[SPARK-15466][SQL] Make SparkSession as the entry point to programming with RDD too

What changes were proposed in this pull request?
SparkSession greatly reduces the number of concepts which Spark users must know. Currently, SparkSession is defined as the entry point to programming Spark with the Dataset and DataFrame API. And, we can easily get RDD by calling Dataset.rdd or DataFrame.rdd, too.
However, many usages (including examples) are observed to extract SparkSession.sparkContext and keep it as own variable to call parallelize.
If SparkSession supports RDD seamlessly too, it would be great for usability. We can do this by simply adding parallelize API.
Example
 object SparkPi {
   def main(args: Array[String]) {
     val spark = SparkSession
       .builder
       .appName("Spark Pi")
       .getOrCreate()
-    val sc = spark.sparkContext
     val slices = if (args.length > 0) args(0).toInt else 2
     val n = math.min(100000L * slices, Int.MaxValue).toInt // avoid overflow
-    val count = sc.parallelize(1 until n, slices).map { i =>
+    val count = spark.parallelize(1 until n, slices).map { i =>
     val count = spark.parallelize(1 until n, slices).map { i =>
       val x = random * 2 - 1
       val y = random * 2 - 1
       if (x*x + y*y < 1) 1 else 0
     }.reduce(_ + _)
     println("Pi is roughly " + 4.0 * count / n)
     spark.stop()
   }
 }

 spark = SparkSession\
   .builder\
   .appName("PythonPi")\
   .getOrCreate()

- sc = spark._sc
-
 partitions = int(sys.argv[1]) if len(sys.argv) > 1 else 2
 n = 100000 * partitions

 def f(_):
   x = random() * 2 - 1
   y = random() * 2 - 1
   return 1 if x ** 2 + y ** 2 < 1 else 0

-count = sc.parallelize(range(1, n + 1), partitions).map(f).reduce(add)
+count = spark.parallelize(range(1, n + 1), partitions).map(f).reduce(add)
 print("Pi is roughly %f" % (4.0 * count / n))

 spark.stop()

How was this patch tested?
Pass the Jenkins test (with new python test) and also manual.

Hi, @rxin .
I'm wondering your opinion about this PR.

Test build #59081 has started for PR 13245 at commit 810f08a.

Test build #59082 has started for PR 13245 at commit 65f9746.

Test build #59081 has finished for PR 13245 at commit 810f08a.

This patch fails PySpark unit tests.
This patch merges cleanly.
This patch adds no public classes.

Merged build finished. Test FAILed.

Test FAILed.
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Test FAILed.

Test build #59085 has started for PR 13245 at commit 4f6a69e.

Test build #59085 has finished for PR 13245 at commit 4f6a69e.

This patch passes all tests.
This patch merges cleanly.
This patch adds no public classes.

Merged build finished. Test PASSed.

Test PASSed.
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Test PASSed.

Test build #59082 has finished for PR 13245 at commit 65f9746.

This patch fails PySpark unit tests.
This patch merges cleanly.
This patch adds no public classes.

Merged build finished. Test FAILed.

Test FAILed.
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Test FAILed.

hm we are trying to avoid returning rdds in the new apis. one thing we can do is to introduce a parallelize api that returns dataset?

I see. Thank you!

Unfortunately, Dataset (or Dataframe) seems not suitable to achieve the goal on Python.
>>> spark.parallelize(range(1, 10)).toDS()
...
AttributeError: 'RDD' object has no attribute 'toDS'
>>> spark.parallelize(range(1, 10)).toDF()
...
TypeError: Can not infer schema for type: <type 'int'>

I'll think about this more until tomorrow and close this if I cannot find a neat solution.

Sorry, it wasn't a good idea of extending SparkSession for RDD. I'm closing this PR.


matchmycolor.Colibri version <IP_ADDRESS>47

[x] Have you signed the Contributor License Agreement?
[x] Have you checked that there aren't other open pull requests for the same manifest update/change?

[x] Does your manifest conform to the 1.4 schema?

Note: <path> is the name of the directory containing the manifest you're submitting.

Microsoft Reviewers: Open in CodeFlow

We would like to update the existing package publisher from matchmycolorLLC to matchmycolor and package id from matchmycolorLLC.Colibri to matchmycolor.Colibri

I now have the package with the new package id and publisher, that's very good. However we would like the old package to be removed:
package id: matchmycolorLLC.Colibri
publisher: matchmycolorLLC
How can we achieve that?


Login with Oauth via Socialite

This PR implements Oauth login and account creation/linking via Socialite.
To enable it you have to add to your twill configuration:
'enabled' => [
    // Options
    'oauth-login' => true,
],
'oauth' => [
    'providers' => ['github', 'facebook', 'google']
],

Possible values for oauth providers are the ones implemented by Socialite: facebook, twitter, linkedin, google, github, gitlab and bitbucket.
See https://laravel.com/docs/6.x/socialite.
Callbacks are automatically setup for you to add them to your apps setup:
https://github.com/ferpetrelli/twill/blob/oauth/config/services.php
And credentials will be managed through environment variables:
GOOGLE_CLIENT_ID=123456
GOOGLE_CLIENT_SECRET=123456
FACEBOOK_CLIENT_ID=123456
FACEBOOK_CLIENT_SECRET=123456

Beautiful PR @ferpetrelli, thank you so much!
And definitely agree. about the new migrations approach, see https://github.com/area17/twill/pull/372#issuecomment-537965676!

Merged in afd14245. Thank you @ferpetrelli!

Merged in afd14245. Thank you @ferpetrelli!


Windows support

The tool is currently not working on Windows.

Fixed in https://github.com/jwanner83/liferay-npm-bundler-improved/releases/tag/1.1.1


Update F-Droid metadata to include new repo name

Describe the chore
Update F-Droid metadata to include new repo name.
Would you like to work on the issue?

[x] Yes
[ ] No

@iamareebjamal Please check: https://gitlab.com/fdroid/fdroiddata/merge_requests/5085

Done.


feat: adjust the chatbot typingdots to have a fixed position

Describe the feature
a user interface issue has been identified where the typing indicator dots are not correctly positioned in long chat conversations. Instead of appearing immediately after the last message, these dots are showing up in an incorrect location within the chat interface.
Use Case
It's better for UX.
Proposed Solution
No response
Other Information
No response
Acknowledgements

[ ] I may be able to implement this feature request.

CDK version used.
2.133.0
Node.js Version
v20.11.1
Environment details (OS name and version, etc.).
MacOS Sonoma 14.3.1

merged into main.


Generic ARM Linux buil

Hello folks,
If I cross-compile (even if not supported) can I build it for an armv6l (no FPU) device which has no HW access (so no GL) and use it to directly draw to the linux framebuffer (/dev/fb)?
Thanks!

No. bgfx requires FPU support, and there is no software rasterizer (there is workaround for this, if you use swift shader as rasterizer).


Add StripDebugInfo pass our MLIR pipeline

Request description
The StripDebugInfo pass in MLIR core is useful to remove the debug information from all the MLIR operations. It would be great if we could add it to our pipeline under a flag. Removing the MLIR-related debug information is critical when we have to provide an LLVM-IR reproducer, especially when it's large, since de debug information can add a considerable amount of noise and size to the final output.
What component(s) does this issue relate to?
MLIR
Additional context
No response

@dcaballe @benvanik Any idea of priority for this? P1 or P2?


Create passenger class

Note to reviewers: This code is not functional yet. The database functions and the other classes have not been created so there are some placeholders here.

I have comments to make, but I think they're all things you mentioned above so I'm not sure what to do...
I think PR submission should be saved for when your code is ready to be reviewed, because if it's not ready I'm not sure how to be helpful. If you've got an idea of what you want looked over lmk.

@rachel-ftw We thought the code was ready to be reviewed.
If you still want to review it you can look at the passenger.js file and assume that the db.* functions do what they say they do.  The names are self-explanatory with the exception of db.updatePassenger which also creates a new passenger in the database if one doesn't already exist with the specified id.


N3 getstate and findstate RPC commands missing from reference documentation

See title
Code added here: https://github.com/neo-project/neo-modules/pull/638

Please kindly check here:
https://docs.neo.org/docs/en-us/reference/rpc/latest-version/api/getstate.html
https://docs.neo.org/docs/en-us/reference/rpc/latest-version/api/findstates.html


Gradle does not shutdown gracefully when build is aborted during busy task

Current Behavior
When using an AutoCloseable BuildService, the close method is not always called, when

the Gradle build is cancelled
during the cancellation, a task was running busily for a certain amount of time

This is also the case for the following alternative APIs to release resources at the end of builds/tasks:

deprecated project.getGradle().buildFinished hook
BuildService with BuildEventsListenerRegistry.onTaskCompletion
new Dataflow Actions feature -> https://docs.gradle.org/current/userguide/dataflow_actions.html

Expected Behavior
BuildService.close should be called even if the Gradle build is aborted during a busy task execution.
Context (optional)
AutoCloseable BuildServices usually manage resources which should be released when the build stops. Builds may be cancelled due to different reasons. Even when builds are aborted, all resources should be released.
Steps to Reproduce
import org.gradle.api.services.BuildService
import org.gradle.api.services.BuildServiceParameters

abstract class Service implements BuildService<Params>, AutoCloseable {
    interface Params extends BuildServiceParameters {
        Property<File> getFile()
    }

    @Override
    void close() throws IOException {
        parameters.file.get().createNewFile()
    }
}

abstract class ServiceTask extends DefaultTask {
    @Internal
    abstract Property<Service> getService();

    @Internal
    long busyTimeMillis = 1

    @TaskAction
    void run() {
        getService().get()
        final long start = System.currentTimeMillis()
        while (true) {
            final long now = System.currentTimeMillis()
            if (now - start > busyTimeMillis) {
                break
            }
        }
    }
}

def serviceProvider = gradle.sharedServices.registerIfAbsent('service', Service) {
    parameters.file.set(project.file('CLOSE'))
}

tasks.register('myTask', ServiceTask) {
    getService().set(serviceProvider)
    usesService(serviceProvider)
}

Call myTask => file CLOSE will be created in the root of the project.
Delete the CLOSE file each time before you restart.
Now change busyTimeMillis to a large value, e.g. 100000.
Soon after the task started, abort the build via CTRL-C => file CLOSE will not be created.
Change busyTimeMillis to 5000.
Again, soon after the task started, abort the build => file CLOSE probably will be created.
Also, when changing the busy loop to a Thread.sleep (with a long sleep time), the CLOSE file will be created reliably.

Expected: The file CLOSE should always be created.
Gradle version
8.4
Build scan URL (optional)
No response
Your Environment (optional)
Windows 11
PowerShell

Thank you for providing a valid report.
The issue is in the backlog of the relevant team, but this area of Gradle is currently not a focus one, so it might take a while before a fix is made.

Thank you for providing a valid report.
The issue is in the backlog of the relevant team and is prioritized by them.

We need to investigate further what else is affected by the ungraceful shutdown and how to fix that in general.


