[GitHub] indhub closed pull request #8327: update ps lite

indhub closed pull request #8327: update ps lite URL: https://github.com/apache/incubator-mxnet/pull/8327 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 foreign pull request (from a

[incubator-mxnet] branch master updated: update ps lite (#8327)

This is an automated email from the ASF dual-hosted git repository. indhub 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 349ebc3 update ps lite (#8327)

[GitHub] cjolivier01 commented on issue #8340: Fill optimizations

cjolivier01 commented on issue #8340: Fill optimizations URL: https://github.com/apache/incubator-mxnet/pull/8340#issuecomment-337758247 You can re-add it if you need it sometime, although it's better to use OpBase::SetToScalar or op_with_req (op_with_req

[GitHub] VikingMew commented on issue #7582: Gluon GPU memory efficiency

VikingMew commented on issue #7582: Gluon GPU memory efficiency URL: https://github.com/apache/incubator-mxnet/issues/7582#issuecomment-337760280 @jermainewang How to do (2)? This is an automated message from the Apache Git

[GitHub] javelinjs commented on issue #8297: [scala] Make accuracy idependant of output size (fix #8226)

javelinjs commented on issue #8297: [scala] Make accuracy idependant of output size (fix #8226) URL: https://github.com/apache/incubator-mxnet/pull/8297#issuecomment-337790078 We should keep it the same as other language bindings, especially python. What if we make it Double in EvalMetric

[GitHub] tqchen commented on issue #8343: [CMAKE] Cmake changes, upgrade training test so it converge

tqchen commented on issue #8343: [CMAKE] Cmake changes, upgrade training test so it converge URL: https://github.com/apache/incubator-mxnet/pull/8343#issuecomment-337796868 cc @piiswrong This is an automated message from

[GitHub] wa1618i commented on issue #5218: core dumped when I try to compile mxnet0.9.3 with nnpack support WHY?

wa1618i commented on issue #5218: core dumped when I try to compile mxnet0.9.3 with nnpack support WHY? URL: https://github.com/apache/incubator-mxnet/issues/5218#issuecomment-337805448 @szha I have same issue here, please re-open. I can build mxnet from the source without error but

[GitHub] ZiyueHuang commented on issue #8337: mx.autograd.grad works or fails depending on use of slices

ZiyueHuang commented on issue #8337: mx.autograd.grad works or fails depending on use of slices URL: https://github.com/apache/incubator-mxnet/issues/8337#issuecomment-337792225 Is this a bug or wrong usage of autograd? Do you have any idea? @szha

[GitHub] kpot commented on issue #8337: mx.autograd.grad works or fails depending on use of slices

kpot commented on issue #8337: mx.autograd.grad works or fails depending on use of slices URL: https://github.com/apache/incubator-mxnet/issues/8337#issuecomment-337796013 @ZiyueHuang Yes, I think the empty line is indeed the argument `''`. But when I replace `mx.nd.ones_like(b)` with

[GitHub] tqchen closed issue #5804: Scala build failed with "undefined symbol: __cudaRegisterFatBinary"

tqchen closed issue #5804: Scala build failed with "undefined symbol: __cudaRegisterFatBinary" URL: https://github.com/apache/incubator-mxnet/issues/5804 This is an automated message from the Apache Git Service. To respond

[GitHub] tqchen closed issue #5580: How to create a Custom Operator with extra parameters in Python?

tqchen closed issue #5580: How to create a Custom Operator with extra parameters in Python? URL: https://github.com/apache/incubator-mxnet/issues/5580 This is an automated message from the Apache Git Service. To respond to

[GitHub] tqchen closed issue #5566: MinPy next step prototype

tqchen closed issue #5566: MinPy next step prototype URL: https://github.com/apache/incubator-mxnet/issues/5566 This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and

[GitHub] tqchen closed issue #5592: [Discussion] CreateBackwardOp interface for `Operator`

tqchen closed issue #5592: [Discussion] CreateBackwardOp interface for `Operator` URL: https://github.com/apache/incubator-mxnet/issues/5592 This is an automated message from the Apache Git Service. To respond to the

