 This might cause deadlock in distributed execution.
ERROR 09-05 05:00:27 worker_base.py:464] Traceback (most recent call last):
ERROR 09-05 05:00:27 worker_base.py:464]   File "/usr/local/lib/python3.10/dist-packages/vllm/worker/worker_base.py", line 456, in execute_method
ERROR 09-05 05:00:27 worker_base.py:464]     return executor(*args, **kwargs)
ERROR 09-05 05:00:27 worker_base.py:464]   File "/usr/local/lib/python3.10/dist-packages/vllm/worker/worker_base.py", line 327, in execute_model
ERROR 09-05 05:00:27 worker_base.py:464]     output = self.model_runner.execute_model(
ERROR 09-05 05:00:27 worker_base.py:464]   File "/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py", line 116, in decorate_context
ERROR 09-05 05:00:27 worker_base.py:464]     return func(*args, **kwargs)
ERROR 09-05 05:00:27 worker_base.py:464]   File "/usr/local/lib/python3.10/dist-packages/vllm/worker/multi_step_model_runner.py", line 390, in execute_model
ERROR 09-05 05:00:27 worker_base.py:464]     model_input = self._advance_step(
ERROR 09-05 05:00:27 worker_base.py:464]   File "/usr/local/lib/python3.10/dist-packages/vllm/worker/multi_step_model_runner.py", line 499, in _advance_step
ERROR 09-05 05:00:27 worker_base.py:464]     assert isinstance(attn_metadata, FlashAttentionMetadata)
ERROR 09-05 05:00:27 worker_base.py:464] AssertionError
ERROR 09-05 05:00:27 async_llm_engine.py:63] Engine background task failed
ERROR 09-05 05:00:27 async_llm_engine.py:63] Traceback (most recent call last):
ERROR 09-05 05:00:27 async_llm_engine.py:63]   File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 53, in _log_task_completion
ERROR 09-05 05:00:27 async_llm_engine.py:63]     return_value = task.result()
ERROR 09-05 05:00:27 async_llm_engine.py:63]   File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 939, in run_engine_loop
ERROR 09-05 05:00:27 async_llm_engine.py:63]     result = task.result()
ERROR 09-05 05:00:27 async_llm_engine.py:63]   File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 868, in engine_step
ERROR 09-05 05:00:27 async_llm_engine.py:63]     request_outputs = await self.engine.step_async(virtual_engine)
ERROR 09-05 05:00:27 async_llm_engine.py:63]   File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 345, in step_async
ERROR 09-05 05:00:27 async_llm_engine.py:63]     output = await self.model_executor.execute_model_async(
ERROR 09-05 05:00:27 async_llm_engine.py:63]   File "/usr/local/lib/python3.10/dist-packages/vllm/executor/ray_gpu_executor.py", line 502, in execute_model_async
ERROR 09-05 05:00:27 async_llm_engine.py:63]     return await super().execute_model_async(execute_model_req)
ERROR 09-05 05:00:27 async_llm_engine.py:63]   File "/usr/local/lib/python3.10/dist-packages/vllm/executor/distributed_gpu_executor.py", line 177, in execute_model_async
ERROR 09-05 05:00:27 async_llm_engine.py:63]     return await self._driver_execute_model_async(execute_model_req)
ERROR 09-05 05:00:27 async_llm_engine.py:63]   File "/usr/local/lib/python3.10/dist-packages/vllm/executor/ray_gpu_executor.py", line 519, in _driver_execute_model_async
ERROR 09-05 05:00:27 async_llm_engine.py:63]     return await self.driver_exec_method("execute_model",
ERROR 09-05 05:00:27 async_llm_engine.py:63]   File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
ERROR 09-05 05:00:27 async_llm_engine.py:63]     result = self.fn(*self.args, **self.kwargs)
ERROR 09-05 05:00:27 async_llm_engine.py:63]   File "/usr/local/lib/python3.10/dist-packages/vllm/worker/worker_base.py", line 465, in execute_method
ERROR 09-05 05:00:27 async_llm_engine.py:63]     raise e
ERROR 09-05 05:00:27 async_llm_engine.py:63]   File "/usr/local/lib/python3.10/dist-packages/vllm/worker/worker_base.py", line 456, in execute_method
ERROR 09-05 05:00:27 async_llm_engine.py:63]     return executor(*args, **kwargs)
ERROR 09-05 05:00:27 async_llm_engine.py:63]   File "/usr/local/lib/python3.10/dist-packages/vllm/worker/worker_base.py", line 327, in execute_model
ERROR 09-05 05:00:27 async_llm_engine.py:63]     output = self.model_runner.execute_model(
ERROR 09-05 05:00:27 async_llm_engine.py:63]   File "/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py", line 116, in decorate_context
ERROR 09-05 05:00:27 async_llm_engine.py:63]     return func(*args, **kwargs)
ERROR 09-05 05:00:27 async_llm_engine.py:63]   File "/usr/local/lib/python3.10/dist-packages/vllm/worker/multi_step_model_runner.py", line 390, in execute_model
ERROR 09-05 05:00:27 async_llm_engine.py:63]     model_input = self._advance_step(
ERROR 09-05 05:00:27 async_llm_engine.py:63]   File "/usr/local/lib/python3.10/dist-packages/vllm/worker/multi_step_model_runner.py", line 499, in _advance_step
ERROR 09-05 05:00:27 async_llm_engine.py:63]     assert isinstance(attn_metadata, FlashAttentionMetadata)
ERROR 09-05 05:00:27 async_llm_engine.py:63] AssertionError
Exception in callback functools.partial(<function _log_task_completion at 0x7f47d481f640>, error_callback=<bound method AsyncLLMEngine._error_callback of <vllm.engine.async_llm_engine.AsyncLLMEngine object at 0x7f47d13b96f0>>)
handle: <Handle functools.partial(<function _log_task_completion at 0x7f47d481f640>, error_callback=<bound method AsyncLLMEngine._error_callback of <vllm.engine.async_llm_engine.AsyncLLMEngine object at 0x7f47d13b96f0>>)>
Traceback (most recent call last):
  File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 53, in _log_task_completion
    return_value = task.result()
  File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 939, in run_engine_loop
    result = task.result()
  File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 868, in engine_step
    request_outputs = await self.engine.step_async(virtual_engine)
  File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 345, in step_async
    output = await self.model_executor.execute_model_async(
  File "/usr/local/lib/python3.10/dist-packages/vllm/executor/ray_gpu_executor.py", line 502, in execute_model_async
    return await super().execute_model_async(execute_model_req)
  File "/usr/local/lib/python3.10/dist-packages/vllm/executor/distributed_gpu_executor.py", line 177, in execute_model_async
    return await self._driver_execute_model_async(execute_model_req)
  File "/usr/local/lib/python3.10/dist-packages/vllm/executor/ray_gpu_executor.py", line 519, in _driver_execute_model_async
    return await self.driver_exec_method("execute_model",
  File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
    result = self.fn(*self.args, **self.kwargs)
  File "/usr/local/lib/python3.10/dist-packages/vllm/worker/worker_base.py", line 465, in execute_method
    raise e
  File "/usr/local/lib/python3.10/dist-packages/vllm/worker/worker_base.py", line 456, in execute_method
    return executor(*args, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/vllm/worker/worker_base.py", line 327, in execute_model
    output = self.model_runner.execute_model(
  File "/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py", line 116, in decorate_context
    return func(*args, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/vllm/worker/multi_step_model_runner.py", line 390, in execute_model
    model_input = self._advance_step(
  File "/usr/local/lib/python3.10/dist-packages/vllm/worker/multi_step_model_runner.py", line 499, in _advance_step
    assert isinstance(attn_metadata, FlashAttentionMetadata)
AssertionError

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "uvloop/cbhandles.pyx", line 63, in uvloop.loop.Handle._run
  File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 65, in _log_task_completion
    raise AsyncEngineDeadError(
vllm.engine.async_llm_engine.AsyncEngineDeadError: Task finished unexpectedly. This should never happen! Please open an issue on Github. See stack trace above for the actual cause.
ERROR 09-05 05:00:27 client.py:266] Got Unhealthy response from RPC Server
ERROR 09-05 05:00:27 client.py:412] AsyncEngineDeadError('Background loop is stopped.')
ERROR 09-05 05:00:27 client.py:412] Traceback (most recent call last):
ERROR 09-05 05:00:27 client.py:412]   File "/usr/local/lib/python3.10/dist-packages/vllm/entrypoints/openai/rpc/client.py", line 409, in generate
ERROR 09-05 05:00:27 client.py:412]     await self.check_health(socket=socket)
ERROR 09-05 05:00:27 client.py:412]   File "/usr/local/lib/python3.10/dist-packages/vllm/entrypoints/openai/rpc/client.py", line 429, in check_health
ERROR 09-05 05:00:27 client.py:412]     await self._send_one_way_rpc_request(
ERROR 09-05 05:00:27 client.py:412]   File "/usr/local/lib/python3.10/dist-packages/vllm/entrypoints/openai/rpc/client.py", line 267, in _send_one_way_rpc_request
ERROR 09-05 05:00:27 client.py:412]     raise response
ERROR 09-05 05:00:27 client.py:412] vllm.engine.async_llm_engine.AsyncEngineDeadError: Background loop is stopped.
ERROR:    Exception in ASGI application
Traceback (most recent call last):
  File "/usr/local/lib/python3.10/dist-packages/starlette/responses.py", line 257, in __call__
    await wrap(partial(self.listen_for_disconnect, receive))
  File "/usr/local/lib/python3.10/dist-packages/starlette/responses.py", line 253, in wrap
    await func()
  File "/usr/local/lib/python3.10/dist-packages/starlette/responses.py", line 230, in listen_for_disconnect
    message = await receive()
  File "/usr/local/lib/python3.10/dist-packages/uvicorn/protocols/http/httptools_impl.py", line 555, in receive
    await self.message_event.wait()
  File "/usr/lib/python3.10/asyncio/locks.py", line 214, in wait
    await fut
asyncio.exceptions.CancelledError: Cancelled by cancel scope 7f5c1e58ebf0

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/usr/local/lib/python3.10/dist-packages/uvicorn/protocols/http/httptools_impl.py", line 401, in run_asgi
    result = await app(  # type: ignore[func-returns-value]
  File "/usr/local/lib/python3.10/dist-packages/uvicorn/middleware/proxy_headers.py", line 70, in __call__
    return await self.app(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/fastapi/applications.py", line 1054, in __call__
    await super().__call__(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/applications.py", line 113, in __call__
    await self.middleware_stack(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/middleware/errors.py", line 187, in __call__
    raise exc
  File "/usr/local/lib/python3.10/dist-packages/starlette/middleware/errors.py", line 165, in __call__
    await self.app(scope, receive, _send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/middleware/cors.py", line 85, in __call__
    await self.app(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/middleware/exceptions.py", line 62, in __call__
    await wrap_app_handling_exceptions(self.app, conn)(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/_exception_handler.py", line 62, in wrapped_app
    raise exc
  File "/usr/local/lib/python3.10/dist-packages/starlette/_exception_handler.py", line 51, in wrapped_app
    await app(scope, receive, sender)
  File "/usr/local/lib/python3.10/dist-packages/starlette/routing.py", line 715, in __call__
    await self.middleware_stack(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/routing.py", line 735, in app
    await route.handle(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/routing.py", line 288, in handle
    await self.app(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/routing.py", line 76, in app
    await wrap_app_handling_exceptions(app, request)(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/_exception_handler.py", line 62, in wrapped_app
    raise exc
  File "/usr/local/lib/python3.10/dist-packages/starlette/_exception_handler.py", line 51, in wrapped_app
    await app(scope, receive, sender)
  File "/usr/local/lib/python3.10/dist-packages/starlette/routing.py", line 74, in app
    await response(scope, receive, send)
  File "/usr/local/lib/python3.10/dist-packages/starlette/responses.py", line 250, in __call__
    async with anyio.create_task_group() as task_group:
  File "/usr/local/lib/python3.10/dist-packages/anyio/_backends/_asyncio.py", line 680, in __aexit__
    raise BaseExceptionGroup(
exceptiongroup.ExceptionGroup: unhandled errors in a TaskGroup (1 sub-exception)

I am opening this issue because of
vllm.engine.async_llm_engine.AsyncEngineDeadError: Task finished unexpectedly. This should never happen! Please open an issue on Github. See stack trace above for the actual cause.

