Results page says "No results found" if a repository query is taking a while

It should indicate that it's loading results in some sort of way. It's only acceptable to say there's no results found if there /are/ no results found.

cc @amb8805 @lukecoy @Lettuceman44


fixed learning, resources, snippet and tests

I think, once this is committed, that we can launch this language and I can get on with the next: OpenEuphoria.

Remind me what needs to be done to go live. I'm fairly sure I've got the documentation up to scratch and I have over 20 exercises.

Remind me what needs to be done to go live.

Let's check the list at: https://exercism.org/docs/building/tracks/new

Request track icon: https://exercism.org/docs/building/tracks/new/prepare-for-launch#h-request-track-icon
Set online_editor.highlightjs_language in the config.json file: https://exercism.org/docs/building/tracks/new/prepare-for-launch#h-update-metadata. See https://github.com/highlightjs/highlight.js/blob/main/SUPPORTED_LANGUAGES.md for the languages supported out-of-the box. It looks like 8th isn't supported. Is there are language with similar syntax in that list? If not, I'd set it to plaintext.
Setup continuous integration: https://exercism.org/docs/building/tracks/new/setup-continuous-integration This is very important to prevent things from breaking.


Optional support for using lmdb as the backend database

Issue summary

The LMDB database might be better suited for storing the Filecoin blockchain than RocksDB. We should implement an optional blockstore backed by heed. Benchmarking the different backends can be done by measuring the time it takes to import a CAR file, the time it takes to finalize a snapshot import, and the time it takes to validate 1000 epochs.
The LMDB database has support doing async flushes which sacrifices some durability for performance. It would be interesting to benchmark with both the default settings and with async flushes enabled.
Importing a snapshot can be done with:
./forest --import-snapshot file.car --halt-after-import

Once a snapshot has been imported, we can validate the last 1000 epochs as such (where EPOCH is the snapshot height minus 1000):
./forest --import-snapshot file.car --skip-load --halt-after-import --height EPOCH

The results should be arranged in two tables like this:
Calibnet:

Change
Import Time
Total Time
Validation Time

rocksdb

lmdb

lmdb (async)

Mainnet:

Change
Import Time
Total Time
Validation Time

rocksdb

lmdb

lmdb (async)

Other information and links

@tyshko5 You want this task?

Please also include the database size after the import & validation.

Due to poor performance and high disk usage we are not supporting LMDB
ref #2310


Mean Radiant Temperature calculation

Hey, when calculating the UTCI based on ECMWF's forecasts, with the typical temporal resolution (hourly for 0-90hours lead time, then 3-hourly until 144 hours, then 6-hourly until 360hours) I sometimes encounter unreasonably high mean radiant temperatures within the 6-hourly resolved data (which in this plot is directly reflected in the "sunshine" contribution in the bottom panel), that can also be seen in UTCI. For further examples check this twitter bot

I call the functions from thermofeel as
sec_in_step = [(timevec[i+1]-timevec[i]).seconds for i in range(len(timevec)-1)]
hrs_in_step = [(timevec[i+1]-timevec[i]).seconds/3600 for i in range(len(timevec)-1)]

# Solar zenith angle, integrated
cosszai = np.zeros(n_time_steps-1)

for i in range(1,n_time_steps):
    cosszai[i-1] = thermofeel.calculate_cos_solar_zenith_angle_integrated(lat=latlon[0],
                                            lon=latlon[1],
                                            y=timevec[i].year,
                                            m=timevec[i].month,
                                            d=timevec[i].day,
                                            h=timevec[i].hour,
                                            base=0,
                                            step=hrs_in_step[i-1])

# mean radiant temperature
mrt = np.zeros_like(t2m[:,1:])

for j in range(n_members):
    mrt[j,:] = thermofeel.calculate_mean_radiant_temperature(
                                         np.diff(ssrd[j,:])/sec_in_step,
                                         np.diff(ssr[j,:])/sec_in_step,
                                         np.diff(fdir[j,:])/sec_in_step,
                                         np.diff(strd[j,:])/sec_in_step,
                                         np.diff(strr[j,:])/sec_in_step,
                                         cosszai)

I was wondering whether you have an idea why the mean radiant temperature is going crazy, or how to test / fix this issue!

We will close this issue as we believe this is now fixed.
Feel free to reopen if you find it is not.

Using thermofeel v1.1.1 I'm now doing
forecast_hours = [int((timevec[i]-timevec[0]).total_seconds()/3600) for i in range(len(timevec))]
cosszai = np.zeros(n_time_steps-1)

for i in range(1,n_time_steps):
    cosszai[i-1] = thermofeel.calculate_cos_solar_zenith_angle_integrated(lat=latlon[0],
                                            lon=latlon[1],
                                            y=timevec[i].year,
                                            m=timevec[i].month,
                                            d=timevec[i].day,
                                            h=timevec[i].hour,
                                            tbegin=forecast_hours[i-1],
                                            tend=forecast_hours[i])

So the ymdh time is provided in UT, latlon defines the location, tbegin is the forecast lead time in hours from the previous time step, tend is the forecast lead time for ymdh. The cosszai array then looks reasonable I guess, plt.plot(forecast_hours[1:],cosszai)

However, the same graph as above now shows weird double peaks in UTCI and again suddenly jumps to unreasonably high values after 5 days.

which are due to peaks in MRT, plt.plot(forecast_hours[1:],mrt[1,:])

Any clue what is going on here?

Feel free to reopen if you find it is not.

I can't somehow?

https://github.com/ecmwf-projects/thermofeel/blob/48d7cf86758e056f4c300815a0c3fbfe725e0c27/thermofeel/thermofeel.py#L164-L174
Okay, I think I found the issue. y, m, d, h are the time from the forecast initialisation, not the actual time step the cosine is calculated for. Resulting figure looks also much better. Sorry for the confusion, to prevent this I'll create a PR with some additional info in the function comments


feature - profile ui

Github Issue URL/Tags (required)
What's this PR do? Please give a technical summary (required)

[x] create profile UI

Any references (stackoverflow …) (optional)

:+1: There are no linter violations.


PID namespace sharing is already available in docker

Official documentation: https://docs.docker.com/engine/reference/run/#pid-settings-pid

This change is

I signed the CNCF CLA


EditorExportPlatformJavascript is using CPU when no Javascript export is present in project

Godot version
v4.0.alpha.calinou [26b21dc0c]
System information
Mac OSX (Intel 2019)
Issue description
I was running perf testing again on the latest version as we had some more performance regressions.
I found that the Javascript editor export platform was using 20% of the CPU this time, but I did not have any related export settings in my project.
I would expect that this loop should only be run when the user actually has some use for it. For now I've reduced the timing of the calls from 1 ms to 6.9 ms to keep updates in line with 144hz monitors.
https://github.com/godotengine/godot/pull/58081
Steps to reproduce

Run godot 4.x

Minimal reproduction project
No response

Is this still reproducible in 4.0 RC 3 or later?

@akien-mga As of 4.rc.3 my performance is doing great.
My fairly heavy project runs at around 3% cpu.
However the GPU usage has climbed significantly since 3.5.1 (before around 4-5% now around 8% using compatibility mode)

I haven't had time to compile the engine and check for this particular performance issue but the engine is no longer using anything close to 20% of my CPU on the same machine.
You guys have been doing a great job of optimisation! 👍
I will close this issue.


Release Google.Shopping.Merchant.Accounts.V1Beta version 1.0.0-beta01

Changes in this release:
Initial release.

Created release for Google.Shopping.Merchant.Accounts.V1Beta-1.0.0-beta01


If there is a secondary jump on the page then the plugin will not work.

I have encountered this problem during use：
When a page condition is set to change the title of a specific page (either in inclusion mode or in ongoing mode), it will only work properly if the target page is opened directly on the current page. If I open more than one eligible page in the background, it will not take effect.
Later I found out that it was because the target page I wanted to open was jumped over after clicking the link.
For example.
I want "www.example.com/myname" as a condition to change the title of the corresponding tab.
Then I clicked on the corresponding link on that site, and it was not a direct link like "www.example.com/myname/. *", but "www.example.com/. *", and then about 1 second after the link, the URL will automatically change to "www.example.com/myname/. *". But the plugin does not recognize this link change, as long as I open it through www.example.com/. *, it will not work.
And if I jump to other www.example.com/myname/. * pages through this page later, it will not work properly. *, it won't work unless I refresh the current page directly.
So I can only set the condition to "www.example.com", but this condition is too broad and not exactly the effect I want.
I don't know if I can optimize it. Thank you very much.

Hi @godefy,
The entire code base has been rewritten. Tab Modifier 1.0 is now available!
Is the issue still persists?
Bests


Adds a pixel format parameter to Linux frame buffer platform setup.

What does the pull request do?
Adds a pixel format parameter to Linux frame buffer platform setup.
What is the current behavior?
Currently Linux frame buffer setup always changes the frame buffer pixel format to RGBA which results in the screen being cleared if the default pixel format is not RGBA (on a Raspberry PI 3 with 7" display it's BGRA) . This clears any splash screen and leaves the screen blank for a period, which is not a good UX.
What is the updated/expected behavior with this PR?
Now the Linux frame buffer setup can select the correct pixel format or use null to leave the pixel format unchanged.
How was the solution implemented (if it's not obvious)?
n/a
Checklist

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

Breaking changes
Default parameters for the StartLinuxFbDev extension method will leave the frame buffer pixel format unchanged rather than force a change to RGBA.
Obsoletions / Deprecations
n/a
Fixed issues
#5291

@kekekeks I found a typo in the committed code, the FbdevOutput should read
public FbdevOutput(string fileName = null) : this(fileName, null)
What is the best way to submit a fix for this, a new PR?


Define package for managing configurations of Kitura apps across different environments

We have released https://github.com/IBM-Swift/Configuration and https://github.com/IBM-Swift/CloudConfiguration to the public. CloudConfiguration will be the package that developers can use to access configurations in different environments transparently.


Rendering one template within another

Liquid does have a syntax for this, but I don't see it within this library. It is a very useful part of Liquid.
https://shopify.github.io/liquid/tags/template/

While we work toward the 100% parity with ruby liquid, we'll ensure this feature gets added. I've labeled this issue as an enhancement for now


Mkl bfc allocator and static memory allocator registry

Pull request for

Static Registry of CPU Memory Allocators that can be queried to return the highest priority allocator
A BFC-based memory allocator that MKL backends can use to request memory from

Can one of the admins verify this patch?

Looks good after the small nit-pick changes I suggested above.

@tensorflow-jenkins test this please

@tensorflow-jenkins Test this please

@tensorflow-jenkins test this please

@tensorflow-jenkins test this please

@tensorflow-jenkins test this please


t.model.foobar({pagination: true}) pagination not exposing args

Hello, I'm trying to expose the pagination args using t.model.foobar({pagination: true}); but it seems to only expose skip:

using "@nexus/schema": "^0.14.0",

Hey @johhansantana, I'm pretty sure this issue must be fixed by now. I'm closing it, but feel free to chime in if it's still the case on the latest versions.


set nginx to use sock instead of fpm method for now

see #38

There is no immediate reason to do so. Fpm is more scalable, sock is faster.


