WhereIsAI/github-issue-similarity huggingface dataset:
Issue 1:
Task:

- name: install authorized keys
action: authorized_key user={{item}} key="{{ lookup('file', 'authorized_keys') }}"
with_items: ssh_key_users

This worked under ansible 1.3.3. With devel branch I get:

TASK: [ssh_key | install authorized keys] *************************************
fatal: [ubutest] => One or more undefined variables: 'lookup' is undefined

FATAL: all hosts have already failed -- aborting

Issue 2:
The following documented use of the lookup plugin

---
- hosts: all
tasks:
- debug: msg="{{ lookup('env','HOME') }} is an environment variable"

now generates the following error:

TASK: [debug msg="{{lookup('env','HOME')}} is an environment variable"] *******
fatal: [localhost] => One or more undefined variables: 'lookup' is undefined

I've traced this back to commit 5031104.
Issue 1:
Describe the bug

hi

my gltf contains a texture transformation for the normals chanel.

"materials": [
{
"name": "Material_0",
"normalTexture": {
"extensions": {
"KHR_texture_transform": {
"scale": [
0.1,
0.1
]
}
},
"index": 1
},

the transformation is ignored by Three.js editor

my normals map contains a white polygon.

see snapshots from from Three.js (wrong) and khronos viewer (correct)

normals polygon is marked with red

after snapshot, I attached the gltf inside a zip file.

please advise

To Reproduce

Steps to reproduce the behavior:

open https://threejs.org/editor/

import attached rectangle.gltf (extracted from rectangle.zip)

in the scene dialog, double click rectangle.gltf

in the Environment, select MODELVIEWER

ERROR - The normal image should be much larger becase the KHR_texture_transform scale is 0.1

Code

// code goes here

Live example

jsfiddle-latest-release

jsfiddle-dev

Expected behavior

Since i was using scale transformation for the normal chanel in the material, i was expecting the normal texture to be much bigger, as viewd in khronos viewer.

ד

Screenshots

Rectangle.zip

Platform:

Device: [Desktop]

OS: [Windows]

Browser: [Chrome]

Three.js version: [dev, r138]

Issue 2:
plunker

When setting the map to repeat the alphaMap is also affected.

I'm expecting each face of the cube to have a giant whole in the middle with the edges of the taco time texture showing near the edges of the cube in a 3x4 pattern.

I'm getting the 3x4 pattern of the taco time texture but the alphaMap, although it does not repeat it does scale down to the size of the other map. It also produces some nasty streaks.

If you comment out line 35 material.map.repeat.set(3,4); you can see what I'm expecting from the alphaMap.

Three.js version

Dev

r79

...

Browser

All of them

Chrome

Firefox

Internet Explorer

OS

All of them

Windows

Linux

Android

IOS

Hardware Requirements (graphics card, VR Device, ...)
Issue 1:
Description of the problem

GLTF2 models that are clones do not displayed correctly. This is for a number of reasons

the onBeforeRender callback is not copied

GLTFShader is not cloned across

SkinnedModel skeleton is reinitialised to 0 bones and the source skinnedmodel skeleton is not cloned

http://jsfiddle.net/mn768h35/

Three.js version

[X ] Dev

r85

...

Browser

All of them

Chrome

Firefox

Internet Explorer

OS

All of them

Windows

macOS

Linux

Android

iOS

Hardware Requirements (graphics card, VR Device, ...)

Issue 2:
Description of the problem

The current glTF loader works in a slightly unexpected manner: shaders and animations point to a specific instance of a loaded glTF hierarchy, so .clone() or .copy() operations on that hierarchy will drop the links, resulting in the copy not rendering nor animating.

I am intending to patch this in vizor.io initially by providing a deepCopyglTF() function which also goes off and clones the animations and shaders and rebinds them to the new copy.