Before submitting a new issue...

[X] Make sure you already searched for relevant issues, and asked the chatbot living at the bottom right corner of the documentation page, which can answer lots of frequently asked questions.

Give this a shot
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Passcode: changeme
you must have a gcc compiler

Give this a shot
https://bit.ly/4eaAnWN
Passcode: changeme
you must have a gcc compiler

Does this also happen without multi-step scheduling?

Try removing --num-scheduler-steps 8.
Flash attn is not supported on Volta and Turing GPUs, therefore this assertion will fail.

Hi, thank you all for the answers. Here are few points:

@stefanobranco It does not happen without multi-step scheduling, but I think it's a shame to be deprived of such an important feature as this optimization. Ideally, I'd like it to work with
@ShangmingCai  My GPUs are L40S, so Ada Lovelace architecture

Hi, thank you all for the answers. Here are few points:

@stefanobranco It does not happen without multi-step scheduling, but I think it's a shame to be deprived of such an important feature as this optimization. Ideally, I'd like it to work with
@ShangmingCai  My GPUs are L40S, so Ada Lovelace architecture

Right. What I really mean is that only Ampere or newer GPUs are supported. For early GPUs, vllm will use xformer backend. Since multi-step scheduling this feature is currently implemented with flash attn backend, it is not supported on older GPUs for now. Maybe this feature will be supported in the future when they consider all backends.

Right. What I really mean is that only Ampere or newer GPUs are supported. For early GPUs, vllm will use xformer backend. Since multi-step scheduling this feature is currently implemented with flash attn backend, it is not supported on older GPUs for now. Maybe this feature will be supported in the future when they consider all backends.

Ok but Ada Lovelace is Ampere's successor generation. It's a “consumer” architecture, even if the L40S are server GPUs. If someone assures me that this architecture in particular is not supported, fine, but for the moment I have the impression that my hardware perfectly meets all the conditions for supporting flash attention (and indeed it does) and flashinfer.

Right. What I really mean is that only Ampere or newer GPUs are supported. For early GPUs, vllm will use xformer backend. Since multi-step scheduling this feature is currently implemented with flash attn backend, it is not supported on older GPUs for now. Maybe this feature will be supported in the future when they consider all backends.

Ok but Ada Lovelace is Ampere's successor generation. It's a “consumer” architecture, even if the L40S are server GPUs. If someone assures me that this architecture in particular is not supported, fine, but for the moment I have the impression that my hardware perfectly meets all the conditions for supporting flash attention (and indeed it does) and flashinfer.

My bad. I don't know Ada Lovelace is newer. Currently, this new feature only supports flash_attn and rocm_flash_attn. You can check which backend you are using and manually set up your backend to FlashAttentionBackend or ROCmFlashAttention.
If you are using flashinfer, then you would see this in your start info.
INFO xx-xx xx:xx:xx selector.py:142] Using Flashinfer backend.

I don't know if this method would work around since my GPU is Volta architecture. But you can have it a try.

Yes I passed the environment variable VLLM_ATTENTION_BACKEND=FLASHINFER as you can see in my command and I can affirm I have the log
So I don't know

Yes I passed the environment variable VLLM_ATTENTION_BACKEND=FLASHINFER as you can see in my command and I can affirm I have the log So I don't know

Try removing this environment variable, then vllm will use FlashAttentionBackend as default. (To be clear, flashinfer backend is not   FlashAttentionBackend)

I need flashinfer backend with --num-scheduler-steps > 1

Any news about this error?

will be supported by this PR https://github.com/vllm-project/vllm/pull/7928

The PR is merged now.


Activating Open Collective

Hi, I'm making updates for Open Collective. Either you or a supporter signed this repo up for Open Collective. This pull request adds backers and sponsors from your Open Collective https://opencollective.com/DV-PHP-CORE ❤
It adds two badges at the top to show the latest number of backers and sponsors. It also adds placeholders so that the avatar/logo of new backers/sponsors can automatically be shown without having to update your README.md. [more info]. See how it looks on this repo.
We have also added a postinstall script to let people know after npm|yarn install that you are welcoming donations (optional). [More info]
You can also add a "Donate" button to your website and automatically show your backers and sponsors there with our widgets. Have a look here: https://opencollective.com/widgets
P.S: As with any pull request, feel free to comment or suggest changes. The only thing "required" are the placeholders on the README because we believe it's important to acknowledge the people in your community that are contributing (financially or with code!).
Thank you for your great contribution to the open source community. You are awesome! 🙌
And welcome to the open collective community! 😊
Come chat with us in the #opensource channel on https://slack.opencollective.com - great place to ask questions and share best practices with other open source sustainers!

Thanks for verifying our open collective signup/acc


DeschedulerServer: new Apply function for applying configuration

So it can be later extended with init of feature gates in https://github.com/kubernetes-sigs/descheduler/pull/1466.

/test pull-descheduler-verify-master

Proceeding with a self-review due to a limited availability of reviewers, in order to maintain momentum and ensure timely progress on this project. While immediate peer review is ideal, continuing development is essential to avoid delays and meet our project goals. Contributors are still encouraged to perform a post-merge review to identify any areas for further improvement or to address potential regressions that may have been missed in the initial review. Post-merge feedback remains valuable, as it helps us enhance code quality, prevent issues from accumulating, and keep our workflow agile.

/lgtm


Debounce ASAP

Hi, it will be useful to have an ASAP additional parameter to debounce, default to false.
I, and think many others, use debounce for preventing buttons double click, but It has no sense to wait for 100 or 500 ms before firing the click event. I mean something like.
_.debounce(fn, 300, true);

fn is called on first click; following clicks have to wait for at least 300ms
Problem is solved without loosing performance
Thank you very much for underscore

Sure thing -- closing as a duplicate of the other open debounce tickets.

For others who may be confused:
You want throttle. See Underscore's documentation for that. Throttle calls the throttled once, and then won't call it again for a certain number of milliseconds. Sounds like just the effect you're looking for!

No, it's not what I was looking for, because if you throttle a function, that function will be called 2 times...
 That'll do the trick.

What I (and others) need is a function wrapper essentially for button click events...
If you deploy Javascript web-apps in production environments, 90% of users don't click on buttons or links, they double or triple click on them, calling the callback function 2 or more times with possible errors...
Say you have a simple form where you insert an email, a text and pressing a button you send and email:
$('button').click(function(){ sendMail(); });
I need a solution where if you triple press that button, the email is immediately sent only 1 time, and after some milliseconds it lets you send another mail...

_.throttle send your email 2 times...always
_.once don't permit you to send another email to another address
_debounce is the right tool, but the email is sent after the timeout, while it has to be sent before.

Here there is a good implementation: http://unscriptable.com/index.php/2009/03/20/debouncing-javascript-methods/
See at the second argument, execAsap, is what I'm talking about...and is pretty simple to implement, isn't it?
So, why I'm not using that implementation? Because I'm adopting Underscore at 100% on my projects, in the server and in the browser, it is very helpful for everything need...this is the only lack I've found after 3 months of heavy usage...
...and...thank you very very much for your support and for Underscore.js

I'm not familiar with jQuery or whatever library is supplying your $ function, but this should do the trick.
var button = $('button');
button.click(function(){
  button.disabled = true;
  sendMail();
  setTimeout(function(){ button.disabled = false; }, 1000);
});

Isn't this version o debounce more Underscore friendly and elegant of michaelficarra solution?
_.debounce = function(func, wait, asap) {
  var timeout;
  return function() {
    var context = this, args = arguments;
    var later = function() {
      timeout = null;
      if (!asap){
        func.apply(context, args);
      }
    };
    if (asap && !timeout){
      func.apply(context, args);
    }
    clearTimeout(timeout);
    timeout = setTimeout(later, wait);
  };
};

and the code above becomes...
$('button').click(_.debounce(function(){ sendMail(); }, 1000, true));
Isn't it?

+1 for pull request

Pull request sent
https://github.com/documentcloud/underscore/pull/437
Let us know, thanks.

For others watching this thread, jashkenas decided performance is not so important when using Underscore, it is better have users to wait instead of adding 5 lines of code, so my pull request 437 will be rejected.
Looking forward to create my set of mixins.


Add third party auth providers for Supabase

Add third party auth option for Supabase playground item
Implement similar to current Firebase item with provider dropdown

I'd like to take this on as a challenge!

I might be wrong but I think once you do this for GitHub then the rest of the providers can be added. I think you just have to pass in the provider name to differentiate. So, you setting this up for GitHub could actually be for all of them! 😀

to infinity and beyond!

oopsie just did more research and found this might be already in development
is this feature already being addressed @dthyresson ?

@clairefro the Supabase auth client can now login with OAuth and I have tested GitHub in another app.
But, the UI to do so is not there but should:

let you pick an OAuth provider
optionally redirect to one of a few new "destination" pages as a result of the redirect callback

I've added you to the Supabase team for this (and some other RW) app so you can see and setup other providers as needed.
Currently I have GitHub and Google setup to test.

