Weird error while training a model with tabular data!!!! Some problem related self.log_dict

Bug description
The code can be accessed at https://www.kaggle.com/code/vigneshwar472/notebook5a03168e34
I am working on multiclass classification task and want to train a nueral network with pytorch lightning on 2x T4 GPUs on kaggle notebook.
Everything seems to work fine but I encounter this error when I fitted the trainer.
Training Step of lightning module
def training_step(self, batch, batch_idx):
        x, y = batch
        logits = self(x)
        loss = F.cross_entropy(logits, y)
        preds = F.softmax(logits, dim=1)
        preds.to(y)
        self.log_dict({
            "train_Loss": loss,
            "train_Accuracy": self.accuracy(preds, y),
            "train_Precision": self.precision(preds, y),
            "train_Recall": self.recall(preds, y),
            "train_F1-Score": self.f1(preds, y),
            "train_F3-Score": self.f_beta(preds, y),
            "train_AUROC": self.auroc(preds, y),
        }, on_step=True, on_epoch=True, prog_bar=True, sync_dist=True)
        return loss

Initializing trainer
trainer = L.Trainer(max_epochs=5,
                    devices=2,
                    strategy='ddp_notebook',
                    num_sanity_val_steps=0,
                    profiler='simple',
                    default_root_dir="/kaggle/working",
                    callbacks=[DeviceStatsMonitor(),
                               StochasticWeightAveraging(swa_lrs=1e-2),
                               #EarlyStopping(monitor='train_Loss', min_delta=0.001, patience=100, verbose=False, mode='min'),
                              ],
                    enable_progress_bar=True,
                    enable_model_summary=True,
                   )

trainer.fit(model, data_mod) => data_mod is LightningDataModule
W1116 14:03:37.546000<PHONE_NUMBER>91584 torch/multiprocessing/spawn.py:146] Terminating process 131 via signal SIGTERM
INFO: [rank: 0] Received SIGTERM: 15
---------------------------------------------------------------------------
ProcessRaisedException                    Traceback (most recent call last)
Cell In[14], line 1
----> 1 trainer.fit(model, data_mod)

File /opt/conda/lib/python3.10/site-packages/lightning/pytorch/trainer/trainer.py:538, in Trainer.fit(self, model, train_dataloaders, val_dataloaders, datamodule, ckpt_path)
    536 self.state.status = TrainerStatus.RUNNING
    537 self.training = True
--> 538 call._call_and_handle_interrupt(
    539     self, self._fit_impl, model, train_dataloaders, val_dataloaders, datamodule, ckpt_path
    540 )

File /opt/conda/lib/python3.10/site-packages/lightning/pytorch/trainer/call.py:46, in _call_and_handle_interrupt(trainer, trainer_fn, *args, **kwargs)
     44 try:
     45     if trainer.strategy.launcher is not None:
---> 46         return trainer.strategy.launcher.launch(trainer_fn, *args, trainer=trainer, **kwargs)
     47     return trainer_fn(*args, **kwargs)
     49 except _TunerExitException:

File /opt/conda/lib/python3.10/site-packages/lightning/pytorch/strategies/launchers/multiprocessing.py:144, in _MultiProcessingLauncher.launch(self, function, trainer, *args, **kwargs)
    136 process_context = mp.start_processes(
    137     self._wrapping_function,
    138     args=process_args,
   (...)
    141     join=False,  # we will join ourselves to get the process references
    142 )
    143 self.procs = process_context.processes
--> 144 while not process_context.join():
    145     pass
    147 worker_output = return_queue.get()

File /opt/conda/lib/python3.10/site-packages/torch/multiprocessing/spawn.py:189, in ProcessContext.join(self, timeout)
    187 msg = "\n\n-- Process %d terminated with the following error:\n" % error_index
    188 msg += original_trace
--> 189 raise ProcessRaisedException(msg, error_index, failed_process.pid)

ProcessRaisedException:

-- Process 1 terminated with the following error:
Traceback (most recent call last):
  File "/opt/conda/lib/python3.10/site-packages/torch/multiprocessing/spawn.py", line 76, in _wrap
    fn(i, *args)
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/strategies/launchers/multiprocessing.py", line 173, in _wrapping_function
    results = function(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/trainer/trainer.py", line 574, in _fit_impl
    self._run(model, ckpt_path=ckpt_path)
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/trainer/trainer.py", line 981, in _run
    results = self._run_stage()
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/trainer/trainer.py", line 1025, in _run_stage
    self.fit_loop.run()
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/loops/fit_loop.py", line 205, in run
    self.advance()
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/loops/fit_loop.py", line 363, in advance
    self.epoch_loop.run(self._data_fetcher)
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/loops/training_epoch_loop.py", line 140, in run
    self.advance(data_fetcher)
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/loops/training_epoch_loop.py", line 250, in advance
    batch_output = self.automatic_optimization.run(trainer.optimizers[0], batch_idx, kwargs)
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/loops/optimization/automatic.py", line 190, in run
    self._optimizer_step(batch_idx, closure)
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/loops/optimization/automatic.py", line 268, in _optimizer_step
    call._call_lightning_module_hook(
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/trainer/call.py", line 167, in _call_lightning_module_hook
    output = fn(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/core/module.py", line 1306, in optimizer_step
    optimizer.step(closure=optimizer_closure)
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/core/optimizer.py", line 153, in step
    step_output = self._strategy.optimizer_step(self._optimizer, closure, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/strategies/ddp.py", line 270, in optimizer_step
    optimizer_output = super().optimizer_step(optimizer, closure, model, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/strategies/strategy.py", line 238, in optimizer_step
    return self.precision_plugin.optimizer_step(optimizer, model=model, closure=closure, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/plugins/precision/precision.py", line 122, in optimizer_step
    return optimizer.step(closure=closure, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/torch/optim/optimizer.py", line 484, in wrapper
    out = func(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/torch/optim/optimizer.py", line 89, in _use_grad
    ret = func(self, *args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/torch/optim/adamw.py", line 204, in step
    loss = closure()
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/plugins/precision/precision.py", line 108, in _wrap_closure
    closure_result = closure()
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/loops/optimization/automatic.py", line 144, in __call__
    self._result = self.closure(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
    return func(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/loops/optimization/automatic.py", line 129, in closure
    step_output = self._step_fn()
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/loops/optimization/automatic.py", line 317, in _training_step
    training_step_output = call._call_strategy_hook(trainer, "training_step", *kwargs.values())
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/trainer/call.py", line 319, in _call_strategy_hook
    output = fn(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/strategies/strategy.py", line 389, in training_step
    return self._forward_redirection(self.model, self.lightning_module, "training_step", *args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/strategies/strategy.py", line 640, in __call__
    wrapper_output = wrapper_module(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1553, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1562, in _call_impl
    return forward_call(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/parallel/distributed.py", line 1636, in forward
    else self._run_ddp_forward(*inputs, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/parallel/distributed.py", line 1454, in _run_ddp_forward
    return self.module(*inputs, **kwargs)  # type: ignore[index]
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1553, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1562, in _call_impl
    return forward_call(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/strategies/strategy.py", line 633, in wrapped_forward
    out = method(*_args, **_kwargs)
  File "/opt/conda/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 433, in _fn
    return fn(*args, **kwargs)
  File "/tmp/ipykernel_30/3650372019.py", line 74, in training_step
    self.log('train_loss', loss, on_step=True, on_epoch=True, prog_bar=True, sync_dist=True)
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/core/module.py", line 437, in log
    apply_to_collection(value, dict, self.__check_not_nested, name)
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/core/module.py", line 438, in torch_dynamo_resume_in_log_at_437
    apply_to_collection(
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/core/module.py", line 484, in torch_dynamo_resume_in_log_at_438
    results.reset(metrics=False, fx=self._current_fx_name)
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/core/module.py", line 508, in torch_dynamo_resume_in_log_at_484
    and is_param_in_hook_signature(self.training_step, "dataloader_iter", explicit=True)
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/core/module.py", line 525, in torch_dynamo_resume_in_log_at_508
    results.log(
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py", line 403, in log
    metric = _ResultMetric(meta, isinstance(value, Tensor))
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py", line 404, in torch_dynamo_resume_in_log_at_403
    self[key] = metric
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py", line 411, in torch_dynamo_resume_in_log_at_404
    self[key].to(value.device)
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py", line 414, in torch_dynamo_resume_in_log_at_411
    self.update_metrics(key, value, batch_size)
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py", line 419, in update_metrics
    result_metric.forward(value, batch_size)
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py", line 270, in forward
    self.update(value, batch_size)
  File "/opt/conda/lib/python3.10/site-packages/torchmetrics/metric.py", line 483, in wrapped_func
    update(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py", line 225, in update
    self._forward_cache = self.meta.sync(value.clone())  # `clone` because `sync` is in-place
  File "/opt/conda/lib/python3.10/site-packages/lightning/pytorch/trainer/connectors/logger_connector/result.py", line 144, in sync
    assert self._sync is not None
AssertionError

Please Help me resolve this error. I am very confused what to do
What version are you seeing the problem on?
v2.4
How to reproduce the bug
Check out the kaggle notebook [](https://www.kaggle.com/code/vigneshwar472/notebook5a03168e34)

Error messages and logs
# Error messages and logs here please

Environment

Current environment
#- PyTorch Lightning Version (e.g., 2.4.0):
#- PyTorch Version (e.g., 2.4):
#- Python version (e.g., 3.12):
#- OS (e.g., Linux):
#- CUDA/cuDNN version:
#- GPU models and configuration:
#- How you installed Lightning(`conda`, `pip`, source):

More info
No response

Did you try avoiding torch.compile to start bisecting the problem?


Follow .editorconfig for guidance on converting to spaces

We have some projects that are old and use tabs.  We've established .editorconfig files for these to control whitespace properly.  Will this package ever support doing whatever the .editorconfig for a given file directs?

The editorconfig package should set the indentation settings for the editors that are open. Since my package will follow the indentation settings for whatever editor it is executed upon, by the commutative property it should already respect the .editorconfig settings you have.


[CI] Add Cypress tests to Github Actions

Adds Cypress tests to GitHub Actions.
A few changes are required for this to work correctly:
Go to project secrets and add the following secrets:
1- CYPRESS_RECORD_KEY (Available in dashboard.cypress.io)
2- CYPRESS_PROJECT_ID (ie9fhh since its easier to manage if it is not hard-coded)
3- PERCY_TOKEN
(you'll need to setup CYPRESS_PROJECT_ID in circleci as well if you want the tests to run in both platforms for the moment)

Once this is merged, we will shutdown the CircleCI integration so no need to update the env variables there.

Tests are failing because env variables are not available. I think this is probably because by default GitHub doesn't expose env variables to PR coming from forks... So annoying.
I will check this but I had a similar issue for the release workflow.

I was not aware of such limitations, the PR is small enough, you can duplicate it on your end if you'd like.

I was not aware of such limitations, the PR is small enough, you can duplicate it on your end if you'd like.

