Download and Install

Please provide guidance for downloading for Android in China since Google Play Services are blocked

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

ID: 640b9158-3bba-2f76-b9f1-c2660e530062
Version Independent ID: d6d2980d-b36b-9dc3-5c0c-4abed8d19ae2
Content: Download and install the Microsoft Authenticator app - Azure Active Directory
Content Source: articles/active-directory/user-help/user-help-auth-app-download-install.md
Service: active-directory
Sub-service: user-help
GitHub Login: @eross-msft
Microsoft Alias: lizross

@Breaker119 Thank you for bringing this to our notice. Please let me check this internally and we will get back to you.

@Breaker119 At present , The product group is in the process of having the Authenticator app uploaded to the most alternative app stores in china officially on Microsoft channel due to google play store being banned in China. This is taking time because of multiple levels of approval from the company side as well during review process.
Alternatively The Microsoft Authenticator has been provided unofficially on the following websites as an alternative to Google Play store which is blocked in China. Please check the link to download the same.
Baidu
Tencent
Disclaimer :- Please scan the files before installing the same on your phone.
The other way of officially downloading this until our Product team published to other Chinese  android stores  is by having someone in Hong kong download the same and distribute it to mainland China users.
Also I would like to point out that in mainland China , the function of Authenticator is restricted. You can only make use of verification code, push notification is not supported. Please keep checking this page . It will soon get updated once the approval process is done and we have published the Authenticator app on any of the websites.
The PG is going to have it published on Mi app store, Huawei app store by the end of this week as per current estimates . We will now close this issue. In case you have any further query , feel free to tag me to your reply. Please keep a check on this page as this would get updated accordingly.
Hope this information helps.
Thank you .


PostAgent: basic_auth not interpolated when validating

First of all thank you for this awesome project :blush:
I think I found a problem.
During validation of the PostAgent, the basic_auth option is not interpolated, whilst it is on runtime.
This result in the impossibility of using the credentials features in the PostAgent.
thank you for your help and precious time :blush:

Thanks for report the bug and the workaround!

If I'm not mistaken, this behavior also means developers have to run extra presence checks if they are going to use an interpolated value in validation... for example, in the Weather Agent:
def wunderground?
  interpolated["service"].present? && interpolated["service"].downcase == "wunderground"
end

def openweather?
  interpolated["service"].present? && interpolated["service"].downcase == "openweather"
end

The above is necessary since validate_options uses these methods.


feat: implement new restore/bucket-metadata API

Closes #21680
Manually tested using the new CLI, can write some unit tests if desired.

Looks solid! As far as testing, I'd hope we get to the point of being able to duplicate a full backup and restore test like the existing one with the new CLI changes that would cover our testing needs. Seems like that would touch everything that the manifest mapper functions do.


run bug: TypeError: Argument 'freq' has incorrect type

Hi,  this is an error when I try to run the command "python ./experiments/run_imputation.py --config imputation/spin.yaml --model-name spin --dataset-name bay_block", and my pandas version is 1.5.3, is there an easy way to fix this?
Thanks for your help!
===============================
Global seed set to 561122547
Traceback (most recent call last):
File "./experiments/run_imputation.py", line 301, in
run_experiment(args)
File "./experiments/run_imputation.py", line 146, in run_experiment
dataset = get_dataset(args.dataset_name)
File "./experiments/run_imputation.py", line 64, in get_dataset
return add_missing_values(PemsBay(), p_fault=p_fault, p_noise=p_noise,
File "C:\ProgramData\Anaconda3\envs\spin\lib\site-packages\tsl\datasets\pems_bay.py", line 32, in init
df, dist, mask = self.load()
File "C:\ProgramData\Anaconda3\envs\spin\lib\site-packages\tsl\datasets\pems_bay.py", line 78, in load
df, dist = self.load_raw()
File "C:\ProgramData\Anaconda3\envs\spin\lib\site-packages\tsl\datasets\pems_bay.py", line 69, in load_raw
datetime_idx = sorted(df.index)
File "C:\ProgramData\Anaconda3\envs\spin\lib\site-packages\pandas\core\arrays\datetimes.py", line 590, in iter
converted = ints_to_pydatetime(
TypeError: Argument 'freq' has incorrect type (expected pandas.libs.tslibs.offsets.BaseOffset, got numpy.bytes)

Hi, I run the code with pandas version 1.4.4 and it works. However, you can change the code to make it work with your version. Lines
datetime_idx = sorted(df.index)
date_range = pd.date_range(datetime_idx[0], datetime_idx[-1], freq='5T')
df = df.reindex(index=date_range)

make the sequence regularly sampled, adding missing timestamps with nan values. You can change this sequence of instructions with
date_range = pd.date_range(df.index.min(), df.index.max(), freq='5T')
df = df.reindex(index=date_range)

or simply
df = df.asfreq('5T')

to obtain the same result.

Thanks for your quick reply! This solution works for me, however, another new issue occurs and it seems to have something to do with the pytorch-lightning version:
==================================
Traceback (most recent call last):
File "./experiments/run_imputation.py", line 301, in
run_experiment(args)
File "./experiments/run_imputation.py", line 274, in run_experiment
trainer.fit(imputer,
File "C:\ProgramData\Anaconda3\envs\spin\lib\site-packages\pytorch_lightning\trainer\trainer.py", line 740, in fit
self._call_and_handle_interrupt(
File "C:\ProgramData\Anaconda3\envs\spin\lib\site-packages\pytorch_lightning\trainer\trainer.py", line 685, in _call_and_handle_interrupt
return trainer_fn(*args, **kwargs)
File "C:\ProgramData\Anaconda3\envs\spin\lib\site-packages\pytorch_lightning\trainer\trainer.py", line 777, in _fit_impl
self._run(model, ckpt_path=ckpt_path)
File "C:\ProgramData\Anaconda3\envs\spin\lib\site-packages\pytorch_lightning\trainer\trainer.py", line 1145, in _run
self.accelerator.setup(self)
File "C:\ProgramData\Anaconda3\envs\spin\lib\site-packages\pytorch_lightning\accelerators\gpu.py", line 46, in setup
return super().setup(trainer)
File "C:\ProgramData\Anaconda3\envs\spin\lib\site-packages\pytorch_lightning\accelerators\accelerator.py", line 93, in setup
self.setup_optimizers(trainer)
File "C:\ProgramData\Anaconda3\envs\spin\lib\site-packages\pytorch_lightning\accelerators\accelerator.py", line 354, in setup_optimizers
optimizers, lr_schedulers, optimizer_frequencies = self.training_type_plugin.init_optimizers(
File "C:\ProgramData\Anaconda3\envs\spin\lib\site-packages\pytorch_lightning\plugins\training_type\training_type_plugin.py", line 245, in init_optimizers
return trainer.init_optimizers(model)
File "C:\ProgramData\Anaconda3\envs\spin\lib\site-packages\pytorch_lightning\trainer\optimizers.py", line 44, in init_optimizers
lr_schedulers = self._configure_schedulers(lr_schedulers, monitor, not pl_module.automatic_optimization)
File "C:\ProgramData\Anaconda3\envs\spin\lib\site-packages\pytorch_lightning\trainer\optimizers.py", line 192, in _configure_schedulers
raise ValueError(f'The provided lr scheduler "{scheduler}" is invalid')
ValueError: The provided lr scheduler "<spin.scheduler.CosineSchedulerWithRestarts object at 0x000001F29D41DCD0>" is invalid
And my pytorch-lightning version is 1.5.10.


