Enable OBS monitoring test for EU-CH2

Please enable OBS monitoring test for EU-CH2.  domain is hardcoded in OTCEXTENSIONS for public OTC domains, but the EU-CH2 is different (non-standard) hence it has to be changed how the EU-CH2 domain is used.

we have currently OBS SDK broken for other regions
2023-09-20 06:01:23.286548 | TASK [Create Container]
2023-09-20 06:01:24.261593 | localhost | ERROR
2023-09-20 06:01:24.261827 | localhost | {
2023-09-20 06:01:24.261867 | localhost |   "changed": true,
2023-09-20 06:01:24.261893 | localhost |   "exception": "NoneType: None\n",
2023-09-20 06:01:24.261916 | localhost |   "msg": "non-zero return code",
2023-09-20 06:01:24.261938 | localhost |   "rc": 1,
2023-09-20 06:01:24.261959 | localhost |   "stderr": "Traceback (most recent call last):\n  File \"/home/apimon/.ansible/tmp/ansible-tmp-1695189683.3033261-2145917-79160665309120/create_container.py\", line 13, in <module>\n    conn.obs.create_container(name=container_name, headers=headers)\n  File \"/usr/local/lib/python3.10/site-packages/otcextensions/sdk/obs/v1/_proxy.py\", line 128, in create_container\n    return self._create(\n  File \"/usr/local/lib/python3.10/site-packages/otcextensions/sdk/sdk_proxy.py\", line 153, in _create\n    persist = res.create(\n  File \"/usr/local/lib/python3.10/site-packages/otcextensions/sdk/obs/v1/container.py\", line 155, in create\n    self._translate_response(response)\n  File \"/usr/local/lib/python3.10/site-packages/otcextensions/sdk/obs/v1/container.py\", line 55, in _translate_response\n    exceptions.raise_from_response(response, error_message=response.text)\n  File \"/usr/local/lib/python3.10/site-packages/otcextensions/common/exc.py\", line 286, in raise_from_response\n    raise cls(\nopenstack.exceptions.BadRequestException: <?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"yes\"?><Error>IllegalLocationConstraintException<Message>The  location constraint is incompatible for the region specific endpoint this request was sent to.</Message><RequestId>0000018AB12DCF20C00DC38D0ED9A8E4</RequestId><HostId>d2pi+WqeYmIMqToo0oZwO1zDKjAxCdIotqdSsP9MA21e5+3zb6Bij/md7EN30JR+</HostId></Error>: Client Error for url: https://scenario9-26d2114066154a-apimon.obs.eu-nl.otc.t-systems.com/, Bad Request\n",
2023-09-20 06:01:24.261982 | localhost |   "stderr_lines": [
2023-09-20 06:01:24.262002 | localhost |     "Traceback (most recent call last):",
2023-09-20 06:01:24.262023 | localhost |     "  File \"/home/apimon/.ansible/tmp/ansible-tmp-1695189683.3033261-2145917-79160665309120/create_container.py\", line 13, in <module>",
2023-09-20 06:01:24.262043 | localhost |     "    conn.obs.create_container(name=container_name, headers=headers)",
2023-09-20 06:01:24.262064 | localhost |     "  File \"/usr/local/lib/python3.10/site-packages/otcextensions/sdk/obs/v1/_proxy.py\", line 128, in create_container",
2023-09-20 06:01:24.262084 | localhost |     "    return self._create(",
2023-09-20 06:01:24.262104 | localhost |     "  File \"/usr/local/lib/python3.10/site-packages/otcextensions/sdk/sdk_proxy.py\", line 153, in _create",
2023-09-20 06:01:24.262124 | localhost |     "    persist = res.create(",
2023-09-20 06:01:24.262145 | localhost |     "  File \"/usr/local/lib/python3.10/site-packages/otcextensions/sdk/obs/v1/container.py\", line 155, in create",
2023-09-20 06:01:24.262165 | localhost |     "    self._translate_response(response)",
2023-09-20 06:01:24.262185 | localhost |     "  File \"/usr/local/lib/python3.10/site-packages/otcextensions/sdk/obs/v1/container.py\", line 55, in _translate_response",
2023-09-20 06:01:24.262205 | localhost |     "    exceptions.raise_from_response(response, error_message=response.text)",
2023-09-20 06:01:24.262225 | localhost |     "  File \"/usr/local/lib/python3.10/site-packages/otcextensions/common/exc.py\", line 286, in raise_from_response",
2023-09-20 06:01:24.262245 | localhost |     "    raise cls(",
2023-09-20 06:01:24.262265 | localhost |     "openstack.exceptions.BadRequestException: <?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"yes\"?><Error>IllegalLocationConstraintException<Message>The  location constraint is incompatible for the region specific endpoint this request was sent to.</Message><RequestId>0000018AB12DCF20C00DC38D0ED9A8E4</RequestId><HostId>d2pi+WqeYmIMqToo0oZwO1zDKjAxCdIotqdSsP9MA21e5+3zb6Bij/md7EN30JR+</HostId></Error>: Client Error for url: https://scenario9-26d2114066154a-apimon.obs.eu-nl.otc.t-systems.com/, Bad Request"
2023-09-20 06:01:24.262296 | localhost |   ]
2023-09-20 06:01:24.262317 | localhost | }

apimon triggers simple container creation playbook
with this sdk script:
https://github.com/opentelekomcloud-infra/apimon-tests/blob/master/playbooks/files/create_container.py
Region seems to be hardcoded on several places in https://github.com/opentelekomcloud/python-otcextensions/blob/master/otcextensions/sdk/obs/v1/_proxy.py (see eu-de references) and eu-nl is not properly taken.
Region and eventually url differs based on different regions
currently the obs is only usable in eu-de and not in eu-nl or eu-ch2

Should fix all issues for regions #360

@vladimirhasko @jmiskani please check on 0.30.4


Cleanup the qz code

It still relies on some old ctypes wrapper by Sven Schreiber.
The reordering routines in lapack seem complicated to wrap because of the need to send callback routines (selectg). The medium run equilibrium could be:

get rid of all ctypes
call the non-reordering routine in scipy
numbaify qzswitch
use qzswitch to write a new reodering function with several options

An alternative for the last point would be to use the current code which reorders based on a threshold value.

Gone for a slightly different plan:

now calling scipy.linalg.ordqz to do the factorization and the reordering
temporarily duplicating some of the scipy code until https://github.com/scipy/scipy/pull/6044 is merged

Numbaification of ordqz won't happen in the short run as one would need to pass a c pointer to a
function.
Numbaify qzswitch is still an option, but one would need to assess the potential benefits (not clear there are).

I'm glad to see that scipy is fixed (or will be soon).
Except for the fact that this blocks us from calling ordqz in a nopython environment, this sounds great.
Are we ready to close the issue?

Fixed here: 21b8f4bb3e018c05a76ce336f2da7715afababcd


Add Objective-C support and example; reorganize project [WIP]

Changes

Adds NSObject to every public class in MapboxDirections.swift.
Adds a new ObjC target to the Xcode project and moves the original Swift example to its own target.
Adds a MapboxDirections.framework target that the two example targets bring in.
Reorganizes the repo — moves MapboxDirections.swift to the MBDirections folder.
Asserts that the access token has been changed (if not properly set).

Issues

The initializer for MBDirectionsRequest will not automatically bridge to ObjC.
waypointCoordinates: [CLLocationCoordinate2D] is the problem.
Temporarily created another initializer that ignores waypoints.
... but this new initializer needs to be differently named, so that the compiler won't complain about ambiguity when you leave out a property when you're initializing in Swift.
Logging output to console is meh, but acceptable for now.
Tests need to be updated for the new project structure.

Will need to solve the initializer bridging problem and minimize disruption before this can be merged.
/cc @1ec5

Given that we expect keep the API surface area of this library fairly minimal, maybe we should have two language-specific libraries, to get around issues like the waypoint parameter.
In the meantime, though, the solution to this ambiguity would be to remove the default value from the waypoint parameter.

Putting this particular attempt aside, for now.


Articulated hand tracking not working with Holographic Remoting after porting game to Unity 2019.4

Describe the bug
Having some problems getting articulated hand tracking to work with Holographic Remoting after porting my game over to Unity 2019.4.11f1 using MRTK 2.4 on a Hololens 2.  I'm not getting any hand tracking as I did in the previous version of my Unity project. Any help figuring out how to debug or solve this issue would be greatly appreciated.
Is there a setting I'm missing? Currently On a blank scene with MRTK added, I can not see any Hand Mesh or Joint Visualizer. I have both Hand Mesh/Joint Visualization Modes set to Everything.
On this web page they mention potential fixes for the issue but I do not see or have Mixed Reality Toolkit > MSBuild option in Unity. Nor can I figure out how to install it
Screenshots
Mixed Reality Toolkit > MSBuild no where in sight.

Your setup

Unity 2019.4.11f1
MRTK 2.4

Target platform

HoloLens 2

Additional context
On a side note, I'm pretty limited on time and would like to continue with this project as soon as I can. In the case that this issue will be difficult to overcome, is there a recommended version of Unity to use that will give me the least amount of issues as of today?

The first try installing NUGet didn't work. Second time for some reason did the trick.


stdbuf -oL libinput debug-events|grep switch doesnt return anything

Hi there, thanks for your project, but i've gotten a weird issue when trying to get it to work on my machine (Lenovo Yoga 530-14ikb) with the current Pop_OS! Version 21.04 and GNOME 3.38.5:
The command you listet for checking the libinput debug-events just doesnt work. I enter it in my Terminal and it doesnt return anything. I tried flipping my screen while the command is running, but even this has the same issue.
And since i'm not sure, which event (ls -lh /dev/input/by-path lists like 7 or 8 different inputs with only the keyboard being similiar named to your example config) is needed for my device, i cant get the script to work.
Did you already stumble upon this issue with the aforementioned command?

If it doesn't return anything it just means that your device is not supported. I've updated the README to clarify how to check if your device is supported.


can't set head.script.src to env var inside nuxt.config.js file

In my nuxt.config.js file I insert a JS file into my site using the head attribute. I set the src of the file to an env var (process.env.FILE_URL) but can't seem to get this working. I am seeing the following behaviour:

When running nuxt dev the env var value is injected correctly and the correct file is loaded.
When running nuxt build && nuxt start the value is not injected and I get undefined.
If I set the src attr to be an immediately executing function which console logs and then returns process.env.FILE_URL, the console log is the correct value, but the src is still set to undefined.

Is this something anyone has seen or can help me with? I can't find any documentation about whether this is expected behaviour, or a bug.

