Understanding feature_parallel distributed learning algorithm in LightGBMClassifier

I want to understand feature_parallel algorithm in LightGBMClassifier.
It describes how it is done traditionally and how LightGBM improves it
The two ways are as follows (verbatim from linked site):
Traditional Feature_parallel:
Feature parallel aims to parallelize the “Find Best Split” in the decision tree. The procedure of traditional feature parallel is:

Partition data vertically (different machines have different feature set).
Workers find local best split point {feature, threshold} on local feature set.
Communicate local best splits with each other and get the best one.
Worker with best split to perform split, then send the split result of data to other workers.

Feature_parallel in LightGBM: (Problem text bold and italicized)
Since feature parallel cannot speed up well when #data is large, we make a little change: instead of partitioning data vertically, every worker holds the full data. Thus, LightGBM doesn’t need to communicate for the split result of data since every worker knows how to split data
The procedure of feature parallel in LightGBM: (Problem text bold and italicized)

Workers find local best split point {feature, threshold} on the local feature set. (Why call it local? Since it is being found on the entire data this is the global best split)

Communicate local best splits with each other and get the best one. (But, earlier it was mentioned that Thus, LightGBM doesn’t need to communicate for the split result of data since every worker knows how to split data)

Perform best split. (Did we not already have the best split?)

Moreover, If each worker is retaining the entire dataset then it is capable of creating the entire estimator itself. What is distributed learning here?

Hi @Nitinsiwach, thanks for your interest in LightGBM.
First I'd like to point out that the feature parallel tree learner isn't available in the C API:
https://github.com/microsoft/LightGBM/blob/4aaeb22932b72aaff632b40ba596ca2533071ca2/src/c_api.cpp#L129 which means that right now you can only use it through the CLI.
I'll try to answer your questions based on what I think, I hope some other maintainer can correct me if I'm wrong:

Each worker finds the best split for the subset of features assigned to it, it is local in the sense that the global best split is the best split across all features.
This refers to saying: hey fellas, I found a split with this gain, and then deciding which one has the greatest gain. The difference with respect to the traditional approach is that using only the split info (i.e. X1 <= 16) each worker knows which indices of the data go left and which go right (because every worker holds the full data so they can make that split locally) whereas in the traditional approach the worker that has that feature locally (X1) has to communicate the indices to the other workers.
This refers to actually splitting the data based on the best split found in the previous step.

Hope this helps.

I'd also like to add... @Nitinsiwach please do not double-post here and on Stack Overflow at the same time: https://stackoverflow.com/questions/70678523/understanding-feature-parallel-distributed-learning-algorithm-in-lightgbmclassif.
Doing that means that it's possible that, for example, I could have been answering this question on Stack Overflow at the same time as @jmoralez was answering it here. That would be a bad outcome for the LightGBM project and its users, not just us personally, since we have limited time to spend on maintenance work here.
I'm also requesting that you not do this because, in my experience, we regularly see double-posting where the poster moves on after getting their answer in one place and does not go back to update the other place. That can lead to dead-ends for people facing the same issue in the future who find the unresolved post from search engines.

@jmoralez - That clears things up for me. Thank you so much for your time, effort and attention :)
@jameslamb - Thank you for helping me understand the proper and efficient code of conduct. I posted it on multiple forums for better reach. I did not think about the downsides of it which I clearly do now


Should we release a new patch with reverted dependencies to make 0.12 work?

Also see https://github.com/prebuild/prebuild/issues/188 and https://github.com/prebuild/prebuild/pull/190

Note that this should only be related to actually building on 0.12, not building for 0.12 :)

Yes should be quite easy to pin these dependencies to the latest working 0.x version, but I also think that noone will ever need it. And if so it's still fixable.


GNOME updates 2024-05-04

Plus some cleanups, see the commit messages.
There is a confidential (?) issue mentioned in https://gitlab.gnome.org/GNOME/vte/-/commit/aa405e4b0b2bf28bef2f7fd741881eaff92d1739 but the code does not seem to appear in vte-0-74.
Things done

Built on platform(s)

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

For non-Linux: Is sandboxing enabled in nix.conf? (See Nix manual)

[ ] sandbox = relaxed
[ ] sandbox = true

[ ] Tested, as applicable:

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

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[x] Tested basic functionality of all binary files (usually in ./result/bin/)
24.05 Release Notes (or backporting 23.05 and 23.11 Release notes)

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

[x] Fits CONTRIBUTING.md.

@ofborg build evince gnome.gnome-terminal vte gnome.gnome-software gnome.gnome-tweaks


Add support for memoroids (linear recurrent models)

What?
Implement FFM in flax
Why?
For https://github.com/EdanToledo/Stoix/issues/54
How?
Simply adds a new model
Extra
More commits coming. Just opening this to keep you in the loop.

Maybe you can help guide me how to integrate this. I was thinking to copy the recurrent PPO script and replace the LSTM with this. I think the biggest issue is I would need to do some plumbing to get the start flag used in memoroids. Basically, start should be 1 at the initial timestep of an episode and zero otherwise.

Amazing! This should be pretty simple to do. Essentially, the timestep.last() function returns if the time step is last and in the current auto reset api, this returns the first observation of the next episode which means that timestep.last() returns the is_first or "start" of an observation but the reward is for the last episode. You should be able to see that in the scanned RNN network, we use this to reset the hidden state as we want the hidden state for a first observation to be zeros. Let me know if that makes sense.

Sorry, I'm less familiar with the dm_env step format. I know with gym, the done flag denotes that the following observation is the terminal observation. With your format, is the done flag (discount == 0) set at the same time as timestep.last() == True? Obviously it's usually either one or the other that's set, but for the purposes of off-by-one errors are they equivalent?

no prob. let me just show how the auto-reset API works with an example to give you a better idea. Imagine a 3-timestep environment where each observation (obs) is simply the timestep number. Here is the rollout trajectory you would get considering you are storing transitions (obs, act, rew, done):
Trajectory Example
Episode 1:
t=0:

obs = 0
act = any (action taken using obs = 0 as input)
rew = reward obtained from taking act using obs = 0 as input
done = False

t=1:

obs = 1
act = any (action taken using obs = 1 as input)
rew = reward obtained from taking act using obs = 1 as input
done = False

t=2 (Last Timestep, terminal as well as start of episode 2):

obs = 0 (we auto-reset to the first observation of the next episode)
act = any (this would now be the action taken using obs = 0 as input)
rew = this would now be the reward obtained from taking act using obs = 0 as input
done = True (indicated by timestep.last or discount == 0)

As you can see in this final transition the obs, act and reward are actually related to the first timestep of the second episode. So when utilising this as a sequence, we would use the done/discount to mask the bootstrap prediction to be zero and we dont use the action and reward from this timestep.
Continuing on we would get:
Episode 2 remainder:
t=3:

obs = 1
act = any (action taken using obs = 1 as input)
rew = reward obtained from taking act using obs = 1 as input
done = False

t=4 (Last Timestep, terminal):

obs = 0 (auto-reset to the first observation of the next episode)
act = any (action taken using obs = 0 as input)
rew = reward obtained from taking act using obs = 0 as input
done = True (indicated by timestep.last or discount == 0)

Explanation
In this scenario, we never actually see obs = 2, which is the terminal observation. For non-truncating environments, the done flags (timestep.last or discount == 0 in this case) and discounts allow us to mask the bootstrap value when bootstrapping from the second obs = 0 prediction. This ensures it doesn't matter that it’s not the true final observation. This does involve care when utilising these sequences to construct value targets however its not that complicated - usually you just chop off the last timesteps reward and action values when doing things. You can see examples of this in any off policy algorithm that uses sequences (see MPO target value construction).
If you need access to the true final observation, it is available in the extras object. This does involve consideration on whether or not your environment truncates or not. For 1-step transitions like dqn I simply save the o_t and o_t+1 which eliminates any possible issue as i can use true observations. The reason for auto resetting like this is that it removes any dummy rewards and discounts for example when going from terminal obs to starting obs, there wouldn't be a real reward action, or discount.
Let me know if this helps.
Lastly, to just explicitly answer your questions. When timestep.last()==True this means that the observation in that timestep object is the terminal obs however as mentioned above this is not actually returned.

I'm just leaving a checklist here of things that need to be done:

[ ] Explicit catering of batch dimension i.e. not relying on flax.nn.vmap
[ ] When feeding in a starting carry i would like it to not need a sequence dimension i.e just a batch dimension and feature dimension. It feels more natural in my head to feed it like this - if we decide otherwise we need to change it for the other RNN classes to expect it this way.
[ ] Add one more type of cell (but only one more since i think we leave others for different PRs) just to check how general the infrastructure is.
[ ] Test on popgym to ensure it works

Additionally, I've officially merged the popgym PR so now we can test on popgym envs easily when we feel ready.

With respect to removing the sequence dimension in initialize_carry: I think you would be unable to run the cell without a singleton sequence dimension.  So basically something like:
class ScannedMemoroid(nn.Module):
    cell: nn.Module

    @nn.compact
    def __call__(self, recurrent_state, inputs):
        ### CHANGE HERE
        recurrent_state = jax.tree.map(lambda x.unsqueeze(0), self.cell.initialize_carry(batch_size, rng))
        # Recurrent state should be ((state, timestep), reset)
        # Inputs should be (x, reset)
        x, _ = inputs
        h = self.cell.map_to_h(inputs)
        recurrent_state = recurrent_associative_scan(self.cell, recurrent_state, h)
        # recurrent_state is ((state, timestep), reset)
        out = self.cell.map_from_h(recurrent_state, x)

        # TODO: Remove this when we want to return all recurrent states instead of just the last one
        final_recurrent_state = jax.tree.map(lambda x: x[-1:], recurrent_state)
        return final_recurrent_state, out

    @nn.nowrap
    def initialize_carry(
        self, batch_size: Optional[int] = None, rng: Optional[chex.PRNGKey] = None
    ) -> Carry:
        ### AND CHANGE HERE
        return jax.tree.map(lambda x.squeeze(0), self.cell.initialize_carry(batch_size, rng))

Let me know what you think?

@smorad I've now added the explicit expectation of a batch dimension - the network now works with rec_ppo.py natively simply by changing the network conf. For example we can do as follows now: python stoix/systems/ppo/rec_ppo.py network=memoroid
We now need to verify correctness, i do worry that there might be a bug somewhere since the performance on cartpole isn't that good, we get to 200+ quite quickly but it struggles to get to 500. Lastly, i had one concern, i see that the start variable is a part of the carry - is this normal? since ideally we feed the start sequence in via the inputs, not the carry. I'm not sure if it should be there? let me know?


