text:
Wink garage door stopped working

Make sure you are running the latest version of Home Assistant before reporting an issue.
You should only file an issue if you found a bug. Feature and enhancement requests should go in the Feature Requests section of our community forum:
Home Assistant release (hass --version):
0.26.3
Python release (python3 --version):
Python 3.4.2
Component/platform:
Wink garage door
Description of problem:
My garage door does not appear in the hass frontend. The rest of my wink devices do appear and are functional.
Expected:
My garage door should be visible. I believe it was before upgrading from 0.26.2 to 0.26.3
Problem-relevant configuration.yaml entries and steps to reproduce:
wink:
  access_token: [redacted]
  refresh_token: [redacted]

group:
  home:
    name: Home
    entities:
      - garage_door.garage_door_opener
      - thermostat.living_room
  default_view:
    name: Default
    icon: mdi:home
    view: yes
    entities:
      - device_tracker.nathan_nathansphone
      - device_tracker.laney_laneysphone
      - sensor.time_to_bus
      - sensor.fastcom_speedtest
      - scene.TurnOnLights
      - scene.JustDeckLightOn
      - group.scripts
      - alarm_control_panel.alarm
      - group.upstairs_lights
      - group.downstairs_lights
      - group.back_deck_lights
      - group.home

Start hass
Verify garage door doesn't appear in the front end
Confirm wink error in log file

Traceback (if applicable):
16-08-22 09:39:06 homeassistant.bootstrap: Error during setup of component wink
Traceback (most recent call last):
  File "/usr/local/lib/python3.4/dist-packages/requests/packages/urllib3/connectionpool.py", line 595, in urlopen
    chunked=chunked)
  File "/usr/local/lib/python3.4/dist-packages/requests/packages/urllib3/connectionpool.py", line 352, in _make_request
    self._validate_conn(conn)
  File "/usr/local/lib/python3.4/dist-packages/requests/packages/urllib3/connectionpool.py", line 831, in _validate_conn
    conn.connect()
  File "/usr/local/lib/python3.4/dist-packages/requests/packages/urllib3/connection.py", line 289, in connect
    ssl_version=resolved_ssl_version)
  File "/usr/local/lib/python3.4/dist-packages/requests/packages/urllib3/util/ssl_.py", line 308, in ssl_wrap_socket
    return context.wrap_socket(sock, server_hostname=server_hostname)
  File "/usr/lib/python3.4/ssl.py", line 364, in wrap_socket
    _context=self)
  File "/usr/lib/python3.4/ssl.py", line 577, in __init__
    self.do_handshake()
  File "/usr/lib/python3.4/ssl.py", line 804, in do_handshake
    self._sslobj.do_handshake()
ssl.SSLEOFError: EOF occurred in violation of protocol (_ssl.c:600)

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/usr/local/lib/python3.4/dist-packages/requests/adapters.py", line 423, in send
    timeout=timeout
  File "/usr/local/lib/python3.4/dist-packages/requests/packages/urllib3/connectionpool.py", line 621, in urlopen
    raise SSLError(e)
requests.packages.urllib3.exceptions.SSLError: EOF occurred in violation of protocol (_ssl.c:600)

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/usr/local/lib/python3.4/dist-packages/homeassistant/bootstrap.py", line 156, in _setup_component
    result = component.setup(hass, config)
  File "/usr/local/lib/python3.4/dist-packages/homeassistant/components/wink.py", line 47, in setup
    if func_exists():
  File "/home/nathan/.homeassistant/deps/pywink/api.py", line 86, in get_locks
    return get_devices(device_types.LOCK)
  File "/home/nathan/.homeassistant/deps/pywink/api.py", line 139, in get_devices
    response_dict = wink_api_fetch()
  File "/home/nathan/.homeassistant/deps/pywink/api.py", line 128, in wink_api_fetch
    response = requests.get(arequest_url, headers=API_HEADERS)
  File "/usr/local/lib/python3.4/dist-packages/requests/api.py", line 70, in get
    return request('get', url, params=params, **kwargs)
  File "/usr/local/lib/python3.4/dist-packages/requests/api.py", line 56, in request
    return session.request(method=method, url=url, **kwargs)
  File "/usr/local/lib/python3.4/dist-packages/requests/sessions.py", line 475, in request
    resp = self.send(prep, **send_kwargs)
  File "/usr/local/lib/python3.4/dist-packages/requests/sessions.py", line 596, in send
    r = adapter.send(request, **kwargs)
  File "/usr/local/lib/python3.4/dist-packages/requests/adapters.py", line 497, in send
    raise SSLError(e, request=request)
requests.exceptions.SSLError: EOF occurred in violation of protocol (_ssl.c:600)
16-08-22 09:40:08 homeassistant.components.switch: Error while setting up platform wink
Traceback (most recent call last):
  File "/usr/local/lib/python3.4/dist-packages/requests/packages/urllib3/connectionpool.py", line 595, in urlopen
    chunked=chunked)
  File "/usr/local/lib/python3.4/dist-packages/requests/packages/urllib3/connectionpool.py", line 352, in _make_request
    self._validate_conn(conn)
  File "/usr/local/lib/python3.4/dist-packages/requests/packages/urllib3/connectionpool.py", line 831, in _validate_conn
    conn.connect()
  File "/usr/local/lib/python3.4/dist-packages/requests/packages/urllib3/connection.py", line 289, in connect
    ssl_version=resolved_ssl_version)
  File "/usr/local/lib/python3.4/dist-packages/requests/packages/urllib3/util/ssl_.py", line 308, in ssl_wrap_socket
    return context.wrap_socket(sock, server_hostname=server_hostname)
  File "/usr/lib/python3.4/ssl.py", line 364, in wrap_socket
    _context=self)
  File "/usr/lib/python3.4/ssl.py", line 577, in __init__
    self.do_handshake()
  File "/usr/lib/python3.4/ssl.py", line 804, in do_handshake
    self._sslobj.do_handshake()
ssl.SSLEOFError: EOF occurred in violation of protocol (_ssl.c:600)

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/usr/local/lib/python3.4/dist-packages/requests/adapters.py", line 423, in send
    timeout=timeout
  File "/usr/local/lib/python3.4/dist-packages/requests/packages/urllib3/connectionpool.py", line 621, in urlopen
    raise SSLError(e)
requests.packages.urllib3.exceptions.SSLError: EOF occurred in violation of protocol (_ssl.c:600)

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/usr/local/lib/python3.4/dist-packages/homeassistant/helpers/entity_component.py", line 98, in _setup_platform
    discovery_info)
  File "/usr/local/lib/python3.4/dist-packages/homeassistant/components/switch/wink.py", line 34, in setup_platform
    add_devices(WinkToggleDevice(switch) for switch in pywink.get_sirens())
  File "/home/nathan/.homeassistant/deps/pywink/api.py", line 106, in get_sirens
    return get_devices(device_types.SIREN)
  File "/home/nathan/.homeassistant/deps/pywink/api.py", line 139, in get_devices
    response_dict = wink_api_fetch()
  File "/home/nathan/.homeassistant/deps/pywink/api.py", line 128, in wink_api_fetch
    response = requests.get(arequest_url, headers=API_HEADERS)
  File "/usr/local/lib/python3.4/dist-packages/requests/api.py", line 70, in get
    return request('get', url, params=params, **kwargs)
  File "/usr/local/lib/python3.4/dist-packages/requests/api.py", line 56, in request
    return session.request(method=method, url=url, **kwargs)
  File "/usr/local/lib/python3.4/dist-packages/requests/sessions.py", line 475, in request
    resp = self.send(prep, **send_kwargs)
  File "/usr/local/lib/python3.4/dist-packages/requests/sessions.py", line 596, in send
    r = adapter.send(request, **kwargs)
  File "/usr/local/lib/python3.4/dist-packages/requests/adapters.py", line 497, in send
    raise SSLError(e, request=request)
requests.exceptions.SSLError: EOF occurred in violation of protocol (_ssl.c:600)

Additional info:

I'm having similar issues today with various Wink components.  They did have a problem earlier with their API, but supposedly only with Nest.  Not sure if it related.  Random components don't load on startup.

@nathanm412 Is this still an issue? I started seeing these errors the other day with all of my Wink devices. I manually tried calling the Wink API it was down. I think they must have been doing maintenance over the last week like @geekofweek stated.

I just restarted hass and my garage door has reappeared.
Thanks,
Nathan
On Sat, Aug 27, 2016, 2:11 PM William Scanlon notifications@github.com
wrote:

@nathanm412 https://github.com/nathanm412 Is this still an issue? I
started seeing these errors the other day with all of my Wink devices. I
manually tried calling the Wink API it was down. I think they must have
been doing maintenance over the last week like @geekofweek
https://github.com/geekofweek stated.
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/home-assistant/home-assistant/issues/2936#issuecomment-242932119,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AAevB07lWImL3KqO18DxZOuj1CKJfYD3ks5qkH3YgaJpZM4Jp5J8
.


text:
deCONZ allow unloading of config entry

Description:
Allow unloading deCONZ config entries and all its' entities

[x] Unload works for binary sensor, light, scene and sensor components
[x] Make removing DeconzEvents possible
[x] Add new tests

Checklist:

[x] The code change is tested and works locally.
[x] Local tests pass with tox. Your PR cannot be merged unless tests pass

If the code does not interact with devices:

[x] Tests have been added to verify that the new code works.

Looks good! Ok to merge when tests pass.
Btw I've added some config entry documentation to https://developers.home-assistant.io and would love some feedback on it since you're the biggest user now 🙂

I'll have a look at it during the day 👍

source: gharchive/pull-request

repo: home-assistant/home-assistant

license_type: permissive

license_source: github-api


text:
Tweak recorder/restore_state

Description:
So this started out as an attempt to fix the flaky helpers.restore_state.test_filling_the_cache test.
While looking into the details, I made the following changes:
Add timeout to restore state
By adding a timeout we will not block all of startup because we're trying to connect to the recorder.
Recorder will now be connected when setup is done.
I want to bring this one up again… Specifying a dependency in Home Assistant means that Home Assistant will guarantee that the dependency is ready to use before your component is set up. Following that logic I think that it makes sense to wait till it is connected.
Clean up connect code
It was a bit messy with using locals.
wait_connection_ready will now return if connection was established
I realized that we would never return from wait_connection_ready if the connection failed. That seems like a weird approach and thus I decided to have it return the result. Updated restore_state to not query if the connection failed.
Example entry for configuration.yaml (if applicable):
recorder:

Checklist:
If the code does not interact with devices:

[x] Local tests with tox run successfully. Your PR cannot be merged unless tests pass
[x] Tests have been added to verify that the new code works.

