feat(sequencer): implement basic app side mempool with nonce ordering

Summary
implement a basic app side mempool with nonce ordering.
the mempool works as follows:

when a tx passes check_tx, it's inserted into the mempool. if a tx fails check_tx it's removed from the mempool (if it was in it already)
during prepare_proposal, txs passed in from cometbft are ignored, and txs are popped from the app's mempool instead.
after a block is finalized, any included txs are removed from the mempool, and the priorities of the txs remaining are updated.
txs in the mempool are ordered by nonce, specifically the differential between the tx nonce and the current account nonce. the lower the differential, the higher the priority. for example, a tx with nonce 7 sent from an account with nonce 7 is a higher priority than a tx with nonce 1 sent from an account with nonce 0.

question (maybe for a follow up): there is no reason for a non-validator node to have the app-side mempool, as it doesn't gossip. should we make a config flag to enable/disable it?
Background

cometbft mempool is too opaque, doesn't know about app-specific ordering, should only be used for tx gossip
will help with the sequencer api (can return pending nonce for an account)
can use for fee-based ordering or tx expiry time in the future

Changes

implementation of a basic nonce-ordered mempool
update App to use this mempool (see summary for how it works)
updated App to have separate functions for executing txs in prepare vs process proposal, as the functionality of the two was diverging too much
update the mempool service to also use the mempool in check_tx

Testing
unit tests
Related Issues
closes #856

I am worried about the potentially very long hold on mempool in update_mempool_after_finalization and what the implications for other parts of the codebase might be.

agreed - the difficulty with implementing this is that we should update the mempool after a block is finalized, otherwise, if we are the proposer next, we might end up including now invalid transactions.
the options are either: update the mempool and only once it's updated move to the next round, ensuring txs in the mempool are more likely to be valid/ordered correctly, but potentially affecting consensus timing; or, update the mempool in one task and move to the next round in another task, so that timing isn't affected but we might have more invalid txs included. it would be good to bench at what mempool size there's a noticeable affect timing-wise

Orthogonal to this: are there any considerations for persisting this mempool?

not at the moment, right now cometbft's mempool persists txs, if we somehow get cometbft to not store any txs then we should figure out persistence on the app-side


Adds a file testing word embedding feature extraction model

word.py converts a glove file (must be downloaded separately) into word2vec form. Then the file uses gensim to compare the distance/similarity of words based on their vector values.

adds requirements.txt for gensim
gitignores the two glove and word2vec files

lots of file changes because I merged main, but the only change made just now is the requirements.txt is now
gensim==4.0.1
numpy==1.21.1
scipy==1.7.1
smart-open==5.1.0

after pip freezing in the virtualenv.


Set up interceptor on axios responses retrying the request if failed

replace the static axios instance by a new custom one axiosInstance. The new instance is using axios' interceptor to retry in case of error codes 500, 502, 503, 504 (max 3 attempts).
makeRetryAxios lets to configure the interceptor.
fetchAndUnblindTxs & fetchAndUnblindUtxos now returns also the errors returned by the generator.

@tiero please review

replaced by #131


[preset-uno & preset-attributify] weird behaviour of text-transform utilities

So, I'm using preset-uno and preset-attributify (with TypeScript) and want to make my text uppercase. The only way do it without errors is using class="uppercase". When I try to specify just the uppercase attribute on the tag, it actually works on the page, but I get TypeScript error telling me that there's no such attribute (because it's not specified here I guess). By the way, the behaviour is the same with lowercase and capitalize.
And that's not all. Somewhere here I've read that there's also case- attributes (case-upper, case-lower, etc.). When I try to use them, I receive no type errors, but they don't affect the page (e.g. don't work).

Similar situation with the scale attribute.

The case-x rules are available in preset-mini. Currently when exporting the rules collection for preset-wind which is fhe base of preset-uno, some of the rules from mini don't get included, and case-x is one of them.

A couple of questions:

Why are those styles not included?
How to deal with attributify types? Looks like they aren't really related with the presets, so that I can have an utility available in classes but not in attributes and vice versa.

For the second point: I guess there are two ways: add absolutely all available utilities to the attributify types (which will make typeacript accept many attributes from presets that are not included; and which is probably not possible anyway) or somehow split attributify for different presets (like preset-attributify-uno or, even better, specify the presets as arguments to the preset-attributify).

The uno-preset is based off as an alias of preset-wind. While preset-wind tried to follow windi/tailwind, some of the rules were skipped. I'll try to open a PR to re-add missing preset-mini rules onto preset-uno.
I'm sorry I can't realy help with the types. Code-wise, preset-attributify is a separate extractor that account for attributes to be extracted out for rule-matching, along with variant that helps 'translating' the atteibute-based tokens into the version that the regular rules can match. So it generates attributify classses only when the non-attibute version of the class can be matched by the currently loaded rules.


modules/test: allow arbitrary warning/assertion expecations

modules/test: allow not building nixvim config
modules/test: allow arbitrary warning/assertion expecations
tests: use warning-expectations options

Long overdue options for "expecting" warnings or assertions to match arbitrary predicates.
Common use-cases can de defined declaratively using an enum of pre-defined predicates, while more advanced use-cases can provide an arbitrary predicate function.
Also made it possible to write a test that does not build nixvim's "wrapped" nvim w/config, although I wonder if such tests are better off written manually using runCommand & evalNixvim?

Thanks a lot for doing this! Maybe we should also document the predicates available by default in the CONTRIBUTING guide? Or at least link to the parts of the codebase where they are defined?

Maybe we should also document the predicates available by default in the CONTRIBUTING guide? Or at least link to the parts of the codebase where they are defined?

I agree this'd be nice, but I'd rather any documentation for this be auto-generated.
It should already be documented to an extend via the expect option's enum type. But I agree it could be better documented. IDK if I want to inflate this PR with that though :thinking:

There seems to be some infinite recursion:
error: derivation 'x86_64-linux.search' does not have valid outputs: error:
              … while calling the 'getAttr' builtin
                at <nix/derivation-internal.nix>:44:19:
                  43|       value = commonAttrs // {
                  44|         outPath = builtins.getAttr outputName strict;
                    |                   ^
                  45|         drvPath = strict.drvPath;
              … while calling the 'derivationStrict' builtin
                at <nix/derivation-internal.nix>:34:12:
                  33|
                  34|   strict = derivationStrict drvAttrs;
                    |            ^
                  35|
              … while evaluating the default value of option `test.predefinedExpectationPredicates.<name>.valueType`
              … while evaluating an attribute `functor`
              … while evaluating an attribute `type`
              (1994 duplicate frames omitted)
              … while evaluating an attribute `_type`
              (stack trace truncated; use '--show-trace' to show the full, detailed trace)
              error: stack overflow; max-call-depth exceeded
              at /nix/store/8fwsiv0hd7nw1brkvka0jf1frk3m7qkr-source/lib/generators.nix:511:25:
                 510|       in
                 511|         if multiline && length lines > 1 then multilineResult else singlelineResult
                    |                         ^
                 512|     else if true  ==   v then "true"
                 ```

There seems to be some infinite recursion:

This is lib.generators.toPretty causing issues trying to pretty-print an option-type, since option-types have a recursive functor.
Providing a non-recursive defaultText or dropping the default as suggested already will resolve.

while evaluating the default value of option `test.predefinedExpectationPredicates.<name>.valueType`

@mergify queue


fisher -V doesn't allow dot characters

Good find. It does support . dots however. The problem is the oddly named theme cmorrel.com fails because of the regex:
/[A-Za-z0-9_-]/

I think we could safely change this to:
/[A-Za-z0-9]([._-]?[a-z0-9]+)/

I will add it to the next milestone.

Good find. It does support . dots however. The problem is the oddly named theme cmorrel.com fails because of the regex:
/[A-Za-z0-9_-]/

I think we could safely change this to:
/[A-Za-z0-9]([._-]?[a-z0-9]+)/

I will add it to the next milestone.

EDIT: This will be fixed in 0.2.0, in the meantime, if you want to use cmorrell.com theme, use the full URL:
fisher install https://github.com/oh-my-fish/theme-cmorrell.com


add support for downloading resources

If you can please add support for download resources like udemy dl

You should be able to use Udemy-dl with the --assets-only option. I'll take a look at adding asset support.

An experimental implementation can be found on the feat-assets-qualities branch. a867f82f2b56840cb6942d251c5207c99dab0d9a


Questions about repeatability metric for line segment detection

Hi! I modified the training code of SOLD2 into a multi-GPU version. The repeatability metric of the model trained on the synthetic dataset is similar to or even better than the one in your publicly released sold2_synthetic.tar. However, the repeatability metric for the model trained on the Wireframe dataset is much lower than the one in your publicly released sold2_wireframe.tar. I'm not sure where the issue might be. Could you please help me check whether it's a problem with my training approach?
Firstly, I trained the model with fixed loss weights set to 1. During training on the synthetic dataset, with a batch size of 16 and other settings kept consistent, I trained for 30 epochs on two RTX 2080 Ti GPUs. The Rep-5 metric for structural distance obtained on the Wireframe dataset was approximately 0.351. In comparison, the publicly released sold2_synthetic.tar achieved a metric of 0.300 on our machine.
For training the detector on the Wireframe real dataset, a batch size of 10 was used, and other settings remained consistent. The model was fine-tuned for 200 epochs on two GPUs, with an interim model around the 90th epoch achieving the highest metric of approximately 0.508. However, your publicly released model sold2_wireframe.tar achieved a metric of 0.587 on our machine.
Next, I conducted training using learnable loss weights. In the training on the synthetic dataset, the settings remained consistent with the previous setup, and the obtained metric was approximately 0.315. For training on the Wireframe real dataset, the achieved metric was 0.505.
Could you please help me identify where the issue lies in the training approach and suggest ways to improve the repeatability metric of the model?

Hi, in your trainings, did you train the full model with descriptors + detector, or the detector only? Training with the descriptor can slightly decrease the performance of the detector.
Furthermore, did you activate the optional candidate suppression (flag "use_candidate_suppression" in the export config) or not?
Finally, did you tune the probability threshold of the line heatmap? This should probably be adjusted for your newly trained model.

Thank you for your replying. Yes, after training the detector with fixed loss weights, I further fine-tuned the full model (descriptors + detector). The batch size was set to 4, and I trained it for 20 epochs. The obtained metric is 0.515.
Yes, I activate the candidate suppression(I kept the default setting in the export config for this option, which is True).
No, I haven't made any adjustments. Are you referring to modifying this parameter in "train_detector.yaml" or "export_line_features.yaml", and would changing it have an impact on training? Could you please guide me on how to modify this parameter?