[auth] Need the realmd package

This provides the tools for realm discovery and enrollment to assist in sssd configuration against directories such as AD or IdM.

and this is were it all begins

:+1: (my comment without the snark)


feature request: option to make the notification stay until dismissed

so if using a warning it would always appear until the user actually dismissed it

Couldn't you set delay to 0?

Yeah - totally missed that.


Added missing LICENSE files.

This PR adds some (well a lot of, actually) missing license files to the license collection process.

Thanks, looks good. I also checked this against your list and couldn't see anything that was missing.


Adding new repository for indexing: md25_driver

MD25 Motor Driver with Odometry tf Twist PID

I'm going to close this PR out for now until the licensing situation is sorted out.  Once that is done, please feel free to open a new pull request.


[BUG] Chapter 13 first cell did not complete after several hours google Colab on chrome - left overnight, timed out eventually - two different machines

Thanks for helping us improve this project!
Before you create this issue
Please make sure you are using the latest updated code and libraries: see https://github.com/ageron/handson-ml2/blob/master/INSTALL.md#update-this-project-and-its-libraries
Also please make sure to read the FAQ (https://github.com/ageron/handson-ml2#faq) and search for existing issues (both open and closed), as your question may already have been answered: https://github.com/ageron/handson-ml2/issues
Describe the bug
Please provide a clear and concise description of what the bug is, and specify the notebook name and the cell number at which the problem occurs (or the chapter and page in the book).
To Reproduce
Please copy the code that fails here, using code blocks like this:
def inverse(x):
    return 1 / x

result = inverse(0)

And if you got an exception, please copy the full stacktrace here:
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 2, in inverse
ZeroDivisionError: division by zero

Expected behavior
A clear and concise description of what you expected to happen.
Screenshots
If applicable, add screenshots to help explain your problem.
Versions (please complete the following information):

OS: [e.g. MacOSX 10.15.7]
Python: [e.g. 3.7]
TensorFlow: [e.g., 2.4.1]
Scikit-Learn: [e.g., 0.24.1]
Other libraries that may be connected with the issue: [e.g., gym 0.18.0]

Additional context
Add any other context about the problem here.

Fixed by author in just one day, amazing, thank you Aurelien Geron!!


graphql with ngnix

Describe the bug
I upgraded to the latest version today, I setup my domains on my vps via ngnix proxy manager. When I redirect domain.tld:333 to something like tasks.domain.tld everything cannot load and project dissapears. Tried this on Chrome, Edge,Firefox and Safari and it gives the same. When I inspect it gives me that it cannot load the graphql
Expected behavior
Everything should be accessed the same like when accessing through port.
Screenshots / Live demo link

Additional context
Add any other context about the problem here.
Inspection logs
This is a sample of the repeated logs
[Network error]: ServerParseError: JSON.parse: unexpected character at line 1 column 1 of the JSON data index.tsx:103:12
[Network error]: ServerParseError: JSON.parse: unexpected character at line 1 column 1 of the JSON data index.tsx:150:16
XHRPOSThttps://tasks.domain.tld/graphql
[HTTP/2 401 Unauthorized 136ms]

[Network error]: ServerParseError: JSON.parse: unexpected character at line 1 column 1 of the JSON data index.tsx:103:12
[Network error]: ServerParseError: JSON.parse: unexpected character at line 1 column 1 of the JSON data index.tsx:150:16
XHRPOSThttps://tasks.domain.tld/graphql
[HTTP/2 401 Unauthorized 132ms]

My own personal instance of Taskcafe uses Nginx as a reverse proxy and it works fine with the 0.3.2 release.
Can you post the taskcafe server logs and your nginx config?

My own personal instance of Taskcafe uses Nginx as a reverse proxy and it works fine with the 0.3.2 release.
Can you post the taskcafe server logs and your nginx config?

I did some debugging, and it seems the problem was that I put taskcafe beyond some access auth that keep promoting to enter auth in background even after you successfully do it.  I'm not sure if it still something important or not, but it is not a big problem since taskcafe have internal auth system anyway.
Thank you for your product and support.


[Question] Serenity.Scripts .net core 2.2 / 3.1 does not include script files into project

Hi @volkanceylan
I am upgrading Serenity.Scripts package for .net core and I see that it does not include scripts files into project so project is still using old files. I tested with both .net core 2.2 and .net core 3.1.
Latest version 3.12.4.
I also tried to install older versions but it looks no version work.
It works with .net framework project.
I thought that when I upgrade Serenity.Scripts package it will overwrite old files, is that correct ?

You should run dotnet sergen restore after updating packages, as specified in guide.
.Net core packages cant install static content unlike classic packages.

dotnet sergen restore

This works, many thanks


Coding Progress on CSA Mini Project 12/1

Individual and Team of 3 coding on CSA Mini Project.  Areas of emphasis...
Fibonacci - Inheritance and Abstraction
Sorting - Algorithms, Inheritance, Abstraction
Analysis - Calculation and Measurements
Each individual must show role in work.  Be prepared to show you personal key commits.  Individuals must have Java contributions.
Frontend
Emaad's commits:

Some of the key commits that I made to the frontend include:

Adding text indicating the user's score and the amount they bet
Adding a finish line to very end of the track of all four cars (that also had the word "finish" written on it)

Before, Emaad proposed that we could have a relatively simple design for the track and finish line, but
what we ended up doing was creating a much more aesthetically pleasing design (made by Tay) and merging his track design with Emaad's finish line, which ended up looking like this:

Tay's commits:

Here are the commits that I did:

Designed the track for sorting and fibonacci
Added lanes
Added user input box at the bottom
Added the car images to each lane

Ethan's commits:

My key commits to the frontend include my progress on the movement of the cars and their speed based off of the sorting algorithm each racer represents
The main function makes a GET request to the backend to retrieve the speed of each sort

Backend
Emaad's commits:

Some of the key commits Emaad made to the backend include:

Adding a folder for betting and some sample code for the betting
Adding a button and input box for the user's bet
Adding a method to CarApiController for returning the message the user gets after guessing right or wrong

Here is what some of the code looks like:
// Betting.java
package com.nighthawk.spring_portfolio.mvc.betting;

public class Betting {

    private int points;
    private String resultMessage;

    public Betting(int startingPoints) { // method for the actual Betting with parameter being the number of points the user begins with
        this.points = startingPoints;
    }

    public void placeBet(int betAmount, boolean isGuessCorrect) {
        if (betAmount > points) {
            System.out.println("Insufficient points to place bet.");
            // user cannot bet a number of points greater than the number of points they currently have, ex. can't be 501 points if they have 500 pts
            return;
        }

        if (isGuessCorrect) {
            points += betAmount*2;
            resultMessage = "Correct guess!  Current points: " + points;

        } else {
            points -= betAmount;
            resultMessage = "Wrong guess! You lost " + betAmount + " points. Current points: " + points;

        }

        System.out.println("Current points: " + points);

    }

    public String getResultMessage(){
        return resultMessage;
    }

    public static void main(String[] args) {
        Betting game = new Betting(500); // example call where user starts with 500 points

        // Example calls to placeBet method
        game.placeBet(150, true);
        game.placeBet(200, false);
    }
}

function placeBet() {
            const betAmount = parseInt(document.getElementById('betAmount').value);
            const userPoints = parseInt(document.getElementById('userPointsDisplay').textContent.split(': ')[1]);

            // Validate the bet amount
            if (isNaN(betAmount) || betAmount <= 0) {
                document.getElementById('betMessage').textContent = 'Error: Please enter a positive number.';
                return;
            }

            if (betAmount > userPoints) {
                document.getElementById('betMessage').textContent = 'Error: Bet amount exceeds available points.';
                return;
            }

            fetch(`http://localhost:8085/api/sort/bet?algorithm=YOUR_CHOSEN_ALGORITHM&betAmount=${betAmount}&startingPoints=${userPoints}`)
                .then(response => response.text())
                .then(data => {
                    document.getElementById('betMessage').textContent = data;
                    // Update user points based on the response
                })
                .catch(error => console.error('Error:', error));
        }

Tay's commits:

Here are some screenshots of my code:

What I worked on in backend:

Helping make the Car java files (most of them were deleted by Ethan because we realized they were not needed)
Making the fibonacci algorithms and creating the code for the fibonacci backend

To Do:

Add inheritance to the backend
Connect to frontend

Ethan's commits:

In the backend, I added the sorting algorithms (merge, insertion, bubble, selection)

It looks like ur all doing ur work, I like how u showed ur committed work and highlighted the code. Maybe some more explanation of the code would be good but overall work looks fine.


Add range functionality for monthly cadence.

Description
Add range functionality for monthly cadence.
Motivation and Context
RangeMonthly simplifies running backfilling jobs that run on a monthly basis, in a similar manner as RangeDaily, RangeHourly, etc.
Note that the PR adds a dependency on python-dateutil for date arithmetic.
Have you tested this? If so, how?
tox -e flake8
tox -e py27-core
No new test failures.
Also running in production since a few days back.
@ulzha, I think you might be a suitable reviewer for this one?

Rebased.


Updating the SDK dependencies for azure-containers-containerregistry (1.0.11)

API change check
APIView has identified API level changes in this PR and created following API reviews.
azure-containers-containerregistry


Snow layers spawn on ice/packed ice when temperature is low

OTG places snow layers on ice and packed ice when the temperature is low.
Snow layers shouldn't be able to spawn on ice or packed ice, breaking a single one currently causes a chain reaction of them disappearing across all adjacent surfaces.

Should be fixed for 1.12.2 v9.0_r9, available on the OTG discord.


Better way to initialize default values

css.gui uses a lot of complex data structures to represent complex properties like background, gradients, etc. Right now, when initializing these complex editors, the user must provide a valid initial value, which can get quite complex. To alleviate this, I can think of two interrelated ideas:

When the user uses a complex input (e.g. <Inputs.Background />, a valid default style should be initialized
The user should be able to specify initial values using pure css (e.g. box-shadow: 1px 2px 3px 4px black) which will be parsed to css.gui's internal spec

@tesseralis love both of the ideas. Is there any reason why all inputs shouldn't have a default value when initialized?


Problem: Signer dylib cannot spawn async tasks

Reopening this issue as the earlier change of passing tokio::runtime::Handle to dylib does not work. Tokio runtime depends on thread local storage to spawn tasks which is not shared with dynamic libraries (explained here).


[Subtask]: Implement collection of scan/commit metrics provided by Iceberg in AMS REST catalog

Search before asking

[X] I have searched in the issues and found no similar issues.