I think we need do discuis what size of timeout make sense for restore. I think we can wait 20sec for it. But let's it do with 10 sec in 0.40 and look at feedbacks

authors: balloob pvizeli


text:
[NL] Align ClimateTemperatureSet with EN

Use <numeric_value_set>
Remove formal sentences like zou je de temperatuur in de woonkamer op 19 graden willen zetten
Remove <name> as target, as this isn't added in EN, and doesn't seem to be working in my tests in a production system.

Compared to EN I did add the really short intents like woonkamer 19 graden or temperatuur 19 graden. I didn't make graden optional there to avoid conflicts with other intents.

Could you have a look at this one @frenck
Inspired by your PR, I just started at the top of the list to see if everything aligns with EN.

repo: home-assistant/intents


text:
backend修正に伴う変更

backend側の以下の仕様変更又は修正に伴う対応化
homenoc/dsbd-backend#22
homenoc/dsbd-backend#31

すでに終了

source: gharchive/issue

repo: homenoc/dsbd-web-admin

license: MIT


text:
ResultCallback 如何解析集合对象

比如List，如果将List当泛型传进去，貌似解析不了

List的泛型也需要指明，比如List，例子中也包含这样的示例。

repo: hongyangAndroid/okhttp-utils

license_source: bigquery


text:
Hono JSX rendering as [Object object] on fly.io

I have a super simple app using bun and hono. I use hono/jsx to render html on the server (like explained in the hono docs: https://hono.dev/middleware/builtin/jsx). When I run bun src/index.tsx locally, everything works fine, I see rendered html (see screenshot), but when I deploy the same application to fly.io, the server always responds with [Object object] when trying to render JSX. Routes that don't render JSX (but just plain text) render just fine. Maybe this is an issue with fly.io, but I have no idea what could be wrong.
You can see my routes and their coresponding urls on fly.io here:
https://bun-hono-htmx.fly.dev/
app.get("/", (c) => {
  return c.html(<App />);
});

https://bun-hono-htmx.fly.dev/list
app.get("/list", (c) => {
  return c.text(<List />)
});

https://bun-hono-htmx.fly.dev/hello
app.get("/hello", (c) => {
  return c.text("Hello World!");
});

Screenshot of the route / working locally:

Hi @terrabythia !
I haven't fully investigated this yet, but it appears to potentially be a bug with Bun. Could you please provide the version numbers of Bun in both your local environment and on fly.io?

Hi @yusukebe, thanks for your reply!
I have version v0.6.14 installed locally, and from the logs I got from fly deploy I can see it's also using v0.6.14
=> [internal] load metadata for docker.io/oven/bun:0.6.14.

Hi, @yusukebe @terrabythia
I was able to reproduce it.
Even locally, if I bun start with NODE_ENV=production, it seems to become [Object object].

@sor4chi Thank you for sharing it!
This seems to be a Bun's bug. I've already reported: https://github.com/oven-sh/bun/issues/3753

Hi @terrabythia @sor4chi,
That was a bug in Bun, but it has now been fixed. The next version of Bun, which is likely to include this fix, will be released soon.

@yusukebe @sor4chi bun 0.7.1 has been released and it contains the fix. My website on fly.io is working now! https://bun-hono-htmx.fly.dev/
So this issue can be closed.

Great!!

authors: sor4chi terrabythia yusukebe

repo: honojs/hono


text:
Implement account.request

account.request(type/*, options*/) // returns promise

Examples
account.request('upgrade', {plan: 'pro', token: 'stripe123'})
.then(function () {
  alert('Upgraded successfully!')
})
.catch(function (error) {
  alert(error)
})

@HipsterBrown I need this one for eHealth, so I'm going to work on this, ok?

Ok I can do some review if you'd like.

go for it sir :)

repo: hoodiehq/hoodie-client-account


text:
🛑 FWAw is down

In 0a0ad08, FWAw ($FWA_SITE) was down:

HTTP code: 0
Response time: 0 ms

Resolved: FWAw is back up in 40fb8cc after 33 minutes.

repo: hoopybe/uptime


text:
Document "classes trick" in WpCache

And add some more API documentation while at it.

done

repo: hoppinger/wp-connector


text:
CMake error building 2.0.0 on Ubuntu 18.04

It seems like a change in version 2.0.0 broke the build for Ubuntu 18.04. Other releases as current as 1.0.15 build fine, but when we try to build 2.0.0 on Ubuntu 18.04, we get a cmake error:
sh-4.4# /bin/bash -c "$(curl -fsSL https://git.io/JerYI)" -s horta/almosthere
[0/7] Library(almosthere==2.0.0)
[1/7] Downloading... done.
[2/7] Extracting... done.
[3/7] Configuring... FAILED.
---------------------------------------- log begin ----------------------------------------
% Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
Dload  Upload   Total   Spent    Left  Speed
100   123  100   123    0     0   1098      0 --:--:-- --:--:-- --:--:--  1098
100  111k    0  111k    0     0   382k      0 --:--:-- --:--:-- --:--:-- 2745k
-- The C compiler identification is GNU 7.5.0
-- Check for working C compiler: /usr/bin/cc
-- Check for working C compiler: /usr/bin/cc -- works
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Detecting C compile features
-- Detecting C compile features - done
-- Looking for pthread.h
-- Looking for pthread.h - found
-- Looking for pthread_create
-- Looking for pthread_create - not found
-- Looking for pthread_create in pthreads
-- Looking for pthread_create in pthreads - not found
-- Looking for pthread_create in pthread
-- Looking for pthread_create in pthread - found
-- Found Threads: TRUE
-- Found Curses: /usr/lib/x86_64-linux-gnu/libcurses.so
-- Found LibRt: /usr/lib/x86_64-linux-gnu/librt.so
-- Looking for gettimeofday
-- Looking for gettimeofday - found
-- Performing Test COMPILER_HAS_HIDDEN_VISIBILITY
CMake Error at /usr/share/cmake-3.10/Modules/CheckCXXSourceCompiles.cmake:97 (try_compile):
Unknown extension ".cxx" for file
/tmp/tmp.GTRrSBfmQualmosthere/almosthere-2.0.0/build/CMakeFiles/CMakeTmp/src.cxx

try_compile() works only for enabled languages.  Currently these are:
C

See project() command to enable other languages.
Call Stack (most recent call first):
/usr/share/cmake-3.10/Modules/CheckCXXCompilerFlag.cmake:49 (CHECK_CXX_SOURCE_COMPILES)
/usr/share/cmake-3.10/Modules/GenerateExportHeader.cmake:215 (check_cxx_compiler_flag)
/usr/share/cmake-3.10/Modules/GenerateExportHeader.cmake:374 (_test_compiler_hidden_visibility)
CMakeLists.txt:95 (generate_export_header)
-- Performing Test COMPILER_HAS_HIDDEN_VISIBILITY - Failed
-- Performing Test COMPILER_HAS_HIDDEN_INLINE_VISIBILITY
CMake Error at /usr/share/cmake-3.10/Modules/CheckCXXSourceCompiles.cmake:97 (try_compile):
Unknown extension ".cxx" for file
/tmp/tmp.GTRrSBfmQualmosthere/almosthere-2.0.0/build/CMakeFiles/CMakeTmp/src.cxx

try_compile() works only for enabled languages.  Currently these are:
C

See project() command to enable other languages.
Call Stack (most recent call first):
/usr/share/cmake-3.10/Modules/CheckCXXCompilerFlag.cmake:49 (CHECK_CXX_SOURCE_COMPILES)
/usr/share/cmake-3.10/Modules/GenerateExportHeader.cmake:216 (check_cxx_compiler_flag)
/usr/share/cmake-3.10/Modules/GenerateExportHeader.cmake:374 (_test_compiler_hidden_visibility)
CMakeLists.txt:95 (generate_export_header)
-- Performing Test COMPILER_HAS_HIDDEN_INLINE_VISIBILITY - Failed
-- Performing Test COMPILER_HAS_DEPRECATED_ATTR
CMake Error at /usr/share/cmake-3.10/Modules/CheckCXXSourceCompiles.cmake:97 (try_compile):
Unknown extension ".cxx" for file
/tmp/tmp.GTRrSBfmQualmosthere/almosthere-2.0.0/build/CMakeFiles/CMakeTmp/src.cxx

try_compile() works only for enabled languages.  Currently these are:
C

See project() command to enable other languages.
Call Stack (most recent call first):
/usr/share/cmake-3.10/Modules/GenerateExportHeader.cmake:191 (check_cxx_source_compiles)
/usr/share/cmake-3.10/Modules/GenerateExportHeader.cmake:234 (_check_cxx_compiler_attribute)
/usr/share/cmake-3.10/Modules/GenerateExportHeader.cmake:375 (_test_compiler_has_deprecated)
CMakeLists.txt:95 (generate_export_header)
-- Performing Test COMPILER_HAS_DEPRECATED_ATTR - Failed
-- Performing Test COMPILER_HAS_DEPRECATED
CMake Error at /usr/share/cmake-3.10/Modules/CheckCXXSourceCompiles.cmake:97 (try_compile):
Unknown extension ".cxx" for file
/tmp/tmp.GTRrSBfmQualmosthere/almosthere-2.0.0/build/CMakeFiles/CMakeTmp/src.cxx

try_compile() works only for enabled languages.  Currently these are:
C

See project() command to enable other languages.
Call Stack (most recent call first):
/usr/share/cmake-3.10/Modules/GenerateExportHeader.cmake:191 (check_cxx_source_compiles)
/usr/share/cmake-3.10/Modules/GenerateExportHeader.cmake:240 (_check_cxx_compiler_attribute)
/usr/share/cmake-3.10/Modules/GenerateExportHeader.cmake:375 (_test_compiler_has_deprecated)
CMakeLists.txt:95 (generate_export_header)
-- Performing Test COMPILER_HAS_DEPRECATED - Failed
CMake Error at /usr/share/cmake-3.10/Modules/GenerateExportHeader.cmake:305 (message):
Unknown keywords given to GENERATE_EXPORT_HEADER():
"INCLUDE_GUARD_NAME;ATHR_EXPORT_H"
Call Stack (most recent call first):
/usr/share/cmake-3.10/Modules/GenerateExportHeader.cmake:377 (_do_generate_export_header)
CMakeLists.txt:95 (generate_export_header)
-- Configuring incomplete, errors occurred!
See also "/tmp/tmp.GTRrSBfmQualmosthere/almosthere-2.0.0/build/CMakeFiles/CMakeOutput.log".
See also "/tmp/tmp.GTRrSBfmQualmosthere/almosthere-2.0.0/build/CMakeFiles/CMakeError.log".
----------------------------------------  log end  ----------------------------------------
LOG: /tmp/tmp.ReTNCAbJVzalmosthere.log

Thank you for the report! I will release a new version with the workaround, thanks!

authors: horta seantcaron

repo: horta/almosthere


text:
Add gpio-poweroff handler that pulls GPIO4_IO19

Add gpio-poweroff handler that pulls GPIO4_IO19 to completely turn off the board. NOTE: another pm_power_off handler is already registered and gpio-poweroff.c needs to be patched to overwrite it.
The power-off functions seems to be the handled by the psci driver that turns off the CPU but we pull the gpio and turn off the power instead.
Reference:
https://www.thegoodpenguin.co.uk/blog/an-overview-of-psci/
A question is should we allow power-off when KL15/start-signal is on.

verified on R5A-3

repo: hostmobility/meta-hostmobility-bsp


text:
🛑 Documentation is down

In 4e66052, Documentation (https://docs.planetary-quantum.com/) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Documentation is back up in 8c3ad87.


text:
Improved: Cycle count bulk import to better handle the erroneous csv.

