Added marker in streetview is now shown.

The code below is taken from the Google Maps sample. https://jsfiddle.net/api/post/library/pure/
Maybe someone can help me spot the issue. Thanks
onMounted(() => {
setTimeout(() => {
if (mapRef.value.ready) {
// const panorama = mapRef.value.api.StreetViewPanorama;
const panorama = mapRef.value.map.getStreetView();
      const cafeMarker = new mapRef.value.api.Marker({
        position: { lat: 53.48161, lng: -2.24212 },
        panorama,
        icon: "https://chart.apis.google.com/chart?chst=d_map_pin_icon&chld=cafe|FFFF00",
        title: "Cafe",
      });

      console.log('cafeMarker', cafeMarker);

      panorama.setPosition(centerPosition.value);
      panorama.setPov(
        /** @type {google.maps.StreetViewPov} */ {
          heading: 265,
          pitch: 0,
        });
    }
  }, 2000);
});

You manually created the marker but never assigned it to the map, try passing the map instance to the marker like in the first code of https://developers.google.com/maps/documentation/javascript/adding-a-google-map.


Add missing options for the spam filter

Add missing options for the spam filter: 'blockedCountries', 'classifier', 'disableRules', 'text'
=> that resolves the issue https://github.com/altcha-org/altcha/issues/45

Merged with small changes in types.


[atip] Improve steps for switch app

Impacted TCs num(approved): New 0, Update 1, Delete 0
Unit test Platform: Crosswalk Project for Android 16.45.421.0
Unit test result summary: Pass 1, Fail 0, Blocked 0

LGTM


Loading shielded context takes too long time on SE

Too long for load block to shielded context and scaning. In SE have more than 120k block. It take maybe 3 - 4 days for fetching block and whenever rpc is or some thing is failed, it make function break. And we need load shielded context again.

Take a long time to shieled sync. Who one need use shieled action.

Duplicate of #662


Fixed robotClass scheme

The default value of robotClass did not have the robot package before
the Robot class.

I don't think this necessarily warrants a change. 99% of cases are going to change the package address anyway, and there's no standard that says it has to use the robot package

@JacisNonsense I understand if you don't want to pull for such a small contribution, but I do think that this is a good change. By default, all classes are in the .robot package. I don't know any teams who change that package around. Seeing as this is in the quickstart folder, it makes sense to leave it as the default location where all the WPI templates place the main Robot class.  I think if there is going to be a default value there at all, it should be where those classes are located by default. I totally understand if you want to keep contributers to people who actually did the bulk of the work, but I do think that someone should make the change. Love this tool, thanks for helping my team ditch eclipse :)

That's a good point. I'll merge this and update the .zip later


Change roleBinding type (reduce scope of query to namespace)

Signed-off-by: Joshua Packer<EMAIL_ADDRESS>
The get is for the incorrect ClusterRoleBinding type, which is showing an error message and trying to create a duplicate resource.  This doesn't cause a real failure today because we absorb the create error. The code should not be trying to create the roleBinding each time.
Added a log message for a problem QE was seeing when the APIVersion was incorrect. Currently there is no error message
Even though the ClusterRole is changed to a Role, the serviceAccount already has access (we create a RoleBinding in the next step)

Issue Reference: https://github.com/open-cluster-management/backlog/issues/16627


Python Yara.Rules API not working with pid parameter

Test code:
import psutil
import yara

rule = r"""
rule dummy
{
    condition:
       false
}
"""

compiled_rule = yara.compile(source=rule)

def psutil_get_pids():
    for proc in psutil.process_iter():
        yield proc.pid

for p in psutil_get_pids():
    print(compiled_rule.match(pid = p))

Test return:
Traceback (most recent call last):
  File "test.py", line 19, in <module>
    print(compiled_rule.match(pid=p))
TypeError: match() takes at least one argument

Environment:
yara-python 4.0.5
python 3.7.9
Windows 10 Pro 19042.928
Visual Studio Code

The match function was not able to distinguish between receiving pid=0 and receiving not argument at all.


Scrape method to allow arrow functions

This is a syntactic sugar for allowing the use of arrow functions for browsers or environments that allow it. I pass the element context in the method function as the second parameter, exposing it in addition to this. It is a backward compatible change.
artoo.scrape('tr tr:has(td.title:has(a)):not(:last)', {
  domain: {
    sel: '.comhead',
    method: ($, el) => $(el).text().trim().replace(/[\(\)]/g, '')
  }
});

Additionally I had to bump the travis build to use more modern node version to get the build passing. I can split that out into a separate pull request if you like.

That seems to be a good addition indeed. Can you just tell me what's breaking the Travis build on earlier node version please?

Sure, the build is here https://travis-ci.org/medialab/artoo/builds/286842529
/home/travis/build/medialab/artoo/node_modules/run-sequence/node_modules/chalk/index.js:2
const escapeStringRegexp = require('escape-string-regexp');
^^^^^
SyntaxError: Use of const in strict mode.

It was using
$ node --version
v0.10.48

Thanks @jbryson3. Will merge now. Will release a public update soon after fixing some things with the ajaxSniffer.

Just released v0.4.0 with your addition.


ScrollPosition does not notify listeners after applyContentDimensions

Steps to Reproduce
Internal Bug: b/173247635
Minimal Reproduction (Reproduces in DartPad):
import 'package:flutter/material.dart';

void main() {
  var poof = false;
  var scrollController = ScrollController();
  scrollController.addListener(() {
    print('Scroll Controller Updated');
    if (scrollController.hasClients) {
      final pos = scrollController.position;
      pos.addListener(() {
        print('Scroll Position Updated: $pos');
      });
    }
  });
  runApp(MaterialApp(
    home: Scaffold(
      appBar: AppBar(),
      body: ListView(
        controller: scrollController,
        children: [
          const SizedBox(height: 1000.0, child: Placeholder()),
          StatefulBuilder(
            builder: (context, setState) {
              return InkWell(
                onTap: () => setState(() => poof = true),
                child: poof
                    ? const SizedBox()
                    : const SizedBox(height: 1000.0, child: Placeholder()),
              );
            },
          )
        ],
      ),
    ),
  ));
}

Expected results: Scrolling down and clicking the second placeholder should print a ScrollPosition with a pixel offset of zero in the log.
Actual results: No notification is dispatched when this happens, only a visible change.
It seems that applyContentDimensions ends up calling correctBy, but the documentation on correctBy suggests that its up to the caller to notify listeners. In this case, the listeners are not notified, but the scroll offset changes.

Hi, @ds84182 , your question maybe the same issue as https://github.com/flutter/flutter/issues/67690, hope helpful ^-^

Yeah, seems related. Worthy to note that this also  breaks TrackingScrollController, which is part of Flutter itself.

flutter doctor -v
[✓] Flutter (Channel master, 1.25.0-5.0.pre.45, on Mac OS X 10.15.7 19H2 darwin-x64, locale en)
    • Flutter version 1.25.0-5.0.pre.45 at /Users/pedromassango/dev/SDKs/flutter_master
    • Framework revision 81e1f7d1ed (12 hours ago), 2020-12-02 17:19:57 -0800
    • Engine revision 20caf54969
    • Dart version 2.12.0 (build 2.12.0-76.0.dev)

[✓] Android toolchain - develop for Android devices (Android SDK version 30.0.2)
    • Android SDK at /Users/pedromassango/Library/Android/sdk
    • Platform android-30, build-tools 30.0.2
    • Java binary at: /Applications/Android Studio.app/Contents/jre/jdk/Contents/Home/bin/java
    • Java version OpenJDK Runtime Environment (build 1.8.0_242-release-1644-b3-6915495)
    • All Android licenses accepted.

[✓] Xcode - develop for iOS and macOS (Xcode 12.1)
    • Xcode at /Applications/Xcode.app/Contents/Developer
    • Xcode 12.1, Build version 12A7403
    • CocoaPods version 1.9.3

[✓] Chrome - develop for the web
    • Chrome at /Applications/Google Chrome.app/Contents/MacOS/Google Chrome

[✓] Android Studio (version 4.1)
    • Android Studio at /Applications/Android Studio.app/Contents
    • Flutter plugin can be installed from:
      🔨 https://plugins.jetbrains.com/plugin/9212-flutter
    • Dart plugin can be installed from:
      🔨 https://plugins.jetbrains.com/plugin/6351-dart
    • Java version OpenJDK Runtime Environment (build 1.8.0_242-release-1644-b3-6915495)

[✓] IntelliJ IDEA Community Edition (version 2020.2.3)
    • IntelliJ at /Applications/IntelliJ IDEA CE.app
    • Flutter plugin version 51.0.3
    • Dart plugin version 202.8070

[✓] VS Code (version 1.51.1)
    • VS Code at /Applications/Visual Studio Code.app/Contents
    • Flutter extension version 3.16.0

[✓] Connected device (3 available)
    • macOS (desktop)  • macos      • darwin-x64     • Mac OS X 10.15.7 19H2 darwin-x64
    • Web Server (web) • web-server • web-javascript • Flutter Tools
    • Chrome (web)     • chrome     • web-javascript • Google Chrome 86.0.4240.198

• No issues found!
Process finished with exit code 0

Why ScrollController's listener doesn't fire when scrollController.position.hasPixels or scrollController.position.hasContentDimensions changes from false to true?

@Piinks We may have fixed this, do you know?

This has been fixed with ScrollMetricsNotification. In the OP, the dimensions of the scroll view change without any scrolling. A normal scroll notification relates to the user interacting with it. Separately, changing the scroll view without interacting directly with the scroll view can be listened to using a ScrollMetricsNotification.
I have updated the original code to demonstrate:
import 'package:flutter/material.dart';

void main() {
  var poof = false;
  var scrollController = ScrollController();
  scrollController.addListener(() {
    print('Scroll Controller Updated');
    if (scrollController.hasClients) {
      final pos = scrollController.position;
      pos.addListener(() {
        print('Scroll Position Updated: $pos');
      });
    }
  });
  runApp(MaterialApp(
    home: Scaffold(
      appBar: AppBar(),
      body: NotificationListener<ScrollMetricsNotification>(
        onNotification: (notification) {
          print('Updated!');
          return false;
        },
        child: ListView(
          controller: scrollController,
          children: [
            const SizedBox(height: 1000.0, child: Placeholder()),
            StatefulBuilder(
              builder: (context, setState) {
                return InkWell(
                  onTap: () => setState(() => poof = true),
                  child: poof
                      ? const SizedBox()
                      : const SizedBox(height: 1000.0, child: Placeholder()),
                );
              },
            )
          ],
        ),
      ),
    ),
  ));
}


