WhereIsAI/github-issue-similarity huggingface dataset:
Issue 1:
Description of the new feature/enhancement

Currently it is not possible to set colorScheme or padding on a global level, only per profile.

Proposed technical implementation details (optional)

Every setting that can be per-profile, minus the obvious ones like name and guid etc, should be able to be set on a global level as well.

Issue 2:
Windows 10 1903 Build 18362.449

Terminal version 0.6.2951.0

Steps to reproduce

Drag the window from either the right or left side and shrink it until the tabs are no longer visible. Extend the window back out until there is enough room for a few tabs.

Expected behavior

The tabs disappear when the window becomes to small to display them. Then slide back out when the window is resized to fit them again.

Actual behavior

The tabs don't reappear on the tab bar unless you click to add a new tab, then they all pop back in. The tab bar scroll buttons are there but don't so anything when clicked.
Issue 1:
It always open in the same window.

Also, when there is an instance of vscode running, runs code . on terminal brings up that instance instead of opening new window with the current folder nor open the current folder on the existing instance.

Issue 2:
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 1:

Issue 2:
Hi,

I just can't use the website with Safari as of the release of the new design.

At any given time there is a blank panel on the right site of the webpage, the only links I can click on are map and chat, they both pop out a new panel that overlaps the blank one, but if I close the panel it does not dismiss the blank one. Screenshot for clarification

Website works fine on Chrome or Firefox on my computer, so I guess its just an safari Issue?
Issue 1:
🚀 Feature request

We have:

finetune_trainer.py has

n_train: Optional[int] = field(default=-1, metadata={"help": "# training examples. -1 means use all."})
n_val: Optional[int] = field(default=-1, metadata={"help": "# validation examples. -1 means use all."})
n_test: Optional[int] = field(default=-1, metadata={"help": "# test examples. -1 means use all."})

some other run_ scripts use --n_obs

--max_steps in the main trainer - which works only on the train_dataset - no ability to limit items on eval_dataset

Requests/Questions:

How does one use --max_steps if one needs to use a different number of items for train and eval?

Can we have a consistent way across examples to do this same thing?

Thank you.

@sgugger

Issue 2:
The examples have an incosistency of how the cl args are defined and parsed. Some rely on PL's main args as finetune.py does: https://github.com/huggingface/transformers/blob/master/examples/seq2seq/finetune.py#L410

parser = argparse.ArgumentParser()
parser = pl.Trainer.add_argparse_args(parser)

others like run_pl_glue.py rely on lightening_base.py's main args: https://github.com/huggingface/transformers/blob/master/examples/text-classification/run_pl_glue.py#L176

parser = argparse.ArgumentParser()
add_generic_args(parser, os.getcwd())

now that we pushed --gpus into lightening_base.py's main args the scripts that run PL's main args collide and we have:

fail.argparse.ArgumentError: argument --gpus: conflicting option string: --gpus

i.e. PL already supplies --gpus and many other args that some of the scripts in examples re-define.

So either the example scripts need to stop using pl.Trainer.add_argparse_args(parser) and rely exclusively on lightning_base.add_generic_args, or we need a different clean approach. It appears that different scripts have different needs arg-wise. But they all use lightning_base.

The problem got exposed in: #6027 and #6307
Issue 1:
Elasticsearch version: 2.3.1

JVM version:

[gsmith@crowley ~ ] > java -version

java version "1.8.0_45"

Java(TM) SE Runtime Environment (build 1.8.0_45-b14)

Java HotSpot(TM) 64-Bit Server VM (build 25.45-b02, mixed mode)

OS version: OS X 10.10.5

Description of the problem including expected versus actual behavior:

Response to _cat/fielddata when there is an actual "ip" field in the indexed data reports the IP address of the node in the column where the size of fielddata used by the "ip" field should appear.

Steps to reproduce:

#0. Delete the index
DELETE test_field_data
#1. Create the index with a document:
POST test_field_data/test_field_data
{"reason": "something is off", "ip": "192.168.1.0"}
#2. Flush
POST _flush
#3. Perform a search that loads fielddata
GET test_field_data/_search
{
"query": {
"match_all": {}
},
"aggs": {
"ip": {
"terms": {
"field": "ip",
"size": 10
}
},
"reason": {
"terms": {
"field": "reason",
"size": 10
}
}
}
}
#4. Inspect the fielddata
GET _cat/fielddata/ip,reason?v

The return looks like:

id host ip node total reason ip
FNsjPCVATN-xsg7O0vxIuQ 127.0.0.1 127.0.0.1 only 2.8kb 488b 127.0.0.1

I have also seen a response from a 3 node cluster, also v 2.3.1, where two of the nodes are reported as shown above, and the third node actually has the fielddata usage reported, both in the correct place and in the column where the node ip address is supposed to appear.

