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

Incorrect ussage of meta tag "dont_merge_cookies" here, causes cookie application here to be skipped.

This is in conflict with defined specs in docs.

Steps to Reproduce

Create a simple spider performing a request with manually set cookies.

Enable CookieMiddleware

add "dont_merge_cookies: True" to the request meta

yield the request

Expected behavior: Request goes out with manual cookies and without stored cookies.

Actual behavior: Request goes out without any cookies.

Reproduces how often: 100%

Versions

2.6.1

Issue 2:
This example is straight from the documentation, and does not work because if dont_merge_cookies is set on the request, then the cookie middleware skips all cookie processing and no cookies are ever set.

Request(url="http://www.example.com",
cookies={'currency': 'USD', 'country': 'UY'},
meta={'dont_merge_cookies': True})

Does not work, however, this does:

Request(url="http://www.example.com",
cookies={'currency': 'USD', 'country': 'UY'})
Issue 1:
The checks in Base_Estimator._get_param_names() mean that subclasses of mixture.GMM that override __init__() must repeat the defaults for all of its keyword arguments, violating DRY. For example, running:

from sklearn import mixture

class My_GMM(mixture.GMM):

def __init__(self, *args, **kwargs):
mixture.GMM.__init__(self, *args, **kwargs)

print My_GMM()

gives the following exception:

RuntimeError: scikit learn estimators should always specify their parameters in the signature of their init (no varargs).

In other words, this seems to me like a problematic overloading of the constructor signature, and it makes it difficult to subclass mixture.GMM.

Thanks for your hard work on scikit-learn!

Issue 2:
Currently RFECV fits the estimator twice for each setting of number of selected features.

I think it could be sped up by a factor of two by not running the RFE estimator. Maybe the inner loop of rfe should be factored out.

Also see: #2403 (comment)
Issue 1:
新版本能不能支持下 tesla k40m的显卡

Issue 2:
🐛 Bug

I am using a Tesla K40m, installed pytorch 1.3 with conda, using CUDA 10.1

To Reproduce

Steps to reproduce the behavior:

Have a box with a Tesla K40m

conda install pytorch cudatoolkit -c pytorch

show cuda is available

python -c 'import torch; print(torch.cuda.is_available());'
>>> True

Instantiate a model and call .forward()

Traceback (most recent call last):
File "./baselines/get_results.py", line 395, in <module>
main(args)
File "./baselines/get_results.py", line 325, in main
log_info = eval_main(eval_args)
File "/mnt/cdtds_cluster_home/s0816700/git/midi_degradation_toolkit/baselines/eval_task.py", line 165, in main
log_info = trainer.test(0, evaluate=True)
File "/mnt/cdtds_cluster_home/s0816700/git/midi_degradation_toolkit/mdtk/pytorch_trainers.py", line 110, in test
evaluate=evaluate)
File "/mnt/cdtds_cluster_home/s0816700/git/midi_degradation_toolkit/mdtk/pytorch_trainers.py", line 220, in iteration
model_output = self.model.forward(input_data, input_lengths)
File "/mnt/cdtds_cluster_home/s0816700/git/midi_degradation_toolkit/mdtk/pytorch_models.py", line 49, in forward
self.hidden = self.init_hidden(batch_size, device=device)
File "/mnt/cdtds_cluster_home/s0816700/git/midi_degradation_toolkit/mdtk/pytorch_models.py", line 40, in init_hidden
return (torch.randn(1, batch_size, self.hidden_dim, device=device),
RuntimeError: CUDA error: no kernel image is available for execution on the device

First tried downgrading to cudatoolkit=10.0, that exhibited same issue.

The code will run fine if you repeat steps above but instead conda install pytorch=1.2 cudatoolkit=10.0 -c pytorch.

Expected behavior

If no longer supporting a specific GPU, please bomb out upon load with useful error message.

Environment

Unfort ran your script after I 'fixed' so pytorch version will be 1.2 here - issue encountered with version 1.3.

