IE, Firefox, Chrome overflow scrolling - header alignment issue caused by margin

Hello!
I am seeing an issue on my page using overflow scrolling, both of which occur once the headers are floating (i.e., you have scrolled down). As you scroll horizontally, the header is aligned with the table but does not cover the complete width of the table, and once you have scrolled horizontally as far as you can, the header becomes misaligned.
I believe that these two issues are caused by an element between the container and the table that has a margin greater than 0.
Here is a jsfiddle showing the issue: https://jsfiddle.net/o4ckgnh3/1/
I have looked through your documentation (particularly about ideal HTML) and past closed issues, but I can't seem to find an explanation for why this happening. I apologize in advance if you have already addressed this in a previous issue or anywhere on your sight!
If you can help me solve this issue or at least explain why this can't be supported, that would be very much appreciated!
Additional information that might help-- 1) overflow scrolling has to be used because this content is within a pane, 2) there are multiple header rows, and 3) setting useAbsolutePositioning to true completely messes up the header rows in terms of position and style (not easily demonstrated in fiddle)
Chrome: Version 43.0.2357.132
IE: 11
Firefox: 39
jQuery.floatThead: 1.2.12
jQuery: 2.0.2
Thank you for any help you can give!

Hi,
here is an update fiddle that works better: https://jsfiddle.net/o4ckgnh3/2/ - your first row in the header was invalid html because it didnt contain the same number of columns as your table.
changing to useAbsolute fixes the other problem.
The reason that it is acting buggy is that this plugin expects that the scrolling container be a parent of the table (though its ok if there is stuff above and below the table, but not on the sides between it and the container) you have stuff on the sides.
Its really hard to calculate where the table header is to position the floating header over it in the layout mode that is broken, so thats why I make some assumptions about the scrolling container.

Okay, thanks for your response! The problem I'm still seeing with useAbsolute is that the header no longer respects the margin. The page I'm working with is a bit outdated, so I expect some things to be buggy! Thanks for the explanation.

If possible, if you put the scrolling container as the direct parent of the table, everything will work much better. You might be able to do that and restyle some other stuff instead of trying to fight the plugin


mac-os-fix for update

I got the updated version fixed for mac os on my own now.
But Multiband_Diffusion is not working.
I assume following the errors, because it heavy relies on torch.
Am I right, or is there a way to use it on CPU, without torch/CUDA enabled?

Still trying to figure out how MBD works, but from what i tested so far it uses far more VRAM..

yes, same impression. I tried to go through the necessary PyScrips to solve occurring errors on Mac with replacing some torch related lines with eG numpy solutions. Solved some issues, but still some way to go... keep you posted if I make progress

Hit this also when trying MDB, AssertionError: Torch not compiled with CUDA enabled, but good to know that it wouldn't probably run anyways on 16GB M1 Mac, medium and melody models run fine.


fix: homepage testimonial section

Description

added heading to the testimonial section
removed extra space between the testimonials

Related issue(s)
Fixes #727

@starlightknown Hi! As @akshatnema wrote, you should not remove package-lock.json but only push changed to the another files in this PR (without changes in package-lock.json) :)

Hope it's fine now

Left some comments.
Also noticed that the Red Hat logo is super small and the logos on the Supported by section are stretched. It shouldn't be because of your changes but I don't see this problem in production right now so I'm wondering if something you're doing is affecting other parts of the page thinking

actually it was small before making this PR, I mentioned it in the issue too. I didn't fix it but now it looks just fine on the site so someone might have fixed it.


Time and Memory consumption

Hi !
I'm trying to generate some sequence embeddings using your code almost directly:
        for b in tqdm(range(0,n,self.params["batch_size"])):
            for sent_ids in sentences_index[b:min(b+self.params["batch_size"], n)]:
                # Truncate if too long
                if len(sent_ids) > self.params['max_seq_length']:
                    sent_ids = sent_ids[:self.params['max_seq_length']]
                sent_mask = [1] * len(sent_ids)
                # Padding
                padding_length = self.params['max_seq_length'] - len(sent_ids)
                sent_ids += ([0] * padding_length)
                sent_mask += ([0] * padding_length)
                # Length Check
                assert len(sent_ids) == self.params['max_seq_length']
                assert len(sent_mask) == self.params['max_seq_length']

                features_input_ids.append(sent_ids)
                features_mask.append(sent_mask)

            batch_input_ids = torch.tensor(features_input_ids, dtype=torch.long)
            batch_input_mask = torch.tensor(features_mask, dtype=torch.long)
            batch = [batch_input_ids.to(self.device), batch_input_mask.to(self.device)]

            inputs = {"input_ids": batch[0], "attention_mask": batch[1]}
            self.model.zero_grad()

            with torch.no_grad():
                features = self.model(**inputs)[1]

            features = [layer_emb.cpu().numpy() for layer_emb in features]
            all_layer_embedding = []
            for i in range(features[0].shape[0]):
                all_layer_embedding.append(np.array([layer_emb[i] for layer_emb in features]))

            embed_method = utils.generate_embedding(self.params['embed_method'], features_mask)
            embedding.extend(embed_method.embed(self.params, all_layer_embedding))

        return embedding

However, this code on a 16Gb GPU takes ~2 seconds to get the embeddings of a batch of 20 sentences (and this time increases for each subsequent batch), and the GPU memory gets filled almost instantly. Am I missing something there or is it the performances I should expect ?
Thanks a lot for your help !

Hi @Thomzoy
You're right. It takes almost that long to obtain sentence features (let's say 2 seconds for 20 sentences). But it should not increase for each subsequent batch.
Can you check

if the gradient got disable all the time?
the batched data have been removed from GPU after they are been processed?
These might be the reason that memory increases and got filled after several batches.

Besides,
Use BERT-models are not very efficient in computation and memory.
I have two suggestions that you may try to speed up:

Change the maximum length setting for BERT model to the maximum length of the current processing batch. Because increasing the maximum length of BERT model can lead to almost linear memory consumption.
Adapt to multiple GPU settings.

Feel free to ask questions if it is not working well.

@BinWang28
Hi, @BinWang28 ,thank you for you great work. Here I also cater to the problem of time consumption. I use the infer coder just like the one from Thomzoy, however, I change then model into bert-base-chinese. When I tested the infer speed via Chinese dataset, I got 40 seconds for 100 sentences. The  maximum length setting for the model is 128, and I used 2 16Gb GPU. I'm wondering if you have any suggestions with my time consuming or did I miss anything?

@SharaLiu
Normally, it will not take so long. I will check within the following two days. Have you encountered the memory explosion issue as well?

No, I don't have the memory explosion issue. Thanks for your reply. :)
Bin Wang<EMAIL_ADDRESS>于2020年3月31日周二 下午12:01写道：

@SharaLiu https://github.com/SharaLiu
Normally, it will not take so long. I will check within the following two
days. Have you encountered the memory explosion issue as well?
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/BinWang28/SBERT-WK-Sentence-Embedding/issues/3#issuecomment-606385509,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AHCSV4SMCGW4UDZTMJ2GYILRKFTJLANCNFSM4LR4GCCQ
.

Hi @BinWang28
I am currently facing the memory explosion issue. The GPU (16G) gets filled after one iteration of @Thomzoy 's code and runs out of memory

Hi Kailash,
I did not see your comment on Github. Does it still happen?
On Tue, Jun 2, 2020 at 7:40 AM Kailash Karthik<EMAIL_ADDRESS>wrote:

Hi @BinWang28 https://github.com/BinWang28
I am currently facing the memory explosion issue. The GPU (16G) gets
filled after one iteration of @Thomzoy https://github.com/Thomzoy 's
code and runs out of memory
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/BinWang28/SBERT-WK-Sentence-Embedding/issues/3#issuecomment-637587111,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AGA37IHRAW53LRYRSKAMSP3RUUFPVANCNFSM4LR4GCCQ
.

--
Bin Wang
Ph.D. Candidate
Signal and Image Processing Institute
Graduate Student in Electrical and Computer Engineering
University of Southern California

Is it possible some of the slow down is because of the number of for loops in the code? Looking through sent_emb.py and util.py, I see several for loops/list comprehensions which could be replaced with vectorized torch/numpy operations.
@BinWang28, I have begun opening PR's for each of these cases if you want to take a look? :)

I too have the same memory consumption problem. I am using this to encode sentences of documents where typically each document has 100-500 sentences and this is taking a lot of time. And if we reproduce this implementation in TensorFlow will it be faster?