How to delete the SubscriptionGroup？

Use admin tool by deleteSubGroup command, you can refer to https://github.com/apache/rocketmq/blob/master/docs/cn/operation.md

Use admin tool by deleteSubGroup command, you can refer to https://github.com/apache/rocketmq/blob/master/docs/cn/operation.md

Not work.
In stand-alone mode,excute below common:
./mqadmin deleteSubGroup -n localhost:9876 -g data-adapter -b localhost:10911 -c DefaultCluster
Return:
delete subscription group [data-adapter] from broker [localhost:10911] success.
But, excute ./mqadmin statsAll -n localhost:9876 ,the column "#Consumer Group" can still see it.

Use admin tool by deleteSubGroup command, you can refer to https://github.com/apache/rocketmq/blob/master/docs/cn/operation.md

Not work.
In stand-alone mode,excute below common:
./mqadmin deleteSubGroup -n localhost:9876 -g data-adapter -b localhost:10911 -c DefaultCluster
Return:
delete subscription group [data-adapter] from broker [localhost:10911] success.
But, excute ./mqadmin statsAll -n localhost:9876 ,the column "#Consumer Group" can still see it.

If your related consumer  closed？

How can it be solved? Alarm due to prometheus monitoring delay

Hi bro, did you solve this problem？

Hi bro, did you solve this problem?


Strip large binaries from history with BFG

Because large data files were previously included in the git history cloning this repository takes an inordinate amount of time. See the previous issue from MultiAssayExperiment on how large binary data files can be cleaned from the history:
https://github.com/waldronlab/MultiAssayExperiment/issues/44
Note that any forks will have to do the same or to re-fork before issuing a pull request, or else history will re-appear. Better to do this now than after there are even more forks.

On it!

Completed with e0e7372, but the docs site has a few large images that make the repos a bit much to download. To fix, I could move the site to another repos if that makes sense.


Detailed message needed when receiving 400 response code

When performing Source Reset all that was displayed was a response code of 400.
Upon running the same command in Postman the same message was displayed but with a couple of additional details over time that provided a better explanation.

Detailed message was that it can't be proceed because there was an Identity Refresh process running and the source could not be reset at that time.
After the Identity Refresh was complete this was the message displayed in Postman:
"msg_template": "Source 'xxx' is currently in use.",
"slpt_error_code": "SLPT-1209",
"formatted_msg": "(SLPT-1209) Source 'xxx' is currently in use.",
"exception_id": "18B206C5CA9",
"error_code": 1209,
"exception_class": "com.cloudmasons.exceptions.SLPTSourceInUseException",
"exception_detail": {
"file": "SourceService.groovy",
"method": "reset",
"line_number": 2140,
"sourcesOwnedByUsersFromThisSource": [
"xxyy",
"yyxx",
"yyyy"
],
"class": "com.cloudmasons.SourceService"
},
"http_response_code": 400,

It would be nice if the message details in the IDN extension contained at least some of this detail.

Here is what I can do for instance:

Released as part of 0.0.24


reconnect on reload

Added 3 attempts for reconnecting to i3 on reload.

This isn't necessarily something I want the library to do by default. Losing a connection to the ipc means one of two things.

i3 has exited. In this case, it makes sense for the library not to reconnect because starting i3 again will usually trigger a new instance of the script. Reconnecting in this case is not useful and I believe this to be the most common use case for the library.

i3 has restarted. In this case, I have always recommended people use the exec_always config directive to start their scripts. Reconnecting by default would break these scripts because they are expecting the old script to die once the restart happens. I do not recommend anyone use the restart command from i3 except if it crashes or for development reasons. Use the reload directive instead. It's a very hard command to support in any ipc library.

I might consider adding this feature if it is by configuration on the Connection in the constructor (such as auto_reconnect=True) if you can provide a strong use case you have for this feature.

I have a use case for this.
When I change the display configuration (single monitor to multi monitor setup) some parts of the screen become black. The only way to fix that is to restart i3.
Just reloading is not enough. For the moment I use os.system('i3-msg restart') to get it working.

@Nebucatnetzer I'm interested in having this in the library, but I think this implementation needs some work. There are some little details that need to be worked out that aren't addressed here. Make a new issue and we'll discuss it there.


No server worker created?

I followed the docs here to setup this plugin. It looks like everything worked except no service worker is actually generated. Looking in the /dist folder, there are no seemingly related files and in the browser console I see "No matching service worker detecte".
What more do I need to do to create the service worker? Here's my vite.config.ts:
import { defineConfig } from 'vite';
import react from '@vitejs/plugin-react';
import { resolve } from 'path';
import { VitePWA } from 'vite-plugin-pwa';

export default defineConfig({
	plugins: [
		react(),
		VitePWA({
			includeAssets: [ 'robots.txt', 'favicon.ico', 'apple-touch-icon.png' ],
			manifest: {
				name: 'My App',
				short_name: 'App',
				description: 'My App',
				theme_color: '#2c2c2c',
				display: 'standalone',
				icons: [
					{
						src: '/android-chrome-192x192.png',
						sizes: '192x192',
						type: 'image/png',
					},
					{
						src: '/android-chrome-512x512.png',
						sizes: '512x512',
						type: 'image/png',
					},
				],
			},
		}),
	],
	build: { sourcemap: true },
	resolve: { alias: { '@': resolve(__dirname, 'src') } },
});

Also note that I'm testing this by following the doc instructions here

it is zero config, not zero development: the plugin will configure a lot of (workbox) defaults for you, but you need to instruct the plugin how to load the sw
it is not about react, it is just another fw: before deploying the app you must fix the behavior you want for your sw, changing the behavior once deployed can be a pain: if only for local testing you can check the guide to uninstall the sw from dev tools
if you want to do a simple test, just add this on the your main.ts(x):
import { registerSW } from 'virtual:pwa-register';
registerSW({ immediate: true })

add this line to your vite plugin pwa configuration:
registerType: 'autoUpdate',

previous configuration will auto update the app on the browser when new version on the app detected
to configure a PWA (offline support) you must add to the manifest entry (on vite plugin pwa options) the name, the short_name, the description and some icons (at least 192x192 and 512x512)

Thanks for the information. Sorry, I did read the docs, but the "getting started" doesn't specify any of this as bare minimum to get everything working like it's suppose to. Even in the Generate Service Worker, all it talks about is setting up the manifest properties.


Add mobilenet v2

Can we get some specifics on how this was trained?
Were image means subtracted?
Is the channel ordering RGB or BGR?
What image set (and labels) were used?

I see there is more detail at https://github.com/caffe2/models/tree/master/mobilenet_v2_quantized , does it all apply equally to the non-quantised model?


Added SMTP Parameter capability

Added SMTP parameter capability per #10
Script will use the parameters if provided. If not, will utilise values from the configuration file.

Let me know what you think of the if statements on lines 124-127. If they're too squished, we can break them out into multi-liners.


html support

Is there anyway for this to work with html, by maintaining the original markup or ignoring html tags, so that only the text is updated, but the html remains intact?

I think this may be as simple as the code below.
var HtmlDiff = new diff.Diff(true)
HtmlDiff.tokenize = function(value) {
	return removeEmpty(value.split(/(<>[{}:;,]|\s+)/));
}
var diffs = HtmlDiff.diff(revision1, revision2)

@webchaz could you elaborate on what you are looking for?

the problem is not solved

Closing in favor of #71. Moving discussion there.


Unexpected limitation of measurement accuracy for lengthscales larger than pixel dimensions

As an experiment to investigate the accuracy of imageruler, we can measure the separation distance between two circles which contain no sharp features or small artifacts. In this example, there are two circles of diameters 80 and 60 and the separation distance (void region) is varied from 1.0 to 20.0 in increments of  1.9. The resolution is 1 pixel per unit length. Given this configuration, we would expect to resolve separation distances down to about 2.0 based mainly on the resolution of the image.
A plot of the measured vs. actual value of the separation distance is shown below. This plot is almost exactly linear for separation distances down to about 5.0 below which the measured value is a constant. In the output, the relative error actually starts to become larger than expected when the separation distance is 6.7.
This could suggest some room for improvement to imageruler's algorithm.

notebook
import sys
sys.path.append("../imageruler")

import imageruler
from matplotlib import pyplot as plt
import numpy as np
from regular_shapes import disc

def separated_discs(
    left_diameter: float,
    right_diameter: float,
    separation_distance: float
) -> np.ndarray:
    left_center = (0, -0.5 * (left_diameter + separation_distance))
    right_center = (0, 0.5 * (right_diameter + separation_distance))

    left_disc = disc(resolution, phys_size, left_diameter, left_center)
    right_disc = disc(resolution, phys_size, right_diameter, right_center)

    return left_disc ^ right_disc

resolution = 1  # number of pixels per unit length
phys_size = (130, 200)  # physical size of the entire image

left_diameter = 80
right_diameter = 60
separation_distance = 3
image = separated_discs(left_diameter, right_diameter, separation_distance)

measured_separation_distance = imageruler.minimum_length_void(image)
print(f"Measured separation distance: {measured_separation_distance:.6f}")
print(f"Actual separation distance:  {separation_distance:.6f}")

Measured separation distance: 4.401367
Actual separation distance:  3.000000

fig, ax = plt.subplots()
ax.imshow(image)
fig.savefig('separated_discs.png', dpi=150, bbox_inches='tight')

min_separation_distance = 1.0
max_separation_distance = 20.0
num_separation_distance = 11
separation_distances = np.linspace(min_separation_distance, max_separation_distance, num_separation_distance)
measured_separation_distance = np.zeros(num_separation_distance)

delta_separation_distance = (max_separation_distance - min_separation_distance) / (num_separation_distance - 1)
pixel_length = 1 / resolution
print(f"Δd = {delta_separation_distance:.6f}, Δp = {pixel_length:.6f}")

for i, separation_distance in enumerate(separation_distances):
    image = separated_discs(left_diameter, right_diameter, separation_distance)
    measured_separation_distance[i] = imageruler.minimum_length_void(image)
    err = abs(measured_separation_distance[i] - separation_distance) / separation_distance
    print(f"separation_distance:, {separation_distance:.6f}, {measured_separation_distance[i]:.6f}, {err:.6f}")

Δd = 1.900000, Δp = 1.000000
separation_distance:, 1.000000, 4.149414, 3.149414
separation_distance:, 2.900000, 4.401367, 0.517713
separation_distance:, 4.800000, 4.401367, 0.083049
separation_distance:, 6.700000, 6.416992, 0.042240
separation_distance:, 8.600000, 8.432617, 0.019463
separation_distance:, 10.500000, 10.448242, 0.004929
separation_distance:, 12.400000, 12.463867, 0.005151
separation_distance:, 14.300000, 14.479492, 0.012552
separation_distance:, 16.200000, 16.495117, 0.018217
separation_distance:, 18.100000, 18.510742, 0.022693
separation_distance:, 20.000000, 20.526367, 0.026318

fig, ax = plt.subplots()
ax.plot(separation_distances, measured_separation_distance, 'bo')
ax.plot(separation_distances, separation_distances, 'k-')
ax.set_xlabel('actual separation distance')
ax.set_ylabel('measured separation distance')

fig.savefig('separation_distance_measured_vs_actual.png', dpi=150, bbox_inches='tight')

This example is showing a ≈ 50% error when the separation is a little under 3 pixels, about a 1.5-pixel error bar.  This seems pretty good to me?
Recall that we only count "interior" pixels when looking at the difference of morphological transforms, in order exclude discretization artifacts.   This seems like it could give error bars of up to 2 pixels, since an interior pixel needs to have one pixel on either side of it.  Maybe there is a different way to define "interior" so that something 2 pixels wide is counted as having 1 "interior pixel", that would lower the error bar.

cc @mawc2019

The needed improvement here likely relates to the manner in which "ignored violations" are calculated. Currently, the algorithm ignores all border features, even if the feature is one or two pixels wide. It is probably better in general to only ignore borders for large features.
I have a version of this implemented here: https://github.com/mfschubert/topology/blob/main/src/tometrics/metrics.py#L340

Closed by #30


Quantum - When creating a folder with special characters downloading/copy pasting files errors

The name i have my folder was zéeuygfzeiuyf\\«««|@"²''\"&éeeeeeee. Can also not download these special folders as a whole.

