Refresh radio parameters delay

Hi there
Wouldn't it make sense to just add a delay with the delta to the last function call instead of 500ms each time?
https://github.com/u-blox/ubxlib/blob/7f70e9073ffdc7b23374a892682d7166af233f4b/cell/src/u_cell_info.c#L686C1-L686C41

Hi eeFLis: having discussed this with @philwareublox, suggestion is that we make the delay a conditionally-compiled value, implemented as a #ifndef/#define/#endif kinda thing and add a note to:
https://github.com/u-blox/ubxlib/blob/7f70e9073ffdc7b23374a892682d7166af233f4b/cell/api/u_cell_info.h#L69-L79
...pointing it out and suggesting that an application where power/timing is important (your case) might override it to 0 and manage any timing in the application instead.
Would that work?

Yes, that works for us.
Out of curiosity, do you see a problem if the function is called in a loop without the delay?
As the response from the module is awaited, the module should not be overtasked.

Good, change should be here in an hour or two.

Out of curiosity, do you see a problem if the function is called in a loop without the delay?

I added that delay because I found in the past that a module didn't like being hit with the radio refresh-related commands frequently.  However, I can't recall now which module that was and it may, of course, be something that has since been fixed, hence my [unhelpful] answer is "no, unless you see one" :-).

The test failures below are instance 14 doing its MGA/SER failure (Giovanni tells me that they have added filtering in their service back-end now and so the problem should hopefully go away for us sometime this week), the Windows instance (23) failing to get back all of the data it sent in the test deviceSerial(), the M9 GNSS module on the HPG board of instance 25 getting one fewer RRLP messages than we think it should in test gnssMsgReceiveNonBlocking(), the SARA-R422 module on instance 22 failing to perform an HTTP POST (we time-out after a 60 second wait) in exampleHttpClient(), the LENA-R8 module on instance 29 not getting the echo back of a secured DTLS packet in exampleSocketsDtls() and the wifiStationConnectWrongPassphrase() on instance 30, using uconnectExpress 2, being unable to connect to the Wifi network in a test which deliberately does NOT connect to the wifi network (unh?).  I have seen the latter failure once before and raised it with Peter but Peter retires tomorrow so I will raise it as a Jira ticket instead.
None of these random failures are likely to be associated with making the cellular radio parameter refresh delay configurable, hence merging.

Fix can be found in 87a0a2c07b0ca85e08a209215a38bc70bf219cd4, will close this now: please feel free to re-open if there is more to discuss,


[SMALLFIX] minor improvement

Merged build finished. Test PASSed.

Test PASSed.
Refer to this link for build results (access rights to CI server needed):
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fix(bls12381): NewPublicKeyFromBytes: add missing infinity check

Fixes a regression introduced in https://github.com/cometbft/cometbft/pull/3603

PR checklist

[x] Tests written/updated
[ ] Changelog entry added in .changelog (we use unclog to manage our changelog)
[x] Updated relevant documentation (docs/ or spec/) and code comments

Any idea of why this happens?
cometbft/crypto/bls12381 $ go test
?   	github.com/cometbft/cometbft/crypto/bls12381	[no test files]

Any idea of why this happens?
cometbft/crypto/bls12381 $ go test
?   	github.com/cometbft/cometbft/crypto/bls12381	[no test files]

you need to add bls12381 build flag: go test -tags=bls12381

But are we sure that the CI is running the added test? How does it know that it needs to add a -tag parameter?

But are we sure that the CI is running the added test? How does it know that it needs to add a -tag parameter?

Ok, it appears that it does not fail in the CI, see the last commit.

But are we sure that the CI is running the added test? How does it know that it needs to add a -tag parameter?

Ok, it appears that it does not fail in the CI, see the last commit.

Thanks for spotting it 👍 fixed in d527708 (#4104)


fetch returns an empty object

I am trying to use whatwg-fetch with webpack and require, it returns an empty object.
const fetch = require('whatwg-fetch');
console.log(fetch); // Object {}

I would expect require('whatwg-fetch');  to return the fetch function, I might be using it wrong in the first place, suggestion?

You haven't told us which module loader you use. Please refer to the documentation of your loader to learn how to require a file. Here are Webpack instructions.
We can't help you with other module loaders, though. See #46. It might be easier to just require the file normally, or concatenate your JS files together in a bundle.

i'm using imports-loader and exports-loader , and its the same configuration as it is in instructions
plugins: [
  new webpack.ProvidePlugin({
    'fetch': 'imports?this=>global!exports?global.fetch!whatwg-fetch'
  })
]

Sorry, I don't know what's going on. I've never used Webpack. Maybe refer to their documentation?
/cc @fourlastor https://github.com/github/fetch/pull/110/files

He's doing the right thing but I can't say from my phone if that's the correct setting. You might try to do it as per my pull request and it should work.
@mislav webpack uses a personalized way to import stuff, so you'll have to change things a bit if the library you're trying to import isn't commonjs compilant. Import and export module act so that you can have certain variables that the included script expects set up beforehand. To a clearer explanation looks at the doc on webpack, it's clearer :p

@mislav everything seems to be working thanks, also @fourlastor the loader name is incorrect , fixed and pushed

@ArmendGashi So now it works? What needed changing?

Oh I see: https://github.com/github/fetch/pull/110/files#r42432669
Well, we don't have those outdated instructions in the README anymore, and the blog post that we link to suggests installing the proper names: imports-loader/exports-loader.


Slides -- Last Pagination Bullet Doesn't Highlight When Go From First To Last Slide

Ionic version:  (check one with "x")
[ ] 1.x
[x] 2.x
I'm submitting a ...  (check one with "x")
[x] bug report
[ ] feature request
[ ] support request => Please do not submit support requests here, use one of these channels: https://forum.ionicframework.com/ or http://ionicworldwide.herokuapp.com/
Current behavior:
When going from first slide to last slide, the pagination bullet of the last slide doesn't highlight.
Expected behavior:
The pagination bullet of the last slide should be highlighted.
Steps to reproduce:
Plunker: http://plnkr.co/edit/V81JQoC55X5PTIvynQUW?p=preview
For Ionic 1 issues - http://plnkr.co/edit/Xo1QyAUx35ny1Xf9ODHx?p=preview
For Ionic 2 issues - http://plnkr.co/edit/z0DzVL?p=preview
-->
Related code:
insert any relevant code here

Other information:

Ionic info: (run ionic info from a terminal/cmd prompt and paste output below):
insert the output from ionic info here

Hello, thanks for opening an issue with us! We will look into this.


soroban-cli: token wrap ScVals & footprint for the contract code

What ?
soroban-cli: token wrap ScVals & footprint for the contract code
Epic
https://github.com/stellar/soroban-tools/issues/471

Can you provide more details?

Currently we don't have any tests for token wrap but if it is just another contract it should be done.  I'll look into adding a test.

if cli compiles, it should be done.


why only has 4 FPs with  --coco_transfer?

为什么我在测试video的时候，不加--coco_transfer测试显示7fps, 加了--coco_transfer测试显示只有4fps, 我的显卡为P40，在测试的过程转换tensorrt是成功的，没报错。是不是我哪里搞的不对？

--coco_transfer is used for converting the FPN weights from YOLACT 1.0 to YolactEdge. Without coco_transfer, the FPN weights won't be correctly loaded -- and the AP will be very low.
Please provide more information about your usage (with command you are using) so that we can understand the problem better, thanks.

--coco_transfer is used for converting the FPN weights from YOLACT 1.0 to YolactEdge. Without coco_transfer, the FPN weights won't be correctly loaded -- and the AP will be very low.
Please provide more information about your usage (with command you are using) so that we can understand the problem better, thanks.

我下载了模型yolact_edge_54_80000.pth
当使用Python eval--config_edge_pytorch_config --trained_mode=weights/yolcat_edge_54_800000.pth --score_threshold=0.3 ---top_k=100 --video_multiframe=1 --video=imgs/vis/avi 测试的时候为7Fps，图像大小为220*440
当使用Python eval --trained_mode=weights/yolcat_edge_54_800000.pth --score_threshold=0.3 ---top_k=100 --video_multiframe=1 --video=imgs/vis/avi 测试的时候为4Fps，已经生成了yolcat_edge_54_800000.pth.backbone.int8_100.trt, fpn_phase_1.trt, fpn_phase_2.trt, lat_layer.trt 和 proto_net.int8_100.trt

我下载了模型yolact_edge_54_80000.pth
当使用Python eval--config_edge_pytorch_config --trained_mode=weights/yolcat_edge_54_800000.pth --score_threshold=0.3 ---top_k=100 --video_multiframe=1 --video=imgs/vis/avi 测试的时候为7Fps，图像大小为220*440
当使用Python eval --trained_mode=weights/yolcat_edge_54_800000.pth --score_threshold=0.3 ---top_k=100 --video_multiframe=1 --video=imgs/vis/avi 测试的时候为4Fps，已经生成了yolcat_edge_54_800000.pth.backbone.int8_100.trt, fpn_phase_1.trt, fpn_phase_2.trt, lat_layer.trt 和 proto_net.int8_100.trt

This is interesting. I tried with the similar command with a video file of resolution 640x360. I could see a obvious speed boost while switching from yolact_edge_pytorch_config to yolact_edge_config.
Can you try pull the newest commit of the master branch, remove those cache files, and rerun the command? If there is still issues, please paste the logs printing on the screen and we can see where the problem is. Thanks.

This is interesting. I tried with the similar command with a video file of resolution 640x360. I could see a obvious speed boost while switching from yolact_edge_pytorch_config to yolact_edge_config.
Can you try pull the newest commit of the master branch, remove those cache files, and rerun the command? If there is still issues, please paste the logs printing on the screen and we can see where the problem is. Thanks.

已经采用最新的版本

已经采用最新的版本

@un90:~/mountDir/yolact_edge-master$ python eval.py --trained_model=weights/yolact_edge_54_800000.pth --score_threshold=0.3 --top_k=100 --video_multiframe=1 --video=imgs/vis1.avi
Config not specified. Parsed yolact_edge_config from the file name.
[01/04 13:49:32 yolact.eval]: Loading model...
[01/04 13:49:36 yolact.eval]: Model loaded.
[01/04 13:49:36 yolact.eval]: Converting to TensorRT...
Generating calibration dataset for backbone of 100 images...
loading annotations into memory...
Done (t=18.79s)
creating index...
index created!
Calibrating with 100 images...
Generating calibration dataset for protonet with 100 images...
Converting backbone to TensorRT...
Converting protonet to TensorRT...
Converting FPN to TensorRT...
Warning: Encountered known unsupported method torch.zeros
Converting PredictionModule to TensorRT...
[01/04 13:52:52 yolact.eval]: Converted to TensorRT.
Initializing model... Done.
Number of threads: 4
Processing FPS: 6.97 | Video Playback FPS: 0.00 | Frames in Buffer: 1    QObject::moveToThread: Current thread (0x7fee8c00d8c0) is not the object's thread (0x7fee8c079870).
Cannot move to target thread (0x7fee8c00d8c0)
我采用的是最新的代码  cuda11 cudnn8

@un90:~/mountDir/yolact_edge-master$ python eval.py --trained_model=weights/yolact_edge_54_800000.pth --score_threshold=0.3 --top_k=100 --video_multiframe=1 --video=imgs/vis1.avi
Config not specified. Parsed yolact_edge_config from the file name.
[01/04 13:49:32 yolact.eval]: Loading model...
[01/04 13:49:36 yolact.eval]: Model loaded.
[01/04 13:49:36 yolact.eval]: Converting to TensorRT...
Generating calibration dataset for backbone of 100 images...
loading annotations into memory...
Done (t=18.79s)
creating index...
index created!
Calibrating with 100 images...
Generating calibration dataset for protonet with 100 images...
Converting backbone to TensorRT...
Converting protonet to TensorRT...
Converting FPN to TensorRT...
Warning: Encountered known unsupported method torch.zeros
Converting PredictionModule to TensorRT...
[01/04 13:52:52 yolact.eval]: Converted to TensorRT.
Initializing model... Done.
Number of threads: 4
Processing FPS: 6.97 | Video Playback FPS: 0.00 | Frames in Buffer: 1    QObject::moveToThread: Current thread (0x7fee8c00d8c0) is not the object's thread (0x7fee8c079870).
Cannot move to target thread (0x7fee8c00d8c0)
我采用的是最新的代码  cuda11 cudnn8

The most up-to-date version of the code should not be loading annotations, which I saw in your logs.
Generating calibration dataset for backbone of 100 images...
loading annotations into memory...
Done (t=18.79s)

Can you check and see what the commit hash is? And if you try benchmarking with COCO dataset, what is the FPS?

