Shadowrun 5th Edition (Advanced) spirits and sprites disappeared

Someone has edited the sheet and in doing so, deleted necessary data that has completely set back my game. If someone is going to continue editing this sheet, please do so without erasing data or making it worse or breaking it, as so many of these edits tend to do. Currently every sprite/spirit that was recorded in every single sheet has vanished and that data is now lost.

Fixed in #10764
If you think my changes make the sheet worse formulate it in a professional and objective way. Explain why it is worse, what did you like before the changes were made, how it impacts you and what are better alternatives

I disagree this should be closed. Alas I have no other option in my reply but to close it. @nmbradley  @mperes The updates continue to erase data, make the sheet worse, and do not match original aesthetic. I do not know who is to blame, as I never accused anyone in particular of being the source of such reckless changes.
To this point, the previous complaint was voiced objectively (the complaint was that edits were made that deleted data and ruined games. That still stands and the only request was to not push edits that erased key data to multi-year long campaigns) and thus warranted no reply: key data was deleted during a needless edit. I explained how it impacted me: key data was deleted, setting back my game. I explained why it was worse: key data was deleted. The better alternative would be: do not push edits that delete data. In light of these suggestions that were already answered in the original post, the suggestion updates be sent to me in advance seemed facetious. The same issues continued after this post on a bimonthly basis.
Nearly every update replaces a pleasing aesthetic with one that no longer matches the original aesthetic and intent. Arrows that previously matched the aesthetic have been moved and changed to an inferior aesthetic and position. Strange needless additions to skills remain, such as a random add button under perception. It serves no purpose and still exists. The roll results have changed to exclude data from rolls about specialties, where specialties were previously indicated. Reaction buttons in combat cannot be resolved without tokens, and not every gm uses tokens in every skirmish. Similarly, when one person does not resolve combat via these various buttons of mismatched aesthetic and varying positions, they cannot send any other dice roll to chat without much clicking and refreshing, even if they resolved it without using said buttons. The aesthetic of totals has needlessly changed to look like an editable box replacing the unique box that clearly could not be edited. The fonts have been changed to an aesthetic that no longer fit the original sheet.
There was no more professional way to request to not make frivolous edits, especially ones that delete data (as has happened many times in the past). But the edits that delete data have been the most difficult to compensate for. I have used this sheet for 7ish years. Sometimes the edits work. Routinely this sheet has been hacked apart and broken so as to be unusable (rolls not working, stats and edge broken, the sheet turning to nonsense code, broken fonts, broken lines, roll buttons failing or disappearing) and then barely cobbled together again a week or two later. Using this sheet is frequently a matter of crossing fingers and hoping no one ruins it any further. My intent is not to be harsh, but I close this topic under duress and expect to open another soon the next time something is broken, data is erased, or the original aesthetic is destroyed.
Again, I do not know who is to blame for frivolous edits, so this is not a targeted response, merely a plea. Please stop making ugly, sheet breaking, data erasing, session ruining edits to the sheets. Please try to respect the original edit and refrain from pushing changes before they re ready.

If you think that this issue is not resolved, dont close it. If this issue was not resolved, why didnt you respond since half a year?
Answering to your rant: You can blame me, since I am the one editing the sheet. I maintain it since 4 years. So all recent changes and bugfixes were done by me.
None of your other issues was ever reported to me. Everyone I talked about like the changes I did.
Which data was deleted? Whenever I moved an obsolete dataset to a new one I wrote a converter that was tested by multiple people and worked. If you had issues, why didnt you report them?
Sending you upcoming changes it not facetious, I only have so much testdata and if you run into issues repeatedly that others dont I think you should really give it a thought.
Aesthetics are discussable, but I am really intrigued by you claiming that I replaced arrows. The recent UI changes where replacing notes checkboxes with arrows. So please add screenshots or point me directly to where it happened. If it was not intentional I am happy to fix it.
If you cannot figure out what the "random" add button below perception is you could try it out. But since your tone is quite dismissive I guess it is rather that it does not match your aesthetic.
Roll results have changed? I didnt touch anything about that for over a year. If that was an issue, why didnt you report it?
Reaction buttons in combat cannot be resolved without tokens, and not every gm uses tokens in every skirmish. => That is true and no problem. The buttons are quite small, so I thought people will just ignore it. But I can add an option to hide it.
Similarly, when one person does not resolve combat via these various buttons of mismatched aesthetic and varying positions, => Varying positions? You mean like, when there are multiple buttons they space out equally below the roll? I guess I need to see some screenshots to get what you mean.
they cannot send any other dice roll to chat without much clicking and refreshing, even if they resolved it without using said buttons. => That has nothing to do with the buttons. If this is happening to you or your fellow players you should open a help desk ticket
The aesthetic of totals has needlessly changed to look like an editable box replacing the unique box that clearly could not be edited. => Nothing I changed, Roll20 had a style update
The fonts have been changed to an aesthetic that no longer fit the original sheet. => Nothing I changed, Roll20 had a style update
There was no more professional way to request to not make frivolous edits, especially ones that delete data (as has happened many times in the past) => That is untrue. If you dont realise which tone and words you are using, you should reflect about it. Also I am intrigued how many times your data and which data was deleted. I think there might be your main problem. You are upset about something, that most likely has nothing to do with the sheet edits.
Routinely this sheet has been hacked apart and broken so as to be unusable (rolls not working, stats and edge broken, the sheet turning to nonsense code, broken fonts, broken lines, roll buttons failing or disappearing) and then barely cobbled together again a week or two later. => This sounds like a browser issue. Which browser are you using? Neither me nor my playgroup or any playgroup I talked to had such an issue since more then 2 years. As far as I remembered it happend once and was fixed the next day.
Using this sheet is frequently a matter of crossing fingers and hoping no one ruins it any further. => If you have a paid roll20 account you can decouple your game from the automatic updates. Then this would be no problem for you.
expect to open another soon the next time something is broken, data is erased, or the original aesthetic is destroyed => Please do so, that is way to work with git issues. One issue per problem you encounter
Again, I do not know who is to blame for frivolous edits, so this is not a targeted response, merely a plea. Please stop making ugly, sheet breaking, data erasing, session ruining edits to the sheets. Please try to respect the original edit and refrain from pushing changes before they're ready. => So what is happening since several years?
I cannot follow your line of thinking. The whole way you phrase your complaint is to say that someone is making everything worse on purpose. If you can not handle change, that is a problem that you got and Roll20 provides way to circumvent it.

Hey folks,
I am going to close this conversation, to allow you both to step back from it and comport yourselves.
I will say to both of you, in general, to remind yourselves of the human on the other side of the screen; nobody is here with bad intentions. Also, to remember that a lot can be lost through the medium of text, particularly via a service that is used by people of multiple different nationalities and levels of proficiency with written English.
@thesweetalpaca while I acknowledge it can certainly be frustrating to have a sheet change and erase data, it is worth bearing in mind that the work that 95% of sheet development is unpaid and difficult work, enacted purely for the love of the community and the game the individual developer is trying to support. I have the utmost faith that these changes were not made maliciously.
I also acknowledge that it can be difficult for non-technical people to know precisely what information to provide when encountering issues like this; but I can say with considerable experience that the information you provided in your original post would not have been enough for Stexinator to identify the issue you were experiencing. I see the initial response to be a good faith, albeit blunt, attempt to engage with you and diagnose the root cause of the issue.
Furthermore, I have absolutely no doubt that Stexinator would delight having additional assistance and guidance on the direction of this sheet. The sheet repository is intended to be a community endeavor; you will arrive at a better sheet if you cooperate and communicate.
To that end, once you have both had a chance to cool off, please re-post this issue and provide as clear, detailed, and objective data and feedback as you can manage. Illustrate with examples of how the issue can cause problems. Screenshots are worth a thousand words in this regard, and they're pretty easy to copy and paste into a github issue. Make several issues if there are several points to be made; that's what they're there for.
@Stexinator I trust you will be open to politely discussing Alpaca's concerns, and we can go from there.
I promise you that if the two of you cooperate in this way, you will end up with a sheet that you are both more satisfied with.


500 Internal Server Error's aren't instances of the DiscordAPIError class.

Please describe the problem you are having in as much detail as possible:
Stack trace: https://pastebin.com/raw/m7umq6q1
This messes up any error handlers that check if the error object is an instance of the DiscordAPIError class.
Include a reproducible code sample here, if possible:
Wait for a discord outage lol
Further details:

discord.js version: 11.1.0

node.js version: 8.1.3

Operating system: Ubuntu 16.04.2

Priority this issue should have: low

[ ] I found this issue while running code on a user account

[ ] I have also tested the issue on latest master, commit hash:

this is purposeful. Discord creates a specific body in 4xx errors which the APIError is designed to handle which isn't guaranteed or even likely to be there on a 5xx

The only additional property on the DiscordAPIError class is the code, which as far as I know, all internal server errors have. I do not understand why a new instance of this error class couldn't be thrown using the same error code and message of the original internal server error.

The bottom line remains. DiscordAPIError is intended to be used exclusively for regular API errors that are the result of a client-side issue. Any non 4xx error codes should be handled properly on your end. It is possible that we could make a more inclusive error that spans all Discord errors, which DiscordAPIError would then extend.

a 5xx error can come from any source in discord's backend chain going from cassandra to loqui to flask to google to cloudflare to you. These errors may not have a JSON body or may have no body at all. As of v11.2 we will automatically retry on a 5xx error anyway, so you do not need to worry about it.

Maybe possibly add a ServerError instance for such events?
It's Hacktoberfest after all :^)

We have HTTPError in discord.js 12-dev.


fix: unbreak Details component

Motivation
After merge #5341 our custom component for details element no longer work correctly, so this PR rolls back changes made in that PR.
Have you read the Contributing Guidelines on pull requests?
Yes
Test Plan
Current state (https://docusaurus.io/docs/markdown-features#details):

Expected one - fixed (https://deploy-preview-5364--docusaurus-2.netlify.app/docs/markdown-features#details):

Related PRs
(If this PR adds or changes functionality, please take some time to update the docs at https://github.com/facebook/docusaurus, and link to your PR here.)

@Josh-Cena this isn't the first time something is broken after your refactoring and I have to fix it, so please check your changes carefully, we don't have dedicated QA to check all incoming PRs, so it's very easy to break things!

Oops, didn't catch that, my bad 😅 Thanks for fixing, I will watch out more carefully next time
After some thinking I think the a11y is wrong in warning that details element is noninteractive because it is clickable

Not all warnings reported by ESLint need actually be fixed. In my opinion, current implementation of details corresponds well with a11y.

Thanks
My fault, I should have tested better the other PR, didn't think it would break anything


Universal

Hello
Any idea if this works well with Universal? trying to find a solution that would work with server side rendering..but most ones I tried do direct access to window  object.

Okay nvm just saw it uses jquery so I guess it wont work.


Fix parsing of docker options.

Fix parsing DOCKER_OPTS to correctly parse them as shell words, rather than splitting on whitespace.
Closes #769.

I think parsing them as a Unix shell is the best idea, since users are likely going to be using a Unix shell, it handles simple cases well, and even on Windows CMD this works for most default cases (unsure about Powershell).