Always remember to also include edit flow. When you have to implement any kind of validation on a create, the same validation should exist for the edit, otherwise it can be bypassed.


Support: Add a default 'self' binding that resolves to the current component instance

Description

This PR provides a default closure dependency name 'self' that can be used to resolve to $this component instance.
The most important use case is components that use the closure dependency system, but don't provide any custom binding. Sometimes we would like to use the current instance, but can't.
For instance there is, AFAIK, currently no way for someone to get the current Filament\Resources\Components\Tab instance in its badge method to easily reuse the query modification function there.
With this PR, you'd be able to write something like this:
namespace App\Filament\Resources\PlaceResource\Pages;

use App\Enums\PlaceStatus;
use App\Filament\Resources\PlaceResource;
use App\Models\Place;
use Filament\Resources\Components\Tab;

class ListPlaces extends ListRecords
{
    public function getTabs(): array
    {
        return [
            Tab::make('All'),
            Tab::make('Active')
                ->modifyQueryUsing(fn(Builder $query) => $query->whereIn('status', [
                    PlaceStatus::CONSIDERING,
                    PlaceStatus::ACTIVELY_LOOKING,
                    PlaceStatus::OK,
                ]))
                ->badge(fn(Tab $self) => $self->modifyQuery(Place::query())->count()),
        ];
    }
}

[x] Visual changes (if any) are shown using screenshots/recordings of before and after.

Code style

[x] composer cs command has been run.

Testing

[x] Changes have been tested.

Documentation

Will edit the docs website's pages related to parameters resolution

[ ] Documentation is up-to-date.

Each component can have an $evaluationIdentifier set to do this. Most components have this. For example, form components have $component. This class just needs its $evaluationIdentifier set to 'tab' instead. Please submit another PR for that if you want to see it.

I wouldn't mind doing so, but this would in all likelihood mean a lot of PRs across all packages that provide components where this would fix the issue once and for all "by default" (and for everyone, including 3rd-party packages) whilst allowing each component to still provide another name (or an override) if needed

I understand, but this is the pattern we have chosen right now. Also, self is a PHP keyword and could be confused with $this in a non-static function


Update to sbt/io 1.0.0-M1, use scala.sys.process rather than sbt process, setup Travis

This won't build until:

sbt/util gets published
A snapshot of sbt 0.13.10 is released

Travis boostrap.

Most of the changes are formatting or fixes to warnings.
The important changes are in:

build.sbt
project/*
JavacProcessLogger.scala (should there be overloads for the old methods?)
AggressiveCompile.scala (same question)
ScalaInstance.scala (I tried to get rid of some deprecated methods, but it looks like we need to keep some deprecated overloads)


Fix #15: Pass user options to writeReports method

@paul-barry-kenzan
Should we add this to the README.md?

@obuckley-kenzan
Updated the README with config options

@paul-barry-kenzan do you need a release ?

fixes #15

@obuckley-kenzan
Not necessary for my current work since coverage has been disabled for my project.


mean_squared_error function returns wrong values with certain input in Jupyter notebook/

I wrote my own function for calculating mean squared error between values of two arrays and it returned wrong values for one particular input (see code below) only . I also tried the same input with built-in MSE function from sklearn.metrics module and the output was the same. It only returns wrong values in Jupyter and works fine in other shells.
Here's the python code and the value 2.99 in the third print line is the one causing the problem:
import numpy as np
from sklearn.metrics import mean_squared_error
print(mean_squared_error(np.array([1, 2, 3]), np.array([0.9, 1.9, 2.9])))
print(mean_squared_error(np.array([1, 2, 3]), np.array([0.98, 1.98, 2.8])))
print(mean_squared_error(np.array([1, 2, 3]), np.array([0.99, 1.99, 2.99])))

This does not appear to concern jupyter or  jupyter_server. Closing.


remove distracting reference in "testing single concept per test"

This distracted me from the code at hand, so I suggest changing the text to be more neutral.

Thanks!

Thanks for being thoughtful!


WIP: Protect index

Add protected keyword to index output.

@LeandroRitter first and foremost check README. I suggest we wait with merge until we decide what to do with the reference sequence configuration.

Yes, agree, let me think and test it


Leaderboard/tests

This PR adds unit tests to the leaderboard project. I added bs-jest as a dependency.
Currently, this PR serves as a baseline to start writing more unit tests as functionality grows. As challenges are required and implemented for the leaderboard project, the tests for the points and metrics should be filled in. This PR also fixes a small bug in Challenges.

ci/circleci: lint is failing, will create another PR to solve this issue.


Adapting Json handling in ErrorHandling

As discussed. Also added some Configuration section convenience extensions.
Issues covered: #65, #67, #68

Cheers!


Working code for 2016 show

Pretty much the whole implementation of the runner in this pull request. I can break it up into a few smaller ones if desired. Mostly trying to get back to master, since I did a poor job syncing my branch with master during development.

Bump

Is that the binary you used? Did you have a problem running?

I found a binary in the repo.  You're not supposed to have binaries in a repo, since each system will built its own.  Normally binaries land in an ./out/ or ./bin/ directory that can be added to .gitignore

Ok, will move into an ignored ./bin directory. This can also be tweaked in PR #8 by providing the path to the proton_cli binary instead of copying it.

Got interesting "library not found" errors when running from the .bin directory. Ended up running cargo install on proton-cli, adding $HOME/.cargo/bin to my path, then assumed that the proton-cli binary could be found. This is cleaner anyway.


the link of 1.js is wrong

the link of 1.js is wrong , it should be https://github.com/libp2p/js-libp2p/blob/master/examples/transports/1.js

completed in https://github.com/libp2p/js-libp2p/pull/115


Reference ANN sstable indexes in case of ann hybrid search

pushed what i mean
not sure if the clear() is meaningful or outdated GC superstition


IBM Cloud install tutorial

IBM Cloud install tutorial
Wrote a detailed tutorial for installing Apache on the IBM Cloud. I've made it  step-by-step with pictures for easier understanding.
Hope it helps others !
Thanks!

This reads like an advert for IBM Cloud, and isn't (IMO) an appropriate use of the httpd documentation.

I'm going to close this, it's off-topic for httpd docs.

I'm going to close this, it's off-topic for httpd docs.


Refactoring of scopes

What was wrong?
How was it fixed?
To-Do

[ ] OPTIONAL: Update Spec if applicable
[ ] Clean up commit history

Codecov Report

Merging #139 (0e37628) into master (e14c087) will increase coverage by 0.05%.
The diff coverage is 93.42%.

@@            Coverage Diff             @@
##           master     #139      +/-   ##
==========================================
+ Coverage   83.37%   83.42%   +0.05%
==========================================
  Files          43       43
  Lines        2966     2981      +15
==========================================
+ Hits         2473     2487      +14
- Misses        493      494       +1

Impacted Files
Coverage Δ

semantics/src/traversal/contracts.rs
100.00% <ø> (ø)

semantics/src/traversal/module.rs
100.00% <ø> (ø)

semantics/src/traversal/expressions.rs
80.24% <66.66%> (+0.61%)
:arrow_up:

semantics/src/namespace/scopes.rs
94.51% <96.15%> (-0.67%)
:arrow_down:

semantics/src/namespace/types.rs
60.36% <100.00%> (-1.22%)
:arrow_down:

semantics/src/traversal/assignments.rs
96.87% <100.00%> (ø)

semantics/src/traversal/declarations.rs
95.65% <100.00%> (ø)

semantics/src/traversal/functions.rs
45.63% <100.00%> (-1.10%)
:arrow_down:

semantics/src/traversal/types.rs
100.00% <100.00%> (ø)

... and 1 more

Continue to review full report at Codecov.

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Bug. Multithreads does not work without explicit instructions from providers

Calling from a thread only works when I explicitly pass parameters like here:
import threading
import asyncio
from proxybroker import Broker

async def show(proxies):
    while True:
        proxy = await proxies.get()
        if proxy is None: break
        print('Found proxy: %s' % proxy)

def main():
    loop = asyncio.new_event_loop()
    asyncio.set_event_loop(loop)
    proxies = asyncio.Queue(loop=loop)
    providers = ['http://www.proxylists.net/', 'http://fineproxy.org/eng/fresh-proxies/']
    broker = Broker(proxies, timeout=8, providers=providers, loop=loop)
    tasks = asyncio.gather(
        broker.find(types=['HTTP', 'HTTPS'], lvl='High', limit=20),
        show(proxies))
    loop.run_until_complete(tasks)

threading.Thread(target=main).start()

If you call so:
broker = Broker(proxies, timeout=8, loop=loop)
that get:
C:\Users\user\Anaconda3\envs\scraper2\lib\site-packages\proxybroker\providers.py:78: DeprecationWarning: The object should be created from async function
  headers=get_headers(), cookies=self._cookies, loop=self._loop
C:\Users\user\Anaconda3\envs\scraper2\lib\site-packages\aiohttp\connector.py:730: DeprecationWarning: The object should be created from async function
  loop=loop)
C:\Users\user\Anaconda3\envs\scraper2\lib\site-packages\aiohttp\cookiejar.py:55: DeprecationWarning: The object should be created from async function
  super().__init__(loop=loop)

and proxies do not reach!

