Can I pass other dataset types to SSD model?

Hi I want to know if I can pass any other data set instead of Pascal VOC for custom object detection code with MobileNet SSD.
The material discussed by @dusty-nv says that VOC is just used for convention as it is standard format .
Other thing - If I want to create my own data set (a custom data set from images/videos I own) then can I use Roboflow ? What should be the data set directory containing? Are there suppose to be sub-folders? If yes then which? **Basically it would be great if you could help me understand the directory setup for my custom dataset ** !
I would appreciate other contributors to take a look and connect on this thread.

I believe it supports Pascal VOC and Google Open Images - its just that Pascal VOC is a significantly easier format to work with.  And I don't mean using the actual Pascal VOC, just organizing the data in the same way.  CVAT tool (cvat.org) can do this and will export in Pascal VOC format

From: Rajesh Roy @.>
Sent: Friday, August 6, 2021 5:30:47 PM
To: dusty-nv/jetson-inference @.>
Cc: Dustin Franklin @.>; Mention @.>
Subject: [dusty-nv/jetson-inference] Can I pass other dataset types to SSD model? (#1177)
Hi I want to know if I can pass any other data set instead of Pascal VOC for custom object detection code with MobileNet SSD.
The material discussed by @dusty-nvhttps://github.com/dusty-nv says that VOC is just used for convention as it is standard format .
Other thing - If I want to create my own data set (a custom data set from images/videos I own) then can I use Roboflowhttps://nam11.safelinks.protection.outlook.com/?url=https%3A%2F%2Froboflow.com%2F&data=04|01|dustinf%40nvidia.com|52e1968999b448582ab208d9592174b4|43083d15727340c1b7db39efd9ccc17a|0|0|637638822503560708|Unknown|TWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D|1000&sdata=mn%2BRHX6BfpLjBV%2FmWwAtbQB%2B9%2BFEPSR7kQtRo97fcsY%3D&reserved=0 ? What should be the data set directory containing? Are there suppose to be sub-folders? If yes then which? **Basically it would be great if you could help me understand the directory setup for my custom dataset **!
I would appreciate other contributors to take a look and connect on this thread.
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Ok I will try CVAT.
Meanwhile when I am using the downloader.py it is not downloading all the classes for dataset
root@jetson-desktop:/jetson-inference/python/training/detection/ssd# python3 open_images_downloader.py --stats-only --class-names "Aircraft, Handbag, Car" --data=data/vehicle
2021-08-08 18:39:45 - Download https://storage.googleapis.com/openimages/2018_04/class-descriptions-boxable.csv.
2021-08-08 18:39:45 - Requested 3 classes, found 3 classes
2021-08-08 18:39:45 - Download https://storage.googleapis.com/openimages/2018_04/train/train-annotations-bbox.csv.
2021-08-08 18:48:18 - Read annotation file data/vehicle/train-annotations-bbox.csv
Killed

Hi @dusty-nv - I tried CVAT to annotate few images but the code ran into precedence error. Please check this:
root@jetson-desktop:/jetson-inference/python/training/detection/ssd# python3 train_ssd.py --dataset-type=voc --data=data/package_counting/ --model-dir=models/package_counting --batch-size=2 --workers=1 --epochs=1
2021-08-08 19:48:52 - Using CUDA...
2021-08-08 19:48:52 - Namespace(balance_data=False, base_net=None, base_net_lr=0.001, batch_size=2, checkpoint_folder='models/package_counting', dataset_type='voc', datasets=['data/package_counting/'], debug_steps=10, extra_layers_lr=None, freeze_base_net=False, freeze_net=False, gamma=0.1, lr=0.01, mb2_width_mult=1.0, milestones='80,100', momentum=0.9, net='mb1-ssd', num_epochs=1, num_workers=1, pretrained_ssd='models/mobilenet-v1-ssd-mp-0_675.pth', resume=None, scheduler='cosine', t_max=100, use_cuda=True, validation_epochs=1, weight_decay=0.0005)
2021-08-08 19:48:52 - Prepare training datasets.
2021-08-08 19:48:52 - No labels file, using default VOC classes.
2021-08-08 19:48:52 - Stored labels into file models/package_counting/labels.txt.
2021-08-08 19:48:52 - Train dataset size: 9
2021-08-08 19:48:52 - Prepare Validation datasets.
2021-08-08 19:48:52 - No labels file, using default VOC classes.
2021-08-08 19:48:52 - Validation dataset size: 9
2021-08-08 19:48:52 - Build network.
2021-08-08 19:48:52 - Init from pretrained ssd models/mobilenet-v1-ssd-mp-0_675.pth
2021-08-08 19:48:53 - Took 0.55 seconds to load the model.
2021-08-08 19:49:07 - Learning rate: 0.01, Base net learning rate: 0.001, Extra Layers learning rate: 0.01.
2021-08-08 19:49:07 - Uses CosineAnnealingLR scheduler.
2021-08-08 19:49:07 - Start training from epoch 0.
/usr/local/lib/python3.6/dist-packages/torch/optim/lr_scheduler.py:123: UserWarning: Detected call of `lr_scheduler.step()` before `optimizer.step()`. In PyTorch 1.1.0 and later, you should call them in the opposite order: `optimizer.step()` before `lr_scheduler.step()`.  Failure to do this will result in PyTorch skipping the first value of the learning rate schedule. See more details at https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate
  "https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate", UserWarning)
warning - image side_1-36_jpeg.rf.e47a4903da95df2407c59da095a1b1a1 has object with unknown class 'Sack'
warning - image side_1-36_jpeg.rf.e47a4903da95df2407c59da095a1b1a1 has object with unknown class 'Sack'
warning - image side_1-13_jpeg.rf.e9f5964fbf6b3b93e3922c2f987b8eb9 has object with unknown class 'Carton'
Traceback (most recent call last):
  File "train_ssd.py", line 343, in <module>
    device=DEVICE, debug_steps=args.debug_steps, epoch=epoch)
  File "train_ssd.py", line 113, in train
    for i, data in enumerate(loader):
  File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py", line 363, in __next__
    data = self._next_data()
  File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py", line 989, in _next_data
    return self._process_data(data)
  File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py", line 1014, in _process_data
    data.reraise()
  File "/usr/local/lib/python3.6/dist-packages/torch/_utils.py", line 395, in reraise
    raise self.exc_type(msg)
IndexError: Caught IndexError in DataLoader worker process 0.
Original Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/worker.py", line 185, in _worker_loop
    data = fetcher.fetch(index)
  File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataset.py", line 207, in __getitem__
    return self.datasets[dataset_idx][sample_idx]
  File "/jetson-inference/python/training/detection/ssd/vision/datasets/voc_dataset.py", line 81, in __getitem__
    image, boxes, labels = self.transform(image, boxes, labels)
  File "/jetson-inference/python/training/detection/ssd/vision/ssd/data_preprocessing.py", line 34, in __call__
    return self.augment(img, boxes, labels)
  File "/jetson-inference/python/training/detection/ssd/vision/transforms/transforms.py", line 55, in __call__
    img, boxes, labels = t(img, boxes, labels)
  File "/jetson-inference/python/training/detection/ssd/vision/transforms/transforms.py", line 345, in __call__
    boxes[:, :2] += (int(left), int(top))
IndexError: too many indices for array: array is 1-dimensional, but 2 were indexed

Here is how my dataset looks like:
root@jetson-desktop:/jetson-inference/python/training/detection/ssd/data/package
_counting# ls
Annotations/  ImageSets/  JPEGImages/  Labels.txt  labelmap.txt

I thought the issue is with Pytorch as I found that it is not already installed in the machine. I went through the docker/build.sh command and later python is recognising the torch:
root@jetson-desktop:/jetson-inference/python/training/detection/ssd# python3
Python 3.6.9 (default, Oct  8 2020, 12:12:24)
[GCC 8.4.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> print(torch.__version__)
1.6.0
>>>
>>> print(torch.cuda.is_available())
True
>>> import torchvision
>>> print(torchvision.__version__)
0.7.0a0+78ed10c
>>>

But the errors are still fresh:
root@jetson-desktop:/jetson-inference/python/training/detection/ssd# python3 train_ssd.py --dataset-type=voc --data=data/package_counting --model-dir=models/package_counting --batch-size=2 --workers=1 --epochs=1
2021-08-08 21:11:55 - Using CUDA...
2021-08-08 21:11:55 - Namespace(balance_data=False, base_net=None, base_net_lr=0.001, batch_size=2, checkpoint_folder='models/package_counting', dataset_type='voc', datasets=['data/package_counting'], debug_steps=10, extra_layers_lr=None, freeze_base_net=False, freeze_net=False, gamma=0.1, lr=0.01, mb2_width_mult=1.0, milestones='80,100', momentum=0.9, net='mb1-ssd', num_epochs=1, num_workers=1, pretrained_ssd='models/mobilenet-v1-ssd-mp-0_675.pth', resume=None, scheduler='cosine', t_max=100, use_cuda=True, validation_epochs=1, weight_decay=0.0005)
2021-08-08 21:11:55 - Prepare training datasets.
2021-08-08 21:11:55 - VOC Labels read from file: ('BACKGROUND', 'Sack', 'Carton')
2021-08-08 21:11:55 - Stored labels into file models/package_counting/labels.txt.
2021-08-08 21:11:55 - Train dataset size: 9
2021-08-08 21:11:55 - Prepare Validation datasets.
2021-08-08 21:11:55 - VOC Labels read from file: ('BACKGROUND', 'Sack', 'Carton')
2021-08-08 21:11:55 - Validation dataset size: 9
2021-08-08 21:11:55 - Build network.
2021-08-08 21:11:55 - Init from pretrained ssd models/mobilenet-v1-ssd-mp-0_675.pth
2021-08-08 21:11:56 - Took 0.54 seconds to load the model.
2021-08-08 21:12:09 - Learning rate: 0.01, Base net learning rate: 0.001, Extra Layers learning rate: 0.01.
2021-08-08 21:12:09 - Uses CosineAnnealingLR scheduler.
2021-08-08 21:12:09 - Start training from epoch 0.
/usr/local/lib/python3.6/dist-packages/torch/optim/lr_scheduler.py:123: UserWarning: Detected call of `lr_scheduler.step()` before `optimizer.step()`. In PyTorch 1.1.0 and later, you should call them in the opposite order: `optimizer.step()` before `lr_scheduler.step()`.  Failure to do this will result in PyTorch skipping the first value of the learning rate schedule. See more details at https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate
  "https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate", UserWarning)
/usr/local/lib/python3.6/dist-packages/torch/nn/_reduction.py:44: UserWarning: size_average and reduce args will be deprecated, please use reduction='sum' instead.
  warnings.warn(warning.format(ret))
Traceback (most recent call last):
  File "train_ssd.py", line 346, in <module>
    val_loss, val_regression_loss, val_classification_loss = test(val_loader, net, criterion, DEVICE)
  File "train_ssd.py", line 150, in test
    for _, data in enumerate(loader):
  File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py", line 291, in __iter__
    return _MultiProcessingDataLoaderIter(self)
  File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py", line 737, in __init__
    w.start()
  File "/usr/lib/python3.6/multiprocessing/process.py", line 105, in start
    self._popen = self._Popen(self)
  File "/usr/lib/python3.6/multiprocessing/context.py", line 223, in _Popen
    return _default_context.get_context().Process._Popen(process_obj)
  File "/usr/lib/python3.6/multiprocessing/context.py", line 277, in _Popen
    return Popen(process_obj)
  File "/usr/lib/python3.6/multiprocessing/popen_fork.py", line 19, in __init__
    self._launch(process_obj)
  File "/usr/lib/python3.6/multiprocessing/popen_fork.py", line 66, in _launch
    self.pid = os.fork()
OSError: [Errno 12] Cannot allocate memory