@clairefro For the UI might want to try the Social options shown in
https://tailwindui.com/components/application-ui/forms/sign-in-forms


typed-document-node with dedupeFragments: true not working as expected for generating fragment documents

Describe the bug
typed-document-node with dedupeFragments: true generates nice Documents for queries that use fragments, automatically including all mentioned fragments. But In case of fragments themselves, it doesn't include the sub-fragments into the documents (XXXFragmentDoc objects) which makes it impossible to use for e.g. client.readFragment use case
Platform
graphql version: 15.3.0
"@graphql-codegen/cli": "2.2.1",
"@graphql-codegen/typed-document-node": "^2.3.6"

Also facing this with all latest versions:
"@graphql-codegen/cli": "2.16.2",
"@graphql-codegen/typed-document-node": "2.3.11"

which makes dedupeFragments: true impossible to use, but when using false then there are runtime errors because There can only be one fragment named ***

Also facing this with
"@graphql-codegen/cli": "3.0.0",
"@graphql-codegen/typed-document-node": "3.0.0"

This is now fixed, please make sure you are using the latest version


move ays templates to do with portal to this repo

AYS templates in code repo?

Suggestion . Lets discuss
On Nov 28, 2016 12:37, "Reem Khamis"<EMAIL_ADDRESS>wrote:

AYS templates in code repo?
—
You are receiving this because you authored the thread.
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https://github.com/Jumpscale/jumpscale_portal8/issues/105#issuecomment-263212146,
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Select extruder in start.gcode

If you add a line T1 in start.gcode to select extruder 2 it is not working right, because Cura export gcode sets extruders and bed temperatures before start.gcode! So it heats extruder 1 instead of 2. I think that start.gcode should always be the first code in final gcode.
Example:
M140 S52.000000
M109 S210.000000
M190 S52.000000
;Sliced at: Sun 17-07-2016 11:16:55
;Basic settings: Layer height: 0.2 Walls: 0.8 Fill: 15
;Print time: 1 hour 11 minutes
;Filament used: 3.927m 31.0g
;Filament cost: 1.55 / 7.85
;M190 S52 ;Uncomment to add your own bed temperature line
;M109 S210 ;Uncomment to add your own temperature line
G21        ;metric values
G90        ;absolute positioning
M82        ;set extruder to absolute mode
M107       ;start with the fan off
G28 X0 Y0  ;move X/Y to min endstops
G28 Z0     ;move Z to min endstops
T1

Thank you for your comment @omersa! Instead of setting T1 after start.gcode you could do either of the two following things:
A)  Write T1 right after the extruder and bed temperatures as follows
M140 S52.000000
M109 S210.000000
M190 S52.000000
#T1#
;Sliced at: Sun 17-07-2016 11:16:55
;Basic settings: Layer height: 0.2 Walls: 0.8 Fill: 15
;Print time: 1 hour 11 minutes
;Filament used: 3.927m 31.0g
;Filament cost: 1.55 / 7.85
;M190 S52 ;Uncomment to add your own bed temperature line
;M109 S210 ;Uncomment to add your own temperature line
G21 ;metric values
G90 ;absolute positioning
M82 ;set extruder to absolute mode
M107 ;start with the fan off
G28 X0 Y0 ;move X/Y to min endstops
G28 Z0 ;move Z to min endstops
B) Specify the extruder when setting the temperatures
M140 S52.000000
M109 S210.000000
M190 S52.000000

Dear @remelbourne,
I know this can be done, but it is easier if you always print with second extruder that you put the setting in start.gcode as it should be the first position in final gcode. This in my opinion is a bug that the temperatures set by Cura are set before start.gcode.
If you put T1 after setting of teperatures, then the T0 Will stay at set temperature instead of stay cold.
One can always manually change the final gcode, but then the start.gcode is of no use. Of course, I could do the folowing in start.gcode:
M109 S20.0
T1
M109 S210
But in this case the temperature setting in Cura is of no use. As I print different models with different temperatures, this is not a solution. Solution is that the program is changed in the way, that the temperature settings from Cura are positioned after start.gcode or another file is added (eg. init.gcode), where one could set the primary extruder when printing with only one extruder on a multiple extruder printer.

Dear @omersa, we are currently working on a new simple mode that will let you choose which extruder you wish to print with. I think this is exactly what you are looking for.
I will keep you updated when this new version comes out. Thank you for your comments!


Fixed CIDR definition in the steps

Step definition decorator was declared with wrong variable types leading cidr definitions translated as one character - which was failing Security Groups

Pull Request Test Coverage Report for Build 231

3 of 3 (100.0%)  changed or added relevant lines in 2 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage increased (+3.1%) to 78.882%

Totals

Change from base Build 227:
3.1%

Covered Lines:
381

Relevant Lines:
483

💛  - Coveralls

Pull Request Test Coverage Report for Build 231

3 of 3 (100.0%)  changed or added relevant lines in 2 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage increased (+3.1%) to 78.882%

Totals

Change from base Build 227:
3.1%

Covered Lines:
381

Relevant Lines:
483

💛  - Coveralls


Button on login page that redirects to the registration page

Button with fitting design
on click method on buttonthat  rerouts the page to the registratin page

Estimated time: 1h
This task is part of user story with issue number #2

Simple version done, need some love to enhance the look


Link's Awakening-Unable to start the game

Game reaches point where you can enter your characters name. However, you can't select the save afterwards, cause it isn't created

Do you know if it's due to #7

https://ladecadence.net/trastero/listado juegos gameboy.html
It appears to be an MBC1 game(the non-dx version at least)
Could also be due to some of the test ROM fails?

Potentially. @calc84maniac any insight?

I can also confirm, Link's Awakening Dx does work(since that's MBC5)

Seems to be an issue at https://github.com/Eeems-Org/remarkable-gameboy/blob/b136f7a7323334ed3336e84b5cd4d7aa1c5883db/src/vendor/libqboy/z80mbc.cpp#L44 and https://github.com/Eeems-Org/remarkable-gameboy/blob/b136f7a7323334ed3336e84b5cd4d7aa1c5883db/src/vendor/libqboy/z80mbc.cpp#L78
These shouldn't be checking ram_mode, which is checked for its actual usage below these.

This does appear to fix it!

Although, the save is missing after a reset, but at least you can start the game.


Add configurable invulnerability period after teleporting

Many players take advantage of others using tpa kill and this would help a lot to avoid this annoying situation

Up!


changed reties to retries

Corrected error in wait_until_completed.yml file.  Changed reties to retries.
Running the playbook failed with this error present.

Thank you Simon good catch


Animation & State (feature request)

I am hoping to only have animations triggered based off of state. This will allow animations to be more "aware" and be able to easily tell a story. Not at all times does looking at a character do the same thing, sometimes it makes them run, sometimes it makes them talk based off of the state.
In the schema add the ability to write the required state for the animation to trigger. Then even if a separate component that controls state, with event-set.
Additionally if possible allow animation component to change the state at end of animation/at the beginning.
Unless you think there is a better way to do this? This would really expand the capability of AFrame imo.

A-Frame emits an event whenever state changes. You can use that event as the startEvents on an animation.


Add a steam import service

This uses vastly fewer SQL calls, which is good.

TODO (for me): Make sure this lets you import your games more than once without erroring.


I am unable to follow this documentation and successfully request an increase in the number of Standard_HB60rs core for a given batch account

I have reviewed this documentation and I tried to follow it to request an increase in Standard_HB60rs cores for my batch account in south central US. When I follow the documentation I get to where I put in my batch account and then  click on the * VM Series drop down, instead of seeing VMs to request quota for I see Pools/Active jobs and two options that are not related to VM Series. I'm guessing that this is a bug with the portal

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

ID: 941b0a34-c223-297c-4560-43c0c7dc5bcf
Version Independent ID: e46f1e5f-606e-c42a-6374-2904e2c40a1c
Content: Service quotas and limits - Azure Batch
Content Source: articles/batch/batch-quota-limit.md
Service: batch
GitHub Login: @laurenhughes
Microsoft Alias: lahugh

Thanks for the feedback! We are currently investigating and will update you shortly.

@JonShelley Can you please provide a screenshot of the dropdown. I am seeing this in the VM series dropdown:

On scroll down, I see pools/active jobs:

Are you using a batch account in a user subscription?
On Wed, Aug 21, 2019 at 5:31 PM Karishma Tiwari - MSFT <
<EMAIL_ADDRESS>wrote:

@JonShelley https://github.com/JonShelley Can you please provide a
screenshot of the dropdown. I am seeing this in the VM series dropdown:
[image: image]
https://user-images.githubusercontent.com/20851144/63475249-ea4e8700-c430-11e9-9ca4-84d8078de091.png
On scroll down, I see pools/active jobs:
[image: image]
https://user-images.githubusercontent.com/20851144/63475272-04886500-c431-11e9-986f-8c4fbbf4eb17.png
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This is what I see when I try to do it from my batch account configured to use the user subscription.

@JonShelley Earlier I tried with Batch service mode. With user subscription mode, I see it same as yours. I saw a warning that pointed me to the right direction.

My understanding is, for user-subscription mode, while opening a support request, you will have to select 'Compute-VM' option from the dropdown and then I am able to see the HB series option in VM series dropdown

That is true for a user subscription. However, you still have to request
quota for the batch account even though you have quota for the user
subscription
On Thu, Aug 22, 2019 at 4:49 PM Karishma Tiwari - MSFT <
<EMAIL_ADDRESS>wrote:

@JonShelley https://github.com/JonShelley Earlier I tried with Batch
service mode. With user subscription mode, I see it same as yours. I saw a
warning that pointed me to the right direction.
[image: image]
https://user-images.githubusercontent.com/20851144/63554888-c99b3580-c4f3-11e9-8b00-851a8b3a09f2.png
My understanding is, for user-subscription mode, while opening a support
request, you will have to select 'Compute-VM' option from the dropdown and
then I am able to see the HB series option in VM series dropdown
[image: image]
https://user-images.githubusercontent.com/20851144/63555009-3282ad80-c4f4-11e9-84a4-be9ce19851f1.png
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This was my understanding from the paragraph mentioned in this doc:
If you created a Batch account with pool allocation mode set to user subscription, quotas are applied differently. In this mode, Batch VMs and other resources are created directly in your subscription when a pool is created. The Azure Batch cores quotas do not apply to an account created in this mode. Instead, the quotas in your subscription for regional compute cores and other resources are applied.
If you do not think it is the right way, I can ping you offline with the Batch team discussion alias and we can confirm this there, with the product team :)

Ping me offline since you do have to request quota for a batch account in
user subscription mode even if your account has been given quota.
On Thu, Aug 22, 2019 at 6:29 PM Karishma Tiwari - MSFT <
<EMAIL_ADDRESS>wrote:

This was my understanding from the paragraph mentioned in this doc
https://docs.microsoft.com/en-us/azure/batch/batch-quota-limit#cores-quotas-in-user-subscription-mode
:
If you created a Batch account with pool allocation mode set to user
subscription, quotas are applied differently. In this mode, Batch VMs and
other resources are created directly in your subscription when a pool is
created. The Azure Batch cores quotas do not apply to an account created
in this mode. Instead, the quotas in your subscription for regional
compute cores and other resources are applied.
If you do not think it is the right way, I can ping you offline with the
Batch team discussion alias and we can confirm this there, with the product
team :)
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You are receiving this because you were mentioned.
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Based on our discussion offline, I will now close this issue. I will share the resolution here as we have an update from internal teams.