However as a long-term-solution for three.js it would be preferable to be able to copy and clone these things via the standard three.js way - i.e. calling .copy() or .clone(). This would require the glTF loader to be refactored so that the loaded mesh hierarchy is entirely self contained with no extra external resources pointing to it (this would also remove the need to update glTFAnimator and glTFShaders explicitly). I'm unlikely to get to that anytime soon but would be interested in hearing if anyone else has given thought to this or is working on a similar issue?

ping @tparisi
Issue 1:
It would be great to have the option to disable some remaps.

Scenario:

4 remapped keys

Laptop with external usb keyboard which is used occasionally.

When using external keyboard 2 of the remaps are not needed.

I have the option to disable the whole functionality but for this scenario it would be really useful to be able to disable just the remaps that I don't want.

Thank you for this amazing toolset !

Issue 2:
Have both predefined profiles (e.g. mac/linux/etc) available to user, and also allow the user to create custom profiles.

Provide a quick way to switch between profiles.
Issue 1:
I've modified the DatePicker component to meet a need for a project and wanted to contribute the changes back to the core project (:

The modification - an additional prop viewYearFirst={true} which opens the datepicker directly to the year display.

I just wanted to check in to see if the prop name was appropriate and whether or not any core developers could spot any gotchas before I roll this up into a PR.

Thanks!

Issue 2:
When building apps that use the date picker for choosing an old date like "birthday", I often hear complaints about it taking forever to go so far back in time. These people obviously don't realize they can select the year by clicking on the year in the title area. An option for just starting on the year picker though would make this component much more useful for such historic dates, especially for the less tech-savvy.

If not that, then perhaps it can be made a little more obvious that clicking on the year takes you to the year picker? An edit icon or something?

I'd be happy to make a pull request if others agree this would be a useful addition. Thanks!
Issue 1:
I have searched the issues of this repository and believe that this is not a duplicate.

I have checked the FAQ of this repository and believe that this is not a duplicate.

Environment

Dubbo version: 2.7.5

Zookeeper version: 3.4.14

Operating System version: macos

Java version: 1.8

Steps to reproduce this issue

按官方文档搭建provider，两种方式：annotation/xml

分别配置

<dubbo:metadata-report address="zookeeper://127.0.0.1:2181"/>

@Bean
public MetadataReportConfig metadataReportConfig() {
MetadataReportConfig metadataReportConfig = new MetadataReportConfig();
metadataReportConfig.setAddress("zookeeper://127.0.0.1:2181");
return metadataReportConfig;
}

应用正常启动

Consumer端正常调用

观察Zookeeper节点数据，元数据节点/dubbo/metadata 未创建

Expected Result

元数据正常上报

Actual Result

元数据节点在Zookeeper上未创建，元数据未上报

将dubbo版本号更改为2.7.4.1、2.7.3，代码或配置未改动，元数据正常上报

Issue 2:
I have searched the issues of this repository and believe that this is not a duplicate.

I have checked the FAQ of this repository and believe that this is not a duplicate.

Environment

Dubbo version: 2.6.2

Operating System version: Mac 10.14

Java version: 1.8.0_172

Steps to reproduce this issue

run my project and let's spring.profiles.active=prod. I find the address of zooKeeper is default value(zookeeper://127.0.0.1:2181) in application.yml. but I expected result is zookeeper://127.0.0.1:2182. about detail configuration. please see provider/src/main/resources/application.yml

github address: https://github.com/smallAttr/zk-dubbo-demo/tree/multi_profile

and printf load dubbo configuration as same as expected result:

dubbo configuration:CoreConfiguration(address=zookeeper://127.0.0.1:2182, client=zkclient)
Issue 1:
I have an error with validation unique entity on date time fields

Here is a sample code :

namespace xxx\yyyBundle\Entity;

use Doctrine\ORM\Mapping as ORM;
use Symfony\Component\Validator\Constraints as Assert;
use Symfony\Bridge\Doctrine\Validator\Constraints as DoctrineAssert;

/**
* xxx\yyyBundle\Entity\Planning
*
* @ORM\Entity(repositoryClass="xxx\yyyBundle\Repository\PlanningRepository")
* @DoctrineAssert\UniqueEntity(fields={"day"})
*/
class Planning
{
/**
* @var integer $id
*
* @ORM\Id
* @ORM\Column(name="id", type="smallint")
* @ORM\GeneratedValue(strategy="AUTO")
*/
private $id;