Ok I will try CVAT.
Meanwhile when I am using the downloader.py it is not downloading all the classes for dataset
root@jetson-desktop:/jetson-inference/python/training/detection/ssd# python3 open_images_downloader.py --stats-only --class-names "Aircraft, Handbag, Car" --data=data/vehicle
2021-08-08 18:39:45 - Download https://storage.googleapis.com/openimages/2018_04/class-descriptions-boxable.csv.
2021-08-08 18:39:45 - Requested 3 classes, found 3 classes
2021-08-08 18:39:45 - Download https://storage.googleapis.com/openimages/2018_04/train/train-annotations-bbox.csv.
2021-08-08 18:48:18 - Read annotation file data/vehicle/train-annotations-bbox.csv
Killed

Figured out that there was no memory left for this. Fixed this with memory swapping. 👍

I thought the issue is with Pytorch as I found that it is not already installed in the machine. I went through the docker/build.sh command and later python is recognising the torch:
root@jetson-desktop:/jetson-inference/python/training/detection/ssd# python3
Python 3.6.9 (default, Oct  8 2020, 12:12:24)
[GCC 8.4.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> print(torch.__version__)
1.6.0
>>>
>>> print(torch.cuda.is_available())
True
>>> import torchvision
>>> print(torchvision.__version__)
0.7.0a0+78ed10c
>>>

But the errors are still fresh:
root@jetson-desktop:/jetson-inference/python/training/detection/ssd# python3 train_ssd.py --dataset-type=voc --data=data/package_counting --model-dir=models/package_counting --batch-size=2 --workers=1 --epochs=1
2021-08-08 21:11:55 - Using CUDA...
2021-08-08 21:11:55 - Namespace(balance_data=False, base_net=None, base_net_lr=0.001, batch_size=2, checkpoint_folder='models/package_counting', dataset_type='voc', datasets=['data/package_counting'], debug_steps=10, extra_layers_lr=None, freeze_base_net=False, freeze_net=False, gamma=0.1, lr=0.01, mb2_width_mult=1.0, milestones='80,100', momentum=0.9, net='mb1-ssd', num_epochs=1, num_workers=1, pretrained_ssd='models/mobilenet-v1-ssd-mp-0_675.pth', resume=None, scheduler='cosine', t_max=100, use_cuda=True, validation_epochs=1, weight_decay=0.0005)
2021-08-08 21:11:55 - Prepare training datasets.
2021-08-08 21:11:55 - VOC Labels read from file: ('BACKGROUND', 'Sack', 'Carton')
2021-08-08 21:11:55 - Stored labels into file models/package_counting/labels.txt.
2021-08-08 21:11:55 - Train dataset size: 9
2021-08-08 21:11:55 - Prepare Validation datasets.
2021-08-08 21:11:55 - VOC Labels read from file: ('BACKGROUND', 'Sack', 'Carton')
2021-08-08 21:11:55 - Validation dataset size: 9
2021-08-08 21:11:55 - Build network.
2021-08-08 21:11:55 - Init from pretrained ssd models/mobilenet-v1-ssd-mp-0_675.pth
2021-08-08 21:11:56 - Took 0.54 seconds to load the model.
2021-08-08 21:12:09 - Learning rate: 0.01, Base net learning rate: 0.001, Extra Layers learning rate: 0.01.
2021-08-08 21:12:09 - Uses CosineAnnealingLR scheduler.
2021-08-08 21:12:09 - Start training from epoch 0.
/usr/local/lib/python3.6/dist-packages/torch/optim/lr_scheduler.py:123: UserWarning: Detected call of `lr_scheduler.step()` before `optimizer.step()`. In PyTorch 1.1.0 and later, you should call them in the opposite order: `optimizer.step()` before `lr_scheduler.step()`.  Failure to do this will result in PyTorch skipping the first value of the learning rate schedule. See more details at https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate
  "https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate", UserWarning)
/usr/local/lib/python3.6/dist-packages/torch/nn/_reduction.py:44: UserWarning: size_average and reduce args will be deprecated, please use reduction='sum' instead.
  warnings.warn(warning.format(ret))
Traceback (most recent call last):
  File "train_ssd.py", line 346, in <module>
    val_loss, val_regression_loss, val_classification_loss = test(val_loader, net, criterion, DEVICE)
  File "train_ssd.py", line 150, in test
    for _, data in enumerate(loader):
  File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py", line 291, in __iter__
    return _MultiProcessingDataLoaderIter(self)
  File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py", line 737, in __init__
    w.start()
  File "/usr/lib/python3.6/multiprocessing/process.py", line 105, in start
    self._popen = self._Popen(self)
  File "/usr/lib/python3.6/multiprocessing/context.py", line 223, in _Popen
    return _default_context.get_context().Process._Popen(process_obj)
  File "/usr/lib/python3.6/multiprocessing/context.py", line 277, in _Popen
    return Popen(process_obj)
  File "/usr/lib/python3.6/multiprocessing/popen_fork.py", line 19, in __init__
    self._launch(process_obj)
  File "/usr/lib/python3.6/multiprocessing/popen_fork.py", line 66, in _launch
    self.pid = os.fork()
OSError: [Errno 12] Cannot allocate memory

@dusty-nv ?

OSError: [Errno 12] Cannot allocate memory

It's running out of memory - try these suggestions:

run train_ssd.py with --batch-size=1 workers=0
mount swap (sounds like you already did this)
disable the desktop GUI


capture async errors

Currently, any error inside the success handler for the indexeddb key lookup results in the database not loading, but the loadDatabase method (or autoload callback) returning successfully (so that the consuming method thinks everything is ok).
With these changes, I just tried to pass the error up through the callbacks, so I will know something is wrong when loadDatabase fails.

Are contributions unwelcome or ...?


react-big-calendar does not display anything but grid

In my case, react-big-calendar does not display antthing on month and agenda, but displays some empty grids on week and day and without styles.
here is my code :+1:

import React, { Component, PropTypes } from 'react';
import {render} from 'react-dom';
import {Meteor} from 'meteor/meteor';
import NavPro from '/imports/ui/components/NavPro.jsx';
import FooterPro from '/imports/ui/components/FooterPro.jsx';
import  'react-big-calendar/lib/css/react-big-calendar.css'
import BigCalendar from 'react-big-calendar';
import moment from 'moment';
import Events from './Events.jsx'; // https://github.com/jquense/react-big-calendar/blob/master/examples/events.js

const styled={
    agenda:{
        backgroundColor: '#af4a68',
    },
    calendar:{
      marginTop:'5vh',
    },
  };

BigCalendar.momentLocalizer(moment);

export default class Agenda extends Component {

 constructor(props, context)
    {

  super(props, context);
        this.context = context;
        this.state = {
          events: Events,
          culture: 'fr',
        };
        BigCalendar.setLocalizer(
        BigCalendar.momentLocalizer(moment)
        );
          this.handleSelectSlot = this.handleSelectSlot.bind(this);
          this.handleSelectEvent = this.handleSelectEvent.bind(this);
    }

    handleSelectSlot({start, end})
    {
        //create an event with title "Test"
        console.log("handleSelectSlot: " + start + " - " + end);
        this.state.events.push({start: start, end: end, title: "Test"});
        this.setState({});

    }

    handleSelectEvent()
    {
        //just for example
        console.log("handleSelectEvent: " + JSON.stringify(arguments));
    }

    EventWeek(props)
    {
        return {props.event.title}
    }

    EventAgenda(props)
    {
        return {props.event.title}
    }

  render() {
  console.log('this.state.events',this.state.events);

    return (

              <NavPro />

                <BigCalendar
                  selectable
                  popup
                  events={this.state.events}
                  onSelectSlot={this.handleSelectSlot}
                  onSelectEvent={this.handleSelectEvent}
                  defaultDate={new Date()}
                  style={styled.calendar}
                  eventPropGetter={e => ({ className: 'test-class'})} /* Here you can define a style for the element */
                  components={{
                  event: this.EventWeek,
                  agenda: {
                  event: this.EventAgenda
                   }
                   }}/>

                 <FooterPro />

    );
  }
}

Can you help, please ??

you probably need to use the startAccessor and endAccessor to point the calendar to the right properties on your events. I don't know what they look like so I can't really help with that

@jquense Thank's for your help, I fixe it by setting an explicit height on the calendar.
But it still in english, any idea on how to make it in french??

looks like you are using Moment, follow their documentation for globally setting cultures

ok

@jquense event this example https://github.com/intljusticemission/react-big-calendar/blob/master/examples/demos/cultures.js , in the documentation, does not work, at least, for me;  it throws an error: Error: Cannot find module 'globalize/lib/cultures/globalize.culture.en-GB' and other languages. Can you help please??

that exmaple uses globalize not moment. check out the internationalization documention for setting cultures in moment: http://momentjs.com/docs/#/i18n/

@jquense me too I'm using globalize

oof sorry, i'm really not an expert on setting up globalize 1.x.x, we use the older 0.1.x which is WAAAY simpler to setup

you can maybe use this as a starting point tho: https://github.com/jquense/react-widgets/blob/v4/.storybook/configure-globalize-new.js

@jquense does not resolve my problem; thank's for your effort.

Have same problem.
Cannot get it work. I use style={style} with the proper .css file but only grid displayed, no hours, no days just today in the week calendar. Could it be that I use it together with material-ui ?

@hoanghiep106 thanks for clarifying this. I was using
new Date(eventDate)
instead of
moment(eventDate)
when creating my events objects causing Safari to not recognise any event.

@

[__](

[ ] @ #

[ ]

[url](`

url

`)
)


pull requests are not being created

Describe the bug
My setup is not creating pull requests after it pushes to the branch
permissions:
  contents: write
  pull-requests: write

      - name: Download from Crowdin
        uses: crowdin/github-action@v1
        with:
          download_translations: true
          commit_message: "synced i18n translations from crowdin"
          localization_branch_name: i18n-translations
          create_pull_request: true
          pull_request_title: New Crowdin Translations
          pull_request_body: 'New Crowdin translations by [Crowdin GH Action](https://github.com/crowdin/github-action)'
          pull_request_base_branch_name: main
          source: "src/locales/en.po"
          translation: "src/locales/%two_letters_code%.po"

          token: ${{ secrets.CROWDIN_PERSONAL_TOKEN }}
          project_id: ${{ secrets.CROWDIN_PROJECT_ID }}

        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

Expected behavior
Creates a pull request as described
Additional context
Here are the relevant logs from the action:
Your branch is up to date with 'origin/main'.
Switched to a new branch 'i18n-translations'
PUSH TO BRANCH i18n-translations
[i18n-translations d97bf48] synced i18n translations from crowdin
 27 files changed, 378 insertions(+), 270 deletions(-)
remote:
remote: Create a pull request for 'i18n-translations' on GitHub by visiting:
remote:      https://github.com/EkuboProtocol/interface/pull/new/i18n-translations
remote:
To https://github.com/EkuboProtocol/interface.git
 * [new branch]      i18n-translations -> i18n-translations
CHECK IF ISSET SAME PULL REQUEST
CREATE PULL REQUEST
PULL REQUEST CREATED: null

Also, please try to explicitly allow GitHub Actions to create pull requests. This setting can be found in a repository's settings under Actions > General > Workflow permissions.
For repositories belonging to an organization, this setting can be managed by admins in organization settings under Actions > General > Workflow permissions.

It's interesting that this option is disabled. Is there a tooltip with the reason for disabling it?

