WhereIsAI/github-issue-similarity huggingface dataset:
Issue 1:
Colin Sampaleanu opened SPR-2285 and commented

The bean factory and application context contract clearly states (as per our docs) that within one definition xml file a bean id must be unique.

This is enforced by the XML parser when using the "id" attribute exclusively because this is flagged as an XML IDREF attribute. However, by combining the use of the id attribute and the name attribute, or just using the name attribute exclusively, it is possible to have 2 or more bean definitions in the same xml file with the same id. This is silently accepted with the last bean definition winning out.

The bean definition reader must basically track ids, however they are supplied, and enforce the same semantics from usage of the "name" attribute as from usage of the "id" attribute.

A related question is what should happen in the case of <import>? An argument could be made either way here.

Affects: 2.0 RC2

Attachments:

spring2285_testcase_and_patch.zip (2.67 kB)

Issue 2:
Chris Beams opened SPR-7888 and commented

Equivalent to context:spring-configured/

Because @Configuration classes don't produce bean definitions in quite the same way that XML configuration files do, an annotation-based @SpringConfigured annotation must work differently than context:spring-configured/. Consider the following approach:

@Configurationpublic class SpringConfiguredBeans {

@SpringConfigured
public void someEntity(MyEntity entity) {
entity.setRepository(myRepository());
}

@Bean
public MyRepository myRepository() {
return new MyRepository(dataSource());
}

// ...}

Issue Links:

#12790 SpringConfiguredBeanDefinitionParser (aop:spring-configured) ("is duplicated by")

#12792 SpringConfiguredBeanDefinitionParser (context:spring-configured) ("is duplicated by")

#12078 Support Java-Based Application Configuration

Referenced from: commits 22e37aa, d356205, 4318ccd

1 votes, 2 watchers
Issue 1:
Currently ControllerResolver is responsible for determining the parameters to pass to controller actions. It does so via Reflection matching request attribute names to action parameter names. For parameters using the Request type hint it however knows to inject the Request instance.

Now in FOSRestBundle we have a need to inject parameters by type hint. Which leads to having to do the same work again. See for example:

FriendsOfSymfony/FOSRestBundle#745

So it might make sense to provide some way to tell the ControllerResolver for whatever other type hints to look for and what attributes to map them to.

Issue 2:
In the https://github.com/symfony/workflow repository, the link to the documentation is not working.

The current link is https://symfony.com/doc/current/components/workflow/introduction.html which returns a 404.
Issue 1:
I have an issue with SelectField having many menu items with "checked" prop when first menu item have buttons as children. The list scrolls to first item immediately when i click on last item or on items near last item.

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

Expected Behavior

The list should not scroll to first item when i check last or near last item. It must stay at the same place where i clicked.

Current Behavior

The list scrolls to first item immediately when i click on last item or on items near last item.

Steps to Reproduce (for bugs)

Here is the live example https://codesandbox.io/s/30z4y4772m

Click on the SelectField

Scroll to the bottom

Click on any item

List scrolled to top

Context

This issue making use of my dropdown component uncomfortable for user as it forces user to verify if he really checked the item in the list. The buttons is also needed.

Your Environment

Tech
Version

Material-UI
0.19.4

React
16.0.0

browser
Google Chrome

OS
Windows 10

Issue 2:
I'm trying to use the React Material tables.

But when I add paging to them I get the following error:

Error: Material-UI: the value property is required when using the Select component with native=false.

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

Expected Behavior

Get paid for the records in the table

Current Behavior

Can not render table much less than page

Steps to Reproduce (for bugs)

Create Table

Add Table Pagination

Context

Your Environment

Tech
Version

Material-UI
@next

React
16.2.0

browser
Chrome

etc
Issue 1:
[Enter steps to reproduce below:]

...

...