Did you set FILE_URL in nuxt start, I think you should set it in nuxt build, because building is the step to process all head resources.
Or you can make head be a function to load configs asynchronously, such as:
// nuxt.config.js
module.exports = {
  head: function () {
    return {title: process.env.headTitle}
  }
}

Thank you! Completely forgot that my env vars are available at runtime but not build time, thus the confusion.


node-gyp configure - issue on Windows

I was able to run: "npm install -g node-gyp" without issue.
What did I not do?
C:\edge>node-gyp configure -g
Node Commands
Syntax:
node {operator} [options] [arguments]
Parameters:
/? or /help   - Display this help message.
list          - List nodes or node history or the cluster
listcores     - List cores on the cluster
view          - View properties of a node
online        - Set nodes or node to online state
offline       - Set one or more nodes to the offline state
For more information about HPC command-line tools,
see http://go.microsoft.com/fwlink/?LinkId=120724.

Make sure node.exe (i.e. the node.js binary) comes before the HPC tools on your PATH.  If you're not using the HPC tools, it may be better to uninstall them to avoid further conflicts.

I'll go ahead and assume it's working for you now.  Closing.


Add Python configuration files to customization and Implement FlaskDetector

What does this PR do?
It adds a list of configuration_files inside the languages-customization.yaml file:
Python:
  configuration_files:
    - "project.toml"
    - "requirements.txt"
  component: true

This allows the component_recognizer to be able to recognize Python components, from their configuration_files, in given projects.
It adds functionality to DjangoDetector in order to be able to recognize if a Python project has django as framework, through requirements.txt or project.toml files.
It also creates the FlaskDetector which allows the PythonEnricher to recognize flask as framework of a python project.
Which issue(s) this PR fixes:
fixes https://github.com/redhat-developer/alizer/issues/147

@kadel / @mike-hoang I've updated the pyproject filename according to PEP 621

Component detections seem to work ok.

testing output
go run alizer.go devfile ~/DEMO/vote/pipelines-vote-ui/
[
	{
		"Name": "python",
		"Language": "Python",
		"ProjectType": "Python",
		"Tags": [
			"Python",
			"Pip",
			"Flask"
		]
	}
]

go run alizer.go component ~/DEMO/vote/pipelines-vote-ui/
[
	{
		"Name": "pipelines-vote-ui",
		"Path": "/Users/tkral/DEMO/vote/pipelines-vote-ui/",
		"Languages": [
			{
				"Name": "Python",
				"Aliases": [
					"python3",
					"rusthon"
				],
				"Weight": 100,
				"Frameworks": [
					"Flask"
				],
				"Tools": [],
				"CanBeComponent": true
			}
		],
		"Ports": [
			8080
		]
	}
]

But language recognizer.Analyze detection still marks this repo as JavaScript.
I guess this goes back to the issue that this function uses only the number of files grouped by extension as a metric.
This PR fixes the most pressing issue (component detection), but the original issues should be kept open until the language detection is more robust.

testing output
go run alizer.go analyze ~/DEMO/vote/pipelines-vote-ui/
[
	{
		"Name": "JavaScript",
		"Aliases": [
			"js",
			"node",
			"nodejs",
			"TypeScript"
		],
		"Weight": 66.66,
		"Frameworks": [],
		"Tools": [],
		"CanBeComponent": true
	},
	{
		"Name": "Python",
		"Aliases": [
			"python3",
			"rusthon"
		],
		"Weight": 33.33,
		"Frameworks": [
			"Flask"
		],
		"Tools": [],
		"CanBeComponent": true
	}
]

Sure @kadel , I'll follow up on the issue to clarify this.


Can I open an ethical issue?

I'm pretty sure this is causing mass trauma. For that reason, I give it 🌭/10, quite... traumatic.

hot dogs have no ethics


Update cpo.py

Hi @murali-shankar we are now getting back to ocpi library maintenance, we will soon take care of the request you created, have you successfully integrated ocpi lib with your project ?


Also Added autocomplete options in SignUpPage, removed useless server/mutation.jsx file, adjusted server/auth to use secret in a .env file.


swaysettings: init at 0.3.0

Description of changes
Added  the swaysettings tool.
The tool is great to edit some part of the configuration of a desktop environment based on sway.
homepage is here https://github.com/ErikReider/SwaySettings
Things done

Built on platform(s)

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

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

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

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

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

[ ] Fits CONTRIBUTING.md.

Closing this because of poor, below novice, quality.

Nice comment. Very helpful

OK, let's restart this.

Not interested anymore, @aacebedo?

Not interested anymore, @aacebedo?

Yes. I switched one my machine to nixos, applied the fixes and tested it this morning actually. Planning to deliver this weekend.

I did a fixup to see the difference from the original. When correction is confirm, I'll squash it and push a single commit.

I squashed the fixup. Is it ready for merge ?

rebased on upstream


Adding documentation for message builder

Not too sure if we want to be drawing the UML diagrams for every little component so I can remove the class diagram if it feels unnecessary


Compilation error due to size_t -> uint64_t on 32bit Arch

Hi,
I tried to compiled ponyc on Linux Manjaro (based on arch linux) (version 4.5.7) 32 bits but I've got an error :
src/libponyc/codegen/genopt.cc: In member function 'llvm::Value* MergeRealloc::mergeConstant(llvm::IRBuilder<>&, llvm::Value*, uint64_t)':
src/libponyc/codegen/genopt.cc:797:37: error: conversion to 'size_t {aka unsigned int}' from 'uint64_t {aka long long unsigned int}' may alter its value [-Werror=conversion]
       size = ponyint_heap_index(size);
                                     ^
cc1plus: all warnings being treated as errors
Makefile:456: recipe for target 'build/debug/obj/libponyc/codegen/genopt.o' failed
make: *** [build/debug/obj/libponyc/codegen/genopt.o] Error 1

I'm using gcc (g++) 6.1.1 to compile (and I tried with clang++ 3.8.0, same error).
Since I'm on a 32bit, size_t is smaller than uint64_t, hence the error.

This was added in:
5637d26f66d9afca01671322f9e22b4af1f8919b
and is almost assuredly a bug. Thanks @n3f4s.

@Praetonus, can you take a look at this at some point?

It's also a bit of a shame that Travis CI doesn't offer 32-bit CI for us to test against...

we have the ability to do it at Sendence but its manual at the moment which isn't much help.

It should be fixed in #941.


Add requireSameNode field for pod dependencies

Previously pod dependencies always required the pod to be on the same
node.  Though this was documented it often did not match user intuition
as merely depending on a pod shouldn't require anything more than it
existing somewhere in the cluster.  This adds a field to pod
dependencies to specify whether the pod is required to be on the same
node.  This defaults to false for the reasons above, which is a breaking
change.

LGTM


Can't remove the "collapse all" keybind

Hello.
So I've been trying to remove the keybind for "collapse all" because the default keybind is alt-1 and so every time I try to use an ASCII code to get a special character that includes 1 like curly brackets or square brackets, my whole code collapses and it's extremely annoying.
This is what I'm trying to do for overriding it
Debug>open user keymap
At the keymap, the file keymap.json opens.
I delete everything from the file (because I only want to override this key) and write exactly this.
<!-->
{
"overrides": {
"<Alt 1>": "null>"
[, "<Alt 1>": "null>"]
}
}
(NOTE: The obvious errors in syntax such as no MINUS between Alt and 1 and the lack of "less than" sign on the nulls were done on purpose because for some reason, when writing them, the post would be blank)
But upon saving I get the message "Error reading file: Your file is not valid JSON, the file will be opened so that you can correct the format"
I honestly cannot see why this is the default keybind for a code editor if the combination of alt-1 is used for so many ascii characters

In the syntax above, you need to replace the <, >, [, and ] chars. Try this:
{
    "documentation": "https://github.com/adobe/brackets/wiki/User-Key-Bindings",
    "overrides": {
        "Alt-1": null
    }
}

Note that I used the Display Shortcuts extension, then right-clicked on item and selected "Disable Shortcut". This updates keymap.json file which then needs to be saved.

In the syntax above, you need to replace the <, >, [, and ] chars. Try this:
{
    "documentation": "https://github.com/adobe/brackets/wiki/User-Key-Bindings",
    "overrides": {
        "Alt-1": null
    }
}

Note that I used the Display Shortcuts extension, then right-clicked on item and selected "Disable Shortcut". This updates keymap.json file which then needs to be saved.

Thank you! I feel a bit silly now. Thought those were actual command tags to be used

Thank you! I feel a bit silly now. Thought those were actual command tags to be used


meta: new maintainer/champion for wagon

hi there,
lately I've found my involvement in wagon to dwindle.
partly because my main interest in wasm+wagon was to be able to build an interpreter for Go, in Go, and that there are now at least 2 Go interpreters (gomacro and yaegi) that fit the bill for me.
partly because I just don't find time to allocate for all the WebAssembly-related activity.
so... this is a meta-issue to look for new maintainers or champions.
please reach out.
(alternatively, wagon could be handed over to gowasm, if they want it)
(I'll give it a month)

ping?


Zeroing ForeignPtrs on deallocation

Given all the warnings and "[REDACTED]" instances I was surprised that there are no memory clean-up for those objects.
Perhaps there should be an mallocForeignPtrBytes wrapper that automatically attaches addForeignPtrFinalizer with fillBytes or sodium_memzero().
OTOH, when you import your secrets from a ByteString or hex, it's already a game over in this department :woman_shrugging:

Or just go all in on sodium_malloc().

Certainly sodium_malloc() could be used, yes.
Do you feel like you'd like to tackle this? :)

closed via #91


I hope that ollama can optimize the parallel performance of CPU computations?

