symphony-java-api community activity

As part of the FINOS project lifecycle work happening with the Symphony PMC, this project has been given an INCUBATING status.
So an informed decision is made by the Symphony PMC whether to ACTIVATE this project, can active contributors to this repository register themselves with a 👍 to best inform the Symphony PMC.
Thank you.

@jonfreedman - Thank you for demonstrating community activity on this repo. I am now making contact with the Symphony PMC to suggest this project is given an ACTIVE status rather than INCUBATING or ARCHIVED.
I will update this thread accordingly.
James.

@jonfreedman - Based on the activation evidence provided on symphony-java-client/issues/136 I have raised a PR to set this project to ACTIVE and will notify the Symphony PMC accordingly.
Kind regards.
James.


detailAction method in UserController.

Creation of detailAction() method in UserController.

1hour

Creation of detail method in UserController is terminated.


Improve docs for enable-version-pinning config constraint

I observed this on a cloud with enable-version-pinning set to true for octavia-ovn-chassis and ovn-chassis.  COU plan/upgrade emits this error output:
Cannot generate plan for 'octavia-ovn-chassis'
        Cannot upgrade 'octavia-ovn-chassis'. 'enable-version-pinning' must be set to 'false'.
Cannot generate plan for 'ovn-chassis'
        Cannot upgrade 'ovn-chassis'. 'enable-version-pinning' must be set to 'false'.

I couldn't find the reason why it must be set to false, and I couldn't find any recommendation for what to do now (is it safe to set the config to false on a production cloud?).
We should improve the docs here.

An idea is to implement a cou lint command to check the environment and print out detail information.


Doesn't update if the page is already scrolled onload

By default, Google Chrome remembers your scrolling position when you reload the page. When using this plugin to create a fixed navbar, this causes some issues: the page loads at a point where the navbar should be visible, but it isn't.
Is there a way around this? Thanks.

You can do something like this:
$("#nav-"+section).addClass("focus").nextAll().removeClass("visited");
$("#nav-"+section).addClass("focus").prevAll().addClass("visited");

@sodle You maybe want to show your code.


Return {ok, result} tuple from NVS function

Functions such as: esp:nvs_get_binary/2 return either a binary or undefined atom.
The API might be improved to return instead {ok, result} | error rather than just the result.
In order to avoid compatibility issues, as alternative to a  return type change, esp:nvs_fetch_binary/2 function might be implemented and the previous might be just deprecated, while the new might return the new result type.

Personally I would prefer we make a breaking change here and retain the current nvs_get_binary and nvs_set_binary function names. If we are going to replace them with the changed functions maybe both should be renamed, so that their names imply the same semantic relationship, like nvs_write_binary and nvs_read_binary.

I don't mind keeping the function name as-is.
Anyway as an additional input, there is an interesting convention in Elixir:

fetch() returns either {ok, result} or error
get() returns either a valid result or a nil atom (that is same as undefined)

One more question:
Right now we are doing:
 70             fprintf(stderr, "Unable to open NVS. namespace '%s' err=%i\n", namespace, err);
 71             RAISE_ERROR(term_from_int(err));

Should we keep raising errors for unexpected internal errors? Which ones should be critical and raise error?
Therefore should we prefer returning {error, error_reason} rather just error?

I think {error, error_reason} is always preferable, it makes the error more obvious, and allows the user to handle different error conditions programmatically.

I don't mind keeping the function name as-is. Anyway as an additional input, there is an interesting convention in Elixir:
* fetch() returns either `{ok, result}` or error

* get() returns either a valid result or a nil atom (that is same as undefined)

Actually that sounds like a very interesting alternative. An argument could be made that returning an error might be overly presumptive anyway, returning undefined might be more useful. But having the fetch option could give the best of both. I assume fetch would also return {error, Reason} in the case of an actual error and just error in the case of and undefined entry?

Fixed with #741


Wrong Windows release files linked for 0.9.15!?

When I go to https://github.com/carla-simulator/carla/releases/tag/0.9.15 and want to download the Windows version the 0.9.14 is linked instead of 0.9.15

It seems that the text is correct, but 3 of 4 links point to the old version - Why did no one notice this?

[Ubuntu] [CARLA_0.9.15.tar.gz] (https://carla-releases.s3.us-east-005.backblazeb2.com/Linux/CARLA_0.9.15.tar.gz) -> correct
[Ubuntu] [AdditionalMaps_0.9.15.tar.gz] (https://carla-releases.s3.us-east-005.backblazeb2.com/Linux/AdditionalMaps_0.9.14.tar.gz) -> wrong
[Windows] [CARLA_0.9.15.zip] (https://carla-releases.s3.us-east-005.backblazeb2.com/Windows/CARLA_0.9.14.zip) ->wrong
[Windows] [AdditionalMaps_0.9.15.zip] (https://carla-releases.s3.us-east-005.backblazeb2.com/Windows/AdditionalMaps_0.9.14.zip) -> wrong

BWT - just modifying the link works

https://carla-releases.s3.us-east-005.backblazeb2.com/Windows/CARLA_0.9.15.zip
https://carla-releases.s3.us-east-005.backblazeb2.com/Windows/AdditionalMaps_0.9.15.zip

We fixed this issue.
Thank you for letting us know.


WLS on Windows 10 and Ubuntu 18.04 azure-cli package not found

Describe the bug
Azure Cli on 18.04 WLS Windows 10 won't install
To Reproduce
Install 18.04 from Windows 10 Store
Update and upgrade 18.04
sudo apt-get update && sudo apt-get install azure-cli
Output
Get:1 http://security.ubuntu.com/ubuntu bionic-security InRelease [83.2 kB]
Hit:2 http://archive.ubuntu.com/ubuntu bionic InRelease
Get:3 http://archive.ubuntu.com/ubuntu bionic-updates InRelease [83.2 kB]
Hit:4 http://archive.ubuntu.com/ubuntu bionic-backports InRelease
Get:5 http://security.ubuntu.com/ubuntu bionic-security/main amd64 Packages [62.5 kB]
Get:6 http://security.ubuntu.com/ubuntu bionic-security/main Translation-en [23.0 kB]
Get:7 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 Packages [80.9 kB]
Get:8 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 Packages [32.4 kB]
Fetched 365 kB in 7s (53.5 kB/s)
Reading package lists... Done
Reading package lists... Done
Building dependency tree
Reading state information... Done
E: Unable to locate package azure-cli
Expected behavior
Azure Cli package should be located.
Environment summary
Followed instructions here: https://docs.microsoft.com/en-us/cli/azure/install-azure-cli-apt?view=azure-cli-latest
Additional context
Add any other context about the problem here.

@rajurs according to the output, the APT didn't visit https://packages.microsoft.com/repos/azure-cli/. Could you double check if the source list is updated correctly?

Closing due to inactivity.

This happens if you are following instructions (https://docs.microsoft.com/en-us/cli/azure/install-azure-cli-apt?view=azure-cli-latest)  but miss a step.
When using the copy button for bash commands on the web page, and pasting it in bash, sometime it is possible that the last command in the group is not executed because an enter wasn't pressed.  In my case, AZ_REPO wasn't set properly.

Note that after setting the AZ_REPO variable as explained by @YasserAsmi, you also have to re-run the sudo apt-get update command before sudo apt-get install azure-cli will resolve the azure-cli package location.


First draft of new internal cluster with helm charts for timelord and…

… harvester.
It's been tested using temp URLS on prod letsencrypt issuer and seems to behaving as expected.
What does this PR do?
Adds helm charts for our current internal apps
Adds Terraform to spawn a bare-minimum cluster in GKE (currently on my test-project)
Documentation to come...
Where should the reviewer start?
Going through all changes and verifying logic / structure
Optimizations are always welcome
How should this be manually tested?
Currently you can visit: https://oliver-the-timelord.reload.dk to test functionality of timelord and that harvester is continuesly updating data.
If you wish to play around with terraform / helm yourself, you can:

Authenticate to GKE via an account or service account who is able to perform changes to the project
Adjust values in terraform.tfvars if you wish to proceed with another project
Intitialise Terraform from the root using: terraform -chdir=./terraform/internal-utils-alpha init or cd'ing into the terraform dir first.
Configure kubectl: gcloud container clusters get-credentials $(terraform -chdir=./terraform/internal-utils-alpha output -raw kubernetes_cluster_name) --region $(terraform -chdir=./terraform/internal-utils-alpha output -raw zone)

Any background context you want to provide?
I've used the following parameters with helm to install/upgrade stuff within the cluster:
helm upgrade timelord ./helm-charts/timelord \
  --atomic \
  --cleanup-on-fail \
  --install \
  --namespace timelord \
  --create-namespace \
  --set timelord.secret=ProdTimelordSecretHere #GoFetch

Can you prepare a PR in https://github.com/reload/infrastructure as well?


Adds validation to add_static_group_members.

A new, optional validate parameter is added to the add_static_group_members method with a default value of False. When set to True, the method will compare the list of members added with the response received from Turbonomic to validate that all members were added successfully. If any were not added, which is what happens if the UUID is invalid, the changes are rolled back and a new error type of VMTGroupValidationError is raised.
Validation is skipped if both the members to add is an empty list and the group itself is currently empty. While shouldn't happen since there would be no point, if it did then a KeyError would be raised since the response will not have a memberUuidList key.

Rebased with the changes discussed to improve readability.


ENH: default cond parameter of linalg.lstsq

This commit changes the default cond to be consistent with the default rcond in numpy and torch.
According to this thread, for most practical purposes, the cond parameter for lstsq should be set to EPS * max(M, N), where EPS is the machine precision of A's dtype and A has shape (M, N).
This is the default behavior in numpy.linalg.lstsq and torch.linalg.lstsq.
According to the StackOverflow thread linked above, the cond parameter in scipy used to be set optimally by default, but looking at the current code, I don't think that's the case now.

Reference issue

What does this implement/fix?