Training with different image size

❓ Questions and Help
Hi all,
I have changed the input image size (2560x2048) of config file to train with high quality masks, as i want them to be as good as possible. The training seemed fine but when testing on same image size  i got really bad detections (few of expected and confidence threshold really low) output following inference tutorial. Should i have changed more parameters on config file apart from INPUT: MAX_SIZE_TRAIN: 2560 MIN_SIZE_TRAIN: 2048   MAX_SIZE_TEST: 2560  MIN_SIZE_TEST: 2048?  Here's my training config. Test config is the same but changing WEIGHTS for model i want to test and adding TEST's size.
Thanks a lot for you're help!!
2019-05-24 14:24:05,621 maskrcnn_benchmark INFO: Using 2 GPUs
2019-05-24 14:24:05,621 maskrcnn_benchmark INFO: Namespace(config_file='/shared/configs/e2e_ms_rcnn_R_50_FPN_1x_from_scratch_HQ_images.yaml', distributed=True, local_rank=0, opts=[], skip_test=False)
2019-05-24 14:24:05,621 maskrcnn_benchmark INFO: Collecting env info (might take some time)
2019-05-24 14:24:07,236 maskrcnn_benchmark INFO:
PyTorch version: 1.1.0.dev20190516
Is debug build: No
CUDA used to build PyTorch: 9.0.176
OS: Ubuntu 16.04.6 LTS
GCC version: (Ubuntu 5.4.0-6ubuntu1~16.04.11) 5.4.0 20160609
CMake version: Could not collect
Python version: 3.7
Is CUDA available: Yes
CUDA runtime version: 9.0.176
GPU models and configuration:
GPU 0: GeForce GTX 1080
GPU 1: GeForce GTX 1080
Nvidia driver version: 384.130
cuDNN version: /usr/lib/x86_64-linux-gnu/libcudnn.so.7.5.0
Versions of relevant libraries:
[pip] numpy==1.16.3
[pip] torch==1.1.0.dev20190516
[pip] torchvision==0.2.1
[conda] blas                      1.0                         mkl
[conda] mkl                       2019.3                      199
[conda] mkl_fft                   1.0.12           py37ha843d7b_0
[conda] mkl_random                1.0.2            py37hd81dba3_0
[conda] pytorch-nightly           1.1.0.dev20190516 py3.7_cuda9.0.176_cudnn7.5.1_0    pytorch
[conda] torchvision               0.2.1                    pypi_0    pypi
Pillow (6.0.0)
2019-05-24 14:24:07,236 maskrcnn_benchmark INFO: Loaded configuration file /shared/configs/e2e_ms_rcnn_R_50_FPN_1x_from_scratch_HQ_images.yaml
2019-05-24 14:24:07,236 maskrcnn_benchmark INFO:
MODEL:
META_ARCHITECTURE: "GeneralizedRCNN"
WEIGHT: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl
#~ WEIGHT: "/shared/Pre-weights/R-50.pkl"
PRETRAINED_MODELS: 'pretrained_models'
BACKBONE:
CONV_BODY: "R-50-FPN"
OUT_CHANNELS: 256
RPN:
USE_FPN: True
ANCHOR_STRIDE: (4, 8, 16, 32, 64)
PRE_NMS_TOP_N_TRAIN: 2000
PRE_NMS_TOP_N_TEST: 1000
POST_NMS_TOP_N_TEST: 1000
FPN_POST_NMS_TOP_N_TRAIN: 1000
FPN_POST_NMS_TOP_N_TEST: 1000
ROI_HEADS:
USE_FPN: True
ROI_BOX_HEAD:
POOLER_RESOLUTION: 7
POOLER_SCALES: (0.25, 0.125, 0.0625, 0.03125)
POOLER_SAMPLING_RATIO: 2
FEATURE_EXTRACTOR: "FPN2MLPFeatureExtractor"
PREDICTOR: "FPNPredictor"
NUM_CLASSES: 3
ROI_MASK_HEAD:
POOLER_SCALES: (0.25, 0.125, 0.0625, 0.03125)
FEATURE_EXTRACTOR: "MaskRCNNFPNFeatureExtractor"
PREDICTOR: "MaskRCNNC4Predictor"
POOLER_RESOLUTION: 14
POOLER_SAMPLING_RATIO: 2
RESOLUTION: 28
SHARE_BOX_FEATURE_EXTRACTOR: False
MASK_ON: True
MASKIOU_ON: True
DATASETS:
TRAIN: ("D42-20_HR", "D42-19_HR", "D42-18_HR", "D42-17_HR", "D42-16_HR",)
TEST: ("D42-02-val",)
DATALOADER:
SIZE_DIVISIBILITY: 32
SOLVER:
BASE_LR: 0.005
IMS_PER_BATCH: 2
WEIGHT_DECAY: 0.0001
#~ STEPS: (60000, 80000)
STEPS: (10000, 20000)
#~ MAX_ITER: 90000
MAX_ITER: 29000 #20000 1 epoch
CHECKPOINT_PERIOD: 2500
TEST:
IMS_PER_BATCH: 1
INPUT:
MAX_SIZE_TRAIN: 2560
MIN_SIZE_TRAIN: 2048
OUTPUT_DIR: "/shared/Training/T-13_HQ"
2019-05-24 14:24:07,237 maskrcnn_benchmark INFO: Running with config:
DATALOADER:
ASPECT_RATIO_GROUPING: True
NUM_WORKERS: 4
SIZE_DIVISIBILITY: 32
DATASETS:
TEST: ('D42-02-val',)
TRAIN: ('D42-20_HR', 'D42-19_HR', 'D42-18_HR', 'D42-17_HR', 'D42-16_HR')
INPUT:
MAX_SIZE_TEST: 1333
MAX_SIZE_TRAIN: 2560
MIN_SIZE_TEST: 800
MIN_SIZE_TRAIN: 2048
PIXEL_MEAN: [102.9801, 115.9465, 122.7717]
PIXEL_STD: [1.0, 1.0, 1.0]
TO_BGR255: True
MODEL:
BACKBONE:
CONV_BODY: R-50-FPN
FREEZE_CONV_BODY_AT: 2
OUT_CHANNELS: 256
DEVICE: cuda
MASKIOU_LOSS_WEIGHT: 1.0
MASKIOU_ON: True
MASK_ON: True
META_ARCHITECTURE: GeneralizedRCNN
PRETRAINED_MODELS: pretrained_models
RESNETS:
NUM_GROUPS: 1
RES2_OUT_CHANNELS: 256
RES5_DILATION: 1
STEM_FUNC: StemWithFixedBatchNorm
STEM_OUT_CHANNELS: 64
STRIDE_IN_1X1: True
TRANS_FUNC: BottleneckWithFixedBatchNorm
WIDTH_PER_GROUP: 64
ROI_BOX_HEAD:
FEATURE_EXTRACTOR: FPN2MLPFeatureExtractor
MLP_HEAD_DIM: 1024
NUM_CLASSES: 3
POOLER_RESOLUTION: 7
POOLER_SAMPLING_RATIO: 2
POOLER_SCALES: (0.25, 0.125, 0.0625, 0.03125)
PREDICTOR: FPNPredictor
ROI_HEADS:
BATCH_SIZE_PER_IMAGE: 512
BBOX_REG_WEIGHTS: (10.0, 10.0, 5.0, 5.0)
BG_IOU_THRESHOLD: 0.5
DETECTIONS_PER_IMG: 100
FG_IOU_THRESHOLD: 0.5
NMS: 0.5
POSITIVE_FRACTION: 0.25
SCORE_THRESH: 0.05
USE_FPN: True
ROI_MASK_HEAD:
CONV_LAYERS: (256, 256, 256, 256)
FEATURE_EXTRACTOR: MaskRCNNFPNFeatureExtractor
MLP_HEAD_DIM: 1024
POOLER_RESOLUTION: 14
POOLER_SAMPLING_RATIO: 2
POOLER_SCALES: (0.25, 0.125, 0.0625, 0.03125)
POSTPROCESS_MASKS: False
POSTPROCESS_MASKS_THRESHOLD: 0.5
PREDICTOR: MaskRCNNC4Predictor
RESOLUTION: 28
SHARE_BOX_FEATURE_EXTRACTOR: False
RPN:
ANCHOR_SIZES: (32, 64, 128, 256, 512)
ANCHOR_STRIDE: (4, 8, 16, 32, 64)
ASPECT_RATIOS: (0.5, 1.0, 2.0)
BATCH_SIZE_PER_IMAGE: 256
BG_IOU_THRESHOLD: 0.3
FG_IOU_THRESHOLD: 0.7
FPN_POST_NMS_TOP_N_TEST: 1000
FPN_POST_NMS_TOP_N_TRAIN: 1000
MIN_SIZE: 0
NMS_THRESH: 0.7
POSITIVE_FRACTION: 0.5
POST_NMS_TOP_N_TEST: 1000
POST_NMS_TOP_N_TRAIN: 2000
PRE_NMS_TOP_N_TEST: 1000
PRE_NMS_TOP_N_TRAIN: 2000
RPN_HEAD: SingleConvRPNHead
STRADDLE_THRESH: 0
USE_FPN: True
RPN_ONLY: False
WEIGHT: https://dl.fbaipublicfiles.com/detectron/ImageNetPretrained/MSRA/R-50.pkl
OUTPUT_DIR: /shared/Training/T-13_HQ
PATHS_CATALOG: /home/maskscoring_rcnn/maskrcnn_benchmark/config/paths_catalog.py
SOLVER:
BASE_LR: 0.005
BIAS_LR_FACTOR: 2
CHECKPOINT_PERIOD: 2500
GAMMA: 0.1
IMS_PER_BATCH: 2
MAX_ITER: 29000
MOMENTUM: 0.9
STEPS: (10000, 20000)
WARMUP_FACTOR: 0.3333333333333333
WARMUP_ITERS: 500
WARMUP_METHOD: linear
WEIGHT_DECAY: 0.0001
WEIGHT_DECAY_BIAS: 0
TEST:
EXPECTED_RESULTS: []
EXPECTED_RESULTS_SIGMA_TOL: 4
IMS_PER_BATCH: 1

If I don't misunderstand your description ("following inference tutorial"), you used code in maskrcnn-benchmark/demo/predictor.py.
In old versions of this code, users should manually pass min_image_size to COCODemo() instead of just using MAX/MIN_SIZE_TEST in specified config to resize the input. So there could be the problem.
I will consider a recheck to whether you run inference with the latest copy of both predictor.py :)

Thanks for you're comment!
When creating the  COCODemo() instance, i'm actually passing the desired min image size, so i guess the problem might be somewhere else.
coco_demo = COCODemo(
cfg,
min_image_size=2048,
confidence_threshold=0.7,
)

How about the version of predictor.py? It does matter.
And, as another way to locate the problem, I recommend you to use print(image.shape)  after line 230 of predictor.py (https://github.com/facebookresearch/maskrcnn-benchmark/blob/master/demo/predictor.py#L230),  then check the shape to make sure the input of network is resized as expected.

I have just update my predictor.py version, so now should be up-to-date. I have also checked the image shape after transform is applied, and it is as expected:
torch.Size([3, 2048, 2560])
Still does not work as expected at all, don't know what might be wrong

You config has the following arguments:
MAX_SIZE_TEST: 1333
MAX_SIZE_TRAIN: 2560
MIN_SIZE_TEST: 800
MIN_SIZE_TRAIN: 2048

Check that you are indeed modifying the test size.

Sorry for not making it clear.
I am using another config file for inference, which is basically the same changing WEIGHTS for the ones i want to do inference with and defining correctly MAX_SIZE_TEST and MIN_SIZE_TEST.
Am I missing something else?
Thanks for you're repply!
MODEL:
META_ARCHITECTURE: "GeneralizedRCNN"
WEIGHT: /shared/Training/T-13_HQ/model_0020000.pth
PRETRAINED_MODELS: 'pretrained_models'
BACKBONE:
CONV_BODY: "R-50-FPN"
OUT_CHANNELS: 256
RPN:
USE_FPN: True
ANCHOR_STRIDE: (4, 8, 16, 32, 64)
PRE_NMS_TOP_N_TRAIN: 2000
PRE_NMS_TOP_N_TEST: 1000
POST_NMS_TOP_N_TEST: 1000
FPN_POST_NMS_TOP_N_TRAIN: 1000
FPN_POST_NMS_TOP_N_TEST: 1000
ROI_HEADS:
USE_FPN: True
ROI_BOX_HEAD:
POOLER_RESOLUTION: 7
POOLER_SCALES: (0.25, 0.125, 0.0625, 0.03125)
POOLER_SAMPLING_RATIO: 2
FEATURE_EXTRACTOR: "FPN2MLPFeatureExtractor"
PREDICTOR: "FPNPredictor"
NUM_CLASSES: 3
ROI_MASK_HEAD:
POOLER_SCALES: (0.25, 0.125, 0.0625, 0.03125)
FEATURE_EXTRACTOR: "MaskRCNNFPNFeatureExtractor"
PREDICTOR: "MaskRCNNC4Predictor"
POOLER_RESOLUTION: 14
POOLER_SAMPLING_RATIO: 2
RESOLUTION: 28
SHARE_BOX_FEATURE_EXTRACTOR: False
MASK_ON: True
MASKIOU_ON: True
DATASETS:
TRAIN: ("D42-20_HR", "D42-19_HR", "D42-18_HR", "D42-17_HR", "D42-16_HR",)
TEST: ("D42-02-val",)
DATALOADER:
SIZE_DIVISIBILITY: 32
SOLVER:
BASE_LR: 0.005
IMS_PER_BATCH: 2
WEIGHT_DECAY: 0.0001
#~ STEPS: (60000, 80000)
STEPS: (10000, 20000)
#~ MAX_ITER: 90000
MAX_ITER: 29000 #20000 1 epoch
CHECKPOINT_PERIOD: 2500
TEST:
IMS_PER_BATCH: 1
INPUT:
MAX_SIZE_TRAIN: 2560
MIN_SIZE_TRAIN: 2048
MAX_SIZE_TEST: 2560
MIN_SIZE_TEST: 2048
OUTPUT_DIR: "/shared/Training/T-13_HQ"

hi bro,do u konw how to modify these parameters MIN_SIZE_TRAIN, MAX_SIZE_TRAIN, if my custom imgs shape larger than 1333*800?