CUDA out of memory. Tried to allocate 15.91 GiB (GPU 0; 15.90 GiB total capacity*

def embed(sentences):
sentences_index = [tokenizer.encode(s, add_special_tokens=True) for s in sentences]
features_input_ids = []
features_mask = []
for sent_ids in sentences_index:
# Truncate if too long
if len(sent_ids) > params["max_seq_length"]:
sent_ids = sent_ids[: params["max_seq_length"]]
sent_mask = [1] * len(sent_ids)
# Padding
padding_length = params["max_seq_length"] - len(sent_ids)
sent_ids += [0] * padding_length
sent_mask += [0] * padding_length
# Length Check
assert len(sent_ids) == params["max_seq_length"]
assert len(sent_mask) == params["max_seq_length"]
      features_input_ids.append(sent_ids)
      features_mask.append(sent_mask)

  features_mask = np.array(features_mask)

  batch_input_ids = torch.tensor(features_input_ids, dtype=torch.long)
  batch_input_mask = torch.tensor(features_mask, dtype=torch.long)
  batch = [batch_input_ids.to(device), batch_input_mask.to(device)]

  inputs = {"input_ids": batch[0], "attention_mask": batch[1]}
  model.zero_grad()

  with torch.no_grad():
      features = model(**inputs)[1]

  # Reshape features from list of (batch_size, seq_len, hidden_dim) for each hidden state to list
  # of (num_hidden_states, seq_len, hidden_dim) for each element in the batch.
  all_layer_embedding = torch.stack(features).permute(1, 0, 2, 3).cpu().numpy()

  embed_method = utils.generate_embedding(params["embed_method"], features_mask)
  embedding = embed_method.embed(params, all_layer_embedding)
  return embedding

@chandu7077
How large is your batch size? A large batch size would lead to higher memory consumption.
Moving to Tensorflow will not bring much difference. It would speed up with multi-GPU enabled.


REST dispatcher for Image Service

Purpose
Resolves wso2/product-is#6971

Describe the problems, issues, or needs driving this feature/fix and include links to related issues in the following format: Resolves issue1, issue2, etc.

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Describe how you are implementing the solutions. Include an animated GIF or screenshot if the change affects the UI (email<EMAIL_ADDRESS>to review all UI text). Include a link to a Markdown file or Google doc if the feature write-up is too long to paste here.

User stories

Summary of user stories addressed by this change>

Release note

Brief description of the new feature or bug fix as it will appear in the release notes

Documentation

Link(s) to product documentation that addresses the changes of this PR. If no doc impact, enter “N/A” plus brief explanation of why there’s no doc impact

Training

Link to the PR for changes to the training content in https://github.com/wso2/WSO2-Training, if applicable

Certification

Type “Sent” when you have provided new/updated certification questions, plus four answers for each question (correct answer highlighted in bold), based on this change. Certification questions/answers should be sent to<EMAIL_ADDRESS>and NOT pasted in this PR. If there is no impact on certification exams, type “N/A” and explain why.

Marketing

Link to drafts of marketing content that will describe and promote this feature, including product page changes, technical articles, blog posts, videos, etc., if applicable

Automation tests

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Details about the test cases and coverage

Security checks

Followed secure coding standards in http://wso2.com/technical-reports/wso2-secure-engineering-guidelines? yes/no
Ran FindSecurityBugs plugin and verified report? yes/no
Confirmed that this PR doesn't commit any keys, passwords, tokens, usernames, or other secrets? yes/no

Samples

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Learning

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Is the image service component released from api-server repo?

Is the image service component released from api-server repo?

No not yet. https://github.com/wso2/identity-api-server/pull/64


#84 messaging

TODO::

test cases
local implementation testing

@nandagopalan have a look at the new archi
A couple of TODO questions, please have a look at them!


Development of an ERA5 cloud storage for efficient access

Description
Raven will need to access ERA5 data as a reference dataset in many workflows. Currently, ERA5 data are stored on THREDDS, but this is not efficient. Pangeo has an implementation of ERA5 that is functional and stored on amazon AWS servers, but the data is chunked for spatial access rather than for time-series. This project aims to develop a new, time-series oriented ERA5 access point using cloud storage and computing.
The Wasabi service will be used to store and access ERA5 data in the Amazon AWS ecosystem. Preliminary tests show that it will take a few seconds at most to extract basin-averaged time-series for multi-decade periods. The data will be stored in zarr format and chunked in such a way as to maximize speed for time-series analysis.
Steps
The implementation will be done in a few steps:
1- ERA5 worldwide domain (total precip [tp] and air temperature [tas] only at this stage, hourly data).
2- ERA5-Land ([tp] and [tas]) for North-America only , (due to file size limitations, only a subset of the global map can be accommodated)
3- ERA5 and ERA5-Land Snow Water Equivalent [sd] for North-America only
We will then consider other variables and regions according to the needs of PAVICS-Hydro and other users, depending on the required resources.  For example, pressure level data and ensembles are to be excluded for now. Only the actual reanalysis is made available.
Spatial Extents
Worldwide is self-explanatory
North-America will cover the region (first approximation/guess):
--- Latitude:    [15 85]
--- Longitude: [-167 -50] *Note that ERA5 data natively uses the [0;360]° convention rather than the [-180;180]° convention.
Temporal parameters
Data will be stored at the native hourly resolution and UTC times.
The covered period will start in 1979 and extend to the most recent periods available on our end.
Updating
Files will be manually updated at first. If all goes well, we should be able to implement an auto-updating scheme to allow users to access the most recent data at all times.
Thanks
Big thanks to @sebastienlanglois for the help and contributions, without whom this project would not be possible!

Thanks @richardarsenault for the exhaustive description.
To add further explanations on why Wasabi was selected as a cloud storage service rather than more traditional ones (AWS S3, GCS, etc.), the main reason is that Wasabi does not charge for egress fees or API requests, only for storage costs. Because we want data to be available to users both on cloud provider platforms and on local networks, the added egress fees from removing large amounts of data from the cloud to users would have added up quickly or the cost would've had to be passed to users!
Also, Wasabi has S3-compatible API connectivity option which means it can be used with the following python libraries : fsspec, s3fs, etc.

After discussions with @richardarsenault, here is a suggestion for bucket naming :
era5/...
  /world/
  /north-america/...
    /reanalysis/
    /ensemble/...
      /single-levels/
      /land/
       /pressure-levels/...
         /netcdf/
         /zarr/

With regards to Step 1 (ERA5 worldwide domain), all tp and t2m (ERA5 name for tas) netcdf files have been uploaded to the following bucket

bucket : era5/world/reanalysis/single-levels/netcdf
region_name : us-east-1
endpoint_url : https://s3.us-east-1.wasabisys.com

New files are added automatically on a daily basis with a 5 days lag with real time as per the CDS API design for ERA5. I will post examples to access the data in the coming days.
Before moving on and creating the ERA5 worldwide zarr dataset (Step 1), we should do some testing on a subset of the data to optimise how the dataset will be chunked. As mentioned by @richardarsenault, our use case is mainly for time series analysis. The optimal chunk to maximise speed for time-series retrieval is theoretically to include all time steps inside a chunk, however such approach would require to update all the chunk each time the dataset is updated (for instance on a daily or monthly basis) which effectively means to recreate the entire dataset each time. With the tests, we will try to find a more suitable approach for chunking that should take into account the dataset update frequency and the speed of data retrieval.
Depending on the size and costs of maintaining the zarr datasets, @huard also suggested to consider having application-specific zarr datasets for time series and spatial analysis applications (such as a zarr-temporal and a zarr-spatial bucket).

Tests - Zarr chunking
As promised, here are a couple of tests to experiment with zarr's chunking (with a subset of ERA5's data in the space dimension for tests purposes).
The tests datasets can be found in the following bucket : s3://era5/world/reanalysis/single-levels/zarr-tests
They are named according to how the dimensions were chunked (more chunking can be tested if requested):

era5-test-time-8784-longitude-2-latitude-2  (1 year per chunk)
era5-test-time-87840-longitude-1-latitude-1  (10 years per chunk)
era5-test-time-87840-longitude-2-latitude-5  (10 years per chunk)
era5-test-time-87840-longitude-5-latitude-5  (10 years per chunk)
era5-test-time-372552-longitude-1-latitude-1  (all timesteps per chunk)
era5-test-time-372552-longitude-2-latitude-2  (all timesteps per chunk)
era5-test-time-372552-longitude-5-latitude-5  (all timesteps per chunk)

The following code was tested both with :

A fairly slow home internet connection (50 Mbits/s (download)) as a baseline and hence the bandwidth speed is the main bottleneck when running it.
A Google Cloud Platform E2 VM instance

