Support finding Visual Studio instances using vswhere.exe

This PR adds another option in attempting to find an installed Visual Studio version by using vswhere.exe.
vswhere.exe has a known location (%ProgramFiles(x86)%\Microsoft Visual Studio\Installer) and is a 32-bit application which means it can be used on Windows ARM64 to locate Visual Studio (see https://github.com/rust-lang/rust/issues/83043).
vswhere.exe is used as a last resort to find VS2015+ if everything else has failed. vswhere.exe itself is launched with parameters to search for only the latest available version that has component Microsoft.VisualStudio.Component.VC.Tools.<ARCH> installed.

Thanks! This seems reasonable enough to me to go ahead and land. AFAIK this is one of the last remaining blocks running rustc on aarch64 Windows itself, right?
It looks like CI says the msrv needs bumping, but that's fine to do, you'll just need to edit the CI configuration

Sorry for the late reply, I missed the notification 😬
I've changed the usage of Self to the explicit type name. This way I guess it should compile on older Rust versions, and it's also consistent with what I've used in into_iter for VsInstances 🙂

Hmm, rustup failed with memory allocation of 16777216 bytes failed 🤔 Should I try upgrading MSRV after all?

I think it may be related to a recent rustup bug? Mind adding a rustup self update to CI to precede this until Github Actions picks up the new version by default?

Let's see if that helps :)

OMG. Another try?

Thanks again!

Thank you! 🙂

@alexcrichton How do I know if this is in the latest crate that rustup-init.exe pulls down?  I'd like to test for my custom Visual Studio 2019 Community installation on E:\ drive for Windows 10 64bit.
@Alovchin91 We may eventually need to do this to actually find the path where vswhere.exe itself lives before we try to begin using it to ask for VS path locations:

Read KEY
Computer\HKEY_LOCAL_MACHINE\SOFTWARE\Microsoft\VisualStudio\Setup
Read Data using Name
Name=SharedInstallationPath
This tells us the Shared Path C:\Program Files (x86)\Microsoft Visual Studio\Installer\Shared
Look 1 level up by removing the ending \Shared and then look in path
This path will have vswhere.exe inside such as
C:\Program Files (x86)\Microsoft Visual Studio\Installer\vswhere.exe
Run vswhere.exe
Use output and parse installationPath to get custom location

According to the vswhere wiki:

Starting with Visual Studio 15.2 (26418.1 Preview) vswhere.exe is installed in %ProgramFiles(x86)%\Microsoft Visual Studio\Installer (use %ProgramFiles% in a 32-bit program prior to Windows 10). This is a fixed location that will be maintained.

So apparently this location is guaranteed for vswhere even if other components are installed elsewhere.

That's the current thinking indeed. I intentionally KISS and did not introduce unnecessary complexity since Microsoft promises to maintain the said path in the foreseeable future. If it ever changes, we might indeed want to reconsider. But for now vswhere.exe is the last resort and to be honest, I really hope that Microsoft fixes the COM component on ARM64. At least it's my impression from talking to them on Twitter that they could fix it (though I guess nobody knows when that would happen 🙈).

This was published in 1.0.68, so if your Cargo.lock contains 1.0.68 then it's using this.


Sporadically invalid highlight colors

Prerequsities

[x] I'm on the latest version of the plugin
[x] I've installed the required dependencies
[x] I've run :h gitlab.nvim.troubleshooting and followed the steps there

Setup Configuration and Environment
I implemented the plugin as follows:
return {
	"harrisoncramer/gitlab.nvim",
	dependencies = {
		"MunifTanjim/nui.nvim",
		"nvim-lua/plenary.nvim",
		"sindrets/diffview.nvim",
		"stevearc/dressing.nvim", -- Recommended but not required. Better UI for pickers.
		"nvim-tree/nvim-web-devicons", -- Recommended but not required. Icons in discussion tree.
	},
	enabled = true,
	build = function()
		require("gitlab.server").build(true)
	end, -- Builds the Go binary
	config = function()
    local gitlab = require("gitlab")
    gitlab.setup()
		vim.keymap.set("n", "<leader>glb", gitlab.choose_merge_request, { desc = "Choose merge request" })
		vim.keymap.set("n", "<leader>glr", gitlab.review, { desc = "Review" })
		vim.keymap.set("n", "<leader>gls", gitlab.summary, { desc = "Summary" })
		vim.keymap.set("n", "<leader>glA", gitlab.approve, { desc = "Approve" })
		vim.keymap.set("n", "<leader>glR", gitlab.revoke, { desc = "Revoke" })
		vim.keymap.set("n", "<leader>glc", gitlab.create_comment, { desc = "Create comment" })
		vim.keymap.set("v", "<leader>glc", gitlab.create_multiline_comment, { desc = "Create multiline comment" })
		vim.keymap.set("v", "<leader>glC", gitlab.create_comment_suggestion, { desc = "Create comment suggestion" })
		vim.keymap.set("n", "<leader>glO", gitlab.create_mr, { desc = "Create merge request" })
		vim.keymap.set("n", "<leader>glm", gitlab.move_to_discussion_tree_from_diagnostic, { desc = "Move to discussion tree" })
		vim.keymap.set("n", "<leader>gln", gitlab.create_note, { desc = "Create note" })
		vim.keymap.set("n", "<leader>gld", gitlab.toggle_discussions, { desc = "Toggle discussions" })
		vim.keymap.set("n", "<leader>glaa", gitlab.add_assignee, { desc = "Add assignee" })
		vim.keymap.set("n", "<leader>glad", gitlab.delete_assignee, { desc = "Delete assignee" })
		vim.keymap.set("n", "<leader>glla", gitlab.add_label, { desc = "Add label" })
		vim.keymap.set("n", "<leader>glld", gitlab.delete_label, { desc = "Delete label" })
		vim.keymap.set("n", "<leader>glra", gitlab.add_reviewer, { desc = "Add reviewer" })
		vim.keymap.set("n", "<leader>glrd", gitlab.delete_reviewer, { desc = "Delete reviewer" })
		vim.keymap.set("n", "<leader>glp", gitlab.pipeline, { desc = "Pipeline" })
		vim.keymap.set("n", "<leader>glo", gitlab.open_in_browser, { desc = "Open in browser" })
		vim.keymap.set("n", "<leader>glM", gitlab.merge, { desc = "Merge" })
		vim.keymap.set("n", "<leader>glu", gitlab.copy_mr_url, { desc = "Copy MR URL" })
		vim.keymap.set("n", "<leader>glP", gitlab.publish_all_drafts, { desc = "Publish all drafts" })
		vim.keymap.set("n", "<leader>glD", gitlab.toggle_draft_mode, { desc = "Toggle draft mode" })
	end,
}

Bug Description
When opening neovim with gitlab.nvim enabled, I sporadically get the following error:
Failed to run `config` for gitlab.nvim

....local/share/nvim/lazy/gitlab.nvim/lua/gitlab/colors.lua:10: Invalid highlight color: '14'

# stacktrace:
  - /gitlab.nvim/lua/gitlab/colors.lua:10
  - /gitlab.nvim/lua/gitlab/init.lua:38 _in_ **setup**
  - ~/.config/nvim/lua/plugins/gitlab.lua:16 _in_ **config**
  - ~/dotfiles/nvim/init.lua:17

Afterwards, I need to restart neovim a few times until the error does not appear.
Reproduction Steps

Check out the feature branch
Open Neovim

Interesting, this appears to be an issue with looking up a local color highlighting for the Directory group. You can trigger this error manually in Neovim like this, because "14" is not a valid color:
vim.api.nvim_set_hl(0, "GitlabDate", { fg = '14' })

Can you please try creating this file on your local system:
-- the-file.lua
local group = "Directory"
local get_colors_for_group = function(group)
  local normal_fg = vim.fn.synIDattr(vim.fn.synIDtrans((vim.fn.hlID(group))), "fg")
  local normal_bg = vim.fn.synIDattr(vim.fn.synIDtrans((vim.fn.hlID(group))), "bg")
  return { fg = normal_fg, bg = normal_bg }
end

local results = get_colors_for_group(group)
vim.print(results)

And then running it with Neovim:
:so the-file.lua

What does it return for you? For me, it returns a Lua table that looks like this:
{
  bg = "",
  fg = "#7e9cd8"
}

Which is then used to color the directories in the discussion tree. It seems likely that for you it's returning an invalid table for some reason which is being fed into lua/gitlab/colors.lua which is then causing the issue.

The file returns the following regardless of if there is an error on startup or not:
{
  bg = "",
  fg = "#7aa2f7"
}

However, if I place the code to run before
local gitlab = require("gitlab")
gitlab.setup()

I sometimes get the following lua table which corresponds to my error message:
{
  bg = "",
  fg = "14"
}

This is tricky for me to debug for you since I'm not able to replicate it locally and it is not happening consistently. A few other things I'd recommend looking into:

Check that you have the Directory group set correctly: :hi Directory
Try changing the setup call for the plugin to use a different color group for the one that's causing you issues:

    require("gitlab").setup({
      colors = {
        discussion_tree = {
          directory = "Normal", -- Use a different highlight group here, like "Normal"
        }
      }
    })

You could also try removing/commenting out other plugins in batches to determine when/where the conflict is arising. It may be that another plugin or color scheme is setting that value incorrectly.

I managed to figure out, that the inconsistent nature of this issue is a race condition between the plugin and my colorscheme being loaded.
If the colorscheme (tokyonight) is loaded first, everything is fine. Otherwise I get this error.
Disabling my colorscheme makes this error happen consistently.
:hi Directory without my colorscheme gives me the following output:
Directory      xxx ctermfg=14 guifg=NvimLightCyan

I also realized that this error only happens when I use nvim in a tmux session.
I run tmux with the following setting:
set-option -g default-terminal "screen-256color"

I appear to have found a workaround by adding my colorscheme to the dependencies of the plugin:
  dependencies = {
    "MunifTanjim/nui.nvim",
    "nvim-lua/plenary.nvim",
    "sindrets/diffview.nvim",
    "folke/tokyonight.nvim",
    "stevearc/dressing.nvim",    -- Recommended but not required. Better UI for pickers.
    "nvim-tree/nvim-web-devicons", -- Recommended but not required. Icons in discussion tree.
  },

Gotcha, I'm glad you were able to find a solution.
This seems like a weird compatibility issue with Tmux, likely something in your settings there is causing this issue. I'm also a Tmux user and haven't been able to replicate it, but since you are unblocked I'll close this out.


[Bug] Invalid BSON field name $numberInt

Description
Setting up Server codebase using docker.
When i run docker-compose.yml @ https://github.com/appsmithorg/appsmith/blob/release/app/server/docker-compose.yml
seeing error
ppsmith-internal-server_1  | Error starting ApplicationContext. To display the conditions report re-run your application with 'debug' enabled.
appsmith-internal-server_1  |  - Application run failed
appsmith-internal-server_1  | java.lang.IllegalStateException: Failed to execute ApplicationRunner
appsmith-internal-server_1  |   at org.springframework.boot.SpringApplication.callRunner(SpringApplication.java:778)
appsmith-internal-server_1  |   at org.springframework.boot.SpringApplication.callRunners(SpringApplication.java:765)
appsmith-internal-server_1  |   at org.springframework.boot.SpringApplication.run(SpringApplication.java:322)
appsmith-internal-server_1  |   at org.springframework.boot.SpringApplication.run(SpringApplication.java:1226)
appsmith-internal-server_1  |   at org.springframework.boot.SpringApplication.run(SpringApplication.java:1215)
appsmith-internal-server_1  |   at com.appsmith.server.ServerApplication.main(ServerApplication.java:12)
appsmith-internal-server_1  |   at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
appsmith-internal-server_1  |   at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
appsmith-internal-server_1  |   at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
appsmith-internal-server_1  |   at java.base/java.lang.reflect.Method.invoke(Unknown Source)
appsmith-internal-server_1  |   at org.springframework.boot.loader.MainMethodRunner.run(MainMethodRunner.java:48)
appsmith-internal-server_1  |   at org.springframework.boot.loader.Launcher.launch(Launcher.java:87)
appsmith-internal-server_1  |   at org.springframework.boot.loader.Launcher.launch(Launcher.java:51)
appsmith-internal-server_1  |   at org.springframework.boot.loader.JarLauncher.main(JarLauncher.java:52)
appsmith-internal-server_1  | Caused by: com.github.cloudyrock.mongock.MongockException: Invalid BSON field name $numberInt
appsmith-internal-server_1  |   at com.github.cloudyrock.mongock.Mongock.executeMigration(Mongock.java:140)
appsmith-internal-server_1  |   at com.github.cloudyrock.mongock.Mongock.execute(Mongock.java:94)
appsmith-internal-server_1  |   at com.github.cloudyrock.mongock.SpringBootMongock.run(SpringBootMongock.java:24)
appsmith-internal-server_1  |   at org.springframework.boot.SpringApplication.callRunner(SpringApplication.java:775)
[What happened]
Steps to reproduce the behaviour:
Add steps to reproduce this behaviour, include console / network logs & screenshots

Clone Repo
cd app/server
rename docker.env.example to docker.env
docker-compose -f docker-compose.yml up

HI @sbansal6 👋
Thank you for reporting this. @mohanarpit can you see why this is happening?