As far as i saw, when you try the CLI interface you are obblied to pass --types HTTP at least to make it work, so i expect that parameter to be also needed in the Broker().find() method used by that CLI.
You can the example here -> https://proxybroker.readthedocs.io/en/stable/#basic-code-example.
You can also note that such parameter is defined and required by the broker.find() method, so you can't call this a bug. https://github.com/constverum/ProxyBroker/blob/d21aae8575fc3a95493233ecfd2c7cf47b36b069/proxybroker/api.py#L142
    :param list types:
        Types (protocols) that need to be check on support by proxy.
        Supported: HTTP, HTTPS, SOCKS4, SOCKS5, CONNECT:80, CONNECT:25
        And levels of anonymity (HTTP only): Transparent, Anonymous, High
    :param data:
        (optional) String or list with proxies. Also can be a file-like
        object supports `read()` method. Used instead of providers

I've created an bug report in aiohttp referencing this issue as it seems to be an issue with aiohttp:
https://github.com/aio-libs/aiohttp/issues/4723


Testing, please ignore. (gbbijj)

This is a bug bounty test.. Please DO NOT APPROVE THIS! (gbbijj)

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.gbbijj jvxmv seems not to be a GitHub user. You need a GitHub account to be able to sign the CLA. If you have already a GitHub account, please add the email address used for this commit to your account.You have signed the CLA already but the status is still pending? Let us recheck it.


page: notification about gsoc

@EverVino I need to merge this ASAP, but please ping me if you find anything weird. thanks


Add contract changes to ARM repo for MFE inference group status

ARM (Control Plane) API Specification Update Pull Request

[!TIP]
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What's the purpose of this PR? Check the specific option that applies. This is mandatory!

[ ] New resource provider.
[ ] New API version for an existing resource provider. (If API spec is not defined in TypeSpec, the PR should have been created in adherence to OpenAPI specs PR creation guidance).
[x] Update existing version for a new feature. (This is applicable only when you are revising a private preview API version.)
[ ] Update existing version to fix OpenAPI spec quality issues in S360.
[ ] Convert existing OpenAPI spec to TypeSpec spec (do not combine this with implementing changes for a new API version).
[ ] Other, please clarify:

edit this with your clarification

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To merge this PR, you must go through the following checklist and confirm you understood
and followed the instructions by checking all the boxes:

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Microsoft.MachineLearningServices

Justification for the change -
This is a new product offering and we made changes to the status api to fit user needs and we want this change to go in before customers start using the status api heavily.
Also this "Get Group Status" api is not being actively used in prod right now. Attached below is the result for last one month for prod regions. There are 0 results.
https://dataexplorer.azure.com/clusters/viennaweu/databases/Vienna?query=H4sIAAAAAAAAA3VTa2%2FTMBT9vl%2Fh5Usb5K5dmAQUhrS1EZvY1tEHEkxVZZK71ii1PdvZqMSP5%2BbpdClf8ri%2B5%2Fj43OMELPmaGitHCT5Bk3PSeeYgBLNgbOfjUYINKxDxnG8BF2OsW%2FzsBoPgrHd62jv9MA%2BC4dm74eD9T79sN5Zpexgw6AVBC4D0SnJhV4LlmE6571rLVL0uKimT1zUNTynKXV3HZXEhuBSTx4skuZFr0%2FW%2B50fyKPGuxSNoEBGMQSVytwVhPf%2Bo3ydRYUC36YZ%2FgvLZL2agpvBPDjAg%2Fi952WCZhOL5DsUZxSIgx5EUlnFhiKfSJPGOqq57DRE3kHk0s2yryOema0zE7Y5P5%2FUcappRQZ%2BN7Zx4vBLWi2tlPaa42xZ1GbYGsmEmcyKSWy7WlXtkMb0Zut6F5uS4bLRersmVeLsUMcH07nV1dLAKzNjUBJAy1aJB0Zqh%2FfniATUxJJbdSnyZQ8v9LVjWb%2BstrXHO9DfAErtxnQV8DRb9RnWOfFr4g%2BHKezh%2F7DYCd4zOM5wtbaQQc9bzfOLGjZnNUpE3O2Kc71bZXXcv%2Fz6RGlNUVHJQHaK9vhZLfTFyhnrLGl2vt5DunuXQL9nvPtZ15FGHPxa1oDFGSWFghNPAi2czbV2jEl49y7zRzvCh4z%2B8XdLOEt%2BDpd9kGaeaWbyuyPB%2F7FmNRfWKaePC%2FMLthrwh3jSc3U%2FuZuFqNBmHwwdvX563JOPF9GJ%2BPbnL1upNsT4Nvy3C2Xx1FV6Mw%2BnMK8iK2uVk%2FKPgymd7KeNdASn32seURQcqBJSobPBKy98Q2db1pi5ltBoddZOge4mg5MpadQt2IzFq1VFo87y0IZg2dVCMOq28%2BwfK5CI4%2FgUAAA%3D%3D
let KustoCluster = 'viennatest';
let _endTime = datetime(2024-11-19T22:47:08Z);
let _startTime = datetime(2024-10-22T22:47:08Z);
let endpoint_name = '';
let group_name = '';
let pool_name = '';
let request_Id = '';
UnionOfAllLogs("Vienna", "InferenceDeployment")
// cluster(KustoCluster).database("Vienna").InferenceDeployment
//| where EnvNamespace !contains "pull"
| where PreciseTimeStamp > _startTime and PreciseTimeStamp <= _endTime
| where Container == "inference-deployment-api"
| where message has "Incoming request URL:"
| where Uri !has "Int" and Uri !has "int" and Uri !has "canary" and Uri !has "Canary" and Uri !has "eastus2euap" and Uri !has "centraluseuap"
| where Uri !has "deltaModels"
| where Uri !has "/meta/" and Uri !has "inferencedeployment/health" and Uri has "/getStatus"
| where RequestId  has iif(request_Id != "all", request_Id, "-")
| where PoolName != ""
| where isempty(endpoint_name) or EndpointName contains endpoint_name
| where isempty(pool_name) or PoolName contains pool_name
| where isempty(group_name) or GroupName contains group_name
//| extend ResponseCode = toint(split(split(message,':[')[3],']')[0])
//| extend Duration = split(split(message,':[')[4],']')[0]
| parse message with * "RESPONSE_CODE:[" ResponseCode "] DURATION:[" Duration "] REQUEST_HEADERS" * "REQUEST_BODY:[" RequestBody "] RESPONSE_HEADERS" * "RESPONSE_BODY:[" ResponseBody "]"
| project PreciseTimeStamp, RequestId,PoolName, GroupName, EndpointName, HttpMethod, Duration,ResponseCode,RequestBody,ResponseBody,Uri, message

Please get the breaking change approval first and after that put the PR back in the review queue.

/azp run

@ritujhams The breaking change label has to be added by someone in the Breaking Change approval board.
Please check - https://aka.ms/brch

/azp run

/azp run


feat: add ability to override wasm_file

hi @ndonfris,
Coming over from https://github.com/NixOS/nixpkgs/pull/320463, I've tried symlinking but that doesn't work.
I think adding the ability to pre-define wasm_file (via environment variables) should work.

Tested building package in nix with:
...
    buildPhase = ''
      runHook preBuild

      export wasm_file=$(find node_modules -type f -a -name tree-sitter-fish.wasm | xargs realpath)
      yarn run sh:build-wasm
      yarn run sh:build-time
      yarn --offline compile
      yarn run sh:relink

      runHook postBuild
    '';
...

That looks like a great solution to the nix related issue.
Have had a lot of interest in this project from nix users so I'm trying to learn more about the project. I'm not sure that I understand what the lsp's file structure looks like after you install the package through nix?
Also, is the buildPhase using fish? We could maybe add similar setups for the other two scripts (sh:build-completions and sh:build-logs).

I've only recently started using nix so I'm not an expert/could definitely be wrong.
This is the file structure of the nix store (/nix/store/q2lyicwcmypgpb18cx8ra3agaiyz81mp-fish-lsp-unstable-2024-07-22)
❯ eza --classify --tree --level=5 --ignore-glob "node_modules"
./
├── bin/
│  └── fish-lsp*
├── libexec/
│  └── fish-lsp/
│     └── deps/
│        └── fish-lsp/
│           ├── bin/
│           ├── CODE_OF_CONDUCT.md
│           ├── docs/
│           ├── fish-lsp -> deps/fish-lsp
│           ├── fish_files/
│           ├── jest.config.js
│           ├── LICENSE.md
│           ├── logs.txt
│           ├── out/
│           ├── package.json
│           ├── README.md
│           ├── renovate.json
│           ├── scripts/
│           ├── src/
│           ├── test-data/
│           ├── tree-sitter-fish.wasm
│           ├── tsconfig.eslint.json
│           ├── tsconfig.jest.json
│           ├── tsconfig.json
│           └── yarn.lock
├── share/
│  └── fish/
│     └── vendor_completions.d/
│        └── fish-lsp.fish
└── tarballs/
   └── fish-lsp-unstable-2024-07-22.tgz

I've excluded the node_modules to make it shorter but there is a node_modules at ./libexec/fish-lsp/node_modules/ and ./libexec/fish-lsp/deps/fish-lsp/node_modules/

./libexec/fish-lsp/node_modules/ seems to have all the yarn packages installed there
./libexec/fish-lsp/deps/fish-lsp/node_modules/ is a symlink to another nix store at /nix/store/m7gcrn7ymv261ypl44j2q2c8h5m08gnk-fish-lsp-modules-unstable-2024-07-22/deps/fish-lsp/node_modules/ (which is empty)

I've tested some improvements to buildPhase and postInstall
    buildPhase = ''
      runHook preBuild

      yarn run sh:build-time
      yarn run sh:build-logs

      # yarn run sh:build-wasm
      wasm_file=$(find node_modules -type f -a -name tree-sitter-fish.wasm)
      cp -f $wasm_file ./deps/fish-lsp

      yarn --offline compile
      yarn run sh:relink
      # yarn run sh:build-completions

      runHook postBuild
    '';
    postInstall = ''
      node $out/libexec/fish-lsp/deps/fish-lsp/out/cli.js complete >fish-lsp.fish
      installShellCompletion fish-lsp.fish

      wrapProgram "$out/bin/fish-lsp" \
        --set-default fish_lsp_logfile "/tmp/fish_lsp_logs.txt"
    '';

I believe buildPhase is using bash or sh.
yarn run sh:build-completions fails because it cannot write in the user's home directory. Instead it seems like I need to use installShellCompletion
I've added yarn run sh:build-logs which works but logging still fails because the file is read-only (everything in the nix store is immutable during runtime)

I greatly appreciate the detailed response you provided. It has clarified so many points for me.
I was primarily asking about the other two scripts because the yarn run postinstall hook appears to almost perfectly duplicate the operations needed here. However, after gaining a better understanding of the requirements, I think we can just use yarn run setup to simplify the first couple operations.

setup script is called first in postinstall. Once dependencies are included in the workspace, this script groups together all steps that can/should come before the compile script.