Unfortunately no

This is probably the reason why the action cannot create a PR. Please try using an alternative action create-pull-request to see if it can create a PR

It's failing but I don't think for the same reason
      - name: Create Pull Request
        uses: peter-evans/create-pull-request@v5
        with:
          title: New Crowdin Translations
          body: 'New Crowdin translations by [Crowdin GH Action](https://github.com/crowdin/github-action)'
          base: main
          token: ${{ secrets.GITHUB_TOKEN }}
          branch: i18n-translations

Create or update the pull request branch
  /usr/bin/git symbolic-ref HEAD --short
  i18n-translations
  Working base is branch 'i18n-translations'
  /usr/bin/git checkout --progress -B 15146006-d319-[41](https://github.com/EkuboProtocol/interface/actions/runs/5660283434/job/15335656860#step:5:47)3f-93c0-4877fb1602b5 HEAD --
  Switched to a new branch '15146006-d319-413f-93c0-4877fb1602b5'
  /usr/bin/git status --porcelain -unormal --
  /usr/bin/git diff --quiet --
  /usr/bin/git diff --quiet --staged --
  /usr/bin/git stash push --include-untracked
  No local changes to save
  Resetting working base branch 'i18n-translations'
  /usr/bin/git checkout --progress i18n-translations --
  Switched to branch 'i18n-translations'
  /usr/bin/git reset --hard origin/i18n-translations
  fatal: ambiguous argument 'origin/i18n-translations': unknown revision or path not in the working tree.
  Use '--' to separate paths from revisions, like this:
  'git <command> [<revision>...] -- [<file>...]'
  Error: The process '/usr/bin/git' failed with exit code 128

i had to change it at the organization level and now the action creates pull requests
could be a good place to show an error message though instead of just pr: null


Update Character “earnest-clay”

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Sankalp_postman_certification

https://github.com/GSSoC24/Postman-Challenge/pull/4416

Merged already

Merged already

When will it be updated on the leaderboard?


How to use quantization methods to load models in a multi-machine environment

I have four 3070 GPUs. How can I use quantization methods to load the model and run Flux.1-dev?

You should find a int8 flux  checkpoint for diffusers.
You can try this one.
https://huggingface.co/Disty0/FLUX.1-dev-qint8
However, xDiT has not been tested with int8 flux-dev version.


change protobuf version to 3.8 then build failed

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

OS Platform and Distribution (e.g., Linux Ubuntu 14.04):
GCC 4.8.4
build CPU only

Describe the problem
when build tensorflow r1.5, upgrade protobuf version by changing proto buf urls, sha256,strip prefix value . Just  As followed:
"http://mirror.tensorflow.org/github.com/protocolbuffers/protobuf/archive/310ba5ee72661c081129eb878c1bbcec936b20f0.tar.gz",        "https://github.com/protocolbuffers/protobuf/archive/310ba5ee72661c081129eb878c1bbcec936b20f0.tar.gz",
PROTOBUF_SHA256 = "b9e92f9af8819bbbc514e2902aec860415b70209f31dfc8c4fa72515a5df9d59"
PROTOBUF_STRIP_PREFIX = "protobuf-310ba5ee72661c081129eb878c1bbcec936b20f0"
build commnd:
bazel build //tensorflow:libtensorflow_cc.so
the error message is :
ERROR: Skipping '//tensorflow:libtensorflow_cc.so': error loading package 'tensorflow': Extension file not found. Unable to load package for '@bazel_skylib//lib:versions.bzl': The repository could not be resolved
WARNING: Target pattern parsing failed.
ERROR: error loading package 'tensorflow': Extension file not found. Unable to load package for '@bazel_skylib//lib:versions.bzl': The repository could not be resolved
INFO: Elapsed time: 0.652s
INFO: 0 processes.
FAILED: Build did NOT complete successfully (0 packages loaded)
currently loading: tensorflow
how could I fix the problem  ?

And  no protobuf installed in my system

The TF team doesn't provide build support for versions as old as r1.5, sorry. Please try building the most recent release instead.


Can't compile set conversions to/from ListOf/TupleOf.

Similar to #333, but for compiled code:
Initializations like
    ListOf(int)(Set(int)({1,2,3}))
or
    Set(int)(ListOf(int)([1,2,3]))
work as interpreted code, but generate errors when compiled:
    Can't convert from type ListOf(Int64) to type Set(Int64)
    Can't convert from type Set(int) to type ListOf(int)
Similar behavior for TupleOf.

Scope can be expanded to exclude conversions from other containers (Dict, ConstDict).  Also could refine _can_convert* functions to make compilation more efficient.


Building iotedge in Yocto Kirkstone on a TI AM68A platform

Describe the bug
Trouble building the iotedge package in Yocto project Kirkstone release using bitbake.
To Reproduce
Steps to reproduce the behavior:

On a host Ubuntu 22.04 machine, download yocto-build and generate build directory using documentation at Processor SDK for AM68A - Building SDK with Yocto
Download meta-iotedge layer in the sources directory and add the path to bbconf file in build directory
Make changes to localconf file in build dir. Added following lines:
BBMASK += "${OEBASE}/sources/oe-core/meta/recipes-devtools/rust" BBMASK += "${OEBASE}/sources/oe-core/meta/recipes-devtools/cargo" PREFERRED_VERSION_rust ?= "1.66%" DISTRO_FEATURES:append = " systemd virtualization" VIRTUAL-RUNTIME_init_manager = "systemd" VIRTUAL-RUNTIME_initscripts = "systemd-compat-units"
Used the following command to build iotedge in the build dir:
bitbake iotedge
Logs
ERROR: aziotctl-1.4.7.AUTOINC+91e058880c-r0 do_compile: ExecutionError('/media/rei-dev/d3e07922-2074-4f99-88d1-18778349e6a9/yocto-build/build/arago-tmp-default-glibc/work/aarch64-oe-linux/aziotctl/1.4.7.AUTOINC+91e058880c-r0/temp/run.do_compile.250136', 101, None, None)
ERROR: Logfile of failure stored in: /media/rei-dev/d3e07922-2074-4f99-88d1-18778349e6a9/yocto-build/build/arago-tmp-default-glibc/work/aarch64-oe-linux/aziotctl/1.4.7.AUTOINC+91e058880c-r0/temp/log.do_compile.250136
Log data follows:
| DEBUG: Executing shell function do_compile
| NOTE: cargo = /media/rei-dev/d3e07922-2074-4f99-88d1-18778349e6a9/yocto-build/build/arago-tmp-default-glibc/work/aarch64-oe-linux/aziotctl/1.4.7.AUTOINC+91e058880c-r0/recipe-sysroot-native/usr/bin/cargo
| NOTE: rustc =
| NOTE: cargo build -v --target aarch64-oe-linux --release --manifest-path=/media/rei-dev/d3e07922-2074-4f99-88d1-18778349e6a9/yocto-build/build/arago-tmp-default-glibc/work/aarch64-oe-linux/aziotctl/1.4.7.AUTOINC+91e058880c-r0/git/aziotctl/Cargo.toml
| error: failed to get anyhow as a dependency of package aziotctl v1.4.7 (/media/rei-dev/d3e07922-2074-4f99-88d1-18778349e6a9/yocto-build/build/arago-tmp-default-glibc/work/aarch64-oe-linux/aziotctl/1.4.7.AUTOINC+91e058880c-r0/git/aziotctl)
|
| Caused by:
|   failed to load source for dependency anyhow
|
| Caused by:
|   Unable to update registry crates-io
|
| Caused by:
|   failed to update replaced source registry crates-io
|
| Caused by:
|   failed to parse manifest at /media/rei-dev/d3e07922-2074-4f99-88d1-18778349e6a9/yocto-build/build/arago-tmp-default-glibc/work/aarch64-oe-linux/aziotctl/1.4.7.AUTOINC+91e058880c-r0/cargo_home/bitbake/byte-unit-4.0.19/Cargo.toml
|
| Caused by:
|   namespaced features with the dep: prefix are only allowed on the nightly channel and requires the -Z namespaced-features flag on the command-line
| WARNING: /media/rei-dev/d3e07922-2074-4f99-88d1-18778349e6a9/yocto-build/build/arago-tmp-default-glibc/work/aarch64-oe-linux/aziotctl/1.4.7.AUTOINC+91e058880c-r0/temp/run.do_compile.250136:193 exit 101 from '"cargo" build -v --target aarch64-oe-linux --release --manifest-path=/media/rei-dev/d3e07922-2074-4f99-88d1-18778349e6a9/yocto-build/build/arago-tmp-default-glibc/work/aarch64-oe-linux/aziotctl/1.4.7.AUTOINC+91e058880c-r0/git/aziotctl/Cargo.toml "$@"'
| WARNING: Backtrace (BB generated script):
| 	#1: oe_cargo_build, /media/rei-dev/d3e07922-2074-4f99-88d1-18778349e6a9/yocto-build/build/arago-tmp-default-glibc/work/aarch64-oe-linux/aziotctl/1.4.7.AUTOINC+91e058880c-r0/temp/run.do_compile.250136, line 193
| 	#2: cargo_do_compile, /media/rei-dev/d3e07922-2074-4f99-88d1-18778349e6a9/yocto-build/build/arago-tmp-default-glibc/work/aarch64-oe-linux/aziotctl/1.4.7.AUTOINC+91e058880c-r0/temp/run.do_compile.250136, line 164
| 	#3: do_compile, /media/rei-dev/d3e07922-2074-4f99-88d1-18778349e6a9/yocto-build/build/arago-tmp-default-glibc/work/aarch64-oe-linux/aziotctl/1.4.7.AUTOINC+91e058880c-r0/temp/run.do_compile.250136, line 159
| 	#4: main, /media/rei-dev/d3e07922-2074-4f99-88d1-18778349e6a9/yocto-build/build/arago-tmp-default-glibc/work/aarch64-oe-linux/aziotctl/1.4.7.AUTOINC+91e058880c-r0/temp/run.do_compile.250136, line 206
ERROR: Task (/media/rei-dev/d3e07922-2074-4f99-88d1-18778349e6a9/yocto-build/sources/meta-iotedge/recipes-core/aziotctl/aziotctl_1.4.7.bb:do_compile) failed with exit code '1'

Build System (please complete the following information):

OS: Ubuntu
Version: 22.04

Target System (please complete the following information):

OS: Arago
Version: 2023
Machine: TI AM68A, j721s2-evm

Additional context
The Yocto project provided by TI has Rust version 1.59 by default

When I update the Rust version to 1.78 using meta-rust, I get the following error (detailed log in attached file)
error: field `0` is never read
|   --> iotedge/src/config/import/old_config/provisioning.rs:21:14
|    |
| 21 |     External(External),
|    |     -------- ^^^^^^^^
|    |     |
|    |     field in this variant
|    |
| note: the lint level is defined here
|   --> iotedge/src/lib.rs:3:27
|    |
| 3  | #![deny(rust_2018_idioms, warnings)]
|    |                           ^^^^^^^^
|    = note: `#[deny(dead_code)]` implied by `#[deny(warnings)]`
| help: consider changing the field to be of unit type to suppress this warning while preserving the field numbering, or remove the field
|    |
| 21 |     External(()),
|    |              ~~
|
| warning: `iotedge` (lib) generated 3 warnings (3 duplicates)
| error: could not compile `iotedge` (lib) due to 1 previous error; 3 warnings emitted
|

error-logs-meta-iotedge.txt

which kirkstone recipe are you building? This error usually comes when not using meta-rust layer but instead relying on the oe-core rust. It is at 1.59 and creates crate problems of versions used from nightly build

After the aforementioned issue, I updated my TI yocto project to Scarthgap so now I don't have issues with rust version. I pulled the main branch from meta-iotedge project, since it has updates for Scarthgap, and added it using bitbake using following commands -
bitbake-layers add-layer meta-iotedge
MACHINE="am68-sk" bitbake iotedge
MACHINE="am68-sk" bitbake -c cleanall tisdk-edgeai-image
MACHINE="am68-sk" bitbake -k tisdk-edgeai-image
I am able to compile and build the iotedge and OS image. But when I inspect the root directory of the OS after booting off of this new image, I don't find any files related to iotedge.
Any guidance as to how I can handle this issue?

