[DO NOT MERGE]demo(atenlib): onnxscript API on torchscript

Fixes #273
Hack into evaluator and demo on using onnxscript API to complete torchscript (we will have our own graph to replace torchscript.)
works with https://github.com/pytorch/pytorch/pull/91930

Op object triggers graph_eval instead of eval to begin op insertion for the graph (Need to figure out how to keep both functionality if they need to stay on the same API.)
TorchscriptEvaluator serves as a manager of input/output graph. In this demo, both of them are torchscript, so this class seems simple (should be more complicated depending on ONNX graph builder API and format requirements).
tensor.py is not modified because onnxscript does not really use the graph value. That, is, it will only have to be compatible with graph builder type only in the future implementation.

Very nice! Do functions need special handling?

cc @xiaowuhu @fatcat-z

Very nice! Do functions need special handling?

In this DEMO, not really. Special handling depends on the future graph builder API. I guess the most effort would be on how to make a fake tensor from a given torch fake tensor (extract information from torch graph and create node in new graph). onnxscript API itself is more like an interface here, and not necessarily check or adapt the value format.

Replaced by https://github.com/microsoft/onnx-script/pull/336 to allow collaboration in the main repo. Closing this for now if you don't mind @titaiwangms


⚠ Bofrost.de has degraded performance

In 4ed0524, Bofrost.de (https://www.bofrost.de) experienced degraded performance:

HTTP code: 200
Response time: 1194 ms

Resolved: Bofrost.de performance has improved in 750056b after 6 minutes.


Merge Preview and Response Tab in Dev tools

Hi, I am wondering if what is the use of Response Tab in Dev tools. We mostly use the raw response to copy it or search for an item there.
We also have Preview tab to explore the response.  I understand that we can manually remove it. Can we just merge all these features in one tab?

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

ID: ee20453a-60c5-91b0-0e1c-4c0fd48de570
Version Independent ID: e61856a8-ad86-bed6-601f-69b69128f06c
Content: What's new in DevTools (Microsoft Edge 94) - Microsoft Edge Development
Content Source: microsoft-edge/devtools-guide-chromium/whats-new/2021/09/devtools.md
Product: microsoft-edge
Technology: devtools
GitHub Login: @MSEdgeTeam
Microsoft Alias: msedgedevrel

@chaurasiagovind - thanks for your suggestion. To ensure this gets routed to the Engineering team, can you use the following link to submit your feedback:
https://docs.microsoft.com/microsoft-edge/devtools-guide-chromium/contact#use-the-send-feedback-window
Thanks again.


Modal private methods unit tests

[x] _show
[x] _hide
[x] _startMove
[x] _stopMove
[x] _startResize
[x] _stopResize

Overall looks good :+1:


Remove meaningless dev and start scripts from buefy-next package

https://github.com/ntohq/buefy-next/blob/5c420e09933677691b004d437c7c7c684070b972/packages/buefy-next/package.json#L39-L40
We use docs package for development instead of buefy-next package.

Closed by #184.


Too many zk watchers created by Console

现状：
exec_num = e
job_num = j
console_watcher = 30j + 5e + 8je + 7
(1)
/$Jobs/<job_name>/config
(28)
/$Jobs/<job_name>/config/xxx
(8)
/$Jobs/<job_name>/servers/<server_name> /
/$Jobs/<job_name>/servers/<server_name> /processSuccessCount
/$Jobs/<job_name>/servers/<server_name> /processFailureCount
/$Jobs/<job_name>/servers/<server_name> /sharding
/$Jobs/<job_name>/servers/<server_name> /ip
/$Jobs/<job_name>/servers/<server_name> /jobversion
/$Jobs/<job_name>/servers/<server_name> /version
/$Jobs/<job_name>/servers/<server_name> /status
(1)
/vip.job.facm/$Jobs/<job_name>/servers/
(5)
/$SaturnExecutors/executors/<server_name>/
/$SaturnExecutors/executors/<server_name>/lastBeginTime
/$SaturnExecutors/executors/<server_name>/clean
/$SaturnExecutors/executors/<server_name>/ip
/$SaturnExecutors/executors/<server_name>/version
-- common  (7)--
/$SaturnExecutors/sharding
/$SaturnExecutors/sharding/content
/$SaturnExecutors/sharding/count
/$SaturnExecutors/leader
/$SaturnExecutors/leader/host
/$SaturnExecutors/leader/latch
/$SaturnExecutors/executors

改造方案：
针对 /$Jobs/<job_name>/config 的children节点，只保留2个：

/$Jobs/<job_name>/config/enabled
/$Jobs/<job_name>/config/forceshard

针对/$SaturnExecutors/executors/<server_name>/的children节点，只保留1个：

/$Jobs/<job_name>/servers/<server_name>/status

因此 当前的console_watcher=4j + 5e + je + 7


wails: 2.7.1 -> 2.8.0

Description of changes
Update Wails app builder to v2.8.0.
Changelog: https://github.com/wailsapp/wails/releases/tag/v2.8.0

Things done

Built on platform(s)

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

For non-Linux: Is sandboxing enabled in nix.conf? (See Nix manual)

[ ] sandbox = relaxed
[ ] sandbox = true

[ ] 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/)
24.05 Release Notes (or backporting 23.05 and 23.11 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

[x] Fits CONTRIBUTING.md.

Add a :+1: reaction to pull requests you find important.

This pull request has been mentioned on NixOS Discourse. There might be relevant details there:
https://discourse.nixos.org/t/pr-stuck-with-incomplete-ofborg-test-that-should-have-been-skipped/40276/1

This pull request has been mentioned on NixOS Discourse. There might be relevant details there:
https://discourse.nixos.org/t/prs-ready-for-review/3032/3525


Bedbase PEP schema in pephub

[x] Create the first version of input schema to bedboss  (PEP will be used in PEPhub)
[ ] Sample name will be a digest of the bedfile, and link will be derived

Steps:

Investigate what metadata we need, and what standards to use
Implement 3d party standards, which are right now in development

Useful information:
https://github.com/fairtracks/fairtracks_standard#overview-of-structure-of-the-fairtracks-standard
here's the full blueprint metadata: https://github.com/fairtracks/fairtracks_standard/tree/master/json/blueprint
alongside encode, we should also add all blueprint files to bedbase

Can the two of you solidify an initial first schema? Ideally just use the fairtracks standard, if it fits.

We have a minimal input schema already:
https://schema.databio.org/?namespace=pipelines&schema=bedboss
We are currently deciding on output schemas for Encode, Fairtracks and a Minimal Output Schema.

For Minimal Encode Input Schema we have narrowed it down from 59 columns found in the raw Encode Data to 20 columns:
File accession - experiment global ID
File type
File format type
Output type - make the header more specific
File assembly - genome / ref genome
Experiment accession - experiment sample ID
Assay - experiment protocol
Biosample term id
Biosample term name
Biosample type
Biosample organism
Biosample treatments
Biosample genetic modifications methods
Biosample genetic modifications categories
Biosample genetic modifications targets                    MAYBE will have to dump JSON and it will add more columns
Experiment target
Library made from - sample molecule (GEO), library source
Experiment date released
Project
File Download URL

After discussion, we have minimal output schema:
Minimal output schema:
- sample_name [Required]
- genome  [Required] (e.g. hg38)
- bed_type [Required] (e.g. bed3)
- format_type [Required] (e.g. narrowPeak)
- organism (e.g. Homo sapiens)
- species_id (e.g. 9606 )
- cell_type (e.g. K562)
- cell_line (e.g. C4-2B)
- exp_protocol (e.g. DNase-seq, TF ChIP-seq, histone ChIP-seq, ATAC-seq)
- library_source (e.g. genomic DNA, DNA-encode)
- target (e.g. H3K36me3)
- antibody (anti-H3K36me3)
- tissue (e.g blood / liver / brain)
- global_sample_id (e.g. "encode:ENCBS192PUU", "geo:GSM1234")
- global_experiment_id  "encode:ENC00000", "geo:GSE1234"
- description
- file_url [Required]
- file_name [Required]

Ok, can you use JSON-schema format? Add type, description, and required annotations

This is fairtrack outut schema for discussion:

Fairtrack schema:
- global_id: (e.g. encode:ENCBS13333)
- local_id: (e.g. fghjkjhgfdfghjhgfdfghj) [Required]
- species_id: (e.g. "taxonomy:9606") [Required] - identifiers.org (NCBI format)
- species_name: (e.g. Homo Sapiens)
- biospecimen_class: ????? (json_obj) [Required]
- Sample_type: [Required] - This is an object
  - cell_type: (e.g. K562)
  - abnormal_cell_type: (e.g.)
  - cell_line: (e.g. C4-2B)
  - organism_part: (e.g. liver)
- phenotype [Required]: Main phenotype (e.g. leukemia)

p.s. It's seems impossible to have all this items for each sample, as this info doesn't exist in each geo sample

Additional columns from experiment:
- technique [Required]: "Main technique used in experiment (e.g., laboratory, computational or statistical technique)" (We probably don't need that)
- target [Required]: "Main target of the experiment" (e.g. H3K4_trimethylation)
- study_reference [Required]:
- gene_id: HGNC identifier for gene targeted by the experiment (e.g., specific transcription factor used as ChIP-seq antibody).
- gene_product_type: Gene product type targeted by the experiment (e.g., miRNA)
- macromolecular_structure: Macromolecular structure targeted by the experiment (e.g., chromatin strucure)
- lab_protocol_description: "Free-text description of lab protocol, or URL to such description"
- compute_protocol_description: Free-text description of computational protocol, or URL to such description

Additional columns from track:
- assembly_id [Required]: Genome assembly identifier: "insdc.gca:GCF_000001405.26"
- assembly_name[Required]: Genome assembly name: "GRCh38"
- experiment_ref[Required]: Reference to the experiment of the track (e.g., "encode:ENCSR000DQP")
- file_url[Required]: URL to the file
- file_name: Name of the file (e.g., "ENCFF000VZC.bed.gz")
- label_short[Required]: A short label of the track file. Suggested maximum length is 25 characters
- label_long[Required]: A long label of the track file. Suggested maximum length is 80 characters
- file_format[Required]: File format (e.g., "bed", "narrowPeak", "broadPeak")
- type_of_condensed_data[Required]: (e.g. "Narrow peaks")
- geometric_track_type[Required]: (e.g. Segments)
- checksum[Required]: Method of checksum generation. (eg. MD5)

some of these are specific to a particular protocol; eg 'antibody' makes sense for ChIP-seq but not for ATAC-seq.
So that wouldn't really be 'minimal', it would be an extension of the schema specific to ChIP-seq

Required fields are minimal output schema

We should store standardize metadata that has schema in bedbase database,
but all other info in pephub


Update Readme, Docs, Migration Guide for 3.x.x simplified version

Readme was revised and cleaned, should be fine now


Use of jettech/kube-webhook-certgen if installed

when using a vanilla minikube and then I add the ingress addon
minikube addons enable ingress
    ▪ Using image us.gcr.io/k8s-artifacts-prod/ingress-nginx/controller:v0.40.2
    ▪ Using image jettech/kube-webhook-certgen:v1.2.2
    ▪ Using image jettech/kube-webhook-certgen:v1.3.0

It fetches jettech/kube-webhook-certgen so maybe it would be nice if devworkspace-operator could work with that mode as well without requiring cert-manager.