Done following -

Added validation service to validated uploaded cycle count csv.
Removed processing records in new transaction.
Added API to get System Message errors related to Cycle Count CSV.
Added API to get the uploaded csv file content.

We can use ec.webFacade.sendResrouceResponse method, need to check how we can utilise this with rest endpoints.

authors: dixitdeepak ravilodhi

repo: hotwax/inventory-count-maarg


text:
Preloader: Rename header to x-purpose to avoid it being stripped

This PR fixes the issue mentioned in #1107 by renaming the header to x-purpose, as the Sec-Purpose header is stripped by fetch.
In this PR, the value is also changed to preview which is consistent with how eg. Safari and Chrome uses the x-purpose header for their "quick view" of eg. favorite pages.

Thanks @pfeiffer and @seanpdoyle!

authors: afcapel pfeiffer

repo: hotwired/turbo


text:
Search field should start search immediately when user enters a search term

Whenever the user enter a search term the search should  be started automatically, maybe with a short delay....

This is a cool feature of RxJS to throttle the reaction of the key event so that the user can enter more than only one character before the search will executed

repo: howcani-project/howcani

license: mit


text:
Possible violation of copyright

Hi,
I strongly believe your GitHub profile violates copyright, particularly regarding the animation about frog guys 🐸
You'd better change your profile picture or Grandpa Mang-Tae would get you soon.
Good luck. Please do not make me say "I told you".

LGTM :+1:

authors: hoyaaaa theverytak


text:
Update README.md

The global variables are in the config.py

Thanks!

authors: FrankLeeeee I-E-E-E

repo: hpcaitech/ColossalAI-Examples


text:
multi-host parallel training cannot recognize all gpu

Hi I am following https://github.com/hpcaitech/ColossalAI/tree/main/examples/images/diffusion and trying to use 2 hosts with each 1 T4 GPU. I changed
lightning:
trainer:
accelerator: 'gpu'
devices: 2
And had error:

lightning.fabric.utilities.exceptions.MisconfigurationException: You requested gpu: [0, 1] But your machine only has: [0]
lightning.fabric.utilities.exceptions.MisconfigurationException: You requested gpu: [0, 1] But your machine only has: [0]

Is there other config I should assign to recognize multi-host?

We have fixed it and will release a detailed blog with the AWS team together. Thanks.

https://aws.amazon.com/cn/blogs/china/run-colossal-ai-based-distributed-finetune-tasks-on-sagemaker/
We are happy to release this blog together. Thanks.

authors: binmakeswell zhaoanbei

repo: hpcaitech/ColossalAI


text:
Shape mismatch error occurs in multiprocessing

If I use 2~ gpus on inference, following error occurs.
Traceback (most recent call last):
  File "/hub_data1/minhyuk/diffusion/opensora/scripts/inference.py", line 114, in <module>
    main()
  File "/hub_data1/minhyuk/diffusion/opensora/scripts/inference.py", line 95, in main
    samples = scheduler.sample(
  File "/home/minhyuk/.conda/envs/opensora/lib/python3.10/site-packages/opensora/schedulers/iddpm/__init__.py", line 72, in sample
    samples = self.p_sample_loop(
  File "/home/minhyuk/.conda/envs/opensora/lib/python3.10/site-packages/opensora/schedulers/iddpm/gaussian_diffusion.py", line 434, in p_sample_loop
    for sample in self.p_sample_loop_progressive(
  File "/home/minhyuk/.conda/envs/opensora/lib/python3.10/site-packages/opensora/schedulers/iddpm/gaussian_diffusion.py", line 485, in p_sample_loop_p
rogressive
    out = self.p_sample(
  File "/home/minhyuk/.conda/envs/opensora/lib/python3.10/site-packages/opensora/schedulers/iddpm/gaussian_diffusion.py", line 388, in p_sample
    out = self.p_mean_variance(
  File "/home/minhyuk/.conda/envs/opensora/lib/python3.10/site-packages/opensora/schedulers/iddpm/respace.py", line 94, in p_mean_variance
    return super().p_mean_variance(self._wrap_model(model), *args, **kwargs)
  File "/home/minhyuk/.conda/envs/opensora/lib/python3.10/site-packages/opensora/schedulers/iddpm/gaussian_diffusion.py", line 267, in p_mean_variance
    model_output = model(x, t, **model_kwargs)
  File "/home/minhyuk/.conda/envs/opensora/lib/python3.10/site-packages/opensora/schedulers/iddpm/respace.py", line 127, in __call__
    return self.model(x, new_ts, **kwargs)
  File "/home/minhyuk/.conda/envs/opensora/lib/python3.10/site-packages/opensora/schedulers/iddpm/__init__.py", line 89, in forward_with_cfg
    model_out = model.forward(combined, timestep, y, **kwargs)
  File "/home/minhyuk/.conda/envs/opensora/lib/python3.10/site-packages/opensora/models/stdit/stdit.py", line 267, in forward
    x = auto_grad_checkpoint(block, x, y, t0, y_lens, tpe)
  File "/home/minhyuk/.conda/envs/opensora/lib/python3.10/site-packages/opensora/acceleration/checkpoint.py", line 24, in auto_grad_checkpoint
    return module(*args, **kwargs)
  File "/home/minhyuk/.conda/envs/opensora/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/minhyuk/.conda/envs/opensora/lib/python3.10/site-packages/opensora/models/stdit/stdit.py", line 111, in forward
    x = x + self.cross_attn(x, y, mask)
  File "/home/minhyuk/.conda/envs/opensora/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/minhyuk/.conda/envs/opensora/lib/python3.10/site-packages/opensora/models/layers/blocks.py", line 313, in forward
    kv = self.kv_linear(cond).view(B, -1, 2, self.num_heads, self.head_dim)
RuntimeError: shape '[4, -1, 2, 16, 72]' is invalid for input of size 105523

I tested on 2/3/4 gpus, and all give the same error.

我有相同的问题

repo: hpcaitech/Open-Sora


text:
在Linux环境下定义了HPM_SDK_BASE但是hpm-sdk-config.cmake依然报错

CMake 环境:
$ cmake --version
cmake version 3.25.1

CMake suite maintained and supported by Kitware (kitware.com/cmake).

相关代码
if(NOT DEFINED $ENV{HPM_SDK_BASE})
message(FATAL_ERROR "HPM_SDK_BASE is not set yet")
endif()
经过测试,删除'$ENV'的'$'即可通过,不知是CMake的什么特性

请提供一下Linux的发行版（如Ubuntu20.04, Ubuntu22.04等），使用的Terminal
目前在Ubuntu，使用系统默认的Terminal无法复现这个问题

请提供一下Linux的发行版（如Ubuntu20.04, Ubuntu22.04等），使用的Terminal
目前在Ubuntu，使用系统默认的Terminal无法复现这个问题

系统为Ubuntu 22.04 虚拟机 默认bash 使用CLion 2024.1 linux #CL-241.14494.288 进行开发 同时在CMake设置中和环境变量中都声明了HPM_SDK_BASE 均报错

在编译的窗口先执行以下命令，然后再执行cmake构建试试看：
export HPM_SDK_BASE=/home/cjk/workspace/sdk_env/hpm_sdk

感觉像是环境变量没有设置成功，参考一下这个知乎的帖子：https://zhuanlan.zhihu.com/p/564229673。

authors: cjkzwe helloeagleyang jhqian


text:
Add Authorization Flow

This flow allows you to decouple the Mondu widget flow from your last checkout step.
Using this, Mondu orders are created, the widget gets shown, but orders then land in the state authorized. You can then confirm this order yourself by calling the confirm order endpoint of the Mondu API.

Feature works, but needs refactoring. Naming things is hard.

repo: hreinberger/mondu-node


text:
Handy json报错

var numberOfFields: Int {
return Int(pointer.pointee.numberOfFields)
}
Thread 1: EXC_BAD_ACCESS (code=1, address=0x2

最新代码已经上传，Xcode 9.3 运行成功。
问题原因参考Xcode9.3 Swift4.1 crash 解决方案。请按照上面的方法改一下代码然后再编译运行试试。😉

已修复，给力！

authors: hrscy narakai

repo: hrscy/TodayNews


text:
Junk characters inside the scroll bar

This only happens with a big list (either large doc or long list of completions). See screenshots below.