I was able to install azure iot edge on the target platform. However, I am having trouble setting up edgeHub. Here is the logs:
`root@am68a-sk:/# sudo iotedge config apply -c '/etc/aziot/config.toml'
Warning: the previous identity config file is unreadable
Note: Symmetric key will be written to /var/secrets/aziot/keyd/device-id
Azure IoT Edge has been configured successfully!
Restarting service for configuration to take effect...
Stopping aziot-edged.service...Stopped!
Stopping aziot-identityd.service...Stopped!
Stopping aziot-keyd.service...Stopped!
Stopping aziot-certd.service...Stopped!
Stopping aziot-tpmd.service...Stopped!
Starting aziot-edged.mgmt.socket...Started!
Starting aziot-edged.workload.socket...Started!
Starting aziot-identityd.socket...Started!
Starting aziot-keyd.socket...Started!
Starting aziot-certd.socket...Started!
Starting aziot-tpmd.socket...Started!
Starting aziot-edged.service...Started!
Done.
root@am68a-sk:/# sudo iotedge check
Configuration checks (aziot-identity-service)
√ keyd configuration is well-formed - OK
√ certd configuration is well-formed - OK
√ tpmd configuration is well-formed - OK
√ identityd configuration is well-formed - OK
√ daemon configurations up-to-date with config.toml - OK
√ identityd config toml file specifies a valid hostname - OK
‼ aziot-identity-service package is up-to-date - Warning
Installed aziot-identity-service package has version 1.5.0 but 1.5.3 is the latest stable version available.
Please see https://aka.ms/aziot-update-runtime for update instructions.
√ host time is close to reference time - OK
√ preloaded certificates are valid - OK
√ keyd is running - OK
√ certd is running - OK
√ identityd is running - OK
√ read all preloaded certificates from the Certificates Service - OK
√ read all preloaded key pairs from the Keys Service - OK
√ check all EST server URLs utilize HTTPS - OK
√ ensure all preloaded certificates match preloaded private keys with the same ID - OK
Connectivity checks (aziot-identity-service)
√ host can connect to and perform TLS handshake with iothub AMQP port - OK
√ host can connect to and perform TLS handshake with iothub HTTPS / WebSockets port - OK
√ host can connect to and perform TLS handshake with iothub MQTT port - OK
Configuration checks
√ aziot-edged configuration is well-formed - OK
√ configuration up-to-date with config.toml - OK
√ container engine is installed and functional - OK
× configuration has correct URIs for daemon mgmt endpoint - Error
Unable to find image 'mcr.microsoft.com/azureiotedge-diagnostics:1.5.5' locally
docker: Error response from daemon: manifest for mcr.microsoft.com/azureiotedge-diagnostics:1.5.5 not found: manifest unknown: manifest tagged by "1.5.5" is not found.
See 'docker run --help'.
‼ aziot-edge package is up-to-date - Warning
Installed IoT Edge daemon has version 1.5.5 but 1.5.3 is the latest stable version available.
Please see https://aka.ms/iotedge-update-runtime for update instructions.
× container time is close to host time - Error
Could not query local time inside container
‼ DNS server - Warning
Container engine is not configured with DNS server setting, which may impact connectivity to IoT Hub.
Please see https://aka.ms/iotedge-prod-checklist-dns for best practices.
You can ignore this warning if you are setting DNS server per module in the Edge deployment.
‼ production readiness: logs policy - Warning
Container engine is not configured to rotate module logs which may cause it run out of disk space.
Please see https://aka.ms/iotedge-prod-checklist-logs for best practices.
You can ignore this warning if you are setting log policy per module in the Edge deployment.
‼ production readiness: Edge Agent's storage directory is persisted on the host filesystem - Warning
The edgeAgent module is not configured to persist its /tmp/edgeAgent directory on the host filesystem.
Data might be lost if the module is deleted or updated.
Please see https://aka.ms/iotedge-storage-host for best practices.
× production readiness: Edge Hub's storage directory is persisted on the host filesystem - Error
Could not check current state of edgeHub container
√ Agent image is valid and can be pulled from upstream - OK
√ proxy settings are consistent in aziot-edged, aziot-identityd, moby daemon and config.toml - OK
Connectivity checks
× container on the default network can connect to upstream AMQP port - Error
Container on the default network could not connect to reijetsons-iothub1.azure-devices.net:5671
× container on the default network can connect to upstream HTTPS / WebSockets port - Error
Container on the default network could not connect to reijetsons-iothub1.azure-devices.net:443
× container on the IoT Edge module network can connect to upstream AMQP port - Error
Container on the azure-iot-edge network could not connect to reijetsons-iothub1.azure-devices.net:5671
× container on the IoT Edge module network can connect to upstream HTTPS / WebSockets port - Error
Container on the azure-iot-edge network could not connect to reijetsons-iothub1.azure-devices.net:443
23 check(s) succeeded.
5 check(s) raised warnings. Re-run with --verbose for more details.
7 check(s) raised errors. Re-run with --verbose for more details.
2 check(s) were skipped due to errors from other checks. Re-run with --verbose for more details.
root@am68a-sk:/# sudo systemctl restart aziot-edged
root@am68a-sk:/# sudo iotedge system status
System services:
aziot-edged             Running
aziot-identityd         Running
aziot-keyd              Running
aziot-certd             Running
aziot-tpmd              Ready
Use 'iotedge system logs' to check for non-fatal errors.
Use 'iotedge check' to diagnose connectivity and configuration issues.
root@am68a-sk:/# sudo iotedge list
NAME             STATUS           DESCRIPTION      Config
edgeAgent        running          Up 27 seconds    mcr.microsoft.com/azureiotedge-agent:1.5`

Just to add to my previous comment, the main issue is as follows -
configuration has correct URIs for daemon mgmt endpoint - Error     Unable to find image 'mcr.microsoft.com/azureiotedge-diagnostics:1.5.5' locally     docker: Error response from daemon: manifest for mcr.microsoft.com/azureiotedge-diagnostics:1.5.5 not found: manifest unknown: manifest tagged by "1.5.5" is no
There is no version 1.5.5 for azureiotedge-diagnostics. I tried changing the azureiotedge-agent version to 1.5.9. However, this change did not resolve this issue. Can you kindly help me resolve this issue?

Just to add to my previous comment, the main issue is as follows - configuration has correct URIs for daemon mgmt endpoint - Error Unable to find image 'mcr.microsoft.com/azureiotedge-diagnostics:1.5.5' locally docker: Error response from daemon: manifest for mcr.microsoft.com/azureiotedge-diagnostics:1.5.5 not found: manifest unknown: manifest tagged by "1.5.5" is not found.
There is no version 1.5.5 for azureiotedge-diagnostics. I tried changing the azureiotedge-agent version to 1.5.9. However, this change did not resolve this issue. Can you kindly help me resolve this issue?

This issue was resolved in #178


Cannot open display :0.0

Is your feature request related to a problem:
No response
Describe the solution you'd like:
I don't know.
Describe alternatives you've considered:
I don't know.
Additional context:
weston.log

yltx@yltx:~$ cat /mnt/wslg/versions.txt
WSLg (x86_64): 1.0.61+Branch.main.Sha.54f177d201aecda01347f952e01777c75480fc74
Built at: Tue Apr 2 20:52:28 UTC 2024
Mariner: VERSION="2.0.20240112"
DirectX-Headers:
mesa:
pulseaudio: 6f045ff0dca233a939a2aba815f84d177e294122
FreeRDP: c4030980b29322a9cb2190711a5fadeeeb8b6a33
weston: f227edd681479ec3cb2290a25d84d2d3462aebfa
yltx@yltx:~$ echo $DISPLAY
:0.0
yltx@yltx:~$ ls -la /tmp/.X11-unix
总计 0
drwxrwxrwt  2 root root  40  7 月 31 17:59 .
drwxrwxrwt 12 root root 240  7 月 31 20:15 ..
yltx@yltx:~$ ls -la /tmp/.X11-unix/
总计 0
drwxrwxrwt  2 root root  40  7 月 31 17:59 .
drwxrwxrwt 12 root root 240  7 月 31 20:15 ..

One not directly relevant comment: This is a bug report but is posted as a feature request because the bug report template contains an error and is therefore no longer available since the last update a month ago. Please fix the template as well.

One not directly relevant comment: This is a bug report but is posted as a feature request because the bug report template contains an error and is therefore no longer available since the last update a month ago. Please fix the template as well.

In fact,you don't even have the tag for bug issue.

ubuntu22.04的wslg是基于systemd的一个bug运行起来的，24.04使用的systemd没有这个bug了反而用不了了，可以使用wslg-links来解决这个问题。#1244
The WSLg in Ubuntu 22.04 runs on a bug related to systemd,  while the systemd used in 24.04 no longer has this bug. You can use this wslg-links to resolve this issue temporary. #1244
另外, 如果你是直接安装的24.04版本，还有另一个问题 WSL/issues/468
wslg只对UID=1000的用户生效，直接安装的ubuntu24.04版本默认ubuntu用户的UID为1000（/mnt/wslg/runtime-dir权限决定），导致wsl创建的用户无法使用wslg。
可以手动编辑/etc/passwd对调UID，再使用chown切换家目录。
Besides, if you're using freshly-installed ubuntu 24.04 version, there's another issue mentioned in  WSL/issues/468 . you can use the method mentioned in the issue reply.

Maybe there is only unstable and insecure method:
manually edit /etc/passwd to swap uid
chown uid for home of swapped user


QPS drop more than 10% when upgrade from 5.2.3 to master with sysbench write only 64 threads workload.

Bug Report

What version of TiKV are you using?

/ # /tikv-server -V
TiKV
Release Version:   5.4.0-alpha
Edition:           Community
Git Commit Hash:   2a6bd805b0d0345e2bfd0b14f89f0301397ff549
Git Commit Branch: heads/refs/tags/v5.4.0-nightly
UTC Build Time:    2021-12-17 08:09:04
Rust Version:      rustc 1.56.0-nightly (2faabf579 2021-07-27)
Enable Features:   jemalloc mem-profiling portable sse test-engines-rocksdb cloud-aws cloud-gcp
Profile:           dist_release
What operating system and CPU are you using?

Cluster configuration:
PD: 3 replica,  4 core 8G Mem
Tidb: 2 replica, 8 core 16G Mem
Tikv: 4 replica, 8 core 16G Mem
Steps to reproduce

run oltp_fun_008 with write only 64 threads workload.
What did you expect?
Qps should same as before.
What did happened?
QPS drop from 24K to 21K.

/feature developing

/found automation


GetBalance(unspentonly=true) false positive

Hello,
We have some reports that GetBalance function with unspentonly flag set to true, for address 38DdqhVuqb36jjmxTbvBkiFPXKA8EmW9Ly (which has large number of outputs and unspents) , sometimes generates outputs which has been spent.
As I have studied logs, the false positives are reported for transactions(tx1) which output to the address and all of these outputs are consumed in transactions (tx2, tx3) such that all tx1, tx2 and tx3 are mined in the same block (This may be also a wrong pointer).
I will update, if was able to generate the case deterministicly..
Any help appreciated.
Can it be related to unclosed https://github.com/MetacoSA/QBitNinja/issues/19 ?
Thanks

1- By GetBalance I mean: https://github.com/MetacoSA/QBitNinja/blob/master/QBitNinja.Client/QBitNinjaClient.cs#L263

does it eventually sort out ?
If there is a double spend (user do routinely double spent by failing to properly lock), then the GetBalance call have a conflcitedOperation part. Which show other operations conflicting with another unconfirmed transaction.

Thanks for the info.
Actually the outputs shown as unspent (just sometimes) are for some months ago.