@sbansal6  please check our contribution guide to look at the steps of how to run the server code base on your local machine.
Incase you are looking to run the entire Appsmith product on your machine, please check the Getting Started Guide on docs.appsmith.com

@mohanarpit :- i have followed the guide, but seeing this error irrespective

In our setup guide, we don't recommend using docker-compose.yml in the
app/server folder at all. Is there a particular reason you are using that
file to start the server? The docker-compose.yml file in the app/server
folder is old and needs to be removed from the codebase. It's no longer the
recommended way to start the server.
Alternatively, if you are looking to run the entire Appsmith project and
not just the server, please follow the steps at
https://docs.appsmith.com/quick-start.
Best
Arpit
On Mon, Nov 23, 2020 at 9:47 PM saurabh bansal<EMAIL_ADDRESS>wrote:

@mohanarpit https://github.com/mohanarpit :- i have followed the guide,
but seeing this error irrespective
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/appsmithorg/appsmith/issues/1831#issuecomment-732265119,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AADQBQXPRLI22WJKPLI5Q23SRKDIHANCNFSM4T5PARSQ
.


Clipping planes

This adds support for arbitrary clipping planes via a new ClippingPlane node. The only renderer backend to support this right now is the RenderMan one. This requires https://github.com/ImageEngine/cortex/pull/401 to be merged before it will build.

You could. My plan was to wait till we tagged Cortex and then update the gafferDependencies release packages so that we could demonstrate the tests passing here before merging. Are you hoping to get a Gaffer build out a bit more sharply than that will allow?

Needs a rebase now that I've merged the Paths thing.
No, I'm fine to wait for that. I was just looking at PRs while you had a look at the wireframe thing that's blocking the Cortex release.

I've updated the gafferDependencies project and rebased this pull request - tests are now passing.


Count lines changed for current file

This PR adds a feature to count lines changed for a specific file if rev control is Git.
Steps to tests:

Build wakatime-cli with make
Change any file inside a git repository
Call ./build/wakatime-cli* --entity "/path/to/changed_file" --log-to-stdout --verbose
It should print an array of heartbeats and the first element must contain lines_added and lines_removed fields
It should sync activity

Closes #609

Closing in favor of #1023.


Italian laguage, fixes and additions

:it: :pizza: :spaghetti:

features translation from japanese
homepage fixes from english

Can be merged? Updated italian translations

Thank you!!

いつもありがとうございます!


Update/improve arangoinspect docs

https://www.arangodb.com/docs/stable/programs-arangoinspect-examples.html
Arangoinspect previously requested metadata via "public" APIs, but was expanded (in version ?.?) to collect performance parameters from the nodes (DB-Servers, Coordinators, also Agents???):

df -h
top
uname
…

This information is only collected if the commands are available, i.e. only partially under macOS (it seems) and not at all under Windows (unless there is a substitute?).
Additionally, the docs should include an actual example output and a more comprehensive list of what is included in the report file, to emphasize its usefulness.

Is arangoinspect a tool that we will maintain or is it awaiting deprecation?


Library not loaded: @rpath/libjvm.dylib

When I try to run a fresh project created via IntelliJ using OpenJDK 11 I get this error:
Cannot open<EMAIL_ADDRESS><EMAIL_ADDRESS>9): Library not loaded: @rpath/libjvm.dylib
  Referenced from<EMAIL_ADDRESS>  Reason: image not found

I switched to Oracle JDK 17 and it seems to work fine now. Any suggestions or insights? I'm on 1.0.0-beta3 and also tried 1.0.0-alpha3
Also posting so that others with the same issue can find it. I wasn't been able to find anything useful.

So it is a JDK issue. Oracle JDK 11 indeed is the most stable now.

Please check the following ticket on YouTrack for follow-ups to this issue. GitHub issues will be closed in the coming weeks.


Proxies are invalid

Using your https://raw.githubusercontent.com/monosans/proxy-list/main/proxies/http.txt .
None of them working (for me)
They are all mocking the response for service to check for IPs (Which your http://ip-api.com/json website is). I even got (with one of the proxies) response just with ip at http://httpbin.org/get (which supposed to send back request object & headers)
Try using https://www.thecolorapi.com/scheme?hex=24B1E0&mode=triad&count=1 first (some public api)

If you run into this problem, you can always change the CheckWebsite setting. I plan to rewrite the code to use httpbin.org and a local geolocation database, but I don't have time for that yet.

I assume, if you have VPS (which I don't) you could exclude usage of any 3rd-party services. Not sure how to be done specifically in python. Socket.remoteAddress, but all checkers using x-forwarded-for or origin headers (not sure which and why)

Can't figure out how to check auth socks5 proxies.

you mean proxies with auth? idk how for your programing language goes, but for nodejs we use socks-proxy-agent lib and url specification for providing auth credentials with proxy ip:port

Fixed in https://github.com/monosans/proxy-scraper-checker/commit/e4047e16aeb9800bbaa91db429c9bd2cef5e0583.

Fixed in e4047e1.

Not really) Half of the https://github.com/monosans/proxy-list/blob/main/proxies/all.txt are duplicates.
I guess you have reasons, but why would you use httpbin while you have your own vps?

Half of the https://github.com/monosans/proxy-list/blob/main/proxies/all.txt are duplicates.

Thanks for bringing this to my attention. It was a bug, I fixed it.

why would you use httpbin while you have your own vps?

I don't want to put a strain on my VPS network because I have other projects running there.


Different Success Response Data Structure for Card and Bank Account Charge

Why is there a different Success Response Data Structure for Card and Bank Account Charge?
Data Structure:

Card (and Bank Account) both return "data" but their values have different objects
Card Charge return "tx"
Bank Account charge doesn't have "tx"
For Card Charge "tx" has object that contains "txRef"
For Bank Account Charge "data" has object that contains "txRef"

Provided this isn't intentional, please consider standardizing this, to minimize potential errors. Let's make both return the same data structure.
Thanks

Following up on this Issue.
Currently on iOS the "responseData" returns nil for function "func tranasctionSuccessful(flwRef: String?, responseData: [String : Any]?)".
Currently we use the "txRef" to verify our transaction using "Verify transaction" API v2. On v3 only "data.id" is required.
Q1. Do we need to "Verify transaction" for both "Card" and "Bank Account" Transaction?
Q2. How do we verify transaction if iOS "responseData" returns nil


Raw Textile in comments?

Just noticed a few old comments that have raw Textile in them:
http://alistapart.com/comments/responsive-web-design#328887
http://alistapart.com/comments/responsive-web-design#328902
http://alistapart.com/comments/responsive-web-design#328903
http://alistapart.com/comments/responsive-web-design#328910
Is this fixable?

This is mentioned in another issue: #147
I think @michellekondou has thoughts on it, but we haven't been able to get to it.

@michellekondou: was this solved when you closed #147 ?

No, this is a different issue.

As discussed in Slack, this looks like it was caused by moving from EE1 to EE2. Tim will manually fix this set of comments and open up a larger issue if we encounter other textile snippets.

I've updated the comments in this thread. It's still on our list to find a comprehensive fix.


Adding x:Bind demo

Demo project for upcoming blog post "Supercharge Your Data Binding"

@gdfonda,
Thanks for your contribution.
To ensure that the project team has proper rights to use your work, please complete the Contribution License Agreement at https://cla.microsoft.com.
It will cover your contributions to all Microsoft-managed open source projects.
Thanks,
Microsoft Pull Request Bot

@gdfonda, thanks for signing the contribution license agreement. We will now validate the agreement and then the pull request.
Thanks, Microsoft Pull Request Bot


Create a form for "Request for Cloud Workspace" to go in the Platform Services catalogue

Describe the issue
Platform Services has established a GitHub catalogue of service requests, and is preparing to move to a more automated v2. We could add our service requests to the menu.
Which Sprint Priority is this issue related to?
The 'Milestone' should clearly list Sprint Priorities - which one is this issue related to?
Additional context
This form will link to several Cloud Pathfinder reference documents and diagrams (Early Adopter Selection Guide, Shared Responsibility Model, ... etc.), and these links will be inactive pending decisions on where our materials will be published - see example "Request for OpenShift Project Set"
Definition of done

Draft form for requesting compliant cloud workspace
Peer review, and review with Product Owner
Product Owner to approve

Here's an example, for requesting an Open Shift Project Set:
Step 0
Are you the product owner or technical lead?
If not, you will need to ask one of those two people to make this request.
If you are one of these two people, please ensure that you also request Openshift access if you don't have it already. This request does NOT grant you access to the platform itself - you will find a separate request for that on the issues page of this repo!
However, you may submit both requests at the same time - there's no need to wait until that request has been completed to submit this one.
Have you had an alignment meeting?
If not, please set up a meeting with the Enterprise DevOps branch leadership prior to submitting a project request.
Step 1
Visit DevHub for detailed instruction on creating a request:
https://developer.gov.bc.ca/Getting-Started-on-the-DevOps-Platform/How-to-Request-a-New-OpenShift-Project
Read through the Platform Onboarding Guide before continue with this request. This helps to get clear expectations of the platform and how to collaborate with the Platform community alone the journey:
https://developer.gov.bc.ca/Welcome-to-our-Platform-Community!

[ ] By checking it I confirm that I have read and understood the roles and responsibilities as described in the Onboarding Guide.

Step 2
Make sure no duplicated request exists, search here:
https://github.com/BCDevOps/devops-requests/issues
Step 3
Are you requesting to:

[x] Create a project set
[ ] Remove a project set

Step 4.1
To address current capacity issues related to the limited Platform CPU, we’ve made the difficult decision to temporarily prioritize new project requests, based on the following criteria, please check the ones that apply to your project.

[ ] Your project addresses the needs of an urgent COVID-19 response
[ ] Your project has been designated as high business priority
[ ] You have the DevOps capacity in place to support the development of resilient architecture suitable for multi-node deployment

This is a temporary situation only, which will be resolved when we migrate to OpenShift 4 (OCP 4) in Fall 2020. Our OCP 4 expansion more than doubles current CPU capacity with new production clusters, plus an additional Azure Cloud offering.
Step 4.2
Fill out the following fields

Short Team/Organization Name:
Product Short Name:
Product Full Name:
Product Description:
Product Group Name (if exists, used to group together OpenShift Project Sets that are related to each other):
Desired Environments: tools, dev, test, prod
GitHub Repository (if exists):

Step 5
Submit this ticket and email us the contact information.
For security purpose, please provide the following contact information to the email address -<EMAIL_ADDRESS>
link to the GitHub ticket you just created
Product Technical Steward

GitHub ID:
Business Email Address:
RocketChat Account Username:

Product Owner

Business Email Address: (BCGov employee)
RocketChat Account Username:
Organization Code:
Organization Unit Code:
(refer to https://dir.gov.bc.ca/)

Other Critical Contacts

(this could be a member of IMB, Architecture, Privacy, etc groups)
Email Address:

BC Government Security Contact Information

Ministry Chief Information Officer:

(refer to https://www2.gov.bc.ca/assets/gov/british-columbians-our-governments/services-policies-for-government/information-technology/ocio/mcio_contact_list.pdf)

Ministry Information Security Officer:

(refer to https://intranet.gov.bc.ca/thehub/ocio/ocio-enterprise-services/information-security-branch/miso-contacts)

Ministry Privacy Officer:

(refer to https://www2.gov.bc.ca/gov/content/governments/services-for-government/information-management-technology/privacy/resources/privacy-officers)

Please note that we will only start processing your request when the email has been received.