Description
Implement collection of scan/commit metrics provided by Iceberg in AMS REST catalog
Parent issue
#1528
Are you willing to submit PR?

[ ] Yes I am willing to submit a PR!

Code of Conduct

[X] I agree to follow this project's Code of Conduct

resolve in https://github.com/NetEase/amoro/pull/2101

resolve in https://github.com/NetEase/amoro/pull/2101


Fixed #4310, print useful message when dependency contains a malformed Cargo.toml

fixed #4310

r? @alexcrichton
(rust_highfive has picked a reviewer for you, use r? to override)

@bors: r+
Thanks!

:pushpin: Commit 0275ca0 has been approved by alexcrichton

:hourglass: Testing commit 0275ca0604b556cb30d0ed0e460a6ca11244f37b with merge 88d15f9885aa3c37ad619f723ea29549601d8dfc...

:sunny: Test successful - status-appveyor, status-travis
Approved by: alexcrichton
Pushing 88d15f9885aa3c37ad619f723ea29549601d8dfc to master...


add 2.9.2 changelog

Prepare 2.9.2 release and add changelog

Coverage remained the same at 90.991% when pulling 913fa9be9e56ef3ff5e37174b4d7f7c1c4d16da1 on Shegox:changelog-2.9.2 into c80a3b3faf12f681f2568a3152b260cdb485b452 on cla-assistant:master.


patch fixes for b2aiprep updates

I'll keep pushing fixes for b2aiprep.

closes #179 (allows for posixpaths)
fixes plugin_args for some pydra workflows
return a tensor to match the annotation

Codecov Report
Attention: Patch coverage is 75.00000% with 1 line in your changes missing coverage. Please review.

Project coverage is 60.24%. Comparing base (9b7209f) to head (ec871cc).
Report is 85 commits behind head on main.

Files with missing lines
Patch %
Lines

...elab/audio/tasks/features_extraction/torchaudio.py
0.00%
1 Missing :warning:

Additional details and impacted files
@@            Coverage Diff             @@
##             main     #180      +/-   ##
==========================================
- Coverage   68.32%   60.24%   -8.08%
==========================================
  Files          95      113      +18
  Lines        3283     4017     +734
==========================================
+ Hits         2243     2420     +177
- Misses       1040     1597     +557

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

@satra I have fixed the last style-related issue and adjusted some returned values to match the annotation

thanks @fabiocat93 - let me keep this open for a bit longer. i'll hit merge if i don't need any more changes.


safe mode by ellekit

16.2 13p Install the ellekit plug-in in safe mode, and have used serotonin and bootstrap before.

no clue, not an issue with dopamine, closing


added the doc 'development-workflow.md'

What problem does this PR solve?
The document can help contributor how to do development workflow.
What is changed and how it works?
I just added a document and update the document CONTRIBUTING.md.

What problem does this PR solve?
The document can help contributor how to do development workflow.
What is changed and how it works?
I just added a document and update the document CONTRIBUTING.md.

In order to solve the issue that the Contributor License Agreement is not signed by superadmin account, I open the new PR. So please close the up PR *:added the doc 'development-workflow.md'

Codecov Report

Merging #1464 into master will decrease coverage by 0.16%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master    #1464      +/-   ##
==========================================
- Coverage    67.8%   67.63%   -0.17%
==========================================
  Files         158      158
  Lines       15262    15262
==========================================
- Hits        10348    10323      -25
- Misses       4003     4019      +16
- Partials      911      920       +9

Impacted Files
Coverage Δ

server/leader.go
82.35% <0%> (-5.89%)
:arrow_down:

server/util.go
72.97% <0%> (-4.73%)
:arrow_down:

server/etcd_kv.go
70.9% <0%> (-3.64%)
:arrow_down:

server/core/kv.go
76.47% <0%> (-1.48%)
:arrow_down:

server/option.go
90.41% <0%> (-0.84%)
:arrow_down:

server/grpc_service.go
53.66% <0%> (-0.48%)
:arrow_down:

client/client.go
68.53% <0%> (-0.24%)
:arrow_down:

server/cluster.go
78.81% <0%> (+0.56%)
:arrow_up:

server/api/redirector.go
84.21% <0%> (+5.26%)
:arrow_up:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 59968e1...95a04b0. Read the comment docs.

/rebuild

/rebuild

@elitecodegroovy Thanks. Merged


Add description field for processes

Add a description field that uses the editor to allow users to capture extra information about processes that is not covered in the template.

Had to write a conversion script for current processes as some processes had a description field, some had a note field, and some had neither. Converted all to a description. Updated backend to allow process description field to be updated. Added call to front end to dynamically update the process description in the backend.


Application doesn't work

Every time when I'm trying something whatever like... decrypt, encrypt application shows error and doesn't actually do anything.

Could you please provide more info/screenshots, so that we can work on this issue?
What is the error you get exactly? Which version of the app? On which OS?


Loosing MQTT connection every ~14 hours

Hi,
We have a sim7000 on a esp32 running mqttloop() in a task every 200 ms.
see https://github.com/vshymanskyy/TinyGSM/issues/574
After approx 14 hours we every time loose MQTT connection, reconnecting GRPS goes oke but reconnecting MQTT fails.
A power cycle of the SIM7000 solves the issue, reconnecting and sending goes oke again.
Any ideas what can be the cause or in which direction to troubleshoot (as it only happens once every 14 hours...)
thx!

I have same problem but it shorter, try to add code to soft reboot the chip with ESP.restart() or check gprs connection and call: modem.gprsConnect(apn, gprsUser, gprsPass)


Update http4s-blaze-client, ... to 0.21.30

Updates

org.http4s:http4s-blaze-client
org.http4s:http4s-blaze-server
org.http4s:http4s-circe
org.http4s:http4s-core
org.http4s:http4s-dsl
org.http4s:http4s-prometheus-metrics

from 0.21.24 to 0.21.30.
GitHub Release Notes - Version Diff
I'll automatically update this PR to resolve conflicts as long as you don't change it yourself.
If you'd like to skip this version, you can just close this PR. If you have any feedback, just mention me in the comments below.
Configure Scala Steward for your repository with a .scala-steward.conf file.
Have a fantastic day writing Scala!

Ignore future updates
Add this to your .scala-steward.conf file to ignore future updates of this dependency:
updates.ignore = [ { groupId = "org.http4s" } ]

labels: library-update, semver-patch

Superseded by #1062.


Error using vllm OpenAI server

INFO:     <IP_ADDRESS>:48532 - "POST /v1/chat/completions HTTP/1.1" 500 Internal Server Error
ERROR:    Exception in ASGI application
Traceback (most recent call last):
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/uvicorn/protocols/http/httptools_impl.py", line 411, in run_asgi
result = await app(  # type: ignore[func-returns-value]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/uvicorn/middleware/proxy_headers.py", line 69, in call
return await self.app(scope, receive, send)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/fastapi/applications.py", line 1054, in call
await super().call(scope, receive, send)
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/applications.py", line 123, in call
await self.middleware_stack(scope, receive, send)
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/middleware/errors.py", line 186, in call
raise exc
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/middleware/errors.py", line 164, in call
await self.app(scope, receive, _send)
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/middleware/cors.py", line 85, in call
await self.app(scope, receive, send)
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/middleware/exceptions.py", line 65, in call
await wrap_app_handling_exceptions(self.app, conn)(scope, receive, send)
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/_exception_handler.py", line 64, in wrapped_app
raise exc
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/_exception_handler.py", line 53, in wrapped_app
await app(scope, receive, sender)
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/routing.py", line 756, in call
await self.middleware_stack(scope, receive, send)
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/routing.py", line 776, in app
await route.handle(scope, receive, send)
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/routing.py", line 297, in handle
await self.app(scope, receive, send)
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/routing.py", line 77, in app
await wrap_app_handling_exceptions(app, request)(scope, receive, send)
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/_exception_handler.py", line 64, in wrapped_app
raise exc
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/_exception_handler.py", line 53, in wrapped_app
await app(scope, receive, sender)
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/routing.py", line 72, in app
response = await func(request)
^^^^^^^^^^^^^^^^^^^
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/fastapi/routing.py", line 278, in app
raw_response = await run_endpoint_function(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/fastapi/routing.py", line 191, in run_endpoint_function
return await dependant.call(**values)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/vllm/entrypoints/openai/api_server.py", line 89, in create_chat_completion
generator = await openai_serving_chat.create_chat_completion(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/vllm/entrypoints/openai/serving_chat.py", line 68, in create_chat_completion
sampling_params = request.to_sampling_params()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/vllm/entrypoints/openai/protocol.py", line 157, in to_sampling_params
return SamplingParams(
^^^^^^^^^^^^^^^
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/vllm/sampling_params.py", line 157, in init
self._verify_args()
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/vllm/sampling_params.py", line 172, in _verify_args
if self.n < 1:
^^^^^^^^^^
TypeError: '<' not supported between instances of 'NoneType' and 'int'
INFO 07-04 07:24:41 metrics.py:218] Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 0 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 0.0%, CPU KV cache usage: 0.0%
INFO 07-04 07:24:51 metrics.py:218] Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 0 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 0.0%, CPU KV cache usage: 0.0%
INFO 07-04 07:25:01 metrics.py:218] Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 0 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 0.0%, CPU KV cache usage: 0.0%
INFO 07-04 07:25:11 metrics.py:218] Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 0 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 0.0%, CPU KV cache usage: 0.0%
INFO 07-04 07:25:21 metrics.py:218] Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 0 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 0.0%, CPU KV cache usage: 0.0%
INFO 07-04 07:25:31 metrics.py:218] Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 0 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 0.0%, CPU KV cache usage: 0.0%
INFO 07-04 07:25:41 metrics.py:218] Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 0 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 0.0%, CPU KV cache usage: 0.0%
INFO 07-04 07:25:51 metrics.py:218] Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 0 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 0.0%, CPU KV cache usage: 0.0%
INFO 07-04 07:26:01 metrics.py:218] Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 0 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 0.0%, CPU KV cache usage: 0.0%
INFO 07-04 07:26:11 metrics.py:218] Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 0 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 0.0%, CPU KV cache usage: 0.0%
INFO 07-04 07:26:21 metrics.py:218] Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 0 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 0.0%, CPU KV cache usage: 0.0%
INFO 07-04 07:26:31 metrics.py:218] Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 0 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 0.0%, CPU KV cache usage: 0.0%
INFO 07-04 07:26:41 metrics.py:218] Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 0 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 0.0%, CPU KV cache usage: 0.0%
INFO 07-04 07:26:51 metrics.py:218] Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 0 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 0.0%, CPU KV cache usage: 0.0%
INFO 07-04 07:27:01 metrics.py:218] Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 0 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 0.0%, CPU KV cache usage: 0.0%
INFO 07-04 07:27:11 metrics.py:218] Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 0 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 0.0%, CPU KV cache usage: 0.0%
INFO 07-04 07:27:21 metrics.py:218] Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 0.0 tokens/s, Running: 0 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 0.0%, CPU KV cache usage: 0.0%
INFO:     <IP_ADDRESS>:53354 - "POST /v1/chat/completions HTTP/1.1" 500 Internal Server Error
ERROR:    Exception in ASGI application
Traceback (most recent call last):
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/uvicorn/protocols/http/httptools_impl.py", line 411, in run_asgi
result = await app(  # type: ignore[func-returns-value]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/uvicorn/middleware/proxy_headers.py", line 69, in call
return await self.app(scope, receive, send)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/fastapi/applications.py", line 1054, in call
await super().call(scope, receive, send)
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/applications.py", line 123, in call
await self.middleware_stack(scope, receive, send)
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/middleware/errors.py", line 186, in call
raise exc
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/middleware/errors.py", line 164, in call
await self.app(scope, receive, _send)
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/middleware/cors.py", line 85, in call
await self.app(scope, receive, send)
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/middleware/exceptions.py", line 65, in call
await wrap_app_handling_exceptions(self.app, conn)(scope, receive, send)
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/_exception_handler.py", line 64, in wrapped_app
raise exc
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/_exception_handler.py", line 53, in wrapped_app
await app(scope, receive, sender)
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/routing.py", line 756, in call
await self.middleware_stack(scope, receive, send)
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/routing.py", line 776, in app
await route.handle(scope, receive, send)
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/routing.py", line 297, in handle
await self.app(scope, receive, send)
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/routing.py", line 77, in app
await wrap_app_handling_exceptions(app, request)(scope, receive, send)
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/_exception_handler.py", line 64, in wrapped_app
raise exc
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/_exception_handler.py", line 53, in wrapped_app
await app(scope, receive, sender)
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/starlette/routing.py", line 72, in app
response = await func(request)
^^^^^^^^^^^^^^^^^^^
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/fastapi/routing.py", line 278, in app
raw_response = await run_endpoint_function(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/fastapi/routing.py", line 191, in run_endpoint_function
return await dependant.call(**values)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/vllm/entrypoints/openai/api_server.py", line 89, in create_chat_completion
generator = await openai_serving_chat.create_chat_completion(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/vllm/entrypoints/openai/serving_chat.py", line 68, in create_chat_completion
sampling_params = request.to_sampling_params()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/vllm/entrypoints/openai/protocol.py", line 157, in to_sampling_params
return SamplingParams(
^^^^^^^^^^^^^^^
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/vllm/sampling_params.py", line 157, in init
self._verify_args()
File "/home/bigdata/anaconda3/envs/vllm/lib/python3.11/site-packages/vllm/sampling_params.py", line 172, in _verify_args
if self.n < 1:
^^^^^^^^^^
TypeError: '<' not supported between instances of 'NoneType' and 'int'

