WhereIsAI/github-issue-similarity huggingface dataset:
Issue 1:
I've been trying to have two different versions of a library available, in order to check which one to use, but I can't find out how to make this work. I even tried to explicitly separate the handles to the two versions of the library, but then ccall always calls the one which was loaded first (i.e. it ignores the library name, and just uses the function name).

Here's the example code:

julia> const pkgd_dl = dlopen("/home/carlo/.julia/GLPK/deps/usr/lib/libglpk")
Ptr{Void} @0x0000000003455da0

julia> const system_dl = dlopen("libglpk")
Ptr{Void} @0x000000000326d740

julia> ccall(:add_library_mapping, Cint, (Ptr{Cchar}, Ptr{Void}), "pkgd_libglpk", pkgd_dl)
0

julia> ccall(:add_library_mapping, Cint, (Ptr{Cchar}, Ptr{Void}), "system_libglpk", system_dl)
0

julia> bytestring(ccall(("glp_version", "pkgd_libglpk"), Ptr{Uint8}, ()))
"4.48"

julia> bytestring(ccall(("glp_version", "system_libglpk"), Ptr{Uint8}, ()))
Warning: Possible conflict in library symbol glp_version
"4.48"

The last line should read "4.45" (and indeed it does if I don't load the other version first).

I checked that the add_library_sym in src/ccall.cpp does find the correct handles and returns different pointers in the two cases.

Is it possible at all to have two different functions with the same name from different libraries? Or am I doing something wrong?

Issue 2:
Ref: https://discourse.julialang.org/t/strange-behavior-with-void/2480

Would it be possible to special-case creating a set out of a large vector of Voids? This is admittedly a weird thing to ask, but it looks like it will be significant for some upcoming LightGraphs work. Right now, if I have a large vector of Voids, Julia knows not to allocate any memory for that vector, but once I try turning it into a Set, it appears that sizehint! is applied based on the number of elements, and this allocates a large amount of memory for a single-element Dict.
Issue 1:
Summary of the new feature/enhancement

Environment variable length cannot exceed 8196 characters. This limitation should be optional only and the user should be able to switch on/off this limit via some reg edit Key.

Thanks.

Proposed technical implementation details (optional)

Issue 2:
Description of the new feature/enhancement

Currently I find it hard to find focus, and confusing to pasting text into unfocused terminals, since you cannot change cursor behaviour in unfocused terminals. For example by changing color or opacity (I do not know the feasability of this).

Proposed technical implementation details

(Speculating without looking at actual code for ease of implementation, and images curtesy of Google image search along the lines of "terminal [window] focus") Since I like box cursors, I will provide three examples with box cursors which can be extended to other types of cursors.

An example from Code (possible today, terminal in focus shows unfilled box as cursor, terminal out of focus does not):

An example from Linux (possible today, specifically Kali and Gnome terminal, focused terminal shown filled box while unfocused terminal shows nothing)

Another example from Linux (not possible today, specifically Ubuntu and Tilix terminal emulator, focused terminal shows filled box while unfocused terminal shows unfilled box)

I do not propose that the result should be static, rather that the user can select what the cursor should look like in a focused window and an unfocused window. I.e.:

... profiles.json ...
"cursorShapeWindowFocus" : "filledBox",
"cursorShapeNoWindowFocus" : "emptyBox",
...

Of course taking height for #1203 so that the "filledBox" setting becomes more meaningful.
Issue 1:
Migrated issue, originally created by Marcin Barczyński (@marcinbarczynski)

I would like to aggregate two columns from a single table with array_agg. Here is the code showing that mapping types in output rows works fine with psycopg2, but can't be done with SQLAlchemy:

from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from sqlalchemy import BigInteger, Column, func, tuple_, ARRAY
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.dialects.postgresql import ARRAY as PG_ARRAY

import psycopg2

engine = create_engine(PG_URI, echo=True)
Session = sessionmaker(bind=engine)
session = Session()

Base = declarative_base()
class Demo(Base):
__tablename__ = 'demo'

key = Column(BigInteger, primary_key=True)
val1 = Column(BigInteger, primary_key=True)
val2 = Column(BigInteger, primary_key=True)

session.execute("DROP TABLE IF EXISTS demo CASCADE")
session.execute("CREATE TABLE demo AS SELECT 1 AS key, gen AS val1, gen + 1 AS val2 FROM generate_series(1, 5) gen")
session.commit()

conn = psycopg2.connect(PG_URI)
cur = conn.cursor()
cur.execute("SELECT array_agg(ARRAY[val1, val2]) FROM demo GROUP BY key")
print cur.fetchone()[0]
# prints list: [[1, 2], [2, 3], [3, 4], [4, 5], [5, 6]]

q = session.query(func.array_agg(ARRAY(tuple_(Demo.val1, Demo.val2)))).group_by(Demo.key)
# fails with AttributeError: 'ARRAY' object has no attribute 'type'