When serving as the LLM provider for GraphRAG, the 100% single CPU usage is preventing full utilization of multiple GPU resources on the server.

settings.yaml
### This config file contains required core defaults that must be set, along with a handful of common optional settings.
### For a full list of available settings, see https://microsoft.github.io/graphrag/config/yaml/

### LLM settings ###
## There are a number of settings to tune the threading and token limits for LLM calls - check the docs.

encoding_model: cl100k_base # this needs to be matched to your model!

llm:
  api_key: ollama # set this in the generated .env file
  type: openai_chat # or azure_openai_chat
  model: llama3.2
  model_supports_json: true # recommended if this is available for your model.
  # audience: "https://cognitiveservices.azure.com/.default"
  api_base: http://localhost:11434/v1
  request_timeout: 1800.0
  max_tokens: 8000

parallelization:
  stagger: 0.3
  # num_threads: 50

async_mode: threaded # or asyncio

embeddings:
  async_mode: threaded # or asyncio
  vector_store:
    type: lancedb
    db_uri: 'output/lancedb'
    container_name: default
    overwrite: true
  llm:
    api_key: ollama
    type: openai_embedding # or azure_openai_embedding
    model: nomic-embed-text:latest
    api_base: http://localhost:11434/v1
    request_timeout: 1800.0

https://github.com/ollama/ollama/issues/6913
Multi-threading will not improve performance.  The reason the CPU is at 100% is because CPU/GPU synchronization is a spin-wait.  The two processors share a bit of memory and use it to tell each other what the current state is.  So the CPU is busy checking "are you ready yet" a million times per second, and once in a while the GPU will say "yes, I am finished", the CPU will spend a few cycles sending a new command to the GPU, and then goes back to spinning on "are you ready yet".
From your screenshot, the model you are using is llama3.2:3b-instruct-q4_K_M, and since all of the processes listed have the same PID, you are probably using OLLAMA_SCHED_SPREAD to force the model to run on all GPUs.  This is not an efficient use of your GPUs, see here for more discussion. The reason your GPU utilization is poor is because each GPU is waiting for the intermediate results from a different GPU.  With a small model like llama3.2:3b, you will get better performance if you run multiple servers as outlined in the linked discussion.

cpu usage is 100% (without set OLLAMA_SCHED_SPREAD env var), same to former case~


⚠ Bofrost.at has degraded performance

In 75ddc89, Bofrost.at (https://www.bofrost.at) experienced degraded performance:

HTTP code: 200
Response time: 4253 ms

Resolved: Bofrost.at performance has improved in 9007f4d.


Wrong prerequisites for using the "Tenant Creator" role

In our docuemtnation, we say "If tenant creation is switched off, ask your Global Administrator to assign you a Tenant Creator role."

I believe the correct term should be "switched ON", since enabling this feature, will restrict the users from creating a tenant, and the role "Tenant Creator" will then be useful.
The above information contradicts with the following statement.

Hello @SaibabaBalapur-MSFT , my apology I assume that you will be able to see the link.
Here are the source of the data I shared earlier:
https://learn.microsoft.com/en-us/azure/active-directory-b2c/tutorial-create-tenant#prerequisites
https://learn.microsoft.com/en-gb/azure/active-directory/fundamentals/users-default-permissions#restrict-member-users-default-permissions
Let me know if you need more information

@NoorKhaldi
Thanks for bringing this to our attention. We have created a PR for this issue and the changes should go live soon.


Add LICENSE file

Thx for this amazing project! 💙
Adding a license would help show go-clack's docs on https://pkg.go.dev/
Currently you get something like:

Hey @Neved4, thanks for the issue!
I just added a License on #4, now you can see the package's documentation on<EMAIL_ADDRESS>

It's showing rn, thx for being awesome! @Mist3rBru


Docker v.4.33.0 can't connect to database

Version of Warden
0.14.3
Operating System and Installation Method
Mac OS 13.4 via github
Image
maria-db:10.6-magento2
Describe the Bug
After updated my Docker Desktop to v.4.33.0 I can't connect to DB neither via PhpStorm or Sequel Pro.
I was able to connect to the tunnel.warden.test via terminal or PhpStorm. But connection to DB doesn't work.
Here is my config in PhpStorm:

But when I'm trying to connect I got "SSH tunnel creation failed: Name does not resolve.":

Solution for the similar issue didn't help: https://github.com/wardenenv/warden/issues/260#issuecomment-722355346

Could you please show your general tab? Chiefly the hostname that you're attempting to connect to


Add support for pattern for regex constrained properties.

The JSON Schema spec includes the pattern constraint for properties, but this gets ignored when generating the markdown. This PR fixes this.
The _construct_description_line function has been extended to also look for the pattern keyword and the markdown generation test has been updated to include a pattern constrained property.

Thanks, You just should adapt the test expected value related to your changes :-)

Thanks, You just should adapt the test expected value related to your changes :-)

Sorry, bad push. Fixed.

pre-commit isn't installed on checkout, then it steals have a little change!
https://github.com/sbrunner/jsonschema2md/pull/373/checks?check_run_id=31171656143


div96th_counter and div192th_counter incorrectly named.

Original MIDICtrl code was incorrectly naming div64th_counter as div96th_counter.
Below:
MidiClock sends 24 ppm
1 measure  = 4 x 16th notes.
Therefore.
6 pulses per 16th note.
--
div16th_counter      6 pulses
div32th_counter     3 pulses
div64th_counter     1 pulse      ~(div96th_counter)~
div128th_counter   0.5 pulse   ~(div192th_counter)~
--

Eh this is wrong.

6 * 4 * 4 = 96 pulses per measure.


Notify Mysensors no longer working

Since the last update the mysensors notify is no longer working (V 0.65.5 or V 0.65.4)
WARNING (MainThread) [homeassistant.core] Unable to find service notify/mysensors
I'm using hassio

Nothing has changed for 7 months for the mysensors notify platform and for 2 months for the notify base component. The last change in the mysensors component was released in 0.64.1.
If the mysensors notify platform worked between then and now it's low chance that the cause lies within home assistant.
I'd try to restart your gateway, then home assistant and then the node to have the node present itself again. And try to capture debug log of when the node starts up. This should trigger the setup of the mysensors notify platform. That should tell us something.

Seems as a automation was breaking the notify sensor.
I added this
- alias: Set TFT switch names on start
  trigger:
    platform: homeassistant
    # Event can also be 'shutdown'
    event: start
  action:
    service: script.set_ftf_switch_names

and in the set_ftf_switch_names script i call the notify.mysensors service.
I removed the automation and everything works fine again.

Ok. Yeah, currently the persistent devices are loaded after home assistant start, so a script that relies on a mysensors device/service and runs when the home assistant start event fires, will mot be reliable.
I plan to move the persistence loading before home assistant start event, in the future.


typo mistake fix

changing Extention to extension , this is my first pull request in open source

Congrats on the first contribution 🙂

actually it says some conflict , so only bro . how to take the latest version , can you please help me on that?

Good job @praveen2896 :tada:
Could you also share the right learning to help them close #8


style: fix components page details

Pull Request Test Coverage Report for Build 740

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage remained the same at 77.825%

Totals

Change from base Build 721:
0.0%

Covered Lines:
1287

Relevant Lines:
1584

💛  - Coveralls


Istio doc websocketUpgrade: true using v1beta1

Bug description
In networking.istio.io/v1alpha3 there was an option to set websocketUpgrade: true , I cannot see this option in v1beta1 or any documentation this has been removed.
I currently using websockets and I am finding that after 20sec the websocket connection becomes stalled and starts another poll
Without Istio using websockets i see the following
?EIO=3&transport=websocket just once and all requests flow through this
With Istio
?EIO=3&transport=websocket which seems to stall then subsequent requests like this
?EIO=3&transport=polling&t=xxxxx&sid=xxxxxxxxxxxx
[ x] Docs
[ ] Installation
[ x] Networking
[ ] Performance and Scalability
[ ] Extensions and Telemetry
[ ] Security
[ ] Test and Release
[ ] User Experience
[ ] Developer Infrastructure
[ ] Upgrade
Expected behavior
Only one websocket and all requests through this
?EIO=3&transport=websocket just once and all requests flow through this
Steps to reproduce the bug
Version (include the output of istioctl version --remote and kubectl version --short and helm version --short if you used Helm)
❯ istioctl version --remote
client version: 1.9.1
control plane version: 1.9.1
data plane version: 1.9.1 (59 proxies)
How was Istio installed?
Helm
Environment where the bug was observed (cloud vendor, OS, etc)
GKE
Additionally, please consider running istioctl bug-report and attach the generated cluster-state tarball to this issue.
Refer cluster state archive for more details.

I found the problem , and websockets work just fine without the extra config.
In my case on GKE using L7 loadbalancer I did not add in for the Istio Ingressgateway a backend which defined timeoutSec value and this was killing my connection.
Refer to this article i found
https://medium.com/johnjjung/how-to-use-gcp-loadbalancer-with-websockets-on-kubernetes-using-services-ingresses-and-backend-16a5565e4702


Networking Tests

This change set does the following:

Adds websockify as a submodule
Automatic submodule initialization for websockify in Makefile
Adds a networking test (Somewhat hacky... It can't run on node.js, so it uses some reflection and runtime checking for node.js)
Adds a networking test server that must be running for networking tests to pass. The networking tests will print out an error asking you to run the server if it can't connect.

Every once and a while, I'll be running the tests and I'll get the following:
/bin/bash: -c: line 1: syntax error: unexpected end of file
Anyone know what that's about?

Closing this PR; superceded by other networking PR.


GDAX API is down! unable to call getBalance

Same issue as #519

GDAX API is down! unable to call getBalance, retrying in 10s
{ Error: non-200 status: 400
at statusErr (/home/main/zenbot/extensions/exchanges/gdax/exchange.js:30:17)
at /home/main/zenbot/extensions/exchanges/gdax/exchange.js:93:25
at Request._callback (/home/main/zenbot/node_modules/gdax/lib/clients/public.js:45:7)
at Request.self.callback (/home/main/zenbot/node_modules/gdax/node_modules/request/request.js:187:22)
at emitTwo (events.js:125:13)
at Request.emit (events.js:213:7)
at Request. (/home/main/zenbot/node_modules/gdax/node_modules/request/request.js:1044:10)
at emitOne (events.js:115:13)
at Request.emit (events.js:210:7)
at IncomingMessage. (/home/main/zenbot/node_modules/gdax/node_modules/request/request.js:965:12)
at emitNone (events.js:110:20)
at IncomingMessage.emit (events.js:207:7)
at endReadableNT (_stream_readable.js:1056:12)
at _combinedTickCallback (internal/process/next_tick.js:138:11)
at process._tickCallback (internal/process/next_tick.js:180:9)
code: 'HTTP_STATUS',
body: { message: 'request timestamp expired' } }
[ { currency: 'USD', asset: 'BTC' } ]

GDax's API documentation mentions that:
400 | Bad Request – Invalid request format
-but everything is set according to Zenbot documentation?
API keys are correct with right permissions.
Files are set with execute permissions (if that would matter in this case).
OS is Debian GNU/Linux 8.9 (jessie).
Server is located in Dallas, TX and API isn't going off of whitelisted IP.
Any ideas?

Will be closing this issue, resolved.
People of the future:
I did some research on some basic API principles (since i'm clueless about API mostly), this happened because my local server time wasn't synced up with GDAX server time.  The way I fixed this was:

sudo apt-get install ntp
sudo systemctl restart ntp
sudo systemctl enable ntp

My time was mostly up to date before, but it was more than 30 seconds off of GDAX's time so it would error out.  Run these 3 commands, check your $ date and it should be more in-sync than it was before.

