zhechen opened a new issue #9823: RCNN example fails for using latest mxnet
URL: https://github.com/apache/incubator-mxnet/issues/9823
I am using mxnet with CUDA9 + CUDNN7 and distributed training enabled.
However, when I re-run the rcnn code in the example, I got the following error:
feevos opened a new issue #9822: gluon HybridBlock wrapper of constant
nd.array, is it possible?
URL: https://github.com/apache/incubator-mxnet/issues/9822
Dear all,
would it please be possible to provide a simple example of a HybridBlock
wrapper around an nd.array object? I need to
stonedl3 commented on issue #9766: DeepLearning on Imagenet with mxnet issues
translating .lst to .rec files
URL:
https://github.com/apache/incubator-mxnet/issues/9766#issuecomment-366580822
Here is the complete error trace
python train_alexnet.py --checkpoints checkpoints --prefix alex
zhreshold commented on a change in pull request #9784: Fix for the case where
there are no detections
URL: https://github.com/apache/incubator-mxnet/pull/9784#discussion_r168968406
##
File path: example/ssd/detect/detector.py
##
@@ -136,31 +132,52 @@ class names
h
gigasquid commented on issue #8971: Clojure Library for mxnet
URL:
https://github.com/apache/incubator-mxnet/issues/8971#issuecomment-366543008
An update - I've ported over the MnistModule example to clojure - yay! ?
https://github.com/gigasquid/incubator-mxnet/blob/clojure-package/clo
KellenSunderland closed pull request #9821: Remove pthread warning for OSX
URL: https://github.com/apache/incubator-mxnet/pull/9821
This is a PR merged from a forked repository.
As GitHub hides the original diff on merge, it is displayed below for
the sake of provenance:
As this is a fore
KellenSunderland opened a new pull request #9821: Remove pthread warning for OSX
URL: https://github.com/apache/incubator-mxnet/pull/9821
This is an automated message from the Apache Git Service.
To respond to the message, pl
KellenSunderland commented on issue #9774: mx.io.ImageRecordIter does not
respect dtype argument
URL:
https://github.com/apache/incubator-mxnet/issues/9774#issuecomment-366532991
@rahul003 If you're only seeing ~15% speedups I'd recommend you run nvprof
before your training. Take a look
DickJC123 commented on issue #9791: CI test randomness 3
URL: https://github.com/apache/incubator-mxnet/pull/9791#issuecomment-366530909
Sure.
> On Feb 18, 2018, at 9:08 AM, Marco de Abreu
wrote:
>
> @DickJC123 would you mind creating another PR which adds documentation for
marcoabreu commented on issue #9791: CI test randomness 3
URL: https://github.com/apache/incubator-mxnet/pull/9791#issuecomment-366530518
@DickJC123 would you mind creating another PR which adds documentation for
these features?
Good places could be the readme in the tests dir or ma
marcoabreu commented on issue #9820: Flaky
test_gluon_model_zoo_gpu.test_training
URL:
https://github.com/apache/incubator-mxnet/issues/9820#issuecomment-366530354
Sounds good. Since we've now got the CI randomness PR merged into the
master, it should be no problem to generate faulty test
zheng-da commented on issue #9820: Flaky test_gluon_model_zoo_gpu.test_training
URL:
https://github.com/apache/incubator-mxnet/issues/9820#issuecomment-366530169
I think we should disable it for now.
I run the tests many times. It seems both CPU and GPU occasionally generate
incorrect
KellenSunderland commented on a change in pull request #9810: remove
MKL_EXPERIMENTAL and update make files for MKL-DNN
URL: https://github.com/apache/incubator-mxnet/pull/9810#discussion_r168958119
##
File path: docker_multiarch/arm.crosscompile.android.mk
##
@@ -82,21 +8
KellenSunderland opened a new pull request #9466: WIP (testing windows builds)
Enable CUDA NVTX extensions for profiler
URL: https://github.com/apache/incubator-mxnet/pull/9466
These extensions mark readable ranges in the NVIDIA Visual Profiler which
helps
show correlations between kern
marcoabreu commented on issue #9817: Example SSD demo doesn't work
URL:
https://github.com/apache/incubator-mxnet/issues/9817#issuecomment-366508807
@larroy might be interested
@tholcman you might want to try out
https://github.com/apache/incubator-mxnet/pull/9808
-
marcoabreu commented on issue #9809: register optimizers only once in
CPP-Package
URL: https://github.com/apache/incubator-mxnet/pull/9809#issuecomment-366508646
Since we are using randomized data in our unit tests, they tend to be flaky
by nature. I have retriggered the build and create a
marcoabreu opened a new issue #9820: Flaky
test_gluon_model_zoo_gpu.test_training
URL: https://github.com/apache/incubator-mxnet/issues/9820
???
==
FAIL: test_gluon_model_zoo_gpu.test_training
-
samhodge commented on issue #9813: Unable to save gluon model to symbolic
network : neural style
URL:
https://github.com/apache/incubator-mxnet/issues/9813#issuecomment-366503862
I have had a bit of a fiddle but I am getting lost
have a look here:
https://github.com/samhodge/incubat
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