WhereIsAI/github-issue-similarity huggingface dataset:
Issue 1:
(Consider this a feature request)

This is most obvious when I do something simple like this:

<dl>
<dt>Your name</dt>
<dd>Eric</dd>
<dt>Timezone</dt>
<dd>Australia/Sydney</dd>
<dt>Created</dt>
<dd>Sunday, 23-Sep-12 22:46:40 UTC</dd>
</dl>
<div class="col-md-offset-2">
<a class="btn btn-default" href="edit">Edit your details</a>
<a class="btn btn-default" href="logout">Logout</a>
</div>

1200 breakpoint:

992 breakpoint:

768 breakpoint:

I've got the result I want by doing the following in my site css (but this only works right with full width containers)

@media (min-width: 768px) {
.dl-horizontal dt {
width: 90px;
}
.dl-horizontal dd {
margin-left: 111px;
padding-left: 15px !important;
}
}
@media (min-width: 992px) {
.dl-horizontal dt {
width: 126px;
}
.dl-horizontal dd {
margin-left: 146px;
}
}
@media (min-width: 1200px) {
.dl-horizontal dt {
width: 160px;
}
.dl-horizontal dd {
margin-left: 180px;
}
}

Issue 2:
It would be great if it was possible to align description lists with the grid system. I have a description list and below a grid and I would like the left and right columns to match.

The columns currently don't match, because:

dt has a fixed width of 160px

grid columns have dynamic widths

dd has a fixed left padding of 20px

grid columns have a padding of 30px by default

Some text

<dt> item 1 | <dd> Description
<dt> item 2 | <dd> Description
<dt> item 3 | <dd> Description

Horizontal form, using a 3:9 grid

Field 1 label | Field 1
Field 2 label | Field 2
Field 3 label | Field 3

^--^
both the column start and the
column padding are different
Issue 1:
You need first "pip install incremental" due to a misspelling in the lines for the installation of dependencies.

Issue 2:
sudo pip3 install Scrapy -i https://pypi.douban.com/simple

Command "python setup.py egg_info" failed with error code 1 in /private/tmp/pip-build-s3504tu6/Twisted/

so I use sudo pip3 install Scrapy -i https://pypi.douban.com/simple but failed again.

Please give me some advices, Thank you so much
Issue 1:
im using glide:3.7.0.

i want to create one folder of cache up to 150mb for specific purpose,and other folder will be for general purposes. ( prefer not to download files to storage on my own unless i have to)

what i actually want to achieve is that specific images must be available offline and their size should not be more than 150 mb.

thanks.

Issue 2:
Sometimes we need to load image for center inside, but I have not found this method!

Can add method for center inside?
Issue 1:
Environment

Windows build number: Microsoft Windows [Version 10.0.18362.175]
Windows Terminal version: 0.2.1715

Steps to reproduce

Open WSL tab.

Press enter until prompt/cursor are on last line.

Resize the window to be narrower.

Actual behavior

Issue 2:
(short) Description of the new feature/enhancement

Problem: Some users don't need/like a window title bar with min/max/close buttons and view these default UI elements as a minor design flaw/waste of screen real estate. Same for an empty tab bar with e.g. add-tab button. Likewise for the window resizing borders (these take to space, but needlessly change the mouse cursor)

Proposed solution: Please add an user configuration option to completely remove all of thse elements:

1-2) the title bar itself AND min/max/close buttons (currently I can only remove the title bar, but leave the buttons with the "showTabsInTitlebar": true

3) window resize borders (so that hovering over the window border would do nothing)

Ideal result: only tabs are visible above the terminal window, nothing extra (no title/tab bars)

User benefit: no unnecessary window elements are visible

(longer) Description

I'm never using the default Window controls as there are way more convenient ways to:

resize: instead of trying to precision-target the little right window border to make the window wider I just WinRMB in the general right area of the window and then move my mouse left/right to change the window's width (thanks, AltDrag)

move: Win+Mouse

minimize/maximize: use mouse gestures, e.g. RMB↑ to maximize (thanks, StrokesPlus)

close: any convenient keyboard shortcut, e.g. CtrlQ

As a result, I consider the default min/max/close buttons in the title bar as well as the title bar itself as well as the empty tab bar to be a waste of space. Also, moving a mouse pointer over the window borders changes its icon, which is not ideal as that's a useless signal to me