This is failing - same error - for me - im on a mac using unstable and greenkeeper 0.6.0 - neither worked


hot off the press - Elliott et al. Signing data citations enables data verification and citation persistence. Sci Data 10, 419 (2023). https://doi.org/10.1038/s41597-023-02230-y hash://sha256/f849c870565f608899f183ca261365dce9c9f1c5441b1c779e0db49df9c2a19d

I am pretty excited to be listed as a co-author on our recent paper [1]. I believe that our paper has some roots in classic 1945 essay "As We May Think" by Vannevar Bush [2] as well as the 1974 Computer Lib/Dream Machines by Ted Nelson [3] - in advocating for a more "intertwingled" approach to recording the complex webs of the knowledge we keep and explore.
Big thanks to @mielliott and many others that have contributed to the development of these (not so new?) ideas, including, but not limited to @btrask @cboettig @seltmann @slint @mbjones @tkuhn, @Daniel-Mietchen and more recently, @GregPost-ASU, @nfranz, and @n8upham. Also, thanks for open infrastructures such as Zenodo @slint (#210 ), The Internet Archive, Software Heritage Library (#70 ) @zacchiro @rdicosmo, DataOne (#181 ) @mbjones, and last but not least, GitHub and their excellent platform to develop open source software/data*.
Please do share your thoughts on the topic of building a media and format agnostic content-addressed knowledge universe.
References
[1] Elliott, M.J., Poelen, J.H. & Fortes, J.A.B. Signing data citations enables data verification and citation persistence. Sci Data 10, 419 (2023). https://doi.org/10.1038/s41597-023-02230-y hash://sha256/f849c870565f608899f183ca261365dce9c9f1c5441b1c779e0db49df9c2a19d
[2] Bush, V.. 1945. As We May Think, The Atlantic . See also https://en.wikipedia.org/wiki/As_We_May_Think .
[3] Nelson, T. 1972. Computer Lib/Dream Machines. See also https://en.wikipedia.org/wiki/Computer_Lib/Dream_Machines and https://archive.org/details/computer-lib-dream-machines .
* I hope, at some point, that GitHub itself could become a little more open, including having a way to easily re-publish issues in archives or other external platforms (#156 ).

Congrats @jhpoelen, I read it yesterday and it's a great paper. I've already forward it to several folks. Nice work! 🎉

Thanks for sharing @jhpoelen , this is wonderful.
Regarding the footnote about GitHub -- where do you see SoftwareHeritage fitting into this?  They can already resolve SHA-256 hashes to a substantial fraction of content found on GitHub, as well as archival copies of said content...  (Though they do impose rate limiting on their API, for obvious reasons).

Thanks @cboettig !

Regarding the footnote about GitHub -- where do you see SoftwareHeritage fitting into this? They can already resolve SHA-256 hashes to a substantial fraction of content found on GitHub, as well as archival copies of said content... (Though they do impose rate limiting on their API, for obvious reasons).

Software Heritage does a great job in making content in repositories accessible. And, in the footnote, I was referring to valuable content in GitHub issues, not just the content in their versioned repositories. I wonder whether Software Heritage is interested in archiving GitHub issues as well as the digital content in their repositories.

closing publication announcement issue.
[1] Elliott, M.J., Poelen, J.H. & Fortes, J.A.B. Signing data citations enables data verification and citation persistence. Sci Data 10, 419 (2023). https://doi.org/10.1038/s41597-023-02230-y hash://sha256/f849c870565f608899f183ca261365dce9c9f1c5441b1c779e0db49df9c2a19d
is already being cited . . . :fireworks:


Merge Task 3 modularized feature engineering

Merge Task 3 modularized feature engineering

Merge Task 3 modularized feature engineering to main repo

Merge Task 3 modularized feature engineering to main


How to Run fMRIPrep once to generate 2 or more sets of results for fMRI data based on 2 more choices of a parameter at a middle point of the workflows without rerunning the entire pipeline again ?

There are many options to choose when preprocessing fMRI data.  For a research purpose, we may want to generate different sets of preprocessing results to study effects of the choices of some parameters on image quality.  For example, we may want to generate two sets of preprocessed results with and without slice timing correction.   The current version of fMRIPrep pipeline gives such a choice (with or skipping slice timing correction) to run.  But it seems that we have to run the entire pipeline twice, one for yes and one for no, for the choice of the slice timing correction.  Can we just run once to get the two sets of results ?   We did not see a document to describe this.  It may not be the documentation problem.  The current version of the software has been implemented that way ?
I understand that fMRIPrep is implemented mainly based on nipype.   From the guide of nipype,  there is a mechanism,  namely, iterables, to implement a loop.  So, I am wondering,  can I make some quick modifications of the scripts in fmriprep to implement such a loop function?
For example, if there is a pseudocode code to define a node of slice timing correction here:
SliceTimer - correct for slice wise acquisition
slicetimer = Node(SliceTimer(STC_choice=True,
interleaved=True,
output_type='NIFTI',
time_repetition=TR)),
name="slicetimer")
slice_timing_correction_choice_list = ['yes', 'no']
slicetimer.iterables = ("STC_choice", slice_timing_correction_choice_list )
By slightly modifying the interface code of  SliceTimer such that it will simply return when the choice of STC_choice is no or will call the old codes when the choice is yes,   then we imagine that we can finish such an implementation.
But we are afraid of that things may not be that simple.   fMRIPrep is a great pipeline, but it is also very sophisticatedly complicated at the same time.  It is far different from any previous software packages, like SPM, which we can debug into each code to do some simple modifications.  So the best solution is to ask the experts from fMRIPrep group to teach us how to modify the codes to implement this function.
The slice timing choice is just an example for the purpose to describe the problems we have.  We may need to implement such a loop function for other choices.
Thank you!

The simple solution that currently exists is re-using the working directory while passing different options. As indicated in #2674, it will be complicated to make a really general solution that will allow you to add an iterable to arbitrary nodes and correctly carry metadata forward to the outputs.

Hi effigies:
Thank you !
 I have another question about using  "DerivativesDataSink":

Is there anyway to control DerivativesDataSink so that
It will do nothing and simply return without triggering an error when the input files do not exist ?


Scrub is not scrubbing

Testing scrub on legend after a few remarks about trouble with it in the LNbits TG group.
Originally wanted to send via split to a wallet and do a scrub from there to a lnaddress (lntipbot), which didnt work. neither to a LNURLp on the same or another instance.
Also tested direct payments to the Scrub-Wallet as well by paying an invoice - also no scrub.

Can confirm. Not working for me on legends, also not working on my own instance (commit c81d3e06c8c4217c1c38a71e24964df0e7b80d2c).

ok, scrubbing works in fakewallet locally for me, it maybe related the a issue that pops up with core lightning right now.  https://github.com/lnbits/lnbits/issues/1565

It works sometimes and sometimes it doesn't, not sure why or how to best debug this. The wallets are well funded, so a lack of funds to pay fees is not it.
I thought it had something to do with multi-path payments, but that was also not it, as both MP and AMP work sometimes. But sometimes, scrubbing fails. Hmm 🤔

+1 here it doesn't work for me either. Using LNTipBot as the backend so I don't think it's an LND issue (iirc, LNTips uses LNBits as a backend itself).

Doesn't work at all for me.
lnbits instance on https://timecatcher.lnbits.de
scrub target on https://card.swiss-bitcoin-pay.ch/

Can this be related to Lightning Network routing issues?

Manually sending to the same destination always works, so it's unlikely to be network routing related.

Related to this issue on split, a periodic rerun would be great:
https://github.com/lnbits/splitpayments/issues/10

i noted this for splits aswell.
maybe a scrub log, with all scrubs would make the failing scrubs more comprehensible and there could be a feature to manually rerun them

As mentioned on Splits, for me an optional setting to periodically rescrub the wallet-balance sub fee reserve is the way to go.
the whole point about split and scrub is that it’s automatic. Right now I need to periodically send Sats to a different wallet and back again manually to retrigger.

It miraculously started working two weeks ago. I assume the operator of timecatcher.lnbits.de updated something.


CheckPoint option

Is there a option for me to save checkpoint while training and then continue training from the checkpoint. Cause right now I cannot start from where I stopped but to start over again

The model is saved at the end of each epoch if the total loss is less than the previous epoch total loss. This is done using a ModelCheckpoint callback. So to resume where you left off, you just have to use the load option the next time you want to initialize your training


dace codegen issues

Describe the bug
There are a few issues I have about the C++ generated code for a simple matrix addition example from dace.

.dacecache/madd/src/cpu/madd.cpp: in the __dace_init_madd() function:
we have a pointer allocation with new but the lines of code following the allocation check for the value in the __result integer. Why is this the case? As I understand it, the new operator with nothrow returns a nullptr, in which case the check should be to see if the pointer (__state) is null or it should be a try_catch block to check for bad_alloc. What am I missing here?

.dacecache/madd/src/cpu/madd.cpp: in the __program_madd_internal() function:
In this case I see that the loop induction termination is set to M and N, but the internal matrix access is specialized to 10 (A[10*i + j] for example). Why is this the case? Why cant the matrix access also be based on the inputs (M, N)?

.dacecache/madd/sample/madd_main.cpp: in the main() function:
I see that the int M, N are set to 42, but the calloc() is specialized correctly to 10x10. Where does the 42 come from? Why is this not also 10?

To Reproduce
Steps to reproduce the behavior:

Run the attached python script to generate the SDFG along with the generated C++ code.
Check the .dacecache/madd/src/cpu/madd.cpp and .dacecache/madd/sample/madd_main.cpp for the described issues

Version
I am using dace v0.14.4
Additional context
Script to reproduce behavior along with the generated code on my machine.
code_gen.zip

There are two points here to comment on:
a. The "default" DaCe code generator doesn't output code for catching allocation failures.
b. As implied by the above, __result doesn't check if the allocation of __state succeeded. However, DaCe code generators can implement custom initialization routines (which may have allocation checks) that return a boolean to indicate success or failure. You can see how the code is exactly generated here. Note that int __result = 0 and if (__result) ... are always printed, regardless if there any targets (code generators) with their own initialization routines.
This is a case where the DaCe program's input/output data are type annotated (therefore, you can do ahead-of-time (AoT) compilation *), but the actual arguments are also passed to the to_sdfg method (needed for just-in-time (JIT) compilation). The matrix sizes are specialized because the JIT mode has higher priority than AoT and DaCe will use the sizes of the actual arguments instead of the type annotations. The loop bounds are not specialized because this is unrelated to the JIT mode, which only creates type annotations for the program's inputs/outputs. Since you passed values for M and N in the to_sdfg method, you probably expected all instances of M and N in the program to be replaced accordingly. @philip-paul-mueller this looks pretty related to #1380.
The subfolder sample is sample C++ code that one can use to call the generated DLL/shared library. Its purpose is to provide the user with the correct signature. The symbolic values in the main.cpp file have no meaning whatsoever other than being syntactically correct. The arrays are allocated with the "correct" size because it has been hardcoded to the SDFG due to using the JIT mode. The number 42 has no special meaning, except being the answer to life, the universe, and everything.