The most up-to-date version of the code should not be loading annotations, which I saw in your logs.
Generating calibration dataset for backbone of 100 images...
loading annotations into memory...
Done (t=18.79s)

Can you check and see what the commit hash is? And if you try benchmarking with COCO dataset, what is the FPS?

$ python eval.py --coco_transfer --trained_model=weights/yolact_edge_54_800000.pth --score_threshold=0.3 --top_k=100 --video_multiframe=2 --trt_batch_size 2 --video=./imgs/vis1.avi
Config not specified. Parsed yolact_edge_config from the file name.
[01/04 16:24:39 yolact.eval]: Loading model...
[01/04 16:24:43 yolact.eval]: Model loaded.
[01/04 16:24:43 yolact.eval]: Converting to TensorRT...
[01/04 16:25:09 yolact.eval]: Converting backbone to TensorRT...
[01/04 16:27:14 yolact.eval]: Converting protonet to TensorRT...
[01/04 16:27:26 yolact.eval]: Converting FPN to TensorRT...
Warning: Encountered known unsupported method torch.zeros
[01/04 16:27:33 yolact.eval]: Converting PredictionModule to TensorRT...
[01/04 16:27:39 yolact.eval]: Converted to TensorRT.
Initializing model... Done.
Number of threads: 4
Processing FPS: 6.70 | Video Playback FPS: 0.00 | Frames in Buffer: 1    QObject::moveToThread: Current thread (0x7f4dbc00d8c0) is not the object's thread (0x7f4dbc07c1a0).
Cannot move to target thread (0x7f4dbc00d8c0)
我刚才重新拉了代码，这次是最新的。但是速度还是没有提升。
我没太明白你说的  if you try benchmarking with COCO dataset, what is the FPS? 我用的是COCO models，测试video,  不可以计算FPs吗

$ python eval.py --coco_transfer --trained_model=weights/yolact_edge_54_800000.pth --score_threshold=0.3 --top_k=100 --video_multiframe=2 --trt_batch_size 2 --video=./imgs/vis1.avi
Config not specified. Parsed yolact_edge_config from the file name.
[01/04 16:24:39 yolact.eval]: Loading model...
[01/04 16:24:43 yolact.eval]: Model loaded.
[01/04 16:24:43 yolact.eval]: Converting to TensorRT...
[01/04 16:25:09 yolact.eval]: Converting backbone to TensorRT...
[01/04 16:27:14 yolact.eval]: Converting protonet to TensorRT...
[01/04 16:27:26 yolact.eval]: Converting FPN to TensorRT...
Warning: Encountered known unsupported method torch.zeros
[01/04 16:27:33 yolact.eval]: Converting PredictionModule to TensorRT...
[01/04 16:27:39 yolact.eval]: Converted to TensorRT.
Initializing model... Done.
Number of threads: 4
Processing FPS: 6.70 | Video Playback FPS: 0.00 | Frames in Buffer: 1    QObject::moveToThread: Current thread (0x7f4dbc00d8c0) is not the object's thread (0x7f4dbc07c1a0).
Cannot move to target thread (0x7f4dbc00d8c0)
我刚才重新拉了代码，这次是最新的。但是速度还是没有提升。
我没太明白你说的  if you try benchmarking with COCO dataset, what is the FPS? 我用的是COCO models，测试video,  不可以计算FPs吗

Because I noticed that there a warning (or an error) like this, and want to see if it is a QT-related issue.
QObject::moveToThread: Current thread (0x7f4dbc00d8c0) is not the object's thread (0x7f4dbc07c1a0).
Cannot move to target thread (0x7f4dbc00d8c0)

Can you try benchmarking on COCO:
python eval.py --coco_transfer --trained_model=weights/yolact_edge_54_800000.pth --benchmark --max_images=1000

Besides, video processing FPS might be lower than benchmarking FPS because there involves some image processing on CPU for drawing texts/boxes. But it does not seem normal with around 5 FPS though.

Because I noticed that there a warning (or an error) like this, and want to see if it is a QT-related issue.
QObject::moveToThread: Current thread (0x7f4dbc00d8c0) is not the object's thread (0x7f4dbc07c1a0).
Cannot move to target thread (0x7f4dbc00d8c0)

Can you try benchmarking on COCO:
python eval.py --coco_transfer --trained_model=weights/yolact_edge_54_800000.pth --benchmark --max_images=1000

Besides, video processing FPS might be lower than benchmarking FPS because there involves some image processing on CPU for drawing texts/boxes. But it does not seem normal with around 5 FPS though.

$ python eval.py --coco_transfer --trained_model=weights/yolact_edge_54_800000.pth --benchmark --max_images=1000
Config not specified. Parsed yolact_edge_config from the file name.
loading annotations into memory...
Done (t=0.70s)
creating index...
index created!
[01/04 17:28:04 yolact.eval]: Loading model...
[01/04 17:28:08 yolact.eval]: Model loaded.
[01/04 17:28:08 yolact.eval]: Converting to TensorRT...
[01/04 17:28:08 yolact.eval]: Converting backbone to TensorRT...
[TensorRT] WARNING: TensorRT was linked against cuDNN 8.0.5 but loaded cuDNN 8.0.2
[TensorRT] WARNING: TensorRT was linked against cuDNN 8.0.5 but loaded cuDNN 8.0.2
[01/04 17:28:11 yolact.eval]: Converting protonet to TensorRT...
[TensorRT] WARNING: TensorRT was linked against cuDNN 8.0.5 but loaded cuDNN 8.0.2
[TensorRT] WARNING: TensorRT was linked against cuDNN 8.0.5 but loaded cuDNN 8.0.2
[01/04 17:28:11 yolact.eval]: Converting FPN to TensorRT...
[TensorRT] WARNING: TensorRT was linked against cuDNN 8.0.5 but loaded cuDNN 8.0.2
[TensorRT] WARNING: TensorRT was linked against cuDNN 8.0.5 but loaded cuDNN 8.0.2
[TensorRT] WARNING: TensorRT was linked against cuDNN 8.0.5 but loaded cuDNN 8.0.2
[TensorRT] WARNING: TensorRT was linked against cuDNN 8.0.5 but loaded cuDNN 8.0.2
[TensorRT] WARNING: TensorRT was linked against cuDNN 8.0.5 but loaded cuDNN 8.0.2
[TensorRT] WARNING: TensorRT was linked against cuDNN 8.0.5 but loaded cuDNN 8.0.2
[01/04 17:28:12 yolact.eval]: Converting PredictionModule to TensorRT...
[01/04 17:28:19 yolact.eval]: Converted to TensorRT.
Processing Images  ██████████████████████████████   1000 /   1000 (100.00%)     4.45 fps
Stats for the last frame:
  Name      | Time (ms)

----------------+------------
Network Extra |     0.4970
backbone |     3.3749
fpn |     1.5788
proto |     0.4687
pred_heads |     2.2909
makepriors |     0.0151
Detect |   214.8394
Postprocess |     0.9802
Sync |     0.0300
----------------+------------
Total |   224.0750
Average:  4.45 fps, 224.85 ms
会有可能是cuda和cudnn版本的问题吗？
1、WARNING: TensorRT was linked against cuDNN 8.0.5 but loaded cuDNN 8.0.2
2、服务器装了cuda10和cuda11, tensorrt安装cuda11版本，会是使用不匹配吗

$ python eval.py --coco_transfer --trained_model=weights/yolact_edge_54_800000.pth --benchmark --max_images=1000
Config not specified. Parsed yolact_edge_config from the file name.
loading annotations into memory...
Done (t=0.70s)
creating index...
index created!
[01/04 17:28:04 yolact.eval]: Loading model...
[01/04 17:28:08 yolact.eval]: Model loaded.
[01/04 17:28:08 yolact.eval]: Converting to TensorRT...
[01/04 17:28:08 yolact.eval]: Converting backbone to TensorRT...
[TensorRT] WARNING: TensorRT was linked against cuDNN 8.0.5 but loaded cuDNN 8.0.2
[TensorRT] WARNING: TensorRT was linked against cuDNN 8.0.5 but loaded cuDNN 8.0.2
[01/04 17:28:11 yolact.eval]: Converting protonet to TensorRT...
[TensorRT] WARNING: TensorRT was linked against cuDNN 8.0.5 but loaded cuDNN 8.0.2
[TensorRT] WARNING: TensorRT was linked against cuDNN 8.0.5 but loaded cuDNN 8.0.2
[01/04 17:28:11 yolact.eval]: Converting FPN to TensorRT...
[TensorRT] WARNING: TensorRT was linked against cuDNN 8.0.5 but loaded cuDNN 8.0.2
[TensorRT] WARNING: TensorRT was linked against cuDNN 8.0.5 but loaded cuDNN 8.0.2
[TensorRT] WARNING: TensorRT was linked against cuDNN 8.0.5 but loaded cuDNN 8.0.2
[TensorRT] WARNING: TensorRT was linked against cuDNN 8.0.5 but loaded cuDNN 8.0.2
[TensorRT] WARNING: TensorRT was linked against cuDNN 8.0.5 but loaded cuDNN 8.0.2
[TensorRT] WARNING: TensorRT was linked against cuDNN 8.0.5 but loaded cuDNN 8.0.2
[01/04 17:28:12 yolact.eval]: Converting PredictionModule to TensorRT...
[01/04 17:28:19 yolact.eval]: Converted to TensorRT.
Processing Images  ██████████████████████████████   1000 /   1000 (100.00%)     4.45 fps
Stats for the last frame:
  Name      | Time (ms)

----------------+------------
Network Extra |     0.4970
backbone |     3.3749
fpn |     1.5788
proto |     0.4687
pred_heads |     2.2909
makepriors |     0.0151
Detect |   214.8394
Postprocess |     0.9802
Sync |     0.0300
----------------+------------
Total |   224.0750
Average:  4.45 fps, 224.85 ms
会有可能是cuda和cudnn版本的问题吗？
1、WARNING: TensorRT was linked against cuDNN 8.0.5 but loaded cuDNN 8.0.2
2、服务器装了cuda10和cuda11, tensorrt安装cuda11版本，会是使用不匹配吗

I'm trying it on Jetson Xavier AGX with --coco_transfer.
On my device, FPS is around 10.
The video size is 256x256.
I tried both 'save video' mode and 'play video' mode, but both are 10.22 fps.
Here is the command I tested:
python eval.py --config yolact_edge_fp16_config --coco_transfer --trained_model=weights/yolact_edge_54_800000.pth --score_threshold=0.3 --top_k=100 --video_multiframe=8 --trt_batch_size 8 --video=videos/test_256x256.mp4
When the batch size was 8 with the 256x256 video, it was the fastest on my device so far.
How can I achieve over 20 FPS written on your paper?