Additional information

Here is a script that shows the conditions under which scipy.linalg.lstsq doesn't match numpy.linalg.lstsq and torch.linalg.lstsq. For some reason, the discrepancies only show up when my input matrices are centered (which, for example, is the default in sklearn.linear_model.LinearRegression when an intercept is fit).
Once the cond is set manually to the optimal (used by numpy and torch), there are no more discrepancies.
The script

Python 3.10
dependencies: numpy, pandas, scipy, torch, tqdm

import os
import pickle
from pathlib import Path

from tqdm.contrib.itertools import product
import numpy as np
import pandas as pd
import scipy.linalg as spla
import torch

def test_consistency(
    n_samples: int = 10,
    n_features: int = 100,
    n_targets: int = 1,
    center: bool = True,
    rcond: str = "optimal",
    driver_scipy: str = "gelsd",
    driver_torch: str = "gelsd",
    threading: str = "single",
) -> tuple[bool, bool, bool]:

    rng = np.random.default_rng(seed=0)

    x = rng.normal(size=(n_samples, n_features))
    beta = rng.normal(size=(n_features, n_targets))
    epsilon = 0.05 * rng.normal(size=(n_samples, n_targets))
    y = x @ beta + epsilon

    if center:
        x_mean = x.mean(axis=-2, keepdims=True)
        x = x - x_mean
        y_mean = y.mean(axis=-2, keepdims=True)
        y = y - y_mean

    if threading == "single":
        os.environ["OMP_NUM_THREADS"] = "1"
        os.environ["MKL_NUM_THREADS"] = "1"
    else:
        os.environ.pop("OMP_NUM_THREADS", None)
        os.environ.pop("MKL_NUM_THREADS", None)

    if rcond == "optimal":
        # https://numpy.org/doc/stable/reference/generated/numpy.linalg.lstsq.html
        # https://stackoverflow.com/a/44678023
        rcond = torch.finfo(torch.from_numpy(x).dtype).eps * max(x.shape[-2:])
    else:
        rcond = torch.finfo(torch.from_numpy(x).dtype).eps

    coef_scipy, _, _, _ = spla.lstsq(x, y, cond=rcond, lapack_driver=driver_scipy)
    coef_numpy, _, _, _ = np.linalg.lstsq(x, y, rcond=rcond)
    coef_torch, _, _, _ = torch.linalg.lstsq(
        torch.from_numpy(x), torch.from_numpy(y), rcond=rcond, driver=driver_torch
    )

    os.environ.pop("OMP_NUM_THREADS", None)
    os.environ.pop("MKL_NUM_THREADS", None)

    return (
        np.allclose(coef_numpy, coef_scipy),
        np.allclose(coef_torch, coef_numpy),
        np.allclose(coef_scipy, coef_torch),
    )

def main() -> pd.DataFrame:
    path_results = Path("lstsq_test.pkl")

    if path_results.exists():
        with open(path_results, "rb") as f:
            results = pickle.load(f)
            return results

    n_samples = [5, 10, 50, 1000]
    n_features = [1, 10, 100, 300, 1000]
    n_targets = [1, 5]
    center = [True, False]
    rcond = ["optimal", "machine precision"]
    driver_scipy = ["gelsd", "gelss", "gelsy"]
    driver_torch = ["gels", "gelsd", "gelss", "gelsy"]
    threading = ["single", "multi"]

    results = []

    for product_ in product(
        n_samples,
        n_features,
        n_targets,
        center,
        rcond,
        driver_scipy,
        driver_torch,
        threading,
    ):
        (
            n_samples_,
            n_features_,
            n_targets_,
            center_,
            rcond_,
            driver_scipy_,
            driver_torch_,
            threading_,
        ) = product_

        numpy_scipy, torch_numpy, scipy_torch = test_consistency(
            n_samples=n_samples_,
            n_features=n_features_,
            n_targets=n_targets_,
            center=center_,
            rcond=rcond_,
            driver_scipy=driver_scipy_,
            driver_torch=driver_torch_,
            threading=threading_,
        )

        results.append((*product_, numpy_scipy, torch_numpy, scipy_torch))

    results = pd.DataFrame(
        results,
        columns=[
            "n_samples",
            "n_features",
            "n_targets",
            "center",
            "rcond",
            "driver_scipy",
            "driver_torch",
            "threading",
            "numpy-scipy",
            "torch-numpy",
            "scipy-torch",
        ],
    )

    with open(path_results, "wb") as f:
        pickle.dump(results, f)
    return results

def _wrap_parameters(parameters: list[tuple[int | str | bool, ...]]) -> pd.DataFrame:
    return pd.DataFrame(
        parameters,
        columns=[
            "center",
            "rcond",
            "driver_scipy",
            "driver_torch",
            "threading",
        ],
    )

if __name__ == "__main__":
    results = main()
    parameters = {"valid": [], "invalid": []}
    for group in results.groupby(
        ["center", "rcond", "driver_scipy", "driver_torch", "threading"]
    ):
        _parameters, subset = group
        if subset.loc[:, ["numpy-scipy", "torch-numpy", "scipy-torch"]].all().all():
            parameters["valid"].append(_parameters)
        else:
            parameters["invalid"].append(_parameters)

    for key in parameters.keys():
        parameters[key] = _wrap_parameters(parameters[key])

A link to the discussion on PyTorch's choice of rcond: https://github.com/pytorch/pytorch/pull/49093#discussion_r574466884_

That's really strange, I thought I fixed this in an earlier version but somehow missed it apparently. Let's see if CI returns green

I've added the recommended test to the class TestLstsq.

Not sure if I should be doing anything else, please let me know if so!

@ilayn any further thoughts on this one? it went missing from the milestone when the head repo was deleted.


Multiple clients

Hi there,
Is it possible to have multiple clients operate the same jrpc server ?
I get a situation where I can connect multiple clients and execute rpc for both clients, however only the most recently connected client will get a message returned.
The oldest client prints out :
{code: -1000, message: "Timed out waiting for response"}
thanks
Matt

Oh - Worked out that you need to setup each remote independently.


Access - rename and update

:x: Validation status: errors

File
Status
Preview URL
Details

:x:Error

Details

[Error] Cannot sync git repo to specified state. Please make sure the pull request is mergeable. Details: Git merge results in conflict, repository remote url: https://github.com/MicrosoftDocs/VBA-Docs, working directory: W:\wope-s, target branch: master, target branch commit: 2f3bf7468570ed2e0f05bfb647734ca8457b4309, source branch: AccessUpdating, source branch commit: .

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


Feature/implement stake feature

Summary

Implement the delegate feature

Tested cases

Cases A: Account doesn't have any delegations

Delegate the valid amount
Delegate the insufficient amount => display error

Case B: Account has existing delegations

Delegate the valid amount to new validator
Delegate the valid amount to the delegated validator

Things to do next

Undelegate

hi @djhahe , I have fixed the table width issue.

hi @djhahe , plz help me to re-review again. There are some changes:

[ ]  Implement the separated forms for delegate and undelegate actions

[ ] Revamp the delegations table and implement the Undelegate button

[ ] Handle the bug when user enters the staked amount which has more than 9 decimal places


Slider doesn't reach max value when not divisible by step

Environment
System:     OS: macOS Mojave 10.14.6     CPU: (16) x64 Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz     Memory: 27.24 MB / 32.00 GB     Shell: 3.2.57 - /bin/bash   Binaries:     Node: 12.14.1 - ~/.nvm/versions/node/v12.14.1/bin/node     Yarn: 1.16.0 - /usr/local/bin/yarn     npm: 6.13.4 - ~/.nvm/versions/node/v12.14.1/bin/npm     Watchman: 4.9.0 - /usr/local/bin/watchman   SDKs:     iOS SDK:       Platforms: iOS 13.2, DriverKit 19.0, macOS 10.15, tvOS 13.2, watchOS 6.1     Android SDK:       API Levels: 23, 24, 25, 26, 27, 28       Build Tools: 23.0.1, 23.0.3, 24.0.1, 25.0.1, 25.0.2, 25.0.3, 26.0.1, 26.0.3, 27.0.3, 28.0.3       System Images: android-26 | Google APIs Intel x86 Atom_64, android-27 | Google APIs Intel x86 Atom   IDEs:     Android Studio: 3.1 AI-173.4697961     Xcode: 11.3.1/11C504 - /usr/bin/xcodebuild   npmPackages:     react: 16.9.0 => 16.9.0      react-native: 0.61.5 => 0.61.5
Description
When the max value is not divisible by the step, the slider stops at the last step before max and can't reach the max value. Below is an example of the props being passed as well as values that trigger this case.
Reproducible Demo
	<Slider 		value={ 10000 } 		step={ 10000 } 		minimumValue={ 10000 } 		maximumValue={ 104200 } 	/>

I'm having the same issue

I'm having the same issue

+1

I have the same issue
+1

+1

Any news on this?

@DavitVosk As you can see I've created a Project for this library, so every user can track the progress of every issue.
As for this one: yes, I got it planned but I need to figure out the API of the solution first, then I'll start a development of that.


fix: Update hooks.md to fix custom equality function example

Custom equality function documentation mixes up the new and previous value variables in the example code.
See logs in this code sandbox example: https://codesandbox.io/s/redux-useselector-usedispatch-sample-forked-zhfnx5?file=/src/Counter.js
You can also see the screenshot below following the example naming in the documentation. The logged result is after incrementing the count.

Huh. That's... extremely odd.
We rely on the use-sync-external-store/withSelector package for this, and it sure looks like it's (prev, current) the couple places I see it called:

https://github.com/facebook/react/blob/v18.2.0/packages/use-sync-external-store/src/useSyncExternalStoreWithSelector.js#L59-L85

Huh. That's... extremely odd.
We rely on the use-sync-external-store/withSelector package for this, and it sure looks like it's (prev, current) the couple places I see it called:

https://github.com/facebook/react/blob/v18.2.0/packages/use-sync-external-store/src/useSyncExternalStoreWithSelector.js#L59-L85

Interesting, are they not possibly making the same error?

@markerikson Further playing around with code sandbox it looks like these values read correctly in ^8.0.0.
Apologies, I guess I just need to update my react-redux dependency

FWIW, it looks like we did indeed do (new, old) in v7!
https://github.com/reduxjs/react-redux/blob/7.x/src/hooks/useSelector.js#L40


Error on build

Hello, when i build the line-number branch i've this error. It's the first time i have this. I'll try using python 2.7 and python 3 but same issue.
Traceback (most recent call last):
  File "tools/build.py", line 304, in <module>
    build(buildfunc, root, args)
  File "tools/build.py", line 282, in build
    buildfunc(root, build_path, filenames, args)
  File "tools/build.py", line 213, in build_browser
    content = compress_content(tools_path, content)
  File "tools/build.py", line 110, in compress_content
    p = subprocess.Popen(args, stdin=subprocess.PIPE, stdout=subprocess.PIPE)
  File "/usr/lib/python2.7/subprocess.py", line 710, in __init__
    errread, errwrite)
  File "/usr/lib/python2.7/subprocess.py", line 1335, in _execute_child
    raise child_exception
OSError: [Errno 2] No such file or directory

Maybe my python install or the build.py file error. I don't know.

We've switched from Python over to node.js a long time ago… Please update the code to the latest version and use the new building tool.


Test depends on CET timezone

In test_compilers.py, there are two assertions which test translating UNIX timestamp to date. This works just fine in CET timezone but fails in different timezones.
https://github.com/honzamach/pynspect/blob/b827fb4d07e40446afb2e93b3c00d03eb50a8b17/pynspect/tests/test_compilers.py#L126-L129
and
https://github.com/honzamach/pynspect/blob/b827fb4d07e40446afb2e93b3c00d03eb50a8b17/pynspect/tests/test_compilers.py#L154-L157

Seems to me that solution could be as simple as something akin to:
stamp =<PHONE_NUMBER>
self.assertEqual(
     repr(compile_timeoper(ConstantRule(str(stamp)))),
     "DATETIME({0!r})".format(datetime.datetime.fromtimestamp(stamp))
 )


add new mass constants to init.py

This should allow the mass constants to be automatically available from an import.

That worked, thank you!


As a customer/visitor, I want to be able to "checkout" the items in my cart so I can purchase my desired goods

Think of a typical user experience on popular websites from a guest user and logged-in user perspective.
You can just start with by simulating the experience of checking out with a simple confirmation page.
Frontend Tasks:

Add a "Checkout" button to the cart page that will direct the user to the checkout experience
Create a "Checkout" React component that will:

List the products in the users cart as well as individual totals (i.e. 3 bottles of whiskey/1 bottle of whiskey and prices for each)
List the total cost of the cart
Includes a dummy payment/billing form section
A button that will 'submit' the order, i.e. clears the users cart and then directs them to an order confirmation page

Update redux store w/ action type, creator, thunk, and reducer to clear out users cart once order is submitted

Backend Tasks:

Create PUT route that removes items from cart table associated with current user

I spent some time thinking about this, I think the approach for user vs. guest checkout will rely on local storage + our Cart table in the db.
I'm thinking whenever a user (whether they're logged in or not) adds an item to the cart we save said cart to sessionStorage as well as the database. Then, when the user proceeds to cart page we can do a conditional type thing ala:
if(user is logged in){
retrieve cart from db using user id and load info that way
} else {
retrieve cart from sessionStorage
}
Still working out the finer details, but i think this will allow us to do a guest + logged in user checkout (allowing users to access cart from wherever, but guest sessions tethered to a browser instance).