Good, then you can indeed modify the parameter "prob_thresh" inside export_line_features.yaml to tune it better to your model. No need of retraining. Ideally, you should do this tuning on a validation set that is different from the test set.

Thank you for your response. The visual results with the default settings seem fine, but I'll experiment further. Thanks again for your assistance!

Sorry, I meant the parameter "detect_thresh", which is used in line_detection.py. You can tune it at test time when exporting the lines.
What exactly do you want to know about steps 4 and 5?

Hi, I used different combinations of "detect_thresh" and "inlier_thresh" from the "sold2_dev_code" you shared to measure the metrics and selected the best result among them. Therefore, I believe the issue might be with the model itself.
I would like to understand the settings for learning rate and the number of epochs in Step 4 and Step 5. I am unsure if there is an issue with my training approach. Could you please share the details? Thank you.

We used a learning rate of 0.0005 and Step 5 was trained for 20 epochs (roughly 24h on a single GPU). But you can simply stop the training whenever the loss and metrics have converged. I don't have the numbers for Step 4 here, but I guess that it was roughly a similar number of epochs.

Thank you very much for your response and assistance. I'll try training again.


Load time with large numbers of nodes is excessive

When you have small numbers of nodes, the load time is snappy and the responsiveness is very good (better than, e.g. ReactFlow, which has VDOM overhead).
When you have large numbers of nodes, the responsiveness is still great, but only once it has loaded, which takes a lot of time.
As far as I can tell, this is because adding each node is forcing a reflow. For example, loading 1k nodes takes around 5 seconds on my machine, whereas with ReactFlow it is around 300ms.
I think that this lib can get MUCH faster by batching DOM reads and writes.
Is there any scope for this?

This might be fairly easy by just rendering into a fragment, and then only appending the fragment into the DOM once all the nodes are ready.

Hi @andyjessop
The problem is connections.
Adding nodes is fast. Calculation connections poijnts is slow.
In this example: adding 3000 nodes is instantly.
Uncomment code comented and is very slow.
<!DOCTYPE html>

  <meta charset="UTF-8" />
  <meta name="viewport" content="width=device-width, initial-scale=1.0" />
  <title>Document</title>
  <link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/jerosoler/Drawflow/dist/drawflow.min.css" />

The problem is that we are going to search the DOM for the x and y position of each input and output. Which takes a lot of time.
Which is currently difficult to modify.

Here is a possible solution:

https://github.com/jerosoler/Drawflow/issues/672


upgrade to akka 2.4.11

To show the new performance with the newest version.

It looks like this wasn't intended as a contribution since you've removed my name from the README, so closing this.

I made a mistake when pulling the request, I am supposed to pull the first
request. I commit two times and only perform the pull request only once
after the first commit. I thought only the first commit was pulled. I am
checking out it to do some performance study.
On 4 Oct 2016 8:03 a.m., "Stephen McDonald"<EMAIL_ADDRESS>wrote:

It looks like this wasn't intended as a contribution since you've removed
my name from the README, so closing this.
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/stephenmcd/curiodb/pull/25#issuecomment-251261538,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AAEd4tfP4RlS35bshIjprTnMadfLUarPks5qwZfJgaJpZM4KMAsb
.


chore: Remove deprecated validThrough cube filters

Closes #1195.

I think not, at least we don't explicitly have validThrough anywhere in the app now, except in RDF typings. As this filter was essentially the same as noExpires, it shouldn't affect the tests 👍


Simple example on how this works

Hi there,
I stumbled across this repo and I'm interested in getting betfair pricing data to a pandas dataframe. I'm having limitations using delayed key and would like to use streaming.
Could you upload a simple example  for instance how to get premier league match data in a dataframe via streaming? Or any league for that matter?
Thanks

Tl;dr

Join the betfairligthtweight Slack group here
Message @liam on the Slack to get your live key activated for free
Adapt this betfairlightweight example using the instructions below

betfairlightweight and flumine
betfairutil fits into an ecosystem of Python Betfair packages that includes betfairlightweight - a Betfair API implementation written in Python - and flumine - a fully featured trading platform built on top of betfairlightweight that can be used for live trading, back testing of strategies, and recording market data from Betfair. To clarify, I'm not the author of either of these, just a dedicated user of betfairlightweight.
If you're not familiar with these packages I strongly suggest you take a look at those repositories, especially the examples. This one from the betfairlightweight repository is very close to what you are trying to achieve with regards getting Premier League data into a data frame except it:

Doesn't construct a data frame, it just prints out part of the data
Is illustrated on GB horse racing

There is also documentation for both packages here and here
Finally, an incredible resource is the betfairlightweight Slack which you can join using this link. Here we discuss all things automated betting, obviously with a heavy focus on betfairlightweight, flumine and Python but topics of discussion also include other betting platforms, cloud service providers, strategy development, etc. etc. Betfair employees also occasionally participate.
Betfair Historic Data
Here I'm referring to data obtained from data purchased from the Betfair historic data service: https://historicdata.betfair.com. Some data is available for free. It is my strong recommendation that you only work with the PRO data. I realise it's costly (aside from the small number of months that are available for free) so standard practice if you're just getting started is to record your own data using flumine. Bear in mind Betfair will frown upon this if you are not placing any bets.
Reading an entire market into one data frame
Assuming you've download the market files - i.e. file type "M" on the historic data website - where each file contains data for a single market then you can read the entire thing into one (large) data frame very simply:
from betfairutil import prices_file_to_data_frame
df = prices_file_to_data_frame(path_to_prices_file)

The prices_file_to_data_frame function takes a number of arguments that can be used to configure exactly what columns are included in the data frame:

should_output_runner_names: by default the data frame won't include the names of the selections, only their IDs. For example, 48351 instead of Man Utd. Set this parameter to True if you want the names
should_format_publish_time: the publish time is the timestamp associated with the streaming update from Betfair. In the raw data it's an integer number of milliseconds since the Unix epoch. If you set this parameter to True then these timestamps will get converted to a nice human readable format
max_depth: As noted, the data frame for a market across its entire lifetime can be very large. One way of limiting the size is to impose a restriction on the maximum depth. For example, if you set this parameter to 3 then the data frame will only contain the 3 best back and lay prices at each timestamp

The rest of the parameters will be discussed in due course where relevant.
Reading an entire event into one data frame
The Betfair historic data can also come in event-level files - i.e. file type "E" - where each file contains data for all markets corresponding to a single event (i.e. football match, horse race meeting, etc.). You can do exactly the same as above:
from betfairutil import prices_file_to_data_frame
df = prices_file_to_data_frame(path_to_prices_file)

and read the entire event into one data frame. This will be even larger than before so there are a few other parameters to prices_file_to_data_frame that might be useful here:

should_output_market_types: you can set this True to include a column in the data frame that indicates the market type. In this case you'll almost certainly want to do this so you can identify whether a price comes from the match odds, correct score, O/U 2.5 goals etc. markets
market_type_filter: this parameter lets you filter out market types you aren't interested in. For example, you might only want match odds and correct score data and discard everything else in the file

Converting a price file to a CSV file
For convenience, betfairutil includes a function prices_file_to_csv_file which is just a wrapper around prices_file_to_data_frame
Converting market books to data frames one at a time
An alternative to reading an entire prices file into one data frame is to convert the market book at each timestamp into a data frame:
from betfairutil import market_book_to_data_frame
from betfairutil import read_prices_file
market_books = read_prices_file(path_to_prices_file)
for market_book in market_books:
    df = market_book_to_data_frame(market_book)
    # Do something with df here

Self-recorded data
If you've recorded data yourself using flumine then those prices files are essentially interchangeable with the ones provided by the Betfair historic data service all of the above code will work almost seamlessly. The caveat is that runner names are not present in data that has been recorded live. prices_file_to_data_frame therefore also takes a parameter market_catalogues which lets you pass one or more saved market catalogues that include the mapping from selection ID to runner name
Live data
As above, the best starting point for consuming live data is the betfairlightweight example available here
To change this from GB horse racing to football, modify the market_filter to:
market_filter = streaming_market_filter(
    event_type_ids=["1"], market_types=["MATCH_ODDS"]
)

Note that it is not possible to filter by competition so you cannot restrict only to Premier League. Best practice is to use a coarse filter like above then locally filter out markets which aren't of interest.
Now in the loop that handles the market books, simply use the market_book_to_data_frame function as above:
# check for updates in output queue
while True:
    market_books = output_queue.get()

    for market_book in market_books:
        df = market_book_to_data_frame(market_book)
        # Do something with data frame here


Does Dynamo-Depth assume access to GT intrinsics during training and inference?

Hello Yihong,
Thank you for releasing the code for your project. It was an interesting read.
In the paper, it saids, "On all datasets, we only use the unlabeled video frames for training."
I was just wondering if Dynamo-Depth also assumes access to GT camera intrinsics during training and inference?
There does not seem to be separate mechanism for predicting the camera intrinsics.
Thank you in advance!

Hi Andrew,
Your intuition is correct. Dynamo-Depth does assume access to GT intrinsics during training, as loaded here in the trainer.
For inference, the GT intrinsics are only used when visualizing the 3D flow field as optical flow and not used when  evaluating model predictions, including depth, odometry, and motion segmentation.
The wording in the paper (indented below) was mainly written in the context of training a monocular depth estimator without any GT LiDAR values, GT semantic mask/bbox annotations, or off-the-shelf detector predictions. Sorry for any confusion about this.

On all datasets, we only use the unlabeled video frames for training; ground truth LiDAR depth is only used for evaluation.

Feel free to reply if you have any other questions or concerns!

Thank you for the detailed response Yihong! Looking forward to your follow-up projects!

Thank you for the detailed response Yihong! Looking forward to your follow-up projects!


How much Rinkeby ETH is required to deploy to the test net?

Hi Patrick, thank you very much for the tutorial video and this codebase.  The video was very informative.
I tried to deploy to the Rinkeby testnet, and I got 7.5 ETH from faucet but I keep getting insufficient funds.  I can only get 7.5 ETH per day, how much ETH do I generally need to deploy to Rinkeby?

Ok I figured it out, if we are using PRIVATE_KEY, we also need to uncomment accounts: [PRIVATE_KEY] in hardhat.config.js and comment accounts: { mnemonic: MNEMONIC }.
Closing.

Yes! Exactly!