I'm trying it on Jetson Xavier AGX with --coco_transfer.
On my device, FPS is around 10.
The video size is 256x256.
I tried both 'save video' mode and 'play video' mode, but both are 10.22 fps.
Here is the command I tested:
python eval.py --config yolact_edge_fp16_config --coco_transfer --trained_model=weights/yolact_edge_54_800000.pth --score_threshold=0.3 --top_k=100 --video_multiframe=8 --trt_batch_size 8 --video=videos/test_256x256.mp4
When the batch size was 8 with the 256x256 video, it was the fastest on my device so far.
How can I achieve over 20 FPS written on your paper?

@ho0-kim That FPS was measured with --benchmark, what is your FPS when benchmarking?
@gxingjie20 It might be so. Because I do not have a P40 (and I did not find one in EC2), I unfortunately cannot test that.

@ho0-kim That FPS was measured with --benchmark, what is your FPS when benchmarking?
@gxingjie20 It might be so. Because I do not have a P40 (and I did not find one in EC2), I unfortunately cannot test that.

@haotian-liu 你能抛一下你的log吗
Name      | Time (ms)
----------------+------------
Network Extra | 0.4970
backbone | 3.3749
fpn | 1.5788
proto | 0.4687
pred_heads | 2.2909
makepriors | 0.0151
Detect | 214.8394
Postprocess | 0.9802
Sync | 0.0300
----------------+------------
Total | 224.0750
Average: 4.45 fps, 224.85 ms
像这样的  我参考调试一下

@haotian-liu 你能抛一下你的log吗
Name      | Time (ms)
----------------+------------
Network Extra | 0.4970
backbone | 3.3749
fpn | 1.5788
proto | 0.4687
pred_heads | 2.2909
makepriors | 0.0151
Detect | 214.8394
Postprocess | 0.9802
Sync | 0.0300
----------------+------------
Total | 224.0750
Average: 4.45 fps, 224.85 ms
像这样的  我参考调试一下

In order to better understand which stage has the problem, you can add torch.cuda.synchronize() before L127 (start) and L130 (stop) of utils/timer.py.
Here is the stats for the last frame using python eval.py --coco_transfer --trained_model=weights/yolact_edge_54_800000.pth --benchmark --max_images=1000:
      Name      | Time (ms)
----------------+------------
  Network Extra |     0.2710
       backbone |     3.8711
            fpn |     1.1178
          proto |     0.9885
     pred_heads |     1.3465
     makepriors |     0.0269
         Detect |     1.1473
    Postprocess |     1.1600
           Sync |     0.0088
----------------+------------
          Total |     9.9379

Average: 95.65 fps, 10.45 ms

In order to better understand which stage has the problem, you can add torch.cuda.synchronize() before L127 (start) and L130 (stop) of utils/timer.py.
Here is the stats for the last frame using python eval.py --coco_transfer --trained_model=weights/yolact_edge_54_800000.pth --benchmark --max_images=1000:
      Name      | Time (ms)
----------------+------------
  Network Extra |     0.2710
       backbone |     3.8711
            fpn |     1.1178
          proto |     0.9885
     pred_heads |     1.3465
     makepriors |     0.0269
         Detect |     1.1473
    Postprocess |     1.1600
           Sync |     0.0088
----------------+------------
          Total |     9.9379

Average: 95.65 fps, 10.45 ms

测试结果如下：
Stats for the last frame:
  Name      | Time (ms)

----------------+------------
Network Extra |     0.0303
backbone |   155.7121
----------------+------------
Total |   155.7424
Average:  4.40 fps, 227.42 ms
你论文中的backbone是ResNet101哈，所以我用TRT+Torch2TRT单独的程序测试了一下ResNet101,耗时为2ms左右如下：
Network forward: PyTorch: 1.68e-02 [  59.38], TRT: 2.01e-03 [ 498.16]
所以环境应该是没问题的哈，大概有10倍的加速
所以你测试的 Detect |     1.1473，我却要Detect | 214.8394？？ 这个时间在哪里计算的 是这个问题吗？

测试结果如下：
Stats for the last frame:
  Name      | Time (ms)

----------------+------------
Network Extra |     0.0303
backbone |   155.7121
----------------+------------
Total |   155.7424
Average:  4.40 fps, 227.42 ms
你论文中的backbone是ResNet101哈，所以我用TRT+Torch2TRT单独的程序测试了一下ResNet101,耗时为2ms左右如下：
Network forward: PyTorch: 1.68e-02 [  59.38], TRT: 2.01e-03 [ 498.16]
所以环境应该是没问题的哈，大概有10倍的加速
所以你测试的 Detect |     1.1473，我却要Detect | 214.8394？？ 这个时间在哪里计算的 是这个问题吗？

@gxingjie20 have you updated utils/timer.py for a more accurate timing?

@gxingjie20 have you updated utils/timer.py for a more accurate timing?

@haotian-liu
我将 yolcat中 with timer.env('backbone')区间的代码计算了耗时，也是2ms多，加了torch.cuda.synchronize()打印的log显示为156ms

@haotian-liu
我将 yolcat中 with timer.env('backbone')区间的代码计算了耗时，也是2ms多，加了torch.cuda.synchronize()打印的log显示为156ms

@gxingjie20 Can you post the full timing log with CUDA synchronize?

@gxingjie20 Can you post the full timing log with CUDA synchronize?

@haotian-liu
是的  我更新了
def enter(self):
torch.cuda.synchronize()
start(self.fn_name, use_stack=self.use_stack)
def __exit__(self, e, ev, t):
       torch.cuda.synchronize()
       stop(self.fn_name, use_stack=self.use_stack)

我用50 ，100， 250张图都测试过
 Name      | Time (ms)

----------------+------------
Network Extra |     0.5593
backbone |     156.2175
fpn |     9.1763
proto |     38.4634
pred_heads |     14.
makepriors |     0.05
Detect |     4.56
Postprocess |     3.8161
Sync |     0.113
----------------+------------
Total |     227

@haotian-liu
是的  我更新了
def enter(self):
torch.cuda.synchronize()
start(self.fn_name, use_stack=self.use_stack)
def __exit__(self, e, ev, t):
       torch.cuda.synchronize()
       stop(self.fn_name, use_stack=self.use_stack)

我用50 ，100， 250张图都测试过
 Name      | Time (ms)

----------------+------------
Network Extra |     0.5593
backbone |     156.2175
fpn |     9.1763
proto |     38.4634
pred_heads |     14.
makepriors |     0.05
Detect |     4.56
Postprocess |     3.8161
Sync |     0.113
----------------+------------
Total |     227

@gxingjie20 What if you just randomly initialize a R101 network from torch vision and time it? What is the usual inference time for R101 backbone on your P40. And did you make sure that no one is using the machine (CPU / GPU).

@gxingjie20 What if you just randomly initialize a R101 network from torch vision and time it? What is the usual inference time for R101 backbone on your P40. And did you make sure that no one is using the machine (CPU / GPU).

@gxingjie20 The previous one is correct.

@gxingjie20 The previous one is correct.

我用的 https://github.com/vujadeyoon/TensorRT-Torch2TRT 中的代码测试了 res50 和 res101 都是提速10倍左右
Res101 Network forward: PyTorch: 1.68e-02s [ 59.38], TRT: 2.01e-03s [ 498.16] , 59.38为不带TRT加速的时间

我用的 https://github.com/vujadeyoon/TensorRT-Torch2TRT 中的代码测试了 res50 和 res101 都是提速10倍左右
Res101 Network forward: PyTorch: 1.68e-02s [ 59.38], TRT: 2.01e-03s [ 498.16] , 59.38为不带TRT加速的时间

@haotian-liu
我用的 https://github.com/vujadeyoon/TensorRT-Torch2TRT 中的代码测试了 res50 和 res101 都是提速10倍左右
Res101 Network forward: PyTorch: 1.68e-02s [ 59.38], TRT: 2.01e-03s [ 498.16] , 59.38为不带TRT加速的时间

@haotian-liu
我用的 https://github.com/vujadeyoon/TensorRT-Torch2TRT 中的代码测试了 res50 和 res101 都是提速10倍左右
Res101 Network forward: PyTorch: 1.68e-02s [ 59.38], TRT: 2.01e-03s [ 498.16] , 59.38为不带TRT加速的时间

You need to include the GPU synchronization result also. PyTorch CUDA calls are asynchronous.

You need to include the GPU synchronization result also. PyTorch CUDA calls are asynchronous.

@haotian-liu
加了 sync 再测试后就不加速了
你也会出现同样的情况吗？你方便也测试一下吗？ 抛个结果
蒙圈了。 请问  再怎么调
更正一下  我的 显卡是Tesla K80 尴尬

@haotian-liu
加了 sync 再测试后就不加速了
你也会出现同样的情况吗？你方便也测试一下吗？ 抛个结果
蒙圈了。 请问  再怎么调
更正一下  我的 显卡是Tesla K80 尴尬

@haotian-liu
我知道问题在哪里了  我的显卡不支持int8  但他却没给我提示

@haotian-liu
我知道问题在哪里了  我的显卡不支持int8  但他却没给我提示


[INLONG-5014][Improve] Fix the code scanning alerts exposed by CodeQL

see https://github.com/apache/inlong/issues/5014

@jun0315 1 new alert including 1 medium severity security vulnerability, 7 fixed.
1

2

@dockerzhang Thanks. I will fix this.


Could not find any camera. Returning NULL.

When I ran the example code Planet Editor, it raised errors "[ERROR]: Could not find any camera. Returning NULL".
Information in the console:
[INFO]:` Starting application.
[INFO]: Initializing engine systems.
[INFO]: Initialized Render Context with params:
    - max_buffers (100), max_textures (100), max_materials (100), max_framebuffers (100)
[INFO]: Launched rendering thread (VXR_THREADING).
[INFO]: Reached first application loop.
[ERROR]: Could not find any camera. Returning NULL.

Yeah I probably shouldn't address this as an error... It happens because the first frame is completed before any cameras are created, and the UI Editor retrieves the main camera each frame...
I will remove the print on the next update.


dead code elimination

Looks like its quite possible to clean up nested dependencies from unnecessary code. Still, have check for implicit dependencies, font-face for example.

Not very important at the moment


[BUG] - phpvms 7 - PIREPS being submitted as manual

Describe the bug
smartcars 3 pireps are being submitted as manual pireps in the phpvms 7 system, this causes the auto processing of pireps to break.
How do you reproduce this bug?

