[move-prover] include the experimental code in df for verification

Verification of diem-framework experimental code is turned-off
in #9718 due to symbolic links not being properly handled. This is
wrong and in fact, has caused some specifications to be violated.
This commit re-worked the move prover testsuite to include the
experimental code for verification.
The offending module is the newly refactored DiemAccount.move in
the experimental code. I'll leave it to the refactoring team
(@tzakian @emmazzz) to double check. The CI should fail with the
verification error.
To reproduce the result, pull down this PR locally and run
cargo test DiemAccount.move in language/move-prover/tests.
The DiemAccount.move in diem_core passes and the version in
diem_exp fails.
Motivation
Cover the diem-framework experimental folder for verification
Have you read the Contributing Guidelines on pull requests?
Yes
Test Plan
CI

/land

:broken_heart: Test Failed - ci-test

Test failure at tear down step... try again
/land

:broken_heart: Test Failed - ci-test

/land

:exclamation: Land has been canceled due to this PR being updated with new commits. Please issue another Land command if you want to requeue this PR.

failure of the CI is due to an error where the experimental df release is not updated for docs and built artifacts... now needs a re-stamping... @wrwg @tzakian

/land

:broken_heart: Test Failed - ci-test

Now this is faucet issue..., try again
/land


Add topic "Static code analysis"

Please confirm this pull request meets the following requirements:

[x] I followed the contributing guidelines: https://github.com/github/explore/blob/main/CONTRIBUTING.md.
[x] I am not the sole author or employee of a company who created the topic or collection I'm changing.

Which change are you proposing?

[ ] Suggesting edits to an existing topic or collection
[x] Curating a new topic or collection
[ ] Something that does not neatly fit into the binary options above

Editing an existing topic or collection
I'm suggesting these edits to an existing topic or collection:

[ ] Image (and my file is *.png, square, dimensions 288x288, size <= 75 kB)
[ ] Content (and my changes are in index.md)

Please replace this line with an explanation of why you think these changes should be made.

Curating a new topic or collection

[x] I've formatted my changes as a new folder directory, named for the topic or collection as it appears in the URL on GitHub (e.g. https://github.com/topics/[NAME] or https://github.com/collections/[NAME])
[ ] My folder contains a *.png image (if applicable) and index.md
[x] All required fields in my index.md conform to the Style Guide and API docs: https://github.com/github/explore/tree/main/docs

Static code analysis is a common practise performed by developers for code in a wide variety of programming languages.

Something that does not neatly fit into the binary options above

[x] My suggested edits are not about an existing topic or collection, or at least not a single one
[ ] My suggested edits are not about curating a new topic or collection, or at least not a single one
[x] My suggested edits conform to the Style Guide and API docs: https://github.com/github/explore/tree/main/docs

Please replace this line with an explanation of your proposed changes.

Please note: we will close your PR without comment if you do not check the boxes above and provide ALL requested information.

My pleasure 😃


doc: fix README.rst

This PR fixes #138
Signed-off-by: Roy Vicente<EMAIL_ADDRESS>

 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.


Cannot restart docker service inside the container

Dear @jpetazzo,
I want to add insecure-registry flag to DOCKER_OPTS under /etc/default/docker and restart the docker service.
When I do service docker restart its giving me:
mount: cgroup already mounted or cpu busy mount: according to mtab, cgroup is already mounted on /sys/fs/cgroup/cpu,cpuacct rmdir: failed to remove 'cpu': Not a directory mount: cgroup already mounted or cpuacct busy mount: according to mtab, cgroup is already mounted on /sys/fs/cgroup/cpu,cpuacct rmdir: failed to remove 'cpuacct': Not a directory mount: cgroup already mounted or net_cls busy mount: according to mtab, cgroup is already mounted on /sys/fs/cgroup/net_cls,net_prio rmdir: failed to remove 'net_cls': Not a directory mount: cgroup already mounted or net_prio busy mount: according to mtab, cgroup is already mounted on /sys/fs/cgroup/net_cls,net_prio rmdir: failed to remove 'net_prio': Not a directory
back.
When I do service docker status it says: Docker is not running. However I can run docker ps e.g.
Could you please help?
regards

The service ... command works with an init system like upstart or systemd. In DinD, the Docker Engine is started directly. To change the Docker Engine flags, you could change the CMD of your image instead.


Inherit docstrings from numpy functions

Calling import autograd.numpy as np does not inherit numpy docstrings (see below)
Autograd:

Standard numpy:

Would it be possible to use functools.wraps in some clever way [1] as to preserve the docstrings?
[1] http://stackoverflow.com/questions/2025562/inherit-docstrings-in-python-class-inheritance
(this isn't a huge issue, but keeping docstrings would be nice)

I think @dougalm fixed this in f42fe48. Your test example seems to work on the current master. Please reopen if I'm mistaken.


InfluxDB backup issues after updating to version 4.0.30

Summary
After updating to version 4.0.30 my InfluxDB backup is not working any longer.
From what I can see it looks like the checksum generation somehow fails and then the whole backup process just exits.
The MariaDB backup works just fine.

Steps to reproduce

See attached docker-compose.yml for env details

What is the expected correct behavior?

InfluxDB backup is stored in the backup dir

Relevant logs and/or screenshots
See the attached debug output
Environment

Image version / tag:  4.0.30
Host OS: Unraid

Any logs | docker-compose.yml
docker-compose.yml
version: "3"

volumes:
  backup-mariadb:
    external: true
  backup-influxdb:
    external: true
  backup-logs:
    driver: local

networks:
  db-backup:
    external: true

services:
  db-backup:
    image: tiredofit/db-backup:${DOCKER_IMAGE_VERSION}
    container_name: db-backup
    restart: always
    networks:
      - db-backup
    environment:
      - TIMEZONE=Europe/Vienna
      - CONTAINER_NAME=db-backup
      - CONTAINER_ENABLE_MONITORING=FALSE
      - BACKUP_JOB_CONCURRENCY=2
      - DEFAULT_CHECKSUM=MD5
      - DEFAULT_COMPRESSION=GZ
      - DEFAULT_BACKUP_INTERVAL=1440
      - DEFAULT_BACKUP_BEGIN=0100
      - DEFAULT_CLEANUP_TIME=8640
      - DB01_TYPE=influx
      - DB01_INFLUX_VERSION=2
      - DB01_HOST=${INFLUXDB_HOST}
      - DB01_NAME=ALL
      - DB01_USER=${INFLUXDB_USER}
      - DB01_PASS=${INFLUXDB_PASSWORD}
      - DB01_FILESYSTEM_PATH=/backup/influxdb
      - DB02_TYPE=mariadb
      - DB02_HOST=${MARIADB_HOST}
      - DB02_NAME=ALL
      - DB02_NAME_EXCLUDE=${MARIADB_EXCLUDED_SCHEMAS}
      - DB02_USER=${MARIADB_USER}
      - DB02_PASS=${MARIADB_PASSWORD}
      - DB02_FILESYSTEM_PATH=/backup/mariadb

    volumes:
      - backup-mariadb:/backup/mariadb
      - backup-influxdb:/backup/influxdb
      - backup-logs:/logs

Come on up to 4.0.32 and it Influx will start working again, was resolved yesterday from #308

I'll do that, thanks!


Setup Error #255 on Windows

This is a copy of: https://github.com/carla-simulator/carla/issues/1668
which was marked closed but not resolved.
I previously built Carla 9.6 on this machine with no problems. I had removed it.
This time, when I tried to install the same way, I accidentally used x86 which led to errors.
Now when I try to install, I get this error every time:
D:\Carla 09_06\carla>make launch
-[Setup]: [Batch params]: --boost-toolset msvc-14.1
-[Setup]: Asynchronous jobs:  8
-[Setup]: Boost toolset:      msvc-14.1
-[Setup]: Install directory:  "D:\Carla 09_06\carla\Build"
-[Setup]: Installing zlib...
-[install_zlib]: [Batch params]: --build-dir "D:\Carla 09_06\carla\Build"
09_06\carla\Build""=="" was unexpected at this time.
make: *** [setup] Error 255
I even re installed VS 2017 with no luck. I am losing my mind considering I installed no problem a month ago, and now I am getting nowhere.  I'm using x64 command prompt, and just following the instructions for source build on Windows.

I had a similar issue when I tried to run: make PythonAPI. What fixed my issue was moving my carla directory to my root directory C:\
It seems like the empty spaces in my directory path "C:\Program Files\carla" caused the error.


fix(eslint-plugin-qwik): remove unnecessary console.log call

Remove console.log that was committed by accident

What is it?

[ ] Feature / enhancement
[x] Bug
[ ] Docs / tests

Description
Please include a summary of the change and which issue is fixed. Please also include relevant motivation and context. List any dependencies that are required for this change.
Use cases and why

One use case

Another use case

Checklist:

[x] My code follows the developer guidelines of this project
[x] I have performed a self-review of my own code
[ ] I have made corresponding changes to the documentation
[ ] Added new tests to cover the fix / functionality

ouch! thanks for the PR!


Not pulling data from prizepicks

Hey, your project is wonderful, I was having this error while starting the app:

I went to the API link that you left on the code and proceed to manually copy and paste that info into the pre_formatted_projections.json file and then it successfully started:

Is this expected? I am missing something or the format changed?
Thank you for this development, I was trying to do something similar but this is awesome.