When working in scientific environments (cloud/academic/corporate networks) with fast bandwidth speed (1Gbps+), we expect the E2 VM instance to more accurately reflect the expected performance. I invite you to test it in your own environment (ping @richardarsenault, @huard, etc.).
# Time to extract all 372522 ERA5 t2m hourly time points at a specific pixel
# and at multiple pixels to simulate the size of a watershed

import fsspec
import xarray as xr
import time
import os
import hvplot.xarray
from dask.distributed import Client

client = Client()

client_kwargs = {'endpoint_url': 'https://s3.wasabisys.com',
                 'region_name': 'us-east-1'}

buckets_dirname = 's3://era5/world/reanalysis/single-levels/zarr-tests'

buckets_basename = ['era5-test-time-8784-longitude-2-latitude-2',
                    'era5-test-time-87840-longitude-1-latitude-1',
                    'era5-test-time-87840-longitude-2-latitude-2',
                    'era5-test-time-87840-longitude-5-latitude-5',
                    'era5-test-time-372552-longitude-1-latitude-1',
                    'era5-test-time-372552-longitude-2-latitude-2',
                    'era5-test-time-372552-longitude-5-latitude-5']

for bucket_basename in buckets_basename:

    bucket = os.path.join(buckets_dirname, bucket_basename)
    store = fsspec.get_mapper(bucket,
                              anon=True,
                              client_kwargs=client_kwargs)

    ds = xr.open_zarr(store, consolidated=True)
    start = time.time()
    da = (ds.t2m - 273.15)[:,-5,-5].load()
    end = time.time()
    print(bucket_basename, ' : ', end-start,' seconds')
    start = time.time()
    da = (ds.t2m - 273.15)[:,0:6,0:6].load()
    end = time.time()
    print(bucket_basename, ' (multiple pixels) : ', end-start,' seconds')

# With the 50 Mbits/s connection :
# era5-test-time-8784-longitude-2-latitude-2  :  1.5577044486999512  seconds
# era5-test-time-8784-longitude-2-latitude-2  (multiple pixels) :  5.472326755523682  seconds
# era5-test-time-87840-longitude-1-latitude-1  :  0.29694294929504395  seconds
# era5-test-time-87840-longitude-1-latitude-1  (multiple pixels) :  5.004878997802734  seconds
# era5-test-time-87840-longitude-2-latitude-2  :  2.889986991882324  seconds
# era5-test-time-87840-longitude-2-latitude-2  (multiple pixels) :  12.184975624084473  seconds
# era5-test-time-87840-longitude-5-latitude-5  :  3.0996978282928467  seconds
# era5-test-time-87840-longitude-5-latitude-5  (multiple pixels) :  11.215736627578735  seconds
# era5-test-time-372552-longitude-1-latitude-1  :  0.33968472480773926  seconds
# era5-test-time-372552-longitude-1-latitude-1  (multiple pixels) :  6.137498378753662  seconds
# era5-test-time-372552-longitude-2-latitude-2  :  0.6167998313903809  seconds
# era5-test-time-372552-longitude-2-latitude-2  (multiple pixels) :  4.357798337936401  seconds
# era5-test-time-372552-longitude-5-latitude-5  :  2.894357919692993  seconds
# era5-test-time-372552-longitude-5-latitude-5  (multiple pixels) :  11.943426370620728  seconds

# On the GCP E2 VM instance :
# era5-test-time-8784-longitude-2-latitude-2  :  1.3091447353363037  seconds
# era5-test-time-8784-longitude-2-latitude-2  (multiple pixels) :  8.865148305892944  seconds
# era5-test-time-87840-longitude-1-latitude-1  :  0.26541686058044434  seconds
# era5-test-time-87840-longitude-1-latitude-1  (multiple pixels) :  4.483410596847534  seconds
# era5-test-time-87840-longitude-2-latitude-2  :  0.6464042663574219  seconds
# era5-test-time-87840-longitude-2-latitude-2  (multiple pixels) :  0.7947907447814941  seconds
# era5-test-time-87840-longitude-5-latitude-5  :  0.32846498489379883  seconds
# era5-test-time-87840-longitude-5-latitude-5  (multiple pixels) :  1.1891248226165771  seconds
# era5-test-time-372552-longitude-1-latitude-1  :  0.27306079864501953  seconds
# era5-test-time-372552-longitude-1-latitude-1  (multiple pixels) :  1.621551513671875  seconds
# era5-test-time-372552-longitude-2-latitude-2  :  0.1411135196685791  seconds
# era5-test-time-372552-longitude-2-latitude-2  (multiple pixels) :  0.5919482707977295  seconds
# era5-test-time-372552-longitude-5-latitude-5  :  0.5591433048248291  seconds
# era5-test-time-372552-longitude-5-latitude-5  (multiple pixels) :  0.8325531482696533  seconds

Here is a snapshot of one of the tests dataset (ds) :

and a quick graph to visualise the data once it is loaded to the user's computer :
%%time
(da.hvplot(grid=True, label='t2m')* \
da.resample(time='1Y').mean().hvplot(label='t2m-yearly')).opts(legend_position='top')

Other food for thoughts
Daily zarr datasets ?
So far, we have kept the hourly time steps for zarr which we should do for the main dataset in Step 1. However, assuming most users will usually need daily time steps, it could be interesting to add another zarr dataset at the daily resolution (t2m, tmax, tmin and tp). Such dataset would be minimal in terms of size and costs (1/12th the size of the main hourly dataset) and would allow for sub-second requests even for users with poor internet connections. The downside with this approach is that conversion to the appropriate timezone from UTC would have to be done before aggregating to the daily time step which means having zarr daily datasets for multiples north american timezones.

 The previous dataset had some issues that are probably related to using Copernicus' experimental netcdf format as a basis for the zarr conversion rather than their native grib format. This current zarr dataset was therefore created from grib files and for now, only this format should be used to append the zarr dataset. ERA5's netcdf files are still fine if they are not transformed to zarr.
What is new :

ERA5 can now be accessed directly from the catalog :

Chunks are more reasonable than previous iteration. The intent is still to speed up data access for queries in the time dimension but some spatial analysis are still possible

What is coming :

Appending the dataset will be achieved with https://github.com/pangeo-forge/pangeo-forge-recipes/issues/37 once the feature is added to the library

A word on performance

The zarr dataset was tested on a large cluster (about 100 cores) to compute the mean temperature along all dimensions which means processing 1.4 Terabytes of data. The calculation took about 11 minutes which means about 17 Gbits were processed every second. The more we throw nodes at the problem, the faster the computation gets done as access to cloud storage can scale linearly (no practical server bandwidth limit) .

Since this issue was created, we've my team has released https://github.com/google-research/arco-era5. I was wondering if the folks in this issue would like to join forces and work together on an Phase 2 of our project :)

Just wanted to document a few updates about this issue before we close it.
I am happy to report that we were able to achieve all the goals we set ourselves at the start of this issue.
We now have 2 datasets:

era5_single_levels_reanalysis (fully operational right now)
era5_land_reanalysis (will be fully operational in a few weeks)

These terabyte-scale analysis-ready cloud-optimised (ARCO) datasets are (will be for ERA5-Land) freely and remotely accessible from anywhere (cloud or local laptop), efficient for time-series analysis + some regional spatial analyses and updated weekly. I believe they are among the firsts climate datasets to share all these properties, so hopefully, they are used a lot !
Up next, we intend to add more variables and possibly, other datasets. Stay tuned!


vk-cli: init at 0.7.6

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Things done

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[ ] macOS
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21.11 Release Notes (or backporting 21.05 Relase notes)

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

[x] Fits CONTRIBUTING.md.

I'm not sure what the policy is for adding abandoned projects to nixpkgs but this might be better added to your own NUR

I'm not sure what the policy is for adding abandoned projects to nixpkgs but this might be better added to your own NUR

I already have it in NUR. But I thought why not in nixpkgs. The package is working.

@ofborg eval
(Sorry, ofborg's certs recently had an issue, meaning that it was unable to
react to PRs. This has been fixed, but all PRs filed in this period will need
ofborg to be manually kicked off.)

@ofborg eval
(Sorry, ofborg's certs recently had an issue, meaning that it was unable to
react to PRs. This has been fixed, but all PRs filed in this period will need
ofborg to be manually kicked off.)

Well thank you

you'll want to squash the 3 commits into one :)

@SuperSandro2000 Okay, I'll fix it later. please check the rest of the PR.

@SuperSandro2000 ?

@SuperSandro2000 Please check my PR


Add SnapshotsInProgressTests

Summary of the changes / Why this improves CrateDB
Follow up for https://github.com/crate/crate/pull/10113
Checklist

[x] Added an entry in CHANGES.txt for user facing changes
[x] Updated documentation & sql_features table for user facing changes
[x] Touched code is covered by tests
[x] CLA is signed
[x] This does not contain breaking changes, or if it does:

It is released within a major release
It is recorded in CHANGES.txt
It was marked as deprecated in an earlier release if possible
You've thought about the consequences and other components are adapted
(E.g. AdminUI)

retest this please


Rename test file so it actually runs

The test file name didn't start with "test" so didn't run before :S. I've also reduced the tolerances so it passes.
By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.

