WhereIsAI/github-issue-similarity huggingface dataset:
Issue 1:
For select field, if we press keyboard, it should focus on the option start with the letter same as key press.

Give a simple select with 3 options:

<Select value={this.state.age} onChange={this.handleChange} inputProps={{ name: 'age', id: 'age-simple', }} > <MenuItem value=""> <em>None</em> </MenuItem> <MenuItem value={1}>One</MenuItem> <MenuItem value={10}>Ten</MenuItem> <MenuItem value={50}>Fifty</MenuItem> </Select>

Expected Behavior

Press O, the first option should be focused

Press F, the last option should be focused

Current Behavior

Press O, T or F does on the keyboard does not have any action.

Tech
Version

Material-UI
1.0.0-beta.30

React
16.2.0

browser
Chrome

etc

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

Expected Behavior

Hi, Im trying to use the updated Hidden with initialWidth

Not sure which one of these is correct:

<Hidden xsDown initialWidth={100}>
</Hidden>
<Hidden xsDown initialWidth={"xs"}>
</Hidden>

Either option gives me a warning

Warning: Failed prop type: Invalid prop initialWidth of type string supplied to Hidden, expected number.

in Hidden

Warning: Failed prop type: Invalid prop initialWidth of value 100 supplied to WithWidth(HiddenJs), expected one of ["xs","sm","md","lg","xl"].

in WithWidth(HiddenJs)

Warning: Failed prop type: Invalid prop width of type number supplied to HiddenJs, expected string.

in HiddenJs

I dont see the property on Hidden.d.ts either in HiddenProps/HiddenJsProps

Current Behavior

Steps to Reproduce (for bugs)

Looking into the source

HiddenJs suggests it should be a number

https://github.com/mui-org/material-ui/blob/b72e77151659484c4c1a4a3853e66ee742d1a845/src/Hidden/HiddenJs.js#L98

However initialWidth also gets passed into withWidth

https://github.com/mui-org/material-ui/blob/b72e77151659484c4c1a4a3853e66ee742d1a845/src/Hidden/HiddenJs.js#L153

Which expects a string

https://github.com/mui-org/material-ui/blob/b72e77151659484c4c1a4a3853e66ee742d1a845/src/utils/withWidth.js#L121

Context

For the moment my workaround is this, which seems to do what I want (ie hidden on SSR)

var hiddenmdprops: any = {
mdDown: true,
initialWidth: 'md',
};
<Hidden {...hiddenmdprops}>
</Hidden>

And just ignore the warning.

Your Environment

Tech
Version

Material-UI
v1.0.0-beta.27

React

browser

etc
Issue 1:
The nav starts out great once you lower the bowser width the nav becomes stacked, this is great. Once you open the window back up the nav items are in two rows. Here's a pic.

This is how it starts out:

http://reggi.myshopify.com/pages/about#

http://stackoverflow.com/questions/19412786/bootstrap-nav-justified-odd-responsive-issue

Issue 2:
The justified nav example (http://getbootstrap.com/examples/justified-nav) collapses perfectly when the screen is narrowed, but when the screen is expanded it get wonky.

expanded
Issue 1:
I am trying to implement Deno in WinGet package manager. I converted the ps1 file into an exe file and i have tested the installer, but I have a 2 big problems.

I dont have a website to host the installer.

Since I cannot create a manifest (for the reason i just said) i cannot test the behaviour of the installer.

I sugest that you hosted the exe installer in your website once you have tried it and you see if it works!!

Issue 2:
Please add support for WinGet Packages releases.

Details on how to available here: https://github.com/microsoft/winget-pkgs
Issue 1:
ISSUE TYPE

Feature Idea

COMPONENT NAME

handlers

ANSIBLE VERSION

ansible 2.1.1.0

CONFIGURATION

OS / ENVIRONMENT

SUMMARY

Duplicate handler task names causes task ordering to get messed up starting in 2.1.1. Ansible should instead error if it detects two or more handlers with the same task name.

STEPS TO REPRODUCE

EXPECTED RESULTS

I expected systemd reload before restarting service foo. Instead, the order was reversed because of the duplicate handler task.

ACTUAL RESULTS

Order was random. Sometimes good, but often it failed.

Ansible shouldn't permit duplicate handlers with the same task name to be used since it produces undesirable behavior.

Issue 2:
same problem as this closed ticket

#10753

ISSUE TYPE

Bug Report

ANSIBLE VERSION

1.9.4 and 2.0.1.0

OS / ENVIRONMENT

Mac OS X El Capitan

SUMMARY

When adding a security group using the ec2_group module. A duplicate entry error is thrown. This does not happen when using IP address with cidr_ip.

