text:
Cannot identify ['] in room topic

Run npm run doctor or wechaty run doctor(for docker user), paste output here
Starting Wechaty ... v0.6.22

> wechaty@0.6.22 doctor /wechaty
> ts-node bin/doctor

SILL Brolog WECHATY_LOG set level to SILLY
SILL StateMonitor constructor(Wechaty, standby)
VERB Wechaty contructor()
SILL Wechaty version() test Error: spawnSync git ENOENT

#### Wechaty Doctor

1. Wechaty version: 0.6.22
2. Linux x64 version 3.16.0-4-amd64 memory 244/2010 MB
3. Docker: true
4. Node version: v7.2.0

Expected behavior
try to invite contact to room when room topic contains "'"
but failed.
Log says WARN PuppetWeb roomFind(c => c === 'Wechaty Developers' Home') rejected: unknown error: Unexpected identifier  I thought it begin to find Wechaty Developers not Wechaty Developers' Home due to "'"
Steps to reproduce the behavior (and fixes, if any)
code as follows:
import {
  Wechaty
  , Room
} from 'wechaty'

const bot = Wechaty.instance()
bot
.on('scan', (url, code) => {
  console.log(`${url}\n[${code}] Scan QR Code in above url to login: `)
})

.on('login',user => {
  console.log(`${user}login`)
})

.on('message',async function(m){
    const content = m.content()
    const contact = m.from()
    if(/wechaty/.test(content)){
        let weRoom = await Room.find({topic:"Wechaty Developers' Home"})
        if(weRoom){
            weRoom.add(contact)
            contact.say('Welcome')
        }
    }
})

.init()

Paste the full output logs here with WECHATY_LOG=silly set
SILL Message constructor() SN:5
SILL Message ready()
SILL Contact constructor(@657d1f0799287f91cb46e7eef77757d2c8f4dcca4ab5e6522dd3c457ebaf9f5d)
SILL Contact ready()
SILL Contact get contact via PuppetWeb
SILL PuppetWebBridge getContact() retryPromise: attampt 1/35 time for timeout 306250
VERB PuppetWebBridge proxyWechaty(getContact, @657d1f0799287f91cb46e7eef77757d2c8f4dcca4ab5e6522dd3c457ebaf9f5d)
SILL PuppetWebBridge execute()
SILL PuppetWebBrowser Browser.execute("return typeof WechatyBro === "undefined"")
SILL StateMonitor Browser:target() open
SILL StateMonitor Browser:current() open
SILL PuppetWebBridge execute()
SILL PuppetWebBrowser Browser.execute(" const callback = arguments[arguments.length - 1] const isAsync = (typeof  ... ")
SILL StateMonitor Browser:target() open
SILL StateMonitor Browser:current() open
SILL Contact contactGetter(@657d1f0799287f91cb46e7eef77757d2c8f4dcca4ab5e6522dd3c457ebaf9f5d) resolved
SILL Contact ready()
SILL Message ready()
SILL Contact ready()
SILL Contact ready()
VERB Room find({ topic: Wechaty Developers' Home })
VERB Room findAll({ topic: Wechaty Developers' Home })
VERB PuppetWebBridge proxyWechaty(roomFind, c => c === 'Wechaty Developers' Home')
SILL PuppetWebBridge execute()
SILL PuppetWebBrowser Browser.execute("return typeof WechatyBro === "undefined"")
SILL StateMonitor Browser:target() open
SILL StateMonitor Browser:current() open
SILL PuppetWebBridge execute()
SILL PuppetWebBrowser Browser.execute(" const callback = arguments[arguments.length - 1] const isAsync = (typeof  ... ")
SILL StateMonitor Browser:target() open
SILL StateMonitor Browser:current() open
SILL PuppetWebBrowser execute() script:  const callback = arguments[arguments.length - 1]
      const isAsync = (typeof callback === 'function')
      return WechatyBro
              .roomFind
              .apply(undefined
                      , isAsync
                        ? JSON.parse(decodeURIComponent(window.atob('JTVCJTIyYyUyMCUzRCUzRSUyMGMlMjAlM0QlM0QlM0QlMjAnV2VjaGF0eSUyMERldmVsb3BlcnMnJTIwSG9tZSclMjIlNUQ='))).concat(callback)
                        : JSON.parse(decodeURIComponent(window.atob('JTVCJTIyYyUyMCUzRCUzRSUyMGMlMjAlM0QlM0QlM0QlMjAnV2VjaGF0eSUyMERldmVsb3BlcnMnJTIwSG9tZSclMjIlNUQ=')))
                    )