2 Notes based on findings today:

Dev had the right idea in using localStorage over sessionStorage- localStorage persists even after the browser closes and the implementation should be similar.
If a user is signed in their auth is saved to localStorage- this can be useful in determining if the cart should be loaded from localStorage vs. database.


Install script should have executable bit set

We should run chmod +x on that file so it's possible to directly execute it.

No longer relevant.


Cant connect to websocket using node ws

var WebSocket = require('ws');

process.env.NODE_TLS_REJECT_UNAUTHORIZED = '0';

var ws = new WebSocket('wss://databox.me/');

ws.on('open', function open() {
  console.log('connected');
  ws.send('ping');
});

ws.on('close', function close() {
  console.log('disconnected');
});

ws.on('message', function message(data, flags) {
  console.log(data);
});

Gives
node test.js

events.js:72
        throw er; // Unhandled 'error' event
              ^
Error: unexpected server response (403)
    at ClientRequest.response (/var/www/ld/test/node_modules/ws/lib/WebSocket.js:674:15)
    at ClientRequest.g (events.js:180:16)
    at ClientRequest.EventEmitter.emit (events.js:95:17)
    at HTTPParser.parserOnIncomingClient [as onIncoming] (http.js:1688:21)
    at HTTPParser.parserOnHeadersComplete [as onHeadersComplete] (http.js:121:23)
    at CleartextStream.socketOnData [as ondata] (http.js:1583:20)
    at CleartextStream.read [as _read] (tls.js:511:12)
    at CleartextStream.Readable.read (_stream_readable.js:320:10)
    at EncryptedStream.write [as _write] (tls.js:366:25)
    at doWrite (_stream_writable.js:223:10)

Same issue on localhost.  I suspect this could be an issue with the node ws module.  Will investigate further.

Seems to work with older versions of ws (npm).  This may be a lead on other websocket related issues such as friefox.
I drilled into the https request and options but could not see anything obvious in the handshake that caused a 403.
I'll close this issue for now, and raise on project specific instances such as GOLD if it persists.


bugfix/welcome-notification-created-from-changelog-cannot-be-deleted

The bug, welcome notification created from the demo changelog cannot be deleted, was fixed.
@svetivanova could you please review the changes?

Codecov Report

Merging #106 into master will increase coverage by 0.33%.
The diff coverage is 100%.

@@             Coverage Diff              @@
##             master     #106      +/-   ##
============================================
+ Coverage     83.02%   83.35%   +0.33%
- Complexity      699      716      +17
============================================
  Files           172      172
  Lines          2933     2992      +59
  Branches        118      119       +1
============================================
+ Hits           2435     2494      +59
  Misses          425      425
  Partials         73       73

Impacted Files
Coverage Δ
Complexity Δ

...ication/command/NotificationCommandController.java
100% <100%> (ø)
6 <0> (ø)
:arrow_down:

...m/tsmms/skoop/user/command/UserCommandService.java
100% <0%> (ø)
25% <0%> (+15%)
:arrow_up:

.../user/command/UserPermissionCommandController.java
100% <0%> (ø)
5% <0%> (+2%)
:arrow_up:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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Codecov Report

Merging #106 into master will increase coverage by 0.33%.
The diff coverage is 100%.

@@             Coverage Diff              @@
##             master     #106      +/-   ##
============================================
+ Coverage     83.02%   83.35%   +0.33%
- Complexity      699      716      +17
============================================
  Files           172      172
  Lines          2933     2992      +59
  Branches        118      119       +1
============================================
+ Hits           2435     2494      +59
  Misses          425      425
  Partials         73       73

Impacted Files
Coverage Δ
Complexity Δ

...ication/command/NotificationCommandController.java
100% <100%> (ø)
6 <0> (ø)
:arrow_down:

...m/tsmms/skoop/user/command/UserCommandService.java
100% <0%> (ø)
25% <0%> (+15%)
:arrow_up:

.../user/command/UserPermissionCommandController.java
100% <0%> (ø)
5% <0%> (+2%)
:arrow_up:

Continue to review full report at Codecov.

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Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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Fix to get all files value for multipart

Fixes # .
Changes proposed in this pull request:

get all values from files by using files.lists()

Thanks @chenguangqi!
Could you update the tests so they take into account the change?

Hi @chenguangqi, did you have a chance to have another look at this? Let me know if you need support.

It's hard to setup test enviroments(3.7, 3.8, 3,9, 3.10) by network question.

Should be fixed, see tests added in https://github.com/spec-first/connexion/pull/1642


Vault is not created

I was able to guess how to generate the initial config files thanks to the help on the commands and start the bm-server.
However I failed at creating a new account because the vault was not found. I checked the code and it seems that the initial creation of the vault is never called.
        // Save new vault when we cannot find one
        if _, ok := err.(*os.PathError); ok {  // <== IT SEEMS THIS IS ALWAYS FALSE
                err = os.MkdirAll(filepath.Dir(p), 0777)
                fmt.Println(err)
                if err != nil {
                        return nil, err
                }
                fmt.Println("Saving")
                err = v.Save()
                return v, err
        }

I modified those lines to force the creation of the vault and I found this error when creating a new account:
* Verifying if address is correct: ok
* Checking if address is already known in the resolver service: not found. This is a good thing.
* Checking if the account is already present in the vault: not found. This is a good thing.
* Generating your secret key to send and read mail: done.
* Doing some work to let people know this is not a fake account: done.
* Adding your new account into the vault: done
* Sending your account information to the server: TRAC[0004] %!s(<nil>)

TRAC[0004] Request POST https://localhost:2424/account
TRAC[0004] HEADER: Content-Type : [application/json]
TRAC[0004] HEADER: Authorization : [Bearer eyJhbGciOiJSUzI1NiIsInR5cCI6IkpXVCJ9.eyJleHAiOjE2MDAyNjQxMTgsImlhdCI6MTYwMDI2MDUxOCwibmJmIjoxNjAwMjYwNTE4LCJzdWIiOiJiY2M2YzgwOTRkMTdkYzdhM2NmNjZmZjFmZmFlMmE0Y2NhYTczZDg3OGVhMTEyZmZhNDEzZTNlZWE3YTAwYWQ3In0.cn1UWoI3TDvoBzRnMXZuGLd8ABWnNOXQlo9_QgPammIhQ5A3mA5iytDlB3XEL8U7BEq2NmyEMYPhUtWJQXZ73RCeAquhWWQdCPOPDcYjVrGhpdMAaFP0C0ij5RU7J7UCBXfY-gPjloPPE20RhAST0jgMygiJew0sQwvcGtIp3aeIh8fSaa9ahGWLLA2ChZD9ggtAGHQVYuoO9zgTdESZIyA1cSyUko5Zk_fVBEPXRsxerVb7UK6rvRUpZXDylpuBhdGkA5lpflr-WlMCX8NHTK7x4F_GHb0Lx_j0190uhM9p8hFhLwiwTHCtmsDQ6DLmQbH22FQxj7rJVTYw0R4vOw]
TRAC[0004] {"address":"bcc6c8094d17dc7a3cf66ff1ffae2a4ccaa73d878ea112ffa413e3eea7a00ad7","token":"40QuLWSNpjIprRSlW8aMZAF+5R9RCp6PkfalCabQIgQ=","public_key":"rsa MIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAu8P9zc3EkMgyt3kigluujzF9CSd+WFakVULMlsxpibLZ+mJBWANGw+0OStlMdExGHVEFYRcFZkP0baIJlwkwOXh47/09ER/gFzTdqUfTnnVY84Nv0M23ZUEFx+6B9XzgtanocgS3+z6be2h+Wv4PiM6ddNv5tg7BHU0MEgj3ZGd3ysKIIBSLLaq5yM9VNRxOQ+fsufhKjFIVzn7ia792HLNYThNEm2ezuqG7LyawN1ywoq5zMSTSwwJgSpxMJCVRagUc6cctCS75wOU4akwY57k0Br/qUpe9zbRWCmbgo/bifGiNazWgSBttFV4tAyMZu6f0rqMHvgMbY8B3g2gDKwIDAQAB","proof_of_work":"22$YmNjNmM4MDk0ZDE3ZGM3YTNjZjY2ZmYxZmZhZTJhNGNjYWE3M2Q4NzhlYTExMmZmYTQxM2UzZWVhN2EwMGFkNw==$1578404"}
2020/09/16 12:48:38 http: TLS handshake error from <IP_ADDRESS>:49926: remote error: tls: bad certificate
TRAC[0004] x509: certificate relies on legacy Common Name field, use SANs or temporarily enable Common Name matching with GODEBUG=x509ignoreCN=0
TRAC[0004]

  X error from API while trying to create account: Post "https://localhost:2424/account": x509: certificate relies on legacy Common Name field, use SANs or temporarily enable Common Name matching with GODEBUG=x509ignoreCN=0

Hi, Thanks for your interest in the project :) :+1
It seems that the vault isn't automatically created. This should be a simple enough fix.
There is a configuration option that allows unsigned certificates on TLS connections: it's server.allow_insecure found in your (client)-configuration.
Btw, i've also setup gitter.im/bitmaelum for a little more responsive support channel for now if you're interested.

solved in master


Automated cherry pick of #10568: fix: avoid listener worker leak

Cherry pick of #10568 on release/3.6.
#10568: fix: avoid listener worker leak

/lgtm

/approve

/approve


Tell template app .flowconfig to look for .native.js files

Motivation
metro-bundler looks for .native.js files (see here). Packages such as react-navigation rely on this functionality (see here). This PR makes it so you can react-native init, yarn add react-navigation, and flow successfully!
Test Plan

react-native init
yarn add react-navigation
flow

Release Notes
[CLI] [MINOR] [Flow] - Tell template app .flowconfig to look for .native.js files

@gabelevi, any chance you could look at this? It's a small change to react-native init's .flowconfig template file, and it's necessary for React Navigation's flow config to work.

@calebmer, could I trouble you to look at this? It's a small change to react-native init's .flowconfig template file, and it's necessary for React Navigation's flow config to work.


Add Slat service to an air conditiner or fan

Hello everyone, I was trying to add a SLAT to a Heater_Cooler or a FAN, I should see the swing mode but I can't see it.
Does anyone have an example of the utilisation os SLAT service?

Are you still planning to share your code?

Yes sorry, I didn’t have the pc with me till today, I went through a surgery last week. I will share it in a few hours.