Hitting error when attempting to update device:base resource

upstream: https://github.com/Juniper/terraform-provider-mist/issues/6

closed as resolved upstream


Feat(eos_cli_config_gen): Support drop command in policy-maps PBR and allow policy index

Change Summary
The old PBR rules were sorted based on the class name, which is not desired. The drop command needs to be added to the PBR rules. This drop policy might end up anywhere in the list based on it's class name. So a new knob was added that supports index (cli specific) and the rules can be added as per user requirement.

Related Issue(s)
Component(s) name
arista.avd.eos_cli_config_gen
Proposed changes
Both policy_maps.pbr and policy_maps_pbr are supported but only one should be used. The drop  knob is added to the old data-model as well, to make sure both work together. As most of the customers might be using old data model.
Old model:
policy_maps:
  pbr:
    < policy-map name >:
      classes:
        < class name >:
          # Set only one of the below actions per class
          drop: < true | false >
          set:
            nexthop:
              ip_address: < IPv4_address | IPv6_address >
              recursive: < true | false >

New model:
policy_maps_pbr:
  - name: < policy_map_name >
    classes:
      - name: < class_name >   # required
        index: < class_index > # required
        # Set only one of the below actions per class
        drop: < true | false >
        set_nexthop:
          ip_address: < IPv4_address | IPv6_address >
          recursive: < true | false >

How to test
molecule

Checklist
User Checklist

N/A

Repository Checklist

[x] My code has been rebased from devel before I start
[x] I have read the CONTRIBUTING document.
[x] My change requires a change to the documentation and documentation have been updated accordingly.
[x] I have updated molecule CI testing accordingly. (check the box if not applicable)

Adding a new model is a bit drastic. I suggest that we just remove the sorts and do arista.avd.default([]) instead. I think it is a bug that we sort.


The Slack link on README is no longer valid

The Slack link on README is no longer valid.
Could anyone update it so that new people can still join the Slack channel?

Updated.   Did not realize this needs to be changed every 30 days, that is kind of obnoxious.


Nudge users to rate the app

To collect more user feedback, we can think about nudging the user to leave a review at their app store.
Ideas:

Add an entry in the about screen saying "Rate this app" / "Bewerten Sie die App" with a link to the Google Play store / App store page.

Possibly also add an entry in the about screen for technical problems, e.g. "Sie haben Probleme mit der App?" linking to some support mail address

Use an in-app review dialog in some reasonable moments of the app usage:
GPlay In-App
iOS review request
Possibly a flutter package
There are some guidelines for using these in-app dialogs, e.g., do not ask for feedback before actually showing the app review dialog, and usually there is some quota that restricts us from showing the dialog too often.
Some ideas:

Request an app review when succesfully activating the card
Request an app review when the user has visited (and closed) the detail screen of accepting stores (a multiple of) 10 times
Request an app review when the user has verified a card successfully

We should implement some restrictions like:

Request at most once per week

i really like the idea. Just checked the flutter package and it didn't look that difficult.
We could start with an "About" entry.
After an activation would also be an option but i wouldn't push it too hard tbh


Fix no scroll on touch devices

Fixed this a while ago on an old modal library I made. Thought I could help here :) Here is a Codepen if you want an easy way to test it on a touch device.

@souporserious The new trick seems to work great in all the browsers I can access right now — so cool! As noted in comments, there are a few code changes that seem unrelated to the primary fix that I'm not sure about.
I'm thinking maybe this should be a breaking change release, since it fundamentally changes one of the two simple things this module does and I can't be 100% sure it's not going to cause a regression for somebody. Does that make sense?

Awesome! Commented back on those. I can revert it back if you need me to, just thought I could do some small optimizations while I was in there. Yeah that makes sense as a breaking change. I can update the CHANGELOG as well. Forgot about that.

@davidtheclark sorry about that. Cleaned it up.  Please let me know if you need anything else from me.

Sorry, @souporserious — I'm busier than I'm used to, so slowing down a little on side projects. Still want to merge this, but it looks like the indentation is changed now?

@davidtheclark sorry about that. Not sure what happened. Fixed now 👍

Cool, probably your editor did it or something. I will try this out again tonight then probably merge & release.

Awesome, thank you!

@souporserious When I pulled this branch down and tried it out, it worked on my desktop browsers but not on my mobile safari: that is, I was still able to scroll on mobile safari. Are you having a different experience?
(In master I set up a little script to run browser-sync that helps with this testing. May want to rebase this branch onto master to use that.)

@davidtheclark hmm I rebased and pushed. I'm unable to get it to scroll on any of my devices. I tested with my Browserstack account and on my personal iPhone 6s and was unable to get it to scroll when activated. Any specific version/sandbox you're testing on?

@souporserious I must have bundled incorrectly or something. Tried again and it worked great. Will cut a new release now.

Published in v2. Thanks again!

Thank you! Glad I was able to share that knowledge :)


[Evaluation] Tweaked some budgeting-related stuff a bit

Some simplification, no benchmarking yet.