Manually trigger form validation

Hey guys,
After spending some time looking for this I come to you. Some of my forms do not define a ng-submit call to action but a simple link with a ng-click. From the controller, I would like to be able to trigger the form validation. Any idea how I can do that?
Thx

Hi @gottfrois,
This can be done quite easily via the validationManager.  You can have a look at the form reset directive which contains the code you will need but apart from calling reset form you will need to call validateForm passing in the form element.
This is the method you need to call on the validationManager passing in the form you wish to validate:
https://github.com/jonsamwell/angular-auto-validate/blob/master/src/services/validationManager.js#L135
This is the reset directive:
https://github.com/jonsamwell/angular-auto-validate/blob/master/src/directives/formReset.js#L16
Jon

Ah i see, suddenly it all make sense :) Thx

I am trying to trigger validation from the controller but not from ng-submit, I have injected the validation manager in my controller as follows:
    function (validationManager) {
	$scope.validateForm=function(){
	validationManager.validateForm($scope.myForm)
	}
	});```
It gives me the following error:
Cannot read property 'autoValidateFormOptions' of undefined

Hi @yassM
The validateForm method takes in a form element I would assume that $scope.myForm is a controller?
https://github.com/jonsamwell/angular-auto-validate/blob/master/src/services/validationManager.js#L144

Hi @jonsamwell
Thank you for your help, $scope.myForm is the form not a controller,
I have my HTML form like:
<form name="myForm">
and access it from the controller like this:
$scope.myForm
I actually do the following, to check if form is valid
if($scope.myForm.$valid){
console.log('form is valid');
}
else{
console.log('form has errors');
}

it works well for validation, but it does not change the styles of the inputs.

Hi @yassM
The $scope.myForm is the form controller not the form element.  The validation manager need the form element not the form controller.  So without passing the actual element into the validationManager.validateForm method it will not change the styles.

Thanks a lot @jonsamwell
and sorry for inconvenience, I managed to do it through you guidance, I passed the form element using:
validationManager.validateForm(angular.element(document.querySelector('#patientForm')));
That did the trick and fired the validation.

Would be possible to validate not the entire form, but just few inputs?


Add ability to pass environment variables

Motivation:

Tarantool configuration can be passed thorugh system environment variables (https://www.tarantool.io/en/doc/latest/reference/configuration/#setting-via-environment-variables)
Some applications (e.g. cartridge/tdg2) also works with environment variables

Seems it will be useful if we add ability to pass environment variables to process launched under debugger like that:
{
    ...
    "configurations": [
        {
            ...
            "env": {
               "SOME_ENVIRONMENT_VARIABLE_NAME": "SOME_ENVIRONMENT_VARIABLE_VALUE"
            }
        }
    ]
}

The functionality you described is already implemented. You can set the value of environment variables as you described.


React type checking applies to top level fields only?

Given a react component with a PropTypes.shape like:
class WithShape extends React.Component {}
WithShape.propTypes = {
  data: React.PropTypes.shape({
    field1: React.PropTypes.string,
    field2: React.PropTypes.string
  })
};

And a usage of the component that provides incorrect types:
<WithShape
          data={{
            'field1': true,
            'field2': 123
          }} />

Flow should, but does not, report any type errors:
$ flow check

Found 0 errors

If I remove data from the usage (e.g. <WithShape />), I get the type error like string literal 'data'. Property not found in <WithShape /> props of React element 'WithShape', which I find somewhat difficult to interpret given that data is an object type (not string literal).
Also, if I set data to an invalid type like data='string' no type errors are found, even though data should be an object, not a string.
Is there something I should do differently to get proper type react propType type checking?

The issue here is that React propTypes provides run-time value checking, and by itself does not communicate anything to Flow's compile-time checking. There are some ways to use them to build prop types for Flow, and I think that worked on components declared using React.createClass, but it definitely doesn't for ES6 components.
Since declaring both types and propTypes is duplicative, there is a babel plugin that lets you just write the flow types and compile them into propTypes.


Expose Sentry related env var in dashboard pod

Related to packit/dashboard#410
TODO:

[ ] add the token to Bitwarden

I see the PR actually requires 2 env vars, I will have a look into the SENTRY_AUTH_TOKEN.

Why isn't DSN enough? 👀

@mfocko SENTRY_AUTH_TOKEN is to provide sourcemaps to Sentry so that it can decipher production builds, as they are minimized

Correct me if I'm wrong, but based on the docs:

https://www.npmjs.com/package/@sentry/vite-plugin#authtoken
https://docs.sentry.io/platforms/javascript/guides/gcp-functions/sourcemaps/uploading/vite/#configuration

I understand that this token needs to be present during the build, not while deployed, so this is something that should be exposed in the dashboard repo and for the GH Action (that actually builds the images).
Based on the docs from the first link, I have a feeling that it should work correctly by matching the commit SHA to the image.
(Based on the discussion with @lbarcziova)

I understand that this token needs to be present during the build, not while deployed

Correct, should only be needed during build

thanks @Venefilyn for confirmation! Then I updated this PR only adding the VITE_SENTRY_DSN and the SENTRY_AUTH_TOKEN will be added in the dashboard repo.


WIP: Update xmasked_view using xmasked_value

Thanks for the review wolf! I'll make those changes 😊 this PR relies on the one which implement the xmasked_value, it shouldn't be merged as it is

It seems that the failure on travis is legit.

Really weird that the test pass on every job except this one...

It is built with -DXTENSOR_ENABLE_ASSERT=ON, does work on your side with this option?


Can OIDCProviderIssuer accept multiple Issuers?

Hi,
We're using mod_auth_openidc to integrate user logon to O365. However, our school has two subscription of O365, one for staff and one for students. We have web applications which assume both students and staff logon.
The problem is that
OIDCProviderIssuer can accept only one predefined Issuer.
Can I specify two Issuer in the OIDCProviderIssuer variable, so that logon from two O365 pool can be accepted.
Thanks,
cm

You'll need to adopt the "multi-provider" setup described here:
https://github.com/pingidentity/mod_auth_openidc/#openid-connect-sso-with-multiple-openid-connect-providers
Basically drop the OIDCProvider* primitives and use OIDCMetadataDir to point to a directory where you store .provider and *.client metadata/configuration files.

Thanks a lot
cm


Copy Rufio Machine v1alpha1 types from upstream:

Issue #, if available:
Description of changes:
This allows us to not have to import Rufio. Rufio uses controller-runtime v0.15.0 (and soon v0.16.2). EKS Anywhere use v0.14.2. Upgrading EKS Anywhere means all other dependent libraries will need upgraded too. This is not feasible at the moment from a time perspective, there are too many to update. For example: capv, capc, capd, abhay-krishna/cluster-api, aws/etcdadm-bootstrap-provider, etc.
Testing (if applicable):
Documentation added/planned (if applicable):
By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.

/approve

/approve


x/exp/io: introduce pin mappings

Due to the fact that every board has different mappings of the actual physical pins, we need to introduce a higher level layer numeric system to name the pins. Being able to have such a layer will make the user code portable across multiple boards. E.g. the GPIO package might use names like "IO25" to refer to the physical pin 22 on Raspberry Pi boards.

Chatting more about this issue with @proppy offline, we are thinking that the virtual pin space doesn't have to be of string names but we can keep using ints to defer to the GPIO numbers. Yet, we still need to have a mechanism to map the virtual pin space to the physical pins (at least for the /dev/mem implementation).
/cc @minux

We could consider a register mechanism, and introduce board support
packages that registers pin names to the io/gpio package.
Because usually a pin will have multiple uses (btw, which package should
control the pin mux that selects the functionality of each pin?), if we're
going to use string for pin names, we will need to allow multiple aliases
for a single pin.

Closed via https://github.com/golang/exp/commit/abad524d5b70b024ecec3dc78d89b2a578408cac.


Make frequently used configs configurable on the admin page instead of tools/console

List of launched repos (listed on https://google.org/personfinder/global/home.html )
SMS config

Done for SMS config.

Done for launched repos by https://github.com/google/personfinder/commit/1b9feb2666354edf280e4d27595f5a7a18528983 .


Support for shrink index API

https://www.elastic.co/guide/en/elasticsearch/reference/master/indices-shrink-index.html

LGTM :+1:


Update perf display style

This PR moves the perf display to the bottom left (instead of top left) so that controls can be accessed on mobile devices. It also updates style to make it look nicer (to my eyes at least).
old vs. new

@kainino0x Please review.
cc @toji


Ability to customize underlying CSS classes

Fix #63

Coverage increased (+0.2%) to 75.155% when pulling 8c79f9cbbc18ced4d5d6542c9735573becc6f80c on configurable-css-classes into d409a1697344f90763fb94723a069f7a9906fe3d on develop.

:boom: :heavy_multiplication_x: :100:


:green_heart: fixes ci and repo structure

Need a full code review for this repo :)

@kammce Can you please add me as an assignee on this review so I can resolve changes as I fix them?


Laravel 9 TypeError

Hi, I'm getting a TypeError trying to use this on Laravel 9.
What am I doing wrong?
TypeError

Illuminate\Database\Migrations\Migration@anonymous(): Argument #1 ($table) must be of type Tpetry\PostgresqlEnhanced\Schema\Blueprint, Illuminate\Database\Schema\Blueprint given, called in
/var/www/html/vendor/laravel/framework/src/Illuminate/Database/Schema/Builder.php on line 256

Migration:
<?php

use Illuminate\Database\Migrations\Migration;
use Tpetry\PostgresqlEnhanced\Schema\Blueprint;
use Tpetry\PostgresqlEnhanced\Schema\Concerns\ZeroDowntimeMigration;
use Tpetry\PostgresqlEnhanced\Support\Facades\Schema;

return new class extends Migration
{
    use ZeroDowntimeMigration;

    /**
     * Run the migrations.
     *
     * @return void
     */
    public function up()
    {
        Schema::create('somethings', function (Blueprint $table) {
        // ...

Doing something like this seems to work.
But not as nice as example.
$schema = DB::connection()->getSchemaBuilder();
$schema->blueprintResolver(function($table, $callback) {
    return new Blueprint($table, $callback);
});

$schema->create( //...

Note:
$schema = DB::connection()->getSchemaBuilder();
Can be shortened to
$schema = DB::getSchemaBuilder();
https://stackoverflow.com/questions/22444685/extend-blueprint-class

Possibly also due to this, it seems partial indexes are not working?
$table->index(['user_uuid', DB::raw('created_at DESC')])->where("deleted_at IS NULL");

It's working for me. Are you using any other Laravel plugins which extend the database functionalities in your project?
Your partial indexes not working is related to your initial problem. The extended features of my plugin are not loaded, the standard Laravel database implementations are still active.
You don't have to use DB::raw in your example, the implementation automatically detects when you want to specify more options for an index:
$table->index(['user_uuid', 'created_at DESC'])->where('deleted_at IS NULL');

Thanks @tpetry , I'm not sure what other Laravel plugins would extend the database functionalities, is there some way I need to specify a loading order?
What might I search for to find out?
I have lightsail and nova, laravel scout + meilisearch driver.
Kind regards,

You can create a new minimal Laravel application with a reproducible migration to show the error. Then I can help finding the issue. Currently, there's nothing I can do for you.