WARN PuppetWebBrowser execute() exception: unknown error: Unexpected identifier
  (Session info: chrome=53.0.2785.92)
  (Driver info: chromedr, WebDriverError: unknown error: Unexpected identifier
  (Session info: chrome=53.0.2785.92)
  (Driver info: chromedriver=2.22 (5e2d5494d735a71aa5c2e7ef9bf5ce96945e92e9),platform=Linux 3.16.0-4-amd64 x86_64)
    at Object.checkLegacyResponse (/wechaty/node_modules/selenium-webdriver/lib/error.js:505:15)
    at parseHttpResponse (/wechaty/node_modules/selenium-webdriver/lib/http.js:509:13)
    at doSend.then.response (/wechaty/node_modules/selenium-webdriver/lib/http.js:440:13)
    at process._tickDomainCallback (internal/process/next_tick.js:129:7)
WARN PuppetWebBridge execute() exception: unknown error: Unexpected identifier
  (Session info: chrome=53.0.2785.92)
  (Driver info: chromedriver=2.22 (5e2d5494d735a71aa5c2e7ef9bf5ce96945e92e9),platform=Linux 3.16.0-4-amd64 x86_64)
VERB PuppetWebBridge proxyWechaty(roomFind, c => c === 'Wechaty Developers' Home')
WARN PuppetWebBridge proxyWechaty() exception: unknown error: Unexpected identifier
  (Session info: chrome=53.0.2785.92)
  (Driver info: chromedriver=2.22 (5e2d5494d735a71aa5c2e7ef9bf5ce96945e92e9),platform=Linux 3.16.0-4-amd64 x86_64)
ERR PuppetWebBridge roomFind() exception: unknown error: Unexpected identifier
  (Session info: chrome=53.0.2785.92)
  (Driver info: chromedriver=2.22 (5e2d5494d735a71aa5c2e7ef9bf5ce96945e92e9),platform=Linux 3.16.0-4-amd64 x86_64)
WARN PuppetWeb roomFind(c => c === 'Wechaty Developers' Home') rejected: unknown error: Unexpected identifier
  (Session info: chrome=53.0.2785.92)
  (Driver info: chromedriver=2.22 (5e2d5494d735a71aa5c2e7ef9bf5ce96945e92e9),platform=Linux 3.16.0-4-amd64 x86_64)
VERB Room findAll() rejected: unknown error: Unexpected identifier
  (Session info: chrome=53.0.2785.92)
  (Driver info: chromedriver=2.22 (5e2d5494d735a71aa5c2e7ef9bf5ce96945e92e9),platform=Linux 3.16.0-4-amd64 x86_64)
(node:22) UnhandledPromiseRejectionWarning: Unhandled promise rejection (rejection id: 1): Error: no room found
(node:22) DeprecationWarning: Unhandled promise rejections are deprecated. In the future, promise rejections that are not handled will terminate the Node.js process with a non-zero exit code.

Good catch!
The latest code of master should fix this, please confirm.

fix
Thanks

authors: lijiarui zixia

repo: wechaty/wechaty


text:
Adding an element to the bottom on an empty grid throws a graphql error

When you use the new "Add to bottom" button to add an element to the bottom on an empty page you'll receive a graphql error

The element gets added because after a page refresh it is added to the grid, so it seem to break on the callback.

Should be fixed in https://github.com/wedevelopnl/silverstripe-elemental-grid/pull/25

source: gharchive/issue

authors: DRuiter erikfrerejean

repo: wedevelopnl/silverstripe-elemental-grid

license: MIT

license_type: permissive

license_source: github-api


text:
Parent Directory Extraction Management

I was thinking about making a contribution to provide parent directory management within Archive itself, instead of just when using the FileManager extension.
Basically, I envision adding a parentDirectory: String? property to Archive that would be utilized in both extraction and compression.
When opening an Archive in .read mode, it would parse the contents and determine if there's a parent directory and, if so, populate the value. During extraction, you'd have the option to include or omit the parent directory. Entrys provided from the Archive could either reflect this value in their path or have an additional pathFromParent property.
When opening an Archive in .create or .update modes, it would either append or ignore the parent directory as appropriate when adding content.
Is there interest for this? Time permitting, I would contribute this myself, but would want to make sure the time invested would be worth it.

Hi Michael,
Archive implements a subset of the ZIP specification  and only contains low-level code that's required to archive/unarchive from/to the file system. All convenience/helper code is implemented in the FileManager extension or can be customized by API users in the closure-based Archive reading/writing methods.
Since the ZIP specification also doesn't outline a concept of hierarchy/parent-child relationships at all (e.g. .file entries can implicitly create directory trees, .directory entries are optional, ...), I'd prefer to keep all hierarchy related stuff in the extension.
Do you have a specific use case that'd benefit from having the parent directory handling in the Archive type?

Do you have a specific use case that'd benefit from having the parent directory handling in the Archive type?

Yes - hence the idea's initial inception. :)
I have a need to inspect individual "root level" Entrys within an Archive that is agnostic to whether there's a parent directory or not (as in, if there is a parent directory, it needs to treat the parent directory contents as if they are in the root).

Since the ZIP specification also doesn't outline a concept of hierarchy/parent-child relationships at all (e.g. .file entries can implicitly create directory trees, .directory entries are optional, ...), I'd prefer to keep all hierarchy related stuff in the extension.