Generate Kit for Mingw with preferred generator and environment includes

Brief Issue Summary
The cmake.mingwSearchDirs allows to find MinGw for build. But the configuration is incomplete.
Expected:
For a successful configuration and build the kit file needs the MinGw in the environment variable and optional the mingw-make as preferred generator.

This issue is created out of the research of #413.

@KoeMai do you want to get this one in 1.1.0?


⚠ Bofrost.fr has degraded performance

In 2710146, Bofrost.fr (https://www.bofrost.fr) experienced degraded performance:

HTTP code: 200
Response time: 1335 ms

Resolved: Bofrost.fr performance has improved in ee9ac5d.


[FIX] Clarify Appendix II: The list of licenses only lists examples

related to #218

Thanks @effigies, that makes it much clearer.


Any license?

What is the license for this code, public domain?

License.txt added now. It's MIT License.


Actual master

Hey - just to be clear I don't have permission to write to this repo anymore.
Try resubmitting here: https://github.com/kevinburke/bump_version.


FlippingBinary/issue83

This pull request fixes #83.

Caffeine must not have kicked in when I deleted the wrong file. I think it's right now.


SCP is broken on CentOS 8.X after kURL installs

There is an issue using kURL on CentOS 8 where libcrypto, and thus things that depend on it, such as scp may have issues
scp: error while loading shared libraries: libcrypto.so.10: cannot open shared object file: No such file or directory

For a workaround, rsync may be used instead
rsync -az [full_path_to_local_file] [username]@[hostname]:[remote_path]

fixed with https://github.com/replicatedhq/kURL/pull/582


Hygiene/single code style for all existing macros

While being not really important, had to do hygiene of all internal macros (since many of which I re-use in other places) such they now follow the same standard/coding style for all namespace prefixes (i.e. starting with :: followed by a fully-clarified name).
Also added doc strings to some of the macros

seems Travis needs reset

I restarted the timed out test.

I have rebased this onto master. Pls let me know if there any need in this.

I'm for better macro hygiene, it will also ease our life when we will update to edition 2018.
it also reduces ambiguity if you have the same type defined under different modules

ack 257ca8e504bd40b4ed13563bc8157b4c843be1fd


Revert "[GitHub Issue Templates] Removed placeholder and moved text to description"

Hey, I just made a Pull Request!
Reverts backstage/backstage#21802 as the change were made to work around a bug that GitHub has now fixed
:heavy_check_mark: Checklist

[ ] A changeset describing the change and affected packages. (more info)
[ ] Added or updated documentation
[ ] Tests for new functionality and regression tests for bug fixes
[ ] Screenshots attached (for UI changes)
[x] All your commits have a Signed-off-by line in the message. (more info)

Thanks @freben 🚀


757 update AADprovider to include PIM for groups data in provider JSON

🗣 Description
This pull request modifies the AAD provider's Get-PrivilegedUser function to support getting user to PIM Group eligible assignments which is a current gap in our code. The PR also addresses a longstanding bug where users would sometimes get a duplicate role in their privileged_users node in the JSON. I also changed the connection module to request the required MS Graph permission scope since we are introducing a new cmdlet and I added the permission to the respective sections in the README file.
Closes #757
Closes #703
🧪 Testing
I tested this by creating test users and groups in all the test tenants that support PIM to ensure that the AAD code picks up the users that are assigned to a PIM group as Eligible. No updates were necessary to the functional tests because nothing changed in the JSON structure that would affect the Rego. I spoke with Crutch and we might want to add Powershell unit tests in the future that will exercise the code in the Get-PrivilegedUser and Get-PrivilegedRole functions of the AAD provider since those are what the types of changes associated with with this PR were associated with.
✅ Pre-approval checklist

[x] This PR has an informative and human-readable title.
[x] Changes are limited to a single goal - eschew scope creep! (kind of - i snuck in a separate bug fix)
[x] All future TODOs are captured in issues, which are referenced
in code comments.
[x] All relevant type-of-change labels have been added.
[x] I have read the CONTRIBUTING document.
[x] These code changes follow cisagov code standards.
[x] All relevant repo and/or project documentation has been updated
to reflect the changes in this PR.
[x] Tests have been added and/or modified to cover the changes in this PR.
[x] All new and existing tests pass.

✅ Pre-merge checklist

[ ] Revert dependencies to default branches.
[ ] Finalize version.

✅ Post-merge checklist

[ ] Create a release.

How to test this PR in your own tenant
**These instructions assume that you are going to test in a Sandia tenant, but if you are a reviewer on this PR I would read this anyway since it describes how I tested these code changes myself.
** It is important when following these setup instructions that you pay special attention to where assignments are made as "Active" or "Eligible" depending on the setup step. You need to make sure that you set that up exactly as described here so that when you run ScubaGear it will exercise the new code fragments that I added for the enhancement. Also, there are assignments that are made to roles and assignments that are made to groups. When assigning to groups, we will be doing that from the PIM for Groups portal page and NOT the Entra ID portal (this may be clear in the instructions but I wanted to call it out anyway). You can change the name of the groups to remove the "GCC High" portion if you want.
Entra ID portal
Create four new security groups named Ted's GCC High PIM Test Group, Ted's 2 GCC High PIM Test Group, Ted's 3 GCC High PIM Test Group, Ted's 4 GCC High PIM Test Group
Make sure to select the option that roles can be assigned to the group
Create 4 new test users with the convention TestPIMUser1 (display name = Test PIM User 1)
When you create the user make sure their account is disabled. We will not be logging in as these users, just using them for group membership testing.
PIM portal
Click Manage > Groups
Click Discover groups at the top of the page
Select the four new groups that were added an then click the Manage groups button at the top. This will "onboard" the groups into PIM.
Entra ID portal
Click Manage > Roles and administrators
Select the role Sharepoint Administrator
Click Add assignments
Assign the group Ted's GCC High PIM Test Group to the role as an "Active" assignment
Repeat the steps above but assign the group Ted's 2 GCC High PIM Test Group as an "Eligible" assignment
Repeat the steps above for the Hybrid Identity Administrator role but assign the group named Ted's 3 GCC High PIM Test Group as an "Active" assignment
Repeat the steps above for the Hybrid Identity Administrator role but assign the group named Ted's 4 GCC High PIM Test Group as an "Eligible" assignment
PIM portal
Click Manage > Groups
Select the group Ted's GCC High PIM Test Group
When the group opens up, select Manage > Assignments
Click Add assignments
Under the Select Role dropdown box, select Member
Under Select member(s) select Test PIM User 1
Click Next and then Assign the user as "Eligible"
When assigning users to the groups in PIM, you can also select users from the tenant that already have other administrative roles assigned to them to provide the new AAD code with more potential states for testing purposes. Look at my sample user assignment to groups in PIM distribution below. In this example the users Test PIM User 1 through 4 will only have a single role assigned to them if you follow my instructions, but the preexisting users Ted and Nanda already have other privileged roles assigned. If you select other users to add to the testing make sure that those users do not have an existing assignment to the roles Sharepoint Administrator or Hybrid Administrator so as not to skew the test.
Ted's GCC High PIM Test Group
Test PIM User 1
Ted Kolovos
Ted's 2 GCC High PIM Test Group
Test PIM User 2
Nanda
Ted's 3 GCC High PIM Test Group
Test PIM User 3
Ted's 4 GCC High PIM Test Group
Test PIM User 4
Testing and what do we expect to see when running ScubaGear?