Issue 2:
If you have minimum_master_nodes set and you don't supply enough nodes in d.z.p.unicast.hosts, a node can fail to join the cluster. Described at http://thread.gmane.org/gmane.comp.search.elasticsearch.user/740.
Issue 1:
Bug Report

Current Behavior

when using babel with plugin-transform-flow-strip-types type imports like import { type MyType } from '...' are not stripped out. Instead they are transformed to require('math');

Input Code

https://babeljs.io/repl/#?babili=false&browsers=&build=&builtIns=false&spec=false&loose=true&code_lz=JYWwDg9gTgLgBAbzjAnmApnAsgQxgCzgF84AzKCEOAchD32oG4g&debug=false&forceAllTransforms=false&shippedProposals=false&circleciRepo=&evaluate=false&fileSize=false&timeTravel=false&sourceType=module&lineWrap=true&presets=react%2Cenv&prettier=false&targets=Node-8.9&version=6.26.0&envVersion=1.6.2

Expected behavior/code

strip out type declaration

Additional context/

Why don't I just use the usual import type { MyType } from '...' you ask...

My form is accepted by flow & intelliSence in VS Code, giving tooltip info on the types, whereas the usual form is accepted, but does not show any type information...

import { type is accepted fine by flow...

Issue 2:
Bug

Named type imports are stripped differently based on which syntax is used. import { type X } from 'X' results in import 'X', while import type { X } from 'X' is stripped completely. As a result, the two statements are not equivalent.

Input Code

import { type X } from 'X';
import type { Y } from 'Y';

Babel Configuration (.babelrc, package.json, cli command)

{
"presets" : ["babel-preset-flow"]
}

Expected Behavior

At the minimum I expect both imports to be treated equally, i.e. either both are stripped or both result in an import. My intuition says that it should be the empty output, since I don't expect types to have runtime behaviour, but flow itself currently doesn't seem to have a stance on this (ref: facebook/flow#4935).

Current Behavior

Output:

import 'X';

Possible Solution

Strip import { type X } statements completely.

Context

I ran into this issue while trying to resolve a circular dependency, where an import { type X } completed the circle (to my surprise). After a long debugging session I noticed that this circle got broken by just replacing import { type X } with import type { X }, something which isn't documented anywhere nor very intuitive.

(The actual context for the circular dependency is quite complicated. If necessary I can still provide it on request)

Your Environment

software
version(s)

Babel
v6.26.0

babel-preset-flow
v6.23.0

node
v8.4.0

npm
v5.3.0

Operating System
Linux (Fedora 25 64-bit)
Issue 1:
I did not really realize that, but the recent change in multi-output behavior means that there are deprecation warnings for each call to score with multi-output data:

DeprecationWarning: Default 'multioutput' behavior now corresponds to 'variance_weighted' value, it will be changed to 'uniform_average' in 0.18.

Is that desired? Is there a way around it?

And do we want to catch them in the tests?

Currently the test output is HUGE.

Issue 2:
There are way too many warnings in the test suite, see https://travis-ci.org/scikit-learn/scikit-learn/jobs/74122431

Function decision_function is deprecated [decision_function was removed from regressors]

DataDimensionalityWarning in random_projection. Not sure if the test should just ignore those or we should have different defaults? ping @ogrisel

"Default 'multioutput' behavior now corresponds to 'variance_weighted' value" not sure if there is a way around these? ping @arjoly @jnothman ?

"The decision_function_shape default value will change from 'ovo' to 'ovr' in 0.18. This will change the shape of the decision function returned by SVC." SVC has a new decision_function shape. Should either be ignored or the shape should be set to ovr explicitly for now.