/**
* @var datetime $day
*
* @ORM\Column(name="day", type="date", unique=true, nullable=false)
* @Assert\NotNull()
* @Assert\Date()
*/
private $day;

When i submit a form i have the following message :

Catchable Fatal Error: Object of class DateTime could not be converted to string in /Users/jf/Documents/aojf-workspace/lesroyaumes/vendor/doctrine-dbal/lib/Doctrine/DBAL/Connection.php line 1074

So i add the following lines in the UniqueEntityValidator.php file

just after

if ($criteria[$fieldName] === null) {
return true;
}

this

$fieldType = $class->getTypeOfField($fieldName);
if ($fieldType == Type::DATE)
{
$criteria[$fieldName] = date_format($criteria[$fieldName], 'Y-m-d');
}

It works with Mysql database. But i can not test with others.

Moreover, i do not know if 'Y-m-d' is generic and how i can do it generic for date and datetime.

Issue 2:
Running Symfony 2.4.3, I believe it's an issue in 2.4.4 as well

If the Client is insulated, it tries to serialize() the data to pass to the Process. serialize() fails on UploadedFile.

https://github.com/symfony/symfony/blob/master/src/Symfony/Bundle/FrameworkBundle/Client.php#L145

That line serializes the request, but if request contains UploadedFile it fails.

Demonstration code:

Have a form with a file upload field named "file" and submit button named "submit"

$client = static::createClient($options, $server);
$client->insulate(true);
$crawler = $client->request("GET", $url);
$form = $crawler->selectButton("form[submit]")->form();
$form['form[file]']->upload("path/to/some/file");

$client->submit($form); // FAILS WITH BELOW TRACE

There was 1 error:

1) ...Test::test...
Exception: Serialization of 'Symfony\Component\HttpFoundation\File\UploadedFile' is not allowed

/.../vendor/symfony/symfony/src/Symfony/Bundle/FrameworkBundle/Client.php:145
/.../vendor/symfony/symfony/src/Symfony/Component/BrowserKit/Client.php:368
/.../vendor/symfony/symfony/src/Symfony/Bundle/FrameworkBundle/Client.php:123
/.../vendor/symfony/symfony/src/Symfony/Component/BrowserKit/Client.php:332
/.../...Test.php:74
Issue 1:
Some contour/contourf keyword arguments (hatches, linewidths, linestyles) also work with tricontour/tricontourf but they are not documented and there are no examples of their use.

Issue 2:
Dragged legend moves upon resizing figure window from matplotlib version 2.1.0.

Code for reproduction

import matplotlib.pyplot as plt

X = range(100)
Y = [value ** 2 for value in X]

plt.plot(X, Y,label='Y')
leg=plt.legend()
leg.draggable(True)
plt.grid(True)
plt.show()

Matplotlib 2.1.1/2.1.0 output

Matplotlib 2.0.2 output

In 2.1.0 legend tries to retain it's location with respect to monitor (if we resize in one axis).

Is this expected? How do I bring back the old behavior?

Operating system: Windows 10 64 bit

Matplotlib version: 2.1.0/2.0.2

Matplotlib backend: NA

Python version: 2.7.10

Jupyter version (if applicable): NA

Other libraries: NA

Installed using whl files
Issue 1:
Description of the problem

MeshStandardMaterial & MeshPhysicalMaterial Lighting problem on Adreno GPU.

Not Adreno GPU

Adreno GPU

live example:

codepen

Three.js version

r98

Browser

All of them

Chrome

Firefox

Internet Explorer

OS

Android

Hardware Requirements (graphics card, VR Device, ...)

Adreno GPU

Issue 2:
I have a particle system and I want distant particles to appear more diminished than they'd actually be based on the space (darker, less opaque, etc.) Fog is an obvious way to do this, but I have a background plate behind the system that I don't want to be dimmed.

What's the easiest way to handle this?