Collecting environment information...
PyTorch version: 1.2.0
Is debug build: No
CUDA used to build PyTorch: 10.0.130

OS: Scientific Linux release 7.6 (Nitrogen)
GCC version: (GCC) 4.8.5 20150623 (Red Hat 4.8.5-36)
CMake version: version 2.8.12.2

Python version: 3.7
Is CUDA available: Yes
CUDA runtime version: Could not collect
GPU models and configuration: GPU 0: Tesla K40m
Nvidia driver version: 430.50
cuDNN version: /usr/lib64/libcudnn.so.6.5.18

Versions of relevant libraries:
[pip3] numpy==1.16.3
[pip3] numpydoc==0.8.0
[conda] blas 1.0 mkl
[conda] mkl 2019.4 243
[conda] mkl-service 2.3.0 py37he904b0f_0
[conda] mkl_fft 1.0.15 py37ha843d7b_0
[conda] mkl_random 1.1.0 py37hd6b4f25_0
[conda] pytorch 1.2.0 py3.7_cuda10.0.130_cudnn7.6.2_0 pytorch
[conda] torchvision 0.4.0 py37_cu100 pytorch

cc @ezyang @gchanan @zou3519 @jerryzh168 @ngimel
Issue 1:
I just installed the atom.

Over this screen that appears when trying to open any file.

Issue 2:
It has come out this error starting Atom

TypeError: Unable to watch path
at HandleWatcher.start (/opt/atom/resources/app/node_modules/pathwatcher/lib/main.js:66:29)
at new HandleWatcher (/opt/atom/resources/app/node_modules/pathwatcher/lib/main.js:30:12)
at new PathWatcher (/opt/atom/resources/app/node_modules/pathwatcher/lib/main.js:120:30)
at Object.exports.watch (/opt/atom/resources/app/node_modules/pathwatcher/lib/main.js:179:12)
at Config.module.exports.Config.observeUserConfig (/opt/atom/resources/app/src/config.js:90:109)
at Config.module.exports.Config.load (/opt/atom/resources/app/src/config.js:67:19)
at Atom.module.exports.Atom.startEditorWindow (/opt/atom/resources/app/src/atom.js:368:19)
at Object.<anonymous> (/opt/atom/resources/app/src/window-bootstrap.js:14:8)
at Object.<anonymous> (/opt/atom/resources/app/src/window-bootstrap.js:20:4)
at Module._compile (module.js:455:26)
at Object.Module._extensions..js (module.js:473:10)
at Module.load (/opt/atom/resources/app/node_modules/coffee-script/lib/coffee-script/register.js:45:36)
at Function.Module._load (module.js:311:12)
at Module.require (module.js:363:17)
at require (module.js:379:17)
at window.onload (file:///opt/atom/resources/app/static/index.js:20:5)
Issue 1:
Just a heads up that Lerna has changed to a non-FLOSS license: lerna/lerna#1616

I haven't seen any indication of whether the Lerna devs intend to change the license of version 2 as well. Pinning to 2.11.0 or 3.2.1 may be wise anyway, unless/until someone commits to maintaining a FLOSS licensed fork.

Issue 2:
test/node_modules/babel-core/lib/babel/transformation/transformer.js:97
throw new TypeError("Transformer " + this.key + " is resolving to a diff
^
TypeError: Transformer foo is resolving to a different Babel version to what is doing the actual transformation...
at Transformer.buildPass (test/node_modules/babel-core/lib/babel/transformation/transformer.js:97:13)
at File.addPlugin (test/node_modules/babel/node_modules/babel-core/lib/babel/transformation/file/index.js:287:48)
at File.buildTransformers (test/node_modules/babel/node_modules/babel-core/lib/babel/transformation/file/index.js:215:12)
at new File (test/node_modules/babel/node_modules/babel-core/lib/babel/transformation/file/index.js:88:10)
at Object.transform (test/node_modules/babel/node_modules/babel-core/lib/babel/transformation/index.js:18:14)
at Object.exports.transform (test/node_modules/babel/bin/babel/util.js:33:22)
at Object.exports.compile (test/node_modules/babel/bin/babel/util.js:41:18)
at test/node_modules/babel/bin/babel/file.js:112:25
at arrayEach (test/node_modules/babel/node_modules/lodash/index.js:1342:13)
at Function.<anonymous> (test/node_modules/babel/node_modules/lodash/index.js:3299:13)

there is no npm links and any kind of locally installed babel. simple downgrading to babel*@5.0 with the same code works fine. am I missing some breaking changes about this?
Issue 1:
Currently, the stringer tool generates the method func (t Type) String() string to get the string name of an enum value.

In several projects I have had the need of exactly the opposite: get the enum value from the string name (for example when parsing a flag or when reading a configuration file).

I have ended up using a switch or a map, but I don't like it as I have to manually maintain it when values are added/changed/deleted. So the next step is to auto-generate it, just like the stringer tool does.

I was wondering if adding this functionality to stringer would be adequate for you guys. In my opinion, it seems pretty convenient and fits very well in that tool. I am sure there will be other people in the same situation than me that will benefit from it.