Document

Key points

[ ] Commands -- PEXPlugins/PermissionsEx#1945
[ ] Contexts -- what are they, how do you transition?
[ ] Permission resoluton
[ ] Tutorial to create a basic setup
[ ] Configuring everything
[ ] Rank ladders

Good to see this at last, I'll help any way I can. May I suggest you add a section on "Automated Conversion from Bukkit's PEx" to the list (btw, it works brilliantly). Enumerating the options for subject-type, subject, type and identifier in the permissionsex permissions would also be helpful.


Initial provider support

Description of your changes
This PR is the initial implementation of the provider. This PR contains the initial resources, and more will be added later as well as documentation.
I have:

[x] Read and followed Crossplane's contribution process.
[x] Run make reviewable test to ensure this PR is ready for review.

How has this code been tested
Tested locally

@haarchri  Can this get reviewed to merge?

Can you Check CI ?

any updates ?


dracut error on kernel replace

I try to replace the default kernel in my image. I've set up adding new repos and launch of custom scripts using the 'script' module in my recipe.
If launch these commands
rpm-ostree cliwrap install-to-root / && \
rpm-ostree override remove kernel kernel-core kernel-modules kernel-modules-core kernel-modules-extra --install kernel-cachyos

I get the next error in action logs:
error: rpm-ostree kernel-install wrapper: Running dracut: Invalid cross-device link (os error 18)
The pipeline does not fail, but if I try to boot from the built image it will stuck on boot screen.

Try to use rpm-ostree override replace method instead:
    rpm-ostree cliwrap install-to-root / && \
    rpm-ostree override replace --experimental --from repo=copr:copr.fedorainfracloud.org:bieszczaders:kernel-cachyos kernel kernel-core kernel-modules kernel-modules-core kernel-modules-extra

I use the same commands in 'startingpoint' based repository and it works fine.
I believe the error message Invalid cross-device link implies something is wrong in mounting or path mapping settings.

Mind posting a link to your repo so I can test it later?

Here is my repository based on new template: https://github.com/antuan1996/formile-cachyos-ublue
Build logs: link

So I think we may have a fix that we pushed to the main branch. You can try it out in your Github action by setting use_unstable_cli to true.

I confirm the problem is gone. Thank you very much!


autofocus on render

I am using react-edit-text for a flashcard application. I have a button that is used to create new cards, and when I press it, a new card with an EditText component is mapped in the DOM.
I have implemented a function through useRef that once the card appears, the "EditText" component is automatically clicked so as not to have to click on the text again to change it.
It would be great if this was implemented.

Hi,
I can consider adding a prop that sets the initial state of the component (either in edit mode or display mode).
For example, the following would resolve your use case:
<EditText initialState="edit"/>

Please let me know whether you think this would work for you.

Well, I already had a workaround at the moment of creating the issue, but with that, it would be much much easier.


Migrate Azure Identity tests from Power Mockito Mockito

Identity tests are heavily using Power Mockito.
Migrate them to use Mockito instead

Adding up for grabs label and moving this to the backlog

This work is complete now.


Update citrix-receiver to 12.4.0

After making all changes to the cask:

[x] brew cask audit --download {{cask_file}} is error-free.
[x] brew cask style --fix {{cask_file}} reports no offenses.
[x] The commit message includes the cask’s name and version.

Released Nov 6, 2016. Release notes at http://docs.citrix.com/en-us/receiver/mac/12-4.html.

@fanquake Thanks for the merge!


pls help me, i can't train the model on custom dataset.