EnergyBar & PowerLine no data display

Hi,
First of all sorry for my English.
I am trying this awesome module and it seems to work very well with my Tesla Powerwall, but I have a problem with EnergyBar and PowerLine.
The other graphs work fine but nothing is shown in Powerline and EnergyBar.
I am probably missing something, can I ask for help?
Thank you

Looks like none of the data from the Tesla API is populating; EnergyBar and PowerLine are purely driven by that data, while the others combine local and cloud data.  I don't see a prompt for you to sign in; is the Tesla username in the config file?

(And if English is not your primary language, feel free to contribute a translation to whatever language is!  You'd just copy the translations/en.json file to your own language's code, then edit the strings with the text which should appear there.)

Hi Mike,
Tanks for your quickly replay and for your explanation.
I have tray to insert the "TeslaAPIUsername" in the config file, and the system say me to go to "MMM-Powerwall/auth", but when insert a password (right user & right password of Tesla account) I receive this:

Thank you in advance for your help.
P.S. I will try to translate the file into Italian

How do I send you the translations/it.json file?

That seems to be a timeout issue that I've seen across multiple HTTP clients within Node when attempting to reach the Tesla auth server.  I have two machines it happens on, and two it doesn't, and I haven't yet figured out the difference between them.

I'm very sorry for the delay -- I eventually gave up trying to solve the problem and worked around it instead.  Can you try the python branch (PR #49) and see if that fixes things for you?
BTW, the translations/it.json file would just go in a separate pull request.

Thank you Mike, now work for me.

Delighted to hear it!  I apologize again for letting it go so long.  I still don't understand why some Node installs can't talk to that API, but Python doesn't seem to have that problem.
If you browse to the translations/ folder on GitHub and try to upload your file, it should offer to create a fork for you since you don't have write access.  Once you have a fork with a change in it, it should prompt you to create a PR to add the file back to this repo.

Hi Mike,
I have created a pull request with the it.json file....  I hope it's right.
Thank you


Making description optional

I just ran into this issue. What can we expect a new release?

@raymondfeng Please upgrade to v1.0.8, where the issue  has been resolved.


Support aemanalyser-maven-plugin in the generated projects (#533)

Description
AEMaaCS provides extended analysis of projects in the build and deployment pipeline. This includes running the Feature Model Analysers on the content packages. If these analysers find a problem they will fail the build and the developer needs to rectify the problem.
This can be problematic for developers as there is an amount of time between these failures in the deployment pipelines and the actual development of the content packages.
The new aemanalyser-maven-plugin makes it possible to run these analysers that are already running in the pipeline on the developer's local machine as part of the Maven build. This will give much quicker feedback to the developer and shortens the developer life cycle.
Note: the aemanalyser-maven-plugin currently under development, this draft PR refers to a SNAPSHOT version of it, we need to get that plugin released before we can use it from this archetype (hence the draft PR).
Motivation and Context
Shorten the development lifecycle and provide early feedback.
How Has This Been Tested?
It has been tested by running the following commandline on my branch:
mvn -B archetype:generate \
 -D archetypeGroupId=com.adobe.aem \
 -D archetypeArtifactId=aem-project-archetype \
 -D archetypeVersion=25-SNAPSHOT \
 -D appTitle="Test1" \
 -D appId="test1" \
 -D groupId="com.mysite

And then running mvn install to see if the analysis is triggered.
The changes to the archetype introduce a new module which sole purpose is to run the analysis. There are no changes needed to the other projects, just an extra dependency and an extra module referenced in the top level pom.
If everything is good then the build will just complete for the developer as before. If the analysers find issues then the build of the new analyse module will fail.
Types of changes

[ ] Bug fix (non-breaking change which fixes an issue)
[x] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to change)

Closing PR due to Java 8 related issue.


Allow Request Transformer to dynamically modify upstream API url

Plugin allows modification of body, query parameters, and headers. It does not allow to modify URL path itself. To use upstream API with URL structure shaped RESTfully (e.g /customer/123/videos/234) where 123 comes from Kong itself (other plugins) is impossible (not original request).
We can dynamically attach 123 as part of query parameters like ?blah=123 for instance but this is not enough when working with modern resource-based RESTful APIs.
Please up-vote this request!

Hey @rdzak,
Thanks for the submission. The Request Transformer plugin available in Mashape Enterprise does indeed have the functionality! This is also noted in the open source request transformer plugin docs (https://getkong.org/plugins/request-transformer/).
BTW, in the future, please try to reserve GitHub issues for actual issues running Kong, not feature or support requests. This is noted in the boilerplate when you create a new issue. :) We can absolutely continue the ongoing discussion in the mailing list: https://groups.google.com/forum/#!topic/konglayer/b3QAaUdOCb4. Please also try to avoid cross-posting like this, as it tends to cause confusion. Thanks!

Apologies - I have see similar posts here so I followed the pattern. From the note you mentioned in https://getkong.org/plugins/request-transformer/ I do not get that the functionality I described indeed exists. There is no mention of ability to place arbitrary dynamic data (not coming from request content, but from other plugins) into upstream variables like customers/{123}/videos/345 for 123 being in my case consumer_id (from auth plugin).


Interactive Documentation: Container does not have font Noto Sans installed

Discussed in https://github.com/ManimCommunity/manim/discussions/4047
It would be nice if the font was added to the built docker image.

for adding the font into the image,
will using the COPY command to copy from a folder into the image be fine?
like COPY fonts/noto-sans.ttf /usr/share/fonts/truetype
or wget should only be used?

@behackl please review this PR. feedback appreciated!


When a gem remove rbi/ folder, sorbet will raise error

Input

Remove rbi/ folder from sorbet-rails.
Reinstall the gem.
Run srb tc

Observed output
It raises error: "cannot find sorbet-rails/rbi/` folder
Expected behavior
It shouldn't raise error at all, by rebuilding the cache due to Gemfile change..
Or there should be an easy way to resolve the error  (eg srb rbi clear-cache)

Going to close this in favor of Tapioca
https://sorbet.org/blog/2022/07/27/srb-tapioca


Handle b'' strings in Python 3

Adds logic to fix bug described https://github.com/splunk/splunk-sdk-python/issues/275 where byte strings b'' do not work for indexing or concatenation in Python 3. This causes ReportingCommands to fail if they have a map() func.

The failed travis CI is unrelated to the code changes. c7f9a0c and 038138f are identical apart from a dummy file used to trigger the build.

I'm hitting the same bug.
Can someone merge this please?

After some investigation: I believe that we have fixed this issue as a side effect of fixing some other Python 3-related problems in 1.6.13. This code seems to be covered in tests/searchcommands/test_searchcommands_app.py::TestSearchCommandsApp::test_sum_as_unit which used to fail when run in Python 3, but now works.
Closing this PR.


Patch v4.12.3

Description
Here is the patch merge for v4.12.3
Please have a final review, and let me know if you spot anything!

Should the notes for this patch merge be part of the PR?


Display on bigger resolution

using 2560×1440  and multiple monitor, the overlay goes to the other monitors.
using x1080 shows correctly.

using 0.5.1

Using 0.5.3 map overlay on left or center fixes the issue.
Still broken if on right side.

fixed a window position bug while set postion=1 in v0.6, you can check if this resolved your problem

Fixed.


Adding cypher middleware

Description
As a user I want to be sure the content I upload/download it's available for me only and the people I share it with.
Acceptance Criteria

[x] Create a cypher middleware to validate if the content requested/sent is being attached to a public key
[x] Create a cypher function which return a hash to be shared

cryptography utilities added for decrypt/encrypt files before download/upload them

cryptography utils added
API endpoints added for upload and get files
(de)crypting file middleware added

Evidence of POST endpoint working

Bugs fixed, content uploaded and download successfully from their endpoints
evidence:


RTSP over UDP

I was wondering if it is possible to reproduce an RTSP content on UDP instead of TCP. If it is, how can I do it?
Thanks for this amazing package

Hi there, i'm trying to run this url udp://{ipaddress}:6000 in the mediakit widget and doesn't work, but if I change the scheme to http:// it works, strange, the packages are the same only the scheme has been changed.
this is my ffmpeg command: "ffmpeg -re -i bbb_sunflower_1080p_30fps_normal.mp4 -listen 1 -map 0:v -map 0:a:0 -c:v libx264 -b:v 1000k -c:a aac -b:a 128k -f mpegts -omit_video_pes_length 1 -maxrate 1000k -bufsize 2000k udp://<IP_ADDRESS>:6000" or http://

@SavageMike, HTTP works on top of TCP. I explicitly asked for RTSP over UDP
Thank you anyway


Single thread driver queue

The README mentions thread-per-core architecture but driver code uses queue with thread synchronization.
Probably it's better to give users a choice?
I'm personally interested to drive IO from a single thread.

Linux could use the first available thread that didn't mask the signal and if the main thread can't be used.
On Linux signaling could be done via eventfd. The thread that owns the queue could issue blocking read of the eventfd descriptor via IO_Uring, while signal handling thread could write signal number to the event file descriptor.
So we will increase overhead of signal handling but optimize the normal IO path.

I've added a Queue wrapper type in this PR.
When "signal" feature is disabled Queue is implemented through UnsafeCell<VecDeque>. Otherwise "signal" enables "sync-queue" feature that depends on crossbeam_queue::SegQueue.
I've included a benchmark that I run inside a container in Docker Desktop VM.
The benchmark creates Driver with default capacity and posts 1024 completions.
Median latency for VecDeque-based queue is 93 microseconds, for SegQueue - 130 microseconds.

PR is merged, closing


Associate a timestamp to pulled packages

This PR adds Decoder::pull_with_timestamp that associate a timestamp structure to a set of data packets. Local timestamps will monotonically increase a delta timestamp counter. Global timestamps will update a base timestamp, and reset the delta to zero, when pulled from the bitstream.

The following must be done before merge:

[ ] write unit tests;
[ ] consider supporting bitstreams that only include global timestamps (the delta counter shall be Option<usize>;
[ ] review the notes in Appendix D4-784.

CC @Yatekii. Thoughts on the the added API and documentation?

https://crates.io/crates/embedded-time should be investigated to see if the API can be improved. Can we abstract the base and delta to an embedded_time::Instant?


add depth_bias to SpecializedMaterial

Objective
allow meshes with equal z-depth to be rendered in a chosen order / avoid z-fighting
Solution
add a depth_bias to SpecializedMaterial that is added to the mesh depth used for render-ordering.

@robtfm - I think additionally, implementing this for StandardMaterial would be good.

@robtfm - I think additionally, implementing this for StandardMaterial would be good.

added for Material and StandardMaterial. with the inlining it should be free for material, so no reason not to.

This seems reasonable. Can we do a quick comparison to what this looks like in other engines?
Godot's closest corollary is probably the "render priority" integer on materials. https://docs.godotengine.org/en/stable/tutorials/3d/spatial_material.html#render-priority. I think depth_bias (with a float representation) more accurately captures whats happening, so unless everyone is doing it the same way, I think we're good.

