benqua commented on issue #8129: [scala] Module api: label (1,1,868,868) and
prediction (1,868,868)should have the same length
URL:
https://github.com/apache/incubator-mxnet/issues/8129#issuecomment-334054179
Yes, I am conducting a segmentation tasks.
My label has only one channel,
eric-haibin-lin opened a new pull request #8141: update sparse LR example
URL: https://github.com/apache/incubator-mxnet/pull/8141
- fix wrong metric name `log_loss` -> `nll_loss`
- fix wrong README instruction for distributed training
- added weighted loss for the output layer
-
Ldpe2G commented on issue #8129: [scala] Module api: label (1,1,868,868) and
prediction (1,868,868)should have the same length
URL:
https://github.com/apache/incubator-mxnet/issues/8129#issuecomment-334057398
No you should. And I suggest you to try the intermediate api
CodingCat commented on issue #8128: Adding code owners
URL: https://github.com/apache/incubator-mxnet/pull/8128#issuecomment-333957516
@gautamkmr I am totally fine and supportive with this..
as long as it is not something like "file a,b,c has to be signed off by Mr
xyz before merge
aseyboldt commented on issue #8133: Infer_shape_partial for rank 0 arrays
URL:
https://github.com/apache/incubator-mxnet/issues/8133#issuecomment-333958354
`ndarray` does allow scalars:
```python
>>> a = mx.nd.ones(())
>>> a.shape
()
>>> a.size
1
>>> a.asnumpy()
CodingCat commented on issue #8128: Adding code owners
URL: https://github.com/apache/incubator-mxnet/pull/8128#issuecomment-333957516
@gautamkmr I am totally fine and supportive with this..
as long as it is not something like "file a,b,c has to be signed off by Mr
xyz before merge
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zhasheng pushed a change to branch szha-patch-1
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at 585b0b8 Update nn.md
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szha opened a new pull request #8134: Update nn.md
URL: https://github.com/apache/incubator-mxnet/pull/8134
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jxie pushed a commit to branch master
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new 236d1c2 Updating code owners (#8128)
mli commented on issue #7995: Problem in acc metric
URL: https://github.com/apache/incubator-mxnet/pull/7995#issuecomment-333984572
can we just use ndarray to compute instead of converting to numpy? if there
is a number of classes, say 10K, then it could be problematic
a sample
aseyboldt commented on issue #8133: Infer_shape_partial for rank 0 arrays
URL:
https://github.com/apache/incubator-mxnet/issues/8133#issuecomment-333958354
That explains a lot :-)
However `ndarray` does allow scalars:
```python
>>> a = mx.nd.ones(())
>>> a.shape
()
anirudh2290 commented on a change in pull request #8020: Get bz2 data fix
URL: https://github.com/apache/incubator-mxnet/pull/8020#discussion_r142521336
##
File path: python/mxnet/test_utils.py
##
@@ -1411,8 +1411,29 @@ def read_data(label_url, image_url):
piiswrong opened a new pull request #8136: stable sum
URL: https://github.com/apache/incubator-mxnet/pull/8136
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aseyboldt commented on issue #8133: Infer_shape_partial for rank 0 arrays
URL:
https://github.com/apache/incubator-mxnet/issues/8133#issuecomment-333958354
That explains a lot :-)
However `ndarray` does allow scalars:
```python
>>> a = mx.nd.ones(())
>>> a.shape
()
szha commented on issue #8136: stable sum
URL: https://github.com/apache/incubator-mxnet/pull/8136#issuecomment-333983441
Do you plan on using Kahan's summation on regular sum too? Our mean is using
that as the reduce function.
piiswrong closed pull request #8128: Adding code owners
URL: https://github.com/apache/incubator-mxnet/pull/8128
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piiswrong opened a new pull request #8135: Stable sum
URL: https://github.com/apache/incubator-mxnet/pull/8135
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piiswrong closed pull request #8135: Stable sum
URL: https://github.com/apache/incubator-mxnet/pull/8135
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zhasheng pushed a commit to branch master
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new 57d59ac Update loss.md (#8131)
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zhasheng pushed a change to branch szha-patch-1
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was c7550b0 Update loss.md
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szha closed pull request #8131: Update loss.md
URL: https://github.com/apache/incubator-mxnet/pull/8131
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szha commented on issue #8133: Infer_shape_partial for rank 0 arrays
URL:
https://github.com/apache/incubator-mxnet/issues/8133#issuecomment-333935130
I don't think we have the concept of scalar in ndarray or symbol. Shape of
`()` doesn't mean it's a scalar, it means its shape is unknown
Ldpe2G commented on issue #8129: [scala] Module api: label (1,1,868,868) and
prediction (1,868,868)should have the same length
URL:
https://github.com/apache/incubator-mxnet/issues/8129#issuecomment-334036151
@benqua are you conducting the segmentation task? If so, the shape of label
gautamkmr commented on issue #8128: Adding code owners
URL: https://github.com/apache/incubator-mxnet/pull/8128#issuecomment-333992063
@CodingCat sure :)
@piiswrong Thanks ?