Codecov Report

Merging #228 into master will increase coverage by 1.28%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master     #228      +/-   ##
==========================================
+ Coverage   87.98%   89.26%   +1.28%
==========================================
  Files         111      111
  Lines        3187     3187
  Branches      337      337
==========================================
+ Hits         2804     2845      +41
+ Misses        318      276      -42
- Partials       65       66       +1

Impacted Files
Coverage Δ

emukit/core/optimization/optimizer.py
80.99% <0%> (-2.48%)
:arrow_down:

emukit/model_wrappers/simple_gp_model.py
98.38% <0%> (+70.96%)
:arrow_up:

Continue to review full report at Codecov.

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LeafletUtil library doesn't work for me

on file @asymmetrik\ngx-leaflet-draw\dist\leaflet-draw\core\leaflet-draw.directive.js. On the line 13, if it's possible to change this line :
import { LeafletDirective, LeafletDirectiveWrapper, LeafletUtil } from '@asymmetrik/ngx-leaflet';
Into this two line :
import { LeafletDirective, LeafletDirectiveWrapper } from '@asymmetrik/ngx-leaflet';
import { LeafletUtil } from<EMAIL_ADDRESS>Other way, the leafletUtil library doesn't work for me ...

Yea, it's true. Angular CLI can not find this class with an existing import.

The latest version of @asymmetrik/ngx-leaflet exports LeafletUtil correctly, so you shouldn't need this change for it to work. Can you verify you're using at least<EMAIL_ADDRESS>

Yeah ! perfect, it's working for me now ! thanks a lot !
And i didn't use<EMAIL_ADDRESS>because i'm using Angular 6 and the<EMAIL_ADDRESS>is for Angular 7 right ?
But in all case that's working perflectly righyt now so many thanks for your reactivity ;)

I'm using the v4.0.0. What am I supposed to do?

v4 of ngx-leaflet?

Sorry if this is not the place to ask, but is there a version that is supported with Angular 6.x.x?
I'm running into brick walls, so if you have any tips I'd appreciate them.
Upgrading to 7.x is not an option at this time.


VRTTrigger and layers TouchCollider and GrabCollider should go.

Subject says all

Implemented and merged. Also got rid of various other old layers, and various tags that are no longer used.


chore: remove unnecessary validation check for multi format schema

Description
After having a look at the multiFormatSchema file for https://github.com/asyncapi/spec-json-schemas/pull/495, there is no reason to do this extra check as everything comes through anySchema.

nope:
AssertionError [ERR_ASSERTION]: Document /Users/pavelbodyachevskiy/IdeaProjects/spec-json-schemas/test/docs/3.0.0/streetlights-all.json must be validated correctly: [
    {
        "instancePath": "/components/schemas/Json-ReferencedSchema",
        "schemaPath": "#/required",
        "keyword": "required",
        "params": {
            "missingProperty": "$ref"
        },
        "message": "must have required property '$ref'"
    },
    {
        "instancePath": "/components/schemas/Json-ReferencedSchema/schema",
        "schemaPath": "#/allOf/2/then/properties/schema/oneOf",
        "keyword": "oneOf",
        "params": {
            "passingSchemas": [
                0,
                1
            ]
        },
        "message": "must match exactly one schema in oneOf"
    },
    {
        "instancePath": "/components/schemas/Json-ReferencedSchema",
        "schemaPath": "#/allOf/2/if",
        "keyword": "if",
        "params": {
            "failingKeyword": "then"
        },
        "message": "must match \"then\" schema"
    },
    {
        "instancePath": "/components/schemas/Json-ReferencedSchema",
        "schemaPath": "#/if",
        "keyword": "if",
        "params": {
            "failingKeyword": "then"
        },
        "message": "must match \"then\" schema"
    },
    {
        "instancePath": "/components/schemas/Json-ReferencedSchema",
        "schemaPath": "#/properties/schemas/patternProperties/%5E%5B%5Cw%5Cd%5C.%5C-_%5D%2B%24/oneOf",
        "keyword": "oneOf",
        "params": {
            "passingSchemas": null
        },
        "message": "must match exactly one schema in oneOf"
    }
]

@Pakisan it does not solve your problem, but it cleans up the definition even more after your PR is merged.

Ok. I thought that this MR is for replace my changes

No not at all :v:
@Pakisan I also see you have this change in your own PR, so if it is merged before this one with these changes I will just close this PR 🙂


Allow web content to load while splashscreen is displayed

Is your feature request related to a problem? Please describe.
Currently, the splashscreen loads in the same window as the main web content. This means that you can't have the splashscreen displayed while your web app loads, so it is only useful if you have a lot of Rust initialization code first.
Describe the solution you'd like
If the splashscreen was loaded in a separate window/process from the main web content, it could be displayed until the web content finishes loading, instead of just when it starts loading.
Describe alternatives you've considered
Build in a splashscreen to the web app itself.
Additional context

Solved with multi window support coming in the next release :tada:


Basic docs outline to be filled in

@mg0716 cool - let me take a shot at writing the docs for auth.

@mg0716 really would love to find a auth API that just does this stuff for us.


Detecting a wrong package name for scipy 1.9.2 installed by pip

It seems that licensed detects a wrong package name for scipy 1.9.2.
The license file in the scipy package seems to be generated by combining the license for scipy itself (BSD 3-clause) and licenses for bundled libraries.
You can find the actual license file (scipy-1.9.2.dist-info/LICENSE.txt) in the distribution package (a ZIP archive):
https://files.pythonhosted.org/packages/af/8e/552314ba91f257c2857d17f5a76dc21c63fe58a24634934cfecdd5eb56b2/scipy-1.9.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
When running licensed cache for scipy 1.9.2, it generates a cache file GCC runtime library.dep.yml with the following contents:
---
name: GCC runtime library
version: 1.9.2
type: pip
summary: Fundamental algorithms for scientific computing in Python
homepage: https://scipy.org/
license: none
licenses: []
notices: []

The license file in the scipy package contains an entry for "GCC runtime library" as third entry of bundled libraries.
I have no idea how licensed picks it up and use its name for the cache file, but there may be two problems here:

It looks like that licensed determines the name of the cache file from information in the license file. I guess it should instead use package information directly.
Licensed might be failing to parse the first part of the scipy license file as a BSD 3-clause licensed. At a glance it looks like a normal BSD 3-clause license sentences.

Thanks for the report!  I'll take a closer look at this during my daytime tomorrow (MST USA timezone) and try to set up a repro, but in the meantime can you provide any info about the following:

run pip list and see if GCC runtime library is listed as an installed package
run pip show scipy in your project and see if there is anything there related to the GCC runtime library dependency
is there a cached license metadata file for scipy.dep.yml with accurate information (name, version, licenses)?

Thank you for a response!

run pip list and see if GCC runtime library is listed as an installed package

No, GCC runtime library doesn't show up in pip list, while scipy does.

run pip show scipy in your project and see if there is anything there related to the GCC runtime library dependency

pip show scipy displays the whole license text including the bundled libraries. There is nothing else related to the GCC runtime library.

is there a cached license metadata file for scipy.dep.yml with accurate information (name, version, licenses)?

No, scipy.dep.yml doesn't exist when installing scipy==1.9.2. When scipy==1.9.1 is installed, the following scipy.dep.yml is generated:
---
name: scipy
version: 1.9.1
type: pip
summary: 'SciPy: Scientific Library for Python'
homepage: https://www.scipy.org
license: other
licenses:
- sources: LICENSE.txt
  text: [The whole license text]
notices: []

Sorry for the delay on this.  I've opened https://github.com/github/licensed/pull/555 as a fix.

It looks like that licensed determines the name of the cache file from information in the license file. I guess it should instead use package information directly.

This was the cause of the issue - the license text that is output from pip show scipy includes Name: GCC runtime library.  The metadata parsing logic was too naive and overwrote the Name: scipy metadata that was encountered earlier in the output.

Licensed might be failing to parse the first part of the scipy license file as a BSD 3-clause licensed. At a glance it looks like a normal BSD 3-clause license sentences.

Licensed uses licensee to parse license text and attempt to match the text to a known license.  Licensee is not setup to read multiple licenses in a single body of text (i.e. read from a single LICENSE file) and will by default report other.  I don't mean to ignore this but this is not the right repo to report that as an issue since Licensed doesn't directly handle license detection 😅
You can open an issue in the licensee repo but I'm not sure that it will get much traction.  Detecting multiple licenses from a single file can get complicated because

AFAIK there's no standard for how to separate the different licenses which makes detection hard and error prone.
many times when multiple licenses are used each license applies to specific parts of the distributed code.  the additional text like "this license applies to files A,B,C" makes it almost a certainty that licensee won't have enough confidence to determine a match.  unfortunately again, fixing that problem is hard and error prone.

Thank you for the fix!
As for reading a license text containing multiple licenses: thank you for clarification, I agree with you that it is error prone, so it may be better to leave it as is. I can override the license once the file name is fixed, so it should not be a problem.