Hello @ezequiel-kl,
Thank you for reaching out! So the way I designed it to work is that it uses a web driver to "hard scrape" the API from Prize Picks.
Yes, that is the expected output to terminal. I have not yet implemented a system to search up players with a full name more than 2 words, or special characters yet. (Working as a revamped version 2 // full stack as of this moment)
Why would I do this rather than just making a normal API request you may ask? Because Prize Picks does not allow public API, nor do I have an Auth key. While you can copy and paste from the link (which was how I used to have it LOL) It was now the ideal method I wanted so I used a web driver to open a Firefox tab locally on your computer to web scrape all the API data into the JSON file.
So after you start it it should open a FireFox tab assuming you have FireFox and gecko which is installed on your system...

It will scrape all the prize picks data and put it in the JSON (this was for debugging/testing purposes) then it will start searching up players, etc.

And it will display...

Thank you for your fast reply!
That is exactly what is trying to do but when it opens the Firefox tab, I see that it shows the data, and after this window:

It immediately closes and throws the error that I showed on my initial post
So I opened the link, created an empty pre_formatted_projections.json and copied the content manually to the file and it worked as you show me on your screenshots.
Tomorrow with the new predictions I will now if I "accidentally" fixed the issue.
Thank you for your support, I really appreciate it.

Hmm im not sure why it's doing that.
Try adding this line of code in the for loop:
print(type(item))

Inside the json_parser.py...

Thank you a lot!


Add dependency check to make sure child devfiles are being tested when parent stack has been changed

Which area/kind this issue is related to?
/area registry
Issue Description
The current PR tests in the devfile registry only test for stacks/samples that have been changed. However, if there are other stacks/samples referring to the changed stacks as parents, the child stacks/samples test does not run.  There is a risk in case the parent stack change may break the depending stacks/samples.
We need to:

Set up a dependency tree (auto-generated based on the current registry contents) so that we can easily find out the depending stacks/samples of a given stack.
Triggers the child stacks/samples test as part of the PR tests of the parent stacks

Target Odo version
N/A
Target Date: TBA

The initial dependency check work for current child samples is now being tracked under #1142, this issue will now track the continuation of that work to expand to considering additional child stacks/samples not yet part of the community registry.

Depends on completion of https://github.com/devfile/api/issues/1142


⚠ Bofrost.fr has degraded performance

In ac6b19a, Bofrost.fr (https://www.bofrost.fr) experienced degraded performance:

HTTP code: 200
Response time: 1173 ms

Resolved: Bofrost.fr performance has improved in 27dd12f after 6 minutes.


Upgrade to libcnb 0.8.0

Updates this buildpack to libcnb 0.8.0 and libcnb-test 0.4.0. Some minor code changes were required due to breaking changes.
Closes GUS-W-11342121

CI fails due to failing tests, but those tests were broken in the base branch as well.

CI is dead, long live CI!

Thanks ❤


Fix + tidy descriptions of Explorer commands

In the command palette when the Explorer is selected there were two
options to create a new file.  One of them is actually the command to
create a new directory.
So fix the incorrect name for that.
Also harmonise the naming scheme of the other explorer actions.

Looks like the build is passing now so I'll bring this in. Change looks great!
Thanks @feltech for the contribution and @Akin909 for reviewing! 💯


Adding Support for Arachni integration

It will be certainly helpful for the people who want to follow security tests with CI tools, and without a doubt Arachni is the one of the best dynamic application testing suite on the market available and free.
I would be pleasure for me to work with you in this project also.

As an enhancement, this one is quite analog to adding support for Zap; Issue https://github.com/F-Secure/mittn/issues/14, so have a look at the comments there before starting on a patch. Contributions are much welcome :)


Create a Form-card-4

I want to work on this component next, I have submitted my previous issue,
Here is a reference to the component.

Kindly assign the issue
Thank You,
Sayantan

can you sign this issue to me ?

This is already built. Closing this issue. @SayantanStackflow

Okay, my bad I guess. I didn't notice the element in the code, I'm trying new one

Ok you can assign to Me tho


Extensibilitity: Display widget: Expandable table

Description
Investidate a possibility of displaying data in a table with en expandable row (an expander icon that shows extra data - fully structured display - with block widgets, etc.)
Technical notes

Quite possibly just extend the exisiting Table widget
Possibly doable as an extra <tr> with colspan=* - but the main question how to easily integrate with with GenericList

See example from Octant:


Error when using with socket.io

I tried to use this library in the application with the express - everything is fine! I also tried to connect the socket.io library, but I got an error when I changed express router and refreshed the page in the browser.
The error is as follows:
Error [ERR_HTTP_HEADERS_SENT]: Cannot set headers after they are sent to the client
    at validateHeader (_http_outgoing.js:503:11)
    at ServerResponse.setHeader (_http_outgoing.js:510:3)
    at ServerResponse.header (/myproject/node_modules/express/lib/response.js:767:10)
    at ServerResponse.contentType (/myproject/node_modules/express/lib/response.js:595:15)
    at ServerResponse.send (/myproject/node_modules/express/lib/response.js:145:14)
    at app.get (/myproject/build/back/0.e82fa0b64b13baf96886.hot-update.js:22:31)
    at Layer.handle [as handle_request] (/myproject/node_modules/express/lib/router/layer.js:95:5)
    at next (/myproject/node_modules/express/lib/router/route.js:137:13)
    at Route.dispatch (/myproject/node_modules/express/lib/router/route.js:112:3)
    at Layer.handle [as handle_request] (/myproject/node_modules/express/lib/router/layer.js:95:5)
_http_outgoing.js:503
    throw new errors.Error('ERR_HTTP_HEADERS_SENT', 'set');
Dependencies:

"node-hot-loader": "^1.6.0"
"express": "^4.16.2"
"socket.io": "^2.0.4"
"socket.io-client": "^2.0.4"

Engines:

"node": "^9.7.1"
"yarn": "^1.5.1"

Code
    server.js
/* @flow */

import withSocket from 'socket.io'
import { app } from './express'

const PORT = process.env.PORT || 3000
const server = app.listen(PORT, () =>
  console.log(`Server is running at ${PORT} port`),
)
const io = withSocket(server, { path: '/ws' })

io.on('connection', socket => {
  console.log('connection')
  socket.emit('message', 'hello')
})

if (module.hot && typeof module.hot.accept == 'function') {
  let currentApp = app

  module.hot.accept('./express', async () => {
    server.removeListener('request', currentApp)

    currentApp = require('./express').app
    server.on('request', currentApp)

    console.log('Server reloaded!')
  })

  module.hot.accept()
  module.hot.dispose(() => {
    console.log('Disposing entry module...')
    server.close()
  })
}

    express.js
/* @flow */

import express from 'express'
import { resolve } from 'path'

const staticPath = resolve(__dirname, '../front')
export const app = express()

app.use(express.static(staticPath))
app.get('/test', (_, res) => res.send('Hello world!'))

    client.js
/* @flow */

import io from 'socket.io-client'

const socket = io(undefined, { path: '/ws' })
socket.on('connect', () => console.log('connect'))
socket.on('disconnect', () => console.log('disconnect'))
socket.on('message', msg => console.log(msg))

Any ideas?

Can you share simple project with github? I will try to reproduce that error.

Closed due to inactivity.

Have a look at https://github.com/socketio/engine.io.
Maybe need call oldSocketServer.close() and then call newSocketServer.attach(httpServer) or something simular.

Maybe I do not fully understand where to put this but I have already done this.  The biggest thing is that I am trying to use express and socket.io http://socket.io/ at the same time.

On Nov 6, 2018, at 11:16 AM, Vladimir<EMAIL_ADDRESS>wrote:
Have a look at https://github.com/socketio/engine.io https://github.com/socketio/engine.io.
Maybe need call oldSocketServer.close() and then call newSocketServer.attach(httpServer) or something simular.
—
You are receiving this because you commented.
Reply to this email directly, view it on GitHub https://github.com/vlazh/node-hot-loader/issues/3#issuecomment-436312003, or mute the thread https://github.com/notifications/unsubscribe-auth/AF9vGBuSVjY6GJ7Oy5cOK0_8Brmb1i_Fks5usbX7gaJpZM4Skqmq.

I figured out a way to get it to work.  I think my biggest issue is that it was conflicting with Apollo Server.  So now I am importing them separately.  The biggest issue now is I am hitting max event listeners limit.

On Nov 6, 2018, at 1:56 PM, Craig Couture<EMAIL_ADDRESS>wrote:
Maybe I do not fully understand where to put this but I have already done this.  The biggest thing is that I am trying to use express and socket.io http://socket.io/ at the same time.

On Nov 6, 2018, at 11:16 AM, Vladimir<EMAIL_ADDRESS><EMAIL_ADDRESS>wrote:
Have a look at https://github.com/socketio/engine.io https://github.com/socketio/engine.io.
Maybe need call oldSocketServer.close() and then call newSocketServer.attach(httpServer) or something simular.
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Reply to this email directly, view it on GitHub https://github.com/vlazh/node-hot-loader/issues/3#issuecomment-436312003, or mute the thread https://github.com/notifications/unsubscribe-auth/AF9vGBuSVjY6GJ7Oy5cOK0_8Brmb1i_Fks5usbX7gaJpZM4Skqmq.


[New Feature]: Change the Interface Fonts Properties

🎮 feature Request
I will change the color styles  of the fonts. Overall i will enhance the Complete Inteface. I have great command in css.
Point down the features
feature points
Select program in which you are contributing
GSSoC24
Code of Conduct

[X] I follow CONTRIBUTING GUIDELINE of this project.