Unity also does "priority integers"<EMAIL_ADDRESS>However at least in godot, these numbers are "first" in the sort order, rather than being "tie breakers" like depth_bias is.
With transparent materials, any higher render priority will force a transparent material to render "before" lower priorities. With opaque materials priority doesn't visibly change anything. I'm guessing unity does the same thing.
I think the are use cases for both. Resolving z-fighting is generally something that happens between "mesh entities" not between "materials". Maybe this should live on mesh entities to enable resolving z-fighting between entities with the same material?
Additionally, this doesn't "resolve" z-fighting, it just "moves" it right? things might still z-fight if they walk "away" from their bias in the direction of the camera.

thinking about it integers might well be better.
for opaque (my motivating case) i think either way resolves it and they're basically the same. it only affects the render sort-order, it doesn't affect the depth written to buffers / "physical" location, so when you have two (or more) equal-depth meshes it will determine which is rendered first, and so which one gets to fill the depth buffer and prevent the others from rendering.
for transparent, integers probably make more sense since all the materials will be rendered regardless, and with integers you can specify the order explicitly without having to worry about using floats "big enough" to overcome depth differences. i don't see any real value in forcing transparent material sort order "up to a specified depth difference" which is what floats allow.

ok now i agree with you - i think floats are good, but maybe integer priority (as the first component of the sort order) is useful as well. i don't think there's anything one method can do that the other can't, but one or the other is cleaner in some cases.
for opaque and alpha-masked materials where we write to the depth buffer, the only use-case for depth_bias is to disambiguate equal depth fragments. bias or priority will both do this equally well by determining which material gets rendered first.
for transparent materials, if we get order-independant transparency then it's all irrelevant. but otherwise there are two uses that i can think of

disambiguate equal depth
choose to render a given material first/last regardless of depth

priority integers

can disambiguate something where we have (e.g.) two pairs of equal depth materials and we want "abab" render order, but only by manually assigning priorities to each of the instances individually.
can cleanly render a material first/last.

bias

can cleanly disambiguate and render "abab".
can render a material first/last, but only by using a large bias value (which has to be a multiple of max scene depth to be safe)

another possible consideration is instancing when a material is shared by multiple renderables, like unity's HDRP.

for opaque, either method will work fine (both potentially with some overdraw).
for transparency with OIT it's still irrelevant, otherwise:
for disambiguating equal depth transparent materials, neither method will work unless instancing is disabled.
for rendering a material first/last, priority will work, but bias will only work with instancing disabled.

so basically i'd like to merge this as is, and possibly add priority integers later. i don't think depth_bias adds much maintenance burden or makes any future plans unworkable, and it's cleaner than priority integers in some cases.

@cart I'll leave the final call to you. Personally, I'm in favor of merging this as is for now.

bors r+


assisted ztp: infraenv check for populated isodownloadurl

The validtion function was missing this check.

cc @trewest @vkolodny

This may be relevant for some situations but it isn't appropriate for the validate method. For example, none of the With methods will work for creating an initial InfraEnv. They would only work for updating an existing InfraEnv


remove-from-mesh does not remove the init container when using IstioCNI

Bug description
remove-from-mesh causes a failure state as it does not remove the injected init container when using Istio CNI.
[ ] Docs
[ ] Installation
[ ] Networking
[ ] Performance and Scalability
[ ] Extensions and Telemetry
[ ] Security
[ ] Test and Release
[X] User Experience
[ ] Developer Infrastructure
Expected behavior
Steps to reproduce the bug
Enable Istio CNI
Version (include the output of istioctl version --remote and kubectl version and helm version if you used Helm)
How was Istio installed?
Environment where bug was observed (cloud vendor, OS, etc)

Closed by PR https://github.com/istio/istio/pull/26812


strictDeps fixes

verified with https://github.com/Artturin/diffing/###### Description of changes

Things done

Built on platform(s)

[ ] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

[ ] For non-Linux: Is sandbox = true set in nix.conf? (See Nix manual)
[ ] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[ ] Tested basic functionality of all binary files (usually in ./result/bin/)
22.05 Release Notes (or backporting 21.11 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module
[ ] (Release notes changes) Ran nixos/doc/manual/md-to-db.sh to update generated release notes

[ ] Fits CONTRIBUTING.md.

Result of nixpkgs-review pr 172093 run on x86_64-linux 1

39 packages built:

cage
cagebreak
cardboard
dwl
fnott
hikari
labwc
nwg-launchers
nwg-panel
phoc
phosh
python310Packages.pywlroots
python39Packages.pywlroots
qt-video-wlr
qtile
river
rivercarro
sway
sway-contrib.grimshot
sway-unwrapped
swaybg
swayidle
swaylock
swaylock-effects
swaylock-fancy
tinywl
waybar
waybox
wayfire
wayfireApplications-unwrapped.wayfire
wayfireApplications-unwrapped.wayfirePlugins.wf-shell
wayfireApplications-unwrapped.wcm
wayfireApplications-unwrapped.wlroots
wcm
wio
wl-gammactl
wlroots
xorg.xcbutilerrors
yambar

This is a semi-automatic executed nixpkgs-review with nixpkgs-review-checks extension. It is checked by a human on a best effort basis and does not build all packages (e.g. lumo, tensorflow or pytorch).
Result of nixpkgs-review pr 172093 run on x86_64-linux 1

39 packages built:

cage
cagebreak
cardboard
dwl
fnott
hikari
labwc
nwg-launchers
nwg-panel
phoc
phosh
python310Packages.pywlroots
python39Packages.pywlroots
qt-video-wlr
qtile
river
rivercarro
sway
sway-contrib.grimshot
sway-unwrapped
swaybg
swayidle
swaylock
swaylock-effects
swaylock-fancy
tinywl
waybar
waybox
wayfire
wayfireApplications-unwrapped.wayfire
wayfireApplications-unwrapped.wayfirePlugins.wf-shell
wayfireApplications-unwrapped.wcm
wayfireApplications-unwrapped.wlroots
wcm
wio
wl-gammactl
wlroots
xorg.xcbutilerrors
yambar


downloading issue

only video and subtitle is downloading study materials file is not downloading how to download that

@iamgovindthakur can you follow the issue repording guideline. this should not be the case i can't reproduce.
and if by study materials you mean quizzes so those are out of scope & i will not add support for downloading quizzes.


Version 1.6.3 not working in Sketch 49.3

Export text styles option still doesn't working in Sketch 49.3. However import option works great.

I have the same problem, but the other way around. Export works, import doesn't.

@davidjost +1

Import is not carrying over the fonts properly. Everything changes to 'Apple Color Emoji'.

Same for me: export works fine, import doesn't


Split mirror node test to multiple steps, help to identify potential failure reason

Feature to Enhance
Sometimes mirror node would fail due to time out

https://github.com/hashgraph/solo/actions/runs/9306586851/job/25616147981
https://github.com/hashgraph/solo/actions/runs/9293382861/job/25576474741

Requested Enhancement
Therefore split existing test to multiple steps, so if it failed again
we can relatively easy to tell which step caused the time out

Business Need
Help to identify mirror test failed reason

Additional Context
No response

:tada: This issue has been resolved in version 0.26.0 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


Best to remove the screencapture

Thank  you.
For me the "screencapture" step   captured the desktop background instead of what I wanted in the image.
After removing that first step of the shortcut,  it worked great!
Just do the screencapture "by hand" first, with e.g. shift-control-cmd-4, then run shortcut.

@professorbeautiful hi, and thanks for the suggestion. Actually, i think the whole action os now outdated, as Apple have fixed the issue that broke a more straight forward solution that did not require the CLI command. I will update the action in the next few days.

@professorbeautiful the action is updated to the one that worked before Apple broke things.


change default sound volume

Each time when I start the service, I found that the sound volume setting has been reset again and a bit loud. Anyway I can set a default sound volume except by voice command each time?

You can set the default pi volume with this command:
amixer  sset PCM,0 70%
Now every time you reboot it should be set to 70%.
Please note if you don't shut down or reboot properly this setting won't be saved. Try and avoid pulling the power plug.

@c8001221, if you reboot safely (eg with the voice command raspberry reboot or raspberry power off, or sudo reboot on the command line) does it still forget your setting?
For me, if I change the volume and reboot safely, the volume setting isn't changed.

Can't reproduce - closing.


Document the version number

Fixes #915

Pull Request Test Coverage Report for Build<PHONE_NUMBER>

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage remained the same at 74.036%

Totals

Change from base Build<PHONE_NUMBER>:
0.0%

Covered Lines:
2401

Relevant Lines:
3243

💛  - Coveralls


libocnn.so: cannot open shared object file: No such file or directory

Hi, I followed the instalation instructions provided in https://github.com/microsoft/O-CNN/blob/master/docs/installation.md ,

install octree
insatll tensorflow with conda

I fixed a problem with the math_functions.h file following your suggestion in #113 ,but i meet similar problem of  https://github.com/microsoft/O-CNN/issues/129#issue-954664455.
then follow the installation steps for tensorflow:
conda create -n tf-1.14.0 tensorflow-gpu==1.14.0
conda install -c conda-forge yacs tqdm
conda activate tf-1.14.0
cd tensorflow/libs
python build.py

but i got an error :
tensorflow.python.framework.errors_impl.NotFoundError: /home/zstuxinxi/wy/O-CNN-master/tensorflow/libs/libocnn.so: cannot open shared object file: No such file or directory