I also think a revision should take place on the variable name wasm_file. Since it now relies on the current installation environment shell, renaming to something like fish_wasm_file would help avoid possible errors/confusion from non nixOS users.
Let me know if this config works for you:
    buildPhase = ''
      runHook preBuild

      export fish_wasm_file=$(find node_modules -type f -a -name tree-sitter-fish.wasm | xargs realpath)
      yarn run setup

      yarn --offline compile
      yarn run sh:relink

      runHook postBuild
    '';
    postInstall = ''
      $out/bin/fish-lsp complete >fish-lsp.fish
      installShellCompletion fish-lsp.fish
    '';

If using the postInstall hook to install the completions causes problems, feel free to remove it.

The --help flag includes an example of how to create the completions so it's not too important.

Regarding future changes that I discovered from messing with this solution, I'm going to try to make the default logging behavior for the server opt-in by defining the variable fish_lsp_logfile and removing the fish-lsp start --enable/--disable logging key. This would avoid the opt-out workarounds the project currently enforces. When logging is not enabled to a file, it will still be available from most language clients because of connection.console.

I greatly appreciate the detailed response you provided. It has clarified so many points for me.
I was primarily asking about the other two scripts because the yarn run postinstall hook appears to almost perfectly duplicate the operations needed here. However, after gaining a better understanding of the requirements, I think we can just use yarn run setup to simplify the first couple operations.

setup script is called first in postinstall. Once dependencies are included in the workspace, this script groups together all steps that can/should come before the compile script.

I am adding a revision to the variable name wasm_file. Since it now relies on the current installation environment shell, renaming to a more descriptive filename like fish_wasm_file would help avoid possible errors/confusion from non nixOS users.
Let me know if this config works for you:
    buildPhase = ''
      runHook preBuild

      export fish_wasm_file=$(find node_modules -type f -a -name tree-sitter-fish.wasm | xargs realpath)
      yarn run setup

      yarn --offline compile
      yarn run sh:relink

      runHook postBuild
    '';
    postInstall = ''
      $out/bin/fish-lsp complete >fish-lsp.fish
      installShellCompletion fish-lsp.fish
    '';

If using the postInstall hook to install the completions causes problems, feel free to remove it.

The --help flag includes an example of how to create the completions so it's not too important.

Regarding future changes that I discovered from messing with this solution, I'm going to try to make the default logging behavior for the server opt-in by defining the variable fish_lsp_logfile and removing the fish-lsp start --enable/--disable logging key. This would avoid the opt-out workarounds the project currently enforces. When logging is not enabled to a file, it will still be available from most language clients because of connection.console.

Tested and working with:
    buildPhase = ''
      runHook preBuild

      export fish_wasm_file=$(find node_modules -type f -a -name tree-sitter-fish.wasm | xargs realpath)
      yarn setup

      yarn --offline compile
      yarn run sh:relink

      runHook postBuild
    '';
    postInstall = ''
      makeWrapper ${pkgs.nodejs}/bin/node "$out/bin/fish-lsp" \
        --add-flags "$out/libexec/fish-lsp/deps/fish-lsp/out/cli.js"

      installShellCompletion --cmd fish-lsp \
        --fish <($out/bin/fish-lsp complete --fish)

      wrapProgram "$out/bin/fish-lsp" \
        --set-default fish_lsp_logfile "/tmp/fish_lsp_logs.txt"
    '';

Looks like $out/bin/fish-lsp doesn't work during both buildPhase and postInstall because of how the files are symlinked. Strangely works are everything has been built though.
I've looked at other nixpkg packages like (https://github.com/NixOS/nixpkgs/blob/443648fe924b0f2d27531dc2444d90c1377def43/pkgs/servers/mjolnir/default.nix#L45) and it seems like using makeWrapper might be the preferred way to do things.
We could probably remove wrapProgram if you can get the opt-in logging out.

Looks like $out/bin/fish-lsp doesn't work during both buildPhase and postInstall (with the bin fish-lsp file ../out/cli.js in the repo) because of how the files are symlinked. Strangely works after everything has been built though.

This might be still related to the logs file dependency? I checked out that link, and would guess that fish is trying to read the default logs file before the last line of your most recent nixpkg.
Will continue looking into it though and get back to you.

We could probably remove wrapProgram if you can get the opt-in logging out.

I will do my best to get that done soon! If you want to work on it I'm considering pushing without githooks for the intial logger.ts file (since its used in many places).
bash-lsp's solution for a logger is pretty good, and probably how the resulting changes will be structured. The current solution uses an inferier singleton pattern IMO

I don't think it's related to the logs, this is the error I get
/nix/store/h9vryg2m4m0cm11mxq1a0r6mm7029fln-fish-lsp-unstable-2024-07-25/bin/fish-lsp: cannot execute: required file not found

Unsure about that error message.
Still think that it could log file related, since the file could be required given the old logging version.
I added a PR (#49) for the opt-in logging feature requested.
Would you mind rebasing the PR #49 over your local clone of this PR and testing if that resovles the issue?


the horizontal chords + split keys toggles dont seem to save when the site is reopened

that's about it :! i feel much cosier playing with horizontal chords when i'm on a keyboard, so it'd be much appreciated if these settings would save too :]

Should be fixed now!


Quality difference between <IP_ADDRESS> stable and <IP_ADDRESS> why?

Naamloos2 is made with stable version <IP_ADDRESS> from staxrip and nvenc 4.32
Naamloos3 is made with beta version <IP_ADDRESS> from staxrip and nvenc 4.32
Why is there such a big difference in quality?
The size of the file should be exactly simular, however it isn't even close to simular.

This is the original.
To have some things to compare.
Was just wondering why <IP_ADDRESS> works at half the speed of <IP_ADDRESS> but has way better quality.
NVEncC64 --master-display G(13250,34500)B(7500,3000)R(34000,16000)WP(15635,16450)L(10000000,1) --max-cll 1000,640 --sar %target_sar% --vbr 25000 --codec h265 --preset quality --output-depth 10 --lookahead 32 --output-buf 128 --cuda-schedule auto --no-b-adapt --no-i-adapt --videoformat pal --max-bitrate 40000 --vbv-bufsize 160000 --aq --colormatrix bt2020nc --colorprim bt2020 --transfer smpte2084 --mv-precision q-pel --chromaloc 2 -i "%script_file%" -o "%encoder_out_file%"
This was the string used.
and here you have a link to the 3 samples
https://drive.google.com/drive/folders/16I0JHWxabP7suokpuIau6khVd4e7DCzq?usp=sharing
Thx for taking the time to explain this.
Kind regards,
Pieter Cooijmans

The version of StaxRip in itself has literally no effects on the encoding speed or the quality of the encode. If you are using the same version of NVENC with the same parameters, your issue may comes from your pre-processing script ( avisynth, vapoursynth, etc. )

LoadCPlugin("E:\Extra
Programs\Staxrip.<IP_ADDRESS>.Beta\Apps\Plugins\both\ffms2\ffms2.dll")
FFVideoSource("C:\Push the Tempo\La La Land (2016) Untouched sample
Original sample.mkv", colorspace = "YV12",
cachefile = "C:\Push the Tempo\La La Land (2016) Untouched
sample Original sample_temp\La La Land (2016) Untouched sample Original
sample.ffindex")
this is version <IP_ADDRESS>
and
LoadPlugin("E:\Extra
Programs\StaxRip-x64-<IP_ADDRESS>-stable\Apps\Plugins\both\ffms2\ffms2.dll")
FFVideoSource("C:\Push the Tempo\La La Land (2016) Untouched sample
Original sample.mkv", colorspace = "YV12",
cachefile = "C:\Push the Tempo\La La Land (201..._temp\La La
Land (2016) Untouched sample Original sample.ffindex")
this is version <IP_ADDRESS>
So what's the issue if there is no difference?
Many thanks for looking at this,
Kind Regards,
Pieter Cooijmans
Op do 14 mrt. 2019 om 17:35 schreef Marc-Olivier Fortin <
<EMAIL_ADDRESS>
The version of StaxRip in itself has literally no effects on the encoding
speed or the quality of the encode. If you are using the same version of
NVENC with the same parameters, your issue may comes from your
pre-processing script ( avisynth, vapoursynth, etc. )
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/Revan654/staxrip/issues/89#issuecomment-472952206,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AdX5NKhQqJwgXY6l3pLu07fXFfcAS0_Gks5vWnpEgaJpZM4b0nB5
.

Do note that there is an api update on 4.32 which goes from 8.1 to 9.0
hopefully this will shed some light into it.
Kind Regards,
Pieter Cooijmans
Op do 14 mrt. 2019 om 18:25 schreef Pieter Cooijmans<EMAIL_ADDRESS>
:

LoadCPlugin("E:\Extra
Programs\Staxrip.<IP_ADDRESS>.Beta\Apps\Plugins\both\ffms2\ffms2.dll")
FFVideoSource("C:\Push the Tempo\La La Land (2016) Untouched sample
Original sample.mkv", colorspace = "YV12",
cachefile = "C:\Push the Tempo\La La Land (2016) Untouched
sample Original sample_temp\La La Land (2016) Untouched sample Original
sample.ffindex")
this is version <IP_ADDRESS>
and
LoadPlugin("E:\Extra
Programs\StaxRip-x64-<IP_ADDRESS>-stable\Apps\Plugins\both\ffms2\ffms2.dll")
FFVideoSource("C:\Push the Tempo\La La Land (2016) Untouched sample
Original sample.mkv", colorspace = "YV12",
cachefile = "C:\Push the Tempo\La La Land (201..._temp\La La
Land (2016) Untouched sample Original sample.ffindex")
this is version <IP_ADDRESS>
So what's the issue if there is no difference?
Many thanks for looking at this,
Kind Regards,
Pieter Cooijmans
Op do 14 mrt. 2019 om 17:35 schreef Marc-Olivier Fortin <
<EMAIL_ADDRESS>
The version of StaxRip in itself has literally no effects on the encoding
speed or the quality of the encode. If you are using the same version of
NVENC with the same parameters, your issue may comes from your
pre-processing script ( avisynth, vapoursynth, etc. )
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/Revan654/staxrip/issues/89#issuecomment-472952206,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AdX5NKhQqJwgXY6l3pLu07fXFfcAS0_Gks5vWnpEgaJpZM4b0nB5
.