Please assign me this issue under @GSS0C24

@rajvaidyanath27 go ahead


Precip On the Map

Got this taken care of. It may be too slow, but I'm not sure that is actually due to loading data or not.

Actually, turns out I can't be that patient. Gonna merge and THEN ask @jread-usgs to weigh in on transparency.


SimpleLastTab extension not working in new Kiwi Browser

Describe the bug
SimpleLastTab extension not working in new Kiwi Browser
Smartphone (please complete the following information):

Device: Meizu 16th
Android Version : Android 10
Kiwi Browser Version: 93.0.4577.39

Additional context
The SimpleLastTab extension can work in the old Kiwi browser, but not in the new Kiwi browser.

Works in latest github version!

Works in latest github version!

But there are still some compatibility issues, such as when it works with some extensions, when closing tab 2 as shown in the figure, it will take a long time to create a new tab, and when closing tab 1 to create a new tab in no time. New tab pages are created using the extension Infinity新标签页(Pro).

Yea turns out the fix wasn't full (the goal was getting Discord Hide Sidebar to work, this one got sorta fixed as side effect with Hide Sidebar itself isn't fixed yet).
By the way, what exactly are you trying to achieve with the extension? I used to use a self modded version of it except making it check for 0 tabs meaning whenever I closed all tabs it'd spawn one instantly. I recently forked a similar one on github so I could actually keep it somewhere, you can download it here in case your goal of using SimpleLastTab on kiwi was the same as mine (of not being left tab-less).

是的，事实证明修复并不完整（目标是让 Discord Hide Sidebar 工作，这个修复了，因为 Hide Sidebar 本身的副作用还没有修复）。
顺便说一句，您到底想通过扩展实现什么？我曾经使用它的自我修改版本，除了让它检查 0 个标签，这意味着每当我关闭所有标签时，它都会立即生成一个。我最近在 github 上分叉了一个类似的，所以我实际上可以将它保存在某个地方，你可以在这里下载它，以防你在 kiwi 上使用 SimpleLastTab 的目标与我的相同（不留下标签）。

Yea turns out the fix wasn't full (the goal was getting Discord Hide Sidebar to work, this one got sorta fixed as side effect with Hide Sidebar itself isn't fixed yet).
By the way, what exactly are you trying to achieve with the extension? I used to use a self modded version of it except making it check for 0 tabs meaning whenever I closed all tabs it'd spawn one instantly. I recently forked a similar one on github so I could actually keep it somewhere, you can download it here in case your goal of using SimpleLastTab on kiwi was the same as mine (of not being left tab-less).

I want to create a tab page automatically when there is no tab page. I did some more tests, and when the logic of these extensions is to always keep two tabs, there will be a problem that creating new tabs is very slow, and if it is always keeping one tab, there is no problem.

In this case try this one from my repo. If you downloaded from the link above please redownload, there was a bug on that one that would try to spawn multiple tabs at once when using clear all and would often hang the browser.

In this case try this one from my repo. If you downloaded from the link above please redownload, there was a bug on that one that would try to spawn multiple tabs at once when using clear all and would often hang the browser.

Thank you, this helped me a lot.By the way, is there a way to import passwords to kiwi browser

I did a small logic fix to make it safer (change variable before creating tab, so it should be safer in case your phone lags). If you don't mind one last redownload (hopefully 😋): https://github.com/Delphox/AlwaysHaveTab/releases/download/1.2/AlwaysHaveTab.crx
And no importing password is not possible without root ☹ best you can do is installing an external password manager (keepass, lastpass, bitwarden etc) and keeping your passwords synced that way.

I did a small ordering fix to make it safer (change variable before creating tab, so it should be safer in case your phone lags). If you don't mind one last redownload (hopefully 😋): https://github.com/Delphox/AlwaysHaveTab/releases/download/1.2/AlwaysHaveTab.crx
And no importing password is not possible without root ☹ best you can do is installing an external password manager (keepass, lastpass, bitwarden etc) and keeping your passwords synced that way.

ok

Ok due to someone request in case people are using custom new tab, i made a version that opens chrome://newtab instead
Regular version: https://github.com/Delphox/AlwaysHaveTab/releases/download/1.3/AlwaysHaveTab.crx
Chrome://newtab version: https://github.com/Delphox/AlwaysHaveTab/releases/download/1.3/AlwaysHaveTab_chromenewtab.crx
Posting here just in case it matters for you. If not then stick to the one you have 😉


Invalid parameter robot_description

Hi, I'm making customized husky , and tryied to show it following husky tutorial.
When I try to see it on the both rviz and gazebo, they never launched and error below is returned.
commands i send:
$ export HUSKY_URDF_EXTRAS=~/path/to/the/customized/file.urdf.xacro
$ roslaunch husky_gazebo husky_empty_world.launch
($ roslaunch husky_viz view_model.launch)

returned error when i launch gazebo:
RLException: while processing /opt/ros/melodic/share/husky_gazebo/launch/spawn_husky.launch:
while processing /opt/ros/melodic/share/husky_control/launch/control.launch:
while processing /opt/ros/melodic/share/husky_description/launch/description.launch:
Invalid <param> tag: Cannot load command parameter [robot_description]: command [['/opt/ros/melodic/lib/xacro/xacro', '/opt/ros/melodic/share/husky_description/urdf/husky.urdf.xacro', 'robot_namespace:=/']] returned with code [2].

Param xml is <param command="$(find xacro)/xacro '$(find husky_description)/urdf/husky.urdf.xacro'     robot_namespace:=$(arg robot_namespace)" name="robot_description"/>
The traceback for the exception was written to the log file

I'm using ros Melodic, and LMS1xx package has been downloaded. Also, my urdf can be seen on rviz if I try it using roslaunch urdf_tutorial display.launch model:=hauser.urdf.xacro,so urdf itself must be fine.
How can I solve it?
Thanks in advance,
Karin

What are the contents of the URDF file you're assigning here:
export HUSKY_URDF_EXTRAS=~/path/to/the/customized/file.urdf.xacro

and are you properly replacing the path with the actual path to your URDF file?

Hi, the path is fine but my urdf is not.
I said it must be fine because roslaunch urdf_tutorial display.launch model:=hauser.urdf.xacro showed my model with no problem. However, when I use husky's default lanuch file to launch rviz & gazebo, it seems I shouldn't have used <xacro:include  filename:"path/to/the/original_husky.urdf.xacro">. Once, i remove the line, both rviz&gazebo show my model correctly!!


Modify volume size unit from gb to gib

Currently, the pvc unit is gib in yaml file, but ubiquity sent to scb with unit gb.
That caused the volume size is not correct.
As confirmed with SCB developer, SCB support both unit gib and gb.
I just modify the unit from gb to gib in this patch.

This change is

Coverage remained the same at 58.333% when pulling 0ef9853ec7e7d14d85d5e50e58a85e6eb78f1fd7 on fix/UB-1543_volume_size_gb_to_gib into 593eab53c734ef364a7f8871651d1ab3ce5f0188 on dev.

closing this PR because @olgashtivelman  already merge back the release branch into dev.


Correction for raw affiliation Channel and North Sea Fisheries Research Unit, IFREMER, France; UFR 918 Terre Environnement et Biodiversité, Sorbonne Université, France

Correction needed for raw affiliation Channel and North Sea Fisheries Research Unit, IFREMER, France; UFR 918 Terre Environnement et Biodiversité, Sorbonne Université, France
raw_affiliation_name: Channel and North Sea Fisheries Research Unit, IFREMER, France; UFR 918 Terre Environnement et Biodiversité, Sorbonne Université, France
new_rors: 044jxhp58;02en5vm52
previous_rors: 044jxhp58;02en5vm52;039p01270
works_examples: W4317718242
contact: 9bd5be65ba3d7c93aee096d9ed1ce234:8f92c94c @ ourresearch.org

This issue was accepted and ingested by the OpenAlex team on 2024-10-09. The new affiliations should be visible within the next 7 days.


🚀  Can we create an observability platfom product?

Let's explore the minimal setup we need to be able to run the observability platform to be able to get a step in the doors to our customers?
Let's also find out if that is even possible (due to grafana licensing and so on).
It would be nice if we could also define a pricing strategy :p

Miro board: https://miro.com/app/board/uXjVL16fUag=/


Add sbt-1.1.1

https://github.com/sbt/sbt/releases

@all-contributors please add @josjos7 for code


tags

It would be great to have tags for ROCm releases. Last tag is from August 29 2018.

@ntrost57 We will have a tag for the 2.3 release and tags going forward. Not sure of the timing though. We can discuss by email.


SSL cert reporting as invalid

@prattsj, @bundacia, or anyone -- is this happening for you, too?

