ionic serve -l has a few bugs (PART 1)

Note: for support questions, please use one of these channels:
https://forum.ionicframework.com/
http://ionicworldwide.herokuapp.com/
Note: for build related issues you can open up an issue on the ionic-app-scripts repo
https://github.com/driftyco/ionic-app-scripts
Please ensure that you are on the latest version of the CLI.
npm view ionic@latest version
Short description of the problem:
Slider on Android is not working (can't slide, slider works on windows and ios and android on a real device)
What behavior are you expecting?
I can slide...
Steps to reproduce:

Build yourself a slider
ionic serve -l
see for yourself

insert any relevant code between the above and below backticks

Post the output of ionic info below please
Other information: (e.g. stacktraces, related issues, suggestions how to fix, stackoverflow links, forum links, etc)
Cordova CLI: 6.5.0
Ionic Framework Version: 2.0.0
Ionic CLI Version: 2.2.1
Ionic App Lib Version: 2.2.0
Ionic App Scripts Version: 1.0.0
ios-deploy version: 1.9.0
ios-sim version: 5.0.13
OS: macOS Sierra
Node Version: v7.4.0
Xcode version: Xcode 8.1 Build version 8B62

`npm ERR! Make sure you have the latest version of node.js and npm installed.
npm ERR! If you do, this is most likely a problem with the ionic-hello-world package,
npm ERR! not with npm itself.
npm ERR! Tell the author that this fails on your system:
npm ERR!     ionic-app-scripts serve "--v2" "--runLivereload" "--isPlatformServe" "--livereload" "--port" "8100" "--livereload-port" "35729" "--address" "<IP_ADDRESS>" "--isco
rdovaserve" "--nobrowser"
npm ERR! You can get information on how to open an issue for this project with:
npm ERR!     npm bugs ionic-hello-world
npm ERR! Or if that isn't available, you can get their info via:
npm ERR!     npm owner ls ionic-hello-world
npm ERR! There is likely additional logging output above.
npm ERR! Please include the following file with any support request:
npm ERR!     D:\Project\Angular2\test\testBlankFinal\npm-debug.log`
`
Your system information:
ordova CLI: 6.5.0
Ionic Framework Version: 2.0.0
Ionic CLI Version: 2.2.1
Ionic App Lib Version: 2.2.0
Ionic App Scripts Version: 1.0.0
ios-deploy version: Not installed
ios-sim version: Not installed
OS: Windows 10
Node Version: v6.9.4
Xcode version: Not installed`


Deprecated warning for the 'ScriptProcessorNode'

Hey guys,
I am receiving a deprecated warning about the ScriptProcessorNode to be replaced by AudioWorkletNode when I call the start().
A screenshot is attached.
Thank you, :)
https://github.com/ai/audio-recorder-polyfill/blob/d72a8c7e56bc178707c8645568d234090d761a36/index.js#L87

We do not need it for modern Safari anyway

I don't exactly understand the correlation between this warning and modern Safari, but I get this warning too on chromium based browsers.
It would be nice if this could be fixed, since it would be very counterproductive it at some random point they decide to cut support for it (since it is deprecated) and everything just stops working.

I get this warning on chromium based browsers

You need this polyfill for Chromium-based browsers too. Just don't use it (or serve it only for old Safari).

Sorry, I'm not quite sure I follow, what do you mean I need this polyfill for chormium browsers? If I need it like you say, how can I not use it? My use case is to encode the audio to mp3 for every browser. Thanks.

@DasGandlaf Chromium browsers has MediaRecorder support wit the same API.
You can use a simple JS check for very old browsers and load this JS bundle of this polyfill only for these old browsers without MediaRecorder support.

Oh so that is what you mean. The problem is, even up-to-date modern browsers (e.g. Chromium browsers) today cannot record mp3s. I want to use mp3 because it has the best support for playback on every browser & platform. That is why I'm interested in fixing this warning, since I want use this package for modern browsers as well, as they could drop support for ScriptProcessorNode at any update randomly, which is risky.

MP3 encoding in browser is very slow, I really recommend to use browser’s built-in encoding. It will use much less battery from client’s hardware, will be faster and better for ecology. Also, browser’s format is much more compact.
They don’t suppor MP3 by a reason.

A chromium browser records in audio/webm by default as far as I know. The problem is that I have to play it back on various platforms. On iOS safari (which I want to support), it's not possible to playback webm audios. But since chromium browsers would record in webm I wouldn't be able to play them back. And firefox uses yet another format. Is there any alternative than mp3 encoding? I'm trying to implement a chat with voice messages. What do you recommend?


Release Google.Cloud.VMMigration.V1 version 2.2.0

Changes in this release:
New features

AWS as a source (commit 8c6bdf0)
Cycles history (commit 8c6bdf0)
Cycle\Clone\Cutover steps (commit 8c6bdf0)

Created release for Google.Cloud.VMMigration.V1-2.2.0


⚠ Avatar API Endpoint has degraded performance

In 3f98f47, Avatar API Endpoint (https://avatar.roblox.com/v1/avatar-rules) experienced degraded performance:

HTTP code: 200
Response time: 1248 ms

Resolved: Avatar API Endpoint performance has improved in 1438fab after 3 minutes.


When I make this code  , there is some err that I can not work it out .