Once you setup the tenant as per the instructions above, execute ScubaGear and examine the ProviderSettingsExport.json
Find each of the users that were assigned above inside the privileged_users node in the JSON
Review each user's respective "roles" in the JSON and make sure that they match the distribution below (yours may vary slightly depending on which additional users you included for the test in your environment)

The following users should have the Sharepoint Administrator role
Test PIM User 1
Ted Kolovos
Test PIM User 2
Nanda
The following users should have the Hybrid Identity Administrator role
Test PIM User 3
Test PIM User 4


compatible of parallelize=True and batch_size=auto

I got the following error when evaluate a 70b model on 4 gpus, with accelerate, parallelize, and batch_size=auto.
python=3.10
lm-eval Version: 0.4.0
accelerate launch --use_fsdp --no_python  lm_eval --model hf \
    --model_args pretrained=meta-llama/Llama-2-70b-hf,parallelize=True,dtype=auto \
    --tasks hellaswag --num_fewshot 10 \
    --batch_size auto
2023-12-30:17:48:00,526 INFO     [utils.py:148] Note: NumExpr detected 64 cores but "NUMEXPR_MAX_THREADS" not set, so enforcing safe limit of 8.
2023-12-30:17:48:33,142 INFO     [__main__.py:156] Verbosity set to INFO
2023-12-30:17:48:49,778 INFO     [__main__.py:229] Selected Tasks: ['hellaswag']
Downloading shards: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 15/15 [00:04<00:00,  3.54it/s]
Loading checkpoint shards: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 15/15 [02:22<00:00,  9.48s/it]
2023-12-30:17:51:41,611 WARNING  [evaluator.py:141] Overwriting default num_fewshot of hellaswag from None to 10
2023-12-30:17:51:41,615 INFO     [task.py:344] Building contexts for task on rank 0...
2023-12-30:17:53:59,991 INFO     [evaluator.py:314] Running loglikelihood requests
  0%|                                                                                | 0/40168 [00:00<?, ?it/s]Traceback (most recent call last):
  File "/lustre/home/haonan.li/miniconda3/bin/lm_eval", line 8, in <module>
    sys.exit(cli_evaluate())
  File "/lustre/home/haonan.li/mygit/lm-evaluation-harness/lm_eval/__main__.py", line 231, in cli_evaluate
    results = evaluator.simple_evaluate(
  File "/lustre/home/haonan.li/mygit/lm-evaluation-harness/lm_eval/utils.py", line 415, in _wrapper
    return fn(*args, **kwargs)
  File "/lustre/home/haonan.li/mygit/lm-evaluation-harness/lm_eval/evaluator.py", line 150, in simple_evaluate
    results = evaluate(
  File "/lustre/home/haonan.li/mygit/lm-evaluation-harness/lm_eval/utils.py", line 415, in _wrapper
    return fn(*args, **kwargs)
  File "/lustre/home/haonan.li/mygit/lm-evaluation-harness/lm_eval/evaluator.py", line 325, in evaluate
    resps = getattr(lm, reqtype)(cloned_reqs)
  File "/lustre/home/haonan.li/mygit/lm-evaluation-harness/lm_eval/models/huggingface.py", line 759, in loglikelihood
    return self._loglikelihood_tokens(new_reqs)
  File "/lustre/home/haonan.li/mygit/lm-evaluation-harness/lm_eval/models/huggingface.py", line 877, in _loglikelihood_tokens
    for chunk in chunks:
  File "/lustre/home/haonan.li/mygit/lm-evaluation-harness/lm_eval/utils.py", line 822, in get_batched
    yield from batch
  File "/lustre/home/haonan.li/mygit/lm-evaluation-harness/lm_eval/utils.py", line 918, in get_chunks
    if len(arr) == (fn(i, iter) if fn else n):
  File "/lustre/home/haonan.li/mygit/lm-evaluation-harness/lm_eval/models/huggingface.py", line 818, in _batch_scheduler
    sched = pos // int(len(n_reordered_requests) / self.batch_schedule)
TypeError: object of type 'generator' has no len()
  0%|                                                                                | 0/40168 [00:01<?, ?it/s]
[2023-12-30 17:57:02,128] torch.distributed.elastic.multiprocessing.api: [ERROR] failed (exitcode: 1) local_rank: 0 (pid: 3615208) of binary: lm_eval
Traceback (most recent call last):
  File "/lustre/home/haonan.li/miniconda3/bin/accelerate", line 8, in <module>
    sys.exit(main())
  File "/lustre/home/haonan.li/miniconda3/lib/python3.10/site-packages/accelerate/commands/accelerate_cli.py", line 45, in main
    args.func(args)
  File "/lustre/home/haonan.li/miniconda3/lib/python3.10/site-packages/accelerate/commands/launch.py", line 966, in launch_command
    multi_gpu_launcher(args)
  File "/lustre/home/haonan.li/miniconda3/lib/python3.10/site-packages/accelerate/commands/launch.py", line 646, in multi_gpu_launcher
    distrib_run.run(args)
  File "/lustre/home/haonan.li/miniconda3/lib/python3.10/site-packages/torch/distributed/run.py", line 797, in run
    elastic_launch(
  File "/lustre/home/haonan.li/miniconda3/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 134, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/lustre/home/haonan.li/miniconda3/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 264, in launch_agent
    raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
============================================================
lm_eval FAILED
------------------------------------------------------------
Failures:
  <NO_OTHER_FAILURES>
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
  time      : 2023-12-30_17:57:02

Hi, thanks for reporting this.
Note that launching using accelerate launch is not supposed to be compatible with parallelize=True. Could you remove one of these and try again?
Rather than using FSDP through Accelerate, which can be slow or buggy during generation, we recommend using vLLM for heavy + multi-GPU inference loads if possible for your usecase--this should speed things up significantly compared to parallelize=True which only fully utilizes one GPU at once.

