Fixed Jewel ComboBox freeze with SearchFilter

Fixed the following issue:

Locate ComboBox on Tour de Jewel components;
Go to Local Search Filter sample;
Select any item with mouse;
Select all text and type "i";
The only option will be "Iron Man" and at this point you coun’t select the option or close the list and the application would freeze.

Hi Hugo,
I could try and that fix the problem in part, checking the code don't understand why it was not working before since seems to be the same. Maybe the remove listener was affecting...
while testing I see that pushing key down is not working too with search filter, that is something we should take a look but I think could be left for other ticket.
About the helper function: I think is important to not mix different things in the same PR. So that should be discussed in other way.
So, since you're a committer, you don't need me to merge, you can do it yourself. I think you can:

Close this PR
Merge the Jewel ComboBox fix
Open a thread in mailing list about the helper function in bead, since @Harbs and others could have something to say. That's because we try to keep core as PAYG as possible so that kind of changes need to be advised.

Thanks!

Hi Carlos,
Yes, in first time the fix was not tested on TDJ. Something that I understand now that should be done for this types of fixs.
However the second time, I did everything (check out Royale source code, compile, etc ...) and tested so, yeah, something was in the middle.
The helper function on this PR was something that I did wrong. However there is another PR just for that.
About commit directly on apache royale:
Is have an e-mail (gmail) that I use to mailling list group, another e-mail (solidsoft) for my git account and there is also the new apache e-mail that was created (I don't have the account setup and password yet).
I should use the apache e-mail as user on github for apache royale or can I use my soldisoft account ?
If should be with the new apache e-mail, where can I recover the password ?

Hi Hugo, I'll contact you in private to see how to commit


Fix memory leak in latest iOS versions

In the latest versions of the system (> 17.0), the component causes a memory leak (did not occur in previous versions). This bug causes the application to freeze after some time of use. Especially if content of the comment is a map.
It is necessary to reference the UIScrollView as a weak reference. I took advantage of the existence of the delegate and added the reference there. I didn't want to create a new object specifically for holding the reference. The modification is minimal, but it works fine.

Hey @algoroq, thank you so much for your work! This is a serious issue you fixed - have a marvellous day!


Set theme before Init PanelHolder

If build and run panel sample then get such error:

panic: runtime error: invalid memory address or nil pointer dereference
[signal 0xc0000005 code=0x0 addr=0x8 pc=0x5e5995]
goroutine 19 [running]:
github.com/nelsam/gxui/themes/basic.(*Theme).Driver(0x0, 0x78e500, 0x3355160)
T:/libraries/Gopath/src/github.com/nelsam/gxui/themes/basic/theme.go:45 +0x5

That is happening because theme is used inside Init method when creating PanelTab.
So setting theme first is fixed the issue.

lgtm


[ENHANCEMENT] Possibility to set a new inbound.mode with other parameters

Describe the use case: / Describe the enhancement/feature:
We use the stripped down version on Camunda (KIND) in some of our testing environments. So the components "Identity", "Tasklist", "Optimize" are disabled. But now we need the component "Operate" for these tests, so that we can test the corresponding connectors.
For our tests the variables
- name: CAMUNDA_CONNECTOR_POLLING_ENABLED
  value: "true"
- name: CAMUNDA_CONNECTOR_WEBHOOK_ENABLED
  value: "true"

but must be set to "true" manually at the moment, otherwise the corresponding processes will not be executed. But because the authentication is disabled accordingly and therefore only the credentials "demo/demo" work, I cannot use any of the tordefined inbound.mode [disabled, credentials or oauth].
So there must be a way to be able to cleanly set the two variables above to true. Temporarily, it's possible to just define these variables twice so that works, but then that often causes helmet errors, like "setElementOrderList is wrong". Or there is a new "inbound.mode" which is called "none", so that simply no variable is set and I can then set it myself.
Affected line in Helm Chart:
https://github.com/camunda/camunda-platform-helm/blob/main/charts/camunda-platform/templates/connectors/deployment.yaml#L45
In addition, a further inboundMode would then have to be allowed here: https://github.com/camunda/camunda-platform-helm/blob/main/charts/camunda-platform/templates/connectors/_helpers.tpl#L11 - It would be enough if you could define something like "none" here, that simply no envs are set predefined.

Hello,
I would like to make sure I understand before I start working on this.
I am assuming you are using our kind values yaml: https://github.com/camunda/camunda-platform-helm/blob/b6dd0fcb05e07f2209215481d50d4819ea7773ac/kind/camunda-platform-core-kind-values.yaml
As stated you have also disabled tasklist, so I also assume that you added the following to the values yaml:
tasklist:
  enabled: false

When running this values yaml, you get the following pods:
NAME                                     READY   STATUS    RESTARTS   AGE
camunda-connectors-6c778fcbb7-mh8wr      1/1     Running   0          4m35s
camunda-elasticsearch-master-0           1/1     Running   0          4m35s
camunda-elasticsearch-master-1           1/1     Running   0          4m35s
camunda-operate-7cbccff75b-j2m9f         1/1     Running   0          4m35s
camunda-zeebe-0                          1/1     Running   0          4m35s
camunda-zeebe-gateway-5b699496c7-kkb6f   1/1     Running   0          4m35s

As you can see, operate is available.
You now need to set values to true for the two env vars you have mentioned within the connectors component in order to test using operate.
You are now suggesting to append another condition to this if statement, so it can accept none which will result in not setting these two env vars at all: https://github.com/camunda/camunda-platform-helm/blob/b6dd0fcb05e07f2209215481d50d4819ea7773ac/charts/camunda-platform/templates/connectors/_helpers.tpl#L11

The problem on my side is that after helm deployment, I modified the values of the two env vars you have listed to true
It ended up crashing the connectors pod with connection refused errors. Could you please help me understand a bit more about your configuration, and why you need these env vars to be set to true
Also I am not sure what consequences would arrive for the connectors component if the two env vars you listed are not present when the none condition is satisfied in the _helpers.tpl file

Commenting with some additional context for what I believe might be a similar use case to where the OP is coming from.
What I would like to do:
Enable inbound connectors for a local cluster while keeping identity at enabled: false.
I tried the following:
connectors:
  enabled: true
  # inbound:
  #   mode: "disabled"
  env:
    - name: CAMUNDA_CONNECTOR_POLLING_ENABLED
      value: "true"
    - name: CAMUNDA_CONNECTOR_WEBHOOK_ENABLED
      value: "true"

After helm upgrade I got a second *-connectors-* pod that kept crashing with the following error:
s.c.c.OperateClientProdAutoConfiguration : An attempt to connect to Operate failed: ...
I'd assume that there's 1 *-connectors-* pod each for in- and outbound connectors and that it was the inbound pod that kept crashing.
A rollback (helm rollback camunda-platform 0) restored my prior working state and removed the 2nd *-connectors-* pod.
All of the above leave me with the question whether or not inbound connectors can be used this way (i.e. without keycloak etc.) at all. And if not, could we maybe get some kind of override for local installations that would make it possible based on the minimal identity.enabled = false config from the docs?

Thanks for the input @ttntm.
The connector team got back saying that the values fo both env vars are already true by default as you can see here. The values in the values.yaml can override these variables.
I am getting the same error you are getting after trying the same:
2023-11-17T09:51:12.571Z  WARN 1 --- [           main] s.c.c.OperateClientProdAutoConfiguration : An attempt to connect to Operate failed: io.camunda.operate.exception.OperateException: org.apache.hc.client5.http.HttpHostConnectException: Connect to http://localhost:8081/ [localhost/<IP_ADDRESS>] failed: Connection refused

The variable responsible for connecting to operate is here. It is referencing localhost. I'm trying to see if that is the correct address that it should be referencing.

I ran the platform with the default values. I added the above env vars with the inbound mode set to oauth and it worked successfully. This isn't really a surprise since identity is enabled and the two env vars are set to to true by default.
I wonder what will happen if I disabled identity and set inbound mode to credentials? If the pod runs successfully, I can then add the two above env vars and check if it still successfully runs.

Seems like the connector pod does not successfully run when the inbound mode is either credentials or oauth
@lukas-beumer could you please send the full values.yaml you use for this use-case?

Hi @lukas-beumer,
Out of curiosity, why cannot you use:
connectors:
  enabled: true
  inbound:
    mode: credentials

?
The original intention was to support environments that can access operate with basic authentication, like demo/demo. To set up credentials, you can use environment variables CAMUNDA_OPERATE_CLIENT_USERNAME=demo and CAMUNDA_OPERATE_CLIENT_PASSWORD=demo.
Also, on a side note, when the connectors.inbound.mode=disabled Connectors still should be running but without inbound capabilities, like webhook or polling, however, outbound connectors, such as REST should work fine.

@igpetrov Thank you for your answer! The problem with inbound.mode = "credentials", my environment variables would no longer be duplicated, but then CAMUNDA_OPERATE_CLIENT_USERNAME, because this is already set with "credentials". In other words, I always have problems here.
The reason why we want to set the two parameters to "true" is that we use the Kafka Connectors as an entry point in our process models, which always has to actively search for new messages in the Kafka topic. And this is not possible if CAMUNDA_CONNECTOR_POLLING_ENABLED is set to false.

Coming back to this, I got inbound connectors working using the recommended changes to the helm chart:
connectors:
  enabled: true
  inbound:
    mode: "credentials"
    auth:
      existingSecret: "demo"
  env:
    - name: CAMUNDA_OPERATE_CLIENT_USERNAME
      value: "demo"
    - name: CAMUNDA_OPERATE_CLIENT_PASSWORD
      value: "demo"

Setting existingSecret to a value other than ""was done because helm complained about it. I had to use the --force flag when running helm upgrade eventually though, but I did not notice any undesired results of doing that so far.
NB: I only tested the inbound webhook connector so far and that one's working (i.e. url -X POST -H "Content-Type: application/json" -d '{"myId": 123456, "myMessage": "Hello, world!"}' http://localhost:8088/inbound/test-webhook)

That's the exact problem. We don't want to use --force always. Thats because helm doesn't allow double defined environment variables.

I think this is no longer an issue because of #1297 .  The PR makes it so that configmaps are used primarily, rather than environment variables, so we shouldn't run into any situations where the env var is duplicated.
I also think this means we can close the draft PR https://github.com/camunda/camunda-platform-helm/pull/1158
@hamza-m-masood , could you verify?