A possible signature for the generated function could be:

func <Type>FromString(s string) (<Type>, error) {...}

// Or
func <Type>String(s string) (<Type>, error) {...}

For example, if the type is Pill the function would be

func PillFromString(s string) (Pill, error) {...}

// Or
func PillString(s string) (Pill, error) {...}

The implementation could leverage the same variable the stringer tool already generates (a string or a map, depending on the number of runs found in the enum values). This requires a deeper reasoning (maybe a switch is the best option here)

Having an error as a second return value is needed to notify about strings that do not belong to the enum type.

The code to add is relatively simple and I can contribute with the needed changes.

Before doing that, I would like to hear your opinions/suggestions and know if you finally agree.

Issue 2:
by cooldudevamsee:

On ubuntu server, I have been trying to install go and was able to install go partially.
8l & three more binaries are getting built in GOBIN but not 8g. Issue found to be
missing package bison. There is no meaningful error to report missing dependencies
during build process.

Thanks.
Issue 1:
I discovered this fact while working with something like the following:

julia> da = distribute(1:10)
10-element DArray{Int64,1,UnitRange{Int64}}:
1
2
3
4
5
6
7
8
9
10

julia> [println((myid(), x)) for x in da];
(1,1)
(1,2)
(1,3)
(1,4)
(1,5)
(1,6)
(1,7)
(1,8)
(1,9)
(1,10)

julia> map((x) -> println((myid(), x)), da);
From worker 2: (2,1)
From worker 3: (3,6)
From worker 2: (2,2)
From worker 2: (2,3)
From worker 2: (2,4)
From worker 2: (2,5)
From worker 3: (3,7)
From worker 3: (3,8)
From worker 3: (3,9)
From worker 3: (3,10)

Which raises the obvious question: why don't array comprehensions simply desugar into maps? This smells of bad language design that apparently identical language features have subtly different semantics.

Issue 2:
typeof(map(x -> x^2, [1,2,3])) = Array{int64,1}

typeof([ x^2 | x=[1,2,3]) = Array{Any, 1}

It seems odd that the comprehension loses the type information, while map retains it.
Issue 1:
Panel footer always in default style, please, create new style for panel footer like panel header.

Issue 2:
Perhaps this was just an oversight, but I was surprised to see that the .panel-footer class isn't set to pick up the contextual panel styles.

Since the existing contextual panel styles (.panel-primary, etc.) don't just affect the background and border colors of .panel-heading, but also the border color for .panel itself, it seems odd that .panel-footer isn't also styled accordingly.

See the following examples:

Bootstrap 3 RC2 Contextual Panel with Panel Footer

Proposed Panel with Contextual Panel Styles Applied to Panel Footers
Issue 1:
Why the module "online_lda.py" can not output normalized doc_topic_distr results? The output results are as follows by using the method "transform" in "online_lda.py":

[[ 2.04193151e-01 1.38896560e+03 2.54894246e+04 2.01201552e-01

2.04449849e-01]

[ 9.88263272e+01 2.02878480e-01 2.05994398e-01 5.55780125e+00

2.06998619e-01]

[ 2.05757668e-01 2.03309842e-01 5.91117318e+02 2.02568793e-01

7.82271046e+02]

...,

[ 2.04400893e-01 2.03986500e-01 1.94936093e+01 6.18911215e+01

2.06881787e-01]

[ 2.04500854e-01 2.02546454e-01 5.16339944e+01 7.84807328e+01

2.14782255e+01]

[ 9.45892479e+01 2.02775532e-01 2.04726492e-01 2.03766982e-01

6.67994831e+01]]

Issue 2:
Why i can't get the normalized doc_topic_distr results by using the module "online_lda.py" ? Who can answer me? Thanks!!!

[[ 2.04193151e-01 1.38896560e+03 2.54894246e+04 2.01201552e-01

2.04449849e-01]

[ 9.88263272e+01 2.02878480e-01 2.05994398e-01 5.55780125e+00

2.06998619e-01]

[ 2.05757668e-01 2.03309842e-01 5.91117318e+02 2.02568793e-01

7.82271046e+02]

...,

[ 2.04400893e-01 2.03986500e-01 1.94936093e+01 6.18911215e+01

2.06881787e-01]

[ 2.04500854e-01 2.02546454e-01 5.16339944e+01 7.84807328e+01

2.14782255e+01]

[ 9.45892479e+01 2.02775532e-01 2.04726492e-01 2.03766982e-01

6.67994831e+01]]
Issue 1:
Actual Behavior

When trying to create new flask object, I get following error:

>>> from flask import Flask
>>> flask_app = Flask(__name__)
python: ../Python-2.7.14/Python/symtable.c:1319: symtable_visit_params: Assertion `arg->v.Name.ctx == Param || (arg->v.Name.ctx == Store && !toplevel)' failed.
Aborted

Environment

Python version: 2.7.14

Flask version: 1.0.3

Werkzeug version: 0.15.4

Issue 2:
When trying to create new flask object, I get following error:

>>> from flask import Flask
>>> flask_app = Flask(__name__)
python: /mnt/builds/jenkins-builds/workspace/pulsar-8/RC/icedge-apl-4/build-intel-apollolake/tmp/work/core2-64-wrs-linux/python/2.7.9-r1/Python-2.7.9/Python/symtable.c:1319: symtable_visit_params: Assertion `arg->v.Name.ctx == Param || (arg->v.Name.ctx == Store && !toplevel)' failed.
Aborted (core dumped)

This assertion error only shows up with Werkzeug version 0.15.3 and 0.15.4. It doesn't appear with version 0.15.2.

OS: Pulsar Linux 8.0.0.14

Python: 2.7.9

Flask: 1.0.2
Issue 1:
Can someone help me, how to refresh the page and call getInitialProps again when i click on back button of the browser? i got no answer on StackOverflow and Gitter so..

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

Your Environment

Tech
Version

next
latest

node
9.4.0

OS
Mac

browser
Chrome

etc

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

I'll start by saying this might be a misunderstanding of mine, but I have gone over this a few times and believe there is an issue here. My apologies if I am mistaken!

Expected Behavior

In the with-mobx example: https://github.com/zeit/next.js/tree/master/examples/with-mobx

The store is implemented both on the server side and on the client side.

As explained in the README, on the server-side a new instance is created for each page request so as not to mix between users/requests, etc. On the client side, it is a singleton so that different components/pages will have the same state and to allow us to keep a global state.

The way the example implements it, state created by the server will be propagated to the client but not to the client's store.

Since getInitialProps on first load is run on the server: https://github.com/zeit/next.js/blob/master/examples/with-mobx/pages/index.js#L7-L11

Then the isServer property will be true on first load on the client as well: https://github.com/zeit/next.js/blob/master/examples/with-mobx/pages/index.js#L15

This would mean that the store created on the client will not be a singleton, and when we navigate to other pages with Link, a new store will be created without the state data propagated from the server.

My desired (expected) behaviour would be to have some way to distinguish between client and server when creating the store even on initial page load (this is critical, to my understanding, for keeping global state between pages). I'm currently achieving this with something like:

getInitialProps ({req}) {
// ...
// here returning isServer as !!req would not be good
// this is not run on the client on initial load,
// so in that case props.isServer would be true on the client as well
return { myData }
}
constructor (props) {
const isServer = typeof window === undefined
initStore(isServer, props.myData)
}

Current Behavior

The example uses const isServer = !!req inside getInitialProps - this results in the initial server begotten state not being stored in the client store.

Context

If I want to store global state, I am only able to do that starting from the second page I navigate to using the with-mobx example. In my workaround I use (as mentioned above) const isServer = typeof window === undefined which I think is a somewhat non-native to next.js solution... if you have a better suggestion I would love to hear it!

I'm mostly opening this issue because I think I won't be the only one affected and confused by it.
Issue 1:
When a tab control is first mounted there is an animation of the indicator to the first selected index.

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

Expected Behavior

The tab indicator should not animate to the first tab index, it should already be there.

Current Behavior

The tab indicator is animated until it reach the first selected index.

Your Environment

Tech
Version

Material-UI
latest beta

React
16

browser
chrome 63

etc
TS 2.6.2

Issue 2:
I came up with a simple idea to make material-ui exportable as bootstrap 3/foundation 5 extension so it will be possible to apply material-ui colors, addons and overrides to these frameworks.
Issue 1:
When my site gets a lot of traffic, I will get a lot of errors like this

request.CRITICAL: Uncaught PHP Exception PDOException: "SQLSTATE[HY000]: General error: 1205 Lock wait timeout exceeded; try restarting transaction" at /var/www/symfony/vendor/symfony/symfony/src/Symfony/Component/HttpFoundation/Session/Storage/Handler/PdoSessionHandler.php line 336

The problem is that I have the lock_mode set to 0 so there shouldn't be any transactions involved in my sessions.