Will this fix be released soon?
I'm not sure if this is the right place to ask, but I'm using https://github.com/jonabc/setup-licensed to install licensed on GitHub Actions, and it seems that it only supports release versions.

@kwkbtr ah sorry, I was trying to also get a fix for  https://github.com/github/licensed/issues/541 into the release but that one is a bit larger and I haven't had enough time to finish it yet.  I'll put out a patch release today

Thank you, my CI has been fixed!


Need docs for "How to do a product release"

User Story
As a maintainer of CAAPH, I would like to have simple, foolproof documentation that leads me through creating a product release.
Detailed Description
The targets and tooling for doing a release appear to be here, but no documentation. Trying to figure it out without a guide that contains specific steps and commands is fraught with peril.
Anything else you would like to add:
/kind feature
/area documentation

/assign


HDFS-14670: RBF: Create secret manager instance using FederationUtil#newInstance

The code looks good.
I think that Yatus used to run by itself but it got disabled?
In Spark there is a way to run it, is anybody aware of how to trigger it?

@goiri  Thanks for the review.
@steveloughran Could you help us know how to kick trigger the build ? I saw that you were trying to trigger yetus in some of the recent PRs.

Thanx @chittshota, On a quick look, the code looks good.
Regarding the yetus I tried to trigger manually too from Jenkins page but I guess that works only for patches, It gave error no patch available. Well I will try to find a solution today

:broken_heart: -1 overall

Vote
Subsystem
Runtime
Comment

0
reexec
49
Docker mode activated.

_ Prechecks _

+1
dupname
0
No case conflicting files found.

+1
@author
0
The patch does not contain any @author tags.

+1
test4tests
0
The patch appears to include 1 new or modified test files.

_ trunk Compile Tests _

+1
mvninstall
1084
trunk passed

+1
compile
35
trunk passed

+1
checkstyle
24
trunk passed

+1
mvnsite
40
trunk passed

+1
shadedclient
732
branch has no errors when building and testing our client artifacts.

+1
javadoc
37
trunk passed

0
spotbugs
69
Used deprecated FindBugs config; considering switching to SpotBugs.

+1
findbugs
67
trunk passed

_ Patch Compile Tests _

+1
mvninstall
31
the patch passed

+1
compile
29
the patch passed

+1
javac
29
the patch passed

+1
checkstyle
17
the patch passed

+1
mvnsite
31
the patch passed

+1
whitespace
0
The patch has no whitespace issues.

+1
shadedclient
758
patch has no errors when building and testing our client artifacts.

+1
javadoc
31
the patch passed

+1
findbugs
76
the patch passed

_ Other Tests _

-1
unit
1315
hadoop-hdfs-rbf in the patch failed.

+1
asflicense
26
The patch does not generate ASF License warnings.

4487

Reason
Tests

Failed junit tests
hadoop.hdfs.server.federation.router.TestRouterWithSecureStartup

hadoop.hdfs.server.federation.security.TestRouterHttpDelegationToken

Subsystem
Report/Notes

Docker
Client=19.03.1 Server=19.03.1 base: https://builds.apache.org/job/hadoop-multibranch/job/PR-1162/1/artifact/out/Dockerfile

GITHUB PR
https://github.com/apache/hadoop/pull/1162

JIRA Issue
HDFS-14670

Optional Tests
dupname asflicense compile javac javadoc mvninstall mvnsite unit shadedclient findbugs checkstyle

uname
Linux ee1bfb6f79f0 4.4.0-138-generic #164-Ubuntu SMP Tue Oct 2 17:16:02 UTC 2018 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
personality/hadoop.sh

git revision
trunk / aebac6d

Default Java
1.8.0_212

unit
https://builds.apache.org/job/hadoop-multibranch/job/PR-1162/1/artifact/out/patch-unit-hadoop-hdfs-project_hadoop-hdfs-rbf.txt

Test Results
https://builds.apache.org/job/hadoop-multibranch/job/PR-1162/1/testReport/

Max. process+thread count
1634 (vs. ulimit of 5500)

modules
C: hadoop-hdfs-project/hadoop-hdfs-rbf U: hadoop-hdfs-project/hadoop-hdfs-rbf

Console output
https://builds.apache.org/job/hadoop-multibranch/job/PR-1162/1/console

versions
git=2.7.4 maven=3.3.9 findbugs=3.1.0-RC1

Powered by
Apache Yetus 0.10.0 http://yetus.apache.org

This message was automatically generated.

It looks like Yetus kicked in.
Not sure if it just triggered everything or what but it works for me.
LGTM +1

@ayushtkn @goiri  Thanks again for the review. Once merged, I can mark the ticket fixed and resolved.

@goiri @ayushtkn Can we merge this? Will update jira once done.

https://issues.apache.org/jira/browse/HDFS-14670

@goiri Thanks for merging this.


Failing to build due to upstream API changes.

https://github.com/sourcegraph/httpcache has had a lot of commits recently. As a result, apiproxy is failing to build:
$ go build github.com/sourcegraph/apiproxy/...
# github.com/sourcegraph/apiproxy
./transport.go:36: undefined: httpcache.XCacheAge

I got the same issue, is there a fix for it yet?


Add support for sources and provenances.

Adds support for specifying sources and provenances in config.json.
Generates triples for them.
Output observation files encode the provenance id in a new provenance column.
Design discussion.

Nice!

Thanks both for the reviews!


Profit Margin Calculator Added (Reverted  The  Changes given by you)

Issue Id you have worked upon -
#146
Briefly explain your program logic -
Developed the UI for User to Enter companyRevenue , goodsSold , operatingExpense , interestExpense and taxes . restricted user to not enter any other value expect number (int) after entering the details gross profit margin , operatingProfitMargin and netProfitMargin are calculated . i have used useState hook to store values entered by user and calculate the results. along with that ,results are only displayed when the clicks on calculate profit button and after all calculations are done doing . user can go back by clicking on back button.
Screenshots(Attach 2 screenshots of your own input and output) -
Attach here

By raising this PR I affirm that -

[x] My code follows the guidelines of this project.

[x] I have performed a self-review of my own code.

[x] I have commented my code.

[x] My code gives the correct output.

[x] I affirm that I strictly follow contributing guidelines and code of conduct.

@Heramb4270,
Once you update your files the PR gets updated automatically, so your old PR was updated and has been reviewed and merged. Congratulation and thank you for contributing.
Old PR - #180
Closing this PR.


How to attach to window scroll?

First of all, thanks for the amazing job done here, this lib is super helpful!
I have one question though, how do I attach the scroll to the window element? On @tanstack/react-virtual grid we can do that by using useWindowVirtualizer but I didn't find a way to achieve the same here, given that the scrollRef param is required too, I'm unsure how to achieve that. Is that possible?

Hey, apologies for not catching this sooner. Unfortunately that's currently not possible.

I haven't really planned it, but I can do so if there's interest


Sonoff attempted to create another Zeroconf instance

HA (supervised) version: 0.115.6
Supervisor version: 245
Docker version: 19.03.12
Kernel: 5.4.50
OS: OpenWrt
Getting this exact error in log:
2020-10-05 09:02:55 WARNING (MainThread) [homeassistant.helpers.frame] Detected integration that attempted to create another Zeroconf instance. Please use the shared Zeroconf via await homeassistant.components.zeroconf.async_get_instance(hass). Please report issue to the custom component author for sonoff using this method at custom_components/sonoff/sonoff_local.py, line 74: self._zeroconf = Zeroconf()
Did some research and, same issue was fixed for esphome component:
https://github.com/esphome/aioesphomeapi/pull/13/files/eaf2aac7dcd40c7d2e082c36f50b0d8320547c95
Issue appears to cause a race condition and high CPU usage.
Unsure how to change sonoff-ewelink to fix.
Thanks; Bill

@rossbcan sorry to say this but your problem is related to another sonoff project not this one


:messages attributes don't change the message.

Probably not this package fault, but the :messages attributes don't work for me.
I checked and it converts it correctly to the data-message-success and so on in the markup. But when testing, it always take the value in the database. So maybe this mechanism is not working in the html forms plugin side.
just as an example, this is what I have (I am using alpinejs)
<x-html-forms :form="$form" :messages="['success' => 'Thank you!', 'error' => 'Yikes! Try again.']"
  class="relative side-form"
  x-data="formComp()"
  @hf-submit="load(0.4, 1, 'in')"
  @hf-submitted=""
  @hf-success="load(0, 0.7, 'out'); success = true"
  @hf-error="load(1, 1, 'out')"
  x-bind:class="{'success': success}"
>
 ...
</x-html-forms>

Hi @SergiArias -
did you ever solve this?