[GitHub] tqchen closed issue #5699: [Discussion] Support Higher-order Gradient

tqchen closed issue #5699: [Discussion] Support Higher-order Gradient URL: https://github.com/apache/incubator-mxnet/issues/5699 This is an automated message from the Apache Git Service. To respond to the message, please log

[GitHub] goodtogood commented on issue #7771: Error when loading JSON network definition with c++ api

goodtogood commented on issue #7771: Error when loading JSON network definition with c++ api URL: https://github.com/apache/incubator-mxnet/issues/7771#issuecomment-337804646 same problem. This is an automated message from

[GitHub] szha commented on issue #8340: Fill optimizations

szha commented on issue #8340: Fill optimizations URL: https://github.com/apache/incubator-mxnet/pull/8340#issuecomment-337758666 As long as `full` is still on the radar it's fine. Would you make the change to properly support `full` in that PR then?

[GitHub] ZiyueHuang commented on issue #8338: master branch cannot build on centos 7 with cuda-8.0

ZiyueHuang commented on issue #8338: master branch cannot build on centos 7 with cuda-8.0 URL: https://github.com/apache/incubator-mxnet/issues/8338#issuecomment-337790437 Seems that @wa1618i got the same problem in https://github.com/apache/incubator-mxnet/issues/8333. Have you got any

[GitHub] ZiyueHuang commented on issue #8337: mx.autograd.grad works or fails depending on use of slices

ZiyueHuang commented on issue #8337: mx.autograd.grad works or fails depending on use of slices URL: https://github.com/apache/incubator-mxnet/issues/8337#issuecomment-337792011 `a`'s shape is `(4,)`. Why "a's first dimension has length 1 and slicing it with 0:4 doesn't really make

[GitHub] tqchen closed issue #2066: Mxnet model visualisation

tqchen closed issue #2066: Mxnet model visualisation URL: https://github.com/apache/incubator-mxnet/issues/2066 This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and

[GitHub] tqchen closed issue #2284: Compiling MxNet: Problems with CMake

tqchen closed issue #2284: Compiling MxNet: Problems with CMake URL: https://github.com/apache/incubator-mxnet/issues/2284 This is an automated message from the Apache Git Service. To respond to the message, please log on

[GitHub] reminisce commented on a change in pull request #8340: Fill optimizations

reminisce commented on a change in pull request #8340: Fill optimizations URL: https://github.com/apache/incubator-mxnet/pull/8340#discussion_r145600607 ## File path: src/operator/tensor/init_op.h ## @@ -164,19 +164,38 @@ inline bool InitStorageType(const nnvm::NodeAttrs&

[GitHub] dslate opened a new issue #8344: Broken link for "MXNet R Reference Manual"?

dslate opened a new issue #8344: Broken link for "MXNet R Reference Manual"? URL: https://github.com/apache/incubator-mxnet/issues/8344 On the MXNet page for the R API (http://mxnet.incubator.apache.org/api/r/index.html) the link to the "MXNet R Reference Manual" seems to point to a

[GitHub] ykim362 commented on issue #7931: MKL-DNN integration: request for reviews

ykim362 commented on issue #7931: MKL-DNN integration: request for reviews URL: https://github.com/apache/incubator-mxnet/pull/7931#issuecomment-337757546 @szha @piiswrong MKL-DNN doesn't support fp64(double) data type. Do you think this is an issue? The library team is more focusing on

[GitHub] vinig opened a new issue #8231: [MXNet 0.11.0 + RPi 3 + Python 2.7] ndarray unit test fails

vinig opened a new issue #8231: [MXNet 0.11.0 + RPi 3 + Python 2.7] ndarray unit test fails URL: https://github.com/apache/incubator-mxnet/issues/8231 ## Description I'm trying to build MXNet (0.11.0) for Raspberry Pi 3 with Python 2.7, OpenBLAS, OPENCV and LAPACK. (cross-compiled