here is build log
(tf-1.14.0) zstuxinxi@pai-worker3:~/wy/O-CNN-master/tensorflow/libs$ python build.py
echo using g++ && cmake .. -DABI=ON -DKEY64=OFF && make -j all
using g++
-- octree: USE_CUDA
-- The CUDA compiler identification is NVIDIA 10.1.105
-- The CXX compiler identification is GNU 7.5.0
-- The C compiler identification is GNU 7.5.0
-- Check for working CUDA compiler: /usr/local/cuda/bin/nvcc
-- Check for working CUDA compiler: /usr/local/cuda/bin/nvcc -- works
-- Detecting CUDA compiler ABI info
-- Detecting CUDA compiler ABI info - done
-- Check for working CXX compiler: /usr/bin/c++
-- Check for working CXX compiler: /usr/bin/c++ -- works
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Detecting CXX compile features
-- Detecting CXX compile features - done
-- Check for working C compiler: /usr/bin/cc
-- Check for working C compiler: /usr/bin/cc -- works
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Detecting C compile features
-- Detecting C compile features - done
-- octree: -D_GLIBCXX_USE_CXX11_ABI=0
-- octree: USE_MINIBALL
-- Found PythonInterp: /home/zstuxinxi/miniconda3/envs/tf-1.14.0/bin/python (found version "3.6.2")
-- Looking for pthread.h
-- Looking for pthread.h - found
-- Looking for pthread_create
-- Looking for pthread_create - not found
-- Looking for pthread_create in pthreads
-- Looking for pthread_create in pthreads - not found
-- Looking for pthread_create in pthread
-- Looking for pthread_create in pthread - found
-- Found Threads: TRUE
-- Configuring done
-- Generating done
-- Build files have been written to: /home/zstuxinxi/wy/O-CNN-master/octree/build
Scanning dependencies of target rply
Scanning dependencies of target gtest
Scanning dependencies of target octree_lib
[  1%] Building C object CMakeFiles/rply.dir/external/octree-ext/rply-1.1.4/rply.c.o
[  4%] Building CXX object CMakeFiles/octree_lib.dir/octree/contour.cpp.o
[  4%] Building CXX object CMakeFiles/octree_lib.dir/octree/marching_cube.cpp.o
[  4%] Building CXX object CMakeFiles/octree_lib.dir/octree/filenames.cpp.o
[  4%] Building CXX object CMakeFiles/octree_lib.dir/octree/marching_cube_table.cpp.o
[  5%] Building CXX object external/octree-ext/googletest/googletest/CMakeFiles/gtest.dir/src/gtest-all.cc.o
[  6%] Building CXX object CMakeFiles/octree_lib.dir/octree/octree_info.cpp.o
[  7%] Building CXX object CMakeFiles/octree_lib.dir/octree/octree.cpp.o
[  8%] Building CXX object CMakeFiles/octree_lib.dir/octree/octree_parser.cpp.o
[ 10%] Building CXX object CMakeFiles/octree_lib.dir/octree/math_functions.cpp.o
[ 10%] Building CXX object CMakeFiles/octree_lib.dir/octree/merge_octrees.cpp.o
[ 10%] Building CXX object CMakeFiles/octree_lib.dir/octree/octree_nn.cpp.o
[ 11%] Building CXX object CMakeFiles/octree_lib.dir/octree/octree_samples.cpp.o
[ 12%] Building CXX object CMakeFiles/octree_lib.dir/octree/mesh.cpp.o
[ 13%] Building CXX object CMakeFiles/octree_lib.dir/octree/octree_value.cpp.o
[ 17%] Building CXX object CMakeFiles/octree_lib.dir/octree/simplify_points.cpp.o
[ 14%] Building CUDA object CMakeFiles/octree_lib.dir/octree/octree_parser.cu.o
[ 14%] Building CXX object CMakeFiles/octree_lib.dir/octree/transform_points.cpp.o
[ 15%] Building CXX object CMakeFiles/octree_lib.dir/octree/points_info.cpp.o
[ 16%] Building CXX object CMakeFiles/octree_lib.dir/octree/transform_octree.cpp.o
[ 18%] Building CUDA object CMakeFiles/octree_lib.dir/octree/octree_nn.cu.o
[ 19%] Building CXX object CMakeFiles/octree_lib.dir/octree/points.cpp.o
[ 20%] Building CXX object CMakeFiles/octree_lib.dir/octree/points_parser.cpp.o
[ 21%] Building CXX object CMakeFiles/octree_lib.dir/octree/octree_conv.cpp.o
[ 22%] Linking C static library librply.a
[ 22%] Built target rply
[ 23%] Linking CXX static library ../../../../lib/libgtest.a
[ 23%] Built target gtest
Scanning dependencies of target gtest_main
[ 25%] Building CXX object external/octree-ext/googletest/googletest/CMakeFiles/gtest_main.dir/src/gtest_main.cc.o
[ 26%] Linking CXX static library ../../../../lib/libgtest_main.a
[ 26%] Built target gtest_main
[ 27%] Linking CXX static library liboctree_lib.a
[ 27%] Built target octree_lib
Scanning dependencies of target points_noise
Scanning dependencies of target upgrade_octree
Scanning dependencies of target octree_zbuffer
Scanning dependencies of target octree_prune
Scanning dependencies of target ply2points
Scanning dependencies of target chamfer_distance
Scanning dependencies of target octree2pts_suncg
Scanning dependencies of target custom_data
Scanning dependencies of target octree_test
Scanning dependencies of target transform_points
Scanning dependencies of target points2ply
Scanning dependencies of target clip_points
Scanning dependencies of target check_octree
Scanning dependencies of target octree_bbox
Scanning dependencies of target octree
Scanning dependencies of target adaptive_octree
Scanning dependencies of target bbox
Scanning dependencies of target octree_dropout
[ 28%] Building CXX object CMakeFiles/points2ply.dir/tools/points2ply.cpp.o
[ 31%] Building CXX object CMakeFiles/octree_bbox.dir/tools/octree_bbox.cpp.o
[ 32%] Building CXX object CMakeFiles/octree_zbuffer.dir/tools/octree_zbuffer.cpp.o
Scanning dependencies of target mesh2points
Scanning dependencies of target octree_samples
[ 33%] Building CXX object CMakeFiles/custom_data.dir/tools/custom_data.cpp.o
[ 34%] Building CXX object CMakeFiles/points_noise.dir/tools/points_noise.cpp.o
Scanning dependencies of target merge_octree
[ 34%] Building CXX object CMakeFiles/transform_points.dir/tools/transform_points.cpp.o
Scanning dependencies of target octree2points
[ 35%] Building CXX object CMakeFiles/bbox.dir/tools/bbox.cpp.o
[ 36%] Building CXX object CMakeFiles/clip_points.dir/tools/clip_points.cpp.o
Scanning dependencies of target upgrade_points
[ 29%] Building CXX object CMakeFiles/octree2pts_suncg.dir/tools/octree2pts_suncg.cpp.o
Scanning dependencies of target play_ground
[ 30%] Building CXX object CMakeFiles/upgrade_octree.dir/tools/upgrade_octree.cpp.o
Scanning dependencies of target octree2mesh
[ 37%] Building CXX object CMakeFiles/octree.dir/tools/build_octree.cpp.o
[ 38%] Building CXX object CMakeFiles/octree_prune.dir/tools/octree_prune.cpp.o
[ 39%] Building CXX object CMakeFiles/check_octree.dir/tools/check_octree.cpp.o
[ 40%] Building CXX object CMakeFiles/chamfer_distance.dir/tools/chamfer_distance.cpp.o
[ 41%] Building CXX object CMakeFiles/octree_test.dir/test/test_octree_nn.cpp.o
[ 42%] Building CXX object CMakeFiles/octree2points.dir/tools/octree2points.cpp.o
[ 39%] Building CXX object CMakeFiles/adaptive_octree.dir/tools/adaptive_octree.cpp.o
Scanning dependencies of target simplify_points
[ 43%] Building CXX object CMakeFiles/octree_samples.dir/tools/octree_samples.cpp.o
[ 44%] Building CXX object CMakeFiles/mesh2points.dir/tools/mesh2points.cpp.o
[ 44%] Building CXX object CMakeFiles/merge_octree.dir/tools/merge_octree.cpp.o
[ 45%] Building CXX object CMakeFiles/octree_test.dir/test/test_octree.cpp.o
[ 46%] Building CXX object CMakeFiles/ply2points.dir/tools/ply2points.cpp.o
[ 47%] Building CXX object CMakeFiles/octree_test.dir/test/test_util.cpp.o
[ 48%] Building CXX object CMakeFiles/play_ground.dir/tools/play_ground.cpp.o
[ 50%] Building CXX object CMakeFiles/octree2mesh.dir/tools/octree2mesh.cpp.o
[ 51%] Building CXX object CMakeFiles/octree_dropout.dir/tools/octree_dropout.cpp.o
[ 52%] Building CXX object CMakeFiles/upgrade_points.dir/tools/upgrade_points.cpp.o
[ 53%] Building CXX object CMakeFiles/simplify_points.dir/tools/simplify_points.cpp.o
[ 54%] Linking CUDA device code CMakeFiles/octree_zbuffer.dir/cmake_device_link.o
[ 55%] Linking CUDA device code CMakeFiles/points_noise.dir/cmake_device_link.o
[ 56%] Linking CUDA device code CMakeFiles/check_octree.dir/cmake_device_link.o
[ 57%] Linking CUDA device code CMakeFiles/custom_data.dir/cmake_device_link.o
[ 58%] Linking CUDA device code CMakeFiles/transform_points.dir/cmake_device_link.o
[ 59%] Linking CUDA device code CMakeFiles/points2ply.dir/cmake_device_link.o
[ 60%] Linking CUDA device code CMakeFiles/clip_points.dir/cmake_device_link.o
[ 61%] Linking CUDA device code CMakeFiles/octree_bbox.dir/cmake_device_link.o
[ 62%] Linking CUDA device code CMakeFiles/octree_samples.dir/cmake_device_link.o
[ 63%] Linking CUDA device code CMakeFiles/mesh2points.dir/cmake_device_link.o
[ 64%] Linking CXX executable points_noise
[ 65%] Linking CUDA device code CMakeFiles/octree2mesh.dir/cmake_device_link.o
[ 66%] Linking CUDA device code CMakeFiles/bbox.dir/cmake_device_link.o
[ 66%] Linking CXX executable custom_data
[ 67%] Linking CXX executable check_octree
[ 67%] Linking CXX executable octree_zbuffer
[ 68%] Linking CUDA device code CMakeFiles/merge_octree.dir/cmake_device_link.o
[ 69%] Linking CXX executable octree_bbox
[ 70%] Linking CUDA device code CMakeFiles/chamfer_distance.dir/cmake_device_link.o
[ 70%] Linking CXX executable points2ply
[ 71%] Linking CXX executable transform_points
[ 72%] Linking CUDA device code CMakeFiles/simplify_points.dir/cmake_device_link.o
[ 73%] Linking CXX executable clip_points
[ 75%] Linking CUDA device code CMakeFiles/octree2points.dir/cmake_device_link.o
[ 75%] Linking CXX executable octree_samples
[ 76%] Linking CUDA device code CMakeFiles/octree2pts_suncg.dir/cmake_device_link.o
[ 77%] Linking CUDA device code CMakeFiles/octree_test.dir/cmake_device_link.o
[ 78%] Linking CUDA device code CMakeFiles/upgrade_points.dir/cmake_device_link.o
[ 79%] Linking CUDA device code CMakeFiles/octree.dir/cmake_device_link.o
[ 80%] Linking CUDA device code CMakeFiles/octree_prune.dir/cmake_device_link.o
[ 81%] Linking CXX executable mesh2points
[ 81%] Built target points_noise
[ 82%] Linking CUDA device code CMakeFiles/play_ground.dir/cmake_device_link.o
[ 83%] Linking CUDA device code CMakeFiles/adaptive_octree.dir/cmake_device_link.o
[ 84%] Linking CUDA device code CMakeFiles/octree_dropout.dir/cmake_device_link.o
[ 86%] Linking CUDA device code CMakeFiles/upgrade_octree.dir/cmake_device_link.o
[ 85%] Linking CXX executable simplify_points
[ 86%] Built target custom_data
[ 87%] Linking CXX executable merge_octree
[ 88%] Linking CXX executable octree2mesh
[ 88%] Built target octree_samples
[ 88%] Built target octree_zbuffer
[ 88%] Built target clip_points
[ 88%] Built target octree_bbox
[ 88%] Built target check_octree
[ 88%] Linking CXX executable chamfer_distance
[ 89%] Linking CXX executable bbox
[ 89%] Built target points2ply
[ 89%] Built target transform_points
[ 90%] Linking CXX executable octree2points
[ 91%] Linking CXX executable octree_prune
[ 92%] Linking CXX executable octree_test
[ 93%] Linking CXX executable upgrade_points
[ 93%] Linking CXX executable octree
[ 93%] Linking CXX executable octree2pts_suncg
[ 94%] Linking CXX executable adaptive_octree
[ 94%] Built target merge_octree
[ 95%] Linking CXX executable play_ground
[ 96%] Linking CXX executable upgrade_octree
[ 97%] Built target mesh2points
[ 97%] Linking CXX executable octree_dropout
[ 97%] Built target simplify_points
[ 97%] Built target octree2mesh
[ 97%] Built target octree2points
[ 97%] Built target bbox
[ 97%] Built target chamfer_distance
[ 97%] Built target octree_prune
[ 97%] Built target adaptive_octree
[ 97%] Built target upgrade_points
[ 97%] Built target octree2pts_suncg
[ 97%] Built target octree
[ 97%] Built target upgrade_octree
[ 97%] Built target play_ground
[ 97%] Built target octree_dropout
[ 97%] Built target octree_test
[ 98%] Linking CUDA device code CMakeFiles/ply2points.dir/cmake_device_link.o
[100%] Linking CXX executable ply2points
[100%] Built target ply2points
Running main() from /home/zstuxinxi/wy/O-CNN-master/octree/external/octree-ext/googletest/googletest/src/gtest_main.cc
[==========] Running 12 tests from 7 test suites.
[----------] Global test environment set-up.
[----------] 2 tests from OctreeTest
[ RUN      ] OctreeTest.TestOctreeBuild
[       OK ] OctreeTest.TestOctreeBuild (0 ms)
[ RUN      ] OctreeTest.TestOctreeTrim
[       OK ] OctreeTest.TestOctreeTrim (0 ms)
[----------] 2 tests from OctreeTest (0 ms total)