The problem is that this limitation will happen for every PR which goes against the goal of running E2E tests to check that PRs are not breaking something 🙈 .

I don't really know how to solve this and couldn't find anything from Percy side.

It seems like quite a big limitation. I think losing the Cypress video recordings is alright, but Percy is too useful.
Then lets just keep it on CircleCI ..

Yes I agree unfortunately 😞

Closing !


Wrong computation result for very large numbers

For example:
> (1 lightyear) / (1 µm)
9460730472580800000000
> ((1^10) lightyear) / (1 pm)
9460730472580800000000000000
> ((1^9) lightyear) / (1 pm)
9460730472580800000000000000

For 1^10, 1^9 just 6 zeros were added, when there should have been 10 zeros and 9 zeros added, respectively.
fend should support arbitrary precision numbers in both results and arguments.
GMP, MPFR, MPIR, and many other arbitrary precision libraries are available.

fend does support arbitrary precision. You need to write 10^10 or 10^9, not 1^10.
> (1 lightyear) / (1 µm)
9460730472580800000000
> ((10^10) lightyear) / (1 pm)
94607304725808000000000000000000000000
> ((10^9) lightyear) / (1 pm)
9460730472580800000000000000000000000


PowerBI dataset and report commands

babylon powerbi
To test the new commands proceed as follow:

Add or edit the following lines in config/platforms/platform.yaml

# Powerbi api scope
powerbi_api_scope: "https://analysis.windows.net/powerbi/api/.default"

Add or edit the following lines in config/deployments/deploy.yaml²

# Powerbi workspace id
powerbi_workspace_id: ""

Commands
Datasets
babylon powerbi dataset get-all

Should list all datasets in the given workspace
Can be checked in the powerBI web app.
babylon powerbi dataset get-all -w [workspace_id]

Should list all datasets in the given workspace
Can be checked in the powerBI web app.
Datasource
babylon powerbi dataset datasource get [dataset-id]

Should display datasource data from the given dataset
Can be checked in the powerBI web app.
babylon powerbi dataset datasource get -w [workspace_id] [dataset-id]

Should display datasource data from the given dataset in the given workspace
Can be checked in the powerBI web app.
Parameters
babylon powerbi dataset parameters get [dataset-id]

Should display parameters data from the given dataset
Can be checked in the powerBI web app.
babylon powerbi dataset parameters get -w [workspace_id] [dataset-id]

Should display parameters data from the given dataset in the given workspace
Can be checked in the powerBI web app.
babylon powerbi dataset parameters update [dataset-id]

Should update parameters data from the given dataset.
Data will use the cluster and database defined in deployment configuration.
Can be checked in the powerBI web app.
babylon powerbi dataset parameters update [dataset-id] -f [parameters-filename]

Should display parameters data from the given dataset in the given workspace
Data will use the parameters file, for an example, read templates/working_dir_template/powerbi_parameters.json.
Can be checked in the powerBI web app.
Report
babylon powerbi report get-all

Should display every report data from the given workspace
Can be checked in the powerBI web app.
babylon powerbi report download [report-id] -o test.pbix

Should download the given report in the test.pbix file.
babylon powerbi report upload [report-file.pbix]

Should upload the file to the powerbi workspace, check in the PowerBI web app.
Workspace
babylon powerbi workspace get

Should display data from the workspace defined in deploy.yml.
Can be checked in the powerBI web app.
babylon powerbi workspace get -w [workspace_id]

Should display data from the given workspace.
Can be checked in the powerBI web app.
babylon powerbi workspace get-all

Should display data from every workspace.
Can be checked in the powerBI web app.

@neomatamune ready for review ! :)


Nothing appears in iPhone when running

Hi.  I like your tutorial on https://www.appcoda.com/swiftui-first-look/ to learn how to make dynamic tableview like widget using SwiftUI programmatically.
I am trying to incorporate your concepts into my app.
Two questions:
1.) what is "some View". That does not seem to be recognized in my xcode -- the inline error says "Cannot find 'some' in scope.
2.) when I run your full sample on github, i will compile and build successfully, but when it launches on my iPhone 8 which is running iOS 14 (not a beta), a black screen appears but nothing inside.  I thought i had accidentally put dark mode on.  But I dont have dark mode turned on my phone.    I am using Xcode 12.0 beta4.
Any help would be appreciated.

And I checked the output of Xcode.
I see several of these messages.
2020-08-08 10:24:06.961397-0700 Tutors[1806:700614] [Assert] Unsupported code path for UIScene-based application.

I figured out the "some" keyword, but the app still does not run correctly.   Still black with no visible items.


Improvement: Added shell code block snippet to the commands.

This PR added the commands into the shell code snippet block which are mentioned under the Cleanup section.
Fixes #39064

hI @natalisucks @onlydole
PTAL!

Thanks
/lgtm
/approve


Silence the FileWatcher from always logging the type of watcher

@allmarkedup I hope you're OK with this proposed change! On application startup, you see one of these messages twice, and it seemed a little chatty.
If someone wants to know which watcher that is used, they can look at Lookbook.debug_data[:dependencies][:lookbook] or Lookbook::Engine.auto_refresh?.

I'm fine with this @agrobbin! Good call, thank you 👍


Replaced AWS CI badge in README for Github Actions

Removed build badge for AWS Codebuild CI,
Added build badge for Github Actions CI

Yes, I've rebased some of my sitting changes on top of that change to see whether CI completes within the context of the pinned rouille dependency, or if there are further failures.  Once #207 is merged, I'll rebase all of them onto main.

@ShaleXIONG can you approve this?

+1 reached, merging.


Support container images with mesos containerizer

This PR introduces support to launch jenkins slave with mesos containerizer within a docker image.
This allows to benefit from mesos containerizer while getting filesystem isolation.
This is my first jenkins plugin patch and I would really appreciate feedback/advices (on jelly files especially).
PR also build against latest mesos version although it is not strictly necessary (I can remove this commit if needed)

Closing since UCR support should be merged by mesosphere


[FLOC-3682] Move all blockdevice backend test helpers into a testtools package

Fixes: https://clusterhq.atlassian.net/browse/FLOC-3682
Sorry for the gigantic branch.
Thought it would be simpler to move all this stuff in one go.
Let's see if the functional tests still pass...

Looks great! One comment to consider about elaborating if and when we could stop exporting the make_XXX_tests from their old location, but in general. Ship it!
I love seeing massive files broken down into smaller bits.

The failed test above was caused by crappy Jenkins. All the tests passed.
I'm going to merge.
22:00:17 ERROR: Step ‘Publish Cobertura Coverage Report’ aborted due to exception:
22:00:17 java.io.IOException: remote file operation failed: /tmp/workspace/ClusterHQ-flocker/iblockdevice-test-reorganization-FLOC-3682/run_trial_on_AWS_Ubuntu_Trusty_flocker.control at hudson.remoting.Channel@4eb04b83:aws-ubuntu-trusty-T2Medium (i-70eda0fe): java.io.InvalidClassException: gnu.trove.map.hash.TIntObjectHashMap; local class incompatible: stream classdesc serialVersionUID = 1, local class serialVersionUID = -8351451342150980185
22:00:17 	at hudson.FilePath.act(FilePath.java:987)
22:00:17 	at hudson.FilePath.act(FilePath.java:969)
22:00:17 	at hudson.plugins.cobertura.CoberturaPublisher.perform(CoberturaPublisher.java:403)
22:00:17 	at hudson.tasks.BuildStepMonitor$3.perform(BuildStepMonitor.java:45)
22:00:17 	at hudson.model.AbstractBuild$AbstractBuildExecution.perform(AbstractBuild.java:785)
22:00:17 	at hudson.model.AbstractBuild$AbstractBuildExecution.performAllBuildSteps(AbstractBuild.java:726)
22:00:17 	at hudson.model.Build$BuildExecution.post2(Build.java:185)
22:00:17 	at hudson.model.AbstractBuild$AbstractBuildExecution.post(AbstractBuild.java:671)
22:00:17 	at hudson.model.Run.execute(Run.java:1766)
22:00:17 	at hudson.model.FreeStyleBuild.run(FreeStyleBuild.java:43)
22:00:17 	at hudson.model.ResourceController.execute(ResourceController.java:98)
22:00:17 	at hudson.model.Executor.run(Executor.java:408)

http://ci-live.clusterhq.com:8080/job/ClusterHQ-flocker/job/iblockdevice-test-reorganization-FLOC-3682/job/run_trial_on_AWS_Ubuntu_Trusty_flocker.control/5/console


Opt in/out on decorators in the global config, not the command script

At the moment, each script stores a list of decorators (e.g. decorators = ['docker']). That's flawed, because scripts don't know exactly which (future) decorators exist. Moreover, it's flawed because for some decorators it makes more sense to use an "opt-out" strategy, where you can indicate which commands do not use the decorator. Therefore, I will refactor the code so that a Decorators section in the global Dodo configuration is used to indicate which commands scripts use which decorators.
This improvement slightly complicates the use-case where a new user gets started on a project. Now, they not only need to run the dodo bootstrap command, but they also need to update the Decorators section of their global configuration.  Therefore, I will add a check-requirements function that reads a requirements file (from the res directory) and checks that:

the commands that are required for the project can be found
you have enabled the required decorators

By default, dodo check-requirements will be executed by dodo bootstrap as well, so that it's clear how to proceed after running dodo bootstrap. Possible, dodo check-requirements will also print the command lines necessary to install the missing dependencies.

Maybe there is a better solution: enable/disable the decorators directly in the project configuration, and merge in a global configuration file with default settings for enabled/disabled decorators:
DECORATORS:
docker: [autoless, django-manage, django-runserver, pytest, runpostgres, tape, webpack]
ROOT:
layers:

~/.dodo_commands/decorators.default.yaml

Solved by adding the mapping /ROOT/decorators to the configuration


Extend aggregation functionality in EnsembleForecaster

Reference Issues/PRs
Fixes #1162.
What does this implement/fix? Explain your changes.

Makes aggregation functionality more modular
Allows passing weights as hyperparameter to aggregation functions.

Does your contribution introduce a new dependency? If yes, which one?
No
What should a reviewer concentrate their feedback on?
What functions do we need to add as valid aggfuncs?
Which ones would require weights parameter (now it's just np.average)?
Any other comments?
This is first draft, I haven't added weights parameter yet.
PR checklist

[ ] I've added myself to the list of contributors.
[ ] Optionally, I've updated sktime's CODEOWNERS to receive notifications about future changes to these files.
[ ] I've added unit tests and made sure they pass locally.