I have created the https://github.com/LykkeCity/Tools/tree/master/FalsePositiveTest to generate the error, but we switched from the address now, and no more large unspent outputs available. So I am not able to reproduce the possible problem now.

let's keep it open

OK. Thanks for your attention.

Unconfirmed transaction generate false Positive balance for me.
var wallet = new BitcoinPubKeyAddress("17QeH1HFQ74mtPrZzRHpyWHkHti9cVC5y9");
		var r = qb.GetBalance(wallet, true).Result;
		var xx = qb.GetBalanceSummary(wallet);
		Debug.WriteLine(xx.Result.Spendable.Amount);

this is incorrect behavior, money is already spent
blockchain.info show it fine

@BruceBayne thanks a lot, will take a look today.

@BruceBayne the reason for yours is because after a while (24H I think) qbitninja stop showing unconfirmed transactions, as it would result in your outputs being lock.

Oh thanks for fast reply, but i am stuck, right now, i cant extract Spendable coins.. can provide you any information about it

@BruceBayne  I just created <IP_ADDRESS> you can then use qbitClient.UnconfirmedExpiration=9999; and do your request like before. This will show your "lost" transaction.
http://qbitninja-mainnet.azurewebsites.net/balances/17QeH1HFQ74mtPrZzRHpyWHkHti9cVC5y9?unconfExpiration=9999
The default is 24.

Yes man! you made my day happy! Thank you a lot.  How i can help for your project?

Just by doing what you did. Identify missing feature, and either report or implement them.
Another suggestion: Creating an azure template to easily host a QBitNinja server.

Maybe we can describe this field in documentation or something similar?

yeah, in the main page of qbitninja there is sample queries, should add it there.


Increase timeout for broker condition polling in e2e

This fixes a problem I've seen in internal CI and reproduced on my own system:
W0216 15:54:33.763903       1 controller_broker.go:216] ClusterServiceBroker "ups-broker": Error getting broker catalog: Get http://ups-broker.e2e-tests-walkthrough-example-n45l2.svc.cluster.local/v2/catalog: net/http: request canceled while waiting for connection (Client.Timeout exceeded while awaiting headers)
Essentially anytime the initial catalog fetch timed out (for reasons I couldn't figure out) the walkthrough or broker e2e failed.

Nice addition with getting the UPS Broker pod logs on failure.  Logs have enough details with jacking up the -V level?

The user broker uses only glog.Info logging, so no reason to turn up the verbosity in this case.

The user broker uses only glog.Info logging, so no reason to turn up the verbosity in this case.

I am not sure if this is true. In my experience, every time I wanted to test the behavior of Service Catalog against ups-broker, there were no logs from ups-broker Pod at all, and I had to fix it by adding -v and -logtostderr to the Helm chart... But maybe I did something wrong, will raise a PR if I see this issue again.


[FEATURE] Create a footer

Is this a unique feature?

[X] I have checked "open" AND "closed" issues and this is not a duplicate

Is your feature request related to a problem/unavailable functionality? Please describe.
Create a footer
Proposed Solution
Create the footer with copyright and the current version of the website.
Screenshots
No response
Do you want to work on this issue?
No
If "yes" to above, please explain how you would technically implement this (issue will not be assigned if this is skipped)
No response

Yes i would like to work on this issue/feature
I went through the code base and noticed you used tailwind for styling so i will add a footer using some pre-built tailwind footer template and customize it according to the need of the site

Thanks @Piyush-Tilokani


Use uniform bucket level access on storage bucket

The requirement to use uniform bucket level access is a common organizational policy enforcement. Setting this to be explicitly true allows this terraform script to be used in projects with this policy.
https://cloud.google.com/storage/docs/uniform-bucket-level-access

Thanks for the PR @mhutchinson - This change makes sense to me. If you could please run terraform fmt on the file we'll get this merged!

Awesome, done! TIL about terraform fmt :-)


Update dependencies to be compatible with JupyterLab 4.x

Developer's Certificate of Origin 1.1
   By making a contribution to this project, I certify that:

   (a) The contribution was created in whole or in part by me and I
       have the right to submit it under the Apache License 2.0; or

   (b) The contribution is based upon previous work that, to the best
       of my knowledge, is covered under an appropriate open source
       license and I have the right under that license to submit that
       work with modifications, whether created in whole or in part
       by me, under the same open source license (unless I am
       permitted to submit under a different license), as indicated
       in the file; or

   (c) The contribution was provided directly to me by some other
       person who certified (a), (b) or (c) and I have not modified
       it.

   (d) I understand and agree that this project and the contribution
       are public and that a record of the contribution (including all
       personal information I submit with it, including my sign-off) is
       maintained indefinitely and may be redistributed consistent with
       this project or the open source license(s) involved.

We need a detailed issue for migration to JupyterLab 4, to keep track of all required steps, this PR could be step one.
In my opinion, it would be best to plan the steps more carefully, so they're better isolated. Changing all dependencies at once can affect everything, and the changes become complex too quickly.


Notifications don't include useful information

User reported

Notifications don't include useful information

this should no longer happen as all comment types are rigidly defined and display all appropriate info


Can you explain why we need to import the stylesheet? I'm curious why the styles aren't included in the components themselves. Also, we reduce the code size if we are not using every component.

That would be awesome if you add this information in the documentation. Thank you!


GoCoverage result incorrect

lines 226, 229, 233, 242 actually ran but coverage result shows red.

bellow is image debugging in line 229:

there is part of cover.cov result:
github.com/xtls/xray-core/app/dns/fakedns/fake.go:224.74,226.57 2 1
github.com/xtls/xray-core/app/dns/fakedns/fake.go:229.2,229.25 1 1
github.com/xtls/xray-core/app/dns/fakedns/fake.go:226.57,228.3 1 0
github.com/xtls/xray-core/app/dns/fakedns/fake.go:232.13,233.122 1 1
github.com/xtls/xray-core/app/dns/fakedns/fake.go:242.2,242.127 1 1
github.com/xtls/xray-core/app/dns/fakedns/fake.go:233.122,236.77 3 0
github.com/xtls/xray-core/app/dns/fakedns/fake.go:239.3,239.16 1 0
github.com/xtls/xray-core/app/dns/fakedns/fake.go:236.77,238.4 1 0
github.com/xtls/xray-core/app/dns/fakedns/fake.go:242.127,245.77 3 0
github.com/xtls/xray-core/app/dns/fakedns/fake.go:248.3,248.16 1 0
github.com/xtls/xray-core/app/dns/fakedns/fake.go:245.77,247.4 1 0

thanks, it was a bug, should have been fixed.

looks coverage highlight not as expect:

It may releated to new config option
  sign_partial_hl = "WarningMsg",

You should see three colors

Please check your colorscheme has WarningMsg

thanks for your reply, I've set color for WarningMsg , there are no need to highlight as partial  in my block

expect:

expect:

If you do not want to see partial tested to be coloured differently, you can set
 sign_partial_hl = "Error",

If you do not want to see partial tested to be coloured differently, you can set  sign_partial_hl = "Error", That will behave the same as the old version.
I mean partial highlight not correct in my blocks

Cool, it should be fixed

@y1rn Does the new version work for you?

new version work great, thx


Bug fixing recall in  _factual_correctness.py

Bug fixing recall in factual correctness:
recall is equal to: tp / (tp + fn)
but was calculated exactly like the precision.
Reference: https://docs.ragas.io/en/latest/concepts/metrics/available_metrics/factual_correctness/#factual-correctness

thanks alot for that catch @GitMarco27 - will be out in todays release ❤


pull request for e2e test at 01/08/2017 23:56:13

:white_check_mark: Validation status: passed
For more details, please refer to the build report.
Note: If you changed an existing file name or deleted a file, broken links in other files to the deleted or renamed file are listed only in the full build report.


Big refactor

Closes #80.

Hard to believe, but as of right now, gradle run -x test passes smoke test.

main/ changes probably done for now, barring bugs. It is able to build and pass basic testing, especially wrt contacts.json storage file read/save.
The tests are a whole different story. Will resume work on this possibly tonight.


Missing bad.robot.excel.Cell Implementation

Not all Excel cell types have equivalents in Simple-Excel. Specifically looking for the percentage type.

Closing for now. If anyone has a suggestion of how to handle things, feel free to reopen with details.


Add Kling-Gupta Efficiency

This PR adds the Kling-Gupta Efficiency hydrological model calibration/evaluation metric.
Gupta, H. V., Kling, H., Yilmaz, K. K., & Martinez, G. F. (2009). Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling. Journal of hydrology, 377(1-2), 80-91.
Additions

hydrotools.metrics.metrics.kling_gupta_efficiency

Removals

None

Changes

None

Testing

Added test_kling_gupta_efficiency to test_metrics

Notes

Closes #167

Todos

Implement later refinements to this metrics, as needed.

Checklist

[x] PR has an informative and human-readable title
[x] PR is well outlined and documented. See #12 for an example
[x] Changes are limited to a single goal (no scope creep)
[x] Code can be automatically merged (no conflicts)
[x] Code follows project standards (see CONTRIBUTING.md)
[x] Passes all existing automated tests
[x] Any change in functionality is tested
[x] New functions are documented (with a description, list of inputs, and expected output) using numpy docstring formatting
[x] Placeholder code is flagged / future todos are captured in comments
[x] Reviewers requested with the Reviewers tool :arrow_right:

Not only does it look good but it showed an error in some of my other code. And... approved.

Thanks for the review!


test: Update workflows for upgrade scenarios

Description

Update workflows for upgrade scenarios

Type of change

New feature (non-breaking change which adds functionality)

How Has This Been Tested?
Locally
Checklist:

[x] My code follows the style guidelines of this project
[x] I have performed a self-review of my own code
[x] I have commented my code, particularly in hard-to-understand areas
[ ] I have made corresponding changes to the documentation
[x] My changes generate no new warnings
[x] I have added tests that prove my fix is effective or that my feature works
[x] New and existing unit tests pass locally with my changes

/ok-to-test sha=28eb5ba60ef944ccc5cbbbb45f94761733635a95

/ok-to-test sha=43808fdfe1b247327549b853e2bab17efce5fdc9

/ok-to-test sha=b0f186310174dcef8fafc399d35464e83d629e03

/ok-to-test sha=b0f186310174dcef8fafc399d35464e83d629e03

/ok-to-test sha=96683b90e32c52f7184e0c96b3b0403e24304f6b


FR: Addition of more options

Hello,
I've been a long-time user of Bulk Rename Utility, but recently started using PowerToys so I gave your program a test.
I would love to see some mroe advanced features added like the Add/Remove n characters, Prefix/Insert/Suffix, numbering, etc.
https://www.bulkrenameutility.co.uk/assets/img-bru/bru_main2.png
All the best,
Dax.

I'd also love to see this!  I think prefix and suffix should be a priority, but adding sequencing either by name or date modified would be nice.  Saving some presets would also be really helpful.  Big fan of the tool - thanks for all of the hard work!

Welp. I just realized many of these advanced features can be done with RegEx and you've provided good documentation on examples.  It'd be great to have basics like Append/Suffix incorporated without the need for RegEx, but even just adding a quick RegEx reference chart to the tool would be helpful for the average user.


init too much list items on the infinite mode

Describe the bug
if we have 3 items originally will clone 18 items on the infinite mode
To Reproduce
go to https://codesandbox.io/s/still-architecture-j2e9m
open console and run document.querySelectorAll('.BrainhubCarouselItem')
Expected behavior
reduce the number of initial list items
Screenshots
If applicable, add screenshots to help explain your problem.
Environment

please paste the result of npx envinfo --system --binaries --browsers --npmPackages '@brainhubeu/*'
desktop or mobile (which device & OS if mobile)?
Browser [e.g. Chrome, Safari]

Additional context
Finally. I found that we have the config numberOfInfiniteClones (current is 3) to control the number of clones.