I'd love to abstract away how we get certs, but the issue we currently face is that the CRDs that get deployed to the cluster need certificates embedded in them, e.g. here. What we currently call the "kubernetes" deployment yaml is actually the "kubernetes + cert-manager" deployment yaml.
As far as I can tell, adding different options here would mean publishing different yaml files for each certificate provider (and also supporting it in the code, as well, potentially). It's not terribly hard though, so we could definitely go down that path if need be.


Player/camera shake and levitating when I enable a pack.

I'm a begginer of this mod (and also I'm not english, so sorry for possible grammar/vocab. errors), When I opened the menu and then I enabled a pack (without nothing), the player camera began to shake when I'm on ground. Also, when I fly, the player levitates up without doing anything, players can jump like the double as the normal and also walking and running speed is a little slow as it should be. (Important: I'm not using any mod, only optifine. And also, I'm using the 0.24 version for 1.12). If there's any solution for this issue, or it's just a bug, notice me. Thanks for reading.

Save and exit, then enter the world again. It's annoying but comes with an easy fix.

I actually found this to be an issue with optifine compatability. After installing the latest version of forge and optifine and mobends I finally got the issue to be fixed

Nice, someone close.

This was actually a long-running bug in Mo' Bends, but it's been fixed in the upcoming 1.0.0 version 🙂


Lot of CPU is being consumed when GIT OS Repository is opened in vscode

VSCode Version: Code - Insiders 1.11.0-insider (a35c7da7b8f324c1e8cc7830173418e392542f6d, 2017-03-28T12:46:15.098Z)
OS Version: Windows_NT ia32 10.0.15164
Extensions:

Extension
Author
Version

Go
lukehoban
0.6.55

cpptools
ms-vscode
0.10.5

csharp
ms-vscode
1.8.0

PowerShell
ms-vscode
0.11.0

resharper9-keybindings
ms-vscode
1.1.0

vscode-docker
PeterJausovec
0.0.13

Steps to Reproduce:

Close OS Git repo
Open the repo in vscode

You would see log of git status  process being forked out for every file in the repo. Machines becomes unusable for an hour. I had to reboot the machine to get it out of that state
I have disabled all git extensions. I believe the default Source Control Git integration is causing this.

What repository are you opening?

Fixed.


Malformed URL

I am getting an error when attempting to instantiate the database and reset the cache. Error is "Malformed URL".
Not sure what the issue with my URL is. I defined it in env.local.

Hi! Could you give me more information about your environment and how did you setup the app?
If you are using docker compose, it may be an issue from the database url, the defaults one needs to be changed.
At least the host needs to change from the default value "<IP_ADDRESS>", like this :
DATABASE_URL="postgresql://app:!ChangeMe!@waistline-api_postgres:5432/waistline?serverVersion=16&charset=utf8"
MONGODB_URL="mongodb://root:!ChangeMe!@waistline-api_mongodb:27017"

It could also come from your database password, if you have a special character in it, you may need to encode it.

That was the issue but now I am getting an error with connecting to postgresql server. Logs are below. I dont have any special characters in the postgres or mongodb passwords. should I change from scram-sha-256?
2024-02-28 16:06:07 2024-02-28 21:06:07.306 UTC [34] FATAL:  password authentication failed for user "app"
2024-02-28 16:06:07 2024-02-28 21:06:07.306 UTC [34] DETAIL:  Connection matched file "/var/lib/postgresql/data/pg_hba.conf" line 128: "host all all all scram-sha-256"

It may be because you changed the password after initializing the database, in this case you could delete the data folder and rerun docker compose up -d. It will recreate everything based on your new configuration.

I have rerun docker compose and still getting the same issue.

This seems to be a configuration issue and I will need more details to be able to help you, can you show me your docker-compose.yml ?

I have gotten it running but I don't think I have the APP_BASE_URL set up correctly. I got postgres runningby adjusting pg_hba.conf My docker-compose.yml is below. I can't access the API using the service address.
`version: '3.8'
services:
waistline-api:
image: waistline-api:latest
container_name: waistline-api
depends_on:
- postgres
- mongodb
volumes:
- .env.local:/var/www/html/.env.local
- ./data/log:/var/log/apache2/ #optional
ports:
- "8081:80"
healthcheck:
test: ["CMD-SHELL", "wget -q --tries=1 http://localhost:80/api/v1/health -O - | grep -Eo '"healthy"\s*:\s*true' || exit 1"]
interval: 60s
timeout: 10s
retries: 3
start_period: 40s
restart: unless-stopped
postgres:
image: postgres:16.1
container_name: waistline-api_postgres
environment:
POSTGRES_DB: 'waistline'
POSTGRES_USER: 'app'
POSTGRES_PASSWORD: ''
volumes:
- ./data/postgres:/var/lib/postgresql/data
restart: unless-stopped
mongodb:
image: mongo:7.0
container_name: waistline-api_mongodb
environment:
MONGO_INITDB_ROOT_USERNAME: 'root'
MONGO_INITDB_ROOT_PASSWORD: ''
volumes:
- ./data/mongodb:/data/db
restart: unless-stopped`

I tried your configuration where I just changed the image source to waistlineapi/waistline-api:latest and it works fine for me.
Here is the .env.local file I used :
APP_ENV=prod
APP_SECRET=03ed5a371f9306722ca7c1b9d22d92bd

DATABASE_URL="postgresql://app:password@waistline-api_postgres:5432/waistline?serverVersion=16&charset=utf8"

APP_BASE_URL="http://<IP_ADDRESS>:8081"
APP_REGISTER=true
API_DAILY_LIMIT=500
MONGODB_URL="mongodb://root:password@waistline-api_mongodb:27017"
MONGODB_NAME="waistline-api"

SENTRY_DSN=

Then I started the docker compose & initialized the db with:
docker compose up -d
docker exec -it waistline-api /bin/sh
php bin/console doctrine:migrations:migrate --quiet
php bin/console cache:clear --quiet
exit

Once the app was started, I went to http://<IP_ADDRESS>:8081/ where I could login/register and get my API Key.
To use the API, I used curl with this command:
curl 'http://<IP_ADDRESS>:8081/api/v1/stats' -H "Authorization: ApiKey 018df6a1-7e65-72b3-9fd6-2b7a698ccbaa"

And got this result:
{"pagination":{"limit":100,"offset":0,"total":0,"count":0},"results":[]}

Is your app deployed on a server? In this case do you use a reverse proxy to serve the app?
ps : In the config the APP_BASE_URL is not really important, it's just used in the dashboard to show the api url but if you put something wrong it will not affect the app.


Error with USE_LADE option

I have installed the requirements successfully, and have got the correct result when running minimal.py.
python minimal.py #no Lookahead decoding
USE_LADE=1 LOAD_LADE=1 python minimal.py #use Lookahead decoding, 1.6x speedup
But there is an error when chatting with chatbot.py bash setting USE_LADE=0
USE_LADE=0 python applications/chatbot.py  --model_path meta-llama/Llama-2-7b-chat-hf --debug --chat #chat, without lookahead
USE_LADE=0 python applications/chatbot.py  --model_path meta-llama/Llama-2-7b-chat-hf --debug #no chat, without lookahead
the log is as following
User: Which methods did Socrates employ to challenge the prevailing thoughts of his time?
Assistant: Traceback (most recent call last):
  File "/workspace/LookaheadDecoding/applications/chatbot.py", line 79, in <module>
    tmp_greedy_output = model.generate(input_ids=input_ids, **tmp_kwargs).tolist() #warmup
  File "/opt/conda/lib/python3.10/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/transformers/generation/utils.py", line 1718, in generate
    return self.greedy_search(
  File "/workspace/LookaheadDecoding/lade/decoding.py", line 26, in greedy_search_proxy
    return FUNC_MAP["greedy_search"](self, *args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/transformers/generation/utils.py", line 2579, in greedy_search
    outputs = self(
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "/workspace/LookaheadDecoding/lade/models/modeling_llama.py", line 1335, in forward
    outputs = self.model(
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
TypeError: _forward_unimplemented() got an unexpected keyword argument 'input_ids'`
/workspace/models/TinyLlama-1.1B-Chat-v1.0 --debug
User: Which methods did Socrates employ to challenge the prevailing thoughts of his time?
Assistant: Traceback (most recent call last):
  File "/workspace/LookaheadDecoding/applications/chatbot.py", line 79, in <module>
    tmp_greedy_output = model.generate(input_ids=input_ids, **tmp_kwargs).tolist() #warmup
  File "/opt/conda/lib/python3.10/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/transformers/generation/utils.py", line 1718, in generate
    return self.greedy_search(
  File "/workspace/LookaheadDecoding/lade/decoding.py", line 26, in greedy_search_proxy
    return FUNC_MAP["greedy_search"](self, *args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/transformers/generation/utils.py", line 2579, in greedy_search
    outputs = self(
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "/workspace/LookaheadDecoding/lade/models/modeling_llama.py", line 1335, in forward
    outputs = self.model(
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
TypeError: _forward_unimplemented() got an unexpected keyword argument 'input_ids'

Furthermore, I can get the correct result when setting USE_LADE=1
I installed the project on Ubuntu 20.04 system with A800 GPUs, with pytorch=1.13.1 and cuda=11.6.

I have the same problem. my environment is ubuntu 20.04 with RTX3090, cuda=12.4


Conda processes left running

@rchiodo - how would I find that info? I can provide just not sure what you mean exactly.
One thing I noticed that is slightly odd is that I choose my interpreter, it's a conda env, and it says "('arcgispro-py3-clone':conda)" in status bar of vscode which is correct...but then at some point it just switches, has the same interpreter path etc. and everything works, but no longer says (:conda), it says "Python 3,7,11 64-bit (system)" - I found that odd, not sure if it means anything.
Originally posted by @augaug in https://github.com/microsoft/vscode-jupyter/issues/1626#issuecomment-1105897320

Please provide the logs as mentioned in the issue template.

Output for Python in the Output panel (View→Output, change the drop-down the upper-right of the Output panel to Python)

XXX

This is very likely caused by https://github.com/conda/conda/issues/11420.

this is what I see after 'conda activate mycondaenv' in the terminal:
Experiment 'pythonaa' is active
Experiment 'pythonTensorboardExperiment' is active
Experiment 'PythonPyTorchProfiler' is active
Experiment 'pythonDeprecatePythonPath' is active
Experiment 'pythonInterpreterInfoPinned' is active

"C:\Program Files\ArcGIS\Pro\Bin\Python\Scripts\conda.exe" info --json
~\AppData\Local\ESRI\conda\envs\arcgispro-py3-clone\python.exe ~.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\get_output_via_markers.py ~.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\interpreterInfo.py
Python interpreter path: ~\AppData\Local\ESRI\conda\envs\arcgispro-py3-clone\python.exe
"C:\Program Files\ArcGIS\Pro\Bin\Python\Scripts\conda.exe" run -n base --no-capture-output --live-stream python ~.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\get_output_via_markers.py -c "import sys;print(sys.executable)"
Starting Pylance language server.
"C:\Program Files\ArcGIS\Pro\Bin\Python\Scripts\conda.exe" run -p  --no-capture-output --live-stream python ~.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\get_output_via_markers.py -c "import sys;print(sys.executable)"
[ERROR 2022-3-25 8:29:50.685]: Error in errorHandler.handleError [Error: Command failed: "C:\Program Files\ArcGIS\Pro\Bin\Python\Scripts\conda.exe" run -p  --no-capture-output --live-stream python c:\Users\maugust.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\get_output_via_markers.py -c "import sys;print(sys.executable)"
usage: conda.exe run [-h] [-n ENVIRONMENT | -p PATH] [-v] [--dev]
[--debug-wrapper-scripts] [--cwd CWD]
[--no-capture-output] [--live-stream]
...
conda.exe run: error: argument -p/--prefix: expected one argument

at ChildProcess.exithandler (node:child_process:406:12)
at ChildProcess.emit (node:events:390:28)
at maybeClose (node:internal/child_process:1064:16)
at Process.ChildProcess._handle.onexit (node:internal/child_process:301:5)] {

killed: false,
code: 2,
signal: null,
cmd: '"C:\Program Files\ArcGIS\Pro\Bin\Python\Scripts\conda.exe" run -p  --no-capture-output --live-stream python c:\Users\maugust\.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\get_output_via_markers.py -c "import sys;print(sys.executable)"'
}

Thanks for the logs, it looks like NodeJS is for some reason unable to kill the process, this should be reported on https://github.com/conda/conda/issues. It might get fixed by https://github.com/conda/conda/issues/11420 as well. What happens if you try to kill the process manually in VSCode terminal using the kill command?