I tried to use tuple_, but then string is returned instead of list:

q = session.query(func.array_agg(tuple_(Demo.val1, Demo.val2))).group_by(Demo.key)
print type(q.first()[0])
# prints string: '{"(1,2)","(2,3)","(3,4)","(4,5)","(5,6)"}'

Issue 2:
Migrated issue, originally created by Michael Bayer (@zzzeek)

I think it might be better to just get the array detection to do the right thing

from sqlalchemy import *
from sqlalchemy.dialects.postgresql import array
from sqlalchemy.dialects import postgresql

c1 = column('foo', Integer)

expr = array([c1])

print expr.compile(dialect=postgresql.dialect())

# fails
function = func.array_agg(expr)

# fails
function = func.array_agg(expr, type_=ARRAY(Integer))
Issue 1:
Please:

Check for duplicate issues.

Provide a complete example of how to reproduce the bug, wrapped in triple backticks like this:

>>> import jax.numpy as jnp
>>> a = [1, 3, 3, 5]
>>> t = jnp.asarray(a, dtype=jnp.bfloat16)
>>> import pickle
>>> pp = pickle.dump(t, file=open('test.pkl','wb'))
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
_pickle.PicklingError: Can't pickle <class 'bfloat16'>: attribute lookup bfloat16 on builtins failed

>>> import jax
>>> jax.__version__
'0.2.25'
>>> import jaxlib
>>> jaxlib.__version__
'0.1.73'

If applicable, include full error messages/tracebacks.

Issue 2:
Jax2tf currently does not support scatter_* in non XLA terms (see docs)

I am planning on implementing this as I need it, but first I wanted to check - is it possible, or is there a very solid reason for why it simply isn't expressible in the tensorflow ops?

Is this a foolish plan?

I want to do it in non-XLA terms so I can use tf2onnx so it can be used as an ONNX model

I was thinking about using a combination of:

tf.math.unsorted_segment_{prod,sum,...} for getting the updates to the array

tf.scatter_nd for applying those updates

Note (to self): x.at[indexs].get() does has a non-XLA implementation.
Issue 1:
Some ideas on what to work on during the scipy sprints

finish 2.0

Altiar

mostly stable

needs mpl rederer

someone who knows both mpl + pandas decently well

scales

unify scale handling and pull out of mpl

domain -> [0, 1] or ints

scaled data -> {color, shape, size, ...}

expose notebook docs through notebook

sprint on how to make this integration work, work with IPython folks

convert some of our examples to notebooks

burn down open PRs

Issue 2:
I noticed an issue related to PolyCollections and all Agg backends. If the linewidth keyword is set to 0, then the entire Polygon patch is not shown, rather than removing only the border line. This happened with MPL release 1.4.1, because 1.4.0 works as expected. I see the same behavior on Python 2.7 and 3.4 from Gentoo Linux and in an Anaconda 3.4 environment. I ran a number of tests and posted them to Matplotlib-users. However, as a simple expample::

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0, np.pi*2, 1000)
y = np.sin(x)

# Change the lw != 0 and this works fine
plt.fill_between(x, y-0.1, y+0.1, lw=0)
plt.show()
Issue 1:
Setting atom as git editor on windows 7 works when I dont have an instance of atom running

> git config --global core.editor "atom --wait"

But when I am editing a file in atom and do a commit, I get below message even though the commit message tmp file opens in a new tab in current atom window.

> git commit
Aborting commit due to empty commit message.
>

Issue 2:
Version 0.118.0 on Windows 7 x64

PS C:\ > atom --wait myfile.txt

Immediately terminates, but does continue to open the file. Expected result is to wait until the file is closed in the editor.

https://github.com/atom/language-git

and

http://blog.atom.io/2014/03/13/git-integration.html

say that the syntax that I'm using is correct. Is there a new syntax to enable this or is this feature no longer supported.
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: 2.7.6

Operating System version: win10

Java version: java8

Steps to reproduce this issue

NacosMetadataReport缺失username和password参数解析，导致nacos开启权限认证的情况下，dubbo元数据无法发送到nacos

Pls. provide [GitHub address] to reproduce this issue.