@GuzalBulatova in terms of the weighting parameter I think we can add weighting to all the existing aggregation functions. See the use of from sklearn.utils.stats import _weighted_percentile in sktime\sktime\performance_metrics\forecasting\_functions.py (for example in one of the functions with median in the name). We can definitely use this for weighted medians, but possibly weighted minimums and maximums (would that just be the 0th and 100th percentiles?).
I also think if we wanted we could add the geometric mean to this aggregation function list (see _weighted_geometric_mean in same file and the regular geometric mean function in scipy.stats).
I also think it would be useful to add "trimmed means" to the aggregation function list. We could accomplish this by writing a helper function that first uses scipy.stats.trimboth and then uses np.average when there are weights and scipy.stats.trim_mean when there aren't. Note that this would require adding an additional hyper-paremeter to control the trimming that would only be used when trimmed mean was selected.
What are your thoughts?

Thank you very much @mloning I'll make suggested changes in the next commit!
@RNKuhns , thanks, I agree with you, I'll try to do this iteratively. I'll add weights to all the functions and also add weighted geometric mean first. 👍

@RNKuhns , @aiwalter , @mloning I need your advice on making the _aggregate function more readable. Is there a more concise way to write it?

@GuzalBulatova I've got a couple suggestions.
First, good news and scipy's gmean function accepts weights -- I believe it didn't when I was using it in performance metrics at first. So we can use that instead of my non-public function.
I also think we can remove the error message about weights and min/max. The 0th percentile of a list of numbers should be the minimum and the 100th percentile should be the maximum. So we should be able to call _weighted_percentile accordingly.

Remove "average" as an aggregation choice. I think we can still call that mean.
Determine what to do if weights is None versus when weights is not None

First option: default to equal weights ( 1/ # of forecasters) and use weighted agg funcs always (except min/max)
Second option: check if weights is None and if so, use non-weighted aggfuncs

I think we go with the 2nd route personally. This would involve a minor refactoring of your code to adjust check_aggfunc and _aggregate, and also creating some quick wrappers around the _weighted_percentile that calculates our percentiles of interest (e.g. 0 for min, 100 for max, 50 for median) and also has the axis paramter, so we can use the same call in _aggregate for all the functions.
Note that _weighted_median, _weighted_min, _weighted_max are my proposed names for those wrapper functions.
def _check_aggfunc(aggfunc, weighted=False):
    _weighted = 'weighted' if weighted == True else 'unweighted'
    valid_aggfuncs = {
        "mean": {'unweighted':np.mean, 'weighted':np.average},
        "median": {'unweighted':np.median, 'weighted':_weighted_median},
        "min": {'unweighted':np.min, 'weighted':_weighted_min},
        "max": {'unweighted':np.max, 'weighted':_weighted_max},
        "geomean": {'unweighted': scipy.stats.gmean, 'weighted':_scipy.stats.gmean},
    }
    if aggfunc not in valid_aggfuncs.keys():
        raise ValueError("Aggregation function %s not recognized." % aggfunc)
    return valid_aggfuncs[aggfunc][_weighted]

def _aggregate(y, aggfunc, weights):
    """Apply aggregation function by row.
    Parameters
    ----------
    y : pd.DataFrame
        Multivariate series to transform.
    aggfunc : str
        Aggregation function used for transformation.
    Returns
    -------
    y_agg: pd.Series
        Transformed univariate series.
    """
    if weights is None:
        aggfunc = _check_aggfunc(aggfunc, weighted=False)
        y_agg = aggfunc(y, axis=1)
    else:
        aggfunc = _check_aggfunc(aggfunc, weighted=True)
        y_agg = aggfunc(y, axis=1, weights=weights)

    return pd.Series(y_agg, index=y.index)

@GuzalBulatova two tweaks to the non-public wrappers on the weighted functions and a quick tweak to the tests of the function and I think this is good to go.
For each of the non-public wrappers around the weighted percentile (e.g. _weighted_median(y, weights)), we probably want the call signature to be the same as the parameters we are using in the NumPy, SciPy functions that accept weights.
Something like:
def _weighted_median(y, axis=1, weights=weights):
    ...

Other tweak to the functions is instead of of using the NumPy version of the function to reduce dimension before applying _weighted_percentile(), I think you want to depending on the supplied axis use pandas functionality to either apply these wrapper functions to each row or each column.
You'll need to either use something like pandas.apply, which lets you specify the axis (so you can pass your function's axis parameter directly to it) or use pandas.iterrows/pandas.itertuples or pandas.iteritems depending on what is passed to the axis parameter.
On the testing part, I think we should make sure there are a pair of test cases of the weighted functionality. 1 that takes a weighted median. Another that takes a weighted median.

@GuzalBulatova noticed that my above comment on testing listed weighted median twice. To clarify, I actually meant a test case that does weighted mean, one that does the weighted median, and one that tests weighted geometric mean.
That should confirm the underlying weighting functionality is all working as expected. Let me know if you want any help on setting up test cases (we'll need to setup an example where we know what the answer will be).

@GuzalBulatova I've got a minor change for you. Your module docstring is just the license information.
Per NumPy doc style, licensing info does not belong in module docstring. Can you switch that back to a comment and include a short blurb as the module docstring.
Something to the effect of module implementing ensemble forecasters that create, optionally weighted, combinations of the predictions from underlying forecasts.
Also any idea what is up with the build-and-test errors? Is that maybe related to the change to where "_update" is located? Doesn't jump out to me why the errors would be generated in the aggregation code.

@mloning thank you for the review! Yes, they should be, still I'd like to run the tests again after merging #1082 to main.


rebase: use go.mod for go version

instead of defining own go version in test files we can use go.mod to setup the required version.

Additional ref: https://github.com/actions/setup-go?tab=readme-ov-file#getting-go-version-from-the-gomod-file


Adjusting constants to deal with media gaps not reflected in manifests

What version of Shaka Player are you using? 2.0.0
Can you reproduce the issue with our latest release version? Yes
I am using Shaka to play DASH manifests from a source where the manifest reports no gap, but the underlying video segments, once loaded, do show gaps as evidenced by multiple source buffers in the video element (i.e. video.buffered.end(i+1) - video.buffered.start(i) > 0). These gaps may differ between browsers (e.g. Chrome and Firefox). In an effort to "play through" gaps, I would like the ability to dynamically control, based on the browser and/or manifest source, what are now constants, specifically:

shaka.media.TimeRangesUtils.GAP_TOLERANCE (used in shaka.media.TimeRangesUtils.bufferedAheadOf to detect media gaps)
shaka.media.Playhead.UNDERFLOW_THRESHOLD_ (used in shaka.media.Playhead.prototype.onWatchdogTimer_ to control signaling of buffering state)

Can these values be changed from constants to variables that may be adjusted at runtime?

These are good questions.  Let me give you a bit of context.
The gaps look different between Firefox and Chrome because of a series of bugs in Chrome that confuse DTS and PTS.  (http://crbug.com/373039, http://crbug.com/398130, http://crbug.com/398141, and http://crbug.com/402502, collectively tracked by us as #377.)  We expect these bugs to be fixed in Chrome eventually, at which point there should be some fair amount of consistency in gap behavior across browsers.
We are also exploring changes in Shaka Player to handle gappy content by jumping over the gaps automatically.  See #180 and #555 for details.  (You may want to subscribe to these issues so you see updates as we make them.)
So given that the Chrome team is working on fixing timestamp data in the media pipeline, and that my team is working on a way to cope with gaps no matter what the browser does, we are not interested in making those constants into variables right now.  I would guess that they would go away in a future version of Shaka Player.
In the mean time, you could certainly make them into variables in your own fork.  That's one of the benefits of open-source, after all.  We will make an announcement once we have a plan, at which point you can consider switching back to an unmodified version of Shaka Player.  Would that work for you?

Thank you for the detailed response and bigger picture perspective. I look forward to the changes coming down the pipe in future releases. In the meantime, I will make local changes on a forked version.
Thank you!


Backpack has no storage slots

Describe the bug
Backpack has no storage space
To Reproduce
Craft backpack, open backpack inventory
Expected behavior
To have slots for backpack to put things in
Screenshots
screenshot attached
Mod List (please list your mods that are being used):
Player Log attached
Additional context

Player.log

I would try to equip and unequip again, or check your config and make sure you haven't completely hosed the config.  Everything about storage is 100% configurable in the config.

So, I was able to actually reproduce this.   And I can't explain it, but on initial Valheim load, if the Explorer's Wisppack Level 1 is the first thing equipped, using default config, it'll show an empty inventory.  Unless one of the following occur:

You equip a different bag, show inventory, then equip Wisppack Level 1, and it'll show just fine.
Change Level 1 Wisppack from a 4x4 inventory configuration to any other non-square amount.

This might be a game bug.  The issue seems to not be present once the backpack has a non-square layout.  Try changing the Inventory Size on the Level 1 to be 5 width and 3 height, and you won't be able to reproduce the issue.

I have relegated myself to the fact that I can't fix this.  It works perfectly as long as the 4x4 grid is not the first grid opened. No idea why.  As a result, I have "fixed" this in 1.6.3 by making the default inventory size on the Level 1 Wisspack 8x2 instead of 4x4.


Simulate energy production

implementing the core function of a model. given a scenario, simulate energy production for a given year

will reopen another PR after I add tests


Monitor expiration of OVN certs

There is currently no monitoring for the expiry of certificates used by ovn-chassis, ovn-central and neutron-api-plugin-ovn:

/etc/ovn/cert_host
/etc/neutron/plugins/ml2/cert_host

If these certificates are left to expire, neutron-server can't talk to ovn NB and neutron API become unreachable. The NRPE relation could be extended to issue a warning or a critical based on configurable threshold that may default respectively to 30 and 15 days.

(by fnordahl)
Hello, Giuseppe, and thank you for your bug report.
Providing a way to easily monitor certificate lifetime in a system that make use of PKI for authentication and authorization is indeed important.
The OVN charms make use of Juju to integrate with an application providing the Certificate Authority and automation for Certificate Issuance, for example Vault.
Would it perhaps make sense to implement monitoring of lifetime of issued certificates in the charm/application responsible for managing the certificates instead?

(by peppepetra)
Hi Frode, thanks for your reply.
If I read correctly you are suggesting to implement the check on the application providing the certs, which in our cases for OVN is 100% of times Vault.
I see some pros and cons of this choice:
Pros:

we get out of the box monitoring for all certs provided by Vault, i.e. OpenStack API certs, Octavia certs, OVN certs etc.

Cons:

We are only monitoring the certs that are in Vault. If the distribution of these certs fails, see LP#1940549, our monitoring will miss that as it will think the certs are all renewed but in reality the certs in the ovn-chassis or ovn-central units are still the old ones as Vault failed to provide the updated ones.

To be on the safe side, I think we should always monitor what is actually being used by the applications so I would like to see these checks in the OVN charms.