Looks good @scayzer good to go after touch point with @sid-gov re capacity

Update: 2021-01-26
Here's a quick draft, based on the form for requesting an Open Shift Project Set:
Step 0
Are you the product owner or technical lead?
If not, you will need to ask one of those two people to make this request.
Have you had an alignment meeting?
If not, please set up a meeting with the Cloud Pathfinder team prior to submitting a cloud workspace request.
Step 1
Visit DevHub to obtain and fill in the Cloud Product Team Profile:
https://developer.gov.bc.ca/Cloud-Product-Team-Profile
Step 2
Make sure no duplicated request exists, search here:
https://github.com/BCDevOps/devops-requests/issues
Step 3
Are you requesting to:

[x] Create a public cloud workspace
[ ] Close down a public cloud workspace

Step 4
Fill out the following fields

Short Team/Organization Name:
Product Short Name:
Product Full Name:
Product Description:
Desired Environments: tools, dev, test, prod
GitHub Repository (if exists):

Step 5
Submit this ticket and email us the contact information.
For security purpose, please provide the following contact information to the email address -<EMAIL_ADDRESS>
link to the GitHub ticket you just created
Product Executive Sponsor

Executive Role
Business Email Address:

Product Technical Steward

GitHub ID:
Business Email Address:
RocketChat Account Username:

Product Owner

Business Email Address: (BCGov employee)
RocketChat Account Username:
Organization Code:
Organization Unit Code:
(refer to https://dir.gov.bc.ca/)

Other Critical Contacts

(this could be a member of IMB, Architecture, Privacy, etc groups)
Email Address:

BC Government Security Contact Information

Ministry Chief Information Officer:

(refer to https://www2.gov.bc.ca/assets/gov/british-columbians-our-governments/services-policies-for-government/information-technology/ocio/mcio_contact_list.pdf)

Ministry Information Security Officer:

(refer to https://intranet.gov.bc.ca/thehub/ocio/ocio-enterprise-services/information-security-branch/miso-contacts)

Ministry Privacy Officer:

(refer to https://www2.gov.bc.ca/gov/content/governments/services-for-government/information-management-technology/privacy/resources/privacy-officers)

Please note that we will only start processing your request when the email has been received.

Update: 2021-01-26
Here's a quick draft, based on the form for requesting an Open Shift Project Set:
Step 0
Are you the product owner or technical lead?
If not, you will need to ask one of those two people to make this request.
Have you had an alignment meeting?
If not, please set up a meeting with the Cloud Pathfinder team prior to submitting a cloud workspace request.
Step 1
Visit DevHub to obtain and fill in the Cloud Product Team Profile:
https://developer.gov.bc.ca/Cloud-Product-Team-Profile
Step 2
Make sure no duplicated request exists, search here:
https://github.com/BCDevOps/devops-requests/issues
Step 3
Are you requesting to:

[x] Create a public cloud workspace
[ ] Close down a public cloud workspace

Step 4
Fill out the following fields

Short Team/Organization Name:
Product Short Name:
Product Full Name:
Product Description:
Desired Environments: tools, dev, test, prod
GitHub Repository (if exists):

Step 5
Submit this ticket and email us the contact information.
For security purpose, please provide the following contact information to the email address -<EMAIL_ADDRESS>
link to the GitHub ticket you just created
Product Executive Sponsor

Executive Role
Business Email Address:

Product Technical Steward

GitHub ID:
Business Email Address:
RocketChat Account Username:

Product Owner

Business Email Address: (BCGov employee)
RocketChat Account Username:
Organization Code:
Organization Unit Code:
(refer to https://dir.gov.bc.ca/)

Other Critical Contacts

(this could be a member of IMB, Architecture, Privacy, etc groups)
Email Address:

BC Government Security Contact Information

Ministry Chief Information Officer:

(refer to https://www2.gov.bc.ca/assets/gov/british-columbians-our-governments/services-policies-for-government/information-technology/ocio/mcio_contact_list.pdf)

Ministry Information Security Officer:

(refer to https://intranet.gov.bc.ca/thehub/ocio/ocio-enterprise-services/information-security-branch/miso-contacts)

Ministry Privacy Officer:

(refer to https://www2.gov.bc.ca/gov/content/governments/services-for-government/information-management-technology/privacy/resources/privacy-officers)

Please note that we will only start processing your request when the email has been received.

Discussed with Shea (2021-01-27) - learned that the Platform Service Catalogue isn't an appropriate tool to manage the workflow that leads to onboarding a ministry team into a public cloud workspace. Let's discuss this further during sprint planning to figure out how to best frame the work we propose to do, and determine where it fits within our priorities.

Discussed with Shea (2021-01-27) - learned that the Platform Service Catalogue isn't an appropriate tool to manage the workflow that leads to onboarding a ministry team into a public cloud workspace. Let's discuss this further during sprint planning to figure out how to best frame the work we propose to do, and determine where it fits within our priorities.


I do not  see any option to train data using local files, is it not available or not yet documented?

[Enter feedback here]

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: 1e3de1b4-a118-efae-0e72-7953c8e891b3
Version Independent ID: 5ad38c9e-c775-8dbc-16ff-705a40b580e1
Content: Quickstart: Form Recognizer client library - Azure Cognitive Services
Content Source: articles/cognitive-services/form-recognizer/quickstarts/client-library.md
Service: cognitive-services
Sub-service: forms-recognizer
GitHub Login: @PatrickFarley
Microsoft Alias: pafarley

@iAmBipinPaul Thanks for the question. We are investigating the issue and will update you shortly.

@iAmBipinPaul Thanks, you can train a Form Recognizer model with labels using the sample labeling tool. Please follow the below document to trian custom model. If possible could you please add more details about the use case.
https://docs.microsoft.com/en-us/azure/cognitive-services/form-recognizer/quickstarts/label-tool?tabs=v2-0

@ram-msft so to train and label ,I must have to upload file to blob storage.

Yes @iAmBipinPaul. For training model using the label data you need to use the  with the Azure Blob storage container's shared access signature (SAS) URL. For analyzing the receipts  you can use the path to your local form document.
We will now proceed to close this thread. If there are further questions regarding this matter, please tag me in your reply. We will gladly continue the discussion and we will reopen the issue.

Thank you !.
Got answer


Segmentation fault in grpc/_channel.py

Please answer these questions before submitting your issue.
This may be related to https://github.com/grpc/grpc/issues/13327.
What version of gRPC and what language are you using?
gapic-google-cloud-datastore-v1 (0.15.3)
gapic-google-cloud-error-reporting-v1beta1 (0.15.3)
gapic-google-cloud-logging-v2 (0.91.3)
gapic-google-cloud-pubsub-v1 (0.15.4)
google-api-core (0.1.4)
google-api-python-client (1.6.5)
google-auth (1.4.1)
google-cloud (0.32.0)
google-cloud-bigquery (0.28.0)
google-cloud-bigquery-datatransfer (0.1.1)
google-cloud-bigtable (0.28.1)
google-cloud-container (0.1.1)
google-cloud-core (0.26.0)
google-cloud-datastore (1.4.0)
google-cloud-dns (0.28.0)
google-cloud-error-reporting (0.28.0)
google-cloud-firestore (0.28.0)
google-cloud-language (1.0.1)
google-cloud-logging (1.4.0)
google-cloud-monitoring (0.28.1)
google-cloud-pubsub (0.26.0)
google-cloud-resource-manager (0.28.1)
google-cloud-runtimeconfig (0.28.1)
google-cloud-spanner (0.29.0)
google-cloud-speech (0.30.0)
google-cloud-storage (1.6.0)
google-cloud-trace (0.17.0)
google-cloud-translate (1.3.1)
google-cloud-videointelligence (1.0.1)
google-cloud-vision (0.29.0)
google-gax (0.15.16)
google-resumable-media (0.3.1)
googleapis-common-protos (1.5.3)
grpc-google-iam-v1 (0.11.4)
grpcio (1.10.0)
What operating system (Linux, Windows, …) and version?
$ lsb_release -a
No LSB modules are available.
Distributor ID:	Debian
Description:	Debian GNU/Linux 9.3 (stretch)
Release:	9.3
Codename:	stretch
What runtime / compiler are you using (e.g. python version or version of gcc)
$ python --version
Python 2.7.13
What did you do?
Virtual Machine: Google Cloud Engine: n1-standard-1 (1 vCPU, 3.75 GB memory)
Point of interest: https://github.com/google/turbinia/blob/master/turbiniactl#L436

Everything is done in Virtualenv
Install and launch Turbinia server and worker
Both the server and worker talks with pubsub
The worker forks itself
Run turbiniactl (which talks with pubsub) to create a task for the worker to process
The worker receives a new message from pubsub

What did you expect to see?
No segmentation fault.
What did you see instead?
NOTE: Two gdb outputs (py-bt and bt) are pasted here.
(turbinia-dev2) turbinia@test-turbinia-test:~$ gdb turbinia-dev2/bin/python2.7
GNU gdb (Debian 7.12-6) <IP_ADDRESS>61007-git
Copyright (C) 2016 Free Software Foundation, Inc.
License GPLv3+: GNU GPL version 3 or later http://gnu.org/licenses/gpl.html
This is free software: you are free to change and redistribute it.
There is NO WARRANTY, to the extent permitted by law.  Type "show copying"
and "show warranty" for details.
This GDB was configured as "x86_64-linux-gnu".
Type "show configuration" for configuration details.
For bug reporting instructions, please see:
http://www.gnu.org/software/gdb/bugs/.
Find the GDB manual and other documentation resources online at:
http://www.gnu.org/software/gdb/documentation/.
For help, type "help".
Type "apropos word" to search for commands related to "word"...
Reading symbols from turbinia-dev2/bin/python2.7...Reading symbols from /usr/lib/debug/.build-id/78/bba47ddc77739d7744bfd0f89bbae01a73d506.debug...done.
done.
(gdb) info auto-load
gdb-scripts:  No auto-load scripts.
libthread-db:  No auto-loaded libthread-db.
local-gdbinit:  Local .gdbinit file was not found.
python-scripts:  No auto-load scripts.
(gdb) source /usr/share/gdb/auto-load/usr/bin/python2.7-gdb.py
(gdb) run /home/turbinia/turbinia/turbiniactl -L /var/tmp/turbinia-psqworker.log -o /var/tmp/ psqworker 2>> /var/tmp/turbinia-psqworker.stdout.log
Starting program: /home/turbinia/turbinia-dev2/bin/python2.7 /home/turbinia/turbinia/turbiniactl -L /var/tmp/turbinia-psqworker.log -o /var/tmp/ psqworker 2>> /var/tmp/turbinia-psqworker.stdout.log
[Thread debugging using libthread_db enabled]
Using host libthread_db library "/lib/x86_64-linux-gnu/libthread_db.so.1".
[New Thread 0x7ffff1ce3700 (LWP 1433)]
[New Thread 0x7ffff14e2700 (LWP 1434)]
[New Thread 0x7ffff0ce1700 (LWP 1435)]
[Thread 0x7ffff0ce1700 (LWP 1435) exited]
[New Thread 0x7ffff0ce1700 (LWP 1436)]
[Thread 0x7ffff0ce1700 (LWP 1436) exited]
[New Thread 0x7ffff0ce1700 (LWP 1437)]
[Thread 0x7ffff0ce1700 (LWP 1437) exited]
[Thread 0x7ffff14e2700 (LWP 1434) exited]
[Thread 0x7ffff1ce3700 (LWP 1433) exited]
[New Thread 0x7ffff1ce3700 (LWP 1440)]
[New Thread 0x7ffff0ce1700 (LWP 1443)]
[New Thread 0x7ffff14e2700 (LWP 1444)]
[New Thread 0x7fffe3de8700 (LWP 1445)]
[New Thread 0x7fffe35e7700 (LWP 1446)]
[New Thread 0x7fffe2de6700 (LWP 1447)]
[Thread 0x7fffe2de6700 (LWP 1447) exited]
[New Thread 0x7fffe2de6700 (LWP 1448)]
[Thread 0x7fffe2de6700 (LWP 1448) exited]
[New Thread 0x7fffe2de6700 (LWP 1449)]
[New Thread 0x7fffe25e5700 (LWP 1450)]
[Thread 0x7fffe25e5700 (LWP 1450) exited]
[New Thread 0x7fffe25e5700 (LWP 1471)]
[Thread 0x7fffe25e5700 (LWP 1471) exited]
[New Thread 0x7fffe25e5700 (LWP 1473)]
[Thread 0x7fffe25e5700 (LWP 1473) exited]
Checking availability and versions of dependencies.
[OPTIONAL]	missing: lzma.
[OK]
Source path	: /mnt/turbinia-mounts/turbiniaErPdFR
Source type	: directory
Processing started.
Processing completed.
Number of errors encountered while extracting events: 2.
Use pinfo to inspect errors in more detail.
Thread 1 "python2.7" received signal SIGSEGV, Segmentation fault.
0x00007ffff335001a in grpc_closure_sched (error=0x0, c=0x7fffec213840) at ./src/core/lib/iomgr/closure.h:297
297	./src/core/lib/iomgr/closure.h: No such file or directory.
(gdb) py-bt
Traceback (most recent call first):
File "/home/turbinia/turbinia-dev2/local/lib/python2.7/site-packages/grpc/_channel.py", line 480, in _blocking
_handle_event(completion_queue.poll(), state,
File "/home/turbinia/turbinia-dev2/local/lib/python2.7/site-packages/grpc/_channel.py", line 486, in call
credentials)
File "/home/turbinia/turbinia-dev2/local/lib/python2.7/site-packages/google/gax/retry.py", line 68, in inner
return a_func(*updated_args, **kwargs)
File "/home/turbinia/turbinia-dev2/local/lib/python2.7/site-packages/google/gax/retry.py", line 121, in inner
return to_call(*args)
File "/home/turbinia/turbinia-dev2/local/lib/python2.7/site-packages/google/gax/api_callable.py", line 376, in inner
return a_func(*args, **kwargs)
File "/home/turbinia/turbinia-dev2/local/lib/python2.7/site-packages/google/gax/api_callable.py", line 438, in base_caller
return api_call(*args)
File "/home/turbinia/turbinia-dev2/local/lib/python2.7/site-packages/google/gax/api_callable.py", line 452, in inner
return api_caller(api_call, this_settings, request)
File "/home/turbinia/turbinia-dev2/local/lib/python2.7/site-packages/google/cloud/gapic/pubsub/v1/subscriber_client.py", line 706, in pull
return self._pull(request, options)
File "/home/turbinia/turbinia-dev2/local/lib/python2.7/site-packages/google/cloud/pubsub/_gax.py", line 440, in subscription_pull
return_immediately=return_immediately)
File "/home/turbinia/turbinia-dev2/local/lib/python2.7/site-packages/google/cloud/pubsub/subscription.py", line 367, in pull
self.full_name, return_immediately, max_messages)
File "/home/turbinia/turbinia-dev2/local/lib/python2.7/site-packages/psq/queue.py", line 104, in dequeue
return_immediately=not block, max_messages=max)
File "/home/turbinia/turbinia-dev2/local/lib/python2.7/site-packages/psq/worker.py", line 45, in inner
return self.queue.dequeue(max=self.tasks_per_poll, block=True)
File "/home/turbinia/turbinia-dev2/local/lib/python2.7/site-packages/retrying.py", line 200, in call
attempt = Attempt(fn(*args, **kwargs), attempt_number, False)
File "/home/turbinia/turbinia-dev2/local/lib/python2.7/site-packages/retrying.py", line 49, in wrapped_f
return Retrying(*dargs, **dkw).call(f, *args, **kw)
File "/home/turbinia/turbinia-dev2/local/lib/python2.7/site-packages/psq/worker.py", line 46, in _safe_dequeue
return inner()
File "/home/turbinia/turbinia-dev2/local/lib/python2.7/site-packages/psq/worker.py", line 53, in listen
tasks = self._safe_dequeue()
File "/home/turbinia/turbinia-dev2/local/lib/python2.7/site-packages/psq/worker.py", line 94, in listen
super(MultiprocessWorker, self).listen()
File "/home/turbinia/turbinia/turbiniactl", line 436, in
worker.listen()
$ gdb python
(gdb) run /home/turbinia/turbinia/turbiniactl -L /var/tmp/turbinia-psqworker.log -o /var/tmp/ psqworker 2>> /var/tmp/turbinia-psqworker.stdout.log
[Thread debugging using libthread_db enabled]
Using host libthread_db library "/lib/x86_64-linux-gnu/libthread_db.so.1".