I am also experincing this issue and I happened to notce that the the original submitter here is also using the conda environment provided by ESRI ArcGIS Pro.
I've collected some logs on my machine as well and things are looking very similar.

Output from Python extension
> conda info --json
> "C:\Program Files\ArcGIS\Pro\bin\Python\envs\arcgispro-py3\python.exe" ~\.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\get_output_via_markers.py ~\.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\interpreterInfo.py
> C:\Python310\python.exe ~\.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\get_output_via_markers.py ~\.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\interpreterInfo.py
Python interpreter path: C:\Program Files\ArcGIS\Pro\bin\Python\envs\arcgispro-py3\python.exe
> conda run -n arcgispro-py3 --no-capture-output --live-stream python ~\.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\get_output_via_markers.py ~/.vscode/extensions/ms-python.python-2022.4.1/pythonFiles/printEnvVariables.py
> conda run -n base --no-capture-output --live-stream python ~\.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\get_output_via_markers.py -c "import sys;print(sys.executable)"
Starting Pylance language server.
> conda run -n arcgispro-py3 --no-capture-output --live-stream python ~\.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\get_output_via_markers.py ~\.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\linter.py -m pylint .\bmi\__init__.py
cwd: .
[ERROR 2022-4-2 10:2:27.340]: getActivatedEnvironmentVariables [Error: Command failed: conda run -n arcgispro-py3 --no-capture-output --live-stream python l:\Users\philna\.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\get_output_via_markers.py l:/Users/philna/.vscode/extensions/ms-python.python-2022.4.1/pythonFiles/printEnvVariables.py

	at ChildProcess.exithandler (node:child_process:406:12)
	at ChildProcess.emit (node:events:390:28)
	at maybeClose (node:internal/child_process:1064:16)
	at Process.ChildProcess._handle.onexit (node:internal/child_process:301:5)] {
  killed: true,
  code: null,
  signal: 'SIGTERM',
  cmd: 'conda run -n arcgispro-py3 --no-capture-output --live-stream python l:\\Users\\philna\\.vscode\\extensions\\ms-python.python-2022.4.1\\pythonFiles\\get_output_via_markers.py l:/Users/philna/.vscode/extensions/ms-python.python-2022.4.1/pythonFiles/printEnvVariables.py'
}

I noticed here that the timestamp on the error message is off by 1 month - not sure where this coming from or if it's important. I'm guessing it's just an issue with converting a datetime to string, but thought I would mention it. My machine clock is correct.

Screenshot from Task Manager showing processes left running after closing VS Code

Command line args for the conda processes left running (as text)

conda run -n arcgispro-py3 python l:\Users\philna.vscode\extensions\ms-toolsai.jupyter-2022.3.1000901801\pythonFiles\printEnvVariablesToFile.py L:/Users/philna/AppData/Local/Temp/tmp-17116sCSfRRjS6hTR.json
conda  run -n arcgispro-py3 --no-capture-output --live-stream python l:\Users\philna.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\get_output_via_markers.py l:/Users/philna/.vscode/extensions/ms-python.python-2022.4.1/pythonFiles/printEnvVariables.py
conda  run -n base --no-capture-output --live-stream python l:\Users\philna.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\get_output_via_markers.py -c "import sys;print(sys.executable)"
conda  run -n arcgispro-py3 --no-capture-output --live-stream python l:\Users\philna.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\get_output_via_markers.py l:/Users/philna/.vscode/extensions/ms-python.python-2022.4.1/pythonFiles/printEnvVariables.py
conda  run -n base --no-capture-output --live-stream python l:\Users\philna.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\get_output_via_markers.py -c "import sys;print(sys.executable)"
conda run -n arcgispro-py3 --no-capture-output --live-stream python l:\Users\philna.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\get_output_via_markers.py l:\Users\philna.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\linter.py -m pylint l:\Users\philna\git_repos\BMI_Library\bmi_init_.py

Since  I thought it was odd that we are both seeing this issue while using an ArcGIS Python environment, I created a separate Miniconda environment with the same Python version. I still see this issue, but not with as many processes. It seems here it is able to find the conda environment variables, which seems to be failing in the ArcGIS environment.

Output from Python extension
> conda info --json
> c:\temp\testenv\python.exe ~\.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\get_output_via_markers.py ~\.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\interpreterInfo.py
> C:\Python310\python.exe ~\.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\get_output_via_markers.py ~\.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\interpreterInfo.py
Python interpreter path: c:\temp\testenv\python.exe
> conda run -p c:\temp\testenv --no-capture-output --live-stream python ~\.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\get_output_via_markers.py ~/.vscode/extensions/ms-python.python-2022.4.1/pythonFiles/printEnvVariables.py
> conda run -n base --no-capture-output --live-stream python ~\.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\get_output_via_markers.py -c "import sys;print(sys.executable)"
Starting Pylance language server.
> conda run -p c:\temp\testenv --no-capture-output --live-stream python ~\.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\get_output_via_markers.py ~\.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\linter.py -m pylint .\bmi\__init__.py
cwd: .

followed by actual linting output, which never gets generated when in the ArcGIS environment.

In this case, I still get orphan `conda.exe` processes after closing VSCode, however, there are only 2

conda  run -n base --no-capture-output --live-stream python l:\Users\philna.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\get_output_via_markers.py -c "import sys;print(sys.executable)"
conda  run -n base --no-capture-output --live-stream python l:\Users\philna.vscode\extensions\ms-python.python-2022.4.1\pythonFiles\get_output_via_markers.py -c "import sys;print(sys.executable)"

Let me know if any other info or troubleshooting steps would be helpful. I am affected by this daily and would be more than happy to help solve this in any way possible.

Wanted to point out another observation. While VS Code is running, the 2 conda.exe processes that are left running and consuming CPU are also constantly running under the VSCode parent process. The one is also constantly using ~20% (1 core on my machine) CPU, the other 0%, while VS Code is running. Even though Task Manager shows this process as being a child of the VS Code process, it does not die when VS Code exits, but rather is "moved" to the background processes section in Task Manager. They stick with the pattern of 1 process using one core, the other not using any CPU.

I believe I was able to resolve this issue by taking the conda.exe shipped with ArcGIS Pro fully out of the equation. It seems there is something "non standard" about this conda setup. I think the actual conda environments used by Pro are fine, this seems to be caused by the conda mechanism itself (it is non-standard, as some default directories like etc are missing).
Steps I took to resolve this:

Download and install a normal Anaconda version for the current Pro Python version. I used miniconda. Can be system or user install (I did a user-install).
Allow conda to add itself to the PATH environment variable.
Remove all references to Pro directories from the PATH variable, if there are any. Specifically want to make sure %PROGRAMFILES%\ArcGIS\Pro\bin\Python\Scripts is not in there, as this is the location of the ArcGIS Pro conda.exe
Run these commands in windows command prompt:

conda config --add envs_dirs %PROGRAMFILES%\ArcGIS\Pro\bin\Python\envs
conda config --add envs_dirs %LOCALAPPDATA%\Local\ESRI\conda\envs

Probably want to make sure python.condaPath is not populated in VSCode settings.json (was not in my case).
Run conda init for your shell(s) of choice.

End Result: Pro should continue using its own conda, while any other calls to conda (including from VS Code) will use the newly install standard conda. I am not seeing any more persistent conda.exe processes, they just stat up briefly and go away like they're supposed to probably.
@augaug I would be interested to see if you can follow these steps and if they would also resolve this in your environment.

@azinsharaf would you be able to try out the steps I outlined above and post here if that resolves this issue for you as well?

hi @philnagel I am afraid I can't test that workaround because I don't have necessary admin access to install Miniconda and change the PATH env var.
The workaround can give us a clue about the root of issue but to me it is not a solution since the users need to apply all of those changes to their machine.

Closing in favor of https://github.com/conda/conda/issues/11506 as this is an upstream issue.


The executable is closing if I try to type something in it

When I open up the executable, all I see is a blank screen, then if I try to type, it shows lots of white text for a split second and then closes. From what I can see my config file is set up correctly.

@epiclashy  add me on discord cyxl#9986

This should be fixed on V2. Reopen one if it's still an issue.


chore: support paste custom

close #3487

Pull Request Checklist

[ ] Related tickets or issues have been linked in the PR description (or missing issue).
[ ] Naming convention is followed (do please check it especially when you created new plugins, commands and resources).
[ ] Unit tests have been added for the changes (if applicable).
[ ] Breaking changes have been documented (or no breaking changes introduced in this PR).

如何测试？

设置 custom

const sheet = univerAPI.getActiveWorkbook().getActiveSheet();

const range = sheet.getRange(0, 0, 1, 1);
range.setValue({
  v: 'Hello, Univer',
  custom: {
      key: 'value',
  },
});

检验下当前 worksheet A1 单元格是否成功设置 custom

univer._univerInstanceService.getFocusedUnit()._snapshot

复制 A1 粘贴到 A2

检验下当前 worksheet A2 单元格是否成功设置 custom


Make example consistent

export is missing in the example, this is slightly confusing

hey! thanks for the PR, but I think adding export will actually make it more confusing not less :) if you look at codesanbox examples all of them are done without export


which version of habitat?

According the "File Setup" part, using the episode dataset will happen a wrong which can't distinguish the key "scene_dataset_config" in the [episode dataset].

I recommend running the code with the provided Docker image, which has all the habitat dependencies already installed. Are you able to use that?

Hello, Could you tell me how to use the ground-truth segmentation of MP3D and HM3D?
Bacause I meet another problem. When I change the '--use_gt_seg' paremeter to 1 in arguments.py, the 'info['goalseg'] = observations['goalseg']' in peanut_agent.py will throw 'keyError: 'goalseg'' .
What's more, When I use MP3D and output the semantic sensor result, I find semantic sensor perspective differ from RGB and depth sensors, but this three kinds of sensors are same state. Following is the result:

And when I use HM3D, I can't get segmentation from semantic sensor, although I have download the 'xxxx.semantic.glb' for scene datasets and add the 'SEMANTIC_SENSOR' in the yaml.
Thanks

In order to let Habitat load the semantic annotations, you need to set the SIMULATOR.SCENE_DATASET variable in the config. This can be done in your code, for example try adding this line
config.SIMULATOR.SCENE_DATASET = 'habitat-challenge-data/data/scene_datasets/hm3d/hm3d_annotated_basis.scene_dataset_config.json'
around here
https://github.com/ajzhai/PEANUT/blob/5fe8358bece89645f7651e524234f967215fa4ac/nav/collect.py#L26
You can also do this in the config yaml. Let me know if it works!