ConvergenceWarning: Objective did not converge. These are in coordinate_decent in the linear models. I'm not sure when they started showing up. Maybe @agramfort knows?
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: all

Operating System version: win 10

Java version: 1.8

Steps to reproduce this issue

consumer more than one service, and specify duplicated interfaceName with different consumer service, such as

@Reference(check = false, interfaceName = "demoService")
private DemoService demoService;

@Reference(check = false, interfaceName = "demoService")
private DemoServiceB demoServiceB;

run provider

run consumer

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

Expected Result

a more meaningful exception

Actual Result

Caused by: java.lang.IllegalArgumentException: Can not set dubbo.test.api.DemoServiceB field dubbo.test.common.consumer.service.ConsumerServiceDemo.demoServiceB to com.alibaba.dubbo.common.bytecode.proxy0
at sun.reflect.UnsafeFieldAccessorImpl.throwSetIllegalArgumentException(UnsafeFieldAccessorImpl.java:167)
at sun.reflect.UnsafeFieldAccessorImpl.throwSetIllegalArgumentException(UnsafeFieldAccessorImpl.java:171)
at sun.reflect.UnsafeObjectFieldAccessorImpl.set(UnsafeObjectFieldAccessorImpl.java:81)
at java.lang.reflect.Field.set(Field.java:764)
at com.alibaba.dubbo.config.spring.beans.factory.annotation.ReferenceAnnotationBeanPostProcessor$ReferenceFieldElement.inject(ReferenceAnnotationBeanPostProcessor.java:367)
at org.springframework.beans.factory.annotation.InjectionMetadata.inject(InjectionMetadata.java:90)
at com.alibaba.dubbo.config.spring.beans.factory.annotation.ReferenceAnnotationBeanPostProcessor.postProcessPropertyValues(ReferenceAnnotationBeanPostProcessor.java:92)
... 12 more

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

Just put your stack trace here!

I think we should check if the type is matched when the interfaceName of Reference annotation is the same.

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: xxx

Operating System version: xxx

Java version: xxx

Step to reproduce this issue

xxx

xxx

xxx

Expected Result

What do you expected from the above steps？

Actual Result

What is actually happen?

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

Just put your stack trace here!
Issue 1:
Kubernetes version (use kubectl version):

Client Version: version.Info{Major:"1", Minor:"4+", GitVersion:"v1.4.0-alpha.2.1807+f80530c7f77e2f", GitCommit:"f80530c7f77e2fd272e6718b7d1754df0869d478", GitTreeState:"clean", BuildDate:"2016-08-29T12:08:57Z", GoVersion:"go1.6.3", Compiler:"gc", Platform:"linux/amd64"}

Server Version: version.Info{Major:"1", Minor:"4+", GitVersion:"v1.4.0-alpha.2.1807+f80530c7f77e2f", GitCommit:"f80530c7f77e2fd272e6718b7d1754df0869d478", GitTreeState:"clean", BuildDate:"2016-08-29T12:03:17Z", GoVersion:"go1.6.3", Compiler:"gc", Platform:"linux/amd64"}

Environment:

2 kubelet nodes + 1 master, deployed by local vagrant provider

What happened:

While working on #31098 I added --eviction-hard=memory.available<90% to evict pets from node-1. It did its job and they were evicted, but after that pod was constantly re-scheduled onto same node.

What you expected to happen:

Expected that eviction-hard will prevent pod from being scheduled onto the same node, as long as evict condition is preserved.

How to reproduce it (as minimally and precisely as possible):

Create petset (i was using cockroachdb example)

Add --eviction-hard=memory.available<90% (or another condition which will evict pods from node)

I didn't try it with regular pods, so you may need to use my patch #31777

Issue 2:
Description of problem

Create a petset, when pod is evicted, the petset can't create a new pod on other node and make sure pod is running.

Kubernetes version (use kubectl version):

v1.4.0-alpha.2.1427+5b6e1c37c66098

How to reproduce it (as minimally and precisely as possible):

Config kubele eviction-hard="memory.available<${value}"

Create a peset and wait all pod is running

Make node MemoryPressure=true

Check all pod status

What happened:

4. pod is evicted and petset can't create new pod and make sure pod is running.

[root@dhcp-140-39 ~]# kubectl get pod --show-all
NAME READY STATUS RESTARTS AGE
hello-petset-0 0/1 Evicted 0 32m
hello-petset-1 0/1 Evicted 0 24m
[root@dhcp-140-39 ~]# kubectl get petset
NAME DESIRED CURRENT AGE
hello-petset 2 2 32m

What you expected to happen:

4. Petset create new pod on other node and make sure pod is running.
Issue 1:
Didn't find engine for operation quantized::conv_prepack NoQEngine (operator () at ..\aten\src\ATen\native\quantized\cpu\qconv_prepack.cpp:264)

(no backtrace available)

win10

python3.6

pytorch1.3

code:

from torch.quantization import convert

model_quantized_and_trained = convert(model_ft_tuned, inplace=True)

cc @peterjc123 @jerryzh168 @jianyuh @dzhulgakov @raghuramank100 @jamesr66a

Issue 2:
🚀 Feature Request [Solved]

The torch::jit::load works well for loading both quantized model and un-quantized model on Linux and MacOS. But it will throw an error on Windows when loading the quantized model.