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benqua commented on issue #8129: [scala] Module api: label (1,1,868,868) and
prediction (1,868,868)should have the same length
URL:
https://github.com/apache/incubator-mxnet/issues/8129#issuecomment-333992969
ok, I checked and log the shapes as suggested and realize that it is not the
zhreshold closed pull request #8137: [Gluon] Object detection preview
URL: https://github.com/apache/incubator-mxnet/pull/8137
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zhreshold opened a new pull request #8137: [Gluon] Object detection preview
URL: https://github.com/apache/incubator-mxnet/pull/8137
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zhasheng pushed a change to branch szha-patch-1
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git.
was 585b0b8 Update nn.md
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szha closed pull request #8134: Update nn.md
URL: https://github.com/apache/incubator-mxnet/pull/8134
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zhasheng pushed a commit to branch master
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The following commit(s) were added to refs/heads/master by this push:
new 8a4221b Update nn.md (#8134)
szha commented on issue #8105: Proposal: PR Template
URL:
https://github.com/apache/incubator-mxnet/issues/8105#issuecomment-334005341
Thanks. @apache/mxnet-committers just to make sure everyone is aware.
This is an
szha commented on issue #8136: stable sum
URL: https://github.com/apache/incubator-mxnet/pull/8136#issuecomment-333994412
I didn't realize that it was already added to mshadow. never mind
https://github.com/dmlc/mshadow/blame/master/mshadow/base.h#L672-L685
piiswrong commented on issue #8136: stable sum
URL: https://github.com/apache/incubator-mxnet/pull/8136#issuecomment-333991002
Which file/function are you talking about?
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szha commented on issue #8136: stable sum
URL: https://github.com/apache/incubator-mxnet/pull/8136#issuecomment-333993695
https://github.com/apache/incubator-mxnet/blob/master/src/operator/tensor/broadcast_reduce_op_value.cc#L81-L88
yxchng commented on issue #8132: How to disable MXNET_CUDNN_AUTOTUNE_DEFAULT
and bucketing log message without turning off MXNET_CUDNN_AUTOTUNE_DEFAULT?
URL:
https://github.com/apache/incubator-mxnet/issues/8132#issuecomment-333791801
I tried exporting or using os.environ but they don't
benqua commented on issue #8129: [scala] Module api: label (1,1,868,868) and
prediction (1,868,868)should have the same length
URL:
https://github.com/apache/incubator-mxnet/issues/8129#issuecomment-333796027
If that helps, the last layer of my network is:
```scala
val out=
yxchng opened a new issue #8132: How to disable MXNET_CUDNN_AUTOTUNE_DEFAULT
log message without turning off MXNET_CUDNN_AUTOTUNE_DEFAULT?
URL: https://github.com/apache/incubator-mxnet/issues/8132
This is an automated
theSparta commented on issue #8126: Not able to train a neural network using
MXNET with C++ API
URL:
https://github.com/apache/incubator-mxnet/issues/8126#issuecomment-333847990
I am adding a very simple example here in which I tried to fit a neural
network on the XOR function but unable
theSparta commented on issue #8126: Not able to train a neural network [XOR
added]
URL:
https://github.com/apache/incubator-mxnet/issues/8126#issuecomment-333847990
I am adding a very simple example here in which I tried to fit a neural
network on the XOR function but unable to do so as
bhavinthaker commented on issue #8105: Proposal: PR Template
URL:
https://github.com/apache/incubator-mxnet/issues/8105#issuecomment-333874115
Looks good to me. Thanks for this suggestion.
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Ldpe2G commented on issue #8129: [scala] Module api: label (1,1,868,868) and
prediction (1,868,868)should have the same length
URL:
https://github.com/apache/incubator-mxnet/issues/8129#issuecomment-333860436
@benqua It seems like the error occurs when calling the `update` method of
the
benqua commented on issue #8129: [scala] Module api: label (1,1,868,868) and
prediction (1,868,868)should have the same length
URL:
https://github.com/apache/incubator-mxnet/issues/8129#issuecomment-333862739
@Ldpe2G all right, I am going to check that (pretty sure it was
(1,1,868,868),
altosaar commented on issue #8130: autograd.backward() segfaults: how to get
gradients with respect to a subset of variables in mxnet?