@sinchang
Thanks for reporting this.
I reproduced that. It happens also in the docs/ demo. It's strange that there are so many slides even before switching slides and it's contrary to the numberOfInfiniteClones.
You're welcome to open a PR.
You can also invite your colleagues to like (👍) this issue, so more 👍it has, it's more likely to be fixed by us.

@Lukasz-pluszczewski can we modify the numberOfInfiniteClones  to 1

The reason it has been set to 3 is to allow controlled carousel to show smooth animation when changing the slide index by a large number (e.g. if you have 3 slides, and want to animate infinite carousel moving by 10 slides to the right)
It may have a significant performance impact especially on mobile, so I'm ok with changing the default value to 1, but keeping in mind the above, I would maybe add it as optional parameter.

@piotr-s-brainhub @Lukasz-pluszczewski is there any way to change numberOfInfiniteClones to 1 through props?
I would be grateful if you would suggest how this can be regulated.
Thank you.

@R1cro
Currently, it's not possible because it's hardcoded in the config but a simple PR should be able to change this.

@R1cro it's possible in carousel v2 (currently in beta). More details here https://brainhubeu.github.io/react-carousel/docs/plugins/plugins#infinite-plugin

@R1cro
Currently, it's not possible because it's hardcoded in the config but a simple PR should be able to change this.

Would a PR making this changeable through props get accepted for release before 2.0? We currently experience crashes on some IOS devices and in our case we don't need that many clones. I would be happy to add it if it would get merged. If not then we can work around it until 2.0 is released.


ak.zip needs to check for empty input and do something appropriate

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/jpivarski/irishep/uproot4/uproot4/behaviors/TBranch.py", line 1164, in arrays
    return library.group(output, expression_context, how)
  File "/home/jpivarski/irishep/uproot4/uproot4/interpretation/library.py", line 528, in group
    return awkward1.zip(
  File "/home/jpivarski/miniconda3/lib/python3.8/site-packages/awkward1/operations/structure.py", line 348, in zip
    out = awkward1._util.broadcast_and_apply(layouts, getfunction, behavior)
  File "/home/jpivarski/miniconda3/lib/python3.8/site-packages/awkward1/_util.py", line 972, in broadcast_and_apply
    out = apply(broadcast_pack(inputs, isscalar), 0)
  File "/home/jpivarski/miniconda3/lib/python3.8/site-packages/awkward1/_util.py", line 564, in apply
    checklength([x for x in inputs if isinstance(x, awkward1.layout.Content)])
  File "/home/jpivarski/miniconda3/lib/python3.8/site-packages/awkward1/_util.py", line 480, in checklength
    length = len(inputs[0])

The problem is in awkward1/operations/structure.py", line 348, in zip; there needs to be a check for length zero arguments.
This ought to be super easy.

I must have written this in a hurry. I think it means that the following doesn't work:
>>> ak.zip([])

and
>>> ak.zip({})

While it might seem silly that someone would try to do that, my stack trace shows that this is coming from Uproot.
The zip is not going to know what the length of the array is supposed to be. When coming from Uproot, the length should be set by num_entries. This really ought to be fixed in Uproot, not in Awkward Array. (Maybe the ak.zip documentation should add the word "non-empty".) Transferring the issue...


619 make partition immutable

Make sure you have checked all steps below.
Issue

My PR resolves issue #619 - Making the partitions immutable

Resolves https://github.com/gchq/sleeper/issues/619

Tests

My PR has changed the partition tests to allow for an immutable model

I've raised some follow-up issues from this:

https://github.com/gchq/sleeper/issues/1034
https://github.com/gchq/sleeper/issues/1035
https://github.com/gchq/sleeper/issues/1036
https://github.com/gchq/sleeper/issues/1037
https://github.com/gchq/sleeper/issues/1038


Oauth2 support without Python

Due to inactivity, I picked up this PR: https://github.com/bazel-contrib/rules_oci/pull/581
I implememented the mentioned workarounds, i.e. in case of windows, I try to run script using powershell, otherwise, I fallback to curl and then wget, both wrapped in a bash script.
I tested these with an azure repo which requires oauth2. I also tested it on windows. I found that the config.json is not found due to "stat" binary not existing on windows, so I fixed this too.

Okay, this looks a bit better, this could use some tests similar to https://github.com/bazel-contrib/rules_oci/blob/2.x/e2e/assertion/oci_pull_auth_tests.bats
We will also need better error messages.

While trying to oci.pull an azure container registry, I still get this error:
Error in download: java.io.IOException: Error downloading [<>] to /home/siyer/.cache/bazel/_bazel_siyer/c0c06e0bd45258079fb49c5a3cba7fd4/external/rules_oci~~oci~ard_x86_64_base/www-authenticate.json: GET returned 401 Unauthorized

The PR #600 had actually fixed that issue for me though I didn't like the way it was done either

we should somehow incorporate that change here. identity tokens are not something we support at the moment, so we might as well it right at once and improve on it.

While trying to oci.pull an azure container registry, I still get this error:
Error in download: java.io.IOException: Error downloading [<>] to /home/siyer/.cache/bazel/_bazel_siyer/c0c06e0bd45258079fb49c5a3cba7fd4/external/rules_oci~~oci~ard_x86_64_base/www-authenticate.json: GET returned 401 Unauthorized

The PR #600 had actually fixed that issue for me though I didn't like the way it was done either

If I az acr login --name <my repo> from terminal and then run bazel with changes in this PR it works. While it doesn't work without these changes at all.

Okay, this looks a bit better, this could use some tests similar to https://github.com/bazel-contrib/rules_oci/blob/2.x/e2e/assertion/oci_pull_auth_tests.bats
We will also need better error messages.

I think I fixed everything requested except for tests.
Current tests do not pass for me so it is hard to develop new, any suggestions?
I run them like this:
% pwd
/Users/lukasz/dev/rules/rules_oci/e2e/pull
% bazel test //:test_nobzlmod

And this is the test log that I get:
test.log

While trying to oci.pull an azure container registry, I still get this error:
Error in download: java.io.IOException: Error downloading [<>] to /home/siyer/.cache/bazel/_bazel_siyer/c0c06e0bd45258079fb49c5a3cba7fd4/external/rules_oci~~oci~ard_x86_64_base/www-authenticate.json: GET returned 401 Unauthorized

The PR #600 had actually fixed that issue for me though I didn't like the way it was done either

If I az acr login --name <my repo> from terminal and then run bazel with changes in this PR it works. While it doesn't work without these changes at all.

I added common --repo_env=OCI_ENABLE_OAUTH2_SUPPORT=1 to my bazelrc
uodated Module.bzl with this commit as a git_override (4f78d52446b074a377d7e12a1baf7ac8072a7343)
az acr login --name <container_registry>

I ran the bazel with the above three changes
ERROR:
File "/home/siyer/.cache/bazel/_bazel_siyer/c0c06e0bd45258079fb49c5a3cba7fd4/external/rules_oci~/oci/private/authn.bzl", line 304, column 30, in _get_token
		rctx.download(
Error in download: java.io.IOException: Error downloading [<redacted>] to /home/siyer/.cache/bazel/_bazel_siyer/c0c06e0bd45258079fb49c5a3cba7fd4/external/rules_oci~~oci~<image_name>/www-authenticate.json: GET returned 401 Unauthorized

So, I think the problem is in parsing the ~/.docker/config.json:
siyer@siyer-ThinkPad-T15g-Gen-2i:~/workspace/container/BuildFarm$ cat ~/.docker/config.json
{
	"auths": {
		"<registry>.azurecr.io": {
			"auth": "MDAwMDAwMDAtMDAwMC0wMDAwLTAwMDAtMDAwMDAwMDAwMDAwOg==",
			"identitytoken": "<redacted>"
		}
	}
}

Line 240 looks for what follows  ":" as password but as per this config it is ["identity_token"] when sep (":") does not exist

So, I think the problem is in parsing the ~/.docker/config.json:
siyer@siyer-ThinkPad-T15g-Gen-2i:~/workspace/container/BuildFarm$ cat ~/.docker/config.json
{
	"auths": {
		"<registry>.azurecr.io": {
			"auth": "MDAwMDAwMDAtMDAwMC0wMDAwLTAwMDAtMDAwMDAwMDAwMDAwOg==",
			"identitytoken": "<redacted>"
		}
	}
}

Line 240 looks for what follows ":" as password but as per this config it is ["identity_token"] . Since here auth is weirdly ending with ":" 00000000-0000-0000-0000-000000000000: , the "if not sep" condition fails and there is no error message and password is empty as well

My best bet is that you are using linux, I managed to reproduce the issue on ubuntu. So the fix in the current PR works for Mac OS, but not for linux.

I integrated fix from @ddeville to this PR, I believe we now have a complete support of azure across operating systems. And for oauth2 hopefully in all cases.

I am going to hold this for a little bit so we can figure out some testing infra for this. i'll circle back to this next week.

Hmm, there are some failures. Can you handle those?

@thesayyn it was a simple check missing, now it's all good

Great work! Looking forward to having it in the next releases.
Any chance @thesayyn we can get this merged for 1.8.1?

Thank you. @thesayyn will this also get pulled to 2.x?


Add code cov to metering points repository

Description
Configure codecov.io for metering points repository

Can we see a report before approving? 😇

Please provide some test that can be used to calculate the coverage


Navbar Responsiveness

The navbar is not aligned properly for mobile view. The logo, login, and Admin should be in a line. Register and Contact us should remain inside the dropbox

if this issue isn't done, i would like to do on it. please assign me to this issue

Sure, go ahead. I am assigning this to you.

Can you please assign this issue to me, am very eager to make it perfectly responsive

It is already done. i am waiting for pull request.


Fix for Updating Worldpay VAP RD commitments

Critical Changes
Changes
Issues Closed
Community Ideas Delivered
Features Intended for Future Release
Features for Elevate Customers
New Metadata
Deleted Metadata

Fixes are included in #6884


Fix parsing webhook message content to request body

Description

Use XContent builder to build json object for webhook request body and covert to string. This prevents escaping \n and keep it in the message string that gets passed
Format the title and message body a bit
fix the allowed config type literals in SPI plugin setting
Add UT

Issues Resolved
For Chime webhook we noticed that escape sequence like new line \n will lead to failed notification with SearializationException in the response from Chime webhook server.  Notice that Slack webhook feature doesn't have such issue before or after this change.
[2021-07-20T13:27:35,679][ERROR][o.o.n.s.f.WebhookDestinationFactory] [3c22fbe8fc7e.ant.amazon.com] Exception sending message: org.opensearch.notifications.spi.model.MessageContent@13f3b910
java.io.IOException: Failed: HttpResponseProxy{HTTP/1.1 400 Bad Request [Content-Type: application/json, Content-Length: 16, Connection: keep-alive, Date: Tue, 20 Jul 2021 20:27:35 GMT, x-amzn-ErrorType: SerializationException, x-amzn-RequestId: 2e761ad3-86a4-4efb-81f7-815baebba67c, X-Cache: Error from cloudfront, Via: 1.1 3f3347264bcaae7af741e2a2f692c6a1.cloudfront.net (CloudFront), X-Amz-Cf-Pop: SEA19-C3, X-Amz-Cf-Id: gYKFJ4ZLhRSmnJxxOg_ezECHcs_ZGKXG8su3-0gyejWEumMLCJx_tg==] ResponseEntityProxy{[Content-Type: application/json,Content-Length: 16,Chunked: false]}}

Check List

[ ] New functionality includes testing.

[ ] All tests pass, including unit test, integration test and doctest

[ ] New functionality has been documented.

[ ] New functionality has javadoc added
[ ] New functionality has user manual doc added

[x] Commits are signed per the DCO using --signoff

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.
For more information on following Developer Certificate of Origin and signing off your commits, please check here.

If not, could you convert the issue section to an issue for tracking?

