WhereIsAI/github-issue-similarity huggingface dataset:
Issue 1:
A long time ago I also did an small tool for renaming files. I also thought about implementing some sophisticated search and replace. But then it came to my mind that 1.) there is always too many exceptions and using rules is too unhandy 2.) a good text editor already has all these sophisticated features already build in

1.) So my idea: take the list of selected files or all files from Windows Explorer

2.) Open an UI with a powerful text editor, e.g. the Avalon editor control is great!

3.) Each file name is one line. Can't add lines or delete lines

4.) Edit the file names using the editor and all the power of a great editor.

5.) When saving apply the new file names.

That would turn out much more useful.

6.) Prio B: implement a file preview pane. When selecting a file name show a preview of the file. This is espacially useful when changing the automatically created names of images from a camera.

Issue 2:
Summary of the new feature/enhancement

Import external file list of new names that will be used on the current queue.

Some people just want to rename with a specific list of custom names, not following the Power Rename configuration tool that consider only sequencial names and strings. for example: I have a list of files that I export from a web based application. I'd like to keep the original name or change the name to original date of file, so I export the names to an external file list.

Proposed technical implementation details (optional)

Download files has a sequence to be list on file system. It depends of the timestamp applied when download was completed. When you load the files you want to PowerRename the list of files follow this rule. But to make it understandable to general users we need to adapt:

Be able to reorder the file list queue

Be able to reorder the new name file list

Be able to load an external file to make new name list column

Follow the system order list to make the origin file list (queue)

Import external file list making possible customize the name of bulk rename process.
Issue 1:
I input any String type eg:"eee", It is accepted's.

**React 15.1.0 windows 10/ chrome 51

Issue 2:
A controlled number input, without a corresponding setState function, still allows e, - and . to be entered (and numbers can be inputted afterwards). I could be incorrect but I don't believe this is the desired behavior.

Here's a JSFiddle demonstrating the issue.
Issue 1:
Code as of 6088134

Your Windows build number: Microsoft Windows [Version 10.0.18362.86]

What you're doing and what's happening:

Clicked the dropdown in the upper right corner

Clicked Settings

Code launched with profiles.json in a compact form

Formatted the JSON so I could more easily read and edit it

Saved the file

File is immediately reloaded and put back into compact, unformatted form, making it difficult to edit again.

What's wrong / what should be happening instead:

Expect formatting to persist after saving a change or if the app needs to modify it after detecting a change to at least format it with indentation / beautify / formatter

Issue 2:
The contents of profile.json are all in the same line, marks its readability very low. Maybe it's better to change the default format of it?
Issue 1:
This may exist so apologies if I couldn't find it and am duplicating here:

Would it be possible to break out the code for a client only API that doesn't include the entire elastic search code base?

Currently we have a lot of modular web services modules that make calls to elastic search and because we want to include the advantages of the transport client we have to use the full elastic search codebase. This means that each web service war file is +30 megabytes.

Ideally we'd like a client jar file that only includes the API and the transport code.

Issue 2:
This may exist so apologies if I couldn't find it and am duplicating here:

Would it be possible to break out the code for a client only API that doesn't include the entire elastic search code base?

Currently we have a lot of modular web services modules that make calls to elastic search and because we want to include the advantages of the transport client we have to use the full elastic search codebase. This means that each web service war file is +30 megabytes.

Ideally we'd like a client jar file that only includes the API and the transport code.
Issue 1:
Describe your issue.

This may be a duplicate of gh-15072, but 1) I don't have a big array (50 values), and 2) this method did not return any NaN's, just unexpected large (negative or positive) values.

I finally caught the issue when I realized I had switched from scipy==1.4.1 to scipy==1.7.3 (before, it was working)

I'm attaching two plots made with the same code example, but each with a different scipy version. In the 1.4.1 one, the decimate result is correct and independent of the type of array, and in the 1.7.3, it's wrong for the float32 array:

Reproducing Code Example

import scipy.signal as ssi
import matplotlib.pyplot as plt
import numpy as np

np.random.seed(1)
n = 50
p = np.random.rand(n)
q = 20
p_d1 = ssi.decimate(np.asarray(p, dtype='float32'), q)
p_d2 = ssi.decimate(np.asarray(p, dtype='float64'), q)
print('max p_d1 (float32): ', max(p_d1)) # scipy==1.4.1: 0.526 / scipy==1.7.3: 5279 <- wrong
print('max p_d2 (float64): ', max(p_d2)) # scipy==1.4.1: 0.526 / scipy==1.7.3: 0.526

