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Fix for issue #6521 and issue #6810 #6808

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merged 5 commits into from
Nov 11, 2019
Merged

Fix for issue #6521 and issue #6810 #6808

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3753a36
fix L_t to L_i
euler16 Apr 9, 2019
0632fe0
another instance of L_i fixed
euler16 Apr 9, 2019
d66f509
adding example to NStepLSTM
euler16 Apr 9, 2019
5ae5084
added example to NStepLSTM
euler16 Apr 9, 2019
75846ea
Merge branch 'master' into master
Crissman Apr 18, 2019
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4 changes: 2 additions & 2 deletions chainer/links/connection/n_step_rnn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -143,7 +143,7 @@ def forward(self, hx, xs, **kwargs):
the hidden units.
xs (list of :class:`~chainer.Variable`): List of input sequences.
Each element ``xs[i]`` is a :class:`chainer.Variable` holding
a sequence. Its shape is ``(L_i, I)``, where ``L_t`` is the
a sequence. Its shape is ``(L_i, I)``, where ``L_i`` is the
length of a sequence for batch ``i``, and ``I`` is the size of
the input and is equal to ``in_size``.

Expand All @@ -156,7 +156,7 @@ def forward(self, hx, xs, **kwargs):
``ys[i]`` holds hidden states of the last layer corresponding
to an input ``xs[i]``. Its shape is ``(L_i, N)`` for
uni-directional RNN and ``(L_i, 2N)`` for bi-directional RNN
where ``L_t`` is the length of a sequence for batch ``i``,
where ``L_i`` is the length of a sequence for batch ``i``,
and ``N`` is size of hidden units.
"""
(hy,), ys = self._call([hx], xs, **kwargs)
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