Expected Result

What do you expected from the above steps？

Actual Result

What actually happens?

If there is an exception, please attach the exception trace:

Just put your stack trace here!

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: 2.7.7

Operating System version: mac

Java version: 1.8

golang version 1.5.1

Steps to reproduce this issue

java-client 泛化调用go的服务

确定go的服务 在使用 go-client 调用时能够调通的

确定使用dubbo-java-client(2.6.5)也是能调通的

Pls. provide [GitHub address] to reproduce this issue.

Expected Result

What do you expected from the above steps？

Actual Result

What actually happens?

If there is an exception, please attach the exception trace:

Just put your stack trace here!
Issue 1:
I am using an older version of Windows 10 (v1809) and cannot upgrade since the upgrades are managed by the company. And would like to see the very needed video utility in older versions of Windows 10.

If you'd like to see this feature implemented, add a 👍 reaction to this post.

Issue 2:
Please add support for earlier Windows versions, e.g. Win10 v1709, Win7, etc. - the main appeal of using Windows is the universal support for legacy programs. Please don't make PowerToys another exception to this rule.
Issue 1:
System information (version)

OpenCV => 3.4.0

Operating System / Platform =>windows 7

Compiler => vs c/c++ compiler

Detailed description

Hellow!

I am trying to make an interface with a button to load an image.

I am writing in C and and i tried to use cvCreateButton as described here.

But after building I am getting this error:

Severity	Code	Description	Project	File	Line	Suppression State Error	LNK2001	unresolved external symbol cvCreateButton

I wrote this :

void ButtonCall(int state, void *userdata) {

printf("ok");

}

And this in another function :

cvCreateButton("button", ButtonCall, NULL, CV_PUSH_BUTTON, 1);

Issue 2:
System information (version)

OpenCV => :4.1.2:

Operating System / Platform => :Windows 7:

Compiler => ❔(I amusing python)

Openvino => :2019.3:

Detailed description

While loading pretrained model face-detection-adas-0001 , it thrown an error,

I found similar question answer but not working Failed to initialize Inference Engine backend: Unsupported primitive of type:

By the answer,

I have build the cpu_extension.dll available in build , As i copied it to

C:\Program Files (x86)\IntelSWTools\openvino\bin\intel64\Release there was no folder , i created ans pasted.

I again ran model using code

def load_to_IE(model_xml):
plugin = IECore()
model_bin = os.path.splitext(model_xml)[0] + '.bin'
net = IENetwork(model=model_xml, weights=model_bin)
plugin.load_network(net, "CPU")
print("IR loaded successfully")
return True

load_to_IE('C:\\Users\\ra\\Desktop\\projects\\Entertainment\\age-gender-face-detection-project\\models\\face-detection-adas-0001\\FP16\\face-detection-adas-0001.xml')

Again throws error

Traceback (most recent call last):

File "feed_network.py", line 50, in

load_to_IE('C:\Users\ra\Desktop\projects\Entertainment\age-gender-face-detection-project\models\face-detection-adas-0001\FP16\face-detection-adas-0001.xml')

File "feed_network.py", line 45, in load_to_IE

plugin.load_network(net, "CPU")

File "ie_api.pyx", line 85, in openvino.inference_engine.ie_api.IECore.load_network

File "ie_api.pyx", line 92, in openvino.inference_engine.ie_api.IECore.load_network

RuntimeError: Unsupported primitive of type: PriorBox name: fc7_mbox_priorbox

but other pretrained models works however.

Steps to reproduce
Issue 1:

Issue 2:
Make sure these boxes are checked before submitting your issue - thank you!

I have checked the superset logs for python stacktraces and included it here as text if any

I have reproduced the issue with at least the latest released version of superset

I have checked the issue tracker for the same issue and I haven't found one similar

Superset version

0.23.0

Expected results

I have a fairly complex dashboard with dozens of slices configured. I'd like to duplicate (via SQL or programmatically if required) the entire dashboard multiple times along with all it's slices, metadata, etc.

The use case is configuring a single customer-specific BI dashboard "template" that can be repurposed without constructing the entire dashboard from scratch.

Curious to hear if there is any way to accomplish this
Issue 1:
VSCode Version: 1.0.0-alpha

OS Version: Windows10

Steps to Reproduce:

Launch app and open any folder which contains ts project.