Issue 2:
After upgrading to 2.6.3 and switching to the new PdoSessionHandler schema I have been getting these errors in my log sporadically:

[2015-01-12 13:28:59] request.CRITICAL: Uncaught PHP Exception PDOException: "SQLSTATE[HY000]: General error: 1205 Lock wait timeout exceeded; try restarting transaction" at /../vendor/symfony/symfony/src/Symfony/Component/HttpFoundation/Session/Storage/Handler/PdoSessionHandler.php line 513 {"exception":"[object] (PDOException(code: HY000): SQLSTATE[HY000]: General error: 1205 Lock wait timeout exceeded; try restarting transaction at /../vendor/symfony/symfony/src/Symfony/Component/HttpFoundation/Session/Storage/Handler/PdoSessionHandler.php:513)"} []

It doesn't appear to be affecting the end users. Seems like it is happening silently.

I followed the updated cookbook article: http://symfony.com/doc/current/cookbook/configuration/pdo_session_storage.html

The sessions table is in the same database as my app. Could that be causing the problem? Reading the comments for PdoSessionHandler::LOCK_TRANSACTIONAL this should not use the same connection but this wouldn't be the case, would it?

I am using MySQL.
Issue 1:
Original ticket http://projects.scipy.org/scipy/ticket/1078 on 2009-12-28 by @kwgoodman, assigned to unknown.

The kmeans function has two modes. In one of the modes the initial

guesses for the centroids are randomly selected from the input data.

The selection is currently done with replacement:

guess = take(obs, randint(0, No, k), 0)

That means some of the centroids in the intial guess might be the

same. I think it would be better to select without replacement:

guess = take(obs, rand(No).argsort()[:k], 0)

Here's an extreme example of what can go wrong if the selection is

done with replacement:

>> obs

array([[ 1, 1],
[-1, -1],
[-1, 1],
[ 1, -1]])
>> vq.kmeans(obs, k_or_guess=4)

(array([[-1, -1],
[-1, 1],
[ 1, -1],
[ 1, 1]]), 0.0) # <--- good
>>
>> k_or_guess = obs[[1,1,1,1],:]
>> k_or_guess

array([[-1, -1],
[-1, -1],
[-1, -1],
[-1, -1]])
>> vq.kmeans(obs, k_or_guess)
(array([[0, 0]]), 1.4142135623730951) # <--- not as good

In most cases it won't make any difference. But the cost of the code

change is small.

Issue 2:
In scipy.cluster.vq.kmeans, the initial guess for the code book uses numpy.random.randint to select observations from the input data. However, randint may return the same index more than once, which produces undesirable results. kmeans2 appears to avoid this by using np.random.permutation.
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:2.7.7

Operating System version: centos7

Java version: 1.8

漏洞链接：http://www.cnnvd.org.cn/web/xxk/ldxqById.tag?CNNVD=CNNVD-202004-377

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: 2.7.3

Operating System version: MacOs

Java version: 1.8

Steps to reproduce this issue

1.start DemoService provider

2.Set onreturn and onthrow for sayHello method in async mode, and then start consumer.

<bean id="demoCallback" class="com.alibaba.dubbo.samples.notify.impl.NotifyImpl" />
<dubbo:reference id="demoService" interface="com.alibaba.dubbo.DemoService">
<dubbo:method name="sayHello" onreturn="demoCallback.onreturn" onthrow="demoCallback.onthrow"/>
</dubbo:reference>

send a request in async mode.

When timeout occurred, demoCallback.onthrow callback have not been invoked.

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

Expected Result

onthrow callback should be invoked.

Actual Result

onthrow have not be invoked.

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

Once exception occurs, CallbackRegistrationInvoker onError will be invoked

@Override
public Result invoke(Invocation invocation) throws RpcException {
Result asyncResult = filterInvoker.invoke(invocation);

asyncResult = asyncResult.whenCompleteWithContext((r, t) -> {
for (int i = filters.size() - 1; i >= 0; i--) {
Filter filter = filters.get(i);
// onResponse callback
if (filter instanceof ListenableFilter) {
Filter.Listener listener = ((ListenableFilter) filter).listener();
if (listener != null) {
if (t == null) {
listener.onResponse(r, filterInvoker, invocation);
} else {
listener.onError(t, filterInvoker, invocation);
}
}
} else {
filter.onResponse(r, filterInvoker, invocation);
}
}
});
return asyncResult;
}

But, the FutureListener's onError is not implemented, cannot invoke the onreturn/onerror callback.

class FutureListener implements Listener {
@Override
public void onResponse(Result result, Invoker<?> invoker, Invocation invocation) {
if (result.hasException()) {
fireThrowCallback(invoker, invocation, result.getException());
} else {
fireReturnCallback(invoker, invocation, result.getValue());
}
}

@Override
public void onError(Throwable t, Invoker<?> invoker, Invocation invocation) {

}
}