size, feature_dim].|
Tensor representing interacted features. It has a dimension