Shortest edge of your image will be rescaled to the MIN_SIZE_TRAIN value you put on your config file. The largest edge will be rescaled according to the aspect ratio of your image up to the MAX_SIZE_TRAIN value. Unless your task is very dependent on the resolution of your images( you need to work with hig resolution images), just don't modify anything and your images will be automatically rescaled to the default values.
Then on test time just be sure your image test is same as train as expained above, and should work correctly (I dont have any problem working on default image size).

@acaelles97 @fmassa
thank u, i'll try it again.

I have just discovered that training masks were correct but bounding box were not. I fixed that and now working really well.
Thanks for your comments.

Hello @acaelles97 , could you tell me how you fix the uncorrected bounding box issue? Thank you very much.


Use a generic assignParameters for *Solvers

Please ensure your pull request adheres to the following guidelines:

[ ] Tests for new functionality/models or Tests to reproduce the bug-fix in code.
[ ] Updated documentation of features that add new functionality.
[ ] Update CHANGELOG.md with major/minor changes.

Fixes https://github.com/econ-ark/HARK/issues/816

The assignParameters in Solvers now also populates a dictionary parameters.

Merging this after checks pass post-update.


Update develop-against-dataview.md

the docs available now is not up-to-date and kind of broken and misleading. I have forgotten to update them after the code review, sorry for that! 🥲

update broken links in published page
correct variable names

btw, make sure to push the changes to published page before informing the devs about the API update

Thanks! And good catch.


IPAM Webhook System Support

Title
IPAM webhook support
Description
Allow hitting a remote endpoint for IP + hostname allocation/release. This would allow for interaction/interoperability with systems that may be internal only (IE, non public facing API's).
Actual Problem
Presently, the only providers supported for IPAM are the FIC and Infoblox.
Solution Proposed
Allow support for arbitrary webhook for IP allocation/release, similar to Cert-Manager and ExternalDNS do:
https://cert-manager.io/docs/configuration/acme/dns01/webhook/
https://github.com/kubernetes-sigs/external-dns?tab=readme-ov-file#new-providers
Alternatives
A pluggable method for introducing new providers.
Additional context
May help w/ the following other issues:

https://github.com/F5Networks/f5-ipam-controller/issues/127
https://github.com/F5Networks/f5-ipam-controller/issues/39
https://github.com/F5Networks/f5-ipam-controller/issues/11

Created [CONTCNTR-4844] for internal tracking.

@dronenb would like to schedule a call for next with the FIC team to discuss this more in detail.


Changing caret position

According to the comments in the EditAsync() definition:
'Initiates an edit request in the host Visual Studio process, enabling the extension
to atomically request one or more Microsoft.VisualStudio.Extensibility.Editor.ITextDocumentSnapshot
edits, caret position changes, or other state changes.'
Is it documented how to make caret position changes?

The selection (caret) is part of https://learn.microsoft.com/en-us/dotnet/api/microsoft.visualstudio.extensibility.editor.itextviewsnapshot?view=vs-extensibility so apply edits to its editable version (ITextViewSnapshot.AsEditable())

'... so apply edits to its editable version (ITextViewSnapshot.AsEditable())'
Are you saying that the Delete/Insert/Replace methods affect the selection (caret)? (the comments in ITextDocumentEditor do not indicate this.
Even if so, I sometimes need to set the caret independent of the above methods - to a position not affected by the above methods.

@LeeMSilver, editing text document implicitly affects caret position, for example inserting some text at the caret will move the caret to the end of the inserted text:
await this.Extensibility.Editor().EditAsync(
batch =>
{
textView.Document.AsEditable(batch).Replace(textView.Selection.Extent, newGuidString);
},
cancellationToken);
You can use ITextViewSnapshot.AsEditable().SetSelections() to set the caret explicitly to a different position, e.g. this code would insert some text, but keep the caret at the original position:|
await this.Extensibility.Editor().EditAsync(
batch =>
{
var caret = textView.Selection.Extent.Start;
textView.Document.AsEditable(batch).Replace(textView.Selection.Extent, newGuidString);
textView.AsEditable(batch).SetSelections([new Selection(activePosition: caret, anchorPosition: caret, insertionPosition: caret)]);
},
cancellationToken);

Thanks - that's exactly what I am looking for.
Is it documented anywhere that AsEditable is also an extension-method for ITextViewSnapshot besides being an extension-method for ITextViewSnapshot.Document?
If I had known this I would not have needed to ask the question.

@LeeMSilver fair point about documentation. I'm tracking this issue internally.

@LeeMSilver, editing text document implicitly affects caret position, for example inserting some text at the caret will move the caret to the end of the inserted text:
await this.Extensibility.Editor().EditAsync(
    batch =>
    {
        textView.Document.AsEditable(batch).Replace(textView.Selection.Extent, newGuidString);
    },
    cancellationToken);

You can use ITextViewSnapshot.AsEditable().SetSelections() to set the caret explicitly to a different position, e.g. this code would insert some text, but keep the caret at the original position:|
await this.Extensibility.Editor().EditAsync(
    batch =>
    {
        var caret = textView.Selection.Extent.Start;
        textView.Document.AsEditable(batch).Replace(textView.Selection.Extent, newGuidString);
        textView.AsEditable(batch).SetSelections([new Selection(activePosition: caret, anchorPosition: caret, insertionPosition: caret)]);
    },
    cancellationToken);

I just tried this code but it did not work. The caret is not preserved.
Even though sometimes it seems to work, in reality, if the user presses up/down, the keyboard real anchor is at the end of the file and not at the caret position specified/displayed.
I can even see two caret markers:
A blue caret (the caret position I specified in SetSelections)

A red caret (the one the keyboard/VS is really responding to).

@olegtk is there something I'm missing or could it be a bug in the API?


Uncaught ReferenceError: ytcfg is not defined

I have an ng-repeat of questions and on click it moves to the next question.

		<ng-youtube-embed url="myQuestion.video_url"  autoplay="true" color="white" disablekb="true" end="20"></ng-youtube-embed>

Question: {{myQuestion.text}

	<button ng-click="selectContinue()">Continue</button>

Here i have a controller:
var app = angular.module('angularMainApp', ['ngRoute', 'ngYoutubeEmbed']);
app.controller('quizctrl', ['$scope', function($scope){

	$http.get('/somlink/quizdata.php').then(function(quizdata){
		$scope.myQuestions = quizdata.data;
		$scope.totalQuestions = $scope.myQuestions.length;
	});
}]);

Here is the error I am getting in my console. Though the video is loading fine and everything works, I am wondering if the error could be fixed.

Seems to be an issue with the YouTube iframe embed api -
http://stackoverflow.com/questions/40622204/uncaught-referenceerror-ytcfg-is-not-defined
https://productforums.google.com/forum/#!topic/youtube/3Z7dSnwkCH4

Yhup I realised that just now. Thanks for the reply.

Sure no prob!


Iterm2 github light colorblind vs github light default only difference is in cursor color

The only difference between github light colorblind and github light default is that the cursor color has been changed.

Is this intended?

And github dark colorblind and github dark default appear to be identical.

@kdheepak I can’t even import the theme, says the files is invalid. How did you do?

I just downloaded the files and double clicked on them. Are you using the latest iTerm2?

I just downloaded the files and double clicked on them. Are you using the latest iTerm2?

yep

it seems I'm not the only one https://github.com/folke/tokyonight.nvim/issues/177


Feature: Add a skip link to the toolbar for keyboard users

Currently it is annoying for keyboard users to reach inside the editor when navigating the page with the tab key they always have to skip through each option until the reach inside the actual text field.
Optimally there is a skip link that is only visible by keyboard focus. Eg:

Would it make sense to "Skip to Editor" if the user presses the Esc button from keyboard? If so, can I look into this enhancement?

Why should escape go into something? Rather it should leave the editor (which doesnt makes sense).
Also esc often closes an dialog or if you open the alignment select, it closes the select.


Be able to create new folders from the "move to folder" dialogue

This would allow a user to search for a folder via the "Move to Folder" command, see that there isn't one there, and create that folder directly from that command in as "Create and Move to Folder".
Users should be able to specify & create nested folders with slashes in the name path.

This has been implemented as of 3d27be60107723b8d2443292c591552faad7bf41, but I'm keeping it open in case issues show up.


p3x-onenote: 2020.10.111 -> 2022.4.127

Description of changes

Things done

Built on platform(s)

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

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

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

[ ] 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/)
22.11 Release Notes (or backporting 22.05 Release notes)

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

[ ] Fits CONTRIBUTING.md.

i386-linux AppImage is no longer released

i386-linux AppImage is no longer released

Actually I think meta.platforms should reflect the change...
Can you also set meta.platforms as [ "aarch64-linux" "armv7l-linux" "x86_64-linux" ]?

p3x-onenote has a new update v2022.10.109.
According to the change log, it only seems to be a minor update, so I don't expect anything will break, however I have not tried it.

The app doesn't start up correctly for me however. I've got a black window and the following errors in the console...
From my usage of it on NixOS it seems to work fine. Do other electron applications work on your machine through nixGL? (also you might as well test with 2022.10.109 while you're at it.)

Other electron apps work fine (discord for example).
The previous version of p3x-onenote crashed hard in the app itself:
(lots of no-name internal p3x-onenote frames)
#33 0x0000562f5ed5d207 _ZN2v88internal9Execution4CallEPNS0_7IsolateENS0_6HandleINS0_6ObjectEEES6_iPS6_ (p3x-onenote + 0x2612207)
#34 0x0000562f5ec5d6de _ZN2v88Function4CallENS_5LocalINS_7ContextEEENS1_INS_5ValueEEEiPS5_ (p3x-onenote + 0x25126de)
...

I've updated to stdenvNoCC.
Shall we raise a separate issue for the app not starting as it's perhaps unrelated to this PR?

Yeah, if it works for others, I'm happy with that


Decal asset preview is blue (2021.2.11f1)

When installing driven decals to a unity 2021.2.11 project the preview is always blue, even when opening in an almost empty project and selecting the example materials. URP version is 12.1.4 .
These errors may be related to the issue.
[Worker1] Attempting to get Camera relative temporary RenderTexture (width || height <= 0) via a CommandBuffer  in a Sriptable Render Pipeline.
[Worker1] Trying to get RenderBuffer with invalid antiAliasing (must be at least 1)

I am having the same problem in Unity 2021.3.28f1, Please can you tell me why is it showing and how to solve the issue.
Regards,

Is it possible can you tell me how to use the same in Unity Standard Pipeline.


Docs.Ms exclude implementation on Track 1, which is not supposed to be

Last year, we launched the feature which exclude implementation for Docs.Ms automatically.
However, this is not true for track 1 as implementation is not internal.
https://github.com/Azure/azure-sdk-for-java/blob/main/sdk/cognitiveservices/ms-azure-cs-computervision/src/main/java/com/microsoft/azure/cognitiveservices/vision/computervision/implementation/ComputerVisionImpl.java

https://review.docs.microsoft.com/en-us/java/api/overview/azure/cognitiveservices/computervision?view=azure-java-preview&branch=main
The implementation package is able to config.