I use tx1 and follow the 8 steps,  but failed. 16G is enough for this project?
First time , I get the note like this
You are using pip version 9.0.1, however version 10.0.1 is available.
You should consider upgrading via the 'pip install --upgrade pip' command.
so ,I use "pip install torch torchvision" to  update ,from https://pytorch.org/
Second time,  the cmake step looks googd
-- Found Qt4: /usr/bin/qmake-qt4 (found version "4.8.7")
-- Copying /home/ubuntu/jetson-reinforcement/utils/loadImage.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/rand.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/pi.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/commandLine.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/camera/v4l2Camera.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/camera/gstUtility.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/camera/gstCamera.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/cuda/cudaOverlay.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/cuda/cudaRGB.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/cuda/cudaNormalize.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/cuda/cudaResize.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/cuda/cudaFont.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/cuda/cudaMappedMemory.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/cuda/cudaUtility.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/cuda/cudaYUV.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/display/glTexture.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/display/glDisplay.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/display/glUtility.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/input/devJoystick.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/input/devInput.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/input/devKeyboard.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/data/fontmapA.png
-- Copying /home/ubuntu/jetson-reinforcement/utils/data/fontmapB.png
-- Configuring done
-- Generating done
-- Build files have been written to: /home/ubuntu/jetson-reinforcement/build
so I  think I can make it
ubuntu@tegra-ubuntu:~/jetson-reinforcement/build$ make
but ,some thing wrong showed up , and I not sure what should do next.
-- Build files have been written to: /home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/build/THC
[  3%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCHalf.cu.o
[  3%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCBlas.cu.o
[  3%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCReduceApplyUtils.cu.o
[  4%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCSleep.cu.o
[  6%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCStorage.cu.o
[  7%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCStorageCopy.cu.o
[  8%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCTensor.cu.o
[  9%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCTensorCopy.cu.o
[ 10%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCTensorMath.cu.o
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
[ 12%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCTensorMath2.cu.o
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
[ 13%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCTensorMathBlas.cu.o
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
[ 14%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCTensorMathMagma.cu.o
[ 15%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCTensorMathPairwise.cu.o
[ 17%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCTensorMathReduce.cu.o
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
[ 18%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCTensorMathScan.cu.o
[ 19%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCTensorIndex.cu.o
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
/usr/local/cuda/include/thrust/detail/tuple.inl(248) (col. 8): catastrophic error: error while writing generated C file: No space left on device
1 catastrophic error detected in the compilation of "/tmp/tmpxft_000030b5_00000000-9_THCTensorIndex.cpp2.i".
Compilation terminated.
CMake Error at THC_generated_THCTensorIndex.cu.o.cmake:267 (message):
Error generating file
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/build/THC/CMakeFiles/THC.dir//./THC_generated_THCTensorIndex.cu.o
CMakeFiles/THC.dir/build.make:161: recipe for target 'CMakeFiles/THC.dir/THC_generated_THCTensorIndex.cu.o' failed
make[2]: *** [CMakeFiles/THC.dir/THC_generated_THCTensorIndex.cu.o] Error 1
make[2]: *** Waiting for unfinished jobs....
In file included from tmpxft_00002ed5_00000000-4_THCTensorCopy.cudafe1.stub.c:1:0:
/tmp/tmpxft_00002ed5_00000000-4_THCTensorCopy.cudafe1.stub.c:3548:27: fatal error: error writing to /tmp/ccx0ZMYE.s: No space left on device
compilation terminated.
CMake Error at THC_generated_THCTensorCopy.cu.o.cmake:267 (message):
Error generating file
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/build/THC/CMakeFiles/THC.dir//./THC_generated_THCTensorCopy.cu.o
CMakeFiles/THC.dir/build.make:105: recipe for target 'CMakeFiles/THC.dir/THC_generated_THCTensorCopy.cu.o' failed
make[2]: *** [CMakeFiles/THC.dir/THC_generated_THCTensorCopy.cu.o] Error 1
CMakeFiles/Makefile2:67: recipe for target 'CMakeFiles/THC.dir/all' failed
make[1]: *** [CMakeFiles/THC.dir/all] Error 2
Makefile:127: recipe for target 'all' failed
make: *** [all] Error 2
running develop
-- Building version 0.3.0b0+af3964a
running egg_info
Many .h files were labled" No such file or directory"
ubuntu@tegra-ubuntu:~/jetson-reinforcement/build$ make
[ 36%] Built target jetson-utils
[ 38%] Building CXX object CMakeFiles/jetson-reinforcement.dir/c/rlAgent.cpp.o
In file included from /home/ubuntu/jetson-reinforcement/build/pytorch/torch/csrc/THP.h:7:0,
from /home/ubuntu/jetson-reinforcement/c/pyTorch.h:16,
from /home/ubuntu/jetson-reinforcement/c/rlAgent.cpp:6:
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THS/THS.h:4:23: fatal error: THGeneral.h: No such file or directory
compilation terminated.

Hi @yi2ha, you may want to try building on an external SATA drive or USB3 drive.
From: yi2ha<EMAIL_ADDRESS>Sent: Monday, June 18, 2018 7:38 PM
To: dusty-nv/jetson-reinforcement<EMAIL_ADDRESS>Cc: Subscribed<EMAIL_ADDRESS>Subject: [dusty-nv/jetson-reinforcement] When I make this code , there is some err that I can not work it out . (#16)
I use tx1 and follow the 8 steps, but failed. 16G is enough for this project?
First time , I get the note like this
You are using pip version 9.0.1, however version 10.0.1 is available.
You should consider upgrading via the 'pip install --upgrade pip' command.
so ,I use "pip install torch torchvision" to update ,from https://pytorch.org/
Second time, the cmake step looks googd
-- Found Qt4: /usr/bin/qmake-qt4 (found version "4.8.7")
-- Copying /home/ubuntu/jetson-reinforcement/utils/loadImage.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/rand.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/pi.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/commandLine.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/camera/v4l2Camera.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/camera/gstUtility.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/camera/gstCamera.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/cuda/cudaOverlay.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/cuda/cudaRGB.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/cuda/cudaNormalize.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/cuda/cudaResize.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/cuda/cudaFont.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/cuda/cudaMappedMemory.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/cuda/cudaUtility.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/cuda/cudaYUV.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/display/glTexture.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/display/glDisplay.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/display/glUtility.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/input/devJoystick.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/input/devInput.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/input/devKeyboard.h
-- Copying /home/ubuntu/jetson-reinforcement/utils/data/fontmapA.png
-- Copying /home/ubuntu/jetson-reinforcement/utils/data/fontmapB.png
-- Configuring done
-- Generating done
-- Build files have been written to: /home/ubuntu/jetson-reinforcement/build
so I think I can make it
ubuntu@tegra-ubuntu:~/jetson-reinforcement/build$ make
but ,some thing wrong showed up , and I not sure what should do next.
-- Build files have been written to: /home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/build/THC
[ 3%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCHalf.cu.o
[ 3%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCBlas.cu.o
[ 3%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCReduceApplyUtils.cu.o
[ 4%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCSleep.cu.o
[ 6%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCStorage.cu.o
[ 7%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCStorageCopy.cu.o
[ 8%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCTensor.cu.o
[ 9%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCTensorCopy.cu.o
[ 10%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCTensorMath.cu.o
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
[ 12%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCTensorMath2.cu.o
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
[ 13%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCTensorMathBlas.cu.o
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
[ 14%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCTensorMathMagma.cu.o
[ 15%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCTensorMathPairwise.cu.o
[ 17%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCTensorMathReduce.cu.o
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
[ 18%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCTensorMathScan.cu.o
[ 19%] Building NVCC (Device) object CMakeFiles/THC.dir/THC_generated_THCTensorIndex.cu.o
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THC/THCNumerics.cuh(38): warning: integer conversion resulted in a change of sign
/usr/local/cuda/include/thrust/detail/tuple.inl(248) (col. 8): catastrophic error: error while writing generated C file: No space left on device
1 catastrophic error detected in the compilation of "/tmp/tmpxft_000030b5_00000000-9_THCTensorIndex.cpp2.i".
Compilation terminated.
CMake Error at THC_generated_THCTensorIndex.cu.o.cmake:267 (message):
Error generating file
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/build/THC/CMakeFiles/THC.dir//./THC_generated_THCTensorIndex.cu.o
CMakeFiles/THC.dir/build.make:161: recipe for target 'CMakeFiles/THC.dir/THC_generated_THCTensorIndex.cu.o' failed
make[2]: *** [CMakeFiles/THC.dir/THC_generated_THCTensorIndex.cu.o] Error 1
make[2]: *** Waiting for unfinished jobs....
In file included from tmpxft_00002ed5_00000000-4_THCTensorCopy.cudafe1.stub.c:1:0:
/tmp/tmpxft_00002ed5_00000000-4_THCTensorCopy.cudafe1.stub.c:3548:27: fatal error: error writing to /tmp/ccx0ZMYE.s: No space left on device
compilation terminated.
CMake Error at THC_generated_THCTensorCopy.cu.o.cmake:267 (message):
Error generating file
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/build/THC/CMakeFiles/THC.dir//./THC_generated_THCTensorCopy.cu.o
CMakeFiles/THC.dir/build.make:105: recipe for target 'CMakeFiles/THC.dir/THC_generated_THCTensorCopy.cu.o' failed
make[2]: *** [CMakeFiles/THC.dir/THC_generated_THCTensorCopy.cu.o] Error 1
CMakeFiles/Makefile2:67: recipe for target 'CMakeFiles/THC.dir/all' failed
make[1]: *** [CMakeFiles/THC.dir/all] Error 2
Makefile:127: recipe for target 'all' failed
make: *** [all] Error 2
running develop
-- Building version 0.3.0b0+af3964a
running egg_info
Many .h files were labled" No such file or directory"
ubuntu@tegra-ubuntu:~/jetson-reinforcement/build$ make
[ 36%] Built target jetson-utils
[ 38%] Building CXX object CMakeFiles/jetson-reinforcement.dir/c/rlAgent.cpp.o
In file included from /home/ubuntu/jetson-reinforcement/build/pytorch/torch/csrc/THP.h:7:0,
from /home/ubuntu/jetson-reinforcement/c/pyTorch.h:16,
from /home/ubuntu/jetson-reinforcement/c/rlAgent.cpp:6:
/home/ubuntu/jetson-reinforcement/build/pytorch/torch/lib/THS/THS.h:4:23: fatal error: THGeneral.h: No such file or directory
compilation terminated.
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I make the  code on my  TX2 , and Verifying PyTorch  like this:

import torch                                 #####not  pytorch

`nvidia@tegra-ubuntu:~$ python
Python 2.7.12 (default, Dec  4 2017, 14:50:18)
[GCC 5.4.0 20160609] on linux2
Type "help", "copyright", "credits" or "license" for more information.

import torch                                 #####not  pytorch
print(torch.version)
0.3.0b0+af3964a
print('CUDA available: ' + str(torch.cuda.is_available()))
CUDA available: True
a = torch.cuda.FloatTensor(2).zero_()
print('Tensor a = ' + str(a))
Tensor a =
0
0`

the  demos below  work well.
python gym-DQN.py
python gym-RL.py --env=LunarLander-v2 --render
./fruit
./gazebo-arm.sh
$ ./gazebo-rover.sh
but
$ cd jetson-reinforcement/python/A3G $ python main.py --env BipedalWalkerHardcore-v2 --workers 8 --gpu-ids 0 --amsgrad True --model CONV --stack-frames 4
I get some thing like
nvidia@tegra-ubuntu:~$  cd jetson-reinforcement/python/A3Gnvidia@tegra-ubuntu:~/jetson-reinforcement/python/A3G$ python main.py --env BipedalWalkerHardcore-v2 --workers 8 --gpu-ids 0 --amsgrad True --model CONV --stack-frames 4 /usr/local/lib/python2.7/dist-packages/requests/__init__.py:83: RequestsDependencyWarning: Old version of cryptography ([1, 2, 3]) may cause slowdown.   warnings.warn(warning, RequestsDependencyWarning) 2018-08-31 21:29:51,935 : load: True 2018-08-31 21:29:51,937 : tau: 1.0 2018-08-31 21:29:51,937 : stack_frames: 4 2018-08-31 21:29:51,937 : optimizer: Adam 2018-08-31 21:29:51,937 : amsgrad: True 2018-08-31 21:29:51,937 : max_episode_length: 100 2018-08-31 21:29:51,938 : workers: 8 2018-08-31 21:29:51,938 : save_model_dir: trained_models/ 2018-08-31 21:29:51,938 : num_steps: 20 2018-08-31 21:29:51,938 : save_max: True 2018-08-31 21:29:51,938 : seed: 1 2018-08-31 21:29:51,938 : lr: 0.0001 2018-08-31 21:29:51,939 : log_dir: logs/ 2018-08-31 21:29:51,939 : env: BipedalWalkerHardcore-v2 2018-08-31 21:29:51,939 : shared_optimizer: False 2018-08-31 21:29:51,939 : load_model_dir: trained_models/ 2018-08-31 21:29:51,940 : model: CONV 2018-08-31 21:29:51,940 : gpu_ids: [0] 2018-08-31 21:29:51,940 : gamma: 0.99 Process Process-4: Process Process-3: Traceback (most recent call last): Traceback (most recent call last):   File "/usr/lib/python2.7/multiprocessing/process.py", line 258, in _bootstrap   File "/usr/lib/python2.7/multiprocessing/process.py", line 258, in _bootstrap     self.run()     self.run()   File "/usr/lib/python2.7/multiprocessing/process.py", line 114, in run   File "/usr/lib/python2.7/multiprocessing/process.py", line 114, in run     self._target(*self._args, **self._kwargs)     self._target(*self._args, **self._kwargs)   File "/home/nvidia/jetson-reinforcement/python/A3G/train.py", line 64, in train   File "/home/nvidia/jetson-reinforcement/python/A3G/train.py", line 64, in train     player.env.render()     player.env.render()   File "/usr/local/lib/python2.7/dist-packages/gym/core.py", line 153, in render   File "/usr/local/lib/python2.7/dist-packages/gym/core.py", line 153, in render     return self._render(mode=mode, close=close)     return self._render(mode=mode, close=close)   File "/usr/local/lib/python2.7/dist-packages/gym/core.py", line 285, in _render   File "/usr/local/lib/python2.7/dist-packages/gym/core.py", line 285, in _render     return self.env.render(mode, close)     return self.env.render(mode, close)   File "/usr/local/lib/python2.7/dist-packages/gym/core.py", line 153, in render   File "/usr/local/lib/python2.7/dist-packages/gym/core.py", line 153, in render     return self._render(mode=mode, close=close)     return self._render(mode=mode, close=close)   File "/usr/local/lib/python2.7/dist-packages/gym/core.py", line 285, in _render   File "/usr/local/lib/python2.7/dist-packages/gym/core.py", line 285, in _render     return self.env.render(mode, close)     return self.env.render(mode, close)   File "/usr/local/lib/python2.7/dist-packages/gym/core.py", line 153, in render   File "/usr/local/lib/python2.7/dist-packages/gym/core.py", line 153, in render     return self._render(mode=mode, close=close)     return self._render(mode=mode, close=close)   File "/usr/local/lib/python2.7/dist-packages/gym/envs/box2d/bipedal_walker.py", line 440, in _render   File "/usr/local/lib/python2.7/dist-packages/gym/envs/box2d/bipedal_walker.py", line 440, in _render     from gym.envs.classic_control import rendering     from gym.envs.classic_control import rendering   File "/usr/local/lib/python2.7/dist-packages/gym/envs/classic_control/rendering.py", line 23, in <module>   File "/usr/local/lib/python2.7/dist-packages/gym/envs/classic_control/rendering.py", line 23, in <module>     from pyglet.gl import *     from pyglet.gl import *   File "/usr/local/lib/python2.7/dist-packages/pyglet/gl/__init__.py", line 100, in <module>   File "/usr/local/lib/python2.7/dist-packages/pyglet/gl/__init__.py", line 100, in <module>     from pyglet.gl.lib import GLException     from pyglet.gl.lib import GLException   File "/usr/local/lib/python2.7/dist-packages/pyglet/gl/lib.py", line 143, in <module>   File "/usr/local/lib/python2.7/dist-packages/pyglet/gl/lib.py", line 143, in <module>     from pyglet.gl.lib_glx import link_GL, link_GLU, link_GLX     from pyglet.gl.lib_glx import link_GL, link_GLU, link_GLX   File "/usr/local/lib/python2.7/dist-packages/pyglet/gl/lib_glx.py", line 50, in <module>   File "/usr/local/lib/python2.7/dist-packages/pyglet/gl/lib_glx.py", line 50, in <module>     gl_lib = pyglet.lib.load_library('GL')     gl_lib = pyglet.lib.load_library('GL')   File "/usr/local/lib/python2.7/dist-packages/pyglet/lib.py", line 131, in load_library   File "/usr/local/lib/python2.7/dist-packages/pyglet/lib.py", line 131, in load_library     libname = self.find_library(name)     libname = self.find_library(name)   File "/usr/local/lib/python2.7/dist-packages/pyglet/lib.py", line 349, in find_library   File "/usr/local/lib/python2.7/dist-packages/pyglet/lib.py", line 349, in find_library     result = ctypes.util.find_library(path)     result = ctypes.util.find_library(path)   File "/usr/lib/python2.7/ctypes/util.py", line 285, in find_library   File "/usr/lib/python2.7/ctypes/util.py", line 285, in find_library     return _findSoname_ldconfig(name) or _get_soname(_findLib_gcc(name))     return _findSoname_ldconfig(name) or _get_soname(_findLib_gcc(name))   File "/usr/lib/python2.7/ctypes/util.py", line 103, in _findLib_gcc   File "/usr/lib/python2.7/ctypes/util.py", line 103, in _findLib_gcc     stdout=subprocess.PIPE)     stdout=subprocess.PIPE)   File "/usr/lib/python2.7/subprocess.py", line 711, in __init__   File "/usr/lib/python2.7/subprocess.py", line 711, in __init__     errread, errwrite)   File "/usr/lib/python2.7/subprocess.py", line 1235, in _execute_child     errread, errwrite)   File "/usr/lib/python2.7/subprocess.py", line 1235, in _execute_child     self.pid = os.fork()     self.pid = os.fork() OSError: [Errno 12] Cannot allocate memory OSError: [Errno 12] Cannot allocate memory nvidia@tegra-ubuntu:~/jetson-reinforcement/python/A3G$
Are there anything I miss ?