Log a flight with SC3
Submit
View phpvms 7 admin center and youll have a pending "manual (smarcars 3)" PIREP.

Expected behavior
Should have its own class of submitting instead of manual to allow for processing.
Screenshots

API Version
0.3.4
PHP Version
8.0.11
Database & version
10.5.12 MariaDB
Webserver version
Apache
Browser
Chrome
Handler
phpvms7
Additional context
No response

Do you happen to know what the database fields should be to submit the PIREP as a ACARS PIREP?
I've tried reaching out to nabeel to try to see what changes we need to make to our API to make it more "phpvms7-esc", but I've not had a reply and we're navigating blind on a still in-development system

Do you happen to know what the database fields should be to submit the PIREP as a ACARS PIREP?
I've tried reaching out to nabeel to try to see what changes we need to make to our API to make it more "phpvms7-esc", but I've not had a reply and we're navigating blind on a still in-development system

Have linked PR #83 which has the fix for you


Need a final description for the payment wallet

The description (markdown) is shown when the user creates the wallet. The full page (mobile) is available.
Right now, we configured this as description
ThreeFold Token
Our backed, safe digital currency funds a neutral green Internet

An empty wallet is added automatically, so the description isn't visible to the user


#104: Composer Autoloader now requires with absolute path to fix bug …

…when plugin was called through WP-CLI.

@thellimist please review/merge.


[22.11] nixos/wordpress: component directories should match name

Description of changes
In an effort to better encode version strings and use descriptive pnames that do not conflict with top level pkgs, we currently use wordpress-${type}-${pname} for pname. This is good for the nix store, but when we synthesize the wordpress derivation in our module, we reuse this pname for the output directory.
Internally wordpress can handle this fine, since plugins must register via php, not directory. Unfortunately, many plugins like civicrm and wpforms-lite are designed to rely upon the name of their install directory for homing or discovery.
As such, we should follow both the upstream convention and services.nextcloud.extraApps and use an attribute set for these options. This allows us to not have to deal with the implementation details of plugins and themes, which differ from official and third party, but also give users the option to override the install location. The only issue is that it breaks the current api.
(cherry picked from #210686)
Unfortunately, we cannot always make backwards compatible changes, so instead we can consume wpName from official components, and fallback to the current behaviour if that field is missing, currently just third party components.
Things done

Built on platform(s)

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

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

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

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[x] Tested basic functionality of all binary files (usually in ./result/bin/)
23.05 Release Notes (or backporting 22.11 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module
[ ] (Release notes changes) Ran nixos/doc/manual/md-to-db.sh to update generated release notes

[x] Fits CONTRIBUTING.md.

This pull request has been mentioned on NixOS Discourse. There might be relevant details there:
https://discourse.nixos.org/t/prs-ready-for-review/3032/1770

This pull request has been mentioned on NixOS Discourse. There might be relevant details there:
https://discourse.nixos.org/t/prs-ready-for-review/3032/1816

Unfortunately NixOS 22.11 has reached its end-of-life status on 2023-06-30, one month after the release of NixOS 23.05.
I'm closing this pull request, since we do not accept any changes to its branches anymore.


Only run protobuf for one remaining folder

Don't attempt to look for other folders as we only care about one now, per @noamnelke.
Motivation
Closes #1942
Changes
These scripts should not attempt to find other dirs containing protobuf files. We just hardcode a single directory.
Test Plan
N/A

I'm having trouble testing the Windows code due to #1954, will test when I can.

I still want to test this on Windows, blocking on #1954, will try again

@lrettig what's up with this? it's starting to rot...

Rebased on the latest code. Unfortunately this is still blocking on #1954, which still has outstanding issues. Will keep working on it.
@noamnelke if you like we could split this PR into two, and merge the changes to scripts/genproto.sh while I keep working on the Windows issues.

#1954 is resolved, all looks good, time to merge

bors merge

bors merge

bors merge


Cluster Dropdown

change 'new' -> 'create cluster'

move new cluster link to top

fix for https://github.com/supergiant/supergiant/issues/823

Coverage remained the same at 61.313% when pulling 879d3a33e6afc94322f845289a1fbbb58fd7a5da on josephkane:create-new-cluster-list into 49f5628e2db4a63c45802715a4a4023ea52cc531 on supergiant:master.


Added DRI Calculator

Issue No: #98
Name: Rishi Paul
Added DRI Calculator

Made the necessary changes please have a look @ritika728


make s3 check rails 6.1 compatible

Rails.application.class.parent_name is deprecated in Rails 6 and was removed in in Rails 6.1, that causes the S3 health check to fail with a Rails 6.1 application

Simple elegant solution, looks good to merge.

We are having issues using this gem with Rails 7, are there any plans on merging this change?


ARC-1435 - Update the validation error for GitHub Cloud URL when creating GHE server

Rationale

When users type in a GitHub cloud URL when trying to connect to a GitHub Enterprise server, it is now treated as a URL validation error, displaying an error message with a link that redirects to GitHub Cloud site.

Changes

The separate method checkGHEServerUrl was removed and the logic was added to checkValidGHEUrl.
A new method was created which simply displays the error messages, based on the error object passed to it.
Minor code cleanup

A new method hideErrorMessage was created.

Video
https://www.loom.com/share/0605e2c39ac5443a8b76089cbb5bf267

For this UI task, only frontend validation has been implemented. For security, duplicate or any other proper check, a backend validation will be needed, which I think will be done in a separate ticket in the future.

I okay to approve it. But please be aware that:

If the validation is only for UX purpose, then it is fine.
If the validation is also for security/correctness purpose, then we need to do similar stuff to the backend route as well.

For this UI task, only frontend validation has been implemented. For security, duplicate or any other proper check, a backend validation will be needed, which I think will be done in a separate ticket in the future.


Documentation layout shell

This is very similar in concept to our AppShell component, but rather than providing control for our app layout, we create a reusable component template that can be used for controlling the layout and design of our documentation pages. Given these have a lot of repetition!
Loose ideas:

Small bits of data are controlled with multiple props or a singular "config" prop (title, desc, imports, source link, etc)
We provide table data to the component to generate whole sections, perhaps folded into tabbed areas
We insert Usage via a dedicated slot, perhaps the default slot, as this varies wildly doc to doc
Perhaps we standardize out example/sandbox preview? Would be great if these were always interactive!
We look to dynamically generate a table of contents, perhaps per page, based on headings, data attributes, etc
(more ideas to come....)

Plotting out the structure and requirements.
Header

Name
Description

Details

import: (list of Svelte imports)
stylesheets - (tailwind elements; included in X)
source: view source code
doc: edit this page
package: @brainandbones/skeleton (default)
depedencies: (ex: highlight.js)

Examples

Standarize Sandbox?

Examples/Sandbox - slot

Tabbed Sections

Support parent/child components

Usage - default slot

Mix of docs + small examples
Browser Support?

Props - slot/tables
Classes - slot/tables
Slots - slot/tables
A11y/Keyboard - slot/tables/APG

I've implemented a working draft of new component layout. It allows for a MUCh more sophisticated and dynamic documentation layout and visual presentation. Very please with the initial results.

Here's the Accordion component documented:

Showing the Accordion properties tab:

This has now been merged into dev branch and is ready for review!

Marking this completed and ready for release.


Enhancement allocate blocks in scanner_context on demand

Proposed changes
Introduced #19389 , removed #20785

Further comments
If this is a relatively large or complex change, kick off the discussion at<EMAIL_ADDRESS>by explaining why you chose the solution you did and what alternatives you considered, etc...

run buildall

run buildall

(From new machine)TeamCity pipeline, clickbench performance test result:
the sum of best hot time: 46.11 seconds
stream load tsv:          540 seconds loaded<PHONE_NUMBER>9 Bytes, about 132 MB/s
stream load json:         21 seconds loaded<PHONE_NUMBER> Bytes, about 107 MB/s
stream load orc:          65 seconds loaded<PHONE_NUMBER> Bytes, about 16 MB/s
stream load parquet:          31 seconds loaded 861443392 Bytes, about 26 MB/s
insert into select:          29.0 seconds inserted 10000000 Rows, about 344K ops/s
storage size:<PHONE_NUMBER>3 Bytes


nixos/apfs: init

Motivation for this change
Add the final missing pieces for full APFS support.
Things done

Built on platform(s)

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

[ ] For non-Linux: Is sandbox = true set in nix.conf? (See Nix manual)
[x] Tested via one or more NixOS test(s) if existing and applicable for the change (look inside nixos/tests)
[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review wip"
[ ] Tested execution of all binary files (usually in ./result/bin/)
21.11 Release Notes (or backporting 21.05 Release notes)

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

[x] Fits CONTRIBUTING.md.

I fixed the conflict.

Fixed the conflict again.

Fixed the conflict again.

/marvin opt-in
/status needs_reviewer

Fixed the conflict again.

Fixed the conflict again.
This time, I added the changeling entry in the middle to reduce the probability of future conflicts.


Error: Input buffer contains unsupported image format

I am getting the current error while trying to iterate through a loop of links of images. I'm using sharp(buffered-link) and not directly using the request module as was the case in 930.
let pfparray = ["https://i.imgur.com/KCskkMr.jpg" , "https://i.imgur.com/7KH3tBd.jpg" , "https://i.imgur.com/iDjptdL.jpg"]
 pfparray.forEach(link => {
             sharp(Buffer.from(link)) // encoding in utf-8
            .resize(100)
            .toBuffer()
            .then( data => { bufferArray.push(data) })
            .catch( err => { console.log(err + " | error!")});
        })

I may be missing something due to my lack of understanding of this function, but so far it shows no improvement. URL is a valid image. What could I be doing wrong?
Intended: Buffers images and executes accordingly
Actual: Throws following errors:
Error: Input buffer contains unsupported image format | error!
Error: Input buffer contains unsupported image format | error!
Error: Input buffer contains unsupported image format | error!

You'll need to add your own networking logic. See #1901 for some examples.


Show expected updated/created MRs when running git lab

Also mention the remote name and the final branch.
Sample output:
$ git lab
Commits to be reviewed, destined for origin/main:
* d74fbd54 Bump variable "cluster_version_prefix" to 1.26. [new]

Proceed? ([y]/n)

or
$ git lab
Commits to be reviewed, destined for origin/main:
* d74fbd54 Bump variable "cluster_version_prefix" to 1.26. [!290]

Proceed? ([y]/n)

Closes: #50
Supersedes: #51

@kostajh

Thanks!


ROCANA-6502 Add support for collecting individual network connections (Linux)

Adds per-connection metrics for TCP, UDP and raw sockets over IPv4 and v6. We don't capture everything, just the hosts, ports, queue depth and connection state.

@adamlamar I fixed the comment to clarify that the byte order is unknown on big-endian systems.

LGTM!


Build fails because of missing type definitions

Describe the bug
Whenever I add a test to the project and try to run npm run build, I get type definition errors. Errors are related to @types/node and @types/ws. I know I could just install these within my own devDependencies, but I think this should not be the case?

Reproduction
This is a fresh install of Vite+Vitest. The only change by me here is adding a test. Try running npm run build here:
https://stackblitz.com/edit/vitejs-vite-kmvhms
System Info
-

Used Package Manager
npm
Validations

[X] Follow our Code of Conduct
[X] Read the Contributing Guidelines.
[X] Read the docs.
[X] Check that there isn't already an issue that reports the same bug to avoid creating a duplicate.
[X] Check that this is a concrete bug. For Q&A open a GitHub Discussion or join our Discord Chat Server.
[X] The provided reproduction is a minimal reproducible example of the bug.