STEPS TO REPRODUCE

- name: Update Security Group
ec2_group:
name: "SSH Access"
description: "Access To That Other Security Group"
region: "{{ item.region }}"
rules:
- proto: tcp
from_port: 22
to_port: 22
group_id: some-other-group

EXPECTED RESULTS

Duplicates should not trigger a play book failure.

ACTUAL RESULTS

This error stops play book execution when using group_id.

An exception occurred during task execution. To see the full traceback, use -vvv. The error was: <Response><Errors><Error><Code>InvalidPermission.Duplicate</Code><Message>the specified rule "peer: sg-xxxxxx, TCP, from port: 22, to port: 22, ALLOW" already exists</Message></Error></Errors>
Issue 1:
While I'm not an Objective-C developer, I did some digging on the webs and it looks like getting the coordinates/position of the Dock Icon for a particular app is possible. Please see this response and the subsequent comment with an update to the method. I verified here that the API still exists and is valid, and the method appears to be sound still.

I investigated using various plists on the machine to determine dock icon size (which doesn't appear to be possible anymore) and the index of a dock icon, but unfortunately that's not possible unless the app has been pinned to the dock.

I think that would add significant benefit for developers if that info was available to app.dock. My particular use case is that I'm rewriting an old app I wrote for windows which makes use of taskbar window thumbnail grouping, something I'm duplicating using a BrowserWindow, but I have no way of knowing how to align the window as I don't have access to the location of the dock icon. At the moment I can only query defaults read com.apple.dock through the shell to glean the position of the dock on the screen, which unfortunately isn't specific enough for my window alignment needs.

Electron version: 1.6.5

Operating system: MacOS 10.12.4

Expected behavior

n/a

Actual behavior

n/a

How to reproduce

n/a

Issue 2:
Problem Description

In electron 5.x, there'll be a LOG file in the ~/Library/Application Support/xxx/(userData directory), which is a duplicate with mine.

Proposed Solution

Disable the creation of this LOG file

Alternatives Considered

None
Issue 1:
The output shape for multi-label predict_proba is inconsistent :-(

The OneVsRest classifier produces (n_samples, n_classes) (like multi-class)

where for example RandomForestClassifier produces a list of probabilities per label, which are each (n_samples, 2) or (n_samples, 1).

Not sure how to do a deprecation for that.

But we should do a common test for whether a classifier supports multi-label and what the output shapes are.

Issue 2:
The decision_function and predict_proba of a multi-label classifier (e.g. OneVsRestClassifier) is a 2d arrays where each column correspond to a label and each row correspond to a sample. (added in 0.14?)

The decision_function and predict_proba of multi-output multi-class classifier (e.g. RandomForestClassifier) is a list of length equal to the number of output with a multi-class decision_function or predict_proba output (a 2d array where each row corresponds to the samples and where each columns correspond to a class).

So this means that multi-output problem with only binary class output is a multi-label task, but isn't consistent with the multi-label format...

This is problematic if you want to code a roc_auc_score function to support multi-label output.
Issue 1:
Challenge http://www.freecodecamp.com/challenges/bonfire-return-largest-numbers-in-arrays has an issue.

This issue occurs no matter what code I put in. Believe something in the background may be broken. I was told in the Helproom that a few others are getting this too.

Issue 2:
Challenge http://www.freecodecamp.com/challenges/waypoint-bring-your-javascript-slot-machine-to-life has an issue.

while trying to type $($(".slot")[0]).html(slotOne);

program freezes, having to close and reopen tab.

however pasting $($(".slot")[0]).html(slotOne); works fine.

something about $($) while typing messes everything up
Issue 1:
Here is the problem:

I would like to train a network with two different shapes of input tensor. Each epoch chooses one type. Here I write a small code:

import tensorflow as tf
import numpy as np

with tf.Session() as sess:

imgs1 = tf.placeholder(tf.float32, [4, 224, 224, 3], name = 'input_imgs1')
imgs2 = tf.placeholder(tf.float32, [4, 180, 180, 3], name = 'input_imgs2')
epoch_num_tf = tf.placeholder(tf.int32, [], name = 'input_epoch_num')

imgs = tf.cond(tf.equal(tf.mod(epoch_num_tf, 2), 0),
lambda: tf.Print(imgs2, [imgs2.get_shape()], message='(even number) input epoch number is '),
lambda: tf.Print(imgs1, [imgs1.get_shape()], message='(odd number) input epoch number is'))

print(imgs.get_shape())

for epoch in range(10):
epoch_num = np.array(epoch).astype(np.int32)
imgs1_input = np.ones([4, 224, 224, 3], dtype = np.float32)
imgs2_input = np.ones([4, 180, 180, 3], dtype = np.float32)

output = sess.run(imgs, feed_dict = {epoch_num_tf: epoch_num,
imgs1: imgs1_input,
imgs2: imgs2_input})

When I execute it, the output of imgs.get_shape() is (4, ?, ?, 3) i.e. imgs.get_shape()[1]=None, imgs.get_shape()[2]=None.