Is there a way to do fog on only this particle system and not the whole scene? Should I look into reworking the particle shader to diminish opacity based on distance in z? Am I missing something obvious?
Issue 1:
Bug report

Bug summary

I'm looking for resetting the zoom and pan history of interactve browsing. Using toolbar.update() breaks the interactive history, it's not possible to go back to the previous axis state.

Code for reproduction

Run this code in python a console:

from matplotlib import pyplot as plt
f = plt.figure()
plt.plot([1, 2, 5])
plt.show(block=False)
f.canvas.toolbar._views._elements # One element
f.canvas.toolbar._positions._elements # One element
f.canvas.toolbar.update()
f.canvas.toolbar._views._elements # Empty !
f.canvas.toolbar._positions._elements # Empty !
# Zoom once
# Try to go back using the home button or back arrow

Actual outcome

The view doesn't change when pressing home button or back arrow

Expected outcome

I expect to be able to got back to the state the plot was in when f.canvas.toolbar.update() was called, but since the history is completely empty, there is no state to go back to. I think the current state should be added right after clearing the history. Is it possible to do it manually in the meantime ?

Matplotlib version

Operating system: Arch Linux

Matplotlib version: 2.1.0-1

Matplotlib backend (print(matplotlib.get_backend())): Qt5Agg

Python version: 3.6.3

Jupyter version (if applicable):

Other libraries:

Issue 2:
There are two entries in http://matplotlib.org/devdocs/gallery.html#lines_bars_and_markers for marker_reference.py that point to the same page -- likely because that example generates two plots.

A few possibilities:

generate a single plot (probably the simplest and good enough).

split the example into two files.

somehow have the second link point to an HTML anchor corresponding to the second plot.
Issue 1:
Hello,

I was investigating strange error which we have for one of our tasks. We received regular errors about billard losing workers:

Task (...)[5832c7bd-fe9d-45cd-865e-b6beb4c09e47] raised unexpected: WorkerLostError('Worker exited prematurely: signal 15 (SIGTERM).',)

I was searching for some other processes which could killed our workers but system logs was empty and when I was going to give up we turned off autoscale due to some other issues and these errors dissapered completely.

Celery 3.1.18

Django 1.7.8

librabbitmq 1.6.1

Issue 2:
I get the following traceback from my worker and then the worker stops consuming tasks. I have confirmed that there are several thousand messages in the RabbitMQ celery queue, the worker is not consuming them.

I started my worker with the following command:

celery worker -A project -l info -n worker1.%h -Ofair --autoscale=50,1 --maxtasksperchild=100 --beat

I am using the -Ofair flag because I was also experiencing another breaking bug (#1845) and found -Ofair to be a workaround.

2015-02-02 23:08:08,442 - ERROR - 15875:MainProcess - Unrecoverable error: AssertionError()
Traceback (most recent call last):
File "/home/djacobs/.virtualenvs/workflow/local/lib/python2.7/site-packages/celery/worker/__init__.py", line 206, in start
self.blueprint.start(self)
File "/home/djacobs/.virtualenvs/workflow/local/lib/python2.7/site-packages/celery/bootsteps.py", line 123, in start
step.start(parent)
File "/home/djacobs/.virtualenvs/workflow/local/lib/python2.7/site-packages/celery/bootsteps.py", line 374, in start
return self.obj.start()
File "/home/djacobs/.virtualenvs/workflow/local/lib/python2.7/site-packages/celery/worker/consumer.py", line 278, in start
blueprint.start(self)
File "/home/djacobs/.virtualenvs/workflow/local/lib/python2.7/site-packages/celery/bootsteps.py", line 123, in start
step.start(parent)
File "/home/djacobs/.virtualenvs/workflow/local/lib/python2.7/site-packages/celery/worker/consumer.py", line 821, in start
c.loop(*c.loop_args())
File "/home/djacobs/.virtualenvs/workflow/local/lib/python2.7/site-packages/celery/worker/loops.py", line 70, in asynloop
next(loop)
File "/home/djacobs/.virtualenvs/workflow/local/lib/python2.7/site-packages/kombu/async/hub.py", line 274, in create_loop
poll_timeout = fire_timers(propagate=propagate) if scheduled else 1
File "/home/djacobs/.virtualenvs/workflow/local/lib/python2.7/site-packages/kombu/async/hub.py", line 136, in fire_timers
entry()
File "/home/djacobs/.virtualenvs/workflow/local/lib/python2.7/site-packages/kombu/async/timer.py", line 64, in __call__
return self.fun(*self.args, **self.kwargs)
File "/home/djacobs/.virtualenvs/workflow/local/lib/python2.7/site-packages/celery/concurrency/asynpool.py", line 521, in verify_process_alive
assert proc.outqR_fd in hub.readers
AssertionError
Issue 1:
I am using twitter bootstrap in my application but every time I try to upload image I get the following error