What if it was done on an Archive extension, or even a second library in the Swift Package? I think there would need to be some minimal support in the base class, but the majority of it could be external, in a Conveniences package.

I think there would need to be some minimal support in the base class, ...

The behavior you are describing in your initial comment can be implemented with the existing extract/addEntry methods outside of the library without any changes to Archive - you have access to .path and the read/write closures allow you to freely choose what happens with the extracted/added entry. Or am I missing something?
I'd prefer to keep the core API surface area small but provide extensible methods (like the existing, closure-based read/write helpers) for API consumers.

authors: mredig weichsel

repo: weichsel/ZIPFoundation

license: mit

license_source: bigquery


text:
Fix ILP solver/motile

Motile recently updated their API, https://github.com/funkelab/motile/pull/108.
This PR fixes it.
I haven't tested locally, I did similar changes in an student's computer at DL@MBL

Lgtm, thanks @JoOkuma.

source: gharchive/pull-request

authors: JoOkuma bentaculum

repo: weigertlab/trackastra


text:
Cannot reproduce the result

I strictly follow the guidance and train the model with
python train.py --data_path ~/data/fMRI-reconstruction-NSD/ --fmri_encoder "brainxs" --subj 1 --model_save_path train_logs/demo_single_subject/sub01_dim1024

and inference by
python inference.py --data_path ~/data/fMRI-reconstruction-NSD/ --fmri_encoder "brainx" --subj 1 --prompt "Describe this image <image> as simply as possible." --brainx_path train_logs/demo_single_subject/sub01_dim1024/last.pth --save_path evaluation/eval_caption/brainx

And evaluate it with BrainHub
python eval_caption.py ../UMBRAE/umbrae/evaluation/eval_caption/brainx/sub01_dim1024/fmricap.json  caption/test_images --references_json caption/fmri_cococap.json

However, I got
BLEU-1: 0.3903
BLEU-2: 0.1504
BLEU-3: 0.0486
BLEU-4: 0.0182
METEOR: 0.0798
ROUGE: 0.2735
CIDER: 0.0331
SPICE: 0.0155
CLIPScore: 0.4534
RefCLIPScore: 0.532

I can reproduce the results with the file https://github.com/weihaox/BrainHub/blob/main/caption/comparison/umbrae/sub01_decoded_caption.json and the checkpoint https://huggingface.co/datasets/weihaox/brainx/resolve/main/train_logs/brainx/last.pth you provided. That means the problem is in the training pipeline.
here are the train/val loss curves

This could be caused by various factors, such as package versions. I will train the model myself to see if I can reproduce the issue. In the meantime, could you provide the results and the pretrained model, and more details about configurations, including the GPU used and package versions?

Sure. Here are my package versions
absl-py==2.1.0
accelerate==0.19.0
addict==2.4.0
aiofiles==23.2.1
aiohappyeyeballs==2.4.0
aiohttp==3.10.5
aiosignal==1.3.1
annotated-types==0.7.0
anyio==4.4.0
async-timeout==4.0.3
attrs==24.2.0
bitsandbytes==0.43.3
braceexpand==0.1.7
certifi==2024.8.30
charset-normalizer==3.3.2
click==8.1.7
contourpy==1.3.0
cycler==0.12.1
dataclasses==0.6
datasets==2.21.0
dill==0.3.8
einops==0.8.0
einops-exts==0.0.4
exceptiongroup==1.2.2
fastapi==0.112.2
ffmpy==0.4.0
filelock==3.15.4
fonttools==4.53.1
frozenlist==1.4.1
fsspec==2024.6.1
gradio==4.42.0
gradio_client==1.3.0
grpcio==1.66.1
h11==0.14.0
httpcore==1.0.5
httpx==0.27.2
huggingface-hub==0.24.6
idna==3.8
importlib_metadata==8.4.0
importlib_resources==6.4.4
Jinja2==3.1.4
joblib==1.4.2
kiwisolver==1.4.5
kornia==0.7.3
kornia_rs==0.1.5
llvmlite==0.43.0
Markdown==3.7
markdown-it-py==3.0.0
MarkupSafe==2.1.5
matplotlib==3.9.2
mdurl==0.1.2
mmengine==0.10.4
mpmath==1.3.0
multidict==6.0.5
multiprocess==0.70.16
networkx==3.3
nltk==3.9.1
numba==0.60.0
numpy==2.0.2
nvidia-cublas-cu12==12.1.3.1
nvidia-cuda-cupti-cu12==12.1.105
nvidia-cuda-nvrtc-cu12==12.1.105
nvidia-cuda-runtime-cu12==12.1.105
nvidia-cudnn-cu12==9.1.0.70
nvidia-cufft-cu12==11.0.2.54
nvidia-curand-cu12==10.3.2.106
nvidia-cusolver-cu12==11.4.5.107
nvidia-cusparse-cu12==12.1.0.106
nvidia-nccl-cu12==2.20.5
nvidia-nvjitlink-cu12==12.6.68
nvidia-nvtx-cu12==12.1.105
opencv-python==4.10.0.84
orjson==3.10.7
packaging==24.1
pandas==2.2.2
pillow==10.4.0
platformdirs==4.2.2
protobuf==5.28.0
psutil==6.0.0
pyarrow==17.0.0
pycocoevalcap==1.2
pycocotools==2.0.8
pydantic==2.8.2
pydantic_core==2.20.1
pydub==0.25.1
Pygments==2.18.0
pynndescent==0.5.13
pyparsing==3.1.4
python-dateutil==2.9.0.post0
python-multipart==0.0.9
pytz==2024.1
PyYAML==6.0.2
regex==2024.7.24
requests==2.32.3
rich==13.8.0
ruff==0.6.3
safetensors==0.4.4
scikit-learn==1.5.1
scipy==1.14.1
semantic-version==2.10.0
sentencepiece==0.2.0
shellingham==1.5.4
six==1.16.0
sniffio==1.3.1
starlette==0.38.4
sympy==1.13.2
tensorboard==2.17.1
tensorboard-data-server==0.7.2
termcolor==2.4.0
threadpoolctl==3.5.0
tokenizers==0.19.1
tomli==2.0.1
tomlkit==0.12.0
torch==2.4.0
torchvision==0.19.0
tqdm==4.66.5
transformers==4.44.2
triton==3.0.0
typer==0.12.5
typing_extensions==4.12.2
tzdata==2024.1
umap-learn==0.5.6
urllib3==2.2.2
uvicorn==0.30.6
wcwidth==0.2.13
webdataset==0.2.100
websockets==12.0
Werkzeug==3.0.4
xxhash==3.5.0
yapf==0.40.2
yarl==1.9.7
zipp==3.20.1