# Optionally plot
t = list(range(n))
t_d = [t[i * q] for i in range(len(p_d1))]
plt.plot(t, p, marker='o')
plt.plot(t_d, p_d1, marker='s')
plt.plot(t_d, p_d2, marker='x')
plt.legend(['float32', 'float32 > decimated', 'float64 > decimated'], loc='upper right')
plt.title('scipy==1.4.1') # scipy==1.4.1 / scipy==1.7.3 (latest to date)
plt.show()

Error message

None!!

SciPy/NumPy/Python version information

No issue with scipy==1.4.1; Issue with scipy==1.7.3

Issue 2:
Original ticket http://projects.scipy.org/scipy/ticket/1269 on 2010-08-30 by @josef-pkt, assigned to unknown.

I don't think including the old fuzz tests in test_distributions are necessary anymore.

They could be replaced by the new tests, which use a seed, and reuse the random variables, which should speed up the tests a bit.

For occasional use, a full fuzz-testing script could be added to the source tree, but with naming so it doesn't run automatically
Issue 1:
I am running Julia in parallel, i.e. I am starting several Julia interpreters simultaneously. Usually this works fine. When a package is outdated, both will recompile it.

However, I just encountered this error. It went away when I tried again, so I assume it is a race condition.

This is with the release branch of Julia 0.4.

$ mpirun -np 2 ~/julia/bin/julia 06-cman-transport.jl MPI
INFO: Recompiling stale cache file /Users/eschnett/.julia/lib/v0.4/MPI.ji for module MPI.
INFO: Recompiling stale cache file /Users/eschnett/.julia/lib/v0.4/MPI.ji for module MPI.
ERROR: LoadError: unlink: no such file or directory (ENOENT)
in unlink at fs.jl:102
in rm at file.jl:59
in create_expr_cache at loading.jl:330
in recompile_stale at loading.jl:461
in _require_from_serialized at loading.jl:83
in _require_from_serialized at /Users/eschnett/julia/lib/julia/sys.dylib
in require at /Users/eschnett/julia/lib/julia/sys.dylib
in include at /Users/eschnett/julia/lib/julia/sys.dylib
in include_from_node1 at /Users/eschnett/julia/lib/julia/sys.dylib
in process_options at /Users/eschnett/julia/lib/julia/sys.dylib
in _start at /Users/eschnett/julia/lib/julia/sys.dylib
while loading /Users/eschnett/.julia/v0.4/MPI/examples/06-cman-transport.jl, in expression starting on line 1
-------------------------------------------------------
Primary job terminated normally, but 1 process returned
a non-zero exit code.. Per user-direction, the job has been aborted.
-------------------------------------------------------

The standard way to handle this in Unix is to write to a temporary file ($output.tmp), and then use an atomic rename to update the cache (mv("$output.tmp", output)). Removing the file beforehand is not necessary, and can't be done safely unless one locks the directory.

Issue 2:
Hi all,

I am trying to run julia from multiple machines (bash launches multiple julia instances from various machines) and all share the same home dir.

The issue is that each machine recompiles the stale cache. (All are share the same package dir). Is this an issue? Is this a known issue? Is there a solution?

Thanks
Issue 1:
Ubuntu 12.04, vscode 0.10.1

Currently when you run Code if there is an instances already running (or shift clicking the app icon in Windows/Ubuntu) it will activate the currently opened window. This should open a new instance, the same goes for opening a new instance of Code with a folder as an argument when an instance is already open.

It's a very common use case for many developers to have multiple editors with the same folder open.

Repro:

Code (open instance of vscode)

Code

Expected:

A new instance of vscode is opened

Actual:

The current instance of vscode is activated

Issue 2:
VSCode Version: 1.1.1

OS Version: current OSX

Steps to Reproduce:

Vscode with github

create a file

add content in the file, but don't save it. Stay on it in the editor.

delete file (move to trash) from tree file browser

File still shows in working files as unsaved file, and on screen. This is confusing, as 'save all' might recreate the deleted file. A deleted file, even if unsaved, should be removed from:

File browser, both tree and working files

editor
Issue 1:
Windows build number: 10.0.18362.30

What you're doing and what's happening: When having one tab (no matter what type of terminal used) open and type exit, the terminal doesn't close and the cursor just blinks. However, when having more than one tabs open, the terminal tab closes just fine.