I should also clarify, that #1297 is not yet in a release. just fixed on latest main

@lukas-beumer ,
If I understand this correctly,
you set your connectors.inbound.mode to disabled to avoid the environment variable duplication with the CAMUNDA_CONNECTOR_POLLING_ENABLED and CAMUNDA_CONNECTOR_WEBHOOK_ENABLED flags.  When you set connectors.inbound.mode to credentials,  you have environment variable duplication problems  due to the CAMUNDA_OPERATE_CLIENT_USERNAME option, because you have configured it to use a different username other than connectors.
I believe after the referenced PR #1297  is made into a release,  the best course of action would be to go back to setting connectors.inbound.mode back to credentials and then to set CAMUNDA_OPERATE_CLIENT_USERNAME to the username you want to override that setting with.
Also, I recognize now that this issue is a little old, so if this isn't a problem for you anymore, no worries. :sweat_smile:

@igpetrov @theburi   Do you have thoughts on whether we should support the unauthenticated inbound connector flow directly in the helm chart ?  The current workflows are to route authentication through identity,  authenticating via static credentials for situations where identity is disabled,  and disabling inbound connectors entirely.  The proposal here is for being able to make requests that aren't protected by authentication.

it seems to be a valid configuration.
The question is how to support it in Helm. connectors.inbound.mode is Helm-defined value. (Correct me if we have this spec in Connectors.)
I think it's fair to define it as connectors.inbound.mode: ignore

Using the credentials inbound mode and overriding the OPERATE_PASSWORD with demo works for us. No duplicated envs needed anymore. Thanks!

Hi @lukas-beumer
I have identity disabled and my values.yaml is below:
connectors:
  enabled: true
  inbound:
    mode: "credentials"
    auth:
      existingSecret: "demo"
  env:
    - name: CAMUNDA_OPERATE_CLIENT_USERNAME
      value: "demo"

Getting a 403 error. Error Message: Response not successful: 403
Could you pls confirm if inbound is working on connectors?


Switch RDS log exporter lambda to Python 3.8 + cleanup.

Make it work with Python 3.8.
Increase the timeout so that in case it runs slowly for any reason, it'll be less likely to fail and never recover because after a failed run there would be an ever-increasing set of files to copy. (It only writes the timestamp file at the end of a successful run; it doesn't save intermediate progress.)
Fix the instructions in the README so that it's possible to test locally.
Format to PEP8, remove unused imports, fix lint errors and poorly-written conditionals.
Simplify the logic and remove some redundant variables.
Simplify error handling and include the original error messages from the API so the messages are more informative as to what failed.
Use a buffer instead of concatenating immutable strings on every read.
Start decomposing the logic into functions (only factored out one function so far but it's a start).
Add a couple of tests.

This still isn't what I would consider production-grade because of the lack of tests, but at least it's in a much better state than before.
Tested:

Fairly extensive manual testing in the integration account using sam local invoke RDSLogsToS3 -e event.json (see README) that the behaviour is still the same as before. Tested both the first-run (no timestamp file) case and the incremental (timestamp file exists so only copy newer files).
The unit tests are passing (for what they're worth). They only cover reading the timestamp file though.

Looks like nothing is using these logs (couldn't find anything in our repos and Cybersecurity says they're not using them either). So let's just get rid of this and switch on RDS logging to CloudWatch instead. The volume is single-digits GB/month so the ingestion cost is negligible.


Background color does not match the design

Describe the bug
https://github.com/near/neardevhub-widgets/blob/37f3fd9f4add94584c3a20ef962194d22aef950d/src/devhub/components/templates/AppLayout.jsx#L8
I believe it has to be #f4f4f4, and it looks better with this color than the current one.
To Reproduce
Steps to reproduce the behavior:

Go to https://neardevhub.org
Notice that the background does not match the design

Resolved in https://github.com/near/neardevhub-widgets/pull/393


merge package template from arlac77/npm-package-template

package.json

chore(devDependencies): remove<EMAIL_ADDRESS>chore(devDependencies): remove<EMAIL_ADDRESS>chore(devDependencies): add<EMAIL_ADDRESS>from template
chore(devDependencies): update<EMAIL_ADDRESS>from template
chore(scripts): update prepare@rollup -c from template
chore(scripts): update docs@documentation readme src/kronos-cluster-node.js --section=API from template
chore(scripts): add lint@documentation lint src/kronos-cluster-node.js from template

.travis.yml

chore(travis): merge from template .travis.yml

README.md

docs(README): update from template

Coverage remained the same at 73.077% when pulling e8c5eb1d752e0aad2a436847917bded8f4cc7224 on template-sync-1 into c227ca43d407e982da6377e092f69f055039d003 on master.


fixed #1064

Please change the title to be descriptive of the changes you have made.
Also state which issues, if any, that this PR closes in the description each on its own line. For example: closes #1337


Automatic PR of restapi_auto_waynekuo_master into dev

Created to sync https://github.com/Azure/azure-rest-api-specs/pull/2383

Closing for now, in response to #1057. These changes will be incorporated shortly.


CUDA out of memory for H100 80GB for lmms-lab/llama3-llava-next-8b

Installed via pip in python 3.10 as readme says, then ran:
export CUDA_VISIBLE_DEVICES=1
python -m sglang.launch_server --model-path lmms-lab/llama3-llava-next-8b --tokenizer-path lmms-lab/llama3-llava-next-8b-tokenizer --port=30000 --host="<IP_ADDRESS>" --tp-size=1 --api-key='62224bfb-c832-4452-81e7-8a4bdabbe164'  --random-seed=1234 --context-length=8192

nothing is on GPU=1, only GPU=0 is filled.
Always hit very early on startup, model not even loaded yet:
  File "/home/ubuntu/miniconda3/envs/sglang/lib/python3.10/site-packages/sglang/srt/models/llama2.py", line 39, in __init__
    self.gate_up_proj = MergedColumnParallelLinear(
  File "/home/ubuntu/miniconda3/envs/sglang/lib/python3.10/site-packages/vllm/model_executor/layers/linear.py", line 333, in __init__
    super().__init__(input_size, sum(output_sizes), bias, gather_output,
  File "/home/ubuntu/miniconda3/envs/sglang/lib/python3.10/site-packages/vllm/model_executor/layers/linear.py", line 236, in __init__
    self.quant_method.create_weights(self,
  File "/home/ubuntu/miniconda3/envs/sglang/lib/python3.10/site-packages/vllm/model_executor/layers/linear.py", line 81, in create_weights
    weight = Parameter(torch.empty(output_size_per_partition,
  File "/home/ubuntu/miniconda3/envs/sglang/lib/python3.10/site-packages/torch/utils/_device.py", line 78, in __torch_function__
    return func(*args, **kwargs)
torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 224.00 MiB. GPU

Initialization failed. detoken_init_state: init ok

I can't believe >80GB needed for this model.
Using CVD "1,2" and -tp-size=2 starts and downloads the model, but seems to get stuck and never gets done loading weight for rank 0.
/home/ubuntu/miniconda3/envs/sglang/lib/python3.10/site-packages/huggingface_hub/file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
  warnings.warn(
/home/ubuntu/miniconda3/envs/sglang/lib/python3.10/site-packages/transformers/models/llava/configuration_llava.py:100: FutureWarning: The `vocab_size` argument is deprecated and will be removed in v4.42, since it can be inferred from the `text_config`. Passing this argument has no effect
  warnings.warn(
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
server started on [<IP_ADDRESS>]:10004
server started on [<IP_ADDRESS>]:10005
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
accepted ('<IP_ADDRESS>', 41688) with fd 36
welcome ('<IP_ADDRESS>', 41688)
accepted ('<IP_ADDRESS>', 48486) with fd 32
welcome ('<IP_ADDRESS>', 48486)
/home/ubuntu/miniconda3/envs/sglang/lib/python3.10/site-packages/transformers/models/llava/configuration_llava.py:140: FutureWarning: The `vocab_size` attribute is deprecated and will be removed in v4.42, Please use `text_config.vocab_size` instead.
  warnings.warn(
/home/ubuntu/miniconda3/envs/sglang/lib/python3.10/site-packages/transformers/models/llava/configuration_llava.py:140: FutureWarning: The `vocab_size` attribute is deprecated and will be removed in v4.42, Please use `text_config.vocab_size` instead.
  warnings.warn(
NCCL version 2.20.5+cuda12.4
Rank 1: load weight begin.
Rank 0: load weight begin.
config.json: 100%|???????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????| 4.76k/4.76k [00:00<00:00, 41.2MB/s]
pytorch_model.bin: 100%|??????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????| 1.71G/1.71G [00:05<00:00, 319MB/s]
Using model weights format ['*.safetensors']
model-00001-of-00004.safetensors: 100%|???????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????| 4.98G/4.98G [00:07<00:00, 636MB/s]
model-00002-of-00004.safetensors: 100%|???????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????| 5.00G/5.00G [00:06<00:00, 798MB/s]
model-00003-of-00004.safetensors: 100%|???????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????| 4.92G/4.92G [00:06<00:00, 750MB/s]
model-00004-of-00004.safetensors: 100%|???????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????| 1.82G/1.82G [00:04<00:00, 383MB/s]
Using model weights format ['*.safetensors']
Rank 1: load weight end.

SGLang seems to be trying to go onto CVD=0 no matter the CVD settings:
|=======================================================================================|
|    0   N/A  N/A   4006212      C   /opt/conda/bin/python3.10                 73028MiB |
|    0   N/A  N/A   4051262      C   python                                     8188MiB |
|    1   N/A  N/A   4051266      C   python                                     9952MiB |
+---------------------------------------------------------------------------------------+

dang, typo on my end.