My gpu
NVIDIA H100 80GB HBM3

I have uploaded the model weights and results to https://drive.google.com/drive/folders/1vwEu3o9e-kllu9YRgFv_KxP8Uw1tUuuW?usp=sharing.
Please let me know if you have any questions! I hope I can make your work more reproducible!

Thanks for sharing. I'm looking into it.

Hi @Boltzmachine,
The issue isn't with the training pipeline; it lies in inference.py, which was originally designed for the BrainX (cross-subject) model. I've added support for BrainXS (single-subject). Please see commit for details. The quantitative evaluation results using your provided checkpoints are as follows:
BLEU-1: 0.5776
BLEU-2: 0.3788
BLEU-3: 0.2491
BLEU-4: 0.1670
METEOR: 0.1787
ROUGE: 0.4187
CIDER: 0.5101
SPICE: 0.1162
CLIPScore: 0.6603
RefCLIPScore: 0.7184

Please have a check and let me know if it works for you.

I have also retrained the BrainXS model from scratch using the default settings. Here are the results:
BLEU-1: 0.5757
BLEU-2: 0.3789
BLEU-3: 0.2506
BLEU-4: 0.1672
METEOR: 0.1834
ROUGE: 0.4188
CIDER: 0.5206
SPICE: 0.1161
CLIPScore: 0.6657
RefCLIPScore: 0.7238

Still not working. My inference command is
 CUDA_VISIBLE_DEVICES=1 python inference.py --data_path ~/data/fMRI-reconstruction-NSD/ --fmri_encoder "brainx" --subj 1 --prompt "Describe this image <image> as simply as possible." --brainx_path train_logs/demo_single_subject/sub01_dim1024/last.pth --save_path evaluation/eval_caption/brainx

Is it correct?

Oh never mind just found I need to set --fmri_encoder to brainxs. And it works! Thanks so much!

Hello, I can't reproduce the result either. when using the last.pth you provided, I can get the correct result, but when I follow “python train.py --data_path 'nsd_data' --fmri_encoder 'brainxs' --subj 1--model_save_path 'train_logs/demo_single_subject/sub01_dim1024' ”，The result from this training is only :
BLEU-1: 0.4807
BLEU-2: 0.2732
BLEU-3: 0.1562
BLEU-4: 0.0977
METEOR: 0.1321
ROUGE: 0.3469
CIDER: 0.2367
SPICE: 0.0694
CLIPScore: 0.5830
RefCLIPScore: 0.6457

hi，the pretrained weight is as follows and I use the correct inference command.
 https://drive.google.com/file/d/1yovTukH-Hqk3MqSdEuSjnldjObq3iimi/view?usp=sharing
---Original---
From: "Weihao @.>
Date: Mon, Nov 18, 2024 17:32 PM
To: @.>;
Cc: @.@.>;
Subject: Re: [weihaox/UMBRAE] Cannot reproduce the result (Issue #5)
@xqoby Could you share the pretrained weight?
—
Reply to this email directly, view it on GitHub, or unsubscribe.
You are receiving this because you were mentioned.Message ID: @.***>

Please share the doc with proper access permissions. Open a new issue if possible.