What's wrong / what should be happening instead: When typing exit in the last tab, the Windows Terminal should close alongside the open tab.

Issue 2:
Description of the new feature/enhancement

Basically I want (hopefully I am not alone) a mode for the Terminal where it is just a blank canvas.

This would allow me to run a Terminal for informational purposes (for example: htop on WSL, or sampler) to see stuff at a glance.

Since this is the only way this Terminal Window would be used (on a secondary monitor for example), it would be nice to reduce the space it takes up and make it more visually appealing by removing the title bar and window controls.

Linux users can achieve this through their window manager, and I have attached a screenshot of someone's config (it's i3 on Linux) to illustrate what I mean.

Proposed technical implementation details (optional)

Mind you, I have not done Windows App development in ages, and I am not sure wether it is even possible to remove the window controls here (Looking for feedback from the devs!).

If it is though, it could be exposed through a toggle with a customizable keybinding.

Quick Note

I know this is like a super superficial feature, and definitely the last thing that should be implemented once everything else is running smoothly. Just thought I'd document here that I think this should be a thing.
Issue 1:
Description

the result of kmeans.labels_ when n_jobs=1 is different from n_jobs > 1

Steps/Code to Reproduce

from sklearn.cluster import KMeans

import numpy as np

X = np.array([[1, 2], [1, 4], [1, 0],

[4, 2], [4, 4], [4, 0]])

kmeans = KMeans(n_clusters=2, random_state=0, n_jobs=1).fit(X)

kmeans.labels_

array([0, 0, 0, 1, 1, 1], dtype=int32)

kmeans = KMeans(n_clusters=2, random_state=0, n_jobs=2).fit(X)

kmeans.labels_

array([1, 0, 1, 0, 0, 1], dtype=int32)

Expected Results

array([0, 0, 0, 1, 1, 1], dtype=int32)

Actual Results

array([1, 0, 1, 0, 0, 1], dtype=int32)

Versions

import platform; print(platform.platform())

Darwin-16.6.0-x86_64-i386-64bit

import sys; print("Python", sys.version)

Python 3.6.1 |Continuum Analytics, Inc.| (default, May 11 2017, 13:04:09)

[GCC 4.2.1 Compatible Apple LLVM 6.0 (clang-600.0.57)]

import numpy; print("NumPy", numpy.version)

NumPy 1.13.0

import scipy; print("SciPy", scipy.version)

SciPy 0.19.1

import sklearn; print("Scikit-Learn", sklearn.version)

Scikit-Learn 0.19.dev0

I found the issues maybe because the radom_state for n_job= 1 is different from n_jobs > 1.

I have a proposal to solve this if you think this issue needs to be fixed.

Thank you.

Issue 2:
Description

I noticed that cluster.KMeans gives a slightly different result depending on if n_jobs=1 or n_jobs>1.

Steps/Code to Reproduce

Below is the code I used to run the same KMeans clustering on a varying number of jobs.

from sklearn.cluster import KMeans
from sklearn.datasets import make_blobs

# Generate some data
X, y = make_blobs(n_samples=10000, centers=10, n_features=2, random_state=2)

# Run KMeans with various n_jobs values
for n_jobs in range(1, 5):
kmeans = KMeans(n_clusters=10, random_state=2, n_jobs=n_jobs)
kmeans.fit(X)
print(f'(n_jobs={n_jobs}) kmeans.inertia_ = {kmeans.inertia_}')

Expected Results

Should expect the the clustering result (e.g. the inertia) to be the same regardless of how many jobs are run in parallel.

(n_jobs=1) kmeans.inertia_ = 17815.060435554242
(n_jobs=2) kmeans.inertia_ = 17815.060435554242
(n_jobs=3) kmeans.inertia_ = 17815.060435554242
(n_jobs=4) kmeans.inertia_ = 17815.060435554242

Actual Results

The n_jobs=1 case has a (slightly) different inertia than the parallel cases.