While I'm able to partially fix it with a script to remove the WS_Caption (0x00C00000) and WS_SizeBox (0x00040000) window properties (thanks, AutoHotkey), I thought that you could support such visual no title/tab bar/no borders modifications natively given the advanced features you plan for it
Issue 1:
For example: https://github.com/6to5/6to5/tree/master/lib/6to5/transformation/transformers/es6-generators

You're effectively forking the code, and making it much more difficult for you to incorporate updates quickly (or contribute changes upstream). It's unclear what version of Regenerator these files even represent. I don't understand the benefit you imagine this has for 6to5 or any of its contributing libraries. This isn't how open source should work!

Sorry for the alarmist tone, but this is a real problem. I'm happy to work with you to make Regenerator easier to use as an NPM package.

Thanks.

Issue 2:
We currently - now after jest has been landed in #7455 - have a mix of different assertion methods in tests.

There is chai in use.

There is assert in use.

There is jests expect in use.

The first two should be removed and rewritten to make use of expect which comes with jest.

so for example

-import chai from "chai";
-import assert from "assert";
-
-chai.expect(actualCode).to.be.equal("var fn;");
+expect(actualCode).toBe("var fn;")
-assert.strictEqual(this.constructor, Bar);
+expect(this.constructor).toBe(Bar)

The jest matchers should be used as good as possible, so for example not expect(x >= 3).toBe(true) but instead expect(x).toBeGreaterThanOrEqual(3)

The doc of jests matchers is here: https://facebook.github.io/jest/docs/en/expect.html

As we have a lot of tests split up in a lot of packages this task can also be split up and only one/some package(s) at a time be migrated.
Issue 1:
Bug Report

For English only, other languages will not accept.

Before report a bug, make sure you have:

Searched open and closed GitHub issues.

Read documentation: ShardingSphere Doc.

Please pay attention on issues you submitted, because we maybe need more details.

If no response anymore and we cannot reproduce it on current information, we will close it.

Please answer these questions before submitting your issue. Thanks!

Which version of ShardingSphere did you use?

master

Which project did you use? ShardingSphere-JDBC or ShardingSphere-Proxy?

proxy

Expected behavior

insert into account values(1,0),(2,100);
select * from account;
id | balance
----+---------
2 | 100
1 | 0

Actual behavior

id | balance
----+---------
2 | 100
1 | 0
2 | 100
1 | 0

config

config-sharding.yaml

schemaName: sbtest_sharding

dataSources:
ds_0:
url: jdbc:postgresql://127.0.0.1:15401/sbtest?useSSL=false&useServerPrepStmts=true&cachePrepStmts=true&prepStmtCacheSize=8192&prepStmtCacheSqlLimit=1024
username: test
password: 12345678
connectionTimeoutMilliseconds: 30000
idleTimeoutMilliseconds: 60000
maxLifetimeMilliseconds: 1800000
maxPoolSize: 2000
minPoolSize: 1
ds_1:
url: jdbc:postgresql://127.0.0.1:15402/sbtest?useSSL=false&useServerPrepStmts=true&cachePrepStmts=true&prepStmtCacheSize=8192&prepStmtCacheSqlLimit=1024
username: test
password: 12345678
connectionTimeoutMilliseconds: 30000
idleTimeoutMilliseconds: 60000
maxLifetimeMilliseconds: 1800000
maxPoolSize: 2000
minPoolSize: 1

rules:
- !SHARDING
tables:
account:
actualDataNodes: ds_${0..1}.account_${0..1}
tableStrategy:
standard:
shardingColumn: id
shardingAlgorithmName: account_inline
keyGenerateStrategy:
column: id
keyGeneratorName: snowflake

defaultDatabaseStrategy:
standard:
shardingColumn: id
shardingAlgorithmName: database_inline

shardingAlgorithms:
database_inline:
type: INLINE
props:
algorithm-expression: ds_${id % 2}
account_inline:
type: INLINE
props:
algorithm-expression: account_${id % 2}
keyGenerators:
snowflake:
type: SNOWFLAKE
props:
worker-id: 123

Issue 2:
Bug Report

Which version of ShardingSphere did you use?

