Default case since arg is optional

What happens when arg is not provided in this case?

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

ID: b9e183d1-17d6-0879-f8bd-eda1cadfebbf
Version Independent ID: 2b99142b-a211-fe10-e16d-e68c818fe45f
Content: getControl (Client API reference) in model-driven apps - Power Apps
Content Source: powerapps-docs/developer/model-driven-apps/clientapi/reference/controls/getControl.md
Service: powerapps
GitHub Login: @KumarVivek
Microsoft Alias: kvivek

@imranakram When you don't pass any value to the formContext.getControl(), it returns an array of all controls in the form.

@Nkrb The point was that the documentation is not provided for the default behavior

@imranakram Sure, will add it to the documentation. Thanks for the feedback. Closing the issue.


Add HBase into hadoop-testing

version: 2.5.7
download page: https://hbase.apache.org/downloads.html
download url: https://www.apache.org/dyn/closer.lua/hbase/2.5.7/hbase-2.5.7-bin.tar.gz
design:

hadoop-master1: HMaster;
hadoop-worker1: HRegionServer1;
hadoop-worker2: HRegionServer2;
hadoop-worker3: HRegionServer3;


KAFKA-5340: Batch splitting should preserve magic and transactional flag

@becketqin Maybe you can take a look at this?

@guozhangwang Comments addressed. Please take another look.

LGTM.

Pushed a fix to address @becketqin's comments. If there are no further comments, I will merge later this evening.

Thanks for the patch. LGTM.


[FEATURE] add an empty Projects page

Description
add an empty "Projects" page
Screenshots
No response

assign it to me

fixed by #246


Portal: Display api owner

Issue
gravitee-io/issues#6485
Description

[x]  to merge after this PR : https://github.com/gravitee-io/gravitee-ui-components/pull/507

Additional context

Gravitee.io Automatic Deployment
📚 View the storybook of this branch here

Gravitee.io Automatic Deployment
Congrats, all the CI steps were 🟢 . The Bot was able to deploy the build of this PR, so you can now try it directly here! 🚀
Notes: The deployed app is linked to the management API of the Element Zero team's environment.

Gravitee.io Automatic Deployment
📚 View the storybook of this branch here

Gravitee.io Automatic Deployment
Congrats, all the CI steps were 🟢 . The Bot was able to deploy the build of this PR, so you can now try it directly here! 🚀
Notes: The deployed app is linked to the management API of the Element Zero team's environment.

⚠  DO NOT MERGE before 3.14 has been released

Replaced by https://github.com/gravitee-io/gravitee-api-management/pull/866


FAIL: test_run_program_failed

Information

Qiskit IBM Provider version:
Python version:
Operating system:

What is the current behavior?
https://github.com/Qiskit-Partners/qiskit-ibm/runs/4376900846?check_suite_focus=true#step:5:775
Steps to reproduce the problem
What is the expected behavior?
Suggested solutions

Test has not failed in 25 days, unable to replicate locally - closing for now


1.12 Botania Petal Apothecary Dupe

Hey, I found a bug in my 1.12 that has Botania:
Sometimes when I throw an item or a stack of items into the Apothecary it holds 1 more than I inserted, this has only happened on a server so far and I wasn't always able to replicate it, only sometimes.
Relevant Mods:
Botania
ExtraBotany
Botania needs these things
Botania Tweaks
Botanic Additions

viddeo?


Guard against falsy render param value for 'funding.allowed'

Fixes https://github.com/paypal/paypal-checkout/issues/1006
Guards against falsy values (e.g. null) passed as the funding.allowed parameter in the Button render code (similar to how allowed is checked for 16 lines above), to avoid breaking the render.

Thanks @dechov for your PR. This bug is a P1 impacting several merchants so we went ahead and filed our own which addresses a couple of other use-cases:

All non-array values (not just falsy)
Disallowed list as well as Allowed.

We really appreciate your report and your quick PR. This fix will be out in the next hour.


role is empty for invited users

Bug report
Describe the bug
The Client throws role '' does not exist.
On looking in the DB, it showed that the role field of new users is empty.
Even after using the invite and setting a password, the role field stays empty.
To Reproduce
Steps to reproduce the behavior, please provide code snippets or a repository:

Invite User via Supabase Studio (Selfhosted)
Try to use Client to query.
Client throws role '' does not exist.

Expected behavior
The role field should be populated with 'authenticated', just as it was the case a few weeks ago.

 GOTRUE_JWT_DEFAULT_GROUP_NAME: authenticated
was not set, creating a new user pulls the role field from this ... why?


Add lemma, proof and theorem environment

Describe the solution you'd like:
Provide these three environment just like LaTeX does
Link to or name of a (La)TeX package that provides the same feature:
Lemma, Proof and Theorem environment.
Describe alternatives you've considered:
I tried to render that by myself, but is not that perfect.

Which LaTeX packages are these environments defined in?

There are many, but amsthm is probably a good starting point.  However, these really only work in text mode, not math mode, so they're probably pretty out-of-scope for KaTeX for the time being.

There are many, but amsthm is probably a good starting point. However, these really only work in text mode, not math mode, so they're probably pretty out-of-scope for KaTeX for the time being.

OK, so any work around here?

@LEXUGE You can format the theorems in HTML, like the rest of your text, and just use KaTeX for the mathematics part.  Or you could use a larger LaTeX → HTML conversion system (ideally one that supports KaTeX, though I don't know one off hand).


Use marker file to skip using/creating artifacts

This allows a Task to run a step before use/create and place a marker .skip-trusted-artifacts file in the source/desitnation directory in order to skip doing any work.
Reference: https://issues.redhat.com/browse/EC-480

This is based on #102, might want to look at that one first. Now tests are added.


Undefined functions

My operation system is Windows 10, and Matlab version is R2016a. MinGW is installed as the C compiler.
When I tried to compile the CPU implementation C code with "mex -v C:\xxx\ADMIRE\ADMIRE_Code\CPU_Implementation_Code\ccd_double_precision.c", errors were reported: "undefined reference to mxGetData' (mxMalloc' and mxFree')". I checked code and found it seemed those functions (mxGetData' mxMalloc' and mxFree') were not defined in 'ccd_double_precision.c' nor 'mex.h'.
Could you please give me some help? Many thanks!

Hi @ys-li16 . I think it might be caused by using MinGW. I've previously tested this code on my Windows 10 machine using Microsoft Visual Studio 2017 as the C/C++ compiler. Can you try installing this compiler and then compiling. If you look at the documentation under CPU Implementation Setup, I give a link to where you can download the compiler.
I hope this helps!
Christopher Khan

Hi Christopher,
Thanks for your kind reply.
I have made it. It was not caused by using MinGW, but one with wrong version. Only TDM-gcc MinGW 4.9.2 was supported (More information could be found at https://ww2.mathworks.cn/matlabcentral/answers/345391-how-to-install-mingw-4-9-2-for-matlab). I downloaded it from https://github.com/mathworks/MinGW_492/releases and correctly set the path. It finally works.
Yongshuai Li

Hi Yongshuai. I'm glad you were able to get it to work. Just as a note, if you end up using the GPU version of ADMIRE instead of the CPU version, you'll probably have to use the compiler that comes with Microsoft Visual Studio instead of MinGW in order to compile the MEX-functions that contain CUDA code.
I'm going to go ahead and close this issue, but let me know if you have any more questions!
Christopher Khan

Hi Yongshuai. I'm glad you were able to get it to work. Just as a note, if you end up using the GPU version of ADMIRE instead of the CPU version, you'll probably have to use the compiler that comes with Microsoft Visual Studio instead of MinGW in order to compile the MEX-functions that contain CUDA code.
I'm going to go ahead and close this issue, but let me know if you have any more questions!
Christopher Khan


fix: unused import from #1683

fix #1683

It should be?? The clippy command used in CI failed for me locally


Question: Are the 2015 MSBuild tools backwards compatible with previous versions?

For example, if I were to change the binding redirects in Visual Studio 2013's devenv.exe.config to use version 14.0.0 do you know what kinds of problems this might cause?
I've tested out some basic WPF, Console, ASP .Net projects and haven't had any issues yet, but I was just wondering if there was anyone here who might know better.
FWIW I'd be modifying them to match VS 2015's redirects:
<dependentAssembly>
    <assemblyIdentity name="Microsoft.Build.Framework" publicKeyToken="b03f5f7f11d50a3a" culture="neutral"/>
    <bindingRedirect oldVersion="<IP_ADDRESS>-<IP_ADDRESS>" newVersion="<IP_ADDRESS>"/>
</dependentAssembly>
<dependentAssembly>
    <assemblyIdentity name="Microsoft.Build" publicKeyToken="b03f5f7f11d50a3a" culture="neutral"/>
    <bindingRedirect oldVersion="<IP_ADDRESS>-<IP_ADDRESS>" newVersion="<IP_ADDRESS>"/>
</dependentAssembly>
<dependentAssembly>
    <assemblyIdentity name="Microsoft.Build.Engine" publicKeyToken="b03f5f7f11d50a3a" culture="neutral"/>
    <bindingRedirect oldVersion="<IP_ADDRESS>-<IP_ADDRESS>" newVersion="<IP_ADDRESS>"/>
</dependentAssembly>

This isn't something that we've tested, we would expect problems to occur.