HOMEKIT_ACCESSORY(.id=3, .category=homekit_accessory_category_fan, .services=(homekit_service_t*[]){
    HOMEKIT_SERVICE(ACCESSORY_INFORMATION, .characteristics=(homekit_characteristic_t*[]){
        HOMEKIT_CHARACTERISTIC(NAME, "FAN"),
        HOMEKIT_CHARACTERISTIC(MANUFACTURER, "YP"),
        HOMEKIT_CHARACTERISTIC(SERIAL_NUMBER, "0012347"),
        HOMEKIT_CHARACTERISTIC(MODEL, "FAN"),
        HOMEKIT_CHARACTERISTIC(FIRMWARE_REVISION, "0.1"),
		HOMEKIT_CHARACTERISTIC(IDENTIFY, light_sensor_identify),
        NULL
    }),
    HOMEKIT_SERVICE(FAN2, .characteristics=(homekit_characteristic_t*[]) {
        HOMEKIT_CHARACTERISTIC(NAME, "Fan2"),
        &fan_active,
        &fan_rotation_speed,
        &fan_swing_mode,
        //&slat_type,
		//&current_slat_state,
        //&swing_mode,
        NULL

    }),
     HOMEKIT_SERVICE(SLAT, .characteristics=(homekit_characteristic_t*[]) {
        HOMEKIT_CHARACTERISTIC(NAME, "Slats"),
        &slat_type,
		&current_slat_state,
        &swing_mode,
        NULL
    }),
     NULL
}),

Can you also provide definitions of all characteristics used in there

homekit_characteristic_t temperature = HOMEKIT_CHARACTERISTIC_(CURRENT_TEMPERATURE, 0);
homekit_characteristic_t humidity    = HOMEKIT_CHARACTERISTIC_(CURRENT_RELATIVE_HUMIDITY, 0);
//homekit_characteristic_t target_temperature  = HOMEKIT_CHARACTERISTIC_(TARGET_TEMPERATURE, 22, .callback=HOMEKIT_CHARACTERISTIC_CALLBACK(on_temp_update));
//AC Required Parameters
homekit_characteristic_t active = HOMEKIT_CHARACTERISTIC_(ACTIVE, 0,.callback=HOMEKIT_CHARACTERISTIC_CALLBACK(on_active_change));
homekit_characteristic_t current_temperature = HOMEKIT_CHARACTERISTIC_(CURRENT_TEMPERATURE, 0);
homekit_characteristic_t current_heater_cooler_state = HOMEKIT_CHARACTERISTIC_(CURRENT_HEATER_COOLER_STATE, 0);
homekit_characteristic_t target_heater_cooler_state = HOMEKIT_CHARACTERISTIC_(TARGET_HEATER_COOLER_STATE, 0, .callback=HOMEKIT_CHARACTERISTIC_CALLBACK(on_update));
//optionals
homekit_characteristic_t units = HOMEKIT_CHARACTERISTIC_(TEMPERATURE_DISPLAY_UNITS, 0);
homekit_characteristic_t cooling_threshold = HOMEKIT_CHARACTERISTIC_(COOLING_THRESHOLD_TEMPERATURE, 18,.callback=HOMEKIT_CHARACTERISTIC_CALLBACK(on_temp_update),.min_value = (float[]) {17},.max_value = (float[]) {30},.min_step = (float[]) {1} );
homekit_characteristic_t heating_threshold = HOMEKIT_CHARACTERISTIC_(HEATING_THRESHOLD_TEMPERATURE, 22,.callback=HOMEKIT_CHARACTERISTIC_CALLBACK(on_temp_update),.min_value = (float[]) {17},.max_value = (float[]) {30},.min_step = (float[]) {1});
homekit_characteristic_t rotation_speed = HOMEKIT_CHARACTERISTIC_(ROTATION_SPEED, 0, .callback=HOMEKIT_CHARACTERISTIC_CALLBACK(on_update));
homekit_characteristic_t swing_mode = HOMEKIT_CHARACTERISTIC_(SWING_MODE, 0, .callback=HOMEKIT_CHARACTERISTIC_CALLBACK(on_update));
homekit_characteristic_t slat_type = HOMEKIT_CHARACTERISTIC_(SLAT_TYPE, 1, .callback=HOMEKIT_CHARACTERISTIC_CALLBACK(on_update));
homekit_characteristic_t current_slat_state = HOMEKIT_CHARACTERISTIC_(CURRENT_SLAT_STATE, 0, .callback=HOMEKIT_CHARACTERISTIC_CALLBACK(on_update));
homekit_characteristic_t fan_active = HOMEKIT_CHARACTERISTIC_(ACTIVE, 0, .setter=fan_active_set);
homekit_characteristic_t fan_rotation_speed = HOMEKIT_CHARACTERISTIC_(
ROTATION_SPEED, 0,
.min_step = (float[]) {33.3},
.callback=HOMEKIT_CHARACTERISTIC_CALLBACK(on_update)
);
homekit_characteristic_t fan_swing_mode = HOMEKIT_CHARACTERISTIC_(
SWING_MODE, 0,
.callback=HOMEKIT_CHARACTERISTIC_CALLBACK(on_update)
);

Are you using the Home app to check this? Not every service is properly displayed in there.

It looks kind of correct, it might be the problem is somewhere else. Also, it would be nice to set primary service for you accessory (e.g. Fan)

Ok, I tried to create simple Fan & Slat accessory and there seemed to be no Slat seen. So I removed fan and left just a Slat. And what I've found is that it paired OK, but in Home.app it showed as generic accessory with message "This accessory is not currently supported by the Home app.".
I guess, at this point we can close this issue. Left me know if you have more questions.


retroarch-nightly: Add version 2022-02-12

@Calinou checkver doesn't seem to run now with version: nightly, just blank/null response

@Calinou checkver doesn't seem to run now with version: nightly, just blank/null response

Indeed, that's how it's designed to work :slightly_smiling_face:


Some NCCL operations have failed or timed out.

System Info
PyTorch version: 2.2.2+cu121                                                                                Is debug build: False                                                                                CUDA used to build PyTorch: 12.1                                                                                ROCM used to build PyTorch: N/A                                                                                OS: Ubuntu 20.04.6 LTS (x86_64)                                                                                GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0                                                                                Clang version: Could not collect                                                                                CMake version: Could not collect                                                                                Libc version: glibc-2.31                                                                                Python version: 3.8.10 (default, Nov 22 2023, 10:22:35)  [GCC 9.4.0] (64-bit runtime)                                                                                Python platform: Linux-5.4.0-144-generic-x86_64-with-glibc2.29                                                                                Is CUDA available: True                                                                                CUDA runtime version: 12.2.91                                                                                CUDA_MODULE_LOADING set to: LAZY                                                                                GPU models and configuration:                                                                                GPU 0: NVIDIA L40                                                                                GPU 1: NVIDIA L40                                                                                GPU 2: NVIDIA L40                                                                                GPU 3: NVIDIA L40                                                                                GPU 4: NVIDIA L40                                                                                GPU 5: NVIDIA L40                                                                                GPU 6: NVIDIA L40
GPU 7: NVIDIA L40
Nvidia driver version: 535.146.02
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
Versions of relevant libraries:
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.24.4
[pip3] torch==2.2.2
[pip3] torchaudio==2.2.2
[pip3] torchvision==0.17.2
[pip3] triton==2.2.0
[conda] No relevant packages
Information

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

🐛 Describe the bug
I run the following command
torchrun --nnodes 1 --nproc_per_node 8  finetuning.py --enable_fsdp  --model_name ./Meta-Llama-3-8B --use_peft --peft_method lora --dataset alpaca_dataset --save_model --dist_checkpoint_root_folder model_checkpoints --dist_checkpoint_folder fine-tuned --pure_bf16 --output_dir ./SFT
Error logs
The output:
`[rank1]:[E ProcessGroupNCCL.cpp:523] [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=1, OpType=_ALLGATHER_BASE, NumelIn=262669312, NumelOut=1050677248, Timeout(ms)=600000) ran for 600487 milliseconds before timing out. [409/1693][rank2]:[E ProcessGroupNCCL.cpp:523] [Rank 2] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=1, OpType=_ALLGATHER_BASE, NumelIn=262669312, NumelOut=1050677248, Timeout(ms)=600000) ran for 600501 milliseconds before timing out.           [rank0]:[E ProcessGroupNCCL.cpp:523] [Rank 0] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=1, OpType=_ALLGATHER_BASE, NumelIn=262669312, NumelOut=1050677248, Timeout(ms)=600000) ran for 600513 milliseconds before timing out.           [rank3]:[E ProcessGroupNCCL.cpp:523] [Rank 3] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=1, OpType=_ALLGATHER_BASE, NumelIn=262669312, NumelOut=1050677248, Timeout(ms)=600000) ran for 600569 milliseconds before timing out.           [rank1]:[E ProcessGroupNCCL.cpp:537] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.                                                       [rank1]:[E ProcessGroupNCCL.cpp:543] To avoid data inconsistency, we are taking the entire process down.                                                                                [rank1]:[E ProcessGroupNCCL.cpp:1182] [Rank 1] NCCL watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=1, OpType=_ALLGATHER_BASE, NumelIn=262669312, NumelOut=1050677248, Timeout(ms)=600000) ran for 600487 milliseconds before timing out.                                                                                Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:525 (most recent call first):                                                                                frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f7d8bda4d87 in /data/home/jwy/.local/lib/python3.8/site-packages/torch/lib/libc10.so)                                                                                frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1e6 (0x7f7d8cf4c6e6 in /data/home/jwy/.local/lib/python3.8/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::workCleanupLoop() + 0x19d (0x7f7d8cf4fc3d in /data/home/jwy/.local/lib/python3.8/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x119 (0x7f7d8cf50839 in /data/home/jwy/.local/lib/python3.8/site-packages/torch/lib/libtorch_cuda.so)
frame #4:  + 0xd6df4 (0x7f7dd6c60df4 in /lib/x86_64-linux-gnu/libstdc++.so.6)
frame #5:  + 0x8609 (0x7f7dd84dc609 in /lib/x86_64-linux-gnu/libpthread.so.0)
frame #6: clone + 0x43 (0x7f7dd8616353 in /lib/x86_64-linux-gnu/libc.so.6)
terminate called after throwing an instance of 'c10::DistBackendError'
what():  [Rank 1] NCCL watchdog thread terminated with exception: [Rank 1] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=1, OpType=_ALLGATHER_BASE, NumelIn=262669312, NumelOut=1050677248, Timeout(ms)=600000) ran for 600487 milliseconds before timing out.
Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:525 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f7d8bda4d87 in /data/home/jwy/.local/lib/python3.8/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1e6 (0x7f7d8cf4c6e6 in /data/home/jwy/.local/lib/python3.8/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::workCleanupLoop() + 0x19d (0x7f7d8cf4fc3d in /data/home/jwy/.local/lib/python3.8/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x119 (0x7f7d8cf50839 in /data/home/jwy/.local/lib/python3.8/site-packages/torch/lib/libtorch_cuda.so)
frame #4:  + 0xd6df4 (0x7f7dd6c60df4 in /lib/x86_64-linux-gnu/libstdc++.so.6)
frame #5:  + 0x8609 (0x7f7dd84dc609 in /lib/x86_64-linux-gnu/libpthread.so.0)
frame #6: clone + 0x43 (0x7f7dd8616353 in /lib/x86_64-linux-gnu/libc.so.6)
Exception raised from ncclCommWatchdog at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1186 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7f7d8bda4d87 in /data/home/jwy/.local/lib/python3.8/site-packages/torch/lib/libc10.so)
frame #1:  + 0xdf6b11 (0x7f7d8cca6b11 in /data/home/jwy/.local/lib/python3.8/site-packages/torch/lib/libtorch_cuda.so)
frame #2:  + 0xd6df4 (0x7f7dd6c60df4 in /lib/x86_64-linux-gnu/libstdc++.so.6)
frame #3:  + 0x8609 (0x7f7dd84dc609 in /lib/x86_64-linux-gnu/libpthread.so.0)
frame #4: clone + 0x43 (0x7f7dd8616353 in /lib/x86_64-linux-gnu/libc.so.6)`
[rank0]:[E ProcessGroupNCCL.cpp:537] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.                                                       [rank0]:[E ProcessGroupNCCL.cpp:543] To avoid data inconsistency, we are taking the entire process down.                                                                                [rank0]:[E ProcessGroupNCCL.cpp:1182] [Rank 0] NCCL watchdog thread terminated with exception: [Rank 0] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=1, OpType=_ALLGATHER_BASE, NumelIn=262669312, NumelOut=1050677248, Timeout(ms)=600000) ran for 600513 milliseconds before timing out.                                                                                Exception raised from checkTimeout at ../torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:525 (most recent call first):                                                                                frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x57 (0x7fbac97edd87 in /data/home/jwy/.local/lib/python3.8/site-packages/torch/lib/libc10.so)                                                                                frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x1e6 (0x7fbaca9956e6 in /data/home/jwy/.local/lib/python3.8/site-packages/torch/lib/libtorch_cuda.so)                      frame #2: c10d::ProcessGroupNCCL::workCleanupLoop() + 0x19d (0x7fbaca998c3d in /data/home/jwy/.local/lib/python3.8/site-packages/torch/lib/libtorch_cuda.so)                                                                                frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x119 (0x7fbaca999839 in /data/home/jwy/.local/lib/python3.8/site-packages/torch/lib/libtorch_cuda.so)                                                                                frame #4:  + 0xd6df4 (0x7fbb146a9df4 in /lib/x86_64-linux-gnu/libstdc++.so.6)                                                                                frame #5:  + 0x8609 (0x7fbb15f25609 in /lib/x86_64-linux-gnu/libpthread.so.0)                                                                                frame #6: clone + 0x43 (0x7fbb1605f353 in /lib/x86_64-linux-gnu/libc.so.6)
...
Expected behavior
run normally