5.1.1

Which project did you use? ShardingSphere-JDBC or ShardingSphere-Proxy?

ShardingSphere-JDBC

Expected behavior

The sql executes correctly

Actual behavior

org.apache.shardingsphere.sql.parser.exception.SQLParsingException: You have an error in your SQL syntax

Reason analyze (If you can)

sql parsing generates errors that are not actually sql errors

Steps to reproduce the behavior, such as: SQL to execute

select o.* from t_order o where o.json_field -> '$.${item.key}' is null and o.create_time > xxx and o.create_time <yyy;

create_time as a sharding field, but doesn't seem to support json syntax? If I remove o.json_field -> '$.${item.key}' is null , there will be no error. However, this sql can be executed normally in mysql.

create_time作为分片字段，但是貌似不支持json语法？如果我移除o.json_field -> '$.${item.key}' is null ，就不会报错。然而这个sql是能在mysql里正常执行的
Issue 1:
I get wrong numerical results (real component is off, imaginary component always near underflow) for sph_harm for scipy 0.16.0 that comes with Miniconda3. scipy on Miniconda seems OK.

Python 3.4.3 |Continuum Analytics, Inc.| (default, Oct 19 2015, 21:52:17)
IPython 4.0.0 -- An enhanced Interactive Python.
In [1]: from scipy.special import sph_harm
In [2]: sph_harm(2,5,0.2,0.5)
Out[2]: (0.44798449902914189+3.1149082468549677e-310j)

Python 2.7.10 |Continuum Analytics, Inc.| (default, Sep 15 2015, 14:50:01)
IPython 4.0.0 -- An enhanced Interactive Python.
In [1]: from scipy.special import sph_harm
In [2]: sph_harm(2,5,0.2,0.5)
Out[2]: (0.41262104797366594+0.17445338099189969j)

conda list reports for Miniconda3 and Miniconda respectively

scipy 0.16.0 np110py34_1
scipy 0.16.0 np19py27_1

(I have not updated the scipy version in a while for Python2.)

Issue 2:
Kind of similar to #4887, I found an inconsistency in sph_harm, but it appears on Python 3.4 (e.g., on Anaconda scipy=0.16 or scipy=0.15) but not on Python 2.7 with equivalent numpy/scipy versions. Running this command in a Python 3.4 Anaconda virtual environment I get:

$ python -c "from scipy.special import sph_harm; print(sph_harm(1, 1, 1., 1.))"
(-0.290723302201-2.02129965364e-310j)

But the correct result is what I get on Python 2.7 (verified using calculations from here:

(-0.157078470549-0.24463522341j)

It does work on my system Python3 when using the Ubuntu-packaged scipy 0.14.1:

(-0.15707847054880641-0.24463522340968866j)

And when I build scipy myself, latest master with MKL or maintenance/0.16.x using system BLAS, they both give the same correct result:

(-0.157078470549-0.24463522341j)

Any idea why it could break for 3.4 and not 2.7? And only some builds (apparently Anaconda)? This is a weird one.

cc @jennystone @argriffing since you were on the last PR merge related to this

cc @wronk
Issue 1:
I've used Cprofile to test my code, and I find that import tensorflow.contrib.layers takes very long time. Here is the quick screenshot of the result:

14495011 function calls (14451561 primitive calls) in 6.324 seconds

Ordered by: cumulative time

ncalls tottime percall cumtime percall filename:lineno(function)
1023/1 0.058 0.000 6.328 6.328 {built-in method builtins.exec}
1 0.000 0.000 6.328 6.328 test_import.py:10(<module>)
1066/1 0.006 0.000 6.328 6.328 <frozen importlib._bootstrap>:966(_find_and_load)
1066/1 0.005 0.000 6.328 6.328 <frozen importlib._bootstrap>:939(_find_and_load_unlocked)
1360/1 0.001 0.000 6.328 6.328 <frozen importlib._bootstrap>:214(_call_with_frames_removed)
759/1 0.002 0.000 6.328 6.328 {built-in method builtins.__import__}
881/2 0.004 0.000 6.328 3.164 <frozen importlib._bootstrap>:659(_load_unlocked)
833/2 0.003 0.000 6.328 3.164 <frozen importlib._bootstrap_external>:667(exec_module)
6575/625 0.005 0.000 6.102 0.010 <frozen importlib._bootstrap>:996(_handle_fromlist)
...

As seen above, it took more than 6 secs to just do import tensorflow.contrib.layers, and I wonder if this is expected. Also, I am pretty interested in why it takes so long time to do importing there.

P.S The profiling test runs on MacOS Sierra 10.12.5 with Tensorflow v1.2 and Python 3.5.

Issue 2:
System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow): No

OS Platform and Distribution (e.g., Linux Ubuntu 16.04): macOS Sierra 10.12.5

TensorFlow installed from (source or binary): source

TensorFlow version (use command below): v1.2.0-2420-g2b4a0f9a4 1.3.0-rc0

Python version: 3.6.2

Bazel version (if compiling from source): 0.5.2-homebrew

CUDA/cuDNN version: CPU only build

GPU model and memory: CPU only build

Exact command to reproduce: time python3 -c "import tensorflow.contrib"

The problem

Doing import tensorflow.contrib take 7.5 seconds on my machine when doing it with Python 3.6.2. With Python 2.7.13 it takes 3.2 seconds.

Investigating this revealed that a lot of time is spent in _inspect.stack() in the function make_decorator in python/util/tf_decorator.py. The stack is inspected to find the name of the caller of the function. With Python2 inspect.stack() is fast, but with Python 3 each call to inspect.stack() take approximately 0.2 seconds and there are 23 calls made, which account for the difference in time between Python 2 and 3.

References

Keras by default imports tensorflow.contrib when the Tensorflow backend is used. Therefore Keras is slow to import when using Python 3: keras-team/keras#7408

There is a stackoverflow question referencing this issue: https://stackoverflow.com/questions/45093653/import-tensorflow-contrib-module-is-slow-in-tensorflow-1-2-1
Issue 1:
By default, the link extractor calls canonicalize_url on the collected links.

The following is not what browsers do:

canonicalize_url('http://example.com/index.php?/a/=/o/')
'http://example.com/index.php?%2Fa%2F=%2Fo%2F' # encoding forward slashes
canonicalize_url('http://example.com/index.php?a')
'http://example.com/index.php?a=' # appending = on empty arguments

I doubt this is a problem in canonicalize_url

because it's not meant to mimic browsers in the first place, is it?

However this is a problem for the link extractor

because it can potentially end up extracting urls

that are wrong from the server's perspective.

In this example, the server doesn't recognise the extractor's url, only the browser's:

# http://forum.laptop.bg/index.php?/discover/
LinkExtractor(restrict_xpaths=('//a[contains(@href, "/topic")]',)).extract_links(response)[0].url
# Extractor: http://forum.laptop.bg/index.php?%2Ftopic%2F57339-%D0%BB%D0%B0%D0%BF%D1%82%D0%BE%D0%BF-asus-w90vp%2F=&comment=221153&do=findComment
# Browser: http://forum.laptop.bg/index.php?/topic/57339-%D0%BB%D0%B0%D0%BF%D1%82%D0%BE%D0%BF-asus-w90vp/&do=findComment&comment=221153

Was this a design decision or a bug?

Issue 2:
Cannot override the default Connection: close header of scrapy requests. I want to scrape a site for which I need to send Connection: keep-alive headers and remove the default Connection: close header.

Tried using custom settings, custom headers and default headers to change Connection: close to Connection: keep-alive but it instead merges and sends two Connection headers.

It works in scrapy shell but not when used in a spider.

I used Fiddler to check the headers scrapy was sending. Please use Fiddler or any other packet sniffing tool to check the headers as it works fine in scrapy shell.