[Release v1.12.4] Update cmd/cmctl's go.mod to v1.12.4

This PR cmd/cmctl's go.mod to v1.12.4 as part of the release process. This change is important for anyone who wants to import<EMAIL_ADDRESS>To the reviewer: the version changes in go.mod must be reviewed.
NONE

/lgtm

/retest

/lgtm

/approve


API endpoint for creating ignition configs

This uses openshift/installer as a library.
Please note the new instructions on how to run the server.

Rebase on #19

Rebase on top of master

Another rebase on master

For development this will be useful, but I kinda wonder if we'll ultimately combine bootstrap-vm and create-ignition-configs, I guess we can iterate on the individual pieces then combine them later though

@hardys I wonder if this is no longer relevant now that kni-installer is in play?

@hardys I wonder if this is no longer relevant now that kni-installer is in play?

Adding @markmc for comment as well

Currently in dev-scripts we do:
cat >> ocp/install-config.yaml <<EOF
...
EOF
kni-install --dir ocp create ignition-configs
cp ocp/master.ign ocp/master.ign.tmp
kni-install --dir ocp create cluster
cp ocp/master.ign.tmp ocp/master.ign

# lots of stuff here to provision the master nodes using master.ign

# wait for the master API to become available

oc --config ocp/auth/kubeconfig get nodes

# We're done!

and then use the ocp/master.ign to provision the master nodes. So facet should do the same as this ... for now.
We will soon be working on moving the master node provisioning into kni-install itself, and then the above becomes simply:
cat >> ocp/install-config.yaml <<EOF
...
EOF
kni-install --dir ocp create cluster

# wait for the master API to become available

oc --config ocp/auth/kubeconfig get nodes

# We're done!

So, no - I don't think a separate API for the "create ignition-configs" makes sense long-term
Thanks for asking!

Alright, closing this as stale.


Prediction Callback

Hi! I recently came across this repo and it looks very promising for my use case!
As I was playing around I wanted to see how the predictions improved throughout the epochs. Ideally, I would like to have a small separate dataset on which the model could be run after each training epoch, or just a random draw of some images from the validation dataset.
I tried to implement this myself with Pytorch lightning Callbacks, but I don't see a clear way to get around having to call trainer.predict inside the callback, and I fear that messes up the trainer.fit loop by deleting the validation losses it keeps track of.
Given that you may have a lot more intuition of how CAREamics works, do you have an idea of something that would work? I am happy to implement it myself and create a PR, but currently I do not see how I can avoid calling training.predict since the prediction loop is modified to stitch the image together.
Thank you,
Conrad

Hi Conrad,
Thank you for your feedback!
Firstly, would you mind sharing a code snippet of what you have so far so we can have a clearer idea of the problem?
This discussion on the pytorch-lightning repo seems to suggest that calling trainer.predict in the Callback hook on_validation_epoch_end shouldn't cause any issues. However, it is over a year old and might be out of date.
We are currently in the process of removing the image stitching logic from the prediction loop and implementing it as a separate function. This should be merged with the main this week. It might make logging predictions throughout training easier. So watch this space!
Some solutions we will consider implementing in the future might include leveraging existing logging frameworks such as Weights & Biases. See their lightning integration docs, where they implement an example LogPredictionSamplesCallback class.
Melisande

Hi Melisande,
Thank you for reply! Shortly after submitting my issue I came across issue #141, and indeed I am almost certain that it would solve the problem I am having.
I was basing my solution on the PyTorch Lightning discussion you shared, but I cannot do it exactly as them since, as it stands, I need to use the prediction loop in order to stitch the images together (and all solutions I could see involve calling predict_step). This should not be an issue anymore after the refactoring. In any case, I will wait until it is all merged before I share the (fairly huge) code snippet needed to reproduce it.
The W&B Callback you shared does pretty much the same I am doing with mine, but I must use TensorBoard with my project, unfortunately. Do you have any plans to allow custom Callbacks being passed to the CAREamist class? (as of now I am just redefining _define_callbacks which is a bit ugly)

Hi @conradkun,
Passing custom callbacks to the CAREamist is a great idea! We will actually need this very soon for the napari plugin, so here ya go: https://github.com/CAREamics/careamics/actions/runs/9567446461/job/26375210174?pr=150
We have not worked much on the loggers so far, but we will try to have some support of both TensorBoard and WandB, with examples of useful cases. Feedback and suggestions always welcome!

Hi @conradkun,
#141 has now been merged with main! I hope this will help to solve your issue.
We no longer use a custom prediction loop, and instead, the outputs of lightning's Trainer.predict are converted at the end of CAREamist.predict with the new function careamics.prediction_utils.convert_output. convert_output needs to know whether the prediction outputs are tiled and this is determined in the initialisation of CAREamicsPredictData, the logic of which has been moved to the function careamics.prediction_utils.create_pred_datamodule. You will see this implemented in the CAREamics.predict method.
Do not hesitate to get in contact with any questions!

Perfect, thanks for the heads up! I will reimplement what I had using the new setup soon and let you know if I come across any issues. Just saw you also merged the custom callbacks branch, so my life is even simpler! Thank you for the quick work.

Unfortunately, I was not able to make it work, so here I go.
What do I want to achieve?
Given a CAREamicsPredictData datamodule, I want to be able to predict on it at specific times: at the end of each training epoch, at the end of X number of training steps, etc... The best tool for this is PyTorch Lightning's Callback.
I want to use a datamodule that is detached from both the training and the validation datasets found in the CAREamicsTrainData for a number of reasons:

I want to predict on a full image in order to visualize it as a whole (as opposed to only looking at the patches that the validation set may contain).
I want to be able to manually decide how many images get predicted on, meaning a setup where I dump a bunch of pictures I want to keep track on inside a folder, and pass that path to CAREamicsPredictData would be ideal.
Similarly to the previous point, I want them to always be the same images for comparison among models, as opposed to randomly drawing from a larger validation set.

I think such functionality is really useful in a model like n2v where metrics are not entirely representative of the perceived performance. Picture a UI where a user is training on an image and selects a patch to see how it develops as the training progresses; this real time feedback would be great to give the user an idea of what's going on and whether training longer is a good idea, etc...
What have I tried?
With the new Callback functionality, I can pass directly the following to the CAREamist class (assuming some config):
class CustomPredictAfterValidationCallback(Callback):
    def __init__(self, pred_datamodule):
        self.pred_datamodule = pred_datamodule

    def setup(self, trainer, pl_module, stage):
        if stage in ("fit", "validate"):
            # setup the predict data for fit/validate, as we will call it during `on_validation_epoch_end`
            # not sure if needed, but doesn't hurt until I get it to work
            self.pred_datamodule.prepare_data()
            self.pred_datamodule.setup("predict")

    def on_validation_epoch_end(self, trainer, pl_module):
        if trainer.sanity_checking:  # optional skip
            return

        predictions = trainer.predict(model=pl_module, datamodule=self.pred_datamodule)
        return convert_outputs(predictions, self.pred_datamodule.tiled)

pred_datamodule = create_pred_datamodule(
    source="image.tiff",
    config=config
)

predict_after_val_callback = CustomPredictAfterValidationCallback(pred_datamodule=pred_datamodule)
engine = CAREamist(config, callbacks=[predict_after_val_callback])

For some reason, PyTorch lightning really does not like this setup. In particular, I get the following error after trying to call fit:
---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
Cell In[32], [line 1](vscode-notebook-cell:?execution_count=32&line=1)
----> [1](vscode-notebook-cell:?execution_count=32&line=1) engine.train(datamodule=data_module)

File ~/miniconda3/envs/dl/lib/python3.11/site-packages/careamics/careamist.py:322, in CAREamist.train(self, datamodule, train_source, val_source, train_target, val_target, use_in_memory, val_percentage, val_minimum_split)
    [320](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/careamics/careamist.py:320) # train
    [321](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/careamics/careamist.py:321) if datamodule is not None:
--> [322](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/careamics/careamist.py:322)     self._train_on_datamodule(datamodule=datamodule)
    [324](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/careamics/careamist.py:324) else:
    [325](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/careamics/careamist.py:325)     # raise error if target is provided to N2V
    [326](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/careamics/careamist.py:326)     if self.cfg.algorithm_config.algorithm == SupportedAlgorithm.N2V.value:

File ~/miniconda3/envs/dl/lib/python3.11/site-packages/careamics/careamist.py:394, in CAREamist._train_on_datamodule(self, datamodule)
    [391](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/careamics/careamist.py:391) # record datamodule
    [392](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/careamics/careamist.py:392) self.train_datamodule = datamodule
--> [394](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/careamics/careamist.py:394) self.trainer.fit(self.model, datamodule=datamodule)

File ~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:544, in Trainer.fit(self, model, train_dataloaders, val_dataloaders, datamodule, ckpt_path)
    [542](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:542) self.state.status = TrainerStatus.RUNNING
    [543](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:543) self.training = True
--> [544](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:544) call._call_and_handle_interrupt(
    [545](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:545)     self, self._fit_impl, model, train_dataloaders, val_dataloaders, datamodule, ckpt_path
    [546](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:546) )