Atom Version: 0.188.0

System: Unknown Windows Version

Thrown From: emmet-atom package, v2.3.4

Stack Trace

Failed to load the emmet-atom package

At Cannot find module 'emmet'

Error: Cannot find module 'emmet'
at Module._resolveFilename (module.js:351:15)
at Function.Module._resolveFilename (C:\Users\Portatil 1050\AppData\Local\atom\app-0.188.0\resources\app\src\module-cache.js:383:52)
at Function.Module._load (module.js:293:25)
at Module.require (module.js:380:17)
at require (module.js:399:17)
at Object.<anonymous> (/C:/Users/Portatil%201050/.atom/packages/emmet-atom/lib/emmet.coffee:10:11)
at Object.<anonymous> (/C:/Users/Portatil%201050/.atom/packages/emmet-atom/lib/emmet.coffee:189:4)
at Module._compile (module.js:475:26)
at Object.requireCoffeeScript (C:\Users\Portatil 1050\AppData\Local\atom\app-0.188.0\resources\app\node_modules\coffee-cash\lib\coffee-cash.js:85:19)
at Module.load (module.js:370:32)

Commands

Config

{
"core": {
"themes": [
"atom-dark-ui",
"atom-dark-syntax"
]
}
}

Installed Packages

# User
emmet-atom, v2.3.4

# Dev
No dev packages

Issue 2:
[Enter steps to reproduce below:]

...

...

Atom Version: 0.187.0

System: Mac OS X 10.10.2

Thrown From: emmet package, v2.3.4

Stack Trace

Failed to load the emmet-atom package

At Cannot find module 'emmet'

Error: Cannot find module 'emmet'
at Module._resolveFilename (module.js:351:15)
at Function.Module._resolveFilename (/Applications/Atom.app/Contents/Resources/app/src/module-cache.js:383:52)
at Function.Module._load (module.js:293:25)
at Module.require (module.js:380:17)
at require (module.js:399:17)
at Object.<anonymous> (/Users/Kayla/.atom/packages/emmet/lib/emmet.coffee:8:11)
at Object.<anonymous> (/Users/Kayla/.atom/packages/emmet/lib/emmet.coffee:188:4)
at Module._compile (module.js:475:26)
at Object.requireCoffeeScript (/Applications/Atom.app/Contents/Resources/app/node_modules/coffee-cash/lib/coffee-cash.js:85:19)
at Module.load (module.js:370:32)

Commands

Config

{
"core": {
"themes": [
"atom-dark-ui",
"monokai"
]
},
"emmet": {}
}

Installed Packages

# User
emmet, v2.3.4
emmet-atom, v2.3.0
file-icons, v1.4.5
linter, v0.10.1
linter-ruby, v0.1.4
monokai, v0.12.0

# Dev
No dev packages
Issue 1:
David Ferbas opened SPR-4100 and commented

The spring-2.5-rc2.pom file contains the wrong version information

<version>2.5-rc1</version> needs to be	<version>2.5-rc2</version>

Affects: 2.5 RC2

Issue Links:

#8787 All POM file in folder /dist/maven (spring-framework-2.5-rc2-with-dependencies.zip) refers to version 2.5-rc1 instead of 2.5-rc2 ("is duplicated by")

Issue 2:
Jing Xue opened SPR-2660 and commented

Currently if items evaluates to a Map, OptionWriter always uses the key for the option value and the value for the option label. However if the value from the Map is a bean and only a property on that bean is meant for the label, the options have to be manually rendered with a forEach loop and option tags.

On the other hand, itemValue and itemLabel attributes are simply ignored in this case, so it would be more convenient and perhaps more consistent if OptionWriter could use itemValue for the property name to retrieve the option value from the map key object, and itemLabel to retrieve the option label from the map value object.

Affects: 2.0 RC4

Issue Links:

#7905 [form:options] itemLabel and itemValue attributes ignored when rendering Map ("is duplicated by")
Issue 1:
I got two snippets code as follows.

numpy.std([766897346, 766897346, 766897346, 766897346, 766897346, 766897346, 766897346, 766897346, 766897346, 766897346])

0

pd.Series([766897346, 766897346, 766897346, 766897346, 766897346, 766897346, 766897346, 766897346, 766897346, 766897346]).std(ddof=0)

10.119288512538814

The two lists are identical but the result are quite different. I think the pandas' result must be wrong. I work on the latest version 0.16.2 with Python 3.4.