possible to share your config with keys redacted? thanks

possible to share your config with keys redacted? thanks

Sure. Here is my settings.yaml
encoding_model: cl100k_base
skip_workflows: []
llm:
api_key: ""
type: openai_chat # or azure_openai_chat
model: Qwen2-72B-Instruct-AWQ
model_supports_json: true # recommended if this is available for your model.
max_tokens: 4000
request_timeout: 180.0
api_base: http://<IP_ADDRESS>:7005/v1
api_version: Qwen2-72B-Instruct-AWQ
organization: <organization_id>
deployment_name: <azure_model_deployment_name>
tokens_per_minute: 150_000 # set a leaky bucket throttle
requests_per_minute: 10_000 # set a leaky bucket throttle
max_retries: 10
max_retry_wait: 10.0
sleep_on_rate_limit_recommendation: true # whether to sleep when azure suggests wait-times
concurrent_requests: 1 # the number of parallel inflight requests that may be made
model_parameters:
n: 1
parallelization:
stagger: 0.3
num_threads: 64 # the number of threads to use for parallel processing
async_mode: threaded # or asyncio
embeddings:
parallelization: override the global parallelization settings for embeddings
async_mode: threaded # or asyncio
llm:
api_key: ${GRAPHRAG_API_KEY}
type: openai_embedding # or azure_openai_embedding
model: text-embedding-3-small
api_base: http://<IP_ADDRESS>:3011/v1
# api_version: 2024-02-15-preview
# organization: <organization_id>
# deployment_name: <azure_model_deployment_name>
# tokens_per_minute: 150_000 # set a leaky bucket throttle
# requests_per_minute: 10_000 # set a leaky bucket throttle
# max_retries: 10
# max_retry_wait: 10.0
# sleep_on_rate_limit_recommendation: true # whether to sleep when azure suggests wait-times
# concurrent_requests: 25 # the number of parallel inflight requests that may be made
batch_size: 16 # the number of documents to send in a single request
batch_max_tokens: 8191 # the maximum number of tokens to send in a single request
# target: required # or optional
chunks:
size: 1500
overlap: 100
group_by_columns: [id] # by default, we don't allow chunks to cross documents
input:
type: file # or blob
file_type: text # or csv
base_dir: "input"
file_encoding: utf-8
file_pattern: ".*\.txt$"
cache:
type: file # or blob
base_dir: "cache"
connection_string: <azure_blob_storage_connection_string>
container_name: <azure_blob_storage_container_name>
storage:
type: file # or blob
base_dir: "output/${timestamp}/artifacts"
connection_string: <azure_blob_storage_connection_string>
container_name: <azure_blob_storage_container_name>
reporting:
type: file # or console, blob
base_dir: "output/${timestamp}/reports"
connection_string: <azure_blob_storage_connection_string>
container_name: <azure_blob_storage_container_name>
entity_extraction:
llm: override the global llm settings for this task
parallelization: override the global parallelization settings for this task
async_mode: override the global async_mode settings for this task
prompt: "prompts/entity_extraction.txt"
entity_types: [organization,person,geo,event]
max_gleanings: 0
summarize_descriptions:
llm: override the global llm settings for this task
parallelization: override the global parallelization settings for this task
async_mode: override the global async_mode settings for this task
prompt: "prompts/summarize_descriptions.txt"
max_length: 500
claim_extraction:
llm: override the global llm settings for this task
parallelization: override the global parallelization settings for this task
async_mode: override the global async_mode settings for this task
enabled: true
prompt: "prompts/claim_extraction.txt"
description: "Any claims or facts that could be relevant to information discovery."
max_gleanings: 0
community_report:
llm: override the global llm settings for this task
parallelization: override the global parallelization settings for this task
async_mode: override the global async_mode settings for this task
prompt: "prompts/community_report.txt"
max_length: 2000
max_input_length: 8000
cluster_graph:
max_cluster_size: 10
embed_graph:
enabled: false # if true, will generate node2vec embeddings for nodes
num_walks: 10
walk_length: 40
window_size: 2
iterations: 3
random_seed: 597832
umap:
enabled: false # if true, will generate UMAP embeddings for nodes
snapshots:
graphml: false
raw_entities: false
top_level_nodes: false
local_search:
text_unit_prop: 0.5
community_prop: 0.1
conversation_history_max_turns: 5
top_k_mapped_entities: 10
top_k_relationships: 10
max_tokens: 12000
global_search:
max_tokens: 12000
data_max_tokens: 12000
map_max_tokens: 1000
reduce_max_tokens: 2000
concurrency: 32

Sure. Here is my settings.yaml
encoding_model: cl100k_base
skip_workflows: []
llm:
api_key: ""
type: openai_chat # or azure_openai_chat
model: Qwen2-72B-Instruct-AWQ
model_supports_json: true # recommended if this is available for your model.
max_tokens: 4000
request_timeout: 180.0
api_base: http://<IP_ADDRESS>:7005/v1

api_version: Qwen2-72B-Instruct-AWQ
organization: <organization_id>
deployment_name: <azure_model_deployment_name>
tokens_per_minute: 150_000 # set a leaky bucket throttle
requests_per_minute: 10_000 # set a leaky bucket throttle
max_retries: 10
max_retry_wait: 10.0

sleep_on_rate_limit_recommendation: true # whether to sleep when azure suggests wait-times
concurrent_requests: 1 # the number of parallel inflight requests that may be made
model_parameters:
n: 1

parallelization:
stagger: 0.3
num_threads: 64 # the number of threads to use for parallel processing

async_mode: threaded # or asyncio

embeddings:

parallelization: override the global parallelization settings for embeddings
async_mode: threaded # or asyncio
llm:
api_key: ${GRAPHRAG_API_KEY}
type: openai_embedding # or azure_openai_embedding
model: text-embedding-3-small
api_base: http://<IP_ADDRESS>:3011/v1
# api_version: 2024-02-15-preview
# organization: <organization_id>
# deployment_name: <azure_model_deployment_name>
# tokens_per_minute: 150_000 # set a leaky bucket throttle
# requests_per_minute: 10_000 # set a leaky bucket throttle
# max_retries: 10
# max_retry_wait: 10.0
# sleep_on_rate_limit_recommendation: true # whether to sleep when azure suggests wait-times
# concurrent_requests: 25 # the number of parallel inflight requests that may be made
batch_size: 16 # the number of documents to send in a single request
batch_max_tokens: 8191 # the maximum number of tokens to send in a single request
# target: required # or optional

chunks:
size: 1500
overlap: 100
group_by_columns: [id] # by default, we don't allow chunks to cross documents

input:
type: file # or blob
file_type: text # or csv
base_dir: "input"
file_encoding: utf-8
file_pattern: ".*\.txt$"

cache:
type: file # or blob
base_dir: "cache"

connection_string: <azure_blob_storage_connection_string>
container_name: <azure_blob_storage_container_name>
storage:
type: file # or blob
base_dir: "output/${timestamp}/artifacts"

connection_string: <azure_blob_storage_connection_string>
container_name: <azure_blob_storage_container_name>
reporting:
type: file # or console, blob
base_dir: "output/${timestamp}/reports"

connection_string: <azure_blob_storage_connection_string>
container_name: <azure_blob_storage_container_name>
entity_extraction:

llm: override the global llm settings for this task
parallelization: override the global parallelization settings for this task
async_mode: override the global async_mode settings for this task
prompt: "prompts/entity_extraction.txt"
entity_types: [organization,person,geo,event]
max_gleanings: 0

summarize_descriptions:

llm: override the global llm settings for this task
parallelization: override the global parallelization settings for this task
async_mode: override the global async_mode settings for this task
prompt: "prompts/summarize_descriptions.txt"
max_length: 500

claim_extraction:

llm: override the global llm settings for this task
parallelization: override the global parallelization settings for this task
async_mode: override the global async_mode settings for this task
enabled: true
prompt: "prompts/claim_extraction.txt"
description: "Any claims or facts that could be relevant to information discovery."
max_gleanings: 0

community_report:

llm: override the global llm settings for this task
parallelization: override the global parallelization settings for this task
async_mode: override the global async_mode settings for this task
prompt: "prompts/community_report.txt"
max_length: 2000
max_input_length: 8000

cluster_graph:
max_cluster_size: 10

embed_graph:
enabled: false # if true, will generate node2vec embeddings for nodes

num_walks: 10
walk_length: 40
window_size: 2
iterations: 3
random_seed: 597832
umap:
enabled: false # if true, will generate UMAP embeddings for nodes

snapshots:
graphml: false
raw_entities: false
top_level_nodes: false

local_search:

text_unit_prop: 0.5
community_prop: 0.1
conversation_history_max_turns: 5
top_k_mapped_entities: 10
top_k_relationships: 10
max_tokens: 12000
global_search:

max_tokens: 12000
data_max_tokens: 12000
map_max_tokens: 1000
reduce_max_tokens: 2000
concurrency: 32

possible to share your config with keys redacted? thanks

Initially I thought maybe a default value which is surrounded by < could be the cause but it doesn't look like anything snuck in there. Which version of vllm are you on?