File ~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/call.py:44, in _call_and_handle_interrupt(trainer, trainer_fn, *args, **kwargs)
     [42](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/call.py:42)     if trainer.strategy.launcher is not None:
     [43](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/call.py:43)         return trainer.strategy.launcher.launch(trainer_fn, *args, trainer=trainer, **kwargs)
---> [44](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/call.py:44)     return trainer_fn(*args, **kwargs)
     [46](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/call.py:46) except _TunerExitException:
     [47](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/call.py:47)     _call_teardown_hook(trainer)

File ~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:580, in Trainer._fit_impl(self, model, train_dataloaders, val_dataloaders, datamodule, ckpt_path)
    [573](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:573) assert self.state.fn is not None
    [574](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:574) ckpt_path = self._checkpoint_connector._select_ckpt_path(
    [575](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:575)     self.state.fn,
    [576](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:576)     ckpt_path,
    [577](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:577)     model_provided=True,
    [578](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:578)     model_connected=self.lightning_module is not None,
    [579](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:579) )
--> [580](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:580) self._run(model, ckpt_path=ckpt_path)
    [582](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:582) assert self.state.stopped
    [583](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:583) self.training = False

File ~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:987, in Trainer._run(self, model, ckpt_path)
    [982](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:982) self._signal_connector.register_signal_handlers()
    [984](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:984) # ----------------------------
    [985](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:985) # RUN THE TRAINER
    [986](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:986) # ----------------------------
--> [987](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:987) results = self._run_stage()
    [989](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:989) # ----------------------------
    [990](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:990) # POST-Training CLEAN UP
    [991](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:991) # ----------------------------
    [992](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:992) log.debug(f"{self.__class__.__name__}: trainer tearing down")

File ~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:1033, in Trainer._run_stage(self)
   [1031](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:1031)         self._run_sanity_check()
   [1032](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:1032)     with torch.autograd.set_detect_anomaly(self._detect_anomaly):
-> [1033](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:1033)         self.fit_loop.run()
   [1034](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:1034)     return None
   [1035](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/trainer.py:1035) raise RuntimeError(f"Unexpected state {self.state}")

File ~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/fit_loop.py:205, in _FitLoop.run(self)
    [203](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/fit_loop.py:203) try:
    [204](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/fit_loop.py:204)     self.on_advance_start()
--> [205](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/fit_loop.py:205)     self.advance()
    [206](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/fit_loop.py:206)     self.on_advance_end()
    [207](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/fit_loop.py:207)     self._restarting = False

File ~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/fit_loop.py:363, in _FitLoop.advance(self)
    [361](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/fit_loop.py:361) with self.trainer.profiler.profile("run_training_epoch"):
    [362](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/fit_loop.py:362)     assert self._data_fetcher is not None
--> [363](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/fit_loop.py:363)     self.epoch_loop.run(self._data_fetcher)

File ~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/training_epoch_loop.py:141, in _TrainingEpochLoop.run(self, data_fetcher)
    [139](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/training_epoch_loop.py:139) try:
    [140](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/training_epoch_loop.py:140)     self.advance(data_fetcher)
--> [141](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/training_epoch_loop.py:141)     self.on_advance_end(data_fetcher)
    [142](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/training_epoch_loop.py:142)     self._restarting = False
    [143](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/training_epoch_loop.py:143) except StopIteration:

File ~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/training_epoch_loop.py:295, in _TrainingEpochLoop.on_advance_end(self, data_fetcher)
    [291](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/training_epoch_loop.py:291) if not self._should_accumulate():
    [292](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/training_epoch_loop.py:292)     # clear gradients to not leave any unused memory during validation
    [293](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/training_epoch_loop.py:293)     call._call_lightning_module_hook(self.trainer, "on_validation_model_zero_grad")
--> [295](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/training_epoch_loop.py:295) self.val_loop.run()
    [296](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/training_epoch_loop.py:296) self.trainer.training = True
    [297](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/training_epoch_loop.py:297) self.trainer._logger_connector._first_loop_iter = first_loop_iter

File ~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/utilities.py:182, in _no_grad_context.<locals>._decorator(self, *args, **kwargs)
    [180](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/utilities.py:180)     context_manager = torch.no_grad
    [181](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/utilities.py:181) with context_manager():
--> [182](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/utilities.py:182)     return loop_run(self, *args, **kwargs)

File ~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/evaluation_loop.py:142, in _EvaluationLoop.run(self)
    [140](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/evaluation_loop.py:140)         self._restarting = False
    [141](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/evaluation_loop.py:141) self._store_dataloader_outputs()
--> [142](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/evaluation_loop.py:142) return self.on_run_end()

File ~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/evaluation_loop.py:254, in _EvaluationLoop.on_run_end(self)
    [251](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/evaluation_loop.py:251) self.trainer._logger_connector._evaluation_epoch_end()
    [253](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/evaluation_loop.py:253) # hook
--> [254](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/evaluation_loop.py:254) self._on_evaluation_epoch_end()
    [256](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/evaluation_loop.py:256) logged_outputs, self._logged_outputs = self._logged_outputs, []  # free memory
    [257](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/evaluation_loop.py:257) # include any logged outputs on epoch_end

File ~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/evaluation_loop.py:336, in _EvaluationLoop._on_evaluation_epoch_end(self)
    [333](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/evaluation_loop.py:333) call._call_callback_hooks(trainer, hook_name)
    [334](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/evaluation_loop.py:334) call._call_lightning_module_hook(trainer, hook_name)
--> [336](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/loops/evaluation_loop.py:336) trainer._logger_connector.on_epoch_end()

File ~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py:195, in _LoggerConnector.on_epoch_end(self)
    [193](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py:193) def on_epoch_end(self) -> None:
    [194](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py:194)     assert self._first_loop_iter is None
--> [195](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py:195)     metrics = self.metrics
    [196](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py:196)     self._progress_bar_metrics.update(metrics["pbar"])
    [197](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py:197)     self._callback_metrics.update(metrics["callback"])

File ~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py:233, in _LoggerConnector.metrics(self)
    [231](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py:231) """This function returns either batch or epoch metrics."""
    [232](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py:232) on_step = self._first_loop_iter is not None
--> [233](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py:233) assert self.trainer._results is not None
    [234](https://file+.vscode-resource.vscode-cdn.net/Users/c.cardona/Documents/Projects/DL/noise2void/CAREamics/notebooks/~/miniconda3/envs/dl/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py:234) return self.trainer._results.metrics(on_step)

AssertionError:

I found a post with a similar error from April, which suggested to use predict_step instead of predict directly on the Lightning Module. Incidentally, that is also what the aforementioned discussion from the Lightning forums seems to converge towards. So I tried version 2:
class CustomPredictAfterValidationCallback(Callback):
    def __init__(self, pred_datamodule):
        self.pred_datamodule = pred_datamodule

    def setup(self, trainer, pl_module, stage):
        if stage in ("fit", "validate"):
            # setup the predict data for fit/validate, as we will call it during `on_validation_epoch_end`
            # not sure if needed, but doesn't hurt until I get it to work
            self.pred_datamodule.prepare_data()
            self.pred_datamodule.setup("predict")

    def on_validation_epoch_end(self, trainer, pl_module):
        if trainer.sanity_checking:  # optional skip
            return

        # not entirely sure about how preds are returned (and how they must be concatenated), take as pseudocode
        predictions = []
        for batch, idx in enumerate(self.pred_datamodule.predict_dataloader()):
            preds = pl_module.predict_step(batch, idx) # breaks here
            predictions += preds
        return convert_outputs(predictions, self.pred_datamodule.tiled)

The problem with this approach is how the predict_step function in CAREamicsModule has changed:
https://github.com/CAREamics/careamics/blob/0a29ea2da44b3745a33bedb93143f4ca6b98a9da/src/careamics/lightning_module.py#L151-L155
Referencing _trainer directly means that it will be looking at the CAREamicsTrainData used for training, and not at the CAREamicsPredictData the current batch comes from. And training modules do not have a .tiled  attribute.
What to do?
Somehow, predict_step should be getting the tiled information from the datamodule that is yielding the current batches. Any ideas?

Thanks for sharing your code!
We've investigated a little and identified what is basically preventing this approach. We will have a deeper look in the next weeks!

That's great to hear, thank you very much!

Hi both,
I know there has been some work done towards this feature, is it fully working yet? Let me know if I could help implementing it, otherwise :)

Hi Conrad! We are hosting I2K so we are a bit overwhelmed at the moment. Let us come back to you beginning of November!