Please share the document with proper access permissions. Open a new issue if possible.

authors: Boltzmachine bdseal weihaox xqoby

repo: weihaox/UMBRAE


text:
可以加个交互，鼠标移动到可编辑区域（列如颜色）变为小手

https://github.com/weijian-zhu/measure.js/pull/37

authors: Rachelllllllllll weijian-zhu


text:
package.json: Update @patternfly/react-icons package dependency

Check for any outstanding update of point version of any outstanding NPM package dependency

[ ] npm-update

npm-update in progress on 4-ci-srv-04.
Log: https://logs.cockpit-project.org/logs/npm-update-910-20200318-115050/

npm-update @patternfly/react-icons done: https://github.com/cockpituous/welder-web/commits/npm-update-@patternfly/react-icons-20200318-115151

Please manually check features related to these files:
components/ListView/BlueprintsDataList.js:import { PficonTemplateIcon } from "@patternfly/react-icons";
components/ListView/ListItemImages.js:import { BuilderImageIcon } from "@patternfly/react-icons";
components/ListView/ListItemUploads.js:import { CaretDownIcon, ServiceIcon } from "@patternfly/react-icons";
package.json:    "@patternfly/react-icons": "3.15.12",

repo: weldr/cockpit-composer


text:
Relation-embedder ECS to lambda

Part of https://github.com/wellcomecollection/platform/issues/5784

One of the main concerns WRT the relation_embedder is the indices' read/write capacity:

it reads from the merged index and writes to the denormalised index
there is existing config to manage the input/load so as to avoid memory and ES (413: Content Too Large) errors

We should replicate this in a relation_embedder lambda by limiting the queue concurrency, scroll size and index batch size

Closing as done.

authors: agnesgaroux kenoir

repo: wellcomecollection/catalogue-pipeline


text:
Delete ingested Proqest MMs for BagIt error clean up

We are looking at recent Proquest errors that need cleaned up. We've once again run into the BagIt error issue (Exception in thread "main" java.lang.NumberFormatException: For input string: "hin-wel-all-00001102"). I've written this issue up so as a reminder, this is the reason we have the error:

One or more parts of the multiple manifestation were ingested prior to migration and the file names were not renamed from the bnumber_hin_wel_all-00000XXX_000X.jp2 format, which does not specify which manifestation these files belong to. This file name type was acceptable in Preservica but the storage service requires files to be renamed into the bnumber_000X_000X.jp2 format, which does specify the manifestation, right after the bnumber.
When ingesting another MM item, the BagIt tool looks up for already existing manifestations in order to create a fetch file for all files that are not updated by the current manifestation. Because the file name format bnumber_hin_wel_all-00000XXX_000X.jp2 does not have the manifestation order number, the BagIt tool doesn't know which files belongs to which manifestation and therefore, cannot ingest the new item.

We can't delete these through the Delete bnumber plugin ourselves as we run into the same BagIt Error. The solution has been to:

Deleting the bnumber from the Storage Service using the Delete bnumber plugin itself will not work due to the same reasons as above: the BagIt tool doesn't know which files belongs to which manifestation and therefore cannot bag the item. Instead, ask Intranda to delete the item via the plugin and manipulate the task BagIt creation and upload by adding a parameter "purge":true to the json.

Can we please "delete" these items from the storage service so we can get everything fixed and ingested?
b12947696_0002
b12947696_0004
b12947696_0005
b1313629x_0001
b13149040_0002
b13149040_0005
b10004300_0002
b10005614_0001
b10916441_0001
b11533353_0001
b11533353_0003
b12201777_0002
b12645163_0001
b12838767_0001
b12946448_0002
b1294662x_0001
b12946795_0002
b12948457_0001
b10326273_0002

"project:SampleProject" "stepopen:automatic MMO archive status check" I've started the delete from storage service process for these now

These have all had a deletion task started for them now.

We have a few more to finish up this work that was left off the previous list:
b11533353_0001
b11533353_0002
b12181110_0002
b10005614_0001

all b-numbers are deleted

authors: aray-wellcome rsehr

repo: wellcomecollection/goobi-infrastructure


text:
Event structure

👇 In the booking info module on the right
Drop in
We programme some drop-in events every month. For these events,
you can just turn up. There's usually room for everyone.
Cost
Heading: Guarateed entry
With our paid events, you are guaranteed entry to the event.
We're unable to offer any refunds unless the event is cancelled.
Concessions are available for people over 60, students, people
on Jobseeker's Allowance and people registered as disabled.
An additional companion ticket for people registered as disabled
is available for free.
If completely sold out
Heading: First come, first seated
Please note, booking a ticket for a free event does not
guarantee a place on the day. Doors usually open 15 minutes
before an event starts, and you can take your seats in order of
arrival. We advise arriving 10 minutes before the event is
scheduled to start.
We hold some spaces for people with access requirements.
Please email
access@wellcomecollection.org
if you would like to request one of these spaces.
If anything else:
Heading: Limited spaces available
Doors will open for this event 15 minutes before the event
starts. Spaces are first come, first served and may run out if
we are busy.
Custom booking info from prismic
heading: Booking information

👇 in the body of the event

Event format description.
If someone puts these into Prismic they'll show.
Part of {eventseries}
event series description
For audience
audience description
Interpretations
interpretation descrition
Contributors

Something we don't have is place.