Thank you for keeping your keys safe :)
How much ETH do you have in your account? Post a link to your wallet?

amazing


Export-MsIdAppConsentGrantReport - The module 'Microsoft.Graph.DirectoryObjects' with version '2.9.1'

Describe the bug
Trying to use the command Export-MsIdAppConsentGrantReport to export report.
Getting error message in PS7 (PSVersion 7.4.5)
PS C:\UAT> Get-InstalledModule
Version              Name                                Repository           Description

2.24.0               Microsoft.Graph.Authentication      PSGallery            Microsoft Graph PowerShell Authentication Module.
2.24.0               Microsoft.Graph.DirectoryObjects    PSGallery            Microsoft Graph PowerShell Cmdlets
2.0.70               MSIdentityTools                     PSGallery            Tools for managing, troubleshooting, and reporting on various aspects of Microsoft Identity products and se…
PS C:\UAT> Export-MsIdAppConsentGrantReport -ReportOutputType ExcelWorkbook -ExcelWorkbookPath C:\Delete\MFA\uat\UAT-App-Report.xlsx
Write-Error: The module 'Microsoft.Graph.DirectoryObjects' with version '2.9.1' not found. To resolve, try installing module 'Microsoft.Graph.DirectoryObjects' with version '2.9.1' to match currently
loaded modules. For example: Install-Module Microsoft.Graph.DirectoryObjects -RequiredVersion '2.9.1'
Write-Error: The module 'Microsoft.Graph.Applications' with version '2.9.1' not found. To resolve, try installing module 'Microsoft.Graph.Applications' with version '2.9.1' to match currently loaded
modules. For example: Install-Module Microsoft.Graph.Applications -RequiredVersion '2.9.1'
PS C:\UAT> $PSVersionTable
Name                           Value

PSVersion                      7.4.5
PSEdition                      Core
GitCommitId                    7.4.5
OS                             Microsoft Windows 10.0.19045
Platform                       Win32NT
PSCompatibleVersions           {1.0, 2.0, 3.0, 4.0…}
PSRemotingProtocolVersion      2.3
SerializationVersion           <IP_ADDRESS>
WSManStackVersion              3.0
To Reproduce
Steps to reproduce the behavior:
To run the report https://azuread.github.io/MSIdentityTools/commands/Export-MsIdAppConsentGrantReport#example-2
Install-Module ImportExcel
PS > Connect-MgGraph -Scopes Directory.Read.All
PS > Export-MsIdAppConsentGrantReport -ReportOutputType ExcelWorkbook -ExcelWorkbookPath .\report.xlsx
Expected behavior
Lists and categorizes privilege for delegated permissions (OAuth2PermissionGrants) and application permissions (AppRoleAssignments).
Screenshots
If applicable, add screenshots to help explain your problem.
Environment (please complete the following information)

Operating System: Windows 10
PowerShell Version: 7.4.5
MS Graph PowerShell SDK Module Version: [e.g. 1.6.2, 1.9.3, 2.0.0]

Additional context
Add any other context about the problem here.

Thanks I'll look into removing the requirement for this specific version.


Create: 1911-maximum-alternating-subsequence-sum.cpp

File(s) Modified: cpp/1911-maximum-alternating-subsequence-sum.cpp
Language(s) Used: C++
Submission URL: https://leetcode.com/problems/maximum-alternating-subsequence-sum/submissions/903085520/

Thanks!

I think there is a typo in the problem number for this problem. It should be 1911 instead of 5782. It's in 2d-dynamic programming section.
Thanks.


Win Prediction of each round

Is there any way to know the result of a fight knowing the champions and rivals?

The objective is to predict placement(1 to 8) using the end game team composition. The pipeline should be able to predict which team has better placement(win).


Support user-defined presets (or similar extension functionality)

In a similar way to how eslint supports extending other user-defined configurations, it would be awesome if esformatter presets weren't limited to the two defined inside of esformatter itself.
This could leverage the existing preset functionality, or possibly be called extend[s] to indicate the nature of it. The value for this field could be resolved in a similar fashion as require.resolve.

Closing since this is a dupe of #328

just a FYI, our idea is to remove the jquery preset from the lib (so we would only have the default rules and all the presets would be stored as external dependencies)

Love the idea!
I wonder if it's worth having another  preset that if basically a no-op, so
esformatter can be entirely unopinionated to start, making all rules
explicit and opt-in. If I remember correctly eslint was making this the
default in a future version.
On Thu, Jul 9, 2015, 2:52 PM Miller Medeiros<EMAIL_ADDRESS>wrote:

just a FYI, our idea is to remove the jquery preset from the lib (so we
would only have the default rules and all the presets would be stored as
external dependencies)
—
Reply to this email directly or view it on GitHub
https://github.com/millermedeiros/esformatter/issues/335#issuecomment-120154780
.

I also wanted a no-op preset, but that is too hard to implement.. we still make some changes to the original indentation and the position of commas/semicolons even if all options are set to -1 (see #113)
there are so many edge cases and some things are simpler to implement without caring about the original formatting.

FYI, this was implemented last night! https://github.com/millermedeiros/esformatter/issues/328#issuecomment-232618074


cvpr16_gmad/database/toolbix.tar.gz was not found on this server

HI，thank you for your RankIQA, I want to be an experiment, but when i download data of  Waterloo,there is a error, toolbix.tar.gz was not found on this server. Excuse me, can you send me a copy of toolbix.tar.gz? thank you very much!

Hi, thanks for your interest, I have tried to download the toolbox you needed, which was available online. Maybe you could try it once again.

thank you , en, i open the link "https://ece.uwaterloo.ca/~zduanmu/cvpr16_gmad/database/toolbix.tar.gz" ,the link has been opened error, named "
Not Found
The requested URL /~zduanmu/cvpr16_gmad/database/toolbix.tar.gz was not found on this server.", can you give me a online link?
HI, I still have another question,Can I reproduce the essay based on the script you provided?

Hi,
It works for me, anyway, I send it to you by email.
Someone already reproduced the similar results as reported in the paper by
using the code, therefore you should be able to do so.
gMADToolboxV1.0-beta3 (1).rar
https://drive.google.com/file/d/1K4IJmJn15mTPbxSpmtWuVKspdL-_ZxoL/view?usp=drive_web

On 8 November 2017 at 11:10, tutu<EMAIL_ADDRESS>wrote:

thank you , en, i open the link "https://ece.uwaterloo.ca/~
zduanmu/cvpr16_gmad/database/toolbix.tar.gz" ,the link has been opened
error, named "
Not Found
The requested URL /~zduanmu/cvpr16_gmad/database/toolbix.tar.gz was not
found on this server.", can you give me a online link?
HI, I still have another question,Can I reproduce the essay based on the
script you provided?
—
You are receiving this because you commented.
Reply to this email directly, view it on GitHub
https://github.com/xialeiliu/RankIQA/issues/1#issuecomment-342771018,
or mute the thread
https://github.com/notifications/unsubscribe-auth/APamPjS5pwP4BpYa6juk7Skw_NbUjrQyks5s0X4BgaJpZM4QUXd9
.

Thank you very much, I have downloaded it, I am going to repeat the thesis.


Exporting List to CSV

Is is possible to export/save the list into CSV?, I know you can save the list to an SQL view, but if we can use an action to save it directly to CSV?

This is possible by creating a CSV Export view and embedding it in the same view/page that the List is in.


Fix: Format replace with no captures in a group should be an empty str

This only applies if no attempt to index the captures occurs.

@gir-bot lgtm


Compose of createSelector return state with type of never

I encounter a problem when upgrading @reduxjs/toolkit from 1.4.0 to 1.7.2. (reselect 4.0.0 to 4.1.5), typescript 4.5.5
Here is the code from your github with some additional types to work with typescript.
`const selectShopItems = (state: any) => state.shop.items;
const selectTaxPercent = (state: any) => state.shop.taxPercent;
const selectSubtotal = createSelector(selectShopItems, (items) =>
items.reduce((subtotal: number, item: any) => subtotal + item.value, 0)
);
const selectTax = createSelector(
selectSubtotal,
selectTaxPercent,
(subtotal, taxPercent) => subtotal * (taxPercent / 100)
);
// it yields error here: ...(state: any) is not assignable to (state: never)
const selectTotal = createSelector(
selectSubtotal,
selectTax,
(subtotal, tax) => ({ total: subtotal + tax })
);`
Upon more inspection, I see that selectTax has (state: never) as its parameter. I guess somehow adding selectSubtotal (created by createSelector) to its parameters leads to this weird error.
Here is the sandbox: https://codesandbox.io/s/typescript-playground-forked-obcgrh?file=/index.ts

Yes, you must not use any as an argument here - you must always provide a real type for each argument.  createSelector tries to infer the types from each argument, so they have to be "real" types.

Thanks for your reply. It fixes my problem.

This is very limiting, I get state: never and cannot override it


duel request & trade request notification/alert

Could an alert be added for when you get a duel request or a trade request?
The same kind of notification you get when you are about to get logged out
tytyty

Would something along the lines of this meet the description?

I would just copy-paste the chat message to the notifications for both events.

It is indeed just "copy pasting" the message into a notification.
notifier.notify(event.getMessage());

Should be addressed by #3163, for anyone looking into this.

Added in #3636


Truncate dataset statement not recognized

Statement does not exist in ABAPv755(or parser error).
Statement exist even in 755.
data:
i_filename type c length 255 value '/user/sap/data/....'.
truncate dataset i_filename at current position.

data i_filename type c length 255 value '/user/sap/data/....'.
truncate dataset i_filename at current position.

heh, there are always more ABAP statements :)


[request][updater][v2] beta updates

I'm using the updater plugin in the app vibe and host the binaries / update artifacts with tauri action on that public repository.
I would like to provide a way in the app to get beta updates. meaning that updater plugin will look for beta public release in Github and not only for the latest release. is that possible?
Thanks

Check this discussion https://github.com/tauri-apps/tauri/discussions/11069#discussioncomment-10699077

I don't use custom server for hosting. Just Github releases.
Any chance I can do it with Github releases and actions and keep it simple as now?

yes, multiple json files and when your user changes from stable to beta or vice versa, you just point them to one of your update files


npm WARN config global --global, --local are deprecated. Use --location=global instead.[BUG]

What / Why
-->

n/a

When

n/a

Where

n/a

How
Current Behavior

n/a

Steps to Reproduce

n/a

Expected Behavior

n/a

Who

n/a

References

n/a

Is it just me or is this actually missing from the docs?

Nothing is deprecated; that message was a bug.


SWAN-59

SWAN-59 issue is resolved in this PR.