Hello, I tried to change almost all the configuration parameters, but nothing helps. The training always stops at 200 iterations, I've spent over 100 hours trying to figure out why. 1400 photos in the train and 450 for validation.
I adapted my custom dataset
I adapted the structure of my dataset to the Kitty_tiny dataset, as shown in the DEMO in mmdetection, in order to train the model exactly as shown in the DEMO
MODEL - SSD300
The training always stops at 200 iterations, i don't know why((((((
tmp/ipykernel_3063/3895221999.py:58: DeprecationWarning: np.long is a deprecated alias for np.compat.long. To silence this warning, use np.compat.long by itself. In the likely event your code does not need to work on Python 2 you can use the builtin int for which np.compat.long is itself an alias. Doing this will not modify any behaviour and is safe. When replacing np.long, you may wish to use e.g. np.int64 or np.int32 to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
labels=np.array(gt_labels, dtype=np.long),
/tmp/ipykernel_3063/3895221999.py:61: DeprecationWarning: np.long is a deprecated alias for np.compat.long. To silence this warning, use np.compat.long by itself. In the likely event your code does not need to work on Python 2 you can use the builtin int for which np.compat.long is itself an alias. Doing this will not modify any behaviour and is safe. When replacing np.long, you may wish to use e.g. np.int64 or np.int32 to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
labels_ignore=np.array(gt_labels_ignore, dtype=np.long))
/home/ivan/Рабочий стол/mmdetection/mmdet/datasets/custom.py:179: UserWarning: CustomDataset does not support filtering empty gt images.
warnings.warn(
2022-03-21 21:46:05,961 - mmdet - INFO - load checkpoint from local path: checkpoints/test.pth
2022-03-21 21:46:07,965 - mmdet - WARNING - The model and loaded state dict do not match exactly
size mismatch for bbox_head.cls_convs.0.0.weight: copying a param with shape torch.Size([324, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 512, 3, 3]).
size mismatch for bbox_head.cls_convs.0.0.bias: copying a param with shape torch.Size([324]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for bbox_head.cls_convs.1.0.weight: copying a param with shape torch.Size([486, 1024, 3, 3]) from checkpoint, the shape in current model is torch.Size([96, 1024, 3, 3]).
size mismatch for bbox_head.cls_convs.1.0.bias: copying a param with shape torch.Size([486]) from checkpoint, the shape in current model is torch.Size([96]).
size mismatch for bbox_head.cls_convs.2.0.weight: copying a param with shape torch.Size([486, 512, 3, 3]) from checkpoint, the shape in current model is torch.Size([96, 512, 3, 3]).
size mismatch for bbox_head.cls_convs.2.0.bias: copying a param with shape torch.Size([486]) from checkpoint, the shape in current model is torch.Size([96]).
size mismatch for bbox_head.cls_convs.3.0.weight: copying a param with shape torch.Size([486, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([96, 256, 3, 3]).
size mismatch for bbox_head.cls_convs.3.0.bias: copying a param with shape torch.Size([486]) from checkpoint, the shape in current model is torch.Size([96]).
size mismatch for bbox_head.cls_convs.4.0.weight: copying a param with shape torch.Size([324, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 256, 3, 3]).
size mismatch for bbox_head.cls_convs.4.0.bias: copying a param with shape torch.Size([324]) from checkpoint, the shape in current model is torch.Size([64]).
size mismatch for bbox_head.cls_convs.5.0.weight: copying a param with shape torch.Size([324, 256, 3, 3]) from checkpoint, the shape in current model is torch.Size([64, 256, 3, 3]).
size mismatch for bbox_head.cls_convs.5.0.bias: copying a param with shape torch.Size([324]) from checkpoint, the shape in current model is torch.Size([64]).
2022-03-21 21:46:07,966 - mmdet - INFO - Start running, host: ivan@ivan-GL73-8RC, work_dir: /home/ivan/Рабочий стол/mmdetection/tutorial_exps
2022-03-21 21:46:07,966 - mmdet - INFO - Hooks will be executed in the following order:
before_run:
(VERY_HIGH   ) StepLrUpdaterHook
(NORMAL      ) CheckpointHook
(LOW         ) EvalHook
(VERY_LOW    ) TextLoggerHook
before_train_epoch:
(VERY_HIGH   ) StepLrUpdaterHook
(NORMAL      ) NumClassCheckHook
(LOW         ) IterTimerHook
(LOW         ) EvalHook
(VERY_LOW    ) TextLoggerHook
before_train_iter:
(VERY_HIGH   ) StepLrUpdaterHook
(LOW         ) IterTimerHook
(LOW         ) EvalHook
after_train_iter:
(ABOVE_NORMAL) OptimizerHook
(NORMAL      ) CheckpointHook
(LOW         ) IterTimerHook
(LOW         ) EvalHook
(VERY_LOW    ) TextLoggerHook
(VERY_LOW    ) CheckInvalidLossHook
after_train_epoch:
(NORMAL      ) CheckpointHook
(LOW         ) EvalHook
(VERY_LOW    ) TextLoggerHook
before_val_epoch:
(NORMAL      ) NumClassCheckHook
(LOW         ) IterTimerHook
(VERY_LOW    ) TextLoggerHook
before_val_iter:
(LOW         ) IterTimerHook
after_val_iter:
(LOW         ) IterTimerHook
after_val_epoch:
(VERY_LOW    ) TextLoggerHook
after_run:
(VERY_LOW    ) TextLoggerHook
2022-03-21 21:46:07,967 - mmdet - INFO - workflow: [('train', 1)], max: 24 epochs
2022-03-21 21:46:07,967 - mmdet - INFO - Checkpoints will be saved to /home/ivan/Рабочий стол/mmdetection/tutorial_exps by HardDiskBackend.
/home/ivan/anaconda3/lib/python3.9/site-packages/torch/nn/functional.py:718: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at  /pytorch/c10/core/TensorImpl.h:1156.)
return torch.max_pool2d(input, kernel_size, stride, padding, dilation, ceil_mode)
2022-03-21 21:46:36,019 - mmdet - INFO - Epoch [1][10/881]	lr: 2.500e-03, eta: 15:59:09, time: 2.723, data_time: 0.817, memory: 1782, loss_cls: 9.9198, loss_bbox: 5.8576, loss: 15.7773
2022-03-21 21:46:53,797 - mmdet - INFO - Epoch [1][20/881]	lr: 2.500e-03, eta: 13:15:12, time: 1.794, data_time: 1.053, memory: 1782, loss_cls: 6.9702, loss_bbox: 7.9114, loss: 14.8815
2022-03-21 21:47:13,140 - mmdet - INFO - Epoch [1][30/881]	lr: 2.500e-03, eta: 12:37:01, time: 1.936, data_time: 1.203, memory: 1782, loss_cls: 6.8268, loss_bbox: 7.8771, loss: 14.7039
2022-03-21 21:47:43,220 - mmdet - INFO - Epoch [1][40/881]	lr: 2.500e-03, eta: 13:43:44, time: 2.914, data_time: 2.131, memory: 1782, loss_cls: 5.4283, loss_bbox: 7.3805, loss: 12.8088
2022-03-21 21:48:02,945 - mmdet - INFO - Epoch [1][50/881]	lr: 2.500e-03, eta: 13:24:00, time: 2.067, data_time: 1.381, memory: 1782, loss_cls: 5.2074, loss_bbox: 7.2640, loss: 12.4714
2022-03-21 21:48:19,138 - mmdet - INFO - Epoch [1][60/881]	lr: 2.500e-03, eta: 12:44:30, time: 1.619, data_time: 0.859, memory: 1782, loss_cls: 5.2744, loss_bbox: 7.4937, loss: 12.7681
2022-03-21 21:48:36,040 - mmdet - INFO - Epoch [1][70/881]	lr: 2.500e-03, eta: 12:19:47, time: 1.690, data_time: 1.008, memory: 1782, loss_cls: 5.6761, loss_bbox: 7.8002, loss: 13.4763
2022-03-21 21:48:55,586 - mmdet - INFO - Epoch [1][80/881]	lr: 2.500e-03, eta: 12:12:47, time: 1.955, data_time: 1.255, memory: 1782, loss_cls: 5.1228, loss_bbox: 8.7396, loss: 13.8623
2022-03-21 21:49:16,196 - mmdet - INFO - Epoch [1][90/881]	lr: 2.500e-03, eta: 12:11:24, time: 2.060, data_time: 1.383, memory: 1782, loss_cls: 5.6127, loss_bbox: 6.9650, loss: 12.5777
2022-03-21 21:49:29,004 - mmdet - INFO - Epoch [1][100/881]	lr: 2.500e-03, eta: 11:42:51, time: 1.281, data_time: 0.631, memory: 1782, loss_cls: 5.2070, loss_bbox: 6.3978, loss: 11.6048
2022-03-21 21:49:45,604 - mmdet - INFO - Epoch [1][110/881]	lr: 2.500e-03, eta: 11:31:33, time: 1.660, data_time: 0.957, memory: 1782, loss_cls: 5.5467, loss_bbox: 6.4412, loss: 11.9879
2022-03-21 21:49:58,321 - mmdet - INFO - Epoch [1][120/881]	lr: 2.500e-03, eta: 11:10:45, time: 1.272, data_time: 0.534, memory: 1782, loss_cls: 5.1328, loss_bbox: 5.7493, loss: 10.8820
2022-03-21 21:50:16,054 - mmdet - INFO - Epoch [1][130/881]	lr: 2.500e-03, eta: 11:06:39, time: 1.774, data_time: 1.048, memory: 1782, loss_cls: 4.5745, loss_bbox: 5.6167, loss: 10.1911
2022-03-21 21:50:31,525 - mmdet - INFO - Epoch [1][140/881]	lr: 2.500e-03, eta: 10:57:24, time: 1.547, data_time: 0.810, memory: 1782, loss_cls: 4.9017, loss_bbox: 6.4228, loss: 11.3245
2022-03-21 21:50:45,390 - mmdet - INFO - Epoch [1][150/881]	lr: 2.500e-03, eta: 10:45:37, time: 1.386, data_time: 0.842, memory: 1782, loss_cls: 4.7573, loss_bbox: 5.2906, loss: 10.0479
2022-03-21 21:51:03,105 - mmdet - INFO - Epoch [1][160/881]	lr: 2.500e-03, eta: 10:43:42, time: 1.771, data_time: 1.122, memory: 1782, loss_cls: 4.5290, loss_bbox: 5.5199, loss: 10.0489
2022-03-21 21:51:23,782 - mmdet - INFO - Epoch [1][170/881]	lr: 2.500e-03, eta: 10:47:59, time: 2.064, data_time: 1.287, memory: 1782, loss_cls: 4.8839, loss_bbox: 5.0466, loss: 9.9305
2022-03-21 21:51:40,147 - mmdet - INFO - Epoch [1][180/881]	lr: 2.500e-03, eta: 10:43:26, time: 1.636, data_time: 1.056, memory: 1782, loss_cls: 4.4631, loss_bbox: 5.1512, loss: 9.6143
2022-03-21 21:51:57,418 - mmdet - INFO - Epoch [1][190/881]	lr: 2.500e-03, eta: 10:41:08, time: 1.733, data_time: 1.045, memory: 1782, loss_cls: 4.4632, loss_bbox: 5.4469, loss: 9.9100
2022-03-21 21:52:14,014 - mmdet - INFO - Epoch [1][200/881]	lr: 2.500e-03, eta: 10:37:46, time: 1.661, data_time: 0.895, memory: 1782, loss_cls: nan, loss_bbox: nan, loss: nan
2022-03-21 21:52:14,738 - mmdet - INFO - loss become infinite or NaN!
AssertionError                            Traceback (most recent call last)
/tmp/ipykernel_3063/79739429.py in
23 # Create work_diri
24 mmcv.mkdir_or_exist(osp.abspath(cfg.work_dir))
---> 25 train_detector(model, datasets, cfg, distributed=False, validate=True)
26
~/Рабочий стол/mmdetection/mmdet/apis/train.py in train_detector(model, dataset, cfg, distributed, validate, timestamp, meta)
206     elif cfg.load_from:
207         runner.load_checkpoint(cfg.load_from)
--> 208     runner.run(data_loaders, cfg.workflow)
~/anaconda3/lib/python3.9/site-packages/mmcv/runner/epoch_based_runner.py in run(self, data_loaders, workflow, max_epochs, **kwargs)
125                     if mode == 'train' and self.epoch >= self._max_epochs:
126                         break
--> 127                     epoch_runner(data_loaders[i], **kwargs)
128
129         time.sleep(1)  # wait for some hooks like loggers to finish
~/anaconda3/lib/python3.9/site-packages/mmcv/runner/epoch_based_runner.py in train(self, data_loader, **kwargs)
49             self.call_hook('before_train_iter')
50             self.run_iter(data_batch, train_mode=True, **kwargs)
---> 51             self.call_hook('after_train_iter')
52             self._iter += 1
53
~/anaconda3/lib/python3.9/site-packages/mmcv/runner/base_runner.py in call_hook(self, fn_name)
307         """
308         for hook in self._hooks:
--> 309             getattr(hook, fn_name)(self)
310
311     def get_hook_info(self):
~/Рабочий стол/mmdetection/mmdet/core/hook/checkloss_hook.py in after_train_iter(self, runner)
21     def after_train_iter(self, runner):
22         if self.every_n_iters(runner, self.interval):
---> 23             assert torch.isfinite(runner.outputs['loss']),
24                 runner.logger.info('loss become infinite or NaN!')
Config:
input_size = 300
model = dict(
type='SingleStageDetector',
backbone=dict(
type='SSDVGG',
depth=16,
with_last_pool=False,
ceil_mode=True,
out_indices=(3, 4),
out_feature_indices=(22, 34),
init_cfg=dict(
type='Pretrained', checkpoint='open-mmlab://vgg16_caffe')),
neck=dict(
type='SSDNeck',
in_channels=(512, 1024),
out_channels=(512, 1024, 512, 256, 256, 256),
level_strides=(2, 2, 1, 1),
level_paddings=(1, 1, 0, 0),
l2_norm_scale=20),
bbox_head=dict(
type='SSDHead',
in_channels=(512, 1024, 512, 256, 256, 256),
num_classes=15,
anchor_generator=dict(
type='SSDAnchorGenerator',
scale_major=False,
input_size=300,
basesize_ratio_range=(0.15, 0.9),
strides=[8, 16, 32, 64, 100, 300],
ratios=[[2], [2, 3], [2, 3], [2, 3], [2], [2]]),
bbox_coder=dict(
type='DeltaXYWHBBoxCoder',
target_means=[0.0, 0.0, 0.0, 0.0],
target_stds=[0.1, 0.1, 0.2, 0.2])),
train_cfg=dict(
assigner=dict(
type='MaxIoUAssigner',
pos_iou_thr=0.5,
neg_iou_thr=0.5,
min_pos_iou=0.0,
ignore_iof_thr=-1,
gt_max_assign_all=False),
smoothl1_beta=1.0,
allowed_border=-1,
pos_weight=-1,
neg_pos_ratio=3,
debug=False),
test_cfg=dict(
nms_pre=1000,
nms=dict(type='nms', iou_threshold=0.45),
min_bbox_size=0,
score_thr=0.02,
max_per_img=200))
cudnn_benchmark = True
dataset_type = 'DOTA'
data_root = 'AdaptedDataset/'
img_norm_cfg = dict(mean=[123.675, 116.28, 103.53], std=[1, 1, 1], to_rgb=True)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='Expand',
mean=[123.675, 116.28, 103.53],
to_rgb=True,
ratio_range=(1, 4)),
dict(
type='MinIoURandomCrop',
min_ious=(0.1, 0.3, 0.5, 0.7, 0.9),
min_crop_size=0.3),
dict(type='Resize', img_scale=(300, 300), keep_ratio=False),
dict(type='RandomFlip', flip_ratio=0.5),
dict(
type='PhotoMetricDistortion',
brightness_delta=32,
contrast_range=(0.5, 1.5),
saturation_range=(0.5, 1.5),
hue_delta=18),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[1, 1, 1],
to_rgb=True),
dict(type='DefaultFormatBundle'),
dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels'])
]
test_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(300, 300),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=False),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[1, 1, 1],
to_rgb=True),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
]
data = dict(
samples_per_gpu=8,
workers_per_gpu=3,
train=dict(
type='RepeatDataset',
times=5,
dataset=dict(
type='DOTA',
ann_file='train.txt',
img_prefix='training/image_2',
pipeline=[
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', with_bbox=True),
dict(
type='Expand',
mean=[123.675, 116.28, 103.53],
to_rgb=True,
ratio_range=(1, 4)),
dict(
type='MinIoURandomCrop',
min_ious=(0.1, 0.3, 0.5, 0.7, 0.9),
min_crop_size=0.3),
dict(type='Resize', img_scale=(300, 300), keep_ratio=False),
dict(type='RandomFlip', flip_ratio=0.5),
dict(
type='PhotoMetricDistortion',
brightness_delta=32,
contrast_range=(0.5, 1.5),
saturation_range=(0.5, 1.5),
hue_delta=18),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[1, 1, 1],
to_rgb=True),
dict(type='DefaultFormatBundle'),
dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels'])
],
data_root='AdaptedDataset/')),
val=dict(
type='DOTA',
ann_file='val.txt',
img_prefix='training/image_2',
pipeline=[
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(300, 300),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=False),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[1, 1, 1],
to_rgb=True),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
],
data_root='AdaptedDataset/'),
test=dict(
type='DOTA',
ann_file='train.txt',
img_prefix='training/image_2',
pipeline=[
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(300, 300),
flip=False,
transforms=[
dict(type='Resize', keep_ratio=False),
dict(
type='Normalize',
mean=[123.675, 116.28, 103.53],
std=[1, 1, 1],
to_rgb=True),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img'])
])
],
data_root='AdaptedDataset/'))
evaluation = dict(interval=1, metric='mAP')
optimizer = dict(type='SGD', lr=0.0025, momentum=0.9, weight_decay=0.0005)
optimizer_config = dict()
lr_config = dict(
policy='step',
warmup=None,
warmup_iters=500,
warmup_ratio=0.001,
step=[16, 22])
runner = dict(type='EpochBasedRunner', max_epochs=24)
checkpoint_config = dict(interval=1)
log_config = dict(interval=10, hooks=[dict(type='TextLoggerHook')])
custom_hooks = [
dict(type='NumClassCheckHook'),
dict(type='CheckInvalidLossHook', interval=50, priority='VERY_LOW')
]
dist_params = dict(backend='nccl')
log_level = 'INFO'
load_from = 'checkpoints/test.pth'
resume_from = None
workflow = [('train', 1)]
opencv_num_threads = 0
mp_start_method = 'fork'
work_dir = 'tutorial_exps'
seed = 0
gpu_ids = range(0, 1)
annotations:
import copy
import os.path as osp
import mmcv
import numpy as np
from mmdet.datasets.builder import DATASETS
from mmdet.datasets.custom import CustomDataset
@DATASETS.register_module()
class DOTA(CustomDataset):
CLASSES = ('ship','small-vehicle','large-vehicle','plane','harbor','storage-tank','tennis-court','bridge',
           'swimming-pool','helicopter','basketball-court','baseball-diamond','roundabout','soccer-ball-field',
           'ground-track-field')

def load_annotations(self, ann_file):
    cat2label = {k: i for i, k in enumerate(self.CLASSES)}
    # load image list from file
    image_list = mmcv.list_from_file(self.ann_file)

    data_infos = []
    # convert annotations to middle format
    for image_id in image_list:
        filename = f'{self.img_prefix}/{image_id}.png'
        image = mmcv.imread(filename)
        height, width = image.shape[:2]

        data_info = dict(filename=f'{image_id}.png', width=width, height=height)