* The syntax for the type annotations is slightly wrong. You should write A: dace.float64[M, N] instead of A=dace.float64[M, N].

Hi @alexnick83
Thanks for the comments.
I just have one follow up on point 2, I tried both the JIT version and AOT versions and it seems like the deciding factor in the generated code is whether I set the arguments as A: dace.float64[M,N] or A= dace.float64[M,N]. In my case regardless of JIT or AOT, if I set the code to the latter, I always get 10 hardcoded inside the loop, and I never see this when I set the arguments to the former, it always correctly generates code without specialization.
I guess the takeaway for me is I should always use A: dace.float64[M, N] form of argument declaration in dace.

Please note that standard Python syntax applies. To use AoT, you need to provide type annotations. A = dace.float64[M, N] is not a type annotation but a default value (which cannot work, because dace.float64[M, N] is a shortcut to dace.data.Array(dtype=dace.float64, shape=(M, N)); not a value).

Since all the questions have been answered, I am closing this issue.


Invalid CommonJS output when transforming a single import declaration into multiple

Bug Report
I've created a TypeScript transformer that transforms a single barrel import declaration into multiple deep import declarations.
Eg changing this:
import { A, B } from 'pkg';
console.log(A, B);

Into something like this:
import { A } from 'pkg/a';
import { B } from 'pkg/b';
console.log(A, B);

This works great when emitting ES modules but not when emitting CommonJS.
🔎 Search Terms
Transform, import, esm, cjs

🕗 Version & Regression Information
Tested with 4.9.5 but I suspect that most versions have this behaviour.

⏯ Playground Link
Since Playground doesn't have support for transforms I don't have a playground link.

💻 Code
Not sure what to post here, any custom transform that replaces a single import declaration into multiple behave this way.
🙁 Actual behavior
When calling ts.setOriginalNode(newNode, node) for all new import declarations when emitted CJS code uses the same variable for all statements like this:
var pkg_1 = require('pkg/a');
var pkg_1 = require('pkg/b');
console.log(pkg_1.A, pkg_1.B);

That is, multiple new nodes having the same, single node as their original node.
When not calling ts.setOriginalNode() at all the ES output is fine but the CJS output is even more broken with something like:
var a_1 = require('pkg/a');
var b_1 = require('pkg/b');
console.log(pkg_1.A, pkg_1.B);

🙂 Expected behavior
I'm not sure how this should be handled but I would have liked to be able to connect multiple new nodes to a single original node and have the CommonJS transform see that and use different require variables. With output that looks something like this:
var pkg_1 = require('pkg/a');
var pkg_2 = require('pkg/b');
console.log(pkg_1.A, pkg_2.B);

I'm not really sure if this is a supported API usage, but if it's straightforward to fix in the emitter we can look at a PR

Thanks! I think I'll be able to hack around it by overriding TransformationContext.getGeneratedNameForNode and returning a different identifier for my new import declarations and then also replacing all uses of the identifiers in the source file, but it feels a bit hacky and error prone since newer TS versions could break my hack.


Project finder improvements

based on feedback from @Yantrio, made project finding configurable (must be turned on, this will be a breaking change in atom), added logging, and enhanced the way we search, and added some unit tests to cover the basic cases.
cc @nosami

What if we simply pass the project folder to omnisharp and let omnisharp decide?
I think we discussed starting up without passing a folder immediately in the past I think this would make everything most consistent.
start omnisharp
/get-all-projects <folder-path>
/connect-to <folder|scriptcs|sln|project.json|global.json>

if get-all-projects only returns one candidate we autostart to that (maybe to endpoint could do that returning with "autostarted": true. Otherwise we present to available solutions to the editor user.
obviously passing the path straight away would still work for bwc.
THoughts?

Do any of these end points exist today?

No.
On Tue, May 12, 2015 at 5:20 PM, David Driscoll<EMAIL_ADDRESS>wrote:

Do any of these end points exist today?
—
Reply to this email directly or view it on GitHub
https://github.com/OmniSharp/omnisharp-node-client/pull/8#issuecomment-101337464
.

@Mpdreamz your question belongs over on omnisharp-roslyn

:ship: set sail!


Issue with certain classads from submitter

When importing submitter.icecube.wisc.edu history.20170905T000000.gz the classad import fails causing the entire import process to fail.  I added a try, catch statement around the classad import, but this is just a band aid.
I suggest that we do these two things:

Run the script without the exception handling to see why condor doesn't like the classad.
Create some sort of output at the end of the script run to report the number of errors to ensure its less than 1% of the total.

Do you know what line(s) cause the problem?

@vbrik https://github.com/WIPACrepo/condor_tools/blob/0059007b0239bc8264249684a4ee4545ee4a61d2/condor_history_to_elasticsearch.py#L454

Sorry, I meant lines in condor history file.


Data isn't served from the docker container.

I can get the json-server working on my local machine but not from docker. I don't know what gives.
docker-compose.yaml:
version: "3.9"
services:
  app:
    build: .
    ports:
      - "3200:8080"
      - "3201:3000"
    volumes:
      - .:/app
    environment:
      - CHOKIDAR_USEPOLLING=true

Dockerfile:
FROM node:lts-alpine
WORKDIR /app
COPY package*.json ./
RUN npm install
RUN npm install @vue/cli -g
COPY . .
EXPOSE 8080
EXPOSE 3000
CMD ["npm", "run", "dev"]

package.json:
{
...
  "scripts": {
    "serve": "vue-cli-service serve",
    "build": "vue-cli-service build",
    "lint": "vue-cli-service lint",
    "server": "json-server --watch ./db.json --port 3204",
    "generate": "node ./src/database_faker/index.js > ./db.json",
    "dev": "npm run serve & npm run server"
  },
  "dependencies": {
    "autoprefixer": "^9",
    "axios": "^0.24.0",
  },
  "devDependencies": {
    "@vue/cli-plugin-babel": "~4.5.0",
    "@vue/cli-plugin-eslint": "~4.5.0",
    "@vue/cli-service": "~4.5.0",
    "@vue/compiler-sfc": "^3.0.0",
    "json-server": "^0.17.0",
...
  },
...
}

Sample from db.json:
{
    "books": [
        {
          "id": 1,
          "title": "Human Data Agent",
          "author": "Paula Stamm"
        },
        {
          "id": 2,
          "title": "Forward Data Developer",
          "author": "Joanna Kshlerin"
        }
    ]
}

The data in the db.json appears on the browser when the server is running on the local machine but not when it is running on the container with an exposed port. The default 3000 port is mapped to 3201.
Any help is greatly appreciated.

Please add the --host option to make it accessible from inside a docker container.  I tried this in a docker-compose yaml and it worked. Got this from 1009
json-server --watch ./db.json --port 3204 --host <IP_ADDRESS>


Add Summary column to fsoc optimize events

Description

add Summary column to fsoc optimize events
exclude OptimizerId column from fsoc optimize events when specified as a parameter
add Table struct member DisableAutoWrapText to get more output on a single line

Type of Change

[ ] Bug Fix
[x] New Feature
[ ] Breaking Change
[ ] Refactor
[ ] Documentation
[ ] Other (please describe)

Checklist

[ ] I have read the contributing guidelines
[ ] Existing issues have been referenced (where applicable)
[ ] I have verified this change is not present in other open pull requests
[ ] Functionality is documented
[ ] All code style checks pass
[ ] New code contribution is covered by automated tests
[ ] All new and existing tests pass

Codecov Report

Merging #233 (5ecd444) into main (2ae141b) will decrease coverage by 0.02%.
The diff coverage is 0.00%.

:exclamation: Your organization needs to install the Codecov GitHub app to enable full functionality.
@@            Coverage Diff             @@
##             main     #233      +/-   ##
==========================================
- Coverage   27.46%   27.44%   -0.02%
==========================================
  Files          43       43
  Lines        4468     4471       +3
==========================================
  Hits         1227     1227
- Misses       3149     3151       +2
- Partials       92       93       +1

Files
Coverage Δ

output/output.go
16.37% <0.00%> (-0.18%)
:arrow_down:


Firefox: Keyboard support?

Would be great if GhostText could be activated from a keyboard shortcut on Firefox. Currently the options page just allows port configuration.
Ctrl-Shift-i could be a good default?

Duplicate of #113


Variable sorting doesn't handle displayOrder values of zero

displayOrder variable annotations of zero are valid and are loaded and served by the EDA back end:

However I believe that
SubSettingClient/index.ts
// !!MUTATION!! order variables in-place
function orderVariables(study: StudyMetadata) {
  for (const entity of preorder(
    study.rootEntity,
    (entity) => entity.children ?? []
  ))
    entity.variables.sort((var1, var2) => {
      if (var1.displayOrder && var2.displayOrder)
        return var1.displayOrder - var2.displayOrder;
      if (var1.displayOrder) return -1;
      if (var2.displayOrder) return 1;
      return var1.displayName < var2.displayName
        ? -1
        : var1.displayName > var2.displayName
        ? 1
        : 0;
    });
  return study;
}

Needs tests for varX.displayOrder changing to varX.displayOrder != null.
Then this protocol variable would be sorted to the top, as intended:

@bobular I have some concerns about making a change like this. Do you know if the value 0 is only used when specifically defined? Do we know every place that it's currently being used, and that this change will be good, or is it possible that this will change the order of variables in an undesirable way in some places?
Out of curiosity, why do we need to support a value of 0? Can't we just use 1, and add 1 to other values, if something needs to be given higher priority?

Why shouldn't sort order be from minus to positive infinity?

displayOrder annotations are made manually I think in most cases.  Do we really want the curator to have to add one to each when they could add a new one at 0, and later another one at -1, etc?

I'm convinced. Thanks!


Add lax.conv_general_dilated_patches

Conv-based approach, inspired originally by @jbcdnr (also thanks @blakehechtman for pointing out where to look!)

For API inspiration, NumPy is currently considering adding a "sliding window" generation function: https://github.com/numpy/numpy/pull/17394/files
It uses strides instead of convolutions, so it probably isn't directly suitable for JAX, but I do think the API is more intuitive (referring only to axes in the original image). It's also nice how it returns the patches in the indicated shape, rather than as 1D vectors. Is it possible to revise this API along these lines, while still retaining the flexibility/power?