Hi! I wonder if this error is reproducible? It may be a worker got killed somehow or NCCL connection is disrupted somehow.  We can first check your NCCL config and here are some ways that help you check the correctness of the NCCL configs. (1) Run official NCCL all_reduce_perf. (2) Try Huggingface multi-GPU debug script. (3) If both tests mentioned above passed, then export NCCL_DEBUG=INFO and rerun the distributed training, see if the NCCL communications info gives any error or warning, you can paste back the NCCL info for me to double check.


Fire a "pageview" event from the client controller

Analytics virtual pageviews need path and page title, so fire an event with
those as soon as they're available on client transition.
Note that on frameback navigation the event will fire in the frame.
This closes #502.
Also updated the website's analytics middleware to use the new event.
Next step: Pull the website's analytics middleware out into a dedicated
package and make it public. :rocket:

I don't think we mention adding event listeners to the client controller anywhere in the docs, let alone which events might be emitted.  We should probably do that.

Hmm... yeah, I think this is the first event that's actually worth listening to from the client controller.
A doc on analytics would be good.  Makes sense to ship with the analytics middleware to serve as an example, I think.

Dear future intrepid soul searching for docs on events emitted by React Server,
We emit the following events: render, showFrame, loadComplete, page, navigateDone, pageview.
Good luck,
<3 The React Server Team

adding event listeners to the client controller
...
We emit the following events: render, showFrame, loadComplete, page, navigateDone, pageview.

Only render is emitted by the client controller...?

yeah, that's all of them from everywhere -- frameback controller, navigator, the whole lot

Gotcha.  Yeah, maybe a doc on events in general would be good.
You know... to go along with our thorough API docs. 👹


Setting SAIC_URI in docker-compose.yml

Hi,
I am based in Australia where the iSmart app uses tap-au.soimt.com (as seen in local DNS logs). Whilst the readme doesn't mention an environment variable for setting SAIC_URL I saw that it looks like it is loaded in mqtt_gateway.py and tried it out with the following in my docker-compose.yml:
services:
  saic-mqtt-gateway:
    image: "saicismartapi/saic-python-mqtt-gateway:latest"
    container_name: "saic-mqtt-gateway"
    environment:
      ...
      - SAIC_URI=https://tap-au.soimt.com
      ...

When I started the container it exited with an account not registered error. I saw from the DNS logs that it was trying to use the default tap-eu.soimt.com server.  I ended up cloning the repository, changing the default SAIC_URL in mqtt_gateway.py and building a local docker image and then it worked ok and I was able to see the results in MQTT.
Do you see any reason why the docker-compose.yml environment variable method would not override the default from the code? I've had a look through the code and can't see why SAIC_USER can be set that way but SAIC_URL cannot - I'm still a bit of a Python newbie though.
Thanks
Paul

I took a piece of code from Stack Overflow  for the argument processing.
It combines the argparse command-line options parser with environment variables.
It looks like the environment variables are used only if there is no default value specified. Since the European URI is set as a default, it never used the environment variable. Thanks mate for pointing this out!
I have modified the code so that an environment variable overwrites the predefined default value.

After this fix my HA Addon needs a default value for every environment variable.... Hope it will work now :D

Can you please provide more details about this @Tonno87

I think I got the issue. Before the environment variable was ignored if a default value is present in the code.
Now, the environment variable is taken if defined. Your HA Addon defines alway all the variables, but they might be empty. So, I also need to check whether the environment variable contains a value.

Yes, for example after updating the addon the default mqtt_topic doesn't work anymore, but I got it fixed with default values:
MQTT_URI: "tcp://localhost:1883"
MQTT_USER: ""
MQTT_PASSWORD: ""
MQTT_TOPIC: "saic"
SAIC_USER: null
SAIC_PASSWORD: null
SAIC_URI: "https://tap-eu.soimt.com"
ABRP_API_KEY: ""
ABRP_USER_TOKEN: ""
OPENWB_LP_MAP: ""
LOG_LEVEL: "INFO"

I just tested the new docker image with the SAIC_URI environment variable and it works fine now.
Thanks for fixing this and also for all the work you have done in making this software. It's great to be able to have the cars state of charge in MQTT and Home Assistant.

Now that it has been running for a few days, I noticed that whilst the SAIC_URI environment variable is picked up and used, after the initial update of battery level, I am seeing no more updates until I restart the docker container. It looks like the same issue as #22

Use 0.2.1 until Bugfix:
saicismartapi/saic-python-mqtt-gateway:0.2.1

Yes, that's good when using the tap-eu endpoint but 0.2.1 doesn't let me override SAIC_URI for the tap-au one so I have reverted back to a customized docker container for now.

You are right... Sry 😅


Request & Response sync.Pool usage

Is your feature request related to a problem? Please describe.
High performance gRPC/Connect services need to avoid allocations for request and response messages.
In the gRPC ecosystem, it's possible to pool request messages with plugins like vtprotobuf, but impossible to pool response messages, as you do not control the lifetime of the response object.
Describe the solution you'd like
Ideally pooling is just built into connect-go so that no one has to think about it.
We live in a world of generics now, so this might be possible.
Describe alternatives you've considered
An alternative would be to provide callback/interface that executes when the library needs a request and is finished with a response.

Related https://github.com/planetscale/vtprotobuf/issues/59

Pooling is certainly a nice optimization, but it's error-prone in this context: no matter how we structure connect-go, you'll need to be completely sure that no interceptor has retained a reference to the message or any of its sub-structures. Because pooling errors are so irritating to debug, I've always avoided exposing pooled objects across team boundaries.
I'm hopeful that arenas will be a safer route to improved overall performance.

...but impossible to pool response messages, as you do not control the lifetime of the response object.

Why not use runtime.SetFinalizer? Finalizers are somewhat distasteful and have some sharp edges, but they're a good fit for this use case. You'd still need to ensure that interceptors aren't retaining references to any sub-structures, byte slices, etc., but you wouldn't need any cooperation from the connect-go runtime.


Default config does not slow down close to ground in position mode

Describe problem solved by this pull request
I heared several times that the ground slow down is not something people expect to see by default. Hence I'm proposing to not slow down at all with default parameters.
People that found it confusing I still remember were: @igalloway on slack https://px4.slack.com/archives/C39C4E709/p1588275046070800, @baumanta , @priseborough (today), ...
I brought it up in the dev call before:
https://discuss.px4.io/t/px4-dev-call-may-06-2020/16511
First question under "Multicopter".
Describe your solution
Set the ground slow down speed to the default maximum speed. This results in no change with defaults but a slow down to 10m/s if the maxiumum speed is set higher than that.
Additional context
Original feature pr: https://github.com/PX4/Firmware/pull/13561

This change is important. Having the slowdown feature on by default when not using a range finder  results in:

Pulsing in forward speed as the Baro height drifts up and down.
Inability to fly takeoff on a hill top and fly down into a valley

I recommend that the description for the parameter that sets the maximum horizontal speed when away from the ground be modified to let the user know that horizontal speed is also controlled by MPC_LAND_VEL_XY when close to  home or ground.
I recommend that the description for MPC_LAND_VEL_XY be further modified to make it clear when height above ground is used vs height above home.


Remove legacy msvc compiler modules.

They were marked as deprecated in c802880bfba39d3072599eef2e0f34568f93e6cd, so they shouldn't be in use.

Notwithstanding that these shouldn't be in use, in practice these appear to be used by cffi, and thus this change breaks cffi: https://github.com/python-cffi/cffi/blob/main/src/cffi/_shimmed_dist_utils.py#L33
I'll file a cffi bug about fixing this.

It also broke gnome: https://gitlab.gnome.org/GNOME/gobject-introspection/-/issues/515

broke pygame

broke pygame

If you have a reference to the downstream report, that would be helpful to follow. I looked briefly into the other issues and I don't think there's anything this project should do, though I could consider re-adding some interfaces to restore compatibility for a limited duration, but only if there's a compelling case. In general, I expect users reliant on these older modules to be in a precarious state anyhow.

For pygame the setuptools for windows msvc compilers have been pinned to previous setuptools version. I haven't looked yet on how to update the code which uses the compiler yet. It's here if you're interested: https://github.com/pygame/pygame/blob/main/buildconfig/vstools.py
I know not everyone can pin their packages to previous versions of setuptools. But for anyone that can pin whilst they fix, I wrote instructions here: https://github.com/pypa/setuptools/issues/4620#issuecomment-2323233905

Looks like the cffi "usage" is an ancient and likely-all-dead monkeypatch- spinning an updated CFFI release now that makes the import/patch optional until we're sure it's "all dead" and can go through its pockets for loose change :wink:.


AzureDevOpsDemoGenerator : Deploying a multi-container application to AKS Issue

Hi,
While creating the project from the AzureDevOpsDemoGenerator : for Deploying a multi-container application to AKS , finding the below Issue/error/
Unable to create the project.
The error message showing as below.
86772e2b5962'. This usually indicates the task isn't installed, and you may be able to install it from the Marketplace: https://marketplace.visualstudio.com. (Task version , job 'Phase_1', step ''.) A task is missing. The pipeline references a task called 'a8515ec8-7254-4ffd-912c-86772e2b5962'. This usually indicates the task isn't installed, and you may be able to install it from the Marketplace: https://marketplace.visualstudio.com. (Task version 3.*, job 'Phase_1', step ''.)

we don't see any issue with the AKS template, if anything is related to the extension, please install the extension manually and try to provision the project.
Thanks!