[----------] 1 test from VecResizeTest
[ RUN      ] VecResizeTest.TestVecResize
[       OK ] VecResizeTest.TestVecResize (0 ms)
[----------] 1 test from VecResizeTest (0 ms total)

[----------] 1 test from BiliearNeigh
[ RUN      ] BiliearNeigh.TestBiliearNeigh
[       OK ] BiliearNeigh.TestBiliearNeigh (0 ms)
[----------] 1 test from BiliearNeigh (0 ms total)

[----------] 1 test from Coord2xyzTest
[ RUN      ] Coord2xyzTest.TestCoord2xyz
[       OK ] Coord2xyzTest.TestCoord2xyz (0 ms)
[----------] 1 test from Coord2xyzTest (0 ms total)

[----------] 3 tests from UtilTest
[ RUN      ] UtilTest.TestExtractPath
[       OK ] UtilTest.TestExtractPath (0 ms)
[ RUN      ] UtilTest.TestExtractFilename
[       OK ] UtilTest.TestExtractFilename (0 ms)
[ RUN      ] UtilTest.TestExtractSuffix
[       OK ] UtilTest.TestExtractSuffix (0 ms)
[----------] 3 tests from UtilTest (0 ms total)

[----------] 2 tests from MeshTest
[ RUN      ] MeshTest.TestFaceCenter
[       OK ] MeshTest.TestFaceCenter (0 ms)
[ RUN      ] MeshTest.TestFaceNormal
[       OK ] MeshTest.TestFaceNormal (0 ms)
[----------] 2 tests from MeshTest (0 ms total)

[----------] 2 tests from MathTest
[ RUN      ] MathTest.TestRotMatrix1
[       OK ] MathTest.TestRotMatrix1 (0 ms)
[ RUN      ] MathTest.TestRotMatrix2
[       OK ] MathTest.TestRotMatrix2 (0 ms)
[----------] 2 tests from MathTest (0 ms total)

[----------] Global test environment tear-down
[==========] 12 tests from 7 test suites ran. (0 ms total)
[  PASSED  ] 12 tests.
g++ -std=c++11 -O2 -c octree2col_op.cc -I/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include -D_GLIBCXX_USE_CXX11_ABI=0 -I../../octree/octree -I /usr/local/cuda-10.1/include   -L /usr/local/cuda-10.1/lib64 -D GOOGLE_CUDA=1 -L/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow -l:libtensorflow_framework.so.1 -L../../octree/build -loctree_lib -fPIC -lcudart  -o object/octree2col_op.cc.o
g++ -std=c++11 -O2 -c octree_align_op.cc -I/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include -D_GLIBCXX_USE_CXX11_ABI=0 -I../../octree/octree -I /usr/local/cuda-10.1/include   -L /usr/local/cuda-10.1/lib64 -D GOOGLE_CUDA=1 -L/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow -l:libtensorflow_framework.so.1 -L../../octree/build -loctree_lib -fPIC -lcudart  -o object/octree_align_op.cc.o
g++ -std=c++11 -O2 -c octree_batch_op.cc -I/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include -D_GLIBCXX_USE_CXX11_ABI=0 -I../../octree/octree -I /usr/local/cuda-10.1/include   -L /usr/local/cuda-10.1/lib64 -D GOOGLE_CUDA=1 -L/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow -l:libtensorflow_framework.so.1 -L../../octree/build -loctree_lib -fPIC -lcudart  -o object/octree_batch_op.cc.o
g++ -std=c++11 -O2 -c octree_bilinear_op.cc -I/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include -D_GLIBCXX_USE_CXX11_ABI=0 -I../../octree/octree -I /usr/local/cuda-10.1/include   -L /usr/local/cuda-10.1/lib64 -D GOOGLE_CUDA=1 -L/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow -l:libtensorflow_framework.so.1 -L../../octree/build -loctree_lib -fPIC -lcudart  -o object/octree_bilinear_op.cc.o
g++ -std=c++11 -O2 -c octree_conv_op.cc -I/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include -D_GLIBCXX_USE_CXX11_ABI=0 -I../../octree/octree -I /usr/local/cuda-10.1/include   -L /usr/local/cuda-10.1/lib64 -D GOOGLE_CUDA=1 -L/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow -l:libtensorflow_framework.so.1 -L../../octree/build -loctree_lib -fPIC -lcudart  -o object/octree_conv_op.cc.o
g++ -std=c++11 -O2 -c octree_gather_op.cc -I/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include -D_GLIBCXX_USE_CXX11_ABI=0 -I../../octree/octree -I /usr/local/cuda-10.1/include   -L /usr/local/cuda-10.1/lib64 -D GOOGLE_CUDA=1 -L/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow -l:libtensorflow_framework.so.1 -L../../octree/build -loctree_lib -fPIC -lcudart  -o object/octree_gather_op.cc.o
g++ -std=c++11 -O2 -c octree_grow_op.cc -I/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include -D_GLIBCXX_USE_CXX11_ABI=0 -I../../octree/octree -I /usr/local/cuda-10.1/include   -L /usr/local/cuda-10.1/lib64 -D GOOGLE_CUDA=1 -L/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow -l:libtensorflow_framework.so.1 -L../../octree/build -loctree_lib -fPIC -lcudart  -o object/octree_grow_op.cc.o
g++ -std=c++11 -O2 -c octree_key_op.cc -I/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include -D_GLIBCXX_USE_CXX11_ABI=0 -I../../octree/octree -I /usr/local/cuda-10.1/include   -L /usr/local/cuda-10.1/lib64 -D GOOGLE_CUDA=1 -L/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow -l:libtensorflow_framework.so.1 -L../../octree/build -loctree_lib -fPIC -lcudart  -o object/octree_key_op.cc.o
g++ -std=c++11 -O2 -c octree_mask_op.cc -I/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include -D_GLIBCXX_USE_CXX11_ABI=0 -I../../octree/octree -I /usr/local/cuda-10.1/include   -L /usr/local/cuda-10.1/lib64 -D GOOGLE_CUDA=1 -L/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow -l:libtensorflow_framework.so.1 -L../../octree/build -loctree_lib -fPIC -lcudart  -o object/octree_mask_op.cc.o
g++ -std=c++11 -O2 -c octree_max_pool_op.cc -I/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include -D_GLIBCXX_USE_CXX11_ABI=0 -I../../octree/octree -I /usr/local/cuda-10.1/include   -L /usr/local/cuda-10.1/lib64 -D GOOGLE_CUDA=1 -L/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow -l:libtensorflow_framework.so.1 -L../../octree/build -loctree_lib -fPIC -lcudart  -o object/octree_max_pool_op.cc.o
g++ -std=c++11 -O2 -c octree_new_op.cc -I/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include -D_GLIBCXX_USE_CXX11_ABI=0 -I../../octree/octree -I /usr/local/cuda-10.1/include   -L /usr/local/cuda-10.1/lib64 -D GOOGLE_CUDA=1 -L/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow -l:libtensorflow_framework.so.1 -L../../octree/build -loctree_lib -fPIC -lcudart  -o object/octree_new_op.cc.o
g++ -std=c++11 -O2 -c octree_pad_op.cc -I/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include -D_GLIBCXX_USE_CXX11_ABI=0 -I../../octree/octree -I /usr/local/cuda-10.1/include   -L /usr/local/cuda-10.1/lib64 -D GOOGLE_CUDA=1 -L/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow -l:libtensorflow_framework.so.1 -L../../octree/build -loctree_lib -fPIC -lcudart  -o object/octree_pad_op.cc.o
g++ -std=c++11 -O2 -c octree_property_op.cc -I/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include -D_GLIBCXX_USE_CXX11_ABI=0 -I../../octree/octree -I /usr/local/cuda-10.1/include   -L /usr/local/cuda-10.1/lib64 -D GOOGLE_CUDA=1 -L/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow -l:libtensorflow_framework.so.1 -L../../octree/build -loctree_lib -fPIC -lcudart  -o object/octree_property_op.cc.o
g++ -std=c++11 -O2 -c octree_samples.cc -I/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include -D_GLIBCXX_USE_CXX11_ABI=0 -I../../octree/octree -I /usr/local/cuda-10.1/include   -L /usr/local/cuda-10.1/lib64 -D GOOGLE_CUDA=1 -L/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow -l:libtensorflow_framework.so.1 -L../../octree/build -loctree_lib -fPIC -lcudart  -o object/octree_samples.cc.o
g++ -std=c++11 -O2 -c octree_search_op.cc -I/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include -D_GLIBCXX_USE_CXX11_ABI=0 -I../../octree/octree -I /usr/local/cuda-10.1/include   -L /usr/local/cuda-10.1/lib64 -D GOOGLE_CUDA=1 -L/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow -l:libtensorflow_framework.so.1 -L../../octree/build -loctree_lib -fPIC -lcudart  -o object/octree_search_op.cc.o
g++ -std=c++11 -O2 -c octree_set_property_op.cc -I/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include -D_GLIBCXX_USE_CXX11_ABI=0 -I../../octree/octree -I /usr/local/cuda-10.1/include   -L /usr/local/cuda-10.1/lib64 -D GOOGLE_CUDA=1 -L/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow -l:libtensorflow_framework.so.1 -L../../octree/build -loctree_lib -fPIC -lcudart  -o object/octree_set_property_op.cc.o
g++ -std=c++11 -O2 -c octree_update_op.cc -I/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include -D_GLIBCXX_USE_CXX11_ABI=0 -I../../octree/octree -I /usr/local/cuda-10.1/include   -L /usr/local/cuda-10.1/lib64 -D GOOGLE_CUDA=1 -L/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow -l:libtensorflow_framework.so.1 -L../../octree/build -loctree_lib -fPIC -lcudart  -o object/octree_update_op.cc.o
g++ -std=c++11 -O2 -c points2octree_op.cc -I/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include -D_GLIBCXX_USE_CXX11_ABI=0 -I../../octree/octree -I /usr/local/cuda-10.1/include   -L /usr/local/cuda-10.1/lib64 -D GOOGLE_CUDA=1 -L/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow -l:libtensorflow_framework.so.1 -L../../octree/build -loctree_lib -fPIC -lcudart  -o object/points2octree_op.cc.o
g++ -std=c++11 -O2 -c points_property_op.cc -I/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include -D_GLIBCXX_USE_CXX11_ABI=0 -I../../octree/octree -I /usr/local/cuda-10.1/include   -L /usr/local/cuda-10.1/lib64 -D GOOGLE_CUDA=1 -L/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow -l:libtensorflow_framework.so.1 -L../../octree/build -loctree_lib -fPIC -lcudart  -o object/points_property_op.cc.o
g++ -std=c++11 -O2 -c points_set_property_op.cc -I/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include -D_GLIBCXX_USE_CXX11_ABI=0 -I../../octree/octree -I /usr/local/cuda-10.1/include   -L /usr/local/cuda-10.1/lib64 -D GOOGLE_CUDA=1 -L/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow -l:libtensorflow_framework.so.1 -L../../octree/build -loctree_lib -fPIC -lcudart  -o object/points_set_property_op.cc.o
g++ -std=c++11 -O2 -c transform_octree_op.cc -I/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include -D_GLIBCXX_USE_CXX11_ABI=0 -I../../octree/octree -I /usr/local/cuda-10.1/include   -L /usr/local/cuda-10.1/lib64 -D GOOGLE_CUDA=1 -L/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow -l:libtensorflow_framework.so.1 -L../../octree/build -loctree_lib -fPIC -lcudart  -o object/transform_octree_op.cc.o
g++ -std=c++11 -O2 -c transform_points_op.cc -I/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include -D_GLIBCXX_USE_CXX11_ABI=0 -I../../octree/octree -I /usr/local/cuda-10.1/include   -L /usr/local/cuda-10.1/lib64 -D GOOGLE_CUDA=1 -L/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow -l:libtensorflow_framework.so.1 -L../../octree/build -loctree_lib -fPIC -lcudart  -o object/transform_points_op.cc.o
/usr/local/cuda-10.1/bin/nvcc -std=c++11 -O2 -c tensorflow_gpu_gemm.cu.cc -I/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include -D_GLIBCXX_USE_CXX11_ABI=0 -I../../octree/octree -I /usr/local/cuda-10.1/include -x cu -Xcompiler -fPIC -D GOOGLE_CUDA=1 -I /usr/local   -expt-relaxed-constexpr -DNDEBUG  -o object/tensorflow_gpu_gemm.cu.cc.o
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/absl/strings/string_view.h(495): warning: expression has no effect