Plugin Hides "normal" comments

I realized that the plugin seemingly hides "normal comments", i.e. those made on the site. Webmentions and likes work a charm. You can see this here:
https://svens.blog/2017/11/25/ia-writers-new-font/
Post shows the comment count, but the comments don't. With SL deactived they show up. Any ideas how I can quickly fix this?
All the best!

thanks for reporting! fixed in version 3.7.2.


Can't interrupt actions with ctrl + c

For an example, when i ping my loopback and want to kill the action, i want to key interrupt this actions with ctrl + c but nothing happens.

Thanks for contribution, but this is relates to the #66
We would be grateful to you @N00D13 and @RoySegall if you help us add this feature.

I guess the other issue is different: it says that one should be able to clear the prompt from a not started command hitting ctrl + c. Reopening.

Oh, my apologies, I misunderstood.

Sorry, Click Fail
To add to what @N00D13 is running into. For something like "top or iostat" ctl +q will get you out of it, this is not the case with the ping command.
All that being said, some of the standard keyboard shortcuts people are accustomed to when working within a shell should really be consistent. Terminating a process should be assigned to "Ctl + c" / "cmd + c" as an experienced command line user would expect.

Also if ctrl + q close the window then this will affect people when they will try to exit the git scroller(similar to git log)

@RoySegall, duly noted.

@shockone I know there is a referenced #143 which references #66 and #68 but Ctrl + C still doesn't kill a process for me when using Black Screen. Any plans on adding support for this?

@jdsimcoe, done. Although, I must send a different signal: SIGTERM instead of SIGINT because of an pty.js issue. It still stops a command execution, which is what you usually want. It might have weird consequences, though.

By the way, interrupted commands have a special icon.

@shockone Nice!

I would like to re open it - ctl+c suppose not only to stop the current process but also start a new line. Try this in normal terminal and see what happens.

@RoySegall, do you mean that when there is no running command it should behave as if you pressed 'return' and just re-draw the prompt?

In deed. it's suppose to create a new line and clear the old one. To me, for example, it's help to order my thoughts before typing my new command in the cli.

@RoySegall, thank you, I'll make it clear the current input, but I won't allow it to create a new prompt. Sorry, you'll have to find a new way to order your thoughts unless you know another reason to have it besides a compulsive behaviour. :)

The ctrl+c doesn't create a new prompt. It's just create a new row.

When I click it repeatedly, I see the following, do you observe a different behaviour?

This is exactly what is suppose to do but I don't get it. I cloned today the project so have the latest version.

Yeah, my screenshot is in iTerm2 and ZSH. But it does display prompts at new lines, doesn't it? Anyway, I'd like to avoid creating empty lines; currently it's impossible to execute an empty command and we plan to disallow execution of incorrect commands.

Fixed.


Carthage compatible

Carthage is very powerful dependency manager.
It is very easy to be compatible with Carthage. - Supporting carthage for your framework
I made DateTools compatible with Carthage in this pull request. I used existing Example project because I don't want to pollute your directory structure. But different directory structure mabye better.
I like this better than Cocoapods because when clean and build project, cocoapods rebuild libraries again, but Carthage doesn't do that. Swift's build time is very long. So, it is helpfull to install library with Carthage.
Thanks!

I REALLY want to add this, but working out the conflicts might be difficult for me as I do not use Carthage. Is there any way you could resolve these conflicts so I can merge your additions in?
Thanks,
-Matt

Hi, thanks:)
But I think you maybe wait for merging this pull request. Because unstable release is not good for you :)
You better take this pull request just as a suggestion.
Any way, I fix the conflict. I like Carthage so, I fork it if it is not compatible with carthage. But it's better library itself is compatible with Carthage:)
I write how to make this project compatible with Carthage.

1. Create framework target

2. Make scheme sharable

3. Add source files and make header public
You can change header as public in File inspector.

4. Edit DateTools.h
Framework target generate default DateTools.h. It's name is same to DateTools.h. So, I merged these to file's content.
5. Check if it works
Use Carthage in sample project.
let timeAgoDate = NSDate(timeIntervalSinceNow: -4)
println("\(timeAgoDate.timeAgoSinceNow())")
println("\(timeAgoDate.shortTimeAgoSinceNow())")

And I think the carthage framework location is not the best place in Example.project. I did there because I hesitated to change your directory structure.
I searched a little about Carthage compatible library written in Objective-C. For example, https://github.com/Mantle/Mantle . It locate framework at the top level. I think it is better. I always put my carthage framework in top level too.

+1

Merged!

Please check to make sure everything is working for you! Thanks,
-Matt

Last time I checked the latest version of Carthage no longer looks for xcodeproj files in subdirectories. If that is still the case this won't work.


[20.09] docker: allow overriding package inputs per docker package

Previously we could not override the input packages to docker at all as
that had been shadowed due to the usage of inherit in all-package.nix.
We are now mixing the "variable" variables for the build and the
dependency declarations for the package and using callPackage as if each
of the docker packages would be separate files that we evaluate.
This now enables overriding e.g. iptables for a single verison of
docker which previously was not feasible without importing the
default.nix again (and passing different arguments).

pkgs.docker.override { iptables = pkgs.iptables-nftables-compat; }

Backport of ed46383416a21ef496c6b52bc89d80f28c2efcad

Motivation for this change
Things done

[x] Tested using sandboxing (nix.useSandbox on NixOS, or option sandbox in nix.conf on non-NixOS linux)
Built on platform(s)

[x] NixOS
[ ] macOS
[ ] other Linux distributions

[ ] Tested via one or more NixOS test(s) if existing and applicable for the change (look inside nixos/tests)
[ ] Tested compilation of all pkgs that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review wip"
[x] Tested execution of all binary files (usually in ./result/bin/)
[ ] Determined the impact on package closure size (by running nix path-info -S before and after)
[ ] Ensured that relevant documentation is up to date
[x] Fits CONTRIBUTING.md.

Please only backport the commit after it is merged into master. If there are changes to the the original commit you needlessly need to update this PR.

Please only backport the commit after it is merged into master. If there are changes to the the original commit you needlessly need to update this PR.


Input 2D augmentation

Hello @SoroushMehraban, Hope you are doing well!
In demo/vis.py, you have been using input_2D_aug which has been flipped(*-1) in the x coordinates if I am not wrong. Further rearranging has been done using left and right joints to my knowledge. But while prediction i.e. output_3D_flip and non flipped only input 2D has been used and no where the augmentated keypoints array has been used. I request you to help me to understand this well. (line 240-249)
Thanking You
Best Regards
Aman

Good catch @a-kungwani.
Fixed it.


"set system services ssh no-passwords" is valid

Invalid syntax:  set system services ssh no-passwords
This configuration is valid.
But junoser say invalid.

set system services ssh no-passwords was introduced in JUNOS 13.3 but junoser is currently based on vSRX 12.1X47 :astonished:

I'm done a quick patch on v0.2.2, Thanks for your reporting !
This is a good time to merge a newer XSD coming from 15.1X49 and maybe other platform too.

thanks :+1:


Refactor terraform configs

What does this PR do?
This PR does a couple of related things

Adds a new ddev utility for copying files in a recursive way
Adds a new templates->terraform directory for common terraform code found in e2e environments
Updates the existing e2e environments to use that new shared template set
(Removes an unrelated extra comment I had noticed 😉)

Motivation
There was a lot of common terraform config code in the existing E2E environments, this allows moving those out and only defining it once.
Terraform allows multiple .tf files in a module, so the terraform runner in ddev will now copy the existing shared .tf files, alongside the one defined for the integration, into a single directory to be run. This has the benefit of defining and pinning a provider, like gcp, only once.
Additional Notes
The runner now supports stating which templates to copy, in case future E2E environments don't need some shared resources
Review checklist (to be filled by reviewers)

[ ] Feature or bugfix MUST have appropriate tests (unit, integration, e2e)
[ ] PR title must be written as a CHANGELOG entry (see why)
[ ] Files changes must correspond to the primary purpose of the PR as described in the title (small unrelated changes should have their own PR)
[ ] PR must have changelog/ and integration/ labels attached

ddev released, switching to no-changelog so the others don't get bumped


upgrade Drupal Libraries

see  https://github.com/jhu-idc/idc-isle-dc/issues/71
Locked version has D9 support, version bump would likely be recommend here as there has been some further deprecation fixes.

Done as of https://github.com/jhu-idc/idc-isle-dc/commit/d216a2d1fa117028fa62396e5f649fa000b74f93


[BFCL] Detailed score for each item

Hello,
I would like to see the detailed scores of java and javascript. Can you provide the scores of all models for each item according to different JSON files?
Thank you

Hi,
They are reported in this file. https://github.com/ShishirPatil/gorilla/blob/gh-pages/data_non_live.csv


Add ratio variance and covariance

Codecov Report
All modified and coverable lines are covered by tests :white_check_mark:

Comparison is base (f8b4f1b) 100.00% compared to head (18ae8cf) 100.00%.
Report is 14 commits behind head on main.

Additional details and impacted files
@@            Coverage Diff             @@
##              main       #16    +/-   ##
==========================================
  Coverage   100.00%   100.00%
==========================================
  Files            6         6
  Lines           37       180   +143
==========================================
+ Hits            37       180   +143

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.


Parameter 'timeout' has invalid type Error  in docs/tutorials/RunWithDocker.md

Parameter 'timeout' has invalid type Error  in doccs/tutorials/RunWithDocker.md
[traffic_simulation_demo-1] terminate called after throwing an instance of 'rclcpp::exceptions::InvalidParameterTypeException'
[traffic_simulation_demo-1]   what():  parameter 'timeout' has invalid type: Wrong parameter type, parameter {timeout} is of type {double}, setting it to {integer} is not allowed.
To Reproduce
Steps to reproduce the behavior:
rocker --x11 tier4/scenario_simulator_v2:galactic ros2 launch cpp_mock_scenarios mock_test.launch.py scenario:=crashing_npc scenario:=traffic_simulation_demo launch_rviz:=true timeout:=60

Thank you for checking our mistake!
I will fix soon!

This problem was solved by #715


save icon

@zgalant @almeidaalajoel @Bloblblobl
Currently have the icon as the home button. It's a good distance since the "Saving" message can also pop up. I also tried the check mark but I think it may need a little bit more styling and since it's the same icon as the one from the Paint page which doesn't actually save may be a bit confusing

@toto4tots do you think you could get the word "Save" added there too?

@zgalant

I wonder if we want to just do 'Save' without the home icon? Although then it would not be obvious that it's a button and bc this is svg I've been finding it a little tricky to style

idk we can keep tinkering.
@almeidaalajoel it also depends how good autosaving can get (if it's good, we can just remove this button)
or maybe even better, the home button can just re-link to codehs.com and then the user will go back to their homepage


Fix setting  roles

Closes https://github.com/ClickHouse/metabase-clickhouse-driver/issues/262
Summary

Split roles and add quotes around them if needed, before setting the role

Checklist
Delete items not relevant to your PR:

[x] Unit and integration tests covering the common scenarios were added

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


Logs

I can't clear logs.

To clear the logs you can temporary disable them by updating the _"Admin UI > Settings > Application > Logs max days retention" field  and set it to 0 (it'll also run VACUUM on the logs db so the previously taken space also should be released).

To clear the logs you can temporary disable them by updating the _"Admin UI > Settings > Application > Logs max days retention" field and set it to 0 (it'll also run VACUUM on the logs db so the previously taken space also should be released).

thank you


[Event Request] Page 392 Phys. Inventory Journal

The following events are required for this object:
    [IntegrationEvent(false, false)]
    local procedure OnBeforeOnDeleteRecord(var ItemJournalLine: Record "Item Journal Line"; var IsHandled: Boolean)
    begin
    end;

    trigger OnDeleteRecord(): Boolean
    var
        ItemJnlLineReserve: Codeunit "Item Jnl. Line-Reserve";
        IsHandled: Boolean;
    begin
        Commit();
        //EVENT REQUEST
        IsHandled := false;
        OnBeforeOnDeleteRecord(Rec, IsHandled);
        If IsHandled then
            exit;
        //EVENT REQUEST
        if not ItemJnlLineReserve.DeleteLineConfirm(Rec) then
            exit(false);
        ItemJnlLineReserve.DeleteLine(Rec);
    end;

Thanks for reporting this. We agree, and we’ll publish a fix asap, either in an update for the current version or in the next major release. Please do not reply to this, as we do not monitor closed issues. If you have follow-up questions or requests, please create a new issue where you reference this one.
Build ID: 12501.