May I ask why? Is it a bug?

Issue 2:
The var method acts inconsistently when used on the Series vs the numpy array returned from values:

dat = pd.DataFrame({'x': [1,2,3,4,0,0,0]})
print(dat['x'].values.var())
print(dat['x'].var())

Prints:
2.24489795918
2.61904761905

This is due to numpy using ddof=0 as its default (calculates the biased variance), whereas pandas calculates the unbiased variance by default. These two should be consistent, so either pandas should adapt or numpy should (maybe it should be numpy since we should calculate unbiased by default?).

The other problem is that pandas does not calculate the variance of this DataFrame properly.

Inconsistent definition aside, the variance should clearly not be zero when calculated from pandas.

dat = pd.DataFrame({'x': [9.0692124699,9.0692124692,9.0692124702,9.0692124686,
9.0692124687,9.0692124707,9.0692124679,9.0692124685,
9.0692124698,9.0692124719,9.0692124698,9.0692124692,
9.0692124689,9.0692124673,9.0692124707,9.0692124714,
9.0692124714,9.0692124734,9.0692124719,9.0692124710,
9.0692124694,9.0692124705,9.0692124713,9.0692124717
]})
print(dat['x'].values.var())
print(dat['x'].var())

Prints:
2.06817742558e-18
0.0

Here is the system information:

INSTALLED VERSIONS:

commit: None

python: 3.4.0.final.0

python-bits: 64

OS: Linux

OS-release: 3.13.0-52-generic

machine: x86_64

processor: x86_64

byteorder: little

LC_ALL: None

LANG: en_CA.UTF-8

pandas: 0.16.1

numpy: 1.9.2
Issue 1:
Model description

FELIX is an encoder-only text editing model, which allows for faster editing and summarization than sequence-to-sequence models, because the summarization can be computed in parallel instead of autoregressively.

Blog

Paper

Open source status

The model implementation is available

The model weights are available

Provide useful links for the implementation

https://github.com/google-research/google-research/tree/master/felix

No weights are available, but code to train it is available. A component of FELIX is BERT, so training FELIX is a matter of fine-tuning a pre-trained BERT model.

@Jmallins

Issue 2:
🌟 New model addition

Model description

New model released by google

Open source status

the model implementation is available: https://github.com/google-research/google-research/tree/master/felix

the model weights are available: https://github.com/google-research/google-research/tree/master/felix (pretrained bert-base-cased can be used)

who are the authors: @Jmallins
Issue 1:
Hi,

After I've upgraded ansible to ansible 1.9.0.1, i've got a problem with ask_sudo_password.

(server asks for sudo password)

(ansible runs on arch linux, the target system is CentOS6)

With earlier versions of ansible (1.8.2, 1.8.4) runs fine

My settings:

sudo_user = root

sudo = True

ask_sudo_pass = True

become=False

become_method='sudo'

become_user=''

become_ask_pass=False

(to fix problem in issue #10547)

In playbook:

...

sudo: True

...

and the command:

ansible -m setup -K

SUDO password:

xxxxxx server xxxxxx | FAILED => ssh connection closed waiting for a privilege escalation password prompt

Issue 2:
Issue Type:

Bug

Ansible Version: 1.9.0.1 from ppa stable.

Environment:

Linux Ubuntu 12.04 host to Linux Debian wheezy target.

Summary:

playbook roles are not executed as sudo anymore.

Steps To Reproduce:

consider the following playbook working with 1.7.2 but no more working with the 1.9.0.1:

test.yml

- hosts: test
roles:
- role: addgroups
sudo: yes

roles/addgroups/tasks/main.yml

---
- name: add toto group
group: name=toto state=present

Expected Results:

add the test group without any failure.

