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Computes the npairs loss between
tfa.losses.npairs_loss( y_true, y_pred )
Npairs loss expects paired data where a pair is composed of samples from
the same labels and each pairs in the minibatch have different labels.
The loss takes each row of the pair-wise similarity matrix,
as logits and the remapped multi-class labels,
y_true, as labels.
The similarity matrix
y_pred between two embedding matrices
[batch_size, hidden_size] can be computed as follows:
# y_pred = a * b^T y_pred = tf.matmul(a, b, transpose_a=False, transpose_b=True)
y_true: 1-D integer
[batch_size]of multi-class labels.
y_pred: 2-D float
[batch_size, batch_size]of similarity matrix between embedding matrices.
npairs_loss: float scalar.