[CARBONDATA-1536] Default value of carbon.bad.records.action is FORCE

Default value of carbon.bad.records.action is FORCE in source code, but the value is fail in documentation

Build Success with Spark 2.1.0, Please check CI http://<IP_ADDRESS>:8080/job/ApacheCarbonPRBuilder1/324/

Build Success with Spark 1.6, Please check CI http://<IP_ADDRESS>:8080/job/ApacheCarbonPRBuilder/200/

SDV Build Fail , Please check CI http://<IP_ADDRESS>:8080/job/ApacheSDVTests/952/

Build Success with Spark 1.6, Please check CI http://<IP_ADDRESS>:8080/job/ApacheCarbonPRBuilder/206/

Build Success with Spark 2.1.0, Please check CI http://<IP_ADDRESS>:8080/job/ApacheCarbonPRBuilder1/330/

SDV Build Success , Please check CI http://<IP_ADDRESS>:8080/job/ApacheSDVTests/958/

LGTM


Test new theme matching and new tokens format

[x] @jrieken
[ ] @chrmarti

Cmplexity: 4
Plan item: #18317
The changes are heavily covered through unit tests, but there are some integration things that might not work, so please check:

create or change a grammar to emit a scope name that contains < or > or &. Please check that these strings do not make it into the editor HTML rendering and also not into the Developer: Inspect TM Scopes widget
change an editor contribution (in code) to add an inline decoration class name (e.g. link contribution) that contains < or > or &. Please check that these strings do not make it into the editor HTML rendering.
check that changing a color theme to X produces the same colorization as loading the workbench fresh with the theme X (i.e. caches are correctly cleared)
open some different files in our most popular languages and in some of the most popular themes. Please compare with the previous stable version, and if you spot differences validate those differences are OK via the Developer: Inspect TM Scopes widget

Is there documentation for this new tokens format for theme developers?  My theme is no longer coloring items as intended after 1.9.0 insider 2017-01-10T09:15:59.757Z.

@smlombardi Could you open a bug report for your case?

Verified using, e.g., "name": "comment.line.doubl>e-slash.js" in JavaScript.tmLanguage.json does not corrupt the output:

Also verified that changing the class name detected-link in links.ts and stylesContributions.ts to include those characters does not let these show up in the editor. I see them in the DOM properly escaped.

Hope that's according to the test description. Also tested the other two points and filed issues.


is it possible to return all voice meter data when recording stopped

hello,
i am trying to build a whatsapp like voice messaging system, when a user record a audio, i would like to receive voice meter data related with recorded audio, i know this library returns metering related data while recording, so is it possible to append result object with those metering data?

I don't feel like I've fully understood your question. Could you kindly show something related? I am not a WhatsApp user 😔

I understand his question. Can I return the audio metadata to show the audio waveform

even i want to do something like this... but there are no much resources on how to do it

Eventually i ended up saving the meter data each second.

Eventually i ended up saving the meter data each second.

i just want to ask how you were showing the bars like in whatsapp , can you send a code snippet


Error: failed to start container "container-disk-binary"

Is this a BUG REPORT or FEATURE REQUEST?:

Uncomment only one, leave it on its own line:
/kind bug
/kind enhancement

What happened:
$ kubectl  get pod
NAME                           READY   STATUS                    RESTARTS   AGE
virt-launcher-vmi-perf-rnvpw   0/2     Init:ContainerCannotRun   0          25m

$ kubectl  get vmi
NAME       AGE   PHASE    IP    NODENAME   READY
vmi-perf   26m   Failed

$ kubectl  describe pod virt-launcher-vmi-perf-rnvpw
Name:         virt-launcher-vmi-perf-rnvpw
Namespace:    default
Priority:     0
Node:         uos-pc/<IP_ADDRESS>
Start Time:   Tue, 19 Oct 2021 15:55:24 +0800
Labels:       kubevirt.io=virt-launcher
              kubevirt.io/created-by=da470d6e-fff3-4259-b1f2-5a7d5f686afe
              special=vmi-perf
Annotations:  k8s.v1.cni.cncf.io/network-status:
                [{
                    "name": "",
                    "interface": "eth0",
                    "ips": [
                        "<IP_ADDRESS>"
                    ],
                    "mac": "c6:84:50:3a:79:1d",
                    "default": true,
                    "dns": {}
                },{
                    "name": "default/sriov-net1",
                    "interface": "net1",
                    "ips": [
                        "<IP_ADDRESS>"
                    ],
                    "mac": "b6:54:ce:49:64:54",
                    "dns": {},
                    "device-info": {
                        "type": "pci",
                        "version": "1.0.0",
                        "pci": {
                            "pci-address": "0000:60:06.5"
                        }
                    }
                }]
              k8s.v1.cni.cncf.io/networks: [{"interface":"net1","name":"sriov-net1","namespace":"default"}]
              k8s.v1.cni.cncf.io/networks-status:
                [{
                    "name": "",
                    "interface": "eth0",
                    "ips": [
                        "<IP_ADDRESS>"
                    ],
                    "mac": "c6:84:50:3a:79:1d",
                    "default": true,
                    "dns": {}
                },{
                    "name": "default/sriov-net1",
                    "interface": "net1",
                    "ips": [
                        "<IP_ADDRESS>"
                    ],
                    "mac": "b6:54:ce:49:64:54",
                    "dns": {},
                    "device-info": {
                        "type": "pci",
                        "version": "1.0.0",
                        "pci": {
                            "pci-address": "0000:60:06.5"
                        }
                    }
                }]
              kubevirt.io/domain: vmi-perf
              traffic.sidecar.istio.io/kubevirtInterfaces: k6t-eth0
Status:       Failed
IP:           <IP_ADDRESS>
IPs:
  IP:           <IP_ADDRESS>
Controlled By:  VirtualMachineInstance/vmi-perf
Init Containers:
  container-disk-binary:
    Container ID:  docker://dd765dda1d6bfdb40c0c1ea32f7626d506e3ce0db65171357e970254cc9c0966
    Image:         quay.io/kubevirt/virt-controller:v0.41.2
    Image ID:      docker://sha256:27968195c4fe5477d5cf0f7eb6ae8bfc4aa05544b90ff86643d1f33bd415a193
    Port:          <none>
    Host Port:     <none>
    Command:
      /usr/bin/cp
      /usr/bin/container-disk
      /init/usr/bin/container-disk
    State:          Terminated
      Reason:       ContainerCannotRun
      Message:      OCI runtime create failed: container_linux.go:380: starting container process caused: exec: "/usr/bin/cp": stat /usr/bin/cp: no such file or directory: unknown
      Exit Code:    127
      Started:      Tue, 19 Oct 2021 15:55:25 +0800
      Finished:     Tue, 19 Oct 2021 15:55:25 +0800
    Ready:          False
    Restart Count:  0
    Limits:
      cpu:     10m
      memory:  40M
    Requests:
      cpu:        10m
      memory:     40M
    Environment:  <none>
    Mounts:
      /init/usr/bin from virt-bin-share-dir (rw)
  volumecontainerdisk-init:
    Container ID:
    Image:         docker.io/kubevirt/fedora-cloud-container-disk-demo:latest
    Image ID:
    Port:          <none>
    Host Port:     <none>
    Command:
      /usr/bin/container-disk
    Args:
      --no-op
    State:          Waiting
      Reason:       PodInitializing
    Ready:          False
    Restart Count:  0
    Limits:
      cpu:     10m
      memory:  40M
    Requests:
      cpu:                10m
      ephemeral-storage:  50M
      memory:             40M
    Environment:          <none>
    Mounts:
      /usr/bin from virt-bin-share-dir (rw)
      /var/run/kubevirt-ephemeral-disks/container-disk-data/da470d6e-fff3-4259-b1f2-5a7d5f686afe from container-disks (rw)
Containers:
  compute:
    Container ID:
    Image:         quay.io/kubevirt/virt-controller:v0.41.2
    Image ID:
    Port:          <none>
    Host Port:     <none>
    Command:
      /usr/bin/virt-launcher
      --qemu-timeout
      5m
      --name
      vmi-perf
      --uid
      da470d6e-fff3-4259-b1f2-5a7d5f686afe
      --namespace
      default
      --kubevirt-share-dir
      /var/run/kubevirt
      --ephemeral-disk-dir
      /var/run/kubevirt-ephemeral-disks
      --container-disk-dir
      /var/run/kubevirt/container-disks
      --grace-period-seconds
      15
      --hook-sidecars
      0
      --less-pvc-space-toleration
      10
      --ovmf-path
      /usr/share/OVMF
    State:          Waiting
      Reason:       PodInitializing
    Ready:          False
    Restart Count:  0
    Limits:
      cpu:                              2
      devices.kubevirt.io/kvm:          1
      devices.kubevirt.io/tun:          1
      devices.kubevirt.io/vhost-net:    1
      intel.com/intel_sriov_netdevice:  2
      memory:<PHONE_NUMBER>
    Requests:
      cpu:                              2
      devices.kubevirt.io/kvm:          1
      devices.kubevirt.io/tun:          1
      devices.kubevirt.io/vhost-net:    1
      ephemeral-storage:                50M
      intel.com/intel_sriov_netdevice:  2
      memory:<PHONE_NUMBER>
    Environment:
      KUBEVIRT_RESOURCE_NAME_sriov-net1:  intel.com/intel_sriov_netdevice
      POD_NAME:                           virt-launcher-vmi-perf-rnvpw (v1:metadata.name)
    Mounts:
      /var/run/kubevirt-ephemeral-disks from ephemeral-disks (rw)
      /var/run/kubevirt/container-disks from container-disks (rw)
      /var/run/kubevirt/hotplug-disks from hotplug-disks (rw)
      /var/run/kubevirt/sockets from sockets (rw)
      /var/run/libvirt from libvirt-runtime (rw)
  volumecontainerdisk:
    Container ID:
    Image:         docker.io/kubevirt/fedora-cloud-container-disk-demo:latest
    Image ID:
    Port:          <none>
    Host Port:     <none>
    Command:
      /usr/bin/container-disk
    Args:
      --copy-path
      /var/run/kubevirt-ephemeral-disks/container-disk-data/da470d6e-fff3-4259-b1f2-5a7d5f686afe/disk_0
    State:          Waiting
      Reason:       PodInitializing
    Ready:          False
    Restart Count:  0
    Limits:
      cpu:     10m
      memory:  40M
    Requests:
      cpu:                10m
      ephemeral-storage:  50M
      memory:             40M
    Environment:          <none>
    Mounts:
      /usr/bin from virt-bin-share-dir (rw)
      /var/run/kubevirt-ephemeral-disks/container-disk-data/da470d6e-fff3-4259-b1f2-5a7d5f686afe from container-disks (rw)
Conditions:
  Type              Status
  Initialized       False
  Ready             False
  ContainersReady   False
  PodScheduled      True
Volumes:
  sockets:
    Type:       EmptyDir (a temporary directory that shares a pod's lifetime)
    Medium:
    SizeLimit:  <unset>
  virt-bin-share-dir:
    Type:       EmptyDir (a temporary directory that shares a pod's lifetime)
    Medium:
    SizeLimit:  <unset>
  libvirt-runtime:
    Type:       EmptyDir (a temporary directory that shares a pod's lifetime)
    Medium:
    SizeLimit:  <unset>
  ephemeral-disks:
    Type:       EmptyDir (a temporary directory that shares a pod's lifetime)
    Medium:
    SizeLimit:  <unset>
  container-disks:
    Type:       EmptyDir (a temporary directory that shares a pod's lifetime)
    Medium:
    SizeLimit:  <unset>
  hotplug-disks:
    Type:        EmptyDir (a temporary directory that shares a pod's lifetime)
    Medium:
    SizeLimit:   <unset>
QoS Class:       Guaranteed
Node-Selectors:  cpumanager=true
                 kubevirt.io/schedulable=true
Tolerations:     node.kubernetes.io/not-ready:NoExecute for 300s
                 node.kubernetes.io/unreachable:NoExecute for 300s
Events:
  Type     Reason            Age                From               Message
  ----     ------            ----               ----               -------
  Warning  FailedScheduling  26m (x2 over 26m)  default-scheduler  0/1 nodes are available: 1 node(s) didn't match node selector.
  Normal   Scheduled         25m                default-scheduler  Successfully assigned default/virt-launcher-vmi-perf-rnvpw to uos-pc
  Normal   AddedInterface    25m                multus             Add eth0 [<IP_ADDRESS>/24]
  Normal   AddedInterface    25m                multus             Add net1 [<IP_ADDRESS>/24] from default/sriov-net1
  Normal   Pulled            25m                kubelet, uos-pc    Container image "quay.io/kubevirt/virt-controller:v0.41.2" already present on machine
  Normal   Created           25m                kubelet, uos-pc    Created container container-disk-binary
  Warning  Failed            25m                kubelet, uos-pc    Error: failed to start container "container-disk-binary": Error response from daemon: OCI runtime create failed: container_linux.go:380: starting container process caused: exec: "/usr/bin/cp": stat /usr/bin/cp: no such file or directory: unknown