1 Log file of version x.<IP_ADDRESS>.0 Stable and 1 Log file of version <IP_ADDRESS>
beta.
Op do 14 mrt. 2019 om 18:27 schreef Pieter Cooijmans<EMAIL_ADDRESS>
:

Do note that there is an api update on 4.32 which goes from 8.1 to 9.0
hopefully this will shed some light into it.
Kind Regards,
Pieter Cooijmans
Op do 14 mrt. 2019 om 18:25 schreef Pieter Cooijmans <
<EMAIL_ADDRESS>
LoadCPlugin("E:\Extra
Programs\Staxrip.<IP_ADDRESS>.Beta\Apps\Plugins\both\ffms2\ffms2.dll")
FFVideoSource("C:\Push the Tempo\La La Land (2016) Untouched sample
Original sample.mkv", colorspace = "YV12",
cachefile = "C:\Push the Tempo\La La Land (2016) Untouched
sample Original sample_temp\La La Land (2016) Untouched sample Original
sample.ffindex")
this is version <IP_ADDRESS>
and
LoadPlugin("E:\Extra
Programs\StaxRip-x64-<IP_ADDRESS>-stable\Apps\Plugins\both\ffms2\ffms2.dll")
FFVideoSource("C:\Push the Tempo\La La Land (2016) Untouched sample
Original sample.mkv", colorspace = "YV12",
cachefile = "C:\Push the Tempo\La La Land (201..._temp\La
La Land (2016) Untouched sample Original sample.ffindex")
this is version <IP_ADDRESS>
So what's the issue if there is no difference?
Many thanks for looking at this,
Kind Regards,
Pieter Cooijmans
Op do 14 mrt. 2019 om 17:35 schreef Marc-Olivier Fortin <
<EMAIL_ADDRESS>
The version of StaxRip in itself has literally no effects on the
encoding speed or the quality of the encode. If you are using the same
version of NVENC with the same parameters, your issue may comes from your
pre-processing script ( avisynth, vapoursynth, etc. )
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/Revan654/staxrip/issues/89#issuecomment-472952206,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AdX5NKhQqJwgXY6l3pLu07fXFfcAS0_Gks5vWnpEgaJpZM4b0nB5
.

https://www.diffchecker.com/ is handy to check the differences in the log
files.
Op do 14 mrt. 2019 om 18:40 schreef Pieter Cooijmans<EMAIL_ADDRESS>
:

1 Log file of version x.<IP_ADDRESS>.0 Stable and 1 Log file of version
<IP_ADDRESS> beta.
Op do 14 mrt. 2019 om 18:27 schreef Pieter Cooijmans <
<EMAIL_ADDRESS>
Do note that there is an api update on 4.32 which goes from 8.1 to 9.0
hopefully this will shed some light into it.
Kind Regards,
Pieter Cooijmans
Op do 14 mrt. 2019 om 18:25 schreef Pieter Cooijmans <
<EMAIL_ADDRESS>
LoadCPlugin("E:\Extra
Programs\Staxrip.<IP_ADDRESS>.Beta\Apps\Plugins\both\ffms2\ffms2.dll")
FFVideoSource("C:\Push the Tempo\La La Land (2016) Untouched sample
Original sample.mkv", colorspace = "YV12",
cachefile = "C:\Push the Tempo\La La Land (2016) Untouched
sample Original sample_temp\La La Land (2016) Untouched sample Original
sample.ffindex")
this is version <IP_ADDRESS>
and
LoadPlugin("E:\Extra
Programs\StaxRip-x64-<IP_ADDRESS>-stable\Apps\Plugins\both\ffms2\ffms2.dll")
FFVideoSource("C:\Push the Tempo\La La Land (2016) Untouched sample
Original sample.mkv", colorspace = "YV12",
cachefile = "C:\Push the Tempo\La La Land (201..._temp\La
La Land (2016) Untouched sample Original sample.ffindex")
this is version <IP_ADDRESS>
So what's the issue if there is no difference?
Many thanks for looking at this,
Kind Regards,
Pieter Cooijmans
Op do 14 mrt. 2019 om 17:35 schreef Marc-Olivier Fortin <
<EMAIL_ADDRESS>
The version of StaxRip in itself has literally no effects on the
encoding speed or the quality of the encode. If you are using the same
version of NVENC with the same parameters, your issue may comes from your
pre-processing script ( avisynth, vapoursynth, etc. )
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/Revan654/staxrip/issues/89#issuecomment-472952206,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AdX5NKhQqJwgXY6l3pLu07fXFfcAS0_Gks5vWnpEgaJpZM4b0nB5
.

Maybe try using the same DLL's ( ffms2.dll )

Ok I ripped the ffms2 completely from <IP_ADDRESS> and put it in <IP_ADDRESS> and now I have exactly the same results I used to have with <IP_ADDRESS> so issue seems fixed.....question remaining is what's the best version?
Is it 2.23.1 of the official github ffms or 2.30 from someone else?
Could you please share your thoughts on this?
Many Thanks,
Pieter Cooijmans

It's just for my knowledge 2.30 of ffms2, no clue where you got that from since the releases only go to 2.23.1

That I don't know.. And since you are using NVENC you can use HW decode as well.. I'm pretty sure @Revan654 updated StaxRip for this.. ( probably in the options section of NVENC encoder --> https://staxrip2.readthedocs.io/en/latest/screenshots.html#nvenc, decoder: avisynth... ).
Another option would be to use DGIndexNV / DGDecNV which is also a GPU Accelerated Decoder but requires a licence ( I'm sure you can find one on internet though )

2.30 might only be a typo... since in the doc it refers to the real repo

This is not the case, and here is the proof:

If you look at the github page of FFMS2, the latest release was on October 2016. My guess is that @Revan654 compiled ( himself ) the latest code because there are still progress made in the source code but no new release yet.

ok thx for the info, no clue what to choose yet, I'll guess I'll just wait till @Revan654 comes with a decent version.
You can close this issue, many thanks for all the fast responses.
Kind Regards,
Pieter Cooijmans

I cannot close this issue but you can :) I'm no admin here


[FLINK-7922][Table API]make FlinkTypeFactory override leastRestrictive to work with Nullable composite types while using super class method to handle basic type

What is the purpose of the change
This pull request address usage of multiple composite type operation such as UNION or CASE WHEN where incorrect output RelDataType was generated due to the fact that Calcite automatically resolve result into basic type or Generic Relation Data Type with false nullability.
Brief change log
Changed leastRestrictive function to resolve types with all identical typeinfomation directly instead of calling the super class method.
Throw exception on ANY as we only support ANY with exact same types across all operands.
Invoke super class if not correctly resolved.
Verifying this change
Integration test and unit test included to address UNION ALL and CASE WHEN.
Does this pull request potentially affect one of the following parts:
no
Documentation
no

Thanks for the PR @walterddr.
I'll add the test for the Streaming API and merge it.
Thanks, Fabian


PHP: fix InterceptorChannel not autoload by composer

Try to fix #15387.

Hi @mehrdada . I remember Internal\ directory is created for the purpose of hiding the InterceptorChannel. Thus I guess you prefer keep this directory.
Another solution is move InterceptChannel.php out of Internal\ directory. By doing so, none code need to by modified.


Spyder 4.1.5 - disable warnings

There is currently no way to disable warnings (apparently).
I'm going nuts, I have an application with thousands rows of code and Spyder prints million of rows because of useless warnings.
Using simple python syntax this should fix the problem but it doesn't:
warnings.filterwarnings("ignore")
Can you please fix your application?
Thanks

https://xbuba.com/questions/46568959
"Tools > Preferences > Editor > Code Introspection/Analysis"
This doesn't exist anymore.
Now, can somebody add something in plain English called "Enable/Disable warnings"?

Hi @andrea83ny to disable the warnings you can go to the Source menu and uncheck Show code style warnings and Show docstring style warnings. Also, there is an option in the Preferences dialog to disable basic linting of the files. For that go to Tools > Preferences > Completion and linting > Linting and uncheck Enable basic linting:
Source menu

Preferences dialog

Hope this info helps navigate the config available :)

Under "Source" the only option I have enabled is "Show code folding". Hence, the expectation is that if "Shoe code style warnings" is disabled that no warnings should be displayed in the console. Right?
I also unchecked the option "Enable basic lintining" and I still get all the warnings.
Thanks in advance for your help

Oh I misunderstood, you are trying to disable warnings in the IPython Console (the config I gave is for warnings in the Editor). I think that using
import warnings
warnings.filterwarnings("ignore")

should work as you say. Are you running those lines directly on the IPython Console or at the start of the code you are running? @impact maybe you can have some suggestions regarding this one?

I have a python application that imports different other modules I wrote.
However, the very first thing the script does is to import os, import sys, and that's also where I have

import warnings
warnings.filterwarnings("ignore")

however, I keep getting all the warnings inside the console :(

Could you give us an example code snippet to reproduce this @andrea83ny ? I'm trying running this (which prints a DepreciationWarning):
import numpy as np
np.random.random_integers(0, 1000, 1000)

but after I add the lines to suppress warnings the message is not printed anymore:

I have a python application that imports different other modules I wrote.
However, the very first thing the script does is to import os, import sys, and that's also where I have

import warnings
warnings.filterwarnings("ignore")

however, I keep getting all the warnings inside the console :(

I can think of two explainations:

Some module you are importing is resetting the warning filter
What you are seeing are not "real" python warnings. What I mean is that if you do:

print("Warning: something went wrong")

This is not a warning but a print, as far as python is concerned.
Could you give a reproducible short example where warnings.filterwarnings("ignore") doesn't disables warnings? Without that we will not be able to help you.

You're actually write, there were some other modules that later in the code were changing the status of the warnings filter (in my case such module was cvxpy). Thanks for your help, much appreciated. I'm a big fan and full time user of Spyder!

Glad you figure it out @andrea83ny ! and thanks for the feedback here @impact much appreciated :)
Closing this one then


feat: add pure variant of toClass

Feature request to add a pure variant of toClass that extends React.PureComponent instead of just React.Component - either as an optional argument to toClass or a separate method, e.g., toPureClass.

@AndersDJohnson I think you can compose in the pure HOC to get the desired affect.

@GollyJer True, though it wouldn't use the native React.PureComponent which might be slightly preferable to pure if only to reduce bundle size, assuming the behavior is identical.

What is the usecase for toClass? Just to allow refs and tests.
It some kind of hack enhancer, and very rarely used.

See https://github.com/acdlite/recompose/issues/251 for discussion of using native PureComponent.


Remove domains

Fixes a problem where expected EventEmitter-related throws are
impossible to test, because the domain hijacks the 'error' event.
Of course, this means that asynchronous unexpected throws will always be
assigned to the global root TAP object, but... what can you do?  If
people complain, we can try to figure out something clever using
continuation-local-storage or something.
Ugh.  Domains.  The not-quite-worst-possible solution to any problem,
which always ends up regrettably.
I am, as always, truly and deeply sorry for inflicting this feature on
Node.js

Apology in the form of removing tap's use of domains accepted.
As for using CLS... please make it opt-in if you do use it. Maybe it's just bad luck, but CLS seems to offer stacktrace obfuscation as a bonus feature, which isn't really what you want when debugging a failing test.

As for using CLS... please make it opt-in if you do use it. Maybe it's just bad luck, but CLS seems to offer stacktrace obfuscation as a bonus feature, which isn't really what you want when debugging a failing test.

Good to know!  Mostly, I just think that the async throw tracking is kind of a shame to lose.  It still tracks the thrown error, of course, just catches it at the top level instead of closer to its origin.


Can we cache the makeStyles internal

Hi Griffel experts!
Recently we noticed that the makeStyles API is the bottleneck of a component runtime cost. So currently we cached the hooks result via useMemo. We looked through the source code of makeStyles and find it seems doesn't cache the styles internal. Since the API can only be called in the file root level and the result is static and time consuming, why not cache the result internal?