Bulk-update cron schedules

Bulk update cron schedule

Please check the Execution Link of the Pipeline for the Website Draft URL. This is located in the Preview Step behind the Harness VPN and also is available in #hdh_alerts. E.g Website Draft URL: https://unique-id--harness-developer.netlify.app. Current Draft URL is: https://65a7e1064814e0045229838d--harness-developer.netlify.app

Please check the Execution Link of the Pipeline for the Website Draft URL. This is located in the Preview Step behind the Harness VPN and also is available in #hdh_alerts. E.g Website Draft URL: https://unique-id--harness-developer.netlify.app. Current Draft URL is: https://65a88650e8dcda1c1b81100d--harness-developer.netlify.app


Update connectivity-settings.md

As working with multiple customers about below user scenario:
Synapse workspace integrates with Git repo, and public network access is disabled.
Under this situation, we found user can still access to the workspace, it "bypass" the network setting due to studio directly calls Git api. And user can commit, create pull request, create branch and delete branch (all operations that relates to Git), but cannot publish changes to synapse live mode (due to block by firewall as sending request to synapse dev endpoint).
As discussed with Synapse Studio PM, currently this is by design and need to have this important note in the public doc. So request this commit to merge the important notes.

@Danzhang-msft
IMPORTANT: When the changes are ready for publication, add a #sign-off comment to signal that the PR is ready for the review team to merge.
#label:"aq-pr-triaged"
@MicrosoftDocs/public-repo-pr-review-team

@xiaoyuanzi1230 - Can you respond to the requested changes or let us know if you would like us to commit them?
@Danzhang-msft - After the changes are made, please add a sign-off command to signal that the PR is ready to merge.

Hello @Court72 I am good for the suggested changes. I believe we can commit the change. Thanks
And @Danzhang-msft Thanks a lot for the suggestion!

@Danzhang-msft,
I committed your suggestions.
When the changes are ready for publication, add a #sign-off comment to signal that the PR is ready for the review team to merge.

#sign-off


Custom MinHeap and MaxHeap Implementation added

Issue Id you have worked upon -
#119
Briefly explain your program logic -
Your answer
Screenshots(Attach 2 screenshots of your own input and output) -
Attach here

Checklist:
Eg - If your code follow the below guidelines. Kindly change [] to [x]
All the conditions should be fulfilled for considering your code for merging -
[x] I have mentioned the question as comment in my solution file.
[x] My code follows the guidelines of this project.
[x] I have performed a self-review of my own code.
[x] I have commented my code.
[x] My code gives the correct output.
[x] I confirm that I have not copied the code from anywhere. In case its found that I have copied I can be banned from the repository.
[x] I affirm that I strictly follow contributing guidelines and code of conduct.

@Monica-Chhabria,
Kindly explain your program logic brieflt in the above PR template.
Also comment you code well.

commented code and added program logic


Create tests for PreferenceModel

Fixes #113
Note: the test test_get_slot_preference depends on PR #117.

I changed the name of the tests where an exception is expected for better readability.


.NET 8 LTS build breaks

Hello can you help with the build update, my laptop shipped with 8 LTS

We will migrate to net8, but not with high priority.
If your PC is missing net6, just download the SDK from Microsoft and you're good to go.

The project is migrated to net8.0 in v4.0.0


date example in readme is incirrect.

Hi,
the example date in the readme file is incrrect. I don't know if this is a typo of something that reflects the code too...
you have: jan 1th 2018; 1 jan 2018
it should be: jan 1st 2018; 1st jan 2018
--also: you would only really drop the st/nd/rd/th if the month is a number too.

Hi.
Yes, this is a typo. This package does not do any translating itself, it uses the Carbon translations. Thanks for noticing, I will change this in the documentation.