What you expected to happen:
$ kubectl  get pod
NAME                           READY   STATUS                    RESTARTS   AGE
virt-launcher-vmi-perf-rnvpw   0/2     Init:ContainerCannotRun   0          25m

$ kubectl  get vmi
NAME       AGE   PHASE    IP    NODENAME   READY
vmi-perf   26m   Failed

How to reproduce it (as minimally and precisely as possible):
After deploying sriov-cni multus-cni sriov-network-device, create a virtual machine. Add label
kubectl  label nodes uos-pc cpumanager=true --overwrite

$ cat vm.yaml
---
apiVersion: kubevirt.io/v1alpha3
kind: VirtualMachineInstance
metadata:
  labels:
    special: vmi-perf
  name: vmi-perf
  annotations:
    k8s.v1.cni.cncf.io/networks: sriov-net1
spec:
  domain:
    cpu:
      model: host-passthrough
      sockets: 2
      cores: 1
      threads: 1
      dedicatedCpuPlacement: true
    resources:
      requests:
        memory: "4Gi"
        intel.com/intel_sriov_netdevice: '1'
      limits:
        memory: "4Gi"
        intel.com/intel_sriov_netdevice: '1'
    devices:
      disks:
      - disk:
          bus: virtio
        name: containerdisk
      - disk:
          bus: virtio
        name: cloudinitdisk
      interfaces:
      - masquerade: {}
        name: default
      - name: sriov-net1
        sriov: {}
      rng: {}
    machine:
      type: ""
  networks:
  - name: default
    pod: {}
  - multus:
      networkName: default/sriov-net1
    name: sriov-net1
  terminationGracePeriodSeconds: 0
  volumes:
  - containerDisk:
      image: docker.io/kubevirt/fedora-cloud-container-disk-demo:latest
      imagePullPolicy: Never
    name: containerdisk
  - cloudInitNoCloud:
      userData: |
        #!/bin/bash
        echo "centos" |passwd centos --stdin
        dhclient eth1
    name: cloudinitdisk

Anything else we need to know?:
Environment:

KubeVirt version (use virtctl version):

Client Version: version.Info{GitVersion:"v0.41.2", GitCommit:"29ce26e09eeed30f89f3fd5d1ad0598955de9648", GitTreeState:"clean", BuildDate:"2021-07-28T16:23:53Z", GoVersion:"go1.13.14", Compiler:"gc", Platform:"linux/amd64"}
Server Version: version.Info{GitVersion:"v0.41.2-dirty", GitCommit:"29ce26e09eeed30f89f3fd5d1ad0598955de9648", GitTreeState:"dirty", BuildDate:"2021-07-28T16:57:02Z", GoVersion:"go1.13.14", Compiler:"gc", Platform:"linux/amd64"}

Kubernetes version (use kubectl version):

Client Version: version.Info{Major:"1", Minor:"18", GitVersion:"v1.18.5", GitCommit:"d5dfb5cb416fcc32ad556b0d253307c9267b1d30", GitTreeState:"", BuildDate:"2020-07-30T01:37:22Z", GoVersion:"go1.14.2", Compiler:"gc", Platform:"linux/amd64"}
Server Version: version.Info{Major:"1", Minor:"18", GitVersion:"v1.18.5", GitCommit:"d5dfb5cb416fcc32ad556b0d253307c9267b1d30", GitTreeState:"", BuildDate:"2020-07-30T01:54:02Z", GoVersion:"go1.14.2", Compiler:"gc", Platform:"linux/amd64"}

VM or VMI specifications:
Cloud provider or hardware configuration:
OS (e.g. from /etc/os-release):
ubuntu
Kernel (e.g. uname -a):

Linux 4.19.0-server-amd64 #3209 SMP Tue Apr 13 10:03:53 CST 2021 x86_64 GNU/Linux

Install tools:
Others:

I think the issue is that some sort of custom modifications to the install have taken place, and the virt-controller container is being used as the VMI pod's container image. That will fail in many ways.
Init Containers:
  container-disk-binary:
    Container ID:  docker://dd765dda1d6bfdb40c0c1ea32f7626d506e3ce0db65171357e970254cc9c0966
    Image:         quay.io/kubevirt/virt-controller:v0.41.2
    Image ID:      docker://sha256:27968195c4fe5477d5cf0f7eb6ae8bfc4aa05544b90ff86643d1f33bd415a193
    Port:          <none>
    Host Port:     <none>

alright, thank you very much


Request: appropriate error codes on success / failure

Hi there
Apparently this netlify go client will be the successor to the node one.
Could you please ensure that this client returns appropriate (unix) error codes, depending on success / failure? E.g. on website deploy success, return 0 else non-zero.
This makes it easier to integrate the netlify client into a large shell script.
Many thanks!
Greg

Thanks for opening this issue.
Yup, it should not return 0 when there is an error. Pull requests really welcome, but we still need to work on errors cases a lot.

@greghuc I just checked and all commands should exit with -1 when there is any errors. Did you find any case where that wasn't the output for an error?

I haven't found any cases where errors returned 0. However I raised this request to ensure the correct behaviour was specifically designed for and tested.
At present, I don't entirely trust the go-client as it's work-in-progress and has no tests. I have also seen the netlify node-client return wrong error codes, so I wanted to be sure that the go-client didn't.
To get round (possibly) wrong error codes, I'm currently wrapping the netlifyctl command in my own shell script that definitely returns correct error codes: I set error codes based on whether the string "your website is live" appears in the netlifyctl output. I think having netlifyctl return a unique string on success is a nice fallback, in additional to correct error codes.
netlifyctl deploy --base-directory ${BUILD_DIR} --access-token ${NETLIFY_TOKEN} --config ${CONFIG_FILE} 2>&1 | tee -a ${DEPLOY_OUTPUT}
cat ${DEPLOY_OUTPUT} | grep -q 'your website is live'
DEPLOY_RESULT=$?
rm ${DEPLOY_OUTPUT}
if [ ${DEPLOY_RESULT} -eq 0 ]
then
  echo "Successfully deployed website from folder: ${BUILD_DIR}" && exit 0
else
  echo "Failed to deploy website from folder: ${BUILD_DIR}" && exit 1
fi

We definitely need to work on more testing. I've added the issue to the Alpha project so we can make sure this is taking care of.


contact mechanics between two uploaded surfaces

It might be nice to allow the user to select two topographies in their library and run the contact calculations between them. When I have done this in the past, I first added them together in matlab, but uploading these "combined" surfaces becomes tedious and a user might be left with a complicated pile of combined surfaces that aren't totally useful.

We discussed this today. With the current UI and database backend this could be implemented by some kind of "filter" (also see #323), which generates a new topography from two given topographies. Then an analysis could be applied on this combined topography.


[BUG]: Contributors Page doesn't show all contributors

Kindly explain, what is the issue or what bug do you want to be fixed?
I want to add perhaps pagination to the contributor's page and show all of the contributors of the repo.
Screenshot of the issue.

What browsers are you seeing the problem on?
Google Chrome
Code of Conduct

[X] i have read the contribution guideline
[X] i am sure, this issue is not raised before.

Do you want to fix the issue?
Yes, I want to fix it

in this case. you have to  maintain the number of contributor in one page, for mobile, desktop with out the overflow scroll.
assigned


Keep running upon reconnection from server

Already implemented, but it's opt-in. If you have Mod Menu installed you can turn "Persist Auto-Run" there. Otherwise you need to manually edit the Auto-Run config located in .minecraft/config.


podman play kube: duplicate volume names lead to stalled process

/kind bug
Description
While working from a git checkout of https://github.com/jayaddison/grocy-docker/tree/b78b1810ff159e583a8770694305e2e5472ddb76, the podman play kube grocy.yaml results in a blocked-process condition.
Steps to reproduce the issue:
# 1. Produce grocy-app:libpod-issue-5631 and grocy-nginx:libpod-issue-5631 images
make build

# 2. Clear state
podman pod stop -a; podman container rm -a ; podman volume rm -a ; podman pod rm -a

# 3. Attempt playthrough (with system-call tracing via strace)
strace podman play kube grocy.yaml

Describe the results you received:
The podman process stalls without producing any output to stdout.
Describe the results you expected:
The podman process should complete after the successful creation of a pod (named grocy) with two containers (named grocy-app and grocy-nginx).
Additional information you deem important (e.g. issue happens only occasionally):
The stall-point doesn't seem consistent between playthroughs; this can be observed by running the repro steps multiple times and comparing the system call information output produced by strace during each run.
A workaround is available: by providing unique distinguishing name values for the three mounts (example), the problem is avoided and the kubectl play kube step succeeds.
Output of podman version:
podman version 1.8.2

Output of podman info:

host:
  BuildahVersion: 1.14.3
  CgroupVersion: v1
  Conmon:
    package: 'conmon: /usr/libexec/podman/conmon'
    path: /usr/libexec/podman/conmon
    version: 'conmon version 2.0.14, commit: '
  Distribution:
    distribution: ubuntu
    version: "19.10"
  IDMappings:
    gidmap:
    - container_id: 0
      host_id: 1000
      size: 1
    - container_id: 1
      host_id: 10000
      size: 65536
    uidmap:
    - container_id: 0
      host_id: 1000
      size: 1
    - container_id: 1
      host_id: 10000
      size: 65536
  MemFree: 658882560
  MemTotal:<PHONE_NUMBER>
  OCIRuntime:
    name: runc
    package: 'runc: /usr/sbin/runc'
    path: /usr/sbin/runc
    version: 'runc version spec: 1.0.1-dev'
  SwapFree: 0
  SwapTotal: 0
  arch: amd64
  cpus: 2
  eventlogger: journald
  hostname: ubuntu
  kernel: 5.3.0-42-generic
  os: linux
  rootless: true
  slirp4netns:
    Executable: /usr/bin/slirp4netns
    Package: 'slirp4netns: /usr/bin/slirp4netns'
    Version: |-
      slirp4netns version 0.4.3
      commit: unknown
  uptime: 3h 6m 58.86s (Approximately 0.12 days)
registries:
  search:
  - docker.io
store:
  ConfigFile: /home/jay/.config/containers/storage.conf
  ContainerStore:
    number: 7
  GraphDriverName: overlay
  GraphOptions:
    overlay.mount_program:
      Executable: /usr/bin/fuse-overlayfs
      Package: 'fuse-overlayfs: /usr/bin/fuse-overlayfs'
      Version: |-
        fusermount3 version: 3.4.1
        fuse-overlayfs: version 0.7.6
        FUSE library version 3.4.1
        using FUSE kernel interface version 7.27
  GraphRoot: /home/jay/.local/share/containers/storage
  GraphStatus:
    Backing Filesystem: ecryptfs
    Native Overlay Diff: "false"
    Supports d_type: "true"
    Using metacopy: "false"
  ImageStore:
    number: 7
  RunRoot: /run/user/1000
  VolumePath: /home/jay/.local/share/containers/storage/volumes

Package info (e.g. output of rpm -q podman or apt list podman):
$ apt list podman
Listing... Done
podman/unknown,now 1.8.2~1 amd64 [installed]
podman/unknown 1.8.2~1 arm64
podman/unknown 1.8.2~1 armhf

My initial inclination would be that passing volumes with duplicate names sounds like a mistake on the user's part, so we should trap it early and inform the user that they need to fix their YAML. Or is this something that Kubernetes allows, so we'll have to handle?