(by hopem)
https://review.opendev.org/c/x/charm-ovn-central/+/887411

(by hopem)
Having looked into this a bit further I think it might actually not be possible. Nrpe checks run as the nagios user and the ovn certs have the following permissions:
ll /etc/ovn/
total 24
dr-xr-xr-x   2 root root 4096 Jun 23 13:07 ./
drwxr-xr-x 101 root root 4096 Jul  3 12:44 ../
-rw-r-----   1 root root 1532 Jun 23 13:07 cert_host
-rw-r-----   1 root root 1674 Jun 23 13:07 key_host
-rw-r--r--   1 root root 1244 Jul  3 10:50 ovn-central.crt
-rw-r-----   1 root root  211 Jun 23 13:07 ovn-northd-db-params.conf
So an nrpe check cannot read the cert file unless its permissions are opened up which I assume is not what anyone wants to do.

(by hopem)
It has been brought to my attention that we do have some charms with nrpe checks for root owned resources and they are implemented using a cron job that runs as root and performs the check itself while the nrpe check checks the output of the cron check e.g. rabbitmq-server:
https://github.com/openstack/charm-rabbitmq-server/blob/3c155e2bdaeaec5090111749a2cf366b55875575/hooks/rabbit_utils.py#L1630
Another option is to use the update-status hook, which runs by default every 5 minutes, to perform the check then store the output in a location that the nrpe check can read.

(by hudson-openstack)
Reviewed:  https://review.opendev.org/c/x/charm-ovn-central/+/887411
Committed: https://opendev.org/x/charm-ovn-central/commit/e3502b2c9c5f65ee8c0f3ed1aff8ef66c94de2f1
Submitter: "Zuul (22348)"
Branch:    master
commit e3502b2c9c5f65ee8c0f3ed1aff8ef66c94de2f1
Author: Edward Hope-Morley
Date:   Fri Jun 30 17:27:22 2023 +0100
Add ovn cert nrpe check

Certs are root readable so we use a cron job to perform
the check and save state for an nrpe check to read and
send back to nagios.

Closes-Bug: #1979539
Change-Id: I7c7cd238ddf3fd9f92bfa5879d19d78c091cf2ac

(by hudson-openstack)
Fix proposed to branch: stable/22.09
Review: https://review.opendev.org/c/x/charm-ovn-central/+/895021

(by hudson-openstack)
Fix proposed to branch: stable/23.03
Review: https://review.opendev.org/c/x/charm-ovn-central/+/895022

(by hudson-openstack)
Fix proposed to branch: master
Review: https://review.opendev.org/c/x/charm-ovn-chassis/+/896409

(by eric-chen)
decide not to implement it in charm-openstack-service-checks , so mark it as invalid

(by hudson-openstack)
Reviewed:  https://review.opendev.org/c/x/charm-ovn-chassis/+/896409
Committed: https://opendev.org/x/charm-ovn-chassis/commit/fec04c22a84e5be8867712f3c925efef69d64d70
Submitter: "Zuul (22348)"
Branch:    master
commit fec04c22a84e5be8867712f3c925efef69d64d70
Author: Edward Hope-Morley
Date:   Mon Sep 25 16:27:48 2023 +0100
Add ovn cert nrpe check

Certs are root readable so we use a cron job to perform
the check and save state for an nrpe check to read and
send back to nagios.

Closes-Bug: #1979539
Change-Id: Ia6df3fc2e3bc0d64ef2128ed65959a5d2d9b3d62


Make filters more visible

Filters have to be more visible, it's not clear where are they

Maybe we can add something like a filter button in the proximity of search

done


Maya: Speed up validate mesh shader connections for large scenes

(cherry picked from commit 46752511e500a54ba9335a325ca09224ef600227)
Brief description
This optimizes the Validate Mesh Shader connection for large scenes - that is scenes with many objects that e.g. all have the lambert1 assigned in a model scene.
Description
Instead of querying the members of e.g. the lambert1 shading engine per object it caches the members during the process to speed up the query. This can make it go down from many seconds on a large scene to near instant.
Testing notes:

Publish some models from large and small scenes - confirm it passes fine as before and is faster.

@antirotor please check this PR?


Support Sid based exclusion

We could use Sid's with a certain prefix (something like RKIGNORE) to exclude statements from repoing.  This would allow us to preserve some parts of an inline policy without excluding the entire role from repo.
In order to support this we need to:

create a new option in config: something like sid_ignore_prefix
add the sid_ignore_prefix check in the right places.  We still want to see these statements and store them for rolling back and searching perms but we want to exclude permissions that are included in these statements when making policy suggestions and performing repo.

Some functions that are going to need to change:

_get_repoed_policy, _get_role_permissions, _get_permissions_in_policy

This is a decent amount of work so we're going to want to make sure we're rock solid here by adding tests, etc.  Finally we'll need to update the documentation to describe this new option.

This was fixed in #219


OSError: [Errno 22] Invalid argument

@hanzhanggit
@taoxugit
please help me, what is the main problem behind this?
(base) H:\StackGAN\StackGAN-Pytorch-master\code>python main.py --cfg cfg/coco_eval.yml --gpu 0
Using config:
{'CONFIG_NAME': 'stageI',
'CUDA': True,
'DATASET_NAME': 'coco',
'DATA_DIR': '../data/coco',
'EMBEDDING_TYPE': 'cnn-rnn',
'GAN': {'CONDITION_DIM': 128, 'DF_DIM': 96, 'GF_DIM': 192, 'R_NUM': 4},
'GPU_ID': '0',
'IMSIZE': 64,
'NET_D': '',
'NET_G': '',
'STAGE': 1,
'STAGE1_G': '',
'TEXT': {'DIMENSION': 1024},
'TRAIN': {'BATCH_SIZE': 128,
'COEFF': {'KL': 2.0},
'DISCRIMINATOR_LR': 0.0002,
'FLAG': True,
'GENERATOR_LR': 0.0002,
'LR_DECAY_EPOCH': 20,
'MAX_EPOCH': 120,
'PRETRAINED_EPOCH': 600,
'PRETRAINED_MODEL': '',
'SNAPSHOT_INTERVAL': 10},
'VIS_COUNT': 64,
'WORKERS': 4,
'Z_DIM': 100}
Load filenames from: ../data/coco\train\filenames.pickle (82783)
embeddings:  (82783, 5, 1024)
This section is run successfully...
STAGE1_G(
(ca_net): CA_NET(
(fc): Linear(in_features=1024, out_features=256, bias=True)
(relu): ReLU()
)
(fc): Sequential(
(0): Linear(in_features=228, out_features=24576, bias=False)
(1): BatchNorm1d(24576, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(2): ReLU(inplace)
)
(upsample1): Sequential(
(0): Upsample(scale_factor=2, mode=nearest)
(1): Conv2d(1536, 768, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
(2): BatchNorm2d(768, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(3): ReLU(inplace)
)
(upsample2): Sequential(
(0): Upsample(scale_factor=2, mode=nearest)
(1): Conv2d(768, 384, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
(2): BatchNorm2d(384, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(3): ReLU(inplace)
)
(upsample3): Sequential(
(0): Upsample(scale_factor=2, mode=nearest)
(1): Conv2d(384, 192, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
(2): BatchNorm2d(192, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(3): ReLU(inplace)
)
(upsample4): Sequential(
(0): Upsample(scale_factor=2, mode=nearest)
(1): Conv2d(192, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
(2): BatchNorm2d(96, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(3): ReLU(inplace)
)
(img): Sequential(
(0): Conv2d(96, 3, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
(1): Tanh()
)
)
STAGE1_D(
(encode_img): Sequential(
(0): Conv2d(3, 96, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
(1): LeakyReLU(negative_slope=0.2, inplace)
(2): Conv2d(96, 192, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
(3): BatchNorm2d(192, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(4): LeakyReLU(negative_slope=0.2, inplace)
(5): Conv2d(192, 384, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
(6): BatchNorm2d(384, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(7): LeakyReLU(negative_slope=0.2, inplace)
(8): Conv2d(384, 768, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
(9): BatchNorm2d(768, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(10): LeakyReLU(negative_slope=0.2, inplace)
)
(get_cond_logits): D_GET_LOGITS(
(outlogits): Sequential(
(0): Conv2d(896, 768, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
(1): BatchNorm2d(768, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(2): LeakyReLU(negative_slope=0.2, inplace)
(3): Conv2d(768, 1, kernel_size=(4, 4), stride=(4, 4))
(4): Sigmoid()
)
)
)
Preparing training data...
Traceback (most recent call last):
File "main.py", line 77, in
algo.train(dataloader, cfg.STAGE)
File "H:\StackGAN\StackGAN-Pytorch-master\code\trainer.py", line 158, in train
for i, data in enumerate(data_loader, 0):
File "C:\ProgramData\Anaconda3\lib\site-packages\torch\utils\data\dataloader.py", line 501, in iter
return _DataLoaderIter(self)
File "C:\ProgramData\Anaconda3\lib\site-packages\torch\utils\data\dataloader.py", line 289, in init
w.start()
File "C:\ProgramData\Anaconda3\lib\multiprocessing\process.py", line 105, in start
self._popen = self._Popen(self)
File "C:\ProgramData\Anaconda3\lib\multiprocessing\context.py", line 223, in _Popen
return _default_context.get_context().Process._Popen(process_obj)
File "C:\ProgramData\Anaconda3\lib\multiprocessing\context.py", line 322, in _Popen
return Popen(process_obj)
File "C:\ProgramData\Anaconda3\lib\multiprocessing\popen_spawn_win32.py", line 65, in init
reduction.dump(process_obj, to_child)
File "C:\ProgramData\Anaconda3\lib\multiprocessing\reduction.py", line 60, in dump
ForkingPickler(file, protocol).dump(obj)
OSError: [Errno 22] Invalid argument

Same issue. Did you solve it somehow?

@matteobsu No dear it's still error I think it's because of memory space. now I am training the tensorflow version of this.

So I Think I actually solved it. Try to open:
C:\ProgramData\Anaconda3\lib\multiprocessing\reduction.py
and replace
ForkingPickler(file, protocol).dump(obj)
with
ForkingPickler(file, protocol).dumps(obj)
at line 60

I changed it to dumps but I got this error:
Traceback (most recent call last):
File "", line 1, in
File "D:\Anaconda\lib\multiprocessing\spawn.py", line 105, in spawn_main
exitcode = _main(fd)
File "D:\Anaconda\lib\multiprocessing\spawn.py", line 113, in _main
preparation_data = reduction.pickle.load(from_parent)
EOFError: Ran out of input
Traceback (most recent call last):
File "", line 1, in
File "D:\Anaconda\lib\multiprocessing\spawn.py", line 105, in spawn_main
exitcode = _main(fd)
File "D:\Anaconda\lib\multiprocessing\spawn.py", line 113, in _main
preparation_data = reduction.pickle.load(from_parent)
EOFError: Ran out of input
Traceback (most recent call last):
File "D:\Anaconda\lib\site-packages\torch\utils\data\dataloader.py", line 724, in _try_get_data
data = self._data_queue.get(timeout=timeout)
File "D:\Anaconda\lib\multiprocessing\queues.py", line 105, in get
raise Empty
_queue.Empty
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "E:/Python文件/机器学习/lab06NN/MyNN.py", line 57, in
for i, data in enumerate(trainloader, 0):
File "D:\Anaconda\lib\site-packages\torch\utils\data\dataloader.py", line 804, in next
idx, data = self._get_data()
File "D:\Anaconda\lib\site-packages\torch\utils\data\dataloader.py", line 771, in _get_data
success, data = self._try_get_data()
File "D:\Anaconda\lib\site-packages\torch\utils\data\dataloader.py", line 737, in _try_get_data
raise RuntimeError('DataLoader worker (pid(s) {}) exited unexpectedly'.format(pids_str))
RuntimeError: DataLoader worker (pid(s) 7668, 8988) exited unexpectedly
How to solve the runtime error?