        # load annotations
        label_prefix = self.img_prefix.replace('image_2', 'label_2')
        lines = mmcv.list_from_file(osp.join(label_prefix, f'{image_id}.txt'))

        content = [line.strip().split(' ') for line in lines]
        bbox_names = [x[8] for x in content]
        bboxes = [[float(info) for info in (x[0:2] + x[4:6])] for x in content]

#[:n] + l[n:]
gt_bboxes = []
gt_labels = []
gt_bboxes_ignore = []
gt_labels_ignore = []
        # filter 'DontCare'
        for bbox_name, bbox in zip(bbox_names, bboxes):
            if bbox_name in cat2label:
                gt_labels.append(cat2label[bbox_name])
                gt_bboxes.append(bbox)
            else:
                gt_labels_ignore.append(-1)
                gt_bboxes_ignore.append(bbox)

        data_anno = dict(
            bboxes=np.array(gt_bboxes, dtype=np.float32).reshape(-1, 4),
            labels=np.array(gt_labels, dtype=np.long),
            bboxes_ignore=np.array(gt_bboxes_ignore,
                                   dtype=np.float32).reshape(-1, 4),
            labels_ignore=np.array(gt_labels_ignore, dtype=np.long))

        data_info.update(ann=data_anno)
        data_infos.append(data_info)

    return data_infos

You can check whether the gt after data enhancement is normal and whether there is a division by zero error during training.

You can check whether the gt after data enhancement is normal and whether there is a division by zero error during training.
How i can do it?


Use named fonts and colors in default theme (and style guide for developers re this)

When developing or customizing the default theme I want to to use standard named fonts and colors so that it is easier to change the theme coherently going forward
We currently tend to implement ad-hoc styling e.g. here is a snippet of Avatar.jsx

    {name}

We should be using standard named colors from tailwind.config.js so that

it is easy for us to maintain consistency
it is easy to for a user to systematically change colors across the whole site

Our default theme does its styling for fonts using font-sans and font-serif. For colors people just add colors ad-hoc as they want. This means that making consistent changes to the theme either for developers or users meaning getting into the templates and components themselves which is painful and error-prone.
Acceptance

[ ] using named semantic fonts for key font areas
[ ] using named semantic colors for key color areas
[ ] style guide for this

Tasks

[ ] Analyse how we implement in config
[ ] Add semantic items
[ ] Refactor existing templates and components to use these semantic labels
[ ] Add a note to developer docs to this (style guide?)

Notes
Research
See https://tailwindcss.com/docs/font-family#customizing-your-theme and https://tailwindcss.com/docs/customizing-colors#using-the-default-colors
❗ complication: we use typography to do our default styling. However, we can customize key parts relatively easily https://tailwindcss.com/docs/typography-plugin#element-modifiers
eg. for headings we can do (in templates)

  {{ markdown }}

Design
What areas do we want to customize by default? What's the KISS answer?

fonts:

default font: defaults to font-sans though you can change this. See https://tailwindcss.com/docs/font-family#customizing-the-default-font

however changing this in typography is painful as we have to change all the block level selectors. => maybe easiest is to set font-sans

body: default font (font-sans)
headings: make these customizable - relatively easy to do

typography is main focus plus recommend usage in style guide

navbar??: just follow default
footer just uses body and headings as usual

colors: (all of these for dark/light)

background
primary
secondary
...

Implementation in tailwind.config.js is something like this:
(note we want to still use tailwind default palette if we can in our default them)
module.exports = {
  theme: {
    fontFamily: {
      'sans': ['ui-sans-serif', 'system-ui', ...], # changes default and body font
      'serif': ['ui-serif', 'Georgia', ...],
      'mono': ['ui-monospace', 'SFMono-Regular', ...],
      'headings': ['Oswald', ...],
    }
  },
  colors: {
    background: {
      DEFAULT: colors.black,
      dark
   },
   primary: {
     DEFAULT: ...
     dark:
   },
   ...
}

@rufuspollock adding the semantic items in tailwind.config.js and refactoring components to use them makes things fairly simple in changing the fonts and colors of the site.
some questions:

although adding this configuration in config.js is possible, the user would still need to add the imports for fonts in styles/global.css meaning they still have to dig in to .flowershow folder.

Add a note to developer docs to this (style guide?)

wouldn't this task be a modification in #345 ?

@khalilcodes we should not do anything here in config.js - the user should edit tailwind.config.js - and styles/globals.css. BTW i don't think setting custom fonts is part of this - that work is separate and part of #292

wouldn't this task be a modification in https://github.com/flowershow/flowershow/pull/345 ?

No, these two tasks are quite distinct - though obviously related. This task is about refactoring the current default them to use named colors and fonts from tailwind.config.js. #292 and #345 are then about explaining to users how to customize the fonts and colors by changing the named values we have added here.

@khalilcodes when do you think you'll get the PR in for this to review. (for future ref, it would have been great to have a first part of this pushed e.g. the fonts) so i could quickly review - and then we move on to the more complex colors part). That way we ensure we are on the same page. 😄

@khalilcodes i'm still not sure we apply font headings font to the prose stuff. Can you confirm we are doing that?

@khalilcodes i'm still not sure we apply font headings font to the prose stuff. Can you confirm we are doing that?

Ans: we are doing in the docs layout atm. Up to you to use this wherever you need.

FIXED. See acceptance. Have added named colors and fonts, using them and have a short docs on this.


Bug in cohortManifest() when new cohorts added to repo

https://github.com/OHDSI/Ulysses/blob/e1f093643e79607e7d98edea9b37091282a918a4/R/cohorts.R#L88-L93
I didn't investigate much yet, but here is the error message.  I added 7 cohorts to my repo and got this error when cohortManifest() was run in my analysis script:
⚠ Circe Cohorts have changed since last check
❯ Update NA to version NA
❯ Update NA to version NA
❯ Update NA to version NA
❯ Update NA to version NA
❯ Update NA to version NA
❯ Update NA to version NA
❯ Update NA to version NA
Error in `$<-`:
! Assigned data `*vtmp*` must be compatible with existing data.
✖ Existing data has 1 row.
✖ Assigned data has 8 rows.
ℹ Row updates require a list value. Do you need `list()` or `as.list()`?
Caused by error in `vectbl_recycle_rhs_rows()`:
! Can't recycle input of size 8 to size 1.
Run `rlang::last_trace()` to see where the error occurred.

yes I know about this, thanks for adding it to the issue log. Thinking about taking this out and re-thinking the function. Lets think about it internally


Issue while enabling Private CDN for multiple site collections and sub-sites through foreach loop using PowerShell script

I have a requirement to enable Private CDN origin to a custom document library for multiple sharepoint site collections and subsites using PowerShell. I have written CSOM PowerShell code to read all sub sites and trying to add new Origin using "Add-SPOTenantCdnOrigin -CdnType Private -OriginUrl <OriginURL> -Confirm:$false" command but after successfully enabling CDN origin for  few subsites, I am facing below issue:
Add-SPOTenantCdnOrigin : Value cannot be longger than 5000.
At line:1 char:1

Add-SPOTenantCdnOrigin -CdnType Private -OriginUrl "OriginURL"

  + CategoryInfo          : NotSpecified: (:) [Add-SPOTenantCdnOrigin], ServerException
  + FullyQualifiedErrorId : Microsoft.SharePoint.Client.ServerException,Microsoft.Online.SharePoint.PowerShell.AddTenantCdnOrigin

I could not find this type of error anywhere.

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

ID: d9a4ae73-5f75-79bb-8bde-0ff57a5a7519
Version Independent ID: 2cb872ee-33af-a8d4-09ab-cdaebd17ddd2
Content: Add-SPOTenantCdnOrigin (sharepoint-online)
Content Source: sharepoint/sharepoint-ps/sharepoint-online/Add-SPOTenantCdnOrigin.md
Service: sharepoint-powershell
GitHub Login: @techwriter40
Microsoft Alias: kirks

Please find the below screen shot for reference

Please find the attached file in preview for the issue reference

@pratyusha-kodumuri Thank you for this feedback
I want to make sure this error is addressed properly. Support can handle this to resolution.
I think the best way forward is if you can open a service ticket in your tenant so this can get resolved ASAP. Based on outcome let me know if it is something that can be called out in the docs.
Here is a quick video on opening a ticket: https://www.youtube.com/watch?v=puuOy0sEg1Y
If you don't mind please keep us posted here on the resolution and I really want to get this information you are discovering back into the docs.

Apologies for commenting on an old ticket, but this is the only result on Google when searching with the error message "Add-SPOTenantCdnOrigin : Value cannot be longger than 5000." (probably because of the typo in the error message itself).
@pratyusha-kodumuri, how were you able to resolve this issue?

@trent-green

@pratyusha-kodumuri Thank you for reporting this feedback here. This list is focused on content issues and I want to make sure your immediate product issue does not get lost in this list. If you would please open a service ticket the support engineers will be able to identify if there is a bug (highly likely) and escalate to the appropriate product team.


questions on voxels and cropping spatial data

Hi,
thank you for this very cool method! very interesting paper, am finally getting around and trying out the method on Visium data.
have a couple of questions with respect to data cropping and spatial data shape

spatial data matrix with shape voxels-by-genes. Voxel can contain multiple cells.

what exactly is a voxel in the case of Visium?
the way I understand is that the maximum voxel is a spot, and so the spatial matrix would be of shape (spots, genes). The minimum therefore would be a pixel? If that's the case, then the mapping (if perfectly converged) would be identical for all the pixels under each spot?
Does the prior on cell density have shape (voxels,) ?
If the above is true, then if I have cell segmentation info for each spot, would it makes sense to generate voxels with shape voxel_shape < spot_shape, so to have something like: voxel_1,voxel_2 = spot_n[0:x,:], spot_n[x:,:], which would make voxel_1, voxel_2 identical in gene expression space, but with different cell density priors (e.g. 3 cells under voxel_1 and 5 cells under voxel_2) ?

I run out of memory when I map: what should I do?
Reduce your spatial data in various parts and map each single part. If that is not sufficient, you will need to downsample your single cell data as well.

this would essentially only happen with non-visium data, where there is pixel-level gene expression value ? (or yes if using an atlas as reference)
Thank you !