Click on extension update icon from status bar to get info about extension to be updated.

Try to uninstall any previously installed extension by clicking on remove extension icon from update extension list.

Note: I am able to uninstall extension from installed extension list.

Actual: Getting error message while trying to remove extension from update window.

Expected: User should be able to uninstall extension if he doesn't want to update.

Dev tool error log message:

workbench.main.js:91 Could not find extension: Error: Could not find extension, at c:\Program Files (x86)\Microsoft VS Code Alpha\resources\app\out\vs\workbench\electron-main\sharedProcessMain.js:7:30783, at Object.p [as _notify](c:Program Files %28x86%29Microsoft VS Code Alpharesourcesappoutvsworkbenchelectron-mainsharedProcessMain.js:5:1987), at Object.__dirname.undefined.N.enter (c:\Program Files (x86)\Microsoft VS Code Alpha\resources\app\out\vs\workbench\electron-main\sharedProcessMain.js:5:5149), at __dirname.undefined.t.Class.define._run (c:\Program Files (x86)\Microsoft VS Code Alpha\resources\app\out\vs\workbench\electron-main\sharedProcessMain.js:5:6975), at __dirname.undefined.t.Class.define._completed (c:\Program Files (x86)\Microsoft VS Code Alpha\resources\app\out\vs\workbench\electron-main\sharedProcessMain.js:5:6416), at FSReqWrap.cb as oncompletee.doShow @ workbench.main.js:91

Issue 2:
VSCode Version: 1.1.0

OS Version: Windows 10

Steps to Reproduce:

Open User Settings file settings.json

Suppose you are going to add a new setting

Press ctrl + space and scroll to editor.lineHeight
Issue 1:
We're working on upgrading Next.js from 2.1.1 to 2.3.1 after reading about all the speed optimizations. We're receiving the following warning about the three preloaded scripts that are now included in the head of the page:

Did we misconfigure something that's causing these scripts to wait on something else to load?

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

Expected Behavior

When building my app using NODE_ENV=production next build, it should only count the actual pages.

Current Behavior

When building my app using NODE_ENV=production next build, it is grabbing any file that is .js under /pages folder.

This includes:

test files (in my case, *.test.js)

page specific components, containers, and views

Context

This results in, the pre-defined webpack.js, having "104 total pages" of which, I really have 12-ish pages. So when it goes to try to bundle "common" modules (ie. lodash, momentjs) they end up not getting bundled because the defined plugin looks for count to be greater than or equal to 1/2 the pages. Lodash usage count is 9-54x and Moment.js usage count is ~24x. These should easily get bundled based on usage and actual pages.

Another option would be to allow a way to define our own bundling methods. Currently, I couldn't figure out a way to accomplish that.

Your Environment

Tech
Version

next
v6

node
v9.11.1

OS
Win 10

browser
Chrome 66

etc
Issue 1:
Is there a way to toggle babel via comments within code?

E.g:

// code for babel to transpile...

/*babel: disable */
// "MASSIVE" inlined 3rd party library here...
/*babel: enable */

// code for babel to transpile...

Issue 2:
I'd like to be able to specify compile options in comments, similar to JSHint, JSCS and the Traceur REPL. For example:

JSHint comments are in the format:

/* exported Harmonic */
/* global __HARMONIC */
/* jshint mocha: true */

JSCS comment directive example:

// jscs: disable disallowSpacesInFunctionExpression, disallowSpacesInAnonymousFunctionExpression

Traceur REPL example:

// Options: --async-functions

Could 6to5 support a similar comment syntax to specify file-specific configs? For instance, it could be a comment that begins with 6to5: followed by a JSON/JS object literal containing options that get merged into the current configs. Whitespace before/after the "6to5:" prefix could be disregarded for readability/user-friendliness. Example:

// 6to5: { optional: null, experimental: true }

To avoid unnecessary complexity, those options could only be valid at the top of the file before any source code (other than comments and whitespace) are processed.

And if this sounds like a reasonable request, have no rush, this can be implemented and documented after the rebranding if you prefer. 😛
Issue 1:
https://k8s-gubernator.appspot.com/build/kubernetes-jenkins/pr-logs/pull/31221/kubernetes-pull-build-test-e2e-gce/56936/

Failed: [k8s.io] InitContainer should invoke init containers on a RestartAlways pod {Kubernetes e2e suite}

/go/src/k8s.io/kubernetes/_output/dockerized/go/src/k8s.io/kubernetes/test/e2e/framework/framework.go:134
Sep 1 04:26:51.696: Couldn't delete ns: "e2e-tests-init-container-9wyzy": the server could not find the requested resource
/go/src/k8s.io/kubernetes/_output/dockerized/go/src/k8s.io/kubernetes/test/e2e/framework/framework.go:338

Happened on a presubmit run in #31221.