[GitHub] rahul003 opened a new pull request #8342: [WIP] 2bit gradient compression

rahul003 opened a new pull request #8342: [WIP] 2bit gradient compression URL: https://github.com/apache/incubator-mxnet/pull/8342 ## Description ## Implements 2bit gradient compression by quantizing each value in gradient array to 2bits using two user specified thresholds, one for

[GitHub] kpot commented on issue #8337: mx.autograd.grad works or fails depending on use of slices

kpot commented on issue #8337: mx.autograd.grad works or fails depending on use of slices URL: https://github.com/apache/incubator-mxnet/issues/8337#issuecomment-337794186 @ZiyueHuang `a`s first dimension is 4, and slicing it like `a[0:4]` is absolutely valid and I didn't care about

[GitHub] tqchen closed issue #4003: Building a visualization tool for MXNet

tqchen closed issue #4003: Building a visualization tool for MXNet URL: https://github.com/apache/incubator-mxnet/issues/4003 This is an automated message from the Apache Git Service. To respond to the message, please log on

[GitHub] tqchen closed issue #3198: Check list for more operators

tqchen closed issue #3198: Check list for more operators URL: https://github.com/apache/incubator-mxnet/issues/3198 This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub

[GitHub] tqchen closed issue #3917: how to use my own loss to compute grad?

tqchen closed issue #3917: how to use my own loss to compute grad? URL: https://github.com/apache/incubator-mxnet/issues/3917 This is an automated message from the Apache Git Service. To respond to the message, please log on

[GitHub] tqchen closed issue #5346: Amalgamation using weBLAS (JS + WebGL) ?

tqchen closed issue #5346: Amalgamation using weBLAS (JS + WebGL) ? URL: https://github.com/apache/incubator-mxnet/issues/5346 This is an automated message from the Apache Git Service. To respond to the message, please log

[GitHub] tqchen closed issue #3987: How to set auxiliary state in Batchnorm manually ?

tqchen closed issue #3987: How to set auxiliary state in Batchnorm manually ? URL: https://github.com/apache/incubator-mxnet/issues/3987 This is an automated message from the Apache Git Service. To respond to the message,

[GitHub] tqchen closed issue #3946: When predicting, does mxnet provide thread-safe interface?

tqchen closed issue #3946: When predicting, does mxnet provide thread-safe interface? URL: https://github.com/apache/incubator-mxnet/issues/3946 This is an automated message from the Apache Git Service. To respond to the

[GitHub] eric-haibin-lin opened a new pull request #8345: Misc fixes for sparse distributed training

eric-haibin-lin opened a new pull request #8345: Misc fixes for sparse distributed training URL: https://github.com/apache/incubator-mxnet/pull/8345 ## Description ## - As #8116 removes

[GitHub] ZiyueHuang commented on issue #8337: mx.autograd.grad works or fails depending on use of slices

ZiyueHuang commented on issue #8337: mx.autograd.grad works or fails depending on use of slices URL: https://github.com/apache/incubator-mxnet/issues/8337#issuecomment-337792011 `a`'s shape is `(4,)`. Why "a's first dimension has length 1 and slicing it with 0:4 doesn't really make

[GitHub] tqchen closed issue #3006: [R] R package roadmap

tqchen closed issue #3006: [R] R package roadmap URL: https://github.com/apache/incubator-mxnet/issues/3006 This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use

[GitHub] tqchen closed issue #1873: Implement a model serving framework

tqchen closed issue #1873: Implement a model serving framework URL: https://github.com/apache/incubator-mxnet/issues/1873 This is an automated message from the Apache Git Service. To respond to the message, please log on

[GitHub] tqchen closed issue #1281: how to prepare data for mxnet.io.NDArrayIter

tqchen closed issue #1281: how to prepare data for mxnet.io.NDArrayIter URL: https://github.com/apache/incubator-mxnet/issues/1281 This is an automated message from the Apache Git Service. To respond to the message, please

[GitHub] tqchen closed issue #1784: Bug in ccSGD optimizer

tqchen closed issue #1784: Bug in ccSGD optimizer URL: https://github.com/apache/incubator-mxnet/issues/1784 This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use