Real thanks you for your interest giovp.
A Visium voxel is a circle with 50 um diameter which (typically) contains more than a cell. If you look at the Tangram paper, Fig 4a, grey circles defines voxel. In the voxel-by-gene data, the x and y coordinates found in the obs dataframe in the AnnData refer to the voxel centers (a.. "spot", if you want). Yet, the corresponding counts in the matrix X are obtained from all molecules within the voxel (hence, within a circle centered on the "spot" but with diameter 50 um).
You do not need any prior on cell density in order to map your data, BUT, if you wish to deconvolve (ie to obtain prediction for each single cell within a voxel) then you do.
Yes the prior on the cell density (or cell counts, you can provide either) has the shape (voxels,).
You can run out of memory with Visium data as well. If you have a lot of single cells, or you are mapping over a large portion of tissue, then you run out of RAM. If that so, we suggest to partition the dataset.
I am closing this issue, but if you think something is not clear please re-open and ask again.
Ciao,


Added fallback message to Rollbar API rejection verbose log

Description of the change

fix if message is not set

Type of change

[x] Bug fix (non-breaking change that fixes an issue)
[ ] New feature (non-breaking change that adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
[ ] Maintenance
[ ] New release

Checklists
Development

[ ] Lint rules pass locally
[ ] The code changed/added as part of this pull request has been covered with tests
[ ] All tests related to the changed code pass in development

Code review

[ ] This pull request has a descriptive title and information useful to a reviewer. There may be a screenshot or screencast attached
[ ] "Ready for review" label attached to the PR and reviewers assigned
[ ] Issue from task tracker has a link to this pull request
[ ] Changes have been reviewed by at least one other engineer

updated to isset()

Hi @danielmorell,
Can you please do a release for v1.8.2. We're currently using<EMAIL_ADDRESS>and requires rollbar/rollbar@^1

@cresjie v1.8.2 has been released.


TypeError: Cannot assign to read only property 'className' of object '#'

When building for production, I get the following error whenever a v-tooltip directive is used on a svg element (e.g. vue-font-awesome):
TypeError: Cannot assign to read only property 'className' of object '#<SVGSVGElement>'
   at p (v-tooltip.esm.js:146)

Recently this line was introduced, which apparently does not resolve to true on SVGSVGElement.
https://github.com/Akryum/v-tooltip/blob/4a02b0fe16007a920e7c7837314885779100aa5a/src/utils.js#L33
From my understanding this is because SVGSVGElement does not have a prototype property.
var svg = document.createElementNS('http://www.w3.org/2000/svg','svg');
svg.prototype
>> undefined

(Tested in Chrome 73)

Hi,
This is happening for me too with SVGGElement (corresponds to the <g> element)
directive tooltip bind hook TypeError: Cannot assign to read only property 'className' of object '#<SVGGElement>'

Hello,
I'm also getting the same error message
Uncaught TypeError: Cannot assign to read only property 'className' of object '#<SVGSVGElement>' at removeClasses (v-tooltip.esm.js?e37d:146)     at Tooltip._hide (v-tooltip.esm.js?e37d:638)     at eval (v-tooltip.esm.js?e37d:835)

Hi, also getting same error:
Cannot assign to read only property 'className' of object '#<SVGSVGElement>'     at addClasses (v-tooltip.esm.js?54de:114)     at createTooltip (v-tooltip.esm.js?54de:1019)     at bind (v-tooltip.esm.js?54de:1055)     at callHook$1 (vue.esm.js?efeb:6685)     at _update (vue.esm.js?efeb:6606)     at Array.updateDirectives (vue.esm.js?efeb:6587)     at invokeCreateHooks (vue.esm.js?efeb:6074)     at initComponent (vue.esm.js?efeb:6007)     at createComponent (vue.esm.js?efeb:5990)     at createElm (vue.esm.js?efeb:5930)

When can we expect the fix for this bug? Or perhaps does anyone know some workaround?

Not sure if this is any help, but I'm only getting this error since I'm using yarn instead of npm to install my packages.

When can we expect the fix for this bug? Or perhaps does anyone know some workaround?

This workaround worked for me
yarn remove v-tooltip
yarn upgrade<EMAIL_ADDRESS>


Guide for Godot 4 using GDExtension?

Is there going to be a guide to use Kompute in Godot 4 using GDExtension? Quite a few things have changed in Godot 4 and it is difficult to translate the guide on GDNative to the newer API.

Thank you for opening the issue @JaryJay - this is something we're keen to explore, and have been waiting for the Godot 4 to stabilise. We would be keen if any contributors would be interested to explore this and provide a contribution - if you'd be open to this we would be able to support as well


Fixing issue #321

Fixing selection issue in output area. If text is selected, focus won't jump to the offending line in the editor. If nothing is selected, focus will jump as usual.

This fixes #321


Constant HTTP 500 Server errors

Hey guys, I’ve been trying to implement the OpenAI PHP client into my PHP web server and I really don’t know what i’m doing wrong.
API KEY created in environment variable
Depedencies are all installed on the server hosting the site.
When I go to the site, it still pronmpts HTTP500 error
CODE BELOW:
chat()->create([ 'model' => 'gpt-4', 'messages' => [ ['role' => 'user', 'content' => 'Hello!'], ], ]); echo $result->choices[0]->message->content; // Hello! How can I assist you today?

I'm using php 8.1.2 cli ubuntu if that matters.

Check the apache error log file, it will show you what is going wrong.

Hi @wolfhuntme
This does not look like an error related to the package.
If you do not agree, feel free to reopen the issue.


Profile bianavic

Pre-Submission Checklist

You have only one commit (if not, squash them into one commit).
All new and existing tests pass the command yarn test and yarn lint.

Description

add "voti", a paulistes dialects

Hi @bianavic, first thanks for contributing.
Could you resolve the conflicts?

Hi @bianavic thanks for merge, but your JSON to be invalid.


Intermittent TypeError related to lru_cache?

Hello!  I'm intermittently getting a 500 from the backend when calling a component method.  Here's an example payload:
{"id":"Ck9kDpm5:table-row:159","data":{"row":{"table":37,"title":"Memory financial give.","order":720,"pk":159}},"checksum":"5YxwpjTk","actionQueue":[{"type":"callMethod","payload":{"name":"print_saving(122)"},"partials":[]}],"epoch":1629327423683,"hash":"3ffoSeN3"}
And a sample traceback:
Field 'id' expected a number but got <TableCell: Certain usually speak pressure gun image manager. Whose prevent state indicate society beautiful decide. Clearly financial shake seem director.>.

Request Method: POST
Request URL: http://localhost:8000/unicorn/message/table-row
Django Version: 3.2.6
Python Version: 3.8.2
Server time: Wed, 18 Aug 2021 22:57:04 +0000
Installed Applications:
['django.contrib.admin',
 'django.contrib.auth',
 'django.contrib.contenttypes',
 'django.contrib.sessions',
 'django.contrib.messages',
 'django.contrib.staticfiles',
 'tables',
 'django_unicorn',
 'django_seed']
Installed Middleware:
['django.middleware.security.SecurityMiddleware',
 'django.contrib.sessions.middleware.SessionMiddleware',
 'django.middleware.common.CommonMiddleware',
 'django.middleware.csrf.CsrfViewMiddleware',
 'django.contrib.auth.middleware.AuthenticationMiddleware',
 'django.contrib.messages.middleware.MessageMiddleware',
 'django.middleware.clickjacking.XFrameOptionsMiddleware']

Traceback (most recent call last):
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django/db/models/fields/__init__.py", line 1823, in get_prep_value
    return int(value)

The above exception (int() argument must be a string, a bytes-like object or a number, not 'TableCell') was the direct cause of the following exception:
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django/core/handlers/exception.py", line 47, in inner
    response = get_response(request)
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django/core/handlers/base.py", line 181, in _get_response
    response = wrapped_callback(request, *callback_args, **callback_kwargs)
  File "<decorator-gen-26>", line 2, in message
    <source code not available>
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django_unicorn/decorators.py", line 66, in timed
    result = func(*args, **kwargs)
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django_unicorn/views/__init__.py", line 42, in wrapped_view
    return view_func(*args, **kwargs)
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django/utils/decorators.py", line 130, in _wrapped_view
    response = view_func(request, *args, **kwargs)
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django/views/decorators/http.py", line 40, in inner
    return func(request, *args, **kwargs)
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django_unicorn/views/__init__.py", line 460, in message
    json_result = _handle_component_request(request, component_request)
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django_unicorn/views/__init__.py", line 310, in _handle_component_request
    return _process_component_request(request, component_request)
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django_unicorn/views/__init__.py", line 118, in _process_component_request
    ) = call_method.handle(component_request, component, action.payload)
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django_unicorn/views/action_parsers/call_method.py", line 86, in handle
    return_data.value = _call_method_name(component, method_name, args, kwargs)
  File "<decorator-gen-24>", line 2, in _call_method_name
    <source code not available>
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django_unicorn/decorators.py", line 66, in timed
    result = func(*args, **kwargs)
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django_unicorn/views/action_parsers/call_method.py", line 132, in _call_method_name
    model = DbModel.objects.get(**{key: value})
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django/db/models/manager.py", line 85, in manager_method
    return getattr(self.get_queryset(), name)(*args, **kwargs)
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django/db/models/query.py", line 424, in get
    clone = self._chain() if self.query.combinator else self.filter(*args, **kwargs)
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django/db/models/query.py", line 941, in filter
    return self._filter_or_exclude(False, args, kwargs)
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django/db/models/query.py", line 961, in _filter_or_exclude
    clone._filter_or_exclude_inplace(negate, args, kwargs)
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django/db/models/query.py", line 968, in _filter_or_exclude_inplace
    self._query.add_q(Q(*args, **kwargs))
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django/db/models/sql/query.py", line 1393, in add_q
    clause, _ = self._add_q(q_object, self.used_aliases)
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django/db/models/sql/query.py", line 1412, in _add_q
    child_clause, needed_inner = self.build_filter(
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django/db/models/sql/query.py", line 1347, in build_filter
    condition = self.build_lookup(lookups, col, value)
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django/db/models/sql/query.py", line 1193, in build_lookup
    lookup = lookup_class(lhs, rhs)
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django/db/models/lookups.py", line 25, in __init__
    self.rhs = self.get_prep_lookup()
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django/db/models/lookups.py", line 77, in get_prep_lookup
    return self.lhs.output_field.get_prep_value(self.rhs)
  File "/Users/triopter/.local/share/virtualenvs/poc_uni-QNOZ3vZ_/lib/python3.8/site-packages/django/db/models/fields/__init__.py", line 1825, in get_prep_value
    raise e.__class__(

Exception Type: TypeError at /unicorn/message/table-row
Exception Value: Field 'id' expected a number but got <TableCell: Certain usually speak pressure gun image manager. Whose prevent state indicate society beautiful decide. Clearly financial shake seem director.>.```

Debugging, I determined that the only cases in which the error was occurring were the ones in which the body of `django_unicorn.call_method_parser.parse_call_method_name` was not entered.  Commenting out the `lru_cache` decorator has resolved the problem, and it now succeeds consistently.  I suspect this has something to do with hydration changing a cached value somewhere.

Hmm, interesting. I don't think I've ever seen this happen while I've been testing. Any chance you could fork this repo and reproduce this in the example project? That way I could see more easily what is going on, thanks!

If I specify typed=True (as referenced in https://docs.python.org/3/library/functools.html#functools.lru_cache) it would prevent the exception (although, not sure if there is a separate issue that is happening). I'm going to try that and you can let me know if it clears up.

Done in 6d72278. Closing, but feel free to open this again if you see it continue to happen in 0.34.0.


Task 'javadoc' not found in root project 'appname'.