This fix essentially adds a delay to when the collapseAllGroups is called. It seems more like a workaround since the actual problem probably lies somewhere else. This fix can also be implemented by using the delayCollapseGroup. Perhaps something to do with how the animations are handled in the list adapter? (Just speculating). It would be good if you could do more digging around for the source which might reside elsewhere. Thanks.


restarting development and criterion's future

I'd like to get criterion back into a usable state, and I'd like to improve the
user experience around it.
Here's my plan so far, input is appreciated and PR are also welcomed.
Immediate actions: criterion 0.1.0
Basically, release criterion with its current public API, refactor its
internals, further improvements shouldn't break the API.

[x] land new timing loops #26
[x] make compilable on current nightly
[x] refactor: use the new Instant/Duration APIs (when stable?)
[x] fix travis
[x] CI: test on mac. see #70
[x] CI: test on windows. see #70
[ ] documentation: explain output/plots, add examples, how to use in a cargo
project
[x] release dependencies
[ ] start making releases.

Short term: criterion 0.1.x

[ ] refactor: reduce usage of unstable features.

Throw away or put simd behind a cargo feature, it's unstable and only works
with x86_64
criterion won't work on stable anytime soon because it depends on
test::black_box

[ ] colorize output messages
[ ] developer documentation: explain the math
[ ] refactor: proper error handling in internals. bubble up errors and report them instead of panicking/unwrapping
[ ] clippy
[ ] rustfmt

Future: criterion 0.2
If we are allowed breaking changes, how can we improve the user experience? Some
ideas:

[ ] simplify the public API

#26 adds several methods, perhaps all the similarly named methods can be
replaced with a function that takes enums or some builder pattern.

[ ] expose errors to user instead of panicking/exiting
[ ] expose more internals, e.g. return an intermediate struct with the benchmark results
instead of directly writing the results to disk.
[ ] move away from gnuplot, produce a web report with interactive plots
[ ] better integration with cargo, output files to target directory, plots
could live in target/doc

If you used criterion in the past, I'd like to hear about your experience.

In general, What worked well? And, What didn't work for you?
How helpful/clear/confusing were the generated plots/the output message?
Was the performance regression detection reliable, or did you get false
positives?
What functionality do you think is missing?
Any suggestion to improve the user experience?

@faern will, hopefully this week, send us some PR to get us close to compiling on a recent nightly. :+1:

Next actions:

publish criterion dependencies
write great docs
publish criterion 0.1.0

@faern if you can land the multiple functions benchmarking method before 0.1.0, excellent. If not it can wait until 0.1.1.

@japaric I did some rebasing of that on top of your latest merge this morning. I will see when I can get it ready. Hopefully within a day.
I have another suggestion. How about we run rustfmt on the entire crate before 0.1.0? My Rust editor runs that automatically on save so I have a hard time to not commit unrelated changes :) Also good to comply to the standards.

@japaric I did some rebasing of that on top of your latest merge this morning. I will see when I can get it ready. Hopefully within a day.

:+1:

I have another suggestion. How about we run rustfmt on the entire crate before 0.1.0?

Sounds good to me. But last time I ran cargo fmt the source files related to plotting looked really bad; they were heavily indented IIRC.
Something I forgot to mention. What do you think about changing the signature of methods like Criterion::warm_up_time to accept a Duration instead of a u64 that represents nanoseconds? We are already using Duration internally. It would be the last breaking change before 0.1, or we could hold wait until 0.2 to land it.
I'll be publishing the criterion dependencies time when I get free time.

PR created: #64
Except the benchmarking over multiple functions it adds another iter method. Tell me if you rather skip that one..
Yes, we should be consistent and use Duration everywhere. I think we can cram that into this release!

cargo fmt made some plotting stuff weird yes, but that was because the code is a little bit strange from the start :P The correct solution is still to format it, but we might want to save that until it can be refactored into not looking like this.

PR created: #64

Will leave comments over there.

Yes, we should be consistent and use Duration everywhere. I think we can cram that into this release!

:+1:
re: cargo fmt. We can put a #![rustfmt_skip] on the plotting modules and cargo fmt the rest. Let's do that after the other PRs land to avoid rebasing them.

I did put #![rustfmt_skip] on the plot files and ran cargo fmt. I didn't want to submit a PR since if it was my project I would want to do such large change myself, but feel free to merge in my master branch if you want to.
What's more left now? I see you did some commits on testing, but didn't check those boxes yet.

The CI stuff is done. I forgot to check those boxes. Dependencies have been released to crates.io as well. Only docs are missing. I'm trying to figure out the simplest way to run benchmarks in a cargo project.

Hi!
Recent adopter of criterion here -- nice work!
Some comments on things that would be helpful for our (@jonhoo's and my) use case:

Was the performance regression detection reliable, or did you get false positives?

We would prefer if this the comparison step could be disabled as part of the configuration, or at least if it avoided failing hard. The experiments we're running are often somewhat noisy, and we run multiple benchmarks in sequence, so it's annoying to fail because of a false positive regression on one of them.

What functionality do you think is missing?

One additional feature (on top of being able to disable the regression testing) that would really help us is the ability to invoke a one-off setup routine, which is only executed once for all benchmarks.
In our use case, we create a benchmark database and populate it with some basic data, but this can take a while. Having to do it once per benchmark seems wasteful, so we're working around this by having multiple Criterion::default().bench_function(...) invocations in a single test routine. However, this is not ideal, because it's now no longer possible for us to run a single benchmark in isolation.

How is it going?

I'd be happy to invest some time in a PR or two if it would be of any use.
Anything in particular you'd like help with?

Hello everyone! I'm bheisler, and with @japaric's permission I've volunteered to take over maintenance of Criterion-rs. At least to start with, I'll probably be following the plan posted here relatively closely. I hope to wrap up release 0.1 at some point in the next few weeks.

@bheisler hello, I have a quick question about criterion-rs future: are the overall trend graphs planned?
It would be nice to have a graph showing how the performance evolved throughout development time, not just compared to the previous build. (or am I missing something that is already there?)

Hmm. I haven't really given that one much thought, to be honest. My workflow when benchmarking is more based on the Profile/Tweak/Benchmark loop rather than tracking performance over days or weeks. I'm not sure what one would want in a long-running trend graph or if Criterion.rs is the right place to generate one. On the other hand, I know that some people are using Criterion.rs for that purpose already, so it might make sense for that workflow to be more directly supported.
Can you describe in more detail what you're looking for?

Okay, mine is structured alike, more or less, but I am constantly running into this scenario:

Run benchmark
Tweak
Run benchmark, see that performance has regressed
Now I need to check out initial version and rerun benchmark to be able to compare the next tweak
As benchmarks are quite complex and take much time, this is not very comfortable.

And lastly, having some squished down version of the report in git tree just for sake of seing overall performance trend would be cool, but that's a bit another story.
I'd be happy to see something similar to graphs that Jenkins-Performance has in their Web UI (https://imgur.com/wavTvXf)
Graph legend shown in the picture is just an example.

One advantage of the long-term performance graph is that it allows one to easily see beyond the noise.  Yes, you can just sample longer to reduce the noise, but that isn't always feasible.  Also, it allows you to see whether you have fixed a regression.  The short tweak optimization cycle works as long as you're only optimizing, but once you intersperse new functionality it becomes trickier.


QFT kata: fix formula formatting in square wave prep exercise

Current version in playground:

Fixed version:


Add support for custom headers

Add an optional customHeader configuration, wich will send custom headers on every authentication request.
Just like http://emberjs.com/api/data/classes/DS.RESTAdapter.html#toc_headers-customization

@leandrocp looks good to me. How about calling it headers instead of customHeader just like how it's done in DS.RESTAdapter?

@jpadilla that´s fine to me. I´ll update the pull request.

@jpadilla done!

@leandrocp Thanks!


grunt exportAll -v downloads the proxies, products and devs only.

When you run the exportAll command it downloads the proxies, products and devs only.
Version from https://github.com/stevetraut/apigee-migrate-tool downloads all entities. But it is not up to date (for example flow hooks support is not added there.)
Please fix this problem in current repository.

Any news on this issue ?

I'm investigating and it looks like it stops processing when there are no entities for a particular type no shared flows, apps, etc.). This appears to be systematic of all entities.

Created a pull request from this repo: https://github.com/kurtkanaskie/apigee-migrate-tool
Fixes for issues 16, 18, 23, 25, 26, 28 and 29.


Update versions.json

clickhouse support 2022-01-01，2019-11-11，2023-05-22

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

Project coverage is 78.98%. Comparing base (2ce2723) to head (0574d1e).

Additional details and impacted files
@@            Coverage Diff             @@
##           master     #971      +/-   ##
==========================================
- Coverage   79.06%   78.98%   -0.08%
==========================================
  Files          47       47
  Lines        4050     4050
==========================================
- Hits         3202     3199       -3
- Misses        713      716       +3
  Partials      135      135

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


Add test data generation / test generation

Given that express-zod-api is currently able to generate swagger documentation would it be possible to add test-data generation too or even full jest test generation?
not as a replacement for tests but as a way to remove the majority of the boilerplate usually required when writing tests for express controllers.
I'm happy to write the code for this myself if needed.

That's an interesting idea, @Isaac-Leonard. Perhaps there should be a property within the .build() method of EndpointsFactory... something like
defaultEndpointsFactory.build({
  // ...,
  tests: [
    { request: {}, expectedResponse: {} }
  ]
})

I need to think a little bit more on it.
Please let me know if you have any suggestions on how this feature could be implemented.

I was more thinking of integrating with something like
https://github.com/anatine/zod-plugins/tree/main/libs/zod-mock
or
https://github.com/dipasqualew/zod-mocking
So that input test data could be generated automatically although I'm not sure what the best way to use it would be?
Like would it be generated once from a console script or something more stable?

Perhaps a good start would be to simply expose the handler function on the Endpoint object after building it so it can be imported and called from test scripts without needing to provide full mockups of request and response objects.

I made a pull request where I've added a method to the endpoint class that runs the handler with a provided input and optional logger for use by tests
https://github.com/RobinTail/express-zod-api/pull/229
I don't think its fully ready yet but I also added a passing test for it so it should work for basic use-cases.

It might just be better to remove the protected modifier from the handler property though now that I think about it more.