I changed it to dumps but I got this error:
Traceback (most recent call last):
File "", line 1, in
File "D:\Anaconda\lib\multiprocessing\spawn.py", line 105, in spawn_main
exitcode = _main(fd)
File "D:\Anaconda\lib\multiprocessing\spawn.py", line 113, in _main
preparation_data = reduction.pickle.load(from_parent)
EOFError: Ran out of input
Traceback (most recent call last):
File "", line 1, in
File "D:\Anaconda\lib\multiprocessing\spawn.py", line 105, in spawn_main
exitcode = _main(fd)
File "D:\Anaconda\lib\multiprocessing\spawn.py", line 113, in _main
preparation_data = reduction.pickle.load(from_parent)
EOFError: Ran out of input
Traceback (most recent call last):
File "D:\Anaconda\lib\site-packages\torch\utils\data\dataloader.py", line 724, in _try_get_data
data = self._data_queue.get(timeout=timeout)
File "D:\Anaconda\lib\multiprocessing\queues.py", line 105, in get
raise Empty
_queue.Empty
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "E:/Python文件/机器学习/lab06NN/MyNN.py", line 57, in
for i, data in enumerate(trainloader, 0):
File "D:\Anaconda\lib\site-packages\torch\utils\data\dataloader.py", line 804, in next
idx, data = self._get_data()
File "D:\Anaconda\lib\site-packages\torch\utils\data\dataloader.py", line 771, in _get_data
success, data = self._try_get_data()
File "D:\Anaconda\lib\site-packages\torch\utils\data\dataloader.py", line 737, in _try_get_data
raise RuntimeError('DataLoader worker (pid(s) {}) exited unexpectedly'.format(pids_str))
RuntimeError: DataLoader worker (pid(s) 7668, 8988) exited unexpectedly
How to solve the runtime error?

Have you solved the this new error?  I have met exactly the same problems with you.

Had a similar issue using multiprocessing, in my case I saw the RAM going to 100.0% in the task manager just before the issue appears. I never had this issue on another computer with more RAM, so I guess it is an error related to RAM overflow (or a process that can't wait long enough until something useful is returned from the memory in case the RAM is full).
Workaround: decrease RAM usage (either in your python script or by closing other programs).

I was able to make it work after a week of trial and error going through the internet and testing each possible way. I did two things. In my case, I was using LdaMulticore which is in gensim.models:
from gensim.models import LdaMulticore
My code was:
lda = LdaMulticore(input_text, num_topics=topic_num, id2word=dictionary, passes=1, workers=8)
I solved it by removing passes=1 and workers=8 totally which led to my code being:
lda = LdaMulticore(input_text, num_topics=topic_num, id2word=dictionary)
as suggested in: https://stackoverflow.com/questions/70218051/oserror-errno-22-invalid-argument-pickle-unpicklingerror-pickle-data-was.
At first, it didn't work.  I created a fresh new environment. Added all the libraries that I used (without requirements.txt since I was suspecting maybe it is a dependency thing). Then VOILA! It is now running like a charm!
In conclusion, first, remove the workers and passes in your code. Secondly, create a fresh new venv (virtual environment) and install all your packages, then try. I hope this works for everyone.


How to rotate two kinematic zero-mass boxes as a group (around shared pivot point in the center) with angularVelocity?

Hi!
I'm trying to make two independent kinematic zero-mass boxes which are going to rotate around their shared pivot point like two bodies are rotating in a group. However I wasn't able to find any solution for grouping cannon bodies. Grouping shapes could be a temporary solution, but in case I would like to keep my boxes separate from each other, I will have to group each box with a second shape which will balance the pivot points (and it seems like a horrible solution to me).
For example a simple setup of two 3x2x3 boxes facing each other like this one:
        upBody = new CANNON.Body({
            mass: 0,
            type: CANNON.Body.KINEMATIC,
            position: new CANNON.Vec3(10,30,0),
            shape: new CANNON.Box(new CANNON.Vec3(1.5,1,1.5))
        });
        world.addBody(upBody);

        lowBody = new CANNON.Body({
            mass: 10,
            type: CANNON.Body.KINEMATIC,
            position: new CANNON.Vec3(10,20,0),
            shape: new CANNON.Box(new CANNON.Vec3(1.5,1,1.5))
        });
        world.addBody(lowBody);

What's the most accurate way to implement this kind of rotation can you advise? e.g. rotating them both with applied angularVelocity so both bodies stay parallel to each other.

Why not create a single body with two box shapes in it?


Maybe add Death toll

Well i dont know the right term. But what i'm referring to is the tax when dieing at vorkath and having to pay the 100k. Make it so the 100k is added as a supply.

I did work on a version of this before and it was buggy but I think I have a better way to do it, I'll try to add it thanks for the suggestion!

added with latest commit


llvmPackages_{12,13,14,15,16,17,18,git}.clang: fix libLTO.dylib path

Description of changes
Clang assumes that libLTO.dylib is located at ../lib in the same prefix as clang, but that’s not true in nixpkgs. libLTO.dylib is actually located at libllvm^lib/lib.libLTO.dylib.
This is the first piece to fixing LTO on Darwin. The other is updating ld64, which I will be doing in a separate PR later this week. This PR does not depend on that PR because there is no harm passing the correct path to ld64. It does not perform LTO by default, and trying to use -flto even with the correct path remains broken.
Testing was done using my WIP PR for ld64 with clang 16. See https://github.com/NixOS/nixpkgs/issues/19098#issuecomment-2041752524 for output. It can also be validated by setting NIX_DEBUG=1 when running clang, then confirming that the path passed to -lto_library actually exists in the store.
Note: Testing was done on https://github.com/NixOS/nixpkgs/pull/302481. I’m building against the common clang branch now.
Things done

Built on platform(s)

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

@RossComputerGuy I rebased and consolidated the patches. Thanks for your work on https://github.com/NixOS/nixpkgs/pull/303948.

@reckenrode Do you want this in 24.05?

@reckenrode Do you want this in 24.05?

It would be nice, but it’s only half the fix to LTO on Darwin. The other half is the ld64 upgrade, which is probably too big for 24.05. I’m still working through getting all the Darwin blocker failures to build.

This pull request has been mentioned on NixOS Discourse. There might be relevant details there:
https://discourse.nixos.org/t/darwin-ld-symbol-s-not-found-for-architecture-arm64/46177/1


timestamp sensor 32-bit? year 2038 overflow?

Sorry, I'm new to BTHome and just want to make sure the timestamp is futureproofed.
Is the timestamp sensor a 32-bit or 48-bit number?
https://bthome.io/format/ says "uint48 (4 bytes)" which seems ambiguous, unless I'm misunderstanding the info.
If it's only 32-bit, then it'll overflow in 2038! https://en.wikipedia.org/wiki/Year_2038_problem
BTW, it might be a good idea to add webpage #anchors to all BTHome.io webpages that have multiple/long sections to them so it's easy for someone to deep-link.

It’s 4 bytes, excl. the byte for the sensor type. I see I made same errors in the example and in the table the example should be 0x50 5d396164, so 4 bytes following 0x50 for timestamp. I’ll change that.
With 0x50 ffffffff We get<PHONE_NUMBER> as integer, which is Sunday 7 February 2106 06:28:15 in epoch time.

Ah, I didn’t recognize that timestamp was also unsigned which helps it last a bit longer. ;) If this is acceptable by other devs in the general HA world, I’m good with it.

By the time we get close to 2108 I’ll add a 5 byte long timestamp, if I still live. Help me remember by that time 😄

Saw this issue but I am still not clear, why the table says uint48 (4 bytes). uint48 would be 6 bytes but all examples (and the parenthesis) hint at 4 bytes so uint32.