Thanks for your help.
But only setting config.SIMULATOR.SCENE_DATASET can't fit this problem in habitat-challenge enviroment (tags/challenge-2022), I have to delete self._config.SIMULATOR.SCENE_DATASET = (     self.current_episode.scene_dataset_config ) in habitat-lab/habitat/core/env.py of habitat-lab library so that I can solve this problem.


Linter rules for Navigator.method(..) vs Navigator.of(..).method()

Describe the rule you'd like to see implemented
Usually in flutter projects It's recommended to use one of the conventions for calling navigator methods:

Navigator.of(context).pop();
Navigator.pop(context);

I think it would be nice if dart had a linter to lint mix of 2 conventions. Because it's very easy to sometimes forget the project wide conventions or new members might not notice the convention.
only_use_navigator_of - Navigator methods should be accessed using Navigator.of(context).
only_use_navigator_static_methods - Navigator methods should be accessed using static methods of Navigator class.
PS: This is just a sample rule names came into my mind, could be changed with something much better.
Examples
BAD:
Navigator.of(context).push(MaterialRoute(          // uses Navigator.of convention
  builder: (context) => MyWidget(
    onClick: () => Navigator.pop(context);         // uses Navigator.method convention
  ),
));

GOOD:
Navigator.of(context).push(MaterialRoute(          // uses Navigator.of convention
  builder: (context) => MyWidget(
    onClick: () => Navigator.of(context).pop();    // uses Navigator.of convention
  ),
));

Additional context
A talk about Navigator by @slightfoot: https://youtu.be/4CYTTW6PMoc?t=486

Wow, I feel the ultimate cringe watching old videos of me 😅
I like the idea of a lint to stick to one convention over the other 👍


XML syntax highlighting does not highlight attributes (like HTML does)

XML doesn't color attributes and attribute values differently to tags.
SVG file using (default) XML highlighting:

SVG file using HTML highlighting:

Fixed by https://github.com/Microsoft/vscode/commit/c37cb211f1f2d6a9c53a96501ed3849ab4c2c1e3 (dupe of #23), just needed to sync from upstream.


load into Vec3r struct from ply

This adds loading into structs directly from ply-rs.
as per your suggestions from #1.
Couple of things:
You may want me to pull the ply stuff out into a submodule, which I can do.
I may not have been using the repr(transparent) properly, I still had to access the inner struct through .0, so I have left that commented out for now.
This has to map from Vec<Vec3r> to Vec<Vector3<R>> manually, so I'm not sure if I'm doing this right.

Any advice welcome...
Thanks!

Well, the trick is to use some unsafe code that we know is actually safe. When you annotate a type with #[repr(transparent)] this means that the new type is represented in memory exactly the same as the inner type. For details, see e.g. https://doc.rust-lang.org/1.26.2/unstable-book/language-features/repr-transparent.html. This allows us on one hand to implement traits and methods on the new type (like you did), but it also allows us to just view instances of the new type as instances of the inner type. This is done by transmuting  (like casting without conversion in other languages). In our case, this would be
// This is safe, because we defined Vec3r<R> as transparent over Vector3<R>
let particles = unsafe { std::mem::transmute::<Vec<Vec3r<R>>, Vec<Vector3<R>>>(particles_ply) };

(we could drop the explicit type arguments on transmute and let type-inference figure it out, but the explicit arguments ensure that we don't accidentally transmute to a wrong type when refactoring)
In the end, the transmute is a no-op and saves us copying and manually converting each individual element.
However, for this to work, your Vec3r definition is missing R: Real as generic argument, which should also be the type used by the Vector3 (because this is the type returned by the particles_from_ply function). So the type definition would be
#[repr(transparent)]
struct Vec3r<R: Real>(Vector3<R>);

and you would have to slightly adapt your trait implementation.
Do you want to make these changes?

Ah, and yes, it would probably make sense to modularize the IO stuff more (maybe move it to the lib) and add some unit tests with sample files, but I don't want to get into this right now.

Whoops, made a mistake. The unsafe code actually has to be
    // Convert the particle vector from `Vec<Vec3r<R>>` to `Vec<Vector3<R>>`
    let particles = unsafe {
        // Ensure the original vector is not dropped.
        let mut particles = std::mem::ManuallyDrop::new(particles);
        // Construct the new vector by casting the data pointer
        Vec::from_raw_parts(
            // This is safe, because we defined Vec3r<R> as transparent over Vector3<R>
            particles.as_mut_ptr() as *mut Vector3<R>,
            particles.len(),
            particles.capacity(),
        )
    };

because, you are only allowed to transmute/cast the actual data of the Rust Vec, not the Vec itself. See the Vec example here and the comment here.

OK, thanks. This makes sense now. I did read the repr(transparent) docs, but it was not clear what it was doing for us.
I will update to use this,
Thanks!

Hrm,
How about we leave it with the (non-idiomatic) approach for now?
I am thinking of solving this on the Ply-rs side, i.e. adding a data marshalling interface for when your types arent local (honestly most people will be using 3rd party structs for their 3d data?).
Cheers

Right, support for this in ply-rs itself would be much cleaner.
I'll add a few comments before merging.

Ok, I moved the file format stuff into submodules. You would have to move your changes into the ply_format module.

Hey,
I'll have a look at this soon, been moving around the last week, so it has been hard to get time at the computer..
Cheers!

No rush


[Questions]Which function service call can be used for get all this users image posts list?

Didn't find it from demos.

@alexliubj I believe you're looking for -[InstagramEngine getMediaForUser:withSuccess:failure:].


az cloud register should support configuring Microsoft Graph endpoint

Context
az cloud register currently has no way to configure Microsoft Graph endpoint:
$ az cloud register -h

Command
    az cloud register : Register a cloud.
        When registering a cloud, specify only the resource manager endpoint for the autodetection
        of other endpoints.

Arguments
    --name -n                                       [Required] : Name of a registered cloud.
    --cloud-config                                             : JSON encoded cloud configuration.
                                                                 Use @{file} to load from a file.
    --endpoint-active-directory                                : The Active Directory login
                                                                 endpoint.
    --endpoint-active-directory-data-lake-resource-id          : The Active Directory resource ID
                                                                 for data lake services.
    --endpoint-active-directory-graph-resource-id              : The Active Directory resource ID.
    --endpoint-active-directory-resource-id                    : The resource ID to obtain AD tokens
                                                                 for.
    --endpoint-gallery                                         : The template gallery endpoint.
    --endpoint-management                                      : The management service endpoint.
    --endpoint-resource-manager                                : The resource management endpoint.
    --endpoint-sql-management                                  : The sql server management endpoint.
    --endpoint-vm-image-alias-doc                              : The uri of the document which
                                                                 caches commonly used virtual
                                                                 machine images.
    --profile                                                  : Profile to use for this cloud.
                                                                 Allowed values: 2017-03-09-profile,
                                                                 2018-03-01-hybrid,
                                                                 2019-03-01-hybrid,
                                                                 2020-09-01-hybrid, latest.
    --suffix-acr-login-server-endpoint                         : The Azure Container Registry login
                                                                 server suffix.
    --suffix-azure-datalake-analytics-catalog-and-job-endpoint : The Data Lake analytics job and
                                                                 catalog service dns suffix.
    --suffix-azure-datalake-store-file-system-endpoint         : The Data Lake store filesystem
                                                                 service dns suffix.
    --suffix-keyvault-dns                                      : The Key Vault service dns suffix.
    --suffix-sql-server-hostname                               : The dns suffix for sql servers.
    --suffix-storage-endpoint                                  : The endpoint suffix for storage
                                                                 accounts.

This makes it impossible to use Microsoft Graph PPE endpoint https://graph.microsoft-ppe.com/ (https://github.com/Azure/azure-cli/issues/17209#issuecomment-791225010).
Proposed solution
az cloud register should support configuring Microsoft Graph endpoint with a parameter like --endpoint-microsoft-graph-resource-id, similar to --endpoint-active-directory-graph-resource-id.
Additional context
Currently, to use Azure Dogfood environment, the cloud should be registered with
az cloud register --name Dogfood --endpoint-active-directory-resource-id https://management.core.windows.net/ --endpoint-gallery https://df.gallery.azure-test.net/ --endpoint-resource-manager https://api-dogfood.resources.windows-int.net/ --endpoint-active-directory https://login.windows-ppe.net/ --endpoint-active-directory-graph-resource-id https://graph.ppe.windows.net/

# Line breaks for legibility
az cloud register
  --name Dogfood
  --endpoint-active-directory-resource-id https://management.core.windows.net/
  --endpoint-gallery https://df.gallery.azure-test.net/
  --endpoint-resource-manager https://api-dogfood.resources.windows-int.net/
  --endpoint-active-directory https://login.windows-ppe.net/
  --endpoint-active-directory-graph-resource-id https://graph.ppe.windows.net/

az cloud register refinement

@yonzhan @jiasli any plan to work on this feature? We need this feature for 'ARCA' custom cloud.
FYI @sarathys

I also need this to run ARC commands against DF endpoints


RuntimeError: CUDA error: no kernel image is available for execution on the device

Error:
RuntimeError: CUDA error: no kernel image is available for execution on the device
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
Compile with TORCH_USE_CUDA_DSA to enable device-side assertions.
nvcc -V
Copyright (c) 2005-2022 NVIDIA Corporation
Built on Tue_May__3_18:49:52_PDT_2022
Cuda compilation tools, release 11.7, V11.7.64
Build cuda_11.7.r11.7/compiler.31294372_0
conda list:
cudatoolkit-dev           11.7.0
cudatoolkit               11.7.0
torch         2.0.1+cu117
nvidia-smi
A100 80G
NVIDIA-SMI 470.141.03   Driver Version: 470.141.03   CUDA Version: 11.4
how to solve this problem? thanks!

lsb_release -a
No LSB modules are available.
Distributor ID: Ubuntu
Description:    Ubuntu 20.04.1 LTS
Release:        20.04
Codename:       focal

cat /proc/version
Linux version 5.4.0-126-generic (buildd@lcy02-amd64-072) (gcc version 9.4.0 (Ubuntu 9.4.0-1ubuntu1~20.04.1)) #142-Ubuntu SMP Fri Aug 26 12:12:57 UTC 2022

cat /proc/version
Linux version 5.4.0-126-generic (buildd@lcy02-amd64-072) (gcc version 9.4.0 (Ubuntu 9.4.0-1ubuntu1~20.04.1)) #142-Ubuntu SMP Fri Aug 26 12:12:57 UTC 2022

cat /proc/version
Linux version 5.4.0-126-generic (buildd@lcy02-amd64-072) (gcc version 9.4.0 (Ubuntu 9.4.0-1ubuntu1~20.04.1)) #142-Ubuntu SMP Fri Aug 26 12:12:57 UTC 2022

lsb_release -a
No LSB modules are available.
Distributor ID: Ubuntu
Description: Ubuntu 20.04.1 LTS
Release: 20.04
Codename: focal
cat /proc/version
Linux version 5.4.0-126-generic (buildd@lcy02-amd64-072) (gcc version 9.4.0 (Ubuntu 9.4.0-1ubuntu1~20.04.1)) https://github.com/vllm-project/vllm/pull/142-Ubuntu SMP Fri Aug 26 12:12:57 UTC 2022

could you check that the problem still exits after rebuilding the repo (pip install -e .)?

