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Dot interaction layer.

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.

self_interaction Boolean indicating if features should self-interact. If it is True, then the diagonal enteries of the interaction matric are also taken.
name String name of the layer.



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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.

inputs List of features with shape [batch_size, feature_dim].

activations Tensor representing interacted features.