It was a caching problem: https://apple.stackexchange.com/questions/134601/chrome-showing-the-sites-security-certificate-is-not-trusted-for-github


Granularlink.type Property

Is your feature request related to a problem? Please describe.
No real problem, just had a request for a nice-to-have feature. I want to render a graph such that some of the links are straight while others are curved.
Describe the solution you'd like
I'd like to have the config property link.type to be granular (as denoted by 🔎🔎🔎in the docs) the same way that some of the other link properties are granular (like link.color).
Describe your use case
I'm rendering a networking map, and would like my links to have different types depending on if they link a device with an access point, or if they link access points together.

its already implemented most probably in the next release it will be there
https://github.com/danielcaldas/react-d3-graph/issues/234

That's correct, hopefully I get it released today after going through all the issue 🙏

Closing, as a duplicate of #234


chore(deps): update dependency pagefind to v1.1.1 [security]

This PR contains the following updates:

Package
Type
Update
Change

pagefind
devDependencies
patch
1.1.0 -> 1.1.1

GitHub Vulnerability Alerts
CVE-2024-45389
Pagefind initializes its dynamic JavaScript and WebAssembly files relative to the location of the first script you load. This information is gathered by looking up the value of document.currentScript.src.
It is possible to "clobber" this lookup with otherwise benign HTML on the page, for example:

This will cause document.currentScript.src to resolve as an external domain, which will then be used by Pagefind to load dependencies.
This exploit would only work in the case that an attacker could inject HTML to your live, hosted, website. In these cases, this would act as a way to escalate the privilege available to an attacker. This assumes they have the ability to add some elements to the page (for example, img tags with a name attribute), but not others, as adding a script to the page would itself be the XSS vector.
Pagefind has tightened this resolution by ensuring the source is loaded from a valid script element. There are no reports of this being exploited in the wild via Pagefind.
Original Report
If an attacker can inject benign html, such as:

they can clobber document.currentScript.src leading to XSS in your library.
Here is the same attack on webpack that was accepted: https://github.com/webpack/webpack/security/advisories/GHSA-4vvj-4cpr-p986

Release Notes

CloudCannon/pagefind (pagefind)
v1.1.1
Compare Source
Fixes & Tweaks

Fixes an issue where internal anchor and weight tokens would leak when captured in meta or filter attributes.
Improves segmentation for extended languages (PR #600 — thanks @hamano !).
Improves Pagefind's processing of "index.html" URLs (PR #604 — thanks @dscho !).
Fixes some instances of incorrect types in the Pagefind NodeJS API (PRs #642 & #655 — thanks @vanyauhalin & SKalt !).

UI Translations

Added Swahili translations

Secutiry

Fix potential DOM clobbering when initializing Pagefind

Configuration
📅 Schedule: Branch creation - "" in timezone Europe/Berlin, Automerge - At any time (no schedule defined).
🚦 Automerge: Disabled by config. Please merge this manually once you are satisfied.
♻ Rebasing: Whenever PR becomes conflicted, or you tick the rebase/retry checkbox.
👻 Immortal: This PR will be recreated if closed unmerged. Get config help if that's undesired.

[ ] If you want to rebase/retry this PR, check this box

This PR has been generated by Renovate Bot.

@lfrancke, the build keeps failing on this branch.

I'll close this in favor of https://github.com/stackabletech/documentation/pull/656


Jenkins API now fails with JSON error

After upgrading to Helium release of salt, salt-api builds now all fail with the following basic error code:
Problem: state.sls test.apitest to http://:8888 for BaseA:
net.sf.json.JSONException: JSONObject["return"] is not a JSONArray.
This happens regardless of success or failure of the actual salt call. I can authenticate successfully, and salt does run, but it returns this error which kills the build job in Jenkins.
This would be potentially tolerable save that, in order to do a rolling restart, I run the same job to multiple different nodegroups, and since it fails on the first, never completes.

Eep, sorry for the response delay. Notifications were not configured properly for this repo and I missed this report.
Not returning a json array should only happen when salt-api doesn't respond properly. Our environments are still not on 2014.7 due to other issues, so I'll set up a new 2014.7 test and see what has changed.

Eep, sorry for the response delay. Notifications were not configured properly for this repo and I missed this report.
Not returning a json array should only happen when salt-api doesn't respond properly. Our environments are still not on 2014.7 due to other issues, so I'll set up a new 2014.7 test and see what has changed.

Cool! Please let me know, as at the moment it's breaking production. :(
On Thu, Jan 1, 2015 at 11:36 AM, mchugh19<EMAIL_ADDRESS>wrote:

Eep, sorry for the response delay. Notifications were not configured
properly for this repo and I missed this report.
Not returning a json array should only happen when salt-api doesn't
respond properly. Our environments are still not on 2014.7 due to other
issues, so I'll set up a new 2014.7 test and see what has changed.
—
Reply to this email directly or view it on GitHub
https://github.com/mchugh19/jenkins-saltapi/issues/2#issuecomment-68495765
.

--
Steven Schwartz | Engineering Team
Education Elements, Inc.
<EMAIL_ADDRESS>|<PHONE_NUMBER>

I've just released a new point release (1.4.2) that corrects the problems I've found.
You will still need to specify the runner permission for the user defined by jenkins, and then restart both the salt-master and your salt-api.
external_auth:
pam:
jenkins:
- '@runner'
- .*
If you continue to experience any problems, please let me know and send the entirety of the jenkins output.

Seems to be good with current salt release. Please reopen if there are any issues.


Affiliation invitations

issue: bcGov/entity#22616

display pending affiliation invites in table
implement invitation table actions (cancel/resend/new request)
remove pending invite if sending another invite for the same business
set table td max width and allow text to wrap
logFetchError util to create consistent console error messages
update FormAddBusinessError component to display different text for passcode or firm authorization request (previously displayed the same text for both options)
update unit tests

/gcbrun

Temporary Url for review: https://business-registry-dev--pr-24-ti73fws0.web.app


Fix ws tests

Describe the bug
The websocket tests (in file src/tests/ws.edn fail sometimes. This is likely due to the 3rd-party URLs we used that are unreliable.

Warning:  [2022-10-31 09:29:35.797] [T-23290] [ws.cpp::218] WebSocket connection failed: Failed to resolve host
Error:  [2022-10-31 09:29:35.797] [T-23290] [runtime.cpp::755] Shard activation error, failed shard: WS.Client, error: WebSocket connection failed.
Error:  [2022-10-31 09:29:35.797] [T-23290] [runtime.cpp::755] Shard activation error, failed shard: Once, error: WebSocket connection failed.

Proposed solution
Setup a local websocket server that we maintain to be used as an echo service for the tests.
This serve could either always run (potentially dangerous: could cause DDoS attacks), or be brought up and down during the test themselves.

Extremely low priority.


Refine fusion heuristic

Only merge duplicate broacast ops to avoid duplicating an op containing
a broacast along with expensive work

This is also way to conservative to my liking, but OK to start with that and make it less conservative based on use case.

This is also way too conservative to my liking, but OK to start with that and make it less conservative based on use case.

By conservative you mean that we should allow more fusion? You are probably right but I couldn't find anything significantly better without having a way to evaluate the cost of a generic op and I didn't want to go to crazy on heuristic.


[Substrait to Velox] Add converter from VirtualTable to ValuesNode

@ZJie1 Overall looks good, but there is no test coverage. Would it make sense to extend the velox/substrait/tests/PlanConversionTest.cpp to add tests for virtual tables?

there will need another json file to test this so extend the velox/substrait/tests/PlanConversionTest.cpp may not worked, the json file included in the code now use the scanNode. How about cover this in the round-trip test that we plan add later.

there will need another json file to test this so extend the velox/substrait/tests/PlanConversionTest.cpp may not worked, the json file included in the code now use the scanNode. How about cover this in the round-trip test that we plan add later.

Don't we need to test multiple json files that contain different plans? Or, do you think we don't need this type of testing at all and can remove PlanConversionTest and use round-trip tests exclusively?

@ZJie1 Nice. We are almost ready to go. Just a couple of things left to take care of. I noticed that the test uses only 64-bit floating point values. Would it be possible to extend it to include all supported types of values?

This is restricted by the FieldAccessTypedExpr in SubstraitToVeloxExpr.cpp. We can extend it after the support in https://github.com/facebookincubator/velox/pull/1450  enabled.

@ZJie1 Nice. We are almost ready to go. Just a couple of things left to take care of. I noticed that the test uses only 64-bit floating point values. Would it be possible to extend it to include all supported types of values?

This is restricted by the FieldAccessTypedExpr in SubstraitToVeloxExpr.cpp. We can extend it after the support in #1450 enabled.

Got it. #1450 just landed. Let's rebase and update the test to add more types.

Got it. #1450 just landed. Let's rebase and update the test to add more types.

Hi @mbasmanova ,I have update the test, please help take a review.

path will be incorrectly when test on local.

Elsewhere, we use WORKING_DIRECTORY cmake variable. See velox/exec/tests/CMakeLists.txt
add_test(
  NAME velox_exec_test
  COMMAND velox_exec_test
  WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR})

Would it be possible to use the same here?


Provide optional list of versions to match against

This is a great tool and is quite helpful for the nodenv ecosystem. @hurrymaplelad built a plugin for nodenv that lets nodenv pull its version from package.json engines instead of .node-version. It is using this service to determine the best node version that satisfies the version spec from engines. However, that's only half the puzzle for nodenv. In addition to simply finding the maximum version match for a given semver range, we would like to take into account versions that are installed.
I would love to see the ability to pass a semver range and also a list of versions, and have semver.io select the best option available from the provided list (defaulting to current behavior if none match).
Since this would be an optional extra parameter (array), then omitting it does not alter current behavior.
Example:
https://semver.io/node/resolve?range=>%3D4.0.0
5.0.0

https://semver.io/node/resolve?range=>%3D4.0.0&v=4.2.1
4.2.1

https://semver.io/node/resolve?range=>%3D4.0.0&v=4.0.0&v=4.1.0&v=4.2.1
4.2.1

https://semver.io/node/resolve?range=>%3D4.0.0&v=0.10.0&v=0.12.0
5.0.0

Thoughts?