Make seasons configurable

A NumericEntityRecognizer can be passed optionally into the CluProcessor constructor.  If passed, it will replace a default NumericEntityRecognizer in
  lazy val numericEntityRecognizer: NumericEntityRecognizer =
      numericEntityRecognizerOpt.getOrElse(NumericEntityRecognizer())

The default one uses a resource "org/clulab/numeric/SEASON.tsv" and we'd like to be able to configure this.  It seems that there should only be one NumER and it has multiple kbs of which this resource will be one.  It shouldn't be separated into its own "thing" so that there are multiple, specialized NumERs.
It seems to me that NumericEntityRecognizer.mkLexiconNer needs to take an argument for this resource (perhaps forwarded by the apply method), one that defaults to the standard tsv file, so that it can be slipped into the constructor call for the LexiconNER, like this:
  // this matches essential dictionaries such as month names
  def mkLexiconNer(customSeasons: String = "org/clulab/numeric/SEASON.tsv"): LexiconNER = {
    val kbs = Seq(
      "org/clulab/numeric/MONTH.tsv",
      "org/clulab/numeric/MEASUREMENT-UNIT.tsv",
      customSeasons
    )
    val isLocal = kbs.forall(new File(resourceDir, _).exists)
    LexiconNER(
      kbs,
      Seq(
        false, // false = case sensitive matching
        true,
        true
      ),
      baseDirOpt = if (isLocal) Some(resourceDir) else None
    )
  }

The question might be how the string gets that far and there are unfortunately two options:
One is to pass the same optional customSeasons String with a default value to the CluProcessor constructor and have it, assuming there is no numericEntityRecognizerOpt, use the string to construct the (almost) default one.  This is a messy kind of a double optional in which one is dependent on the other, but it is easy for the caller.
The other is to use the customSeasons String to construct the desired NumericEntityRecognizer in advance and then pass it as the numericEntityRecognizerOpt.  This is slightly more work for the caller, but it seems cleaner.
Mihai wanted the first option.  I'm double checking and making sure I understand it correctly.

@kwalcock : I'll let you decide on this. I can leave with either one :)

If the optional, custom resource is specified with the CluProcessor and if there is already a numericEntityRecognizerOpt specified, we would not try to somehow edit that NumER so that it used the custom resource.  This would be an error.  What we really want is either a numericEntityRecognizer or a customSeasons, but that is about as difficult to do as the second option in which the customSeason is used to create the numericEntityRecognizer.  For the first option there is an effective
require(numericEntityRecognizerOpt.isEmpty || customSeasonsOpt.isEmpty)

It is looking more complicated.  There is a SeasonNormalizer that wants to use the same SEASON.tsv file that the default NumericEntityRecognizer does.  If the latter is customized with a different seasons file, I assume that the SeasonNormalizer should take it into account.  Unfortunately the SeasonNormalizer isn't even a class.  It is a (companion) object.  It is initialized on demand and cannot take any arguments for the constructor.  There is not a good way to pass information at runtime from the NumericEntityRecognizer to the SeasonNormalizer.  A global, mutable variable is a possibility, but that is a last resort.
The SeasonNormalizer is used from mentions.package.scala (unfortunately one of the strange package objects) which calls SeasonNormalizer.norm() and SeasonNormalizer.adjustYearRange().  This is a package object calling a method on a companion object.  Methods in the package IIRC are dynamically loaded and called by Odin based on rules with actions like
- name: date-range-1
  priority: ${rulepriority}
  label: DateRange
  type: token
  example: "It took place between 12 May 2000 and 12 June 2020"
  action: mkDateRangeMention
  pattern: |
    /(?i)between/ @date1:Date /(?i)(and|to)/ @date2:Date

It looks like the NumericEntityRecognizer creates the Odin ExtractorEngine that will invoke the actions.  Perhaps that can be a custom ExtractorEngine that has a little inside information so that the SeasonNormalizer can be called in a way that uses the correct tsv file...

Agreed.
Maybe the SeasonNormalizer can be made a class, and added as a field in NumericEntityRecognizer, so your option 2 still holds?

Thanks for the hint!  If SeasonNormalizer can be a class, then I have a plan, convoluted, but a plan.

The NumericEntityRecognizer is supposed to be reloadable.  It looks like the reload was intended to account for changes made in the rules, but not changes made to the lexiconNER or the actions, even though both of these are influenced by the contents of files that might need to be reloaded.  @MihaiSurdeanu, is it OK to leave it this way?  The SEASON.tsv ends up affecting both the lexiconNER and also the actions via the SeasonNormalizer that uses the comments in the file.  It gets complicated and is probably not even necessary.

It's fine for now. Thanks for checking!
(The key info to debug are the rules. As long as those are reloadable, I'm Ok)

Part of the discussion above is a little off the mark because the main constructor for CluProcessor is protected.  The simplified, public version does not have the numericEntityRecognizerOpt.  I've used a seasonPathOpt there and am converting it into the numericEntityRecognizerOpt for the call to the protected version.


Rotated interactive forms matrix bug

Attach (recommended) or Link to PDF file here:
Subcontract-Performance-Bond.pdf
Configuration:

Web browser: Any
Operating system and its version: Any
PDF.js version: Latest
Is a browser extension: no

Steps to reproduce the problem:

Render the pdf with renderInteractiveForms = true

What is the expected behavior?
The text in the inputs not be incorrectly rotated
What went wrong?
The default viewport from the PDF has a rotation of 270. The container uses the transform to create a matrix transformation to position the input elements. This would be all well and good, but HTML inputs always start with text alignment left to right, while the annotation logic for the widgets incorrectly assumes the text alignment matches the page's rotation property. This results in an incorrect text alignment of the text:
https://imgur.com/a/y7MHp1Q
What really has to happen is that the matrix needs to be pre-rotated so that it's alignment is left to right (0), and the css matrix transformations are performing no skewing on the container contained in _createContainer for widgets.
I don't know if that means having a overriden _createContainer in WidgetAnnotationElement or what the best way to pre-rotate the matrix for the container is.
And if 'pre-rotate the matrix' isn't the right term, I apologize, but matrixes are not really my strong suite.
Subcontract-Performance-Bond.pdf
Thanks!
Ned Andre
(btw I love the new forms rendering layer. Much easier to work with and override)

Duplicate of #9596.


Delete RUNTIME-EXCEPTION

As the project is now MIT-licensed, this exception no longer applies.

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.

Hi @stuartpb , this exception applies to the core NectarCPP (https://github.com/nectar-lang/NectarCPP)


Refactoring ConvNeXt code

Refactor the ConvNeXt model from PyTorch to use symmetric padding and quantile regression

FYI, I added generic encoder and decoder classes and a wrapper for the ConvNext blocks from torchvision in quantnn. It might be worth starting out with those and only add the symmetric padding if it's really required.


Wink hub reboots while running wink-mqtt

I have a rooted wink hub running the latest firmware (3.4.4).  When I run ./mqtt start I see the 'Starting mqtt...' message and my mqtt broker log shows the connection and subscription requests.  I can publish a message from another mqtt client and the wink hub will turn on/off a Z-Wave device as requested.  Everything seems to be working as expected.
The problem is, the wink hub will do a full reboot a few minutes after starting wink-mqtt.  If I don't start wink-mqtt, the same hub will run indefinitely as expected.  The reboot doesn't seem linked to sending or receiving messages - it will happen if I simply run ./mqtt start then leave the wink basically idle.  I started the app from a ssh session and checked the log from the serial terminal during the run - no errors or anything suspicious.
Any thoughts on how I might find some clues about what is causing the reboot?

