qingzhouzhen commented on a change in pull request #7568: modify parameters
counting of FC and CONV
URL: https://github.com/apache/incubator-mxnet/pull/7568#discussion_r134659231
##
File path: python/mxnet/visualization.py
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@@ -134,12 +134,20 @@ def
voidrank commented on issue #5756: why mxnet ndarray not support
multi-dimension indexing ?
URL:
https://github.com/apache/incubator-mxnet/issues/5756#issuecomment-324220783
@horserma @itijyou
Assigning operation is prohibited in functional programming. You can create
a new node
fasahath commented on issue #6852: Segmentation fault during ab load test
URL:
https://github.com/apache/incubator-mxnet/issues/6852#issuecomment-311926200
Stumbled upon this #3946 issue and understood the problem much better.
Got to know that the engine is not thread-safe!
fasahath closed issue #6852: Segmentation fault during ab load test
URL: https://github.com/apache/incubator-mxnet/issues/6852
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CodingCat opened a new pull request #7571: [scala-package][spark] Resources
running PS (role = server) should be explicit to Spark
URL: https://github.com/apache/incubator-mxnet/pull/7571
another PR to facilitate the further work on integrating with Spark
The current implementation
piiswrong commented on issue #7570: Gluon InstanceNorm and ReflectancePadding
URL: https://github.com/apache/incubator-mxnet/pull/7570#issuecomment-324211809
Please add doc. see
http://pytorch.org/docs/master/nn.html#torch.nn.InstanceNorm1d
eric-haibin-lin commented on issue #7569: should add row_sparse_push for kvstore
URL:
https://github.com/apache/incubator-mxnet/issues/7569#issuecomment-324210209
The push method accepts row_sparse values already, but for pull it requires
row id that's why row_sparse_pull was added.
zhanghang1989 opened a new pull request #7570: Gluon InstanceNorm and
ReflectancePadding
URL: https://github.com/apache/incubator-mxnet/pull/7570
InstanceNorm and ReflectancePadding are important for generative models and
style transfer.
piiswrong commented on a change in pull request #7568: modify parameters
counting of FC and CONV
URL: https://github.com/apache/incubator-mxnet/pull/7568#discussion_r134647714
##
File path: python/mxnet/visualization.py
##
@@ -134,12 +134,20 @@ def
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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 491f81e add resnet50_v2 pretrained
starimpact opened a new issue #7569: should add row_sparse_push for kvstore
URL: https://github.com/apache/incubator-mxnet/issues/7569
hi, all,
I noticed that you have add a function for kvstore , named
'row_sparse_pull', why not to add a 'row_sparse_push'. it is very like my
'partial
qinhui99 closed issue #7529: As keras use mxnet as backend, I can not use the
GPU to train .
URL: https://github.com/apache/incubator-mxnet/issues/7529
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everwind commented on issue #3946: When predicting, does mxnet provide
thread-safe interface?
URL:
https://github.com/apache/incubator-mxnet/issues/3946#issuecomment-324198209
I think we should separate "data" and the model weights . when predicting,
each thread can share the model
everwind commented on issue #3946: When predicting, does mxnet provide
thread-safe interface?
URL:
https://github.com/apache/incubator-mxnet/issues/3946#issuecomment-324198209
I think we should separate "data" and the model weights . when predicting,
each thread can share the model
everwind commented on issue #3946: When predicting, does mxnet provide
thread-safe interface?
URL:
https://github.com/apache/incubator-mxnet/issues/3946#issuecomment-324198209
I think we should separate "data" and the model weights . when predicting,
each thread can share the model
qingzhouzhen opened a new pull request #7568: modify parameters counting of FC
and CONV
URL: https://github.com/apache/incubator-mxnet/pull/7568
I am using computer of my company which restrict to push large mount of code
to internet, so I open a new pull request and I will close the
everwind commented on issue #3946: When predicting, does mxnet provide
thread-safe interface?
URL:
https://github.com/apache/incubator-mxnet/issues/3946#issuecomment-324193029
I have the same question. Any progress here?
rnunziata opened a new issue #7567: run time error after compile on ubuntu16,
cuda8 , cudnn6
URL: https://github.com/apache/incubator-mxnet/issues/7567
Trying to run on ubunut 16 cuda 8 cudnn 6. compiled ok...but when I run I
get the following . seems to be looking for cudnn 5?
nswamy closed pull request #7566: update NEWS/README
URL: https://github.com/apache/incubator-mxnet/pull/7566
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nswamy pushed a commit to branch v0.11.0
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
The following commit(s) were added to refs/heads/v0.11.0 by this push:
new 7f12fcf update NEWS/README (#7566)
nswamy opened a new pull request #7566: update NEWS/README
URL: https://github.com/apache/incubator-mxnet/pull/7566
@mbaijal
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szha commented on issue #7564: add resnet50_v2 pretrained
URL: https://github.com/apache/incubator-mxnet/pull/7564#issuecomment-324188618
Yeah, these two transformation should result in the same data range. (e.g.