WFLY-6552 NPE when absolute ordering is used and a web fragment is mi…

…ssing

Linux Build 9495 outcome was FAILURE using a merge of f65a3b1f777a4f237a4832c77e92c1712551aa47
Summary: Tests failed: 1 (1 new), passed: 3330, ignored: 195 Build time: 01:16:51
Failed tests
org.jboss.as.test.clustering.cluster.web.passivation.CoarseSessionPassivationTestCase(SYNC-tcp).test: java.lang.AssertionError: response doesn't contain header 'result', all response headers = {name=Connection, value=keep-alive}, {name=gTC8Hqv3nzA5vYjaTknt38ZgK2js-tzVGlRW3qTF, value=PASSIVATION}, {name=X-Powered-By, value=Undertow/1}, {name=Set-Cookie, value=JSESSIONID=dH2Dl_RQudIbeacBP9jbDS1NpFcxTvBOqnwjhCHA.node-0; path=/passivation}, {name=Server, value=WildFly/10}, {name=Content-Length, value=0}, {name=jsessionid, value=dH2Dl_RQudIbeacBP9jbDS1NpFcxTvBOqnwjhCHA}, {name=Date, value=Thu, 05 May 2016 22:07:54 GMT},
	at org.jboss.as.test.clustering.cluster.web.passivation.SessionPassivationTestCase.getRequiredHeaderValue(SessionPassivationTestCase.java:207)
	at org.jboss.as.test.clustering.cluster.web.passivation.SessionPassivationTestCase.test(SessionPassivationTestCase.java:153)
------- Stdout: -------
15:07:53,893 INFO  [org.jboss.as.test.clustering.NodeUtil] (main) Starting deployment=NONE, container=container-0
15:07:53,893 INFO  [org.jboss.as.test.clustering.NodeUtil] (main) Starting deployment=NONE, container=container-1
15:07:53,893 INFO  [org.jboss.as.test.clustering.NodeUtil] (main) Deploying deployment=deployment-0
 [0m15:07:53,911 INFO  [org.jboss.as.repository] (management-handler-thread - 3) WFLYDR0001: Content added at location /opt/buildAgent/work/a31d203e70e89f90/testsuite/integration/clustering/target/wildfly-SYNC-tcp-0/standalone/data/content/23/a9ccb72963e5c2ad937e37ccc669659c467ad8/content
 [0m [0m15:07:53,914 INFO  [org.jboss.as.server.deployment] (MSC service thread 1-6) WFLYSRV0027: Starting deployment of "passivation.war" (runtime-name: "passivation.war")
 [0m [0m15:07:53,990 INFO  [org.infinispan.configuration.cache.EvictionConfigurationBuilder] (ServerService Thread Pool -- 81) ISPN000152: Passivation configured without an eviction policy being selected. Only manually evicted entities will be passivated.
 [0m [0m15:07:53,990 INFO  [org.infinispan.configuration.cache.EvictionConfigurationBuilder] (ServerService Thread Pool -- 81) ISPN000152: Passivation configured without an eviction policy being selected. Only manually evicted entities will be passivated.
 [0m [0m15:07:53,993 INFO  [org.infinispan.configuration.cache.EvictionConfigurationBuilder] (ServerService Thread Pool -- 81) ISPN000152: Passivation configured without an eviction policy being selected. Only manually evicted entities will be passivated.
 [0m [0m15:07:53,993 INFO  [org.infinispan.configuration.cache.EvictionConfigurationBuilder] (ServerService Thread Pool -- 81) ISPN000152: Passivation configured without an eviction policy being selected. Only manually evicted entities will be passivated.
 [0m [0m15:07:54,002 INFO  [org.infinispan.configuration.cache.EvictionConfigurationBuilder] (ServerService Thread Pool -- 83) ISPN000152: Passivation configured without an eviction policy being selected. Only manually evicted entities will be passivated.
 [0m [0m15:07:54,003 INFO  [org.infinispan.configuration.cache.EvictionConfigurationBuilder] (ServerService Thread Pool -- 83) ISPN000152: Passivation configured without an eviction policy being selected. Only manually evicted entities will be passivated.
 [0m [0m15:07:54,065 INFO  [org.jboss.as.clustering.infinispan] (ServerService Thread Pool -- 83) WFLYCLINF0002: Started routing cache from web container
 [0m [0m15:07:54,065 INFO  [org.jboss.as.clustering.infinispan] (ServerService Thread Pool -- 81) WFLYCLINF0002: Started passivation.war cache from web container
 [0m [0m15:07:54,086 INFO  [org.wildfly.extension.undertow] (ServerService Thread Pool -- 81) WFLYUT0021: Registered web context: /passivation
 [0m [0m15:07:54,096 INFO  [org.jboss.as.server] (management-handler-thread - 3) WFLYSRV0010: Deployed "passivation.war" (runtime-name : "passivation.war")
 [0m15:07:54,116 INFO  [org.jboss.as.test.clustering.NodeUtil] (main) Deploying deployment=deployment-1
 [0m15:07:54,133 INFO  [org.jboss.as.repository] (management-handler-thread - 1) WFLYDR0001: Content added at location /opt/buildAgent/work/a31d203e70e89f90/testsuite/integration/clustering/target/wildfly-SYNC-tcp-1/standalone/data/content/ac/5dc78bbfa19c822c7d2226ca743b7b7e3f6a27/content
 [0m [0m15:07:54,136 INFO  [org.jboss.as.server.deployment] (MSC service thread 1-6) WFLYSRV0027: Starting deployment of "passivation.war" (runtime-name: "passivation.war")
 [0m [0m15:07:54,250 INFO  [org.infinispan.configuration.cache.EvictionConfigurationBuilder] (ServerService Thread Pool -- 78) ISPN000152: Passivation configured without an eviction policy being selected. Only manually evicted entities will be passivated.
 [0m [0m15:07:54,259 INFO  [org.infinispan.configuration.cache.EvictionConfigurationBuilder] (ServerService Thread Pool -- 78) ISPN000152: Passivation configured without an eviction policy being selected. Only manually evicted entities will be passivated.
 [0m [0m15:07:54,265 INFO  [org.infinispan.configuration.cache.EvictionConfigurationBuilder] (ServerService Thread Pool -- 78) ISPN000152: Passivation configured without an eviction policy being selected. Only manually evicted entities will be passivated.
 [0m [0m15:07:54,265 INFO  [org.infinispan.configuration.cache.EvictionConfigurationBuilder] (ServerService Thread Pool -- 78) ISPN000152: Passivation configured without an eviction policy being selected. Only manually evicted entities will be passivated.
 [0m [0m15:07:54,274 INFO  [org.infinispan.configuration.cache.EvictionConfigurationBuilder] (ServerService Thread Pool -- 81) ISPN000152: Passivation configured without an eviction policy being selected. Only manually evicted entities will be passivated.
 [0m [0m15:07:54,275 INFO  [org.infinispan.configuration.cache.EvictionConfigurationBuilder] (ServerService Thread Pool -- 81) ISPN000152: Passivation configured without an eviction policy being selected. Only manually evicted entities will be passivated.
 [0m [0m15:07:54,290 INFO  [org.infinispan.CLUSTER] (ServerService Thread Pool -- 81) ISPN000310: Starting cluster-wide rebalance for cache routing, topology CacheTopology{id=1, rebalanceId=1, currentCH=DefaultConsistentHash{ns=80, owners = (1)[node-0: 80+0]}, pendingCH=DefaultConsistentHash{ns=80, owners = (2)[node-0: 40+40, node-1: 40+40]}, unionCH=null, actualMembers=[node-0, node-1]}
 [0m [0m15:07:54,321 INFO  [org.infinispan.CLUSTER] (ServerService Thread Pool -- 78) ISPN000310: Starting cluster-wide rebalance for cache passivation.war, topology CacheTopology{id=1, rebalanceId=1, currentCH=DefaultConsistentHash{ns=80, owners = (1)[node-0: 80+0]}, pendingCH=DefaultConsistentHash{ns=80, owners = (2)[node-0: 40+40, node-1: 40+40]}, unionCH=null, actualMembers=[node-0, node-1]}
 [0m [0m15:07:54,343 INFO  [org.infinispan.CLUSTER] (transport-thread--p19-t24) ISPN000336: Finished cluster-wide rebalance for cache routing, topology id = 1
 [0m [0m15:07:54,344 INFO  [org.jboss.as.clustering.infinispan] (ServerService Thread Pool -- 81) WFLYCLINF0002: Started routing cache from web container
 [0m [0m15:07:54,353 INFO  [org.infinispan.CLUSTER] (transport-thread--p19-t7) ISPN000336: Finished cluster-wide rebalance for cache passivation.war, topology id = 1
 [0m [0m15:07:54,354 INFO  [org.jboss.as.clustering.infinispan] (ServerService Thread Pool -- 78) WFLYCLINF0002: Started passivation.war cache from web container
 [0m [0m15:07:54,365 INFO  [org.wildfly.extension.undertow] (ServerService Thread Pool -- 78) WFLYUT0021: Registered web context: /passivation
 [0m [0m15:07:54,374 INFO  [org.jboss.as.server] (management-handler-thread - 1) WFLYSRV0010: Deployed "passivation.war" (runtime-name : "passivation.war")
 [0m [0m15:07:54,408 INFO  [stdout] (default task-34) http://[::1]:8080/passivation/listener?operation=set&name=a&value=1;jsessionid=gTC8Hqv3nzA5vYjaTknt38ZgK2js-tzVGlRW3qTF
 [0m [0m15:07:54,457 INFO  [stdout] (default task-35) http://[::1]:8080/passivation/listener?operation=set&name=a&value=2;jsessionid=4zQCJGRgGZx7XDDqPFF1ygoWp-TMcL2a7m3428kf
 [0m [0m15:07:54,469 INFO  [stdout] (default task-36) http://[::1]:8080/passivation/listener?operation=get&name=a;jsessionid=gTC8Hqv3nzA5vYjaTknt38ZgK2js-tzVGlRW3qTF
 [0m [0m15:07:54,516 INFO  [stdout] (default task-37) http://[::1]:8080/passivation/listener?operation=get&name=a;jsessionid=dH2Dl_RQudIbeacBP9jbDS1NpFcxTvBOqnwjhCHA
 [0m15:07:54,520 INFO  [org.jboss.as.test.clustering.NodeUtil] (main) Starting deployment=NONE, container=container-0
15:07:54,520 INFO  [org.jboss.as.test.clustering.NodeUtil] (main) Starting deployment=NONE, container=container-1
15:07:54,521 INFO  [org.jboss.as.test.clustering.NodeUtil] (main) Undeploying deployment=deployment-0
 [0m15:07:54,571 INFO  [org.wildfly.extension.undertow] (ServerService Thread Pool -- 83) WFLYUT0022: Unregistered web context: /passivation
 [0m [0m15:07:54,593 INFO  [org.infinispan.eviction.impl.PassivationManagerImpl] (ServerService Thread Pool -- 80) ISPN000029: Passivating all entries to disk
 [0m [0m15:07:54,594 INFO  [org.infinispan.eviction.impl.PassivationManagerImpl] (ServerService Thread Pool -- 80) ISPN000030: Passivated 5 entries in 1 milliseconds
 [0m [0m15:07:54,611 INFO  [org.jboss.as.clustering.infinispan] (ServerService Thread Pool -- 80) WFLYCLINF0003: Stopped passivation.war cache from web container
 [0m [0m15:07:54,622 INFO  [org.jboss.as.server.deployment] (MSC service thread 1-4) WFLYSRV0028: Stopped deployment passivation.war (runtime-name: passivation.war) in 79ms
 [0m [0m15:07:54,633 INFO  [org.jboss.as.clustering.infinispan] (ServerService Thread Pool -- 79) WFLYCLINF0003: Stopped routing cache from web container
 [0m [0m15:07:54,644 INFO  [org.jboss.as.repository] (management-handler-thread - 4) WFLYDR0002: Content removed from location /opt/buildAgent/work/a31d203e70e89f90/testsuite/integration/clustering/target/wildfly-SYNC-tcp-0/standalone/data/content/23/a9ccb72963e5c2ad937e37ccc669659c467ad8/content
 [0m [0m15:07:54,645 INFO  [org.jboss.as.server] (management-handler-thread - 4) WFLYSRV0009: Undeployed "passivation.war" (runtime-name: "passivation.war")


[fuzzing] suppress leak in json-rpc runtime mock

Motivation
Suppress the indirect mem leak in json-rpc's mempool runtime mock.
Test Plan
Tested with local fuzzing runs.

@bors-libra r= christinacelee

:pushpin: Commit 237e3e0 has been approved by ``

@bors-libra r=christinacelee

:pushpin: Commit 237e3e0 has been approved by christinacelee

:hourglass: Testing commit 237e3e0642faf90533acd5f560feda3e68598c6f with merge 8827c531f6cb2c88df6888bd096cc38583f9e28c...

:sunny: Test successful - checks-actions_land_blocking_test, checks-circle_commit_workflow
Approved by: christinacelee
Pushing 8827c531f6cb2c88df6888bd096cc38583f9e28c to master...


currently patched

currently i tried with checker and it gives me all invalid when they are not,
and in joiner it gives:
Illegal header value b'OTY1OTMxNTUxMjQwMTEwMTAw.Yl6X_g.l2jskjXBjp9YcOy2SfruQnOwOmY '
so yea discord patched all the tools, we would really like if you unpatch this like vanshaj did, because you are really helping us to raid server with this tool, and so if you fix it im sure i will give you a little donation.
keep it up

put token whitout "" or ''

Yep, i have noticed this problem, I am working on a fix with a couple of new features that are 🔥.


bug

I didn't receive the Xml

I had the same issue.