BTW, I've been trying to get this to play nice with the Iodine Validation Library but I am not very good at this stuff.
https://github.com/mattkingshott/iodine
Everything validates great but I can't get the form to submit.
If anyone has any ideas, this would be a super useful library to use along side this.
<x-html-forms
    :form="$form"
    id="contact"
    class="flex flex-wrap w-full space-y-8"
>

            <input
                name="name"
                id="name"
                type="text"
                class="w-full border border-gray-400 px-4 py-2 placeholder-gray-500"
                placeholder="Name..."
            >

            <input
                name="email"
                id="email"
                type="email"
                class="w-full border border-gray-400 px-4 py-2 placeholder-gray-500"
                placeholder="Email Address..."
            >

            <textarea
                name="message"
                id="message"
                class="w-full border border-gray-400 px-4 py-2 placeholder-gray-500"
                placeholder="Enter your message..."
                rows="6"
            ></textarea>

        <input
        type="submit"
        value="Submit Your Quote"
        class="btn-gray-700"
        onclick="register(event)"
      />

</x-html-forms>

Hi @SergiArias -
did you ever solve this?

No, I gave up. As I can update the messages in the wordpress panel, it's not a big problem. But I think the feature should be taken off the readme instructions as it doesn't work.
About the iodine, I don't have any idea, sorry...


nativescript-socketio path option is not working on Android

in nativescript-socketio path option is not working on Android.
I had a look into the code and saw for some reason opts[key] = options[key] is not working anymore and the setPath() method should be called. I expect the same thing for other options. So a generic function call may be useful.

Sent a PR. I should also check iOS to make sure it's working as is.


Fix ramachandran plot and update UI layout

This update includes the following changes to the UI:

Move sequence viewer and console viewer to side bar.
Move button bar to the bottom of the screen.
Contents of side bar are scrollable.
Ramachandran plot dimensions are determined based on viewport dimensions. The plot also resizes when there are changes in window size.

Accepting. We might as well try it out.


add header3

Related PRs: #317, #335

@wgaurav please ask others to help review this

@arthurbuhl at this stage to encourage participation & to evaluate skills/contributor interest level, I have requested for duplicate work.
We will discuss later how to streamline. Now let the wild ride continue!

Ok, got it.  :100:

what's this debug.log?

There's an extra file here as spotted by @tusharkandpal

@UnevenCoder @NahuelAlfano could you take another look

There's an extra file here as spotted by @tusharkandpal

Sorry for that. I deleted that extra file it was of no use


Add support for quantized qwen2-0.5b

This PR adds support for quantized(q4f16_1) qwen2-0.5b. Solves issue . PR must be merged before merging this.
@Neet-Nestor

Unfortunately, this won't fix the issue since the model Qwen2-0.5B-Instruct-q4f16-MLC you added is not available in WebLLM yet. Instead we need to compile the model, upload to huggingface, update WebLLM, and finally update our app.

Unfortunately, this won't fix the issue since the model Qwen2-0.5B-Instruct-q4f16-MLC you added is not available in WebLLM yet. Instead we need to compile the model, upload to huggingface, update WebLLM, and finally update our app.

I saw that and so I have also created the required PR in the web-llm repo.

Thanks! Let me try

Thanks! It's working perfectly on my end. I will leave the other 2 PRs for my team to review, but I can merge this one and publish a new version of the webapp so that you can use it immediately.


Legend

Hello Jorge,
I would like to add a legend on the charts and change the lines and axis color. Do you know how to do this?
I´ve tried the chart.js documentation but the colors are not changing.
The widgets are running good on my dashing.
Thanks & Regards,
Mario

Hello Jorge,
I´m able to change the graphs appearance using options on send_event.
I still don´t know how to add legends. Thanks In advance, Mario

Hi Mario,
Not sure I understand your question but you can add a legend to most widgets using the moreinfo data bind. Have a look at the example provided. Also, this data-bind can be updated via a job (passing JSON) or via API. Check the documentation page. Is this what you are looking for?
Regards,
Jorge

Hello Jorge,
Thanks for your reply!
I Would like to add a legend like this one https://camo.githubusercontent.com/64691a56adb5a2536f9ece2d174f645dfb3f8a7f/687474703a2f2f692e696d6775722e636f6d2f4555664f3870762e706e67
With the values and colors always displaying below the chart. Is it possible?
Thanks & Regards,
Mario

First the bad news: this is not a widget feature, but rather a Chart.js one. And version 1.0.2 it does not seem to support really what you want. The latest version of Chart.js does support legend, but the widget does not support the latest version. I might add this support later in the future but as usual, no guarantees.
But there's hope... There is an extension for the old version that adds the legend you are looking for. You can check it here and there's a demo here. It should be fairly simple to add this support on the widget but you still need to find a way to pass this data via the API and/or a job. If you make it work, send me a pull request - it could be a good solution until the support for the latest version is implemented.

I've just released the new version with support for Chat.js v2. In the new version, legend is enabled by default so this should do what you were looking.


[PDI-16365]-Spaces in connection name can cause unexpected behavior

additinal fix for case editing single old connection

Build Completed
:white_check_mark: This pull request has passed all validations.
Build Commands
mvn -B -fn -f 'pom.xml' -pl 'ui' -P '!assemblies' -amd clean install && mvn -B -f 'pom.xml' -pl 'ui' -P '!assemblies' -amd site

Cleanup Commands
mvn -B -f 'pom.xml' -pl 'ui' -P '!assemblies' -amd build-helper:remove-project-artifact

Changed files
  ui/src/main/java/org/pentaho/di/ui/spoon/delegates/SpoonDBDelegate.java

Unit test coverage change
These statistics help you identify how your changes have affected the coverage of the following files. If a file is not in this list, then its coverage was not affected by your changes. To get some help interpreting these metrics, please refer to Jacoco's documentation.
org.pentaho.di.trans.steps.googleanalytics.GaInputStepMeta

Branch Change:  + 1.85%
Complexity Change:  + 1.06%

org.pentaho.di.trans.steps.gpload.GPLoadMeta

Branch Change: -.93%:small_red_triangle_down:
Complexity Change: -.80%:small_red_triangle_down:
Instruction Change: -.17%:small_red_triangle_down:

org.pentaho.di.trans.steps.salesforceupsert.SalesforceUpsertMeta

Instruction Change:  + .14%

org.pentaho.di.ui.spoon.delegates.SpoonDBDelegate

Instruction Change: -.00%:small_red_triangle_down:
Line Change: -.01%:small_red_triangle_down:

@mbatchelor @pamval please review the changes

@mbatchelor @pamval please review the changes


update generated files and expand note on generation in CONTRIBUTING.md

Update generated files and expand note on generation in CONTRIBUTING.md

CI gfxreconstruct build queued with queue ID 186125.

CI gfxreconstruct build # 4176 running.

CI gfxreconstruct build # 4176 passed.


etcd3.0.0: etcdctl and curl

If I use curl to store a KV, and then through the tool etcdct to get the KV, found that there is no the KV,The opposite is also the result.
1../etcd 启动etcd
2.curl http://<IP_ADDRESS>:2379/v2/keys/a -XPUT -d value="bbbbbbbbbbbbb"
3../etcdctl get --endpoints=<IP_ADDRESS>:2379  a
you will find  that you have nothing to get,why?

../etcd 启动etcd

That's not a valid flag; etcd should refuse to start. What version of etcd are you running? What is the curl output?
This is the output using the master branch:
$ bin/etcd
$ curl http://<IP_ADDRESS>:2379/v2/keys/a -XPUT -d value="bbbbbbbbbbbbb"
{"action":"set","node":{"key":"/a","value":"bbbbbbbbbbbbb","modifiedIndex":4,"createdIndex":4}}
$ bin/etcdctl  --endpoints=<IP_ADDRESS>:2379 get a
bbbbbbbbbbbbb

I cannot reproduce this either. So closing. Please report back with more information if this problem still exists. (like what is the output of curl, what is the output of etcdctl?)