Actual Results:

failed: [zoo] => {"failed": true, "name": "test"}

msg: groupadd: Permission denied.

groupadd: cannot lock /etc/group; try again later

digging into the verbose mode we can observe that the addgroups role is still called with sudo with older version i.e. 1.7.2 and not any more called with sudo with 1.9.0.1

1.7.2

u'/bin/sh -c \'sudo -k && sudo -H -S -p "[sudo via ansible, key=hgpjwxwhvkcrvjywzmwiwhxnnamxrfln] password: " -u root /bin/sh -c \'"\'"\'echo SUDO-SUCCESS-hgpjwxwhvkcrvjywzmwiwhxnnamxrfln; LANG=C LC_CTYPE=C /usr/bin/python /home/test/.ansible/tmp/ansible-tmp-1427390484.81-80330223816703/group\'"

1.9.0.1

/bin/sh -c 'LANG=C LC_CTYPE=C /usr/bin/python /home/test/.ansible/tmp/ansible-tmp-1427392790.43-74683051810820/group

Cheers
Issue 1:
If I have a function prototype something like this:

doit(a::Array{Tuple{Int, MyType}, 1}, b::Int, c::MyType)

where MyType is an ordinary Julia GC/heap allocated type, then the following line of code within the function seems to lead to a heap allocation of a tuple (the same is the case for any immutable type).

a[1] = b, c

There seem to be two issues here:

There seems to be no efficient way to write an immutable value directly into an array in Julia. The above shouldn't require any allocation of any kind, stack or heap.

Apparently, Julia GC/heap-allocates immutables if they contain heap references. I don't understand why, since surely the GC scans the stack conservatively for pointers.

Anyway, I have been unable to find a ticket or PR which deals with the above serious performance issue (which we hit in practice), directly.

(Obliquely) relevant tickets/PRs/tickets seem to include [1]. [2], [3] and [4] and of course the tupocalypse itself. There are also some relevant sounding things on Jeff's compiler optimisation tracker [5], though I am not clear if any are directly relevant.

[1] #8134

[2] #12205

[3] https://groups.google.com/forum/#!topic/julia-users/F_ncyfP2vxg

[4] https://groups.google.com/forum/#!topic/julia-users/LthfABeDN50

[5] #3440

Issue 2:
Using enumerate to iterate through array of mutable objects allocates, but using a simple for loop does not:

type MyMutable
a::Int
end

immutable MyImmutable
a::Int
end

function sumit(arr)
val = 0
for i=1:length(arr)
val += arr[i].a
end

return val
end

function sumit2(arr)
val = 0
for (i, obj) in enumerate(arr)
val += obj.a
end

return val
end

nel = 5000
arr = Array(MyMutable, nel)
arr2 = Array(MyImmutable, nel)
for i=1:nel
arr[i] = MyMutable(i)
arr2[i] = MyImmutable(i)
end

# warmup
@time sumit(arr)
@time sumit(arr2)
@time sumit2(arr)
@time sumit2(arr2)

println("\nfinal times:")
@time sumit(arr)
println(" mutable explicit for loop @time printed above\n")

@time sumit(arr2)
println(" immutable explicit for loop @time printed above\n")

@time sumit2(arr)
println(" mutable enumerate @time printed above\n")

@time sumit2(arr2)
println(" immutable enumerate @time printed above\n")

results:

final times:
0.000043 seconds (5 allocations: 176 bytes)
mutable explicit for loop @time printed above

0.000009 seconds (5 allocations: 176 bytes)
immutable explicit for loop @time printed above

0.000123 seconds (10.01 k allocations: 312.688 KB)
mutable enumerate @time printed above

0.000008 seconds (6 allocations: 192 bytes)
immutable enumerate @time printed above

also, using for obj in arr rather than enumerate does not allocate.
Issue 1:
Are there any plans to supports automatic imports for typescript? I don't think this currently works even if typings files are included.