Thanks for the suggestion Stephan,
I tried to make the API as close to lax.conv_general_dilated as possible, since I think (at least this was so in my case, when implementing locally-connected networks) there are cases when users would want to answer "what input patches are subject to the receptive field of a given CNN layer" (same as in https://www.tensorflow.org/api_docs/python/tf/image/extract_patches). In this case  going through a different API could be a bit tedious, and potentially wasteful since internally it would reduce back to a CNN call.
What if perhaps I rather move this function to something like lax.conv_general_dilated_patches, and then np.sliding_window_view view could be built on top of it later?

What if perhaps I rather move this function to something like lax.conv_general_dilated_patches, and then np.sliding_window_view view could be built on top of it later?

Sounds good to me! I really like this idea of separate low-level and high-level interfaces. It's a great fit for jax.lax vs jax.numpy (or jax.image).

Thanks, moved to lax!

Someone is going to have to remind me how our internal pulldowns from GitHub work (which is how we finalize merging PRs these days), but this looks good to me!

You'll need to rebase this PR on top of head: we moved some files around. Thanks!

rebased


Tests, Badges and Requests fix.

Changes Unknown when pulling 2a96cc6f534b3c64fa2e02c44f5d45c342c60ef4 on travis into ** on master**.


NoMethodError when using the :visible locator with element collections

A NoMethodError occurs when using the :visible locator with element collections:
browser.divs(visible: true).count
#=> C:/Ruby23/lib/ruby/gems/2.3.0/gems/watir-6.0.2/lib/watir/xpath_support.rb:5:in `escape': undefined method `include?' for true:TrueClass (NoMethodError)
#=>   from C:/Ruby23/lib/ruby/gems/2.3.0/gems/watir-6.0.2/lib/watir/locators/element/selector_builder/xpath.rb:48:in `equal_pair'
#=>   from C:/Ruby23/lib/ruby/gems/2.3.0/gems/watir-6.0.2/lib/watir/locators/element/selector_builder/xpath.rb:32:in `block in attribute_expression'
#=>   from C:/Ruby23/lib/ruby/gems/2.3.0/gems/watir-6.0.2/lib/watir/locators/element/selector_builder/xpath.rb:28:in `each'
#=>   from C:/Ruby23/lib/ruby/gems/2.3.0/gems/watir-6.0.2/lib/watir/locators/element/selector_builder/xpath.rb:28:in `map'
#=>   from C:/Ruby23/lib/ruby/gems/2.3.0/gems/watir-6.0.2/lib/watir/locators/element/selector_builder/xpath.rb:28:in `attribute_expression'
#=>   from C:/Ruby23/lib/ruby/gems/2.3.0/gems/watir-6.0.2/lib/watir/locators/element/selector_builder/xpath.rb:18:in `build'
#=>   from C:/Ruby23/lib/ruby/gems/2.3.0/gems/watir-6.0.2/lib/watir/locators/element/selector_builder.rb:122:in `build_xpath'
#=>   from C:/Ruby23/lib/ruby/gems/2.3.0/gems/watir-6.0.2/lib/watir/locators/element/selector_builder.rb:103:in `build_wd_selector'
#=>   from C:/Ruby23/lib/ruby/gems/2.3.0/gems/watir-6.0.2/lib/watir/locators/element/selector_builder.rb:49:in `build'
#=>   from C:/Ruby23/lib/ruby/gems/2.3.0/gems/watir-6.0.2/lib/watir/locators/element/locator.rb:140:in `find_all_by_multiple'
#=>   from C:/Ruby23/lib/ruby/gems/2.3.0/gems/watir-6.0.2/lib/watir/locators/element/locator.rb:60:in `locate_all'
#=>   from C:/Ruby23/lib/ruby/gems/2.3.0/gems/watir-6.0.2/lib/watir/element_collection.rb:98:in `elements'
#=>   from C:/Ruby23/lib/ruby/gems/2.3.0/gems/watir-6.0.2/lib/watir/element_collection.rb:84:in `to_a'
#=>   from C:/Ruby23/lib/ruby/gems/2.3.0/gems/watir-6.0.2/lib/watir/element_collection.rb:28:in `each'
#=>   from watir-webdriver.rb:98:in `count'
#=>   from watir-webdriver.rb:98:in `<main>'

Ideally, we should be able to use the locator. If we do not want to support it, we should raise an ArgumentError like we do for the :index locator.

Yes, agreed; I'll take a look at it.

merged - a6d71bb
will be available in the next release.


Proper lookup of collection

Description:
Readded looking for the collection in dlite storages which for some strange reasons was removed.
Type of change:

[x] Bug fix.
[ ] New feature.
[ ] Documentation update.

Checklist for the reviewer:

This checklist should be used as a help for the reviewer.

[ ] Is the change limited to one issue?
[ ] Does this PR close the issue?
[ ] Is the code easy to read and understand, including clearly named variables?
[ ] Do all new feature have an accompanying new test?
[ ] Has the documentation been updated as necessary?

Codecov Report
Patch coverage: 61.53% and project coverage change: -0.67 :warning:

Comparison is base (127ca43) 67.32% compared to head (7a40b54) 66.66%.

:exclamation: Your organization is not using the GitHub App Integration. As a result you may experience degraded service beginning May 15th. Please install the Github App Integration for your organization. Read more.
Additional details and impacted files
@@            Coverage Diff             @@
##           master     #145      +/-   ##
==========================================
- Coverage   67.32%   66.66%   -0.67%
==========================================
  Files          14       14
  Lines         352      357       +5
==========================================
+ Hits          237      238       +1
- Misses        115      119       +4

Flag
Coverage Δ

linux
66.66% <61.53%> (-0.67%)
:arrow_down:

windows
?

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files
Coverage Δ

oteapi_dlite/utils/utils.py
69.81% <58.33%> (-5.19%)
:arrow_down:

oteapi_dlite/strategies/parse_excel.py
89.85% <100.00%> (ø)

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Do you have feedback about the report comment? Let us know in this issue.

Can you add a unit test that checks for this behavior? This will also prevent it from being 'strangely removed' again in the future :)


Please add support export Godot Game to Android AAR file for AD SDK integrate.

Godot version:
3.1
OS/device including version:
Android
Issue description:
Please add support export Godot Game to Android AAR file.
Some custom AD SDK must done by other sdk's department, and modify frequency.
if godot cannot export to aar file, The integrate AD SDK task must be done by Game Program Engineer.
It's waste time for Game Program Engineer.

When I  program with Libgdx.
I can proguard code and export core project to a jar, named game.jar .
this jar can send to a android engineer to integrate AD SDK and export to Android APK.
They can integrate many AD SDKs, and can export to many APKs with  different market version .

@m4gr3d Did #31919 solve this issue?

@akien-mga yes it does.
Running the following command will generate an Godot aar archive file in the platform/android/java/lib/build/outputs/aar directory:
cd platform/android/java
./gradlew :lib:build


OTLP Exporter for Logs

Our current OTLP exporter is set up to exclusively send traces. This issue will either adapt current exporters or create a new, temporary exporter to send logs over OTLP. Support for HTTP will likely come first, followed by gRPC.

Hey @kaylareopelle, do you know where this project is at? Just curious when we might get to use a more generalized logging exporter. Thanks.

Hi @travisbell thanks for checking in! Apologies about the delay here.
There is an unreviewed OTLP logs exporter, along with other code to make Ruby spec-compliant for the Logs signal, available in this PR on my fork: https://github.com/kaylareopelle/opentelemetry-ruby/pull/6
The current process is to release small parts of this code to the main opentelemetry-ruby repository for review, and then revise the WIP branch as needed. I don't have a good sense of when all those code will be merged into main.
If you'd like to test out the WIP logs implementation, you can follow the instructions in this gist: https://gist.github.com/kaylareopelle/76079747c1a7528449670b8bd1c78893
I also have a demo repository that integrates OpenTelemetry logs into a small Rails application: https://github.com/kaylareopelle/otel_ruby_logs_demo
I'm updating the branches about once a week to stay in sync with the latest changes upstream.
If you decide to give this experimental code a try, please let me know how it goes. You can comment here, open an issue on the demo repo, or add a comment to the gist.

WIP, unreviewed code for this issue, along with other parts of the logs SDK, can be found in https://github.com/kaylareopelle/opentelemetry-ruby/pull/6

What progress has been made and what else remains to be done?  We would like to use this for logging from our ruby code.

Hi @cidemaxio! Thanks for reaching out. It's great to hear you'd like to use OTel Ruby logs.
Here's the project board for the Logs signal that tracks what remains to be done. I have a draft PR for the OTLP exporter on my fork with a todo list in the description for work to do before opening the PR in the main repo.
There is at least one other PR that needs to be opened for the SDK/API regarding configuration and instrument registries. After both that PR and https://github.com/open-telemetry/opentelemetry-ruby/pull/1696 are merged, we should be ready to release the logs SDK, API and OTLP exporter gems.

Hi, @cidemaxio! PR is now opened for the OTLP Log Record Exporter: #1727
Please take a look if you're interested! Additional feedback from the community may help speed up the process to merge/release the gem.
The other PR related to the SDK/API I mentioned in my last comment has been opened too: #1725

Thanks for the update @kaylareopelle!  We will look at that PR.

@kaylareopelle both PRs seem to have conflicts.  Could you bring them up to date with main if you have a chance?

Thank you, @wsmoak! The merge conflicts have been resolved 😄

This is fantastic news. Thanks for testing, @wsmoak!
Where did you find the docker run command? I'm wondering if there's a place we could update the documentation to include your port finding.
It's a bit off-topic for this issue, but if you're interested in trialing a Ruby Logger bridge to automatically emit your Rails logs as OpenTelemetry Logs, you can pull in the branch on this PR: https://github.com/open-telemetry/opentelemetry-ruby-contrib/pull/983
This is intended for the standard Ruby Logger class. If you're using semantic logger, there's a prototype here: https://github.com/reidmorrison/semantic_logger/pull/292

The docker run command I mentioned is the one in the otel collector quickstart:   https://opentelemetry.io/docs/collector/quick-start/ -> step 3
I had that running, but when I started the Rails app, it complained that it couldn't export logs. Could this error have more details about where it was trying to send them?
E, [2024-10-17T18:47:03.126824 #86414] ERROR -- : OpenTelemetry error: Unable to export 3 log records
I eventually sorted out that the Ruby SDK was speaking HTTP and I nothing was listening on 4318 in the collector.
(And I did see it wrapping the Rails logs already, I think I picked up the contrib gem from your otel_ruby_logs_demo Rails example.) Thanks!