See #3180

Fixed in #3180


text:
Alternative quote style

To accommodate recent articles which feature a quote directly after the stand-first, we need to add a new quote style which can only be used in this particular area of an article.
Text size is same as normal body copy. Indent text 30px from the left and add larger quote mark (Helvetica). Quote reference name is same style as other quote styles

Discussed this design with @Norvard today and we agreeed that it looks better with the bold quote to start the epigraph, but leave off the smaller quote marks at closing. Looks good as a short one/two-liner as well.

I'd like to make sure we use this small quote style in articles now.
https://cardigan.wellcomecollection.org/components/detail/blockquote--small.html
@jamesgorrie @davidpmccormick @gestchild What needs to happen from an editorial POV to style these quotes in articles?
@dannybirchall @RussellDornan @Norvard

Nothing from an editorial POV.
We're probably best to name this blockquote, and the other pullQuote for clarity.

...and correctness! :nerd_face:

authors: Norvard jamesgorrie jennpb


text:
Add body-content type styles

Adding some h2, ul, a and ::selection styles for content contained within a class="body-content" block. This should allow styling of e.g. article content elements without requiring us to class every element during parsing.
The styles I've added so far are based on type styles from the visual designs, but I imagine there will likely be other elements that we want to have default styling.
Do we think e.g. tables should belong in here, or would we specifically add classes to them during the parsing stage? Any other obvious omissions.

Do we think e.g. tables should belong in here

I would be be tempted to wait till we can receive them from the CMS - which we currently can't.

authors: davidpmccormick jamesgorrie


text:
怎么设置指示器大小

用资源图片作为指示器时，怎么设置指示器大小。
同时怎么设置指示器和banner的间距，让其距离banner图片较远。
banner.setIndicatorRes(R.drawable.banner_indicator, R.drawable.banner_indicator_selected);

@siny-yao  用资源图片的时候为了防止变形是没有暴露方法去修改指示器大小的，只有让 UI 切个合适的图片，设置指示器和 banner 的间距用 indicator_margin 属性

indicator_margin 属性会让指示器网上，我想让指示器在banner下边，并且有一段距离

@siny-yao 看 #13 ，demo 中有的

刚好看到，已经实现了，谢谢大大

@siny-yao 看 #13 ，demo 中有的
刚好看到，已经实现了，谢谢大大

设置指示器一个长条形，一个圆形，被裁减了，应该是被写死宽高

authors: ShuaiJing siny-yao wenchaosong

repo: wenchaosong/Banner


text:
refactor(deepspeed): Refine traning code

Brief

split train.py & executor.py into multiple unified API calls
launch torchddp & deepspeed via torchrun

TODO (in current PR)

[ ] check training is correct (both ddp & ds)

TODO (in next PR)

[ ] impl model.join for deepspeed

Training Pipeline:
    # 1. Read config
    with open(args.config, 'r') as fin:
        configs = yaml.load(fin, Loader=yaml.FullLoader)
    if len(args.override_config) > 0:
        configs = override_config(configs, args.override_config)

    # 2. Init env for ddp OR deepspeed
    world_size, local_rank, rank = init_distributed(args)

    # 3. Do some sanity checks and save config to arsg.model_dir
    configs = check_modify_and_save_config(args, configs)

    # 4. Get dataset & dataloader
    train_dataset, cv_dataset, train_data_loader, cv_data_loader = \
        init_dataset_and_dataloader(args, configs)

    # 5. Init asr model from configs
    infos, model = init_model(args, configs)

    # 6. Check model is jitable & print model archtectures
    trace_and_print_model(model, enable_trace=True)

    # 7. Tensorboard summary
    writer = init_summarywriter(args)

    # 8. Dispatch model from cpu to gpu
    model, device = wrap_cuda_model(args, model)

    # 9. Get optimizer & scheduler
    model, optimizer, scheduler = init_optimizer_and_scheduler(
        args, infos, configs, model)

    # 10. Save checkpoints
    save_model(args, model, tag="init", infos=None)

    # 11. Get executor
    executor = init_executor(infos)

    # 12. Init scaler, used for pytorch amp mixed precision training
    scaler = None
    if args.use_amp:
        scaler = torch.cuda.amp.GradScaler()

    # 13. Start training loop
    for ...

To better organize arguments, this PR also split and classify different args into different category.
def get_args():
    parser = argparse.ArgumentParser(description='training your network')
    parser.add_argument...
    parser.add_argument...
    parser.add_argument...