[OPTIONAL]	missing: lzma.
[OK]
Source path	: /mnt/turbinia-mounts/turbinia0HXEJu
Source type	: directory
Processing started.
Processing completed.
Number of errors encountered while extracting events: 2.
Use pinfo to inspect errors in more detail.
Thread 1 "python" received signal SIGSEGV, Segmentation fault.
0x00007ffff335001d in grpc_closure_sched (error=0x0, c=0x7fffec16e940) at ./src/core/lib/iomgr/closure.h:297
297	./src/core/lib/iomgr/closure.h: No such file or directory.
(gdb) bt
#0  0x00007ffff335001d in grpc_closure_sched (error=0x0, c=0x7fffec16e940) at ./src/core/lib/iomgr/closure.h:297
#1  grpc_core::LockfreeEvent::SetReady (this=this@entry=0x7fffec002ac8) at src/core/lib/iomgr/lockfree_event.cc:236
#2  0x00007ffff3347ec4 in fd_become_readable (notifier=0x55555651a710, fd=0x7fffec002ac0) at src/core/lib/iomgr/ev_epoll1_linux.cc:385
#3  process_epoll_events (pollset=0x55555651a710) at src/core/lib/iomgr/ev_epoll1_linux.cc:618
#4  pollset_work (ps=0x55555651a710, worker_hdl=0x0, deadline=) at src/core/lib/iomgr/ev_epoll1_linux.cc:970
#5  0x00007ffff336f758 in cq_next (cq=0x55555651a640, deadline=..., reserved=) at src/core/lib/surface/completion_queue.cc:930
#6  0x00007ffff337090b in grpc_completion_queue_next (cq=, deadline=..., reserved=reserved@entry=0x0) at src/core/lib/surface/completion_queue.cc:1005
#7  0x00007ffff330bde1 in __pyx_pf_4grpc_7_cython_6cygrpc_15CompletionQueue_2poll (__pyx_v_deadline=, __pyx_v_self=0x7ffff00b4558)
at src/python/grpcio/grpc/_cython/cygrpc.c:13746
#8  __pyx_pw_4grpc_7_cython_6cygrpc_15CompletionQueue_3poll (__pyx_v_self=0x7ffff00b4558, __pyx_args=, __pyx_kwds=)
at src/python/grpcio/grpc/_cython/cygrpc.c:13607
#9  0x000055555564fb9a in call_function (oparg=, pp_stack=0x7fffffffb858) at ../Python/ceval.c:4352
#10 PyEval_EvalFrameEx () at ../Python/ceval.c:2989
#11 0x000055555565542f in fast_function (nk=, na=, n=, pp_stack=0x7fffffffb9a8, func=0x7ffff3028758) at ../Python/ceval.c:4437
#12 call_function (oparg=, pp_stack=0x7fffffffb9a8) at ../Python/ceval.c:4372
#13 PyEval_EvalFrameEx () at ../Python/ceval.c:2989
#14 0x000055555564dd45 in PyEval_EvalCodeEx () at ../Python/ceval.c:3584
#15 0x000055555566ac38 in function_call.lto_priv () at ../Objects/funcobject.c:523
#16 0x000055555563c413 in PyObject_Call () at ../Objects/abstract.c:2547
#17 0x000055555568135e in instancemethod_call.lto_priv () at ../Objects/classobject.c:2602
#18 0x000055555563c413 in PyObject_Call () at ../Objects/abstract.c:2547
#19 0x00005555556df937 in slot_tp_call.lto_priv () at ../Objects/typeobject.c:5546
#20 0x000055555563c413 in PyObject_Call () at ../Objects/abstract.c:2547
#21 0x0000555555656998 in ext_do_call (nk=0, na=0, flags=, pp_stack=0x7fffffffbf30, func=0x7ffff005df50) at ../Python/ceval.c:4666
#22 PyEval_EvalFrameEx () at ../Python/ceval.c:3028
#23 0x000055555564dd45 in PyEval_EvalCodeEx () at ../Python/ceval.c:3584
#24 0x000055555566aa7e in function_call.lto_priv () at ../Objects/funcobject.c:523
#25 0x000055555563c413 in PyObject_Call () at ../Objects/abstract.c:2547
#26 0x0000555555656998 in ext_do_call (nk=0, na=0, flags=, pp_stack=0x7fffffffc1e0, func=0x7ffff0066aa0) at ../Python/ceval.c:4666
#27 PyEval_EvalFrameEx () at ../Python/ceval.c:3028
#28 0x000055555564dd45 in PyEval_EvalCodeEx () at ../Python/ceval.c:3584
#29 0x000055555566ac38 in function_call.lto_priv () at ../Objects/funcobject.c:523
#30 0x000055555563c413 in PyObject_Call () at ../Objects/abstract.c:2547
#31 0x0000555555656998 in ext_do_call (nk=0, na=0, flags=, pp_stack=0x7fffffffc490, func=0x7ffff00669b0) at ../Python/ceval.c:4666
#32 PyEval_EvalFrameEx () at ../Python/ceval.c:3028
#33 0x000055555564dd45 in PyEval_EvalCodeEx () at ../Python/ceval.c:3584
#34 0x000055555566aa7e in function_call.lto_priv () at ../Objects/funcobject.c:523
#35 0x000055555563c413 in PyObject_Call () at ../Objects/abstract.c:2547
#36 0x0000555555656998 in ext_do_call (nk=0, na=0, flags=, pp_stack=0x7fffffffc740, func=0x7ffff0066a28) at ../Python/ceval.c:4666
#37 PyEval_EvalFrameEx () at ../Python/ceval.c:3028
#38 0x000055555564dd45 in PyEval_EvalCodeEx () at ../Python/ceval.c:3584
#39 0x0000555555655f15 in fast_function (nk=0, na=, n=, pp_stack=0x7fffffffc948, func=0x7ffff0063e60) at ../Python/ceval.c:4447
#40 call_function (oparg=, pp_stack=0x7fffffffc948) at ../Python/ceval.c:4372
#41 PyEval_EvalFrameEx () at ../Python/ceval.c:2989
#42 0x000055555564dd45 in PyEval_EvalCodeEx () at ../Python/ceval.c:3584
#43 0x0000555555655738 in fast_function (nk=0, na=, n=, pp_stack=0x7fffffffcb58, func=0x7ffff0063ed8) at ../Python/ceval.c:4447
#44 call_function (oparg=, pp_stack=0x7fffffffcb58) at ../Python/ceval.c:4372
#45 PyEval_EvalFrameEx () at ../Python/ceval.c:2989
#46 0x000055555564dd45 in PyEval_EvalCodeEx () at ../Python/ceval.c:3584
#47 0x0000555555655738 in fast_function (nk=1, na=, n=, pp_stack=0x7fffffffcd68, func=0x7ffff2bdb9b0) at ../Python/ceval.c:4447
#48 call_function (oparg=, pp_stack=0x7fffffffcd68) at ../Python/ceval.c:4372
#49 PyEval_EvalFrameEx () at ../Python/ceval.c:2989
#50 0x000055555564dd45 in PyEval_EvalCodeEx () at ../Python/ceval.c:3584
#51 0x0000555555655738 in fast_function (nk=0, na=, n=, pp_stack=0x7fffffffcf78, func=0x7ffff2b757d0) at ../Python/ceval.c:4447
#52 call_function (oparg=, pp_stack=0x7fffffffcf78) at ../Python/ceval.c:4372
#53 PyEval_EvalFrameEx () at ../Python/ceval.c:2989
#54 0x000055555564dd45 in PyEval_EvalCodeEx () at ../Python/ceval.c:3584
#55 0x0000555555655738 in fast_function (nk=2, na=, n=, pp_stack=0x7fffffffd188, func=0x7ffff2fc4de8) at ../Python/ceval.c:4447
#56 call_function (oparg=, pp_stack=0x7fffffffd188) at ../Python/ceval.c:4372
#57 PyEval_EvalFrameEx () at ../Python/ceval.c:2989
#58 0x000055555564dd45 in PyEval_EvalCodeEx () at ../Python/ceval.c:3584
#59 0x0000555555655738 in fast_function (nk=2, na=, n=, pp_stack=0x7fffffffd398, func=0x7ffff2bbb6e0) at ../Python/ceval.c:4447
#60 call_function (oparg=, pp_stack=0x7fffffffd398) at ../Python/ceval.c:4372
#61 PyEval_EvalFrameEx () at ../Python/ceval.c:2989
#62 0x000055555564dd45 in PyEval_EvalCodeEx () at ../Python/ceval.c:3584
#63 0x000055555566ac38 in function_call.lto_priv () at ../Objects/funcobject.c:523
#64 0x000055555563c413 in PyObject_Call () at ../Objects/abstract.c:2547
#65 0x0000555555656998 in ext_do_call (nk=0, na=0, flags=, pp_stack=0x7fffffffd650, func=0x7ffff0049b90) at ../Python/ceval.c:4666
#66 PyEval_EvalFrameEx () at ../Python/ceval.c:3028
#67 0x000055555564dd45 in PyEval_EvalCodeEx () at ../Python/ceval.c:3584
#68 0x000055555566ac38 in function_call.lto_priv () at ../Objects/funcobject.c:523
#69 0x000055555563c413 in PyObject_Call () at ../Objects/abstract.c:2547
#70 0x0000555555656998 in ext_do_call (nk=0, na=2, flags=, pp_stack=0x7fffffffd900, func=0x7ffff26120c8) at ../Python/ceval.c:4666
#71 PyEval_EvalFrameEx () at ../Python/ceval.c:3028
#72 0x000055555564dd45 in PyEval_EvalCodeEx () at ../Python/ceval.c:3584
#73 0x0000555555655f15 in fast_function (nk=0, na=, n=, pp_stack=0x7fffffffdb08, func=0x7ffff0049e60) at ../Python/ceval.c:4447
#74 call_function (oparg=, pp_stack=0x7fffffffdb08) at ../Python/ceval.c:4372
#75 PyEval_EvalFrameEx () at ../Python/ceval.c:2989
#76 0x000055555564dd45 in PyEval_EvalCodeEx () at ../Python/ceval.c:3584
#77 0x0000555555655f15 in fast_function (nk=0, na=, n=, pp_stack=0x7fffffffdd18, func=0x7ffff2612410) at ../Python/ceval.c:4447
#78 call_function (oparg=, pp_stack=0x7fffffffdd18) at ../Python/ceval.c:4372
#79 PyEval_EvalFrameEx () at ../Python/ceval.c:2989
#80 0x000055555564dd45 in PyEval_EvalCodeEx () at ../Python/ceval.c:3584
#81 0x0000555555655f15 in fast_function (nk=0, na=, n=, pp_stack=0x7fffffffdf28, func=0x7ffff2612488) at ../Python/ceval.c:4447
#82 call_function (oparg=, pp_stack=0x7fffffffdf28) at ../Python/ceval.c:4372
#83 PyEval_EvalFrameEx () at ../Python/ceval.c:2989
#84 0x000055555564dd45 in PyEval_EvalCodeEx () at ../Python/ceval.c:3584
#85 0x0000555555655f15 in fast_function (nk=0, na=, n=, pp_stack=0x7fffffffe138, func=0x7ffff26125f0) at ../Python/ceval.c:4447
#86 call_function (oparg=, pp_stack=0x7fffffffe138) at ../Python/ceval.c:4372
#87 PyEval_EvalFrameEx () at ../Python/ceval.c:2989
#88 0x000055555564dd45 in PyEval_EvalCodeEx () at ../Python/ceval.c:3584
#89 0x000055555564db09 in PyEval_EvalCode (co=, globals=, locals=) at ../Python/ceval.c:669
#90 0x000055555567e14f in run_mod.lto_priv () at ../Python/pythonrun.c:1376
#91 0x0000555555678fc2 in PyRun_FileExFlags () at ../Python/pythonrun.c:1362
#92 0x0000555555678b0e in PyRun_SimpleFileExFlags () at ../Python/pythonrun.c:948
#93 0x0000555555629aa1 in Py_Main () at ../Modules/main.c:640
#94 0x00007ffff6f182e1 in __libc_start_main (main=0x5555556293d0 , argc=7, argv=0x7fffffffe578, init=, fini=, rtld_fini=,
stack_end=0x7fffffffe568) at ../csu/libc-start.c:291
#95 0x00005555556292ca in _start ()
Anything else we should know about your project / environment?