@mheon Although this is a slightly indirect answer, I do currently believe that mounting a single named-volume at multiple volume mounts is supported by Kubernetes.
This is my initial understanding after having discovered current Kubernetes documentation that explains the subPath option on volume mounts.  That documentation includes an example illustrating a single named-volume (site-data) mounted at two different locations within a pod.
Less strongly, but also in support of this theory, there is an absence of any documented restrictions on uniqueness of the name field in the Kubernetes VolumeMount documentation (unlike the Volume name, which according to the docs must be unique within a pod).
These lead me to believe that it's valid for a single volume name to be valid across multiple entries within volumeMounts, for the purpose of accessing volume contents via multiple filesystem paths.

This isn't a volume, though, but a volumeMount - they're very different, AFAIK (volumes are fully managed, volumeMount is a simple bind mount from host to container). I agree that volumes should be allowed to be mounted at multiple points; I'm less convinced about volume mounts.
Hmmm... @haircommander Looking at the full description, Name in a volume mount only points to volumes, which we don't implement at present. Should we be restricting its use for now?

@mheon to answer your thought, in kubernetes, volumes are a generic structure of "here's some data to mount into the container". volumeMount is the interface for a user to specify a volume (specified by name) should be mounted into a container. I.e. they reference the same thing, but from a different perspective. The name field needs to match from volumeMount to Volume, which tells the manager which volume points to which container path.
I don't see any reason why we couldn't mount a hostPath to multiple spots in the container, but I'm not convinced k8s does this. subPath seems to provide uniqueness, and seems like a different use case than mounting one hostPath to multiple container points.

While I'd like to revisit the kube functionality in podman in future (both generation-of and play-from kube yaml), I've opted to skip this for now and use the 'native' podman management commands to perform volume management and sharing instead.  From my point of view this issue is fine to resolve as wontfix; apologies for any distraction caused.


New Deno icon changed

Add New Icon(s)
Icon Details

Icon ID
Icon

deno-light

deno-dark

Notes

Provide any specific notes about the new icon(s), such as design choices, color adjustments, etc.
Mention if there were any deviations from the standard style or guidelines.

Checklist

[x] Added icon(s) to the appropriate directory
[x] Updated documentation with the new icon(s)
[x] Verified the icon(s) display correctly
[x] If the icon has light and dark, verified the auto switch works correctly
[x] The Svg does not contain any sort of strokes

https://deno.com/

Please read the COC and the contributing guidelines of the project.

Please read the COC and the contributing guidelines of the project.

Already did


ImportExport's export outputs invalid files when executed synchronously

Description
I needed to implement a functionality which would trigger and execute the Shopware ImportExport exports and imports synchronously for larger imports and exports.
It turned out that when processing more than 1 batch, the partial files created by executing the export function synchronously would not just include that batch, but also the preceding files' contents.
I suspect it had something to do with the fact that after each execution of export asynchronously, the buffer would be replaced for the next batch. With synchronous execution. the buffer is not flushed and as such still contains the previous partial file's contents.
This is related to the following Shopware code (Shopware\Core\Content\ImportExport\ImportExport):
do {
    $result = $this->repository->search($criteria, $context);
    if ($this->total === null) {
        $this->total = $result->getTotal();
        $criteria->setTotalCountMode(Criteria::TOTAL_COUNT_MODE_NONE);
    }

    $entities = $result->getEntities();
    if (\count($entities) === 0) {
        // this can happen if entities are deleted while we export
        $progress->setTotal($progress->getOffset());

        break;
    }

    $progress = $this->exportChunk($config, $entities, $progress, $targetFile);

    $criteria->setOffset($criteria->getOffset() + $criteria->getLimit());
} while ($fullExport && $progress->getOffset() < $progress->getTotal());

if ($progress->getTotal() > $progress->getOffset()) {
    return $progress;
}

$this->writer->finish($config, $targetFile);

return $this->mergePartFiles($this->logEntity, $progress);

If $this->writer->finish($config, $targetFile); was executed in the loop, this wouldn't have been reproducible. This is probably not the best solution for this issue, but it's just an idea how to look for one.
Steps to reproduce

Write a functionality that will export any entity with any profile to a file, using the ImportExportFactory to generate the ImportExport entity, then calling export in a loop, with the offset increasing based on the progress.
Make sure the batch size is lower than the number of entities.
Trigger the functionality
Observe that the output is far longer than it should be, and incorrect

Exanple code (with a lot of abstraction)
$log = $this->importExportService->prepareExport(
    $context,
    $profileId,
    $expireDate,
    $originalFileName,
    $config,
    $destinationPath
);

$export = $this->importExportFactory->create($log->getId(), 10, 10);

$progress = $export->export($context, new Criteria());

while (!$progress->isFinished()) {
    $progress = $export->export($context, new Criteria(), $progress->getOffset());
}

Expected result
During synchronous export, partial files contain only b records, with b being the batch size. The final output file contains a correct output with all n records, for n entities being exported.
For example partial file $filename_10 should contain the header followed by 10 records' worth of data, $filename_20 should contain just the next 10 records etc, and the output file after the export is complete should contain n+1 rows in total, where n is the number of exported elements.
Actual result
Each partial file contains its own b records, plus the entire contents of the previous partial file. The output file contains far more than n records, with multiple repetitions and column-name rows in the middle of the file.

[public] Automated response: This issue is linked to the internal issue https://shopware.atlassian.net/browse/NEXT-34833.
[created from NEXT-34833, comment 486430]

[public] Hello,
Within our company roadmap and work capacity, we try to address each bug or improvement request but admit that not each one will be resolved. To continue our culture of honesty and openness, we are closing this issue to focus on our roadmap on behalf of all Shopware users.
If you feel like this issue is still impacting you, please create a new issue and let us know. Thank you again for your valuable feedback.
[created from NEXT-34833, comment 501187]


Multi-node inference: invalid device ordinal

System Info
NCCL version 2.19.3+cuda12.0
TensorRT-LLM version: 0.11.0.dev2024052100
Ubuntu 22.04
Who can help?
@byshiue
Information

[X] The official example scripts
[ ] My own modified scripts

Tasks

[ ] An officially supported task in the examples folder (such as GLUE/SQuAD, ...)
[ ] My own task or dataset (give details below)

Reproduction
I try to run Llama3-70B on two nodes which have 8 L4 GPUs each.
For this purpose I converted the model using TP=8, PP=2. I checked that the mapping in config.json is correct:
"world_size": 16
"tp_size": 8,
"pp_size": 2,
"gpus_per_node": 8
Now when I run the example script with mpirun like this:
mpirun -H $HOST1:8,$HOST2:8 -n 16 python3 examples/run.py ...
Expected behavior
script runs without errors
actual behavior
I see errors like these:
[TensorRT-LLM][ERROR] CUDA runtime error in cudaDeviceCanAccessPeer(&canAccessPeer, firstDeviceId, secondDeviceId): invalid device ordinal (/home/jenkins/agent/workspace/LLM/main/L0_PostMerge/tensorrt_llm/cpp/tensorrt_llm/plugins/ncclPlugin/allreducePlugin.cpp:341)
additional notes
I made sure that nccl-tests where running and there have been no problems.

Please share the full end to end scripts to help reproducing your issue. But you can try disabling the use_custom_all_reduce (--use_custom_all_reduce disable) during building engine.

Thank you. I'll try setting -use_custom_all_reduce disable.
In the meantime those where my exact scripts.
 \
   --run_profiling

I get the same error when building the model with the said option -use_custom_all_reduce disable.

Thanks for the try. It seems that the error happens at initializing the nccl plugin and not related to custom all reduce.
This issue is fixed in latest main branch (commit id: f430a4b447ef4cba22698902d43eae0debf08594), please take a try.


Cannot import tensor_util in TF 1.14.

Please make sure that this is a bug. As per our GitHub Policy, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:bug_template
System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow): No
OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Ubuntu 18.04
Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:
TensorFlow installed from (source or binary):
TensorFlow version (use command below): 1.14.0rc1
Python version: 3.5
Bazel version (if compiling from source): 0.25.2
GCC/Compiler version (if compiling from source): 7.4.0
CUDA/cuDNN version: 10.1
GPU model and memory: TITAN V

You can collect some of this information using our environment capture
script
You can also obtain the TensorFlow version with: 1. TF 1.0: python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)" 2. TF 2.0: python -c "import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"
Describe the current behavior
Cannot import tensor_util.
$ python
Python 3.6.8 (default, Jan 14 2019, 11:02:34)
[GCC 8.0.1 20180414 (experimental) [trunk revision 259383]] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> from tensorflow.python.framework import tensor_util
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ImportError: cannot import name 'tensor_util'

Describe the expected behavior
We can import tensor_util in TF 1.13.
Code to reproduce the issue
See above.
Other info / logs
Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached.

Cannot reproduce
mihaimaruseac@ankh:/tmp/5$ virtualenv . -p python3.5
Running virtualenv with interpreter /usr/bin/python3.5
Using base prefix '/usr'
New python executable in /tmp/5/bin/python3.5
Also creating executable in /tmp/5/bin/python
Installing setuptools, pkg_resources, pip, wheel...source bin/activate
pipdone.