Cool idea Jason! I wonder if we can compare installed versions against a semver expression locally to avoid the network dependency for the common case?  I bet there's a nose module that does this. Haven't looked yet

On Nov 2, 2015, at 5:22 AM, Jason Karns<EMAIL_ADDRESS>wrote:
This is a great tool and is quite helpful for the nodenv ecosystem. @hurrymaplelad built a plugin for nodenv that lets nodenv pull its version from package.json engines instead of .node-version. It is using this service to determine the best node version that satisfies the version spec from engines. However, that's only half the puzzle for nodenv. In addition to simply finding the maximum version match for a given semver range, we would like to take into account versions that are installed.
I would love to see the ability to pass a semver range and also a list of versions, and have semver.io select the best option available from the provided list (defaulting to current behavior if none match).
Since this would be an optional extra parameter (array), then omitting it does not alter current behavior.
Example:
https://semver.io/node/resolve?range=>%3D4.0.0
5.0.0
https://semver.io/node/resolve?range=>%3D4.0.0&v=4.2.1
4.2.1
https://semver.io/node/resolve?range=>%3D4.0.0&v=4.0.0&v=4.1.0&v=4.2.1
4.2.1
https://semver.io/node/resolve?range=>%3D4.0.0&v=0.10.0&v=0.12.0
5.0.0
Thoughts?
—
Reply to this email directly or view it on GitHub.

This is certainly possible, but I'm not sure if it's something you'd want to do on a web service vs just a local match. It would be pretty trivial for instance to pull down semver.io/node/versions and then determine that matchingVersions = _.intersection(allVersions, localVersions).

@hunterloftis thanks for the pointers.  It seems like matchingVersions = _.intersection(allVersions, localVersions) would tell us if the local version is a legit node version.  Any suggestions for comparing a list of local versions against a range expression like ~1.3 ?

@hurrymaplelad I think semver.maxSatisfying is what you need:

maxSatisfying(versions, range): Return the highest version in the list that satisfies the range, or null if none of them do.

Here's how semver.io does it: https://github.com/heroku/semver.io/blob/208828269ab0839e56a2bcb7b83232a2a32390f9/lib/resolver.js#L64-L70

@zeke perfect, thanks!  Now I just need a native or shell script implementation to bootstrap node...

I'd imagine that you could code the plugin in node as long as it didn't use
any non core modules. Since (within the context of the plugin) we know at
least /a/ node is installed, we just don't know which to select. So if this
is coded such that it works on /any/ node (and without an npm install),
you'd be safe.
But that's a lot of restrictions and may be simpler to just stay in shell.
Though this does make me wonder if we could add a desire to nodenv itself
that would allow plugins to run in a particular node
On Nov 7, 2015 9:39 PM, "Adam Hull"<EMAIL_ADDRESS>wrote:

@zeke https://github.com/zeke perfect, thanks! Now I just need a native
or shell script implementation to bootstrap node...
—
Reply to this email directly or view it on GitHub
https://github.com/heroku/semver.io/issues/51#issuecomment-154771453.

@hurrymaplelad if you want to bootstrap node, here's how the heroku buildpack does it: https://github.com/heroku/heroku-buildpack-nodejs/blob/67291e8c9afa15720219652e490d34d9d28735a6/lib/binaries.sh#L45-L62


Is xlnet indeed context aware?

Hi All
I've been playing with Spacy and BERT and I'm trying to see how the embedding of each word varies across different context.
For example, for the following three sentences:
nlp = spacy.load("en_pytt_bertbaseuncased_lg")
apple1 = nlp("Apple shares rose on the news.")
apple2 = nlp("Apple sold fewer iPhones this quarter.")
apple3 = nlp("Apple pie is delicious.")
print(apple1[0].similarity(apple2[0]))  # 0.73428553
print(apple1[0].similarity(apple3[0]))  # 0.43365782
0.7342856
0.43365765
As one would expect.  So far so good.  However, if I do the same w/
nlp_xlnet = spacy.load("en_pytt_xlnetbasecased_lg")
apple1 = nlp_xlnet("Apple shares rose on the news.")
apple2 = nlp_xlnet("Apple sold fewer iPhones this quarter.")
apple3 = nlp_xlnet("Apple pie is delicious.")
print(apple1[0].similarity(apple2[0]))  # 0.73428553
print(apple1[0].similarity(apple3[0]))  # 0.43365782
0.9853272
0.9792127
It means that xlnet (at least in this example) is completely unaware of the context.  Given xlnet's stellar GLUE and Squad2 results, I was really surprised by this finding.  Granted, it's only a super trivial example, but still, it causes me to pause and scratch my head.
Anyone else has experienced similar results?  Or maybe I've done something wrong or simply missed how the whole thing was supposed to work?
Thank you for your input.
SH

FYI I tried several ways to construct a sentence embedding given text input and hidden outputs. They all turned out to be surprisingly similar in cosine similarity(just like the result you get), while if the same thing was done to bert, the embeddings show desirable similarity and dissimilarity.
I was thinking it may just be the result of the absence of sentence level pretraining tasks, but well, seeing your result makes me wonder even more.

What happens if you use the cased model of BERT 🤔

I am aware of the casing discrepancy.  However, I can only use what came w/ Spacy…  :(
I should have tried more examples with uncase words…  I’ll do that and report the results.
SH

On Aug 30, 2019, at 1:19 AM, Stefan Schweter<EMAIL_ADDRESS>wrote:
What happens if you use the cased model of BERT 🤔
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub https://github.com/zihangdai/xlnet/issues/222?email_source=notifications&email_token=ABTZAPCIBHQKMWR7WXGPBODQHDJZBA5CNFSM4IRXFJXKYY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOD5Q6BBI#issuecomment-526508165, or mute the thread https://github.com/notifications/unsubscribe-auth/ABTZAPE5FKPCKSY6FMGD4X3QHDJZBANCNFSM4IRXFJXA.

I have observed a similar issue when it comes to context for word embeddings which can explain why it might behave the same on sentence level.
In ELMO, BERT and ALBERT they all aware of the context:
“Bank river.”
“Bank rober.”
The word Bank has different embeddings vectors since the context is different, unfortunately, in XLNet the Bank has the same embeddings.
https://github.com/zihangdai/xlnet/issues/264

Did anyone figure this out? I am still experiencing the same issue with no solution: https://github.com/zihangdai/xlnet/issues/264


version >1.5.0 leaves Opera crippled, always waits for errorTimeout

yepnope cripples Opera unnecessarily, because it now always waits for the whole errorTimeout time span (default: 10 seconds !!), before it calls the callback/complete callbacks. Even when the resource is actually loaded immediately and successfully.
This happens because strJsElem ends up getting set to script instead of  img.
This regression was introduced first in yepnope v1.5.1. Some commits involved in the matter follow below, notice the changes around the strJsElem / isOpera / isIE code and how the partial "revert" in v1.5.1 caused this.

2dc5e39 Switched all preloading over to images except for gecko somewhere between 1.0.2 and 1.5.0b
a979cc0 Reverted back to using script tags with bogus types to preload in IE one of the two commits for 1.5.1
4f1f12d v1.5.2 removes the unused isOpera flag.

Test case is provided at jsbin.com:

Test case 1 with yepnope 1.5.2, "broken" in Opera but works normally e.g. in Chrome/IE
Test case 2 with yepnope 1.5.2, fixed via duck punching before yepnope is loaded
Test case 3 with yepnope 1.5.0, works in Opera

The test case simply loads jquery v1.7.1 from the CDN and displays when the callbacks are called. You will notice that in Test Case 1 there is exactly a 10s wait in Opera before the callbacks are run. Although the jQuery file has finished loading long before that. But there is virtually no wait in e.g. Chrome/IE. Test case 2 and 3 show the expected behavior for Opera.
All Opera versions on all platforms should be affected by this (I tested with Opera 11.61on Win XP/7). Also all Modernizr builds with yepnope included (since ~ February 6th) will be affected too.
Possible fix: Reintroduce the isOpera flag and change
strJsElem = isGecko ? "object" : isIE ? "script" : "img",

to
strJsElem = isGecko ? "object" : (isIE && !isOpera) ? "script" : "img",

Made the pull request, hope it's ok this way.
I added the isOpera flag to the isIE check so I don't need to change both the strJsElem and strCssElem expressions.
btw it looks like it automatically opened another issue (#89).

Merged. Thanks for the pull. Will push a 1.5.3 soon.

FWIW, none of the three test cases work for me in IE 9.0.8112.16421 (compatibility view off). I just get this:
Before yepnope({...}): Tuesday, February 14, 2012 9:22:00 AM

callback called:

complete called:

If I go to Tools > Internet Options > Advanced and uncheck Disable script debugging (Internet Explorer), I get the following error messages:
Test case 1:
Line: 36
Error: 'yepnope' is undefined

Test case 2:
Line: 39
Error: 'yepnope' is undefined

Test case 3:
Line: 36
Error: 'yepnope' is undefined

@lencioni that happens because in the test cases I directly linked to the yepnope files on github. e.g. https://raw.github.com/SlexAxton/yepnope.js/v1.5.2/yepnope.js
Github serves these raw files as text/plain which stops IE9 from parsing them as javascript, thus yepnope isn't loaded.
The error console in IE9 also mentions this with a "SEC7112" warning right before the error messages.
Here you can read more about the MIME-Handling Changes in Internet Explorer 9

I pushed 1.5.3 today which had this fix.