Below is the different things I tried:

Using custom settings:

custom_settings = {
'DEFAULT_REQUEST_HEADERS': {
'Connection': 'keep-alive'
}
}

Using custom headers:

headers = {"Connection": "keep-alive"}

for url in urls:
yield scrapy.Request(url=url, callback=self.parse, headers=headers)

Changing default header settings:

DEFAULT_REQUEST_HEADERS = {
'Connection': 'keep-alive',
}
Issue 1:
I updated to version 0.152.0 and its showing me these release notes below

Issue 2:
I use Atom on two different machines and I'm seeing anomalies when looking at the release notes. On one of my machines the release notes are always blank with only a button showing to view previous release notes. On the other machine the release notes are old. Here is a current screenshot but keep in mind this isn't the only time the release notes have been outdated compared to the release I was using.

Currently using Atom 0.136 on Windows 8.1 (on two different systems).
Issue 1:
This issue is opened to host a discussion about the recurrent attention API for keras.

Related issues:

#11142.

#8296.

#7633.

Issue 2:
Handling Tensors of tf.Tensor outside a custom layer is not a problem.

For example:

InputTensor = np.array([[[[255,0,0],[255,0,0]],[[255,0,0],[0,144,0]]],
[[[0,255,0],[0,255,0]],[[0,255,0],[144,0,0]]],
[[[0,245,0],[0,245,0]],[[0,245,0],[144,0,0]]]])

X = tf.constant(InputTensor)
print(X[0,0,0,0].numpy()) #--->255
print(tf.shape(X)[0].numpy() #--->3
print(X.shape[0]) #--->3
print(X) #---->
<tf.Tensor: shape=(3, 2, 2, 3), dtype=int64, numpy=
array([[[[255, 0, 0],
[255, 0, 0]],

[[255, 0, 0],
[ 0, 144, 0]]],

[[[ 0, 255, 0],
[ 0, 255, 0]],

[[ 0, 255, 0],
[144, 0, 0]]],

[[[ 0, 245, 0],
[ 0, 245, 0]],

[[ 0, 245, 0],
[144, 0, 0]]]])>

You get all the values you need for calculating. But inside custom layers the input tensor has another type:

Something like

Tensor("model_10/Cast:0", shape = (None,2,2,3), dtype = float32)

There is no numpy(). tf.shape(X)[0].numpy() does not work or X.shape[0] to get the batch. The numpy() function is helpful to get the values of a tensor. The following example is inside of a custom layer. If I make a tensor with tf.constant, then I receive a tensor without the numpy() function.

The next example is a dirty example which works fine but you must handle it with attention:

from keras.layers import Layer
import numpy as np
import tensorflow as tf
from keras.layers import Input
from keras.models import Model

InputTensor = np.array([[[[255,0,0],[255,0,0]],[[255,0,0],[0,144,0]]],
[[[0,255,0],[0,255,0]],[[0,255,0],[144,0,0]]],
[[[0,245,0],[0,245,0]],[[0,245,0],[144,0,0]]]])

class MyLayer(Layer):
def __init__(self,indexmax, **kwargs):
self.indexmax = indexmax
super(MyLayer,self).__init__(**kwargs)

def build(self, input_shape):
self.built = True
super(MyLayer,self).build(input_shape)

def call(self, X):
print(X)
y = np.array([[[[0,0,0]]],[[[0,0,0]]],[[[0,0,0]]]])
if X[0,0,0,0] == 255:
y[0,0,0,0] = 10
if X[1,0,0,1] == 255:
y[1,0,0,1] = 20
if X[2,0,0,1] == 245:
y[2,0,0,1] = 30 #y[2,0,0,1] = x[2,0,0,1]-30 # <--- Does not work!