Hi @conradkun,
Sorry for the delay, life's always more busy than expected.
I had a go at it and came up with a hacky way to make it fit together (https://github.com/CAREamics/careamics/actions/runs/11783874603?pr=266), in essence it looks like this:
import numpy as np
from pytorch_lightning import Callback, Trainer

from careamics import CAREamist, Configuration
from careamics.lightning import PredictDataModule, create_predict_datamodule
from careamics.prediction_utils import convert_outputs

config = Configuration(**minimum_configuration)

class CustomPredictAfterValidationCallback(Callback):
    def __init__(self, pred_datamodule: PredictDataModule):
        self.pred_datamodule = pred_datamodule

        # prepare data and setup
        self.pred_datamodule.prepare_data()
        self.pred_datamodule.setup()
        self.pred_dataloader = pred_datamodule.predict_dataloader()
        self.data = None

    def on_validation_epoch_end(self, trainer: Trainer, pl_module):
        if trainer.sanity_checking:  # optional skip
            return

        # update statistics in the prediction dataset for coherence
        # (they can computed on-line by the training dataset)
        self.pred_datamodule.predict_dataset.image_means = (
            trainer.datamodule.train_dataset.image_stats.means
        )
        self.pred_datamodule.predict_dataset.image_stds = (
            trainer.datamodule.train_dataset.image_stats.stds
        )

        # predict on the dataset
        outputs = []
        for idx, batch in enumerate(self.pred_dataloader):
            batch = pl_module.transfer_batch_to_device(batch, pl_module.device, 0)
            outputs.append(pl_module.predict_step(batch, batch_idx=idx))

        self.data = convert_outputs(outputs, self.pred_datamodule.tiled)

array = np.arange(32 * 32).reshape((32, 32))
pred_datamodule = create_predict_datamodule(
    pred_data=array,
    data_type=config.data_config.data_type,
    axes=config.data_config.axes,
    image_means=[11.8], # random placeholder
    image_stds=[3.14],
)

predict_after_val_callback = CustomPredictAfterValidationCallback(
    pred_datamodule=pred_datamodule
)
engine = CAREamist(config, callbacks=[predict_after_val_callback])
engine.train(train_source=array)

This raised a few issues pertaining to the logic of CAREamics that I detail in the PR. We are undergoing a dataset refactoring step, and we will consider the aforementioned points during the refactoring.
Regarding the PR, I need to test it with a real example before merging it (providing that it passes review), as I only made it run through a simple test! You are welcome to try it and comment in the PR, hoping that I am not making you try a faulty example.
We would also be super interested in knowing how and why you are using CAREamics! And if you ever want to use it in production, we would be happy to potentially integrate specific integration tests to make sure the API is stable for your use cases.

Hi @conradkun !
I tested it on the SEM notebook, with a slightly modified version of the example code in my previous message (actually saving the images, and using tiling), and it seemed to have worked well!
It adds some complexity to our codebase, but only in a part we were not happy with anyway so at least we will have it in mind in the next refactoring and we will maintain this feature. We will merge the PR in a few moments.
I leave this issue open, so you can let us know whether it worked for your application!

Hi @jdeschamps !
Indeed life gets busy for me too, sorry for the late reply. This is great news, though! I will test it later this week, but it's a good sign that you got it to work on a test dataset yourself.
About why I am using CAREamics, I'm not sure about how much of it I am allowed to share publicly, but I would love to talk about it with you. Let me know if there is another channel where we could talk further about this.

I consider that this issue is close! Don't hesitate to reopen if you have problems with the current implementation, or reopen an issue!


Speed up CI

Switched from the National Bank of Poland to Ipify for the API to test against. You would think a National Bank could handle high-ish traffic on their API, unless we were perhaps triggering some DDoS protection?
Ipify offers an XML version of their API (few APIs seemed to do this nowadays, it's either this or Reddit in terms of "guaranteed to  keep existing" APIs). But the XML data seems off, and likely will fail when we actually need to utilize it for testing (currently, since XML handling is incomplete in EasyVCR, the unit tests for XML are disabled). So we'll punt on this for now.
So far, I'm seeing mild speedups on our test suite:
.NET Framework: Old | New (faster)
.NET Core 3.1: Old | New (slower)
.NET 5.0: Old | New (faster)
.NET 6.0: Old | New (faster)

@jchen293 please review this when you have time.


fail to load httpOnly cookies "connect.sid"

I can retrieve the cookie values in my react application except for one httpOnly cookie called "connect.sid". So I wonder if this is the problem?

Can you copy/paste your raw value of document.cookie here?

document.cookie do not have connect.sid field. But from Chrome debug console connect.sid is in there and shows http only

It is because httpOnly means only the server has access to the cookie. You cannot have access client-side with javascript.
You can take a look at httpOnly on Wikipedia.

I was using a boilerplate called isomorphic500 where both client and server share some states and it appears that we have access to req in both places.  So is this doable in this current project?

You can't use the cookie inside client-side code unless your cookie is not http. Here is how you can do it with express:
app.use(express.session({
    secret: 'mySecret',
    cookie: { httpOnly: false }
}));


AttributeError: 'NoneType' object has no attribute 'filename'

sqlitedict.py:158: AttributeError
return "SqliteDict(%s)" % (self.conn.filename)

because SqliteDict has been closed, self.conn is None.

Yes, should probably be just self.filename. Can you fix it?

OK


[Wave Collect] [Xero] Hide guides as exporters

Slack 🧵
We should hide the assignedGuide in the preferred exporter list, like we hide them from the members table on the workspace. There should be logic for this somewhere from QBO to follow.
Also, the current preferred exporter should be highlighted in the selection list.

thank you, i couldn't reproduce it on my account but let me debug it on a new account

Any luck on that?

@trjExpensify yes, im able to repro this on a new workspace

@trjExpensify this same bug is repro for Quickbooks too -
This is because exportConfiguration.exporter is undefined on connect and remains undefined till we manually select.
I think this should be fixed on the backend when the connection is made. @lakchote what do you think?

Looking at this now.

This seems kinda' strange, why can't I find exportConfiguration.exporter in the policyConnections data in the console on OldDot?
g_policyPage.policy.policy.connections.xero.config

Is it possible you never opened the config modal in OldDot and clicked "Save"? It's supposed to open by default when you connect the policy, and you're supposed to choose which accounts to export to, etc. My guess is that the exporter is only saved at that point.

Is it possible you never opened the config modal in OldDot and clicked "Save"?

Yeah, I made the connection via NewDot. But I would have thought at least the preferredExporter would be there and null if not set? I can try again afresh on OldDot.

Okay yeah.. so a couple of things:

After making the connection and the config settings pop-up opens, the preferred exporter has a value selected, but the exporter field does not appear in the policyConnections data
I hit Save and then the exporter field appears in the policyConnections data.

https://github.com/Expensify/App/assets/16232057/9187047c-3d68-4aab-bad0-b2467d50a566

Not sure how that is going to translate to NewDot though. We don't have to click "Save" after making the connection to trigger that.

@trjExpensify this same bug is repro for Quickbooks too -

By contrast, it seems fine and selected when I connect a new workspace to QBO on NewDot:

After making the connection and the config settings pop-up opens, the preferred exporter has a value selected, but the exporter field does not appear in the policyConnections data

It's "selected" because it's the first option in the dropdown and that's what your browser does if we don't specify which value it should show as selected by default, but it's not saved in the policy config.
We need a small backend change to set a default value for the exporter when we create the config, feel free to open an internal issue and assign it to me.

(Or I guess we can reuse this one too 😄)

Haha yeah, we can just use this one. I'll co-assign yah.. thanks!

The backend changes to always set an exporter are on staging now.

@rushatgabhane @hungvu193 were paid centrally for the Xero project, closing!


Remove nesting of AblyMessages

In Platform_object.dart, we have:
https://github.com/ably/ably-flutter/blob/78144602ab1b63568e3eaea4f79b7035e541231a/lib/src/platform/src/platform_object.dart#L68-L75
Where message can either be a nested message or not, depending on the what you pass the method. This makes it more complicated when deserializing on the platform side, since we are not sure if the message being received will be nested or not. This results in a lot of complicated code, and in fact it also tricks Android Studio, resulting in a lot of errors in the linter.
We should stop nesting AblyMessages.
I've tried to do this in https://github.com/ably/ably-flutter/pull/199, but I added three other unrelated changes (described in that PR). The PR got bigger and bigger, so I should recreate all 4 things in that PR in 4 separate PRs. This branch is also significantly out of date with the latest work done in the repo.
@QuintinWillison

Poorly defined, making it unclear as to why this change was deemed necessary.


vbump sts to bring in a dacfx fix

Pull Request Test Coverage Report for Build<PHONE_NUMBER>

0 of 0   changed or added relevant lines in 0 files are covered.
10 unchanged lines in 3 files lost coverage.
Overall coverage decreased (-0.01%) to 42.215%

Files with Coverage Reduction
New Missed Lines
%

src/sql/workbench/services/connection/browser/connectionDialogWidget.ts
1
71.43%

extensions/notebook/src/dialog/configurePython/configurePathPage.ts
2
57.02%

extensions/notebook/src/dialog/configurePython/configurePythonWizard.ts
7
38.66%

Totals

Change from base Build<PHONE_NUMBER>:
-0.01%

Covered Lines:
28157

Relevant Lines:
62331

💛  - Coveralls


Edit hdinsight-hadoop-streaming-python.md

Edit complete

Hi @ClarityQueen, I'm your friendly neighborhood Azure Pull Request Bot (You can call me AZPRBOT). Thanks for your contribution!

This seems like a small (but important) contribution, so no contribution license agreement is required at this point. Real humans will now evaluate your PR.