0.485*255 = 123.675.)
szha commented on issue #7564: add resnet50_v2 pretrained
URL: https://github.com/apache/incubator-mxnet/pull/7564#issuecomment-324187927
Input to the network should be after applying the following transformation,
which is consistent with other models in the gluon model zoo:
```
szha commented on issue #7564: add resnet50_v2 pretrained
URL: https://github.com/apache/incubator-mxnet/pull/7564#issuecomment-324187927
Input to the network should be after applying the following transformation,
which is consistent with other models in the gluon model zoo:
```
szha commented on issue #7564: add resnet50_v2 pretrained
URL: https://github.com/apache/incubator-mxnet/pull/7564#issuecomment-324187927
Input to the network should be after applying the following transformation,
which is consistent with other models in the gluon model zoo:
```
nswamy commented on issue #7565: Update License and Notice Files.
URL: https://github.com/apache/incubator-mxnet/pull/7565#issuecomment-324186272
Not relocating the licenses as in Spark but linking them in the top level
license as specified by.
1. Apache License
nswamy closed pull request #7565: Update License and Notice Files.
URL: https://github.com/apache/incubator-mxnet/pull/7565
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nswamy opened a new pull request #7565: Update License and Notice Files.
URL: https://github.com/apache/incubator-mxnet/pull/7565
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zhreshold commented on issue #7564: add resnet50_v2 pretrained
URL: https://github.com/apache/incubator-mxnet/pull/7564#issuecomment-324185858
0-255
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piiswrong commented on a change in pull request #7494: gluon save/load
optimizer states
URL: https://github.com/apache/incubator-mxnet/pull/7494#discussion_r134631033
##
File path: python/mxnet/optimizer.py
##
@@ -969,12 +969,21 @@ def sync_state_context(self, state,
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nswamy 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 68cd9c9 Updating the LICENSE and
nswamy commented on issue #7563: Updating the LICENSE and NOTICE Files
URL: https://github.com/apache/incubator-mxnet/pull/7563#issuecomment-324184158
The licenses were not deleted and moved to a top level directory as in
apache spark because:
1. the licenses are in other
piiswrong commented on a change in pull request #7421: Resolve more compile
warnings
URL: https://github.com/apache/incubator-mxnet/pull/7421#discussion_r134627096
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##
@@ -28,7 +28,7 @@
namespace mshadow {
template
bool
cjolivier01 opened a new pull request #7562: nightly build stochastically
choose optimizer (#7559)
URL: https://github.com/apache/incubator-mxnet/pull/7562
* Only call MKL script once
* Fix 'momentum' and 'multi_precision' optimizer args
* fix cmake build for active kvstore
cjolivier01 commented on a change in pull request #7559: nightly build
stochastically choose optimizer
URL: https://github.com/apache/incubator-mxnet/pull/7559#discussion_r134611795
##
File path: tests/nightly/test_all.sh
##
@@ -72,9 +80,15 @@ check_val() {
cjolivier01 commented on a change in pull request #7559: nightly build
stochastically choose optimizer
URL: https://github.com/apache/incubator-mxnet/pull/7559#discussion_r134585168
##
File path: tests/nightly/test_all.sh
##
@@ -72,9 +80,15 @@ check_val() {
piiswrong opened a new pull request #7561: refactor cudnn algo reg to no use
string
URL: https://github.com/apache/incubator-mxnet/pull/7561
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piiswrong commented on issue #7494: gluon save/load optimizer states
URL: https://github.com/apache/incubator-mxnet/pull/7494#issuecomment-324117938
I think it's better to also serialize the optimizer object so that learning
rate schedule is preserved.