/cc @aarontp

gRPC doesn't support fork as such. Can you give more details about how the worker is forking? Does it have an ongoing pubsub stream when it forks?
Can you dump c when it segfaults at c->scheduler->vtable->sched(c, error) ?

Forking is done by using this function psq.MultiprocessWorker(...). This should have a pubsub stream when it forks.
$ ps auxf
turbinia 30197  4.3  2.8<PHONE_NUMBER>32 pts/3   S    20:52   0:01  |                   _ gdb turbinia-dev2/bin/python2.7
turbinia 30211  5.4  1.7<PHONE_NUMBER>4 pts/3    Sl+  20:52   0:00  |                       _ /home/turbinia/turbinia-dev2/bin/python2.7 /home/turbinia/turbinia/turbiniactl -L /var/tmp/turbinia-psqworker.log -o /var/tmp/ psqworker
turbinia 30227  0.0  1.3<PHONE_NUMBER>2 pts/3    Sl+  20:53   0:00  |                           _ /home/turbinia/turbinia-dev2/bin/python2.7 /home/turbinia/turbinia/turbiniactl -L /var/tmp/turbinia-psqworker.log -o /var/tmp/ psqworker
Thread 1 "python2.7" received signal SIGSEGV, Segmentation fault.
0x00007ffff335001a in grpc_closure_sched (error=0x0, c=0x7fffec21e580) at ./src/core/lib/iomgr/closure.h:297
297	./src/core/lib/iomgr/closure.h: No such file or directory.
1: c = (grpc_closure *) 0x7fffec21e580
(gdb)
(gdb)
(gdb)
(gdb) print c
$14 = (grpc_closure *) 0x7fffec21e580

Thread 1 "python2.7" received signal SIGSEGV, Segmentation fault.
0x00007ffff335001a in grpc_closure_sched (error=0x0, c=0x7fffec3daf10) at ./src/core/lib/iomgr/closure.h:297
297     ./src/core/lib/iomgr/closure.h: No such file or directory.
(gdb)
(gdb)
(gdb)
(gdb)
(gdb)
(gdb) print *c
$1 = {next_data = {next = 0x0, atm_next = {next = 0}, scratch = 0}, cb = 0x45, cb_arg = 0x7fffec3dc710, scheduler = 0x0,
error_data = {error = 0x0, scratch = 0}}

I re-ran and got a different result:
Thread 1 "python2.7" received signal SIGSEGV, Segmentation fault.
0x00007ffff335001d in grpc_closure_sched (error=0x0, c=0x7fffec000188) at ./src/core/lib/iomgr/closure.h:297
297     ./src/core/lib/iomgr/closure.h: No such file or directory.
(gdb) print *c
$1 = {next_data = {next = 0x7fffec000178, atm_next = {next =<PHONE_NUMBER>11384}, scratch =<PHONE_NUMBER>11384}, cb = 0x7fffec000178,
cb_arg = 0x7fffec225da0, scheduler = 0x7fffec225da0, error_data = {error = 0x7fffec000198, scratch =<PHONE_NUMBER>11416}}

In the first segfault, c->scheduler was null. Can you please also print *(c->scheduler) and *(c->scheduler->vtable). The conclusion is going to be same. Since fork() is not supported, the gRPC runtime is in weird state in the forked process.

Thread 1 "python2.7" received signal SIGSEGV, Segmentation fault.
0x00007ffff335001d in grpc_closure_sched (error=0x0, c=0x7fffec16e710) at ./src/core/lib/iomgr/closure.h:297
297     ./src/core/lib/iomgr/closure.h: No such file or directory.
(gdb) print *c
$1 = {next_data = {next = 0x0, atm_next = {next = 0}, scratch = 0}, cb = 0x121, cb_arg = 0x7fffec225da0,
scheduler = 0x7fffec18d650, error_data = {error = 0x0, scratch = 0}}
(gdb) print *(c->scheduler)
$2 = {vtable = 0x0}
(gdb) print *(c->scheduler->vtable)
Cannot access memory at address 0x0

I have come to know that the newer version of PSQ is not using multiprocessing. You could upgrade or you could use --single-threaded option to get around this crash.

Keeping this issue open as there are plans to support client-side fork in future. Timeline is not yet clear.

I'm going to mark this issue closed, as #15334 now tracks our plans for client-side fork.
But just to add a bit more detail on this particular failure case: I was able to reproduce this failure. The child process (the PSQ worker) was itself creating a gRPC channel to communicate with Datastore. This was triggering a segfault due to a bug since fixed by https://github.com/grpc/grpc/pull/14448 - the Python backup poller thread no longer existed in the child, and attempting to add it as a watcher for a newly created channel led to an inconsistent library state.
This particular use case may have worked just fine with fork() after the fix in #14448, but there are still other sources of shared state across fork() that may cause additional problems: more robust support for fork() is now tracked in #15334.


pretrain dataset?

Thanks for the great work, what dataset did you use for the pretrain weights?
Is it possible to provide the weights for the kinetics dataset?

The weights are the same as the pre-trained models on Tensorflow (on kinetics), released by the authors.
I will update the readme to make it more clear and provide some tests that verify that the two networks are equivalent.

Thank you very much for your time.


readme updates for migration website

additional doc updates removing awestruct references and updating the docker image reference

Perfect, exactly what I needed right now :) Thanks, @mdrillin!

@gunnarmorling sure - @uidoyen may have some additional pending updates, not sure.  Taking PTO this afternoon - I will check with them Monday

No worries, i'll leave https://github.com/debezium/debezium.github.io/issues/559 open then for the time being. Have a nice afternoon off!


translateSourcepaths to relative paths + refactor

J2objConfig changes:

translateSourcepaths to List
Refactor translateSourcepaths, translateClasspaths & generatedSourceDirs
SourcePath => sourcepath, ClassPath => classpath

Task changes:

Remove @Optional from List @Inputs (always defined)
Reorder @Inputs for consistency
Remove advanced CycleFinder setup instructions

Rename:

Utils.srcDirs => srcSet, indicates a set of files
Utils.sourcepathJava => srcDirsJava, indicates dirs only

Testing:

Added testJ2objcHome
Added testSrcSet
Added testSrcDirsJava

@advayDev1, @confile - this commit currently breaks the plugin. Nonetheless, I'm sharing an early version, so I get your preliminary feedback. Ultimately, I would like to share as much between the CycleFinder and Translation tasks as possible.
I'm also going to look at mocking project.exec {...}. I'm not sure how to do that yet, so let me know if you have any good ideas for that.

i take it this is intentionally being delayed past 0.3?

see my comment then LGTM

Can you please point out the functional changes only?  The refactors generally look good, but it would be great to split the pure refactors from the changes that affect what the plugin does into two separate PRs.  AFAICT there are some changes regarding the source files vs. directories vs. trees but they are hard to find.  Can we make this a pure refactor only?

Please review #262 first. The second commit within this PR is more constrained. I could separate out some of the changes in J2objcConfig but it's hard to do much more of that. Hopefully looking at the 2nd commit is separated enough.

Fixes #229

I will PTAL this once all your other PRs are in and this is rebased.

Sure thing Advay. I will follow up on this and the others on Monday.
On Fri, Jul 10, 2015, 1:37 PM Advay Mengle<EMAIL_ADDRESS>wrote:

I will PTAL this once all your other PRs are in and this is rebased.
—
Reply to this email directly or view it on GitHub
https://github.com/j2objc-contrib/j2objc-gradle/pull/234#issuecomment-120515814
.

@advayDev1 - PTAL again for this. It's not quite a perfect refactor but pretty close. Some points I'd like to highlight for you:

I've removed the sourcepathJava method and inlined calls to .getSrcDirs(). I was very confused by this before and I think it helps to make it more explicit. So for two extra lines of code, you get to remove a method and it's test code.
What does it mean to add this to the classpathArgs: :${project.buildDir}/classes? Note that I'm also adding this to CycleFinderTask when it wasn't present there before. I want to add a comment better explaining its' purpose.
I'd like to refactor out common code between CycleFinderTask and TranslateTask in a future PR. I'm undecided between a common base class or util methods. I'm interested in your thoughts on this.

Responses:

Yep SGTM, looks much more readable.
No idea why we add /build/classes.  I assume it has something to do with autogenerated code where the final class file is present there but no source exists.  Have you tried translation without that argument?  I suspect in the normal case it isn't needed.  @confile - thoughts?
I think we should go inheritance or composition, but not utility methods.  The long Utils class is one of the less readable parts of our codebase.

I'll try inheritance. Merging now...


Plugin won't load, null reference.

here's the activity log. My guess is a file in the list was deleted or something.