TTYL, AZPRBOT;


error compiling after update fastled 3.26

error message
Arduino: 1.8.5 (Windows 8.1), Board: "NodeMCU 0.9 (ESP-12 Module), 80 MHz, Flash, Disabled, All SSL ciphers (most compatible), 4M (no SPIFFS), v2 Lower Memory, Disabled, None, Only Sketch, 115200"
In file included from sketch\led_sysdefs.h:43:0,
             from sketch\FastLED.h:44,

             from sketch\FastLED.cpp:2:

C:\Users\rugby\AppData\Local\Arduino15\packages\esp8266\hardware\esp8266\2.5.1\cores\esp8266/Arduino.h:191:14: error: conflicting declaration 'typedef bool boolean'
typedef bool boolean;
          ^

In file included from sketch\led_sysdefs.h:27:0,
             from sketch\FastLED.h:44,

             from sketch\FastLED.cpp:2:

sketch\platforms/esp/8266/led_sysdefs_esp8266.h:15:17: error: 'boolean' has a previous declaration as 'typedef uint8_t boolean'
typedef uint8_t boolean;
             ^

In file included from sketch\platforms/esp/8266/fastled_esp8266.h:8:0,
             from sketch\platforms.h:27,

             from sketch\FastLED.h:55,

             from sketch\FastLED.cpp:2:

sketch\platforms/esp/8266/clockless_esp8266.h:11:21: note: #pragma message: Using RGBW controller as per FASTLED_RGBW define
pragma message "Using RGBW controller as per FASTLED_RGBW define"
                 ^

exit status 1
Error compiling for board NodeMCU 0.9 (ESP-12 Module).

Hi,
take a look:
https://github.com/FastLED/FastLED/issues/790
"Official" fix committed below; in the meantime if you need to you're welcome to do your own local work-around by opening arduino/libraries/FastLED/platforms/esp/8266/led_sysdefs_esp8266.h and deleting line 15, the one that says typedef uint8_t boolean;.


Add support for types.

Currently, javascript client doesn't have type definitions. It would be really useful to add type definitions for development with typescript.

Hi,
we already have an issue for this here and an open PR here.
Closing this as duplicate


join terminals shows empty quickpick

create split terminals
run join terminals
none are listed

added a smoke test for a few more cases
https://github.com/microsoft/vscode/blob/7b3078d9318848abe8b42bc7bdd3df1fa22ef94f/test/smoke/src/areas/terminal/terminal-tabs.test.ts#L90-L108

I got confused because I tried joining terminals when there was only one terminal group. Is there a way to notify the user or to disable the command for that case?

yes, we should probably not show that command unless there are at least 2 un-joined terminals.


go tool yacc -> goyacc changes for golang1.8

since we need goyacc in compilation for parser changes, add it to bootstrap.sh
also, for convenience, 'make parser' will now call goyacc with the usual incantation

LGTM


Add options to display year and score and sort options

Thanks for adding these features.
And I fixed some typos in your branch and merged it.


US152268 - Simple table vdiff migrations

This was created from https://github.com/BrightspaceUI/core/pull/4007 and then adjusted to try to reuse fixtures (which is probably both better and worse).  This only moves the "easy" diffs this first pass.  The next PR will deal with the tricky "sticky" ones.

Nice! Thanks, this pattern makes it much more readable and less repetitive.

Yeah, I find it makes the create* functions look a bit like gibberish, but the individual tests are hopefully readable and small and you can see what is different between each one a bit easier. But still not 100% awesome, maybe because we're trying not to change the diffs and they'd be a bit cleaner writing them this way from the start


Switched insertion and deletion queries to use ktx coroutines.

Added the suspend keyword to DAO insertion and deletion methods in order to force them off of the main thread, as an optimization. Based off of this Android documentation. Thanks!

This fix was adopted by another commit: 5d666383d89e478a5ee76a71f4f5df2e711f5dfe. #503

Thanks for following up on this @markfonte !


Add CI pipeline for Swift 5.10

Motivation:
Now that Swift 5.9 is GM we should update the CI pipelines
Modifications:

Add a 5.10 nightly docker compose file
Update the 5.9 compose file to stop using nightlies
Update benchmark thresholds

Result:
Remove add CI support for 5.10

@swift-server-bot add to allowlist

@swift-server-bot test this please


Limit number of concurrent jobs in batch mode

First off, this is a superb tool, thanks a lot!
Question: Is it possible to limit the number of concurrent jobs allowed in batch mode? Would be great in situations where you share your CPU quota with other services (e.g. app engine) and don't want them to be disrupted.

There's currently no direct option to limit the number of concurrent jobs, but I can see that it would be useful in scenarios like you mention. I'll leave this issue open as a potential feature request.
A current solution I can think of involves the use of the --after flag. Say you have a batch of 100 tasks, but want to limit to 50 concurrently. You'd need to separate the tasks file into two and run dsub on the first 50:
JOBID_FIRST_FIFTY=$(dsub ...)

Then pass these values to the --after flag for launching the second batch:
dsub ... --after "${JOBID_FIRST_FIFTY}"

Admittedly this isn't perfect since it has to wait for the first 50 to finish completely before starting the next 50. You could be more granular if you wanted to. See the docs on --after for more detail.

Another potential solution would be to have a separate cloud project for dsub, with its own quotas.

Awesome, thanks for the quick response! I wasn't aware of --after so I'll try that (I already have a bash script that constantly checks my quotas and launches a new batch when available but it's super hacky)


Show hover information in a scratch buffer v2

This is built on top of https://github.com/kak-lsp/kak-lsp/pull/564,
with review comments address, and some extra features.
The most important behavior change is that the new binding (lsp H)
by default shows the *hover* buffer in the current client.
I'm not super sure about that yet, but it seems like the smallest
common denominator.

I elaborated most of my review changes in 20f28ca and squashed & cleaned up review artifacts in 23d2c6b

If this patch is still on the table, I'd be interested in testing it. How do I do that? And what's the latest version?


Define a PowerShell BinaryFormatter Obsoletion Strategy

dotnet team has published his BinaryFormatter Obsoletion Strategy (07/23/2020)
There is already an impact for PowerShell 7.1 as ASP.NET projects disable BinaryFormatter by default (but can enable)
See https://github.com/PowerShell/PowerShell/issues/14032
The next impacts will be :

.NET 7 (Nov 2022) BinaryFormatter disabled by default across all project types
.NET 8 (Nov 2023) BinaryFormatter infrastructure removed from .NET

The documentation about BinaryFormatter security guide is published.

BinaryFormatter is really only used by remoting for TimeZone.  The only other case is the communication between Out-GridView WPF app and the cmdlet which we can update as that's an internal communication.  However, the remoting change may require a rev to PSRP protocol specification and will break legacy clients although we could have a fallback strategy in the protocol.

This seems to also hit remoting from .NET interactive, for which there doesn't appear to be a work around currently.

@SteveL-MSFT @fMichaleczek we've recently managed to get our first .NET 6 builds of Devolutions Server, and we've encountered this issue which is fixed for now using EnableUnsafeBinaryFormatterSerialization. Can you confirm that whatever happens with the binary formatter deprecation, future versions of the PowerShell SDK will still be able to connect to older versions of PowerShell, especially for Windows PowerShell 5.1 over a WinRM transport?

future versions of the PowerShell SDK will still be able to connect to older versions of PowerShell, especially for Windows PowerShell 5.1 over a WinRM transport?

As said in the BinaryFormatter Obsoletion Strategy, the code will be removed in .Net 8. Until that you can use the code with EnableUnsafeBinaryFormatterSerialization.

future versions of the PowerShell SDK will still be able to connect to older versions of PowerShell, especially for Windows PowerShell 5.1 over a WinRM transport?

As said in the BinaryFormatter Obsoletion Strategy, the code will be removed in .Net 8. Until that you can use the code with EnableUnsafeBinaryFormatterSerialization.

Yes, but that doesn't answer the question of backward compatibility with Windows PowerShell 5.1 servers when using a future .NET 8 PowerShell SDK client. I don't know how much it relies on BinaryFormatter, but is it possible to replace just the required bits in the PowerShell SDK such that it keeps working? BinaryFormatter may be deprecated, but Windows PowerShell 5.1 will still be officially supported for years to come as it ships built-in with Windows Server

Yes, but that doesn't answer the question of backward compatibility with Windows PowerShell 5.1 servers

Obviously, the distance between .Net and the .Net Framework increases with each new version and the ecosystem is obviously splitting into two parts. As for PowerShell, this split has already happened and is doubly amplified by the split in .Net, so in my opinion it is not serious to talk about forward or backward compatibility.

Correct me if I'm wrong, but from your answer it really looks like we're crossing fingers that by the time PowerShell uses .NET 8, Windows PowerShell 5.1 won't really be a thing anymore.
I agree with deprecating BinaryFormatter, and it makes sense to drop support for it from the .NET runtime, but we need a plan to have a working PowerShell SDK that can still connect to the still-supported Windows PowerShell 5.1 when this happens. It is going to be there for a LONG time, it's built-in to Windows Server, and Windows Server has a long lifetime before reaching its EOL.
I really don't know much about BinaryFormatter, and from Steve's previous answer, it looks like we're using it only in two places (time zones and Out-GridView). If someone could point to the source files affected maybe we could better assess ways to retain compatibility?
Another possibility would be to move the required classes in a nuget package separate from the .NET runtime that could be used in PowerShell, like Microsoft.Windows.Compatibility: https://docs.microsoft.com/en-us/dotnet/core/porting/windows-compat-pack

Correct me if I'm wrong, but from your answer it really looks like we're crossing fingers that by the time PowerShell uses .NET 8, Windows PowerShell 5.1 won't really be a thing anymore.