Fix issue on Neovim v0.2.0 or drop that support

https://travis-ci.org/lambdalisue/vital-Whisky/jobs/553067393
I think dropping v0.2.0 is fair enough.

Dropped.


webview node integeration on & require 'module'

I have a webrower-plus(http://atom.io/packages/browser-plus) package for atom. and I am using webview with node-integeration-on but this has problem when showing web pages which has require module...https://github.com/skandasoft/browser-plus/issues/18

Looks like the node require is getting in the way. I suspect you'd need to do some sort of "intelligent" switching around to move it out of the way, eg. assigning the node require to another variable so requirejs's require could work. The "intelligent" part is magic because if you are using node-integration and loading random pages off the net that use requirejs then things are going to get ugly unless you can "know" eg parse the pages to see if they use requirejs or some other require that would break your webview.
Having node integration turned on for a web browser plugin seems very risky unless you know exactly what and have control over the pages you are loading.

I have move away from node-integeration on for the browser-plus..I am not sure if this ticked is need to open to check the possibility for node-integeration with require module

This is a quite classic problem of browsers with node integration, see also:
https://github.com/nwjs/nw.js/wiki/faq-name-conflict


trivial-builders.nix: Add input argument passthru to makeSetupHook

This patch add an input argumnet passthru to makeSetupHook, and enable users to specify passthru attributes the way they specify the meta attributes in makeSetupHook
One significant use case is adding passthru.tests to setup-hooks,
and help increase test coverage for mission-critical setup-hooks.
The Nix expression of postgresqlTestHook has been updated to make use of the passthru attirbute. (No overrideAttrs are needed now.) This should evaluates to the same output as before.
wrapGappsHook could also be updated. However, as it currently passes the passthru through substitutions (weird enough), the modification would change the derivation hash, resulting in a large-scale rebuild. A successive PR will be made targeting the staging branch as this one gets merged.
Cc: @roberth postgresqlTestHook maintainer
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

[X] 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
[ ] Tested basic functionality of all binary files (usually in ./result/bin/) (Nothing has changed.)
22.11 Release Notes (or backporting 22.05 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
[ ] (Release notes changes) Ran nixos/doc/manual/md-to-db.sh to update generated release notes

[X] Fits CONTRIBUTING.md.

Just notice that passing passthru = { }; breaks nixpkgs-review's and OfBorg's evaluation of outputs.
Now it is only passed when specified by the user.

@ofborg build postgresqlTestHook postgresqlTestHook.passthru.tests

I think I've found the problem.
@ofborg build postgresqlTestHook postgresqlTestHook.passthru.tests firefox-esr gnome3.zenity

I see it now. Some hooks ends up specifying  passthru inside substitute, causing conflict when another passthru = { } is specified by the inheritance of the default value.

I see it now. Some hooks ends up specifying  passthru inside substitutions, causing conflict when another passthru = { } is specified by the inheritance of the default value.
To deprecate the substitutions.passthru, we'll have to correct all the hooks using such pattern. If the substitutions attribute set contains nothing else, the build script of the hook will change, leading to the change of the derivation hash. One such hook is wrapGApps, the change of which will definitely trigger a mass rebuild.

Hmm, I didn't expect a mass rebuild, but like you say, I've changed the outcome of lib.optionalString (substitutions != {}).

To deprecate the substitutions.passthru, we'll have to correct all the hooks using such pattern.

That's what I did.
wrapGAppsHook is the only one for which builder changes. I've checked that the hook script does not rely on unspecified variables to be substituted, so this change should not pose a problem.
I'll change the branch to staging.

The Ofborg failure is probably a wrapGAppsHook.passthru.tests issue, as this PR should not even change the build process.

@roberth @Ericson2314 Anything else I could help to get it merge?


Install hirak/prestissimo globally on the php containe

Any reason against installing hirak/prestissimo globally on the php container?
Just trying out ddev and find it odd it wasn't already installed. Performance-wise is a very good improvement.

Depends on how many use the app container for composer install

This would be great!

I haven't used prestissimo before, so I don't know if it possibly has a side effect on normal install processes with composer.
Also it's very easy to install by yourself if you really need it.
hooks:
  post-start:
    - exec: composer global require hirak/prestissimo

So, from my point of view it's not really necessary to include it.
But: If it doesn't kill my composer setups and speeds things up a bit, why not.

I went ahead and did a PR #1654  to add hirak/prestissimo, would love any feedback. You can just temporarily add webimage: drud/ddev-webserver:20190618_prestissimo to your .ddev/config.yaml file and do a composer build.


Having issue on EnvironmentFileNotFound

Describe the bug
(base) samchen@Sams-MacBook-Pro miniconda3 % conda env create -f environment.yml
EnvironmentFileNotFound: '/Users/samchen/miniconda3/environment.yml' file not found
To Reproduce
Steps to reproduce the behavior:

Install miniconda3
run " conda env create -f environment.yml"

Expected behavior
Should be move to next step
Screenshots
(base) samchen@Sams-MacBook-Pro miniconda3 % conda env create -f environment.yml
EnvironmentFileNotFound: '/Users/samchen/miniconda3/environment.yml' file not found
Desktop (please complete the following information):

OS: [MacOS]

Additional context
Add any other context about the problem here.

Thanks. Let me try again


IDS-696: update test data to be freely licensed

@nrempel not sure how much of this you want to review in detail, but please have a look. Also happy to get questions about where it's not obvious why/how something is done so I can clarify the code or add more comments.

Does it make sense to keep the data files out of git?

We had them in git before. I think we wanted to make them easy to get to for users, but I suppose we could do that some other way. What alternative way of hosting these files would you suggest?

Are the files available from where you originally downloaded them? Could we download and cache the files on first run of the test? I don't think it's a horrible offence to have the data files checked in but it's nice to keep the git repo lean.

The data files we have checked in after this PR are generated, so they are not available from anywhere. We could put them up for downloads somewhere (I suppose we can upload assets to GitHub somehow), but then having to download them for the tests adds substantial complexity (pulling in more dependencies, etc). It's 6 MB but at least it's text so it diffs well.
(BTW, we already have the current data files checked in, so this discussion is largely orthogonal to this PR.)

Ah, yes in that case keeping the data in git seems like the best solution!


govulncheck results

Hi All,
Recently, the Go Dev Team, has released a Vulnerability Management System  to support developers scan/analyze their code and fix known vulnerabilities. This System consists in the following components :

Go vulnerability database
govulncheck command
API client

Should we consider having these components part of this Operator codebase, at least in the CI/CD workflows ?
Many Thanks,
Erlis

I think it would be a good idea.
On Sat, Sep 10, 2022, 12:16 PM Erlis Balla @.***> wrote:

Hi All,
Recently, the Go Dev Team, has released a Vulnerability Management System
https://go.dev/blog/vuln to support developers scan/analyze their code
and fix known vulnerabilities. This System consists in the following
components :

Go vulnerability database https://vuln.go.dev/
govulncheck command
https://pkg.go.dev/golang.org/x/vuln/cmd/govulncheck
API client https://pkg.go.dev/golang.org/x/vuln/client

Should we consider having these components part of this Operator codebase,
at least in the CI/CD workflows ?
Many Thanks,
Erlis
—
Reply to this email directly, view it on GitHub
https://github.com/redhat-cop/vault-config-operator/issues/74, or
unsubscribe
https://github.com/notifications/unsubscribe-auth/ABPERXACP6LSIAO3BZB33DDV5SX37ANCNFSM6AAAAAAQJMRHYE
.
You are receiving this because you are subscribed to this thread.Message
ID: @.***>

We are also looking at incorporating sbom generation using syft and image signing using cosign

@erlisb Would you be able to add an issue in the github-workflows-operators repository?

@sabre1041 done. Closing this,


[Snyk] Upgrade @webcomponents/webcomponentsjs from 2.7.0 to 2.8.0

This PR was automatically created by Snyk using the credentials of a real user.Snyk has created this PR to upgrade @webcomponents/webcomponentsjs from 2.7.0 to 2.8.0.
:information_source: Keep your dependencies up-to-date. This makes it easier to fix existing vulnerabilities and to more quickly identify and fix newly disclosed vulnerabilities when they affect your project.

The recommended version is 1 version ahead of your current version.
The recommended version was released 22 days ago, on 2023-03-30.

Release notes

Package name: @webcomponents/webcomponentsjs

2.8.0 - 2023-03-30<EMAIL_ADDRESS>

2.7.0 - 2022-10-20<EMAIL_ADDRESS>

    from @webcomponents/webcomponentsjs GitHub release notes

Note: You are seeing this because you or someone else with access to this repository has authorized Snyk to open upgrade PRs.
For more information:
🧐 View latest project report
🛠 Adjust upgrade PR settings
🔕 Ignore this dependency or unsubscribe from future upgrade PRs

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.


Merge Intervals code in java

Merge Intervals explained with comments and complexity(time & space both)

please merge my pull request


[BUG] Reading vacant study is not added to RegisteredStudyIdentifiers.

Have ARC
Delete study/assay folders from ARC (only tested with study)
read ARC
ARC.ISA.RegisteredStudyIdentifiers contains only non-vacant studies

This was a bug in the read-in. Corrected the faulty line.


add commonLabels and commonAnnotations

Preflight Checklist

[X] I agree to follow the Code of Conduct that this project adheres to.
[X] I have searched the issue tracker for an issue that matches the one I want to file, without success.

Problem Description
No possibilities to define labels and annotation for resources in chart.
Proposed Solution
Best practice for helm chart development consists to add following metadata definitions on each template :
  labels:
    app.kubernetes.io/name: {{ template "dex.name" . }}
    helm.sh/chart: {{ template "dex.chart" . }}
    app.kubernetes.io/managed-by: {{ .Release.Service }}
    app.kubernetes.io/instance: {{ .Release.Name }}
    {{- if .Values.commonLabels }}
    {{- include "common.tplvalues.render" ( dict "value" .Values.commonLabels "context" $ ) | nindent 4 }}
    {{- end }}
  annotations:
    {{- if .Values.commonAnnotations }}
    {{- include "common.tplvalues.render" ( dict "value" .Values.commonAnnotations "context" $ ) | nindent 4 }}
    {{- end }}

and following block in templates :
{{/* vim: set filetype=mustache: */}}
{{/*
Renders a value that contains template.
Usage:
{{ include "common.tplvalues.render" ( dict "value" .Values.path.to.the.Value "context" $) }}
*/}}
{{- define "common.tplvalues.render" -}}
    {{- if typeIs "string" .value }}
        {{- tpl .value .context }}
    {{- else }}
        {{- tpl (.value | toYaml) .context }}
    {{- end }}
{{- end -}}

(or integrate common helm chart from bitnami as dependency: https://artifacthub.io/packages/helm/bitnami/common)
Alternatives Considered
No response
Additional Information
No response

Pull request #67


Include items between git tag, and this build in GenerateReleaseNotes (XPlat version)

Is your feature request related to a problem? Please describe.
We have a Build pipeline that is run daily. This pipeline is also used when we create a release. This makes it impossible as I understand to include all items (e.g. work items, pullrequests etc) from last release as the extension seems to only include items since the last pipeline run.
Describe the solution you'd like
My question is if it is somehow possible to tell GenerateReleaseNotes (XPlat version), to take all items between a user specified git tag, e.g. Release, and this current build. Would this be a interesting feature to the extension?
Describe alternatives you've considered
Another solution would maybe be to, every time it is time to do a release, merge the master branch (or whatever branch the release is going to be base on) into a release branch. If this is done only one time each time it's time to do a release, I guess the extension will take all, to that particular branch, new items since last successfull build. I havn't tried yet if it works like that though.
If nothing of this would be possible, do you know of any workaround? Can the Azure DevOps REST API be used to somhow solve this problem?
Additional context
Add any other context or screenshots about the feature request here.