New Version
0.71.1
Old Version
0.63.4
Build Target(s)
android
Output of react-native info
FAILURE: Build failed with an exception.

What went wrong:
Task 'javadoc' not found in root project 'appname'.

Issue and Reproduction Steps
on cleaning the caches in order to get rid of
React Native version mismatch. JavaScript version: 0.63.4 Native version: 0.71.1 this error

Task 'javadoc' not found in root project 'appname'.

Please also share your android/app/build.gradle and android/build.gradle

android\build.gradle
// Top-level build file where you can add configuration options common to all sub-projects/modules.
buildscript {
ext {
buildToolsVersion = "33.0.0"
minSdkVersion = 23
compileSdkVersion = 33
targetSdkVersion = 33
androidXCore = "1.7.0"
kotlin_version = '1.6.10'
      // We use NDK 23 which has both M1 support and is the side-by-side NDK version from AGP.
    ndkVersion = "23.1.7779620"

}
repositories {
    google()
    mavenCentral()
    //mavenCentral()
}
dependencies {

    classpath('com.android.tools.build:gradle:7.3.1')
    classpath("com.facebook.react:react-native-gradle-plugin")

}

}
// will checkout later on
subprojects { subproject ->
if(project['name'] == 'react-native-reanimated'){
project.configurations { compile { } }
}
}
android\app\build.gradle
apply plugin: "com.android.application"
apply plugin: "com.facebook.react"
import com.android.build.OutputFile
/**

This is the configuration block to customize your React Native Android app.
By default you don't need to apply any configuration, just uncomment the lines you need.

*/
// project.ext.react = [
//     entryFile: "index.js",
//     enableHermes: true, //false
//     // deleteDebugFilesForVariant: { false }
//       deleteDebugFilesForVariant: {
//         def variant -> variant.name.toLowerCase().contains("release") || variant.name.toLowerCase().contains("canary") ||
//         variant.name.toLowerCase().contains("beta")
//     }
//     //bundleCommand: "ram-bundle",
//     // bundleInDebug: true,
//  ]
// apply from: '../../node_modules/react-native-unimodules/gradle.groovy'
// apply from: "../../node_modules/react-native/react.gradle"
//apply from: "../../node_modules/expo-updates/scripts/create-manifest-android.gradle" //*&
react {
/* Folders /
//   The root of your project, i.e. where "package.json" lives. Default is '..'
// root = file("../")
//   The folder where the react-native NPM package is. Default is ../node_modules/react-native
// reactNativeDir = file("../node_modules/react-native")
//   The folder where the react-native Codegen package is. Default is ../node_modules/react-native-codegen
// codegenDir = file("../node_modules/react-native-codegen")
//   The cli.js file which is the React Native CLI entrypoint. Default is ../node_modules/react-native/cli.js
// cliFile = file("../node_modules/react-native/cli.js")
/ Variants /
//   The list of variants to that are debuggable. For those we're going to
//   skip the bundling of the JS bundle and the assets. By default is just 'debug'.
//   If you add flavors like lite, prod, etc. you'll have to list your debuggableVariants.
// debuggableVariants = ["liteDebug", "prodDebug"]
/ Bundling /
//   A list containing the node command and its flags. Default is just 'node'.
// nodeExecutableAndArgs = ["node"]
//
//   The command to run when bundling. By default is 'bundle'
// bundleCommand = "ram-bundle"
//
//   The path to the CLI configuration file. Default is empty.
// bundleConfig = file(../rn-cli.config.js)
//
//   The name of the generated asset file containing your JS bundle
// bundleAssetName = "MyApplication.android.bundle"
//
//   The entry file for bundle generation. Default is 'index.android.js' or 'index.js'
// entryFile = file("../js/MyApplication.android.js")
//
//   A list of extra flags to pass to the 'bundle' commands.
//   See https://github.com/react-native-community/cli/blob/main/docs/commands.md#bundle
// extraPackagerArgs = []
/ Hermes Commands */
//   The hermes compiler command to run. By default it is 'hermesc'
// hermesCommand = "$rootDir/my-custom-hermesc/bin/hermesc"
//
//   The list of flags to pass to the Hermes compiler. By default is "-O", "-output-source-map"
// hermesFlags = ["-O", "-output-source-map"]
}
/**

Set this to true to create two separate APKs instead of one:
Set this to true to create four separate APKs instead of one,
one for each native architecture. This is useful if you don't
use App Bundles (https://developer.android.com/guide/app-bundle/)
and want to have separate APKs to upload to the Play Store.
*/
def enableSeparateBuildPerCPUArchitecture = false

/**

Set this to true to Run Proguard on Release builds to minify the Java bytecode.
*/
def enableProguardInReleaseBuilds = true

/**

The preferred build flavor of JavaScriptCore (JSC)

For example, to use the international variant, you can use:
def jscFlavor = 'org.webkit:android-jsc-intl:+'

The international variant includes ICU i18n library and necessary data
allowing to use e.g. Date.toLocaleString and String.localeCompare that
give correct results when using with locales other than en-US.  Note that
this variant is about 6MiB larger per architecture than default.
*/
def jscFlavor = 'org.webkit:android-jsc:+'

/**

Private function to get the list of Native Architectures you want to build.
This reads the value from reactNativeArchitectures in your gradle.properties
file and works together with the --active-arch-only flag of react-native run-android
*/
// def enableHermes = project.ext.react.get("enableHermes", false)//false

/**

Architectures to build native code for.
*/
def reactNativeArchitectures() {
def value = project.getProperties().get("reactNativeArchitectures")
return value ? value.split(",") : ["armeabi-v7a", "x86", "x86_64", "arm64-v8a"]
}

android {
compileSdkVersion rootProject.ext.compileSdkVersion
namespace "com.pushthivardhan.foods.consumer"
defaultConfig {
    applicationId "com.pushthivardhan.foods.consumer"
    minSdkVersion rootProject.ext.minSdkVersion
    // compileSdkVersion rootProject.ext.compileSdkVersion
    targetSdkVersion rootProject.ext.targetSdkVersion
    versionCode 235
    versionName "2.3.5"
    missingDimensionStrategy 'react-native-camera', 'general'
    multiDexEnabled true
    vectorDrawables.useSupportLibrary = true
    ndk {
        abiFilters 'armeabi-v7a','arm64-v8a','x86','x86_64'
    }

}

splits {
    abi {
        reset()
        enable enableSeparateBuildPerCPUArchitecture
        universalApk false  // If true, also generate a universal APK
        // include "armeabi-v7a", "x86", "arm64-v8a", "x86_64"
        include (*reactNativeArchitectures())
    }
}
signingConfigs {
    debug {
        storeFile file('debug.keystore')
        storePassword 'android'
        keyAlias 'androiddebugkey'
        keyPassword 'android'
    }
    release {
        storeFile file('release.keystore')
        storePassword 'pushthivardhan'
        keyAlias 'pushthivardhan'
        keyPassword 'pushthivardhan'
    }
    staging {
        storeFile file('release.keystore')
        storePassword 'passme'
        keyAlias 'dummy'
        keyPassword 'toolDummy'
    }
}
buildTypes {
    debug {
        signingConfig signingConfigs.debug
    }
    release {
        // Caution! In production, you need to generate your own keystore file.
        // see https://reactnative.dev/docs/signed-apk-android.
        signingConfig signingConfigs.release
        minifyEnabled enableProguardInReleaseBuilds
        proguardFiles getDefaultProguardFile("proguard-android.txt"), "proguard-rules.pro"
    }
}

// applicationVariants are e.g. debug, release
applicationVariants.all { variant ->
    variant.outputs.each { output ->
        // For each separate APK per architecture, set a unique version code as described here:
        // https://developer.android.com/studio/build/configure-apk-splits.html
        def versionCodes = ["armeabi-v7a": 1, "x86": 2, "arm64-v8a": 3, "x86_64": 4]
        def abi = output.getFilter(OutputFile.ABI)
        if (abi != null) {  // null for the universal-debug, universal-release variants
            output.versionCodeOverride =
            defaultConfig.versionCode * 1000 + versionCodes.get(abi)

        }

    }
}

}
dependencies {
// Execution failed for task ':react-native-keychain:processDebugUnitTestManifest'.
// implementation "androidx.test:core:1.4.0"
// The version of react-native is set by the React Native Gradle Plugin
implementation("com.facebook.react:react-android")
implementation("androidx.swiperefreshlayout:swiperefreshlayout:1.1.0")

debugImplementation("com.facebook.flipper:flipper:${FLIPPER_VERSION}")
debugImplementation("com.facebook.flipper:flipper-network-plugin:${FLIPPER_VERSION}") {
    exclude group:'com.squareup.okhttp3', module:'okhttp'
}

debugImplementation("com.facebook.flipper:flipper-fresco-plugin:${FLIPPER_VERSION}")
if (hermesEnabled.toBoolean()) {
    implementation("com.facebook.react:hermes-android")
} else {
    implementation jscFlavor
}

}
// Run this once to be able to run the application with BUCK
// puts all compile dependencies into folder libs for BUCK to use
task copyDownloadableDepsToLibs(type: Copy) {
from configurations.implementation
into 'libs'
}
apply from: file("../../node_modules/@react-native-community/cli-platform-android/native_modules.gradle"); applyNativeModulesAppBuildGradle(project)
// Execution failed for task ':react-native-keychain:processDebugUnitTestManifest'.
// project(':react-native-keychain').tasks.withType(Test) {
//     enabled = false
// }

Task 'javadoc' not found in root project 'appname'.

Please also share your android/app/build.gradle and android/build.gradle

Your file looks fine. I'm unsure what's causing the "Task 'javadoc' not found in root project 'appname'." Error. Are you able to provide a reproducer?

just like to closed as it's already been resloved long days back.🏁

closed


How can I use Team Drives

I can start checking how this works and document in README.md if you want @nao-pon

I found how to use team drive with your library, is it ok if I add that to your README.md and create a pull request?

@Sealtyel Sorry for not being able to reply immediately. Of course, PR is welcome.
Thank you!


UWP implementation for SqliteStorage.

@dryganets and I work on the same team. Here are some notes I have about the UWP implementation:
The UWP implementation is very similar to the iOS implementation. There are some differences. Most of them are because we didn't have time to port certain features and we haven't needed them. Here's the list of differences:

Reading and writing blobs isn't supported.
We didn't port the sqlcipher stuff.
We didn't port the custom regex SQL function so REGEXP may not be supported.
attach isn't supported.
Some open options aren't supported:

dblocation. We weren't sure how to map it to UWP. Also, the Android implementations don't seem to support this.
key (related to sqlcipher)

Differences with delete:

The dblocation option isn't supported
Closes the DB if it's open. This felt like the right thing to do.

All of the code in the SQLite.Net-PCL directory is from https://github.com/oysteinkrog/SQLite.Net-PCL. It provides a thin wrapper around the C SQLite APIs which enables them to be called from C#. A couple of tweaks were made to the code to fix these bugs:

https://github.com/oysteinkrog/SQLite.Net-PCL/issues/374
https://github.com/oysteinkrog/SQLite.Net-PCL/issues/375

This implementation requires at least the Windows 10 Anniversary Update. This is because it relies on the version of SQLite that is built into Windows 10 and this was introduced in the Anniversary Update. You can learn more at https://blogs.windows.com/buildingapps/2017/02/06/using-sqlite-databases-uwp-apps/.
With a little work, this module could be updated to support earlier versions of Windows 10. Here's how:

When constructing SQLiteApiWinRT, pass false for the useWinSqlite parameter.
Install the "SQLite for Universal Windows Platform" extension which will bring a version of SQLite into your app: https://marketplace.visualstudio.com/items?itemName=SQLiteDevelopmentTeam.SQLiteforUniversalWindowsPlatform

Adam Comella
Microsoft Corp.