I got this issue when I migrated the etcd from etcd2 to etcd3. The values put into were stored in etcd2's store.
$ curl http://<IP_ADDRESS>:2379/v2/keys/a -XPUT -d value="bbbbbbbbbbbbb"
$ etcdctl ls
/a
$ export ETCDCTL_API=3
$ etcdctl get a
# nothing shown

@heyujiaan Please migrate the data or use etcdctl(v3) do the key/value put.


storage: add unix socker for spdk

Signed-off-by: Boris Glimcher<EMAIL_ADDRESS>

works!
$ docker-compose up opi-spdk-client
storage_spdk_1 is up-to-date
storage_opi-spdk-server_1 is up-to-date
Starting storage_opi-spdk-client_1 ... done
Attaching to storage_opi-spdk-client_1
opi-spdk-client_1  | 2022/07/26 21:56:40 Added: Hello OPI-Nvme got {"jsonrpc":"2.0","id":"1","result":[{"name":"Malloc0","aliases":["f0471525-0bb1-45f4-bba2-b57e2c00ce22"],"product_name":"Malloc disk","block_size":512,"num_blocks":131072,"uuid":"f0471525-0bb1-45f4-bba2-b57e2c00ce22","assigned_rate_limits":{"rw_ios_per_sec":0,"rw_mbytes_per_sec":0,"r_mbytes_per_sec":0,"w_mbytes_per_sec":0},"claimed":false,"zoned":false,"supported_io_types":{"read":true,"write":true,"unmap":true,"write_zeroes":true,"flush":true,"reset":true,"nvme_admin":false,"nvme_io":false},"driver_specific":{}},{"name":"Malloc1","aliases":["db285515-bdbd-4f00-8e24-4907778ecf22"],"product_name":"Malloc disk","block_size":512,"num_blocks":131072,"uuid":"db285515-bdbd-4f00-8e24-4907778ecf22","assigned_rate_limits":{"rw_ios_per_sec":0,"rw_mbytes_per_sec":0,"r_mbytes_per_sec":0,"w_mbytes_per_sec":0},"claimed":false,"zoned":false,"supported_io_types":{"read":true,"write":true,"unmap":true,"write_zeroes":true,"flush":true,"reset":true,"nvme_admin":false,"nvme_io":false},"driver_specific":{}}]}
opi-spdk-client_1  | 2022/07/26 21:56:40 Deleted: Hello OPI-Nvme
opi-spdk-client_1  | 2022/07/26 21:56:40 Got: Hello OPI-Nvme
opi-spdk-client_1  | 2022/07/26 21:56:40 Added: Hello OPI-Nvme
opi-spdk-client_1  | 2022/07/26 21:56:40 Deleted: Hello OPI-Nvme
opi-spdk-client_1  | 2022/07/26 21:56:40 Got: Hello OPI-Nvme
opi-spdk-client_1  | 2022/07/26 21:56:40 Added: Hello OPI-Nvme
opi-spdk-client_1  | 2022/07/26 21:56:40 Deleted: Hello OPI-Nvme
opi-spdk-client_1  | 2022/07/26 21:56:40 Got: Hello OPI-Nvme
opi-spdk-client_1  | 2022/07/26 21:56:40 Disconnected: Hello OPI-Nvme
storage_opi-spdk-client_1 exited with code 0


Issue with PriceQuote Parser

Hi!
Im having some unexpected results where priceAction.getPrice(type="BID") returns a different column in the testfile.
The CSV looks like this:
timestamp, bid, ask, bidsize, asksize
1556805604162,14.55,14.66,18,300
1556805604162,14.55,14.66,18,400
1556805604162,14.55,14.66,18,600
1556805604162,14.55,14.66,18,700
1556805604162,14.55,14.66,18,800

My actual data looks a little different so I defaulted to customizing the parsers from the beginning. I then tought I was making a mistake there and simplified the data to the above.
My CSVConfig looks like this:
val csvConfig = CSVConfig(hasHeader = true,
    priceParser = PriceQuoteParser(autodetect = false, bid = 1, ask = 2, bidVolume = 3, askVolume = 4),
    timeParser = AutoDetectTimeParser(0)
)

I also  tried the autodetection (usually  i dont use headers neither, so i added them according to the  autodetect init.
I am using this test function:
override fun generate(event: Event): List<Signal> {
        val signals = mutableListOf<Signal>()
        for ((asset, priceAction) in event.prices) {
            println("Ask: ${priceAction.getPrice(type="ASK")}")
            println("Bid: ${priceAction.getPrice(type="BID")}")
         }
        return signals
    }

To get this output:
Ask: 14.66
Bid: 900.0
Ask: 14.66
Bid: 900.0
Ask: 14.66
Bid: 900.0
Ask: 14.66
Bid: 800.0

So basically getPrice(type = "BID") returns my asksize column.

Indeed a bug. In the  PriceQuoteParser calling the PriceQuote constructor with the wrong order of arguments :(
Will fix it.

Could find it yesterday but yes that fixes it. I just used named arguments like this and it works:
    override fun parse(line: List<String>, asset: Asset): PriceQuote {
        val volume1 = if (askVolume != -1) line[askVolume].toDouble() else Double.NaN
        val volume2 = if (bidVolume != -1) line[bidVolume].toDouble() else Double.NaN
        return PriceQuote(
            asset = asset,
            askPrice = line[ask].toDouble(),
            bidPrice = line[bid].toDouble(),
            askSize = volume1,
            bidSize = volume2
        )
    }

}


[bp/1.28] Bump rules-go to 0.41.0

This version contains the fix for using local sdk with go >= 1.21
https://github.com/bazelbuild/rules_go/pull/3600

/retest

ci failures look ~real
Repository rule http_archive defined at:
  /build/bazel_root/base/external/bazel_tools/tools/build_defs/repo/http.bzl:372:31: in <toplevel>
ERROR: /build/bazel_root/base/external/com_github_cncf_xds_go/xds/type/v3/BUILD.bazel:3:11: no such package '@go_googleapis//google/api/expr/v1alpha1': The repository '@go_googleapis' could not be resolved: Repository '@go_googleapis' is not defined and referenced by '@com_github_cncf_xds_go//xds/type/v3:type'
ERROR: Analysis of target '//contrib/golang/router/cluster_specifier/test/test_data/simple:plugin.so' failed; build aborted:
INFO: Elapsed time: 49.836s
INFO: 0 processes.

this has come up before @mmorel-35 might know why this happens

that's weird, we already applied that change to our fork and it's building fine...

Current main branch rules_go is at 0.46.0 - should we bump to that version?

Current main branch rules_go is at 0.46.0 - should we bump to that version?

i think lets land these (once ci issues are resolved)
we can bump main further and backport more if required

hmm - actually @jwendell i just realized that this isnt actually a backport - i think @moderation is right - that we should just pick the actual backport - same with PRs on other branches

Yeah, you're right, this is not a backport. I was just trying to be moderate and bump the versions only to the minimal version required, but if bringing it in pair with main is not an issue, I'll do it.
Thanks for the review folks.


The voc results

Hi, that is an excellent work, thanks for sharing.
I have a question about the Table 2. in your paper. When i run the code to generate the Initial CAM, Initial + CAA and Initial + CAA + dCRF, it get 49.12, 70.7, 71.1 mIoU. Is this because different settings use different thresholds?
And maybe the different way to generate the voc2012 dataset causes this problem, so could you please release how to generate the voc2012 dataset?
Thanks for your reading. Your work is interesting!

Hi, thanks for your attention to our work.
The results in Table 2 are based on the train set (1464 images in total) rather than the train_aug set (10582 images in total). Did you set it correctly in --split_file?  Besides, you don't need to manually set thresholds and the links to obtain images and gt masks for voc dataset have been provided in README. If you still fail to get the results, you can show us more details, like the running command, your revision of the code and the environment you used.

Hi, Thanks for your reply.
I reinstall the pydensecrf package and download the dataset again, it is work! I get the same mIoU as your paper.
By the way, is there any implementation about the Initial + MHSA in Table 2?
Thank you very much!

To implement the initial + MHSA, you can simply comment out or delete the following line: https://github.com/linyq2117/CLIP-ES/blob/9094660d91a52ab5e855b51be43627b8e26b5137/generate_cams_voc12.py#L188)

Thanks for your comment!


Finished cleaning up base install, initial commit to repo.

Cleaned and sorted base install file structure from create-react-app.


vttest: character sets

The vttest for some character sets is not setting the second part of the attribute correctly for the second half

Should be:

This long standing bug has been fixed - missing save/restore of attribute


remove qdrant_openapi_client

@joein Can you please give some brief information about the issue? I would like to work on it.
Thanks

#731


Model load problem in 64 bit devices

I compiled amalgamation for armeabi-v7a and arm64-v8a, I am trying to test model https://github.com/flyingzhao/mxnet_VanillaCNN/blob/master/vanilla-0001.params and https://github.com/flyingzhao/mxnet_VanillaCNN/blob/master/vanilla-symbol.json
devices with arch armeabi-v7a loads model without any problem. But arm64-v8a devices can not load model. Exception:
org.dmlc.mxnet.MxnetException: [21:53:21] jni/../mxnet_predict-all.cc:18084: Check failed: from.shape() == to->shape() operands shape mismatch
When I try same model with python this exception occurs as arm64 device. Exception:
Shape inconsistent, Provided = [100,576], inferred shape=(100,256)
My python code:
import mxnet as mx
from mxnet import model
import numpy as np
import cv2
img=cv2.imread("test.jpg")
img=cv2.resize(img,(40,40))
m=model.FeedForward.load('vanilla',1,num_batch_size=1)
b=np.zeros((1,3,40,40),dtype=np.float32)      #change chanels into shape[1,3,40,40]
b[0,0,:,:]=img[:,:,2]
b[0,1,:,:]=img[:,:,1]
b[0,2,:,:]=img[:,:,0]
points=m.predict(b)
print(points)
Please help.