Thank you @Isaac-Leonard , I will check out your PR
👍🏽

Thank you for your PR @Isaac-Leonard , your contribution and ideas are highly appreciated.
I realized that I need to clarify in the documentation on how to test endpoints.
Unfortunately I can not accept the offered solution due to the imbalance of efforts in relation to benefits.
The reason is that the offered method tests the output of the endpoint's handler, instead of its actual response, but more importantly — overlooking the error handling implemented in the ResultHandler that is part of the Endpoint's workflow.
The handler may throw an error, but how exactly it will affect on the Endpoint — decides the ResultHandler, which may be customized by design as well.
Therefore, testing handler is not enough. What should be tested is the public execute() method of Endpoint.
And there is no need for additional methods, since it is public.
So, how to test endpoints.

Mock request, response and logger
Invoke .execute({request, response, config, logger})
Assert expectations on response and/or logger methods.

Here is an example:
const requestMock = {
  method: "POST",
  header: jest.fn(() => "application/json"),
  body: {...},
};
const responseMock: Record<string, jest.Mock> = {
  set: jest.fn(() => responseMock),
  status: jest.fn(() => responseMock),
  json: jest.fn(() => responseMock),
};
const configMock = {
  cors: true, // or your actual config
};
await endpoint.execute({
  request: requestMock as unknown as Request,
  response: responseMock as unknown as Response,
  config: configMock as CommonConfig,
  logger: loggerMock,
});

expect(loggerMock.error).toBeCalledTimes(0);
expect(responseMock.status).toBeCalledWith(200);
expect(responseMock.json).toBeCalledWith({
  status: "success",
  data: {...},
});

That's it.
I hope you'll find this helpful, and I'm going increase the visibility of this information.
Thank you once again for your contribution!


initialized summer2024 bootcamp material for week1

I initialized Lectures/Summer2024_Bootcamp/Week_1 and Codes/Summer2024_Bootcamp/Week_1, and prepoulating them with adapted notebooks from (https://earth-env-data-science.github.io) -- How do I properly cite their work in my notebooks?

Updated README by moving previous bootcamp under the Past Events section, and putting a placeholder for the Summer 2024 Bootcamp

TODO: add the ngbitpuller once I have access to the folder link (i.e., once its merged)

Can you resolve the conflicts in the README?

How do I properly cite their work in my notebooks?

Seems to be an open issue: https://github.com/earth-env-data-science/earth-env-data-science-book/issues/46 . Not sure what to recommend here other than for now citing the website of the book.

These notebooks look amazing @juannat7! Great work. Ill merge this once the conflict is resolved.

Thanks @jbusecke I have resolved the conflict... I will make further updates to the material this coming week

Amazing. Ill merge and make you a maintainer here, so you are not blocked by me.


merge package from arlac77/npm-package-template

package.json

chore(package<EMAIL_ADDRESS>chore(package<EMAIL_ADDRESS>chore(package<EMAIL_ADDRESS>chore(scripts): cover@#overwrite c8 --temp-directory build/coverage ava && c8 report -r lcov --temp-directory build/coverage
chore(package): add nyc from template
chore(package): delete xo
chore(package): set $.ava.require='esm' as in template
chore(package): set $.ava.files='tests/*-test.js' as in template
chore(package): set $.ava.babel='false' as in template
chore(package): set $.ava.compileEnhancements='false' as in template

Coverage remained the same at 100.0% when pulling 2f4c5311820834184d653ecc27fcc91a2bb7a15f on template-sync-1 into c91b812200c199ccde987987ec6b4f529906de94 on master.

:tada: This PR is included in version 2.1.0 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


RTByte 1.1.4

Let's try this again...
Oh boy another new update
Key updates:

Pinboard
Management commands for all server settings (customcmds, filters, greetings, logs, moderation, pinboard, settings, starboard)
Better guild initialization checks
Fix to permission inconsistencies
Ban log failing when user is softbanned
Changing timestamps to be more readable and easily understandable
Adding when member joined server to member leave log
Optionally get messages from a specified member when using -star or -pin
Switch -roles command to use rolename argument instead, allowing users to not have to type out the whole role name completely correctly

RTByte/rtbyte-frontend#2 will merge alongside this one.


airbyte starrocks destination run error

Based on the hints from the following URL, I configured the StarRocks destination in my self-deployed Airbyte and created a Google Sheets to StarRocks connection. When executing the task, the following error occurred, indicating that "streamLoadBody" is null. Please help me look into the reason.
https://github.com/StarRocks/starrocks/issues/24180

Facing the same issue.
@Bennettsong Have you figured this by chance?

did you use the following to set up the airbyte connector? https://github.com/StarRocks/starrocks/discussions/23713

another option is to use sql insert.  however you'll have to create the table first.

Or you can use Sling Data.


convert_plan.py error

Hi,
I am using the following command:
python scripts/convert_plan.py data/frozen_graphs/inception_v1.pb data/plans/inception_v1.plan input 224 224 InceptionV1/Logits/SpatialSqueeze 1 0 float to convert my network based on the pix2pix tensorflow model, but I am met with the following error:

Using output node generate_output/output
Converting to UFF graph
Warning: No conversion function registered for layer: Cast yet.
Converting as custom op Cast generate_output/output
name: "generate_output/output"
op: "Cast"
input: "generate_output/output/Minimum"
attr {
key: "DstT"
value {
type: DT_UINT8
}
}
attr {
key: "SrcT"
value {
type: DT_FLOAT
}
}

Traceback (most recent call last):
File "scripts/convert_plan.py", line 71, in
data_type
File "scripts/convert_plan.py", line 22, in frozenToPlan
text=False,
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/conversion_helpers.py", line 103, in from_tensorflow_frozen_model
return from_tensorflow(graphdef, output_nodes, **kwargs)
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/conversion_helpers.py", line 75, in from_tensorflow
name="main")
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 64, in convert_tf2uff_graph
uff_graph, input_replacements)
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 51, in convert_tf2uff_node
op, name, tf_node, inputs, uff_graph, tf_nodes=tf_nodes)
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 28, in convert_layer
fields = cls.parse_tf_attrs(tf_node.attr)
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 177, in parse_tf_attrs
for key, val in attrs.items()}
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 177, in
for key, val in attrs.items()}
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 172, in parse_tf_attr_value
return cls.convert_tf2uff_field(code, val)
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 146, in convert_tf2uff_field
return TensorFlowToUFFConverter.convert_tf2numpy_dtype(val)
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 74, in convert_tf2numpy_dtype
return np.dtype(dt[dtype])
TypeError: list indices must be integers, not AttrValue

I believe it is due to some unsupported layers. Does anyone know of a work around for this?

It looks like there is no supported TensorRT operation for the TensorFlow operation "Cast".  Potentially there is a way to modify the TensorFlow graph to avoid the unsupported operation, but it is highly dependent on the model architecture.  There is a webinar discussing TensorFlow to TensorRT on Jetson which discusses unsupported operations which may provide some insight
https://devtalk.nvidia.com/default/topic/1030314/jetson-tx2/nvidia-webinar-mdash-tensorflow-to-tensorrt-on-jetson/

I have managed to change the layers that weren't supported by TensorRT. Now I am facing the following error:

Using output node generate_output/deprocess/add
Converting to UFF graph
No. nodes: 361
UFF Output written to data/tmp.uff
UFFParser: parsing generate_output/generator/encoder_9/lrelu/mul/x
UFFParser: parsing generate_output/generator/encoder_8/lrelu/mul/x
UFFParser: parsing generate_output/generator/encoder_7/lrelu/mul/x
UFFParser: parsing generate_output/generator/encoder_6/lrelu/mul/x
UFFParser: parsing generate_output/generator/encoder_5/lrelu/mul/x
UFFParser: parsing generate_output/generator/encoder_4/lrelu/mul/x
UFFParser: parsing generate_output/generator/encoder_3/lrelu/mul/x
UFFParser: parsing generate_output/generator/encoder_2/lrelu/mul/x
UFFParser: parsing image_tensor
UFFParser: parsing generate_output/load_images/preprocess/mul/y
UFFParser: parsing generate_output/load_images/preprocess/mul
UFFParser: parsing generate_output/load_images/preprocess/sub/y
UFFParser: parsing generate_output/load_images/preprocess/sub
UFFParser: parsing generate_output/input_images/Reshape/shape
UFFParser: parsing generate_output/input_images/Reshape
UFFParser: parsing generator/encoder_1/conv/filter
UFFParser: parsing generate_output/generator/encoder_1/conv/Conv2D
UFFParser: parsing generate_output/generator/encoder_2/lrelu/mul
UFFParser: parsing generate_output/generator/encoder_2/lrelu/mul_1/x
UFFParser: parsing generate_output/generator/encoder_2/lrelu/Abs
UFFParser: Parser error: generate_output/generator/encoder_2/lrelu/Abs: Unary not supported for other non-constant node
Failed to parse UFF

Not really answering your question, but here is another possible option: if your model has a lot of operations that are not fully supported by UFF and/or TensorRT, you can take a different approach of generating the code (i.e. TensorRT C++/Python API) yourself. In this case you can write the plugins that implement the missing functionality. This is what we do in NVStereo DNN project. Note that it's not exactly easy approach, so it probably should be a last resort.

@Alexey-Kamenev thanks! I will look into your project if all fails.
I have managed to replace all unsupported TensorRT operations, but I am stuck dealing with the operations not supported by UFF. This has been an incredibly difficult process, and I am still stuck with quite a few errors. _

Hi groot-1313.
If you are okay with using the TensorFlow runtime, the recent 1.7 release of TensorFlow supports TensorRT integration.
https://devtalk.nvidia.com/default/topic/1031300/jetson-tx2/tensorflow-1-7-wheel-with-jetpack-3-2-/
The TensorRT package in TensorFlow 1.7 will optimize supported sections of the graph with TensorRT and run the unsupported parts in plain TensorFlow.  I have not tested the build provided in that forum post but it may be worth a shot if you are having difficulty replacing unsupported operations in the graph with supported operations.
If that does not work, or you don't want to use the TensorFlow runtime I may be able to help provided more information about the issues / model, or you could try the method Alexey mentioned.