Current MSFT PowerShell team policy is to release next pwsh in the day next .Net version is released.
If we look .Net roadmap .Net 8 is  scheduled for November 2023. So 2024 is a time we lost BinaryFormatter. It is worth noting that we also lose SecurityString and more.
MSFT also officially announced that it is not worth starting projects related to .Net Framework, all new projects should be on .Net.
If you already have a project on the .Net Framework, you are doomed to struggle with incompatibilities. It will get worse every day. Moreover, .Net is based on a short lifecycle, so you will not have time to pause and respawn.

Correct me if I'm wrong, but from your answer it really looks like we're crossing fingers that by the time PowerShell uses .NET 8, Windows PowerShell 5.1 won't really be a thing anymore.

Current MSFT PowerShell team policy is to release next pwsh in the day next .Net version is released. If we look .Net roadmap .Net 8 is scheduled for November 2023. So 2024 is a time we lost BinaryFormatter. It is worth noting that we also lose SecurityString and more. MSFT also officially announced that it is not worth starting projects related to .Net Framework, all new projects should be on .Net. If you already have a project on the .Net Framework, you are doomed to struggle with incompatibilities. It will get worse every day. Moreover, .Net is based on a short lifecycle, so you will not have time to pause and respawn.

IHMO, integrate System.Text.Json and JsonSerializer, is the first thing to do. Because it's the future and maybe the solution (clijson ?).

I made a twitter thread about this yesterday, and @jborean93 came up with the simplest possible solution for the BinaryFormatter API obsoletion: https://twitter.com/BoreanJordan/status/1512978332887175170?t=VwkOfkZ-zt69Vj8J0TEJzA&s=19
All we really need is custom code to handle the time zone stuff during the connection sequence. It is benign in nature, and we could make a fix already such that connections work with .NET 6 without re-enabling BinaryFormatter. The real BinaryFormatter APIs are not required, Jordan was able to write custom code for the time zone stuff in his own Python implementation, there aren't that many possible combinations to handle.
As for Out-GridView, it is only really used interactively, so I suggest we should update the PowerShell server not to use it unless it is already the case, and not bother about backward compatibility since interactive PowerShell clients can reasonably switch to PowerShell 7. non-interactive use through the PowerShell SDK is what truly matters.
Should we create a separate issue to add a proper fallback for the time zone stuff in the current code base, link it to this issue? It would fix at least the current problem.
As for other planned deprecated APIs, are there issues opened for all of them, and can someone link them here so we have a good idea of other issues coming up that would break backward compatibility with Windows PowerShell servers?

A small point - I would not wish to see a "powershell server" edition as noted in the third para.