按照自述文件所述通过 python 3.10 中的 pip 安装，然后运行：
export CUDA_VISIBLE_DEVICES=1
python -m sglang.launch_server --model-path lmms-lab/llama3-llava-next-8b --tokenizer-path lmms-lab/llama3-llava-next-8b-tokenizer --port=30000 --host="<IP_ADDRESS>" --tp-size=1 --api-key='62224bfb-c832-4452-81e7-8a4bdabbe164'  --random-seed=1234 --context-length=8192

GPU=1 上没有任何内容，只有 GPU=0 被填充。
总是在启动时很早就点击，模型甚至还没有加载：
  File "/home/ubuntu/miniconda3/envs/sglang/lib/python3.10/site-packages/sglang/srt/models/llama2.py", line 39, in __init__
    self.gate_up_proj = MergedColumnParallelLinear(
  File "/home/ubuntu/miniconda3/envs/sglang/lib/python3.10/site-packages/vllm/model_executor/layers/linear.py", line 333, in __init__
    super().__init__(input_size, sum(output_sizes), bias, gather_output,
  File "/home/ubuntu/miniconda3/envs/sglang/lib/python3.10/site-packages/vllm/model_executor/layers/linear.py", line 236, in __init__
    self.quant_method.create_weights(self,
  File "/home/ubuntu/miniconda3/envs/sglang/lib/python3.10/site-packages/vllm/model_executor/layers/linear.py", line 81, in create_weights
    weight = Parameter(torch.empty(output_size_per_partition,
  File "/home/ubuntu/miniconda3/envs/sglang/lib/python3.10/site-packages/torch/utils/_device.py", line 78, in __torch_function__
    return func(*args, **kwargs)
torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 224.00 MiB. GPU

Initialization failed. detoken_init_state: init ok

我不敢相信这个型号需要 >80GB。
使用 CVD "1,2" 和 -tp-size=2 启动并下载模型，但似乎陷入困境并且永远无法完成加载等级 0 的权重。
/home/ubuntu/miniconda3/envs/sglang/lib/python3.10/site-packages/huggingface_hub/file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
  warnings.warn(
/home/ubuntu/miniconda3/envs/sglang/lib/python3.10/site-packages/transformers/models/llava/configuration_llava.py:100: FutureWarning: The `vocab_size` argument is deprecated and will be removed in v4.42, since it can be inferred from the `text_config`. Passing this argument has no effect
  warnings.warn(
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
server started on [<IP_ADDRESS>]:10004
server started on [<IP_ADDRESS>]:10005
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
accepted ('<IP_ADDRESS>', 41688) with fd 36
welcome ('<IP_ADDRESS>', 41688)
accepted ('<IP_ADDRESS>', 48486) with fd 32
welcome ('<IP_ADDRESS>', 48486)
/home/ubuntu/miniconda3/envs/sglang/lib/python3.10/site-packages/transformers/models/llava/configuration_llava.py:140: FutureWarning: The `vocab_size` attribute is deprecated and will be removed in v4.42, Please use `text_config.vocab_size` instead.
  warnings.warn(
/home/ubuntu/miniconda3/envs/sglang/lib/python3.10/site-packages/transformers/models/llava/configuration_llava.py:140: FutureWarning: The `vocab_size` attribute is deprecated and will be removed in v4.42, Please use `text_config.vocab_size` instead.
  warnings.warn(
NCCL version 2.20.5+cuda12.4
Rank 1: load weight begin.
Rank 0: load weight begin.
config.json: 100%|???????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????| 4.76k/4.76k [00:00<00:00, 41.2MB/s]
pytorch_model.bin: 100%|??????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????| 1.71G/1.71G [00:05<00:00, 319MB/s]
Using model weights format ['*.safetensors']
model-00001-of-00004.safetensors: 100%|???????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????| 4.98G/4.98G [00:07<00:00, 636MB/s]
model-00002-of-00004.safetensors: 100%|???????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????| 5.00G/5.00G [00:06<00:00, 798MB/s]
model-00003-of-00004.safetensors: 100%|???????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????| 4.92G/4.92G [00:06<00:00, 750MB/s]
model-00004-of-00004.safetensors: 100%|???????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????| 1.82G/1.82G [00:04<00:00, 383MB/s]
Using model weights format ['*.safetensors']
Rank 1: load weight end.

May I ask where the problem occurred and how it was resolved? I have the same problem as you initially had

I had misspelled "CUDA_VISIBLE_DEVICES" and it was still running on a GPU that was consumed already.


Add support for components to wasmtime run --invoke

You can currently call a core module export with wasmtime run --invoke <func> <module.wasm> [params...], but using --invoke with components is not supported.
While it should (presumably) be fairly straightforward to add support for invoking nullary functions, it would be much more useful to be able to pass arguments, which brings up the challenge of encoding complex parameter values. I have developed a component model value encoding (and library) called WAVE which could be used for this.
I see a few ways that WAVE could be used here:

The simplest extension of the existing feature would just add WAVE parsing for params:
wasmtime run --invoke my-func component.wasm '"arg1"' 2 '[3,4]'
A variation of this could allow "undelimited" values (which would require further spec/implementation work), e.g.:
wasmtime run --invoke my-func component.wasm arg1 2 3,4
A more radical change would be to change the way arguments are passed to look more like a "normal" function call, which might help with some confusion with the existing --invoke syntax:
wasmtime run --invoke 'my-func("arg1", 2, [3, 4])' component.wasm
Make some other even more radical (breaking, probably) change to how --invoke works

I have implemented a prototype of the "function call" encoding option 3, though I would actually prefer the "undelimited" option 2 if the params could appear immediately after the function name.

Another open question here would be how to reference functions that aren't top-level exports, e.g. something like wasi:cli/run@0.2.0-rc-2023-11-05::run(), though hopefully we can have something a little nicer than that.

I think adding this is a great idea, and I like the idea of having a well-defined encoding for types-to-strings-and-back like WAVE, so I'm all for this 👍. As to the bikesheddy details, I'm down to defer to you and see how it plays out over time, these are all six-to-one-half-dozen to me.

I think adding this is a great idea, and I like the idea of having a well-defined encoding for types-to-strings-and-back like WAVE, so I'm all for this 👍. As to the bikesheddy details, I'm down to defer to you and see how it plays out over time, these are all six-to-one-half-dozen to me.

six-of-one
Is there any update on this issue?

While it should (presumably) be fairly straightforward to add support for invoking nullary functions, it would be much more useful to be able to pass arguments, which brings up the challenge of encoding complex parameter values. I have developed a component model value encoding (and library) called WAVE which could be used for this.

If it's too difficult to implement full parameter passing from the CLI, what about just supporting nullary (and possibly integer) functions for now?


is it working with angularJS, any example ?

Yes why not
See here for some examples how you can call it.
I am not used to AngularJS so I have no example availble


text widgets overflowing from credit card in credit card page

i will submit a pr for this issue

it also causes the issue in landscape mode cause we are defining hight as 1/3 of the screen we should make it of a constant height

The app is not yet optimized for landscape mode and I opened this
orientation just to see how many users actually use it. Regarding the
overflow pixels, that needs to be fixed so I'll fix it in the next update.
On Wed 19 Sep, 2018, 8:38 AM Parth Jansari<EMAIL_ADDRESS>wrote:

it also causes the issue in landscape mode cause we are defining hight as
1/3 of the screen we should make it of a constant height
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
https://github.com/iampawan/Flutter-UI-Kit/issues/15#issuecomment-422634509,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AMCOnFPmDiIj5CUVRd7kfzAOUKcSVJCsks5ucbVKgaJpZM4WvVBx
.

then should we use a fixed height for the card or increase the ratio from 0.3 to 0.4

Fixed


Publish to live

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webcord: revert to electron_25, fix #254539

Fixes #254539.
Electron 26 has a bug which causes the app to not display properly. The fix for now is to revert back to 25, until 27 is released, which fixes this issue.
See SpacingBat3/WebCord#452 and electron/electron#39515
Description of changes

Things done

Built on platform(s)

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

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

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

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[x] Tested basic functionality of all binary files (usually in ./result/bin/)
23.11 Release Notes (or backporting 23.05 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module

[x] Fits CONTRIBUTING.md.

Result of nixpkgs-review pr 254588 run on x86_64-linux 1

2 packages built:

webcord
webcord-vencord


[firebase_core]: not working with cocoapods 1.15.2

Is there an existing issue for this?

[X] I have searched the existing issues.

Which plugins are affected?
Core, Messaging
Which platforms are affected?
Android, iOS
Description
I got an error when run pod update in my flutter project:
Updating local specs repositories
Analyzing dependencies
firebase_core: Using Firebase SDK version '10.24.0' defined in 'firebase_core'
firebase_messaging: Using Firebase SDK version '10.24.0' defined in 'firebase_core'
[!] CDN: trunk URL couldn't be downloaded: https://cdn.jsdelivr.net/cocoa/Specs/0/3/5/Firebase/10.25.0/Firebase.podspec.json Response: SSL peer certificate or SSH remote key was not OK

[!] Automatically assigning platform `iOS` with version `12.0` on target `Runner` because no platform was specified. Please specify a platform for this target in your Podfile. See `https://guides.cocoapods.org/syntax/podfile.html#platform`.

Reproducing the issue
In pubspec.yaml, I added:
flutter_local_notifications: ^17.1.1
firebase_core: ^2.30.1
firebase_messaging: ^14.9.1

Then I go to ios folder and run pod update command
I have tried with pod install --repo-update too
Then I got above issue
Firebase Core version
2.30.1
Flutter Version
3.19.6
Relevant Log Output
Updating local specs repositories
Analyzing dependencies
firebase_core: Using Firebase SDK version '10.24.0' defined in 'firebase_core'
firebase_messaging: Using Firebase SDK version '10.24.0' defined in 'firebase_core'
[!] CDN: trunk URL couldn't be downloaded: https://cdn.jsdelivr.net/cocoa/Specs/0/3/5/Firebase/10.25.0/Firebase.podspec.json Response: SSL peer certificate or SSH remote key was not OK

[!] Automatically assigning platform `iOS` with version `12.0` on target `Runner` because no platform was specified. Please specify a platform for this target in your Podfile. See `https://guides.cocoapods.org/syntax/podfile.html#platform`.

Flutter dependencies

Expand Flutter dependencies snippet

Dart SDK 3.3.4
Flutter SDK 3.19.6
mytestapp 1.0.0+1

dependencies:
- carousel_slider 4.2.1 [flutter]
- connectivity_plus 6.0.3 [flutter flutter_web_plugins connectivity_plus_platform_interface web meta nm collection]
- cupertino_icons 1.0.8
- firebase_core 2.30.1 [firebase_core_platform_interface firebase_core_web flutter meta]
- firebase_messaging 14.9.1 [firebase_core firebase_core_platform_interface firebase_messaging_platform_interface firebase_messaging_web flutter meta]
- flutter 0.0.0 [characters collection material_color_utilities meta vector_math sky_engine]
- flutter_local_notifications 17.1.1 [clock flutter flutter_local_notifications_linux flutter_local_notifications_platform_interface timezone]
- go_router 14.0.2 [collection flutter flutter_web_plugins logging meta]
- html 0.15.4 [csslib source_span]
- image_picker 1.1.1 [flutter image_picker_android image_picker_for_web image_picker_ios image_picker_linux image_picker_macos image_picker_platform_interface image_picker_windows]
- mobile_scanner 5.0.2 [flutter flutter_web_plugins plugin_platform_interface web]
- provider 6.1.2 [collection flutter nested]
- shared_preferences 2.2.3 [flutter shared_preferences_android shared_preferences_foundation shared_preferences_linux shared_preferences_platform_interface shared_preferences_web shared_preferences_windows]
- url_launcher 6.2.6 [flutter url_launcher_android url_launcher_ios url_launcher_linux url_launcher_macos url_launcher_platform_interface url_launcher_web url_launcher_windows]

dev dependencies:
- flutter_lints 3.0.2 [lints]
- flutter_test 0.0.0 [flutter test_api matcher path fake_async clock stack_trace vector_math leak_tracker_flutter_testing async boolean_selector characters collection leak_tracker leak_tracker_testing material_color_utilities meta source_span stream_channel string_scanner term_glyph vm_service]