Hi @jaybdub-nv , thanks for pointing out the Tensorflow release integrated with TensorRT. Will check it out.
I am posting my error log here. From what I understand, it doesnt support the Neg operation, which in my case involves subtraction.
I have replaced 1-a with 1+tf.negative(a), 1+(-1*a), but the error remains. How can Neg not be supported as an operation, since it is such a basic arithmetic operation. The line that causes the error looks like this:
return (0.5 * (1 + a)) * x + (0.5 * (1 - a)) * tf.abs(x)

Converting to UFF graph
Warning: No conversion function registered for layer: Neg yet.
Converting as custom op Neg generate_output/generator/encoder_2/lrelu/Neg
name: "generate_output/generator/encoder_2/lrelu/Neg"
op: "Neg"
input: "generate_output/generator/encoder_2/lrelu/Identity"
attr {
key: "T"
value {
type: DT_FLOAT
}
}

Traceback (most recent call last):
File "scripts/convert_plan.py", line 71, in
data_type
File "scripts/convert_plan.py", line 22, in frozenToPlan
text=False,
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/conversion_helpers.py", line 103, in from_tensorflow_frozen_model
return from_tensorflow(graphdef, output_nodes, **kwargs)
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/conversion_helpers.py", line 75, in from_tensorflow
name="main")
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 64, in convert_tf2uff_graph
uff_graph, input_replacements)
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 51, in convert_tf2uff_node
op, name, tf_node, inputs, uff_graph, tf_nodes=tf_nodes)
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 28, in convert_layer
fields = cls.parse_tf_attrs(tf_node.attr)
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 177, in parse_tf_attrs
for key, val in attrs.items()}
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 177, in
for key, val in attrs.items()}
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 172, in parse_tf_attr_value
return cls.convert_tf2uff_field(code, val)
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 146, in convert_tf2uff_field
return TensorFlowToUFFConverter.convert_tf2numpy_dtype(val)
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 74, in convert_tf2numpy_dtype
return np.dtype(dt[dtype])
TypeError: list indices must be integers, not AttrValue

The Neg operation is not supported by TensorRT, but Subtract is supported.  For example, you could implement -x as
x_neg = tf.subtract(x * 0.0, x)

Using x * 0.0 instead of just 0.0 as the left argument is necessary because TensorRT does not accept a constant as the left argument for the subtract function.  I think this is also the case for other binary operations.
Also, it also looks like you implement the absolute value of x, as tf.maximum(0., x) + tf.maximum(0., -x).  Perhaps try
tf_x_abs = tf.relu(x) + tf.relu(x_neg)

The relu operation is supported, and is equivalent to max(0, x).  Given the above, perhaps the following substitution will work
a_neg = tf.subtract(a * 0.0, a)
x_neg = tf.subtract(x * 0.0, x)
return ((a + 1.0) * 0.5) * x + ((a_neg + 1.0) * 0.5) * (tf.nn.relu(x) + tf.nn.relu(x_neg))

Maybe there is room for further optimization, but I think the above should succeed.  I hope to hear if this works for your case.

Hey! That worked for me! Thanks! I have replaced a few other functions, but I am stuck with one more. I think this is the last change to be made. The problem is with the line:
mean, variance = tf.nn.moments(input, axes=[0, 1, 2], keep_dims=False)
give the error:

Converting to UFF graph
Warning: keep_dims is not supported, ignoring...
Warning: No conversion function registered for layer: SquaredDifference yet.
Converting as custom op SquaredDifference generate_output/generator/decoder_2/batchnorm/moments/SquaredDifference
name: "generate_output/generator/decoder_2/batchnorm/moments/SquaredDifference"
op: "SquaredDifference"
input: "generate_output/generator/decoder_2/batchnorm/Identity"
input: "generate_output/generator/decoder_2/batchnorm/moments/StopGradient"
attr {
key: "T"
value {
type: DT_FLOAT
}
}
Traceback (most recent call last):
File "scripts/convert_plan.py", line 71, in
data_type
File "scripts/convert_plan.py", line 22, in frozenToPlan
text=False,
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/conversion_helpers.py", line 103, in from_tensorflow_frozen_model
return from_tensorflow(graphdef, output_nodes, **kwargs)
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/conversion_helpers.py", line 75, in from_tensorflow
name="main")
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 64, in convert_tf2uff_graph
uff_graph, input_replacements)
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 51, in convert_tf2uff_node
op, name, tf_node, inputs, uff_graph, tf_nodes=tf_nodes)
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 28, in convert_layer
fields = cls.parse_tf_attrs(tf_node.attr)
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 177, in parse_tf_attrs
for key, val in attrs.items()}
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 177, in
for key, val in attrs.items()}
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 172, in parse_tf_attr_value
return cls.convert_tf2uff_field(code, val)
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 146, in convert_tf2uff_field
return TensorFlowToUFFConverter.convert_tf2numpy_dtype(val)
File "/usr/local/lib/python2.7/dist-packages/uff/converters/tensorflow/converter.py", line 74, in convert_tf2numpy_dtype
return np.dtype(dt[dtype])
TypeError: list indices must be integers, not AttrValue

I replaced it with, Alternate 1:
mean = tf.reduce_mean(input, axis = [0, 1, 2], keep_dims=False)
devs_squared = tf.multiply(input - mean, input - mean)
variance = tf.reduce_mean(devs_squared, axis = [0, 1, 2], keep_dims=False)
But it gave me the error:

UFFParser: Parser error: generate_output/generator/encoder_2/batchnorm/Mean: Reduce operator not supported

I replaced mean with, Alternate 2:
mean = tf.keras.backend.sum(input, axis = [0, 1, 2])
div_factor_1 = input.get_shape().as_list()[0]*input.get_shape().as_list()[1]*input.get_shape().as_list()[2]
mean = mean * (1 / div_factor_1)
devs_squared = tf.multiply(input - mean, input - mean)
variance = tf.keras.backend.sum(devs_squared, axis = [0, 1, 2])
div_factor_2 = devs_squared.get_shape().as_list()[0]*devs_squared.get_shape().as_list()[1]*devs_squared.get_shape().as_list()[2]
variance = variance * (1 / div_factor_2)
I got the following error:

UFFParser: Parser error: generate_output/generator/encoder_2/batchnorm/Sum: Reduce operator not supported

I also used reduce_sum in alternate 2 instead of keras.backend.sum, to meet the same error.
I am hoping this is the last error I have to deal with


Can not reproduce results on the Fishscapes static dataset

Hi, thanks for your contribution! I am currently having trouble on reproducing the reported results on the Fishscapes static dataset.
I use the offered pre-trained model "r101_os8_base_cty.pth" and can get the exactaly same results on the Fishscapes lost & found as reported in the paper and roughly same results on the Road Anomaly dataet (difference < 1%). However, when I simply change the "ood_dataset_path" to Fishscapes static dataset. I get the following statistics, which are different from the reported values in the paper. Could you please kindly explain this?
AUROC score: 0.9547932440646849 AUPRC score: 0.51792152018834 FPR@TPR95: 0.2243785053302718

Hello @gaozhitong,
Thank you for your interest in our work!
There are several versions of the Fishyscapes static dataset, and if I remember correctly, we used version 3.
Please check your version of the static dataset, and let me know if you cannot reproduce the results with the same version.
Thank you.

Got it! Thanks for your quick reply. I will check with the static dataset with version 3.

Hi, @gaozhitong
Have you done that? Could you share your experience of how to prepare static dataset with version 3?


Sample config is outdated

The sample config (config/config.sample.yaml) lists userStorePath and roomStorePath, but they no longer seem to be in use.
Starting the bridge with them provided leads to the following warnings:

[DiscordAS] warn: [DEPRECATED] The room store is now part of the SQL database.The config option roomStorePath no longer has any use.
[DiscordAS] warn: [DEPRECATED] The user store is now part of the SQL database.The config option userStorePath no longer has any use

I wonder if there are other unnecessary things in the sample config.. or if there are new and useful things which are omitted.

The README also mentions userStorePath and roomStorePath.

This seems worse than a documentation problem, as described in https://github.com/spantaleev/matrix-docker-ansible-deploy/issues/230
Starting the bridge with userStorePath and userStorePath provided makes the bridge complain (as mentioned above).
Starting it without these parameters makes it die with an error.
It's confusing..


[main] Upgrade to latest dependencies

Cron. -knative-prow-robot
/cc knative-sandbox/api-core-wg-leads
/assign knative-sandbox/api-core-wg-leads
Produced via:
./hack/update-deps.sh --upgrade --release v0.22
./hack/update-codegen.sh

Details:
bumping knative.dev/pkg cc278e1...bbe0bb3:
  > bbe0bb3 Implement getter machinery to generically fetch all injected clients (# 2054)
  > 85bc723 Add benchmark for metrics recording (# 2052)

I did, I don't think I have rights in this repo. I will add myself.


chore: release 4.1.0

:robot: I have created a release *beep* *boop*
4.1.0 (2019-05-29)
Bug Fixes

deps: update dependency google-auth-library to v4 (#705) (2b13344)

Features

use X-Goog-Api-Key header (#719) (35471d0)

Let's release it!

Release is at https://github.com/googleapis/google-auth-library-nodejs/releases/tag/v4.1.0

The release build has started, the log can be viewed here. :sunflower:

:egg: You hatched a release! The release build finished successfully! :purple_heart:


Pins, polygon vertices and shape origins are offset from cursor

This issue is for a: (mark with an x)
- [x] bug report
- [ ] feature request
- [ ] documentation issue or request
- [ ] regression (a behavior that used to work and stopped in a new release)

Description

Pin drops, vertices and origins are progressively offset from cursor as cursor moves down and right on map.

Example:

Expected/desired behavior

Pin would be dropped directly below cursor
Polygon origin and vertices will be drawn directly below cursor
Shape origins will be drawn directly below cursor

OS, Browser and Version?

Windows 10
Firefox

Mention any other details that might be useful
Please see issue reported on StackOverflow here.

I see that you have reported this on the forums. which is the best place to ask such questions. Since this is a specific issue related to the SDK itself and not with a specific code sample, I'll close this issue here.


[Bug]: Cannot include package.json (needed for resolution) in srcs when resolve_json_module = True

What happened?
The target resembles
ts_project(
    name = "ts_prod",
    srcs = glob([
        "src/**/*.ts",
    ]) + [
        # need the package.json so TS can resolve the type: "module"
        ":package.json",
    ],
    resolve_json_module = True,
    # ...
)

When the target is analysed the following error is raised
ERROR: Traceback (most recent call last):
        File "/___/___/BUILD.bazel", line 21, column 11, in <toplevel>
                ts_project(
        File "/___/bazel_output_root/a0311ccbc25922c56ee2769278435101/external/aspect_rules_ts~/ts/defs.bzl", line 378, column 20, in ts_project
                ts_project_rule(
Error in ts_project: rule 'ts_prod' has file 'package.json' as both an input and an output
ERROR: package contains errors: ___: Traceback (most recent call last):
        File "/___/___/BUILD.bazel", line 21, column 11, in <toplevel>
                ts_project(
        File "/___/bazel_output_root/a0311ccbc25922c56ee2769278435101/external/aspect_rules_ts~/ts/defs.bzl", line 378, column 20, in ts_project
                ts_project_rule(
Error in ts_project: rule 'ts_prod' has file 'package.json' as both an input and an output

This does not occur in Rules TS v2.2.0, and only occurs in conjunction with resolve_json_module = True.
Version
Development (host) and target OS/architectures:
Output of bazel --version: 7.3.0
Version of the Aspect rules, or other relevant rules from your
WORKSPACE or MODULE.bazel file: 3.1.0
Language(s) and/or frameworks involved: NA
How to reproduce
1. Define a target with `ts_project` that takes `package.json` as an explicit input and `resolve_json_module = True`.
2. Perform any action which results in analysis of the containing `BUILD` file.