My config:
    local cmp = require('cmp')
    local luasnip = require('luasnip')

    local has_words_before = function()
        local line, col = unpack(vim.api.nvim_win_get_cursor(0))
        return col ~= 0 and vim.api.nvim_buf_get_lines(0, line - 1, line, true)[1]:sub(col, col):match('%s') == nil
    end

    cmp.setup {
        formatting = {
            format = function(entry, vim_item)
                local lspkind_icons = {
                    Text = '',
                    Method = '',
                    Function = '',
                    Constructor = '',
                    Field = 'ﰠ',
                    Variable = '',
                    Class = 'ﴯ',
                    Interface = '',
                    Module = '',
                    Property = 'ﰠ',
                    Unit = '塞',
                    Value = '',
                    Enum = '',
                    Keyword = '',
                    Snippet = '',
                    Color = '',
                    File = '',
                    Reference = '',
                    Folder = '',
                    EnumMember = '',
                    Constant = '',
                    Struct = '',
                    Event = '',
                    Operator = '',
                    TypeParameter = ''
                }
                -- load lspkind icons
                vim_item.kind = string.format('%s %s', lspkind_icons[vim_item.kind], vim_item.kind)

                vim_item.menu = ({
                    luasnip = '[SNIP]',
                    path = '[PATH]',
                    buffer = '[BUF]',
                    -- calc = '[CALC]',
                    -- nuspell = '[SPELL]',
                    spell = '[SPELL]',
                    emoji = '[EMOJI]',
                    -- treesitter = '[TS]',
                    nvim_lsp = '[LSP]',
                    -- cmp_tabnine = '[TN]',
                    latex_symbols = '[TEX]',
                    -- tmux = '[TMUX]',
                    -- conjure = '[CJ]',
                    orgmode = '[ORG]'
                })[entry.source.name]

                return vim_item
            end
        },
        -- documentation = {
        --     border = {'╭', '─', '╮', '│', '╯', '─', '╰', '│'}
        -- },
        mapping = {
            ['<C-Space>'] = cmp.mapping.complete(),
            ['<C-p>'] = cmp.mapping.select_prev_item(),
            ['<C-n>'] = cmp.mapping.select_next_item(),
            ['<C-b>'] = cmp.mapping.scroll_docs(-4),
            ['<C-f>'] = cmp.mapping.scroll_docs(4),
            ['<C-d>'] = cmp.mapping.close(),
            -- Change choice nodes for luasnip
            ['<C-j>'] = cmp.mapping(function(fallback)
                if luasnip.choice_active() then
                    luasnip.change_choice(-1)
                else
                    fallback()
                end
            end, {'i', 's'}),
            ['<C-k>'] = cmp.mapping(function(fallback)
                if luasnip.choice_active() then
                    luasnip.change_choice(1)
                else
                    fallback()
                end
            end, {'i', 's'}),
            -- supertab-like mapping
            ['<Tab>'] = cmp.mapping(function(fallback)
                if cmp.visible() then
                    cmp.select_next_item()
                elseif luasnip.expand_or_jumpable() then
                    luasnip.expand_or_jump()
                elseif has_words_before() then
                    cmp.complete()
                else
                    fallback()
                end
            end, {'i', 's'}),
            ['<S-Tab>'] = cmp.mapping(function(fallback)
                if cmp.visible() then
                    cmp.select_prev_item()
                elseif luasnip.jumpable(-1) then
                    luasnip.jump(-1)
                else
                    fallback()
                end
            end, {'i', 's'})
        },
        snippet = {
            expand = function(args)
                luasnip.lsp_expand(args.body)
            end
        },
        sources = {
            {name = 'luasnip'},
            {name = 'path'},
            {name = 'buffer'},
            -- {name = 'calc'},
            -- {name = 'nuspell'},
            {name = 'spell'},
            {name = 'emoji'},
            -- {name = 'treesitter'},
            {name = 'nvim_lsp'},
            -- {name = 'cmp_tabnine'},
            {name = 'latex_symbols'},
            -- {name = 'tmux'},
            -- {name = 'conjure'},
            {name = 'orgmode'}
        }
    }

Yes. The list is here (lazily copied from PackerStatus):
 • LuaSnip (not loaded)
 • alpha-nvim
 • asyncrun.vim (not loaded)
 • asynctasks.vim (not loaded)
 • bracey.vim (not loaded)
 • bufferline.nvim
 • cmp-buffer (not loaded)
 • cmp-emoji (not loaded)
 • cmp-latex-symbols (not loaded)
 • cmp-nvim-lsp (not loaded)
 • cmp-path (not loaded)
 • cmp-spell (not loaded)
 • cmp_luasnip (not loaded)
 • diffview.nvim (not loaded)
 • editorconfig-vim
 • feline.nvim
 • filetype.nvim
 • friendly-snippets (not loaded)
 • gitsigns.nvim
 • hop.nvim (not loaded)
 • indent-blankline.nvim
 • iswap.nvim (not loaded)
 • lsp_signature.nvim
 • markdown-preview.nvim (not loaded)
 • neogen (not loaded)
 • neogit (not loaded)
 • neoscroll.nvim
 • null-ls.nvim
 • nvim-autopairs (not loaded)
 • nvim-cmp (not loaded)
 • nvim-colorizer.lua (not loaded)
 • nvim-comment (not loaded)
 • nvim-dap
 • nvim-dap-ui
 • nvim-lspconfig
 • nvim-spectre
 • nvim-tree.lua (not loaded)
 • nvim-treesitter
 • nvim-treesitter-context
 • nvim-treesitter-textobjects
 • nvim-ts-autotag (not loaded)
 • nvim-ts-rainbow
 • nvim-web-devicons
 • octo.nvim (not loaded)
 • orgmode.nvim (not loaded)
 • packer.nvim (manually loaded)
 • parinfer-rust (not loaded)
 • persistence.nvim
 • plenary.nvim
 • popup.nvim (not loaded)
 • project.nvim
 • rest.nvim (not loaded)
 • sniprun (not loaded)
 • sqls.nvim (not loaded)
 • symbols-outline.nvim (not loaded)
 • telescope-fzf-native.nvim (not loaded)
 • telescope-project.nvim (not loaded)
 • telescope-symbols.nvim (not loaded)
 • telescope.nvim (not loaded)
 • toggleterm.nvim (not loaded)
 • translate-shell.vim (not loaded)
 • trouble.nvim (not loaded)
 • twilight.nvim (not loaded)
 • undotree (not loaded)
 • vim-easy-align (not loaded)
 • vim-eft
 • vim-illuminate
 • vim-matchup
 • vim-sandwich (not loaded)
 • vim-startuptime (not loaded)
 • which-key.nvim
 • zen-mode.nvim (not loaded)

Thank you. I think it relates to persistence.nvim.
I've fixed it maybe .


text:
Add cooling off period

add cooling off period to display app open ads. Useful when users are toggling the app.
example : user will only show 1 time app open ads in the period of x minutes.

Updated version 1.0.0
https://pub.dev/packages/flutter_admob_app_open/changelog

authors: hsangtini nickgoh


text:
dynamically change data-validetta=' ' attributes

Hi Hasan. It has been quite a few years since I had any issues with Vaildetta. All power to you! It also means I am quite rusty with the code.
I am trying to dynamically change the data-validetta=' ' attribute using jQuerry.
$('#oldMem').click(function() {
	$('#oldDates').attr('data-validetta','required');
	//alert($('#oldDates').attr('data-validetta')) // this shows the change has been made
		});

I would have thought that on submission the change would be recognized?

	* Yes:
<input id='oldMem' type='radio' name='memRenew' value='yes'></input>

	What is the most recent year you had membership?
	<select id='oldDates' name="oldDates" style='font-size:18px;' data-validetta="required">
	<option value='selectOne'>Select One</option>
	<?php
	for ($i=date('Y'); $i>date("Y")-10; $i-=1) {
		echo "<option value='$i'>$i</option>"; }
	?>
	</select>

* No:
<input id='newMem' type='radio' name='memRenew' value='no'></input>

Other (hard coded) validetta errors are working fine. The form is being written to file - mail sent but...
the dynamic change is not working. Am I just too rusty and there is something I am missing or is there a bug?
I hope this is enough to make my situation clear. I could put up a temp page if that helps.
thanks as always... Kusalo (lost my arfa tag :(

Sorry to waste time here. My bad.
The problem was giving the default first-option a value
<option value='selectOne'>Select One</option>

repo: hsnaydd/validetta


text:
NoSuchMethodError in IDEA 2016.2 EAP

I'm getting the following stacktrace in IDEA 2016.2 EAP.
com.intellij.util.containers.ContainerUtil.intersection(Ljava/util/Collection;Ljava/util/Collection;)Ljava/util/Collection;
java.lang.NoSuchMethodError: com.intellij.util.containers.ContainerUtil.intersection(Ljava/util/Collection;Ljava/util/Collection;)Ljava/util/Collection;
	at mobi.hsz.idea.gitignore.codeInspection.IgnoreCoverEntryInspection$2.visitEntry(IgnoreCoverEntryInspection.java:153)
	at mobi.hsz.idea.gitignore.psi.IgnoreVisitor.visitEntryFile(IgnoreVisitor.java:19)
	at mobi.hsz.idea.gitignore.psi.impl.IgnoreEntryFileImpl.accept(IgnoreEntryFileImpl.java:20)
	at com.intellij.psi.impl.source.tree.SharedImplUtil.acceptChildren(SharedImplUtil.java:200)
	at com.intellij.psi.impl.source.PsiFileImpl.acceptChildren(PsiFileImpl.java:822)
	at mobi.hsz.idea.gitignore.codeInspection.IgnoreCoverEntryInspection.checkFile(IgnoreCoverEntryInspection.java:144)
	at com.intellij.codeInspection.LocalInspectionTool$1.visitFile(LocalInspectionTool.java:156)
	at mobi.hsz.idea.gitignore.psi.IgnoreFile.accept(IgnoreFile.java:120)
	at com.intellij.codeInspection.InspectionEngine.acceptElements(InspectionEngine.java:81)
	at com.intellij.codeInspection.InspectionEngine.createVisitorAndAcceptElements(InspectionEngine.java:69)
	at com.intellij.codeInsight.daemon.impl.LocalInspectionsPass.a(LocalInspectionsPass.java:294)
	at com.intellij.codeInsight.daemon.impl.LocalInspectionsPass.access$200(LocalInspectionsPass.java:73)
	at com.intellij.codeInsight.daemon.impl.LocalInspectionsPass$2.process(LocalInspectionsPass.java:261)
	at com.intellij.codeInsight.daemon.impl.LocalInspectionsPass$2.process(LocalInspectionsPass.java:256)
	at com.intellij.concurrency.ApplierCompleter.c(ApplierCompleter.java:123)
	at com.intellij.concurrency.ApplierCompleter.b(ApplierCompleter.java:212)
	at com.intellij.concurrency.ApplierCompleter.c(ApplierCompleter.java:141)
	at com.intellij.openapi.application.impl.ApplicationImpl.tryRunReadAction(ApplicationImpl.java:1063)
	at com.intellij.concurrency.ApplierCompleter.a(ApplierCompleter.java:96)
	at com.intellij.openapi.progress.impl.CoreProgressManager.a(CoreProgressManager.java:472)
	at com.intellij.openapi.progress.impl.CoreProgressManager.executeProcessUnderProgress(CoreProgressManager.java:421)
	at com.intellij.openapi.progress.impl.ProgressManagerImpl.executeProcessUnderProgress(ProgressManagerImpl.java:54)
	at com.intellij.concurrency.ApplierCompleter.b(ApplierCompleter.java:106)
	at com.intellij.concurrency.ApplierCompleter.compute(ApplierCompleter.java:91)
	at java.util.concurrent.CountedCompleter.exec(CountedCompleter.java:731)
	at java.util.concurrent.ForkJoinTask.doExec(ForkJoinTask.java:289)
	at java.util.concurrent.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1056)
	at java.util.concurrent.ForkJoinPool.runWorker(ForkJoinPool.java:1692)
	at java.util.concurrent.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:157)

@ohlle Thank you for reporting this issue. What exacly IDE build and plugin version do you have ?
I've tried to reproduce it on build IC-162.74.16 without any problems.