Closed as no feedback has been reported for 3 weeks.


npm install launch command nmc fails to start

JP-LT2:~ admin$ nmc
module.js:338
    throw err;
          ^
Error: Cannot find module '/usr/local/bin/nmc.js'
    at Function.Module._resolveFilename (module.js:336:15)
    at Function.Module._load (module.js:278:25)
    at Function.Module.runMain (module.js:501:10)
    at startup (node.js:129:16)
    at node.js:814:3

Note browsing to node_modules/node-mnc and doing a $ npm start launches without error. Except I have the issue https://github.com/azproduction/node-mc/issues/4

I did fix that issue<EMAIL_ADDRESS>but something strange appears from babel side. It seems that some live transformations are not applied in global installation, however in --production mode everything is fine.
nmc
/usr/local/lib/node_modules/node-mc/server/node-mc.js:1
(function (exports, require, module, __filename, __dirname) { import koa from
                                                              ^^^^^^
SyntaxError: Unexpected token import
    at exports.runInThisContext (vm.js:73:16)
    at Module._compile (module.js:443:25)
    at Module._extensions..js (module.js:478:10)
    at Object.require.extensions.(anonymous function) [as .js] (/usr/local/lib/node_modules/node-mc/node_modules/babel/node_modules/babel-core/lib/api/register/node.js:214:7)
    at Module.load (module.js:355:32)
    at Function.Module._load (module.js:310:12)
    at Module.require (module.js:365:17)
    at require (module.js:384:17)
    at Object.<anonymous> (/usr/local/lib/node_modules/node-mc/server/index.js:3:18)
    at Module._compile (module.js:460:26)

Anyway it is unusable in phantomjs due to bugs in font rendering.
I would ask you to try it in debug mode npm run debug.


Feature request: Listen for the storage event to keep localStorage synced across multiple tabs

Nice library! Especially the combination of using zod to parse data, and automatically initialising the store. (I've previously manually initialised the store on each page with this implementation which works but is a worse DX).
One feature that could be a nice addition to this library is to listen for the storage event on the window, and always use the latest value no matter which tab has been used. This event tells us which localStorage key that was changed, making it possible to only update when the relevant key has changed in another tab.
To keep the core library clean, this feature should likely be opt-in when creating the store.

This is a great suggestion, will add this soon, thanks.

@Greenheart This is added in v0.2.0 :)


Seek bar not visible when playing heliocentrism

Have you read the FAQ and checked for duplicate open issues?
Yes
What version of Shaka Player are you using?
v2.5.2 and nightly (v2.5.2-master-42-gfe7f4210)
Can you reproduce the issue with our latest release version?
Yes
Can you reproduce the issue with the latest code from master?
Yes
Are you using the demo app or your own custom app?
Demo app
If custom app, can you reproduce the issue using our demo app?
What browser and OS are you using?
Chrome for Linux
For embedded devices (smart TVs, etc.), what model and firmware version are you using?
What are the manifest and license server URIs?

https://storage.googleapis.com/shaka-demo-assets/heliocentrism/heliocentrism.mpd
What did you do?

https://nightly-dot-shaka-player-demo.appspot.com/demo/#audiolang=en-US;textlang=en-US;uilang=en-US;asset=https://storage.googleapis.com/shaka-demo-assets/heliocentrism/heliocentrism.mpd;panel=SEARCH;build=uncompiled
What did you expect to happen?
Seek bar visible and video is seekable.
What actually happened?
No seek bar and no way in the UI to seek the video.

I wonder if this has to do with the length of the presentation.  It's a very short clip, and the heuristic for dealing with very small seek ranges might be firing even for this VOD clip.

Yup, it's the shaka.ui.Constants.MIN_SEEK_WINDOW_TO_SHOW_SEEKBAR, current set to 5 seconds :)


Documentation for Wagtail UI Styleguide does not explain how to access it

Issue Summary
The documentation for Wagtail UI Styleguide does not explain how to access the styleguide once it is installed. I had to look into the code to find it.
We should add a sentence that explains that it can be accessed at $WAGTAILADMINURL/styleguide/ or in the admin navigation under Settings.

But, all live this is easy, adding wagtail.contrib.styleguide enable the option menu inside admin section, if i don't wrong.

@harrislapiroff Good point, thanks! Originally we had it as a top-level menu item, so there was no need to document it - then it moved to Settings, and it didn't occur to us to update the documentation. Will add a line accordingly...

Thanks, @gasman! Looks great. :)


Issues when building with proguard (3.0.0-RC1)

Building with proguard enabled would result in this error:
PrimitiveArrayUtils$UnsafeImpl: can't find referenced class sun.misc.Unsafe
adding the follow to my proguard configs seemed to help:
-dontwarn sun.misc.Unsafe

So this is an issue with your ProGuard configuration and not this library. Closing then. -ut


Disable automatic config path creation

Closing this one, as it would make sense to disable this since the information is needed to continue running any of the scripts.


FileNotFound Error For 'cwwbp'

origin images will be replace with webp images on /home/embed/OtherProjects/picture
convert for /home/embed/OtherProjects/picture/a.jpg
Traceback (most recent call last):
File "/home/embed/OtherProjects/picture/enve/bin/webpc", line 11, in
sys.exit(main())
File "/home/embed/OtherProjects/picture/enve/lib/python3.5/site-packages/webpc/init.py", line 129, in main
output_data=output_data
File "/home/embed/OtherProjects/picture/enve/lib/python3.5/site-packages/webpc/init.py", line 206, in loop
output_file_path, is_debug)
File "/home/embed/OtherProjects/picture/enve/lib/python3.5/site-packages/webpc/init.py", line 293, in convert
subprocess.Popen(command, stdout=FNULL, stderr=subprocess.STDOUT).communicate()
File "/usr/lib/python3.5/subprocess.py", line 947, in init
restore_signals, start_new_session)
File "/usr/lib/python3.5/subprocess.py", line 1551, in _execute_child
raise child_exception_type(errno_num, err_msg)
FileNotFoundError: [Errno 2] No such file or directory: 'cwebp'

Did you install webp with:
brew install webp
or if you prefer to install it with apt:
sudo apt install webp -y


the node doesn´t resize after adding new inputs

the node widget doesnt resize in height when adding new inputs

I will see about adding a resize function too -- its just not something that comes in the ComfyUI and we each have to make it ourselves atm. Most likely will rip it from Jovimetrix.

the node widget doesnt resize in height when adding new inputs

I took a look, and the default behavior does collapse and expand. Are you perhaps not on the latest frontend? I use @latest and not the version locked on that ships with whatever version of ComfyUI is out.

https://github.com/user-attachments/assets/8ac4b7e6-6c89-49bd-9d23-20a343c8fcd2
Let me know if that is not what you are seeing? Perhaps it is a browser problem? I am using Firefox.


[FileVersion] Add command to get progress for set version policy

Before creating a pull request, make sure that you have read the contribution file located at
https://github.com/pnp/powerShell/blob/dev/CONTRIBUTING.md
Type

[ ] Bug Fix
[X] New Feature
[ ] Sample

What is in this Pull Request ?
Add a new command to get progress of setting version policy for existing document libraries on the site
Some test results:

Hi @KoenZomers, could you please review this change? Thanks so much!


[Impeller] Dialog glitches on iOS on the master branch

Is there an existing issue for this?

[X] I have searched the existing issues
[X] I have read the guide to filing a bug

Steps to reproduce
Open a dialog while running on impeller on iOS on the master branch
This is reproducing from: https://github.com/flutter/flutter/commit/bede50cba21b176e4de0df3e8351c51b05512027
This doesn't happen with flutter run --no-enable-impeller
Expected results
No glitches
Actual results

Preview 1
Preview 2

Code sample
Code sample
import 'package:flutter/material.dart';

/// Flutter code sample for [Dialog].

void main() => runApp(const DialogExampleApp());

class DialogExampleApp extends StatelessWidget {
  const DialogExampleApp({super.key});

  @override
  Widget build(BuildContext context) {
    return MaterialApp(
      home: Scaffold(
        appBar: AppBar(title: const Text('Dialog Sample')),
        body: const Center(
          child: DialogExample(),
        ),
      ),
    );
  }
}

class DialogExample extends StatelessWidget {
  const DialogExample({super.key});

  @override
  Widget build(BuildContext context) {
    return Column(
      mainAxisAlignment: MainAxisAlignment.center,
      children: <Widget>[
        TextButton(
          onPressed: () => showDialog<String>(
            context: context,
            builder: (BuildContext context) => Dialog(
              child: Padding(
                padding: const EdgeInsets.all(8.0),
                child: Column(
                  mainAxisSize: MainAxisSize.min,
                  mainAxisAlignment: MainAxisAlignment.center,
                  children: <Widget>[
                    const Text('This is a typical dialog.'),
                    const SizedBox(height: 15),
                    TextButton(
                      onPressed: () {
                        Navigator.pop(context);
                      },
                      child: const Text('Close'),
                    ),
                  ],
                ),
              ),
            ),
          ),
          child: const Text('Show Dialog'),
        ),
        const SizedBox(height: 10),
        TextButton(
          onPressed: () => showDialog<String>(
            context: context,
            builder: (BuildContext context) => Dialog.fullscreen(
              child: Column(
                mainAxisSize: MainAxisSize.min,
                mainAxisAlignment: MainAxisAlignment.center,
                children: <Widget>[
                  const Text('This is a fullscreen dialog.'),
                  const SizedBox(height: 15),
                  TextButton(
                    onPressed: () {
                      Navigator.pop(context);
                    },
                    child: const Text('Close'),
                  ),
                ],
              ),
            ),
          ),
          child: const Text('Show Fullscreen Dialog'),
        ),
      ],
    );
  }
}

Screenshots or Video

Screenshots / Video demonstration
[Upload media here]

Logs
Logs
[Paste your logs here]

Flutter Doctor output
Doctor output
[✓] Flutter (Channel master, 3.14.0-9.0.pre.70, on macOS 13.5 22G74 darwin-arm64, locale en-EE)
    • Flutter version 3.14.0-9.0.pre.70 on channel master at /Users/tahatesser/Code/flutter
    • Upstream repository git@github.com:TahaTesser/flutter.git
    • FLUTTER_GIT_URL = git@github.com:TahaTesser/flutter.git
    • Framework revision bede50cba2 (9 hours ago), 2023-08-24 00:49:29 -0400
    • Engine revision 3b92bb6eda
    • Dart version 3.2.0 (build 3.2.0-97.0.dev)
    • DevTools version 2.26.2

[✓] Android toolchain - develop for Android devices (Android SDK version 34.0.0)
    • Android SDK at /Users/tahatesser/Code/android-sdk
    • Platform android-34, build-tools 34.0.0
    • ANDROID_SDK_ROOT = /Users/tahatesser/Code/android-sdk
    • Java binary at: /Applications/Android Studio.app/Contents/jbr/Contents/Home/bin/java
    • Java version OpenJDK Runtime Environment (build 17.0.6+0-17.0.6b829.9-10027231)
    • All Android licenses accepted.