===>
def get_args():
    parser = argparse.ArgumentParser(description='training your network')
    parser = add_model_args(parser)
    parser = add_dataset_args(parser)
    parser = add_ddp_args(parser)
    parser = add_deepspeed_args(parser)

Test Script:
bash run.sh --stage 4 --stop_stage 4 --data_type raw --train_set dev --train_engine torch_ddp --dir exp/conformer

bash run.sh --stage 4 --stop_stage 4 --data_type raw --train_set dev --train_engine deepspeed --dir exp/conformer_ds

可以把optimizer和scheduler分开
把optimzier传给scheduler
可以方便使用者hack各种optimizer 比如lion adamw等

Impl join for deepspeed:
for batch_idx, batch in enumerate(data_loader):
     if wenet_join(args, device, group_join):
         break
    ...  # training step

where wenet_join is defined as:
test

The lines of the core files:

wenet/bin/train.py: 425 -> 157
wenet/utils/excutor.py: 204 -> 122

deepspeech 现在还有启动hang的问题吗？

deepspeecd 现在还有启动hang的问题吗？

没有了，服务器有多个网卡，NCCL_SOCKET_IFNAME指定网卡就可以handshake了

重构的版本有出现显存占用变多，训练变慢的情况吗？

重构的版本有出现显存占用变多，训练变慢的情况吗(torch_ddp)？

有对比数据吗？是不是从某个checkpoint开始恢复训练的（如果是，那么现象估计是0号卡显存明显高于其他卡，要修改checkpoint.py的load checkpoint函数，torch.load要用cpu）训练变慢是因为torchddp也用了wenetjoin，额外增加了30s超时，小数据上可能会比较明显地增加端到端时间

重构的版本有出现显存占用变多，训练变慢的情况吗(torch_ddp)？

version
显存占用
训练时长(100 batch)

Base
15~20G
35 s

Refactor
35~40G
70 s

我这边观察到的现象是这样的，没有加载模型，也跳过了wenet_join()，你们没有出现这个问题是吗？

重构的版本有出现显存占用变多，训练变慢的情况吗(torch_ddp)？

version	显存占用	训练时长(100 batch)
Base	15~20G	35 s
Refactor	35~40G	70 s
我这边观察到的现象是这样的，没有加载模型，也跳过了wenet_join()，你们没有出现这个问题是吗？

没有，我这一直用2080ti做的实验，原来的recipe，batch最高开到16，refactor之后同样的配置是可以train的

重构的版本有出现显存占用变多，训练变慢的情况吗(torch_ddp)？

version	显存占用	训练时长(100 batch)
Base	15~20G	35 s
Refactor	35~40G	70 s
我这边观察到的现象是这样的，没有加载模型，也跳过了wenet_join()，你们没有出现这个问题是吗？

没有，我这一直用2080ti做的实验，原来的recipe，batch最高开到16，refactor之后同样的配置是可以train的，方便加个微信吗，沟通更快点，微信号：currycode

好的，加你了，麻烦通过一下。

update: 8*2080ti， torch 1.13.0，测试结果显示新旧代码loss曲线和训练耗时是一致的

torch从1.12.0更新到1.13.0之后显存占用跟速度正常了

@whiteshirt0429  @robin1001 @Mddct, I think this PR is ready for a final review

Great job! 后续我们精简注释，把如何做多机多卡支持写到文档引用就行。

authors: Mddct kobenaxie robin1001 xingchensong


text:
Fixed formatting to comply with Checkstyle standards

Fixed indentation and shortened some lines that exceeded 100 characters.

Codecov Report

Merging #126 into master will decrease coverage by 0.14%.
The diff coverage is 61.9%.

@@             Coverage Diff              @@
##             master     #126      +/-   ##
============================================
- Coverage     79.37%   79.22%   -0.15%
  Complexity      226      226
============================================
  Files            28       28
  Lines          1057     1064       +7
  Branches        105      106       +1
============================================
+ Hits            839      843       +4
- Misses          189      192       +3
  Partials         29       29

Impacted Files
Coverage Δ
Complexity Δ

...nnect/bigquery/retrieve/MemorySchemaRetriever.java
100% <ø> (ø)
7 <0> (ø)
:arrow_down:

...ka/connect/bigquery/config/BigQuerySinkConfig.java
78.78% <ø> (ø)
20 <0> (ø)
:arrow_down:

...ect/bigquery/write/row/AdaptiveBigQueryWriter.java
0% <0%> (ø)
0 <0> (ø)
:arrow_down:

...om/wepay/kafka/connect/bigquery/SchemaManager.java
61.53% <0%> (-2.47%)
3 <0> (ø)

...fka/connect/bigquery/write/row/BigQueryWriter.java
89.47% <100%> (+0.18%)
19 <0> (ø)
:arrow_down:

...wepay/kafka/connect/bigquery/BigQuerySinkTask.java
71.55% <100%> (+0.75%)
22 <0> (ø)
:arrow_down:

...onnect/bigquery/config/BigQuerySinkTaskConfig.java
93.02% <100%> (ø)
4 <0> (ø)
:arrow_down:

repo: wepay/kafka-connect-bigquery


text:
Publish pictures Pibooth

Hello
I'm looking for a solution to use photos taken with Pibooth and publish them on my Facebook or Instagram profile or send them to a cloud (online folder) or through a QR code integration. Is there a way to integrate command lines to your program to have this feature via a dedicated GPIO button? Thank you !