IntelliJ IDEA (Community Edition) 2016.2 EAP
Build #IC-162.74.16, built on May 13, 2016
JRE: 1.8.0_92-b14 amd64
JVM: Java HotSpot(TM) 64-Bit Server VM by Oracle Corporation

@hsz
IntelliJ IDEA 2016.2 EAP
Build #IU-162.74.16, built on May 13, 2016
JRE: 1.8.0_76-release-b66 amd64
JVM: OpenJDK 64-Bit Server VM by JetBrains s.r.o
.ignore
Version: 1.3.3

Same issue on a mac with a simple .dockerignore (see below)
IntelliJ IDEA 2016.2 EAP
Build #IU-162.74.16, built on May 13, 2016
IntelliJ IDEA EAP User
Expiration date: June 12, 2016
JRE: 1.8.0_76-release-b185 x86_64
JVM: OpenJDK 64-Bit Server VM by JetBrains s.r.o

node_modules
config.json
database.json

Oh, I forgot to mention. I'm using Ubuntu 16.04.

@ohlle @bountin Can you confirm that attached build fixes the problem ?
idea-gitignore-1.3.3.zip

@oliviersalzburg @sheltonn @ohlle @bountin
Can you confirm that attached build fixes the problem ?
idea-gitignore-1.3.3.zip

@oliversalzburg @sheltonn @ohlle @bountin
Can you confirm that attached build fixes the problem ?
idea-gitignore-1.3.3.zip

@hsz Looks good

@hsz I'm unable to reproduce the error with the new version of the plugin. Thanks!

authors: bountin hsz ohlle oliversalzburg

repo: hsz/idea-gitignore


text:
Add Version Increment Check Workflow

Adds a GitHub workflow that automatically checks the version number has been incremented in a PR. It fails if the version has not been incremented appropriately. This PR also removes the duplicate specifications of version numbers by having setup.py read the version number from README.rst to avoid self-inconsistency issues.
This feature was requested in #52 .
Note: This PR should intentionally fail the version increment check initially as part of testing.

Certainly seems to work, though I've personally never been a fan of writing def main() only to call that and nothing else under if __name__ == "__main__", though that might just be trauma from Java
otherwise lgtm

Looks good @ThomasGesseyJones! Just one query about the get_version.py script.
@AdamOrmondroyd lgmt??

@AdamOrmondroyd what is lgmt hahaa?

Looks good to me (one I've picked up from pandas PRs), though it seems to cause no end of confusion with you lot

Codecov Report
All modified and coverable lines are covered by tests :white_check_mark:

Comparison is base (6dbc685) 82.35% compared to head (6130693) 82.35%.

:exclamation: Your organization needs to install the Codecov GitHub app to enable full functionality.
Additional details and impacted files
@@           Coverage Diff           @@
##           master      #53   +/-   ##
=======================================
  Coverage   82.35%   82.35%
=======================================
  Files           5        5
  Lines         578      578
=======================================
  Hits          476      476
  Misses        102      102

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.

I have removed get_version.py as it was unused.
I mistakenly copied it over alongside check_version.py from globalemu. The get_version.py script is used as part of automatic tagging workflows. It can be restored in the future if we decide to implement automatic tagging.

Awesome lgtm thanks @ThomasGesseyJones! Please go ahead and squash and merge

authors: AdamOrmondroyd ThomasGesseyJones codecov-commenter htjb

repo: htjb/margarine


text:
Bug in DynamoDB query DSL: unable to use key condition "(hashAttr eq val1) and (sortAttr eq val2)"

Unfortunately there's a defect in the newly introduced query DSL that prevents me from writing
table.index(refIndex).query {
    keyCondition {
        (ownerAttr eq ownerId) and (refAttr eq refId)
    }
}

if the participating hash key and sort key attributes have different types (in the example above owner is a UUID and ref is a string).
The problem is the refAttr eq refId part because there is no eq function for the sort key attribute.
My original proposal (see this gist) didn't have this problem, since eq was just defined with a generic type attribute T:
infix fun <T> Attribute<T>.eq(value: T) = ...

So this function is used for both hash key and sort key attributes.
However, in the pull request to support paging and the queryPage function, I made the builder aware of the HashKey and SortKey generic types, so the eq function became
infix fun Attribute<HashKey>.eq(value: HashKey) = ...

and I missed that this function can no longer be invoked for the sort key attribute.
Simply adding a eq function for the SortKey generic type unfortunately doesn't work. If HashKey and SortKey happen to be the same type, then the compiler doesn't know which eq function to invoke.
I can think of two solutions to fix this:

Change the generic type for eq back to any T, and the type of KeyCondition.exclusiveStartHashKey to Any?. This requires a type cast in the DynamoDbQueryBuilder.build() function (line 308):

exclusiveStartHashKey = delegate.keyCondition?.exclusiveStartHashKey as HashKey?

You would lose the type safety in the keyCondition block, i.e. the compiler won't prohibit using a non-hashKey attribute in the first eq condition, so you wouldn't see the mistake until the query is executed. A union type would be a great thing, but afaik there's no support in Kotlin for something like this. (On the other hand, even with the type check you could use the wrong attributes, if they just have the same type as the hash key ...)

Use different names for the two eq functions. This would solve all compiler type problems, however I have no idea what to call these functions. And it would be a breaking change (for a feature that was released yesterday,  but still ...)

Do you have any opinions on that @daviddenton and @oharaandrew314 (or a third option)? I think option 1 is a pragmatic solution.
Sorry for the trouble.

Hey @daviddenton, unless you have a better idea, could you please review and merge https://github.com/http4k/http4k-connect/pull/381? Thank you!

So I'm wondering with this - can't the ExclusiveStartKey always be a Key (aka Item) instead of this pair which then gets converted to a Key? Then I think we will have all of the options available and there won't be the need for any casting :)

it will be a break, but I think it would be better if we can make it work 🙃

I just had another idea: you mentioned using just Key or Item would perhaps solve the type cast problem. However, the DynamoDbTableMapper already knows about the hash and sort key attributes, that's why a user only needs to provide the actual values. So why should we "go back" to unspecific Keys?  However, this led me to an idea: the same approach could be applied to the query DSL as well: instead of allowing any Attributes, in the keyCondition we could do a trick that removes the actual attributes from the DSL expression.
My PR should be ready in a couple of minutes.

For what it's worth, I just updated the DynamoDbIndexMapper to accept an ExclusiveStartKey: Key?.  Getting it to work with the typed keys isn't worth it when the start key for a GSI could actually be 4 attributes total.

I'm not sure I understand. Do you mean that in a GSI (with keys x/y) the start key of a query or scan could use the unrelated primary keys (say a/b) of the table? Never thought of that. (And does this even make sense?) However, now that the query DSL no longer needs to remember the hash key, that typing issue I mentioned above is gone.
Nevertheless, I would like to make the keyCondition part in the DSL as type-safe as possible, so my second PR will address this (and add the missing eq function).

Given this example:
Primary Schema: HASH=id, SORT=date
names GSI: HASH=name, SORT=id
If you were to query on the names index, then the LastEvaluatedKey would contain the id, date, and name.
The issue with the previous interface was that while table.index(names).query(hashKey=name, exclusiveStartKey=prevId) can reproduce part of the ExclusiveStartKey, it has no idea what to include as the date attribute.  I'm sure you could come up with a way to make it work in a typesafe way, but I don't think it's worth the complexity.

Ah, thanks for the explanation. Makes perfect sense! I didn't know that DynamoDB returns also the keys of the primary index in the LastEvaluatedKey.

OK - I'm officially a little lost now with the existence of https://github.com/http4k/http4k-connect/pull/387 . Is this fixed now or am I missing something (probably!)
Thanks for the contributions so fer everyone! :)

The original problem is still there, however #387 offers a third solution for this.
Instead of adding a (different) function for the sort key (say, equ)
infix fun Attribute<SortKey>.equ(value: SortKey) = ...

or generalizing the existing eq function (my previous PR #381) by changing it to
infix fun <T : Any> Attribute<T>.eq(value: T) = ...

#387 will add two objects HashKeySubstitute and SortKeySubstitute to the DSL (and two values hashKey and sortKey in the keyCondition context), which will have the eq function (and all other allowed functions) defined like this
infix fun HashKeySubstitute.eq(value: HashKey) = ...
infix fun SortKeySubstitute.eq(value: SortKey) = ...

The implementations will then build a query using the attributes from the schema.
With this, my original example will have to be rewritten as
table.index(refIndex).query {
    keyCondition {
        (hashKey eq ownerId) and (sortKey eq refId) // no attributes involved
    }
}

This solution solves the naming/typing conflict with the current eq function.
It additionally improves the type safety since I cannot use the wrong attributes in the key condition (which would be the case with a generic eq(value: T) function). Funny enough, there is already a test for the count function, which was successful querying the fake, but it used the wrong index! After the migration to the new syntax the test failed (and so I discovered the bug I introduced previously).
I made the current functions @Deprecated (in case someone is already using the DSL).
Note, for the filterExpression the existing solution is unchanged, since the set of attributes that can be used in the filter expression is not defined by the schema (apart from the little detail, that the key attributes mustn't be used, but this is nothing the DSL syntax can solve).

authors: daviddenton obecker oharaandrew314


text:
Fix ping pong and close frames

This fulfills all the tests of Autobahn test suite 1 and 2, except for some proper cleaning of the connection.

unbelievable !

repo: httpswift/swifter


text:
Add Whatsapp support

This will add Whatsapp support.
Given Whatsapp doesn't have a desktop web sharing URL like other
services, we have to do some out-of-the-box implementation here.
Whatsapp sharing URL starts with whatsapp://send, not https://,
which works on mobile but not on desktop (unless you have the Whatsapp Desktop
app). That means it will break for the majority of people on desktop.
To minimize risks, we:

don't add whatsapp by default and leave this decision up
to the developer. If they want to add it, they just need to add whatsapp to
the allow_sites config initializer.
we have a new CSS rule that will hide it on desktop browsers.
Developers are free to override it if they want to show it everywhere.