Adding serialization to the package toml file

Added Serialization dependency to the toml file.

@JuliaRegistrator register()

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self condition question

Hi, i notice the self-condition training strategy is FrameDiff is not same as in RFdifussion:
Self condition training in RFdiffusion in supplementary : Algorithm 3
▷ Train step with self-conditioning x(t+1)
    x(t+1) = ForwardNoise(x(0), t + 1)  ▷ Sample (x(t+1), x(t)) ∼ q(x(t:t+1) | x(0))
    x(t) = ReverseStep(x(t+1), x(0))
   Compute self-conditioning input:
    x(0) prev = RF diffusion(x(t+1), 0)
    x(0)_prev = StopGradient(ˆ x(0) prev.)
 x(0) = RF diffusion(x(t), x(0)_prev)

So i rewrite framediff code to the same logic in RFdifusion :
# experiment/train_se3_diffusion.py
if self._model_conf.embed.self_condition.version and self._generator.random() > 0.5:
            prev_batch = {}
            # prepare common feature for both step
            prev_batch = ({k:v for k,v in batch.items() if "self_condition_" not in k})
            # prepare diffused feature for prev step
            prev_batch.update({k[len("self_condition_"):]:v for k,v in batch.items() if "self_condition_" in k})
            with torch.no_grad():
                self_condition = self._model(prev_batch)
                if self._generator.random() < 0.5:
                    self_condition = {k:v for k,v in self_condition.items() if  k not in ['edge_embed','node_embed']}

And i fix delta_t_range = [1] to only condition on one step
# pdb_dataloader.py Class PdbDataSet  Function __getitem__(self, idx):
if self.is_training:
          # prev step feature for self-condition
          t = np.random.uniform(self._data_conf.min_t, 1.0)
          diff_feats_t_prev = self._diffuser.forward_marginal(
              rigids_0=gt_bb_rigid,
              t=t,
              diffuse_mask=None
          )
          diff_feats_t_prev['t'] = t
          # training step feature
          dt = (1.0-self._data_conf.min_t)/self._data_conf.num_t
          dt = [min(t-self._data_conf.min_t,dt*i) for i in self._data_conf.delta_t_range][rng.integers(len(self._data_conf.delta_t_range))]
          rigids_t = self._diffuser.reverse(
              rigid_t=rigid_utils.Rigid.from_tensor_7(diff_feats_t_prev['rigids_t']),
              rot_score=du.move_to_np(diff_feats_t_prev["rot_score"]),
              trans_score=du.move_to_np(diff_feats_t_prev["trans_score"]),
              diffuse_mask=None,
              t=t,
              dt=dt,
              center=False,
              noise_scale=1.0,
          )
          rot_score = self._diffuser.calc_rot_score(
              rigids_t.get_rots()[None,...],
              gt_bb_rigid.get_rots()[None,...],
              t = torch.Tensor([t-dt])
          )[0]
          trans_score = self._diffuser.calc_trans_score(
              rigids_t.get_trans()[None,...],
              gt_bb_rigid.get_trans()[None,...],
              t = torch.Tensor([t-dt]),
          )[0]
          rot_score_scaling,trans_score_scaling = self._diffuser.score_scaling(t-dt)
          diff_feats_t = {
              'rigids_t': rigids_t.to_tensor_7(),
              'trans_score': trans_score,
              'rot_score': rot_score,
              'trans_score_scaling': trans_score_scaling,
              'rot_score_scaling': rot_score_scaling,
              'fixed_mask': fixed_mask,
              **{"self_condition_"+k:v for k,v in diff_feats_t_prev.items()}
          }
          diff_feats_t['t'] = t-dt

But this self-condition traning strategy gives obvious poor performance on secondary structure while training loss is almost same, which makes me rather confused:

Seems this self-condition strategy shows greater inconsistency between training and inference while from itution, it is  is more consistent between training and inference and RFdifusion proves it can work.

Hi, are you sure there's no bug in your inference code? I wouldn't expect a noticeable difference between the two strategies. FrameDiff follows the original self-conditioning implementation while RFdiffusion trains self-condioning with one step forward (t+1) which I guess just works better. I honestly have no scientific explanation of why one would work better than the other. Keep in mind these are two very different models so what works for one will not necessarily work for the other.

Closing due to inactivity.


Remove unused import from README example

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New Profile Image is not reflected in Calendar events

Update Profile Picture
View Calendar entry for that person
Expected : New profile image replaces existing image
Actual : old image is still displayed

I believe that's a result of the old image being cached for a length of time (I think 12 hours). Do you see the new picture if you clear the browser cache and refresh?

Cleared the cache, refreshed, closed and reopened browser - still seeing old image

Added this to the list of known issues in the overview.md - https://github.com/Microsoft/vsts-team-calendar/blob/master/overview.md


[4.x] Mod Hooks: comments in function parameters

func method(
	one, #Some comment
	two, 	three:  int, # More comments
		four
):
	pass

Generates:
func method(one, #Somecommenttwo, three: int, #Morecommentsfour):
	_ModLoaderHooks.call_hooks(vanilla_2078531418_method, [one, two, three, four],<PHONE_NUMBER>)

closed by #497


Support DeploymentItem in .Net Core projects

Description
[DeploymentItem] attribute is a no-op in the .Net Core world. This is however supported in Desktop and is required for functional testing scenarios and to provide isolation for test runs. Filing this work-item to add in that support for .Net Core based projects as well.
Steps to reproduce

In a .Net Core project add a DeploymentItem on a class/method linking to an xml resource(say) needed for the run.
Run a test that reads this xml resource.

Expected behavior
The test deploys the xml resource to a deployment directory and runs the test from there.
Actual behavior
The test fails complaining about not being able to find the resource file.

I am currently using this workaround for simple cases:
        // Declare this property - this is set by MSTest
        public TestContext TestContext { get; set; }

        // In test initialization - note the signature should be exactly this
        // A static void method with one argument of type TestContext
        [TestInitialize]
        public void TestSetup()
        {
            var testName = TestContext.TestName;
            var method = new StackFrame().GetMethod().DeclaringType.GetMethod(testName);
            var attributes = method.GetCustomAttributes(typeof(DeploymentItemAttribute)).ToArray();
            foreach(DeploymentItemAttribute att in attributes)
            {
                var origin = Path.Combine(Path.GetDirectoryName(Assembly.GetExecutingAssembly().Location), att.Path);
                var targetDir = Path.Combine(Path.GetDirectoryName(Assembly.GetExecutingAssembly().Location), att.OutputDirectory);
                // Creates dir for deployment item
                Directory.CreateDirectory(targetDir);
                // Copies item
                try
                {
                    File.Copy(origin, targetDir);
                }
                catch (Exception ex)
                {
                    System.Diagnostics.Debug.WriteLine("Error copying deployment item {0} to {1} message {2}", origin, targetDir, ex.Message);
                }
            }
        }

Fixed with https://github.com/Microsoft/testfx/pull/565


Pegging docker to alpha1.3

Closes #386
Closes #501
Please note that this pull request assumes that the next release will be alpha-1.3 for the docker image.  It was tested on alpha-1.2
Also, added warning if the pon version does not match the latest version in NormalizeReadCounts.
Adding warning if the PoN is not the current version in NormalizeSomaicReadCounts.
Setting to be the next version number of gatk-protected.
Adding plotting error dump to gitignore

👍


Restore ability to use STDIN

Restore ability to use standard input for svgcheck.
This functionality was unintentionally removed in #28.

We need a test suite :-)

We need a test suite :-)

I assume you are talking about a test suite that covers all popular tools used by the community.

I really hope the path to redefining what svg is acceptable is opening. It would be a much better investment to build a more maintainable checker against those rules than continuing to build infrastructure around a set of rules we know we're going to leave. (And to be explicit, I would expect to write something new for those rules rather than adjust this current implementation).

The problem is this line https://github.com/ietf-tools/svgcheck/blob/40c2914c688de757b9e72560920dfd890ff0f8f9/svgcheck/run.py#L110 - it looks for a "stdin" file in the current working directory instead of reading from the moral equivalent of /dev/stdin.
(Via https://github.com/cabo/kramdown-rfc/issues/233)

(Via cabo/kramdown-rfc#233)

Replacing the line in run.py by
    if len(args) < 1:
        source = "/dev/stdin"

as mentioned there works for me.


local_file data source usage for certain config files

Hi, we are trying to setup aft on our end but we have security check that is preventing local_file data source on terraform. Is it possible for us to move those config files into inline definitions such as variables or locals? Also there's another file function in terraform which is file. Are there any specific reasons behind not using file instead of local_file?
Paths contains local_file definitions:

~/data.tf
modules/aft-code-repositories/codebuild.tf
modules/aft-customizations/data.tf
modules/aft-lambda-layer/data.tf

@rfum please may you give us more context on the security check that prevents use of local_file resource?

We have a policy check in our Atlantis setup to make sure that unsafe and unknown providers and data sources are not used.
local file (and file) can use used to exfiltrate secrets from the server running terraform, and thus we have them blocked. This prevents e.g. a compromised developer machine being used to obtain credentials.
I believe this to be pretty common in defense-in-depth setups.

@snebhu3 any updates on this?

@rfum , @rbtcollins thanks for the additional context.
Is the feature request to replace use of local_file data source to file function to read content from a given file?

@snebhu3 Hi, no we'd like to get rid of file access through local_file function as @rbtcollins explained in his previous comment. We'd like to know why the function has been used in the first hand. I'm preparing a pr in our fork to make things faster but cannot ensure whether it will break anything if I move file contents into inline variables.

Hey @rfum!
Thank you for bring this to our attention! I created an item in our backlog to review this request. Thanks!


feat: add ci/cd elements and storybook, wire up operations

fixes #158
fixes #164

PR Storybook available here

Looking good! For some reason, the action buttons are clickable only near the borders on my Chrome (incognito or not), but they work fine on FF. Do you see the same?

I do!  I'm probably not using the patternfly-react buttons properly, but I
haven't worried about it yet, mostly wanted to get to this off the laptop
just to be on the safe side :-). That being said there's no docs in the
button's storybook and it's just a re-export looks like, sheesh...
On Fri, Apr 19, 2019, 4:03 AM Riccardo Forina<EMAIL_ADDRESS>wrote:

Looking good! For some reason, the action buttons are clickable only near
the borders on my Chrome (incognito or not), but they work fine on FF. Do
you see the same?
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/syndesisio/syndesis-react/pull/161#issuecomment-484800005,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AACV3LDRP2Z7XV46ILJXB23PRF4F7ANCNFSM4HG74IMQ
.

Try using the <ButtonLink> component, also from the ui package, the interface should be the same.

Yup, will give that a go.  That's an odd behavior for their button component though :-)

PR Storybook available here

PR Storybook available here

PR Storybook available here

PR Storybook available here

Interesting, so the button issue shown in the storybook is because the list-group-item-text div that holds the used by n integrations is for whatever reason spilled out and over the button area and partially covering them:

PR Storybook available here

Found a workaround I guess, the list needs the additionalInfo column set to calculate widths, so added in an empty span.  Other than that I think there's not much else I can do for the UI on this one,

@dongniwang FYI if you want, check out the storybook link under 'CiCd'.