I think its a CPU/resource utilization problem - there's some lines in....... monitrc? about auto-rebooting if the CPU is above a certain amount for some amount of time (might be wrong about the time portion - it may just reboot).
I was never able to actually get this working on.. I want to say 3.3xsomething
You might be able to get around it by commenting out the lines in (I think) monitrc, though given the lack of heat sinks and cooling, it might be related to keeping the CPU from doing bad things if they didn't think to include any thermal protection (the poor mans temp control lol).  Have to test that theory :-P
As an aside, I'm curious if any of this going to get updated for the newer firmware(s) or is this project going to get dropped in lieu of the new wink hub?

This project has died out.  I haven't kept up with the firmware updates.
On Tue, Jan 3, 2017 at 12:58 PM causalloop<EMAIL_ADDRESS>wrote:

I think its a CPU/resource utilization problem - there's some lines
in....... monitrc? about auto-rebooting if the CPU is above a certain
amount for some amount of time (might be wrong about the time portion - it
may just reboot).
I was never able to actually get this working on.. I want to say
3.3xsomething
You might be able to get around it by commenting out the lines in (I
think) monitrc, though given the lack of heat sinks and cooling, it might
be related to keeping the CPU from doing bad things if they didn't think to
include any thermal protection (the poor mans temp control lol). Have to
test that theory :-P
As an aside, I'm curious if any of this going to get updated for the newer
firmware(s) or is this project going to get dropped in lieu of the new wink
hub?
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😞
If you don't mind me asking, did you move on to a different platform etc or did you just lose motivation (totally understandable all things considered)

Thanks danielolson13 for the work you've done.  I don't think it's far from working with the latest firmware.  It's completely functional on 3.4.4 until the reboot.
I think causalloop is correct about the reboot coming from monitrc.  At first glance, I see reboots dependant on the amount of memory used by node processes.  It seems likely that some resource is being hit harder than the original devs expected.  I'm going to try upping limits and/or commenting out reboots in monitrc to see if I can keep it running.

Looks like the reboot is triggered by a high memory usage situation in 3.4.4.  When I change the monitrc reboot actions to alerts, I see monit log errors about memory usage that would have definitely triggered a reboot.  The interesting thing is, after I had left the wink running for about a day without running wink-mqtt, the errors triggered immediately and wink-mqtt would abort.  After a reboot, wink-mqtt will start and run for several hours before the high memory usage alerts are triggered.  It seems there is a memory leak in the 3.4.4 firmware or at least some process that gradually consumes more memory.
I'll do some more digging to see if I can find the process that's eating memory.

Maybe a cron job of some sort that restarts 'x' service intermittently would help prevent that - kill the leak before it gets noticed etc.
On Wed, Jan 4, 2017 08:33:56, jfath<EMAIL_ADDRESS>wrote:
Looks like the reboot is triggered by a high memory usage situation in 3.4.4. When I change the monitrc reboot actions to alerts, I see monit log errors about memory usage that would have definitely triggered a reboot. The interesting thing is, after I had left the wink running for about a day without running wink-mqtt, the errors triggered immediately and wink-mqtt would abort. After a reboot, wink-mqtt will start and run for several hours before the high memory usage alerts are triggered. It seems there is a memory leak in the 3.4.4 firmware or at least some process that gradually consumes more memory.
I'll do some more digging to see if I can find the process that's eating memory.
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My Wink got so messed up after the last update that I gave up on it and
upgraded to the Wink 2 for my primary automation.
There are memory problems with my application but I don't know if it's the
version of Node installed on the wink or my poor programming, probably the
programming. Hitting the database for the current state of devices is
memory intensive and can cause issues. I never really got around the memory
usage issues. I'd welcome any pull requests. Need to dig back into my old
Wink and get it going again.
Wish that Wink would just open up their local control API.
On Wed, Jan 4, 2017 at 11:38 AM causalloop<EMAIL_ADDRESS>wrote:

Maybe a cron job of some sort that restarts 'x' service intermittently
would help prevent that - kill the leak before it gets noticed etc.
On Wed, Jan 4, 2017 08:33:56, jfath<EMAIL_ADDRESS>wrote:
Looks like the reboot is triggered by a high memory usage situation in
3.4.4. When I change the monitrc reboot actions to alerts, I see monit log
errors about memory usage that would have definitely triggered a reboot.
The interesting thing is, after I had left the wink running for about a day
without running wink-mqtt, the errors triggered immediately and wink-mqtt
would abort. After a reboot, wink-mqtt will start and run for several hours
before the high memory usage alerts are triggered. It seems there is a
memory leak in the 3.4.4 firmware or at least some process that gradually
consumes more memory.
I'll do some more digging to see if I can find the process that's eating
memory.
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This may be a bit out in left field.. I wonder if it might be possible to set up either a pi or a vm or whatever and "clone" the wink hub - I say "clone" as a sort of placeholder for an over simplified first step - basically my thinking is if its a memory issue, and we obviously can't give it more.. why not move the hungry things to something that can handle it.  A file share mounted via ssh would I believe be possible, and I imagine some of the processes don't actually need the hardware in the hub.. maybe apron's commands can be piped somehow (ssh over an already unreliable wifi may not be the best solution, but we do have UART.. file shares via UART?  :-P )
A bit out of the box, I know, but in principal, it seems like we just need to trick it into doing our bidding... and/or make it think its running on the hub..  I mean, if apron's looking for an "attached" device - for giggles, lets say 'ttyAM1' - couldn't that be mounted to a shared folder via a symlink or somesuch?  (I haven't even looked up any of this so I'm literally just sort of stream of thought-ing here).
Point being, whatever's bogging things down - assuming the leak can't be plugged so easily - it seems like thing should be offload-able, or even turned off.  For instance, I really only keep my wink around to control lutron stuff.. so potentially I could prevent Zigbee and Zwave stuff from starting their services etc.  More I imagine if I wanted to get nitpicky (do I really need a process for the RGB led?)
Anyway, food for thought..
On Wed, Jan 4, 2017 08:50:03, Dan Olson<EMAIL_ADDRESS>wrote:
My Wink got so messed up after the last update that I gave up on it and
upgraded to the Wink 2 for my primary automation.
There are memory problems with my application but I don't know if it's the
version of Node installed on the wink or my poor programming, probably the
programming. Hitting the database for the current state of devices is
memory intensive and can cause issues. I never really got around the memory
usage issues. I'd welcome any pull requests. Need to dig back into my old
Wink and get it going again.
Wish that Wink would just open up their local control API.
On Wed, Jan 4, 2017 at 11:38 AM causalloop<EMAIL_ADDRESS>wrote:

Maybe a cron job of some sort that restarts 'x' service intermittently
would help prevent that - kill the leak before it gets noticed etc.
On Wed, Jan 4, 2017 08:33:56, jfath<EMAIL_ADDRESS>wrote:
Looks like the reboot is triggered by a high memory usage situation in
3.4.4. When I change the monitrc reboot actions to alerts, I see monit log
errors about memory usage that would have definitely triggered a reboot.
The interesting thing is, after I had left the wink running for about a day
without running wink-mqtt, the errors triggered immediately and wink-mqtt
would abort. After a reboot, wink-mqtt will start and run for several hours
before the high memory usage alerts are triggered. It seems there is a
memory leak in the 3.4.4 firmware or at least some process that gradually
consumes more memory.
I'll do some more digging to see if I can find the process that's eating
memory.
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I wasn't completely clear in stating memory usage steadily increases when wink-mqtt isn't running at all.  I think the wink firmware has a problem and the monit reboot is a brute force fix.  That threshold is reached more quickly when wink-mqtt is running due to expected increased memory usage.
If I can figure out the offending process and restart that process instead of doing a full reboot, we may have a simple solution.