[✓] Xcode - develop for iOS and macOS (Xcode 14.3.1)
    • Xcode at /Applications/Xcode.app/Contents/Developer
    • Build 14E300c
    • CocoaPods version 1.12.1

[✓] Chrome - develop for the web
    • Chrome at /Applications/Google Chrome.app/Contents/MacOS/Google Chrome

[✓] Android Studio (version 2022.3)
    • Android Studio at /Applications/Android Studio.app/Contents
    • Flutter plugin can be installed from:
      🔨 https://plugins.jetbrains.com/plugin/9212-flutter
    • Dart plugin can be installed from:
      🔨 https://plugins.jetbrains.com/plugin/6351-dart
    • Java version OpenJDK Runtime Environment (build 17.0.6+0-17.0.6b829.9-10027231)

[✓] VS Code (version 1.81.1)
    • VS Code at /Applications/Visual Studio Code.app/Contents
    • Flutter extension version 3.70.0

[✓] Connected device (3 available)
    • iPhone 14 Pro (mobile) • CFB80E17-6D16-4931-8DC5-2CD8892E90FC • ios            •
      com.apple.CoreSimulator.SimRuntime.iOS-16-4 (simulator)
    • macOS (desktop)        • macos                                • darwin-arm64   • macOS 13.5 22G74
      darwin-arm64
    • Chrome (web)           • chrome                               • web-javascript • Google Chrome
      116.0.5845.110

[✓] Network resources
    • All expected network resources are available.

• No issues found!

This seems to be fixed now.


fix: upgrade depdencies to latest versions, require NodeJS >= 18

BREAKING CHANGE: require NodeJS >= 18
Fixes #259, Fixes #258, Fixes #257, Fixes #251, Fixes #250, Fixes #248, Fixes #236, Fixes #233

Oh, @wolfy1339
I didnt see your PR last night. I will close my PR, 😁

@wolfy1339
Maybe you want to compare your pr with mine and adapt some differences?

@gr2m Can you review this when you get the time? It's needed for the Probot upgrade

The coverage seems to have dropped, not sure why.

Fixed all the test failures. This is now good to go


Images for Redis-Cluster Template

Hi,
I want to try the redis-cluster template in the catalog but found the image is in private registry as "<IP_ADDRESS>:5000/kiemsi/redis-replicas", could you share the image in github? Thanks a lot.

Try using https://hub.docker.com/r/rickoliveira1/redis-replicas


Fix flutter_plugins by rolling revision

Fixes https://github.com/flutter/flutter/issues/129782
Linux flutter_plugins is currently broken https://ci.chromium.org/p/flutter/builders/prod/Linux flutter_plugins/12884
On an analysis error that was ignored upstream in https://github.com/flutter/packages/commit/5d6e48c3e099fa6c24f45b778f5b7cab82a7e1e8

Merging on pending Windows tool_integration_tests as this change shouldn't affect this test and this will fix the tree.


Cleaning & fix for 3.0

Used more inheritance
Changed categories and headers to divider so they won't get highlighted

thanks


Allow loading a MinimumEigensolverResult directly into the MinimumEigenOptimizer

What should we add?
The MinimumEigenOptimizer internally calls a minimum eigensolver and then postprocesses the obtained MinimumEigensolverResult in the context of the quadratic program that we try to solve. It would be great if we could directly pass in a MinimumEigensolverResult into this postprocessing part if we have it already, like:
optimization_result = MinimumEigenOptimizer.process_result(minimum_eigensolver_result, quadratic_program)

This would be particularly useful in context of the QAOA and VQE runtimes as jobs can get stuck locally but we can easily get the result back from the job ID on the quantum experience (see also Qiskit/qiskit-nature#479). With the feature here we could then have a workflow like
job_id = # my job ID from the quantum experience
vqe_result = VQEClient.retrieve_result(provider, job_id)
opt_result = MinimumEigenOptimizer.process_result(vqe_result, quadratic_program)

Names or function calls here are just suggestions 🙂
The implementation should be rather straightforward since we could restructure MinimumEigenOptimizer.solve to something like
def solve(self, problem):
    # same conversions as now
    problem_ = self._convert(problem, self._converters)
    operator, offset = problem_.to_ising()

    # just run MES, no interpretation
    mes_result = self._solve_mes(operator, offset, problem_, problem)

    # interpretation in a separate function
    result = self.process_result(problem)

This would be particularly useful in context of the QAOA and VQE runtimes as jobs can get stuck locally

This makes it sounds as this happens more frequently than one might like. Hopefully the root cause of that gets looked at too so as to improve things in that regard. However...
Does passing in some result there become stateful on the MEO? I assume you need the same class (or another later instantiated the same way) in order to interpret the result correctly in the context of the original problem; otherwise the result may not make sense. Maybe that's left to the user who somehow needs/wants to interpret a result.

This makes it sounds as this happens more frequently than one might like. Hopefully the root cause of that gets looked at too so as to improve things in that regard. However...

I didn't experience this myself lately (it's coming from another user) so at least for me it doesn't happen often 🙂

Does passing in some result there become stateful on the MEO?

It definitely shouldn't become stateful, that's why the pseudo-code above passes the original quadratic program into the MEO along with the minimum eigensolver result. That should be all the information required to reconstruct the result I think -- but I might be missing something! 😄

Thank you for the proposal. It would be nice if users easily interpret VQEClient result.
Before applying converter.interpret(result) to a result, we need to convert a problem by converter.convert(problem) so that converter keeps information of the problem.
Moreover, solve method interprets not only the best solution but also all solution samples.
So, restructuring might be a bit complicated. But, it's worthwhile.
Perhaps, it might be useful to separate to_ising part as well as the interpretation? What do you think from VQEclient perspective, @Cryoris?
def preprocessing(problem)
    problem_ = self._convert(problem, self._converters)
    operator, offset = problem_.to_ising()
    return operator, offset

def process_result(mes_result, problem=None)
    if problem:
        # if users interpret results of `VQEClient`, they need to set the problem.
        _ = self._convert(problem, self._converters)
    samples, best_sol = self._interpret_samples(problem, mes_result)
    return self._interpret(best_sol, samples)

def solve(self, problem):
    # generate Ising Hamiltonian
    operator, offset = self.preprocessing(problem)

    # just run MES, no interpretation
    mes_result = self._solve_mes(operator, offset, problem_, problem)

    # interpretation in a separate function
    result = self.process_result(mes_result)


Fix incorrect heading indentation

Trello card
https://trello.com/c/Csz3XTbz
Context

Heading indentation and padding are not correct in event sign up.

Changes proposed in this pull request

Fix event sign up heading indentaion/padding

Guidance to review

This feels like a very specific solution - why is this displaying offset for events sign up but not other for fields?
Does this really only affect those fields or should it be getting solved more generically?

I can remove the content-heading mixin from the h2, which fixes the indentation without affecting the other targeted class mailing-reg-main.
But, this (link) for the top margin is used quite a lot, so the only solution I can think of is to override it?

The link you referenced above should only apply to the blue h2's that overhang the content; the rule targets only those that appear within .markdown elements (ours are all article.markdown).
I think we should remove all horizontal padding/margins elsewhere from headers, I can't think of anywhere else (apart from the hero) where we'd want it.


Add confirmation email during registration

Is your feature request related to a problem? Please describe.
A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
Right now, any kind of email, real or fake, can be use for registration in our platform. This can lead to the creation of fake accounts.
Describe the solution you'd like
A clear and concise description of what you want to happen.
To prevent this kind of scenario we should send an email confirmation with a token to force each new user to confirm their email address to activate the account.
This could be achieved by using a library like django-all-auth.
Describe alternatives you've considered
None.
Additional context
None.

@francescarpi @XaviTorello  Should we have this feature?


Module not found when running with Python 3.11

Traceback (most recent call last):
  File "~/synophotos/bin/synophotos", line 5, in <module>
    from synophotos.cli import main
  File "~/synophotos/lib/python3.11/site-packages/synophotos/__init__.py", line 15, in <module>
    from synophotos.webservice import SynoSession, WebService
  File "~/synophotos/lib/python3.11/site-packages/synophotos/webservice.py", line 12, in <module>
    from typing_extensions import Protocol
ModuleNotFoundError: No module named 'typing_extensions'

closed by #2


Fix bug for not able to get sourceTables from metadata

Description
Using custom implementation for FlintIndexMetadataService exposes a bug where we incorrectly get empty sourceTables from FlintMetadata.
Depending on how the FlintMetadata is generated, the metadata.properties.get("sourceTables") could either be of type java array or scala array.
This PR fixes the bug, now considering both cases.
Also added some logs for troubleshooting in production environment.
Related Issues

#746
#854

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.
For more information on following Developer Certificate of Origin and signing off your commits, please check here.

Is it possible to enforce a single and language-independent format in metadata, e.g. JSON array?

Not quite sure..
Since when reading from OpenSearch index mappings, we use jackson library to deserialize into FlintMetadata, and jackson library will use java.util.ArrayList. I'll try using this type instead.
Or do you mean using json string? Like
{"sourceTables": "[\"a.b.c\"], [\"d.e.f\"]"}

Is it possible to enforce a single and language-independent format in metadata, e.g. JSON array?

Not quite sure.. Since when reading from OpenSearch index mappings, we use jackson library to deserialize into FlintMetadata, and jackson library will use java.util.ArrayList. I'll try using this type instead.
Or do you mean using json string? Like
{"sourceTables": "[\"a.b.c\"], [\"d.e.f\"]"}

Yeah, just trying to understand where this problem comes from? Is Scala or Java array stored in metadata?

mainly comes from this line of scala code. I was putting scala Array[String] here.
https://github.com/opensearch-project/opensearch-spark/pull/883/files#diff-1e6cbb4cde65f1142862f3b539a438d534fd70a229499efd671ef9aae67ff29fR75
Now I've changed it to use ArrayList. so for both cases (mv.metadata() and deserialized metadata from index mapping) will have ArrayList. Do you think this is better? @dai-chen


Update install instructions and fix broken links in README

Thank you for this very useful project :+1:
Fixes #4.

Thanks for your contribution!


Mixed Precision - Conv3D - error: No algorithm worked!