transitive dependencies:
- _flutterfire_internals 1.3.32 [collection firebase_core firebase_core_platform_interface flutter meta]
- args 2.5.0
- async 2.11.0 [collection meta]
- boolean_selector 2.1.1 [source_span string_scanner]
- characters 1.3.0
- clock 1.1.1
- collection 1.18.0
- connectivity_plus_platform_interface 2.0.0 [flutter meta plugin_platform_interface]
- cross_file 0.3.4+1 [meta web]
- csslib 1.0.0 [source_span]
- dbus 0.7.10 [args ffi meta xml]
- fake_async 1.3.1 [clock collection]
- ffi 2.1.2
- file 7.0.0 [meta path]
- file_selector_linux 0.9.2+1 [cross_file file_selector_platform_interface flutter]
- file_selector_macos 0.9.3+3 [cross_file file_selector_platform_interface flutter]
- file_selector_platform_interface 2.6.2 [cross_file flutter http plugin_platform_interface]
- file_selector_windows 0.9.3+1 [cross_file file_selector_platform_interface flutter]
- firebase_core_platform_interface 5.0.0 [collection flutter flutter_test meta plugin_platform_interface]
- firebase_core_web 2.16.0 [firebase_core_platform_interface flutter flutter_web_plugins meta web]
- firebase_messaging_platform_interface 4.5.34 [_flutterfire_internals firebase_core flutter meta plugin_platform_interface]
- firebase_messaging_web 3.8.4 [_flutterfire_internals firebase_core firebase_core_web firebase_messaging_platform_interface flutter flutter_web_plugins meta web]
- flutter_local_notifications_linux 4.0.0+1 [dbus ffi flutter flutter_local_notifications_platform_interface path xdg_directories]
- flutter_local_notifications_platform_interface 7.1.0 [flutter plugin_platform_interface]
- flutter_plugin_android_lifecycle 2.0.19 [flutter]
- flutter_web_plugins 0.0.0 [flutter characters collection material_color_utilities meta vector_math]
- http 1.2.1 [async http_parser meta web]
- http_parser 4.0.2 [collection source_span string_scanner typed_data]
- image_picker_android 0.8.11 [flutter flutter_plugin_android_lifecycle image_picker_platform_interface]
- image_picker_for_web 3.0.4 [flutter flutter_web_plugins image_picker_platform_interface mime web]
- image_picker_ios 0.8.10+1 [flutter image_picker_platform_interface]
- image_picker_linux 0.2.1+1 [file_selector_linux file_selector_platform_interface flutter image_picker_platform_interface]
- image_picker_macos 0.2.1+1 [file_selector_macos file_selector_platform_interface flutter image_picker_platform_interface]
- image_picker_platform_interface 2.10.0 [cross_file flutter http plugin_platform_interface]
- image_picker_windows 0.2.1+1 [file_selector_platform_interface file_selector_windows flutter image_picker_platform_interface]
- leak_tracker 10.0.0 [clock collection meta path vm_service]
- leak_tracker_flutter_testing 2.0.1 [flutter leak_tracker leak_tracker_testing matcher meta]
- leak_tracker_testing 2.0.1 [leak_tracker matcher meta]
- lints 3.0.0
- logging 1.2.0
- matcher 0.12.16+1 [async meta stack_trace term_glyph test_api]
- material_color_utilities 0.8.0 [collection]
- meta 1.11.0
- mime 1.0.5
- nested 1.0.0 [flutter]
- nm 0.5.0 [dbus]
- path 1.9.0
- path_provider_linux 2.2.1 [ffi flutter path path_provider_platform_interface xdg_directories]
- path_provider_platform_interface 2.1.2 [flutter platform plugin_platform_interface]
- path_provider_windows 2.2.1 [ffi flutter path path_provider_platform_interface win32]
- petitparser 6.0.2 [meta]
- platform 3.1.4
- plugin_platform_interface 2.1.8 [meta]
- shared_preferences_android 2.2.2 [flutter shared_preferences_platform_interface]
- shared_preferences_foundation 2.3.5 [flutter shared_preferences_platform_interface]
- shared_preferences_linux 2.3.2 [file flutter path path_provider_linux path_provider_platform_interface shared_preferences_platform_interface]
- shared_preferences_platform_interface 2.3.2 [flutter plugin_platform_interface]
- shared_preferences_web 2.3.0 [flutter flutter_web_plugins shared_preferences_platform_interface web]
- shared_preferences_windows 2.3.2 [file flutter path path_provider_platform_interface path_provider_windows shared_preferences_platform_interface]
- sky_engine 0.0.99
- source_span 1.10.0 [collection path term_glyph]
- stack_trace 1.11.1 [path]
- stream_channel 2.1.2 [async]
- string_scanner 1.2.0 [source_span]
- term_glyph 1.2.1
- test_api 0.6.1 [async boolean_selector collection meta source_span stack_trace stream_channel string_scanner term_glyph]
- timezone 0.9.3 [path]
- typed_data 1.3.2 [collection]
- url_launcher_android 6.3.1 [flutter url_launcher_platform_interface]
- url_launcher_ios 6.2.5 [flutter url_launcher_platform_interface]
- url_launcher_linux 3.1.1 [flutter url_launcher_platform_interface]
- url_launcher_macos 3.1.0 [flutter url_launcher_platform_interface]
- url_launcher_platform_interface 2.3.2 [flutter plugin_platform_interface]
- url_launcher_web 2.3.1 [flutter flutter_web_plugins url_launcher_platform_interface web]
- url_launcher_windows 3.1.1 [flutter url_launcher_platform_interface]
- vector_math 2.1.4
- vm_service 13.0.0
- web 0.5.1
- win32 5.5.0 [ffi]
- xdg_directories 1.0.4 [meta path]
- xml 6.5.0 [collection meta petitparser]

Additional context and comments
No response

same issue, cocoapods issue.
related ticket maybe help https://github.com/jsdelivr/jsdelivr/issues/18565
maybe the question, how to update the url ?

source 'https://github.com/CocoaPods/Specs.git'
You can add the .

Seems it happened with all GoogleML kit

@thuydtshop - this seems like an issue with your setup rather than FlutterFire. For instance, you're installing firebase iOS 10.24.0 yet you have a failure downloading firebase iOS 10.25.0. See:
[!] CDN: trunk URL couldn't be downloaded: https://cdn.jsdelivr.net/cocoa/Specs/0/3/5/Firebase/10.25.0/Firebase.podspec.json Response: SSL peer certificate or SSH remote key was not OK

You seem to have a source different than what I would expect. If you run pod repo, what do you get? I have:
cocoapods
- Type: git (remotes/origin/master)
- URL:  https://github.com/CocoaPods/Specs.git
- Path: /Users/russellwheatley/.cocoapods/repos/cocoapods

trunk
- Type: CDN
- URL:  https://cdn.cocoapods.org/
- Path: /Users/russellwheatley/.cocoapods/repos/trunk

You could also try downgrading cocoapods but I don't suspect it is because of your cocoapods version.

I am currently experiencing the same issue.

Having the same issue, app crashes

@hrithikm2 Can you open another issue with reproduction steps if you still facing this issue?

It's sloved. I think because cdn down last time (for the url)


Autorest Regen Preview to 3.0.0-alpha.20231031.8 by Dapeng Zhang from refs/pull/3894/merge

Triggered from https://github.com/Azure/autorest.csharp/pull/3894

API change check
API changes are not detected in this pull request.


Feat smartmeter set tariff on meter

connects to osgp/platform#243

All is well.

https://github.com/OSGP/Platform/issues/243

All is well.

All is well.

All is well.

All is well.


Select: feature proposal

I often find myself that I want to use the select component to select for an array of objects. Then I have to create something like {1: "label_1", 2: "label_2",... } with the keys corresponding to the index of the original array of objects. It would be much easier to pass the objects as options and specify a key for the labels. and on select e.target.value would hold the selected object.
Is that something that could be in the rmwc package or should this be left to the developer? Or am I missing something and there is a ways easier solution already in place?

right now we can pass options in 3 ways

as an array which will be used as both the label and value ['One', 'Two', 'Three']
an object of value -> label {one: 'One', two: 'Two', three: 'Three}
directly as children

<Select
  value={text('value', 'Cookies')}
  onChange={evt => action('onChange: ' + evt.target.value)()}
>
  <ListItem role="option" id="Cookies" tabIndex="0">
    Cookies
  </ListItem>
  <ListItem role="option" id="Pizza" tabIndex="-1" aria-disabled="true">
    Pizza
  </ListItem>
  <ListItem role="option" id="Icecream" tabIndex="0">
    Icecream
  </ListItem>
</Select>

There is some work that needs to be done to improve the select handling, by I have no issue with supporting a variety of common ways to populate the select. Your case makes sense, I can see about adding it.
Related to #44 #43

Oh, didn't read carefully enough through the issues, sorry. I think it's best to close this and continue in #44.


Make possible to use Terraform init -reconfigure

I didn't find a way or issue here mentioning a way to pass -reconfigure into TF init.
https://github.com/gruntwork-io/terratest/blob/09df87fed520518a32aa8423a70258a312e475fc/modules/terraform/options.go#L40-L71
Terraform reconfigure makes easy to fix issues in the backend
https://www.terraform.io/docs/cli/commands/init.html#backend-initialization

Seems reasonable to add a new option for to configure it! We are a bit buried with other initiatives, so most likely won't get to implement this anytime soon, but happy to review a PR if you are up for it.

Since terraform v0.15.4 behavior on terraform init has changed. If init now encounters a change to the stored backend configuration, it will always return an error when neither -reconfigure or -migrate-state is supplied. This change was merged in https://github.com/hashicorp/terraform/pull/28718 . PR to add this missing options has been raised see: https://github.com/gruntwork-io/terratest/pull/923


Tooltip on line chart is not working correctly

Use the try it out online page and set syntax to:
data('sample:US States.csv') line y(dem_rep) x(population) tooltip(#all)
It doesn't matter which part of the line you hover over, the tooltip is always the same.

The tooltip currently shows an arbitrary value.  This is a defect.
However, a line generally has one tooltip.  Would it be possible to use both points and line to show tooltips for each value.  Note, you can use styles to make the points invisible.

Here's a way to do this, hiding the points:
line x(population) y(dem_rep) + x(population) y(dem_rep) tooltip(#all) style('opacity:0;size:20px')

Thanks Dan and Graham! I will use both a line and a point and show the point at 6px. The problem with invisible points is that it would be difficult for the user to know where to hover to get a tooltip.

On the development branch I have modified the code for tooltips to allow exactly the desired behavior without the need for invisible points. However, it can be quite hard to hover exactly over the line, so it may be advisable still to use that method

Thanks Graham!


Update the Ollama for hosting in notebook

This updates the details to include how to run Ollama server from within notebook.

Hi @hickeyma, I'm currently converting this recipe to use Replicate. The idea is to have all recipes written using Replicate by default, with a one-cell copy-and-paste from LLMs with Langchain to switch to Ollama (or WatsonX) for the LLM.