/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/absl/strings/string_view.h(495): warning: expression has no effect

/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h: In instantiation of ‘void google::protobuf::Map<Key, T>::InnerMap::iterator_base<KeyValueType>::SearchFrom(google::protobuf::Map<Key, T>::size_type) [with KeyValueType = google::protobuf::Map<std::basic_string<char>, tensorflow::AttrValue>::KeyValuePair; Key = std::basic_string<char>; T = tensorflow::AttrValue; google::protobuf::Map<Key, T>::size_type = long unsigned int]’:
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:400:11:   required from ‘google::protobuf::Map<Key, T>::InnerMap::iterator_base<KeyValueType>::iterator_base(const google::protobuf::Map<Key, T>::InnerMap*) [with KeyValueType = google::protobuf::Map<std::basic_string<char>, tensorflow::AttrValue>::KeyValuePair; Key = std::basic_string<char>; T = tensorflow::AttrValue]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:516:28:   required from ‘google::protobuf::Map<Key, T>::InnerMap::iterator google::protobuf::Map<Key, T>::InnerMap::begin() [with Key = std::basic_string<char>; T = tensorflow::AttrValue; google::protobuf::Map<Key, T>::InnerMap::iterator = google::protobuf::Map<std::basic_string<char>, tensorflow::AttrValue>::InnerMap::iterator_base<google::protobuf::Map<std::basic_string<char>, tensorflow::AttrValue>::KeyValuePair>]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:1040:25:   required from ‘google::protobuf::Map<Key, T>::const_iterator google::protobuf::Map<Key, T>::begin() const [with Key = std::basic_string<char>; T = tensorflow::AttrValue]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/tensorflow/core/framework/node_def_util.h:173:168:   required from here
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:428:29: error: cannot call member function ‘bool google::protobuf::Map<Key, T>::InnerMap::TableEntryIsNonEmptyList(google::protobuf::Map<Key, T>::size_type) const [with Key = std::basic_string<char>; T = tensorflow::AttrValue; google::protobuf::Map<Key, T>::size_type = long unsigned int]’ without object
           if (m_->TableEntryIsNonEmptyList(bucket_index_)) {
           ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:431:30: error: cannot call member function ‘bool google::protobuf::Map<Key, T>::InnerMap::TableEntryIsTree(google::protobuf::Map<Key, T>::size_type) const [with Key = std::basic_string<char>; T = tensorflow::AttrValue; google::protobuf::Map<Key, T>::size_type = long unsigned int]’ without object
           } else if (m_->TableEntryIsTree(bucket_index_)) {
              ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h: In instantiation of ‘bool google::protobuf::Map<Key, T>::InnerMap::iterator_base<KeyValueType>::revalidate_if_necessary(google::protobuf::Map<Key, T>::InnerMap::TreeIterator*) [with KeyValueType = google::protobuf::Map<std::basic_string<char>, tensorflow::AttrValue>::KeyValuePair; Key = std::basic_string<char>; T = tensorflow::AttrValue; google::protobuf::Map<Key, T>::InnerMap::TreeIterator = std::_Rb_tree_const_iterator<std::basic_string<char>*>]’:
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:610:12:   required from ‘void google::protobuf::Map<Key, T>::InnerMap::erase(google::protobuf::Map<Key, T>::InnerMap::iterator) [with Key = std::basic_string<char>; T = tensorflow::AttrValue; google::protobuf::Map<Key, T>::InnerMap::iterator = google::protobuf::Map<std::basic_string<char>, tensorflow::AttrValue>::InnerMap::iterator_base<google::protobuf::Map<std::basic_string<char>, tensorflow::AttrValue>::KeyValuePair>]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:1139:1:   required from ‘google::protobuf::Map<Key, T>::iterator google::protobuf::Map<Key, T>::erase(google::protobuf::Map<Key, T>::iterator) [with Key = std::basic_string<char>; T = tensorflow::AttrValue]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:1144:14:   required from ‘void google::protobuf::Map<Key, T>::erase(google::protobuf::Map<Key, T>::iterator, google::protobuf::Map<Key, T>::iterator) [with Key = std::basic_string<char>; T = tensorflow::AttrValue]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:1147:21:   required from ‘void google::protobuf::Map<Key, T>::clear() [with Key = std::basic_string<char>; T = tensorflow::AttrValue]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map_field_inl.h:188:1:   required from ‘void google::protobuf::internal::MapField<Derived, Key, T, key_wire_type, value_wire_type, default_enum_value>::Clear() [with Derived = tensorflow::NameAttrList_AttrEntry_DoNotUse; Key = std::basic_string<char>; T = tensorflow::AttrValue; google::protobuf::internal::WireFormatLite::FieldType kKeyFieldType = (google::protobuf::internal::WireFormatLite::FieldType)9; google::protobuf::internal::WireFormatLite::FieldType kValueFieldType = (google::protobuf::internal::WireFormatLite::FieldType)11; int default_enum_value = 0]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/tensorflow/core/framework/attr_value.pb.h:1790:15:   required from here
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:490:29: error: cannot call member function ‘bool google::protobuf::Map<Key, T>::InnerMap::TableEntryIsNonEmptyList(google::protobuf::Map<Key, T>::size_type) const [with Key = std::basic_string<char>; T = tensorflow::AttrValue; google::protobuf::Map<Key, T>::size_type = long unsigned int]’ without object
         if (m_->TableEntryIsNonEmptyList(bucket_index_)) {
         ~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:504:24: error: cannot call member function ‘bool google::protobuf::Map<Key, T>::InnerMap::TableEntryIsList(google::protobuf::Map<Key, T>::size_type) const [with Key = std::basic_string<char>; T = tensorflow::AttrValue; google::protobuf::Map<Key, T>::size_type = long unsigned int]’ without object
         return m_->TableEntryIsList(bucket_index_);
         ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h: In instantiation of ‘void google::protobuf::Map<Key, T>::InnerMap::iterator_base<KeyValueType>::SearchFrom(google::protobuf::Map<Key, T>::size_type) [with KeyValueType = google::protobuf::Map<unsigned int, tensorflow::FunctionDef_ArgAttrs>::KeyValuePair; Key = unsigned int; T = tensorflow::FunctionDef_ArgAttrs; google::protobuf::Map<Key, T>::size_type = long unsigned int]’:
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:400:11:   required from ‘google::protobuf::Map<Key, T>::InnerMap::iterator_base<KeyValueType>::iterator_base(const google::protobuf::Map<Key, T>::InnerMap*) [with KeyValueType = google::protobuf::Map<unsigned int, tensorflow::FunctionDef_ArgAttrs>::KeyValuePair; Key = unsigned int; T = tensorflow::FunctionDef_ArgAttrs]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:516:28:   required from ‘google::protobuf::Map<Key, T>::InnerMap::iterator google::protobuf::Map<Key, T>::InnerMap::begin() [with Key = unsigned int; T = tensorflow::FunctionDef_ArgAttrs; google::protobuf::Map<Key, T>::InnerMap::iterator = google::protobuf::Map<unsigned int, tensorflow::FunctionDef_ArgAttrs>::InnerMap::iterator_base<google::protobuf::Map<unsigned int, tensorflow::FunctionDef_ArgAttrs>::KeyValuePair>]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:1037:27:   required from ‘google::protobuf::Map<Key, T>::iterator google::protobuf::Map<Key, T>::begin() [with Key = unsigned int; T = tensorflow::FunctionDef_ArgAttrs]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:1147:27:   required from ‘void google::protobuf::Map<Key, T>::clear() [with Key = unsigned int; T = tensorflow::FunctionDef_ArgAttrs]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map_field_inl.h:188:1:   required from ‘void google::protobuf::internal::MapField<Derived, Key, T, key_wire_type, value_wire_type, default_enum_value>::Clear() [with Derived = tensorflow::FunctionDef_ArgAttrEntry_DoNotUse; Key = unsigned int; T = tensorflow::FunctionDef_ArgAttrs; google::protobuf::internal::WireFormatLite::FieldType kKeyFieldType = (google::protobuf::internal::WireFormatLite::FieldType)13; google::protobuf::internal::WireFormatLite::FieldType kValueFieldType = (google::protobuf::internal::WireFormatLite::FieldType)11; int default_enum_value = 0]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/tensorflow/core/framework/function.pb.h:1059:19:   required from here
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:428:29: error: cannot call member function ‘bool google::protobuf::Map<Key, T>::InnerMap::TableEntryIsNonEmptyList(google::protobuf::Map<Key, T>::size_type) const [with Key = unsigned int; T = tensorflow::FunctionDef_ArgAttrs; google::protobuf::Map<Key, T>::size_type = long unsigned int]’ without object
           if (m_->TableEntryIsNonEmptyList(bucket_index_)) {
           ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:431:30: error: cannot call member function ‘bool google::protobuf::Map<Key, T>::InnerMap::TableEntryIsTree(google::protobuf::Map<Key, T>::size_type) const [with Key = unsigned int; T = tensorflow::FunctionDef_ArgAttrs; google::protobuf::Map<Key, T>::size_type = long unsigned int]’ without object
           } else if (m_->TableEntryIsTree(bucket_index_)) {
              ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h: In instantiation of ‘bool google::protobuf::Map<Key, T>::InnerMap::iterator_base<KeyValueType>::revalidate_if_necessary(google::protobuf::Map<Key, T>::InnerMap::TreeIterator*) [with KeyValueType = google::protobuf::Map<unsigned int, tensorflow::FunctionDef_ArgAttrs>::KeyValuePair; Key = unsigned int; T = tensorflow::FunctionDef_ArgAttrs; google::protobuf::Map<Key, T>::InnerMap::TreeIterator = std::_Rb_tree_const_iterator<unsigned int*>]’:
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:610:12:   required from ‘void google::protobuf::Map<Key, T>::InnerMap::erase(google::protobuf::Map<Key, T>::InnerMap::iterator) [with Key = unsigned int; T = tensorflow::FunctionDef_ArgAttrs; google::protobuf::Map<Key, T>::InnerMap::iterator = google::protobuf::Map<unsigned int, tensorflow::FunctionDef_ArgAttrs>::InnerMap::iterator_base<google::protobuf::Map<unsigned int, tensorflow::FunctionDef_ArgAttrs>::KeyValuePair>]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:1139:1:   required from ‘google::protobuf::Map<Key, T>::iterator google::protobuf::Map<Key, T>::erase(google::protobuf::Map<Key, T>::iterator) [with Key = unsigned int; T = tensorflow::FunctionDef_ArgAttrs]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:1144:14:   required from ‘void google::protobuf::Map<Key, T>::erase(google::protobuf::Map<Key, T>::iterator, google::protobuf::Map<Key, T>::iterator) [with Key = unsigned int; T = tensorflow::FunctionDef_ArgAttrs]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:1147:21:   required from ‘void google::protobuf::Map<Key, T>::clear() [with Key = unsigned int; T = tensorflow::FunctionDef_ArgAttrs]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map_field_inl.h:188:1:   required from ‘void google::protobuf::internal::MapField<Derived, Key, T, key_wire_type, value_wire_type, default_enum_value>::Clear() [with Derived = tensorflow::FunctionDef_ArgAttrEntry_DoNotUse; Key = unsigned int; T = tensorflow::FunctionDef_ArgAttrs; google::protobuf::internal::WireFormatLite::FieldType kKeyFieldType = (google::protobuf::internal::WireFormatLite::FieldType)13; google::protobuf::internal::WireFormatLite::FieldType kValueFieldType = (google::protobuf::internal::WireFormatLite::FieldType)11; int default_enum_value = 0]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/tensorflow/core/framework/function.pb.h:1059:19:   required from here
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:490:29: error: cannot call member function ‘bool google::protobuf::Map<Key, T>::InnerMap::TableEntryIsNonEmptyList(google::protobuf::Map<Key, T>::size_type) const [with Key = unsigned int; T = tensorflow::FunctionDef_ArgAttrs; google::protobuf::Map<Key, T>::size_type = long unsigned int]’ without object
         if (m_->TableEntryIsNonEmptyList(bucket_index_)) {
         ~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:504:24: error: cannot call member function ‘bool google::protobuf::Map<Key, T>::InnerMap::TableEntryIsList(google::protobuf::Map<Key, T>::size_type) const [with Key = unsigned int; T = tensorflow::FunctionDef_ArgAttrs; google::protobuf::Map<Key, T>::size_type = long unsigned int]’ without object
         return m_->TableEntryIsList(bucket_index_);
         ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h: In instantiation of ‘void google::protobuf::Map<Key, T>::InnerMap::iterator_base<KeyValueType>::SearchFrom(google::protobuf::Map<Key, T>::size_type) [with KeyValueType = google::protobuf::Map<std::basic_string<char>, std::basic_string<char> >::KeyValuePair; Key = std::basic_string<char>; T = std::basic_string<char>; google::protobuf::Map<Key, T>::size_type = long unsigned int]’:
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:400:11:   required from ‘google::protobuf::Map<Key, T>::InnerMap::iterator_base<KeyValueType>::iterator_base(const google::protobuf::Map<Key, T>::InnerMap*) [with KeyValueType = google::protobuf::Map<std::basic_string<char>, std::basic_string<char> >::KeyValuePair; Key = std::basic_string<char>; T = std::basic_string<char>]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:516:28:   required from ‘google::protobuf::Map<Key, T>::InnerMap::iterator google::protobuf::Map<Key, T>::InnerMap::begin() [with Key = std::basic_string<char>; T = std::basic_string<char>; google::protobuf::Map<Key, T>::InnerMap::iterator = google::protobuf::Map<std::basic_string<char>, std::basic_string<char> >::InnerMap::iterator_base<google::protobuf::Map<std::basic_string<char>, std::basic_string<char> >::KeyValuePair>]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:1037:27:   required from ‘google::protobuf::Map<Key, T>::iterator google::protobuf::Map<Key, T>::begin() [with Key = std::basic_string<char>; T = std::basic_string<char>]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:1147:27:   required from ‘void google::protobuf::Map<Key, T>::clear() [with Key = std::basic_string<char>; T = std::basic_string<char>]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map_field_inl.h:188:1:   required from ‘void google::protobuf::internal::MapField<Derived, Key, T, key_wire_type, value_wire_type, default_enum_value>::Clear() [with Derived = tensorflow::FunctionDef_RetEntry_DoNotUse; Key = std::basic_string<char>; T = std::basic_string<char>; google::protobuf::internal::WireFormatLite::FieldType kKeyFieldType = (google::protobuf::internal::WireFormatLite::FieldType)9; google::protobuf::internal::WireFormatLite::FieldType kValueFieldType = (google::protobuf::internal::WireFormatLite::FieldType)9; int default_enum_value = 0]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/tensorflow/core/framework/function.pb.h:1104:14:   required from here
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:428:29: error: cannot call member function ‘bool google::protobuf::Map<Key, T>::InnerMap::TableEntryIsNonEmptyList(google::protobuf::Map<Key, T>::size_type) const [with Key = std::basic_string<char>; T = std::basic_string<char>; google::protobuf::Map<Key, T>::size_type = long unsigned int]’ without object
           if (m_->TableEntryIsNonEmptyList(bucket_index_)) {
           ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:431:30: error: cannot call member function ‘bool google::protobuf::Map<Key, T>::InnerMap::TableEntryIsTree(google::protobuf::Map<Key, T>::size_type) const [with Key = std::basic_string<char>; T = std::basic_string<char>; google::protobuf::Map<Key, T>::size_type = long unsigned int]’ without object
           } else if (m_->TableEntryIsTree(bucket_index_)) {
              ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h: In instantiation of ‘bool google::protobuf::Map<Key, T>::InnerMap::iterator_base<KeyValueType>::revalidate_if_necessary(google::protobuf::Map<Key, T>::InnerMap::TreeIterator*) [with KeyValueType = google::protobuf::Map<std::basic_string<char>, std::basic_string<char> >::KeyValuePair; Key = std::basic_string<char>; T = std::basic_string<char>; google::protobuf::Map<Key, T>::InnerMap::TreeIterator = std::_Rb_tree_const_iterator<std::basic_string<char>*>]’:
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:610:12:   required from ‘void google::protobuf::Map<Key, T>::InnerMap::erase(google::protobuf::Map<Key, T>::InnerMap::iterator) [with Key = std::basic_string<char>; T = std::basic_string<char>; google::protobuf::Map<Key, T>::InnerMap::iterator = google::protobuf::Map<std::basic_string<char>, std::basic_string<char> >::InnerMap::iterator_base<google::protobuf::Map<std::basic_string<char>, std::basic_string<char> >::KeyValuePair>]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:1139:1:   required from ‘google::protobuf::Map<Key, T>::iterator google::protobuf::Map<Key, T>::erase(google::protobuf::Map<Key, T>::iterator) [with Key = std::basic_string<char>; T = std::basic_string<char>]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:1144:14:   required from ‘void google::protobuf::Map<Key, T>::erase(google::protobuf::Map<Key, T>::iterator, google::protobuf::Map<Key, T>::iterator) [with Key = std::basic_string<char>; T = std::basic_string<char>]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:1147:21:   required from ‘void google::protobuf::Map<Key, T>::clear() [with Key = std::basic_string<char>; T = std::basic_string<char>]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map_field_inl.h:188:1:   required from ‘void google::protobuf::internal::MapField<Derived, Key, T, key_wire_type, value_wire_type, default_enum_value>::Clear() [with Derived = tensorflow::FunctionDef_RetEntry_DoNotUse; Key = std::basic_string<char>; T = std::basic_string<char>; google::protobuf::internal::WireFormatLite::FieldType kKeyFieldType = (google::protobuf::internal::WireFormatLite::FieldType)9; google::protobuf::internal::WireFormatLite::FieldType kValueFieldType = (google::protobuf::internal::WireFormatLite::FieldType)9; int default_enum_value = 0]’
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/tensorflow/core/framework/function.pb.h:1104:14:   required from here
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:490:29: error: cannot call member function ‘bool google::protobuf::Map<Key, T>::InnerMap::TableEntryIsNonEmptyList(google::protobuf::Map<Key, T>::size_type) const [with Key = std::basic_string<char>; T = std::basic_string<char>; google::protobuf::Map<Key, T>::size_type = long unsigned int]’ without object
         if (m_->TableEntryIsNonEmptyList(bucket_index_)) {
         ~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~
/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/include/google/protobuf/map.h:504:24: error: cannot call member function ‘bool google::protobuf::Map<Key, T>::InnerMap::TableEntryIsList(google::protobuf::Map<Key, T>::size_type) const [with Key = std::basic_string<char>; T = std::basic_string<char>; google::protobuf::Map<Key, T>::size_type = long unsigned int]’ without object
         return m_->TableEntryIsList(bucket_index_);
         ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~
Makefile:91: recipe for target 'object/tensorflow_gpu_gemm.cu.cc.o' failed
make: *** [object/tensorflow_gpu_gemm.cu.cc.o] Error 1
INFO from ocnn: The octree key is 32 bits, the octree depth should be smaller than 8.
Traceback (most recent call last):
  File "test_all.py", line 5, in <module>
    from test_octree2col import Octree2ColTest
  File "/home/zstuxinxi/wy/O-CNN-master/tensorflow/test/test_octree2col.py", line 8, in <module>
    from libs import *
  File "../libs/__init__.py", line 20, in <module>
    _tf_ocnn_module = tf.load_op_library(os.path.join(_current_path, 'libocnn.so'))
  File "/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/python/framework/load_library.py", line 61, in load_op_library
    lib_handle = py_tf.TF_LoadLibrary(library_filename)
tensorflow.python.framework.errors_impl.NotFoundError: /home/zstuxinxi/wy/O-CNN-master/tensorflow/libs/libocnn.so: cannot open shared object file: No such file or directory

my ubuntu version is 18.04  and the  cuda version is 10.1 , i also check the  CUDA environment, but have no idea
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64
export PATH=/usr/local/cuda/bin:$PATH
export CUDA_HOME=$CUDA_HOME:/usr/local/cuda
export CPATH=/usr/local/cuda/targets/x86_64-linux/include:$CPATH

Any help would be greatly appreciated.