PR Storybook available here

This does have a few issues here and there that I'm addressing in a subsequent PR as I start to use these UI elements.

Well, this work has to park for now.  The environment tag API isn't quite correct to implement the new design for the CI/CD management page, but in any case this PR is ready to be merged, it fetches environments, you just can't create/edit/remove them:

PR Storybook available here

The Add New button won't work until there's an API to support it.   - But I saw a blank CI/CD management page using link from this commenet https://github.com/syndesisio/syndesis-react/pull/161#issuecomment-485428336... should I check back later?

@gashcrumb - nvm, was looking at the wrong page...found it now

It's implemented, barring two needed changes to the API, #5266 and #5263.
Need to add some strings to the locale file, and the dialog for marking an integration for CI/CD was a bit tricky to implement, so may revisit that further.

 Who said the CI thing was a small one?

Right?


added #6 script

We're on a roll! Keep'em coming. I think this repo could grow into something super cool.
Just a few thoughts moving forward just so we keep the repo and commit history clean: in general I like to keep the commit messages using the present tense. They should indicate to a potential merger or someone reading the thread of commits what they do. You can think of them as being the second part of the sentence: When I merge this commit it will [...]. In this case it could be something like Add descriptor-from-mnemonic Swift script.


Virtlet pod CrashLoopBackOff

kubectl logs virtlet-8z5tn -n kube-system -c virtlet
UnixSocket Listener started
Starting server on socket /run/virtlet.sock
grpc: Server.Serve failed to create ServerTransport:  connection error: desc = "transport: write unix /run/virtlet.sock->@: write: broken pipe"
transport: http2Server.HandleStreams failed to read frame: read unix /run/virtlet.sock->@: read: connection reset by peer (<--note: this message repeats every 10 seconds)
Host: Ubuntu 18.04
K8S: 1.16.0
CNI: flannel
DNS: CoreDNS
Docker: v19.03.2
Virtlet: vLatest or 1.5.1
Could someone shed light on the root cause of this?

UPDATE:
I was trying to run the demo DIND. Everything has gone normally until the point for cirros-vm to be installed and created. Following is event logs for cirros-vm pod:
Events:
Type     Reason   Age                   From                  Message

Warning  Failed   55m (x247 over 119m)  kubelet, kube-node-1  Error: ImagePullBackOff
Warning  Failed   5m1s (x25 over 119m)  kubelet, kube-node-1  Failed to pull image "virtlet.cloud/cirros": rpc error: code = Unknown desc = "/run/virtlet.sock": rpc error: code = 2 desc = error downloading "https://github.com/mirantis/virtlet/releases/download/v0.9.3/cirros.img": Get https://github.com/mirantis/virtlet/releases/download/v0.9.3/cirros.img: dial tcp: i/o timeout
Normal   BackOff  9s (x471 over 119m)   kubelet, kube-node-1  Back-off pulling image "virtlet.cloud/cirros"
It looks like that it is related to the original issue with /run/virtlet.sock.

I got a brand new ubuntu linux box, installed CRI proxy by following instructions given for Installation on kubeadm clusters for use with Virtlet, and deployed Virtlet DaemonSet as instructed. After removed taint from my single master node, virtlet pod was created successfully. Apologize for any confusion.


v1.5.0 break Bootstrap 3 modals

Hi, thanks for this gem, it made replacing confirm alerts with modals a breeze.
The latest version brought Rails 5 and Bootstrap 4 support. In the pull #55 you where wondering about the backward compatibility and said that everything is fine. But I noticed the Bootstrap 4 modal change break the Bootstrap 3 modals.
v1.5.0 with Bootstrap 3 looks like this:
Here a jsfiddle(your example with the latest version) to demonstrate: http://jsfiddle.net/ze2Lz8tm/56/
Downgrading solved it for me, but maybe you should create a Bootstrap 3 compatible version and add a notice in the readme.

Thanks for the report. I will look into this. Sorry for the inconvenience.

Hi,
issue fixed and new version released as 1.6.0.
Cheers,


Hello, I have issue as I try to use another english dataset. And I'm wondering why Inference from packed test set can work (CUDA_VISIBLE_DEVICES=0 python tasks/run.py --config usr/configs/midi/e2e/opencpop/ds100_adj_rel.yaml --exp_name $MY_DS_EXP_NAME --reset --infer) but inference model from raw input (python inference/svs/ds_e2e.py --config usr/configs/midi/e2e/opencpop/ds100_adj_rel.yaml --exp_name $MY_DS_EXP_NAME) needs same phoneme set size?

    Hello, I have issue as I try to use another english dataset. And I'm wondering why Inference from packed test set can work (`CUDA_VISIBLE_DEVICES=0 python tasks/run.py --config usr/configs/midi/e2e/opencpop/ds100_adj_rel.yaml --exp_name $MY_DS_EXP_NAME --reset --infer`) but inference model from raw input (`python inference/svs/ds_e2e.py --config usr/configs/midi/e2e/opencpop/ds100_adj_rel.yaml --exp_name $MY_DS_EXP_NAME`) needs same phoneme set size?

Originally posted by @Wayne-wonderai in https://github.com/MoonInTheRiver/DiffSinger/issues/29#issuecomment-1260673475

same issue

When using our configs on your dataset, Please do check the "binary_data_dir" in hparams to make sure it points to your binarized data directory because the phoneme dictionary text file will decide the dimension of phone_encoder in the model.

so, by pointing to our own binarized data in  "binary_data_dir"  this should change the dimension of phone_encoder to fit our model?

we get this issue

When using our configs on your dataset, Please do check the "binary_data_dir" in hparams to make sure it points to your binarized data directory because the phoneme dictionary text file will decide the dimension of phone_encoder in the model.

I get this issue,

Sorry I may have misunderstood your issue. If you want to infer from our pretrained ckpt, please make sure your phoneme dictionary is exactly the same as ours because some layers in the pretrained ckpt are related to this. Or the phoneme unit may be wrongly encoded due to different dictionaries.

If you want to use customed phoneme dictionary, please follow our guidance and re-run the training.

If you want to use customed phoneme dictionary, please follow our guidance and re-run the training.

we did that but ran into the issue above. We retrained FFT, and Diffsinger and whenwe try to put in sequence, the error above is shown. Can you point us to where the model is written so we can debug what is causing this issue?  we cant pinpoint what is requiring the missing keys.

If you want to use customed phoneme dictionary, please follow our guidance and re-run the training.

我們是依照這個教學用英文資料集重新訓練, 但是當將FFT 跟Diffsinger 接起來時 會報上面這個錯誤. 我們找不到是哪隻程式 會吃這些state_dict 的key. 您可以將我們指向是哪一行程式嗎. 另外, Diffsinger model 每個 layer 是寫在哪一個程式裡? 我們也找不到

If you want to use customed phoneme dictionary, please follow our guidance and re-run the training.

when we retrain (using different phoneme dimension)  and don't care about the phoneme, the validation script can be used to create singing voice that resemble the new data. but the inference script doesnt work.

They are in the modules/***.

They are in the modules/***.

Where does the run.py file get the list of modules to load?

They are in the modules/***.

Thank you last question, Which code is responsible for checking the model size and parameters? that gives the errror in loading state_dict for fastspeech2MIDI “ “missing keys in state_dict”

They are in the modules/***.

Thank you last question, Which code is responsible for checking the model size and parameters? that gives the errror in loading state_dict for fastspeech2MIDI “ “missing keys in state_dict” and do we ignore that if training own model?

您好，请问下呗，您使用diffsinger在英文数据集成功训练模型了嘛，感谢🙏


vsphere driver can't create

Using the vsphere driver, the IP address that's detected for the docker VM is the IP of eth0 - which is the docker private IP address. The outgoing interface is eth1. So then docker-machine can't connect to the VM it just created.
INFO[0283] Configuring virtual machine vsphere-docker...
ERRO[0374] Error creating machine: dial tcp <IP_ADDRESS>:22: operation timed out
The vSphere summary panel also shows the private IP. It would probably simplify things if eth0 were the public IP, and eth1 was the private one.

/cc @frapposelli

Can't reproduce, are you using a custom b2d iso?

I'm no longer able to reproduce it, either.
I was not using a custom boot2docker, but at the time I reported the issue the iso that was downloaded by docker-machine was named boot2docker-vmw.iso (on Feb 26.) Now it's boot2docker-1.5.0-GH747.iso.
It seems likely that the current boot2docker iso resolves the issue. In any case, something has resolved it.


[Question] Using cache network image package

I have a question. Why exactly is cached network image being used here as it will fill the cache without any way to clear that particular cache , also it adds a minimum 1.20.0 version restriction which is quiet unstable for now. I would propose to use extended_image or just no caching

I use for speed up loading gif, but I'll try with extended_image, thanks i don't know this library. Could you make this PR?


docs: dt-531 component combinator

Description
Implement the dialtone-combinator package in the dialtone documentation website.

To include the combinator in markdown simply use the tag like you would in a vue template, passing in the target component to use:
<component-combinator component-name="DtButton" />

Currently displayed below the initial preview on the component pages, however this can be changed easily.

Uses variants from the variantBank export in the dialtone-combinator package, this is a good place to keep them as they will be shared between whatever uses the combinator in the future. However if needed these can be customized by passing custom data into the combinator variants prop.

Clear variant:

The showBlueprints prop can also be used to show a group of variants in a container below the combinator, leveraging the combinators 'blueprint' mode.
<component-combinator component-name="DtButton" show-blueprints />

This is currently not used anywhere however could be very useful for easily conveying the code required to create different variants, which is a problem in storybook right now.
Pull Request Checklist

[x] Ask the contributors if a similar effort is already in process or has been solved.
[x] Review the contribution guidelines.
[x] Use staging as your pull request's base branch. (All PRs using production as its base branch will be declined).
[x] Ensure all gulp scripts successfully compile.
[x] Update, remove, or extend all affected documentation.
[x] Ensure no private Dialpad links or info are in the code or pull request description (Dialtone is a public repo!).

Obligatory GIF (super important!)

really great work on the combinator project!

Thanks! I'm honoured to get the legendary "Jose approves" gif 🤣

It finally works on the deploy preview!

Sweet! looks like everything is working. We should probably hold off on actually merging this at the moment as there are probably some design changes we need to make before publishing it so it fits in visually with the rest of the site. But by doing this we've still figured out everything we had to in order to get this published an implemented in the doc site. We can just keep this PR open for the time being.

Just so we don't have to have this PR sitting here forever and getting way out of date with staging, I've commented out the usage of combinator on the pages themselves and I'm going to merge it in. Should have no visual change to the current doc site.


neutrinorpc: remove getblockhash

Removes the getblockhash function from the neutrino sub-server. The functionality and endpoint has been moved to the chainrpc sub-server in 0.16.

@yyforyongyu Ok, I will write a pr to deprecate it for 0.17 and remove it for 0.18 or 0.19 then.

@yyforyongyu Or actually... the reason I removed it was because it was already removed from lncli interface (https://github.com/lightningnetwork/lnd/blob/2fd40d16f1ec7a93d17870d27dfc3d488d34a7c9/cmd/lncli/neutrino_active.go#LL238C5-L243C23).

Yeah, if a mobile app developer already started using this after updating to 0.16, it would be a bit premature to remove it again in 0.17, even if there's an alternative.