[GitHub] tqchen closed issue #2944: v1.0 Stable Release TODO List

tqchen closed issue #2944: v1.0 Stable Release TODO List URL: https://github.com/apache/incubator-mxnet/issues/2944 This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub

[GitHub] tqchen closed issue #3084: Scala Package for v1.0 TODO List

tqchen closed issue #3084: Scala Package for v1.0 TODO List URL: https://github.com/apache/incubator-mxnet/issues/3084 This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub

[GitHub] tqchen commented on issue #8343: [CMAKE] Cmake changes, upgrade training test so it converge

tqchen commented on issue #8343: [CMAKE] Cmake changes, upgrade training test so it converge URL: https://github.com/apache/incubator-mxnet/pull/8343#issuecomment-337801113 failure in the tests appears due to the missing ci machine. need retrigger when they are up

[GitHub] szha commented on issue #8340: Fill optimizations

szha commented on issue #8340: Fill optimizations URL: https://github.com/apache/incubator-mxnet/pull/8340#issuecomment-337758666 As long as `full` is still on the radar it's fine. This is an automated message from the Apache

[GitHub] zhangqianghd closed issue #8309: asnumpy is slowly ,how can I speed up it?

zhangqianghd closed issue #8309: asnumpy is slowly ,how can I speed up it? URL: https://github.com/apache/incubator-mxnet/issues/8309 This is an automated message from the Apache Git Service. To respond to the message,

[GitHub] zhangqianghd commented on issue #8309: asnumpy is slowly ,how can I speed up it?

zhangqianghd commented on issue #8309: asnumpy is slowly ,how can I speed up it? URL: https://github.com/apache/incubator-mxnet/issues/8309#issuecomment-337780811 When I add wait_to_read,I have found the detail . Thanks All.

[GitHub] tqchen opened a new pull request #8343: [CMAKE] Cmake changes, upgrade training test so it converge

tqchen opened a new pull request #8343: [CMAKE] Cmake changes, upgrade training test so it converge URL: https://github.com/apache/incubator-mxnet/pull/8343 ## Description ## (Brief description on what this PR is about) ## Checklist ## ### Essentials ### - [ ] Passed code

[GitHub] ZiyueHuang commented on issue #8337: mx.autograd.grad works or fails depending on use of slices

ZiyueHuang commented on issue #8337: mx.autograd.grad works or fails depending on use of slices URL: https://github.com/apache/incubator-mxnet/issues/8337#issuecomment-337796480 Sorry, I just paste the codes you posted at first comment, without adding slice.

[GitHub] tqchen closed issue #3200: [OP] Array manipulation

tqchen closed issue #3200: [OP] Array manipulation URL: https://github.com/apache/incubator-mxnet/issues/3200 This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use

[GitHub] tqchen closed issue #3487: [PERF] Call for NN Layer Kernel Improvement

tqchen closed issue #3487: [PERF] Call for NN Layer Kernel Improvement URL: https://github.com/apache/incubator-mxnet/issues/3487 This is an automated message from the Apache Git Service. To respond to the message, please

[GitHub] tqchen closed issue #3523: Operator documents issues tracking

tqchen closed issue #3523: Operator documents issues tracking URL: https://github.com/apache/incubator-mxnet/issues/3523 This is an automated message from the Apache Git Service. To respond to the message, please log on

[GitHub] tqchen closed issue #3504: [RFC] Documentation of MXNet

tqchen closed issue #3504: [RFC] Documentation of MXNet URL: https://github.com/apache/incubator-mxnet/issues/3504 This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub

[GitHub] tqchen closed issue #3724: asnumpy() of NDArray @cpu halted

tqchen closed issue #3724: asnumpy() of NDArray @cpu halted URL: https://github.com/apache/incubator-mxnet/issues/3724 This is an automated message from the Apache Git Service. To respond to the message, please log on

[GitHub] tqchen closed issue #3201: [OP] Mathematical functions

tqchen closed issue #3201: [OP] Mathematical functions URL: https://github.com/apache/incubator-mxnet/issues/3201 This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and

[GitHub] moakra commented on issue #8248: A3C code does not learn

moakra commented on issue #8248: A3C code does not learn URL: https://github.com/apache/incubator-mxnet/issues/8248#issuecomment-337756962 I was talking about this code: https://github.com/apache/incubator-mxnet/tree/master/example/reinforcement-learning/a3c Now it works.