Issue 2:
The client library has NewGenericServerResponse for handling unexpected errors. It's supposed to be invoked in transformUnstructuredResponseError which is called from transformResponse. That error is supposed to be semantically equal to valid api.StatusErrors returned by the server so that apierrors.IsNotFound(err) would return true for any 404.

In #31873 the teardown code of e2e tests which delete the namespace get back an error (that from the apiserver reports a 404) but that error does not report true for apierrors.IsNotFound(err). As a result it flags the error.

Either the error from the server is wrong (malformed, bad content type, bad proxy) or the client is improperly handling the response. I can't find any proof that the client mishandles generic 404s from the server (via restclient transformUnstructuredResponseError).

Setting to p1 while I triage to see what the impact of correcting the issue is. Potentially 1.4 if this indeed is hiding / causing other errors.
Issue 1:
Installed TF with following command pip3 install tensorflow. The installation is successful but gave me this error.

tensorflow 1.10.1 has requirement numpy<=1.14.5,>=1.13.3, but you'll have numpy 1.15.1 which is incompatible.

Do I need to downgrade my numpy version?

Issue 2:
I have successfully built tensorflow 1.10.1 from source but when I installed the whl with pip3 it downloaded and installed numpy-1.14.5 and removed numpy-1.15.1.

After tensorflow was installed I manually uninstalled numpy-1.14.5 and reinstalled numpy-1.15.1, pip gave a warning that tensorflow-1.10.1 requires numpy <= 1.14.5 but went ahead anyway. Afterwards I ran some tests on tensorflow and it works just fine with numpy 1.15.1 so this requirement appears to be unnecessary. Edited: there is no complaint about incompatibility with numpy-1.15.1 for tensorflow-1.9

Is there a file I can edit to get rid of this requirement? I am ok with compiling again.

OS Ubuntu 16.04.5 LTS 64 bits , python3.5 (cuda-9.2)
Issue 1:
Axel Fontaine opened SPR-6901 and commented

Using the regular task:scheduler element in conjunction with the task:scheduled-tasks element, results, at least with Tomcat, in a server that is unable to shut down.

The server hangs after having logged the following statement:

Destroying singletons in org.springframework.beans.factory.support.DefaultListableBeanFactory@d81cda: defining beans []; parent: org.springframework.beans.factory.support.DefaultListableBeanFactory@1d49247

Manually defining a task scheduler and setting the threads to run as daemon provides a workaround:

<task:scheduled-tasks scheduler="taskScheduler">
<task:scheduled ref="myTask" method="run" cron="0 0 0 * * ?"/>
</task:scheduled-tasks>

<bean id="taskScheduler" class="org.springframework.scheduling.concurrent.ThreadPoolTaskScheduler">
<property name="daemon" value="true"/>
</bean>

However this is only a workaround, and the default behavior should work out of the box. As you can see from the forum post reference, I am not the only one facing this issue.

Affects: 3.0.1

Reference URL: http://forum.springsource.org/showthread.php?t=83687

Issue Links:

#11620 TaskExecutor created with task:executor not shutdown when context closes ("duplicates")

#11620 TaskExecutor created with task:executor not shutdown when context closes

#11890 Tomcat does not shutdown correctly when using @Scheduled

Referenced from: commits 8d7df01, bca067a

Issue 2:
Bozhidar Bozhanov opened SPR-8607 and commented

(This is not an issue for the code or the framework, so this might not be the right place for it, but I don't see where to report it)

The issue reporting interfaces has some serious drawbacks:

you can't edit your own bug report. If you mistype something in the title, or want to add a stacktrace/code to the description, you can't.

you can't edit your own comments below the issue

Tomcat has a stable version 7 for a year already and it does not appear in the list of tomcat versions. Perhaps it's the same for other containers/servers.

Affects version/s does not provide an option for "SNAPSHOT". I'm using the snapshot builds, but have to report M2

This issue is a sub-task of #12773

Issue Links:

#13889 Unable to edit JIRA issue description after creation ("is duplicated by")

2 votes, 4 watchers