Any other information?
resolve_json_module = True is not used to import file listed in srcs with this scenario, rather this is being used to retrieve package version information in a strictly typed manner.
import eslintPackageJson from 'eslint/package.json' with { type: 'json' };

My attempt to reproduce it at HEAD has failed. Can you checkout https://github.com/aspect-build/rules_ts/pull/711 and see if you can reproduce it at HEAD or confirm it's fixed?


test: disable flaky ssl test

The test Page.goto should fail when navigating to bad SSL is flaky. See #1195

Closing in favor of #1237


Rename the crunchers for brevity

We should remove the string 'DatabaseCruncher' from the crunchers' names.

Closed by #80


[WIP] Add Matrix support

Following on from #376 adding Matrix support (also #266).

@42wim any thoughts on getting this landed?
I think it's worth landing this as an experimental feature then will follow up with additional PRs adding threading, reactions, replay, scrollback, etc. Going to overhaul threading and reactions moving them into bridge so that the same code can be reused between Mattermost and Matrix.


Partially resolves issue #262

Partial resolution to issue #262 .  Converted the "Related To" input field to a select field and populated it with the existing tasks for the record you have pulled up.
However, this fix creates a new issue.  When filling out the form, if you select one of the options in the new "Related To" field and click "Create" you receive an error that says "The given data was invalid."  I haven't been able to track down what causes this error, but I wanted to go ahead and submit this to see if this is the kind of solution you are looking for before looking into it any further.

@cdterry87 check the rules in this file, related_to currently accepts string, change that to integer perhaps


Update pom.xml

Update pom-scijava from 33.2.0 to 37.0.0

Replaced by https://github.com/mastodon-sc/mastodon/pull/261


dashboard: Clicking a component in panels moves interactive map to center on its icon

Feature request
Description

It is sometimes difficult for users to find the object of interest (robot, door, lift, etc) on the interactive map if the scale of the map is large. Consider centering the interactive map onto the object's icon when the object is clicked on the other panels, in the tabs that the interactive map exists.
Implementation considerations

There might be users who do not want this feature, as they have zoomed out to make the whole map visible, this might make them need to zoom out every time they click on an object to check its state. Consider adding a toggle in the settings if this feature should be enabled.

We should start with a figma prototype first.

I think @ChawinTan has built this centering feature in one of the branches previously? Correct me if I am wrong!
But also there would be the design issue of one-click performing 2 different interactions, similar to what we discussed previously for the task panel right, @koonpeng? if clicking on a component shows information on a side panel and performs the centering on the map.

I foresee it would look something like this? the space below the map is empty for now, perhaps the toggle mentioned could be here, or it can be in the settings drawer

We should start with a figma prototype first.

Agreed! @koonpeng, I just added this line in the self-check, let me know what you think, https://github.com/open-rmf/rmf-web/pull/513

I think @ChawinTan has built this centering feature in one of the branches previously? Correct me if I am wrong!

Yup! It is in one of the branches and it was previously blocked by the removal of the omni-panel. I think the individual tabs should be a priority, before the feature for centering of icons on itneractive maps can be added in.

Per VC, this is blocked by the implementation of different Tabs,

[ ] https://github.com/open-rmf/rmf-web/issues/504
[ ] https://github.com/open-rmf/rmf-web/issues/505

but can be started on independently when each tab is completed.

@val and @aaronchongth  Will the object be centered when it is clicked on the map itself or when the cell associated with it in the panel is clicked on?
The animation suggest the former but my understanding of this feature is the latter.

Oh good catch! I think we would like the latter as mentioned by @ChawinTan. The implementation would hopefully be just a migration from our other feature branches. @vallq could you help update the prototype when you have some free cycles?

Oh okay I always thought it was the former with the clicking of icons, got it!

The zooming logic is implemented in both panels, now pending both to be merged


Allow generation of keys without key flags

Related to #406
Currently, the API for generating keys has a workaround in place to forbid generation of keys without key flags (by having a method signature that takes (KeyFlag first, KeyFlag... additional), hindering a user from passing zero key flags in.
Apparently though, the standard allows for key-flag-less primary keys, which results in a primary key that cannot issue third-party certifications.
We should think about modifying the current API to allow this. On the other hand, we should make an effort to hinder the user from generating useless keys as well. I believe that subkeys MUST have a key flag.

https://mailarchive.ietf.org/arch/msg/openpgp/oZazxTDfRwz_I8V0mA69UA8wPQE/

This is now implemented.


chore: Use dedicated sklearn directory for wrappers of sklearn functions

Closes https://github.com/probabl-ai/skore/issues/696

I understand the tech need and agree with you about keeping a close repository. for now, on the user side, I find it cumbersome without any reason for the users to ask them to add "sklearn" in their import. Is there a way to have a clean repo without adding this load to the user?

If we know that, in a near future, other third-parties will be wrapped, we should now remove the alias.
We won't be able to remove aliases easily because it implies API breaking-changes.
As i said in the issue, imagine two libraries with a same function that we want to adresss:

Currently, if pytorch and scikit-learn have a cross_validation functions, we must change the signature of the functions:
from skore import cross_validation_sklearn
from skore import cross_validation_pytorch

it's unlikely that we will wrap two different functions from two libraries which have the same function names (actually, even as an example, I can't think of anything). So we can keep the alias for now :)!

Ready to review.

Ready for review, as it doesn't have impact on user API anymore.


Add support for SRV records

SRV records allow to specify ip address & port through dns queries. See.

Fyi, I implemented very basic SRV support, on top of the ECIP-Checkpointing branch and https://github.com/input-output-hk/ouroboros-network/pull/2876, in https://github.com/input-output-hk/ouroboros-network/tree/ECIP-Checkpointing-SRV. Didn't have the chance to test it yet though.

Fyi, I implemented very basic SRV support, on top of the ECIP-Checkpointing branch and https://github.com/input-output-hk/ouroboros-network/pull/2876, in https://github.com/input-output-hk/ouroboros-network/tree/ECIP-Checkpointing-SRV. Didn't have the chance to test it yet though.


Create

^_ good
Pada tanggal 15 Sep 2022 08:27, "23Zerazera_store" @.***>
menulis:

You can view, comment on, or merge this pull request online at:
https://github.com/zall-4RT/kumpulan-code-termuxs-lenkap/pull/1
Commit Summary
5579f20 Create README.md
0ba7a80 Create main.yml
File Changes
(2 files)
A .github/workflows/main.yml (36)
A README.md (5)
Patch Links:
https://github.com/zall-4RT/kumpulan-code-termuxs-lenkap/pull/1.patch
https://github.com/zall-4RT/kumpulan-code-termuxs-lenkap/pull/1.diff
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Dev

Describe what this PR does / why we need it
vendor kubeadm/v1beta2 rather than directly import this golang file
Does this pull request fix one issue?

Fixes #1754
Describe how you did it
I deleted the kubeadm/v1beta2 and vendor kubeadm/v1beta2 rather than directly import this golang file,then I modified the other affected files
Describe how to verify it
Special notes for reviews

I think we can close this pull request.


Paste from clipboard multiples everything

I see it on osx in both iTerm and Terminal. Attempt to paste something relatively large (50 lines and more) driving micro crazy - it inserts the same thing again and again, like 10 times.

Are you pasting with Ctrl-V or Cmd-V. Both should work, but it's useful for me to know. Using Ctrl-V everything worked when I tried to paste the 700+ lines from view.go. But Cmd-V went crazy with auto-indent. Is this the problem you are experiencing?

The issue is when using Cmd-V we get paste events in chunks of 128 bytes which means that one paste can be multiple events. Anyway I think I know what the problem is here, but I'll get back to it after lunch :).

This will be fixed with the addition of bracketed paste to tcell.
Also note that using ctrl-v to paste should work perfectly fine.

With support for bracketed paste added to my fork of tcell (still waiting for the upstream version), this issue should be resolved.


TypeError: 'NoneType' object has no attribute 'getitem'

Facing "TypeError: 'NoneType' object has no attribute 'getitem' "when running below code:
*** Settings ***
Library  BuiltIn
Library  OperatingSystem
Library  Process
Library  AutoItLibrary
Library  Collections
Library  ImageHorizonLibrary  reference_folder=c:\downloads
*** Test Case ***
Run Application
App
*** KeyWords ***
App
AutoItLibrary.Run  C:\Downloads\CinebenchR20\app.exe
Sleep  5s
Locate  file
Click Image  file
Sleep  1s
locate  selectall
Click Image  selectall
Setup details:
Python v2.7
Pillow==2.9.0
PyAutoGUI==0.9.42
PyGetWindow==0.0.4
robotframework==3.1.2
robotframework-autoitlibrary==1.2.4
robotframework-imagehorizonlibrary==0.1

again, provide the full stacktrace. you are not even telling where (which keyword? or in import?) this fails

Robot framework log report has below error:

Documentation:
Locate image on screen.

20190618 13:19:02.972 / 20190618 13:19:04.209 / 00:00:01.237

FAIL | TypeError: 'NoneType' object has no attribute 'getitem'

It would be more helpful if you could just attach the log.html instead of screenshot...

It would be more helpful if you could just attach the log.html instead of screenshot...

log.zip

log.zip

@Tattoo any update? Did you get a chance to look at the logs?

Turns out the error is actually related to pyscreeze's locateCenterOnScreen() and center(coords). If you edit pyscreeze's init.py and change center(coords) to
def center(coords):     if coords is None:         return coords     else:         return Point(coords[0] + int(coords[2] / 2), coords[1] + int(coords[3] / 2))
then rerun the setup.py install it will now return None when the image isn't found. This will allow all of image horizon's errors to display properly.
There is an issue for this on pyscreeze's git page from May.

