Sphinx (2.2.1 or master) produces the following two kinds of warnings in my environment.

duplicate object description

I think cross refs to such object is ambiguous.

autosummary: stub file not found

There are

• chainer.dataset.Converter base class and
• chainer.dataset.converter decorator.

Therefore the filesystem has to allow to store `chainer.dataset.Conver

I can not find the tutorial on the main page. Can someone share how to use it and the performance results? Thanks a lot!

The choice of best action is weighted towards actions with an earlier index (in pi). Instead of taking the argmax(counts) to get the best action, we should pick randomly between all actions which have value of max(counts).
see #165

Since counts is an integer, taking bestA = np.argmax(counts) always weights our action choice towards earlier entries (in the list of actions) when multiple (s,a

Checklist for public release

We plan to separate the docs into 4 parts:

• Manual for data scientists: This manual is for data scientists to learn how to submit job, debug job, manage data, use Marketplace, VSCode / Jupyter extension and CLI support on OpenPAI.
• Manual for cluster administrators: This manual is for cluster administrators to learn the installation and uninstal

The function mask_head_loss_pre takes gt_bboxes as the 4th positional argument, but the docstring does not contain what this argument is.
https://github.com/chainer/chainercv/blob/master/chainercv/links/model/fpn/mask_head.py#L171

2019-09-17 15:58:06.381228 STDOUT 2012] | chainerrl/tests/links_tests/test_stateless_recurrent_sequential.py .F... [100%]
-- | --
2019-09-17 15:58:06.381228 STDOUT 2012] |  
2019-09-17 15:58:06.381229 STDOUT 2012] | =================================== FAILURES ===================================
2019-09-17 15:58:06.381230 STDOUT 2012] | ___________ TestStatelessRecurrentSequential.test_n_

Great work!

I discovered in https://github.com/arogozhnikov/einops/blob/master/einops/einops.py#L199 that you also support ellipsis. Its an important feature so you may want to add it to the documentation.

When I run text_recognition_demo.py with parameters gpu=-1(that is cpu), it can return the results.
But if I set gpu=0, there is something wrong.
The error is
ValueError：numpy and cupy must not be used together type(W):<class 'numpy.ndarray'>, type(x):<class 'cupy.core.core.ndarray'>,type(b):<class 'numpy.ndarray'>
I know nothing about Chainer, what should I do to solve it?

I noticed in example code, some argument are inconsistent in the commented parts, such as lines in examples/molnet/train_molnet.py:
https://github.com/chainer/chainer-chemistry/blob/56e83dedb5de9dc9eb08ebf292be9ba76a4883ba/examples/molnet/train_molnet.py#L267-L274

args.gpu and concat_mols are not consistent with other codes and will throw errors. They should be modified to device and

term1 = 4 * sq_tan_alpha + matmul(f + f_p, transpose(f_p))
is not term1 = 4 * sq_tan_alpha * matmul(f + f_p, transpose(f_p)) ?
The paper's formula：
fa;p;n = 4 tan2 α(xa + xp)T xn − 2(1 + tan2 α)xT a xp