Hi @Shamepoo
Investigating at this it seems this could be due to some faulty parsing of the n parameter when building the configuration class on our end that ends up sending a None to the vllm backend.
I will submit a fix for this.

@AlonsoGuevara Yes, looking forward to that.

Support for Vllm would be highly appreciated.
Also any tutorial on how to adapt any LLM / Embedding endpoint to fit the GraphRag specifications.

Just submmited #390 This shall fix the error you're experiencing on vllm

Code is now merged, if you are running from source this should fix it. If running from pypi, on v0.1.2 I'll be including this fix

Code is now merged, if you are running from source this should fix it. If running from pypi, on v0.1.2 I'll be including this fix

Now works for me, thanks!

⠦ GraphRAG Indexer
├── Loading Input (csv) - 1 files loaded (1 filtered) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00 0:00:00
├── create_base_text_units
├── create_base_extracted_entities
└── create_final_covariates
❌ create_final_covariates
ERROR 07-16 12:08:18 api_server.py:247] Error in applying chat template from request: Conversation roles must alternate user/assistant/user/assistant/...

vllm is up and running properly but at this steps its showing that message


Application Error with matching domain

I get an error that an application can not be constructed ("cannot pass argument") although the type of the argument matches the domain exactly:
  '(0:(.Idx<PHONE_NUMBER>), _6524550, 1:(.Idx<PHONE_NUMBER>), _6524522, forOut_0, _6524540)' of type
  '[.Idx<PHONE_NUMBER>, .Idx<PHONE_NUMBER>, .Idx<PHONE_NUMBER>, [%mem.M, %matrix.Mat (2, (__6522473#1:(.Idx 2), __6522473#0:(.Idx 2)), T_6522475)], .Cn [.Idx<PHONE_NUMBER>, [%mem.M, %matrix.Mat (2, (__6522473#1:(.Idx 2), __6522473#0:(.Idx 2)), T_6522475)], .Cn [%mem.M, %matrix.Mat (2, (__6522473#1:(.Idx 2), __6522473#0:(.Idx 2)), T_6522475)]], .Cn [%mem.M, %matrix.Mat (2, (__6522473#1:(.Idx 2), __6522473#0:(.Idx 2)), T_6522475)]]' to
  '%affine.For<PHONE_NUMBER>, 2, (%mem.M, %matrix.Mat (2, (__6522473#1:(.Idx 2), __6522473#0:(.Idx 2)), T_6522475)))' of domain
  '[.Idx<PHONE_NUMBER>, .Idx<PHONE_NUMBER>, .Idx<PHONE_NUMBER>, [%mem.M, %matrix.Mat (2, (__6522473#1:(.Idx 2), __6522473#0:(.Idx 2)), T_6522475)], .Cn [.Idx<PHONE_NUMBER>, [%mem.M, %matrix.Mat (2, (__6522473#1:(.Idx 2), __6522473#0:(.Idx 2)), T_6522475)], .Cn [%mem.M, %matrix.Mat (2, (__6522473#1:(.Idx 2), __6522473#0:(.Idx 2)), T_6522475)]], .Cn [%mem.M, %matrix.Mat (2, (__6522473#1:(.Idx 2), __6522473#0:(.Idx 2)), T_6522475)]]'

Fork: NeuralCoder3
Branch: ad_ptr_merge
Commit: ee33da0a76068dc4743dabb08f7a39fd3679f17d
Command: ./build/bin/thorin -d matrix -d affine -d direct -d clos -d math -d autodiff lit/autodiff/matrix/prod.thorin -o - -VVVV
Situation: In the matrix medium level lowering pass.

Looks to me that sth in alpha-equiv is broken. I hope to finally have #153 ready this week. As this contains a major overhaul of this code, I don't want to touch it in master. Let's first merge #153, then I will investigate if the problem still persists.

Possibly related:
Nested calls like
.con print_m2d [mem:%mem.M] = {
    print_double_matrix_wrap (mem, l, n, m2d, return_cont)
};
.con print_m1d [mem:%mem.M] = {
    print_double_matrix_wrap (mem, k, l, m1d, print_m2d)
};
print_double_matrix_wrap (mem, k, n, m, print_m1d)

(or the inlined version
print_double_matrix_wrap (mem, k, n, m  , .cn [mem: %mem.M] = {
print_double_matrix_wrap (mem, k, l, m1d, .cn [mem: %mem.M] = {
print_double_matrix_wrap (mem, l, n, m2d, return_cont)
})

)
lead to application errors involving proxies:
lit/autodiff/matrix/prod.thorin:33:15-33:94: error: cannot pass argument
  '.proxy#8#0 print_double_matrix_wrap_6406994, 3' of type
  '%matrix.Mat (2, (k_6407046, l_6407048), %math.F (52, 11))' to
  '%core.bitcast (%matrix.Mat (2, ‹2; ⊤:.Nat›, %math.F (52, 11)), %matrix.Mat (2, (.proxy#8#0 print_double_matrix_wrap_6406994, 1, .proxy#8#0 print_double_matrix_wrap_6406994, 2), %math.F (52, 11)))' of domain
  '%matrix.Mat (2, (.proxy#8#0 print_double_matrix_wrap_6406994, 1, .proxy#8#0 print_double_matrix_wrap_6406994, 2), %math.F (52, 11))

The error does not occur with a single print call.
Fork: NeuralCoder3
Branch: ad_ptr_merge
Commit: 04c5f385f898c8d506eb936e4c61f124f04276d7
Command: ./build/bin/thorin -d autodiff lit/autodiff/matrix/prod.thorin -d affine -d matrix -d direct -d clos -d math -o - -VVVV --output-ll T.ll

Good thing: In my recent PR, I changed the alpha-equiv magic to always work optimistically. I.e. if you invoke checker().alpha_equiv(a, b), a and b must be alpha-equiv or there is a type error. This makes the logic a bit simpler and I can revert it how it used to work a few months ago.

#180 :
I've just fixed a problem in the matrix/product.thorin.disabled. Is this a different test case?
Now, I get:
../build/bin/thorin matrix/product.thorin.disabled                                                                                thorin: /home/roland/neural/dialects/matrix/passes/lower_matrix_mediumlevel.cpp:275: thorin::matrix::LowerMatrixMediumLevel::rewrite_(const thorin::Def*)::<lambda(thorin::u64)>: Assertion `idx == i && "output indices must be consecutive 0..n-1"' failed.

#180 : I've just fixed a problem in the matrix/product.thorin.disabled. Is this a different test case? Now, I get:
../build/bin/thorin matrix/product.thorin.disabled
thorin: /home/roland/neural/dialects/matrix/passes/lower_matrix_mediumlevel.cpp:275: thorin::matrix::LowerMatrixMediumLevel::rewrite_(const thorin::Def*)::<lambda(thorin::u64)>: Assertion `idx == i && "output indices must be consecutive 0..n-1"' failed.

The index issue was temporarily from switching the map to the absl one.
At one point I assumed an order which coincidentally was created by the std::map and in debug mode.
This should be fixed by e147add.

Can you check with #219?

Can you check with #219?

I will test it. But it will take time to resolve all the merge conflicts.


Connections UI - Addiotnal columns to view

Currently the only columns returning values in the grid are 'Connected To' and 'Role To'
Other columns such as Full Name and Job Title are coming up as blank.
Do we have to develop this additional functionality?

currently the view doesn't support adding columns from related records.


How to filter on EC2 instance limits

The following document suggests there's a way to filter based on resource limits.
How would one go about filtering based on specific instance types?
For example, last night we reached 25/25 of p3.16xlarges in us-east-1 and would like to create a policy that alerts us when we're near it the next time as well as for a list of other specific instance types.

OK to close.
I read through the man page for custodian schema account.filters.service-limit and ran the following policy just for grins:
policies:
  - name: account-service-limits
    resource: account
    filters:
      - type: service-limit
        services:
          - EC2
        threshold: 1.0

only to discover:
ClientError: An error occurred (SubscriptionRequiredException) when calling the DescribeTrustedAdvisorCheckResult operation: AWS Premium Support Subscription is required to use this service.
which we don't have at the moment.
Will likely try it out in the future.


chore: put toil execs on the path

Make sure the toil executables are in a directory that is on PATH
You can verify that this fixes the problem by starting this session, then doing renku update --all. It should update without errors.

ok now it actually works... 🙈


fix: split file at 00:00:01 && adjust publish tag

Checklist

[ ] npm test passes
[ ] tests and/or benchmarks are included
[ ] documentation is changed or added
[ ] commit message follows commit guidelines

Affected core subsystem(s)

Description of change

https://github.com/eggjs/egg/issues/1616

Codecov Report

Merging #14 into 2.x will increase coverage by 0.17%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##              2.x      #14      +/-   ##
==========================================
+ Coverage   95.67%   95.85%   +0.17%
==========================================
  Files          12       12
  Lines         185      193       +8
==========================================
+ Hits          177      185       +8
  Misses          8        8

Impacted Files
Coverage Δ

app/schedule/rotate_by_file.js
100% <ø> (ø)
:arrow_up:

app/schedule/clean_log.js
100% <0%> (ø)
:arrow_up:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 02f5a12...e7ba34c. Read the comment docs.