Interesting, how are you monitoring that? Are you just periodically checking top/ps or do you have some method (I'm no Linux guru) to log it? I ask because I don't think mines been doing that... but I also may have monkeyed with something and forgot.. (im terrible about keeping track of that stuff... too impatient lol)
On Wed, Jan 04, 2017 at 11:56am, jfath <<EMAIL_ADDRESS><EMAIL_ADDRESS>> wrote:
I wasn't completely clear in stating memory usage steadily increases when wink-mqtt isn't running at all. I think the wink firmware has a problem and the monit reboot is a brute force fix. That threshold is reached more quickly when wink-mqtt is running due to expected increased memory usage.
If I can figure out the offending process and restart that process instead of doing a full reboot, we may have a simple solution.
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I first saw the steady memory increase when I changed the monitrc reboots to alerts.  Eventually, monit started logging memory usage alerts: 75%, 75.1%, 75.2% ....
I also checked top with wink-mqtt running and neither wink-mqtt.js nor server.js (the main node based process) were increasing in memory usage, so I think it's something else.  I turned on logging in my terminal and ran top -b to capture about 10 minutes of top measurements.  When I get a few minutes, I need to go through the log and see if I can pick out the offending process.

@jfath Were you able to find anything out here? Tired of my hub rebooting at night and turning all of my lights on (so tired in fact that I am about to just buy a zigbee/zwave stick).

First off, thanks for this great project Dan. I know I am super late to this. Anyways, I faced similar instability issues (reboots etc.) on my wink and my hunch was a memory leak in nodejs was the culprit. I rewrote part of the application in golang and I am having good results stability wise. Hope this can help others too: https://github.com/sandman0/wink-mqtt-go


hello, I have met this error.Does i lack of anything about the pretrained model?

Traceback (most recent call last):
File "/home/LasUIE/run_finetune.py", line 289, in
model_wrapper = ModelWrapper(**config)
File "/home/LasUIE/run_finetune.py", line 46, in init
self.model = get_model(self.model_type, self.lm_location)
File "/home/LasUIE/run_finetune.py", line 35, in get_model
return model_dict[model_type].from_pretrained(lm_location)
File "/home/anaconda3/envs/lasuie/lib/python3.8/site-packages/transformers/modeling_utils.py", line 2795, in from_pretrained
) = cls._load_pretrained_model(
File "/home/anaconda3/envs/lasuie/lib/python3.8/site-packages/transformers/modeling_utils.py", line 3008, in _load_pretrained_model
raise ValueError(
ValueError: The state dictionary of the model you are trying to load is corrupted. Are you sure it was properly saved?

Hi, if you are using the framework the first time, you need to first train (finetune) the model, then the second time you may load from checkpoints for incremental fine-tuning or inference.
So just mark the argument load_from_checkpoint as False.

Thank you for your reply. I have checked the parameters. The load_from_checkpoints is seted False.
I just follow the README. It says "can directly make 2.3.2 finetuning without post-training."
So I run the finetune program.
When it runs here,it error.
if args.load_from_checkpoint:
model_wrapper = ModelWrapper.load_from_checkpoint(args.model_checkpoint)
else:
model_wrapper = ModelWrapper(**config)//this!!!
Does i need to download the " google/flan-t5-base" myself? Does it can download automaticaly when running?
Besides, when will you release the pretrained checkpoint? Looking forward your reply.
王梦影
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------------------ 原始邮件 ------------------
发件人:                                                                                "ChocoWu/LasUIE"                                                                                @.>;
发送时间: 2023年4月21日(星期五) 下午3:03
@.>;
<EMAIL_ADDRESS>主题: Re: [ChocoWu/LasUIE] hello, I have met this error.Does i lack of anything about the pretrained model? (Issue #4)
Hi, if you are using the framework the first time, you need to first train (finetune) the model, then the second time you may load from checkpoints for incremental fine-tuning or inference.
So just mark the argument load_from_checkpoint as False.
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Hi, if you denote google/flan-t5-base in config.json, then it should be automatically downloaded.
The post-trained checkpoint will be considered to be released the next day, as we are constructing the demo system. But you may directly use the existing LM (e.g., T5-base), and I suggest you do the fine-tuning yourself with your datasets.

Hello, I have confirmed again and again that there are no issues with the settings of the config file or parameters. The problem lies in downloading the flan-t5-base model. Let me list my debugging process for you. Can you help me see where the problem is? thank you very much indeed.
the red line is the step that the program is running.
if args.load_from_checkpoint://(False)
model_wrapper = ModelWrapper.load_from_checkpoint(args.model_checkpoint)
else:
model_wrapper = ModelWrapper(**config)class ModelWrapper(LightningModule):
def init(self, dataset, model_type, task_type, lm_location, learning_rate, other_learning_rate, adam_epsilon, warmup_steps, weight_decay,
train_batch_size, val_batch_size, max_length, gradient_accumulation_steps, is_train=True):
super(ModelWrapper, self).init()
self.save_hyperparameters()
self.model_type = model_type
self.task_type = task_type
self.lm_location = lm_location
self.model = get_model(self.model_type, self.lm_location)
def get_model(model_type, lm_location):
return model_dict[model_type].from_pretrained(lm_location)
then it goes to the "python3.8/site-packages/transformers/modeling_utils.py".
if dtype_orig is not None:
torch.set_default_dtype(dtype_orig)
(
model,
missing_keys,
unexpected_keys,
mismatched_keys,
offload_index,
error_msgs,
) = cls._load_pretrained_model(//跳转
model,
state_dict,
loaded_state_dict_keys,  # XXX: rename?
resolved_archive_file,
pretrained_model_name_or_path,
ignore_mismatched_sizes=ignore_mismatched_sizes,
sharded_metadata=sharded_metadata,
_fast_init=_fast_init,
low_cpu_mem_usage=low_cpu_mem_usage,
device_map=device_map,
offload_folder=offload_folder,
offload_state_dict=offload_state_dict,
dtype=torch_dtype,
load_in_8bit=load_in_8bit,
keep_in_fp32_modules=keep_in_fp32_modules,
)
Make sure we are able to load base models as well as derived models (with heads)
start_prefix = ""
model_to_load = model
if len(cls.base_model_prefix) > 0 and not hasattr(model, cls.base_model_prefix) and has_prefix_module:
start_prefix = cls.base_model_prefix + "."
if len(cls.base_model_prefix) > 0 and hasattr(model, cls.base_model_prefix) and not has_prefix_module:
model_to_load = getattr(model, cls.base_model_prefix)
base_model_expected_keys = list(model_to_load.state_dict().keys())
if any(key in expected_keys_not_prefixed and key not in base_model_expected_keys for key in loaded_keys):
raise ValueError(
"The state dictionary of the model you are trying to load is corrupted. Are you sure it was "
"properly saved?"
)
where it error as follows:
File "/home/anaconda3/envs/lasuie/lib/python3.8/site-packages/transformers/modeling_utils.py", line 2795, in from_pretrained
    ) = cls._load_pretrained_model(File"/home/anaconda3/envs/lasuie/lib/python3.8/site-packages/transformers/modeling_utils.py", line 3008, in _load_pretrained_model
    raise ValueError(
ValueError: The state dictionary of the model you are trying to load is corrupted. Are you sure it was properly saved?
王梦影
@.***