Thanks.

Issue 2:
Initial loading of VS Code can take between 10 and 20 seconds.

The Reload Window command takes about 10 seconds to complete.

I've tried it from the installer and also building from source with similar problems.

CPU profiling shows ChildProcess.spawn is the biggest problem, which calls all the way down to node.js _tickCallback. I'd be happy to email someone the profile if it would help.

I suppose this issue could be with node itself? I'm at a loss, since VS Code works perfectly on my home computers which have no proxy.

System Properties

Windows 7 Enterprise SP1

Intel i5-4590, 8GB RAM, Samsung 950Pro SSD

Corporate Environment

Behind a NTLM proxy. Have CNTLM installed with environment variables http_proxy and https_proxy pointing to it. npm works fine with this setup.

Symantec Endpoint is installed also.
Issue 1:
In Matlab there's the format command, which provides output format modification for e.g. the displayed precision and other things like engineering format. As an engineer, the latter is of particular interest to me, since only showing exponents which are multiples of 3, makes it a lot easier to work with calculated values. This should affect both display() and show(). Could this be implemented?

Issue 2:
I want change output format for numbers (stand alone floats, float matrix, BigFloats). I can do it in IPython by using %precision magic function. I didn't find any equivalent in Julia.

I know that I can use round but it actually returns different number. It's also cumbersome to convert arrays with combination map + round. One another problem: I didn't get how to change real or output precision of BigFloat: set_bigfloat_precision changes precision for all new BigFloats, copy and deepcopy don't help (they copy value irrespective of new default BigFloat precision), naive precision change via BigFloat.prec corrupts it.

I know, that I handle lot's of different topics in this question and I as a programmer understand that lot's of difficulties lays in output formats. But my friend, mathematician asked me: "Why can I just type %precision in my IPython notebook but not in Julia? Isn't output format change essential feature?".
Issue 1:
Describe the bug

https://scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.CategoricalNB.html#sklearn.naive_bayes.CategoricalNB

NB can not treat new values in test data

it is bug since real data has new values

Issue 2:
Description

Calling predict() / predict_proba() / predict_log_proba() on CategoricalNB model throws IndexError.

Steps/Code to Reproduce

import numpy as np
from sklearn.datasets import make_classification
from sklearn.naive_bayes import CategoricalNB
from sklearn.model_selection import train_test_split

X, y = make_classification(n_features=10, n_classes=3, n_samples=1000, random_state=42,
n_redundant=0, n_informative=6)
X = np.abs(X.astype(np.int))
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.5, random_state=42)
model = CategoricalNB().fit(X_train, y_train)

model.predict(X_test)

Expected Results

Predictions for X_test(integer labels).

Actual Results

---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
<ipython-input-3-551bb8080923> in <module>
10 model = CategoricalNB().fit(X_train, y_train)
11
---> 12 model.predict(X_test)

~/Documents/MachineLearning/onnx_projects/skl_env/lib/python3.6/site-packages/sklearn/naive_bayes.py in predict(self, X)
75 check_is_fitted(self)
76 X = self._check_X(X)
---> 77 jll = self._joint_log_likelihood(X)
78 return self.classes_[np.argmax(jll, axis=1)]
79

~/Documents/MachineLearning/onnx_projects/skl_env/lib/python3.6/site-packages/sklearn/naive_bayes.py in _joint_log_likelihood(self, X)
1217 for i in range(self.n_features_):
1218 indices = X[:, i]
-> 1219 jll += self.feature_log_prob_[i][:, indices].T
1220 total_ll = jll + self.class_log_prior_
1221 return total_ll

IndexError: index 5 is out of bounds for axis 1 with size 5

Versions

System:

python: 3.6.8 (v3.6.8:3c6b436a57, Dec 24 2018, 02:04:31) [GCC 4.2.1 Compatible Apple LLVM 6.0 (clang-600.0.57)]

executable: /Users/prroy/Documents/MachineLearning/onnx_projects/skl_env/bin/python3

machine: Darwin-19.2.0-x86_64-i386-64bit

Python dependencies:

pip: 18.1

setuptools: 40.6.2

sklearn: 0.22.1

numpy: 1.18.0

scipy: 1.4.1

Cython: 0.29.14

pandas: 0.25.3

matplotlib: None

joblib: 0.14.1

Built with OpenMP: True
Issue 1:
Do you want to request a feature or report a bug?