I'm currently converting this recipe to use Replicate

Isn't replicate a paid service for which recipe users will need to setup an account and pay? I would think a using ollama for free on their workstation or even in colab would be more inclusive.

Yea, we need to add the adr about why we're supporting replicate, not ollama. And why ollama isn't supposed to be in the notebooks.

The replicate_api_token is not included in the ollama notebooks, that's why this is failing.
Again, I don't think this is the way we want to go, but if we do well need a new test workflow that supports ollama AND replicate, but getting away from that is why we broke them up...

Thank you for the contribution @hickeyma . We've decided a while ago that setting up ollama in the notebook created too much clutter, I can refer you to some notebooks where we removed it if you would like to see the implementation. Ollama has a major draw back of only supporting smaller models on most standard machines, while Replicate supports larger models via API call. We understand the hesitancy of paying for usage of large GPUs, and have secured a deal with Replicate to give users free credit. @adampingel can give more details.
If you would like create a notebook that starts ollama as an example, you'll need to create a new workflow (see example, be sure to change the paths to only reference your new example, and to create a textfile with the same path) (I know the two text file thing is hacky, I'll be working on that today, it was an expedient solution).

@hickeyma here is the PR where I've replaced Ollama with Replicate in the Text_to_Shell recipe.
I think this was the first recipe written, so it also needed some updating to more fully embrace Langchain.


Validate step

Need to validate step process and proceed to next step only if validation has passed

Need to validate step process and proceed to next step only if validation has passed

Did you find a solution ?

Implemented in v1.2.0. Thank you.


Update types to properly reflect Cypress commands returning jQuery objects

Fixes #39 by correcting TypeScript definitions.
Checklist:

[x] Documentation N/A
[x] Tests
[x] Ready to be merged

cc @airato who contributed the previous type definitions

Thanks for this! I don't currently use the typescript typings, so I'd prefer to have someone else review this as well.

hi @simenbrekken! thanks for the PR!
I'm wondering if these helpers actually return jQuery collections or not, since it uses dom-testing-library underneath, which doesn't use jQuery
https://github.com/kentcdodds/dom-testing-library/blob/dea7b7bd94dd4332e1e031929cdf01a15ac225a4/src/query-helpers.js#L39-L50

@airato Did you verify this behavior after authoring the types? After converting my own tests from plain cy.get(…) to using the matchers from this package I'm getting jQuery objects from all the commands.

@simenbrekken unfortunately I don't quite remember. But according to this, Cypress wraps all DOM elements with their own jQuery, so it should be fine
https://github.com/cypress-io/cypress/blob/07c915c6521257a8729358582f3cba65148ec1c2/packages/driver/src/cypress/cy.coffee#L302-L310
One thing though, Cypress's own jQuery is v2.2.4, so need to figure out which version of @types/jquery to install with this library, and how it would work out if consumer of this lib have some other version of jquery types installed

Interestingly Cypress Docs mention the return type for elements as "DOM element", while it seems to be jQuery wrapped DOM element
https://docs.cypress.io/api/commands/get.html#Yields

https://docs.cypress.io/guides/core-concepts/introduction-to-cypress.html#Cypress-is-Not-Like-jQuery

Maybe it worth creating and issue in cypress repo to figure this out and maybe fix the documentation

@simenbrekken @airato regarding the version of the jQuery typings, I think we could say that the APIs typically used in Cypress are very stable, so are less likely to need changes. My own usage tends to be reading off the state of certain attributes such as disabled.
I know this approach comes with some risks, but what do you think?

@aaronmcadam I don't really know if there is a way to use 2 different versions of the @types/jquery in one project. That would solve this issue.
One somewhat hacky way I can see is for Cypress to make a copy of jquery types in Cypress repo for the version of jquery that's bundled with Cypress, and make sure it doesn't declare it's types in global somehow. End result we should look for with this approach - when we use bundled jquery, we get correct types.
Otherwise, I think it's okay to have maybe "@types/jquery": "*" as dependency for this package, it's better than nothing

@airato I agree with setting the version of the types to *. As I say, I doubt they have changed the core APIs that most tests would use

@simenbrekken do you have time to pick this up again soon? I'm happy to make the jQuery types change if we think that's the way forward. I wonder if we could reach out to @bahmutov from the Cypress team for his opinion on this.

@aaronmcadam Sorry for the late reply. My project has since switched to another E2E library so I haven't been able to verify or work on this issue. I'll see if I can get around to producing a test-case but my schedule is quite busy before summer so I can't really make any promises.

@simenbrekken would you mind if I took over this work instead?

@aaronmcadam That would be great! Thanks for stepping in.

#56 supersedes this.


测试时遇到ValueError: not enough values to unpack (expected 8, got 7)问题

Traceback (most recent call last):
File "test.py", line 145, in
main()
File "test.py", line 142, in main
trainer.evaluation()
File "test.py", line 88, in evaluation
img, _, gt, idx, gt_hcam, gt_pitch, imgname, _ = batch
ValueError: not enough values to unpack (expected 8, got 7)

解决办法是

解决方法是将：
img, _, gt, idx, gt_hcam, gt_pitch, imgname, _ = batch
修改为
img, gt, idx, gt_hcam, gt_pitch, imgname, _ = batch


Replace Google Group with Github Discussions

Github is becoming more and more the "everything and the kitchen sink" platform for software development. One new feature is Github Discussions: https://docs.github.com/en/discussions .
I'm thinking it might be a good idea to switch our main user forum over to that from Google groups. It has several advantages:

everything in one place
easy linking to issues and code samples
if anybody creates an issue ticket that really should be a question, we can do a one-click transfer.
it offers both "discussion" style forums as well as more "Q&A" style interactions

Possible downsides:

it requires a github account to participate
~2. it does not allow interaction via e-mail~ EDIT this is perhaps not right, I think it may be possible to reply to e-mail notifications from discussion via mail (similar to how this works for issues) - I haven't tested this yet though.
it's in beta, which means there may be bugs
it's relatively unknown, which means it may be hard to find/figure out for our users

I'm also not sure if the EMO has any views on the use of this as opposed to the more classical mailinglist, but before I bother them with I thought I'd sound you all out first. Any thoughts?
If you want to have a play, I've created a throwaway test repo with dicussions enabled, see https://github.com/jeenbroekstra/test-github/discussions

Of course, another option we have is to start using the Eclipse Forum at https://www.eclipse.org/forums/index.php/f/316/ .
It's a little old-fashioned perhaps but it's hosted and maintained for us, and seems easy enough to use.

@eclipse/technology-rdf4j-committers I'd like to hear your opinions on this.
I'm personally inclined to just do it. I find the Google group painful to work with, myself. But I'd prefer not to make this decision unless I have some support from others :)

I have not tried the GitHub based forum before. I'm very open to new things though as I find Google Groups to be absolutely terrible on mobile!

Request to enabled logged at https://bugs.eclipse.org/bugs/show_bug.cgi?id=573860

Discussions are enabled, but we've hit a problem: I should be able to post in announcements category as maintainer, but for some reason I can't. This looks like a bug at Github's side. See https://github.com/github/feedback/discussions/4063 .

Bug is fixed. We're up and running. We'll trial for a while in parallel and once we're confident we'll shut down the Google group.
I'll add a link to our support page.


Setting Global Timeouts beyond 60000 causes 500 error

When we set:
betweenBytesTimeout
firstByteTimeout
connectTimeout

to 180000 from 60000 the Compute experienced complete failure.  According to the Fastly documentation, this value can go up to<PHONE_NUMBER> as per the documentation here: https://js-compute-reference-docs.edgecompute.app/docs/fastly:experimental/allowDynamicBackends#parameters

I believe the reason we diagnosed before with changes on this service was that changing these options can result in the Fastly compute systems overloading your backend itself causing failures.
Previously I believe @ulyssa discussed the fix to this being better controlling / restricting the concurrent connections made to your backend across the network to avoid overloading it.

Yes, it is possible when increasing the connection or other backend timeout that all of the spots available for a given service get used up by instances of the service waiting on something to hit the backend. If they hit the max guest runtime (~120s) then they'll get killed and a 5xx error will be generated for them.
When dealing with origin requests that might take a while to send a body, as long as it returns the response headers then you can send the response body handle and exit the guest. (I'm not entirely sure what this looks like in the JS SDK, but @guybedford may be able to point you at an example.) This then frees up the guest slot and its memory and allows handling a new incoming request while the response gets streamed in the background.

We didn't see any increase of connections at the origin.  In fact, we saw the opposite, nothing was getting through at all.

Do you have a test service that you use here? Can you replicate the issue on the test service with a single request? Are you able to check the error logs for that 500 request to determine the 500 error data?

This was the original error from the Compute.  I'll setup a test next weekend.
stdout | b3c222fb | Error: DOMException { code: 19, message: "HTTP response timeout", name: "NetworkError", INDEX_SIZE_ERR: 1, DOMSTRING_SIZE_ERR: 2, HIERARCHY_REQUEST_ERR: 3, WRONG_DOCUMENT_ERR: 4, INVALID_CHARACTER_ERR: 5, NO_DATA_ALLOWED_ERR: 6, NO_MODIFICATION_ALLOWED_ERR: 7, NOT_FOUND_ERR: 8, NOT_SUPPORTED_ERR: 9, INUSE_ATTRIBUTE_ERR: 10, INVALID_STATE_ERR: 11, SYNTAX_ERR: 12, INVALID_MODIFICATION_ERR: 13, NAMESPACE_ERR: 14, INVALID_ACCESS_ERR: 15, VALIDATION_ERR: 16, TYPE_MISMATCH_ERR: 17, SECURITY_ERR: 18, NETWORK_ERR: 19, ABORT_ERR: 20, URL_MISMATCH_ERR: 21, QUOTA_EXCEEDED_ERR: 22, TIMEOUT_ERR: 23, INVALID_NODE_TYPE_ERR: 24, DATA_CLONE_ERR: 25 }
Not very informative unfortunately as to the true cause.

This is exactly the error for the timeout triggering. Yes a test setup would help to check it is the expected timeout behaviour.