Hi @wsmoak, I updated the OTLP log exporter to log an OpenTelemetry error with more detail whenever it returns a FAILURE status code. Could you give it a try and let me know if that information would have helped debug the connection problem you encountered?
Here's the commit that introduced the logging: abfcd5466902b1eb21b4a3b4e8519fec10d5f0ab

Hi @marcelaraujo! Thank you for the reminder! I'm in the process of updating the branch with the latest changes. There are a few discrepancies I want to take a closer look on and a few more tests I want to run. I'm not certain if the latest push works. I'll add a comment here when it's ready to go.

Hi @kaylareopelle again,
I pulled your demo repo, installed the deps and tried to run the Rails
 /usr/local/bundle/bundler/gems/opentelemetry-ruby-contrib-d00bc1da07fe/instrumentation/logger/lib/opentelemetry/instrumentation/logger/instrumentation.rb:22:in `<class:Instrumentation>': uninitialized constant OpenTelemetry::Instrumentation::Logger::VERSION (NameError)

        option :version, default: OpenTelemetry::Instrumentation::Logger::VERSION, validate: :string

Hi @marcelaraujo! The branch is updated and ready for use. 🚀

The folder exporter/otlp-logs/*.gemspec is missing.

Hi @marcelaraujo. My apologies, I should've mentioned this in my earlier comment.
To use experimental logs, we no longer need to install opentelemetry-exporter-otlp from the branch source. I had a few problems with versioning when I initially copied the OTLP traces exporter to build the OTLP logs exporter.
If you'd like to export traces, I recommend installing the latest version of opentelemetry-exporter-otlp from RubyGems. Do   not install it from my fork.
# OTLP Exporters with logging enhancements
+ gem 'opentelemetry-exporter-otlp'
- gem 'opentelemetry-exporter-otlp',
-   git: 'https://github.com/kaylareopelle/opentelemetry-ruby',
-   branch: 'log-record-processor3',
-   glob: 'exporter/otlp/*.gemspec'

I'll update my gist to stop installing opentelemetry-exporter-otlp from my fork.
If you install the gem from source and still run into this problem, let me know. Something else may be going on.

@marcelaraujo - Something else was going on with the OTLP exporter. 🤦
The namespaces for the OTLP exporter for traces and the OTLP exporter for logs collided because they both had the same constant. I've updated the OTLP log exporter now to have its own unique namespace: OpenTelemetry::Exporter::OTLP::Logs. This follows the pattern we implemented for metrics. You can find the full discussion here.
This fix is now part of the log-record-processor3 branch on my fork.


fix(compile): compile source code on windows os

hotfix to compile source code on windows
this issue is related to https://github.com/BuilderIO/qwik/issues/2515

Thanks @leifermendez !
LGTM
@adamdbradley WDYT?


Python: allow more options for FunctionCallContent constructor

Motivation and Context

Fix #6932
Added ability to supply function_name and plugin_name as well as name (name keeps precedence)
Added ability to supply arguments as a dict, instead of string.
Description

Contribution Checklist

[x] The code builds clean without any errors or warnings
[x] The PR follows the SK Contribution Guidelines and the pre-submission formatting script raises no violations
[x] All unit tests pass, and I have added new tests where possible
[x] I didn't break anyone :smile:

Python 3.10 Test Coverage Report • FileStmtsMissCoverMissingsemantic_kernel/contents   function_call_content.py82791%49, 56, 58, 69, 71, 73, 122TOTAL664575989%
Python 3.10 Unit Test Overview

Tests
Skipped
Failures
Errors
Time

1575
1 :zzz:
0 :x:
0 :fire:
25.475s :stopwatch:


react-equal-height/clean doesn't work on NextJS app router

Hi, thanks for amazing work, I've used your library on several projects now.
There's a problem with building NextJS app with new app router (I didn't try this on pages router, so I don't know if it's limited to app router):
error node_modules/react-equal-height/index.js (1:8585) @ e.exports [as insertStyleElement]
error ReferenceError: document is not defined

I cloned the library and narrowed down the issue. When I'm importing <EqualHeightElement /> from react-equal-height/clean it seems like that component imports context from the main package and thus trying to inject css styles. Then it fails on ssr, because document is undefined.
I just copied the EqualHeightElement component and changed import to:
import { EqualHeightContext } from 'react-equal-height/clean';

and it worked

Thanks for sharing, I can confirm that I experience the same issue when using the pages router with Next v13.

Hi, sorry for the long reaction time.
Fixed in new version v1.3.0 and published NPM


Fix serviceclass to serviceclasses

This PR is a

[ ] Feature Implementation
[ ] Bug Fix
[x] Documentation

Fix serviceclass to serviceclasses

/ok-to-test

/lgtm
/approve


Support D&D between staged changes and changes

Testing #183587
Now that we have D&D would be cool to support that scenario as well.

I believe this requires implementing this method for when the targetElement is an SCM resource group https://github.com/microsoft/vscode/blob/cea7c824a5430f5fff7e474ed455308847a702c6/src/vs/workbench/contrib/scm/browser/scmViewPane.ts#L279-L280

Closing as duplicate of https://github.com/microsoft/vscode/issues/152250.


Issues with test_seesr_turbo with solutions

Great work on this - lots of improvements - this is a great, and memory efficient approach.
when I navigate to the sd-turbo model using the provided link there is no feature_extractor. I used the sd 2.1 feature extractor.
I think the below is a bug? Seems to be looking for unet in two places. I assume the correct path is  args.seesr_model_path?
unet = UNet2DConditionModel.from_pretrained_orig(args.pretrained_model_path, args.seesr_model_path, subfolder="unet", use_image_cross_attention=True)

Hello, Your handling of the feature_extractor is necessary, but kindly remind you that seesr is based on sd2-base, not sd2-1. This has already been corrected in the README.
Please put the pretrained sd-turbo model into args.pretrained_model_path and put the seesr model into args.seesr_model_path.
The former provides pretrained unet, and the latter provides the soft prompt cross attention modules.

Delete args.pretrained_model_path in unet = UNet2DConditionModel.from_pretrained_orig(args.pretrained_model_path, args.seesr_model_path, subfolder="unet", use_image_cross_attention=True)


JumpCloud now has an Identity Connector for Github Enterprise Cloud SCIM

Code of Conduct

[X] I have read and agree to the GitHub Docs project's Code of Conduct

What article on docs.github.com is affected?
https://docs.github.com/en/enterprise-cloud@latest/organizations/managing-saml-single-sign-on-for-your-organization/about-scim-for-organizations#supported-identity-providers
JumpCloud isn't shown as a supported IdP for SCIM under the title "Supported identity providers"
What changes are you suggesting?
JumpCloud has support to do the SCIM Provision/ Deprovision via their Identity Connectors functionality.
https://support.jumpcloud.com/s/article/Identity-Management-with-GitHub
Additional information
No response

@elliotnichols Thank you for opening an issue and linking it to your PR! ✨


Cannot download pywinauto_recorder.exe from website / cannot run pywinautorecorder.py

I was hopeful to use this tool to automate some of the more manual tasks that I have as a part of my job.  When I attempted to download the 'pywinauto_recorder.exe' from your website https://pywinauto-recorder.readthedocs.io/en/latest/ either it would download itself over and over on Chrome and Edge or display with a 'failed' download state in firefox.  I then downloaded and attempted to run the 'pywinautorecorder.py' file but received an error when trying to run the file saying that main was not found.  I have attached two screenshots.  Hopefully this correctly conveys my issue.  Please let me know if you need any further information.

Hi @josephbarsness,
I did not notice any problem with 'pywinauto_recorder.exe', I was able to download, install and run it.
To run the Python code, try:
python.exe .\pywinauto_recorder.py

Thank you @beuaaa for your response and looking into this issue.  Clearly it is user error on my end.

@beuaaa The official exe download link on doc page now return 404, can you recheck please?

You're right @Ben-Mack , the download link no longer works.
I need to find a reliable host and update the link.
Can you recommend a free host?

I usually see other repo provide exe file in Release page, in the Assets toggle of each release: https://github.com/beuaaa/pywinauto_recorder/releases

You're right, it's a good solution. That's what I'll do. I'll get the download link and update it in the documentation.
I'll do that tomorrow if I can find the time. I'll keep you posted.


训练出错但没有报错信息

按照readme里的步骤来的，只把模型换成了llama-2-70B。
输出：
Training Epoch: 0 / 1     0% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ -- it./s 0:00:00 / -:--:--
Training Batch: 0 / 157   0% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ -- it./s 0:00:00 / -:--:--  /usr/local/lib/python3.10/dist-packages/torch/utils/checkpoint.py:426: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/usr/local/lib/python3.10/dist-packages/torch/utils/checkpoint.py:426: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/usr/local/lib/python3.10/dist-packages/torch/utils/checkpoint.py:426: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
/usr/local/lib/python3.10/dist-packages/torch/utils/checkpoint.py:426: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly.
The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use
use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
Training Epoch: 0 / 1     0% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ -- it./s 0:00:07 / -:--:--
Training Batch: 0 / 157   0% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ -- it./s 0:00:07 / -:--:--  [2023-08-08 03:08:43,774] torch.distributed.elastic.multiprocessing.api: [ERROR] failed (exitcode: -7) local_rank: 0 (pid: 51194) of binary: /usr/bin/python3
Traceback (most recent call last):
  File "/usr/local/bin/torchrun", line 33, in <module>
    sys.exit(load_entry_point('torch==2.1.0.dev20230725+cu121', 'console_scripts', 'torchrun')())
  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 346, in wrapper
    return f(*args, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/run.py", line 797, in main
    run(args)
  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/run.py", line 788, in run
    elastic_launch(
  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/launcher/api.py", line 134, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/launcher/api.py", line 264, in launch_agent
    raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
=====================================================
collie.py FAILED
-----------------------------------------------------
Failures:
[1]:
  time      : 2023-08-08_03:08:43
  host      : 58283303bbb0
  rank      : 1 (local_rank: 1)
  exitcode  : -7 (pid: 51195)
  error_file: <N/A>
  traceback : Signal 7 (SIGBUS) received by PID 51195
[2]:
  time      : 2023-08-08_03:08:43
  host      : 58283303bbb0
  rank      : 2 (local_rank: 2)
  exitcode  : -7 (pid: 51196)
  error_file: <N/A>
  traceback : Signal 7 (SIGBUS) received by PID 51196
[3]:
  time      : 2023-08-08_03:08:43
  host      : 58283303bbb0
  rank      : 3 (local_rank: 3)
  exitcode  : -7 (pid: 51197)
  error_file: <N/A>
  traceback : Signal 7 (SIGBUS) received by PID 51197
-----------------------------------------------------
Root Cause (first observed failure):
[0]:
  time      : 2023-08-08_03:08:43
  host      : 58283303bbb0
  rank      : 0 (local_rank: 0)
  exitcode  : -7 (pid: 51194)
  error_file: <N/A>
  traceback : Signal 7 (SIGBUS) received by PID 51194
=====================================================