and change the name to
cjolivier01 commented on a change in pull request #7559: nightly build
stochastically choose optimizer
URL: https://github.com/apache/incubator-mxnet/pull/7559#discussion_r134561760
##
File path: tests/nightly/test_all.sh
##
@@ -72,9 +80,15 @@ check_val() {
cjolivier01 commented on a change in pull request #7559: nightly build
stochastically choose optimizer
URL: https://github.com/apache/incubator-mxnet/pull/7559#discussion_r134561760
##
File path: tests/nightly/test_all.sh
##
@@ -72,9 +80,15 @@ check_val() {
madjam commented on a change in pull request #7559: nightly build
stochastically choose optimizer
URL: https://github.com/apache/incubator-mxnet/pull/7559#discussion_r134556457
##
File path: tests/nightly/test_all.sh
##
@@ -72,9 +80,15 @@ check_val() {
cjolivier01 commented on a change in pull request #7559: nightly build
stochastically choose optimizer
URL: https://github.com/apache/incubator-mxnet/pull/7559#discussion_r134547748
##
File path: tests/nightly/test_all.sh
##
@@ -72,9 +80,15 @@ check_val() {
madjam commented on a change in pull request #7559: nightly build
stochastically choose optimizer
URL: https://github.com/apache/incubator-mxnet/pull/7559#discussion_r134544058
##
File path: tests/nightly/test_all.sh
##
@@ -72,9 +80,15 @@ check_val() {
dma100180 opened a new issue #7560: Creating a layer-by-layer network
URL: https://github.com/apache/incubator-mxnet/issues/7560
[MyData2.zip](https://github.com/apache/incubator-mxnet/files/1242794/MyData2.zip)
Hi, I have a model of a layer that I would like to train, to then
piiswrong commented on issue #7528: I found a bug, modify counting parameters
of FullyConnected layer
URL: https://github.com/apache/incubator-mxnet/pull/7528#issuecomment-324084345
Please rebase your pr on upstream master
piiswrong commented on a change in pull request #7548: add last_axis option to
fc
URL: https://github.com/apache/incubator-mxnet/pull/7548#discussion_r134537001
##
File path: tests/python/unittest/test_gluon.py
##
@@ -90,6 +90,26 @@ def test_basic():
assert
piiswrong closed pull request #7547: Fix optimizer parms in fit.py + Don't
repeatedly call slow prepare_mk?
URL: https://github.com/apache/incubator-mxnet/pull/7547
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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 f517d9d Fix optimizer parms in fit.py +
cjolivier01 opened a new pull request #7559: nightly build stochastically
choose optimizer
URL: https://github.com/apache/incubator-mxnet/pull/7559
Also gfixed build problem with USE_KVSTORE enabled when using cmake
This is
thomasmooon commented on issue #7475: Paradox VRAM demand as a function of
batch size: Low batch size, high VRAM demand
URL:
https://github.com/apache/incubator-mxnet/issues/7475#issuecomment-324051043
Someone else any idea?
chinakook commented on issue #7558: error LNK2019: ? "class nnvm::Graph
__cdecl nnvm::ApplyPasses
URL:
https://github.com/apache/incubator-mxnet/issues/7558#issuecomment-324033471
On Windows, VS2015 update 3 is OK.
I have only tried Release mode.
chinakook commented on issue #7443: tf.boolean_mask equivalent in MxNet
URL:
https://github.com/apache/incubator-mxnet/issues/7443#issuecomment-324032091
You can use Anaconda Python to accelerate the calculation of numpy as it is
compiled with the Intel MKL. You may got less performance
Godricly commented on issue #7554: There is a problem in distribute training
with dtype=fp16
URL:
https://github.com/apache/incubator-mxnet/issues/7554#issuecomment-324018339
So the old issue never dies. :laughing: Try converting them into fp32
before kvstore operations. The time cost
ZiyueHuang commented on issue #7554: There is a problem in distribute training
with dtype=fp16
URL:
https://github.com/apache/incubator-mxnet/issues/7554#issuecomment-323993848
https://github.com/apache/incubator-mxnet/blob/master/src/kvstore/kvstore_dist.h#L243.
`real_t* data =
ZiyueHuang commented on issue #7554: There is a problem in distribute training
with dtype=fp16
URL:
https://github.com/apache/incubator-mxnet/issues/7554#issuecomment-323993848
https://github.com/apache/incubator-mxnet/blob/master/src/kvstore/kvstore_dist.h#L243.
`real_t* data =
xiaoyulu2014 commented on issue #7190: add variational autoencoder example
URL: https://github.com/apache/incubator-mxnet/pull/7190#issuecomment-323990030
Any suggestions/updates of what I can do to sort this out?
Thanks!
ufukcbicici commented on issue #7443: tf.boolean_mask equivalent in MxNet
URL:
https://github.com/apache/incubator-mxnet/issues/7443#issuecomment-323985432
That is the problem; I am using a lot of glue code to implement this
conditional behavior for minibatches. I keep the track of the
wuchuanying commented on issue #7558: error LNK2019: ? "class
nnvm::Graph __cdecl nnvm::ApplyPasses
URL:
https://github.com/apache/incubator-mxnet/issues/7558#issuecomment-323982249
cpu??