could you check that the problem still exits after rebuilding the repo (pip install -e .)?
pip install -e . :
Building wheels for collected packages: vllm
Building editable for vllm (pyproject.toml) ... done
Created wheel for vllm: filename=vllm-0.1.2-0.editable-cp310-cp310-linux_x86_64.whl size=8465 sha256=8154890edc8a5b3b0100d83308d973ec25ecee72b02d479023542312fee2fd1d
Stored in directory: /tmp/pip-ephem-wheel-cache-vg3isffo/wheels/33/fc/d6/f27b3ac96c14477426ab8fd6d5573e139cf29c857e206d16a3
Successfully built vllm
Installing collected packages: vllm
Attempting uninstall: vllm
Found existing installation: vllm 0.1.2
Uninstalling vllm-0.1.2:
Successfully uninstalled vllm-0.1.2
Successfully installed vllm-0.1.2

CUDA_VISIBLE_DEVICES=0 python offline_inference.py:
File "/home/anaconda3/envs/vllm/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in call_impl
return forward_call(*args, **kwargs)
File "/cg/vllm/vllm/model_executor/models/opt.py", line 102, in forward
output, _ = self.out_proj(attn_output)
File "/home/anaconda3/envs/vllm/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in call_impl
return forward_call(*args, **kwargs)
File "/cg/vllm/vllm/model_executor/parallel_utils/tensor_parallel/layers.py", line 443, in forward
output = output + self.bias if self.bias is not None else output
RuntimeError: CUDA error: no kernel image is available for execution on the device
Compile with TORCH_USE_CUDA_DSA to enable device-side assertions.
Processed prompts:   0%|                                                                                | 0/4 [00:00<?, ?it/s]
still not resolved

I met same issue. The problem is I could run vllm on V100 with cuda 11.3, while can not run on A100 with cuda 12.0. I used exact same codes and docker, except cuda.

I have the same issue. Same nvcc/driver both 11.7 When running: python -m vllm.entrypoints.openai.api_server --model meta-llama/Llama-2-7b-chat-hf This solution works for me.

could you check that the problem still exits after rebuilding the repo (pip install -e .)?

I use A100 A40 T4 and use langchain to integrate vllm to encounter this problem in cuda11.7, but I am normal on RTX4090 and RTX3090
Here is the exception output:
INFO 08-25 10:41:25 llm_engine.py:70] Initializing an LLM engine with config: model='meta-llama/Llama-2-7b-chat-hf', tokenizer='meta-llama/Llama-2 -7b-chat-hf', tokenizer_mode=auto, trust_remote_code=False, dtype=torch.float16, use_dummy_weights=False, download_dir=None, use_np_weights=False, tensor_parallel_size=1, seed=0)
INFO 08-25 10:41:25 tokenizer.py:29] For some LLaMA-based models, initializing the fast tokenizer may take a long time. To eliminate the initialization time, consider using 'hf-internal-testing/llama-tokenizer ' instead of the original tokenizer.
Traceback (most recent call last):
File "/root/miniconda3/lib/python3.10/runpy.py", line 196, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/root/miniconda3/lib/python3.10/runpy.py", line 86, in _run_code
exec(code, run_globals)
File "/root/miniconda3/lib/python3.10/site-packages/vllm/entrypoints/api_server.py", line 78, in
engine = AsyncLLMEngine. from_engine_args(engine_args)
File "/root/miniconda3/lib/python3.10/site-packages/vllm/engine/async_llm_engine.py", line 232, in from_engine_args
engine = cls(engine_args. worker_use_ray,
File "/root/miniconda3/lib/python3.10/site-packages/vllm/engine/async_llm_engine.py", line 55, in init
self. engine = engine_class(*args, **kwargs)
File "/root/miniconda3/lib/python3.10/site-packages/vllm/engine/llm_engine.py", line 104, in init
self._init_cache()
File "/root/miniconda3/lib/python3.10/site-packages/vllm/engine/llm_engine.py", line 182, in _init_cache
num_blocks = self._run_workers(
File "/root/miniconda3/lib/python3.10/site-packages/vllm/engine/llm_engine.py", line 470, in _run_workers
output = executor(*args, **kwargs)
File "/root/miniconda3/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "/root/miniconda3/lib/python3.10/site-packages/vllm/worker/worker.py", line 108, in profile_num_available_blocks
self.model(
File "/root/miniconda3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/root/miniconda3/lib/python3.10/site-packages/vllm/model_executor/models/llama.py", line 253, in forward
hidden_states = self.model(input_ids, positions, kv_caches,
File "/root/miniconda3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/root/miniconda3/lib/python3.10/site-packages/vllm/model_executor/models/llama.py", line 220, in forward
hidden_states = layer(
File "/root/miniconda3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/root/miniconda3/lib/python3.10/site-packages/vllm/model_executor/models/llama.py", line 172, in forward
hidden_states = self.self_attn(
File "/root/miniconda3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in call_impl
return forward_call(*args, **kwargs)
File "/root/miniconda3/lib/python3.10/site-packages/vllm/model_executor/models/llama.py", line 132, in forward
qkv, = self.qkv_proj(hidden_states)
File "/root/miniconda3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/root/miniconda3/lib/python3.10/site-packages/vllm/model_executor/parallel_utils/tensor_parallel/layers.py", line 309, in forward
output_parallel = F. linear(input_parallel, self. weight, bias)
RuntimeError: CUDA error: no kernel image is available for execution on the device
Compile with TORCH_USE_CUDA_DSA to enable device-side assertions.

same the model meta-llama/Llama-2-7b-chat-hf

how to fix？
File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/usr/local/lib/python3.8/dist-packages/vllm/model_executor/parallel_utils/tensor_parallel/layers.py", line 309, in forward
output_parallel = F.linear(input_parallel, self.weight, bias)
RuntimeError: CUDA error: no kernel image is available for execution on the device
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
Compile with TORCH_USE_CUDA_DSA to enable device-side assertions.
root@fa4b127ca2bf:/workspace# python

Also running into this same issue. Has anyone found a fix?

Same issue +1! ANY updates or issues? Anyone tried updating Driver Version: 470.141.03 to 515?

Same issue +1! ANY updates or issues? Anyone tried updating Driver Version: 470.141.03 to 515?

Solved, by recompiling and reinstalling the lib when deploying on V100. Previously it was compiled on A100.

I need to switch between several GPUs (A100, V100, RTX8000) and cuda version, when the CUDA version changes, I need to reinstall it from source. It's a shot-time solution, but it works now!

same issue
root@server-1:~/vllm# python3 -m vllm.entrypoints.api_server --model /workspace/Qwen-7B/weights/Qwen-7B-Chat/ --trust-remote-code
2023-09-25 06:17:03,382 INFO worker.py:1642 -- Started a local Ray instance.
INFO 09-25 06:17:04 llm_engine.py:72] Initializing an LLM engine with config: model='/workspace/Qwen-7B/weights/Qwen-7B-Chat/', tokenizer='/workspace/Qwen-7B/weights/Qwen-7B-Chat/', tokenizer_mode=auto, trust_remote_code=True, dtype=torch.float16, download_dir=None, load_format=auto, tensor_parallel_size=4, seed=0)
WARNING 09-25 06:17:05 tokenizer.py:66] Using a slow tokenizer. This might cause a significant slowdown. Consider using a fast tokenizer instead.
Traceback (most recent call last):
File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/usr/lib/python3.8/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/root/vllm/vllm/entrypoints/api_server.py", line 177, in
engine = AsyncLLMEngine.from_engine_args(engine_args)
File "/root/vllm/vllm/engine/async_llm_engine.py", line 442, in from_engine_args
engine = cls(engine_args.worker_use_ray,
File "/root/vllm/vllm/engine/async_llm_engine.py", line 250, in init
self.engine = self._init_engine(*args, **kwargs)
File "/root/vllm/vllm/engine/async_llm_engine.py", line 279, in _init_engine
return engine_class(*args, **kwargs)
File "/root/vllm/vllm/engine/llm_engine.py", line 105, in init
self._init_cache()
File "/root/vllm/vllm/engine/llm_engine.py", line 185, in _init_cache
num_blocks = self._run_workers(
File "/root/vllm/vllm/engine/llm_engine.py", line 687, in _run_workers
all_outputs = ray.get(all_outputs)
File "/usr/local/lib/python3.8/dist-packages/ray/_private/auto_init_hook.py", line 24, in auto_init_wrapper
return fn(*args, **kwargs)
File "/usr/local/lib/python3.8/dist-packages/ray/_private/client_mode_hook.py", line 103, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.8/dist-packages/ray/_private/worker.py", line 2547, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(RuntimeError): ray::RayWorker.execute_method() (pid=13558, ip=<IP_ADDRESS>, actor_id=60a52a454709a59765dbb35e01000000, repr=<vllm.engine.ray_utils.RayWorker object at 0x7f3ad7c33370>)
File "/root/vllm/vllm/engine/ray_utils.py", line 29, in execute_method
return executor(*args, **kwargs)
File "/usr/local/lib/python3.8/dist-packages/torch/utils/_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "/root/vllm/vllm/worker/worker.py", line 108, in profile_num_available_blocks
self.model(
File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/root/vllm/vllm/model_executor/models/qwen.py", line 240, in forward
hidden_states = self.transformer(input_ids, positions, kv_caches,
File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/root/vllm/vllm/model_executor/models/qwen.py", line 205, in forward
hidden_states = layer(
File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/root/vllm/vllm/model_executor/models/qwen.py", line 171, in forward
hidden_states = residual + hidden_states
RuntimeError: CUDA error: no kernel image is available for execution on the device
I use cuda118 docker，builded in H800 , The Same Docker copy to H100 GPU, When it restart, there was this issue,  The problem persists after rebuild

I've been having the same issue for the last week.
GPU: Titan XP with CUDA 12.0
nvcc --version == 11.8
torch.version.cuda == 11.8
I've tried reinstalling PyTorch but nothing has worked so far.

I've been having the same issue for the last week.
GPU: Titan XP with CUDA 12.0 nvcc -V == 11.8 torch.version.cuda == 11.8
I've tried reinstalling PyTorch, which did not resolve the problem.

@schnurromafia I don't think Titan Xp is supported, since its compute capacity is 6.1. One of vLLM's requirements is GPU with compute capability 7.0 or higher.

@Fr4nk1inCs thanks for the message!
There is not technical limitation to running vllm with CC < 7.0 (see https://github.com/vllm-project/vllm/issues/963#issuecomment-1714100911), apart from not being able to load some models like Falcon.
The workaround is to build from source and comment out a couple lines: https://github.com/vllm-project/vllm/issues/463#issuecomment-1636070685
I've been able to run vllm without having this issue for weeks. Reverting back to old commits does not resolve it, which probably means that vllm is not responsible for this error. Just curious if anyone else has had this happen to them...

@schnurromafia Thanks for the message! I was also trying to run vLLM on Pascal GPUs. I'll build it from source and see if it works.

@hmellor What resolved this issue?

I am also experiencing this using both T4 and V100 GPU's on Colab

@cccx3 in that case, could you please open a new issue using the new templates so we can better understand the cause of your issue?