[GitHub] liuzhi136 opened a new issue #8341: Training error always fluctuates and doesn't decrease.

liuzhi136 opened a new issue #8341: Training error always fluctuates and doesn't decrease. URL: https://github.com/apache/incubator-mxnet/issues/8341 I had implemented a model which defined in "Training RNNs as Fast as CNNs". The structure I wrote as below:

[GitHub] kaisark commented on issue #6846: Check failed: err == cudaSuccess (8 vs. 0) Name: MapPlanKernel ErrStr:invalid device function

kaisark commented on issue #6846: Check failed: err == cudaSuccess (8 vs. 0) Name: MapPlanKernel ErrStr:invalid device function URL: https://github.com/apache/incubator-mxnet/issues/6846#issuecomment-337768151 I was able to build mxnet on my TX1 with gpu today. I did add 53 in the

[GitHub] ZiyueHuang commented on issue #8338: master branch cannot build on centos 7 with cuda-8.0

ZiyueHuang commented on issue #8338: master branch cannot build on centos 7 with cuda-8.0 URL: https://github.com/apache/incubator-mxnet/issues/8338#issuecomment-337789562 Thanks for your suggestions. Seems wired. It can build successfully on ubuntu. Why centos cannot? Yes,

[GitHub] tqchen closed issue #792: Support a parameter for maximum memory usage

tqchen closed issue #792: Support a parameter for maximum memory usage URL: https://github.com/apache/incubator-mxnet/issues/792 This is an automated message from the Apache Git Service. To respond to the message, please log

[GitHub] tqchen closed issue #4783: [v0.9.3] Amalgamation for Android broken

tqchen closed issue #4783: [v0.9.3] Amalgamation for Android broken URL: https://github.com/apache/incubator-mxnet/issues/4783 This is an automated message from the Apache Git Service. To respond to the message, please log

[GitHub] tqchen closed issue #4989: How to use mxnet?

tqchen closed issue #4989: How to use mxnet? URL: https://github.com/apache/incubator-mxnet/issues/4989 This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the

[GitHub] tqchen closed issue #3509: [RELEASE] Announcing v0.9 Release Candidate 1

tqchen closed issue #3509: [RELEASE] Announcing v0.9 Release Candidate 1 URL: https://github.com/apache/incubator-mxnet/issues/3509 This is an automated message from the Apache Git Service. To respond to the message, please

[GitHub] tqchen closed issue #4851: error: ISO C++ forbids comparison between pointer and integer

tqchen closed issue #4851: error: ISO C++ forbids comparison between pointer and integer URL: https://github.com/apache/incubator-mxnet/issues/4851 This is an automated message from the Apache Git Service. To respond to the

[GitHub] tqchen commented on issue #6996: Label smoothing for SoftmaxOutput / cross-entropy loss

tqchen commented on issue #6996: Label smoothing for SoftmaxOutput / cross-entropy loss URL: https://github.com/apache/incubator-mxnet/issues/6996#issuecomment-337798214 close as it is enabled This is an automated message

[GitHub] tqchen closed issue #1237: can mxnet provide the sparse gradient update for word embedding

tqchen closed issue #1237: can mxnet provide the sparse gradient update for word embedding URL: https://github.com/apache/incubator-mxnet/issues/1237 This is an automated message from the Apache Git Service. To respond to

[GitHub] tqchen closed issue #5807: Model Parallelism

tqchen closed issue #5807: Model Parallelism URL: https://github.com/apache/incubator-mxnet/issues/5807 This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the