Thanks for your prompt response and suggestion.
Here is my observation:
There is no bug when I use accelerate launch and parallelize=True, with batch_size=16.
There is no bug when I use parallelize=True, with batch_size=16.
There is bug when I use accelerate launch and parallelize=True, with batch_size=auto.
vllm is really good and easy to use. But I met some bug there.
So, do you have any suggestion on how to accelerate the evaluation without vllm?
If the answer is no, I will close this issue, and open another issue to discuss vllm.
Thanks.

Opening an issue about any problems you've had using vllm would be very helpful.
What about when you use parallelize=True, with batch_size=auto and no accelerate launcher? I think there may be a bug here w.r.t. auto batching but a relatively simple one to fix.

To your question, even without accelerate, there is the same bug when I set parallelize=True, with batch_size=auto.


Release Build #148 jobFailureActionEmail not receiving email when SMTP cfg good

Description
OSC can send email on alerts e.g. jobFailed action=email but not receiving email
Expected Behavior
If user config alarm with email, should receive email when alarm occurred
Actual Behavior
Email validation got email but not alarm action=email which does not get email?
Steps to Reproduce
1)Manage-Server-Email-Edit with SMTP <IP_ADDRESS>, port 25, EmailID myIntelEmailAddr
2)Click Validate and I receive email saying "This email is to verify your Email settings provided on OSC server!"
3)Manage-Alarms-DefaultJobFailureAlarm-Edit select AlarmAction-Email
4)Create e.g. Sync my DS and got jobFailed "VM in bad state" in Status-Jobs BUT no email received on this!
Additional Information
Logs attached. Also tried external IP OSC. All OSC can ping SMTP IP. Log saw connection to SMTP failure?
b148EmailFailJobFailLog900.txt
Environment

OSC Version/Build: v08Build148
Cloud Provider Info:
Plugin Info:
Other:

Status

[ ] Reproduced
[ ] In Progress
[ ] Validated     =>    Verified in Version/Build:

Other system alert sending email works, this could be the env issue. Close for now.  __AL


Not Activated/Multiple Win Checker (5.3) shows inaccurate results/partially not working

Description

The "Not Activated/Multiple Win Checker" (5.3) shows inaccurate results
Multiple Win Checker is not available on profiles other than my own

Steps to Reproduce
1.1 Go to my SG profile page
1.2 Click on "Not Activated/Multiple Win Checker" and search for non-activated wins
1.3 See error - says I have 1 non activated win.
1.4 Click on the link to SGTools to see what game that would be - see that there is no non-activated win.
2.1 Go to someones SG profile page
2.2 Click on "Not Activated/Multiple Win Checker"
2.3 See that only the option to check for "Not Activated" is available
Expected Behavior

It should display the correct number as per SGTools
Both, multiple wins and non-activated wins checker should be available

Console Errors
none
Screenshots
1: Check result and SGTools page do not match as the checker display out of date data

2: Only Not Activated Checker is available

System (please complete the following information):

ESGST: Extension, Current Version: 8.1.5
Browser: Current Version Chrome 64bit

Additional Context
1: This is from when I won a "Steam is learning" game after which I used the "Not Activated/Multiple Win Checker" on myself. After reporting the game/issue to knsys he added the game to his list of false positives. This was a few days ago.
I'd expect that after syncing SGTools and SG today and doing the check again that the result would give me a green checkmark for both tests. Unfortunately it doesn't. Actually the test went by so quick that I assume the result was taken from cache.
I'd suggest adding a "Clear Cache" button - just like "User Giveaway Data" (5.12 - by the way, it's mouse over still says 5.11) has one. That way we can force the checker to get new data from SGTools for cases like these, or cases where people have fixed their problems.
2: Both options should be available, but they are not on any other profile than my own.

That option is exclusive. If you uncheck it, it will check for both. Try it and you'll see what I'm talking about.

Unchecking it fixed problem 2. Which leaves us only with problem 1, where now false results remain being displayed instead of updated correct ones.

The first problem is just a matter of caching (results are cached for 7 days), I'll add an option to clear cache.
As for User Giveaway Data displaying wrong number, can you confirm this in the latest version? It shows correctly as 6.12 for me (I have SteamTrades enabled, so I have an additional Trades section, which is why my count is 6 instead of 5).

For 8.1.6 (Dev.20) I can confirm that there's a clear cache option.
I can also confirm - for the same version - that the mouse over still says 5.11 instead of 5.12:

The number is correct. User Giveaway Data is at 5.11 for non-SteamTrades users.


Height/width calculation fix

We should only be subtracting margin * 2 not margin * 4 in a couple places.  Discovered this while creating an indeterminate HUD in a view where height > width and I'd set hud.square = YES.  Result was a tall skinny HUD instead of a square one.

The layout code is now using auto layout.


[SPARK-8603][SPARKR] Incorrect file separator passed to Java and Scripts from R in windows

What changes were proposed in this pull request?
This PR corrects R file separator to accept Windows.
According to the R API, file,

file.path(..., fsep = .Platform$file.sep)

file.path API takes .Platform$file.sep but the default value for this is, / regardless of OS type.
Also, this is written as a note in the document as below:

The components are by default separated by / (not ) on Windows.

How was this patch tested?
Jenkins tests and manually tested in a Window machine as below:
> .Platform$OS.type
[1] "windows"

> .Platform$file.sep
[1] "/"

Closes #7025

Please let me cc @sun-rui and @JoshRosen

Test build #58758 has started for PR 13165 at commit 454b7f5.