I am also experiencing this using both T4 and V100 GPU's on Colab

@cccx3 Could you tell me how you resolved it, if you did? I'm also trying to run it on colab

@cccx3 in that case, could you please open a new issue using the new templates so we can better understand the cause of your issue?

I also encountered the same problem

CUDA kernel failed : no kernel image is available for execution on the device
void prescan_small(int *, int *, int, int, CUstream_st *) at L:126 in C:\Users\reall\Softwares\Miniconda3\envs\Wonder3D_Projects\torchmcubes\cxx\pscan.cu
Having this when working with 3d in ComfyUI

same error

same error

Please open a new issue and provide your own error trace.

same error, worked on V100 and fails on P100

Same issue +1! ANY updates or issues? Anyone tried updating Driver Version: 470.141.03 to 515?

Solved, by recompiling and reinstalling the lib when deploying on V100. Previously it was compiled on A100.

I think this is the current solution to this error. Recompiling and reinstalling the vllm works for me.

@schnurromafia Thanks for the message! I was also trying to run vLLM on Pascal GPUs. I'll build it from source and see if it works.

Did you come up with a solution? I am trying to use multiple gpu (2 P40) but ı could not figure it out.

@ekmekovski I am running into this with 2xP40s as well

Does it mean I cannot run it because compute capability I have is 6.1?
And where are models stored, that I can reuse them with other software?


Update 2015-09-01-sass.md

Was checking your Sass piece, found this small typo. Thanks for the tutorial!

+1


Dependency Tree failing for yarn.lock files

For some reason the dependency tree can't be generated for yarn.lock. You can take any yarn.lock file for this example.

Hi @kakumanivrn, it seems to work locally for me for a sample project. Can you share the yarn.lock and the generated sbom?

@kakumanivrn, are you still seeing the issues?

@prabhu due to company's code I can't share the BOM directly as it contains internal component names that are private. Maybe could you please share a working yarn.lock file of any open source code, so I can test if the problem is with our yarn.lock file.

@varkakumani, there are lots of test data here - https://github.com/CycloneDX/cdxgen/tree/master/test/data/yarn_locks. You may be using a yarn.lock version that has some differences. You can feel free to share the file directly with me too prabhu @ appthreat.com

This was tested offline and found to be working fine.


Can it use integrated GPU?

I've  AMD integrated GPU 4GB, but it's still showing "No GPU being used. Careful, inference might be extremely slow!"
Does this program not use integrated GPU?

It's looking for Nvidia and CUDA installed.  I have multiple GPU's with 6GB but this is not enough to load the model :(

have you tried using small versions of model (specified in preload_models?)
not sure about amd support, right now only cuda and cpu are supported

are the issues here related? is everyone on AMD or is this mixed with cuda issues?

So it will not work until I use the Nvidia Graphics card!

it should work on cpu, albeit slower of course..

how to run on cpu? it doesn't seem to have a option to pass device on init of the model!

preload_models has arguments to disable gpu, but either way it should happen automatically if you don't have a supported gpu

Closing for now since I can’t reproduce the issue


chore(main): release 0.5.0

:robot: I have created a release beep boop
0.5.0 (2024-05-29)
Features

set up GitHub Actions workflow for selective packaging and release (26f4997)

This PR was generated with Release Please. See documentation.

:robot: Release is at https://github.com/hakuna-max/course_report/releases/tag/v0.5.0 :sunflower:


Improve Name Formatting Logic Based on Number of Cards in Row and Screen Size

In the Explore.jsx component, update the logic for displaying card names to conditionally apply the formatName function based on the number of cards in a row and the screen size.
Current Behavior:

All card names are passed through the formatName function, regardless of the number of cards in a row or screen size.

Desired Behavior:

Based on Number of Cards in Row:

If there is only one card in a row (occupying the full width), the full name should be displayed without any formatName logic.
If there are 2 or 3 cards in a row, the formatName logic should be applied to shorten the names as necessary.

Based on Screen Size:

On mobile devices (screen width ≤ 800px), the formatName logic should be applied to all card names, regardless of the number of cards in a row.

Impact:
This change will improve the readability and user experience by displaying full names for cards that occupy the entire row while still maintaining a neat and compact display for rows with multiple cards. On mobile devices, all names will be formatted to ensure consistency and optimal use of space.
Note for Pull Request
When raising the pull request, please attach screenshots of the UI demonstrating that the logic has been successfully implemented. This will help reviewers understand and verify that the desired behavior has been achieved. The screenshots should include:

A view with only one card in a row, showing the full name displayed.
A view with 2 or 3 cards in a row, showing the shortened names.
Views on a mobile device (screen width ≤ 800px), showing all names formatted using the formatName function.

Fix: Improved /Adjusted name formatting in Explore cards
I will work to resolve the issue where names were not properly formatted on cards, within provided details


"Anonymous user id" do not exist in .net SDK. Looks like it's just User.Id

Could you take sometime and review this "Anonymous user id"  and tell us- exact field name for popular SDKs such as .net sdk.

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

ID: 36c3dfe3-25e4-6899-9bb9-22c1690c8e83
Version Independent ID: d8ec3295-937e-5e64-132e-7bd503b0e5fc
Content: Azure Application Insights Telemetry Data Model - Telemetry Context - Azure Monitor
Content Source: articles/azure-monitor/app/data-model-context.md
Service: azure-monitor
Sub-service: application-insights
GitHub Login: @mrbullwinkle
Microsoft Alias: mbullwin

Hello @SychevIgor ,
You can find the complete endpoint schema declaration in he below doc:
https://github.com/microsoft/ApplicationInsights-Home/blob/master/EndpointSpecs/Schemas/Bond/ContextTagKeys.bond
As you can see in the above doc , you can use User.Id for the same purpose:
[Description("Anonymous user id. Represents the end user of the application. When telemetry is sent from a service, the user context is about the user that initiated the operation in the service.")]
    [MaxStringLength("128")]
    515: string 	 UserId = "ai.user.id";

You can find the endpoint schema declaration for ApplicationInsight JS version in the below doc:
https://github.com/microsoft/ApplicationInsights-JS/blob/master/legacy/JavaScript/JavaScriptSDK.Interfaces/Contracts/Generated/ContextTagKeys.ts
Hope it helps.

@MohitVerma-MSFT  thank you. I did all what I need, but it is not about me, it's about up-to-date documentation.

Hello @SychevIgor ,
Assigned content-author for further review.

@MohitVerma-MSFT any news?

Thanks for your feedback. I will combine this issue and the other you made 48222 in an internal work item to update the Telemetry context: Application Insights data model doc.  I'll close out this issue for now but will @mention you when the update is complete.
#please-close


Add the Race to the character (in edit)

Needs #27
In the character edit screen the should should be selectable/editable. Races are hard coded for now

:tada: This issue has been resolved in version 1.7.0 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


2 expose database fetching endpoints

for requirements.txt, there may be no need to write into all packages and sub-packages but it works fine if needed I will change it
change the directory of the example.env and add the necessary info
remove query.sql syntax error
fix init.py and database.py running issues, such as path issues, handle more errors,  change query, etc. Overall 3 endpoints run well
use try_post.py to manually post-game, check it, if you want
there are 2 HTTPExceprion 409 404, if I need more, I will improve it later
MariaDB database named flight_game 1 table named airports, if you got this error adjust database structure
in branch 2 install requirement.txt and run FastAPI then run try_post you can see post-game works,
visit endpoints at http://<IP_ADDRESS>:8000/airports you can see the airport getting well
visit endpoints at http://<IP_ADDRESS>:8000/game?game_id=1 you will see the game you created

there are conflicts with init.py, database.py, and requirements.txt I have already tested locally after fixing conflicts in the dev branch it works well for 3 endpoints. and also need to clarify I moved example.env into the Dracula file, and the try_post and request.py 2 files running well.

about airport running tests under the  dev branch

try_post under dev branch

request.py  running under dev branch

it works now


chore: suppress no-param-reassign eslint warnings

Type
enhancement

Description

Disabled the no-param-reassign ESLint rule to allow parameter reassignment in functions.
Improved readability of the ESLint configuration by reformatting the plugins and prettier/prettier rules.

Changes walkthrough
Relevant filesConfiguration changes

.eslintrc.jsonEnhance ESLint Configuration and Disable `no-param-reassign` Rule

.eslintrc.json
Reformatted plugins and prettier/prettier rules for better readability.  Disabled the no-param-reassign rule.

+9/-3

✨ PR-Agent usage:
Comment /help on the PR to get a list of all available PR-Agent tools and their descriptions

:tada: This PR is included in version 2.0.0 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


You're putting me off my Bourbon :(

I'm using Bourbon's linear-gradient mixin and ember-cli-sass is generating incorrect css.  I provide the following input:
%some-color {
  @include linear-gradient(to bottom, #151A20 0%, #0B0E11 100%);
}

.my-class {
  @extend %some-color
}

and I receive the following output from ember-cli-sass:
.my-class {
  background-image: linear-gradient(to bottom,#151A20 0%, #0B0E11 100%, , , , , , , , ); }

whereas compiling with sass 3.4.13 running on ruby gives the correct css:
.my-class {
  background-image: linear-gradient(to bottom,#151A20 0%, #0B0E11 100%); }

Having the same issue with both font-face & radial-gradient too.
:(

This is an issue with node-sass. ember-cli-sass is a thin wrapper around this library. You should open a ticket over there.
This issue may be a result of the fact that ember-cli-sass is currently using a beta version of node-sass. You may find that downgrading to v3.1.x fixes the problem.

See #44 for details on this issue.

Hey - thanks for getting back on this.
After looking into this issue a bit further it seems like the rabbit hole goes deeper than even node-sass; see this issue from libsass https://github.com/sass/libsass/issues/676
To anyone wanting to use bourbon with Ember I've found that it compiles correctly using
in bower.json
"devDependencies": {
  "bourbon": "3.2.1",
  "neat": "1.5.1"
}

& in package.json
`"broccoli-sass": "^0.3.3"``
not ideal, but at least it works for now.

<EMAIL_ADDRESS>might fix this, can you confirm

<EMAIL_ADDRESS>fixed the @font-face issue that I was having — but
@include linear-gradient nor @include radial-gradient were still not rendering correctly for me across browsers.
Having said that it looks like both of these are soon going to be deprecated by bourbon soon as browser support is pretty much there now.
I've replaced all the instances of linear & radial gradients using @includes with a simple mixin ( just a fallback color).
This wasn't much work & now means that the latest versions of node/io, node-sass, bourbon & neat all seem to work together — for me thats good enough, as the approach I posted above meant sticking on node 10.36...
Thanks for all your help @aexmachina !

node-sass is now a peerDependency, so you specify which version of<EMAIL_ADDRESS>to use in your package.json file. You may find that using<EMAIL_ADDRESS>fixes your problem until they fix the issue.