Twitter login support

DO NOT REMOVE OR SKIP THE ISSUE TEMPLATE

[X] I understand that I will be blocked if I intentionally remove or skip any mandatory* field

Checklist

[X] I'm requesting a feature unrelated to a specific site
[X] I've looked through the README
[X] I've verified that I'm running yt-dlp version 2023.03.04 (update instructions) or later (specify commit)
[X] I've searched known issues and the bugtracker for similar issues including closed ones. DO NOT post duplicates
[X] I've read the guidelines for opening an issue

Provide a description that is worded well enough to be understood
twitter currently does not have specific support for credential authentication.
Provide verbose output that clearly demonstrates the problem

[X] Run your yt-dlp command with -vU flag added (yt-dlp -vU <your command line>)
[X] If using API, add 'verbose': True to YoutubeDL params instead
[X] Copy the WHOLE output (starting with [debug] Command-line config) and insert it below

Complete Verbose Output
[debug] Command-line config: ['-vU', '--username', 'PRIVATE', '--password', 'PRIVATE', 'https://twitter.com/ShitpostGate/status/1651904099749699590']
[debug] User config "C:\Users\japri\AppData\Roaming\yt-dlp\config.txt": ['--downloader', 'aria2c']
[debug] Encodings: locale cp1252, fs utf-8, pref cp1252, out utf-8, error utf-8, screen utf-8
[debug] yt-dlp version<EMAIL_ADDRESS>[4d9280c9c] (win_exe)
[debug] Python 3.8.10 (CPython AMD64 64bit) - Windows-10-10.0.19045-SP0 (OpenSSL 1.1.1k  25 Mar 2021)
[debug] exe versions: ffmpeg n6.0-7-gadb4688bfb-20230316 (setts), ffprobe n6.0-7-gadb4688bfb-20230316
[debug] Optional libraries: Cryptodome-3.17, brotli-1.0.9, certifi-2022.12.07, mutagen-1.46.0, sqlite3-2.6.0, websockets-11.0.2
[debug] Proxy map: {}
[debug] Loaded 1810 extractors
[debug] Fetching release info: https://api.github.com/repos/yt-dlp/yt-dlp-nightly-builds/releases/latest
Available version<EMAIL_ADDRESS>Current version<EMAIL_ADDRESS>Current Build Hash: 5f6363a11a63e1ed08553785fa7704f5207bfb1be4639a80f05f67cc4f4e4976
yt-dlp is up to date<EMAIL_ADDRESS>WARNING: [twitter] Login with password is not supported for this website. Use --cookies-from-browser or --cookies for the authentication. See  https://github.com/yt-dlp/yt-dlp/wiki/FAQ#how-do-i-pass-cookies-to-yt-dlp  for how to manually pass cookies
[twitter] Extracting URL: https://twitter.com/ShitpostGate/status/1651904099749699590
[twitter]<PHONE_NUMBER>749699590: Downloading guest token
[twitter]<PHONE_NUMBER>749699590: Downloading JSON metadata
[debug] [twitter] Extracting from video info:<PHONE_NUMBER>675703809
[twitter]<PHONE_NUMBER>749699590: Downloading m3u8 information
[debug] Sort order given by extractor: res, br, size, proto
[debug] Formats sorted by: hasvid, ie_pref, res, tbr, vbr, abr, filesize, fs_approx, proto, lang, quality, fps, hdr:12(7), vcodec:vp9.2(10), channels, acodec, asr, vext, aext, hasaud, source, id
[debug] Default format spec: bestvideo*+bestaudio/best
[info]<PHONE_NUMBER>675703809: Downloading 1 format(s): http-950
[debug] Invoking aria2c downloader on "https://video.twimg.com/ext_tw_video/1651747074675703809/pu/vid/480x600/-yNzlUc4KXyR40kE.mp4?tag=12"
[download] ShitpostGateway - https：⧸⧸t.co⧸uvHY9r5noW [1651747074675703809].mp4 has already been downloaded
[download] 100% of  226.24KiB

This one's a lot harder to implement than Reddit's login. The website uses a multi-step login flow, and the 2nd step requires POST JSON data with multiple parameters (I am assuming are generated by the javascript) looking like this:
"response": {
  "rf": {
    "e5ba13d8c9a2c1de100f11e8dc7b3d08a5a77ac8f485b1a3fdbb9b3e969b2d5e": -62,
    "ca7b4cc404b09126894cd257f10ca0be610a769d23c568a3de19dad7163836c3": -10,
    "a1a33537de11bf80c8e2a77cb08e71de90e694ac9d14e2681182527025d88f56": -11,
    "ad66f8a765857badba52d26ac4f38c637fd170b1e1d29e6af022697ab265790d": 8
  },
  "s": "MlsKpre5bmN65UMb5tB078IAZ6PN8eOp_MgnTy4mnQUOZWwMw-4qQkus0NGgPmLj8PHxasopFX2_2ndeqdPliz3eODvKdZXaqUanwFHOwIdoZKus6WtzoN9fPY5tP7rGkU7M-xuUmc9Wieof0a_b1UyYrvnGkPJbv56PtjZHlV8gtnqonkbw68gvRdH3DkJaMtTo4FZL4ydpVAPk1cSQQC1PoNDrpPJDjGq3JVhfWKZe7yukyGwmXBcFo-XT_WtdfafeRoIdjOH15YOjkp9We9Sq9f0aBQ2Xl0LJepJAvg9lXsjNT7tfEPztwVFnoNXkPJCw3ADCRT6hgfM1ij6fNi9ntQawUt5K"
}

Since this would require some experimentation and a lot could go wrong, I don't want to risk my personal acct. If I had a burner/throwaway account to play around with, I might be up for digging deeper into it. But Twitter requires phone # for new accounts now

I have an old account that i don't longer use, can i pass you the credentials?

Sure, DM on discord: bashonly#4457

This would be a really handy feature to have!
Not sure whether it helps or not to point out that gallery-dl does already implement twitter auth with username and password?
Not sure the licensing situation there though

I wrote a plugin for twitter login before I knew gallery-dl had implemented it
https://github.com/bashonly/yt-dlp-TwitterLogin
I was hesitating to PR it proper because there was some anti-bot junk that made the code really ugly/messy, but my takeaway from gallery-dl's implementation is that a simple '{}' can be passed in place of the anti-bot parameters. (I see the new owner is really "taking care of the bot problem"). So I'll see about cleaning up the code some more and opening a PR for this


ghcide: panic! dynamic linker not initialised

In VisualStudio code using the ghcide plugin I get this problem at startup
ghcide: panic! (the 'impossible' happened)
  (GHC version 8.6.5 for x86_64-apple-darwin):
	Dynamic linker not initialised

Please report this as a GHC bug:  http://www.haskell.org/ghc/reportabug

Looking at the exe/Main.hs the version I am using was built against the head two days ago and
this line seems to be present
    initDynLinker env

The problem seems to correct itself after a while -- maybe ghcide --lsp server re-starts itself... any pointers? Could there be multiple copies of ghcide involved? How does this all work if there are different versions of ghc in use in projects?
ghcide runs ok in the (only) project at issue here. I'll see if I can track this down a bit.

That code in GHC looks horrific... but it seems like in 8.8 all threads will synchronise on the state of the dynamic linker and I guess this issue has all the hallmarks of just the non-determinism one would expect from such a bug. It also points to the observation that the GHC compiler was never intended to be used as it now is. I bet this is fraught with problems... especially memory management of all that horrible state. You guys deserve medals if you can make this work for an ide.

I guess we can close this as an "upstream" problem. ;-)

Not entirely sure it’s an upstream problem simply because I tend to blame my own code first but if it isn’t it’s probably a duplicate of #28 so we can close it either way :slightly_smiling_face: If we still encounter it with 8.8 it probably deserves a deeper investigation.


Fix mouse wheel events being eaten on ComboBox on browser

What does the pull request do?
This fixes an issue I noticed where if you have enough items in a ComboBox on browser to have a scrollbar, scrolling is ignored. It forces the user to drag the scrollbar.
What is the current behavior?
Due to https://github.com/AvaloniaUI/Avalonia/issues/2285, every time a mouse wheel event occurs, the event is eaten if the TopLevel is the same then the ComboBox. This works fine on Desktop platforms because the PopUp is a PopUpRoot which has its own TopLevel so the 2 TopLevels should never be the same otherwise the aforementioned issue occurs.
This however doesn't work with browser because there's only one TopLevel being the WebEmbeddableControlRoot and the PopUp is actually an OverlayPopupHost which doesn't have its own TopLevel. What this meant is that this check actually eats every mouse wheel events.
What is the updated/expected behavior with this PR?
After a lot of testing, I found that the original issue is actually not reproducible on browser, only on desktops. It seems the popup itself prevents the outer views to get scrolled. I am not sure why exactly, but considering I can't reproduce the issue that justified this code, it's probably okay. FYI, this is the original PR: https://github.com/AvaloniaUI/Avalonia/pull/2287
How was the solution implemented (if it's not obvious)?
Simply add an additional condition to have this input eating behavior to not do it if the popup is an OverlayPopupHost.
Checklist

[ ] Added unit tests (if possible)?
[ ] Added XML documentation to any related classes?
[ ] Consider submitting a PR to https://github.com/AvaloniaUI/Documentation with user documentation

Breaking changes
None.
Obsoletions / Deprecations
None.
Fixed issues
No issue was filed for this, I investigated this myself and found I could file the PR directly. If this is a problem, I could file an issue.

You can test this PR using the following package version. 11.0.999-cibuild0033671-beta. (feed url: https://pkgs.dev.azure.com/AvaloniaUI/AvaloniaUI/_packaging/avalonia-all/nuget/v3/index.json) [PRBUILDID]

Not sure if relying on OverlayPopupHost is the best solution.
In the future we might switch to "native" popups on browser backend by creating a new canvas for each popup. This way there avalonia overlay layer won't be used.

Not sure if relying on OverlayPopupHost is the best solution. In the future we might switch to "native" popups on browser backend by creating a new canvas for each popup. This way there avalonia overlay layer won't be used.

Would checking if it is a PopupRoot be a better solution then? This way, only PopUpRoot will have this event handler which implicitly would not include the overlay one.

Can I get an update if this is what I should try to do?

@maxkatz6 ping.

Since this fix doesn't require any breaking changes and can be pushed later, I keep postponing the review of this PR. Sorry about that.
As I stated above, relying on OverlayPopup in the controls code isn't the best solution. Probably redoing part of #2287 is better.
For now what I found, the same issue is reproducible on desktop as well, if you enable overlay popups in BuildAvaloniaApp builder:
.With(new Win32PlatformOptions()
{
    OverlayPopups = true
})

Actually, I don't think I can reproduce that issue from #2287 now. If I add combobox to each listbox item, scrolling is properly handled on combobox instead of listbox, even without that hack with top level handling.
Possibly light dismiss layer does the job now?

@aldelaro5 after discussion with @grokys it seems to be safe to remove that old hack with toplevel wheel handling.

@aldelaro5 after discussion with @grokys it seems to be safe to remove that old hack with toplevel wheel handling.

To clarify, is that what my pr was doing or it's a completely different solution?

@aldelaro5 OverlayHost check is a hack on top of an old hack. A safer solution seems to just remove an old hack as it's not needed anymore. I.e. removing the whole AddDisposableHandler(PointerWheelChangedEvent) block.

@maxkatz6 There, I removed it and made sure it was still fixing the issue.