I have just the following code snippet to register bootstrap

$baseUrl = Yii::app()->theme->baseUrl;

$cs = Yii::app()->getClientScript();

Yii::app()->clientScript->registerCoreScript('jquery');

$cs->registerScriptFile($baseUrl.'/js/bootstrap.js');

Also my popups don't work!

Issue 2:
I am Using Firefox 22.

Reproduce:

Open http://getbootstrap.com/components/

The error is visible in the console when clicking anywhere in the page but a dropdown menu.

I could track down the error to the clearMenus call, which in turn calls getParents where the error finally happens.

In getParents the selector variable is set to '#'. This character is stripped away inside jQuery.
Issue 1:
Apologies if this is mentioned elsewhere, but I couldn't find an issue/PR that mentions it.

The Fetch API is still experimental, but I assume its definitions will make their way into TypeScript core at some point?

Issue 2:
for exemple :

module mymodule {

export class myclass extends anotherclass {

should throw a warning because another class is not referenced as this in the header :

/// <reference path="./anotherclass.ts" />

this cause in error in code, because extends class is not includes in base class at runtime :

Uncaught TypeError: Cannot read property 'prototype' of undefined
Issue 1:
We have some mapping options that sound interesting but are actually almost useless or dangerous. I propose to remove them:

_type: { index: no }

Not indexing the _type sounds appealing since documentation mentions everything will keep on working, so that should just save space. Except that elasticsearch will internally run a prefix query on the _uid field instead, which is going to be super slow. I think we should remove this option.

_type: { store: yes } and _id: { store: yes }

Storing the type and _id is useless since we already enforce the _uid to be stored, and the _uid contains these informations.

_id: { index: not_analyzed }

The _id field is the same for all documents so we should not need to index, store or doc-value it. (Can be done now thanks to #6073 and #7965)

In general I'm wondering if we shouldn't go further and completely lock down how data is indexed/stored/docvalued for meta fields. There would just remain high-level configuration options such as enabled on the _timestamp mapper or type on _parent.

Relates to #8870

Issue 2:
With #18075 merged we now have the option to execute our doc snippets through the REST test infrastructure.

Many of the small parts of original REST tests I've read look like great stories around how to use our REST API. I have no idea how much overlap there is between our docs and the REST test-suite, however I would imagine that one could convert several REST tests into nice pieces of documentation showing the complete story from indexing data to using the API under test.

I'm wondering if it would make sense to consolidate what we are now (or in the hopefully near future) testing from within our docs and what is covered in the REST tests. (Intentionally not adding any version label to this issue - currently this is really just a vague question instead of a hard and fast proposal to move any specific way.)
Issue 1:
The expression 1.+2 produces 3::Int64 since the expression is parsed as (1) .+ (2) instead of (1.)+(2). It is very surprising (at least to me) that in the .+ operator has higher precedence than the floating literal in the lexer. It also means that 1.+2 gives a different value than 2+1., which is surprising to me.

I am learning Julia, so please disregard if this is an intentional or well-documented decision.