@dryganets @rigdern Those are some good insights, though I think @andpor meant the instructions about How to use (Windows) equally to the How to use (iOS) and How to use (Android) section.
So if we have a fresh inited RN project with RN-windows added, what steps have to be taken to be able to use it?
Probably

Right Click on Solution in VS2017 --> Add --> Existing Project
Navigate to ../node_modules/libraryName/windows and select the .csproj
Right click on your React Native Windows app under your solutions directory and click Add > Reference....
Check the libraryName you just added and press Ok
Open MainReactNativeHost.cs, import/using libraryName and add the Package to the list of Packages


最后执行readme中的python代码,报错日志如下,请问是什么原因?

错误日志
/root/anaconda3/envs/cosyvoice/lib/python3.8/site-packages/torch/_jit_internal.py:726: FutureWarning: ignore(True) has been deprecated. TorchScript will now drop the function call on compilation. Use torch.jit.unused now. {}
  warnings.warn(
/root/anaconda3/envs/cosyvoice/lib/python3.8/site-packages/diffusers/models/lora.py:393: FutureWarning: `LoRACompatibleLinear` is deprecated and will be removed in version 1.0.0. Use of `LoRACompatibleLinear` is deprecated. Please switch to PEFT backend by installing PEFT: `pip install peft`.
  deprecate("LoRACompatibleLinear", "1.0.0", deprecation_message)
2024-08-01 21:48:02.137567384 [W:onnxruntime:, session_state.cc:1162 VerifyEachNodeIsAssignedToAnEp] Some nodes were not assigned to the preferred execution providers which may or may not have an negative impact on performance. e.g. ORT explicitly assigns shape related ops to CPU to improve perf.
2024-08-01 21:48:02.137604955 [W:onnxruntime:, session_state.cc:1164 VerifyEachNodeIsAssignedToAnEp] Rerunning with verbose output on a non-minimal build will show node assignments.
Illegal instruction (core dumped)

sorry, never meet this error

有解决吗? 我基于 Oracle VirtualBox 中安装的Ubuntu 在最后执行时也遇到了这个.

试试 pip uninstall ttsfrd
我用 gdb调试, 发现报错信息是在 ttsfrd中.
你可以试下
apt install gdb
gdb --args python3 webui.py --port 50000 --model_dir pretrained_models/CosyVoice-300M
(gdb) run
(gdb) backtrace
看看是不是和我的错误信息一样
Thread 1 "python3" received signal SIGILL, Illegal instruction.
0x00007fff2d5d8e71 in ?? () from /root/miniconda3/envs/cosyvoice/lib/python3.8/site-packages/ttsfrd.cpython-38-x86_64-linux-gnu.so
(gdb) backtrace
#0  0x00007fff2d5d8e71 in ?? () from /root/miniconda3/envs/cosyvoice/lib/python3.8/site-packages/ttsfrd.cpython-38-x86_64-linux-gnu.so
#1  0x00007fff2d66b126 in ?? () from /root/miniconda3/envs/cosyvoice/lib/python3.8/site-packages/ttsfrd.cpython-38-x86_64-linux-gnu.so


Temperature needs to be rounded

I have identified an issue. Let's start with the WiFi Module I use:
[10/9/2018, 12:40:32 PM] [Daikin Office] response success [10/9/2018, 12:40:32 PM] [Daikin Office] Your Model is: 0AB9 [10/9/2018, 12:40:32 PM] [Daikin Office] response success [10/9/2018, 12:40:32 PM] [Daikin Office] Set firmware version to 1.2.48
I experienced a problem that most commands were ignored. I finally found out that these commands where temp was either a full or a half degree worked.
Examples working: 22.0, 22.5, 23.0, 23.5
Examples not working: 22.1, 22.2, 22.3
So it seems we need some rounding.
If the URL looks like this: "http://<IP_ADDRESS>/aircon/set_control_info?pow=1&mode=3&stemp=22.1&shum=0" the HTTP response is: ret=PARAM NG

fixed in this fork: https://github.com/cbrandlehner/homebridge-daikin-local


Define all Product Classes

Currently, we describe product classes as building upon standards in 1.3.3, but (for some terms) we do not explicitly define what they are or explain their purpose anywhere in the document.
Since, we link to 1.3.3 when these product classes occur in the document, it would be helpful if we defined them as well! Even if they seem self-explanatory, imho we should make them explicit.

I'm unclear about your inquiry. Is it that some products classes are underdefined or needs better definitions, or is it to define new products?
It is true that each concept in the concept scheme (#classes-of-products) doesn't link out to the rest of the document, but the concept scheme does provide some orientation FWIW:

These products are referenced throughout this specification.

Subscription Client, Subscription Server and Resource Server can do with one line definitions of what they are and/or what they do (not just what they build on) as these products are repeatedly referenced to throughout the document.


Newsletters: add 92 (2020-04-08)

[ ] LND #4087 @moneyball
[ ] LND #4079 @dongcarl
[ ] Bitcoin Core PR review club writeup @jnewbery (optional; we didn't publicly commit to doing this monthly)

LND #4079 adds support for funding channels with PSBTs, and by extension, any PSBT-compatible wallet. Previously, channel funding was only possible with lnd's internal wallet. Users can supply the --psbt flag to lncli openchannel to start an interactive dialog for completing the funding flow, more instructions here.

Proposed review club writeup here: https://github.com/jonatack/bitcoinops.github.io/commit/dfb1d0dd23e204a948332cfd0e522cba49849a32

Pushed addition of a news item of the LN HackSprint work on ECDSA adaptor signatures implemented using 2-of-2 multisig and DLEQ.  I think this is ok, but if we want to go into significantly more detail about their construction, I'll need to bump this topic to next week.  (Topic suggested by @jnewbery; thanks!).
I'll begin working on integrating Carl and Jon's writeups momentarily.

Thanks for the markup fixes and edits, @harding!

Pushed a release note for Eclair, an updated lede to account for updated news and additional sections, and made most of the suggested edits (thanks @jnewbery and @jonatack!).  Hopefully that wraps it up for major edits; I'll check again around 20:00 UTC and make any final requested edits.  Thanks everyone!

Pushed some minor edits to the PR Review Club section. Everything else looks great to me. Thanks all!

ACK 7cb821b73482b6029425d7efc0f2b87b2289dde1

Big array of contributors this week! @harding @moneyball @dongcarl @jonatack all authoring sections this week, awesome guys.
Thanks for @jonatack and @jnewbery for the reviews.
Squashed and off to the presses!


Change the ready checks for ats to use the actual ats port

Currently the autest for syntax checks if the miniserver port is ready when marking ATS as ready. This should be the ATS port.  Also adding a readiness check for the miniserver on it's port.

Cherry-picked to v9.0.x branch.

Marking this for 9.0.0, you will need to make a new PR for 8.0.6 I think (a "git cherry-pick -x" of this).

https://github.com/apache/trafficserver/pull/6047


After installation facing problem in accessing the site

We followed all the steps and installed the Peatio but when we are trying to access the exchange front end is not loading properly :(
http://<IP_ADDRESS>:3000/

Also not able to accesses admin panel always going to :+1:
http://<IP_ADDRESS>:3000/settings

You need to add two factor authentication before you can access admin panel.

@hrishikeshio hey , can you tell me how to "add two factor authentication before you can access admin panel."?thank you!

Hi Wang,
Thanks for using Yunbi Exchange.
You can download Google Authenticator on your phone.
Then follow the steps offered on that authentication page.
Let me know if you have any other questions.
Thanks.
2016-04-12 15:20 GMT+08:00 wangyijunjunjun<EMAIL_ADDRESS>
@hrishikeshio https://github.com/hrishikeshio hey , can you tell me how
to "add two factor authentication before you can access admin panel."?thank
you!
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thanks for your helpbut I’m following https://github.com/peatio/peatio/blob/master/doc/setup-local-osx.md to install Peatio on my Macbook. When I made it and log in with 'user<EMAIL_ADDRESS>pass: Pass@word8' ,I found that I cannot get into the admin panel which means 'http://<IP_ADDRESS>:3000/settings' is no responseI’m looking forwards to receiving your reply !                             Original Message                             Sender<EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS>Tuesday, Apr 12, 2016 15:53Subject: Re: [peatio/peatio] After installation facing problem in accessingthe site (#454)Hi Wang,
Thanks for using Yunbi Exchange.
You can download Google Authenticator on your phone.
Then follow the steps offered on that authentication page.
Let me know if you have any other questions.
Thanks.
2016-04-12 15:20 GMT+08:00 wangyijunjunjun<EMAIL_ADDRESS>
@hrishikeshio https://github.com/hrishikeshio hey , can you tell me how
to "add two factor authentication before you can access admin panel."?thank
you!
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—You are receiving this because you commented.Reply to this email directly or view it on GitHub

send us 1 bitcoin we will configure it for you

On Apr 12, 2016, at 11:00 AM, wangyijunjunjun<EMAIL_ADDRESS>wrote:
thanks for your helpbut I’m following https://github.com/peatio/peatio/blob/master/doc/setup-local-osx.md to install Peatio on my Macbook. When I made it and log in with 'user<EMAIL_ADDRESS>pass: Pass@word8' ,I found that I cannot get into the admin panel which means 'http://<IP_ADDRESS>:3000/settings' is no responseI’m looking forwards to receiving your reply !  Original Message  Sender<EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS>Tuesday, Apr 12, 2016 15:53Subject: Re: [peatio/peatio] After installation facing problem in accessingthe site (#454)Hi Wang,
Thanks for using Yunbi Exchange.
You can download Google Authenticator on your phone.
Then follow the steps offered on that authentication page.
Let me know if you have any other questions.
Thanks.
2016-04-12 15:20 GMT+08:00 wangyijunjunjun<EMAIL_ADDRESS>
@hrishikeshio https://github.com/hrishikeshio hey , can you tell me how
to "add two factor authentication before you can access admin panel."?thank
you!
—
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I will check with our engineers.
2016-04-12 16:00 GMT+08:00 wangyijunjunjun<EMAIL_ADDRESS>
thanks for your helpbut I’m following
https://github.com/peatio/peatio/blob/master/doc/setup-local-osx.md to
install Peatio on my Macbook. When I made it and log in with 'user:
<EMAIL_ADDRESS>pass: Pass@word8' ,I found that I cannot get into the
admin panel which means 'http://<IP_ADDRESS>:3000/settings' is no responseI’m
looking forwards to receiving your reply !  Original Message
Sender<EMAIL_ADDRESS>peatio/peatio<
<EMAIL_ADDRESS><EMAIL_ADDRESS>Tuesday,
Apr 12, 2016 15:53Subject: Re: [peatio/peatio] After installation facing
problem in accessingthe site (#454)Hi Wang,
Thanks for using Yunbi Exchange.
You can download Google Authenticator on your phone.
Then follow the steps offered on that authentication page.
Let me know if you have any other questions.
Thanks.
2016-04-12 15:20 GMT+08:00 wangyijunjunjun<EMAIL_ADDRESS>
@hrishikeshio https://github.com/hrishikeshio hey , can you tell me
how
to "add two factor authentication before you can access admin
panel."?thank
you!
—
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Reply to this email directly or view it on GitHub
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--
Mike Li
International Project Manager of Peatio Team
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https://yunbi.com/
—You are receiving this because you commented.Reply to this email directly
or view it on GitHub
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You are receiving this because you commented.
Reply to this email directly or view it on GitHub
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International Project Manager of Peatio Team
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https://yunbi.com/


Link and multi links field types do not add " " around each link in frontmatter

Link and Multiple links options do not add " " around the link in frontmatter.
This means that when you create a dataview table of these values they do not actually appear as links in the table, but show instead as plain text.
It would also be really useful to be able to add a "new" link that doesn't currently exist as a note yet (but gives you the option to create it when you hover... like regular internal links).