I've been looking for something similar, but I really have no idea of how to do it .
My idea would be to have one setting to either send or store  pictures in a cloud folder (via a account I guess) , so people just have to access this through a link.
Here is some stuff I found on internet that might be a lead:
https://github.com/wyolum/TouchSelfie
https://github.com/laurentalacoque/TouchSelfie-extended/wiki/CreateGoogleProject
maybe it can help!
Aurel

Hi @DEhrhardt ,
Thanks for your post, we have imagined the same solution but never succeed.
Have a look to https://github.com/werdeil/pibooth/blob/master/docs/lychee.rst
Maybe we can improve the doc with your feedback.
anxuae

hi all
I got some basic "sharing" by using andreafabrizi's Dropbox-Uploader script.
Basically connected the script to a shared app in dropbox and added a crontab job to upload pibooth images folder every 2 minutes.
You can share the dropbox folder to whoever you want and from there.. it is "their thing" :-)
I'm not a developer and this is not too much, but it is enough to me. Hope it helps

Example on how to upload pictures on a FTP server will be provided with the new plugin system.

New plugin system will let you the possibility to add custom code to upload pictures.
Will be available in next pibooth major release (date to be planned).
See plugins example at https://github.com/werdeil/pibooth/blob/master/docs/plugin.rst .

repo: werdeil/pibooth


text:
chore: release 1.2.269

:robot: I have created a release *beep* *boop*
1.2.269 (2023-11-10)
Bug Fixes

werf-in-image: unable to update tuf meta (#5846) (fd41be1)

This PR was generated with Release Please. See documentation.

:robot: Release is at https://github.com/werf/werf/releases/tag/v1.2.269 :sunflower:

repo: werf/werf


text:
External Ip Not Working

Cant seem to connect to external ip address. Is there anyway i can do this?

I have had mixed reports about that bug, I will try to narrow down what’s
wrong next week. Thank you for your report!
On Thu 22. Feb 2018 at 06:07, Logan RIos notifications@github.com wrote:

Cant seem to connect to external ip address. Is there anyway i can do this?
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
https://github.com/werkamsus/Lilith/issues/11, or mute the thread
https://github.com/notifications/unsubscribe-auth/ABcNuxn6qlCmzq7xoDEaUFCMWRnjtJtlks5tXPYlgaJpZM4SOv1U
.

See #12

repo: werkamsus/Lilith


text:
Inspect Option Support?

Should have support for:
inspect:
Inspect defaults to true which is great for dev environments, but not so good if it's a production one.

entrypoint.zip

repo: wernight/docker-ngrok


text:
Is the API down?

I'm just seeing a Cloudflare error page. Something up? @andrieslouw @kleisauke (friendly poke)

One of our servers seems to have issues, working on it.

Thanks for the super quick response @andrieslouw - much appreciated! <3

Everything looks fine to me now. Super fast'n smooth.

Immediately took it out of the loadbalancers, but I am still working on the server itself, seems to have been some filesystem issues.

Found & fixed: we recently (API 5) changed the location of some of the log-files, but forgot to exclude this new path from backups.
Issue: Backup-server tried to backup the access-log of nginx (which was still being written to), which, after ~30 hours, caused the filesystem to limp into read-only mode. This caused nginx to hang because it couldn't read nor write to the logfile anymore. Issue was amplified because we gzip (all) logfiles on-the-fly, so the file needs to be read before writing any additions to it.
Fix: Excluded the path from backups, and removed all backups of this path (to comply with what is stated in the privacy-policy: max. 7 days of logging, only on server, no backups of logs).

authors: andrieslouw raRaRa

repo: weserv/images


text:
grey div

Hello everybody,
this is my first use of googlemaps plugin, i can't understand why when i run examples i just have a grey div, and the map is not loaded, i'v tried the examples provided with plugin in

---
Want to back this issue? **[Post a bounty on it!](https://www.bountysource.com/issues/10041271-grey-div?utm_campaign=plugin&utm_content=tracker%2F637500&utm_medium=issues&utm_source=github)** We accept bounties via [Bountysource](https://www.bountysource.com/?utm_campaign=plugin&utm_content=tracker%2F637500&utm_medium=issues&utm_source=github).

https://github.com/wf9a5m75/phonegap-googlemaps-plugin/wiki/TroubleShooting:-Blank-Map

thank you very much


text:
Dados das rodadas anteriores

Pessoal, muito massa o API, parabéns a todos. Queria saber se é possível acessar os dados de pontuação das rodadas anteriores ? minha ideia é criar um modelo estatístico.

Sim, esta duvida ja foi respondida aqui:
https://github.com/wgenial/cartrolandofc/issues/14

Vlw, Mateus!

authors: MateusNascimento lourencoerick

repo: wgenial/cartrolandofc