重启容器之后恢复正常。
再次重启之后换成8卡 CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 torchrun --rdzv_backend=c10d --rdzv_endpoint=localhost:29402 --nnodes=1 --nproc_per_node=8
输出：
Training Epoch: 0 / 1    0% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ -- it./s 0:00:00 / -:--:--
Training Batch: 0 / 79   0% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ -- it./s 0:00:00 / -:--:--  /usr/local/lib/python3.10/dist-packages/torch/utils/checkpoint.py:426: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/usr/local/lib/python3.10/dist-packages/torch/utils/checkpoint.py:426: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/usr/local/lib/python3.10/dist-packages/torch/utils/checkpoint.py:426: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/usr/local/lib/python3.10/dist-packages/torch/utils/checkpoint.py:426: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/usr/local/lib/python3.10/dist-packages/torch/utils/checkpoint.py:426: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/usr/local/lib/python3.10/dist-packages/torch/utils/checkpoint.py:426: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/usr/local/lib/python3.10/dist-packages/torch/utils/checkpoint.py:426: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
/usr/local/lib/python3.10/dist-packages/torch/utils/checkpoint.py:426: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly.
The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use
use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
Training Epoch: 0 / 1    0% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ -- it./s 0:00:13 / -:--:--
Training Batch: 0 / 79   0% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ -- it./s 0:00:13 / -:--:--  [2023-08-08 03:20:09,633] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 96 closing signal SIGTERM
[2023-08-08 03:20:09,639] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 98 closing signal SIGTERM
[2023-08-08 03:20:09,641] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 99 closing signal SIGTERM
[2023-08-08 03:20:09,643] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 100 closing signal SIGTERM
[2023-08-08 03:20:09,645] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 101 closing signal SIGTERM
[2023-08-08 03:20:09,648] torch.distributed.elastic.multiprocessing.api: [WARNING] Sending process 102 closing signal SIGTERM
[2023-08-08 03:20:11,395] torch.distributed.elastic.multiprocessing.api: [ERROR] failed (exitcode: -7) local_rank: 0 (pid: 95) of binary: /usr/bin/python3
Traceback (most recent call last):
  File "/usr/local/bin/torchrun", line 33, in <module>
    sys.exit(load_entry_point('torch==2.1.0.dev20230725+cu121', 'console_scripts', 'torchrun')())
  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 346, in wrapper
    return f(*args, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/run.py", line 797, in main
    run(args)
  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/run.py", line 788, in run
    elastic_launch(
  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/launcher/api.py", line 134, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/launcher/api.py", line 264, in launch_agent
    raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
==================================================
collie.py FAILED
--------------------------------------------------
Failures:
[1]:
  time      : 2023-08-08_03:20:09
  host      : 06a78451e09d
  rank      : 2 (local_rank: 2)
  exitcode  : -7 (pid: 97)
  error_file: <N/A>
  traceback : Signal 7 (SIGBUS) received by PID 97
--------------------------------------------------
Root Cause (first observed failure):
[0]:
  time      : 2023-08-08_03:20:09
  host      : 06a78451e09d
  rank      : 0 (local_rank: 0)
  exitcode  : -7 (pid: 95)
  error_file: <N/A>
  traceback : Signal 7 (SIGBUS) received by PID 95
==================================================

请问这种情况应该如何debug呢……

你好， 感谢你的反馈，我们会优化一下训练过程中的报错。 目前可以尝试用try catch包一下trainer.train()，比如
try:
    trainer.train()
except BaseException as e:
    import sys
    import traceback
    from rich.console import Console
    file = open("./traceback.log", 'a+')
    sys.stdout = file
    traceback.print_exc(file=file)
    file.write("\n\n")
    Console().print_exception()
    raise e

感谢回复！
用try catch之后也没有任何报错信息。
又搜了一下好像是deepspeed的问题。或者说是docker设置的问题。
解决方法在这里：
https://github.com/microsoft/DeepSpeed/issues/4002


Feature: binary release assets

I did this primarily for Linux, but it's pretty easy to have it build one for macOS too, so I went ahead and did that.
Also contains a fix for the homebrew formula & bottle update actions to not run on pre-releases (which I could have sworn was how it was behaving before, but not now! 🤷♂).

perfect ty, will pull this in on https://github.com/quorumcontrol/dgit-github-action


Add option to hide "More" button in main menu

Hey, I just got my first Kobo and I've been loving NickelMenu so far!
I'm not sure if this is already configurable - it looks like you gave it some thought in #78 - but I was wondering if you could add a way to hide the "More" button from the tab select in the main menu. It's just kind of redundant with NM installed, seeing as you can access everything it contains using nickel-open.
Thanks for your time!

Seconded! Maybe merge the two menus somehow?
Anyway, thanks for all your work!

For me (just got a Libra 2) I would prefer a config that allows me to move the the NickelMenu inside the More menu.
Since my current config only has items for non-main locations.

Same, it feels weird to have 2 hamburger menu at the bottom


Direct local .aar file dependencies are not supported when building an AAR.

I updated the following-
Gradle version from 5.4.1 to 6.5.1
Plugin version from 3.5.3 to 4.0.0
Kotlin version from 1.3.61 to 1.3.72
My Android Studio version is 4.0. After gradle sync the build failed with the below error.
Direct local .aar file dependencies are not supported when building an AAR
Expected Behavior

The build should not fail
Current Behavior

The build fails with the below error .
Direct local .aar file dependencies are not supported when building an AAR. The resulting AAR would be broken because the classes and Android resources from any local .aar file dependencies would not be packaged in the resulting AAR. Previous versions of the Android Gradle Plugin produce broken AARs in this case too (despite not throwing this error).
Context

Steps to Reproduce

Your Environment
Android Studio 4.0

Build scan URL:

Thank you for your interest in Gradle!
This is an issue with the Android Gradle Plugin which is developed by Google and cannot be addressed in the core of the Gradle Build Tool.
Please open such Android-related issues on the Android Issue Tracker at https://source.android.com/source/report-bugs


Readme: Installation instructions

"Ich bin grad zpatschert dafür..."
I downloaded GPT4ll recently and would like to try Zicklein with it, but unfortunately i'm a bit stumped on how to get it into GPT4all so i can try it.
It might be worth expanding the readme on that part?

I have not heard of GPT4all to be honest, but i'll look into it, sounds interesting!

Same for me, relatively new to all the stuff.
To explain gpt4all uses llama ggml q4_0 models in a single bin file.
Like: wizardlm-13b-v1.1-superhot-8k.ggmlv3.q4_0.bin
So we need a way to get the three models into one, thats what my zpatchert Hirn (smached brain) tells me.
From what i understood it's,
the base model: decapoda-research/llama-7b-hf
the stanford mod: tloen/alpaca-lora-7b
and the German mod: avocardio/alpaca-lora-7b-german-base-52k
but since im no developer i can't write a python-converter.py which does this for us and also i guess my hardware isn't able to fight it.
If it would, i guess running the generator.py would the correct way to get it.
Helping hands needed


Add LRU Cache program to classical_algorithms

I want to add LRU Cache program to leetcode folder with a sub-folder called hybrid. LRU problem is a very famous interview problem for product based companies. This problem needs concepts of linked-list and hash table so it needs to be added to a different folder.

Great @sr-sweta , I assigned this to you!

I wanna ask. Is this repo still considered for Hacktoberfest contribution?

@larissalages

yes, it is @sr-sweta


Year, month and week support added

I need to print duration as a year, month and week too,  I just add these features to your package and update the version, the changelog of the package. pub publish is enough 💯
I need these features so can you publish the new version of the package as soon as possible by the way, Would you consider adding me as an uploader to be able to upload new features?

Month is not always 30 days and year is not always 365 days. Anything above week cannot be computed accurately for generic durations.

@tejainece Yes, I know it but I just get the average values from google, this is not correct fully but it may be the optimum solution.


Estimate cluster instances and generate cost savings

This PR generates cost savings in user tools by estimating cluster shape (instances and count). It uses the cluster information json generated by the qualification core tool.
Usage and Output for EMR Platform:
CMD:
spark_rapids_user_tools emr qualification -t $TOOLS_JAR --eventlogs $HOME/Work/event-logs/emr-cpu

Cluster Information Json (from Core Tools):

[ {
  "appName" : "NDS - Power Run",
  "appId" : "application_1692643187882_0001",
  "eventLogPath" : "emr-cpu/application_1692643187882_0001",
  "clusterInfo" : {
    "coresPerExecutor" : 16,
    "numExecutorNodes" : 8
  }
} ]

Inferred Cluster (from User Tools):

INFO rapids.tools.qualification: Inferred Cluster => Driver: i3.2xlarge, Executor: 8 X m5d.4xlarge

Cost Savings:

Report Summary:
------------------------------  ------
Total applications                   1
RAPIDS candidates                    1
Overall estimated speedup         1.98
Overall estimated cost savings  35.46%
------------------------------  ------

Instance types conversions:
-----------  --  ------------
m5d.4xlarge  to  g4dn.4xlarge
-----------  --  ------------

Output for other platforms can be found here - Link
Estimation of Cluster Shape:

For EMR, Dataproc - Stores a map of cores -> instance type. Using the coresPerExecutor value from core tools, we get the instance type.
For Databricks - Instance types are already defined in the json output. Use them directly.
For each platform,:

store a default JSON which is same as the output while describing a cluster (eg for emr: aws describe-cluster --cluster-id <id>)
Populate this JSON from the cluster shape detected above.
Create an object of CPU cluster instance.
Rest of the flow remains same.

Limitation:
Currently estimation of only single cluster is supported in user tools. Supporting multiple cluster would require deeper design changes in user tools. We inform the user about this limitation in logging.

To confirm -- does this also work with the new CLI spark_rapids?  Your example shows legacy command spark_rapids_user_tools and I want to make sure it works fine with new CLI.

Yes, it works with the new CLI. Since 24.02 is not released yet, new CLI is failing due to some of the changes made during this release. Hence I am using the old CLI and passing my local jar.

Currently estimation of only single cluster is supported in user tools. Supporting multiple cluster would require deeper design changes in user tools. We inform the user about this limitation in logging.

The feature is not really complete until we make that change in the user_tools. With the current changes we can get away with it when we do 1 eventlog at a time.

@mattahrens
Are you okay with the PR getting merged? The limitation is that it only works if user-tools runs on a single eventlog. I opened a new issue #809 to do the remaining changes in uder-tools

Yes I'm fine with it going on as it does enable new functionality for single event-log runs.