If not, could you convert the issue section to an issue for tracking?

opened an issue for this


Example not 100% success

I followed steps listed in this page, and I cannot make it work locally with emulator. It prompts 500 error.
Here is my environment information:

OS: Windows 10 1909
Python version: 3.7.7

I tried this example in a new virtual env.
After troubleshoot, I figured out that the latest package of cookiecutter not compatible with botbuilder-core. This issue has been mentioned in below repo, but you didn't update this document.

Dependency mismatch

The fix would be easy, we just uninstall cookiecutter then install a specific version 1.7.0 by pip. Then issue just gone.
please keep this document updated or list the correct package version.
Thanks,
-Tony

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

ID: 30a20df2-727c-1afd-2b87-836ea1ea4f7a
Version Independent ID: 157fc262-fb1f-f12d-0890-e90119feb444
Content: Create a bot using Bot Framework SDK for Python - Bot Service
Content Source: articles/python/bot-builder-python-quickstart.md
Service: bot-service
GitHub Login: @emgrol
Microsoft Alias: kamrani

Thanks for pointing this out @kuacci. Closing this issue since it's a duplicate of issue 1807.


issue with react-native IOS 3DS integration

Contexte
As specified in the doc (see https://github.com/Adyen/adyen-react-native/blob/develop/docs/Configuration.md#example), we setup Adyen with theses informations (see returnUrl. We changed on purpose the package name for this issue):
const configuration = {
      environment: 'test',
      clientKey: 'SOME_CLIENT_KEY',
      countryCode: 'FR',
      amount: { currency: 'EUR', value: 1500 }, // Value in minor units
      returnUrl: `fr.gkueny.myapp://`,
      card: {
        showStorePaymentField: true,
        supported: ['maestro', 'mc', 'visa', 'cb'],
      },
    }

But on iOS 3DS payment, we face this error before 3DS action :
"Field value incorrect. Fields affected: [threeDSRequestorAppURL]"

To Reproduce
Steps to reproduce the behavior:

Setup a project with Adyen
Set your app package as returnUrl (exemple fr.gkueny.myapp://)
Try a 3DS payment
See the threeDSRequestorAppURLerror

Expected behavior
3DS work
Resolution
After getting in touch with Adyen support (Request #3786041), they suggest us a solution
Could you please leave the adyen package name in front of your package name?

"returnUrl":"adyencheckout://fr.gkueny.myapp",

This should solve the issue you are encountering.

It's indeed resolve our issue.
Is the documentation not up to date on this package? Or is there a deeper problem and the solution proposed by the support is just a workaround?

Hey @gkueny
Thanks for reaching out :)

"returnUrl":"adyencheckout://fr.gkueny.myapp",

I would suggest to do it other way around:
"returnUrl":"fr.gkueny.myapp://adyencheckout",

It is mentioned in README, but you are right - our Docs need to be updated. Thanks for pointing it out!

thanks and sorry I missed the right info in the doc 🤦♂

FYI, This issue is only effecting TEST environment.

Good to know !

Our documentation indeed need some grooming :)
It is always good to ask, so in future others can find the answer.


NumPy 2.0 support

NumPy 2.0 is coming out soon ( https://github.com/numpy/numpy/issues/24300 ). NumPy 2.0.0rc1 packages for conda & wheels came out at the beginning of April ( https://github.com/numpy/numpy/issues/24300#issuecomment-2030603395 ). Also NumPy is planning to release 2.0 on June 16th ( https://github.com/numpy/numpy/issues/24300#issuecomment-2125643448 )
To prepare for NumPy 2.0, it might be worthwhile to start testing against NumPy 2 in CI
NumPy has put out a migration guide. More details are in the release notes
If ITK makes use of NumPy's C API (and produces wheels that use it), having a release of ITK with wheels built against NumPy 2.0.0rc1 would be helpful to ensure NumPy 1 & 2 compatible wheels (as wheels built against NumPy 1 won't be compatible with NumPy 2). More details in this NumPy 2 ABI doc
Also as NumPy is tracking ecosystem support for NumPy 2.0, it would be helpful to share ITK current support status in issue (with any plans): https://github.com/numpy/numpy/issues/26191

@jakirkham thanks for the issue and links! :pray:
ITK has NumPy 1 & 2 compatible wheels, including the recently released itk-5.4.0.
I added CI-testing for NumPy pre-releases (currently NumPy 2.0 RC 2) in #4701 .
ITK uses the Python Buffer Protocol to work with NumPy so there are not NumPy C API issues. itk-5.4.0 includes fixes for NumPy Python API deprecation warnings from 1.X.

Great thanks Matt! 🙏


feat: dynamic limits for the Kafka Metrics dashboard

What this PR does / why we need it:
This adds support for dynamic limits coming from the API.
Which issue(s) this PR fixes
https://issues.redhat.com/browse/MGDSTRM-8426

:tada: This PR is included in version 1.35.0 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


Bug: env var not read from system anymore since version update v.4.1.2

Describe the bug
After updating to version 4.1.2 the deployment failed due to missing baseURL var.
Type:        InvalidArgumentException
Message:     _get_uri() requires a valid baseURL.
Filename:    */vendor/codeigniter4/framework/system/Helpers/url_helper.php
Line Number: 43

CodeIgniter 4 version
4.1.2
Affected module(s)
This is not yet clear.
Expected behavior, and steps to reproduce if appropriate
We are using heroku for deploying a ci4 project. As far as i know Heroku does not write a .env file into the root folder, but writes the vars into the systems env vars.
So here then defining baseURL worked until the latest update. With the latest update it does not read the baseURL var from the system anymore causing the issue mentioned on top.
Context

OS: Ubuntu (16?)
Apache 2.4.46
PHP version 7.4.19

My only guess is maybe it was this? https://github.com/codeigniter4/CodeIgniter4/pull/4561/files
Are you using app.baseURL for the key? if not, try that. Otherwise, maybe share the whole trace stack? I'm curious if somehow it is trying to load App before server variables have been propagated.

I usually only have to set baseURL.
But i tried to set app.baseURL and baseURL into the heroku settings without any luck.
Issue comes within the "post-install-cmd".
defined in my composer.json like this
"scripts": {
	"post-update-cmd": [
	     "@composer dump-autoload"
	],
	"post-install-cmd": [
            "php spark assets:publish",
	    "php spark migrate"
        ],
	"test": "phpunit"
},

The package used is "tatter/assets": "^2.2", here for the spark assets:publish cmd.
...
Published FontAwesome.json
Published Select2.json
Published Swiper.json
Published jQuery.json
6 manifests published.
An uncaught Exception was encountered

Type:        InvalidArgumentException
Message:     _get_uri() requires a valid baseURL.
Filename:    /Users/kjellweibrecht/Sites/mukken/simplefox-mukken-frontend/vendor/codeigniter4/framework/system/Helpers/url_helper.php
Line Number: 43
Script php spark assets:publish handling the post-install-cmd event returned with error code 9

6 manifests published.
That's the end of the Assets publish script, so I don't believe it is related.

It's very odd that your first spark command succeeds but not the second one. I cannot dig on this any more right now but maybe try setting $baseURL in app/Config/App.php to something benign (like http://localhost) and see if that fixes the CLI yet still uses your env setting for HTTP?
Also N.B. you can remove this, Composer handles it automatically now:
"post-update-cmd": [
	     "@composer dump-autoload"
	],

It's very odd that your first spark command succeeds but not the second one.
php spark migrate does not run before, php spark assets:publish is first.

Defining anything inside app/Config/App.php (http://localhost) worked fine here. Deployment runs fine now and page still looks good and does take the correct var.
Thanks for the tip!
But no clue what happens here.

That's the end of the Assets publish script, so I don't believe it is related.
Thought because of the line Script php spark assets:publish handling the post-install-cmd event returned with error code 9

Yay! Glad it worked. Please leave this issue open though, since that was definitely a bug that needs addressing.

Thought because of the line

You're totally right, I missed that. It runs the entire command and then proceeds to handleRequest() and crashes. Definitely something fishy there.

Alright, let me know if you need anything to reproduce the issue.
Thanks for your help.

@MGatner do you think this is due to the (string) cast on the URI object returned by current_url(true)? This is the diff of the change between v4.1.2...HEAD in system/CodeIgniter.php:
-$this->storePreviousURL((string) current_url(true));
+$this->storePreviousURL(current_url(true));

If I recall, string casting is problematic for URI?

String casts for URI are only a problem when it might be not be a project URI. In this case we're guaranteed it is this should be safe.

My best guess is due in part of #4561 disallowing non-namespaced calls to env vars and Heroku's policy of enforcing alphanum and underscore for its env vars' keys. Since @sfox-developer has said he's setting only baseURL as config var, app.baseURL won't be populated.
In this case, I think we can use our own env function to retrieve directly the env var. @sfox-developer can you try change app/Config/App.php and change $baseURL to env('baseURL', http://localhost);. Then in heroku dashboard, set baseURL to any URL other than localhost to see if it can retrieve the correct base url.

public $baseURL = env('baseURL', 'http://localhost');
@paulbalandan this leads to a
PHP Fatal error:  Constant expression contains invalid operations in /tmp/build_455805ae/app/Config/App.php on line 24

Since @sfox-developer has said he's setting only baseURL as config var, app.baseURL won't be populated.

I inserted both vars recently just to be sure (before 4.1.2 i was able to use baseURL only):

app.baseURL
baseURL

I tried to remove app.baseURL right now which leads to having localhost as baseURL as defined in app/Config/App.php
public $baseURL = 'http://localhost';
Having app.baseURL set in heroku, it works fine, and the correct URL is used.

public $baseURL = env('baseURL', 'http://localhost');
@paulbalandan this leads to a
PHP Fatal error: Constant expression contains invalid operations in /tmp/build_455805ae/app/Config/App.php on line 24

Sorry for this dumb suggestion. I forgot scalars and arrays are only allowed there.
This seems to be a side effect of #4561 disallowing non-namespaced getenv calls (to prevent calling the PATH system variable by mistake, and others). But since we have documented this change here, I think this should be anticipated.

In order for Config** classes to get their respective properties’ values from the .env, it is now necessary to namespace the property with the name of the class. Previously, the property names are enough but now disallowed because it can get system environment variables, like PATH.


Hotspot sync info delayed by several hours

I’ve noticed that it takes many hours for hotspot changes to register in the explorer. Not sure if this is a more fundamental blockchain issue or related to the explorer  itself, but I’m pretty sure it’s the explorer. Hotspots that go offline will take hours to register as such, and when the go back online (show a green light) the same thing happens.
Why is this the case? Has any thought been put into speeding this up?

this is a symptom of libp2p and slow gossip around the network. as more hotspots come online, some with poor or sub-par internet connection, it can greatly affect how hotspot status updates.
the next generation of light hotspots will remove dependency on libp2p and gossip.


#323 - created XmlException

Part of #323
Created XmlException class and used it in meta package.

Job gh:artipie/rpm-adapter#372 is not assigned, can't get performer


Compound extended

Syncing https://okgraph.xyz/?q=messari%2Fcompound-ethereum-extended

prefer https://github.com/messari/subgraphs/pull/480


INVALID_LOGIN: Invalid username, password, security token; or user locked out.

I am certainly correct that my credentials are correct. I even tried logging in into salesforce successfully a few times using those credentials. Is there anything that I am missing? I followed the installation docs.

#18

The pull request solved my issue.