592
2017/08/16 16:58:45.488
Error
VisualStudio
    LegacySitePackage failed for package [WorkingFilesWindowPackage]Source: 'WorkingFilesList.ToolWindow' Description: Object reference not set to an instance of an object.
System.NullReferenceException: Object reference not set to an instance of an object.
   at WorkingFilesList.ToolWindow.ViewModel.DocumentMetadataManager.Synchronize(Documents documents, Boolean setUsageOrder)
   at WorkingFilesList.WorkingFilesWindowPackage.InitializeServices(IKernel kernel, IOptionsPageService optionsPageService) in F:\Visual Studio Projects\WorkingFilesList\Solution\WorkingFilesList\WorkingFilesWindowPackage.cs:line 124
   at WorkingFilesList.WorkingFilesWindowPackage.Initialize() in F:\Visual Studio Projects\WorkingFilesList\Solution\WorkingFilesList\WorkingFilesWindowPackage.cs:line 100
   at Microsoft.VisualStudio.Shell.Package.Microsoft.VisualStudio.Shell.Interop.IVsPackage.SetSite(IServiceProvider sp)
{26BF5782-13D2-4168-B979-BFCDE9BD63DD}
80004003 - E_POINTER

593
2017/08/16 16:58:45.489
Error
VisualStudio
    SetSite failed for package [WorkingFilesWindowPackage](null)
{26BF5782-13D2-4168-B979-BFCDE9BD63DD}
80004003 - E_POINTER

594
2017/08/16 16:58:45.491
Error
VisualStudio
    End package load [WorkingFilesWindowPackage]
{26BF5782-13D2-4168-B979-BFCDE9BD63DD}
80004003 - E_POINTER

Hi
When the plugin loads, it tries to get a list of all open documents to populate the tool window; it does this by trying to getting an instance of the Visual Studio automation model, and querying its Documents.
From looking at the stack trace provided, the error could possibly be caused by being unable to get an instance of the automation model for some reason. Is this the first time that you've tried running the plugin, or was it running ok previously?
If the latter, is it possible that a recent update of Visual Studio/another plugin modified something: maybe you could try uninstalling Working Files List and re-installing it?
If this is the first time that you've tried to use Working Files List, which version of Visual Studio are you running, and is it the latest Update version?

It's been 14 days since this was raised, and no further details have been provided. I'm going to assume that this is no longer a problem; closing issue.


Supported font formats

Which font formats does hover support?
.otf and .ttf works for me, while .woff and .woff2 causes runtime crash:
[ERROR:flutter/third_party/txt/src/minikin/FontFamily.cpp(184)] Could not get cmap table size!
[FATAL:flutter/third_party/txt/src/minikin/FontCollection.cpp(95)] nTypefaces == 0
hover: App 'test_woff' exited with error: exit status<PHONE_NUMBER>

Full run log
C:\Users\Pavel\AndroidStudioProjects\test_woff>hover run
hover: Building flutter bundle
hover: Using engine from cache
hover: Compiling 'go-flutter' and plugins
hover: Successfully compiled executable binary for windows
hover: Build finished, starting app...
hover: Running test_woff in debug mode
go-flutter: calculated pixelRatio limited to a minimum of 1.0. metrics: {"dpi":96.18934911242603,"monitorWidthMm":338,"monitorWidthSc":1280,"mscpi":96.18934911242603,"pixelRatio":0.6011834319526627,"ppsc":1,"windowWidthPx":1000,"windowWidthSc":1000}
flutter: Observatory listening on http://<IP_ADDRESS>:50300/
hover: Connecting hover to 'test_woff' for hot reload
[ERROR:flutter/third_party/txt/src/minikin/FontFamily.cpp(184)] Could not get cmap table size!

[FATAL:flutter/third_party/txt/src/minikin/FontCollection.cpp(95)] nTypefaces == 0
hover: App 'test_woff' exited with error: exit status<PHONE_NUMBER>

Hover doctor
C:\Users\Pavel\AndroidStudioProjects\test_woff>hover doctor
hover: Hover version v0.42.0 running on windows
hover: Sharing flutter version
Flutter 1.18.0-11.1.pre • channel beta • https://github.com/flutter/flutter.git
Framework • revision 2738a1148b (3 weeks ago) • 2020-05-13 15:24:36 -0700
Engine • revision ef9215ceb2
Tools • Dart 2.9.0 (build 2.9.0-8.2.beta)
hover: Flutter engine commit: https://github.com/flutter/engine/commit/ef9215ceb2884ddf520d321bcd822d1461330876
hover: Finding out the C compiler version
gcc (tdm64-1) 9.2.0
Copyright (C) 2019 Free Software Foundation, Inc.
This is free software; see the source for copying conditions.  There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

hover: Sharing the content of go.mod
module test_woff/go

go 1.14

require (
        github.com/go-flutter-desktop/go-flutter v0.41.0
        github.com/pkg/errors v0.9.1
)
hover: Sharing the content of hover.yaml
application-name: ""
executable-name: ""
package-name: ""
license: ""
target: lib/main_desktop.dart
branch: ""
cache-path: ""
opengl: ""
engine-version: ""
hover: Sharing the content of go/cmd
go\cmd\main.go  go\cmd\options.go

Does this work with googles desktop embedding? I think it's a flutter issue, not a go-flutter issue.

This is indeed a flutter issue: https://github.com/flutter/flutter/issues/13823

@pchampio woff and woff2 fonts are working in Flutter itself, e.g. in Android

@PiN73 Please read this comment from the issue linked above!!
In summary:

The woff decoder is 100k of code. This code isn't shipped with Flutter.
If the platform supports (e.g. Android) woff, then flutter can the platform decoder (e.g. the android woff decoder) to parse woff font.
If the platform doesn't support woff, then it fails.

The issue you are having is from the engine, not go-flutter.
If you want more information on that subject:

Flutter renders text using a combination of Skia, Harfbuzz, Minikin, and ICU using a library called LibTxt. https://github.com/flutter/engine/tree/master/third_party/txt

You see, there is nothing we can do at the go-flutter level. We only provide an embedder. Font is simply not handled at our level.


feat: Implement Kubernetes Gateway API

Please describe the Improvement and/or Feature Request

Scope (please mark with X where applicable)

New Functionality              [x]
Install                        [ ]
Gateway API - GatewayClass     [x]
Gateway API - Gateway          [x]
Gateway API - HTTPRoute        [x]
Gateway API - TLSRoute         [ ]
Gateway API - TCPRoute         [ ]
Gateway API - UDPRoute         [ ]
Gateway API - PolicyReference  [ ]
Ingress                        [x]
Egress                         [ ]
MultiCluster                   [ ]
PIPY Control Plane             [ ]
PIPY Script/Config             [ ]
CLI Tool                       [ ]
Metrics                        [ ]
Certificate Management         [ ]
Sidecar Injection              [ ]
Logging                        [ ]
Debugging                      [ ]
Tests                          [ ]
Demo                           [ ]
CI System                      [ ]
Project Release                [ ]

Possible use cases

Implement Kubernetes Gateway API, should cover  at least GatewayClass, Gateway and HTTPRoute

Should support rate-limiting, #140

GatewayAPI v0.6.0 was announced:
https://github.com/kubernetes-sigs/gateway-api/discussions/1615

@reaver-flomesh  The gateway API can work with fsm today?


Fix onDestroy directive

Fix #23

Coverage increased (+0.07%) to 95.902% when pulling 91825a5754d69a83804544f974f67e51cb97b4b4 on fix-ondestroy-directive into 281727d867e055aea99ce9740ab887622f23111d on master.


Higher Order Meshing Results (Example 2)

Hi there, I am completing a 2D convergence study for example 2 and am using 3 sample meshes; coarse (45 elements), medium (1002 elements)  fine (1724 elements).  I have created the mesh in Gmsh and have therefore commented out (//) section 4 of ex2.cpp.  I am trying each mesh with increasing order from 1-5 and have encountered a problem for the finer meshes at a high order.
When testing the medium mesh, order 1-4 showed converging results (ideal answer is 0.375) and order 5 was showing this:

Why is this answer so small?
Is the mesh too fine for the higher order equations?
When testing the fine mesh I could only get accurate results for order 1-3.
I can send in the .msh files or the ex2.cpp files if needed.
Any help would be great. Thanks!

Did the linear solve converge for the larger problems?
The serial version, ex2.cpp does only 500 iterations with diagonal preconditioner. Try using the parallel version, ex2p.cpp (even on 1 MPI rank) which has much more robust AMG preconditioner.

Here are my results for the max deflection. The ideal value is 0.375. I used 3 meshes; coarse, medium and fine and used 5 orders to get results for the convergence study. For mesh 1 (coarse mesh, t1.msh) the answers converge with increasing order.  For mesh 2 (medium) the first four orders get very close to the answer but then the deflection becomes 0.04456 for order 5. The first 3 orders for the fine mesh are converging then order 4 and 5 are very small.

I tried running the parallel version, ex2p.cpp and this error report came up when I tried to make ./ex2p:

I think it is very likely that the high-resolution serial results are not converged. You can increase the number of PCG iterations (from the default 500) to check that.
For the parallel version you need to rebuild mfem with make parallel, see https://mfem.org/building/#parallel-mpi-version-of-mfem


removed JDNSSEC from Traffic Router

What does this PR do?
Removes JDNSSEC-tools from the Traffic Router build process. It also updates documentation regarding tests for Traffic Router
Which TC components are affected by this PR?

[ ] Documentation
[ ] Grove
[ ] Traffic Analytics
[ ] Traffic Monitor
[ ] Traffic Ops
[ ] Traffic Ops ORT
[ ] Traffic Portal
[x] Traffic Router
[ ] Traffic Stats
[ ] Traffic Vault
[ ] Other _________

What is the best way to verify this PR?
Build and test Traffic Router - probably run unit testing suite.
Check all that apply

[ ] This PR includes tests
[x] This PR includes documentation updates
[ ] This PR includes an update to CHANGELOG.md
[ ] This PR includes all required license headers
[ ] This PR includes a database migration (ensure that migration sequence is correct)
[ ] This PR fixes a serious security flaw. Read more: www.apache.org/security

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/trafficcontrol-PR/2835/
Test PASSed.


139 clear cache

Fixes #139
The last test is the important one, the rest of the test changes are just bringing search tests in line with the code style for case / method / organization tests using async / await.
Clears the cache when we add a new "thing".

Aside from accidentally checking in swagger noise.


KeyError: 'base_model.model.model.layers.0.self_attn.qkv_proj.lora_A.weight'

When I try to inference my finetuned code llama model using vllm, getting this error
 File "/usr/local/lib/python3.9/dist-packages/vllm/engine/ray_utils.py", line 32, in execute_method     return executor(*args, **kwargs)   File "/usr/local/lib/python3.9/dist-packages/vllm/worker/worker.py", line 70, in init_model     self.model = get_model(self.model_config)   File "/usr/local/lib/python3.9/dist-packages/vllm/model_executor/model_loader.py", line 103, in get_model     model.load_weights(model_config.model, model_config.download_dir,   File "/usr/local/lib/python3.9/dist-packages/vllm/model_executor/models/llama.py", line 367, in load_weights     param = state_dict[name.replace(weight_name, "qkv_proj")] KeyError: 'base_model.model.model.layers.0.self_attn.qkv_proj.lora_A.weight'

Some Shape Of my models
`

model.layers.0.input_layernorm.weight
[4096]
BF16

model.layers.0.mlp.down_proj.weight
[4096,11008]
BF16

model.layers.0.mlp.gate_proj.weight
[11008,4096]
BF16

model.layers.0.mlp.up_proj.weight
[11008,4096]
BF16

model.layers.0.post_attention_layernorm.weight
[4096]
BF16

model.layers.0.self_attn.k_proj.weight
[4096,4096]
BF16

model.layers.0.self_attn.o_proj.weight
[4096,4096]
BF16

model.layers.0.self_attn.q_proj.weight
[4096,4096]
BF16

model.layers.0.self_attn.v_proj.weight
[4096,4096]
BF16

`
Any Suggestion or help is highly appreciated.