Hmm
The application I installed ember-cli-sass to yesterday (which is working) looks like this:
⇒  npm list node-sass
<EMAIL_ADDRESS>/Users/username/git/my-app
└─┬<EMAIL_ADDRESS>  └─┬<EMAIL_ADDRESS>    └──<EMAIL_ADDRESS>
Whereas trying to follow the peerDependency route in another app I took this approach
ember new test-sass
cd test-sass
npm install<EMAIL_ADDRESS>--save-dev
npm install ember-cli-sass --save-dev

gives an error (I think others are having too)
https://github.com/aexmachina/ember-cli-sass/issues/46
npm ERR! notarget No compatible version found<EMAIL_ADDRESS><4.0.0'
npm ERR! notarget Valid install targets:
npm ERR! notarget ["0.9.4-rc1","0.2.0","0.2.1","0.2.2","0.2.3","0.2.4","0.2.5","0.2.6","0.3.0","0.4.0","0.4.1","0.4.2","0.4.3","0.4.4","0.5.0","0.5.1","0.5.2","0.5.3","0.5.4","0.6.0","0.6.1","0.6.2","0.6.3","0.6.4","0.6.5","0.6.6","0.6.7","0.7.0-alpha","0.7.0","0.8.0","0.8.1","0.8.2","0.8.3","0.8.4","0.8.5","0.8.6","0.9.0","0.9.1","0.9.2","0.9.3","0.9.4-rc1","0.9.4","0.9.5-rc1","0.9.5","0.9.6","1.0.0","1.0.1","1.0.2-alpha","1.0.2","1.0.3","1.1.0","1.1.1","1.1.2","1.1.3","1.1.4","1.2.0","1.2.1","1.2.2","1.2.3","2.0.0-beta","2.0.0","2.0.1","3.0.0-alpha.0","3.0.0-beta.2","3.0.0-beta.3","3.0.0-beta.4","2.1.0","2.1.1","3.0.0-beta.5"]

which is strange because
⇒  npm list node-sass
<EMAIL_ADDRESS>/Users/username/git/test-sass
└──<EMAIL_ADDRESS>
seems to show it there...
I checked my other (working) app and it shows this
⇒  npm list node-sass
<EMAIL_ADDRESS>/Users/username/git/my-app
└─┬<EMAIL_ADDRESS>  └─┬<EMAIL_ADDRESS>    └──<EMAIL_ADDRESS>
any suggestions what is going wrong this time around?
thanks again...

@chrism npm/semver treats a x.x.x-beta tag as prior to the x.x.x release itself. So because broccoli-sass-source-maps (the project that this addon relies on) requires >= 3.0.0, the<EMAIL_ADDRESS>doesn't satisfy that condition.

@davewasmer thanks for the explanation :)


Kanban issue: Cannot see the content of backlinks when using [[]] to search.

thanks for the issue; it should be fixed in the latest version


Resolves that return a promise

I have used the router and ui-router extensively and there is an issue that has always puzzled me.
When returning promises from the "resolve" block the current route don't switch until they are all resolved. this is an excellent mechanism that allows for a centralized way of handling you application flow.
The thing is the url does change and that causes an inconsistency in the way things are handled.
I think a route should have three stated - active, inactive and pending, and perhaps add events for the state going in and out of pending/loading mode.
This can help when your code needs to see what the current state is and act accordingly.
Have you addressed this issue on the new router?
Hope I'm clear - this is a complex but fundamental issue.

Thanks for taking this into consideration.
Just to reiterate:
The problem is the user has control of the address-bar/history.
This means you can't really associate a state to a url directly if there is a pending stage (building up the component and it's asynchronous dependancies) .
Say a user manually changes the url to "/users" and users needs to load with an ajax call.
Since the address bar should be your source of truth, you should be in a state called "users",
but your not since users ajax hasn't returned.
This is especially a problem when your rapidly moving between states.
The ui-router has an issue were if you return to a state before the new state is loaded,
It thinks nothing has changed and when the ajax call returns it jumps to the new old state which is now longer what the user choose.
That's why I suggest the framework should be as clear on this as possible, and let me know at what state I'm in - or which intermediate state, along with events that will help me manage the flow of the app.


Use envs to set basic configs

Provide option to declare basic settings (at startup) using env variables

What env variables were you thinking of using?  Would these be used to replace the "setup" screen?

What env variables were you thinking of using?  Would these be used to replace the "setup" screen?

Yeah, the basic idea is to optionally bypass the setup page by providing the variables when bootstrapping the container, much like the wordpress image does:
Here's what I'm using so far: https://github.com/phpcollab/docker/blob/ci-test/docker-entrypoint.sh#L156-L159
You can see an example of how they'd be used at: https://github.com/phpcollab/docker/blob/ci-test/README.md in the stack.yml file.
If you look at the top of the script there's a few more that are inherited from WordPress. We'll either repurpose the others or remove them.

Yeah, the basic idea is to optionally bypass the setup page by providing the variables when bootstrapping the container, much like the wordpress image does:
Here's what I'm using so far: https://github.com/phpcollab/docker/blob/ci-test/docker-entrypoint.sh#L156-L159
You can see an example of how they'd be used at: https://github.com/phpcollab/docker/blob/ci-test/README.md in the stack.yml file.
If you look at the top of the script there's a few more that are inherited from WordPress. We'll either repurpose the others or remove them.


How to doing Right to Left Direction of GridSter

Dear Friends,
direction of gridster fulfillment is left to right and start from Left-Top , finish to Right-down,
i want to change this direction, that start from right-top and finiesh left-down,
additional to keeping anothers darg&drop movements.

+1

+1

+1

+1

+1

+1

+1


[chromatic] Error: Exported function not found at $$mock$$

Hi !
Thanks in advance for your great work. I'm experiencing some issues using the addon on Chromatic.
I'm getting the following error message.
It runs development but fails on build doing npm run build-storybook
any idea what could be happening ?

We're seeing the same issue

I had the same issue. The problem was I had 2 dependencies storybook-addon-module-mock and storybook-addon-mock both installed.


Add section about credential scanning

This pull request adds a section about credential scanning to the engineering playbook. The section is based on findings from a customer project and answers questions such as:

What is credential scanning?
Why do we need credential scanning?
How can we implement credential scanning?

The section is included as part of the continuous integration heading since for consistency it makes sense to enforce credential scanning policies at the build server level.

@SaraSp @cloudbeatsch flagging for review, thanks!


Support non utf symlink targets

What does this PR change? What problem does it solve?
Currently symlinks whose target name is invalid utf8 are not backed up correctly. The invalid characters are replaced with \ufffd. This PR introduces an optional quoted field which is used for symlink targets which might not encode correctly. The old linktarget field in a Node still exists and continues to be set to stay backwards compatible to older clients. Thus, for old clients the symlink will behave just as before, whereas later restic versions which support the new field will use that one automatically instead.
This allows for a backwards compatible addition of a correct symlink encoding. I've decided against binding the symlink encoding to a specific repository version as that would create all sorts of headaches when copying snapshots between repositories with different versions.
Was the change previously discussed in an issue or on the forum?
Fixes #3311
Checklist

[x] I have read the contribution guidelines.
[x] I have enabled maintainer edits.
[x] I have added tests for all code changes.
[ ] I have added documentation for relevant changes (in the manual).
[x] There's a new file in changelog/unreleased/ that describes the changes for our users (see template).
[x] I have run gofmt on the code in all commits.
[x] All commit messages are formatted in the same style as the other commits in the repo.
[x] I'm done! This pull request is ready for review.

Seems like a sound design overall. Does need a changelog entry, though.

Let's say, you have a file names " linking to "a.
Then current restic generated the json:
{"nodes":[{"name":"\\\"","linktarget":"\"a"},{"name":"\\\"a"}]}
So, quoting filenames but not quoting linktarget not only broke non-unicode linktargets, but also introduced a mess in the tree format.
Of course you can add more quirks and either add stuff to handle only unicode (leaving this as above) or also change this example to:
{"nodes":[{"name":"\\\"","linktarget":"\"a", "linktarget_quoted":"\\\"a"},{"name":"\\\"a"}]}
Sorry, but this is still a mess!
IMO the only clean solution is to deprecate linktarget and add a new field like target to let this always look
{"nodes":[{"name":"\\\"", "target":"\\\"a"},{"name":"\\\"a"}]}
(or rethink the quoting altogether, but this you have already declined in #3808 ...)
I know, this breaks forward-compatibility but so does the repo v2 format which supports compression. I know that this adds some headache if you want to correct existing repos. But this could be done by adding this to a new repo version an supplying a migrate command.

Just a comment from the sidelines: if the symlink target field is just an arbitrary sequence of bytes, then we should handle it as such and store/restore a byte slice, e.g. keep the linktarget field, but add a linktarget_raw field which is []byte and encodes as base64 in JSON.

@fd you are right. And I also strongly support a convention that valid UTF-8 (which is the standard case) should be stored as-is, as this makes reading the JSON tree (e.g. using restic cat) much easier for most files.
However, all these arguments also apply to the name field...

Hmm, the cost-benefit calculation would probably be different if we clean up the name field along with other breaking changes. I'm thinking of adding support for chunked trees to the nodes, which won't be possible in a backwards compatible way. But that could be an opportunity to clean up other stuff.
I'm wondering whether it would be a good idea to just store name and linktarget always as base64 encoded. It won't make much of a difference in the filesize, at least after it's compressed. But it would simplify decoding.

@MichaelEischer May I suggest to also add a name_raw field which is filled if the (encoded) name field doesn't exactly reflect the filename? When created that way, program reading trees can always base64-decode a *_raw field when given and use the * (without _raw) field directly, if not.
Of course that wouldn't work with already-written data or older program versions. But it would provide a migration path towards a clean solution by first making the name_raw field optional, then required and later deprecating name fields which contain encoding.

@aawsome I'd like to discuss the name field separately  from linktarget. I've created issue https://github.com/restic/restic/issues/4408  for that. The main difference in my opinion is that the linktarget modifications add support for non-UTF8 symlink targets, whereas the suggested name changes are purely cosmetic (strconv.Quote is perfectly capable of handling non-UTF8).

Of course that wouldn't work with already-written data or older program versions. But it would provide a migration path towards a clean solution by first making the name_raw field optional, then required and later deprecating name fields which contain encoding.

So your suggestion is to only keep name_raw and linktarget_raw and deprecate both name and linktarget? If we make such a change, I'd like to coordinate it with https://github.com/restic/restic/pull/4006 and the support for chunked trees (likely won't happen this year) to minimize the resulting disruptions.

(strconv.Quote is perfectly capable of handling non-UTF8).

I actually have two issues with strconv.Quote:

I personally am not able to judge if it is perfectly capable of handling non-UTF8. I tried to find a specification of what it does and wasn't able so far. Even in https://github.com/restic/restic/blob/master/doc/design.rst we are not able to tell, what it exactly does. So it's kind of a black box we are using here. For a backup format this IMO is even worse than an open question about whether it's possible to handle non-UTF.
Its use is easy to oversee as for many common filenames it doesn't change anything. This leads uninformed consumers to just use that field - and maybe make mistakes. E.g. using \"abc\" as filename which in fact was "abc" before getting backup'ed. See https://github.com/juergenhoetzel/pyrrhic/issues/1 for example.

So your suggestion is to only keep name_raw and linktarget_raw and deprecate both name and linktarget?

No. Actually I like the solution you implemented here with linktarget and linktarget_raw very much. So I propose to change the repository tree-format step-by-step to also use name and name_raw in exactly the same way. I.e. deprecate the usage of strconv.Quote on the name field.
(an alternative could be introduce new fields like filename/filename_raw and deprecate name.)

LGTM.

@MichaelEischer Shouldn't this treatment of symlink targets be added to https://github.com/restic/restic/blob/master/doc/design.rst?