You can test this PR using the following package version. 11.0.999-cibuild0035491-beta. (feed url: https://pkgs.dev.azure.com/AvaloniaUI/AvaloniaUI/_packaging/avalonia-all/nuget/v3/index.json) [PRBUILDID]

Hum, what happened? it passed the CI for auto merge, but failed the CI for the actual merge?

@aldelaro5 must be a fluke, typical with ours CI


build bug in branch foxy

System Info

OS

[e.g. Ubuntu 20.04]

ROS version and installation type

[e.g. foxy/binary, rolling/source]

RTI Connext DDS version and installation type

[e.g. Pro 5.3.1/apt, Micro 3.0.3/rtipkg]

RMW version or commit hash

[e.g. 44cbdc3f45365890921195cf8ed10aaea9633270]

Bug Description
In branch foxy,the parameters of function DDS_DataReader_return_loan_untypedI() are too many when RTI_DDS_VERSION_MAJOR  > 7.
The parameter data_len should be removed.
Expected Behavior
Successfully compiled.
How to Reproduce
git switch foxy
colcon build --symlink-install

Workarounds
The parameter data_len should be removed.

Ths package isn't supported in Foxy, so it isn't too surprising that it failed.  I'll suggest updating to one of the supported distributions (I can recommend Humble), and trying again.


Swift 2.0 Branch + Use of undeclared type '...'

Hi,
I'm using CocoaLumberjack 2.0.1 of the Swift 2.0 branch in my project.
I install it with Pods here is the line in my PodFile
pod 'CocoaLumberjack/Swift', :git => "https://github.com/CocoaLumberjack/CocoaLumberjack.git", :branch => 'swift_2.0'

But when i try to compile i got differents errors on the file CocoaLumberjack.swift who is in my project.

I don't understand why i got those errors that i didn't have in the previous version.
Thanks

Closing in favor of #588. Please search before opening new issues.


Crash when training RNN model - tensorflow.python.framework.errors_impl.CancelledError:  [Derived]RecvAsync is cancelled.

Please make sure that this is a bug. As per our GitHub Policy, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:bug_template
System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow): Yes
OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Elementary OS (based on Ubuntu 18.04)
Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:
TensorFlow installed from (source or binary): binary
TensorFlow version (use command below): 2.0.0 (pip install tensorflow-rocm)
Python version:3.7.5
Bazel version (if compiling from source):
GCC/Compiler version (if compiling from source):
ROCm/MIOpen version: 2.9
GPU model and memory: Vega 56 8Gb
CPU / RAM : Ryzen 5 3600 / 32 Gb Ram

Describe the current behavior
Crash shortly after training is started (in the 1st epoch): Error is the following:
tensorflow.python.framework.errors_impl.CancelledError:  [Derived]RecvAsync is cancelled.
[[{{node Adam/Adam/update/AssignSubVariableOp/_41}}]]
[[Reshape_11/_38]] [Op:__inference_distributed_function_6315]
Function call stack:
distributed_function
Describe the expected behavior
Code to reproduce the issue
This code is coming from official tensorflow tutorial here:
https://www.tensorflow.org/tutorials/text/text_classification_rnn
from __future__ import absolute_import, division, print_function, unicode_literals

import tensorflow_datasets as tfds
import tensorflow as tf

import matplotlib.pyplot as plt

def plot_graphs(history, string):
  plt.plot(history.history[string])
  plt.plot(history.history['val_'+string], '')
  plt.xlabel("Epochs")
  plt.ylabel(string)
  plt.legend([string, 'val_'+string])
  plt.show()

dataset, info = tfds.load('imdb_reviews/subwords8k', with_info=True,
                          as_supervised=True)
train_dataset, test_dataset = dataset['train'], dataset['test']

encoder = info.features['text'].encoder
print ('Vocabulary size: {}'.format(encoder.vocab_size))

sample_string = 'Hello TensorFlow.'

encoded_string = encoder.encode(sample_string)
print ('Encoded string is {}'.format(encoded_string))
original_string = encoder.decode(encoded_string)
print ('The original string: "{}"'.format(original_string))
assert original_string == sample_string
for index in encoded_string:
  print ('{} ----> {}'.format(index, encoder.decode([index])))

BUFFER_SIZE = 10000
BATCH_SIZE = 64

train_dataset = train_dataset.shuffle(BUFFER_SIZE)
train_dataset = train_dataset.padded_batch(BATCH_SIZE, train_dataset.output_shapes)

test_dataset = test_dataset.padded_batch(BATCH_SIZE, test_dataset.output_shapes)

model = tf.keras.Sequential([
    tf.keras.layers.Embedding(encoder.vocab_size, 64),
    tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(64)),
    tf.keras.layers.Dense(64, activation='relu'),
    tf.keras.layers.Dense(1, activation='sigmoid')
])

model.compile(loss='binary_crossentropy',
              optimizer=tf.keras.optimizers.Adam(1e-4),
              metrics=['accuracy'])

history = model.fit(train_dataset, epochs=10,
                    validation_data=test_dataset,
                    validation_steps=30)

Other info / logs
The issue seems to be GPU related. If I run the same code on a tensorflow 2.0.0 without rocm, the code runs on the CPU and it does not crash

Just a few more infos. I realised that my linux was running a 5.XX kernel which is not not supported according to ROCM 2.9 installation guide.
So I tried to runt he same code on a Ubuntu 18.04 with a 4.15.66 kernel (and ROCM 2.9 dkms installed).
I get the exact same error message than aboce:
The error message in the first post is the end of it, it however looks like the row below is actually the first row causing the the error.
2019-11-02 21:00:45.034231: W tensorflow/core/framework/op_kernel.cc:1622] OP_REQUIRES failed at cudnn_rnn_ops.cc:1491 : Unimplemented: createRnnDescriptor is unimplemented
What is strange, is that I can run ANN and CNN succesfully, but the 2 times I tries to run an RNN/LSTM, it fails with mentionning that something RNN related is unimplemented. The code runs fine with CPU only.

Hi @mfrey777 , thank you for reporting this issue, we'll try to repro it locally and let you know.

Confirmed the error message locally, assigning to @jerryyin  to take a deeper look.

Just a few more infos. I realised that my linux was running a 5.XX kernel which is not not supported according to ROCM 2.9 installation guide.
So I tried to runt he same code on a Ubuntu 18.04 with a 4.15.66 kernel (and ROCM 2.9 dkms installed).
I get the exact same error message than aboce:
The error message in the first post is the end of it, it however looks like the row below is actually the first row causing the the error.
2019-11-02 21:00:45.034231: W tensorflow/core/framework/op_kernel.cc:1622] OP_REQUIRES failed at cudnn_rnn_ops.cc:1491 : Unimplemented: createRnnDescriptor is unimplemented
What is strange, is that I can run ANN and CNN succesfully, but the 2 times I tries to run an RNN/LSTM, it fails with mentionning that something RNN related is unimplemented. The code runs fine with CPU only.

the same error in issue#33721, AniTho  said 'the problem was solved after downgrading tensorflow to 1.14' ，it would occur in TF2.0. And if you run on cpu ,it won't crash

Just a few more infos. I realised that my linux was running a 5.XX kernel which is not not supported according to ROCM 2.9 installation guide.
So I tried to runt he same code on a Ubuntu 18.04 with a 4.15.66 kernel (and ROCM 2.9 dkms installed).
I get the exact same error message than aboce:
The error message in the first post is the end of it, it however looks like the row below is actually the first row causing the the error.
2019-11-02 21:00:45.034231: W tensorflow/core/framework/op_kernel.cc:1622] OP_REQUIRES failed at cudnn_rnn_ops.cc:1491 : Unimplemented: createRnnDescriptor is unimplemented
What is strange, is that I can run ANN and CNN succesfully, but the 2 times I tries to run an RNN/LSTM, it fails with mentionning that something RNN related is unimplemented. The code runs fine with CPU only.

the same error in issue#33721,you may need to update the cuda to 7.6.2,Use TF_FORCE_GPU_ALLOW_GROWTH=true to force allow GPU growth

Just a few more infos. I realised that my linux was running a 5.XX kernel which is not not supported according to ROCM 2.9 installation guide.
So I tried to runt he same code on a Ubuntu 18.04 with a 4.15.66 kernel (and ROCM 2.9 dkms installed).
I get the exact same error message than aboce:
The error message in the first post is the end of it, it however looks like the row below is actually the first row causing the the error.
2019-11-02 21:00:45.034231: W tensorflow/core/framework/op_kernel.cc:1622] OP_REQUIRES failed at cudnn_rnn_ops.cc:1491 : Unimplemented: createRnnDescriptor is unimplemented
What is strange, is that I can run ANN and CNN succesfully, but the 2 times I tries to run an RNN/LSTM, it fails with mentionning that something RNN related is unimplemented. The code runs fine with CPU only.

the same error in issue#33721,you may need to update the cuda to 7.6.2,Use TF_FORCE_GPU_ALLOW_GROWTH=true to force allow GPU growth, the detail in
https://stackoverflow.com/questions/58359153/cancellederror-derived-recvasync-is-cancelled

Thank you, I also found that post on stackoverflow, but adding that parameter did not help. I tried in 2 different ways, first in the code:
gpus = tf.config.experimental.list_physical_devices('GPU')
for gpu in gpus:
tf.config.experimental.set_memory_growth(gpu, True)
and then to export the variable in the shell, but that did not work either.
I am still getting the same error message.
I was however confused by the Cuda Version part of that past, as I thouth that ROCM was the Cude equivalent for AMD. Do I need to install some Cuda drivers ?

@mfrey777 Thank you for opening the issue. Apparently this is caused by us letting behind a commit in the 2.0.0 release branch. This will be fixed in 2.1.0. At the same time, could you give rocm/tensorflow-autobuilds:rocm2.8-f4df78b image a shot?

$ docker pull rocm/tensorflow-autobuilds:rocm2.8-f4df78b
$ alias drun='sudo docker run -it --network=host --device=/dev/kfd --device=/dev/dri --group-add video --cap-add=SYS_PTRACE --security-opt seccomp=unconfined'
$ drun rocm/tensorflow-autobuilds:rocm2.8-f4df78b
# Execute the script inside this docker container.

Let me know if you run into any issues.