(n_jobs=1) kmeans.inertia_ = 17815.004991244623
(n_jobs=2) kmeans.inertia_ = 17815.060435554242
(n_jobs=3) kmeans.inertia_ = 17815.060435554242
(n_jobs=4) kmeans.inertia_ = 17815.060435554242

Versions

Darwin-16.7.0-x86_64-i386-64bit

Python 3.6.1 |Continuum Analytics, Inc.| (default, May 11 2017, 13:04:09)

[GCC 4.2.1 Compatible Apple LLVM 6.0 (clang-600.0.57)]

NumPy 1.13.1

SciPy 0.19.1

Scikit-Learn 0.20.dev0
Issue 1:
Do you want to request a feature or report a bug?

Bug

What is the current behavior?

When you have an unexpected prop in a component but that prop is not meant to be generated on the HTML DOM so that is set to {null}, React triggers this warning:

Warning: Unknown prop `activeClassName` on <h1> tag. Remove this prop from the element. For details, see https://fb.me/react-unknown-prop
in h1 (created by HelloWorldComponent)
in HelloWorldComponent

The actual use case is to have a reusable component called <Anchor> and it'd be either <Link activeClassName="'is-active" /> or <a activeClassName={null} />. Here's our actual code.

In the HTML output, there's no any activeClassName attribute for the second case, so there shouldn't be any react warning.

Example reproducing it

I've reproduced the issue in a simple example here:

https://jsbin.com/bozuwuq/edit?html,js,console,output

What is the expected behavior?

Don't warn when a prop is defined to {null} and, therefore, never generated in the DOM.

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

React version: 15.3.0

OS: Ubuntu and Mac OS X. Chromium and Google Chrome.

Issue 2:
Warning: Unknown prop ... on ... tag. Remove this prop from the element.

These are emitted even if the property value is undefined. Should undefined perhaps be treated as not existing perhaps? That's how it is intended AFAIK.
Issue 1:
I've upgraded from 0.10.3 to 0.10.5, and the javascript syntax highlighting doesn't work as well as before (OSX El Capitan):

from this:

to this:

I also removed any extension I've installed, but it didn't fix it...

Issue 2:
VSCode Version: 0.10.11

OS Version: Windows 7

Steps to Reproduce:

Enter function call fn("{};"); anywhere in a C++ file

Syntax higlighting for the rest of the file gets confused - the string is not ended correctly

However string literal in an expression works fine, e.g. a = "{}";
Issue 1:
When the number of layers in the GRU and the number of layers in the hidden size do not match, the GPU throws an error while the CPU does not.

The following snippet to illustrates the same:

rnn = torch.nn.GRU(input_size=5,hidden_size=4)
x = torch.randn(3, 4, 5)
hidden = torch.autograd.Variable(torch.randn(2, 4, 4))
x = torch.autograd.Variable(x)
if torch.cuda.is_available():
rnn = rnn.cuda()
x = x.cuda()
hidden = hidden.cuda()
rnn(x, hidden)

Issue 2:
I run RNN sucessfully with the code.

rnn = nn.RNN(features, hidden_size, num_layers)
o, hidden = rnn(x, hidden)

and I run embedding example. Then, got RuntimeError.

RuntimeError: inconsistent tensor size, expected r_ [5 x 25], t [5 x 25] and src [2 x 25] to
have thesame number of elements, but got 125, 125 and 50 elements respectively at
/opt/conda/conda-bld/pytorch_1503970438496/work/torch/lib/TH/generic/THTensorMath.c:887

I set batch_first=True to use Embedding

x.size is [5, 8, 15]
hidden_size is [5, 2, 25]

nothing seems wrong.

And the error info seems not the dim problem?

The error is so strange.
Issue 1:
Pods with RestartPolicyNever are leaving behind infra pods. Those infra pods should be nuked as soon as the last successful run is completed.

For people with lots of successful / failed never pods this consumes IP addresses which is bad when IP addresses are in use.

I suspect this is because we don't have another marker that the pod has completed, but we probably need to get that fixed before 1.0.

Issue 2:
I have noticed it a couple of times that when I am trying to export a resource, selflinks stay around and the namespace is not part of the link anymore.