Add missing  entry to example route

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


Remove arch64Windows from nightly until new machine available

Signed-off-by: Andrew Leonard<EMAIL_ADDRESS>

run tests


Memory leak with UITableView binding

Hi,
i did a binding between an ObservableArray and a UITableView:
myArray.bind(to: tableView) {
   (array, tableView, indexPath) in

    return tableView.dequeueReusableCell(withIdentifier: "cell", for: indexPath)
}

but when I leave my view controller, the table view is deinit as it should be, but the cells are kept in memory. I don't observe this behavior when implementing UITableViewDelegate/DataSource and observing myArray to manually apply changes using Event<ObservableArray, NoError>.

Hi @XavierQuincieux,
Can you check what version you are using? There have been some fixes around that recently, but v6.5.2 should be good to go. I just run some additional tests and my cells are properly deallocating.


Can't open 'https://www.kognitio.com/software/KognitioJDBC.jar': Not Found or other driver

Description
Hi. I decided to download all the drivers. I find that it is not possible to download them
Official site: Kognitio acquired by WP Bolt
DBeaver Version
CE 23.1.0
Operating System
Win 10 x64
Database and driver
KognitioJDBC.jar
machbase.jar
Steps to reproduce
No response
Additional context
Download driver:
Can't open 'https://www.kognitio.com/software/KognitioJDBC.jar': Not Found
Can't open 'https://www.machbase.com/dist/machbase.jar': Not Found

https://artifacts.opensearch.org/opensearch-clients/jdbc/opensearch-sql-jdbc-<IP_ADDRESS>.jar Connection time out

@Steel-DSi Can reproduce for the machbase and kognitio, can download OpenSearch without issues. Thank for the report

https://mvnrepository.com/artifact/com.machbase/machjdbc machbase has this driver


Typo

At the end of the page it says "encyption algorithm" rather than "encryption algorithm". Missing an "r".

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

ID: 8f28f994-ad0f-72e5-79d2-6898421cb2fd
Version Independent ID: dbb83bbb-73cc-8233-15fb-1363b8ad1cd1
Content: Setting the BitLocker encryption algorithm for Autopilot devices - Windows Deployment
Content Source: windows/deployment/windows-autopilot/bitlocker.md
Product: w10
Technology: windows
GitHub Login: @greg-lindsay
Microsoft Alias: greglin

Fixing this now, thanks!

@GenerAhl : "This ensures that the default encrytion algorithm is not applied automatically when this is not the desired setting." Anyway, fair report, thanks.
(may as well dub myself "Captain Obvious" for this single comment)


ocrd-anybaseocr-textline: create inverted images

The following workflow produces inverted images of lines:
ocrd-anybaseocr-binarize
ocrd-anybaseocr-deskew
ocrd-anybaseocr-crop
ocrd-anybaseocr-tiseg
ocrd-anybaseocr-textline

This issue is resolved.

This issue is resolved.

How? Where?

https://github.com/mjenckel/ocrd_anybaseocr/pull/27/commits/0ac8567b1faffdd8bc5e1c67a74fb03761404661

Is https://github.com/mjenckel/ocrd_anybaseocr/compare/region_cropping_problem the current development branch? Why is it not up-to-date with master?

This branch is 28 commits ahead, 10 commits behind master.


Ion-slide , first image problem

Ionic version 2 rc3
I made a thumbnail list with images. After click on the image, image is opening in ion-slide.
After loading the ion-slide, each time shown is the first picture from ng-repeat for about a second (just quick blink), then after that the right image.

Hello, thanks for opening an issue with us! Would you be able to provide a plunker that demonstrates this issue? Thanks for using Ionic!

Hello, I am using the same version and I was able to reproduce the issue.
Here an example using numbers instead of images: http://plnkr.co/edit/WrwhdG?p=preview
I hope it helps.
Regards.
Alejandro.

Yes exactly, this is it! :) . I hide this bug in my project by fadein in css, but still would be good to fix it.

Thanks for the plunker @AleDurand !


Wrong scope analysis for for (var ....) statement

input
function bar(event) {
  for (var a = 0, l = array.length; a < l; a++) {
    array[a].call(this, event);
  }
}

Seems that the a in  a++ doesn't point to var a = 0.
visualized scope id by https://github.com/oxc-project/oxc/pull/2498
function bar#0(event#1) {
        for (var a#1 = 0, l#1 = array.length; a#1 < l#1; a#1++) {
                array[a#1].call(this, event#1);
        }
}

I found that l#1 = array.length is also suspicious. l should be resolved as a global binding instead of having the same scope with event#1.

I found that the scope analysis is correct in latest oxc main branch. I need to figure out why it's wrong in rolldown.


 Avoid validation on a YAML field, do not parse YAML

YAML parsing causes a fatal error if the field is not a string

@8book Where do you see this happening?

Actually I was trying to use the same Yaml I do with the other tags. And it was an error.
taxonomy:
author: exemplo
After testing a lot I found an example in the GRAV documentation that appeared something like below. And there it was!
items:
<EMAIL_ADDRESS>exemplo
But in the midst of so many tests I also discovered that this way when we switch to normal mode and save it gives error because the field "Items" in the Admin tries to rewrite and makes it go wrong.

To me it looks like your issue isn't the one in this issue and that you're trying to do something in a wrong way.

It's exceedingly simple what I wanted to do just to make the author collection.
Either way works the second way, so an hour is solved


Gardena support

Hi, I was wondering whether it would be possible to add support for Gardena Mowers in your plugin? I know that the Husqvarna and Gardena mowers are closely aligned, and I therefore thought the possibility could be there?
Regards,
Joachim

Hi,
As I already said to a similar request, since I don't' own a Gardena mower it will be quite difficult to adapt . At least I would need some http request with headers and payload to the servers . Husqvarna app was doing certificate pinning, so it was quite difficult, don't know about Gardena .

Hi Nicolas
Thank you for your response. I would very much like to be of assistance and help with any information needed in the proces of making a Gardena homebridge plugin.
I can see on the Husqvarna Group website, that there is a detailed read me on the subject on the smart system API with the aim of enabling developers to control the Gardena smart system:
https://developer.husqvarnagroup.cloud/apis/GARDENA+smart+system+API#/readme
Do think there is possibility of developing such a plugin?
Kind regards,
Joachim Becker,
Denmark.
Den 18. jul. 2021 kl. 12.52 skrev Nicolas Dujardin @.***>:
Hi,
As I already said to a similar request, since I don't' own a Gardena mower it will be quite difficult to adapt . At least I would need some http request with headers and payload to the servers . Husqvarna app was doing certificate pinning, so it was quite difficult, don't know about Gardena .
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub https://github.com/nicoduj/homebridge-automower/issues/29#issuecomment-882037407, or unsubscribe https://github.com/notifications/unsubscribe-auth/AUVZXWSOQXMFWW4CEAR5RXDTYKW6NANCNFSM5AMFBWVQ.


Clarify argument naming

Some function had really unclear argument names, specifically the capsule ones. I was completely stumped when I first saw the capsule function.
Also removed some abbreviations in the arguments, while pt is relatively obvious, it is better to be as explicit as possible in the user facing API.

Thanks!


Support TLC module ToString Operator

TLC module has a ToString operator that converts an input to string. Currently, it's not possible to use this in an MPCal spec.

Can you include a link to where this operator is documented / specified? I'd like to attach it to the correct import, etc...

https://github.com/tlaplus/tlaplus/blob/master/tlatools/org.lamport.tlatools/src/tla2sany/StandardModules/TLC.tla#L121


Nightly Build Binaries

@av8ramit Are there any updates on ways to obtain nightly builds for the dynamic libraries (i.e., libtensorflow.so and libtensorflow_framework.so)? In the beginning of the summer you had mentioned that you were working on a new way to do that.

Hey @eaplatanios sorry for the delay we are still in the process of doing so.
@asimshankar any thoughts on the best place to store these?

@av8ramit : Where are the nightly pip wheels stored? Can we use the same location? (Or if not, can we carve out a nightly directory in storage.googleapis.com?)

@asimshankar nightly pip whls are stored on pypi which I don't think is feasible. Does storage.googleapis.com work?

I don’t know if you are expecting a reply from me but this solution would be great! One option would be to put them alongside the release versions and change the version number to something along the lines of 1.11-nightly, or even just nightly.

@eaplatanios I'll try my best to accommodate soon!

@av8ramit That’s great, thanks!:)

Status update: Blocked on something @eaplatanios but still working on it.

@av8ramit Thanks a lot for the update and sorry for the slow response but I was traveling all this time. Do you have an approximate ETA by any chance?

1-2 weeks.

Nightly LibtensorFlow Ubuntu
JNI CPU
JNI GPU
Proto
CPU
GPU
SRC-jar
jar
Here are the nightly links for now until I get a cleaner chance to present them.

@av8ramit That's great and sufficient for me as I only need links. I notice though that there is no option for mac binaries. Are those available too? I tried changing the platform name to "darwin" for the CPU links you posted, but couldn't get a valid link. Thanks a lot! :)

I've only been able to do linux binaries so far. Mac and windows will come soon.

How about now for mac?

@asimshankar do you see value in making these links public or adding them to the README?

@av8ramit Sorry I never responded. Thanks for the Mac binaries too! Regarding value in these links, I believe that other people using the C API may find those useful, same way that I do.

Nagging Assignees @asimshankar, @av8ramit: It has been 14 days with no activity and this issue has an assignee. Please update the label and/or status accordingly.

@av8ramit There seems to be an issue with the Linux GPU binaries, that I can't figure out. I get the following error when using the GPU prebuilt binaries:
undefined symbol: _ZN10tensorflow12OpDefBuilder4AttrESs

I don't get this error with the CPU binaries. Do you know what may be causing this? Are they both compiled using GCC 4?

@av8ramit I see that the precompiled GPU binary (libtensorflow_framework.so) contains this symbol:
_ZN10tensorflow12OpDefBuilder4AttrEN4absl11string_viewE

whereas the CPU one contains:
_ZN10tensorflow12OpDefBuilder4AttrESs

Should this be expected? And even so, why does this inconsistency exist?