Looking at the code a bit further, it seems like for the SessionCapability message both the client and server exchange don't even use the TimeZone value, it just defaults to the default time zone of that host https://github.com/PowerShell/PowerShell/blob/7cc9c874730e87b06dbe54d50e77c1c472996c54/src/System.Management.Automation/engine/remoting/common/WireDataFormat/EncodeAndDecode.cs#L2376-L2392. This means that as a client there doesn't seem to be any consequence to omitting the value at all and they both already ignore it. Going back versions, v2 will try to deserialize this value but is fine if it is omitted. PowerShell 3 is when they removed this deserialization on the server due to what looks like security concerns so I'm fairly confident it's ok for PowerShell as a client to just stop sending that field altogether. Event when looking at what ultimately uses this data from the server it seems like it's only set for PSSenderInfo.ClientTimeZone and nothing else internally.
The other mentioned usage is with Out-GridView, this is not something I'm really knowledgeable on. I cannot even get it working on Linux after following https://devblogs.microsoft.com/powershell/out-gridview-returns/. When attempting to see what it looks like across the wire within PSRemoting not even WinPS allows it so if it uses the binary serializer in any way it should just require an update in the pwsh code and we don't need to worry about being backwards compatible for remoting sessions there
> "a" | Out-GridView
Out-GridView : Out-GridView does not work in a remote session.
At line:1 char:7
+ "a" | Out-GridView
+       ~~~~~~~~~~~~
    + CategoryInfo          : InvalidOperation: (Microsoft.Power...GridViewCommand:OutGridViewCommand) [Out-GridView],
    NotSupportedException
    + FullyQualifiedErrorId : RemotingNotSupported,Microsoft.PowerShell.Commands.OutGridViewComman

https://github.com/dotnet/runtime/issues/72132

As far as I know, binary formatter is supposed to be removed in .NET 8. Is this still on the radar?

As far as I know, binary formatter is supposed to be removed in .NET 8. Is this still on the radar?

The updated plan is for the entirety of the BinaryFormatter infrastructure to be removed in .NET 9. Functionality may be moved to an unsupported out-of-band package.
https://github.com/dotnet/designs/blob/main/accepted/2020/better-obsoletion/binaryformatter-obsoletion.md

Isn't this still a problem because of: https://github.com/dotnet/runtime/issues/98245

See also:
https://github.com/dotnet/wpf/issues/1131
https://github.com/dotnet/winforms/issues/6267

So .NET 9 just dropped and since there was no recent activity on this issue i wonder what is going to happen moving forward?

There is one issue at least https://github.com/PowerShell/PowerShell/pull/20300


cant switch to channel beta

Cannot switch to flutter beta channel with the command 'flutter channel beta'

Hi @mikdhadc
Please switch to beta channel like this
flutter channel beta
flutter upgrade
flutter doctor -v
If the problem persist, Can you please provide your flutter doctor -v and flutter channel beta -v
Thank you

@TahaTesser Thank You for your response.It is working now.

Hi @mikdhadc
Please switch to beta channel like this
flutter channel beta
flutter upgrade
flutter doctor -v
If the problem persist, Can you please provide your flutter doctor -v and flutter channel beta -v
Thank you

Hi .I have the same problem.I can not switch to beta channel. I've copied my flutter sdk and named it sdk_flutter_web and changed my environment variable Path to this sdk to store my stable sdk unchanged.Also in android studio I reference to this copy. and this is the log:
F:\Projects\Flutter\Projects\flutter_web\test_web>flutter channel beta
Warning! The 'flutter' tool you are currently running is from a different Flutter repository than the one last used by this package. The repository from which the 'flutter' tool is currently executing will be used
instead.
  running Flutter tool: C:\sdk_flutter_web\flutter
  previous reference  : C:\sdk_flutter\flutter
This can happen when you have multiple copies of flutter installed. Please check your system path to verify that you are running the expected version (run 'flutter --version' to see which flutter is on your path).

Switching to flutter channel 'beta'...
git: error: The following untracked working tree files would be overwritten by checkout:
git:    packages/flutter_tools/lib/src/base/platform.dart
git: Please move or remove them before you switch branches.
git: Aborting
Switching channels failed with error code 1.

F:\Projects\Flutter\Projects\flutter_web\test_web>flutter upgrade
Warning! The 'flutter' tool you are currently running is from a different Flutter repository than the one last used by this package. The repository from which the 'flutter' tool is currently executing will be used
instead.
  running Flutter tool: C:\sdk_flutter_web\flutter
  previous reference  : C:\sdk_flutter\flutter
This can happen when you have multiple copies of flutter installed. Please check your system path to verify that you are running the expected version (run 'flutter --version' to see which flutter is on your path).

Flutter is already up to date on channel stable
Flutter 1.17.5 • channel stable • https://github.com/flutter/flutter.git
Framework • revision 8af6b2f038 (7 days ago) • 2020-06-30 12:53:55 -0700
Engine • revision ee76268252
Tools • Dart 2.8.4

F:\Projects\Flutter\Projects\flutter_web\test_web>flutter doctor -v
Warning! The 'flutter' tool you are currently running is from a different Flutter repository than the one last used by this package. The repository from which the 'flutter' tool is currently executing will be used
instead.
  running Flutter tool: C:\sdk_flutter_web\flutter
  previous reference  : C:\sdk_flutter\flutter
This can happen when you have multiple copies of flutter installed. Please check your system path to verify that you are running the expected version (run 'flutter --version' to see which flutter is on your path).

[√] Flutter (Channel stable, v1.17.5, on Microsoft Windows [Version 10.0.10240], locale en-US)
    • Flutter version 1.17.5 at C:\sdk_flutter_web\flutter
    • Framework revision 8af6b2f038 (7 days ago), 2020-06-30 12:53:55 -0700
    • Engine revision ee76268252
    • Dart version 2.8.4

[!] Android toolchain - develop for Android devices (Android SDK version 30.0.0)
    • Android SDK at C:\sdk
    • Platform android-30, build-tools 30.0.0
    • ANDROID_HOME = C:\sdk
    • Java binary at: C:\Program Files\Android\Android Studio1\jre\bin\java
    • Java version OpenJDK Runtime Environment (build 1.8.0_242-release-1644-b01)
    ! Some Android licenses not accepted.  To resolve this, run: flutter doctor --android-licenses

[√] Android Studio (version 4.0)
    • Android Studio at C:\Program Files\Android\Android Studio1
    • Flutter plugin version 47.1.2
    • Dart plugin version 193.7361
    • Java version OpenJDK Runtime Environment (build 1.8.0_242-release-1644-b01)

[√] VS Code, 64-bit edition (version 1.39.2)
    • VS Code at C:\Program Files\Microsoft VS Code
    • Flutter extension version 3.7.1

[√] Connected device (1 available)
    • SM E700H • 134cce44 • android-arm • Android 4.4.4 (API 19)

! Doctor found issues in 1 category.

Could everyone who still has this problem please file a new issue with the exact description of what happens, logs and the output of flutter doctor -v.
All system setups can be slightly different, so it's always better to open new issues and reference related issues.

Getting the same error:
Error waiting for a debug connection: The log reader stopped unexpectedly
Error launching application on Redmi Note 7S.
Response of flutter channel -v
[ +144 ms] executing: [/home/dell/flutter/] git -c log.showSignature=false log -n 1 --pretty=format:%H [  +41 ms] Exit code 0 from: git -c log.showSignature=false log -n 1 --pretty=format:%H [        ] 8874f21e79d7ec66d0457c7ab338348e31b17f1d [   +1 ms] executing: [/home/dell/flutter/] git tag --points-at HEAD [  +18 ms] Exit code 0 from: git tag --points-at HEAD [        ] 1.22.3 [  +10 ms] executing: [/home/dell/flutter/] git rev-parse --abbrev-ref --symbolic @{u} [   +5 ms] Exit code 0 from: git rev-parse --abbrev-ref --symbolic @{u} [        ] origin/stable [        ] executing: [/home/dell/flutter/] git ls-remote --get-url origin [  +11 ms] Exit code 0 from: git ls-remote --get-url origin [        ] https://github.com/flutter/flutter.git [  +54 ms] executing: [/home/dell/flutter/] git rev-parse --abbrev-ref HEAD [   +7 ms] Exit code 0 from: git rev-parse --abbrev-ref HEAD [        ] stable [  +53 ms] Artifact Instance of 'AndroidMavenArtifacts' is not required, skipping update. [        ] Artifact Instance of 'AndroidGenSnapshotArtifacts' is not required, skipping update. [        ] Artifact Instance of 'AndroidInternalBuildArtifacts' is not required, skipping update. [        ] Artifact Instance of 'IOSEngineArtifacts' is not required, skipping update. [        ] Artifact Instance of 'FlutterWebSdk' is not required, skipping update. [   +3 ms] Artifact Instance of 'WindowsEngineArtifacts' is not required, skipping update. [        ] Artifact Instance of 'MacOSEngineArtifacts' is not required, skipping update. [        ] Artifact Instance of 'LinuxEngineArtifacts' is not required, skipping update. [        ] Artifact Instance of 'LinuxFuchsiaSDKArtifacts' is not required, skipping update. [        ] Artifact Instance of 'MacOSFuchsiaSDKArtifacts' is not required, skipping update. [        ] Artifact Instance of 'FlutterRunnerSDKArtifacts' is not required, skipping update. [        ] Artifact Instance of 'FlutterRunnerDebugSymbols' is not required, skipping update. [  +14 ms] Artifact Instance of 'MaterialFonts' is not required, skipping update. [        ] Artifact Instance of 'GradleWrapper' is not required, skipping update. [        ] Artifact Instance of 'AndroidMavenArtifacts' is not required, skipping update. [        ] Artifact Instance of 'AndroidGenSnapshotArtifacts' is not required, skipping update. [        ] Artifact Instance of 'AndroidInternalBuildArtifacts' is not required, skipping update. [        ] Artifact Instance of 'IOSEngineArtifacts' is not required, skipping update. [        ] Artifact Instance of 'FlutterWebSdk' is not required, skipping update. [        ] Artifact Instance of 'FlutterSdk' is not required, skipping update. [        ] Artifact Instance of 'WindowsEngineArtifacts' is not required, skipping update. [        ] Artifact Instance of 'MacOSEngineArtifacts' is not required, skipping update. [        ] Artifact Instance of 'LinuxEngineArtifacts' is not required, skipping update. [        ] Artifact Instance of 'LinuxFuchsiaSDKArtifacts' is not required, skipping update. [        ] Artifact Instance of 'MacOSFuchsiaSDKArtifacts' is not required, skipping update. [        ] Artifact Instance of 'FlutterRunnerSDKArtifacts' is not required, skipping update. [        ] Artifact Instance of 'FlutterRunnerDebugSymbols' is not required, skipping update. [        ] Artifact Instance of 'IosUsbArtifacts' is not required, skipping update. [        ] Artifact Instance of 'IosUsbArtifacts' is not required, skipping update. [        ] Artifact Instance of 'IosUsbArtifacts' is not required, skipping update. [        ] Artifact Instance of 'IosUsbArtifacts' is not required, skipping update. [        ] Artifact Instance of 'IosUsbArtifacts' is not required, skipping update. [        ] Artifact Instance of 'FontSubsetArtifacts' is not required, skipping update. [  +36 ms] Flutter channels: [   +2 ms] executing: [/home/dell/flutter/] git branch -r [  +67 ms] * stable [  +16 ms] "flutter channel" took 151ms. [ +260 ms] ensureAnalyticsSent: 254ms [   +1 ms] Running shutdown hooks [        ] Shutdown hooks complete [   +1 ms] exiting with code 0
I want to use the beta channel. Kindly help.

I have the same problem!
Any kind of help?

I had this same problem, resolved by reversing changes in the flutter branch
"git reset --hard HEAD"


Update README and add new logo

@patrick477 Any idea why the tests are suddenly failing?

It is not suddenly, previous builds also failed. I have no write access for this one.

Hello,
I fixed this error with this commit https://github.com/BitBagCommerce/SyliusMolliePlugin/commit/72f51c8bb753fca2c5ee9b24f26dc3dc13a1207c
you must do a merge with our repositories


Testing Swag Bot

Hello @audreythomas,Thanks again for the PR! We want to show our appreciation by sending                                              you some swag. Could you please fill out                                              this form so we can send it to you? Thanks!                                             Team SendGrid DX


Dangling xref prep

@m-holger FYI. I don't usually do pure "test-driven development", but I believe the XFAIL test case I added will pass once the fix is made. I can verify that it passes if I insert an extra call to fixDanglingReferences(true) in test_driver.cc. Anyway, this confirms my suspicion that the existing code is wrong with respect to xref reconstruction. It was harder than I thought  to reproduce this. I had to create the dangling reference inside of an unreferenced object. Finding a file like this in the wild that would actually trigger this bug seems unlikely, but it's not impossible. In the current code, adding a new object actually does collide with an existing object.