[GitHub] tqchen closed issue #6996: Label smoothing for SoftmaxOutput / cross-entropy loss

tqchen closed issue #6996: Label smoothing for SoftmaxOutput / cross-entropy loss URL: https://github.com/apache/incubator-mxnet/issues/6996 This is an automated message from the Apache Git Service. To respond to the

[GitHub] chinakook opened a new issue #8335: Performance of MXNet on Windows is lower than that on Linux by 15%-20%

chinakook opened a new issue #8335: Performance of MXNet on Windows is lower than that on Linux by 15%-20% URL: https://github.com/apache/incubator-mxnet/issues/8335 I've been testing MXNet on both Win10 and Ubuntu 16.04 in a long time. I found that the performance of Windows is lower

[GitHub] benqua commented on issue #8297: [scala] Make accuracy idependant of output size (fix #8226)

benqua commented on issue #8297: [scala] Make accuracy idependant of output size (fix #8226) URL: https://github.com/apache/incubator-mxnet/pull/8297#issuecomment-337598650 @javelinjs , you're right, it changes the definition of accuracy for output.size > 1. What is the exact

[GitHub] benqua commented on issue #8297: [scala] Make accuracy idependant of output size (fix #8226)

benqua commented on issue #8297: [scala] Make accuracy idependant of output size (fix #8226) URL: https://github.com/apache/incubator-mxnet/pull/8297#issuecomment-337598650 @javelinjs , you're right, it changes the definition of accuracy for output.size > 1. What is the exact

[GitHub] mseeger commented on issue #8323: clean up math operators

mseeger commented on issue #8323: clean up math operators URL: https://github.com/apache/incubator-mxnet/pull/8323#issuecomment-337591796 I am looking at pages like this: https://stackoverflow.com/questions/15911890/overriding-return-type-in-function-template-specialization

[GitHub] chinakook opened a new issue #8336: Building with libjpeg-turbo error

chinakook opened a new issue #8336: Building with libjpeg-turbo error URL: https://github.com/apache/incubator-mxnet/issues/8336 ## Description I've installed libjpeg-turbo by "sudo apt install libjpeg-turbo8-dev" on Ubuntu 16.04 ## Environment info (Required) ```

[GitHub] tdomhan opened a new pull request #8334: Bugfix: Python 3 compatiblity during optimizer serialization.

tdomhan opened a new pull request #8334: Bugfix: Python 3 compatiblity during optimizer serialization. URL: https://github.com/apache/incubator-mxnet/pull/8334 ## Description ## In python 3 `pickle.dumps` returns a `bytes` object (instead of the `str` object in python 2). The `c_str`

[GitHub] mseeger commented on issue #8323: clean up math operators

mseeger commented on issue #8323: clean up math operators URL: https://github.com/apache/incubator-mxnet/pull/8323#issuecomment-337589379 It is funny this should work. If you define float name(DType a) in the templated class, I thought you cannot specialize this to be double name(double

[GitHub] javelinjs commented on issue #8297: [scala] Make accuracy idependant of output size (fix #8226)

javelinjs commented on issue #8297: [scala] Make accuracy idependant of output size (fix #8226) URL: https://github.com/apache/incubator-mxnet/pull/8297#issuecomment-337584492 Thanks @benqua , I think a better way is to change `sumMetric` to `Double`. The fix here changes the definition

[GitHub] mseeger commented on issue #8323: clean up math operators

mseeger commented on issue #8323: clean up math operators URL: https://github.com/apache/incubator-mxnet/pull/8323#issuecomment-337660985 Independent of this PR, I'd like to do one more change. I am not happy with many of the backward expressions: different to the forward ones, they

[GitHub] piiswrong commented on issue #8337: mx.autograd.grad works or fails depending on use of slices

piiswrong commented on issue #8337: mx.autograd.grad works or fails depending on use of slices URL: https://github.com/apache/incubator-mxnet/issues/8337#issuecomment-337666156 a's first dimension has length 1. Slicing it with 0:4 doesn't really make sense. It should raise an error.