I suspect what happened is that one of the binaries is built with https://github.com/tensorflow/tensorflow/commit/6fa6bd045c98bdc89424a3425e15b5161586a9a7 and the other with https://github.com/tensorflow/tensorflow/commit/3f23f4ddeabbdc0704444d84c158bd6c348a9f10
@av8ramit can correct me if I'm wrong, but I believe we don't currently guarantee that all the nightlies are built from the exact same version (as per https://github.com/tensorflow/community/blob/master/rfcs/20181026-tf-nightly.md)

@asimshankar @av8ramit I see that makes sense. So, it used to be that there was a Travis interface where we could go and check when the last successful build was. Does that something like that still exist, so we have some information about when the nightlies are obtained from?

@asimshankar @av8ramit Sorry for the spamming, but are there any updates on this?

Hi @eaplatanios Sorry about the delay. I'll look into this this week. Hopefully have it fixed after the holiday. Prioritizing ubuntu GPU for you.

@av8ramit That's great. Thanks a lot! :)

@eaplatanios has this been fixed?

@eaplatanios is this working for you now?

@av8ramit Sorry I was away for the break. Yes it is. Thank you very much!
Are there any plans to gave a build status page on your CI server like you used to so we know what day the current build is from?

There is no immediate plan to create a better UI or adopt Travis for libtensorflowbuilds.


SecondaryDeserializer should not be a singleton

Hi,
we are migrating our deserializers to GLUE using the fallback option with SecondaryDeserializer.
We have both Avro SpecificDatumReader and GenericDatumReader in our project so we need to have different types of SecondaryDeserializer.
However, the SecondaryDeserializer is a singleton and we can't have two instances of it.
It would be better if the we can have one SecondaryDeserializer instance per AWSKafkaAvroDeserializer.

I can update the changelog on your behalf. Thanks for the PR.


Modify player spawn in end...still not working

Maybe I'm dumb but still not working can someone help ?
Here is the code, still not working i go inside minecraft and put the datapack in folder. but when i go in the world, the origin isn't there, i try to F3+T and still nothing... can someone make like his own power for spawing in end and send it here ?
Here is everything i've wrote :
{
"powers": [
"inanis:air_swimming",
"inanis:damage_from_no_sky",
"inanis:no_exhaustion",
"inanis:end_spawn",
"origins:translucent",
"origins:water_vulnerability"
],
"icon": "minecraft:end_crystal",
"order": 10,
"impact": 3,
"name": "Inanis",
"description": "Born in the overworld, the Inanis has been cursed by the Master of the end this way they will always wander in his dimension."
}
{
"type": "origins:damage_over_time",
"interval": 200,
"onset_delay": 40,
"damage": 1,
"condition": {
"type": "origins:exposed_to_sky",
"inverted": true
},
"name": "Desire for Freedom",
"description": "You always want to be able to see the sky, because otherwise you will slowly take damage."
}
{
"type": "origins:modify_exhaustion",
"modifier": {
"name": "No exhaustion from Origin power",
"operation": "multiply_total",
"value": 0
},
"name": "Ethereal Body",
"description": "You do not exhaust."
}
{
"type": "origins:swimming",
"condition": {
"type": "origins:fluid_height",
"fluid": "minecraft:water",
"comparison": ">",
"compare_to": 0.0,
"inverted": true
},
"name": "Spirit of Void",
"description": "You are able to swim through the air."
}
{
"type": "origins:modify_player_spawn",
"dimension": "minecraft:the_end",
"structure": "minecraft:endcity"
}

this is probably due to how you can't modify the search range of spawn locations.
It's only searching the end island (the one with the dragon on it) essentially.


Automatic PR of restapi_auto_dmakwana_capabilities-in-properties into dev

Created to sync https://github.com/Azure/azure-rest-api-specs/pull/2392

Closing for now, in response to #1057. These changes will be incorporated shortly.


Unhandled exception after login

[x] I have searched open and closed issues for duplicates
[x] I am submitting a bug report for existing functionality that does not work as intended
[x] This isn't a feature/enhancement request or a discussion topic

Bug description
I'll describe later
Steps to reproduce the bug

using hyphens as bullet points
list the steps
that reproduce the bug

Actual result: Describe here what happens after you run the steps above (i.e. the buggy behavior)
Expected result: Describe here what should happen after you run the steps above (i.e. what would be the correct behavior)
Screenshots

Logs

Version info

Shotr Version: 3.0.9

@Tursko any more details on this one?

Only happens on a fresh install. Just try to login, it will log you in but throw an exception.

Saving this here for later:


Fixes a crashing issue on snapshot between iOS7 and iOS8

Fixes a crashing issue on snapshot between iOS7 and iOS8

Thanks


Changed application icon

Issue #140

Coverage remained the same at 69.476% when pulling 2bedf073c8c2a2089bb9a1489e1595d808935757 on change-application-icon into 8e326a023c339a6a4d0707f1e6ad89b0503d9a42 on master.

reviewed


bug(Navisworks): Incorrect number of objects reported as sent.

The logic for counting the actual number of objects sent is broken with changes to the traversal of Collections.
A new logic for counting post-conversion is needed.

Closing this ticket as we are moving to Jira to reduce noise. You can access it there.


docs: Add automatic IAM Authentication Example

Change Description
I would like to add Automatic IAM Authentication to the examples on https://cloud.google.com/sql/docs/mysql/connect-kubernetes-engine
One step in doing that is adding an example .yaml file for the sidecar deployment.

Maybe I misunderstand, but should this be an entirely separate example file? The paragraph https://cloud.google.com/sql/docs/mysql/connect-kubernetes-engine#run_the_in_a_sidecar_pattern is part of a parent paragraph about IAM authentication with the Cloud SQL Auth Proxy sidecar entirely I think, either through Workload Identity or a service account key.
I think the - "--enable-iam-login" flag should be added to the existing proxy_with_workload_identity.yaml example rather than introducing a new file.

@eightfourseventwo There's a distinction between IAM authz and authn here. Workload identity enables authz (is this IAM principal allowed to connect to Cloud SQL). Auto IAM AuthN (enabled with --enable_iam_login in v1 and --auto-aim-authn in v2) makes it possible to log into the database using the environment's IAM principal. When you have both workload identity and auto IAM authn enabled, you use the same IAM principal to both control connecting to Cloud SQL and to log in to Cloud SQL.
In any case, I think this is a stale PR. @LukeSchlangen if you want to pick this work back up again let's talk about the best way forward.


Fix brew tap integration via GoRelease

Fixed as part of https://github.com/goyalmunish/reminder/pull/143 and https://github.com/goyalmunish/reminder/commit/e11a6bf5bd212aaedf4ba6dca2db999281e03e9e


Typo fix

Bandit: execlude -> exclude

Status
Ready
Related Issues
fixes: https://github.com/demisto/content-docs/blob/master/docs/integrations/linting.md#bandit
Description
Typo fix in the ## Bandit section. execlude -> exclude

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


California - Core Bio Labs - Baseline Research

Problem Statement
Naval Health Clinic Lemoore (NHCL) has requested to be onboarded to ReportStream and the CSV Uploader.
Contact Info
Andrew Bronkema
Site Manager
Source BioScience
<EMAIL_ADDRESS>Request Email
https://app.zenhub.com/files/304423150/72648e1a-7dc7-47c8-851d-715fc0a4c6ff/download

@rhood23699 @victorialb-usds @rachelhanster @drew-usds

Here is where I am going to track where things are. https://cdc.sharepoint.com/:x:/r/teams/USDSatCDC/_layouts/15/Doc.aspx?sourcedoc={1653409F-6449-4D8C-8707-958767522CAD}&file=Sender Pipeline Onboarding Tracker.xlsx&action=default&mobileredirect=true&DefaultItemOpen=1 once they are in production I would like to do check-in call and then at 45 days post production and at these check-ins maybe do some UI testing. CC: @drew-usds @inkandsound

Information is logged in here: Information entered into tracking sheet: https://cdc.sharepoint.com/:x:/r/teams/USDSatCDC/_layouts/15/Doc.aspx?sourcedoc={431D9FDE-C408-43E7-B643-E1D30652155C}&file=CSV pilot cohort 1_Pre Post Data.xlsx&action=default&mobileredirect=true&DefaultItemOpen=1&cid=f5f8bd31-6856-436a-b8c2-e7629f60d9ca
Specific notes in here: call 1/25; email from CADOPH; https://cdc.sharepoint.com/:w:/r/teams/USDSatCDC/_layouts/15/Doc.aspx?sourcedoc={DC5BA733-8548-40B5-A897-DE197A425016}&file=CA_SenderCore_Biolabs_CSV upload pilot discovery research_1.25.22.docx&cid=579372c3-c8e9-46b6-add4-87092db311de


Celsius Temperature Setting Not Merged Correctly

Though 63e73195acf76fb7cc1180dabe5605e335c1d7af adds Celsius support, this appears to be accidentally reverted by 30cec1005949a8c1822bc1bd1d4e93caf78b26b8

(Hopefully) resolved via #39


cups 2.2.8 and papercut compatibility (Possible CUPS 2.2.8 windows lpd bug?)

I've been having some "issues" working with cups 2.2.8 on Linux and Papercut Windows Mobility Client.
Specifically:
The Papercut Windows Mobility Client/Server setup validates a user once (when the printer queue is setup) then never bothers do so so again (ie, takes no notice of password changes or if the user has been disabled).
The server side of the Papercut software submits to CUPS via LPD to localhost.
On Linux RHEL7,  CUPS 2.2.8 "lpd localhost" asks for a password by default - at which point the Papercut software barfs and silently drops the job.
If CUPS is set to not require authentication then the job prints OK, but user is smashed to "anonymous" and print accounting fails (I'm happy with this. Blocking paths to spoofing is a good thing)
Papercut claim that the Windows version of CUPS 2.2.8 doesn't exhibit the same behaviour, that CUPS shouldn't be asking for passwords, that it's too hard for them to fix their software so that it verifies passwords at least once per session like every other (well-behaved) print client does and that the correct fix is to disable authentication or to use a Windows CUPS server.
I tend to disagree....
I believe that the cause of their misguided behaviour and advice is down to CUPS 2.2.8 LPD on windows accepting unauthenticated jobs without smashing them down to "anonymous" .
Would the devs mind looking into this and see what the defaults are and fixing it if need be?
(Of course, if there actually WAS a properly decent IPP interface for windows, a lot of these outfits would be out of business, but that's another issue.)

(WRT the comment about an IPP interface - it may not be common knowledge yet, but MS have stated that the Samba print interface is going away in 2019, so a MS Windows IPP printer GUI is about to become a critical issue for many people)

@Stoatwblr The default for printer sharing is not authenticated - you have to choose the policy. Since LPD does not support authentication at all, enabling authentication effectively disables (incoming) LPD print jobs.
I'm not aware of a CUPS package for Windows that offers LPD support. Certainly Windows has/had an LPD listener service to support legacy clients, but AFAIK it isn't widely used.
Do you have any public references/URLs on MS dropping SMB printing? That would be a surprise to me given that CIFS has been a central part of Windows networking...