Extra: added a pt-BR locale file.

it can't work in desktop browser

Yes, it doesn't, reason why it's hidden there and not on by default.

So, merge?

authors: huacnlee kurko

repo: huacnlee/social-share-button


text:
移动网络下不显示图片能不能不要一直提示呢？

这个一直提示确实有点烦，希望大佬可以改一下

不开启智能无图就没事 即使开启了 手动点击关闭 就可以下次不提示

没有开智能无图呀

软件由于考虑到并不是太多人需要更新 所以不手动检测更新是不会接受到最新版本的 你可以在关于查看是否为最新版

repo: huajiqaq/Hydrogen


text:
jyson supports an array of objects

Added in testing for node 8

Resolves Issue #9

@misshula @etorrejon I am going to propose we merge this and then figure out a better way to solve this issue later

repo: hubba/jyson


text:
8th release notes content

Starting to draft content in Google Doc: 8th Release Notes

Ready for dev

Please create a new page/URL using the release notes template for 8th Release Notes.

https://humanatlas.io/release-notes/v2.2 or whatever @bherr2 recommends!

Please add the content and links from the Google Document.
@bherr2, can you please provide us with summary numbers for the top of the data section? Thank you!

Team, please reach out with any questions. I appreciate you!
Resources

Content source of truth: Google Doc - 8th Release Notes
Figma mockup for visual guidance of sections: 8th Release Notes

Superseded by #880

repo: hubmapconsortium/hra-ui


text:
don’t load unsupported files

closes #1355

@technicalpickles the GitHub CLA status is stuck again, can I ignore and just merge things in when there is a approving review?

I disabled the CLA check for now.
FYI @mlinksva

repo: hubotio/hubot


text:
🛑 VGMdb API is down

In 79e34ec, VGMdb API (https://vgmdb.info) was down:

HTTP code: 0
Response time: 0 ms

Resolved: VGMdb API is back up in 84568f3 after 10 hours, 9 minutes.

repo: hufman/upptime


text:
🛑 Akkoma is down

In 979b90c, Akkoma (https://akkoma.chez.chat) was down:

HTTP code: 404
Response time: 481 ms

Resolved: Akkoma is back up in 7787b2e after 6 minutes.


text:
Add PaliGemma2 examples

Description
This PR adds some PaliGemma2 examples along with the Hugging Face DLC for TGI (3.0.1) release on Google Cloud!
The examples cover the following:

PaliGemma2 3B 224px deployment on GKE, including how to run inference and some use-cases / scenarios for PaliGemma2
PaliGemma2 on Vertex AI / Cloud Run (WIP)

[!NOTE]
Note that the example structure has changed a bit to make it more readable, easy to follow, and adding or removing information when needed and when not needed, respectively.

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

authors: HuggingFaceDocBuilderDev alvarobartt

repo: huggingface/Google-Cloud-Containers


text:
It seems deepspeed activation checkpointing is not support in accelerate?

I use the following setting in deepspeed config and launch with
accelerate launch \
    --use_deepspeed \
    --deepspeed_config_file  my_deepspeed_config\
    ...

"activation_checkpointing": {
        "partition_activations": true,
        "cpu_checkpointing": true,
        "contiguous_memory_optimization": true,
        "number_checkpoints": 8,
        "synchronize_checkpoint_boundary": true,
        "profile": true
    }

But the GPU memory usage is the same as turning this off

cc @pacman100

Deepspeed's activation checkpointing has some superior features, so it'd be probably useful to explore:
https://deepspeed.readthedocs.io/en/latest/activation-checkpointing.html
The thing is you need to change the modeling code to replace the pytorch checkpointing code with deepspeed's one for this to work. So you don't need Accelerate to do that for you, you can just do it.
I wonder if some monkey patching could be used to keep the HF Transformers modeling code intact and replace torch.utils.checkpoint with deepspeed.checkpointing.checkpoint

Is there a tutorial for using DeepSpeed's activation checkpointing instead of PyTorch's?

authors: chenjianhuii huyiwen muellerzr stas00

repo: huggingface/accelerate


text:
Using DDP with Huggingface Trainer

How is it that this autotrainer is able to do DDP with model initialisation with device_map='auto' while I get the following error when trying to do DDP with the native Huggingface trainer?

ValueError: You can't train a model that has been loaded with device_map='auto' in any distributed mode. Please rerun your script specifying --num_processes=1 or by launching with python {{myscript.py}}.

it uses accelerate

You can't train a model that has been loaded with device_map='auto' in any distributed mode. Please rerun your script specifying --num_processes=1 or by launching with python {{myscript.py}}.
i am using torchrun for dist trainning.

I have same situation, is there any way to train model with DDP?

what is the situation? write full log and create new issue please. all models train with ddp in a multi gpu setup by default.

what is the situation? write full log and create new issue please. all models train with ddp in a multi gpu setup by default.

yep, my situation is when i use torchrun for training and set --nproc_per_node as more than 2, it just copy the parameters of model to every avaliable gpus, instead of loading model's different part to different GPUs.
I wonder know how can I load model's different layer to different gpu while training.

is this a autotrain issue? where does torchrun come from in autotrain? if its not a issue concerning this repo, please find appropriate repo to ask the question in.

sorry, if I want to use autotrainer to do DDP, how can I set parameters?

as i mentioned, it automatically uses ddp. ill lock this issue now as it was never relevant to autotrain. please feel free to create a new issue with all the logs in order for me to help.

repo: huggingface/autotrain-advanced


text:
NVIDIA Cloud Functions backend

Add NVIDIA Cloud Functions (NVCF) backend support
Allow non-blocking autotrain job submissions
Enable polling for appropriate function cleanup until native job support is enabled for NVCF

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

authors: HuggingFaceDocBuilderDev liveaverage


text:
Add a RAG via Elasticsearch, Hugging Face models cookbook

What does this PR do?
I thought it would be useful to provide a cookbook for a RAG backed by Elasticsearch, Hugging Face models, and Gemma.
Users can easily toggle between vectorisation that is offloaded to ES and self-provided (pre)-vectorisation.
Who can review?
Feel free to tag members/contributors who may be interested in your PR.

@merveenoyan
@stevhliu.

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

Thanks for your thorough review @stevhliu 🙇♂
As noted above, the image change requires merging https://huggingface.co/datasets/huggingface/cookbook-images/discussions/20

Thanks @stevhliu , really appreciate your patience in this review; it's my first Jupyter notebook PR and I'm not used to the UI (e.g. accidentally adding a blank cell 🤦🏻♂)  and the way diffs/suggestions are shown.

authors: HuggingFaceDocBuilderDev lloydmeta

repo: huggingface/cookbook


text:
Translate Romanian Chapter 0

This is the romanian translation of chapter 0, the introduction.
Ping @lewtun  and @stevhliu for a review

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

Hi, I am Ludmila, I am a native Romanian speaker, I had a look through eduard-balamatiuc 's translation process. Everything looks good till now!

repo: huggingface/course


text:
Scifi_TV_Shows: Having trouble getting viewer to find appropriate files

Dataset viewer issue for 'Science Fiction TV Show Plots Corpus  (Scifi_TV_Shows)'
Link: link
I tried adding both a script (https://huggingface.co/datasets/lara-martin/Scifi_TV_Shows/blob/main/Scifi_TV_Shows.py) and some dummy examples (https://huggingface.co/datasets/lara-martin/Scifi_TV_Shows/tree/main/dummy), but the viewer still has a 404 error ("Not found. Maybe the cache is missing, or maybe the ressource does not exist."). I'm not sure what to try next. Thanks in advance!
Am I the one who added this dataset? Yes

Hi ! I think this is because iter_archive doesn't support ZIP files yet. See https://github.com/huggingface/datasets/issues/3272
You can navigate into the archive this way instead:
# in split_generators
data_dir = dl_manager.download_and_extract(url)
train_filepath = os.path.join(data_dir, "all-sci-fi-data-train.txt")
return [
        datasets.SplitGenerator(
            name=datasets.Split.TRAIN,
            gen_kwargs={
                "filepath": train_filepath,
            },
        ),
...
])

# in generate_examples
with open(filepath, encoding="utf-8") as f:
    ...

It's working: https://huggingface.co/datasets/lara-martin/Scifi_TV_Shows/viewer/Scifi_TV_Shows/test

authors: lara-martin lhoestq severo

repo: huggingface/datasets


text:
Unit 2 finetune_model.py crashes on line 117 image_pipe.save_pretrained(...)