Currently vLLM does not support merging LoRA weights. Hence the model loader is erroring. Contribution strongly welcomed here! Ideally you can apply the LoRA weights automatically on the model loading process. I believe this PR does what you want: https://github.com/vllm-project/vllm/pull/289
I'm closing this PR in favor of #182

Also facing this problem!
  File "/usr4/ec523/brucejia/.local/lib/python3.8/site-packages/vllm/entrypoints/llm.py", line 93, in __init__
    self.llm_engine = LLMEngine.from_engine_args(engine_args)
  File "/usr4/ec523/brucejia/.local/lib/python3.8/site-packages/vllm/engine/llm_engine.py", line 231, in from_engine_args
    engine = cls(*engine_configs,
  File "/usr4/ec523/brucejia/.local/lib/python3.8/site-packages/vllm/engine/llm_engine.py", line 110, in __init__
    self._init_workers(distributed_init_method)
  File "/usr4/ec523/brucejia/.local/lib/python3.8/site-packages/vllm/engine/llm_engine.py", line 142, in _init_workers
    self._run_workers(
  File "/usr4/ec523/brucejia/.local/lib/python3.8/site-packages/vllm/engine/llm_engine.py", line 700, in _run_workers
    output = executor(*args, **kwargs)
  File "/usr4/ec523/brucejia/.local/lib/python3.8/site-packages/vllm/worker/worker.py", line 70, in init_model
    self.model = get_model(self.model_config)
  File "/usr4/ec523/brucejia/.local/lib/python3.8/site-packages/vllm/model_executor/model_loader.py", line 98, in get_model
    model.load_weights(model_config.model, model_config.download_dir,
  File "/usr4/ec523/brucejia/.local/lib/python3.8/site-packages/vllm/model_executor/models/llama.py", line 322, in load_weights
    param = params_dict[name.replace(weight_name, param_name)]
KeyError: 'model.layers.0.self_attn.qkv_proj.base_layer.weight'

@SuperBruceJia , did you found any other methods to tackle this error ?

@SuperBruceJia , did you found any other methods to tackle this error ?

Yes!
git clone --branch support_peft https://github.com/SuperBruceJia/vllm.git
cd vllm
pip install -e . --user

Then,
import gc

from vllm import LLM, SamplingParams
from vllm.model_executor.adapters import lora
from vllm.model_executor.parallel_utils.parallel_state import destroy_model_parallel

# Load the model
save_dir = "YOUR_PATH"
llm = LLM(model=model_name, download_dir=save_dir_llm, tensor_parallel_size=num_gpus, gpu_memory_utilization=0.70)
lora.LoRAModel.from_pretrained(llm.llm_engine.workers[0].model, save_dir)

# Delete the llm object and free the memory
destroy_model_parallel()
del llm
gc.collect()
torch.cuda.empty_cache()
torch.distributed.destroy_process_group()
print("Successfully delete the llm pipeline and free the GPU memory!")

If you use some models that need Hugging Face login:
from huggingface_hub import login

login(token="YOUR_HUGGING_FACE_TOKEN")

While setting the dependencies by pip install -e . --user , getting error `  error: subprocess-exited-with-error
× Building editable for vllm (pyproject.toml) did not run successfully.
│ exit code: 1
╰─> [125 lines of output]
/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/torch/nn/modules/transformer.py:20: UserWarning: Failed to initialize NumPy: No module named 'numpy' (Triggered internally at ../torch/csrc/utils/tensor_numpy.cpp:84.)
device: torch.device = torch.device(torch._C._get_default_device()),  # torch.device('cpu'),
running editable_wheel
creating /var/tmp/pip-wheel-eybkk3v0/.tmp-9hphfyi9/vllm.egg-info
writing /var/tmp/pip-wheel-eybkk3v0/.tmp-9hphfyi9/vllm.egg-info/PKG-INFO
writing dependency_links to /var/tmp/pip-wheel-eybkk3v0/.tmp-9hphfyi9/vllm.egg-info/dependency_links.txt
writing requirements to /var/tmp/pip-wheel-eybkk3v0/.tmp-9hphfyi9/vllm.egg-info/requires.txt
writing top-level names to /var/tmp/pip-wheel-eybkk3v0/.tmp-9hphfyi9/vllm.egg-info/top_level.txt
writing manifest file '/var/tmp/pip-wheel-eybkk3v0/.tmp-9hphfyi9/vllm.egg-info/SOURCES.txt'
reading manifest file '/var/tmp/pip-wheel-eybkk3v0/.tmp-9hphfyi9/vllm.egg-info/SOURCES.txt'
reading manifest template 'MANIFEST.in'
adding license file 'LICENSE'
writing manifest file '/var/tmp/pip-wheel-eybkk3v0/.tmp-9hphfyi9/vllm.egg-info/SOURCES.txt'
creating '/var/tmp/pip-wheel-eybkk3v0/.tmp-9hphfyi9/vllm-0.1.2.dist-info'
creating /var/tmp/pip-wheel-eybkk3v0/.tmp-9hphfyi9/vllm-0.1.2.dist-info/WHEEL
running build_py
running build_ext
Traceback (most recent call last):
File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/command/editable_wheel.py", line 156, in run
self._create_wheel_file(bdist_wheel)
File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/command/editable_wheel.py", line 345, in _create_wheel_file
files, mapping = self._run_build_commands(dist_name, unpacked, lib, tmp)
File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/command/editable_wheel.py", line 268, in _run_build_commands
self._run_build_subcommands()
File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/command/editable_wheel.py", line 295, in _run_build_subcommands
self.run_command(name)
File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/_distutils/cmd.py", line 318, in run_command
self.distribution.run_command(command)
File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/dist.py", line 963, in run_command
super().run_command(command)
File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 988, in run_command
cmd_obj.run()
File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/command/build_ext.py", line 88, in run
_build_ext.run(self)
File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/_distutils/command/build_ext.py", line 345, in run
self.build_extensions()
File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/torch/utils/cpp_extension.py", line 525, in build_extensions
_check_cuda_version(compiler_name, compiler_version)
File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/torch/utils/cpp_extension.py", line 413, in _check_cuda_version
raise RuntimeError(CUDA_MISMATCH_MESSAGE.format(cuda_str_version, torch.version.cuda))
RuntimeError:
The detected CUDA version (11.8) mismatches the version that was used to compile
PyTorch (12.1). Please make sure to use the same CUDA versions.
  /var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/_distutils/dist.py:988: _DebuggingTips: Problem in editable installation.
  !!

          ********************************************************************************
          An error happened while installing `vllm` in editable mode.

          The following steps are recommended to help debug this problem:

          - Try to install the project normally, without using the editable mode.
            Does the error still persist?
            (If it does, try fixing the problem before attempting the editable mode).
          - If you are using binary extensions, make sure you have all OS-level
            dependencies installed (e.g. compilers, toolchains, binary libraries, ...).
          - Try the latest version of setuptools (maybe the error was already fixed).
          - If you (or your project dependencies) are using any setuptools extension
            or customization, make sure they support the editable mode.

          After following the steps above, if the problem still persists and
          you think this is related to how setuptools handles editable installations,
          please submit a reproducible example
          (see https://stackoverflow.com/help/minimal-reproducible-example) to:

              https://github.com/pypa/setuptools/issues

          See https://setuptools.pypa.io/en/latest/userguide/development_mode.html for details.
          ********************************************************************************

  !!
    cmd_obj.run()
  Traceback (most recent call last):
    File "/opt/conda/lib/python3.10/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 353, in <module>
      main()
    File "/opt/conda/lib/python3.10/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 335, in main
      json_out['return_val'] = hook(**hook_input['kwargs'])
    File "/opt/conda/lib/python3.10/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py", line 273, in build_editable
      return hook(wheel_directory, config_settings, metadata_directory)
    File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/build_meta.py", line 436, in build_editable
      return self._build_with_temp_dir(
    File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/build_meta.py", line 389, in _build_with_temp_dir
      self.run_setup()
    File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/build_meta.py", line 311, in run_setup
      exec(code, locals())
    File "<string>", line 145, in <module>
    File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/__init__.py", line 103, in setup
      return distutils.core.setup(**attrs)
    File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/_distutils/core.py", line 185, in setup
      return run_commands(dist)
    File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/_distutils/core.py", line 201, in run_commands
      dist.run_commands()
    File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 969, in run_commands
      self.run_command(cmd)
    File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/dist.py", line 963, in run_command
      super().run_command(command)
    File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 988, in run_command
      cmd_obj.run()
    File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/command/editable_wheel.py", line 156, in run
      self._create_wheel_file(bdist_wheel)
    File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/command/editable_wheel.py", line 345, in _create_wheel_file
      files, mapping = self._run_build_commands(dist_name, unpacked, lib, tmp)
    File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/command/editable_wheel.py", line 268, in _run_build_commands
      self._run_build_subcommands()
    File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/command/editable_wheel.py", line 295, in _run_build_subcommands
      self.run_command(name)
    File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/_distutils/cmd.py", line 318, in run_command
      self.distribution.run_command(command)
    File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/dist.py", line 963, in run_command
      super().run_command(command)
    File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/_distutils/dist.py", line 988, in run_command
      cmd_obj.run()
    File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/command/build_ext.py", line 88, in run
      _build_ext.run(self)
    File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/setuptools/_distutils/command/build_ext.py", line 345, in run
      self.build_extensions()
    File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/torch/utils/cpp_extension.py", line 525, in build_extensions
      _check_cuda_version(compiler_name, compiler_version)
    File "/var/tmp/pip-build-env-xc4n5tmk/overlay/lib/python3.10/site-packages/torch/utils/cpp_extension.py", line 413, in _check_cuda_version
      raise RuntimeError(CUDA_MISMATCH_MESSAGE.format(cuda_str_version, torch.version.cuda))
  RuntimeError:
  The detected CUDA version (11.8) mismatches the version that was used to compile
  PyTorch (12.1). Please make sure to use the same CUDA versions.

  [end of output]

note: This error originates from a subprocess, and is likely not a problem with pip.
ERROR: Failed building editable for vllm
Failed to build vllm
ERROR: Could not build wheels for vllm, which is required to install pyproject.toml-based projects` .
Similar error can be found here .
@SuperBruceJia , I want to use vllm for inferencing by fine-tuned Codellama base model .
Below is the code to inference Codellama
`from transformers import AutoTokenizer
import transformers
import torch
tokenizer = AutoTokenizer.from_pretrained("codellama/CodeLlama-7b-hf")
pipeline = transformers.pipeline(
"text-generation",
model="codellama/CodeLlama-7b-hf",
torch_dtype=torch.float16,
device_map="auto",
)
sequences = pipeline(
'def fibonacci(',
do_sample=True,
temperature=0.2,
top_p=0.9,
num_return_sequences=1,
eos_token_id=tokenizer.eos_token_id,
max_length=100,
)
for seq in sequences:
print(f"Result: {seq['generated_text']}")`.
Could you  tell me how use vllm to infer Codellama . Your proposed solution is giving me above error . Any help is highly appreciated .

@SuperBruceJia , I fixed the CUDA version & PyTorch version issue . The problem was my PyTorch was having 2.1.0+cu121  this version but my vm having cuda 11.8 so when I changed my PyTorch version to 2.1.0+cu118 issue resolved . Now I am have setted environment . But now If I am running your given script , In line
llm = LLM(model=model_name, download_dir=save_dir_llm, tensor_parallel_size=num_gpus, gpu_memory_utilization=0.70)
getting error NameError: name  is not defined. How to fix this . Let say I want to infer model codellama/CodeLlama-7b-Python-hf from hugging face . What should I do to infer it via your proposed modified vllm .