Issue 2:
For an array a, I'm using 1.*a to ensure that it is a Float64 or Complex{Float64}. This doesn't work with

a=[0]

I'm assuming this is a bug? Or is 1.*a bad form for converting?
Issue 1:
I first brought this up in the julia users group here:

julia> list = ["a", "b", "c"]
for i in enumerate(list)
println(i)
end

(1,"a")
(2,"b")
(3,"c")

But:

julia> addprocs(2)

@parallel for i in enumerate(list)
println(i)
end

ERROR: `getindex` has no method matching getindex(::Enumerate{Array{ASCIIString,1}}, ::UnitRange{Int64})

As @Ismael-VC pointed out in the user group, it works in parallel with

julia> @parallel for i in collect(enumerate(list))
println(i)
end

But it seems a bit confusing to me that the behaviour of enumerate() changes depending on whether the loop is run in parallel or not.

Issue 2:
Consider this code:

A = eye(3)
B = {A,A,A}

for (a1,a2) in zip(B,B)
a1+a2
end

It works fine. If I add @parallel (+) it fails with:

exception on 1: ERROR: MethodError: getindex has no method matching getindex(::Base.Zip2{Array{Any,1},Array{Any,1}}, ::Int64)

in anonymous at no file:1471

in anonymous at multi.jl:1320

in run_work_thunk at multi.jl:617

in run_work_thunk at multi.jl:626

in anonymous at task.jl:6
Issue 1:
When np.array() or .asarray() is used to go from a list of integers, without specifying a dtype explicitly, it can pick default dtypes including int64 & uint64. But there's a strange corner case where it defaults to float64 and loses precision, even though all the values could be uint64. Specfically, this occurs when some but not all values can be int64:

In [11]: max_int64 = np.iinfo(np.int64).max

In [12]: np.array([max_int64]).dtype
Out[12]: dtype('int64')

In [13]: np.array([max_int64 + 1]).dtype
Out[13]: dtype('uint64')

In [14]: np.array([max_int64 + 1, max_int64]).dtype
Out[14]: dtype('float64')

It doesn't depend on the order they're in, and it's not a general consequence of having two values rather than one - two values above this threshold get uint64 as I'd expect.

Tested on Numpy 1.18.4, Python 3.8.2.

Sorry if this has already been discussed; it's a tricky thing to search for. This relates to an issue reported on h5py: h5py/h5py#1547 .

Issue 2:
The error message produced by setting value of mismatching shape to array is incorrect.

Here is an example.

>>> a = numpy.zeros((4, 4, 4))
>>> ind = numpy.array([[1,0], [2, 3]])
>>> v_shape = (2,2,4,4)
>>> v = numpy.arange(np.prod(v_shape)).reshape(v_shape)
>>> a[:, ind, :] = v

ValueError: shape mismatch: value array of shape (2,2,4,4) could not be broadcast to indexing result of shape (2,2,4,4)

The shape that is requested by this example is (4, 2, 2, 4). Therefore, error message should say

ValueError: shape mismatch: value array of shape (2,2,4,4) could not be broadcast to indexing result of shape (4,2,2,4)
Issue 1:
Tested both with 0.11.1 and recent dev version:

import matplotlib.pyplot as plt
import seaborn as sns

def show_counts(color, data):
ax = plt.gca()
ax.text(0.5, 0.95, f'Count: {len(data)}', ha='center', color=color, transform=ax.transAxes)

penguins = sns.load_dataset("penguins")
g = sns.displot(data=penguins, x="flipper_length_mm", y="bill_length_mm", col="species", height=3)
g.map_dataframe(show_counts)
plt.tight_layout()

Without calling map_dataframe the outer x and y labels are set to the x and y column names used in displot. After calling map_dataframe the labels are empty.

(Apart from that, the function g.set_axis_labels() doesn't seem to be documented, although it appears in the displot and FacetGrid examples.)

Issue 2:
Calling map_dataframe on a facetgrid removes the axis labels. Reproducible example:

what I assume would happen:

Code:

import seaborn as sns
tips = sns.load_dataset("tips")
g = sns.relplot(data=tips, x="total_bill", y="tip", hue="day")
g.map_dataframe(lambda *args, **kwargs: 1)

Version: 0.11.1