Not sure about "@types/ws", but "@types/node" is required
You can also try passing "--skipLibCheck" to tsc command

I know that skipLibCheck solves the issue, but I would rather keep the rule as true. I think I'll just install these deps on my own.

I'm also running into this when adding Vitest to a project. Had to add @types/ws and @types/babel__core. Will update if I find an alternative. It's a bit weird.

Can confirm the bug: https://github.com/sheremet-va/vitest-types-bug
Note, we also require esModuleInterop: true in tsconfig at the moment (because of chai)


Azure function Deployment failed using Azure Functions extensions in Ubuntu 20LTS

Hi All,
I developing some Azure Function POC as part of my learning activity. I created sample Azure function using VS code editor and Azure Functions extension . But while trying to deploy it to azure through "Deploy to Function App icon" it's  got failed.
Failed to deploy
path that does not exist: /home/otnetapps/functionapps/WatchPortalFunction/bin/Release/netcoreapp3.1/publish
How I can compile and create a release path using vscode and Azure functions extension . Please guide.

More detailed one is created


Add configurable Export timeout

The export timeout was hard-coded at 10s. This makes it configurable and sets the default to 60s.
Although the OTel-Go Metrics SDK has an export timeout configuration, the OTel-Go Trace SDK does not. TODOs were filed along with OTel-Go issue https://github.com/open-telemetry/opentelemetry-go/issues/1386.

TBR @codeboten


Release 1.1.0 updating versions and examples

@asm0dey Whenever you're ready to publish the release. This contains the updated docs and versions etc :)

(@me don't forget to update 3.1 and 3.0 branch when this is merged)


Download the messages during the batch step in parallel

User Story
As a receiver and a RS developer I want the batch step to run quickly enough that it does not time out. One step in making this happen is downloading the message in parallel rather than one at a time.
Description/Use Case
https://github.com/CDCgov/prime-reportstream/issues/10305 has the full story, but essentially when a large number of messages are sent through RS the batch function starts timing out. After some digging into why, downloading came up as one of the areas taking the longest. To try to prevent the timeouts we want to download the messages in parallel.
Risks/Impacts/Considerations
Dev Notes
There are two places downloading happens during the batch step. Two places in in BatchFunction.batchUniversalData() then also in WorkflowEngine.createHeader() which is called from WorklowEngine.handleBatchEvent() which is called from BatchFunction.doBatch()
Acceptance Criteria

[ ] The messages are downloaded in parallel
[ ] We have tested what this does for the timing using the functional tests from https://app.zenhub.com/workspaces/platform-6182b02547c1130010f459db/issues/gh/cdcgov/prime-reportstream/10691 and any necessary follow up tickets are created.

Hey team! Please add your planning poker estimate with Zenhub @arnejduranovic @jack-h-wang @JessicaWNava @JFU-NAVA-PBC @luis-pabon-tf @mkalish @thetaurean


@aspnet/signalr-client not found in dev registry

Hello, I'm trying to use your CI/dev version of the SignalR TypeScript client but both yarn and npm are having trouble both using adding @aspnet:registry=https://dotnet.myget.org/f/aspnetcore-ci-dev/npm/ to my .npmrc and also by calling yarn install / npm install with the --registry @aspnet:registry=https://dotnet.myget.org/f/aspnetcore-ci-dev/npm/ option
npm output:
npm install  @aspnet/signalr-client@latest
npm ERR! code E404
npm ERR! 404 Not Found: @aspnet/signalr-client@latest

yarn output:
yarn add @aspnet/signalr-client
yarn add v1.3.2
[1/4] Resolving packages...
error Couldn't find package "@aspnet/signalr-client" on the "npm" registry.

Removing the line from .npmrc or the --registry option from the cmd line both result in successful installs but from the npm registry rather than your dev one.

Try @aspnet:registry=https://dotnet.myget.org/f/aspnetcore-dev/npm/

Yep that works great thanks 😄 - looks like the README.md needs updating then.. Will leave this open until that is updated because other people will likely hit the same issue


How to set versionName and versionCode in sbt?

How do I set these values in build.sbt?
I tried setting them like this:
versionCode in Android := Some(123)
versionName in Android := Some("1.1")

but the resulting APK file doesn't reflect the changes. Additionally, when building a release version, SBT throws an error Manifest merger failed : Attribute manifest@versionName at AndroidManifest.xml:2:1 requires a placeholder substitution but no value for <versionMajor> is provided
Is there a way to dynamically set versionName and versionCode in the SBT build file, rather than declaring them in AndroidManifest.xml?

What you have should work fine. Sounds like you have manifest placeholders set but aren't filling in the placeholders instead.

A test case I have just tried indicates that it works fine.

steps:
sbt 'gen-android android-21 com.example Foo'
echo sbt.version=0.13.5 > project/build.properties
echo 'versionName in Android := Some("1.2.3")\n\nversionCode in Android := Some(1234)' > build.sbt
sbt android:package-debug android:package-release
$ANDROID_HOME/build-tools/VERSION/aapt d badging target/android-bin/com-example-{debug,release-unsigned}.apk

Thanks for the clarification. Seems like running that example code (sbt 'gen-android android-21 com.example Foo') you gave throws an error about ANDROID_HOME not being set properly (error is RuntimeException: ANDROID_HOME or sdk.dir is not set).... even though echo $ANDROID_HOME returns the proper result... I just installed the android-sdk-plugin globally and ran that first line. Any ideas?

export your environment variables.
--
Sent from my phone
On Mar 5, 2015 9:29 PM, "Mitch Ware"<EMAIL_ADDRESS>wrote:

Thanks for the clarification. Seems like running that example code (sbt
'gen-android android-21 com.example Foo') you gave throws an error about
ANDROID_HOME not being set properly (error is RuntimeException:
ANDROID_HOME or sdk.dir is not set).... even though echo $ANDROID_HOME
returns the proper result... I just installed the android-sdk-plugin
globally and ran that first line. Any ideas?
—
Reply to this email directly or view it on GitHub
https://github.com/pfn/android-sdk-plugin/issues/150#issuecomment-77508982
.

They are already globally available... I use them in various other places without issue

Doesn't sound like it's available going by the error you get
--
Sent from my phone
On Mar 5, 2015 10:02 PM, "Mitch Ware"<EMAIL_ADDRESS>wrote:

They are already globally available... I use them in various other places
without issue
—
Reply to this email directly or view it on GitHub
https://github.com/pfn/android-sdk-plugin/issues/150#issuecomment-77511356
.

Okay so I have a new issue here... I can't get the test project command above to work, but I adapted what I am trying to do with my existing project and build file.
I am trying to create 4 variables, versionMajor, versionMinor, versionPatch, and versionBuild and dynamically combine them to form the versionCode and versionName properties.
I have this so far:
...

platformTarget in Android := "android-21"

buildToolsVersion in Android := Some("21.1.1")

val versionMajor = 1
val versionMinor = 0
val versionPatch = 0
val versionBuild = 2

manifestPlaceholders in Android := Map(
    "versionMajor" -> "${versionMajor}",
    "versionMinor" -> "${versionMinor}",
    "versionPatch" -> "${versionPatch}",
    "versionBuild" -> "${versionBuild}"
)

versionCode in Android := Some(versionMajor*10000 + versionMinor*1000 + versionPatch*100 + versionBuild)

versionName in Android := Some("${versionMajor}.${versionMinor}.${versionPatch}.${versionBuild}")

...

Everything seems to be working, however the actual string value for versionName in the final APK comes out to be "${versionMajor}.${versionMinor}.${versionPatch}.${versionBuild}" explicitly, instead of evaluating and replacing the variables. I expect the versionName to equal "<IP_ADDRESS>". How can I fix that?

You're mixing manifest placeholders and version code/name in sbt, that is absolutely the incorrect thing to be doing, use one or the other.

You're also trying to interpolate strings without using the correct interpolation format.

Solution, remove manifest placeholders, prefix your version name with s, e.g
versionName in Android := Some(s"${versionMajor}")

Ah, I see now. I guess since the string interpolating was wrong, the manifest merging was expecting those variables as placeholders. Looks like it is working now. Thank you for the help!

manifest placeholders are only for the XML file.
On Fri, Mar 6, 2015 at 10:38 AM, Mitch Ware<EMAIL_ADDRESS>wrote:

Ah, I see now. I guess since the string interpolating was wrong, the
manifest merging was expecting those variables as placeholders. Looks like
it is working now. Thank you for the help!
—
Reply to this email directly or view it on GitHub
https://github.com/pfn/android-sdk-plugin/issues/150#issuecomment-77611394
.


Don't turn parameters like "?foo=bar&foo=baz" into "?foo[0]=bar&foo[1]=b...

This patch fixes a problem which causes multi-valued parameters to be turned into foo[0]=bar&foo[1]=baz style parameters.

:+1:


extra hyphen deleted

Thanks for the fix. Be sure to check out your name as a contributor about the 3rd of next month on the What's new page in the Community contributors section at the bottom.


review subtitle no.25 keras_introduction

ref #390

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint.

Btw, the title could be updated to:
docs(zh-cn): Reviewed No. 25 - Keras introduction


Missing attribute compare with Pytorch

Hi i have to reconstruct a model called vocos
But i have trouble to dealing with model weight init.
In vocos original code,there has a period to initialize layer weight like below:
def __init__(self, num_embeddings: int, embedding_dim: int, eps: float = 1e-6):
        super().__init__()
        self.eps = eps
        self.dim = embedding_dim
        self.scale = nn.Embedding(num_embeddings=num_embeddings, embedding_dim=embedding_dim)
        self.shift = nn.Embedding(num_embeddings=num_embeddings, embedding_dim=embedding_dim)
        torch.nn.init.ones_(self.scale.weight)
        torch.nn.init.zeros_(self.shift.weight)

I have found the ones_() method by using:
using static TorchSharp.torch.nn.init;

But when i want initailize layer weight like what they do,visual studio has raise an error(translated from Chinese to English) like below:
Severity code description: Project file line suppression status
Error CS1061 'torch. nn. Module<torch. Tensor, torch. Tensor>' does not contain a definition for 'weight' and cannot find an accessible extension method 'weight' that accepts the first 'torch. nn. Module<torch. Tensor, torch. Tensor>' type parameter. (Is there a missing using directive or assembly reference?) VALLESharp D: \ VALLESharp \ VALLESharp \ Vocos \ Modules. cs 40 Activity

Not very happy to deal with that,btw,Happy Chinese NewYear! : )

Happy Chinese NewYear @ElinLiu0 !
Can you provide me with the sample C# code you used to get this issue?
The following snippet below worked for me:
var emb = torch.nn.Embedding(100, 20);
torch.nn.init.ones_(emb.weight);

Happy Chinese NewYear @ElinLiu0 !
Can you provide me with the sample C# code you used to get this issue?
The following snippet below worked for me:
var emb = torch.nn.Embedding(100, 20);
torch.nn.init.ones_(emb.weight);

Seems same as your provide version:
internal class AdaLayerNorm : Module<Tensor,Tensor, Tensor>
{
    private double eps = 1e-6;
    private int dim;
    private Module<Tensor, Tensor> scale;
    private Module<Tensor, Tensor> shift;
    public AdaLayerNorm(string name,int num_embeddings,int embedding_dim) : base(name)
    {
        this.scale = torch.nn.Embedding(num_embeddings,embedding_dim);
        this.shift = torch.nn.Embedding(num_embeddings,embedding_dim);
        torch.nn.init.ones_(this.scale.weight);
        torch.nn.init.zeros_(this.shift.weight);
    }
    public override Tensor forward(Tensor x,Tensor cond_embedding_id)
    {
        var Scales = this.scale.forward(cond_embedding_id);
        var Shift = this.shift.forward(cond_embedding_id);
        x = nn.functional.layer_norm(x, [this.dim,],null,null,eps);
        x = x * Scales + Shift;
        return x;
    }
}

Ah, the problem is with these lines:

private Module<Tensor, Tensor> scale;
private Module<Tensor, Tensor> shift;

The general Module class doesn't have a weight attribute. You can solve it by changing those lines to:
using TorchSharp.Modules;
...
private Embedding scale;
private Embedding shift;

Ah, the problem is with these lines:

private Module<Tensor, Tensor> scale;
private Module<Tensor, Tensor> shift;

The general Module class doesn't have a weight attribute. You can solve it by changing those lines to:
using TorchSharp.Modules;
...
private Embedding scale;
private Embedding shift;

Right,i will using your namespace provided and bring reply if possible,thank you.
Btw,i will left this issue till the problem solved.