The supported targets are only limited to
target_modules=[
            "q_proj",
            "k_proj",
            "v_proj",
        ],

Hello everyone. Can I get help? I'm using inference on phi2 customed model and for inference I'm using MODAL and VLLM and I'm getting : base_model.model.model.layers.0.mlp.fc2.lora_A.weight @Soumendraprasad @SuperBruceJia

The supported targets are only limited to
target_modules=[
            "q_proj",
            "k_proj",
            "v_proj",
        ],

Hi, @SuperBruceJia I'm also getting this error: KeyError: 'base_model.model.lm_head.base_layer.weight' Can you please help?
Here is my notebook: https://colab.research.google.com/drive/1hYdz4JYFuqzMM3pKFvsgH2ZMMc6KSy_y?usp=sharing
and here is my model: https://huggingface.co/marksuccsmfewercoc/llava-1.5-7b-hf-ft-mix-vsft

Hi, @SuperBruceJia I'm also getting this error: KeyError: 'base_model.model.lm_head.base_layer.weight' Can you please help?
Here is my notebook: https://colab.research.google.com/drive/1hYdz4JYFuqzMM3pKFvsgH2ZMMc6KSy_y?usp=sharing
and here is my model: https://huggingface.co/marksuccsmfewercoc/llava-1.5-7b-hf-ft-mix-vsft

It seems that the repository only contains an adapter:
https://huggingface.co/marksuccsmfewercoc/llava-1.5-7b-hf-ft-mix-vsft/tree/main.
You need to load the base model first:
https://huggingface.co/marksuccsmfewercoc/llava-1.5-7b-hf-ft-mix-vsft/blob/main/adapter_config.json#L7
And then load the adapter:
https://huggingface.co/marksuccsmfewercoc/llava-1.5-7b-hf-ft-mix-vsft/blob/main/adapter_config.json#L21-L42
You may need the LoRA for vLLM:
https://docs.vllm.ai/en/latest/models/lora.html

I'm confused, How that will work? Can you give me an example?
On Mon, 22 Apr 2024, 22:59 Shuyue Jia (Bruce Jia), @.***>
wrote:

Hi, @SuperBruceJia https://github.com/SuperBruceJia I'm also getting
this error: KeyError: 'base_model.model.lm_head.base_layer.weight' Can you
please help?
Here is my notebook:
https://colab.research.google.com/drive/1hYdz4JYFuqzMM3pKFvsgH2ZMMc6KSy_y?usp=sharing
and here is my model:
https://huggingface.co/marksuccsmfewercoc/llava-1.5-7b-hf-ft-mix-vsft
It seems that the repository only contains an adapter:
https://huggingface.co/marksuccsmfewercoc/llava-1.5-7b-hf-ft-mix-vsft/tree/main
.
You need to load the base model first:
https://huggingface.co/marksuccsmfewercoc/llava-1.5-7b-hf-ft-mix-vsft/blob/main/adapter_config.json#L7
And then load the adapter:
https://huggingface.co/marksuccsmfewercoc/llava-1.5-7b-hf-ft-mix-vsft/blob/main/adapter_config.json#L21-L42
You may need the LoRA for vLLM:
https://docs.vllm.ai/en/latest/models/lora.html
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You are receiving this because you commented.Message ID:
@.***>

Hi, @SuperBruceJia I'm also getting this error: KeyError: 'base_model.model.lm_head.base_layer.weight' Can you please help?
Here is my notebook: https://colab.research.google.com/drive/1hYdz4JYFuqzMM3pKFvsgH2ZMMc6KSy_y?usp=sharing
and here is my model: https://huggingface.co/marksuccsmfewercoc/llava-1.5-7b-hf-ft-mix-vsft

It seems that the repository only contains an adapter: https://huggingface.co/marksuccsmfewercoc/llava-1.5-7b-hf-ft-mix-vsft/tree/main.
You need to load the base model first: https://huggingface.co/marksuccsmfewercoc/llava-1.5-7b-hf-ft-mix-vsft/blob/main/adapter_config.json#L7
And then load the adapter: https://huggingface.co/marksuccsmfewercoc/llava-1.5-7b-hf-ft-mix-vsft/blob/main/adapter_config.json#L21-L42
You may need the LoRA for vLLM: https://docs.vllm.ai/en/latest/models/lora.html

I'm confused, How that will work? Can you give me an example?

https://docs.vllm.ai/en/latest/models/lora.html

Please check this simple example: https://docs.vllm.ai/en/latest/models/lora.html

(1) You first load the based model
(2) Then, load the LoRA adapter
(3) Finally, merge the base model with LoRA adapter (by vLLM internal codes)
(4) Run the llm.generate

https://docs.vllm.ai/en/latest/models/lora.html

Please check this simple example: https://docs.vllm.ai/en/latest/models/lora.html

(1) You first load the based model (2) Then, load the LoRA adapter (3) Finally, merge the base model with LoRA adapter (by vLLM internal codes) (4) Run the `llm.generate`

Ok, so first I need to download the model from Huggingface hub and use llava model in the llm class and set enable lora to true

https://docs.vllm.ai/en/latest/models/lora.html

Please check this simple example: https://docs.vllm.ai/en/latest/models/lora.html

(1) You first load the based model (2) Then, load the LoRA adapter (3) Finally, merge the base model with LoRA adapter (by vLLM internal codes) (4) Run the llm.generate

Ok, so first I need to download the model from Huggingface hub and use llava model in the llm class and set enable lora to true

Since there is a max lora rank in the current vLLM + LoRA implementations, the max LoRA r is 64: https://github.com/vllm-project/vllm/blob/main/vllm/config.py#L809-L815
And your adapter's rank is 64:
https://huggingface.co/marksuccsmfewercoc/llava-1.5-7b-hf-ft-mix-vsft/blob/main/adapter_config.json#L22
So, I think it should work.

Got it, I will try this. But Thank you very very much 😊🙏
On Mon, 22 Apr 2024, 23:18 Shuyue Jia (Bruce Jia), @.***>
wrote:

https://docs.vllm.ai/en/latest/models/lora.html
Please check this simple example:
https://docs.vllm.ai/en/latest/models/lora.html
[image: image]
https://private-user-images.githubusercontent.com/31528604/324555956-bbf5ab4b-4667-4701-b300-a668b8e972e0.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.OLv7uIYUHUJKjOc_FRHkF8UJeQ3IXVZzhD-QBicpFzk
(1) You first load the based model (2) Then, load the LoRA adapter (3)
Finally, merge the base model with LoRA adapter (by vLLM internal codes)
(4) Run the llm.generate
Ok, so first I need to download the model from Huggingface hub and use
llava model in the llm class and set enable lora to true
Since there is a max lora rank in the current vLLM + LoRA
implementations, the max LoRA r is 64:
https://github.com/vllm-project/vllm/blob/main/vllm/config.py#L809-L815
And your adapter's rank is 64:
https://huggingface.co/marksuccsmfewercoc/llava-1.5-7b-hf-ft-mix-vsft/blob/main/adapter_config.json#L22
So, I think it should work.
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You are receiving this because you commented.Message ID:
@.***>

https://docs.vllm.ai/en/latest/models/lora.html

Please check this simple example: https://docs.vllm.ai/en/latest/models/lora.html

(1) You first load the based model (2) Then, load the LoRA adapter (3) Finally, merge the base model with LoRA adapter (by vLLM internal codes) (4) Run the llm.generate

Ok, so first I need to download the model from Huggingface hub and use llava model in the llm class and set enable lora to true

Since there is a max lora rank in the current vLLM + LoRA implementations, the max LoRA r is 64: https://github.com/vllm-project/vllm/blob/main/vllm/config.py#L809-L815
And your adapter's rank is 64: https://huggingface.co/marksuccsmfewercoc/llava-1.5-7b-hf-ft-mix-vsft/blob/main/adapter_config.json#L22
So, I think it should work.

Hey, @SuperBruceJia I'm getting this error: AssertionError: To be tested: vision language model with LoRA settings., I think it's not supported yet.

https://docs.vllm.ai/en/latest/models/lora.html

Please check this simple example: https://docs.vllm.ai/en/latest/models/lora.html

(1) You first load the based model (2) Then, load the LoRA adapter (3) Finally, merge the base model with LoRA adapter (by vLLM internal codes) (4) Run the llm.generate

Ok, so first I need to download the model from Huggingface hub and use llava model in the llm class and set enable lora to true

Since there is a max lora rank in the current vLLM + LoRA implementations, the max LoRA r is 64: https://github.com/vllm-project/vllm/blob/main/vllm/config.py#L809-L815
And your adapter's rank is 64: https://huggingface.co/marksuccsmfewercoc/llava-1.5-7b-hf-ft-mix-vsft/blob/main/adapter_config.json#L22
So, I think it should work.

Hey, @SuperBruceJia I'm getting this error: AssertionError: To be tested: vision language model with LoRA settings., I think it's not supported yet.

Can we please have support for vision models? @ywang96

https://docs.vllm.ai/en/latest/models/lora.html

Please check this simple example: https://docs.vllm.ai/en/latest/models/lora.html

(1) You first load the based model (2) Then, load the LoRA adapter (3) Finally, merge the base model with LoRA adapter (by vLLM internal codes) (4) Run the llm.generate

Ok, so first I need to download the model from Huggingface hub and use llava model in the llm class and set enable lora to true

Since there is a max lora rank in the current vLLM + LoRA implementations, the max LoRA r is 64: https://github.com/vllm-project/vllm/blob/main/vllm/config.py#L809-L815
And your adapter's rank is 64: https://huggingface.co/marksuccsmfewercoc/llava-1.5-7b-hf-ft-mix-vsft/blob/main/adapter_config.json#L22
So, I think it should work.

I think we can't use fine-tuned VLM on vllm?

still does not work.
I have tried mistralai/Mistral-7B-Instruct-v0.3 and mistralai/Ministral-8B-Instruct-2410
here is the code:
llm = LLM(model= args.llm_name, dtype='bfloat16', max_model_len= max_len,
            tensor_parallel_size=torch.cuda.device_count(), gpu_memory_utilization= args.gpu_memory_utilization, #seed=None,
            trust_remote_code=True,
            quantization="bitsandbytes", load_format="bitsandbytes", enforce_eager=True,
            enable_lora=enable_lora,
            tokenizer_mode= "mistral" if args.llm_name.startswith('mistralai') else 'auto'
        )

here is the error:

Loading safetensors checkpoint shards:   0% Completed | 0/4 [00:00<?, ?it/s]
Loading safetensors checkpoint shards:  25% Completed | 1/4 [00:00<00:02,  1.34it/s]
Loading safetensors checkpoint shards:  50% Completed | 2/4 [00:01<00:01,  1.27it/s]
[rank0]: Traceback (most recent call last):
[rank0]:   File "/home/ubuntu/moa/eval.py", line 169, in
[rank0]:     llm = LLM(model= args.llm_name, dtype='bfloat16', max_model_len= max_len,
[rank0]:   File "/opt/conda/lib/python3.10/site-packages/vllm/entrypoints/llm.py", line 177, in init
[rank0]:     self.llm_engine = LLMEngine.from_engine_args(
[rank0]:   File "/opt/conda/lib/python3.10/site-packages/vllm/engine/llm_engine.py", line 573, in from_engine_args
[rank0]:     engine = cls(
[rank0]:   File "/opt/conda/lib/python3.10/site-packages/vllm/engine/llm_engine.py", line 334, in init
[rank0]:     self.model_executor = executor_class(
[rank0]:   File "/opt/conda/lib/python3.10/site-packages/vllm/executor/executor_base.py", line 47, in init
[rank0]:     self._init_executor()
[rank0]:   File "/opt/conda/lib/python3.10/site-packages/vllm/executor/gpu_executor.py", line 40, in _init_executor
[rank0]:     self.driver_worker.load_model()
[rank0]:   File "/opt/conda/lib/python3.10/site-packages/vllm/worker/worker.py", line 183, in load_model
[rank0]:     self.model_runner.load_model()
[rank0]:   File "/opt/conda/lib/python3.10/site-packages/vllm/worker/model_runner.py", line 1058, in load_model
[rank0]:     self.model = get_model(model_config=self.model_config,
[rank0]:   File "/opt/conda/lib/python3.10/site-packages/vllm/model_executor/model_loader/init.py", line 19, in get_model
[rank0]:     return loader.load_model(model_config=model_config,
[rank0]:   File "/opt/conda/lib/python3.10/site-packages/vllm/model_executor/model_loader/loader.py", line 1148, in load_model
[rank0]:     self._load_weights(model_config, model)
[rank0]:   File "/opt/conda/lib/python3.10/site-packages/vllm/model_executor/model_loader/loader.py", line 1082, in _load_weights
[rank0]:     model.load_weights(qweight_iterator)
[rank0]:   File "/opt/conda/lib/python3.10/site-packages/vllm/model_executor/models/llama.py", line 582, in load_weights
[rank0]:     loader.load_weights(
[rank0]:   File "/opt/conda/lib/python3.10/site-packages/vllm/model_executor/models/utils.py", line 203, in load_weights
[rank0]:     autoloaded_weights = list(self._load_module("", self.module, weights))
[rank0]:   File "/opt/conda/lib/python3.10/site-packages/vllm/model_executor/models/utils.py", line 182, in _load_module
[rank0]:     yield from self._load_module(prefix,
[rank0]:   File "/opt/conda/lib/python3.10/site-packages/vllm/model_executor/models/utils.py", line 169, in _load_module
[rank0]:     module_load_weights(weights)
[rank0]:   File "/opt/conda/lib/python3.10/site-packages/vllm/model_executor/models/llama.py", line 397, in load_weights
[rank0]:     param = params_dict[name]
[rank0]: KeyError: 'layers.0.self_attn.qkv_proj.weight'