Y =tf.constant(y)
Y= tf.compat.v1.placeholder_with_default(Y,(None,1,1,3))
return Y

indexmax = InputTensor.shape[0]
inputlayer = Input(shape = InputTensor[0].shape)
layer = MyLayer(indexmax)(inputlayer)

model = Model(inputlayer, layer ) #Model wird erzeugt
model.summary()

Output = model.predict(InputTensor)
Output = np.array(Output)
print("Output = "+str(Output))

But if I try to assign the value of X[2,0,0,1] to a variable or to another tensor, it does not work. I need the value of the input tensor X for calculating to build output-tensors for example with index maps. To slice the input tensor make the access very complicated and also do not work either. What I wish to avoid the parameter indexmax in the custom layer to transport the batch size into the custom layer, which has first the value None. This is also a very important value to know! If there is no possibility to get these values custom layers make no sense!
Issue 1:
In Firefox when using InputAdornement on a TextField of type="number the adornment is moving outside if the field / wrapper is not big enough. I prepared an example (see link below). For that I copied the example from the docs and just added the type property.

I have no idea why this is happening or how to fix that.

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

Steps to Reproduce (for bugs)

https://pmpx74419m.codesandbox.io/

https://codesandbox.io/s/pmpx74419m

Your Environment

Tech
Version

Material-UI
v1.0.0-beta.21

browser
Firefox 57

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

Expected Behavior

I ran the commandsnpm install material-ui and npm install material-ui@next to get all the modules for an example I'm trying to run. Since they are all material-ui modules, there should've been no error in importing anything.

Here is the link to the example I'm trying to run: SimpleGrid

Current Behavior

I am still getting import errors saying that the following two modules aren't found.

Steps to Reproduce (for bugs)

Import all material-ui modules

run npm install material-ui and npm install material-ui@next

Get the example code from this file: SimpleGrid

setup your environment and run npm start

Context

I tried importing the specific modules required as well (npm install material-ui/Subheader) but I got more errors.

Your Environment

Tech
Version

Material-UI
1.0.0-beta.20

React
16.1.0

browser
Chrome
Issue 1:
What problem does this feature solve?

I would like to have an optional component but with the content being always rendered (so v-if doesn't work with this use case)

It's currently not possible without a lot of code duplication

<my-component v-if="condition">
<the-content>I'm visible</the-content>
</my-component>
<the-content v-else>I'm visible</the-content>

What does the proposed API look like?

What I would like to be able to write instead is this

<my-component v-if-parent="condition">
<the-content>I'm visible</the-content>
</my-component>

Issue 2:
What problem does this feature solve?

In large applications, there are often families of components, within which components share most of the look/behavior, but vary slightly. This makes it desirable to reuse code between them. Some reuse can be achieved with slots, other is better with component inheritance. But while most of the parent component definition can be smart-merged with child definition, the template has to be either kept as is, or replaced entirely.

I have seen multiple approaches to reusing component templates:

Write very granular appearance-only components with many slots. While this sounds good in theory, in practice the granularity needed often makes this approach into an obstruction rather than abstraction.

Implement all required variation in a single component and make it configurable with slots and props. The downside is that you are stuck with a god-component, which is hard to maintain and extend further.

Extend the component, and use <parent>...</parent> in the child template, using slots as "parts". The downside is that you have to "proxy" all props and slots down and events up. This is very cumbersome and fragile.

Split the component in question further into "part" components, so that you can override only certain part. This gets tedious very quickly, especially when you need v-bind or v-on inside of the overridden part.

Define "part" render functions among the methods, so that they can be overridden. The downside is that you can not really write such parts in template DSL, and the parts get disconnected from the main template, which makes it harder to understand.

What does the proposed API look like?

The Pug template engine (former Jade) implements a feature called blocks, which allows templates to extend other templates while overwriting (or extending) certain named blocks. I think this feature ported to Vue would fill the gap described above, and allow the templates to be more reusable.

A possible syntax:

<!-- parent.vue -->
<template>
<div>
<block name="header">
<h3>Default header</h3>
</block>
<block name="body">
<p>Default body</p>
</block>
<block name="footer">
<!-- no footer by default -->
</block>
</div>
</template>

<!-- child.vue -->
<!-- there is no root element (only blocks), so the parent template is reused -->
<template>
<block name="header">
<h2>More pronounced header</h2>
</block>
<block name="footer">
<p>Footer added by the child</p>
</block>
</template>