Could you add a test case for Windows specific test? @shivaram

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Does this apply to other cases:
https://github.com/apache/spark/blob/d6dc12ef0146ae409834c78737c116050961f350/R/pkg/inst/worker/daemon.R#L22
https://github.com/apache/spark/blob/d6dc12ef0146ae409834c78737c116050961f350/R/pkg/inst/profile/shell.R#L20
https://github.com/apache/spark/blob/6ab4d9e0c76b69b4d6d5f39037a77bdfb042be19/examples/src/main/r/dataframe.R#L37
(last one is an example)

@sun-rui @felixcheung Let me try to build and run all tests for R first in Windows and then will try to correct and add each test one by one. This will take a bit of time and I might have to ask a lot of questions but anyway I will try.

@felixcheung, this issue seems to relate to system2() only. However, let's wait for HyukjinKwon's test result.
@HyukjinKwon, great, go ahead please.

@sun-rui @felixcheung Right. It seems finally I made it. I made gists and upload a PDF file for Spark UI.
Let me tell you the test results first.
Here is the stdout output for the tests on Windwos 7 32bit, output.msg.
Here is the stderr output for the tests on Windwos 7 32bit, output.err.
Here is the PDF for Spark UI PDF

I run tests after building Spark on Windows according to [./R/WINDOWS.md] (https://github.com/apache/spark/blob/master/R/WINDOWS.md)

It seems $HADOOP_HOME should be set.

It seems winutils.exe is required which is included in Hadoop official binary although it reads file in the local file system.

And run the tests by the command below:

cd bin
spark-submit2.cmd --conf spark.hadoop.fs.defualt.name="file:///" ..\R\pkg\tests\run-all.R > output.msg 2> output.err

This raises some questions to me.

It seems several tests were failed. Could you please inform me your thoughts?

Now, I think I can add some tests but could you please where I should write the related tests and maybe rough ideas of the tests I should add?

A rough scan of the test failures shows most of them are probably related to path handling. You can replay the failed test case in R on Windows.  For debug facilities in R, refer to http://www.inside-r.org/r-doc/base/traceback, https://stat.ethz.ch/R-manual/R-devel/library/base/html/debug.html, http://www.inside-r.org/r-doc/base/browser
You can add a new file named test_Windows.R under R/pkg/inst/tests/testthat
Sure.

I checked the source code of system2. Since a batch file with .cmd extension is to be launched on Windows, I think it is more formal to use shell() instead of system2(). Refer to http://www.astrostatistics.psu.edu/datasets/R/html/base/html/shell.html. The proposed fix is like follows:
if (.Platform$OS.type == "windows") {
  shell(sparkSubmitBin, translate = TRUE, ...)
} else {
  system2(sparkSubmitBin, ...)
}

@sun-rui Thank you so much. I will try to add a test.

Related to my comment on #13217 -- I will test this out on windows using the new instructions.

@shivaram Thank you so much. Let me try to add a test meanwhile.

@shivaram and @sun-rui I addressed the comment, added a test for this PR and fixed some tests not working on Windows due to path separator.
This PR also fixes the test failures below.

Fixed case 1

Failure: sparkJars sparkPackages as comma-separated strings (@test_context.R#128)
Failure: sparkJars sparkPackages as comma-separated strings (@test_context.R#131)
Failure: sparkJars sparkPackages as comma-separated strings (@test_context.R#134)