@Stoatwblr Ping...

Sorry, illness getting in the way.
Yes, CIFS has been a central part of MS networking and appears to be being retained for filehandling but my interpretation of the report is that print shares will be phased out - and more importantly the handing off of print drivers via CIFS will be removed earlier than that, which will cripple print-via-samba  even if print shares are retained as being unable to manage printer drivers will result in network chaos on any medium sized network.
(CIFS hs a lot of issues WRT mixed environments performance and compatibility-wise anyway. Whilst not an issue for printing it's not uncommon to find that file latencies are in the order of a few milliseconds via samba when the underlaying disks are shared via other means, due to the need to avoid lock/write contention. This may not sound like much but it translates to complaints of Samba file shares being 1/3 the speed (Linux and BSD servers) of native NT ones, and opening directories with hundreds-to-thousands of files being a major performance hit (likewise opening 2500 16kB files - almost instant on local disk, a few seconds when on a NT fileserver, yet can take 5 minutes when on a *nix fileserver nfs exporting over 10GB/s to a samba server re-exporting to windows clients thanks to uncacheable lock checks)
I will have to dig the MS report up, but what's clear is that MS seem to be determined to remove a lot of the legacy networking protocols. Please give me a day or so.
As you should be aware, network browsing (groups/neighbourhoods) was disabled in Win10 a few months back. One of the reasons for needing Papercut is the issue that whilst CUPS provides mDNS (multicast) support for unrouted networks, similar support for DNSSD (service discovery) isn't there and that's another critical need in complex routed networks - yes you can set DNSSD up statically on a BIND server, but that means if a CUPS server or queue goes down, things can start breaking.
DNSSD is (of course) critical for both OSX and WIN10 systems to find printers
Back to the other issues:
The LPD I'm testing with is your cups-lpd, which on our test RHEL7 environment (cups 2.2.8 local build) either smashes everything to anonymous or requires anthentication enabled. (I'm not overly complaining about this. Whilst Kerberos works to keep the *nixen and SSO systems in line, trusting that supplied IPP userIDs will be accurate on jobs coming from portable systems is "optimistic" at best.)
Papercut are testing with cups on Windows, and a windows-specific LPD (not cups-lpd)
Longer-term there is a crying need for a decent IPP interface on Windows.
The existing MS IPP interface is beyond user-unfriendly. Commercial alternatives aren't much better - and they're expensive for what they do. Needing to deploy a hefty java-based print management/accounting system primarily to be able to cope with windows users (portables and desktops) which have constant driver updates and subsequently keep "losing" printers is a support nightmare in an academic environment.
Is there any way of implementing a workable CUPS gui client on WIn8/10? (the older OSes are EOL, so no need to bother)
The constant refrain of users is "This works fine at home. Why is it so ********ing broken at work?" and I've heard it in virtually every complex networked environment I've stepped into. "We" (the geeks) are felt to be making things too hard, for no good reason. The result is frequently "guerilla printing" - unauthorised printers deployed in offices over USB connections, with their associated costs and security risks - We've run into a couple which were effectively bridging their host computer onto printer-based Wifi APs as one example (with knock on effects on the wifi network too)

@Stoatwblr Again, current CUPS does not run on Windows (you can run ippfind and ipptool and build applications against libcups, but that's it) so I have no idea what Papercut is doing on Windows.
Unfortunately, the current Windows print system is not friendly to CUPS - Win10 can send PWG Raster data now (as an IPP Everywhere client) but Win8 is a lost cause. And PWG Raster isn't the ideal format to be sending to a print server - we'd really want PDF but MS doesn't do PDF...


Replaced opencv with imagesize to get the actual image size

As described in https://github.com/RangiLyu/nanodet/issues/530, this PR replaces the use of opencv with the imagesize package to increase performance.

Strange, I did not change anything for the one-stage detector...


for reference README should mention the paper describing a deployment of GDRCopy in MPI

the paper is https://ieeexplore.ieee.org/abstract/document/7116873
"Designing efficient small message transfer mechanism for inter-node MPI communication on InfiniBand GPU clusters" HiPC2014

fixed with 746ba63


Refactor point selection code

🧰 Task
The point selection code is messy with one callback doing many things, the logic is a bit confusing but nicely summarised by @mstabrin in #5022
Click

All points are deselected, except the one below the cursor.

Drag

If there is a selection and the cursor is above a points, the points are dragged
if there is no selection a drag box to select the points within the box is shown.

Click with modifiers

The point below the cursor is added to the selection if not selected, it is deselected when already selected.

Drag with modifiers

A drag box to select the points within the box is shown. Selected box within the box are deselected, deselected ones are selected.

I am merging #5022 as a strict improvement over what we have and high value for 0.4.17, but we should really tidy this up ASAP

To me, the select behavior of the Points and the shapes layer is quite inconsistent both in behavior and in implementation. Should be considered during a tidy up :)

Great point! Could you be a little more specific? I personally don't use the shapes layer much


Envelope.delay problem

Hallo TSynth. Nice projekt :)
But i have a problem with envelope.delay funktion in exp. envelope.  If I set envelope.delay to 6ms and play more notes, the envelope freezes. With 0ms delay, the envelope works without any problems. Envelope.delay from P. Stoffregen has no problems.
Thanks for your help :)

It looks as if the issue is that exp_count doesn't get set in noteOn(). If you trigger a new note exactly as the release phase finishes, so state == STATE_IDLE but an update() hasn't occurred to set exp_count to the delay value, it will have the stale value from the end of the decay phase, which is -2 32, so your delay suddenly becomes very long indeed.

Discussion in the Teensy Forum: https://forum.pjrc.com/index.php?threads/teensy-exponential-envelopes.75646/#post-348080

Result:
void AudioEffectEnvelope::noteOn(void) {   //__disable_irq();   if(release_forced_count==0)      state=STATE_IDLE;      switch(state)   {     case STATE_IDLE:     case STATE_IDLE_NEXT:       count=delay_count;       if(count>0)       {         state=STATE_DELAY;         inc_hires=0;       }       else       {         state=STATE_ATTACK;         count=attack_count;       inc_hires = 0x40000000 / (int32_t)count;       }       exp_count=((uint32_t)(delay_count))*8; //!!!!FRE as per advise from h4yn0nnym0u5e teensy forum       ysum=0;       break;         case STATE_DELAY:     case STATE_HOLD:     case STATE_ATTACK:     case STATE_DECAY:     case STATE_SUSTAIN:     case STATE_SUSTAIN_FAST_CHANGE:     case STATE_RELEASE:       state=STATE_FORCED;       count=release_forced_count;       inc_hires=(-mult_hires)/(int32_t)count;     case STATE_FORCED:       break;     default:       state=STATE_RELEASE;       break;   }   //__enable_irq(); }


missing middleware for parsing json

Update to Use express.json(): If you're planning to handle JSON requests in your Express application, ensure that your main application file includes express.json() as middleware.
Ensure Proper Initialization: If there's a specific test failing, make sure the app is correctly initialized before running requests against it.
Improve Error Handling: Make sure to handle errors gracefully, especially for any routes that might throw errors.

@Virendrapro I was not able to understand what this PR does. Currently you overwritten all the exports functions defined in this file. This change will break the library.


Data Acquisition

[ ] get Data
[ ] split into train test
[ ] get the important columns
[ ] save the progress

data has been acquired and saved


Updating rollup-plugin-postcss stopped the build extracting CSS correctly

A clean install of v1.19.5 now outputs all css files as [object Object]
v1.19.4 works as expected.

Yep, this was a bug.  Updated post-css to fix a security issue.  Latest post-css only works with a newer version of rollup.  Just updated rollup right now.
Please try v.1.19.6 really quick and let me know what happens.

There's some deprecation warnings now but seems to work 👍
(!) node-resolve plugin: The onwrite hook used by plugin node-resolve is deprecated. The generateBundle hook should be used instead.

I will look into getting rid of those deprecation warnings in the near future.  I just wanted to get you fixed first.


[enhancement] add supercronic docker image to docker hub

it will be awesome to see in docker hub the official docker image of supercronic.
any chance that it will happen?

Kinda unlikely — Supercronic isn't really a base you build on, it's something you add to an existing image to be able to run cron there. I think providing a base image encourages people to use this the wrong way, TBH.

Hi @krallin , it's still seems that can be relevant by using the Supercronic in k8s as a side car container which can mount crontab file and other scripts by using configmaps.
But thanks anyway for your fast response!


Remove version: Autodesk.sketchbook version <IP_ADDRESS>

[Automated] It returns code over 400 in all urls
Microsoft Reviewers: Open in CodeFlow

For moderators
This account is automated by Github Actions and the source code was created by CoolPlayLin. If you have any questions about any pull request, don't hesitate to ping Exorcism0666.

[!warning]
With the new version of Komac, numerous Pull Requests may contain bugs or unwanted elements. If such issues arise, please tag russellbanks so that these bugs can be addressed in future updates.

[!important]
Please carefully review these Pull Request before merging. If it is a Pull Request for removing incorrect content and the URLs are issue, free upon manual checking, please close this Pull Request directly. (It is best to inform Exorcism0666 of the closure.)

良い一日をお過ごしください！

URL: https://download.autodesk.com/us/support/files/sketchbook/sketchbook_2019/sketchbook_<IP_ADDRESS>_win64.exe
Status Code: 200
(Automated message - build 870)

Hi @Exorcism0666,
This manifest has the highest version number for this package. Is it available from another location? (This might be in error if the version is switching from semantic to string, or string to semantic.)
(Automated response - build 870.)

URL: https://download.autodesk.com/us/support/files/sketchbook/sketchbook_2019/sketchbook_<IP_ADDRESS>_win64.exe
Response status code does not indicate success: 404 (Not Found).
(Automated message - build 870)

URL: https://download.autodesk.com/us/support/files/sketchbook/sketchbook_2019/sketchbook_<IP_ADDRESS>_win64.exe
Status Code: 200
(Automated message - build 870)

URL: https://download.autodesk.com/us/support/files/sketchbook/sketchbook_2019/sketchbook_<IP_ADDRESS>_win64.exe
Status Code: 200
(Automated message - build 871)

URL: https://download.autodesk.com/us/support/files/sketchbook/sketchbook_2019/sketchbook_<IP_ADDRESS>_win64.exe
Status Code: 200
(Automated message - build 876)