@karlpatrickespiritu , thx for your collaboration.

no problem @davispeixoto. nice plugin btw 👍


support modern tokenizers for NLP

if we can support recent standard tokenizers (byte-pair, sentencepiece) etc such as used for modern transformer models, we'll have much better compatibility with current NLP models. (and the tokenizers can later be used for any kind of small/big word2vec/lstm/transformer etc models)
the only thing needed at first will be the ability to load and use a predefined (pretrained) tokenizer, such as the ones for say GPT-style models, or from huggingface.
here is a suitable codebase in typescript
https://github.com/botisan-ai/gpt3-tokenizer
let's evaluate if we can use it and if it can load existing pretrained tokenizers (a nice vocabulary size is 2^15 = 32k, but can start smaller for a proof of concept)

this will help for #491

are you guys looking towards allowing general huggingface tokenizers? maybe like https://praeclarum.org/2022/08/25/transformers-js.html
(no need to support the actual transformers yet in this issue, we'll make a follow-up issue later)

Yes, that's exactly the one we were looking into ( the latest web version from https://github.com/praeclarum/web-transformers), to find a way to implement  it in TFJS rather than ONNX as they did.

and this one as well:
https://github.com/xenova/transformers.js
but same problem again is that it usually does conversion pytorch->js via ONNX, which doesn't allow training. but as transformer architecture is simpler than CNNs (and same for all layers), it should be easy to later have the transformer trainable in tfjs.
but anyway, we only need tokenizers at first. standard LSTMs etc can also run nicely on top of tokenized input, which we can support as preprocessing for all NLP tasks


Connection refused when trying to use through a proxy

Firstly, thanks for creating this tool.
I am trying to use gobuster through a proxy and I am getting the following error:
gobuster dir -p 'http://<IP_ADDRESS>:3128' -u 'http://<IP_ADDRESS>/' -w /usr/share/wordlists/dirbuster/directory-list-2.3-medium.txt
===============================================================
Gobuster v3.0.1
by OJ Reeves (@TheColonial) & Christian Mehlmauer (@_FireFart_)
===============================================================
[+] Url:            http://<IP_ADDRESS>/
[+] Threads:        10
[+] Wordlist:       /usr/share/wordlists/dirbuster/directory-list-2.3-medium.txt
[+] Status codes:   200,204,301,302,307,401,403
[+] Proxy:          http://<IP_ADDRESS>:3128
[+] User Agent:     gobuster/3.0.1
[+] Timeout:        10s
===============================================================
2019/10/17 16:42:00 Starting gobuster
===============================================================
Error: error on running gobuster: Get http://<IP_ADDRESS>/0a6b3c25-426f-4143-81a0-e51b97ae998a: proxyconnect tcp: dial tcp <IP_ADDRESS>:3128: connect: connection refused

However, using curl, on the same url, it works:
 curl -x http://<IP_ADDRESS>:3128 http://<IP_ADDRESS>/0a6b3c25-426f-4143-81a0-e51b97ae998a
<!DOCTYPE HTML PUBLIC "-//IETF//DTD HTML 2.0//EN">

<title>404 Not Found</title>

Not Found

The requested URL /0a6b3c25-426f-4143-81a0-e51b97ae998a was not found on this server.

<address>Apache/2.2.22 (Ubuntu) Server at <IP_ADDRESS> Port 80</address>

Same problem here

could you please try this again with the latest version? I never had this problem when using gobuster via a proxy like burp

same here

can not reproduce


EPH: Bumping minimum version of @azure/event-hubs to "1.0.4".

:white_check_mark: Validation status: passed

File
Status
Preview URL
Details

processor/changelog.md
:white_check_mark:Succeeded

processor/lib/util/constants.ts
:white_check_mark:Succeeded

processor/package-lock.json
:white_check_mark:Succeeded

processor/package.json
:white_check_mark:Succeeded

processor/tests/eph.spec.ts
:white_check_mark:Succeeded

For more details, please refer to the build report.
Note: If you changed an existing file name or deleted a file, broken links in other files to the deleted or renamed file are listed only in the full build report.


2.0.0-RC1 release

release plan
date : will be updated

release note
will be updated

Some settings have not been changed, so change them and release again.


casia SURF test.zip password.

I have downloaded the casia surf dataset but I am unable to unzip the test set. I tried casia-cefa-test-572121-usd89f but it says incorrect password.
I would greatly appreciate if someone can provide the password for test.zip
thank you.
rachel

Even though you got the test images, it has no labels.

please can you share the password（dataset: casia-surf-cefa）?


onMouseOut event missing

Like in the title. I'm using newest ngx-leaflet release (5.0.1 i belive) and onmouseout event seems to be missing in leaflet.directive.

Huh... yeah, that event is totally missing. If you're feeling ambitious, you could put in a PR off the develop branch. You can mimic how the other events are handled. Otherwise, I'll take care of it when I get a chance. Though, I'm pretty slammed this month.
Thanks for noticing!

PR is in for Angular v8 that includes this change.

ngx-leaflet v6.x provides this event now. It's also the release that supports Angular v8. If you need it back-ported to Angular 7, let me know.


Bump to chart 3.1.0

Why are we making this change?
Releasing chart version 3.1.0

I bumped the badges in the chart readme too


Android Basics: Activity Lifecycle

URL of codelab
https://developer.android.com/codelabs/basic-android-kotlin-training-activity-lifecycle?continue=https%3A%2F%2Fdeveloper.android.com%2Fcourses%2Fpathways%2Fandroid-basics-kotlin-unit-3-pathway-1%23codelab-https%3A%2F%2Fdeveloper.android.com%2Fcodelabs%2Fbasic-android-kotlin-training-activity-lifecycle#4
In which task and step of the codelab can this issue be found?
Explore Configuration Changes
Describe the problem
While calling showCurrentDessert() method form onCreate() method when I rotate device's screen it only updates the image.
So I tried calling onDessertClicked() method instead of showCurrentDessert() it both updates the image, Desserts Sold and
the price but it increments the Dessert Sold and price each time I rotate the device screen.
Steps to reproduce?

Go to...
Click on...
See error...

Versions
Android Studio version:
Android Studio 4.1.1
API version of the emulator:
Using the actual device running on android pie
Additional information
Include screenshots if they would be useful in clarifying the problem.

It's important where you put the code to restore the instance state.  You must do it right after the line that initializes the binding.  It's important that you also restore the instance state before calling the lines to "Set the TextViews to the right values", so that revenue and amountSold will have the correct values before you set them in the text views.

It's important where you put the code to restore the instance state. You must do it right after the line that initializes the binding. It's important that you also restore the instance state before calling the lines to "Set the TextViews to the right values", so that revenue and amountSold will have the correct values before you set them in the text views.

Thank you !


Android ArrayIndexOutOfBoundsException and AbsListViewRecycleBin.addScrapView

Android ArrayIndexOutOfBoundsException and AbsListViewRecycleBin.addScrapView
java.lang.ArrayIndexOutOfBoundsException: length=2; index=894640594
Mapper.viewTypeFromViewClass(builder.viewType(object, position, mapper))

+1!

Is the same model class used for rendering multiple views? If so, allowsMultimapping should be returning true.

I have already added it (it was specified in your documentation) but I had no luck.
Anyway, I have found a way in order to fix it in your files.
In the file "MultiAdapter.java" you need to edit the "getViewTypeCount()" function in order to return always: 1.
@Override public int getViewTypeCount() {         return 1;         //return mapper.viewSize();     }
This has fixed the problem in every ListView.

mapper class
public static int viewTypeFromViewClass(Class<? extends BindableLayout> viewClass) {
return viewClass.getCanonicalName().hashCode();
}
if (viewClass.getCanonicalName().hashCode()) value is positive number
baseApdater method getItemViewType() value  > getViewTypeCount()
crash


Bad normalization when a collection contains multiple type

When a collection contains multiple type, the normalizer tries to normalize relation with a bad resource type.
Ex:
A Product class has a collection of Option.
Option class is abstract.
TextOption extends Option.
TimeOption extends Option.
When the product contains TimeOption and TextOption, the normalizer tries to normalize TextOption and TimeOption with the Option resource type.
This change guess resource type on each object in the collection before normalize relation.

Thank you @pvgnd. Even if the performance will be a bit degraded by this change, I think it make sense.
By the way, can you add proper Behat tests please?

:+1:

Ok, I'll try to add them this week.
Le 4 oct. 2015 7:39 PM, "Kévin Dunglas"<EMAIL_ADDRESS>a écrit :

[image: :+1:]
—
Reply to this email directly or view it on GitHub
https://github.com/dunglas/DunglasApiBundle/pull/290#issuecomment-145368446
.

Just having this problem when dealing with file uploads. Do you have the time to write a test or do you want me to do it?

I am quite busy this week due to holiday at the end of the week \o/
So if you have time to write tests, it's welcome :)

@pvgnd do you have the time to work on that?

Fixed in 2.0.


Testing for config file and environmental variable setup

Should be pretty basic, but needs to be checked off before merge.

Fixed in latest merge.


support osx_arm64 and linux_aarch64

Checklist

[ ] Used a personal fork of the feedstock to propose changes
[ ] Bumped the build number (if the version is unchanged)
[ ] Re-rendered with the latest conda-smithy (Use the phrase @conda-forge-admin, please rerender in a comment in this PR for automated rerendering)
[ ] Ensured the license file is being packaged.

Trying to get QGIS working under ARM: https://github.com/conda-forge/qgis-feedstock/pull/289

Hi! This is the friendly automated conda-forge-linting service.
I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.

@conda-forge-admin, please rerender

$BUILD_PREFIX/bin/../lib/gcc/aarch64-conda-linux-gnu/11.3.0/../../../../aarch64-conda-linux-gnu/bin/ld: $PREFIX/lib/libQt5WebKit.so: undefined reference to<EMAIL_ADDRESS>
Anyone have any ideas?

@conda-forge-admin, please rerender

@conda-forge/arm-arch any thoughts on this error? Seems like the wrong g++ is being picked up on aarch64? Appreciate any pointers, I'm out of ideas.

It is very likely that 5.15 does not support cross compilation on Linux well.
Try building natively on Travis, or through emulation on azure.

@conda-forge-admin, please rerender

Is it normal that it seems to be generating bindings for non Webkit stuff too?

Hmm I've often wondered that, but it only seems to create a package with the webkit stuff (plus QtDesigner which probably isn't ideal) maybe because the other stuff is already installed by pyqt? Happy to take any suggestions on improvements, but I can't see how to restrict what is built.
Would Travis be faster? Seems the error is now fixed anyway - thanks!

Travis would be faster...... But you have a 55 min limit.
Qemu is about 5x slower (at best) and typically 6x slower.
It's kinda a wash considering that the limit is 6 hours on azure, and 1 on Travis.

@conda-forge-admin please rerender

It really does seem to me that it is trying to rebuild all. which is why you might be running out of time.

Well, isn't the source from full pyqt?
If I recall, we tried to include this in PyQt feedstock, but folks don't want it there...

https://github.com/conda-forge/pyqt-feedstock/pull/117

@izahn I know you did lot's of work around this on the pyqt-feedstock. Any ideas?

That conversation indicates that our understanding, that it is recompiling everything is commensurate with the old understanding of others.
I think that it would be appropriate to work to consolidate the two feedstocks
We have made many dependencies optional for pyside2
https://github.com/conda-forge/pyside2-feedstock/blob/main/recipe/meta.yaml#L31
See how the tests down the line are adapted.

With regards to my old comment. I think the approach here strikes the right balance, between some optimization that is specific to conda-forge's unique constraints (i.e. build time) and having more granular control over dependencies.

I agree, thanks for your help and nudging me to have a closer look at how things were working 'under the hood'. The sip stuff is a mystery to me....

Uhmm, seems that something strange happened in the final build. Travis failed to pass. Since this is much faster now, maybe we can just go back to CI for everything?

No output has been received in the last 10m0s, this potentially indicates a stalled build or something wrong with the build itself.

Weird, might have to go back to Azure.


feat: instrument http gem

Provides instrumentation for https://github.com/httprb/http

Some small things, but this looks great, thanks!

@fbogsany https://github.com/open-telemetry/opentelemetry-ruby/pull/618