  The cases above were due to a weird behaviour of `normalizePath()`. On Linux, if the path does not exist, it just prints out the input but it prints out including the current path on Windows.

  ```r
# On Linus
path <- normalizePath("aa")
print(path)
[1] "aa"

# On Windows
path <- normalizePath("aa")
print(path)
[1] "C:\\Users\\aa"

Fixed case 2

Failure: sparkJars tag in SparkContext (@test_includeJAR.R#34)
Failure: sparkJars tag in SparkContext (@test_includeJAR.R#36)

The cases above were due to using of `system2`.

Here is full stdout of my testing, [output.msg](https://gist.github.com/HyukjinKwon/c72b747a15948bd062a26aba7c42115b) on Windows.

Test build #59275 has started for PR 13165 at commit 64141d2.

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I just addressed the comments and here is the (stdout)[https://gist.github.com/HyukjinKwon/4bf35184f3a30f3bce987a58ec2bbbab] of testing on Windiws.

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retest this please

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@sun-rui Thanks, I just updated it. There is the stdout for this time

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LGTM

could you rebase it to latest master. It is hopeful other test failures will gone

Sure, Thanks!

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@HyukjinKwon Thanks for the update. I verified this today using a Windows VM and followed the instructions you have written up as well. All the tests passed and the stdout I got is at https://gist.github.com/shivaram/bd3c8bf7466d6cd515f4877f2a9611b3
One minor thing - there is a typo in the last line of https://github.com/apache/spark/blob/branch-2.0/R/WINDOWS.md
spark.hadoop.fs.defualt.name should be spark.hadoop.fs.default.name (typo in the spelling of default).
Could you make that change as a part of this PR ?

@shivaram Thank you so much! I will keep this machine as it is anyway. Please cc me if there are some PRs dealing with Windows in the future. I can run tests and leave some comments.

@shivaram

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Merging this to master and branch-2.0


Cointainer get new instance

I have realized that Container.get method returns same instance whenever it's called. I have tried to put this test case and it fails:
    class Logger {}

    class App {
      static inject() { return [Logger]; };
      constructor(logger) {
        this.logger = logger;
      }
    }

    var container = new Container();
    var firstApp = container.get(App);
    var secondApp = container.get(App);

    expect(firstApp).not.toBe(secondApp);

Do I need to create new container instance every time when I want new instance of App class?

I need multiple instances of the same viewModel class to be active at the same time (I have a tree view on the left side of the screen and as I click the node in the treeview the right side is populated with data. Every node has it's own instance of viewModel)
I copied routerView element and changed process method to read the viewModel from cache (based on the route fragment). This works but it feels like it's the wrong place to do it because aurelia creates the viewModel somewhere before the process method and then if I have a viewModel in the cache I discard the created view model. (This works because I have registered my view models as transient).
I would like to read my cache (based on the route fragment) before Aurelia creates the view model and if the view model exists in the cache pass that down the pipeline.
Is that even possible? Were is the best place to do it?


Add Dogecoin current fee calculation logic

Introduces 1 COIN/kb fees, rounded up to the next 1 COIN.
Disable free transactions
Dust outputs incur a 1 COIN additional fee.
Add unit tests for fee calculation.
Update existing unit tests with higher transaction values so that transactions are still standard.

This isn't fully tested due to time limitations, but I figure it at least moves us closer to a functioning wallet even if we require later cleanup.

Yay for magic numbers. See those that basically prevent sending a normal DOGE tx. Although I think the first one is fine, the other two will complain with 1DOGE fee. I'd suggest 100 DOGE for us? Or 50?
https://github.com/dogecoin/dogecoin/blob/1.10-dev/src/main.cpp#L1035
https://github.com/dogecoin/dogecoin/blob/1.10-dev/src/qt/walletmodel.cpp#L293
https://github.com/dogecoin/dogecoin/blob/1.10-dev/src/qt/sendcoinsdialog.cpp#L531

Thanks for the edit. Going to merge after some basic playing with it.


Draft content for deployments

This PR contains new content about deployments, plus copied & pasted content from the old site.

Please fix tests before merging.


Check validity of run_type early

Check validity of run_type early to avoid puzzling errors later.

@ebattat should I merge this with #284?

Closing in favor of #284.


Port event-stream changes from vscode

Specifically the following commits https://github.com/Microsoft/vscode/commit/981d0ab0d510e9bd4325124a1674cadab6c36daa#diff-b9cfc7f2cdf78a7f4b91a753d10865a2 and https://github.com/Microsoft/vscode/commit/dc68051e07ec95a22f0f2ab45aedd90a175f52ce#diff-b9cfc7f2cdf78a7f4b91a753d10865a2

vbump-only


Update Readme

Update readme to name of project, removing YashKumarVerma's name

I am working on this issue.

@YashKumarVerma  with reference to #6,
we should also delete 'typescript starter template' and other content related to starter template.
the content is still there in the readme.md.

@vivekshah1801 send a PR.

@vivekshah1801 Yes, you are right and also at that time I didn't notice the issue #1
You can update the content and send a PR.

Why isn't there a PR for this yet ?

@YashKumarVerma Why did you reopen this issue?

@VershaCoder  check README file. Still not updated.


Useless documentation...

 No word how to actually use URLs with this. Deleting this again. Timewaster.

Hello there!
I understand your exhaustion and our project is meant to be helpful. To input the URL is just like passing any file path to the program. We have included an example in demo.ipynb and added support for running the program via command lines.
I suggest checking out the updated instructions and our ChatGPT plugin at https://chat.openai.com/?model=gpt-4-plugins.


fix copayerName decryption in certain cases

as per title

Coverage decreased (-0.03%) to 93.421% when pulling a0da3d4e34889cc50c90f041cbe0c1edcf05cd72 on matiu:bug/copayer-name-enc into fddee1f3b00531462e2d7dfc81d46dcbca82e613 on bitpay:master.


Python kernel dies executing fc.mef.get_transform_fxn()

When trying to fit bead data with the method fc.mef.get_transform_fxn(), the Python kernel dies for an unknown reason.
Code (run in Jupyter Notebook):
# coding: utf-8

# In[1]:

get_ipython().magic(u'matplotlib inline')

home = False
import numpy as np
import scipy as sp
import numpy.ma as ma
import matplotlib.pyplot as plt
import math, cmath, csv, sys, cPickle, os, os.path, gc
import lmfit as lm
import FlowCal as fc

# In[2]:

base_dir = os.path.abspath(os.path.join(os.path.abspath('__file__'), '..', '..'))
fig_dir = os.path.join(base_dir, 'Figures')
data_dir = os.path.join(base_dir, 'Flow Data')

# In[3]:

dates = ['20170117', '20170124']

# In[4]:

bead_dir = os.path.join(data_dir, dates[0], 'Data005.fcs') ## Bead data
bead_data = fc.io.FCSData(bead_dir)

# In[5]:

bead_MEFs = np.array([np.nan]+[792, 2079, 6588, 16471, 47497, 137049, 271647])
sc_channels = ['FSC', 'SSC']
fl_channels = ['FL1', 'FL2', 'FL3']

# In[ ]:

bead_data = fc.gate.start_end(bead_data, num_start=250, num_end=100)
#bead_data = fc.gate.high_low(bead_data, sc_channels)
gated_bead_data, _, gate_contour = fc.gate.density2d(data=bead_data,channels=sc_channels,
                                                     gate_fraction=0.4, full_output=True)

# In[ ]:

to_mef = fc.mef.get_transform_fxn(gated_bead_data, [bead_MEFs], clustering_channels=fl_channels,
                                  mef_channels=['FL1'], verbose=True, plot=True, plot_dir=None)

OS: Linux Mint 18.1
Packages installed:
linux_packages.txt
Working pacakges (produce no error on Windows 10):
windows_packages.txt

Did you ever try to run this on a regular python script, as opposed to an ipython notebook? Also, can you include the relevant flow files? (I guess 'Data0005.fcs' would be enough).

Did you ever try to run this on a regular python script, as opposed to an ipython notebook?

Running this in an IPython instance in the console yields the following message:
/home/lucas/anaconda2/lib/python2.7/site-packages/sklearn/utils/deprecation.py:52: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.