A bug?

What is the current behavior?

Cannot set property 'memoizedState' of null

If the current behavior is a bug, please provide the steps to reproduce and if possible a minimal demo of the problem. Your bug will get fixed much faster if we can run your code and it doesn't have dependencies other than React. Paste the link to your JSFiddle (https://jsfiddle.net/Luktwrdm/) or CodeSandbox (https://codesandbox.io/s/new) example below:

const processLink = html => {

return renderToStaticMarkup()

};

const RichText = ({ html }) => {

const htmlProcessed = useMemo(() => processLink(html), [html]);

}

See

What is the expected behavior?

Which versions of React, and which browser / OS are affected by this issue? Did this work in previous versions of ### React?

The current behavior

The expected behavior

Issue 2:
In terms of performance, is there any difference between using arrow functions and bind manually when using es6 classes? Using arrow functions the methods are not on the class prototype, it will be on the class instance only. Using bind will attach the methods to class prototype. It sounds like bind manually will have better performance, does that mean we should consider using bind instead of arrow functions for class methods?

Any suggestions or comments are really appreciated!

So in terms of performance, would you recommend using

class MyComponent extends React.Component {
constructor(props) {
super(props)
}

methodA = () => { ... }
}

or

class MyComponent extends React.Component {
constructor(props) {
super(props)
this.methodA = this.methodA.bind(this)
}

methodA() { ... }
}
Issue 1:
Lets say you have the following:

library example;

import 'dart:html';
import "package:angular2/angular2.dart";
import "package:angular2/src/reflection/reflection.dart" show reflector;
import "package:angular2/src/reflection/reflection_capabilities.dart" show ReflectionCapabilities;

main() {
reflector.reflectionCapabilities = new ReflectionCapabilities();
bootstrap(MyApp);
}

@Component(selector: "my-app", host: const {'foo': 'bar'})
@View(template: '<div>hello</div>')
class MyApp {
}

It will not set the attribute foo onto the my-app element that lives in your html. It does actually set the attribute on a my-app element, just not the one in the dom. It appears there is some sort of temporary element being created and the attribute is being set on that one.

Issue 2:
Repro: https://gist.github.com/jakemac53/795c4f1af486ccfb0014

This seems to be caused by the fact that we are creating a second temporary host element for the root component and calling setAttribute before we attach content to the target host element.

/cc @jakemac53
Issue 1:
Uncaught Error: spawn mono ENOENT

Atom Version: 0.158.0

System: Mac OS X 10.10.1

Thrown From: Atom Core

Steps To Reproduce

... Create a new empty file in Atom

... Toggle the Omnisharp plugin

... Uncaught Error!

Stack Trace

At events.js:85

Error: spawn mono ENOENT
at exports._errnoException (util.js:742:11)
at Process.ChildProcess._handle.onexit (child_process.js:1051:32)
at child_process.js:1142:20
at process._tickCallback (node.js:378:11)

Issue 2:
I've installed all the pieces successfully, yet when I open up a .cs file and start omnisharp, I get this error:

Running KRE 1.0.0-beta1
Issue 1:
Just tried to sort an array with .localCompare(), which failed with an error, then tried new Intl.Collator(), which also failed. E.g. I assume those browser features are missing in Deno or am I doing something wrong?

Issue 2:
As seen in #1952 / #1636 ICU needs to be added in Deno build.

Switching this flag to true maybe: https://github.com/denoland/deno/blob/master/.gn#L50 ?

ref: https://v8.dev/docs/i18n