🍪 Currently, official FBGEMM can be compiled with PyTorch for Windows.

PR: #33250

🍪 Current Unofficial Method

Currently we compile libtorch-1.3.1 with FBGEMM marian-nmt version by @ykim362 on windows successfully. And the quantized model works pretty well on windows (200 ms -> 57 ms). Thanks for the effort from @ykim362. Hope fbgemm for windows can be aggregated in the future/next release of PyTorch. You know, the need of quantization for windows is as much as for Linux and ARM.

Some details:

PyTorch-1.3.1 : released branch with tag-1.3.1

FBGEMM : marian-nmt version by @ykim362

set CAFFE2=OFF when compiling on windows

To Reproduce

Quick steps to reproduce the behavior:

Use a model under torchvision/models/quantization, for example, mobilenet.

In model definition py file, add

if __name__ == '__main__':
model = mobilenet_v2(pretrained=False, progress=True, quantize=True)
torch.jit.save(torch.jit.script(model), 'mov2.pt')

Load the scripted model in Linux, MacOS, and Windows

#include <torch/torch.h>
#include <torch/script.h>
#include <iostream>
#include <memory>

int main(int argc, const char* argv[]) {
torch::jit::script::Module quant_model;
quant_model = torch::jit::load(argv[1]);
}

Expected behavior

The torch::jit::load works well for loading both quantized model and un-quantized model on Linux and MacOS. But it will throw an error on Windows when loading the quantized model:

The field 'training' was left unitialized after __setstate__, but expected a value of type 'bool' (postSetStateValidate at ..\..\torch\csrc\jit\import.cpp:52)
(no backtrace available)

Environment

PyTorch Version: 1.3.1

LibTorch Version: 1.3.1

OS: Ubuntu, MacOS, and Windows10

cc @suo @jerryzh168 @jianyuh @dzhulgakov @raghuramank100 @jamesr66a @soumith
Issue 1:
Do you want to request a feature or report a bug?

BUG.

What is the current behavior?

Here is JSFiddle, just try to edit the default value 2.34 to something else, like 3.45. As soon as i insert dot, cursor stars to jump in input.

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

It is not working in Chrome v53 on React v15.3.2 and also v15.3.1. I did not try to go very far back, but i tried it on old JSBin with React v0.13.2 and that worked.

On Firefox it is correctly working.

Issue 2:
This appears to have been introduced in a new Chrome version, but I can't find any reference to where.

Affected/Tested Browsers (OS X):

Chrome 51.0.2704.106 (64-bit)

Opera 39.0.2256.15

Unaffected Browsers:

Safari 9.1

Firefox 49

Backspacing in an input element with value or defaultValue set causes some very odd behavior. Once a decimal point is gone, it can't easily be re-added.

Example:

In this example, I simply backspaced twice. On the second backspace, when I expect 3. to be showing, the input instead reads 3 and the cursor has moved to the beginning. The next two jumps are my attempts to add another decimal point.

Fiddle: https://jsfiddle.net/kmqz6kw8/

Tested with React 15.2.

Notes: This only occurs when value or defaultValue is set. If neither is set, the input behaves properly. We are currently working around this issue by (unfortunately) setting the input value on componentDidMount via a ref.
Issue 1:
When attempting to detect a TextField in a test using containsMatchingElement, the detection failed. I narrowed it down to some issue with boolean properties.

Version: 0.19.4

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

Expected Behavior

Current Behavior

Steps to Reproduce (for bugs)

Here's the example code that is failing. I would expect both tests to pass, but only the first one does. I will move this code to codesandbox.io and add link Looks like codesandbox doesn't support running tests.

import React from 'react'
import { assert, expect } from 'chai'
import { shallow } from 'enzyme'

import TextField from 'material-ui/TextField'

// Successfully detect TextField
class TestComponent1 extends React.Component {
render(){
return (
<TextField />
)
}
}

describe('<TestComponent1 />', function(){
it('detects TextField', function(){
const testComponentWrapper = shallow(<TestComponent1 />)

assert.isTrue(testComponentWrapper.containsMatchingElement(<TextField />))
})
})

