Computes a state that maximizes a joint probability of the given CRF.
- cost (Variable) – A \(K \times K\) matrix which holds transition cost between two labels, where \(K\) is the number of labels.
- xs (list of Variable) – Input vector for each label.
len(xs)denotes the length of the sequence, and each
Variableholds a \(B \times K\) matrix, where \(B\) is mini-batch size, \(K\) is the number of labels. Note that \(B\)s in all the variables are not necessary the same, i.e., it accepts the input sequences with different lengths.
A tuple of
ps. The shape of
Bis the mini-batch size. i-th element of
s[i], represents log-likelihood of i-th data.
psis a list of
cupy.ndarray, and denotes the state that maximizes the point probability.
len(ps)is equal to
len(xs), and shape of each
ps[i]is the mini-batch size of the corresponding
xs[i]. That means,
ps[i].shape == xs[i].shape[0:1].