@guggero @yyforyongyu Deprecated the neutrinorpc getblockhash in #7712.


feat: confluence url is mandatory arg

Closes #138
Proposed Changes
-Change to README file.
-Change to confluence file in the DefineCommand function.
I submit this contribution under the Apache-2.0 license.

I'll do it.

Suggestion:
There's the net/url package available. Would you like me to utilize it for a more comprehensive URL validation? If not, I'm prepared to proceed with the simpler version.


first commit for BLING - Reggaeton Token

I agree to not ping anybody on Discord/Twitter/email about this pull request. Instead I will inquire by posting a new comment in the pull request if needed.

PRs are reviewed in bulk and and can take up to two weeks to be merged.
This repository is managed using an auto merge action. Please ensure your PR has no deleted lines, and it will be merged.
Please provide the following information for your token.
Please include change to the src/tokens/solana.tokenlist.json file in the PR.
DON'T modify any other token on the list.
At minimum each entry should have

Token Address:
Token Name:
Token Symbol:
Logo: (logo should be uploaded under assets/mainnet//*.<png/svg>)
Link to the official homepage of token:
Coingecko ID if available (https://www.coingecko.com/api/documentations/v3#/coins/get_coins__id_):

Please close this fork. The name Reggaeton Token is incorrect.
The name for this token should be Crypto Cristo.


Improvement event section card ui

Description
This PR fixes # #134
Notes for Reviewers
You can check the following improvement
Adding blur navbar to the event section

remove too much border-radius and shadow

Chapter Section navbar

Thanks @SubhamB2003 , we will review and merge it soon:)

Thanks @SubhamB2003 , we will review and merge it soon:)

Hey, can you please add the GSSOC23 label


Explore using bioblend for Galaxy remote workflow execution

Documentation is at https://bioblend.readthedocs.io/en/latest/index.html

galaxy project also provides a higher interface for workflow execution with a CLI tool called Planemo ran e.g. as planemo run workflow.ga job.yml. The docs and the training material could serve as a starting/melding point.
https://training.galaxyproject.org/training-material/topics/galaxy-interface/tutorials/workflow-automation/tutorial.html
https://planemo.readthedocs.io/en/latest/automating_workflows.html


Loading box throws up some errors

The loading box currently produces some errors - we should replace this with a better solution.

This is fixed now, with a custom Loading box


Add the subject of the email to the debug when failing to sync

Should make it slightly easier to figure out which email is breaking synchronisation.

Thanks!


Update Readme.md

Adding note on repo moving to maintenance mode.

Any chance that the existing PR for initial shadow support (#57) and my PR for fixing :where detection (#65) can be merged and released?
Appreciate everyone's work on this, thanks!


Missing library files when installing through Bower

Hello!
Thank you for this great module!
However, when I install the package using Bower: bower install angular-ui-router.stateHelper there are no library files in bower_components directory, only README and such are present.
~/test/bower_components/angular-ui-router.stateHelper$ ls -lah
total 24K
drwxrwxr-x 2 sfomin sfomin 4.0K Dec 27 17:29 .
drwxrwxr-x 3 sfomin sfomin 4.0K Dec 27 17:29 ..
-rw-rw-r-- 1 sfomin sfomin  455 Dec 27 17:29 .bower.json
-rw-rw-r-- 1 sfomin sfomin   35 Jul 13 23:43 .gitignore
-rw-rw-r-- 1 sfomin sfomin 1.1K Jul 13 23:43 LICENSE
-rw-rw-r-- 1 sfomin sfomin 3.7K Jul 13 23:43 README.md

Please advise )

Looks like problem with Bower itself after all, sorry for the false alarm = )


dispatcher should accept override history_address and authority_address rollups deployent configuration

📚 Context
So that I can use AWS KMS keys to sign/verify transactions, I need to deploy the Auhority and History contracts using the same KMS key.
When I configure a validator-node's dispatcher, the history_address and authority_address configurations are read from the --rollups-deployment-file CLI argument, and a file that could be used as a value for that argument is currently being distributed within the rollups-dispather container image at /opt/cartesi/share/deployments/$network.json.
✔ Solution
It should be possible to override only these parameters (history_address, authority_address) via CLI argument to reuse the rollups deployment file already distributed but override only those addresses.

This should be done in https://github.com/cartesi/rollups-node/issues/88


Recommend SDATE use single Gregorian dates

Fixes #160
Signed-off-by: Dave Thaler<EMAIL_ADDRESS>

Merging per agreement in meeting 21 JUN 2022


Double execution of loop inside async place_orders

Loop of batch orders inside async place_orders is:
_async def place_orders(self):
for loop 10 of batch order of size 10
  self.trader.create_orders(orders_data)_

async/await seem to enter the above loop  before completing ,
instead of waiting for completion of the loop.
Thus I solved in ad hoc way as
async def place_orders(self):
...if bPaceOrdersExecuted==False:
......loop 50 of batch order of size 10
.........bPaceOrdersExecuted=True  #<----- tell the program that loop has already started
.........self.trader.create_orders(orders_data)
......bPaceOrdersExecuted=False #<----- tell the program that loop has completed and safe to enter again
We tell the program that loop has begun its loop by boolean bPaceOrdersExecuted of PlaceOrders EXECUTED as True.
I want to understand async/await and its handling of loop such that it is completed before
other intrudes again.  The result of instead of 10x10=100 but twice the size 200.
I googled but failed to find intuitive articles to learn solving this particular problem.
Best regards,
Ingyu

@igkoh Hi,You can try the async locker decorator to avoid entering the above loop before completing,such as async_method_locker("place_order",wait=True) https://github.com/hbdmapi/hbdm_Python/blob/master/alpha/utils/decorator.py#L20

@foonsun,
What a great joy.  Erratic behavior of double execution, strange cancellation disappear with
decorator async_method_locker, modifying behavior of place_orders and cancel_orders without lock.
After imorting
from alpha.utils.decorator import async_method_locker
in strategy.py, behaviors of place_orders and cancel_orders are modified to be locked.
@async_method_locker('place_ordersLocker1')
async def place_orders(self):
...loop of n batch of 10 orders  create_orders<--- no interruption from other methods
@async_method_locker('CancLocker')
async def cancel_orders(self):
...loop of n bach of 10 revoke_order<--- no interruption from other methods
I have tested with unusually large numbers (100 of 10 batch orders) and obtained clean results.
Your clean instructions really give me joy.
Best regards,
Ingyu

@igkoh Great!


how to install keras 2 in raspberry pi 3

Hi @marcosscorpain7,
if you run sudo pip3 install  Keras  you will have the latest version (should be 2.x).


Eager loaded ci and alert spec stability

Description
This PR was inspired by an open issue for a flaky test but does not necessarily directly resolve it. While attempting to debug a different flaky test I discovered that another test case in spec/system/partner_system_spec.rb was flaky in my local environment.
Specifically if I ran bundle exec rspec --order rand:18075 ./spec/system/partner_system_spec.rb:149 it would fail quite consistently locally with:
Partner management
  #index
WARN: Screenshot could not be saved. `page.current_path` is empty.
    allows a user to invite a partner (FAILED - 1)

Failures:

  1) Partner management #index allows a user to invite a partner
     Failure/Error: expect(page.find(".alert")).to have_content "invited!"

     Capybara::ElementNotFound:
       Unable to find css ".alert"

     [Screenshot Image]: /home/malf/code/human-essentials/tmp/screenshots/failures_r_spec_example_groups_partner_management_index_allows_a_user_to_invite_a_partner_935.png

     # ./spec/system/partner_system_spec.rb:160:in `block (3 levels) in <top (required)>'

Finished in 33.91 seconds (files took 7.76 seconds to load)
1 example, 1 failure

Failed examples:

rspec ./spec/system/partner_system_spec.rb:149 # Partner management #index allows a user to invite a partner

When watching it in a browser I saw that the expected behavior does eventually occur but the browser sits and waits to load the next bit of UI after accepting the invite alert in the spec. When I enabled eager loading in the test env the test passed. However eager loading locally tends to mean slower tests in the local env.
So I put together two changes in this PR:

Enable eager loading for the CI environment only
Wrap the test that is still flaky locally with some additional wait time which gets it passing pretty consistently locally for me

I did investigate a few other alternatives:
Alternative 1: Always eager load system specs
While you can run tasks before(:suite) and even before(:each, type: :system) triggering a Rails.application.eager_load! at those times did not seem to help the stability of the flaky test. It was only improved when the actual config/test.rb file changed. I imagine that has something to do with when/how the application is loaded for a system test but I didn't dig too deeply into it. I was not able to get the eager loading to run conditionally so I gave up on that approach after a bit
Alternative 2: Always eager load even locally
I ran some extremely unscientific benchmarks locally with and without eager loading running each spec file one at a time. In general the outcome was:

Most files spent about 3.5-5 seconds more loading files for the test run
Most files spent 0-2 seconds less time on test execution (they were actually slightly faster)
The overall result was that most runs of an individual test file took about 2-3 seconds longer with eager loading enabled
Some tests, particularly the long/slow ones, did show a net benefit. For example the item system spec took around 8 seconds less total (including file loading time) with eager loading enabled.

So while some cases looked better at the per-file level it was mostly just a bit slower across the board. Additionally if you were to compare a single test case it's going to almost always be slower. In practice I suspect most developers are going to run a single file or a single test case locally much more often than the whole suite so keeping the setting off for local envs is probably for the best for now.
Type of change

Bug fix (non-breaking change which fixes an issue)

How Has This Been Tested?
Ran a series of tests before and after the change. Primarily running individual test files one at a time before and after.

@all-contributors add @matt-glover for coding


build が失敗する

chunagon> yarn build
yarn run v1.22.10
$ react-scripts build
Creating an optimized production build...
Failed to compile.

.\src\App.tsx
Cannot find file './App.css' in '.\src'.

error Command failed with exit code 1.
info Visit https://yarnpkg.com/en/docs/cli/run for documentation about this command.

直しときます

WSLで実行したけど同じく
/mnt/c/---/chunagon > yarn build
yarn run v1.22.10
warning ../package.json: No license field
$ react-scripts build
Creating an optimized production build...

環境
$ lsb_release -a
No LSB modules are available.
Distributor ID: Ubuntu
Description:    Ubuntu 20.04.2 LTS
Release:        20.04
Codename:       focal

最新版プルした？

ディレクトリ削除したあとにもう一回cloneしたら行けたわ
なんでやろな

手元やと出来るんやけどなあ


Not working on server

I have an SMP with my friends and I think I did everything right (downloaded it installed it on the server and in my mods folder)
but it just wont work. It works if I load up a single player and use the mod in that world just not in the server.

same problem to be solved

Both client and server needs to install this mod

not this problem, the server cant even launch normally, it would stuck at world loading when this mod is added

@EnderTheCoder post the server log. Does the stuck happen randomly?

And if you are using bukkit4fabric, IP is incompatible with bukkit4fabric

Close due to not having complete information to diagnose the issue.


.macOS(.v10_12) instead of .macOS(.v10_10) in Package.swift

Is there a specific reason for having a higher macOS version requirement enforced for the Swift Package Manager?

That's a mistake. I lowered the requirement in https://github.com/sindresorhus/Preferences/commit/669fc93c7092d70ebb8b52b82000765731fe63ab, but I forgot to update Package.swift.