This is an automated
wuchuanying opened a new issue #7558: error LNK2019: ? "class
nnvm::Graph __cdecl nnvm::ApplyPasses
URL: https://github.com/apache/incubator-mxnet/issues/7558
For bugs or installation issues, please provide the following information.
The more information you provide, the more
solin319 opened a new pull request #7556: Update vgg.py in
example/classification
URL: https://github.com/apache/incubator-mxnet/pull/7556
Reference to the program in gluon/model_zoo/vision/vgg.py, I update the
vgg.py in example/classification.
1. The new vgg include vgg-11,13,16,19.
chinakook commented on issue #7443: tf.boolean_mask equivalent in MxNet
URL:
https://github.com/apache/incubator-mxnet/issues/7443#issuecomment-323951268
Actually, you can transform the nd to np.array with .asnumpy(), and then use
numpy to do that. Slicing is not mature in mxnet.
Godricly opened a new issue #7555: tutorial for ImageDetIter
URL: https://github.com/apache/incubator-mxnet/issues/7555
Is there any more detailed tutorial about ImageDetIter? Its documentation is
almost identical to ImageIter.
Godricly commented on issue #7554: There is a problem in distribute training
with dtype=fp16
URL:
https://github.com/apache/incubator-mxnet/issues/7554#issuecomment-323942435
Try bypassing it with float32. I'm not sure if there any update since #5818.
Godricly closed issue #5813: link in mxnet.io mismatch
URL: https://github.com/apache/incubator-mxnet/issues/5813
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Godricly closed issue #5955: mx.ndarray.random with native int type support
URL: https://github.com/apache/incubator-mxnet/issues/5955
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ZiyueHuang commented on issue #7532: using python interface,some doubts for c++
api
URL:
https://github.com/apache/incubator-mxnet/issues/7532#issuecomment-323939208
Other parameters(name, attr, out...) are related to symbol. You can refer to
`MXSymbolCompose` and
solin319 opened a new issue #7554: There is a problem in distribute training
with dtype=fp16
URL: https://github.com/apache/incubator-mxnet/issues/7554
1. There is a problem in distribute training with dtype=fp16. The command is
as below.
python ../../tools/launch.py -n 2
ZiyueHuang commented on issue #7532: using python interface,some doubts for c++
api
URL:
https://github.com/apache/incubator-mxnet/issues/7532#issuecomment-323939208
Other parameters(`name`, `attr`, `out`...) are related to symbol. You can
refer to `MXSymbolCompose` and
ZiyueHuang commented on issue #7532: using python interface,some doubts for c++
api
URL:
https://github.com/apache/incubator-mxnet/issues/7532#issuecomment-323939208
Other parameters(name, attr, out...) are related to symbol. You can refer to
`MXSymbolCompose` and
ZiyueHuang commented on issue #7532: using python interface,some doubts for c++
api
URL:
https://github.com/apache/incubator-mxnet/issues/7532#issuecomment-323939208
Other parameters are related to symbol. You can refer to `MXSymbolCompose`
and
piiswrong commented on issue #7551: How to get the symbol of gluon's RNN model
by hybridizing
URL:
https://github.com/apache/incubator-mxnet/issues/7551#issuecomment-323936311
RNN is not a HybridBlock so you cannot use it as a children of a HybridBlock.
This is currently a
piiswrong commented on issue #7551: How to get the symbol of gluon's RNN model
by hybridizing
URL:
https://github.com/apache/incubator-mxnet/issues/7551#issuecomment-323936311
RNN is not a HybridBlock so you cannot use it as a children of a HybridBlock.
RNN will be changed to a
sxjscience opened a new pull request #7553: Update MShadow
URL: https://github.com/apache/incubator-mxnet/pull/7553
The MShadow side has fixed the bug in the reduce kernel and has enhanced the
speed of batch_gemm.
This is
jeremiedb commented on issue #7476: R-package RNN refactor
URL: https://github.com/apache/incubator-mxnet/pull/7476#issuecomment-323931760
rnn.model.R is compatible with regular iterator and non RNN models.
However, the need to bind at each batch results in a slower training time of
tornadomeet commented on issue #7536: mx.sym.L2Normalization has bug when
shpae[0] is bigger than 65536 and multi-gpus
URL:
https://github.com/apache/incubator-mxnet/issues/7536#issuecomment-323929403
this has been fixed from https://github.com/dmlc/mshadow/pull/287 thanks
@sxjscience
tornadomeet closed issue #7536: mx.sym.L2Normalization has bug when shpae[0] is
bigger than 65536 and multi-gpus
URL: https://github.com/apache/incubator-mxnet/issues/7536
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