I get the error when running the script using the suggested command line.
python finetune_model.py --image_size 128 --batch_size 8 --num_epochs 16 --grad_accumulation_steps 2 --start_model "google/ddpm-celebahq-256" --dataset_name "Norod78/Vintage-Faces-FFHQAligned" --wandb_project 'dm-finetune' --log_samples_every 100 --save_model_every 1000 --model_save_name 'vintageface'
Running Python 3.11.8 on Windows 11.
Error is "TypeError: Object of type WindowsPath is not JSON serializable"
It does create the "vintageface \ unet" directory and an empty file "config.json"
Here is the end of the log:
File "C:\Users\Vincent Dovydaitis\Build\diffusion-models-class\unit2\finetune_model.py", line 117, in train
image_pipe.save_pretrained(model_save_name)
File "C:\Users\Vincent Dovydaitis.conda\envs\vision\Lib\site-packages\diffusers\pipelines\pipeline_utils.py", line 284, in save_pretrained
save_method(os.path.join(save_directory, pipeline_component_name), **save_kwargs)
File "C:\Users\Vincent Dovydaitis.conda\envs\vision\Lib\site-packages\diffusers\models\modeling_utils.py", line 315, in save_pretrained
model_to_save.save_config(save_directory)
File "C:\Users\Vincent Dovydaitis.conda\envs\vision\Lib\site-packages\diffusers\configuration_utils.py", line 168, in save_config
self.to_json_file(output_config_file)
File "C:\Users\Vincent Dovydaitis.conda\envs\vision\Lib\site-packages\diffusers\configuration_utils.py", line 610, in to_json_file
writer.write(self.to_json_string())
^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Vincent Dovydaitis.conda\envs\vision\Lib\site-packages\diffusers\configuration_utils.py", line 599, in to_json_string
return json.dumps(config_dict, indent=2, sort_keys=True) + "\n"
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\Vincent Dovydaitis.conda\envs\vision\Lib\json_init_.py", line 238, in dumps
**kw).encode(obj)
^^^^^^^^^^^
File "C:\Users\Vincent Dovydaitis.conda\envs\vision\Lib\json\encoder.py", line 202, in encode
chunks = list(chunks)
^^^^^^^^^^^^
File "C:\Users\Vincent Dovydaitis.conda\envs\vision\Lib\json\encoder.py", line 432, in _iterencode
yield from _iterencode_dict(o, _current_indent_level)
File "C:\Users\Vincent Dovydaitis.conda\envs\vision\Lib\json\encoder.py", line 406, in _iterencode_dict
yield from chunks
File "C:\Users\Vincent Dovydaitis.conda\envs\vision\Lib\json\encoder.py", line 439, in _iterencode
o = _default(o)
^^^^^^^^^^^
File "C:\Users\Vincent Dovydaitis.conda\envs\vision\Lib\json\encoder.py", line 180, in default
raise TypeError(f'Object of type {o.class.name} '
TypeError: Object of type WindowsPath is not JSON serializable

I these two days have also met this question.

@vincedovy Have you solved the problem?

There is a pull request in diffusers that fixes this issue. https://github.com/huggingface/diffusers/pull/8662

See above, there is an issue and pull request in diffusers that fixes this issue. https://github.com/huggingface/diffusers/pull/8662

repo: huggingface/diffusion-models-class


text:
Add list_repo_likers method to HfApi

Summary
This PR introduces the list_repo_likers method to the HfApi class, allowing users to retrieve a list of likers for a given model repository on the Hugging Face Hub.
Changes

Implemented list_repo_likers method in HfApi.
Added corresponding dataclass User to represent users who liked a repo.
Integrated a new API endpoint to fetch likers for a given model repository.
Added unit tests to ensure the correctness of the method.

Motivation

Fixes #1705 - Return the liked users for a Hugging Face model
Users will now have the ability to see who liked their models, fostering community interactions and recognition.

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint.

awesome job @issamarabi 🔥


text:
Fix ACT temporal ensembling

What this does
Fixes an issue with the weighting scheme for the temporal ensembling:

The fix is to directly use the exponential weighting scheme referred to in Algo2 of https://arxiv.org/abs/2304.13705

Here I implement it in an online update fashion so we don't have the ugliness of storing a cache of actions.
How it was tested
I added a test for CI.
I tried eval'ing https://huggingface.co/lerobot/act_aloha_sim_transfer_cube_human/tree/main for 500 episodes with temporal ensembling.

Setup
Success rate

Without temporal ensembling
87.6%

Prior implementation α=0.99
72.6%

This implementation m=0.01
70.8%

This implementation m=-0.01
62.2%

Here's an episode for m=0.01:
https://github.com/user-attachments/assets/057b357e-0de2-4dcb-ade2-307fbdc41cae
How to checkout & try? (for the reviewer)
Try it with python lerobot/scripts/eval.py -p lerobot/act_aloha_sim_transfer_cube_human eval.n_episodes=10 eval.batch_size=10 +policy.temporal_ensemble_coeff=0.01 policy.n_action_steps=1

@Alternmill for review please.

@Cadene it doesn't break unit tests because of this https://github.com/huggingface/lerobot/blob/5ffcb48a9a1d53cedd92632b3d95052343cdd801/lerobot/common/policies/factory.py#L25-L44, which means temporal_ensemble_momentum will be ignored and temporal_ensemble_coeff will get a warning.
I think we should probably make consider making the former case raise an exception, but there may be a good reasons I didn't do that in the first place.
Yes, I'll mention it on Discord.

@alexander-soare Could be better to raise an exception to avoid people overriding an argument from command line and it is actually ignored, but they didnt see the warning.
When we go out of alpha into beta, we should try our best to be backward compatible instead of raising exceptions.

@Cadene I'm not sure I understand. I suggested raising an exception if someone provides an unknown param. Are you saying something else?

authors: Cadene alexander-soare

repo: huggingface/lerobot


text:
feat: Add adaptors for various backends (ollama, tgi, api-inference)

Allow users to specify the key the input will be sent to in the request to the llm (defaults to "input")
Allow users to add arbitrary data to be sent in the request to the llm

This should resolve issue https://github.com/huggingface/llm-ls/issues/17, by allowing users to remap "input" to "prompt" add adding { model: "model:nb-code" }
This will require further changes on clients as well (such as llm.nvim) - happy to contribute here as well

Hey McPatate, my limited understanding is that a server usually responds with a text stream. If not the case I can see how that would need to be addressed, maybe for a separate PR.
I feel that adding support through an identifier might be more hefty to maintain, if the project ends up having logic to handle dozens of possible backends I could see it becoming bloated.
Perhaps supporting a plugin or middleware approach would make more sense, and let the community create what they need for their backend when they need it.
I'm still playing around with this, but I'm aiming to support usage of Ollama through llm.nvim

Ollama's response is not supported by llm-ls currently, it needs to be handled otherwise it won't work.
I wonder if we'll ever get to dozens of different backends. I believe at some point we'll stabilise on an API and people will implement "the standard" rather than re-invent a new thing.
But yes at first we'll need to implement a few of them before that crystallises. Not sure if the plugin route will solve anything and might be too much work compared to just adding different backends.

@McPatate do you think it's worth me re-implementing https://github.com/huggingface/llm-ls/pull/42 as an adaptor?

@McPatate do you think it's worth me re-implementing https://github.com/huggingface/llm-ls/pull/42 as an adaptor?

Yes good idea

Thanks for the feedback @McPatate, it's been really helpful

Thank you for your contribution!

Keen to know if there's anything else you think we need to get this through

How have you tested your PR? If the CI passes and your testing is conclusive then we should be able to merge.
We will need to update all clients to match the new API as well, is this something you'd be willing to do as well?

Thanks for the feedback @McPatate, it's been really helpful

Thank you for your contribution!

Keen to know if there's anything else you think we need to get this through

How have you tested your PR? If the CI passes and your testing is conclusive then we should be able to merge.
We will need to update all clients to match the new API as well, is this something you'd be willing to do as well?

I've been testing by hacking around in llm.nvim. I'll need to retest though as I haven't tested this in a good while.
I don't think I have time to update all the clients, but I can make a PR for what I've done in llm.nvim when ready

I'm trying to test this but running into an issue where it's complaining about the case of the request parameters given.

I'm using https://github.com/noahbald/llm.nvim as my client here.
Is this something to do with #[serde(rename_all = "camelCase")]?

Is this something to do with #[serde(rename_all = "camelCase")]?

Yes, I've recently changed the API to make the case consistent across parameters. I haven't released a version of llm-ls yet since it's a breaking change. I was waiting for a few other things before creating a new release, like your PR and what I'm currently working on.

I've got it working using my fork of llm.nvim - I'll make a PR for that!
You may want to test with openai and huggingface as well. I don't have accounts with either so I haven't tested there

@noahbald @McPatate
Thanks for the amazing work.
I managed to test it locally by running Open Hermes Mistral 2.5-7B by Teknium

However, I had to copy paste all snake_case configs to camelCase
  local params = lsp.util.make_position_params()
  params.model = utils.get_model()
  params.tokens_to_clear = config.get().tokens_to_clear
  params.tokensToClear = config.get().tokens_to_clear
  params.api_token = config.get().api_token
  params.apiTokens = config.get().tokens_to_clear
  params.request_params = config.get().query_params
  params.request_params.do_sample = config.get().query_params.temperature > 0
  params.requestParams = config.get().query_params
  params.requestParams.doSample = config.get().query_params.temperature > 0
  params.fim = config.get().fim
  params.tokenizer_config = config.get().tokenizer
  params.tokenizerConfig = config.get().tokenizer
  params.context_window = config.get().context_window
  params.contextWindow = config.get().context_window
  params.tls_skip_verify_insecure = config.get().tls_skip_verify_insecure
  params.tlsSkipVerifyInsecure = config.get().tls_skip_verify_insecure
  params.adaptor = config.get().adaptor
  params.request_body = config.get().request_body
  params.requestBody = config.get().request_body
  params.ide = "neovim"

Hopefully, the changes will get merged to main branch soon. Really excited for this one 🤠

@noahbald @McPatate Thanks for the amazing work.
I managed to test it locally. Models:

 Open Hermes Mistral 2.5-7B merged with Intel neural chat v3.3
 Open Hermes Mistral 2.5-7B by Teknium

However, I had to copy paste all snake_case configs to camelCase
  local params = lsp.util.make_position_params()
  params.model = utils.get_model()
  params.tokens_to_clear = config.get().tokens_to_clear
  params.tokensToClear = config.get().tokens_to_clear
  params.api_token = config.get().api_token
  params.apiTokens = config.get().tokens_to_clear
  params.request_params = config.get().query_params
  params.request_params.do_sample = config.get().query_params.temperature > 0
  params.requestParams = config.get().query_params
  params.requestParams.doSample = config.get().query_params.temperature > 0
  params.fim = config.get().fim
  params.tokenizer_config = config.get().tokenizer
  params.tokenizerConfig = config.get().tokenizer
  params.context_window = config.get().context_window
  params.contextWindow = config.get().context_window
  params.tls_skip_verify_insecure = config.get().tls_skip_verify_insecure
  params.tlsSkipVerifyInsecure = config.get().tls_skip_verify_insecure
  params.adaptor = config.get().adaptor
  params.request_body = config.get().request_body
  params.requestBody = config.get().request_body
  params.ide = "neovim"

Hopefully, the changes will get merged to main branch soon. Really excited for this one 🤠

Thanks for testing, the casing changes are expected at the moment, McPatate is working on that separately

Yes, I've recently changed the API to make the case consistent across parameters. I haven't released a version of llm-ls yet since it's a breaking change. I was waiting for a few other things before creating a new release, like your PR and what I'm currently working on.