------------------ 原始邮件 ------------------
发件人:                                                                                "ChocoWu/LasUIE"                                                                                @.>;
发送时间: 2023年4月21日(星期五) 下午3:27
@.>;
<EMAIL_ADDRESS>主题: Re: [ChocoWu/LasUIE] hello, I have met this error.Does i lack of anything about the pretrained model? (Issue #4)
Hi, if you denote google/flan-t5-base in config.json, then it should be automatically downloaded.
The post-trained checkpoint will be considered to be released the next day, as we are constructing the demo system. But you may directly use the existing LM (e.g., T5-base), and I suggest you do the fine-tuning yourself with your datasets.
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That's pretty weird. Try manually download the Flan-T5-base model yourself at one specific fold. Then specify the LM-file with your own path.

Seems solved. I'll close this one.


Update Facebook login to expect name

Facebook stopped returning first_name and last_name, and instead returns only a single name field. Our User model requires both first_name and last_name.
A better fix would be to remove this requirement from our User model and require only a name. But an easier fix for now is to just best effort parse the returned name into the format that we need.

Awesome! thx for the fix :)


Add notes endpoints

Add create and edit for notes

Note -- haven't addressed or tested validation errors yet.


DS - Discovery - Component search and statistic gathering

Description
This discovery ticket is to determine the feasibility and strategy for a tool that will allow the design system team to search a codebase and identify usage statistics for components.
As a secondary use for the tool it should accept a text string search option to be used when trying to find instances of a component that isn't yet added into the system.
Tool details:

[ ] Web App that searches a codebase for instances of a component (Flagship only at first)
[ ] Be able to pull usage statistics out of the app to be used in reporting and potentially displayed in the documentation

AC:

[ ] Determine and document high-level technical strategy for creating the tool
[ ] Document open questions
[ ] Create stub stories for implementation

Notes & Open Questions

Dependencies/Roadblocks:

Any internal/external dependencies?
Test accounts needed?

Does this require QA?

Dev Notes:

Ticket Checklist

[ ] Acceptance criteria defined
[ ] Labels added (front-end, back-end, feature)
[ ] Linked to an Epic

Potential tool we can use: https://github.com/moroshko/react-scanner


Rename BlogPage component

Self explanatory, appears to have been pasted from pages/about but not renamed.

oops - good catch, thank you :)


Add function to send whatsapp message with twilio

Implemented appwrite/appwrite#1913 in Deno.

[x]   Tested
[x]   Documented

@lucaoskaique closing this PR for now since there has been no activity in quite a long time. Feel free to reopen it when you're ready to start working on it once again. 🙂


Admin: Authorization

This issue is from the card created by Alastair on the LeanKitKanBan board we were using.

Which charities can I access?  Keep this separate from Authentication for maximum flexibility

Moved to https://github.com/GiveCampUK/GiveCRM.Admin/issues/14


Feature Request: Run Command Sensor

Would it be possible to provide a sensor with the command line output from a CustomCommand run?

Thanks for creating an issue! This would be pretty cool as it makes possibilities endless.

Thanks for creating an issue! This would be pretty cool as it makes possibilities endless.


ERROR: 'episodes'

i keep getting this error everytime i try to download an anime: ERROR: 'episodes'.
Can someone help me?

Post detailed logs with anime -ll DEBUG dl ... with ... being the rest of the command you are using. I cannot debug your issue without those logs.

Post detailed logs with anime -ll DEBUG dl ... with ... being the rest of the command you are using. I cannot debug your issue without those logs.

 [Query: '...']
+--------+---------------------------+--------+
|      5 | Accel World               |        |
|      4 | Absolute Duo              |        |
|      3 | Toaru Majutsu no Index II |        |
|      2 | Toaru Majutsu no Index    |        |
|      1 | 07-Ghost                  |        |
|--------+---------------------------+--------|
|   SlNo | Title                     | Meta   |
+--------+---------------------------+--------+
Enter the anime no:  [1]:

I don't see any issues with what you posted, but I mean that you'd substitute the .... Eg if the original command was
anime dl "neverland" --provider dubbedanime -c 1 -e 1 the updated command would be
anime -ll DEBUG dl "neverland" --provider dubbedanime -c 1 -e 1

I don't see any issues with what you posted, but I mean that you'd substitute the .... Eg if the original command was
anime dl "neverland" --provider dubbedanime -c 1 -e 1 the updated command would be
anime -ll DEBUG dl "neverland" --provider dubbedanime -c 1 -e 1

oops my bad thanks btw

why did this close? is it solved?


Show title for the Location information

Currently, there is no "title" for the information storage in the location field. So when it is displayed, the result is confusing (see screenshot).
The proposal are:

add more margin on top
add a title (fixed "Location", or configurable by Drupal setting)

The template file is: /usr/share/drupal7/sites/all/modules/location/locations.tpl.php

Just to add to this, now it seems to somehow show up under the 'Phone number' field:

https://landportal.info/organization/agricultural-applied-economics-association
Can we simply add a header saying 'Location'?
Thanks!

this page still does not look awesome, but the location field label is there apparently (on beta)


[2.2.x] Fixed #30216 -- Doc'd that BooleanField is no longer blank=True in Django 2.1.

Changed de documentation to alert for this implicit behavior change.
Following the /pull/11831 comments

@davidmgvaz Thanks! Welcome aboard :boat:

Well done @davidmgvaz. Super!

Thanks, it is nice to finally be a part of this


Grant controller abilit to update service/plan status

Fixes a bug where the controller, as deployed by the helm chart, could not update the status subresource of ClusterServiceClasses and ClusterServicePlans, meaning that handling of removed service/plans from broker catalog was not working correctly.

LGTM


Feature Request - Session Migration between clustered brokers

is this implemented in 0.9.0 alpha? as following entry in the change log
Feature: Support to resume a persistent session on other clustered node.

@sufish, supported in 0.9.0

'Session across nodes' feature has been implemented in 1.1.x release.


Add moon phase to scheduler #239

Added moonops table
Added configmoonop action and modified removeop and pauseop to interact with the moon operations
Removed action confirm this action wasn't helping to confirm the correct execution, it was just consuming cpu time

Modified contracts:

[ ] Scheduler

No migrations nor permissions update is needed

Merged

Deployed