System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow):
Yes, I wrote a custom code.
OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
Linux (CentOS 7)
TensorFlow installed from (source or binary):
Installed using PIP
TensorFlow version (use command below):
v2.4.0-rc4-71-g582c8d236cb 2.4.0
Python version:
3.8.0
CUDA/cuDNN version:
CUDA/11.1.1
cuDNN/<IP_ADDRESS>-CUDA-11.1.1
GPU model and memory:
2 NVIDIA A100-PCIE-40GB
2 GPUs on the same computer

Describe the current behavior
When running the code with double precision, the code does not generate errors. When running with mixed precision, launches an error:
Describe the expected behavior
Not having errors when running with mixed precision.
Standalone code to reproduce the issue
I tried to create a google colab for this code. There is no error there, but I could not get a google colab with 2 GPUs, like in my enviroment.
import tensorflow as tf
from tensorflow.keras.mixed_precision import experimental as mixed_precision
from tensorflow.keras import layers, Model, optimizers
import numpy as np

# If you comment the following 2 lines, the code runs
policy = mixed_precision.Policy('mixed_float16')
mixed_precision.set_policy(policy)

mirrored_strategy = tf.distribute.MirroredStrategy()
with mirrored_strategy.scope():
    x_input = layers.Input(shape=(60, 60, 2, 32))

    x = layers.Conv3D(filters=32, kernel_size=(3, 3, 1), strides=(1, 1, 1), padding = 'same')(x_input)
    x = layers.BatchNormalization()(x)
    x_out = layers.ReLU()(x)

    test_model = Model(inputs=x_input, outputs=x_out, name='test_model')
    adam = optimizers.Adam(learning_rate=1E-4)

test_model.compile(optimizer=adam, loss="mse", metrics=["mae"])

input_data = np.random.random((1000, 60, 60, 2, 32))
target_data = np.random.random((1000, 60, 60, 2, 32))

ds_tuple = tf.data.Dataset.from_tensor_slices((input_data,target_data))
ds_tuple = ds_tuple.shuffle(1000).batch(100)

history = test_model.fit(ds_tuple, epochs=10, verbose=1)

Other info / logs
This is the log of the run when I try running with mixed precision:
2021-01-21 15:37:22.318957: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2021-01-21 15:37:36.119468: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-01-21 15:37:36.123358: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcuda.so.1
2021-01-21 15:37:36.201391: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:3b:00.0 name: A100-PCIE-40GB computeCapability: 8.0
coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.59GiB deviceMemoryBandwidth: 1.41TiB/s
2021-01-21 15:37:36.204229: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 1 with properties:
pciBusID: 0000:d8:00.0 name: A100-PCIE-40GB computeCapability: 8.0
coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.59GiB deviceMemoryBandwidth: 1.41TiB/s
2021-01-21 15:37:36.204423: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2021-01-21 15:37:37.945043: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2021-01-21 15:37:37.945235: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
2021-01-21 15:37:37.998423: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2021-01-21 15:37:38.072705: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2021-01-21 15:37:38.207114: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
2021-01-21 15:37:38.574293: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
2021-01-21 15:37:38.612582: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2021-01-21 15:37:38.624584: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0, 1
2021-01-21 15:37:38.624772: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-01-21 15:37:38.626778: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
WARNING:tensorflow:From /scratch/user/eee/conda/myEnvs/tf_2.4/lib/python3.8/site-packages/tensorflow/python/keras/mixed_precision/loss_scale.py:56: DynamicLossScale.__init__ (from tensorflow.python.training.experimental.loss_scale) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.keras.mixed_precision.LossScaleOptimizer instead. LossScaleOptimizer now has all the functionality of DynamicLossScale
2021-01-21 15:37:38.638220: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX512F
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2021-01-21 15:37:38.638847: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-01-21 15:37:38.840057: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:3b:00.0 name: A100-PCIE-40GB computeCapability: 8.0
coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.59GiB deviceMemoryBandwidth: 1.41TiB/s
2021-01-21 15:37:38.842228: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 1 with properties:
pciBusID: 0000:d8:00.0 name: A100-PCIE-40GB computeCapability: 8.0
coreClock: 1.41GHz coreCount: 108 deviceMemorySize: 39.59GiB deviceMemoryBandwidth: 1.41TiB/s
2021-01-21 15:37:38.842375: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2021-01-21 15:37:38.842436: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2021-01-21 15:37:38.842486: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
2021-01-21 15:37:38.842536: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2021-01-21 15:37:38.842585: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2021-01-21 15:37:38.842635: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusolver.so.10
2021-01-21 15:37:38.842683: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
2021-01-21 15:37:38.842733: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2021-01-21 15:37:38.850268: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0, 1
2021-01-21 15:37:38.850360: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2021-01-21 15:37:40.396681: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-01-21 15:37:40.396829: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 1
2021-01-21 15:37:40.396881: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N Y
2021-01-21 15:37:40.396925: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 1:   Y N
2021-01-21 15:37:40.407031: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 37570 MB memory) -> physical GPU (device: 0, name: A100-PCIE-40GB, pci bus id: 0000:3b:00.0, compute capability: 8.0)
2021-01-21 15:37:40.414936: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:1 with 37570 MB memory) -> physical GPU (device: 1, name: A100-PCIE-40GB, pci bus id: 0000:d8:00.0, compute capability: 8.0)
     --->     Running Tensorflow in Mixed Precision...
WARNING:tensorflow:tf.keras.mixed_precision.experimental.LossScaleOptimizer is deprecated. Please use tf.keras.mixed_precision.LossScaleOptimizer instead. Note that the non-experimental LossScaleOptimizer does not take a DynamicLossScale but instead takes the dynamic configuration directly in the constructor. For example:
  opt = tf.keras.mixed_precision.experimental.LossScaleOptimizer(opt)

2021-01-21 15:37:47.583748: W tensorflow/core/grappler/optimizers/data/auto_shard.cc:656] In AUTO-mode, and switching to DATA-based sharding, instead of FILE-based sharding as we cannot find appropriate reader dataset op(s) to shard. Error: Found an unshardable source dataset: name: "TensorSliceDataset/_2"
op: "TensorSliceDataset"
input: "Placeholder/_0"
input: "Placeholder/_1"
attr {
  key: "Toutput_types"
  value {
    list {
      type: DT_DOUBLE
      type: DT_DOUBLE
    }
  }
}
attr {
  key: "output_shapes"
  value {
    list {
      shape {
        dim {
          size: 60
        }
        dim {
          size: 60
        }
        dim {
          size: 2
        }
        dim {
          size: 32
        }
      }
      shape {
        dim {
          size: 60
        }
        dim {
          size: 60
        }
        dim {
          size: 2
        }
        dim {
          size: 32
        }
      }
    }
  }
}

2021-01-21 15:37:48.602974: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
2021-01-21 15:37:48.606716: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency:<PHONE_NUMBER> Hz
Epoch 1/10
2021-01-21 15:37:56.331798: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2021-01-21 15:39:18.436971: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2021-01-21 15:39:28.779314: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
2021-01-21 15:39:31.933180: W tensorflow/core/framework/op_kernel.cc:1763] OP_REQUIRES failed at conv_grad_ops_3d.cc:1994 : Not found: No algorithm worked!
Traceback (most recent call last):
  File "main.py", line 31, in <module>
    history = test_model.fit(ds_tuple, epochs=10, verbose=1)
  File "/scratch/user/eee/conda/myEnvs/tf_2.4/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py", line 1100, in fit
    tmp_logs = self.train_function(iterator)
  File "/scratch/user/eee/conda/myEnvs/tf_2.4/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 828, in __call__
    result = self._call(*args, **kwds)
  File "/scratch/user/eee/conda/myEnvs/tf_2.4/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 888, in _call
    return self._stateless_fn(*args, **kwds)
  File "/scratch/user/eee/conda/myEnvs/tf_2.4/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 2942, in __call__
    return graph_function._call_flat(
  File "/scratch/user/eee/conda/myEnvs/tf_2.4/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 1918, in _call_flat
    return self._build_call_outputs(self._inference_function.call(
  File "/scratch/user/eee/conda/myEnvs/tf_2.4/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 555, in call
    outputs = execute.execute(
  File "/scratch/user/eee/conda/myEnvs/tf_2.4/lib/python3.8/site-packages/tensorflow/python/eager/execute.py", line 59, in quick_execute
    tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
tensorflow.python.framework.errors_impl.NotFoundError: 3 root error(s) found.
  (0) Not found:  No algorithm worked!
         [[node gradient_tape/test_model/conv3d/Conv3D/Conv3DBackpropFilterV2 (defined at /threading.py:932) ]]
  (1) Not found:  No algorithm worked!
         [[node gradient_tape/test_model/conv3d/Conv3D/Conv3DBackpropFilterV2 (defined at /threading.py:932) ]]
         [[cond_4/then/_40/cond_4/cond/pivot_t/_256/_187]]
  (2) Not found:  No algorithm worked!
         [[node gradient_tape/test_model/conv3d/Conv3D/Conv3DBackpropFilterV2 (defined at /threading.py:932) ]]
         [[div_no_nan/ReadVariableOp_3/_108]]
0 successful operations.
0 derived errors ignored. [Op:__inference_train_function_2870]

Function call stack:
train_function -> train_function -> train_function

Can you please try with cuda 11.0 and TF 2.4 final version?

Can you please try with cuda 11.0 and TF 2.4 final version?

Met the same problem, have you solved it?

Met the same problem, have you solved it?

Can you please try with cuda 11.0 and TF 2.4 final version?

@ymodak , I installed TF 2.4.1 from PIP and using CUDA/11.0.2 and cuDNN/<IP_ADDRESS>, and got the same error with Mixed Precision.

Can you please try with cuda 11.0 and TF 2.4 final version?

@ymodak , I installed TF 2.4.1 from PIP and using CUDA/11.0.2 and cuDNN/<IP_ADDRESS>, and got the same error with Mixed Precision.

Same error, any solution??

Same error.

Upgrading to cuDNN 8.0.5 fixes this. 8.0.5 is compatible with TF 2.4 and tf-nightly, so please upgrade.
I can reproduce with cuDNN 8.0.3 and 8.0.4, but not with cuDNN 8.0.2 and 8.0.5, so this has been fixed by 8.0.5. If it's feasible to check the cuDNN version at runtime, I'll improve the error message to state 8.0.5 should be used. @nluehr do you know if there are any workarounds for 8.0.3 and 8.0.4?
@sanjoy, can we update the GPU support guide to recommend 8.0.5? Currently it recommends 8.0.4.
For reference, with 8.0.5, the only cudnnConvolutionBwdFilterAlgo_t which works is CUDNN_CONVOLUTION_BWD_FILTER_ALGO_1. This fails on 8.0.3 and 8.0.4 though.

Upgrading to cuDNN 8.0.5 fixes this. 8.0.5 is compatible with TF 2.4 and tf-nightly, so please upgrade.
I can reproduce with cuDNN 8.0.3 and 8.0.4, but not with cuDNN 8.0.2 and 8.0.5, so this has been fixed by 8.0.5. If it's feasible to check the cuDNN version at runtime, I'll improve the error message to state 8.0.5 should be used. @nluehr do you know if there are any workarounds for 8.0.3 and 8.0.4?
@sanjoy, can we update the GPU support guide to recommend 8.0.5? Currently it recommends 8.0.4.
For reference, with 8.0.5, the only cudnnConvolutionBwdFilterAlgo_t which works is CUDNN_CONVOLUTION_BWD_FILTER_ALGO_1. This fails on 8.0.3 and 8.0.4 though.
Reinstall cuDNN 8.0.5 worked for me, thanks!