I love your work! It's a step up to add structure to our Obsidian workflow!
Hope this issue is solved! (btw, why do you see it as enhancement? Currently, when you add wikilinks to frontmatter, they do not work as wikilinks. When you add quotes, it solves the issue! If you then use another plugin such as frontmatter links, it's perfect!)

released in 0.4.0


Prefix USE_SUDO with HELM_INSTALL

What this PR does / why we need it:
Because we probably want to set HELM_INSTALL_DIR and USE_SUDO in our.bashrc file, the variable name USE_SUDO is too wide. It's safier to use HELM_INSTALL_USE_SUDO.
Special notes for your reviewer:
Maybe we can leave USE_SUDO that reads HELM_INSTALL_USE_SUDO for backward compatibility
Signed-off-by: Patrice Ferlet<EMAIL_ADDRESS>

This breaks backwards compatibility for those currently using the script. For that reason we cannot accept this PR. Just unset USE_SUDO before invoking the script.

This breaks backwards compatibility for those currently using the script. For that reason we cannot accept this PR. Just unset USE_SUDO before invoking the script.

I can change this to have backward compatibility so


Bebop 2 improved control gains (and force failsafe)

I've done some tuning on the PID settings on Bebop 2. It flies much better now, see video https://youtu.be/SsnzYhiuWiE. Still a little bit of overshoot in yaw, but not excessive. Also the frame is not very rigid, so you literally see it twisting when yawing. More agressive yaw control is tricky with such a flexible frame.
I also disabled the rangefinder for now, because it has real-time problems. When it is enabled, the compass notifies me sometimes that a frame was skipped. The compass runs at 100Hz and is polled at 200Hz. It looks like something within the rangefinder driver occupies the driver framework thread for more than 10ms.
Another minor addition: shut down motors on armed.force_failsafe. I added this to be able to kill the motors on a geofence violation (terminate).

Looking good! Thanks for sharing the video.

Great video. FYI, I added that to the bebop page too: https://docs.px4.io/en/flight_controller/bebop.html


Touch Events do not fire after clicking on border of canvas

Hi,
When you click on the border of the canvas the events do not seem to fire anymore. This occurs in both the two examples that are in the easeljs demos (linked below). It causes you to no longer be able to draw anymore on the canvas after this has happened.
Thanks
http://createjs.com/demos/easeljs/curveto
http://createjs.com/demos/easeljs/alphamaskreveal

I get the same, Chrome Android 53.0.2784.124
What's happening is that when you press on the border, for whatever reason instead of giving a touchstart event the browser is issuing a mousedown event.  Then when it's handling the event in Stage.js _handlePointerDown it's overwriting the _primaryPointerID with -1
From that point on the touch events will never be primary, and get rejected in the example's handleMouseMove


Avoided a syntax rule just to get a loc

This syntax rule has an influence on the parser caching logic of the interpreter
As discussed in usethesource/rascal#1650
Fixes #7

Strange, the test fail, but the same test (also run via maven) succeeds on my machine. It started failing after this commit: a0c06e638196bee17810d5dd2bbdb151fed26b5a.

@PaulKlint since I know you've been working on typepal. I'm gonna not try and fix those bugs untill I hear from you. The pascal one seems to be related to how with statement is implemented. That might have changed due to recent changes in typepal?
The java is about how the super call resolves the defined constructor, reading that code I'm a bit confused as how it has ever worked.

Originally I did need the tree, but currently only the loc. So indeed we can optimize this.


"unauthorized error cannot add subdomain ahmedthabet-wiki-w1 to zone tfgw-testnet-01.3x0.me",

when deploying a wiki I used w1 i'm sure i used it before somewhere, but wasn't in my workloads list. after continuing with the chatflow it failed node 6RZfnjuXVLFdtZh218hn4BLzsoKkTVpweqWECk5YUKud with workload id 478645
https://explorer.testnet.grid.tf/api/v1/reservations/workloads/478645
the error message was "unauthorized error cannot add subdomain ahmedthabet-wiki-w1 to zone tfgw-testnet-01.3x0.me",
I think we can do some more validation on the domain user or even adding extra character or something

Can't reproduce the issue.
I tried to with the following steps:

deploy wiki with the name 'w1' on all domains [ ava.tf, 3x0.me, gateway.tf ] and subdomain was created successfully.

delete the container workload and leave the subdomain workload alive.
deploy anther wiki with the same name w1 and subdomain was created with appending random number successfully.

remove all workloads and create another wiki with the same name w1 and created successfully.

I was able to reproduce it with the following steps:

Find a friend and gain his trust then take his identity information.
Add yourself as an admin to his identity and make it the default one. And restart the 3Bot server.
Login into the local marketplace package and create a peertube solution with the name "hamada".
Created? Accessible and listed on the solutions? Now delete it.
Change the identity back to yours then restart the server.
Create a peertube solution with the name "hamada", you should get this error.


Is epoch block required?

Sorry for create this issue but I'm a little concerned about epoch block and I'm wondering if this is really required and I'm not sure if discord is the best place to address this.
One of the main reason to have a epoch blocks is to have the ability to provide pruning however isn't already possible?
If the database keep the track of all required information (representative and balance) isn't the pruning possible?
I.E.: I have a send as the latest block. Before pruning I can keep in the database information about this transaction plus representative and current balance, similar to state block. Knowing this I could just delete every transaction before.
Add epoch block it seems more work in development side than the opposite from my perspective.
Am I mistaken?

Epoch blocks is to deprecate the old block types.

@clemahieu is it required? Won't the code stay forever there anyways to handle legacy blocks?
It's even possible to just make up-to-date nodes to reject legacy blocks not allowing them to be added to the ledge.

The problem is nodes get upgraded at different times. If some reject a block and some accept, which wins? Right now our election system has no ability to reject a transaction, it can only pick one answer within a fork. We like this property because there's no ability for a transaction to be rejected and we want to keep it that way.
So we're in a situation of

Wanting to allow graceful upgrades
Having a fully asynchronous system
Not wanting the ability to reject transactions

We came up with epoch blocks which is a way to solve this.
What problems do epoch blocks present to you?

Just to give some further clarification: All other cryptocurrencies out there have multiple keys per chain. In blockchain coins, all keys are in a single chain, in other DAGs, multiple keys are on a single chain. The concept of one signing key per chain is a performance optimization, it isn't a statement of ownership.
Private keys will always retain ownership of their balance and representative. Epoch blocks cannot modify either.

Thanks for the clarification @clemahieu. My comment about reject blocks it was just one idea but my main concern is the real gain (maintenance and maybe security) from the epoch blocks.
Probably I can't see something obvious that you guys can see. I'll give more thoughts to that while working in jnano-node.
Thank again

I gave more thoughts about it and I think I understood what you want to achieve.
But I'd like to hear your thoughts in a alternative idea: what if an new state block is introduced (i.e. 7) which also contain the version of the account. If an account want to receive a transfer from another account with higher version it should produce a state receive block with matching version or higher (if available).
Main advantages

Decentralized
Less complexity from code perspective (at least, from my perspective)
Gradual upgrade
Future-proof, if the number of the account explode

Disadvantage

Lost seed accounts will never be upgraded
An account will be never obligate to upgrade if they don't receive a block with a higher account

One of the requirements for epoch blocks be that they completely sunset the era of old-style blocks.  The old style blocks have complicated further developments because they do not completely specify the state of the account and thus if we can make plans where only they are used we are better able to implement features that bring the software and protocol forward.


Build or identify a suitable Docker image for Strelka.

https://github.com/genome/docker-strelka/issues/2

Done! https://hub.docker.com/r/mgibio/strelka-cwl/ has built.


Git pre-commit hook to format src.

Adds a pre-commit hook script to format go src.
Sample hook:
> cat .git/hooks/pre-commit
#!/usr/bin/env bash

set -e

# format all scala soruce
$OPENWHISK_HOME/tools/git/pre-commit-scalafmt-native.sh

# format all go source
ROOT_DIR="$(git rev-parse --show-toplevel)"
$ROOT_DIR/tools/git/pre-commit-gofmt.sh

# scan all other files for conformance
python $OPENWHISK_UTILS_HOME/scancode/scanCode.py --config $OPENWHISK_UTILS_HOME/scancode/ASF-Release.cfg "$ROOT_DIR"

@mrutkows perhaps we should add the scala formatting and pre-commit hooks to the utils repo so that there is a canonical place for these to be accessed from all the repos.
Related to https://github.com/apache/incubator-openwhisk-cli/pull/324.

@dubee @mdeuser if you're ok with the PR can you approve and merge?


feat: make where to install the completion files configurable

Description
As a developer that does not like my system to be touched without consent from me, by any software, I love that we can disable the auto install. But it would be even better if there is an API that allows me to specify where to install. I could then hook this up on my own CLI to give my users more fine-grained control.
Requirements

[ ] Being able to specify where to install the auto-completion files

We have two levels in which this can be customized:

The package provides an API in which CLI maintainers can customize the install location (which is pretty much what you are suggesting, I guess).
The package provides an API in which the CLI users can customize the install location. For that, we can introduce a command that echoes the completion script and people can do this:

my_cli completion >> ~/.zshrc

Looks like this issue can be closed, since (from the comment above):

approach (1) is already possible
approach (2) is tracked in issue #58


ngrok: parse error responses and surface the msg and code

Resolves ngrok-private/ngrok#21498
Adds an ErrResp proto struct and an NgrokError trait.
The ErrResp gets parsed from the stringly-typed error message that
comes from tunnel protocol RPC calls, and holds both the messge and code
fields. The NgrokError trait allows us to bubble these fields up
through the thiserror wrappings to make it easier to get the ngrok
code/message at the top-level, i.e. ConnectError and RpcError.

Nice, thanks for doing this parsing.
I started seeing that oauth error in similar tests for python, in addition to google-site-verification i also search for the generic accounts.google.com which seems currently dependable.


Split the hibernate shard in two

It's the long pole in CI and splitting it into two should reduce the wall-clock time to finishing the CI run.
This is admittedly very rough and can be refined later if we need to.

I don't have admin permissions on misk, but need somebody to update the branch protection checks. (Drop the requirement on testShardHibernate, merge the PR, then add requirements on testShardHibernate1 and testShardHibernate2)

@staktrace I've updated the branch protection rules accordingly and will merge this on green.