If you can get the test case to go to unexpected pass, you can do the inverse of 32251497c1c7185380dd7f7836613bfe024285b8 ("Temporary (revert after fix)...") not as a separate commit but inlined with the commit that fixes the bug.

Ultimately all I did to create the test file was add a dangling object with an unreferenced object in it to the file, then break the xref table for an existing object.

I don't think #822 will address the dangling-bad-xref test. The problem is that the new object is inserted before reconstruct_xref is called.
I can achieve a pass if I call reconstruct_xref at the beginning of fixDanglingReferences but I don't think this is desirable. To me it would make more sense to either not preserve clashing dangling references or renumber them. Either case would be out of scope of #822

Another possible solution would be to if necessary renumber inserted objects as part of reconstruct_xref. I'll look into that possibility.

Another possible solution would be to if necessary renumber inserted objects as part of reconstruct_xref. I'll look into that possibility.

I don't think that would make sense. reconstruct_xref is basically right from an earlier version of the PDF spec, though I am not able to put my hands on the section. I don't think we should mess with the logic of reconstruct_xref.

Not sure we are talking about the same thing. What I am contemplating is:
damaged xref table shows first free object (10, 0)
we insert new objects (10 0) and (11 0).
reconstruct_xref finds object (10 0)
I am suggesting renumbering the new objects from (10 0) and (11 0) to (11 0) and (12 0) in response to the newly discovered object (10 0).

When you insert a new object, findDanglingRefs gets called first exactly to avoid this problem. Unless I'm misunderstanding. In other words, the fact that reconstruct_xref finds 10 means that when we insert a new object, it will be 11, not 10.

Except, as I understand it, reconstruct_xref gets only called when we try to load a damaged object. So, if we insert the new object before trying to resolve either (10 0) or (11 0), the new object will mask (10 0).
I think if we insert two new objects first, qpdf  will not call reconstruct_xref at all.

nextObjGen calls fixDanglingReferences. The fixDangingReferences function was added specifically to fix the bug you are describing. There is no normal path to insert a new object that does not call fixDanglingReferences, so the situation you are describing can't happen. You can't insert a new object before trying to resolve either 10 or 11. The act of inserting a new object calls fixDanglingReferences before the object ID is assigned.
Do you see a code path for adding a new object that does not call fixDanglingReferences?


Readme modified

Changes
I have added few badges, fixed some indentations and modified few text to enhance the look and readability  of the README.md file.
Checklist

[x] My code follows the style guidelines of this project
[x] I have performed a self-review of my own code
[x] I have commented my code, particularly in hard-to-understand areas
[x] I have made corresponding changes to the documentation
[x] My changes generate no new warnings

@novonimo  added.

LGTM


My wallet is already unclock ,but show "Error 3120006: No available wallet"

duplicate of #5250 see that issue for resolution


Add Commodore 64 target

That would be cool! I'm absolutely fine cross-compiling from linux.
I tried getting the BBC target to work with the following makefile:
COWGOLDIR=../cowgol
FE=$(COWGOLDIR)/bin/cowfe-6502.lx386.lx386.exe
BE=$(COWGOLDIR)/bin/cowbe-6502.lx386.lx386.exe
LINKER=$(COWGOLDIR)/bin/cowlink-bbcti.lx386.lx386.exe

%.cob: %.cow
	$(FE) -I$(COWGOLDIR)/ -I$(COWGOLDIR)/rt/ -I$(COWGOLDIR)/rt/bbcti/ $< $@

%.coo: %.cob
	$(BE) $< $@

%.s: %.coo
	$(LINKER) $< -o $@

all: test.s

clean:
	rm *.cob
	rm *.coo
	rm *.s

but that gave me link errors. I guess the standard library isn't done for that target yet?

There is one! Er, somewhere. Possibly I haven't merged it yet. Sadly the C64 can't actually run the compiler itself, but simple programs work. Here's the frontend starting but not finding a source file.

...although I don't like that 1AKb string much (this may have been taken prior to some bugfixes). This is running under cshell, which is a very simple CP/M-like shell for running programs off disk with scripts and command-line arguments; see https://github.com/davidgiven/cshell; but the programs are also perfectly ordinary Basic-stub machine code programs which can be loaded and run. Unfortunately the C64 OS and DOS are both thoroughly cursed, which makes working with files no fun at all, but Cowgol certainly works.
Re the BBC version: you have explicitly tell it where the libraries are. For a BBC Tube machine, you want .obj/rt/bbc/cowgol.coo.
Update: Yes, I haven't merged it. It's in the c64 branch if you're interested, but there are a few broken bits.

Alright, I've got it to generate a prg! Thanks for the help :-) I turned it into a hello world thing and stored it here if others want to do the same: https://github.com/matozoid/cowgol-hellow-world-linux-c64/

Looks good --- thanks for wanting to use this! Let me know if you run into any problems. (I'll try and get the branch merged soon.)


[Q] How to enter the sat position for DiSEqC 1.1?

In the PDF, I read

--satellite-number
value
Used for satellite tuners only.
Satellite/dish number. Must be 0 to 3 with DiSEqC switches and 0 to 1 for non-DiSEqC
switches. The default is zero.

But a friend of mine wants to use DiSEqC 1.1 as he has up to 16 different sat positions.
https://en.wikipedia.org/wiki/DiSEqC

Hi @andimik
There is currently no support for more recent versions of DiSEqC. The current limit is 4 dishes.
I keep this suggestion for improvement. However, I will not be able to test this kind of reception. So, the improvement will be implemented only if there is a commitment from a user to test it and provide feedback.
The improvement will be implemented on Linux only. On Linux, the DiSEqC commands are explicitly built by the application (TSDuck) and updates are possible. On Windows, this support is built inside DirectShow and BDA, the Windows framework for broadcasting which is more or less abandoned by Microsoft and I do not expect any improvement.

Thank you for the fast response.
I forgot to tell that the OS is Ubuntu.

However, I will not be able to test this kind of reception.

Me too, I will only install tsduck on his laptop, but he needs to test it.
But we think we have a workaround: A DVB-S(2) receiver with DiSEqC 1.1 support and LNB loop-through might help here. So the receiver tunes to that satellite and I expect that there is no need to use any DiSEqC parameters under Ubuntu.

https://www.digitalfernsehen.de/ratgeber/workshop-bis-zu-64-sat-positionen-mit-diseqc-1-1-empfangen-555892/
The author of this article (and also of many other sat books) is the person where I wanted to try that and it's his sat antenna.
I'm not a programmer, just a user, but maybe that helps: https://github.com/Barracuda09/SATPI/issues/150
Or https://www.i-have-a-dreambox.com/wbb5/forum/index.php?thread/106589-probleme-mit-diseqc/&postID=911621#post911621


Add note about encrypting internalsecrets.core.gardener.cloud in etcd

How to categorize this PR?

/area security
/kind enhancement
What this PR does / why we need it:
Before upgrading to<EMAIL_ADDRESS>operators should configure gardener-apiserver to encrypt the internalsecrets.core.gardener.cloud resource in etcd.
Otherwise, configuring encryption afterwards will become more painful.
We can't really do this by default from within g/g (only once we have gardener-operator). Hence, let's add it to the docs and values to encourage encryption, but also push a breaking release note to make this prominent enough.
Which issue(s) this PR fixes:
Part of https://github.com/gardener/gardener/issues/7999
Special notes for your reviewer:
This should go into the v1.73.0 release.
/milestone v1.73
/cc @timuthy
Release note:

Before upgrading to this gardener version, operators should configure `gardener-apiserver` to encrypt the `internalsecrets.core.gardener.cloud` resource in etcd.

/milesonte v1.73

/milestone v1.73


feat: Support regex payload

Close #35

Coverage remained the same at 100.0% when pulling a02fd1d89a30aa41ac7a03e7606c3c237440fe05 on support-regex-payload into 91450ce929ec1960c7d8d80074a509e442e3189d on master.


Using Multiple Similarity Metrics and Features for SVM and RandomForest Model

Hi,
I was reading this documentation (http://sampleclean.org/guide/) and I see that you can use any similarity metric to find the similarity between two strings on one column attribute. Can you use multiple similarity metrics to find the similarity between two strings rather than one? If so, how can you include multiple similarity metrics?
Also, what is the matrix that is fed into SVM and RandomForest? What are the columns for this matrix. Are the values different string metrics?

Hi,
The exposed API in the guide is a subset of the possible things you can do.  See the scala docs (esp. http://sampleclean.org/api/#sampleclean.clean.featurize.AnnotatedSimilarityFeaturizer, http://sampleclean.org/api/#sampleclean.clean.featurize.Featurizer).
You can define metrics between a set of strings and use the included libraries for similarity--however, there is no guarantee that our internal optimizations such a prefix filtering will hold.
The learning for deduplication learns a discriminative model given a feature vector representing similarities between strings. For N data, there are N^2 similarities, so a subset L \subset N^2 are labeled. The features are an ensemble of similarity metrics comparing the strings. However, this is flexible as well and you are free to write your own featurizer. The Active Learning should be agnostic to the choice of featurization.

Thank you for the response. I see in the API that it returns a list of R^d elements. By default, if I feed the system a list of strings coming from one column or attribute, would it use an ensemble of string metrics? If so, what are the metrics? Also, can you show a brief example of using AnnotatedSimilarityFeaturizer and Featurizer and how I can import my own similarity metrics into these functions. Specifically, if I have the metrics, Jaro Distance, edit distance and LCS, how would I use these abstract classes to make my own class.


Made some updates

Made some updates / changes in titles size, and added a link to my name. I hope this can be pushed again. Thanks for your help!!! ;-)

Made some updates in my profile page. I noticed there are issues with the extension of my avatar. Thanks for your help!!!

Closing your pull request (see above).


updated example

Hey @kylemcdonald , done. :) Glad to collaborate.
I just modified:

the ofApp.cpp code error + monitor overlay values
the project deployment target and sdk to 10.10 + 64 bit intel architecture
also I deleted and re-added the 2 sdk files. If there's some license problem you can delete it.

It's the first time I do this, so tell me if it's ok please or if I need do something else.
Thanks for the addon!

thanks! it's very close, but you're right about the 2 sdk files. if you look at the original repo you can see they're not checked in. is it possible for you to re-do this without the sdk files?


When using Redis queues a failure of the Redis server causes infinite exception logging.

I've reported this against Laravel but we actually use your queue implementation since we use Doctrine. That being the case I'm reporting it here too since you re-implement the same, not quite right, code that handles this.
https://github.com/laravel/framework/issues/16537
Essentially, it's taken three servers with hard drives full of exception logs to track down that workers should not try to do the same thing over and over again.

Yeah this is a problem I've seen myself actually, but I think it's one that will have to be handled in Laravel itself and we'll adapt around what they do.
For testing purposes mainly we do have a QueueMustStop interface that if attached to an exception forces the daemon to exit. Laravel needs something similar or a more sophisticated backoff mechanism certainly.

@cooperaj I'm going to close this, laravel/framework#16537 is the problem and I don't see how we could really solve this here without further hacking apart the upstream functionality. At that point I'd probably be better off writing my own implementation that can consume messages Laravel produces.


Add SingleChildScrollView

This widget is a replacement for ScrollableViewport that uses the new
Scrollable2 machinery. The widget is not based on Slivers but does use the new
scroll behavior classes.

@Hixie

SingleChildScrollView itself should have a test