piiswrong commented on issue #7319: [RoadMap] Legacy issue resolution before
1.0 release
URL:
https://github.com/apache/incubator-mxnet/issues/7319#issuecomment-322110140
@ptrendx @madjam @bhavinthaker The removed tutorials need to be brought back
ASAP!
-
ZhaoxiaZhang commented on issue #7406: inconsistent accuracy: ImageRecordIter
vs ImageIter
URL:
https://github.com/apache/incubator-mxnet/issues/7406#issuecomment-322109650
@melody-rain Thanks for your comments. I will try the imageiter.
BTW, any insights why ImageRecordIter does,'t wor
melody-rain commented on issue #7406: inconsistent accuracy: ImageRecordIter vs
ImageIter
URL:
https://github.com/apache/incubator-mxnet/issues/7406#issuecomment-322105871
@ZhaoxiaZhang Hi, I suggest that you use ImageIter instead of
ImageRecordIter all the time, such that you get good a
CodingCat commented on issue #7411: [scala-package][spark] fix example script
URL: https://github.com/apache/incubator-mxnet/pull/7411#issuecomment-322097900
@javelinjs @terrytangyuan any comments on this?
This is an automat
KeyKy opened a new issue #7448: out of memory when training imagenet with .rec
file.
URL: https://github.com/apache/incubator-mxnet/issues/7448
## Environment info
Operating System: ubuntu 16.04
Compiler: gcc (Ubuntu 5.4.0-6ubuntu1~16.04.4) 5.4.0 20160609
Package used (
ysh329 commented on issue #7424: train_mnist.py failed: TypeError: __init__()
got an unexpected keyword argument 'multi_precision'
URL:
https://github.com/apache/incubator-mxnet/issues/7424#issuecomment-322086687
@ptrendx So stupid I am, I forgot `make` and `pip install -e .`. It's okay
o
ysh329 closed issue #7424: train_mnist.py failed: TypeError: __init__() got an
unexpected keyword argument 'multi_precision'
URL: https://github.com/apache/incubator-mxnet/issues/7424
This is an automated message from the A
ysh329 commented on a change in pull request #7363: Add tensorboard configure
into ./common/fit.py and ./train_mnist.py
URL: https://github.com/apache/incubator-mxnet/pull/7363#discussion_r132864670
##
File path: example/image-classification/common/fit.py
##
@@ -168,10 +16
ysh329 commented on a change in pull request #7363: Add tensorboard configure
into ./common/fit.py and ./train_mnist.py
URL: https://github.com/apache/incubator-mxnet/pull/7363#discussion_r132864621
##
File path: example/image-classification/train_mnist.py
##
@@ -75,5 +75,
DickJC123 opened a new pull request #7447: Tensorcore fullyconnected support2
URL: https://github.com/apache/incubator-mxnet/pull/7447
Consider this an alternative approach to getting TensorCore working with
FullyConnected. It is far simpler than my first PR for this new functionality.
I
piiswrong closed pull request #7304: gluon bce loss
URL: https://github.com/apache/incubator-mxnet/pull/7304
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jxie pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
The following commit(s) were added to refs/heads/master by this push:
new 568b5a2 bce loss (#7304)
568b5a2 is desc
ArturIndio opened a new issue #7446: format input data using mx.rnn
URL: https://github.com/apache/incubator-mxnet/issues/7446
[data_ex_git.zip](https://github.com/apache/incubator-mxnet/files/1220978/data_ex_git.zip)
I've trying to forecast time-series using mx.rnn model but I can't
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qkou pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
The following commit(s) were added to refs/heads/master by this push:
new 0142ea0 [R] vignette update (#7437)
0142
thirdwing closed pull request #7437: [R] vignette update
URL: https://github.com/apache/incubator-mxnet/pull/7437
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szha commented on issue #7445: Using cuDNN for CTC Loss
URL:
https://github.com/apache/incubator-mxnet/issues/7445#issuecomment-322064100
Thanks for raising this, @sbodenstein. I'm working on using the cudnn7
implementation of CTC for GPU.
sbodenstein opened a new issue #7445: Using cuDNN for CTC Loss
URL: https://github.com/apache/incubator-mxnet/issues/7445
@piiswrong, @szha: Now that cuDNN 7 supports CTC loss, perhaps we should
discard the current GPU implementation in contrib.ctc_loss (adapted from the
WarpCTC implementa
ZhaoxiaZhang commented on issue #7398: inconsistent results when infering
URL:
https://github.com/apache/incubator-mxnet/issues/7398#issuecomment-322030662
HI, I have met the similar problems. Have you figured this out?
This
ZhaoxiaZhang commented on issue #7406: inconsistent accuracy: ImageRecordIter
vs ImageIter
URL:
https://github.com/apache/incubator-mxnet/issues/7406#issuecomment-322030133
HI, I met something maybe similar with you. I trained ImageRecordIter and
get a very good accuracy. However when I
xzqjack commented on issue #7426: mx random seed doesn't work for
random_uniform/random_normal on gpu
URL:
https://github.com/apache/incubator-mxnet/issues/7426#issuecomment-322027770
The same error happened in my service (ubuntu16.04, gpu,
mxnet-version:0.10.1)
xzqjack commented on issue #7427: how to set dataiter with multi data?
URL:
https://github.com/apache/incubator-mxnet/issues/7427#issuecomment-322027400
You can look up the definition of class module
(python/mxnet/module/module.py), and init module by
`mod = mx.mod.Module(..., data_name
xzqjack opened a new issue #7444: define a new Parametrized symbol layer and
how to use (bind, init, set learning rate ) it?
URL: https://github.com/apache/incubator-mxnet/issues/7444
I have been learning to define Parametrized layer, of which parameters will
be leared during training tim
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