[GitHub] piiswrong commented on issue #8323: clean up math operators

piiswrong commented on issue #8323: clean up math operators URL: https://github.com/apache/incubator-mxnet/pull/8323#issuecomment-337674663 Its not specialization. Its overloading. This is an automated message from the Apache

[GitHub] piiswrong commented on issue #8323: clean up math operators

piiswrong commented on issue #8323: clean up math operators URL: https://github.com/apache/incubator-mxnet/pull/8323#issuecomment-337674663 Its not specialization. Its overloading. Compiler prefers exact match over templates

[GitHub] mseeger commented on issue #8338: master branch cannot build on centos 7 with cuda-8.0

mseeger commented on issue #8338: master branch cannot build on centos 7 with cuda-8.0 URL: https://github.com/apache/incubator-mxnet/issues/8338#issuecomment-337678983 The line in question in tensor_gpu-inl.cuh is: Saver::Save(dst.REval(y, x), exp.Eval(y, x)); Is this

[GitHub] mseeger commented on issue #8323: clean up math operators

mseeger commented on issue #8323: clean up math operators URL: https://github.com/apache/incubator-mxnet/pull/8323#issuecomment-337679717 Well if this works, it is fine. Just make sure that if the arg is double, then the computation is done in double. But I think my new unit tests would

[GitHub] piiswrong commented on issue #8334: Bugfix: Python 3 compatiblity during optimizer serialization.

piiswrong commented on issue #8334: Bugfix: Python 3 compatiblity during optimizer serialization. URL: https://github.com/apache/incubator-mxnet/pull/8334#issuecomment-337664167 You should use py_str from base for this

[GitHub] eric-haibin-lin closed pull request #8307: [sparse] Remove usage of arange in FillDnsZerosRspImpl

eric-haibin-lin closed pull request #8307: [sparse] Remove usage of arange in FillDnsZerosRspImpl URL: https://github.com/apache/incubator-mxnet/pull/8307 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

[GitHub] piiswrong commented on issue #8338: master branch cannot build on centos 7 with cuda-8.0

piiswrong commented on issue #8338: master branch cannot build on centos 7 with cuda-8.0 URL: https://github.com/apache/incubator-mxnet/issues/8338#issuecomment-337669338 @mseeger This is an automated message from the

[GitHub] szha commented on issue #8330: ndarray issue

szha commented on issue #8330: ndarray issue URL: https://github.com/apache/incubator-mxnet/issues/8330#issuecomment-337669799 Here's the path for CPU broadcast_greater. https://github.com/apache/incubator-mxnet/blob/master/python/mxnet/ndarray/ndarray.py#L293-L295

[GitHub] aaronmarkham opened a new issue #8339: data iterators tutorial errors

aaronmarkham opened a new issue #8339: data iterators tutorial errors URL: https://github.com/apache/incubator-mxnet/issues/8339 ## Description Testing [this tutorial](https://github.com/apache/incubator-mxnet/blob/master/docs/tutorials/basic/data.md) on Python 3 shows an error.

[GitHub] mseeger commented on issue #8338: master branch cannot build on centos 7 with cuda-8.0

mseeger commented on issue #8338: master branch cannot build on centos 7 with cuda-8.0 URL: https://github.com/apache/incubator-mxnet/issues/8338#issuecomment-337676796 The warnings relate to smooth_l1_loss in mshadow_op.h. What I did there, is to replace constants like 0.5f by

[GitHub] kpot commented on issue #8337: mx.autograd.grad works or fails depending on use of slices

kpot commented on issue #8337: mx.autograd.grad works or fails depending on use of slices URL: https://github.com/apache/incubator-mxnet/issues/8337#issuecomment-337678517 I'm afraid you miss the point. The failing code works fine being run using ordinary `.backward()` call: ```

[GitHub] tdomhan closed issue #8321: Custom operators with distributed kvstore

tdomhan closed issue #8321: Custom operators with distributed kvstore URL: https://github.com/apache/incubator-mxnet/issues/8321 This is an automated message from the Apache Git Service. To respond to the message, please log

