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Merge 20debd4 into 6b4f388
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unnonouno committed Mar 19, 2018
2 parents 6b4f388 + 20debd4 commit a8b8a3b
Showing 1 changed file with 18 additions and 9 deletions.
27 changes: 18 additions & 9 deletions chainer/functions/loss/ctc.py
Expand Up @@ -326,23 +326,32 @@ def connectionist_temporal_classification(
Args:
x (list or tuple of :class:`~chainer.Variable`):
RNN output at each time. Each element of ``x``, ``x[i]``
is a :class:`~chainer.Variable` representing output of RNN at time
``i``.
A list of unnormalized probabilities for labels.
Each element of ``x``, ``x[i]`` is a :class:`~chainer.Variable`
object, which has shape ``(B, V)``, where ``B``
is the batch size and ``V`` is the number of labels.
The softmax of ``x[i]`` represents the probabilities of the labels
at time ``i``.
t (:class:`~chainer.Variable` or :class:`numpy.ndarray` or \
:class:`cupy.ndarray`):
Expected label sequence.
Its shape is ``(B, M)``, where ``B`` is the batch size and ``M`` is
the maximum length of the label sequences.
All elements in ``t`` must be less than ``V``, the number of
labels.
blank_symbol (int): Index of blank_symbol.
This value must be non-negative.
input_length (:class:`~chainer.Variable` or :class:`numpy.ndarray` or \
:class:`cupy.ndarray`):
Length of valid sequence for each of mini
batch ``x`` (optional). If input_length is skipped, It regards that
:class:`cupy.ndarray` or ``None``):
Length of sequence for each of mini batch ``x`` (optional).
Its shape must be ``(B,)``.
If the ``input_length`` is omitted or ``None``, it assumes that
all of ``x`` is valid input.
label_length (:class:`~chainer.Variable` or :class:`numpy.ndarray` or \
:class:`cupy.ndarray`):
Length of valid sequence for each of mini
batch ``t`` (optional). If label_length is skipped, It regards that
:class:`cupy.ndarray` or ``None``):
Length of sequence for each of mini batch ``t`` (optional).
Its shape must be ``(B,)``.
If the ``label_length`` is omitted or ``None``, it assumes that
all of ``t`` is valid input.
reduce (str): Reduction option. Its value must be either
``'mean'`` or ``'no'``. Otherwise,
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