Since I can't seem to run the CI without risking to leak the tokens to the world, I ran it locally and things seem to be broken:
cargo +nightly run --bin testbed -r -- --api-token $API_TOKEN -r `pwd`/crates/testbed/repositories-ci.yaml -f simple

Produces:

Repository name
Source type
Average hole completion time (s)
Pass percentage

simple
local
0.14864999
0%

Total
--
0.14864999
0%

When it should be 100%

I'd suggest using a debugger or just adding random prints in the the testbed code and try to see where the IO error is coming from.
You have to be at the root of the folder to run the command and your API_TOKEN should be your HF token.
If you're really struggling I'll take a look. I haven't completely documented testbed and there are some subtleties that may not be very user friendly at times, sorry about that.

I've done a sync with main and unfortunately I can't seem to run the tester at all in my environment (wsl)

Try setting LOG_LEVEL=debug when running testbed to see if you get more information. You can set the log level per crate as well, see how RUST_LOG format works, it's the same for the LOG_LEVEL var.
Also, you'll need to run testbed from the root of the directory, so:
--r ../../crates/testbed/repositories-ci.yaml
+-r crates/testbed/repositories-ci.yaml

With pwd returning /path/to/llm-ls

Thanks Luc, I hadn't run a release build so llm-ls was missing from target/release.
I've run the test and it's passing for me. Maybe I'm missing something or maybe it was fixed with a recent commit.
2023-12-31T03:53:29.708931Z  INFO testbed: 726: simple from local obtained 100.00% in 3.544s
2023-12-31T03:53:29.709274Z  INFO testbed: 747: all tests were run, exiting

Thank you very much for the hard work on this PR @noahbald, especially while putting up with my incessant pestering 😉

authors: McPatate manish-baghel noahbald

repo: huggingface/llm-ls


text:
Fix camelCase API compatibility

building on top of https://github.com/huggingface/llm-vscode/pull/122
fixing the casing also for the acceptCompletion call

@McPatate thanks for reviewing and merging all my PRs in llm-ls, I have a few open in here as well, would be great if you could have a look, thanks!

repo: huggingface/llm-vscode


text:
FileNotFoundError raised when calling sysctl -n machdep.cpu.brand_string

This results in https://app.warp.dev/block/NDK6NzeHhzHjb32CEAHlpB, although https://app.warp.dev/block/ujVpYSCSEJmXfMkODF8Bgt.

I believe this was fixed in https://github.com/huggingface/optimum-benchmark/pull/63

authors: IlyasMoutawwakil keyboardAnt

repo: huggingface/optimum-benchmark


text:
Enable t.compile for Granite20B

Enable t.compile for Granite20B
Granite20B model uses the GPTBigCode model type. In this model, model object uses model.transformer instead of model.model for the actual model. This is a pointed fix for this model, in future other models may need similar change.
What does this PR do?

Fixes # (issue)
Before submitting

[ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
[ ] Did you make sure to update the documentation with your changes?
[ ] Did you write any new necessary tests?

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repo: huggingface/optimum-habana


text:
fix perf drop in flan-t5 summarization

Upto 7% performance drop observed in flan-t5 8x summarization task with deepspeed-fork (synapse 1.16 version).
This PR fixes that.

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

https://github.com/HabanaAI/optimum-habana-fork/pull/173


text:
Fixed examples test error to adapt to neural_compressor v2.3

What does this PR do?
Fixed examples test error to adapt to neural_compressor v2.3

Before submitting

[ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
[ ] Did you make sure to update the documentation with your changes?
[ ] Did you write any new necessary tests?

Thanks a lot for adding this in anticipation to the neural-compressor release. Is there any additional modification that needs to be added so that everything stays compatible ?

No more changes for neural compressor 2.3 version

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint.

authors: HuggingFaceDocBuilderDev PenghuiCheng

repo: huggingface/optimum-intel


text:
raises value error for bert tokenizer for long sequences

addesses #125
(all pre-trained bert models have a positional embedding matrix with 512 embeddings. Sequences longer than 512 tokens will cause indexing errors when you attempt to run a bert forward pass on them)
added a max_len arg to bert tokenizer. the function convert_tokens_to_indices will raise a value error if the inputted list of tokens is longer than max_len.
if no max_len is supplied, then no value error will be raised, however long the sequence is
Pre-trained bert models have max_len set to 512 at object construction time (in BertTokenizer.from_pretrained. It can be overridden by explicitly passing max_len to BertTokenizer.from_pretrained as a kwarg
if bert models with larger positional embedding matrices are released, it is possible to have different max_lens for different pretrained_models.

Thanks @patrick-s-h-lewis, this is nice.
The max number of positional embeddings is available in the pretrained models configuration files also (as max_position_embeddings) but this requires some change in the models stored on S3 so I will take care of it in the next release.

authors: patrick-s-h-lewis thomwolf

repo: huggingface/pytorch-pretrained-BERT


text:
How to restore a training?

For example, I use "run_glue.py" to train a model and stop at Epoch 30, and how to restore the training process from Epoch 30?

You will have to modify the provided example to save/reload the model, optimizer and scheduler states.
I've updated the scheduler classes in #872 so that we can save/reload the schedulers with the standard PyTorch serialization practice:
torch.save(schedule.state_dict(), FILE_NAME)           # save
schedule.load_state_dict(torch.load(FILE_NAME))    # reload

Thanks for the response~

@thomwolf - I happen to need save/resume training for run_glue.py; I'm willing to implement this and make a PR if I can get feedback about the overall approach.
It looks like I would want to save:

global_step
step (from this one could presumably skip to the right place in the epoch_iterator of train)
optimizer, model, scheduler (these look like they should be trivially amenable to torch.save)
random seed, torch's random seed, numpy's random seed

Based on the current set up, I'm not actually sure what the right way to preserve the train_sampler and train_dataloader states are (without also serializing them too, which seems like a waste, but is by far the easiest way to handle it if they are so amenable), since their states can't be recreated with the above information. In my case, punting on these is an acceptable option, as well as being wasteful and saving to disk.
Thoughts?

authors: bingyupiaoyao jayded thomwolf

repo: huggingface/pytorch-transformers


text:
🕊 DPO padding free

What does this PR do?
demo
from datasets import load_dataset
from transformers import AutoModelForCausalLM, AutoTokenizer
from trl import DPOConfig, DPOTrainer
import torch

model_id = "Qwen/Qwen2-0.5B-Instruct"
model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.bfloat16, attn_implementation="flash_attention_2")
tokenizer = AutoTokenizer.from_pretrained(model_id)
dataset = load_dataset("trl-lib/ultrafeedback_binarized", split="train[:10%]")
training_args = DPOConfig(output_dir="Gemma2-2B-DPO-pf", max_prompt_length=128, max_completion_length=128, logging_steps=10, padding_free=True)
trainer = DPOTrainer(model=model, args=training_args, train_dataset=dataset, processing_class=tokenizer)
trainer.train()

Before submitting

[ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
[ ] Did you read the contributor guideline,
Pull Request section?
[ ] Was this discussed/approved via a GitHub issue? Please add a link
to it if that's the case.
[ ] Did you make sure to update the documentation with your changes? Here are the
documentation guidelines.
[ ] Did you write any new necessary tests?

Who can review?
Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

authors: HuggingFaceDocBuilderDev qgallouedec

repo: huggingface/trl


text:
Handle lazy loading of Agents in gems during Agent.receive!

I was having Events fail to propagate and traced it back to my Agent Gem not showing up as const_defined? in Agent.receive!. Inspired by https://github.com/rails-api/active_model_serializers/pull/615/files, I updated this, and it seems to have fixed the issue for me.

Thanks!

Nice, thanks. I am wondering why it happened in the first place, we trigger HuginnAgent.require! in an initializer which then requires all Agent files. Does const_get trigger lazy loading, it can't work across gem, can't it?

authors: cantino dsander

repo: huginn/huginn


text:
Neetty高性能网络通讯框架 - YangZheng Blog

https://huiyideshalouya.github.io/2024/07/07/Netty 高性能网络通讯框架/

不错哟!!!

repo: huiyideshalouya/GitTalk


text:
fix: remove bottom toolbar

Description
This PR removes bottom toolbar in tools table.
Summary of changes

How test the changes

Related issues
Keywords for linking issues

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you all sign our Contributor License Agreement before we can accept your contribution.9 out of 10 committers have signed the CLA.:white_check_mark: KacperKoza343:white_check_mark: eugenvoronov:white_check_mark: rozekmichal:white_check_mark: portuu3:white_check_mark: dnechay:white_check_mark: zhiltsov-max:white_check_mark: flopez7:white_check_mark: Bobronium:white_check_mark: Dzeranov:x: mpblockyYou have signed the CLA already but the status is still pending? Let us recheck it.

authors: CLAassistant mpblocky

repo: humanprotocol/human-protocol


text:
Feat/dependabot updates

Description
Manually upgrade packages versions from automatic upgrades (#576  #577 #578  #579 ). Automatic upgrades create PRs to main and had conflicts
How test the changes
CI
Related issues
Closes #576  #577 #578  #579

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you all sign our Contributor License Agreement before we can accept your contribution.5 out of 6 committers have signed the CLA.:white_check_mark: Jalal-1:white_check_mark: portuu3:white_check_mark: leric7:white_check_mark: basit511:white_check_mark: m00n620:x: snyk-botYou have signed the CLA already but the status is still pending? Let us recheck it.


text:
Set default if no value is set for variables which require that

Fix #30, #34, #37.

@humboldtux, will you able to merge that?

Thanks

authors: humboldtux paskal

repo: humboldtux/startbootstrap-clean-blog


text:
Fix minimum swift-nio version to use async/await FileIO APIs.

2.0.0-beta.2 uses async/await FileIO APIs in NIO.
Package.swift points to 2.62.0 as the minimum version, but this API was introduced in 2.63.0.
INFO: https://github.com/apple/swift-nio/releases/tag/2.63.0

Thank you

authors: adam-fowler sidepelican

repo: hummingbird-project/hummingbird


text:
Getting an error when trying to approve token

Hi Team, I run "gateway approve-tokens uniswap_ethereum_mainnet WETH" to approve the token through docker env. of Hummingbot. But I am facing below error after run the above command. I have attached the screenshot.

Please help me. Thanks in advance for your support.

Hi @debanjanAqb good day,
As per error I would like to check whether I have a working node or ok internet connection. Another is we are missing out the details we need to investigate which is available on our bug report template. Please resubmit and make further look into it. Thank you

authors: debanjanAqb rapcmia

repo: hummingbot/hummingbot