So currently we cached the hooks result via useMemo. We looked through the source code of makeStyles and find it seems doesn't cache the styles internal. Since the API can only be called in the file root level and the result is static and time consuming, why not cache the result internal?

@Leolewin I don't follow what you're caching in a React component. After the first expensive pass, a hook returned by makeStyles() will do nothing:
https://github.com/microsoft/griffel/blob/f134bc6056599a78cf27b71dec854224a162ee22/packages/core/src/makeStyles.ts#L30-L60
Can you please clarify WDYM?

Anyway, yes, makeStyles() and makeResetStyles() are expensive as any other CSS-in-JS, that's why AOT and CSS extraction should be used it in production.

So currently we cached the hooks result via useMemo. We looked through the source code of makeStyles and find it seems doesn't cache the styles internal. Since the API can only be called in the file root level and the result is static and time consuming, why not cache the result internal?

@Leolewin I don't follow what you're caching in a React component 🤔 After the first expensive pass, a hook returned by makeStyles() will do nothing:
https://github.com/microsoft/griffel/blob/f134bc6056599a78cf27b71dec854224a162ee22/packages/core/src/makeStyles.ts#L30-L60
Can you please clarify WDYM?
Anyway, yes, makeStyles() and makeResetStyles() are expensive as any other CSS-in-JS, that's why AOT (that removes computation cost) and CSS extraction should be used it in production.

Hi @layershifter
Sorry for the late reply and the misunderstanding caused by the issue description.
At very beginning, I fond the makeStyles API has large runtime cost. So I tried to use React.useMemo API to cache the styles returned by hook like:
const useStyles = makeStyles({ root: {color: 'red'}});

const Component = (props) => {
    const styles = React.useMemo(() => useStyles());
    // ...
}

But as the codes you mentioned, the large styles computation and stylesheet insertion is just happened in the first time been called. In following re-render time the styles result is get and returned directly from the closure variables. So it has almost zero runtime cost and useMemo will increase the time consuming in this case.
Thanks for your help to resolve my puzzles. Will close this issue.


Add code coverage report + badge

https://about.codecov.io/blog/code-coverage-for-android-development-using-kotlin-jacoco-github-actions-and-codecov/

Due to a bug in versions of the Kotlin compiler < 1.5, it is necessary to force an upgrade to Jacoco 0.8.7
"Unexpected SMAP line: *S KotlinDebug"

https://youtrack.jetbrains.com/issue/KT-44757
https://github.com/jacoco/jacoco/issues/1155


Does it support SFTP?

Hi
I have a running SSH server that supports SFTP. Would this work?

Yep! Any formally supported SFTP server should be accessible.

Thanks for the reply. It looks like there is not a way to provide  a key file for SFTP. Do you plan to support it?

I initially hadn't but the base package that is used for the connection does provide key file functionality. I'll take a look at adding that, as that shouldn't be an issue to implement


FontAwesomeImage broken

Hello there
I just upgraded to version 5.15.4 and now the FontAwesomeImage seems to be broken. As seen on the screenshot below, it just displays weird symbols (the raw ascii code I assume?).

Tested with .NET Framework 4.6.1 and .NET Core 5 on a Windows IoT device.
The Icon I used for testing is SolidHiking but it seems as it does not work for every other icon too.
Thanks for fixing and thank you for this awesome repository :D

A new version has been published on nuget and will be available in the next few hours. Thanks for reporting! c:


Quick review of some renaming in prep for adding RS pull into this workflow

Yo, KW!
Here's a mindless PR. I'm just making room to move the remote sensing pull over from our Landsat-C2-SRST repo to satisfy #8 now that we have a functioning pull with new masks. All this really means is that I've renamed a bunch of stuff so that I can plug it in at targets group -b-.
So, all that should be happening is naming convention changes (from b->c, c->d, ..., e->f) across the board.
The only other thing is the tiniest fix that happens on lines 70, 81, 118... etc in c_historical_RS_data_collation/src/combine_metadata_with_pulls.R where I fix an if statement so I actually get data spit out of this pipeline.
This is unlikely to run as I've probably missed a few renames, so really, this is the most mindless PR ask ever.
You're the best.

Thank you KW!


New Endpoint: <playlist_id>/analysis/popularity

Create a new API endpoint to analyze the popularity of songs in a playlist either a.) over time/course of playlist, or b.) as a distribution/density function similar to loudness or duration or tempo.
Required Params: Spotify Playlist ID Number
Headers: Authorization: <access_token>
Route: <playlist_id>/analysis/lyrics
Return Type: JSON Object
Format: {word1: 40, word2: 19, word3: 87, ... }
The data can be visualized with Charts.JS as a line chart to display the data.

No longer in development - efficiency/performance issues dictate all analysis stays within one route


returned non-zero exit status 1. RuntimeError: _th_or not supported on CUDAType for Bool

Traceback (most recent call last):
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/tools/train_net.py", line 201, in
main()
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/tools/train_net.py", line 194, in main
model = train(cfg, args.local_rank, args.distributed)
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/tools/train_net.py", line 94, in train
arguments,
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/maskrcnn_benchmark/engine/trainer.py", line 72, in do_train
for iteration, (images, targets, _) in enumerate(data_loader, start_iter):
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 582, in next
return self._process_next_batch(batch)
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 608, in _process_next_batch
raise batch.exc_type(batch.exc_msg)
IndexError: Traceback (most recent call last):
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/utils/data/_utils/worker.py", line 99, in _worker_loop
samples = collate_fn([dataset[i] for i in batch_indices])
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/utils/data/_utils/worker.py", line 99, in
samples = collate_fn([dataset[i] for i in batch_indices])
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/utils/data/dataset.py", line 85, in getitem
return self.datasets[dataset_idx][sample_idx]
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/maskrcnn_benchmark/data/datasets/coco.py", line 94, in getitem
target = target.clip_to_image(remove_empty=True)
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/maskrcnn_benchmark/structures/bounding_box.py", line 223, in clip_to_image
return self[keep]
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/maskrcnn_benchmark/structures/bounding_box.py", line 208, in getitem
bbox.add_field(k, v[item])
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/maskrcnn_benchmark/structures/segmentation_mask.py", line 555, in getitem
selected_instances = self.instances.getitem(item)
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/maskrcnn_benchmark/structures/segmentation_mask.py", line 464, in getitem
selected_polygons.append(self.polygons[i])
IndexError: list index out of range
index created!
Traceback (most recent call last):
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/tools/train_net.py", line 201, in
main()
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/tools/train_net.py", line 194, in main
model = train(cfg, args.local_rank, args.distributed)
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/tools/train_net.py", line 94, in train
arguments,
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/maskrcnn_benchmark/engine/trainer.py", line 84, in do_train
loss_dict = model(images, targets)
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in call
result = self.forward(*input, **kwargs)
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/nn/parallel/distributed.py", line 376, in forward
output = self.module(*inputs[0], **kwargs[0])
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in call
result = self.forward(*input, **kwargs)
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/apex-0.1-py3.7-linux-x86_64.egg/apex/amp/_initialize.py", line 197, in new_fwd
**applier(kwargs, input_caster))
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/maskrcnn_benchmark/modeling/detector/generalized_rcnn.py", line 52, in forward
x, result, detector_losses = self.roi_heads(features, proposals, targets)
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in call
result = self.forward(*input, **kwargs)
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/maskrcnn_benchmark/modeling/roi_heads/roi_heads.py", line 26, in forward
x, detections, loss_box = self.box(features, proposals, targets)
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in call
result = self.forward(*input, **kwargs)
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/maskrcnn_benchmark/modeling/roi_heads/box_head/box_head.py", line 43, in forward
proposals = self.loss_evaluator.subsample(proposals, targets)
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/maskrcnn_benchmark/modeling/roi_heads/box_head/loss.py", line 111, in subsample
img_sampled_inds = torch.nonzero(pos_inds_img | neg_inds_img).squeeze(1)
RuntimeError: _th_or not supported on CUDAType for Bool
Traceback (most recent call last):
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/tools/train_net.py", line 201, in
main()
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/tools/train_net.py", line 194, in main
model = train(cfg, args.local_rank, args.distributed)
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/tools/train_net.py", line 94, in train
arguments,
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/maskrcnn_benchmark/engine/trainer.py", line 84, in do_train
loss_dict = model(images, targets)
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in call
result = self.forward(*input, **kwargs)
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/nn/parallel/distributed.py", line 376, in forward
output = self.module(*inputs[0], **kwargs[0])
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in call
result = self.forward(*input, **kwargs)
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/apex-0.1-py3.7-linux-x86_64.egg/apex/amp/_initialize.py", line 197, in new_fwd
**applier(kwargs, input_caster))
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/maskrcnn_benchmark/modeling/detector/generalized_rcnn.py", line 52, in forward
x, result, detector_losses = self.roi_heads(features, proposals, targets)
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in call
result = self.forward(*input, **kwargs)
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/maskrcnn_benchmark/modeling/roi_heads/roi_heads.py", line 26, in forward
x, detections, loss_box = self.box(features, proposals, targets)
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in call
result = self.forward(*input, **kwargs)
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/maskrcnn_benchmark/modeling/roi_heads/box_head/box_head.py", line 43, in forward
proposals = self.loss_evaluator.subsample(proposals, targets)
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/maskrcnn_benchmark/modeling/roi_heads/box_head/loss.py", line 111, in subsample
img_sampled_inds = torch.nonzero(pos_inds_img | neg_inds_img).squeeze(1)
RuntimeError: _th_or not supported on CUDAType for Bool
Traceback (most recent call last):
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/tools/train_net.py", line 201, in
main()
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/tools/train_net.py", line 194, in main
model = train(cfg, args.local_rank, args.distributed)
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/tools/train_net.py", line 94, in train
arguments,
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/maskrcnn_benchmark/engine/trainer.py", line 84, in do_train
loss_dict = model(images, targets)
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in call
result = self.forward(*input, **kwargs)
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/nn/parallel/distributed.py", line 376, in forward
output = self.module(*inputs[0], **kwargs[0])
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in call
result = self.forward(*input, **kwargs)
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/apex-0.1-py3.7-linux-x86_64.egg/apex/amp/_initialize.py", line 197, in new_fwd
**applier(kwargs, input_caster))
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/maskrcnn_benchmark/modeling/detector/generalized_rcnn.py", line 52, in forward
x, result, detector_losses = self.roi_heads(features, proposals, targets)
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in call
result = self.forward(*input, **kwargs)
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/maskrcnn_benchmark/modeling/roi_heads/roi_heads.py", line 26, in forward
x, detections, loss_box = self.box(features, proposals, targets)
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in call
result = self.forward(*input, **kwargs)
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/maskrcnn_benchmark/modeling/roi_heads/box_head/box_head.py", line 43, in forward
proposals = self.loss_evaluator.subsample(proposals, targets)
File "/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/maskrcnn_benchmark/modeling/roi_heads/box_head/loss.py", line 111, in subsample
img_sampled_inds = torch.nonzero(pos_inds_img | neg_inds_img).squeeze(1)
RuntimeError: _th_or not supported on CUDAType for Bool
Traceback (most recent call last):
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/runpy.py", line 193, in _run_module_as_main
"main", mod_spec)
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/distributed/launch.py", line 235, in
main()
File "/home/ai/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/distributed/launch.py", line 231, in main
cmd=process.args)
subprocess.CalledProcessError: Command '['/home/ai/anaconda3/envs/maskrcnn_benchmark/bin/python', '-u', '/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/tools/train_net.py', '--local_rank=0', '--config-file', '/media/ai/fcb4c527-7fb0-41df-b900-75a0d4a92991/lq/maskrcnn-benchmark/configs/e2e_mask_rcnn_X_101_32x8d_FPN_1x.yaml']' returned non-zero exit status 1.
Environment
PyTorch version: 1.1.0
Is debug build: No
CUDA used to build PyTorch: 9.0.176
OS: Ubuntu 16.04.4 LTS
GCC version: (Ubuntu 5.4.0-6ubuntu1~16.04.9) 5.4.0 20160609
CMake version: version 3.5.1
Python version: 3.7
Is CUDA available: Yes
CUDA runtime version: 9.0.176
GPU models and configuration:
GPU 0: GeForce GTX 1080 Ti
GPU 1: GeForce GTX 1080 Ti
GPU 2: GeForce GTX 1080 Ti
GPU 3: GeForce GTX 1080 Ti
Nvidia driver version: 390.25
cuDNN version: Could not collect
Versions of relevant libraries:
[pip3] numpy==1.15.0
[pip3] numpydoc==0.7.0
[pip3] torch==1.1.0
[pip3] torchfile==0.1.0
[pip3] torchnet==<IP_ADDRESS>
[pip3] torchvision==0.3.0
[conda] blas                      1.0                         mkl
[conda] mkl                       2019.4                      243
[conda] mkl-service               2.3.0            py37he904b0f_0
[conda] mkl_fft                   1.0.15           py37ha843d7b_0
[conda] mkl_random                1.1.0            py37hd6b4f25_0
[conda] pytorch                   1.1.0           py3.7_cuda9.0.176_cudnn7.5.1_0    pytorch
[conda] pytorch-nightly           1.0.0.dev20190328 py3.7_cuda9.0.176_cudnn7.4.2_0    pytorch
[conda] torchvision               0.3.0           py37_cu9.0.176_1    pytorch
how to fix it?