According to the error message,  the building process of tensorflow_gpu_gemm.cu.cc failed. Please run the command nvcc --version  in the bash to check whether the compiler nvcc can be found.
Otherwise, I think the following export commands that explicitly specify the cuda-10.1 might be helpful:
export PATH="/usr/local/cuda-10.1/bin:$PATH"
export CUDA_HOME="/usr/local/cuda-10.1"
export LD_LIBRARY_PATH="/usr/local/cuda-10.1/lib64:$LD_LIBRARY_PATH"

Thanks for  your help. I follow your advice, but the error doesn't disappear.

Makefile:91: recipe for target 'object/tensorflow_gpu_gemm.cu.cc.o' failed
make: *** [object/tensorflow_gpu_gemm.cu.cc.o] Error 1
INFO from ocnn: The octree key is 32 bits, the octree depth should be smaller than 8.
Traceback (most recent call last):
File "test_all.py", line 5, in
from test_octree2col import Octree2ColTest
File "/home/zstuxinxi/wy/O-CNN-master/tensorflow/test/test_octree2col.py", line 8, in
from libs import *
File "../libs/init.py", line 20, in
_tf_ocnn_module = tf.load_op_library(os.path.join(_current_path, 'libocnn.so'))
File "/home/zstuxinxi/miniconda3/envs/tf-1.14.0/lib/python3.6/site-packages/tensorflow/python/framework/load_library.py", line 61, in load_op_library
tensorflow.python.framework.errors_impl.NotFoundError: /home/zstuxinxi/wy/O-CNN-master/tensorflow/libs/libocnn.so: cannot open shared object file: No such file or directory

I checked the nvcc -version command, it works well.

(tf-1.14.0) zstuxinxi@pai-worker3:~/wy/O-CNN-master/tensorflow/libs$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Fri_Feb__8_19:08:17_PST_2019
Cuda compilation tools, release 10.1, V10.1.105

here is my cuda info

(tf-1.14.0) zstuxinxi@pai-worker3:~/wy/O-CNN-master/tensorflow/libs$ ll /usr/local/
总用量 56
drwxr-xr-x 14 root      root      4096 9月  17 11:33 ./
drwxr-xr-x 13 root      root      4096 8月  18 14:15 ../
drwxr-xr-x  2 root      root      4096 6月  30 15:52 bin/
lrwxrwxrwx  1 root      root        20 9月  17 11:33 cuda -> /usr/local/cuda-10.1/
drwxr-xr-x 18 root      root      4096 9月  17 11:32 cuda-10.1/
drwxr-xr-x 18 root      root      4096 9月  14 11:33 cuda-10.2/
drwxr-xr-x 16 root      root      4096 7月   7 07:31 cuda-11.1/
drwxr-xr-x  2 root      root      4096 8月   7  2020 etc/
drwxrwxr-x  3 zstuxinxi zstuxinxi 4096 6月  17 18:18 frp/
drwxr-xr-x  2 root      root      4096 8月   7  2020 games/
drwxr-xr-x  3 root      root      4096 6月  25 15:10 include/
drwxr-xr-x  5 root      root      4096 6月  21 21:03 lib/
lrwxrwxrwx  1 root      root         9 5月  23 17:16 man -> share/man/
drwxr-xr-x  2 root      root      4096 8月   7  2020 sbin/
drwxr-xr-x  8 root      root      4096 6月  21 21:14 share/
drwxr-xr-x  2 root      root      4096 8月   7  2020 src/

Sorry that I can not reproduce your error on my own PC.  Did you strictly follow the readme to build the code? Or please provide the executed commands?

I strictly followed the readme, expect git clone --recursive https://github.com/wang-ps/octree-ext.git command.
Due to the internet speed limitation, I used an accelerated url.
git clone  https://hub.fastgit.org/wang-ps/octree-ext.git

then i modify urls in .gitmodules  to download fast
[submodule "pybind11"]
	path = pybind11
	url = https://github.com.cnpmjs.org/pybind/pybind11.git
[submodule "nanoflann"]
	path = nanoflann
	url = https://github.com.cnpmjs.org/jlblancoc/nanoflann.git
[submodule "googletest"]
	path = googletest
	url = https://github.com.cnpmjs.org/google/googletest.git
[submodule "glog"]
	path = glog
	url = https://github.com.cnpmjs.org/google/glog.git
[submodule "happly"]
	path = happly
	url = https://github.com.cnpmjs.org/wang-ps/happly.git

finally i use these commands to update url and download, i also update .gitmodules of pybind11
git submodule sync
git submodule update --init --recursive

I follow the readme to build code
cd .. && mkdir build && cd build
cmake ..  && cmake --build . --config Release

here is the build log

(base) zstuxinxi@pai-worker3:~/wy/O-CNN/octree/build$ cmake ..  && cmake --build . --config Release
-- octree: USE_CUDA
-- octree: CMAKE_CUDA_STANDARD=11
-- octree: _GLIBCXX_USE_CXX11_ABI=1
-- octree: USE_MINIBALL
CMake Deprecation Warning at external/octree-ext/googletest/CMakeLists.txt:4 (cmake_minimum_required):
Compatibility with CMake < 2.8.12 will be removed from a future version of
CMake.
Update the VERSION argument  value or use a ... suffix to tell
CMake that the project does not need compatibility with older versions.
CMake Deprecation Warning at external/octree-ext/googletest/googlemock/CMakeLists.txt:45 (cmake_minimum_required):
Compatibility with CMake < 2.8.12 will be removed from a future version of
CMake.
Update the VERSION argument  value or use a ... suffix to tell
CMake that the project does not need compatibility with older versions.
CMake Deprecation Warning at external/octree-ext/googletest/googletest/CMakeLists.txt:56 (cmake_minimum_required):
Compatibility with CMake < 2.8.12 will be removed from a future version of
CMake.
Update the VERSION argument  value or use a ... suffix to tell
CMake that the project does not need compatibility with older versions.
-- Configuring done
CMake Warning (dev) in CMakeLists.txt:
Policy CMP0104 is not set: CMAKE_CUDA_ARCHITECTURES now detected for NVCC,
empty CUDA_ARCHITECTURES not allowed.  Run "cmake --help-policy CMP0104"
for policy details.  Use the cmake_policy command to set the policy and
suppress this warning.
CUDA_ARCHITECTURES is empty for target "octree_lib".
This warning is for project developers.  Use -Wno-dev to suppress it.
-- Generating done
-- Build files have been written to: /home/zstuxinxi/wy/O-CNN/octree/build
Consolidate compiler generated dependencies of target gtest
[  2%] Built target gtest
Consolidate compiler generated dependencies of target octree_lib
[  3%] Building CXX object CMakeFiles/octree_lib.dir/octree/mesh.cpp.o
[  4%] Building CXX object CMakeFiles/octree_lib.dir/octree/octree.cpp.o
[  6%] Building CXX object CMakeFiles/octree_lib.dir/octree/octree_conv.cpp.o
[  7%] Building CXX object CMakeFiles/octree_lib.dir/octree/octree_info.cpp.o
[  8%] Building CXX object CMakeFiles/octree_lib.dir/octree/octree_nn.cpp.o
[  9%] Building CXX object CMakeFiles/octree_lib.dir/octree/octree_parser.cpp.o
[ 10%] Building CXX object CMakeFiles/octree_lib.dir/octree/octree_samples.cpp.o
[ 12%] Building CXX object CMakeFiles/octree_lib.dir/octree/octree_value.cpp.o
[ 13%] Building CXX object CMakeFiles/octree_lib.dir/octree/points.cpp.o
[ 14%] Building CXX object CMakeFiles/octree_lib.dir/octree/points_info.cpp.o
[ 15%] Building CXX object CMakeFiles/octree_lib.dir/octree/points_parser.cpp.o
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[ 18%] Building CXX object CMakeFiles/octree_lib.dir/octree/transform_octree.cpp.o
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[ 20%] Building CUDA object CMakeFiles/octree_lib.dir/octree/octree_nn.cu.o
[ 21%] Building CUDA object CMakeFiles/octree_lib.dir/octree/octree_parser.cu.o
[ 22%] Linking CXX static library liboctree_lib.a
[ 30%] Built target octree_lib
[ 31%] Building CXX object external/octree-ext/googletest/googletest/CMakeFiles/gtest_main.dir/src/gtest_main.cc.o
[ 32%] Linking CXX static library ../../../../lib/libgtest_main.a
[ 32%] Built target gtest_main
[ 33%] Building CXX object CMakeFiles/octree_test.dir/test/test_octree.cpp.o
[ 34%] Building CXX object CMakeFiles/octree_test.dir/test/test_octree_nn.cpp.o
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[ 46%] Linking CXX executable play_ground
[ 46%] Built target play_ground
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[ 87%] Linking CXX executable simplify_points
[ 87%] Built target simplify_points
[ 89%] Building C object CMakeFiles/rply.dir/external/octree-ext/rply-1.1.4/rply.c.o
[ 90%] Linking C static library librply.a
[ 90%] Built target rply
[ 91%] Building CXX object CMakeFiles/clip_points.dir/tools/clip_points.cpp.o
[ 92%] Linking CXX executable clip_points
[ 92%] Built target clip_points
[ 93%] Building CXX object CMakeFiles/custom_data.dir/tools/custom_data.cpp.o
[ 95%] Linking CXX executable custom_data
[ 95%] Built target custom_data
[ 96%] Building CXX object CMakeFiles/octree2mesh.dir/tools/octree2mesh.cpp.o
[ 97%] Linking CXX executable octree2mesh
[ 97%] Built target octree2mesh
[ 98%] Building CXX object CMakeFiles/octree2points.dir/tools/octree2points.cpp.o
[100%] Linking CXX executable octree2points
[100%] Built target octree2points

The building process of octree is OK. The error is from the tensorflow-based ocnn.
How do you build the code in the folder tensorflow?
For your reference, you can use the docker with the ocnn-tf which is ready to use:  docker pull wangps/ocnn:tf-1.14.0

I use conda to create tensorflow  environment followed by readme .
I followed your advice and it works well in docker.Thanks for your help, it's very kind of you.

@flyKite1998 @wang-ps I have the same problem and same environment condition but I still cannot solve this issue after I run the docker pull wangps/ocnn:tf-1.14.0 , how did you solve it then?