  warnings.warn(msg, category=DeprecationWarning)
/home/lucas/anaconda2/lib/python2.7/site-packages/sklearn/utils/deprecation.py:70: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.
  warnings.warn(msg, category=DeprecationWarning)
Intel MKL FATAL ERROR: Cannot load libmkl_avx2.so or libmkl_def.so.

Based on this, I ran conda install mkl. Running the code again yields:
/home/lucas/anaconda2/lib/python2.7/site-packages/sklearn/utils/deprecation.py:52: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.
  warnings.warn(msg, category=DeprecationWarning)
/home/lucas/anaconda2/lib/python2.7/site-packages/sklearn/utils/deprecation.py:70: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.
  warnings.warn(msg, category=DeprecationWarning)
/home/lucas/anaconda2/lib/python2.7/site-packages/sklearn/utils/deprecation.py:70: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.
  warnings.warn(msg, category=DeprecationWarning)
/home/lucas/anaconda2/lib/python2.7/site-packages/sklearn/utils/deprecation.py:70: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.
  warnings.warn(msg, category=DeprecationWarning)
/home/lucas/anaconda2/lib/python2.7/site-packages/sklearn/utils/deprecation.py:70: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.
  warnings.warn(msg, category=DeprecationWarning)
Step 1: Clustering
  Number of populations to find: 8
  Percentage of events in each population:
    [ 11.2   13.85  12.87  13.72  11.93  12.22  12.39  11.82]
(FL1) Step 2: Population Statistic
  Fluorescence of each population (RFI):
    [ 102.  197.  197.  199.  484.  587.  483.  587.]
(FL1) Step 3: Population Selection
  3 populations selected.
  Fluorescence of selected populations (RFI):
    [ 197.  197.  199.]
  Fluorescence of selected populations (MEF):
    [  792.  2079.  6588.]
(FL1) Step 4: Standard Curve Fitting
  Parameters of bead fluorescence model:
    [  6.37e+00  -2.24e+01   7.67e+04]

This looks like progress, but  I'm concerned that FlowCal is only identifying 3 bead populations in my bead data file. :(

Also, can you include the relevant flow files? (I guess 'Data0005.fcs' would be enough).

Available here: link.
Just let me know if you have any other questions.

I found the problem. Your code is only going to work with FlowCal 1.0.0 (which you are using in windows). Since FlowCal 1.1.0, transformation to arbitrary units is required as an intermediate step, and should be done before calculating the MEF transformation function and applying the transformation function to cell sample files. The reason why we did this is complicated, but the short story is that this was needed to improve compatibility with other flow cytometers.
Your code can be fixed by adding this line before calculating the MEF transformation function:
bead_data = fc.transform.to_rfi(bead_data, sc_channels + fl_channels)

If you plan on writing code for FlowCal >= 1.1.0, using the above line right after you load an .fcs file should be enough.
Without this line, the following results:

With this line, the following results:

(plots look a little different because matplotlib2.)
Hope this helps. I'll close the issue now.

btw, FlowCal 1.1.0 is very different under the hood from FlowCal 1.0.0, and we do not recommend anybody to use anything below 1.1.0 at this point.


FizzBuzz implementation in Kotlin along with JUnit Tests

A very simple and clean FizzBuzz implementation in Kotlin along with JUnit Tests
This PR consists of two files:

fizzBuzz-ram.kt - it is the implementation of FizzBuzz
fizzBuzz-ram-test.kt - it is the JUnit test of the said implementation

Thank you for your PR!
Unfortunately a solution similar to yours has already been submitted :/
A unit test doesn't necessarily make the solution more creative.
The goal is to find creative/abstract new solutions to FizzBuzz.
See The top 5 samples here.
Thanks anyway! :)


Solved fluxmap support for IBM PC (upd765a) formats

A2R has a concept of a "solved fluxmap" - e.g. a flux map that has been machine generated to be perfect, not a raw read from a disk.
These can be created with gw indirectly right now, by reading to an image format and then writing back to a flux image. However, doing so loses some data that can be seen by the upd765a's Read Track command.
There are several ways to fix this. One method that I'd like to try is doing a full decode of the track (and multiple retries, if needed, to get the best possible read) but then extracting the post-PLL-recovery bitstream and encoding that to the solved fluxmap, possibly with a small amount of rotation around the index.

To preserve gap protections etc?

Yes. This isn't the only way to do it, of course. This method has some downsides, too - it can't combine good sectors from separate reads, it preserves potentially useless data between sectors, etc.

Yeah the raw.* formats should be enough, I'll try them out and see what happens.
I was thinking that it would also be good to run the decode in this case so that the "best" of multiple tracks can be used, but I'll have to play around and figure out how much of an actual problem that is first.

FWIW I've been testing the raw.* formats with HFE and it's worked great so far. My current workflow then involves checking that the result is reasonable with HxCTools, but of course having a generic IBM track resolver could avoid that step (and potentially allow rereads during dumping). That would be enough to close this.
I've run into a couple of other minor issues but I'll file them separately.

You should try the new format ibm.scan


typo on help page - missing word in description

Current: "You can set options, project or filter to if you don't want to set them. Available reporters are:"
Should be: "You can set options, project or filter to null if you don't want to set them. Available reporters are:"
(missing the word "null") I think.

@rjperrella Is this from the readme.md file? The file I'm seeing says undefined.

You can set options, project or filter to undefined if you don't want to set them. Available reporters are:

I'm looking at the copy on npmjs.org
https://www.npmjs.com/package/gulp-typescript
And you are correct - it should read undefined. I just saw that in the unit tests.

@rjperrella I see, that is odd. I verified that the package version currently published to npm is 2.6.0. My guess is there is a bug in the markdown rendering engine that npmjs.com is using.

Looks like it's fixed again, I don't know how but it shows undefined again on npm.


Issue with update

reported by pool owner zpool in discord

And that's exactly what's happening right now I suppose..

And that's exactly what's happening right now I suppose..

The community is working to reclaim the coin. I was asked to volunteer to create a new QT wallet which im doing now.


Fail to reproduce performance on Traffic dataset.

Dear authors,
I currently try to reproduce the experiments of your fascinating work. Performance on dataset like Electricity is fine, but I fail to obtain the performance on dataset Traffic in single-step forecasting scenario with setting suggested in the paper.
Concretely, the RRSE of Traffic-horizon3 is $0.4162$ in the paper, but I just obtain performance close to $0.4294$ (average over 10 seeds).
Look forward to your reply, thanks a lot!
Best,
JiaWei

Solved. Thanks a lot!


Transition issue when using redirect in validate

Version
v2.0.0
Reproduction link
https://github.com/therddlr/transition-issue
Steps to reproduce
If you navigate to issue page you can see that next route instantly appears without waiting page transition to finish.
The ok page is working fine.
Also, if you comment out validate in issue page then transition mode is not broken. So this is somehow related with redirect in validate.
What is expected ?
I expect normal page transition
What is actually happening?
Transition mode is broken.

This bug report is available on Nuxt community (#c7816)

I'm also having this issue. Is there a workaround?

@Guizzoni I ended up with not using validate at all.

How would you return a 404 error without using validate?

I still would sole to see the fix. How can you close this only if it's not active, if this is a bug?

I believe this is related to #4132 which was also closed without a solution.

It is discouraging that the error reports with reproduction steps are being closed without any check :(

This still happens in the latest nuxt-edge version.


Release/1.0.0

:white_check_mark: Build TheIdServer 1.0.1.build.705 completed (commit https://github.com/Aguafrommars/TheIdServer/commit/6eb11569ee by @semantic-release-bot)