Thank your for the quick reply. I executing my script in the docker container and it does run, but it does run slower than when I run it with CPU (on a not ROCM Tensorflow 2.0).
Epoch 1 took 541s on the docker image (with GPU enabled, so a Vega 56 8Gb)

Running the same code a TF 2.0 (without gpu acceleration) runs about twice as fast (253 s)

I tried to run a simple text classification to compare runtimes, so another tutorial from the TF 2.0 website: https://www.tensorflow.org/tutorials/keras/text_classification_with_hub
local Ubuntu 18.04 / Python 3.7.5 / ROCM 2.9 / TF 2.0 upstream

CPU: 90ms/step
GPU: 78ms/step
docker image
GPU: 66ms/step

So the GPU is actually a faster than the CPU

Your task involves a lot of small operations and the gains from using a GPU are outweighed by the overhead associated with launching each GPU operation. And I think there's some room for improvement in the ROCm stack.
With a Vega 64 / Ryzen 7 1700x, I see 405 s/epoch as in the original post, but 274 s/epoch at batch size 128 (larger batch size - fewer individual ops - less overhead). Unfortunately, it won't go much higher than 128 because it runs out of memory.
Profiling data for the script:

"Name","Calls","TotalDurationNs","AverageNs","Percentage"
"Op2dTensorLite",67925,574807248,8462,24.5170400952
"Cijk_Ailk_Bljk_SB_MT128x64x8_SE_APM1_AF0EM1_AF1EM1_AMAS0_ASEM1_BL0_DTL0_EPS0_FL0_GRVW1_GSU1_ISA000_IU1_K1_KLS_LPA0_LPB0_LDL1_MGWVW1_NLCA1_NLCB1_PK0_PGR0_PLR0_RK0_SU32_SNLL0_TT8_4_USFGRO0_VAW1_VW1_WG16_16_1_WGM8",7018,482528072,68755,20.581090669
"Cijk_Ailk_Bjlk_SB_MT128x128x8_SE_APM1_AF0EM1_AF1EM1_AMAS0_ASEM1_BL0_DTL0_EPS0_FL0_GRVW1_GSU1_ISA000_IU1_K1_KLS_LPA0_LPB0_LDL1_MGWVW1_NLCA1_NLCB1_PK0_PGR0_PLR0_RK0_SU32_SNLL0_TT8_8_USFGRO0_VAW1_VW1_WG16_16_1_WGM8",21,354002416,16857257,15.0991335914
"Cijk_Alik_Bljk_SB_MT128x64x12_SE_APM1_AF0EM1_AF1EM1_AMAS0_ASEM1_BL0_DTL0_EPS0_FL0_GRVW1_GSU1_ISA000_IU1_K1_KLS_LPA0_LPB0_LDL1_MGWVW1_NLCA3_NLCB3_PK0_PGR1_PLR1_RK0_SU32_SNLL0_TT8_4_USFGRO0_VAW1_VW1_WG16_16_1_WGM8",8628,290601231,33681,12.3949063915
"MIOpenActiveFwd2DLite",25847,240416872,9301,10.254411563
"Op2dTensorSquash",5,189359114,37871822,8.07666397123
"MIOpenActiveBwd2DLite",21031,177073549,8419,7.55265232951
"void (anonymous namespace)::hip_fill_n<256u, unsigned int*, unsigned long, unsigned int>(unsigned int*, unsigned long, unsigned int)",48,12642428,263383,0.539232786738

Rows 1, 5, 6, 7 are internal MIOpen helper functions. Rows 2, 3, 4 are GEMM operations:

./rocblas-bench -f gemm_ex --transposeA T --transposeB N -m 256 -n 64 -k 64 --alpha 1 --a_type f32_r --lda 64 --b_type f32_r --ldb 384 --beta 1 --c_type f32_r --ldc 384 --d_type f32_r --ldd 384 --compute_type f32_r --algo 0 --solution_index 0 --flags 0
./rocblas-bench -f gemm_ex --transposeA N --transposeB N -m 64 -n 64 -k 256 --alpha 1 --a_type f32_r --lda 64 --b_type f32_r --ldb 384 --beta 1 --c_type f32_r --ldc 384 --d_type f32_r --ldd 384 --compute_type f32_r --algo 0 --solution_index 0 --flags 0

mostly tiny (256x64 * 64x64) and executing in ~30 us or less.

Thank you for the detailed explanation, i makes more sense to me now.

having the same bug on my device when I using keras.layers.LSTM

2019-11-18 04:36:20.298226: W tensorflow/core/framework/op_kernel.cc:1622] OP_REQUIRES failed at cudnn_rnn_ops.cc:1491 : Unimplemented: createRnnDescriptor is unimplemented
2019-11-18 04:36:20.298246: W tensorflow/core/common_runtime/base_collective_executor.cc:216] BaseCollectiveExecutor::StartAbort Unimplemented: createRnnDescriptor is unimplemented

when I used tf.compat.v1.keras.layers.LSTM or tf.keras.layers.RNN, it worked fine ,except it was very slow,actually as slow as training on a CPU, and I deeply doubt that the program was running on CPU.
here is a comment on https://tensorflow.google.cn/api_docs/python/tf/keras/layers/LSTM?hl=en

Based on available runtime hardware and constraints, this layer will choose different implementations (cuDNN-based or pure-TensorFlow) to maximize the performance. If a GPU is available and all the arguments to the layer meet the requirement of the CuDNN kernel (see below for details), the layer will use a fast cuDNN implementation.

rocm-dkms  version 2.9.6

python version 3.6

Linux version 5.3.11-050311-generic

TensorFlow version (use command below): 2.0.0 (pip install tensorflow-rocm)

GPU model and memory: Radeon vii  16Gb

OS Platform and Distribution :Ubuntu 18.04.3 LTS

@mfrey777 Thank you for opening the issue. Apparently this is caused by us letting behind a commit in the 2.0.0 release branch. This will be fixed in 2.1.0. At the same time, could you give rocm/tensorflow-autobuilds:rocm2.8-f4df78b image a shot?

$ docker pull rocm/tensorflow-autobuilds:rocm2.8-f4df78b
$ alias drun='sudo docker run -it --network=host --device=/dev/kfd --device=/dev/dri --group-add video --cap-add=SYS_PTRACE --security-opt seccomp=unconfined'
$ drun rocm/tensorflow-autobuilds:rocm2.8-f4df78b
Execute the script inside this docker container.

Let me know if you run into any issues.

@jerryyin Hi, which changes solves the problem? I've tested the image rocm/tensorflow-autobuilds:rocm2.8-f4df78b and it works. But I've tested it on a computer with AVX, now I need to make it work on a computer without AVX instructions. Do I need to compile a specific commit from this repo or the official one ?


ImportError: No module named '_signal'

Can trigger with the following:
import signal

Error:
  File "/switch/PyNX/lib/python3.5/signal.py", line 1, in <module>
    import _signal
ImportError: No module named '_signal'

As I recall switch's os does not have signals, so there is no point in
using signal module
On Wed, Aug 8, 2018, 5:44 AM Niema Moshiri<EMAIL_ADDRESS>wrote:

Can trigger with the following:
import signal
Error:
File "/switch/PyNX/lib/python3.5/signal.py", line 1, in
import _signal
ImportError: No module named '_signal'
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
https://github.com/nx-python/PyNX/issues/9, or mute the thread
https://github.com/notifications/unsubscribe-auth/AIlQWRtUq9PXjEFSxhqJ9-2bFmapTv_jks5uOiZVgaJpZM4VzDZj
.

I was trying to set up pyftpdlib to try to have a PyNX-backed FTP server

You will have to manually remove every usage of subprocess and signal modules in the source


⚠ Jenkins Plugins Artifactory has degraded performance

In 55d7364, Jenkins Plugins Artifactory (https://get.jenkins.io/plugins/artifactory/) experienced degraded performance:

HTTP code: 200
Response time: 1373 ms

Resolved: Jenkins Plugins Artifactory performance has improved in 07c6c38 after 18 minutes.


bug: Casdoor Provider for Okta broken

The provider for Okta seems to be broken. When configured as described in the docs here: https://casdoor.org/docs/provider/oauth/okta
The login with the credentials of the okta user (calling the /v1/authorize endpoint) seems to be working correctly but when casdoor is trying to call /v1/token right before calling the callback url of the application the following error occurred: There was a problem signing you in. Post “/v1/token”: unsupported protocol scheme “”
This error looks a lot like it originates from faulty or empty hosturl. We were able to workaround this problem by using a custom provider with the following urls:
Auth URL: https://dev-123456.okta.com/oauth2/default/v1/authorize
Token URL: https://dev-123456.okta.com/oauth2/default/v1/token
UserInfo URL: https://dev-123456.okta.com/oauth2/default/v1/userinfo

@julzds did you provide the domain parameter? It should be something like:

See docs: https://casdoor.org/docs/provider/oauth/okta/

Hi @hsluoyz,
yes I configured the provider as described in the docs and used the domain of our dev account at okta which looks like this: https://dev-123456.okta.com/oauth2/default


fix: change the task name of the component rating

What type of PR is this?
/kind bug

What this PR does / why we need it
fix: change the task name of the component rating
Which issue(s) this PR fixes

Fixes #
Special notes for your reviewer

@0xff-dev should we also hardcode our pipeline names ?

@0xff-dev should we also hardcode our pipeline names ?

I think it's fine, kubebb-core should only be deployed once.


Fixes various Line2D and Polygon2D editor bugs

See https://github.com/godotengine/godot/issues/15097
Also found and fixed two other bugs I introduced in the Line2D editor refactoring.

Also should fix

https://github.com/godotengine/godot/issues/15096
display of previous outlines (got broken)
line thickness on retina displays


tailspin: 2.2.0 -> 2.3.0

Signed-off-by: Muhammad Falak R Wani<EMAIL_ADDRESS>Description of changes
Diff: https://github.com/bensadeh/tailspin/compare/2.2.0...2.3.0
Changelog: https://github.com/bensadeh/tailspin/blob/2.3.0/CHANGELOG.md

Things done

Built on platform(s)

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

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

[ ] sandbox = relaxed
[ ] sandbox = true

[ ] Tested, as applicable:

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

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[x] Tested basic functionality of all binary files (usually in ./result/bin/)
24.05 Release Notes (or backporting 23.05 and 23.11 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module

[x] Fits CONTRIBUTING.md.

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

Duplicate of #279574

Duplicate of #279574

:( data race with the bot. before creating a PR i checked .... and looks like while creating the PR bot already had a PR up :)


Support multiple firehose delivery streams

Seeing as Firehose only supports a single destination per delivery
stream, we must support multiple delivery streams in snoop to be able to
support redshift and elasticsearch at the same time. I did this by
changing the config parameter to streams which should look like this:
streams:
  - rtcstats-redshift-stream
  - rtcstats-es-stream

Note that stream is removed and this requires a config change to run
correctly.
Source for my claim is:
"A delivery stream can only be configured with a single destination,
Amazon S3, Amazon Elasticsearch Service, or Amazon Redshift. For correct
CreateDeliveryStream request syntax, specify only one destination
configuration parameter: either S3DestinationConfiguration,
ElasticsearchDestinationConfiguration, or
RedshiftDestinationConfiguration."

http://docs.aws.amazon.com/AWSJavaScriptSDK/latest/AWS/Firehose.html#createDeliveryStream-property

Definitely, but I can always add this to my own fork!

might come with an updated version that supports other things than firehose maybe :-)