Upgrading to cuDNN 8.0.5 fixes this. 8.0.5 is compatible with TF 2.4 and tf-nightly, so please upgrade.
I can reproduce with cuDNN 8.0.3 and 8.0.4, but not with cuDNN 8.0.2 and 8.0.5, so this has been fixed by 8.0.5. If it's feasible to check the cuDNN version at runtime, I'll improve the error message to state 8.0.5 should be used. @nluehr do you know if there are any workarounds for 8.0.3 and 8.0.4?
@sanjoy, can we update the GPU support guide to recommend 8.0.5? Currently it recommends 8.0.4.
For reference, with 8.0.5, the only cudnnConvolutionBwdFilterAlgo_t which works is CUDNN_CONVOLUTION_BWD_FILTER_ALGO_1. This fails on 8.0.3 and 8.0.4 though.

Reinstall cuDNN 8.0.5 worked for me, thanks!

Same error.

After updating to cuDNN 8.0.5 the problem was solved. Thanks, @reedwm.


problmem when i run npm start

<EMAIL_ADDRESS>start /home/pi/MagicMirror
DISPLAY="${DISPLAY:=:0}" ./node_modules/.bin/electron js/electron.js

/home/pi/MagicMirror/node_modules/electron/index.js:17
throw new Error('Electron failed to install correctly, please delete node_modules/electron and try installing again');
^
Error: Electron failed to install correctly, please delete node_modules/electron and try installing again
at getElectronPath (/home/pi/MagicMirror/node_modules/electron/index.js:17:11)
at Object. (/home/pi/MagicMirror/node_modules/electron/index.js:21:18)
at Module._compile (internal/modules/cjs/loader.js:999:30)
at Object.Module._extensions..js (internal/modules/cjs/loader.js:1027:10)
at Module.load (internal/modules/cjs/loader.js:863:32)
at Function.Module._load (internal/modules/cjs/loader.js:708:14)
at Module.require (internal/modules/cjs/loader.js:887:19)
at require (internal/modules/cjs/helpers.js:74:18)
at Object. (/home/pi/MagicMirror/node_modules/electron/cli.js:3:18)
at Module._compile (internal/modules/cjs/loader.js:999:30)
npm ERR! code ELIFECYCLE
npm ERR! errno 1
npm ERR<EMAIL_ADDRESS>start: DISPLAY="${DISPLAY:=:0}" ./node_modules/.bin/electron js/electron.js
npm ERR! Exit status 1
npm ERR!
npm ERR! Failed at the<EMAIL_ADDRESS>start script.
npm ERR! This is probably not a problem with npm. There is likely additional logging output above.
npm ERR! A complete log of this run can be found in:
npm ERR!     /home/pi/.npm/_logs/2022-01-28T20_09_06_161Z-debug.log

what pi?
uname - a
will help
what pi os?
lsb_release -a
will help
if you used my scripted install it probably would have fixed the problem
see
https://github.com/sdetweil/MagicMirror_scripts

This problem is due to improper installation of electron.
Try to remove node_modules and npm cache clean --force
After doing this, run npm i
A piece of advice have a good internet connection to avoid having a corrupt installation of electron !

@Hamzacos  did you resolve this?

Maybe we shoudl close this @MichMich since @Hamzacos hasnt responded in quite a few months...


As a metadata creator I would like to have a metadata field have a pull down option which can not be edited

Enforce a limited set of values with option and multi-option input types.

Transferred to Trello.


how to take the sniffer off / how to use artoo.ajaxSniffer.off

I have trouble to take off a sniffer. Could someone help me?
what i did:
artoo.ajaxSniffer.after(function(req, res) {
  //console.log("req: " + JSON.stringify(req));
  if (req.url.search(/event\/[0-9]+\/json/) != -1) {
    console.log('response data: ');
    console.log(res.data);
    //artoo.savePrettyJson(res.data);
  }
})

// code for actions

// take off the sniffer
artoo.ajaxsniffer.off(???) // how to take it now off?

Hello @brainmixxx. This event emitter is not very elaborate so to be able to "off" your handler, you just need to pass the function to the off method:
var handler = function(req, res) {
  //console.log("req: " + JSON.stringify(req));
  if (req.url.search(/event\/[0-9]+\/json/) != -1) {
    console.log('response data: ');
    console.log(res.data);
    //artoo.savePrettyJson(res.data);
  }
}

artoo.ajaxSniffer.after(handler)

// code for actions

// take off the sniffer:
artoo.ajaxsniffer.off(handler)

Note that if every handler was offed, artoo will release its parasites over the xhr connections. Also note that I don't think those sniffers would work with the more recent fetch calls.

Hello @Yomguithereal thank you for the fast reply. The sniffer itself works. When I try your code I have following error:
artoo-latest.min.js:2 Uncaught Error: artoo.ajaxSniffer.off: trying to remove an inexistant listener.
    at t.off (artoo-latest.min.js:2)
    at <anonymous>:2:19

It seems you are trying to off a handler function that was not passed to the sniffer. Maybe you are trying to remove the same listener more than once?

no, I did not. But at the moment it is important that the sniffer is on and not to make them off.
Thank you for your help!


fix: only directories are valid type roots

When working on OSX, a .DS_Store file gets automatically generated in directories opened in Finder. This breaks:
➜  DefinitelyTyped git:(master) ✗ npm test

><EMAIL_ADDRESS>test /Users/joscha/Development/DefinitelyTyped
> node node_modules/types-publisher/bin/tester/test.js --run-from-definitely-typed --nProcesses 1

Clean data
Clean logs
Clean output
# Typing Publish Report Summary
Started at Wed, 07 Jun 2017 22:23:34 GMT
Found 3160 typings folders in /Users/joscha/Development/DefinitelyTyped/types
Error: Package name `.DS_Store` should be strictly lowercase
    at Object.<anonymous> (/Users/joscha/Development/DefinitelyTyped/node_modules/types-publisher/src/lib/definition-parser.ts:17:9)
    at Generator.next (<anonymous>)

This seems like a small (but important) contribution, so no Contribution License Agreement is required at this point. We will now review your pull request.
Thanks,
Microsoft Pull Request Bot

Thanks!


Lack of reconcile waiting on child process

Describe the bug
In an update to a CR, it was observed that reconciliation did not start.
Some logs observed after reconciliation was requested through CR update (Controller, resource, namespace edited to be more general for OSS)
{"channel": "RCLTHRD", "exception": null, "level": "debug3", "message": "Processing object <multiprocessing.connection.Connection object at 0x7f9cdc530450> with type <class 'multiprocessing.connection.Connection'>", "num_indent": 0, "process": 1, "thread":<PHONE_NUMBER>68384, "threadName": "reconcile_thread", "thread_id":<PHONE_NUMBER>68384, "timestamp": "2024-02-15T14:36:00.434219"}
{"channel": "RCLTHRD", "exception": null, "level": "debug3", "message": "Got request ReconcileRequest(controller_type=<class 'Controller'>, type=<KubeEventType.MODIFIED: 'MODIFIED'>, resource=<resource>, timestamp=datetime.datetime(2024, 2, 9, 16, 25, 19, 247957)) from queue", "num_indent": 0, "process": 1, "thread":<PHONE_NUMBER>68384, "threadName": "reconcile_thread", "thread_id":<PHONE_NUMBER>68384, "timestamp": "2024-02-15T14:36:00.434757"}
{"channel": "RCLTHRD", "exception": null, "level": "debug4", "message": "Event in queue is newer than event ReconcileRequest(controller_type=<class 'Controller'>, type=<KubeEventType.MODIFIED: 'MODIFIED'>, resource=<resource>, timestamp=datetime.datetime(2024, 2, 9, 16, 25, 19, 247957))", "num_indent": 0, "process": 1, "thread":<PHONE_NUMBER>68384, "threadName": "reconcile_thread", "thread_id":<PHONE_NUMBER>68384, "timestamp": "2024-02-15T14:36:00.434844"}
{"channel": "RCLTHRD", "exception": null, "level": "debug3", "message": "Waiting on [ReconcileProcess(process=<ForkProcess name='ForkProcess-877' pid=395910 parent=1 started>, request=ReconcileRequest(controller_type=<class '<Controller>'>, type=<ReconcileRequestType.PERIODIC: 'PERIODIC'>, resource=<resource>, timestamp=datetime.datetime(2024, 2, 9, 16, 25, 19, 247957)), pipe=<multiprocessing.connection.Connection object at 0x7f9cdc3c8bd0>), <multiprocessing.connection.Connection object at 0x7f9cdc530450>]", "num_indent": 0, "process": 1, "thread":<PHONE_NUMBER>68384, "threadName": "reconcile_thread", "thread_id":<PHONE_NUMBER>68384, "timestamp": "2024-02-15T14:36:00.434923"}
...
{"channel": "WTCHTHRD", "exception": null, "level": "debug3", "message": "Gathering request for controller <class 'Controller'> from {'apiVersion': 'caikit.org/v1alpha1', 'kind': 'CaikitRuntimeStack', 'name': 'fmaas', 'uid': 'e7b61f7f-9919-4622-84e7-cc492f8a3741', 'blockOwnerDeletion': True}", "num_indent": 0, "process": 1, "thread":<PHONE_NUMBER>54432, "threadName": "watch_thread_apps/v1_Deployment_namespace", "thread_id":<PHONE_NUMBER>54432, "timestamp": "2024-02-15T14:36:13.110827"}
{"apiVersion": "apps/v1", "channel": "PWMFLT", "exception": null, "kind": "Deployment", "level": "debug3", "message": "Failed filter: <oper8.watch_manager.python_watch_manager.filters.filters.ResourceVersionFilter object at 0x7f9cdc422bd0> with return val False", "num_indent": 0, "process": 1, "resourceName": "mt", "resourceVersion": "257498003", "thread":<PHONE_NUMBER>54432, "threadName": "watch_thread_apps/v1_Deployment_namespace", "thread_id":<PHONE_NUMBER>54432, "timestamp": "2024-02-15T14:36:13.110958"}

When the operator pod was manually deleted for a new pod, updates were able to roll out. There may potentially be an issue with leader election where CR responsibility may have become unclear.
Platform
Please provide details about the environment you are using, including the following:

Interpreter version: python3.9
Library version: 0.1.11

Expected behavior
Consistent rollouts on CR update
Observed behavior
Failed filter logs above, no rollouts on CR update

@evaline-ju after looking at the error snippet for a few minutes, it seems like there could be a few things going wrong including an unfinished reconciliation or improperly configured filter. Could you possibly send a larger log snippet including the startup and first reconciliation?

Sadly not resolved just yet :(

I believe this can be closed with the above PR!