def argmax(self, xs, transpose=False):
"""Computes a state that maximizes a joint probability.
Args:
xs (list of Variable): Input vector for each label.
transpose (bool): If ``True``, input/output sequences
will be sorted in descending order of length.
Returns:
tuple: A tuple of :class:`~chainer.Variable` representing each
log-likelihood and a list representing the argmax path.
.. seealso:: See :func:`~chainer.frunctions.crf1d_argmax` for more
detail.
"""
if transpose:
indices = argsort_list_descent(xs)
xs = permutate_list(xs, indices, inv=False)
trans_x = transpose_sequence.transpose_sequence(xs)
score, path = crf1d.argmax_crf1d(self.cost, trans_x)
path = transpose_sequence.transpose_sequence(path)
path = [p.array for p in path]
path = permutate_list(path, indices, inv=True)
else:
score, path = crf1d.argmax_crf1d(self.cost, xs)
return score, path
def argmax(self, xs, transpose=False):
"""Computes a state that maximizes a joint probability.
Args:
xs (list of Variable): Input vector for each label.
transpose (bool): If ``True``, input/output sequences
will be sorted in descending order of length.
Returns:
tuple: A tuple of :class:`~chainer.Variable` representing each
log-likelihood and a list representing the argmax path.
.. seealso:: See :func:`~chainer.frunctions.crf1d_argmax` for more
detail.
"""
if transpose:
indices = argsort_list_descent(xs)
xs = permutate_list(xs, indices, inv=False)
trans_x = transpose_sequence.transpose_sequence(xs)
score, path = crf1d.argmax_crf1d(self.cost, trans_x)
path = transpose_sequence.transpose_sequence(path)
path = [p.array for p in path]
path = permutate_list(path, indices, inv=True)
else:
score, path = crf1d.argmax_crf1d(self.cost, xs)
return score, path
def argmax(self, xs):
"""Computes a state that maximizes a joint probability.
Args:
xs (list of Variable): Input vector for each label.
Returns:
tuple: A tuple of :class:`~chainer.Variable` representing each
log-likelihood and a list representing the argmax path.
.. seealso:: See :func:`~chainer.frunctions.crf1d_argmax` for more
detail.
"""
return crf1d.argmax_crf1d(self.cost, xs)
def argmax(self, xs):
"""Computes a state that maximizes a joint probability.
Args:
xs (list of Variable): Input vector for each label.
Returns:
tuple: A tuple of :class:`~chainer.Variable` representing each
log-likelihood and a list representing the argmax path.
.. seealso:: See :func:`~chainer.frunctions.crf1d_argmax` for more
detail.
"""
return crf1d.argmax_crf1d(self.cost, xs)
def argmax(self, xs):
return crf1d.argmax_crf1d(self.cost, xs)