mihaimaruseac@ankh:/tmp/5$ source bin/activate

(5) mihaimaruseac@ankh:/tmp/5$ pip install tensorflow==1.14.0rc1
Collecting tensorflow==1.14.0rc1
  Downloading https://files.pythonhosted.org/packages/d3/29/cd1f608f260addce161745be44e5696c3d4ef04a9974940bce32787b2711/tensorflow-1.14.0rc1-cp35-cp35m-manylinux1_x86_64.whl (109.2MB)
     |████████████████████████████████| 109.2MB 45.0MB/s
Collecting gast>=0.2.0 (from tensorflow==1.14.0rc1)
Collecting tensorflow-estimator<1.15.0rc0,>=1.14.0rc0 (from tensorflow==1.14.0rc1)
  Using cached https://files.pythonhosted.org/packages/35/3c/c2ac7a2f56045adf1c94869fe012362b51bc8c94ac9e330823d207864904/tensorflow_estimator-1.14.0rc1-py2.py3-none-any.whl
Collecting protobuf>=3.6.1 (from tensorflow==1.14.0rc1)
  Using cached https://files.pythonhosted.org/packages/7c/d2/581ebc3c41879aca2c4fce5c37cdb8d779c4ea79109b6da7f640735ea0a2/protobuf-3.8.0-cp35-cp35m-manylinux1_x86_64.whl
Collecting keras-applications>=1.0.6 (from tensorflow==1.14.0rc1)
  Using cached https://files.pythonhosted.org/packages/71/e3/19762fdfc62877ae9102edf6342d71b28fbfd9dea3d2f96a882ce099b03f/Keras_Applications-1.0.8-py3-none-any.whl
Collecting keras-preprocessing>=1.0.5 (from tensorflow==1.14.0rc1)
  Using cached https://files.pythonhosted.org/packages/28/6a/8c1f62c37212d9fc441a7e26736df51ce6f0e38455816445471f10da4f0a/Keras_Preprocessing-1.1.0-py2.py3-none-any.whl
Collecting astor>=0.6.0 (from tensorflow==1.14.0rc1)
  Using cached https://files.pythonhosted.org/packages/d1/4f/950dfae467b384fc96bc6469de25d832534f6b4441033c39f914efd13418/astor-0.8.0-py2.py3-none-any.whl
Collecting absl-py>=0.7.0 (from tensorflow==1.14.0rc1)
Collecting six>=1.10.0 (from tensorflow==1.14.0rc1)
  Using cached https://files.pythonhosted.org/packages/73/fb/00a976f728d0d1fecfe898238ce23f502a721c0ac0ecfedb80e0d88c64e9/six-1.12.0-py2.py3-none-any.whl
Collecting wrapt>=1.11.1 (from tensorflow==1.14.0rc1)
Collecting google-pasta>=0.1.6 (from tensorflow==1.14.0rc1)
  Using cached https://files.pythonhosted.org/packages/d0/33/376510eb8d6246f3c30545f416b2263eee461e40940c2a4413c711bdf62d/google_pasta-0.1.7-py3-none-any.whl
Collecting termcolor>=1.1.0 (from tensorflow==1.14.0rc1)
Collecting numpy<2.0,>=1.14.5 (from tensorflow==1.14.0rc1)
  Using cached https://files.pythonhosted.org/packages/bb/ef/d5a21cbc094d3f4d5b5336494dbcc9550b70c766a8345513c7c24ed18418/numpy-1.16.4-cp35-cp35m-manylinux1_x86_64.whl
Collecting tensorboard<1.14.0,>=1.13.0 (from tensorflow==1.14.0rc1)
  Downloading https://files.pythonhosted.org/packages/0f/39/bdd75b08a6fba41f098b6cb091b9e8c7a80e1b4d679a581a0ccd17b10373/tensorboard-1.13.1-py3-none-any.whl (3.2MB)
     |████████████████████████████████| 3.2MB 33.4MB/s
Collecting grpcio>=1.8.6 (from tensorflow==1.14.0rc1)
  Using cached https://files.pythonhosted.org/packages/14/19/f1858ed60786ff681a5f8681448b56bffaaa87a81e9a7ca5cd075a873b35/grpcio-1.21.1-cp35-cp35m-manylinux1_x86_64.whl
Requirement already satisfied: wheel>=0.26 in ./lib/python3.5/site-packages (from tensorflow==1.14.0rc1) (0.33.4)
Requirement already satisfied: setuptools in ./lib/python3.5/site-packages (from protobuf>=3.6.1->tensorflow==1.14.0rc1) (41.0.1)
Collecting h5py (from keras-applications>=1.0.6->tensorflow==1.14.0rc1)
  Using cached https://files.pythonhosted.org/packages/4c/77/c4933e12dca0f61bcdafc207c7532e1250b8d12719459fd85132f3daa9fd/h5py-2.9.0-cp35-cp35m-manylinux1_x86_64.whl
Collecting werkzeug>=0.11.15 (from tensorboard<1.14.0,>=1.13.0->tensorflow==1.14.0rc1)
  Using cached https://files.pythonhosted.org/packages/9f/57/92a497e38161ce40606c27a86759c6b92dd34fcdb33f64171ec559257c02/Werkzeug-0.15.4-py2.py3-none-any.whl
Collecting markdown>=2.6.8 (from tensorboard<1.14.0,>=1.13.0->tensorflow==1.14.0rc1)
  Using cached https://files.pythonhosted.org/packages/c0/4e/fd492e91abdc2d2fcb70ef453064d980688762079397f779758e055f6575/Markdown-3.1.1-py2.py3-none-any.whl
Installing collected packages: gast, tensorflow-estimator, six, protobuf, numpy, h5py, keras-applications, keras-preprocessing, astor, absl-py, wrapt, google-pasta, termcolor, werkzeug, grpcio, markdown, tensorboard, tensorflow
Successfully installed absl-py-0.7.1 astor-0.8.0 gast-0.2.2 google-pasta-0.1.7 grpcio-1.21.1 h5py-2.9.0 keras-applications-1.0.8 keras-preprocessing-1.1.0 markdown-3.1.1 numpy-1.16.4 protobuf-3.8.0 six-1.12.0 tensorboard-1.13.1 tensorflow-1.14.0rc1 tensorflow-estimator-1.14.0rc1 termcolor-1.1.0 werkzeug-0.15.4 wrapt-1.11.1

(5) mihaimaruseac@ankh:/tmp/5$ python
Python 3.5.4 (default, Sep  5 2017, 18:32:10)
[GCC 7.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> from tensorflow.python.framework import tensor_util
>>> import tensorflow as tf
>>> tf.__version__
'1.14.0-rc1'
>>> tensor_util
<module 'tensorflow.python.framework.tensor_util' from '/tmp/5/lib/python3.5/site-packages/tensorflow/python/framework/tensor_util.py'>
>>>

Most likely there's some issue on your system?

@leimao Did you get chance to look on @mihaimaruseac comment. Let us know if that resolves your issue. Thanks!

Looks like the installation has some problems.
$ python3
Python 3.6.8 (default, Jan 14 2019, 11:02:34)
[GCC 8.0.1 20180414 (experimental) [trunk revision 259383]] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
>>> tf.__version__
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: module 'tensorflow' has no attribute '__version__'
>>>

I will try to install again.

Can also try
import tensorflow as tf
print(tf)

And that will give you the install location (something like /tmp/1/lib/python3.6/site-packages/tensorflow/__init__.py). Then, in the same directory you'll have a tensorflow-${version}/tf-nightly-${version} directory which gives you the version (for example /tmp/1/lib/python3.6/site-package/tf-nightly...)

Can also try
import tensorflow as tf
print(tf)

And that will give you the install location (something like /tmp/1/lib/python3.6/site-packages/tensorflow/__init__.py). Then, in the same directory you'll have a tensorflow-${version}/tf-nightly-${version} directory which gives you the version (for example /tmp/1/lib/python3.6/site-package/tf-nightly...)

My output looks funny.
$ python3
Python 3.6.8 (default, Jan 14 2019, 11:02:34)
[GCC 8.0.1 20180414 (experimental) [trunk revision 259383]] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
>>> tf.__version__
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: module 'tensorflow' has no attribute '__version__'
>>> print(tf)
<module 'tensorflow' (namespace)>

what if you print tf.VERSION instead?

what if you print tf.VERSION instead?

$ python3
Python 3.6.8 (default, Jan 14 2019, 11:02:34)
[GCC 8.0.1 20180414 (experimental) [trunk revision 259383]] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
>>> tf.__version__
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: module 'tensorflow' has no attribute '__version__'
>>> print(tf)
<module 'tensorflow' (namespace)>
>>> print(tf.VERSION)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: module 'tensorflow' has no attribute 'VERSION'

I will reinstall TensorFlow 1.14 anyway.

Were you able to resolve this issue? Thanks!

Were you able to resolve this issue? Thanks!

I have not got time to reinstall recently. I will try to make an install tomorrow. Which branch of the repository do you recommend me to use by the way? I am using Ubuntu 18.04 and CUDA 10.1. Thanks.

For 1.14 should use the r1.14 branch if you want to install from source.
Recommend doing a pip install if possible, though. Less chances for environment differences to cause issues

For 1.14 should use the r1.14 branch if you want to install from source.
Recommend doing a pip install if possible, though. Less chances for environment differences to cause issues

Looks like you guys have just uploaded a new wheel file for installation via pip. It seems to work for me now. Thanks.
$ python
Python 3.6.8 (default, Jan 14 2019, 11:02:34)
[GCC 8.0.1 20180414 (experimental) [trunk revision 259383]] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
>>> tf.__version__
'1.14.0'

While running the object detection using tensorflow , i'm getting the below error. I uninstalled and installed the tensorflow and have the latest version. Any help in this regard is appreciated.
Thanks much in advance.
"AttributeError: module 'wrapt' has no attribute 'ObjectProxy' "

Please open a new issue, @periraviteja Please fill in all the details in the issue template and also provide a proper minified reproducer.

@periraviteja have you been able to solve this error: "AttributeError: module 'wrapt' has no attribute 'ObjectProxy' "

@periraviteja您是否能够解决此错误：“ AttributeError：模块'wrapt'没有属性'ObjectProxy'“

我也遇到了这个问题

@DS-ejike , @periraviteja I have solved the problem, it due to wrapt using wrong version. Please install wrapt==1.11.1

pip install wrapt==1.11.1


Change index.html for website counter

Added a PHP function within the index file which counts the number of visitors on the website
Best,
Awaiting for your review.

Thanks @Ashleyt28 ,
It seems to be working, would you mind to change the the old picture with the new one along with the visitor counter in ReadMe.md?


Program aborts and reboots soon after startup

I have installed, compiled and flashed the project per instructions with latest esp toolchain and idf, but it fails and reboots every second or so.
Here is a gist of runtime log: https://gist.github.com/ruddy17/2bbe604671b0baacfa493007957604ca
There is a readable backtrace in the end of the log. Something wrong seem to happen in httpd_bind call, program goes to abort from there, then reboots.

Recompiled with v3.2.2 idf and it works like charm.


[v1.16] github: update rhel8 LVH image to rhel8.6

[ upstream commit 0eb46ada10527d3a1d3214fd83140c3dd9e58443 ]
When the LVH project started producing RHEL 8.9 images, the naming of the 8.6 images needed tweaking. Pick up the new naming scheme.

/test-backport-1.16

@aanm mind pressing the scary red button? CI is unhappy about a datapath flake when testing with 5.4 kernel. But this PR only touches the rhel8 kernel.


Add four argument vectorization for one and two lists

Not sure what to do for three & four lists yet...

So...

Behavior was changed for three-list vectorization to do zip(a, b, c)
Four argument vectorization added
¨v added for simple vectorization

We really need to fix those failing tests

Yeah it's blocking merge on everything


[Removal]: Cool Chili Griffin

Hotspot Name
Cool Chili Griffin
Hotspot b58 Address
11zvVVwTGiPRWvBRsD4HsWgi5c8Wzbt91tvBE5WvTx7E7h9mnoP
Discord Handle
No response
Hotspot Manufacturer
sensecap
Removal Reason
I searched in Romania, sensecap of 8gb ram, and I found on facebook marketplace, these 4 miners, at a quite attractive price, but unfortunately today I found today about this denylist! maybe you can help me use them in some way! I would like to make a small network in Calarasi! thanks!
Modifications
No
Extra forwarders
No
Extra antennas
No
Additional Information
I searched in Romania, sensecap of 8gb ram, and I found on facebook marketplace, these 4 miners, at a quite attractive price, but unfortunately today I found today about this denylist!
maybe you can help me use them in some way! I would like to make a small network in Calarasi! thanks!

We have taken into account this removal request in the next iteration of the denylist. It may take some time before it's processed. This is an automated comment due to the volume of addition and removal requests. A future tool is in the works to provide more insight into the analysis approach made by the Helium team and community members that maintain this list.


feat: add disabling of validators

Codecov Report

Merging #125 (8824c36) into main (8944a49) will decrease coverage by 0.19%.
The diff coverage is 94.44%.

:exclamation: Current head 8824c36 differs from pull request most recent head 99c2492. Consider uploading reports for the commit 99c2492 to get more accurate results

@@            Coverage Diff             @@
##             main     #125      +/-   ##
==========================================
- Coverage   99.79%   99.60%   -0.20%
==========================================
  Files          50       51       +1
  Lines        1460     1513      +53
  Branches      311      326      +15
==========================================
+ Hits         1457     1507      +50
- Misses          3        6       +3

Impacted Files
Coverage Δ

src/validators/RecordValidator.ts
96.77% <85.71%> (-3.23%)
:arrow_down:

src/validators/BaseValidator.ts
96.07% <86.66%> (-3.93%)
:arrow_down:

src/index.ts
100.00% <100.00%> (ø)

src/lib/configs.ts
100.00% <100.00%> (ø)

src/validators/ArrayValidator.ts
100.00% <100.00%> (ø)

src/validators/MapValidator.ts
100.00% <100.00%> (ø)

src/validators/ObjectValidator.ts
98.17% <100.00%> (+0.05%)
:arrow_up:

src/validators/SetValidator.ts
100.00% <100.00%> (ø)

src/validators/TupleValidator.ts
100.00% <100.00%> (ø)

Continue to review full report at Codecov.

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