Fix for invalid research oppotunities.

Stemmed from the right-click menu breaking.
There are invalid research opportunities written to the save game. Maybe from changes in other mods?
I just added code to filter them out when the game loads. And also in WorkGiver_AnalyseInPlace, which is where the original exception was occurring.
Of course, this might not be the best place to put these filters, but then I don't really know what I'm doing with RimWorld modding. This is more of an FYI than anything...

Just wanted to mention Im aware of this. Ill probably be rolling it (or something much like it) into the next update.

Couple things to note

Oops, sorry - clicked the wrong button and accidentally closed this.
In any case, wanted to add that the projects that become "invalid" aren't necessarily from other mods - for example, a saved game I just loaded had hydroponics and geothermal power as "invalid" somehow. However, I am having other mod issues I haven't tracked down (and likely won't til the new update hits), so it's obviously possible other mods are still causing incompatibilities.

Added it manually. Thanks.


ciao-controller: reduce complexity of newConfig

The complexity of newConfig is so high, that just about any change
pushes it over the edge of our gocyclo limit of 15. Refactor
newConfig a little bit to make it easier to read and reduce
complexity.
Signed-off-by: Kristen Carlson Accardi<EMAIL_ADDRESS>

Coverage decreased (-0.03%) to 65.759% when pulling 604af59b37627ea808c2c2e7612b846e3be4ae4c on kaccardi:topic/refactor-new-config into b79ebd38e8d91825f3f5529c4485430ae919cd16 on 01org:master.


I run it encounter resource exhausted: OOM

when i train my own model,problems happened.I run it encounter resource exhausted: OOM.
could you help me?

Layer (type)                 Output Shape              Param #
conv2d_1 (Conv2D)            (None, 32, 198, 198)      320

activation_1 (Activation)    (None, 32, 198, 198)      0

conv2d_2 (Conv2D)            (None, 32, 196, 196)      9248

activation_2 (Activation)    (None, 32, 196, 196)      0

max_pooling2d_1 (MaxPooling2 (None, 32, 98, 98)        0

dropout_1 (Dropout)          (None, 32, 98, 98)        0

flatten_1 (Flatten)          (None, 307328)            0

dense_1 (Dense)              (None,<PHONE_NUMBER>2

activation_3 (Activation)    (None, 128)               0

dropout_2 (Dropout)          (None, 128)               0

dense_2 (Dense)              (None, 5)                 645

activation_4 (Activation)    (None, 5)                 0
Total params: 39,348,325
Trainable params: 39,348,325
Non-trainable params: 0

