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Computes the clustering loss.

The following structured margins are supported: nmi: normalized mutual information ami: adjusted mutual information ari: adjusted random index vmeasure: v-measure const: indicator checking whether the two clusterings are the same.

labels 2-D Tensor of labels of shape [batch size, 1]
embeddings 2-D Tensor of embeddings of shape [batch size, embedding dimension]. Embeddings should be l2 normalized.
margin_multiplier float32 scalar. multiplier on the structured margin term See section 3.2 of paper for discussion.
enable_pam_finetuning Boolean, Whether to run local pam refinement. See section 3.4 of paper for discussion.
margin_type Type of structured margin to use. See section 3.2 of paper for discussion. Can be 'nmi', 'ami', 'ari', 'vmeasure', 'const'.
print_losses Boolean. Option to print the loss.


clustering_loss A float32 scalar Tensor.

ImportError If sklearn dependency is not installed.