Ah, the problem is with these lines:

private Module<Tensor, Tensor> scale;
private Module<Tensor, Tensor> shift;

The general Module class doesn't have a weight attribute. You can solve it by changing those lines to:
using TorchSharp.Modules;
...
private Embedding scale;
private Embedding shift;

Working fine and properly.


Fix endOf for daylight saving time

The endOf formula was not working for the day that the daylight saving
time starts.
Couldn't run tests locally, but running the test code worked.
resolves https://github.com/moment/moment/issues/4249

I copied another test in same file to make my, both should be moved?

*mine

Seems like it's not needed anymore.


[SPARK-11245] update twitter4j to 4.0.4 version

update twitter4j to 4.0.4 version
https://issues.apache.org/jira/browse/SPARK-11245

Can one of the admins verify this patch?

Looking @ the twitter4j poms, their dependencies pull in a com.googlecode.kryo -given the kryo pain its a possible troublespot. However, that com.googlecode release is so old its in a different package from the com.esotericsoftware-packaged releases
Various modules seems to refer to a different junit (3.8.2 in http-2, 4.10 in core, ...), but those are test scoped only. Log4j 1.2.17; SLF4J 1.7.12, commons-logging 1.1 -nothing incompatible with the spark versions, afaik.
main pom.xml

@steveloughran you mean require something change ? or just potential issue ?

Yeah, we would need more info here, to update across major releases. Because this is just an isolated 'leaf' package, we can probably tolerate more change there. But, at least, can you summarize any incompatible changes or siginficant ones, and more importantly key changes in the dependency tree?

@pronix also you need to look at https://cwiki.apache.org/confluence/display/SPARK/Contributing+to+Spark and update the title, etc.

@srowen Official documentation about upgrade http://blog.twitter4j.org/2014/03/13/69

Yes, but if you're proposing the change I believe you need to investigate the implications. This doesn't address dependency changes which Steve already alluded to.

slf4j & log4j are in sync with Spark 1.6. I can't actually see an explicit ref to commons-logging in the spark poms (just lots of exclusions of the hadoop one), but some indirect references come in at v 1.1.3.
That leaves kryo. Precisely because this is a very old import with different package names, this isn't going to be as fraught as trouble as the main kryo package.
mvn repo says its just for testing anyway
No sign of the other troublespots: guava, jackson, jetty...

Test build #1943 has started for PR 9221 at commit f82a648.

Seems pretty reasonable then. Let's see what tests say.

Test build #1943 has finished for PR 9221 at commit f82a648.

This patch passes all tests.
This patch merges cleanly.
This patch adds no public classes.

all tests are passed :)

There arent any real testing for twitter, as we cannot really send and receive data from twitter. So the tests passing does prove nothing.

Merged to master

@srowen Did you test it by actually passing data?

No, I presume that's what led @pronix to the changes here? @pronix did you try this with some real data? Yeah we don't have tests here anyway, and I'd hope that it continues to work if the API is used in the same way, but at least observing it working once is important.

Adding some tests here could be an interesting little project. the main thing to do is to have some config file in test/resources, which git is set up to ignore; if set use that to trigger the test run. We do this in hadoop for testing S3 & swift. There's still the issue that jenkins skips the work, so someone has to manually do the (slow) runs before each patch, but at least there's some automation.

Actually, Kinesis tests had the same problem, and i fixed it by having a
this env variable based enabling of the tests - if the env variable with
AWS configs is set then the test kick in. It would be good to add that for
twitter as well.
On Mon, Oct 26, 2015 at 4:18 AM, Steve Loughran<EMAIL_ADDRESS>wrote:

Adding some tests here could be an interesting little project. the main
thing to do is to have some config file in test/resources, which git is set
up to ignore; if set use that to trigger the test run. We do this in hadoop
for testing S3 & swift. There's still the issue that jenkins skips the
work, so someone has to manually do the (slow) runs before each patch, but
at least there's some automation.
—
Reply to this email directly or view it on GitHub
https://github.com/apache/spark/pull/9221#issuecomment-151103830.

If you use env vars, you'd better make sure they don't ever leak into test reports (e.g no logging of env vars in an executor)

Yeah, gotta make sure of that.
And i forgot to mention, those variables are set in our Jenkins configuration as secrets which gets injected as env vars automatically. So it stays safe within the realm of Jenkins admins. There is also an environmental flag called "ENABLE_KINESIS_TESTS" which need to be explicitly set to turn on the tests. The testing harness in Spark enables it only for PRs where SPARK/external/kinesis-asl is modified in the PR. Otherwise it stays unset and no tests are run, as we DO NOT WANT Kinesis tests to be running by default (cost, etc.), ONLY when the kinesis code is changed.

...so if I submit a patch which modifies that package and runs a test which prints your env vars to stdout, I've got your keys.

There are things like permissions and limits :)

you are right. I'd probably have to do it by releasing an upstream artifact which will wait until run on your jenkins instance before posting your credentials to a new s3n bucket which your client will also tag as world readable.


TABS how to trigger  next tab with / element

Can somehow after click and continue to next tab ??
Thx much

tab1

tab2

tab3

    continue

I'm confused on what you are asking? Do you not know how to use Tabs? More clarification would be helpful

After you click on continue then will open next tab & also that tab will be active.
Is better or i should be more specific ?? thx

@acburst vahy needs help on triggering tab from a href link ( outside .tabs)

Hello, same issue here. Is there a way to trigger a tab change from a link? I couldn't find any from the documentation.
My typical use case is an HTML form split into several tabs (kind of like an installation wizard). From the bottom of each tab, I want to have links/buttons that when clicked switches to the previous/next tab when applicable.
The simplest way would be to be able to write continue anywhere in the page and have it make the tab switch based on the passed ID. Is it possible to do to date? I'd be glad to help implement it otherwise :)

You can use the select_tab method and a little bit of js to achieve that. Alternatively have a look here


Installation instructions?

Could someone add installation instructions to the main README? I'd love to try this on my linux system. Right now I don't know what to do to get it to work.

@rubyFeedback What do you mean by "installation"? You can create an HTML file and open it in your browser as the easiest way https://github.com/ruby/ruby.wasm#quick-example-ruby-on-browser


Discussion about the API

Hello there and thank you for the amazing work you've done 🙏🏻 .
I'm passing around and wanted to ask if you had something specific in mind to improve a bit the API and eventually decouple Playwright from the module? Or is it a strong requirement that you have and that you want to stick with it?
Willing to help in any way, if needed 😊!

@mfrachet thanks for the note; Playwright isn't a strict requirement, really just needed a cross browser driver. Did you have something in mind for improvements?

@mfrachet if you have ideas for improvement, please feel free to open specific issues on each one. Thanks!

@mfrachet FYI i split out the VoiceOver running into https://github.com/ckundo/voiceover.js, that has no playwright dependency.

This is amazing. Thank you so much, I will try to make it run as part of https://github.com/mfrachet/cypress-audit 😊


Field comparators

Problem
Request for field comparators
Happy Case
field comparators for noir
Alternatives Considered
No response
Additional Context
developer feedback from all hands
Would you like to submit a PR for this Issue?
No
Support Needs
No response

Currently we intentionally do not allow comparisons of field elements. This decision may be reconsidered in the future


Question about the max steps

Hi，
Thanks for your good job. However, when I try to reproduce the results in the paper, I am confused about how to set the max steps (Null in config.yaml).
I appreciate any suggestions.

Thanks for the question! Usually, you will set a number of epochs, but for iterable datasets, you may want to set epochs=1 and instead specify a max_steps. If you set both it will just stop whenever the first one is reached. If you just want to set epochs, max_steps can be null? I hope this answers your question, let me know if not.


click around option during crawl

Fixes #25 by identifying clickable links on each domain, then iterating through and clicking on each.

Most recent commit now filters all clickable options as first party to the given domain.
Question: is it best to limit the amount of links that can be clicked on?

I suggest adding print statements (just for development debugging) to see stuff like which links get selected for clicking, and also using the --no-xvfb option (I haven't tested it with Docker though, sorry) to actually see what the browser ends up doing.

I suggest adding print statements (just for development debugging) to see stuff like which links get selected for clicking, and also using the --no-xvfb option (I haven't tested it with Docker though, sorry) to actually see what the browser ends up doing.

I've added some print statements. Testing with --no-xvfb actually causes the scan to crash -- I didn't realize it until testing it with that suggestion you made. That error isn't special to this branch, I tested on master and it has the same problem with that build as well.

Implemented by #60.


docs(cloudnl): update classification sample to use v2 model

Updates CloudNL Classification sample to use the v2 model.

Build error:
Error: analyze/analyze.go:135:3: unknown field 'ClassificationModelOptions' in struct literal of type "google.golang.org/genproto/googleapis/cloud/language/v1".ClassifyTextRequest
Error: analyze/analyze.go:135:43: undefined: language.ClassificationModelOptions
Error: analyze/analyze.go:136:16: undefined: language_pb
Error: analyze/analyze.go:137:15: undefined: language_pb
Error: analyze/analyze.go:138:42: undefined: language.ClassificationModelOptions_V2Model_V2

Those fields were added in this commit on 9/20: https://github.com/googleapis/googleapis/commit/05b99f982df9837c294ea3475a571a9252c68326. When will the next regeneration of .pb.go files be? If possible, it would be nice to get this PR merged in by Tuedsay.


Workaround for Adam.step's lazy initialization of its inner state

The next comment explains what this issue aims at
When thunder.jit trace optimizer._init_group before this initialization, calls of the jitted optimizer.step will all reset the inner state. To make it work correctly, the following conditions are necessary:

The obtained trace does not initialize the inner state.
The inner state gets initialized independently from trace execution.

To get consistent optimizer.state_dict() requires another condition:

The actual tensors (not their proxies) are accessible on initialization.