I have the same problem. Please let me know if you can solve it. Thank you

Me ,too.The same problem has confused me so many days

Traceback (most recent call last):
File "/home/ok/anaconda3/envs/pytorchm/lib/python3.7/runpy.py", line 193, in _run_module_as_main
"main", mod_spec)
File "/home/ok/anaconda3/envs/pytorchm/lib/python3.7/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/home/ok/anaconda3/envs/pytorchm/lib/python3.7/site-packages/torch/distributed/launch.py", line 253, in
main()
File "/home/ok/anaconda3/envs/pytorchm/lib/python3.7/site-packages/torch/distributed/launch.py", line 249, in main
cmd=cmd)
subprocess.CalledProcessError: Command '['/home/ok/anaconda3/envs/pytorchm/bin/python', '-u', 'tools/train_net.py', '--local_rank=3', '--config-file', 'config/e2e_mask_rcnn_R_50_C4_1x.yaml']' returned non-zero exit status 1.
This is my traceback

Traceback (most recent call last):
File "/home/ok/anaconda3/envs/pytorchm/lib/python3.7/runpy.py", line 193, in _run_module_as_main
"main", mod_spec)
File "/home/ok/anaconda3/envs/pytorchm/lib/python3.7/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/home/ok/anaconda3/envs/pytorchm/lib/python3.7/site-packages/torch/distributed/launch.py", line 253, in
main()
File "/home/ok/anaconda3/envs/pytorchm/lib/python3.7/site-packages/torch/distributed/launch.py", line 249, in main
cmd=cmd)
subprocess.CalledProcessError: Command '['/home/ok/anaconda3/envs/pytorchm/bin/python', '-u', 'tools/train_net.py', '--local_rank=3', '--config-file', 'config/e2e_mask_rcnn_R_50_C4_1x.yaml']' returned non-zero exit status 1.
This is my traceback

I've solved the problem and started training. To reinstall, you'll need to upgrade pytorch to 1.3, and the corresponding cuda and drivers will also need to be updated, but that's pretty quick.

Traceback (most recent call last):
File "/home/ok/anaconda3/envs/pytorchm/lib/python3.7/runpy.py", line 193, in _run_module_as_main
"main", mod_spec)
File "/home/ok/anaconda3/envs/pytorchm/lib/python3.7/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/home/ok/anaconda3/envs/pytorchm/lib/python3.7/site-packages/torch/distributed/launch.py", line 253, in
main()
File "/home/ok/anaconda3/envs/pytorchm/lib/python3.7/site-packages/torch/distributed/launch.py", line 249, in main
cmd=cmd)
subprocess.CalledProcessError: Command '['/home/ok/anaconda3/envs/pytorchm/bin/python', '-u', 'tools/train_net.py', '--local_rank=3', '--config-file', 'config/e2e_mask_rcnn_R_50_C4_1x.yaml']' returned non-zero exit status 1.
This is my traceback

I've solved the problem and started training. To reinstall, you'll need to upgrade pytorch to 1.3, and the corresponding cuda and drivers will also need to be updated, but that's pretty quick.

But I can't update cuda, what should I do if I must use cuda9

Traceback (most recent call last):
File "/home/ok/anaconda3/envs/pytorchm/lib/python3.7/runpy.py", line 193, in _run_module_as_main
"main", mod_spec)
File "/home/ok/anaconda3/envs/pytorchm/lib/python3.7/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/home/ok/anaconda3/envs/pytorchm/lib/python3.7/site-packages/torch/distributed/launch.py", line 253, in
main()
File "/home/ok/anaconda3/envs/pytorchm/lib/python3.7/site-packages/torch/distributed/launch.py", line 249, in main
cmd=cmd)
subprocess.CalledProcessError: Command '['/home/ok/anaconda3/envs/pytorchm/bin/python', '-u', 'tools/train_net.py', '--local_rank=3', '--config-file', 'config/e2e_mask_rcnn_R_50_C4_1x.yaml']' returned non-zero exit status 1.
This is my traceback

I've solved the problem and started training. To reinstall, you'll need to upgrade pytorch to 1.3, and the corresponding cuda and drivers will also need to be updated, but that's pretty quick.

But I can't update cuda, what should I do if I must use cuda9

You can try to change the bug code in a python file (such as a few lines of code in loss.py), but the reality is that an operating system can have several cudas co-existing, and you can switch cudas by modifying the soft connection.

Traceback (most recent call last):
File "/home/ok/anaconda3/envs/pytorchm/lib/python3.7/runpy.py", line 193, in _run_module_as_main
"main", mod_spec)
File "/home/ok/anaconda3/envs/pytorchm/lib/python3.7/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/home/ok/anaconda3/envs/pytorchm/lib/python3.7/site-packages/torch/distributed/launch.py", line 253, in
main()
File "/home/ok/anaconda3/envs/pytorchm/lib/python3.7/site-packages/torch/distributed/launch.py", line 249, in main
cmd=cmd)
subprocess.CalledProcessError: Command '['/home/ok/anaconda3/envs/pytorchm/bin/python', '-u', 'tools/train_net.py', '--local_rank=3', '--config-file', 'config/e2e_mask_rcnn_R_50_C4_1x.yaml']' returned non-zero exit status 1.
This is my traceback

I've solved the problem and started training. To reinstall, you'll need to upgrade pytorch to 1.3, and the corresponding cuda and drivers will also need to be updated, but that's pretty quick.

But I can't update cuda, what should I do if I must use cuda9

You can try to change the bug code in a python file (such as a few lines of code in loss.py), but the reality is that an operating system can have several cudas co-existing, and you can switch cudas by modifying the soft connection.

Thanks, but i can't change the drive (for some reasong) and that's the newest version of cuda i can use.

I have the same problem. Please let me know if you can solve it. Thank you

https://github.com/facebookresearch/maskrcnn-benchmark/issues/1172#issuecomment-562123695
He fixed it by upgrade pytorch to 1.3. Maybe you can try it.

I met the problem in torch_nightly==1.0 , and I fixed it in #1182

Have you solved this problem by not upgrading the version of pytorch?

Have you solved this problem by not upgrading the version of pytorch?

Just replace all torch.bool with torch.uint8 in file modeling/balanced_positive_negative_sampler.py and file structures/segmentation_mask.py.
Works for me (Pytorch 1.1.0 and CUDA 9.0)

@hongfz16 The solution method you said works to me, thank you very much.


How can I run models on GPU?

How can run models on GPU?

You can initialize a torch.device, then pass it when you initialize DataLoader and Trainer.

Done


Token created, how to handle?

I have successfully created a token, and I'm wondering how do I pass this thing to my client (CORS)?

For us we just return the token in the reply and set it in the cookies with the correct domain on the client.  We had to make sure that the domain we used with the .domain.com not api.domain.com or web.domain.com; we use the same base domain for our web and api.

This library doesn't create new tokens, it verifies existing ones. You should create your own login endpoint that allows a user to authenticate (check username/password) and upon success return a token in the response body. On the client side you can store the token however you want...in a cookie or in local storage.


fix(cypress): use a real url when making a request

Ah ha! Thank you 👍

at least the first part of the puzzle 🙃


Issue with k8s.io/docs/tutorials/kubernetes-basics/create-cluster/cluster-intro/

Went to run the tutorial and got the following:  Internal Server Error - Request ID: 01FXQH82VAN6SYS7BN1GKJRWHD

/kind bug
This was due a problem at Netlify. I think it's fixed - are things working for you @WaltSection ?


Fix: Scroll line vertically to the center if opened with initialRow

Fixes issue #12253
Added center: true for autoscroll to get this behaviour.
Also, regarding the specs, I couldn't find any existing behaviour tests that can distinguish between center: true and center: false for autoscroll. The current initialLine tests are here and the autoscroll tests are here (These just check if there is a certain amount of scroll amount from top and not whether the actual location of the cursor is in the center of the displayed screen )
Will add specs if someone can suggest how to proceed.

FYI, @stale shouldn't mark issues as stale that have currently attached fixes (like this one).

Thanks very much for your effort on this.
Unfortunately, we can't merge this without specs and since it is so out of date there are significant merge conflicts that would need to be fixed. Given that it is in this state, I'm going to close this. If anyone wants help bringing this across the finish line, come find me in the Atom Slack or ping me here.
Thanks again :+1:


Docpy

Codecov Report
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@@           Coverage Diff           @@
##           master      #59   +/-   ##
=======================================
  Coverage   94.00%   94.00%
=======================================
  Files          37       37
  Lines         801      801
  Branches       76       76
=======================================
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  Misses         48       48

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