Another remark - and sorry if there are errors or things are not fully understandable, I don't use windows and am no expert in its details (just did dig into how Rust handles filenames and it is very pedantic about being correct)...
Actually, I still don't know what's going on on Windows and IMO this also needs documentation. On Windows, filenames are not stored as byte-sequences but as sequences of 16-bit words. This means, we cannot talk about utf8 on windows, at least when we are talking about how the OS stores filenames. I know that Golang does some internal conversion, so all filenames always look at byte-sequences and you can treat them as UTF8 if they are valid unicode. But I don't know how non-unicode filenames (if they are allowed) are converted from 16-bit words to an 8-bit byte sequence. Moreover, I don't even know if there are cases where a valid Windows filename cannot be transformed to a non-UTF8 byte sequence and what Golang would do in such a case. Can anyone provide information about this topic?
Besides this, I also don't know if this linktarget topic anyway applies to Windows or if this topic would only arise when applying it to "standard" filenames....

@MichaelEischer Shouldn't this treatment of symlink targets be added to https://github.com/restic/restic/blob/master/doc/design.rst?

Oh indeed. I'll open a PR later.

On Windows, filenames are not stored as byte-sequences but as sequences of 16-bit words.

The Windows API methods suffixed with a W use UTF-16 which is converted by Go into UTF-8 . On the filesystem NTFS stores all names as Unicode: https://learn.microsoft.com/en-us/windows/win32/intl/character-sets-used-in-file-names .

The Windows API methods suffixed with a W use UTF-16 which is converted by Go into UTF-8 . On the filesystem NTFS stores all names as Unicode:

Ah great, thanks for the information!
So, on Windows there is no non-unicode topic at all and a conversion into UTF-8 is sufficient. Maybe this is also a good info for the design document?

I've opened https://github.com/restic/restic/pull/4422


Units would be good

Hi,
i installed your plugins yesterday on my relay server, and the work great, thank you. But i noticed: Some units on the y-axis would be helpful.
For example, the countries: I know that Canada has currently 123.89. But - 123.89 of what? Connections? Traffic?
And the traffic - i know that currently 5.46k are read. Do you mean inbound or outbound traffic? 5.46k of what? Bytes?
Maybe i'll look in the source myself, fix it and create a pull request, but i just wanted to create this issue first ;)

ACK. In what unit is the value of tor_traffic? E.g. Bits/s or Byte/s? Would be good to have the unit displayed.

Hello @wodry I guess having the same label as https://github.com/munin-monitoring/contrib/blob/master/plugins/tor/example-graphs/tor_-1.png would work, wouldn't it ?

untested ACK 84e3c62a51f0908640dad226f0e966c9dbd39a8d

Tested ACK 84e3c62a51f0908640dad226f0e966c9dbd39a8d

@wodry this has been merged in https://github.com/munin-monitoring/contrib/commit/168f6f924fc8efc2719af852977e8c2da5ffb0e0
I think this ticket can be closed.


HorizontalView breaks in Edge

The HorizontalView works as expected on all major browsers except IE Edge (tested von version 16).  I can observe a weird scrolling behaviour. Probably it has something to do how heights and CSS units are utilised.

Thanks for reporting this. I actually saw the same behaviour on Chrome. A simple wrapper View with overflow: hidden was enough to get rid of this.

@HorstMumpitz ping :)

@dan-lee The fix did not solve my particular Edge bug but seems to work in general. In my case most of my view use additionally a SimpleLayout.

Could you perhaps provide a simple CodeSandbox?
I tried it with the horizontal view example in Edge and it worked out. But maybe your circumstances change things

Is this still valid? It looks fine in our implementations afaik - maybe we need a better documentation for it (suggest we close it due to inactivity for now?)


add method to clear the cache directory

add a method to the OfflineCache class to clear the content of the cache directory

implemented in 1.7.1


Service hanging at Start/Pending after OS Reboot

Hi there,
thanks for sharing this nice script. I have problems after rebooting the os (Win10), the service i created didn't come up afterwards.
greetings

Well, I'm afraid that's your problem, not mine :-)
Review the changes you've done.
Look into the log files.
Good luck!


Would it be possible to add a stubfile?

Hey all,
I've started using typing in python and have managed to get literally all my packages working with pylint, with the exception of jsonpickle.

Any chance we could get a stub file included?

Sure! I'm backlogged on school work at the moment, so if you can submit a PR with a stub file then I'd be happy to merge it, but otherwise I probably won't be able to make one myself for a few weeks or more :(

Note that since the minimum supported Python version seems to be 3.7. You can use inline annotations rather than a separate stub file that can fall out of sync.


Fix Snippets' failing tests

Maybe add
waitsForPromise(() => atom.packages.activatePackage(path.join(__dirname, 'fixtures', 'package-with-snippets')));

below https://github.com/atom/snippets/blob/b1ac84ef7dc988ee0417ad9c44f5dd397c929411/spec/snippet-loading-spec.js#L103
for fixing CI.
Or it could be https://github.com/atom/snippets/commit/2de9091b3d6f5ba9889c448c929865aef960ffc5
I guess it's just some sort of flaky test; I wonder happens if you try my suggestion
Originally posted by @ThatXliner in https://github.com/atom-community/atom/issues/399#issuecomment-1170517945

@thatXliner could you make a PR?


chore(page): delete announcement bar

Since we add / remove the announcement bar often, is it better practice to comment it out (for easy un-commenting upon a new major release), or to delete the code?
For now I've deleted the code.


autoBuildFlags does not impact the install

Context
I'm working on building opencv4nodejs in a lambda layer, the project can be found in https://github.com/piercus/opencv4nodejs-lambda-layer
Lambda layer maximal size is 250MB. I cannot put the whole opencv build in it.
Currently, i want to limit the layer to "core" and "calib3d".
I have set the corresponding flags in
https://github.com/piercus/opencv4nodejs-lambda-layer/blob/master/guest/package.json#L13
    "autoBuildFlags": "-DCMAKE_BUILD_TYPE=RELEASE -DBUILD_LIST=core,calib3d -DWITH_IPP=OFF -DWITH_V4L=OFF -DWITH_FFMPEG=OFF -DWITH_GSTREAMER=OFF -DWITH_GTK=OFF -DWITH_PROTOBUF=OFF -DBUILD_PROTOBUF=OFF -DOPENCV_DNN_OPENCL=OFF -DWITH_WIN32UI=OFF -DWITH_PNG=OFF -DWITH_JPEG=OFF -DWITH_TIFF=OFF -DWITH_WEBP=OFF -DWITH_OPENJPEG=OFF -DWITH_JASPER=OFF -DWITH_OPENEXR=OFF -DBUILD_opencv_python=OFF -DBUILD_opencv_java=OFF"

The packaging is made in a github action : see the job
Inside a docker which is doing npm install
Actual
The resulting asset is 312MB big and contains all the libs
Expected
The resulting asset should contain only calib3d and core libs

Oups...
I will check that soon.

I find the code that is incorrect, but that will not change the result.
to build the openCV the way you want the current implementation, you should replace :
-DBUILD_LIST=core,calib3d with:
-DBUILD_opencv_core=ON
-DBUILD_opencv_calib3d=ON
-DBUILD_opencv_python_tests=OFF
-DBUILD_opencv_core=OFF
-DBUILD_opencv_imgproc=OFF
-DBUILD_opencv_imgcodecs=OFF
-DBUILD_opencv_videoio=OFF
-DBUILD_opencv_highgui=OFF
-DBUILD_opencv_video=OFF
-DBUILD_opencv_calib3d=OFF
-DBUILD_opencv_features2d=OFF
-DBUILD_opencv_objdetect=OFF
-DBUILD_opencv_dnn=OFF
-DBUILD_opencv_ml=OFF
-DBUILD_opencv_flann=OFF
-DBUILD_opencv_photo=OFF
-DBUILD_opencv_gapi=OFF
-DBUILD_opencv_face=OFF
-DBUILD_opencv_img_hash=OFF
-DBUILD_opencv_text=OFF
-DBUILD_opencv_tracking=OFF
-DBUILD_opencv_videostab=OFF
-DBUILD_opencv_xfeatures2d=OFF
-DBUILD_opencv_ximgproc=OFF

Should -DBUILD_LIST have a higher priority than the -DBUILD_opencv ?
and should a -DBUILD_LIST disable all build -DBUILD flags when present?
I do not have access to my regular PC, I only have access to a M1 Mac. now,

Thanks for the quick response @UrielCh !
I will confirm in few hours that this is working!

I made a patch to ensure that this approach works, but I did not commit it yet

I'm waiting for your next feed back then I will publish a first patched version.

I confirm that changes suggested in https://github.com/UrielCh/opencv4nodejs/issues/73#issuecomment-1427076308 are not changing the end result.
See https://github.com/piercus/opencv4nodejs-lambda-layer/releases/tag/layer-cv-v4.6.0
If the patch is available in a specific branch, tell me which one so i will test.

Still not able to make it work (see the job and the release)
Even when using --verbose, I'm still not able to get the logs of the npm install command.
I have made few attemps, but if you have a tips to get the logs displayed it would help me give you more infos.

My internet connection quality is too low to test my changes.
but using your first autoBuildFlags should output those new lines:
info config cmake flag contains "-DBUILD_LIST=core,calib3d" automatic cmake flags are now disabled.
info config adding cmake flag "-DCMAKE_BUILD_TYPE=RELEASE"
info config adding cmake flag "-DBUILD_LIST=core,calib3d"
info config adding cmake flag "-DWITH_IPP=OFF"
info config adding cmake flag "-DWITH_V4L=OFF"
info config adding cmake flag "-DWITH_FFMPEG=OFF"
info config adding cmake flag "-DWITH_GSTREAMER=OFF"
info config adding cmake flag "-DWITH_GTK=OFF"
info config adding cmake flag "-DWITH_PROTOBUF=OFF"
info config adding cmake flag "-DBUILD_PROTOBUF=OFF"
info config adding cmake flag "-DOPENCV_DNN_OPENCL=OFF"
info config adding cmake flag "-DWITH_WIN32UI=OFF"
info config adding cmake flag "-DWITH_PNG=OFF"
info config adding cmake flag "-DWITH_JPEG=OFF"
info config adding cmake flag "-DWITH_TIFF=OFF"
info config adding cmake flag "-DWITH_WEBP=OFF"
info config adding cmake flag "-DWITH_OPENJPEG=OFF"
info config adding cmake flag "-DWITH_JASPER=OFF"
info config adding cmake flag "-DWITH_OPENEXR=OFF"
info config adding cmake flag "-DBUILD_opencv_python=OFF"
info config adding cmake flag "-DBUILD_opencv_java=OFF"

try to check your auto-build.json in the ${OPENCV_BUILD_ROOT}/version/
the file contains the effective cmake config parameters.

For the record :
In order to get the logs i need to do
npm install --foreground-scripts

see https://github.com/npm/cli/issues/3347

fixed in v6.4.3 thanks @UrielCh


unify font Draw and DrawRunes

I don't think the small allocation savings from supporting two code paths is worthwhile. It translates into a lot of API surface down the road.
But in trying to get rid of one, I discovered they work differently. LayoutRunes+DrawRunes produces different (seemingly incorrect) results compared to Draw. Is this on purpose, @ben-clayton? If not, I'll make LayoutRunes+DrawRunes behave like Draw now and remove Draw.

Nope, they were written to behave similarly, but I can completely believe I've screwed up some of the logic - as you can see it's full of fiddly DIP -> pixel space conversion, ascent and alignment calculations.
I'm not opposed to killing Draw and keeping the more explicit APIs.

I believe this to be fixed. Closing.