// Fails to detect TextField
class TestComponent2 extends React.Component {
render(){
return (
<TextField
fullWidth={true}
/>
)
}
}

describe('<TestComponent2 />', function(){
it('detects TextField', function(){
const testComponentWrapper = shallow(<TestComponent2 />)

assert.isTrue(testComponentWrapper.containsMatchingElement(<TextField />))
})
})

Context

Trying to use best practice containsMatchingElement(Element w/ Props) instead of find(Element).props()

Your Environment

Tech
Version

Material-UI
0.19.4

React
15.6.2

enzyme
3.1.1

Issue 2:
The top component is AppContainer, which yields the App component which build as a class. App component is wrapped with the MuiThemeProvider wrapper, which has one child - div element. In the console there is a warning "Warning: Failed prop type: The prop 'theme' is marked as required in 'MuiThemeProvideWrapper', but its value is 'undefined'."

I later get the error "Uncaught TypeError: Cannot read property 'prepareStyles' of undefined

at DatePicker.render" which seems to be related. According to the documentation there is no need to provide a theme as the Light Theme is used as default (http://www.material-ui.com/#/customization/themes & http://www.material-ui.com/#/get-started/usage). However, the problem persists also when I apply the Dark Theme according to instuctions on the Theme page.

I couldn't find any info about this warning.

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

Steps to Reproduce (for bugs)

Here is a link to the app with the warnings and errors in the console:

Here is a link to my code: https://github.com/carpben/notifications/tree/master/src

npm install material-ui -S

in the top component import MuiThemeProvider.

3.render MuiThemeProvider with one child

Render a material Ui Component somewhere in your app.

Context

At the moment I can't use Material UI at all.

Your Environment

Tech
Version

Material-UI
0.22

React
16

browser
chrome

etc
Windows 10, create react app, redux, bash on ubuntu on windows
Issue 1:
elasticsearch - 0.90.2

/opt/elasticsearch-0.90.2 # bin/plugin --url /opt/mobz-elasticsearch-head-0c2ac0b.zip --install head

Usage:

-u, --url [plugin location] : Set exact URL to download the plugin from

-i, --install [plugin name] : Downloads and installs listed plugins [*]

-r, --remove [plugin name] : Removes listed plugins

-l, --list : List installed plugins

-v, --verbose : Prints verbose messages

-h, --help : Prints this help message

[*] Plugin name could be:

elasticsearch/plugin/version for official elasticsearch plugins (download from download.elasticsearch.org)

groupId/artifactId/version for community plugins (download from maven central or oss sonatype)

username/repository for site plugins (download from github master)

Message:

Command [--url] unknown.

Issue 2:
may be duplicate of or related to #5170

using elasticsearch 1.0.0

I have a query where I would like to use search_type=scan to scroll through all contacts owned by a user. It works fine if the user has enough contacts but I have one user where there are only two contacts and this fails.

So I do a GET on

http://localhost:9200/users/contact/_search?search_type=scan&scroll=60m&size=100

{

"query": {

"term": {

"userId": {

"value": "1o"

}

}

}

}

I get back the following response

{

"_scroll_id":"c2Nhbjs1OzIwMTpxS1hwWW80MFJvV0hwbjdBcm5JRkF3OzIwNDpxS1hwWW80MFJvV0hwbjdBcm5JRkF3OzIwMzpxS1hwWW80MFJvV0hwbjdBcm5JRkF3OzIwMjpxS1hwWW80MFJvV0hwbjdBcm5JRkF3OzIwNTpxS1hwWW80MFJvV0hwbjdBcm5JRkF3OzE7dG90YWxfaGl0czoyOw==",

"took":1,

"timed_out":false,

"_shards":{

"total":5,

"successful":5,

"failed":0

},

"hits":{

"total":2,

"max_score":0.0,

"hits":[

]
}

}

and then http://localhost:9200/_search/scroll?scroll=60m

c2Nhbjs1OzIwMTpxS1hwWW80MFJvV0hwbjdBcm5JRkF3OzIwNDpxS1hwWW80MFJvV0hwbjdBcm5JRkF3OzIwMzpxS1hwWW80MFJvV0hwbjdBcm5JRkF3OzIwMjpxS1hwWW80MFJvV0hwbjdBcm5JRkF3OzIwNTpxS1hwWW80MFJvV0hwbjdBcm5JRkF3OzE7dG90YWxfaGl0czoyOw==

fails with a SearchContextMissingException

The same query for a user with 30000 contacts works fine and pages through the results like I would expect. The above query returns the two results normally if I query without search_type=scan

So it only fails if the result set is smaller than the page size