The OpenCV is merged to master branch, will make a release in upcoming days/weeks, I hope that it solves this issue also

Yes, the opencv support should alleviate problems. Closing this issue, if there are further problems please open a new ticket


fix : missing key when inputing combination keys

When HidQueue's ExecutionLevel= WdfExecutionLevelPassive and WdfIoQueueRetrieveNextRequest is called in IRQL=
DISPATCH ,so WdfRequestForwardToIoQueue(in hid.c EvtIoDeviceControl)can not be called timely for inserting request to HIdQueue.

You could have deleted the line instead of commenting it out. But either way, looks good. Thanks!

Better delete in order not to carry unused code in source files.
Best regards,
Yan.
On Tue, Feb 7, 2017 at 10:10 AM, Ladi Prosek<EMAIL_ADDRESS>wrote:

You could have deleted the line instead of commenting it out. But either
way, looks good. Thanks!
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OK ,I have deleted.

Thanks!
Another request - please add "Sign Off" to commit message. Check the
example here:
https://github.com/YanVugenfirer/kvm-guest-drivers-windows/commit/7e319d95ea1214f8de28ae72f977247584993fb1
The easy way to do it is to use "-s" option with "git commit" command.
Best regards,
Yan.
On Thu, Feb 9, 2017 at 10:44 AM, Peng Hao<EMAIL_ADDRESS>wrote:

OK ,I have deleted.
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Thanks! Applied.


Add IRC adapter

As part of Hacktoberfest, I implemented a simple IRC adapter for joe. This PR adds a link the repository in the README.

Nice!


seeds fix route

Tasks

[ ] Rename route from seed end point from new to create
[ ] Update frontend guidelines about names of routes

Use case
No response
Related Pull request
No response

I've split the issue as this is not about usability.
Moved from https://github.com/ElektraInitiative/PermaplanT/issues/866#issue-1869513065

Different endpoints (one is .../create one is .../new)

Thx, let us settle with create. This should be also updated in frontend guidelines. Probably it would have been better to create a different issue about this, as it is not about usability.
@4ydan I think you mean route instead of API here and it is unrelated to backend? Backend API is afaics only /api/seeds. Or do I miss something?

@4ydan I think you mean route

Yes thank you for opening this separate issue, I was not sure what to do.
I did not know if it was maybe also /new and /create in the backend. I did not investigate further.

Also I think the route should be /inventory now not /seeds


NavigationRegion3D.bake_navigation_mesh() crashes application when Parsed Geometry Type, Source Geometry Mode, Source Group Name were set

Godot version:
4.0.dev
Commit: f05b4fea33e84ea3322702d774d69926a41ba913 [f05b4fe]
OS/device including version:
Windows 10 x64 Bit
Issue description:
Thru GDScript:
NavigationRegion3D.bake_navigation_mesh() crashes application when this following were set for the NavigationMesh:

set_parsed_geometry_type(0)
set_source_geometry_mode(1)
set_source_group_name("navmesh")

Steps to reproduce:
Thru GDScript:

Create a scene with the following nodes:

Navigation3D
NavigationMesh
NavigationRegion3D
3 MeshInstance with CubeMesh (1 floor, 2 boxes)

Position the 3 MeshInstance with the floor on the bottom and the 2 boxes on top of the floor.
Add_to_group "navmesh" the FloorMeshInstance
Set the following parameters for the NavigationMesh:

set_parsed_geometry_type(0)
set_source_geometry_mode(1)
set_source_group_name("navmesh")

Assign the NavigationRegion3D.navmesh = NavigationMesh
Run NavigationRegion3D.bake_navigation_mesh()

I also tried using a pre-made NavigationMesh.tres file with the said parameters set, still it crashes on baking.
Expected Result:
NavigationMesh is baked properly (check the generated test.tscn in Maps folder, see attached minimal reproduction project)
Minimal reproduction project:
Run the Lobby Scene, Click Create Map
BakeNavmeshCrash.zip

cc @AndreaCatania

I removed everything from the MRP that had nothing to do with the issue as meshes and more were broken in newer Godot versions. The described steps work without any issues until the scripted baking except that boxes are ignored if only floor has groupname but that is not a bug.
The different baking settings do not contribute to any error here.
The issue is that NavigationRegion3D.navmesh = NavigationMesh.new() will already trigger a navmesh update on the NavigationServer. An immediate call to NavigationRegion3D.bake_navigation_mesh() will break the navmesh while it is registering. Need to wait a frame or call the baking function deferred.
@Calinou @akien-mga
I think this issue can be closed as a duplicate as the problem with users creating procedual navmeshes and immediatly baking to a crash is noted in other open issues with more detail.


Update laravel mix 6

I've tried that but unfortunately it breaks everything...
If someone could PR it that would be great!

I've tried that but unfortunately it breaks everything...
If someone could PR it that would be great!

mix 6 is too raw. even out of the box, he does not understand everything. wach/poll behave unpredictably, for example. and this, I repeat, is out of the box.
lets wait some months?
@cretueusebiu can you make sseparate builder based on webpack@latest - may be it is more useful, than dubiousdubious wrappers?

@h-zone I think I'll try Vite first since it's so much faster than webpack.

mix 6 work with vue like bellow
mix.js('asset/app.js'), 'public/js').vue()

I have a repository that started from this started pack, and has now been updated to use laravel 8 and laravel-mix 6.
The config file need to change quite a bit (also hot reload now works).
If anyone wants to see it the link is here: https://github.com/Zelig880/BooksBank/blob/main/webpack.mix.js

Fixed in 6.0


 Should also be greyed out.
#113

Cancelled because of time constraints


[FR]

Hi! You have a pretty cool tool that helps you work with data and thank you for the opportunity to use it.
I also have suggestions for improving this tool to make it even more convenient and cool to use. I work for a company that has made its own dataset format, thus we do not have the opportunity to use your tool. However, in addition to my company, there are also many different dataset formats that also cannot interact with your tool. I would like to correct this moment and make some changes in your code, however, I came across the fact that there are 2 ways, one of which I like more, but entails much more changes in the code base, the other is simpler and easier to implement, but it will work slower.
The first option, which is simple, is to make a code for distilling datasets from one format to another and, at startup, specify which dataset format to work with now, and then the dataset will be distilled from its original format to COCO format, however, this is very resource-intensive and will work slower + disk space is needed to implement this format distillation
The second option is to make a dataset class that will act as an API to the data and apply a factory that will pull up the necessary dataset class and provide all the necessary data, respectively, then support for the new format will be conditioned only by another class and work with your tool will not be slowed down, since the dataset will be read without transformations. However, this will require more code changes.
Thank you for your attention, and I will wait for your answer, because I want not just to implement the functionality, but to give all users the opportunity to use it, since these changes, in my opinion, will be useful and expand the use of your cool tool.

Hi @VLDMR-BS 👋  glad you like the project and want to help improve it for both you and others!
Building an API to pull data dynamically from another source into FiftyOne would be very difficult, because pretty much all of FiftyOne's features, such as querying for samples through the App or in code (dataset views), require the dataset's metadata to be available in FiftyOne's standard format in MongoDB.
Therefore, my recommendation would be to pursue your option 1: write an importer that can translate your dataset format into FiftyOne's format. This will involve pulling the metadata into MongoDB, but, importantly, it does not require modifying or moving the actual media files on disk.
Here's our documentation on all the formats that FiftyOne natively supports importing from (eg COCO):
https://voxel51.com/docs/fiftyone/user_guide/dataset_creation/datasets.html#supported-import-formats
For loading custom formatted data into FiftyOne, there are two basic options:

Write a simple Python function that does the conversion: https://voxel51.com/docs/fiftyone/user_guide/dataset_creation/index.html#custom-formats
Write a customer dataset importer that formalizes the above function into a reusable component: https://voxel51.com/docs/fiftyone/user_guide/dataset_creation/datasets.html#custom-formats


Adding the Search Bar in Book review

Is your feature request related to a problem? Please describe.
Currently, the book review application lacks a search functionality, making it difficult for users to find specific book reviews. Users must scroll through a large number of reviews, which is time-consuming and inefficient.
Describe the solution you'd like
I propose adding a search bar to the book review application with the following features:
Search Functionality: Users should be able to type in keywords (e.g., book titles, authors, genres) to find relevant book reviews quickly.
Auto-Suggestions: As users type, the search bar should provide auto-suggestions to help them find what they are looking for faster.
Filters: Allow users to filter search results by criteria such as rating, date, and review length.
Highlighting Search Terms: Highlight the keywords in the search results to help users easily identify relevant information.
Responsive Design: Ensure the search bar is accessible and functional across different devices and screen sizes.
Describe alternatives you've considered
Category Navigation: Implementing a category-based navigation system where users can browse reviews by predefined categories, but this may still require a lot of navigation and may not be as efficient as a search bar
Additional context (Mandatory )
Adding a search bar will significantly improve the user experience by making it easier and faster for users to find specific book reviews. It will enhance the overall usability of the application and encourage users to spend more time reading and engaging with the content.
Are you contributing under any open-source program ?
Yes

Please assign this issue to me.

@RithikaSundaram this is a good issue .But as per the rule of the repo . I have to close this issue .
Please don't raise more than 2 issues at a time. You can raise this issue again after completion of the previous 2 issues.


Backup Wikis

Describe the feature or enhancement
Currently, we are backing up just the code, but Wikis are another important piece of information that needs to be backed up for projects which uses them heavily.

Added as part of this release: https://github.com/AkashRajpurohit/git-sync/releases/tag/v0.8.0


Improve editor tooltips related to debugging

Some option names have also been made longer as we can afford using more space to display them.
Note: Not cherry-pickable without conflicts. It's probably better to copy-paste the new options names and their tooltips editor/editor_node.cpp when backporting this to the 3.2 branch.

Thanks!

Cherry-picked for 3.2.4.


[BUG REPORT] Raiders aren't getting logged keys. Handaewi getting database error and he verified correctly. He is in VC and bot did not dm him when key.

Version
0.6.2-pre.5
Description
Happens in Event-Bot-Commands and Stergar can log keys for himself but cannot for Handaeri same for Handaewi.
Reproduction Steps
Tried to log keys
Other Information
nope
Submitter Information
Discord Tag: BluBlazing#0151
Discord ID:<PHONE_NUMBER>42911488
Date/Time Submitted: 9/11/2020, 9:34:26 PM
Disclaimer: PLEASE READ
This issue was NOT written by the author of the repository OR the account that posted this issue. This issue was submitted through the program hosted in this repository, via Github's API, by someone that uses the program ("user"). The user can be found above.

will look into.

Resolved. The person needs to verify with the bot (i.e. the bot needs to give the Verified role)