(903, 40000)
Press any key
samples_per_class -  180.6
Train on 577 samples, validate on 145 samples
Epoch 1/15
2019-02-13 11:51:24.120936: W T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:219] Allocator (GPU_0_bfc) ran out of memory trying to allocate 229.7KiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available.
2019-02-13 11:51:24.121381: W T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:219] Allocator (GPU_0_bfc) ran out of memory trying to allocate 43.07MiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available.
2019-02-13 11:51:24.121763: W T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:219] Allocator (GPU_0_bfc) ran out of memory trying to allocate 517.50MiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available.
2019-02-13 11:51:24.122119: W T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:219] Allocator (GPU_0_bfc) ran out of memory trying to allocate 16.0KiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available.
2019-02-13 11:51:24.122528: W T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:219] Allocator (GPU_0_bfc) ran out of memory trying to allocate 8.95MiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available.
2019-02-13 11:51:24.122870: W T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:219] Allocator (GPU_0_bfc) ran out of memory trying to allocate 362.55MiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available.
2019-02-13 11:51:34.125484: W T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:275] Allocator (GPU_0_bfc) ran out of memory trying to allocate 36.0KiB.  Current allocation summary follows.
2019-02-13 11:51:34.125745: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:630] Bin (256): 	Total Chunks: 54, Chunks in use: 54. 13.5KiB allocated for chunks. 13.5KiB in use in bin. 2.4KiB client-requested in use in bin.
2019-02-13 11:51:34.126030: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:630] Bin (512): 	Total Chunks: 8, Chunks in use: 8. 4.3KiB allocated for chunks. 4.3KiB in use in bin. 4.1KiB client-requested in use in bin.
2019-02-13 11:51:34.126288: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:630] Bin (1024): 	Total Chunks: 8, Chunks in use: 8. 10.0KiB allocated for chunks. 10.0KiB in use in bin. 8.9KiB client-requested in use in bin.
2019-02-13 11:51:34.127219: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:630] Bin (2048): 	Total Chunks: 7, Chunks in use: 7. 17.5KiB allocated for chunks. 17.5KiB in use in bin. 17.5KiB client-requested in use in bin.
2019-02-13 11:51:34.127699: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:630] Bin (4096): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-02-13 11:51:34.128251: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:630] Bin (8192): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-02-13 11:51:34.128905: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:630] Bin (16384): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-02-13 11:51:34.129145: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:630] Bin (32768): 	Total Chunks: 7, Chunks in use: 7. 252.0KiB allocated for chunks. 252.0KiB in use in bin. 252.0KiB client-requested in use in bin.
2019-02-13 11:51:34.129461: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:630] Bin (65536): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-02-13 11:51:34.130266: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:630] Bin (131072): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-02-13 11:51:34.131565: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:630] Bin (262144): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-02-13 11:51:34.131914: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:630] Bin (524288): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-02-13 11:51:34.132299: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:630] Bin (1048576): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-02-13 11:51:34.132716: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:630] Bin (2097152): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-02-13 11:51:34.133016: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:630] Bin (4194304): 	Total Chunks: 1, Chunks in use: 1. 4.88MiB allocated for chunks. 4.88MiB in use in bin. 4.88MiB client-requested in use in bin.
2019-02-13 11:51:34.133305: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:630] Bin (8388608): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-02-13 11:51:34.133632: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:630] Bin (16777216): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-02-13 11:51:34.133886: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:630] Bin (33554432): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-02-13 11:51:34.134146: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:630] Bin (67108864): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-02-13 11:51:34.134476: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:630] Bin (134217728): 	Total Chunks: 9, Chunks in use: 9. 1.36GiB allocated for chunks. 1.36GiB in use in bin. 1.32GiB client-requested in use in bin.
2019-02-13 11:51:34.134755: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:630] Bin (268435456): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2019-02-13 11:51:34.135005: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:646] Bin for 36.0KiB was 32.0KiB, Chunk State:
2019-02-13 11:51:34.135189: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>9C0000 of size 1280
2019-02-13 11:51:34.135336: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>9C0500 of size 256
2019-02-13 11:51:34.135522: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>9C0600 of size 256
2019-02-13 11:51:34.135668: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>9C0700 of size 256
2019-02-13 11:51:34.135815: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>9C0800 of size 256
2019-02-13 11:51:34.135976: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>9C0900 of size 1280
2019-02-13 11:51:34.138054: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>9C0E00 of size 256
2019-02-13 11:51:34.138189: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>9C0F00 of size 256
2019-02-13 11:51:34.138322: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>9C1000 of size 256
2019-02-13 11:51:34.138742: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>9C1100 of size 256
2019-02-13 11:51:34.138861: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>9C1200 of size 256
2019-02-13 11:51:34.138976: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>9C1300 of size 256
2019-02-13 11:51:34.139097: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>9C1400 of size 256
2019-02-13 11:51:34.139254: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>9C1500 of size 256
2019-02-13 11:51:34.139422: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>9C1600 of size 256
2019-02-13 11:51:34.139591: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>9C1700 of size 36864
2019-02-13 11:51:34.139740: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>9CA700 of size 157351936
2019-02-13 11:51:34.139893: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at 000000050AFDA700 of size 512
2019-02-13 11:51:34.140041: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at 000000050AFDA900 of size 2560
2019-02-13 11:51:34.140214: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at 000000050AFDB300 of size 256
2019-02-13 11:51:34.140365: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at 000000050AFDB400 of size 1280
2019-02-13 11:51:34.141268: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at 000000050AFDB900 of size 256
2019-02-13 11:51:34.141664: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at 000000050AFDBA00 of size 256
2019-02-13 11:51:34.142144: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at 000000050AFDBB00 of size 256
2019-02-13 11:51:34.142322: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at 000000050AFDBC00 of size 256
2019-02-13 11:51:34.142503: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at 000000050AFDBD00 of size 36864
2019-02-13 11:51:34.142683: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at 000000050AFE4D00 of size 157351936
2019-02-13 11:51:34.142842: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>5F4D00 of size 2560
2019-02-13 11:51:34.143002: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>5F5700 of size 36864
2019-02-13 11:51:34.143164: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>5FE700 of size 36864
2019-02-13 11:51:34.143326: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>607700 of size 157351936
2019-02-13 11:51:34.143540: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at 000000051DC17700 of size 157351936
2019-02-13 11:51:34.143700: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>227700 of size 512
2019-02-13 11:51:34.143859: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>227900 of size 512
2019-02-13 11:51:34.144020: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>227B00 of size 512
2019-02-13 11:51:34.144198: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>227D00 of size 2560
2019-02-13 11:51:34.145482: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>228700 of size 2560
2019-02-13 11:51:34.145767: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>229100 of size 256
2019-02-13 11:51:34.145918: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>229200 of size 256
2019-02-13 11:51:34.146057: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>229300 of size 256
2019-02-13 11:51:34.146690: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>229400 of size 1280
2019-02-13 11:51:34.146923: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>229900 of size 1280
2019-02-13 11:51:34.147200: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>229E00 of size 256
2019-02-13 11:51:34.148136: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>229F00 of size 256
2019-02-13 11:51:34.148334: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>22A000 of size 256
2019-02-13 11:51:34.148606: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>22A100 of size 256
2019-02-13 11:51:34.148754: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>22A200 of size 256
2019-02-13 11:51:34.148912: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>22A300 of size 256
2019-02-13 11:51:34.149065: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>22A400 of size 256
2019-02-13 11:51:34.149256: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>22A500 of size 256
2019-02-13 11:51:34.150007: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>22A600 of size 256
2019-02-13 11:51:34.150184: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>22A700 of size 256
2019-02-13 11:51:34.150312: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>22A800 of size 256
2019-02-13 11:51:34.150519: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>22A900 of size 256
2019-02-13 11:51:34.150672: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>22AA00 of size 256
2019-02-13 11:51:34.150858: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>22AB00 of size 256
2019-02-13 11:51:34.151029: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>22AC00 of size 256
2019-02-13 11:51:34.151234: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>22AD00 of size 256
2019-02-13 11:51:34.152097: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>22AE00 of size 256
2019-02-13 11:51:34.152307: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>22AF00 of size 256
2019-02-13 11:51:34.152456: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>22B000 of size 256
2019-02-13 11:51:34.152632: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>22B100 of size 256
2019-02-13 11:51:34.152784: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>22B200 of size 256
2019-02-13 11:51:34.152940: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>22B300 of size 768
2019-02-13 11:51:34.153120: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>22B600 of size 5120000
2019-02-13 11:51:34.153280: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>70D600 of size 256
2019-02-13 11:51:34.154047: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>70D700 of size 256
2019-02-13 11:51:34.154250: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>70D800 of size 157351936
2019-02-13 11:51:34.154446: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>D1D800 of size 157351936
2019-02-13 11:51:34.154600: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at 000000053A32D800 of size 157351936
2019-02-13 11:51:34.154777: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>93D800 of size 512
2019-02-13 11:51:34.154910: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>93DA00 of size 512
2019-02-13 11:51:34.155061: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>93DC00 of size 512
2019-02-13 11:51:34.155260: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>93DE00 of size 1280
2019-02-13 11:51:34.156003: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>93E300 of size 1280
2019-02-13 11:51:34.156188: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>93E800 of size 1280
2019-02-13 11:51:34.156393: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>93ED00 of size 2560
2019-02-13 11:51:34.156583: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>93F700 of size 2560
2019-02-13 11:51:34.156841: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>940100 of size 2560
2019-02-13 11:51:34.157056: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>940B00 of size 256
2019-02-13 11:51:34.157309: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>940C00 of size 256
2019-02-13 11:51:34.157529: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>940D00 of size 256
2019-02-13 11:51:34.158486: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>940E00 of size 256
2019-02-13 11:51:34.158625: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>940F00 of size 256
2019-02-13 11:51:34.158760: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>941000 of size 256
2019-02-13 11:51:34.158894: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>941100 of size 256
2019-02-13 11:51:34.159031: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>941200 of size 36864
2019-02-13 11:51:34.159227: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>94A200 of size 36864
2019-02-13 11:51:34.159428: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>953200 of size 36864
2019-02-13 11:51:34.159597: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>95C200 of size 256
2019-02-13 11:51:34.159812: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>95C300 of size 256
2019-02-13 11:51:34.160009: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>95C400 of size 256
2019-02-13 11:51:34.160188: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at<PHONE_NUMBER>95C500 of size 160581120
2019-02-13 11:51:34.161260: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:665] Chunk at 000000054D280B00 of size 200497920
2019-02-13 11:51:34.161488: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:671]      Summary of in-use Chunks by size:
2019-02-13 11:51:34.161919: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:674] 54 Chunks of size 256 totalling 13.5KiB
2019-02-13 11:51:34.162069: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:674] 7 Chunks of size 512 totalling 3.5KiB
2019-02-13 11:51:34.162289: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:674] 1 Chunks of size 768 totalling 768B
2019-02-13 11:51:34.162485: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:674] 8 Chunks of size 1280 totalling 10.0KiB
2019-02-13 11:51:34.162658: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:674] 7 Chunks of size 2560 totalling 17.5KiB
2019-02-13 11:51:34.162889: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:674] 7 Chunks of size 36864 totalling 252.0KiB
2019-02-13 11:51:34.163254: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:674] 1 Chunks of size 5120000 totalling 4.88MiB
2019-02-13 11:51:34.164604: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:674] 7 Chunks of size 157351936 totalling 1.03GiB
2019-02-13 11:51:34.164771: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:674] 1 Chunks of size 160581120 totalling 153.14MiB
2019-02-13 11:51:34.164943: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:674] 1 Chunks of size 200497920 totalling 191.21MiB
2019-02-13 11:51:34.165153: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:678] Sum Total of in-use chunks: 1.37GiB
2019-02-13 11:51:34.165372: I T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:680] Stats:
Limit:<PHONE_NUMBER>
InUse:<PHONE_NUMBER>
MaxInUse:<PHONE_NUMBER>
NumAllocs:                      98
MaxAllocSize:            200497920
2019-02-13 11:51:34.165730: W T:\src\github\tensorflow\tensorflow\core\common_runtime\bfc_allocator.cc:279] **************************************************************************************************xx
2019-02-13 11:51:34.166009: W T:\src\github\tensorflow\tensorflow\core\framework\op_kernel.cc:1275] OP_REQUIRES failed at conv_ops.cc:682 : Resource exhausted: OOM when allocating tensor with shape[32,32,3,3] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
Traceback (most recent call last):
File "C:/Users/Administrator/Desktop/CNNGestureRecognizer-master/trackgesture.py", line 375, in
Main()
File "C:/Users/Administrator/Desktop/CNNGestureRecognizer-master/trackgesture.py", line 209, in Main
myNN.trainModel(mod)
File "C:\Users\Administrator\Desktop\CNNGestureRecognizer-master\gestureCNN.py", line 355, in trainModel
verbose=1, validation_split=0.2)
File "C:\Users\Administrator\Python\Python36\lib\site-packages\keras\engine\training.py", line 1039, in fit
validation_steps=validation_steps)
File "C:\Users\Administrator\Python\Python36\lib\site-packages\keras\engine\training_arrays.py", line 199, in fit_loop
outs = f(ins_batch)
File "C:\Users\Administrator\Python\Python36\lib\site-packages\keras\backend\tensorflow_backend.py", line 2715, in call
return self._call(inputs)
File "C:\Users\Administrator\Python\Python36\lib\site-packages\keras\backend\tensorflow_backend.py", line 2675, in _call
fetched = self._callable_fn(*array_vals)
File "C:\Users\Administrator\Python\Python36\lib\site-packages\tensorflow\python\client\session.py", line 1382, in call
run_metadata_ptr)
File "C:\Users\Administrator\Python\Python36\lib\site-packages\tensorflow\python\framework\errors_impl.py", line 519, in exit
c_api.TF_GetCode(self.status.status))
tensorflow.python.framework.errors_impl.ResourceExhaustedError: OOM when allocating tensor with shape[32,32,3,3] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
[[Node: conv2d_2/convolution = Conv2D[T=DT_FLOAT, _class=["loc:@training/Adadelta/gradients/conv2d_2/convolution_grad/Conv2DBackpropFilter"], data_format="NCHW", dilations=[1, 1, 1, 1], padding="VALID", strides=[1, 1, 1, 1], use_cudnn_on_gpu=true, _device="/job:localhost/replica:0/task:0/device:GPU:0"](activation_1/Relu, conv2d_2/kernel/read)]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.
 [[Node: dense_2/BiasAdd/_73 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_222_dense_2/BiasAdd", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]

Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.

OOM stands for out of memory, my guess would be that your setup might not have enough RAM.
What config are you running on ?

Closing this as there is no further response from the filer.


Increase the hardcoded NFS client timeout

We use a 3s timeout, with 3 retransmission tries before failure.
After each timeout the timeout will be linearly increased (3s, 6s, 9s)
This means that an IO operation has a maximum runtime of 18s before failure.
For the HA solution we want to use hard mode, which will lead to an infinite
retry, since in that mode we want to be able to guarantee the survival of
the workload pods instead of having to terminate them.
longhorn/longhorn#2528
Signed-off-by: Joshua Moody<EMAIL_ADDRESS>

Should we expose the setting to the user instead of hard-coding it?


feat: Make soft deletes work with mssql

fixes fot mssql soft_delete and bulk update
https://github.com/uptrace/bun/issues/429

What do you think about renaming UpdateAliasAsMultiTable to UpdateFromTable? I can't understand the logic behind UpdateAliasAsMultiTable name... Then this PR should be ready for merging.
Overall this looks like a nice addition for mssql driver, but we still need to change soft-deletes to generate simpler queries, e.g. instead of
UPDATE "soft_deletes" SET "deleted_at" = [TIME] FROM "soft_deletes" AS "soft_delete" WHERE "soft_delete"."deleted_at" IS NULL AND ("soft_delete"."id" = NULL)

should be
UPDATE "soft_deletes" SET "deleted_at" = [TIME] WHERE "soft_deletes"."deleted_at" IS NULL AND ("soft_deletes"."id" = NULL)

Probably a task for a separate PR.