[GitHub] tdomhan commented on issue #8321: Custom operators with distributed kvstore

tdomhan commented on issue #8321: Custom operators with distributed kvstore URL: https://github.com/apache/incubator-mxnet/issues/8321#issuecomment-337566261 I can confirm that this fixes the issue. Thanks a lot! While testing I ran into a python 3 compatibility issue. Here's a fix for

[GitHub] ZiyueHuang opened a new issue #8338: master cannot build on my machine

ZiyueHuang opened a new issue #8338: master cannot build on my machine URL: https://github.com/apache/incubator-mxnet/issues/8338 Note: Providing complete information in the most concise form is the best way to get help. This issue template serves as the checklist for essential

[GitHub] kpot commented on issue #621: Support for other Device Types, OpenCL AMD GPU

kpot commented on issue #621: Support for other Device Types, OpenCL AMD GPU URL: https://github.com/apache/incubator-mxnet/issues/621#issuecomment-337656791 Hi all, Guys, can anyone explain why mxnet still doesn't support OpenCL out of the box, even though it is based on nnvm now

[GitHub] ptrendx commented on issue #8336: Building with libjpeg-turbo error

ptrendx commented on issue #8336: Building with libjpeg-turbo error URL: https://github.com/apache/incubator-mxnet/issues/8336#issuecomment-337658368 Yes, unfortunately libjpeg-turbo version available in Ubuntu package compiles turbojpeg only as a static library (turbojpeg.a) instead of

[incubator-mxnet] branch v0.12.0 updated: Fix unused type warning (#8316)

This is an automated email from the ASF dual-hosted git repository. cjolivier01 pushed a commit to branch v0.12.0 in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git The following commit(s) were added to refs/heads/v0.12.0 by this push: new 4f2af2d Fix unused type

[incubator-mxnet] branch v0.12.0 updated (d84da0a -> cab51bf)

This is an automated email from the ASF dual-hosted git repository. cjolivier01 pushed a change to branch v0.12.0 in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git. from d84da0a fixed broken links. https was pointing to http for mxnet.io (#8300) new 6ba1cde

[incubator-mxnet] 03/03: update ps lite (#8327)

This is an automated email from the ASF dual-hosted git repository. cjolivier01 pushed a commit to branch v0.12.0 in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git commit cab51bf4a7c392a5e2bdf2a6b6d755a50cbb8dee Author: Eric Junyuan Xie

[GitHub] yimyom commented on issue #5326: Train-accuracy=0.000000

yimyom commented on issue #5326: Train-accuracy=0.00 URL: https://github.com/apache/incubator-mxnet/issues/5326#issuecomment-337615967 any hope to have the solution to this problem ? even by using other datasets/learning rate/etc... I keep having exactly a train-accuracy = 0

[incubator-mxnet] 02/03: fluent methods for missed ops (#8329)

This is an automated email from the ASF dual-hosted git repository. cjolivier01 pushed a commit to branch v0.12.0 in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git commit 1135f523f6e0bd9955703bf85ca8ea866e2e8f5f Author: Sheng Zha AuthorDate:

[incubator-mxnet] 01/03: Update rnn.md (#8320)

This is an automated email from the ASF dual-hosted git repository. cjolivier01 pushed a commit to branch v0.12.0 in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git commit 6ba1cde37bd7d17091737d5c4de79875896e1d0a Author: Sheng Zha AuthorDate:

[incubator-mxnet] branch master updated: Fix unused type warning (#8316)

This is an automated email from the ASF dual-hosted git repository. cjolivier01 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 f9e25b4 Fix unused type warning

[GitHub] cjolivier01 closed pull request #8316: Fix unused type warning

cjolivier01 closed pull request #8316: Fix unused type warning URL: https://github.com/apache/incubator-mxnet/pull/8316 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 foreign pull

[GitHub] vinig commented on issue #8231: [MXNet 0.11.0 + RPi 3 + Python 2.7] ndarray unit test fails

vinig commented on issue #8231: [MXNet 0.11.0 + RPi 3 + Python 2.7] ndarray unit test fails URL: https://github.com/apache/incubator-mxnet/issues/8231#issuecomment-337706524 #8292 @larroy thanks for looking into this This

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