URL:
https://github.com/apache/incubator-mxnet/issues/8130#issuecomment-333903906
Thanks @piiswrong !
I installed the newest mxnet (`pip install
aseyboldt opened a new issue #8133: Infer_shape_partial for rank 0 arrays
URL: https://github.com/apache/incubator-mxnet/issues/8133
In the python interface of mxnet it seems to be impossible to distinguish
between an array of unknown shape and an array with known shape of `()`:
szha commented on issue #8136: stable sum
URL: https://github.com/apache/incubator-mxnet/pull/8136#issuecomment-334013658
Looks like square sum needs updating too:
https://github.com/apache/incubator-mxnet/blob/master/src/operator/tensor/square_sum-inl.h#L127-L130
eric-haibin-lin commented on issue #7893: Add barriers in kvstore init
URL: https://github.com/apache/incubator-mxnet/pull/7893#issuecomment-334014237
The test failure seems irrelevant. Do you mind sync up with master again to
see if it passes?
Regarding fp16, yes I think we need that
eric-haibin-lin opened a new pull request #8138: add storage type logging to
graph executor
URL: https://github.com/apache/incubator-mxnet/pull/8138
This is mentioned in the tutorial PR #7921 and should be merged before that.
The log message will be printed if env_var
szha commented on issue #8136: stable sum
URL: https://github.com/apache/incubator-mxnet/pull/8136#issuecomment-334013658
Looks like square sum needs updating too:
https://github.com/apache/incubator-mxnet/blob/master/src/operator/tensor/square_sum-inl.h#L127-L130
ZiyueHuang commented on issue #8130: autograd.backward() segfaults: how to get
gradients with respect to a subset of variables in mxnet?
URL:
https://github.com/apache/incubator-mxnet/issues/8130#issuecomment-334040825
Instead of using two `autograd.grad`, please try
```
print
caiqi opened a new issue #8139: mxnet ssd training speed slow down after some
batches
URL: https://github.com/apache/incubator-mxnet/issues/8139
## Environment info
Operating System:
Windows
Package used (Python/R/Scala/Julia):
Python
MXNet version:
0.11.0
solin319 commented on issue #7893: Add barriers in kvstore init
URL: https://github.com/apache/incubator-mxnet/pull/7893#issuecomment-334041868
Sorry,I am in holiday these days. l didn't bring my computer back to my
hometown. When I go back,I will sync the code and add a test file as soon
eric-haibin-lin commented on issue #7893: Add barriers in kvstore init
URL: https://github.com/apache/incubator-mxnet/pull/7893#issuecomment-334042834
@solin319 no worries. Happy mid-autumn festival!
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szha opened a new pull request #8140: use fma in fully connected.
URL: https://github.com/apache/incubator-mxnet/pull/8140
when use bias, broadcast the bias to output first and then use kAddTo, which
in turn keeps beta in gemm to be 1.
zhreshold commented on issue #8139: mxnet ssd training speed slow down after
some batches
URL:
https://github.com/apache/incubator-mxnet/issues/8139#issuecomment-334045504
Seems like thermal throttling. Are you using workstation with multiple GPUs?
If so, you need to address the
caiqi commented on issue #8139: mxnet ssd training speed slow down after some
batches
URL:
https://github.com/apache/incubator-mxnet/issues/8139#issuecomment-334047247
I'm using muti GPUs on a server and it works well for other programs. When I
train ssd on a single GPU, there is no
caiqi commented on issue #8139: mxnet ssd training speed slow down after some
batches
URL:
https://github.com/apache/incubator-mxnet/issues/8139#issuecomment-334047544
I have read this page
https://github.com/msracver/Flow-Guided-Feature-Aggregation, FAQ 2. I
originally thought the
eric-haibin-lin commented on issue #8062: CSVIter and LibSVMIter not returning
correct number of batches per epoch
URL:
https://github.com/apache/incubator-mxnet/issues/8062#issuecomment-334051905
The number of batches will be correct if reset() is moved to the end of the
epoch:
```
eric-haibin-lin closed issue #8062: CSVIter and LibSVMIter not returning
correct number of batches per epoch
URL: https://github.com/apache/incubator-mxnet/issues/8062
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