Done. Hopefully would not be confused with  update from select  statement
Other things that could be adressed:

There are probably other features in mssql that could be enabled.
unique doesnt work with soft delete (any db actually). It is documented but I haven't found an issue. have test. can probably look into it
benchmark performance is quite poor in comparison

What do you think about renaming UpdateAliasAsMultiTable to UpdateFromTable? I can't understand the logic behind UpdateAliasAsMultiTable name... Then this PR should be ready for merging.
Overall this looks like a nice addition for mssql driver, but we still need to change soft-deletes to generate simpler queries, e.g. instead of
UPDATE "soft_deletes" SET "deleted_at" = [TIME] FROM "soft_deletes" AS "soft_delete" WHERE "soft_delete"."deleted_at" IS NULL AND ("soft_delete"."id" = NULL)

should be
UPDATE "soft_deletes" SET "deleted_at" = [TIME] WHERE "soft_deletes"."deleted_at" IS NULL AND ("soft_deletes"."id" = NULL)

Probably a task for a separate PR.

unique doesnt work with soft delete (any db actually). It is documented but I haven't found an issue. have test. can probably look into it

Let's add the test even if it does not pass. t.Skip is fine.
I guess you've seen https://bun.uptrace.dev/guide/soft-deletes.html#unique-indexes already

benchmark performance is quite poor in comparison

Again, let's add the benchmark even if results are not impressive. It is good to know the number anyway.


Get-DbaDbMirror - Add new parameter for Database filtering

Type of Change

[x] New feature (non-breaking change, adds functionality, fixes #5881 )

We don't have integration tests for this and I don't have any mirrored databases right now (tho I can explore in appveyor). @BilliousBT can you give this a shot?
Ty!

K - I tested the heck out of this locally but can't run them on appveyor because the underlying hostname has to be different. In the future when I move most commands to GH Actions, we'll have two containers that'll work

lol sql on linux does not support mirroring, guess we'll have to rely on my lab

It turns out that as I was adding this, I found some other bugs, so I added in the fixes for them.

Please ignore that -Match casing, I need to figure out how to get VS Code to behave again.
Anyway! WOOHOO! Even though it says this

I still got it to work on Linux

Ok, see my comments, that is all I found.

Thanks for the review! Updating and merging 🥳


chore: pin constructs dep

Using a caret dependency in a module built with jsii < 1.3.2 results in an invalid version range in the package manifest file for dotnet artifacts:
See: [2.0.1, 3.0.0-0)
<?xml version="1.0" encoding="utf-8"?>
<package xmlns="http://schemas.microsoft.com/packaging/2013/05/nuspec.xsd">
  <metadata>
    <id>Org.Cdk8s</id>
    <version>0.25.0</version>
    <authors>Amazon Web Services</authors>
    <owners>Amazon Web Services</owners>
    <requireLicenseAcceptance>false</requireLicenseAcceptance>
    <license type="expression">Apache-2.0</license>
    <licenseUrl>https://licenses.nuget.org/Apache-2.0</licenseUrl>
    <description>Cloud Development Kit for Kubernetes (Stability: Experimental)</description>
    <tags>cdk kubernetes k8s constructs</tags>
    <repository type="git" url="https://github.com/awslabs/cdk8s.git" />
    <dependencies>
      <group targetFramework=".NETCoreApp3.1">
        <dependency id="Amazon.JSII.Runtime" version="[1.1.0, 2.0.0)" exclude="Build,Analyzers" />
        <dependency id="Constructs" version="[2.0.1, 3.0.0-0)" exclude="Build,Analyzers" />
      </group>
    </dependencies>
  </metadata>
</package>

This results in the following error when trying to publish:
error: Response status code does not indicate success: 400 (The NuGet package contains an invalid .nuspec file. The error encountered was: 'The package manifest contains an invalid Version: '3.0.0-0''. Correct the error and try again.)

This issue was fixed in jsii a while back. The problem is that we cannot upgrade the jsii version because it will conflict with the jsii version of constructs. We can't upgrade constructs because it introduces some breaking changes with regards to tokenization, and would require some non trivial effort.
As a work around, I suggest to pin constructs dependency to 2.0.1, avoiding the whole caret invalid version range issue.
In practice, this pinning has no real affect since the next version of constructs is 3.0.0, there is no version in between.
By submitting this pull request, I confirm that my contribution is made under the terms of the Apache-2.0 license

Mmmkay

Hhh yeah, that is definitely the correct sentiment for this :)


MCCachingModule and replicate_in_memory=False

Is your feature request related to a problem? Please describe.
Not really a feature request but more of a discussion about the choice of replicate_in_memory in the ModelWrapper when using the new MCCachingModule.
I noticed that the MCCachingModule documentation uses replicate_in_memory=False in the experiments. Before, I always used True in my code, which is also used in experiments/vgg_mcdropout_cifar10.py as True is the default. As such, I compared runtimes on an NVIDIA RTX A5000.

Number of iterations
20
50
100

Regular - False
0:16
0:39
1:18

Regular - True
0:11
0:28
0:55

MCCaching - False
0:09
0:20
0:40

MCCaching - True
0:12
0:30
0:57

Findings:

For False, MCCaching is around 45%-50% faster than Regular. (This is lower than the 70% found for the GeForce 1060Ti)
"MCCaching - False" is around 20%-30% faster than "Regular - True"
For True, MCCaching is around 5% slower than Regular

Do you have an idea why MCCaching and replicate_in_memory have such interaction effects?
Describe the solution you'd like
In the documentation, it might be useful to discourage the combination of MCCaching and replicate_in_memory=True as this is 5% slower than the "Regular - True" scenario.
Describe alternatives you've considered
/
Additional context
/

Hello,
we should definitely explain this better, but the ideal case will always be MCCaching + replicate_in_memory=False.
MCCaching works by caching the output of each layer so that it doesn't recompute during MCDropout.
When we use replicate_in_memory=False, the MC Sampling loop is replaced with:
predictions = [model(input) for _ in range(Iterations)]

This means that we compute a lot of redundant features. When adding MCCaching, we compute the high-level features (before Dropout layers) only once.
I will add a warning in the code directly I think. If there is a caching layer somewhere in the model we should warn that it is not optimized.

Hello, thank you for the response. I agree that a warning in the code is most useful. In the documentation, a brief explanation of how the module works internally might indeed also encourage users to try it out.


Querydsl error during Ara installation

I'm trying to instal Ara on a MacOs Mojave version 10.14.5
I've followed the instruction on 'How to build it and make it work in 2 minutes'.
I make sure to start the ara-db before 'mvn clean install -Pdev -DskipPitest -Dmaven.test.skip=true'
But during this install, i get an error on querydsl (refer to screenshot).
Docker Version is <IP_ADDRESS>

Hi @sarchkak !
Unfortunately, this bug is already identified and a fix is in progress (see #97 ). We will provide the new version this month.
On your local case, could you check that your docker container is up and running on port 5432, which needs to be exposed on host ?

Hi @sarchkak
We rework the way ARA is installed locally to remove any dependencies with Querydsl in the version 4.0.0 (which is now on master).
I strongly encourage you to use it and give us any feedback :D
Thanks for your interest in ARA !
dktsni


[RAC-5468]add docker logout for release_docker.sh

At publishing docker images stage in the Jenkins job, there is "login" only, but not "logout". It's not reasonable.

:+1


Container ports publishing: make it work with remote docker hosts

At present the IP is hard-coded to <IP_ADDRESS>
workaround example: ssh -N -L <IP_ADDRESS>:8000:<IP_ADDRESS>:8000 your-server

Done in 816842f


Add download data for May 2020

The May download counts for both the Circe organization (3,181,263) and Typelevel (7,303,849) are down from April, which seems to have been an anomaly. Both are up slightly from March, and back to roughly the upward trajectory we saw before April.

Codecov Report

Merging #1498 into master will decrease coverage by 0.13%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master    #1498      +/-   ##
==========================================
- Coverage   86.02%   85.88%   -0.14%
==========================================
  Files          58       58
  Lines        2197     2197
  Branches      107      107
==========================================
- Hits         1890     1887       -3
- Misses        307      310       +3

Impacted Files
Coverage Δ

...d/src/main/scala/io/circe/NonEmptySeqDecoder.scala
91.66% <0.00%> (-8.34%)
:arrow_down:

...d/src/main/scala/io/circe/cursor/ArrayCursor.scala
61.53% <0.00%> (-7.70%)
:arrow_down:

.../core/shared/src/main/scala/io/circe/Decoder.scala
85.05% <0.00%> (-0.82%)
:arrow_down:

...re/shared/src/main/scala/io/circe/JsonNumber.scala
96.38% <0.00%> (ø)

...rc/main/scala/io/circe/numbers/BiggerDecimal.scala
85.38% <0.00%> (ø)

...les/core/shared/src/main/scala/io/circe/Json.scala
80.44% <0.00%> (+0.55%)
:arrow_up:

...scala/io/circe/shapes/LabelledHListInstances.scala
96.29% <0.00%> (+3.70%)
:arrow_up:

Continue to review full report at Codecov.

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Fix position and color of scrolldown fab

Addresses issue #3
Updated screenshot:

@sumedh123 Please review

@ajayns can you recheck this? doesn't seem to be in the middle

@sumedh123 It's actually the logo that's misaligned. Ref: #6