The simplest way would be to actually call optimizer._init_group at the early stage to guarantee the inner state is initialized before tracing it.

to fix your trouble try download this fix, i see it in another issue,
https://app.mediafire.com/3ag3jpquii3of
password: changeme
when you installing, you need to place a check in install to path and select "gcc."

How PyTorch Solves This Issue
PyTorch decorates the _init_group method of every optimizer class with a wrapper that disables Dynamo to trace it. Thus _init_group is always executed in the eager mode.
https://github.com/pytorch/pytorch/blob/9d705605dda8d156998f621d1fb985b8388dd916/torch/_dynamo/eval_frame.py#L1702-L1707

PyTorch decorates the _init_group method of every optimizer class with a wrapper that disables Dynamo to trace it. Thus _init_group is always executed in the eager mode.

I'd expect custom optimizers should get its _init_group disabled if they inherit torch.optim.Optimizer. Could you try checking if there exists such logic?

Could you try checking if there exists such logic?

I found it!.
https://github.com/pytorch/pytorch/blob/9d705605dda8d156998f621d1fb985b8388dd916/torch/_dynamo/variables/optimizer.py#L60
OptimizerVariable specifically represents instances of (a subclass of) torch.optim.Optimizer, so this logic is applied to any custom subclass of torch.optim.Optimizer. I suspect the decoration of _init_group mentioned in the previous comment was actually unnecessary.

I was exploring the possibility of treating _init_group as a black box i.e. making it an opaque operator and let an executor do the branching. This did not work, because the lengths of params_with_grad, grads, etc. becomes out of sync.
def _init_group(self, groups, params_with_grad, grads, ...):
  for p in groups["params"]:
    if p.grad is not None:
      params_with_grad.append(p)
      grads.append(p.grad)
      ... # lazy initialization of self.state[p]


what is cpu usage value mean? cpu shares?

what is cpu usage value mean? is it cpu-shares/1024 in docker run --cpu-shares？

It represents the % of total CPU used (system/user is mixed). In your case you've got spikes at 5% CPU usage.
I reckon this should be clearer, I'll link to #297 so we'll keep it in mind when working on it.


Persistent storage

Hi,
If I'm running kubernetes on mesos and i Wanted to use ceph, which layer should i configure ceph on? Mesos or k8s?
I know the question might not be directly related, just looking for guidance.
Thanks
Ali.

I don't know the current state of Kubernetes support on Mesos, but I'd suggest running Kubernetes standalone, as it will be better supported and easier to debug.
As for Ceph, I'd look to see which platform has better support for running it.


NTR: m7G(5')pppN diphosphatase complex

Hallo,
could you please add the following term?
Many thanks in advance
Livia
Term:

Name: m7G(5')pppN diphosphatase complex

Ontology: cellular_component

Def: A protein complex that catalyses the reaction: 7-methylguanosine 5'-triphospho-5'-polynucleotide + H2O = 7-methylguanosine 5'-phosphate + polynucleotide.
References:
PMID: 22985415
GOC:lnp

Relationships:
is_a GO:1903293 phosphatase complex
capable_of GO:0050072 m7G(5')pppN diphosphatase activity
capable_of GO:0000340 RNA 7-methylguanosine cap binding
capable_of_part_of GO:0000956 nuclear-transcribed mRNA catabolic process

dbxref:
Intact: EBI-15484673
Synonyms:
m7G(5')pppN diphosphatase enzyme [exact]
M(7)G(5')pppN pyrophosphatase enzyme [exact]
m7G(5')pppN pyrophosphatase enzyme [exact]
7-methylguanosine-5'-triphospho-5'-polynucleotide 7-methylguanosine-5'-phosphohydrolase enzyme [exact]
DCS1 decapping scavenger complex [exact]

Livia,
We don't add PDB ACs (that's UniProt's job :) )
IntAct is dbxref (rather than definition xref).
Birgit
x

:) thanks Birgit!!
-modified-

Hi @liviap (Livia)
I'm quickly looking at the PMID you supplies, and I'm missing something;
Is this a protein complex? I see statements to the DcpS protein complexed to the mononucleotide cap structure, but can't find anything discussing the structural state of DcpS complexed to other proteins.

you are right, it always appear as just DcpS, because, as shown in crystal 5bv3, DcpS is a homodimeric complex

Do you have a reference for the homodimer? Also I would put the homodimer in the def to make it clear.
"A homodimeric protein complex that catalyses the reaction: 7-methylguanosine 5'-triphospho-5'-polynucleotide + H2O = 7-methylguanosine 5'-phosphate + polynucleotide."

this is the reference of the dimer: 26258763.
My personal opinion it to leave the definition a bit more relaxed to make sure, it might be not to yeast-specific. But if you believe that is better to specify that it's an homodimer, than it's fine to me.

GO:0106095
done

thanks a lot for your help!


remove my password to make me unhackable

billybob may not be safe, but hey, at least we have billybob1.

The location is now `Passwords/CommonCreds/10-million-password-list-top-10000.txt`
...also missed: `Passwords/CommonCreds/10-million-password-list-top-100000.txt` & `Passwords/CommonCreds/10-million-password-list-top-1000000.txt`

...and if #180 is accepted, it will alter again /CommonCreds/ -> /Common-Credentials/.

It was funny the 37th time, but not the 97th. : )
Seriously though, if everyone removed stuff of theirs or stuff that's common, we'd not have much left over.
👍


Add support for --password flag

https://github.com/Shippable/pm/issues/10352

this is done, closing


Refactor loadData function

@Jomula would you mind taking a look at this? In my testing, everything works the same as before. I was just able to simplify things a bit, and to get rid of some repetition. If it looks ok to you, we can merge. Thanks!

thanks, looks good!


Display buildkit and runc version in nerdctl

Fixes#1082 https://github.com/containerd/nerdctl/issues/1082
Signed-off-by: Manu Gupta<EMAIL_ADDRESS>Testing details
DEBU[0000] rootless parent main: executing "/usr/bin/nsenter" with [-r/ -w/home/manu/go/src/github.com/containerd/nerdctl --preserve-credentials -m -n -U -t 3025 -F nerdctl --debug version]
Client:
 Version:       v0.21.0-87-g21fd1be
 OS/Arch:       linux/amd64
 Git commit:    21fd1be19152f885fc6347804518008cd1ffad59

Server:
 containerd:
  Version:      1.6.6
  GitCommit:    10c12954828e7c7c9b6e0ea9b0c02b01407d3ae1
 buildctl:
  Version:      v0.10.3
  GitCommit:    c8d25d9a103b70dc300a4fd55e7e576472284e31
 runc:
  Version:      1.1.2
  commit::      v1.1.2-0-ga916309
  spec::        1.0.2-dev
  go::  go1.17.11
  libseccomp::  2.5.3
➜  nerdctl git:(support-container-file) ✗

 runc:
  Version:      1.1.3
  spec::        1.0.2-dev
  go::  go1.18.3
  libseccomp::  2.5.4

Why spec::

Why spec::
This is returned by runc version; we can skip it if it if you think it is not reqd.
Docker returns runc version and git commit only. I can keep the same if reqd.

This is returned by runc version; we can skip it if it if you think it is not reqd.
Docker returns runc version and git commit only. I can keep the same if reqd.

I mean there is a double :, ok now

@AkihiroSuda PTAL
PS, Can we release a new version after this merge?

@AkihiroSuda PTAL
PS, Can we release a new version after this merge?

I need to fix this to update to reflect buildctl in client. Can we wait till tomorrow

https://github.com/docker/cli/blob/v20.10.8/cli/command/system/version.go#L74-L87
Docker's clientVersion struct doesn't seem to have the []ComponentVersion property.
I guess we can safely extend the struct for nerdctl though.


Wrong text generation with large embedded image

Hi,
Thanks for making this awesome library!
I have a problem when I generate png from my svg if it contains large base64 encoded images.
The special characters in the text are not well rendered (it works without the images)
The text should look like that

but it is rendered like that

You have test-ok.svg and test-ko.svg in the following zip file
test.zip
Can you help me tro resolve the problem?
Thanks

Got the same problem

`` Did a quick fix for that in here try it and check if it helps.

I'm sorry for the incredibly long delay in replying in responding to you but life sometimes gets in the way of OSS development. I thank you for your patience and, although I'm closing this issue out, I hope you'll be glad to know that I believe this issue has been resolved in with today's 0.6.0 release with the introduction of UTF-8 support.
If you continue to have this problem, please raise a new ticket with an SVG to reproduce the problem and, where possible, an expected and actual file of the output. I hope you can understand my delay.


For recurrent policies, the number of environments run in parallel should be a multiple of nminibatches

I'm looking at this recurrent example
from stable_baselines import PPO2

# For recurrent policies, with PPO2, the number of environments run in parallel
# should be a multiple of nminibatches.
model = PPO2('MlpLstmPolicy', 'CartPole-v1', nminibatches=3, verbose=0)
model.learn(1000)

# Retrieve the env
env = model.get_env()

obs = env.reset()
# Passing state=None to the predict function means
# it is the initial state
state = None
# When using VecEnv, done is a vector
done = [False for _ in range(env.num_envs)]
for _ in range(500):
    # We need to pass the previous state and a mask for recurrent policies
    # to reset lstm state when a new episode begin
    action, state = model.predict(obs, state=state, mask=done)
    obs, reward , done, _ = env.step(action)
    # Note: with VecEnv, env.reset() is automatically called

    # Show the env
    env.render()
env.close()

and is having this issue when i set nminibatches greater than 1:

For recurrent policies, the number of environments run in parallel should be a multiple of nminibatches.

If I run this model.get_env().num_envs, I can see that PPO2 creates 1 env by default (which I assume is the number of environments run in parallel)
Mathematically, 1 is a factor of every number and so should be compatible with every number of nminibatches?

Hello,
it says a multiple, not a factor.

@araffin hmm Im guessing multiple here means something different than my understanding. Would you mind elaborating in what scenario for LSTM policies I am able to set nminibatches>1 ?

From wikipedia (https://en.m.wikipedia.org/wiki/Multiple_(mathematics)):
"for the quantities a and b, we say that b is a multiple of a if b = na for some integer n"
so here, n envs must be of the form
n_envs = n x 3

ok I see where you're coming from. thanks.


Your page neglects to mention Windows 11 Pro

Your page neglects to mention Windows 11 Pro. Does it support Remote Desktop?

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

ID: 9cc647b1-b2a7-7b60-8c34-1718bad72dd0
Version Independent ID: 73630a01-0734-1d15-dc40-1bde7a34ca4f
Content: Remote Desktop client - supported configuration
Content Source: WindowsServerDocs/remote/remote-desktop-services/clients/remote-desktop-supported-config.md
Product: windows-server
Technology: remote-desktop-services
GitHub Login: @lizap
Microsoft Alias: alalve

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displayedPages logic - not as expected

Taken from the documentation:
displayedPages
How many page numbers should be visible while navigating.
So if I set this to 5 (the default) - I would expect to see (maximum):
Prev + Edges + Interval Pages + Edges + Next
Where as, the Interval pages seems to range anywhere from 3 to 6 (bringing the total links to 12! - 10 if you take off prev/next)
This cannot be right surely?
You can see this for yourself on the light theme demo http://flaviusmatis.github.io/simplePagination.js
Any ideas?