Can you try to come up with a minimal reproducible example? That will make it easier to help you


(refactor) some opportunities to use Multi-Catch

It is extremely unlikely the project will merge patches that are just refactors for the sake of refactors. Please see our “how to contribute” guide:
https://cassandra.apache.org/doc/latest/development/patches.html#patches

Given this is 5 years old and without ticket I am closing this PR. Feel free to raise this in mailing list or file a ticket etc.


How to clean multi queue correctly?

Hello!
Let say, I have a node.js server script, that accepts connections & does something...
During that activity it should collect (queue) some commands and exec what is queued once a second.
    var redis  = require("redis"),
        client = redis.createClient(), multi;

    // start a separate multi command queue
    multi = client.multi();

setInterval(function...
    // drains multi queue and runs atomically
    multi.exec(function (err, replies) {
        console.log(replies);
    });
, 1000);

var server =  ....
server.on('data', function() {
  ....
  // queues some commands to redis!
    multi.incr("incr thing", redis.print);
    multi.incr("incr other thing", redis.print);
)

Certainly, I need to clean my queue after exec, so that each 1 second queue will exec only once,, but will it be correct to do that in exec callback?
Because, if the queue will be added, before I get the callback called, and I will clean that in callback (by calling multi = client.multi()), then I will lose new data (that was added) ?

@EugenyPavlenko both .multi and .batch are from now on pipelining the commands better and work faster that way.


fix: add delay to sync alert firing

Signed-off-by: John Pitman<EMAIL_ADDRESS>What type of PR is this?

/kind bug

What does this PR do / why we need it:
Report from a user:

We are seeing the below concern from some GitOps users with respect to the ArgoCD alerting mechanisms.
Applications naturally go out of sync for 10's of seconds which a git change is being synced. Most other Prometheus alerts have a "For" set to for example 5m, so an alert is only generated if the condition lasts for 5m, ie. there is a problem.
The ArgoCDSyncAlert Prometheus rule doesn't have a "For" set, therefore the instant an Application goes out of sync an alert is raised.
it is being expected that the "For" parameter be set to something reasonable.

Have you updated the necessary documentation?

[ ] Documentation update is required by this PR.
[ ] Documentation has been updated.

Which issue(s) this PR fixes:
Fixes #?
Test acceptance criteria:

[x] Unit Test
[ ] E2E Test

How to test changes / Special notes to the reviewer:

Install the operator into OpenShift
Create a namespace, for example argocd
Install an argocd instance into the namespace
Install an application into the namespace, with auto-sync turned off
In the admin console, after a short delay the ArgoCDSyncAlert alert rule associated with the namespace should go into pending state
After five minutes, the the ArgoCDSyncAlert alert rule associated with the namespace should go into firing state

/retest

/test v4.7-e2e

/lgtm
/approve


The new syntax does not allow you to create an initial state without violating the hook creation rules

The new 0.6 syntax makes it impossible to activate the initial state of an application without breaking the rules for using hooks.
Using the 0.5 application initial syntax, use_context_provider initializes the creation of the initial application state inside the function:
fn App() -> Element {
    use_context_provider(|| Signal::new("en".to_string()))
}

The new syntax is like a street with two red lights on it, where you can’t initialize state without breaking the hook rules, because launch is a closure and causes a hook error.
fn main () {
use_context_provider(|| Signal::new("en".to_string()))
launch(|| {
    rsx! {
        // Your component code here
    }
});
}

Has an error: hook called outside component or hook
launch(|| {
    use_context_provider(|| Signal::new("en".to_string()))
    rsx! {
        // Your component code here
    }
});

Has an errors hook called in a closure and hook called outside component or hook
Environment:

Dioxus version:  0.6 from git
Rust version:    rustc 1.81.0
OS info:         win11
App platform:    web

Would something like this work for you?
fn main () {
  // If you need to load from env vars or etc
  let locale = String::from("en");

  launch(move || {
    rsx! {
      App { locale: locale.clone() }
    }
  });
}

#[component]
fn App(locale: String) {
  use_context_provider(|| Signal::new(locale))

  // Your component code here
}

GlobalSignal might also fit your use case

It's the same thing
fn main() {
    dioxus_logger::init(Level::INFO).expect("failed to init logger");
    info!("starting app");
    launch(App);
}

fn App() -> Element {
    use_context_provider(|| Signal::new("en".to_string()));
    let mut lang: Signal<String> = use_context();

The new syntax replaces the code above
fn main() {
    launch(|| {
        use_context_provider(|| Signal::new("en".to_string()));
        rsx! {}
    });
}

Evan says it's fine and the rules are not broken, but because the app is not directly defined as a component. dx check will constantly generate a signals violation error


problem with select2 plugin

hi
when validating a form with the jquery-ui (combobox) plugin.
http://jqueryui.com/autocomplete/#combobox
while validating... all select lists pop open.
example:
http://jsfiddle.net/tLcqs0ak/1/
thanks allot
Avi

Finally got around to tracking the cause of this down. It's because the plugin is triggering an input event on all fields to trigger validation.  I need to namespace these event triggers to avoid calling any other third-party input event handlers by accident. It will be fixed in the next release.

Thanks alot
Avi


Provide more details to "Current MAC address" field in "Status information"

There were people that thought they'd need to enter their phones MAC address in order to be able to use the WLAN.  I can understand this confusion to some extend and think we should provide more details next to the field as well as the form for changing.
(thanks @jnsga)

I thing this should be working


Using CPM_SOURCE_CACHE and CPMFindPackage, CPM still continues to download and configure the project each time

The caching aspect was the main reason I tried to give it a try but it doesn't seem to be working. Based on the title, is there something I'm missing about how this is supposed to work?

Well for one, the CPM_SOURCE_CACHE can only avoid the download step. The dependencies still need to be configured and built, as every project can have different configuration options. If you want to cache the build as well, check out projects such as ccache.
To test if the source cache works, you can try the following:

In an empty directory create a file CMakeLists.txt containing the following:

cmake_minimum_required(VERSION 3.14 FATAL_ERROR)

# ---- Project ----

project(Playground LANGUAGES CXX)

# ---- Fetch CPM ----

set(CPM_DOWNLOAD_LOCATION "${CMAKE_BINARY_DIR}/cmake/CPM.cmake")
set(CPM_DOWNLOAD_VERSION 0.27.1)

if(NOT (EXISTS ${CPM_DOWNLOAD_LOCATION} AND CPM_VERSION STREQUAL CPM_DOWNLOAD_VERSION))
  message(STATUS "Downloading CPM.cmake")
  file(DOWNLOAD https://github.com/TheLartians/CPM.cmake/releases/download/v${CPM_DOWNLOAD_VERSION}/CPM.cmake ${CPM_DOWNLOAD_LOCATION})
endif()

include(${CPM_DOWNLOAD_LOCATION})

# ---- Add dependencies via CPM ----

CPMFIndPackage(
  NAME BitLens
  GITHUB_REPOSITORY TheLartians/BitLens
  VERSION 2.2
)

In a bash or similar shell run the following command from the directory:

CPM_SOURCE_CACHE=$(pwd)/deps cmake -H. -Bbuild

If everything worked there should now be two new directories in the current folder: build, containing the build, and deps, containing the dependency sources. You can verify that the cache works by creating a new build e.g. through:
CPM_SOURCE_CACHE=$(pwd)/deps cmake -H. -Bbuild2

CPM.cmake should find the cached dependencies of the first build and no new download (besides the CPM.cmake source) will occur.

@jeremyong did this help you find the issue?
If not, some details about what your tried so far and the output would be great. :)

Sorry for the lack of a response, for some reason I was under the impression that ccache support was built-in.
Regarding the "redownloading" of the files, I traced this to an actual VSCode bug on my machine that was not actually setting the cache directory properly. Sorry for troubling you (closing).

FYI if you're looking for an easy Ccache integration for Cmake, you might want to look at ccache.cmake.


a MIR wrapper for vlang

here it is: https://github.com/v-script/vmir

Than you for pointing this out.  It is interesting.
I wish vlang a success.  I always like languages designed by one author instead of big groups of people.
Vlang looks very promising but it will be hard to get a considerable set of users.  Language market is enormously competing and w/o backing by big companies the success is practically impossible.  Even with support of big companies the success is not guaranteed.

What you say is the truth, but I still like it. thank you~


token refresh need 60 minutes to populate

Added a note that token refresh may take up to 60 minutes.

@TomGeske : Thanks for your contribution! The author(s) have been notified to review your proposed change. @saudas

@mlearned can you help to review?

#sign-off

@sauryadas: I'm sorry - only the author of this article, @saudas, can sign off on your changes. But we do have an exception process - if you are on the Microsoft content or product team for this product area, you can ask the PR review team to review and merge it by sending mail to the techdocprs alias.