The way this task is written is based on using an Azure DevOps API call that gets the changes between builds. There is no equivalent option to do this via tags. So any change would be a complete re-write of how associations are discovered. Not something I indent to do.
For people with your requirement, the option I have seen done most commonly is to add a stage to your Release Pipeline that generates the release notes that is not run nightly, but only on release (whether manually or via some conditional flag). As the task checks for the last successful release of the stage it is running it, this means it will generate the associated items related to the last release build, not the nightly build.
Hope that helps

Ok, a follow up on this. When you write between builds, would it be possible to tell the task between which specific builds we want it to create release notes. For an instance I can see that the REST api supports this like this:
GET https://dev.azure.com/{organization}/{project}/_apis/build/workitems?fromBuildId={fromBuildId}&toBuildId={toBuildId}&api-version=5.1-preview.2
...with fromBuildId and toBuildId.

That is what it uses, it gets the to and from ID from the list based on artefacts in the last successful deployment to the stage the task is in and the current releases artefacts

As per my standard practice I am closing this issue as I have heard nothing for a while. If this issue remains a problem please do not hesitate to re-open it

@rfennell I'm in a similar situation here I believe.
Our company is switchign to YAML pipelines off of CI/CD.
I love the behavior of Releases where it grabs all workitems associated between that stage of that release pipeline.
Is there a way to emulate this behavior for YAML pipelines? This is necessary as we deploy to DEV always, deploy to TEST often, and deploy to PROD once - and I need the set of workitems on each.
At the moment I think I'll have to retain release pipelines solely to retain this behavior.

That is an interesting request and one I think deserves its own issue i think.
I will have a look to see what I can do, my guess is I could look for last successful release to a stage, I will check


adding year field when exporting with Better Biblatex

First of all I want to thank you for all your efforts on zotero-better-bibtex.
Recently, I was working on a paper for an ASME publication and noticed that the years are not printed correctly in the paper. I could figure out, that the ASME bibtex style rather uses the 'year' field and ignores the 'date' field. Could you please add the 'year' field in addition to the date field?

Are you exporting with "Better BibTeX" or with "Better BibLaTeX"?

Thank you for the quick response.
as written in the title, I use Better BibLaTeX.

The reason I I'm asking is that you mention using a bibtex style, not a biblatex style, and you're asking for bibtex fields, not biblatex fields. Why not export using Better BibTeX?

I just checked it. You are right, I get the year when exporting with Better BibTeX. Just out of habit I guess I was using Better BibLaTeX without thinking too much.

That's cool, it happens.

Why this can not be added? I am exporting with Better BibLaTeX because the presentation type does not export the name of the event with Better BibTeX, and have the same problem.

What can what not be added?

Yes, I know. The thing is that the export format for the presentation type in Zotero is better for BibLaTeX (where the type is unpublished, and more information is preserved) than for BibTeX. I was wondering if there is anything wrong with adding the year and month fields to the BibLaTeX export, so that it could be used in plain BibTeX, or if the BibTeX export could be improved.

month is not a biblatex field. If your date has a month, it will show up in the date field. biblatex supports that.

If you want the meeting name in bibtex, where would you put it?

In the note field, I suppose. It is a shame that there is no specific type for presentations without an attached paper 😞

Yeah, but bibtex is getting a bit long in the tooth. It's best to move to biblatex when possible. I don't want to add unsupported fields to Better BibLaTeX just so it can be used with bibtex, sorry. You can add your meeting name for the bibtex export with a postscript:
if (Translator.BetterBibTeX && item.itemType ===  'presentation' && item.meetingName && !reference.has.note) {
  reference.add({ name: 'note', value: item.meetingName })
}

Thank you!


Cell renderer v6 -> v7 interface change

Is there a reason the Cell renderer in columns needs this change in v7 compared to v6?

v6
v7

Cell: ({ value }) => value
Cell: ({ cell: { value } }) => value

I think the ({ value }) was one of the most used cases, in v7 it becomes a bit more awkward.
What I propose: keep the new cell property there with the value inside, but also add back the value linked to the same value. This would make a lot of use cases more elegant and easier both to write and read.

I know this is awkward at first, but since you are technically dealing with an extended version of the table instance, but with cell, row, and column information this is more consistent.

Is this change not reflected to documentation or am I misinterpreting it? I still see:

Oops, I did forgot to mention this issue in my recent PR: https://github.com/tannerlinsley/react-table/pull/2073 — from 7.0.1 the ({ value }) is available again.


Metadata with negative timestamps and gyroscopic scale meanings?

Part of the gyroscope metadata I got is as follows:
gyrodata:
'Data':[{'t': -2.316133000000054, 'x':<PHONE_NUMBER>726403, 'y': -94.22785488252927, 'z': -367.63533285095224}, {'t': -2.3151330000000536, 'x':<PHONE_NUMBER>561125, 'y': -112.0764583655591, 'z': -410.69751866875436}, {'t': -2.3141330000000537, 'x':<PHONE_NUMBER>9067564, 'y': -128.9180670895991, 'z': -453.7609785702092},...]
'Unit':'deg/s'
'Scale':16.384
'Orientation':'Xyz'

What does  mean by the output above having a negative value for t, is it invalid, and is it correct if it is followed by a positive one? Also what is the meaning of 'Scale', is it dividing 'x', 'y', 'z' of 'Data' by 'Scale' to get the real angular velocity data (deg/s)? thanks in advance!

It depends on the camera, but generally it means that the gyro data is sampled before the first video frame.
All cameras have different timing though, so to get accurate per-video-frame data, you'll need some additional calculations depending on the camera, look for per_frame_time_offsets in gyroflow's source code
the number in Data divided by Scale will result in Unit. If you're using normalized_imu functions then this is already calculated for you


Drawing filled bitmap to transparent bitmap does not render

When creating a Shape that has a fill, attempting to draw that Shape onto a transparent BitmapData will have no effect. Example code:
	public function new ()
	{
		super();
		this.x = this.y = 20;
		var shape = new Shape();
		shape.graphics.beginFill(0xAAAAFF);
		shape.graphics.lineStyle(1, 0xFF0000);
		shape.graphics.drawCircle(50, 50, 49.5);
		addChild(shape);
		addBitmap(shape, true, 110);
		addBitmap(shape, false, 220);
	}

	public function addBitmap(shape:Shape, transparent:Bool, x:Float)
	{
		var bitmapData = new BitmapData(100, 100, transparent, 0);
		bitmapData.draw(shape);
		var bitmap = new Bitmap(bitmapData);
		addChild(bitmap);
		bitmap.x = x;
	}

In the image below, the top row was created by targeting Flash, and the bottom row with a native target. The first column is the shape itself, followed by the transparent bitmap, and then the opaque bitmap.

Commenting out shape.graphics.beginFill(0xAAAAFF); will allow the shape to render, albeit without the desired fill. It makes no difference if a lineStyle is applied or not. Adding an endFill line also has no effect. For that matter, neither does supplying 32bit color to begin fill (0xFFAAAAFF), although that was wishful thinking...
Sorry for dogpiling on the Graphics class lately!

Ah sorry, I missed #402.  Thanks for the fix!


Problems when using ZAP theme

hi,
Sorry for the late response.
You are right it works with the default odoo theme.
I'm using the Zap theme and it doesn't i tried to find you but nothing. The same with the TABS module ( the tabs are not visible when using the zap theme.

Hello sharkutz,
This module was meant to be used on default themes.
I do not have a commercial themes and its sources are not public therefore I cannot test it.
Nedas


Android 11 issues while choose camera

Unable to get intent data (data: Intent?)  in onActivityResult method while choose camera. Getting only null value.
But while choose gallery, I'm able to get image Uri.
It also happing in emulator, I'm getting the following error and app crashes
android.os.FileUriExposedException: file:///storage/emulated/0/............. exposed beyond app through ClipData.Item.getUri()

I am also getting the same issue in android 11.

THIS LIBRARY IS NOT MAINTAINED, PLEASE READ THIS #806
I start a new project to handover this library
https://github.com/CanHub/Android-Image-Cropper
The ideia is that we keep improving because this project don’t have updates since 2018
Hope I can count with your help.
Open to contribute, next pieces of work will be Android 11 permissions, refactor into Kotlin and ActivityContract


New Release please?

Why has there not been a release for so long? The documentation states that I should use the ->accepNotification() method but I can see that wasn't implemented until Q4 2016, whereas the last release was in Feb 2016.
For now I'm going to have to use dev-master, but obviously moving forward I don't want to have to do that.

Okay, I'll make it my priority next week (just busy as hell until this Sunday though).
Yes, do use dev-master in the meantime. There should be nothing unstable in it at the moment, and we'll aim to keep it that way.

Awesome - thanks @judgej!

I got too busy, and allowed too many changes to go through without a release. Then it kind makes it more difficult to release stuff without knowing I am available to react quickly enough to inevitable issues as people upgrade. Sorry about that - I really should be more on top of this.

Don't worry - we all get busy :)

Released as 2.4.0

Thanks @judgej!


Upgrade to spring-webmvc-pac4j v6.1.0

Two things are done when upgrading:

passing the JEEHttpActionAdapter.INSTANCE to the SecurityInterceptor is useless, it is the default HttpActionAdapter: https://github.com/pac4j/spring-webmvc-pac4j/blob/spring-webmvc-pac4j-6.1.0/src/main/java/org/pac4j/springframework/web/SecurityInterceptor.java#L89
the "smart" builder SecurityInterceptor.build can be used for multiple input types: https://github.com/apereo/cas/compare/master...leleuj:cas:springwebmvcpac4j61?expand=1#diff-68d41d51d66f4e3c4fa771feef620c44c6482e98cc7f1549fed760706816ca0aR192

This is only a proposal. Keep what you think is clearer to you.

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.

LGTM. Thank you!

@apereocas-bot runci