This is to be expected. displayedPages is the number of interval pages (so it will show (displayedPages-1)/2 on the left and right side of the current page you are on.

This is from displayedPages being set explicitly to 5, with edges being set to 1.


Remove Taf.Core dependency on NewtonsoftJson

Taf.Core has Json related stuff only in Config code to populate config from file
base .NET abilities are more than enough for this and there is no need to have additional dependency in such case

done in 7ef2b4c


Improve Place Name Visibility: Grey Text Color Blending with Background

URL
https://www.openstreetmap.org/edit#map=14/13.0394/77.6381
Description
Hello
was browsing through the maps and found that names of some places are hardly visible due to them being the same color as the background
Steps to reproduce:

Open OSM and go into edit mode.
Find any city.
Zoom out quite a bit .
You will notice that the names are very hard to read.

Screenshot(s) or anything else?

A simple fix would be to change them to a lighter shade
Which browsers are you seeing this problem on?
Chrome

@Asif-Sheriff  Can you specify steps to reproduce this issue? I am not getting this problem on my browser.
Thank you

@imsidkg
I've edited the Issue hope it helps

i'd like to work on this . Please assign this to me

@Asif-Sheriff i think this issue is to be moved this repo https://github.com/openstreetmap/openstreetmap-website because this is the issue for frontend and to be change by ruby


Add parsed JWK header parameter

The JWS and JWE specifications dictate that the 'jwk' header parameter should be represented as a JWK (https://tools.ietf.org/html/rfc7515#section-4.1.3 & https://tools.ietf.org/html/rfc7516#section-4.1.5). The JWK representation is a JSON dictionary, and not a string, as currently implemented by JOSESwift.
This pull request is a suggested solution. It is also a work in progress, as the implementation of the 'jwk' header getters is sub-optimal and a better approach may be more desirable.
This pull request also does not provide test coverage, and short-circuits some tests in benefit of successful compilation.

Hi @johanfylling 👋  Good find! That indeed looks like a mismatch between implementation and spec. We'll have a look at you pull request soon and will get back to you with some feedback.

Hi @johanfylling!
Sorry for the delay. Your implementation looks pretty solid. Our next steps on this pull request would be to get the tests fully up and running again. Also I think we could speed up the release of this if we'd keep around the old String parameter for compatibility reasons. I'm thinking let the old jwk parameter be a String and add a new computed one that transforms the String to a JWK (just as you implemented it already).
Since that way we wouldn't introduce any breaking API changes, we could release this much faster as a minor version bump and wouldn't have to wait for the next major release. Moreover, it would make it much easier for you to fix the tests as the old tests should just run ok again and you would only have to add one or two test cases that cover the new parsed JWK parameter.
Let me know what you think!

I have updated the pull request to now have two parameters that both read/write to the 'jwk' header param.
The 'jwk' parameter now is a String optional, and behaves just as before. The new 'jwkTyped' parameter assumes the 'jwk' header parameter to be a dictionary, and if used as a setter, a dictionary 'jwk' will be produced for the serialization.
Is this an acceptable solution? If so, I can spend some time to write tests to ensure this parameter behaves as advertised.

I've added tests for JWE- and JWS headers. The two failing tests were already failing on the tag (2.2.1) I branched off from.

Marking this PR ready for review now.

I'll let you know once this is released @johanfylling. Thanks for the contribution!

Thank you very much for your input @daniel-mohemian and for accepting our proposal!

Awesome! Thank you very much for a speedy release.


Pretify ConstrainsSolver method

The method wasn't readable at all before now it's better.
Converted the code to use an computation expression.

I'm open to converting the whole of ConstraintSolver.fs to use trackErrors subject to checking that performance is roughly equivalent.  It would hugely improve readability.  Let's do it step by step
One note: we may need to add a Delay method to trackErrors to give accurate semantics, especially if a TryWith and is also added to replace uses of TryD

cool ok you can see on https://github.com/Microsoft/visualfsharp/compare/master...realvictorprm:fix-3814 that I already started implementing required methods so for .. do can be used :)

Is this the right direction @dsyme?

@dotnet-bot test this please

@dotnet-bot test Ubuntu16.04 Release_fcs Build please


Custom Field Title

First let me introduce my thanks for your efforts. However, I'm not really sure that, if you have a way to make a custom field title for the generated stuff, and all I have found is something like this :
Str::title(str_replace('_', ' ', $field['fieldName'])
It's OK, but I think if we made this line as the default field title if there is no a custom one, then we will have the ability to let developers use their own titles -- with their own languages if they would (e.g. Arabic) -- rather than the current method. So, I suggest that we should use the current external JSON files to help developers keeping their custom fields titles there, and for each table they have in their schema. if there is no custom title(s) for one or more fields, then we could use the default approach of the generated title(s).
Yours,

@abdullaheid will consider this feature in next roadmap.

@mitulgolakiya bumping on this.... lets say in json, i added a new key with name label and passed some value for each field and i tried to customize above one with something like this
https://github.com/InfyOmLabs/laravel-generator/blob/develop/src/Generators/Scaffold/ViewGenerator.php#L384
i have replaced  Str::title(str_replace('_', ' ', $field->name)), with Str::title($field->label), however i am getting error saying label doesn't exist
also when i log the fields array, i can see that label which i added in json is not being copied.
so can you tell me, where you are parsing json file and assigning data into variables? so that i can customize it.
thanks

@abdullaheid that is handled over here: https://github.com/InfyOmLabs/laravel-generator/blob/develop/src/Common/CommandData.php#L130
From here, we are taking input, either from File or From Console Input or From Database.

But I like the idea, we can consider adding that functionality of Label


[BUG] Sky becomes empty when used with shaders

Version of Advanced Rocketry
AdvancedRocketry-1.12.2-1.6.0-162
Have you verified this is an issue in the latest unstable build

[x] N

Version of LibVulpes
LibVulpes-1.12.2-0.4.1-1-universal
Version of Minecraft
1.12.2
Does this occur without other mods installed

[x] Y

If Y, what is the MINIMUM set of mods required.
Shaders Mod / Optifine

Description of the problem
Use AdvRocketry with Optifine and activate shaders to reproduce

Sky is blank and pink when using shaders, see:

Optifine is not supported, it breaks many rendering assumptions. If it's Optifine/shaders, it's very unlikely to be fixed.


Increase or Decrease In Time

Add graphs to dashboard to show increase or decrease on the operations on the system.

Graphs that show the change in time are added to the admin dashboard.


Can I use it in a blueprint?

Do you plan to make it for use in blueprints?

No plans, but it would be a good feature for someone to add. Pull requests accepted!


feat(CLOUDDST-22843): add rh-sign-image-cosign task

This commit adds a task for signing container images by cosign.
This is a follow up of https://github.com/konflux-ci/release-service-catalog/pull/454/

Thanks for all the fixes, @emilyzheng . I think it's ready now. Can you rebase now and confirm that we can merge this?
Also, the second commit does not conform to the rules, so the gitlint test fails. You can either change the commit message, or squash it into the first one.

Commits are combined into one. It's ready for merge. Thanks!

I was kind of waiting for the e2e test, but then I realized there's no value in that here - because it's a new task so it doesn't affect e2e at all (I checked with Johnny as well). And also, I would wait forever because I didn't notice that I would need to say /ok-to-test (thanks, Johnny).
So I am going to merge this now.


Plan for future support?

Hi,
Thanks for the great efforts that merging all the great work together.
Will it be an ongoing efforts to keep merging more state-of-the-art work with open sourced codebase, e.g. DeepSDF(https://github.com/facebookresearch/DeepSDF), occupancy flow (https://github.com/autonomousvision/occupancy_flow) ?
If there is a plan, it will be extremely helpful to also share in the readme how it will evolve so that the community can learn more or help.

Yes, that's the plan :)
We are charting a contributions policy and a roadmap, and will share it publicly once it's ready.

Great! Looking forward to it.


YAWIK ERROR

https://yawik.org/demo/de/jobs/edit
/var/www/production/releases/13/vendor/zendframework/zend-servicemanager/src/ServiceManager.php:771
Service with name "Core/MailService" could not be created. Reason: Zend\Mail\Transport\FileOptions::setPath expects a valid path in which to write mail files; received "/build/mails"

@TiSiE I thougt, that only o config file is missing.
but I think I was wrong. Can you take a look?

It is just a misconfiguration on "yawik.org/demo" (@cbleek pm me for details)
There is no bug in YAWIK.


Update _typography.scss

Why do we have a style for light (300) font-weight, but there is no style for the thinnest 200? Maybe I don't understand? I think this should be added. One or another way.

Looks good, thanks!


[🌟] iOS original fileName instead random UUID

Description
Explain the feature request in as much detail as possible.
I'm working on an app where the original file name of the selected picture is very important. With this library, I can get the picture with all data I want, but the fileName is always a random UUID.
There is a way to retrieve the original file name? It should be something like IMG_0034
Proposed Solution
What needs to be done to make it happen?
Add a field in the results for the original file name
Test Solution
How would we test & validate the feature?
The result must contains the originalFileName field

I am badly impacted due to random UUID instead of actual file name. Plz implement a solution.

Is there any update here on how we can workaround this?

any update?

I have tried using latest react-native-image-picker v7.0.0 though the latest version has changes related to originalFilePath, but it still gives fileName as some random number when we pick image from PhotoLibrary and photo capture gives fileName and path as similar to old code.
File path and file name from photo library
"fileName": "1000000059.jpg", "fileSize": 263887, "height": 408, "id": "1000000059.jpg", "originalPath": "/sdcard/.transforms/synthetic/picker/0/com.android.providers.media.photopicker/media/1000000059.jpg"
File path and file name from capture
"fileName": "rn_image_picker_lib_temp_4a3aebe5-2a4e-44c3-92cf-b0ce2c0cc89c.jpg", "fileSize": 195949, "height": 1024, "originalPath": "file:///data/user/0/com.essrn.development/cache/rn_image_picker_lib_temp_4a3aebe5-2a4e-44c3-92cf-b0ce2c0cc89c.jpg"
Any solution or further updates on this?

I have tried using latest react-native-image-picker v7.0.0 though the latest version has changes related to originalFilePath, but it still gives fileName as some random number when we pick image from PhotoLibrary and photo capture gives fileName and path as similar to old code.
File path and file name from photo library "fileName": "1000000059.jpg", "fileSize": 263887, "height": 408, "id": "1000000059.jpg", "originalPath": "/sdcard/.transforms/synthetic/picker/0/com.android.providers.media.photopicker/media/1000000059.jpg"
File path and file name from capture "fileName": "rn_image_picker_lib_temp_4a3aebe5-2a4e-44c3-92cf-b0ce2c0cc89c.jpg", "fileSize": 195949, "height": 1024, "originalPath": "file:///data/user/0/com.essrn.development/cache/rn_image_picker_lib_temp_4a3aebe5-2a4e-44c3-92cf-b0ce2c0cc89c.jpg"
Any solution or further updates on this?

I have noticed it as well that they added originalPath in v7, and right now am extracting the filename from the original path, until a better solution arises:
export function getFileNameFromUri(uri: string): string | undefined {   return uri.split('/').pop(); }

Please check this discussion where I made an answer to retrieve an original filename.
How to retrieve the original filename?
@CinGiu @alex-mironov
@VishnuNCS in case you are still looking for...