[mkargaki@dhcp129-211 kubernetes.github.io]$ kc get quota -o yaml
apiVersion: v1
items:
- apiVersion: v1
kind: ResourceQuota
metadata:
creationTimestamp: 2016-09-29T16:53:38Z
name: object-counts
namespace: default
resourceVersion: "63"
selfLink: /api/v1/namespaces/default/resourcequotas/object-counts
uid: 4494594b-8665-11e6-9fad-68f72840e7df
spec:
hard:
pods: "2"
status:
hard:
pods: "2"
used:
pods: "0"
kind: List
metadata: {}
$ kc get quota object-counts --export -o yaml
apiVersion: v1
kind: ResourceQuota
metadata:
creationTimestamp: null
name: object-counts
selfLink: /api/v1/namespaces//resourcequotas/object-counts
spec:
hard:
pods: "2"
status: {}

We could maybe have this issue as a duplicate of #24855 but I thought we already cleaned up object meta.

@kubernetes/sig-apps
Issue 1:
Seaborn rugplot plot nothing in version 0.10.0

Same code works fine under 0.9.0 and I checked https://seaborn.pydata.org/whatsnew.html to find out if there was an update regarding rugplot but there wasn't.

import seaborn
from matplotlib import pyplot
iris = seaborn.load_dataset('iris')

x = iris.petal_length.values

seaborn.rugplot(x)
pyplot.show()

Issue 2:
import seaborn as sns
a = [1, 2, 4]
sns.rugplot(a)

With matplotlib 3.1.2:

With matplotlib 3.2.1:

I assume this is related to autoscaling changes in matplotlib 3.2 but don't know if it's a bug or if we were previously relying on undefined behavior.

See also #2013
Issue 1:
Matlab has cholupdate for rank 1 updates and downdates to Cholesky factorizations. It would be nice to have something similar, but perhaps with better syntax.

LINPACK had these, but LAPACK left out the Cholesky update/downdate capabilities.

http://icl.cs.utk.edu/lapack-forum/viewtopic.php?f=2&t=2646

For the dense case, perhaps these should be implemented in julia. For the sparse case, I believe that CHOLMOD does provide these capabilities.

Updated by @andreasnoack:

Dense Cholesky

Sparse Cholesky

Dense QR (actually there are three different storage schemes)

Issue 2:
I'm still seeing regression in line number coverage. I've seen this in a number of instances. Below is a partial list:

convert(::Type{BigInt},::Int64)

finalizer(::Any,::Ptr{Void})
Issue 1:
Feature gates are generally checked before expansion so feature gates are defeated by code inside macros.

Issue 2:
This uses the log_syntax! macro without the log_syntax feature gate:

#[feature(macro_rules)];
// This should be required
// #[feature(log_syntax)];

macro_rules! hey ( () => { log_syntax!() } )

fn main() {
hey!()
}

Nominating.
Issue 1:
Context:

GOOD Playwright Version: 1.29.0

BAD Playwright Version: 1.35.1

Operating System: Mac

Extra: N/A

Code Snippet

Minimal repro:

await page.setContent(`<button style="display:contents">DISPLAY CONTENTS</button>`)
await expect(page.getByRole('button')).toBeVisible()

Describe the bug

Elements that use display: contents; are no longer deemed visible, breaking a lot of our selectors when upgrading. I've found similar issues, however the exact reproduction described in this issue seems to be working fine: #11202

This problem seems specific to getByRole.

I also was able to reproduce this issue in 1.32.0.

Issue 2:
Context:

GOOD Playwright Version: ? (Fixed less than year ago here #15034)

BAD Playwright Version: 1.34.3

Operating System: Mac

Extra: None

Code Snippet

React code

export function App(props) {
return (
<div className='App'>
<h1>Hello React.</h1>
<h2>Start editing to see some magic happen!</h2>

<Table />
</div>
);
}

const contentsStyle = {
color: "red",
display: "contents"
};

function Table() {
return (
<div role="table">
<div role="row" style={contentsStyle}>
<div role="cell">
<p>Cell content</p>
</div>
</div>
<div role="row">
<div role="cell">
<p>Cell content</p>
</div>
</div>
</div>
);
}

Test code to reproduce:

import { test, expect } from "@playwright/test";

test("locate table rows", async ({ page }) => {
await page.goto(url);
await expect(page.getByRole("row")).toHaveCount(2);
});

The page.getByRole('row') can not see element with style display: "contents"; applied.

In the code example above, there are two rows in table, one of them has no styles and one of them has display: "contents";. The test can locate only one of these two rows.

It works fine in Webkit, but not in Chrome and Firefox (see screenshot of test run below).