But I will use the value of the output of imgs.get_shape() to define the kernel (ksize) and strides size (strides) of the tf.nn.max_pool() e.g. ksize=[1,imgs.get_shape()[1]/6, imgs.get_shape()[2]/6, 1] in the future code. I think ksize and strides cannot support tf.Tensor value.

How to solve this problem?

I also asked in the stackoverflow.

Issue 2:
I am trying to build a convolution (followed by max_pool) for variable length input size. Since the length of the input in a batch should be the same, I set the batch size to 1. However, for some reason ksize in tf.nn.max_pool is a list attribute required at run-time. This would prevent any neural network that uses variable input size to apply max pool. Is there a workaround for this? Should ksize be an input tensor otherwise?
Issue 1:
Describe your issue.

Version used : Using cached scipy-1.6.1.tar.gz (27.3 MB)

I've attached the log file and the suspected issue - scipy-compile.log

Reproducing Code Example

pip install scipy
Pip version - pip 22.1.1 from /home/rishacha/.local/lib/python3.11/site-packages/pip (python 3.11)
Python version - Python 3.11.0b1
OS - elementaryOS

>>> import sys, numpy; print("Numpy version: ", numpy.__version__,"\nSys version: ", sys.version_info)
Numpy version: 1.22.3

Sys version: sys.version_info(major=3, minor=11, micro=0, releaselevel='beta', serial=1)

### Error message

```shell
2022-05-24T23:43:03,313 scipy/cluster/_vq.c:196:12: fatal error: longintrepr.h: No such file or directory
2022-05-24T23:43:03,313 196 | #include "longintrepr.h"
2022-05-24T23:43:03,313 | ^~~~~~~~~~~~~~~
2022-05-24T23:43:03,313 compilation terminated.

SciPy/NumPy/Python version information

import sys, numpy; print("Numpy version: ", numpy.version,"\nSys version: ", sys.version_info) Numpy version: 1.22.3 Sys version: sys.version_info(major=3, minor=11, micro=0, releaselevel='beta', serial=1)

Issue 2:
My issue is about ...

Reproducing code example:

Sample code to reproduce the problem

Error message:

Traceback (most recent call last):
File "<stdin>", line 1, in <module>
...

Scipy/Numpy/Python version information:
Issue 1:
Describe the workflow you want to enable

Can we add a feature in LinearRegression that could remove collinearity (exact collinearity) in the data?.

Describe your proposed solution

My proposal is to add an extra argument like remove_collinearity if it is set by the user then we can remove exact collinear variables using the rank of the matrix or collinear variables using VIF. This can save some time instead of going for Ridge regression.

Issue 2:
I wonder whether we should add unsupervised feature selection using correlation. It's a strategy that's very common in statistics and might just have it for completeness.

It's certainly more useful than the variance based one, which I think is useless for any threshold != 0.
Issue 1:
Essentially, store whatever is stored in a sysimage with user packages compiled into it in the standard precompile files.

I would assume that this, in combination with #30487, would go a very long way to make the interactive REPL experience of julia competitive.

I know that the core team has been thinking about this, and I did look for an existing issues that tracks this, but couldn't find any. So, I'm mainly creating the issue so that it can be assigned to a milestone and that I can follow progress :) If this is a duplicate (which I really had expected) and I just didn't find the original, please close.

Issue 2:
Try running Pkg.available()
Issue 1:
Challenge Confirm the Ending has an issue.

User Agent is: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Ubuntu Chromium/53.0.2785.143 Chrome/53.0.2785.143 Safari/537.36.

Please describe how to reproduce this issue, and include links to screenshots if possible.

My code:

function confirmEnding(str, target) {
// "Never give up and good luck will find you."
// -- Falcor
if (str.endsWith(target)){
return true;
}
else return false;
return str;
}

confirmEnding("Bastian", "n");

Issue 2:
function confirmEnding(str, target) {
// "Never give up and good luck will find you."
// -- Falcor
return str.endsWith(target) // if I don't end with semi-colon it will pass.
}

confirmEnding("Bastian", "n");
Issue 1:
When trying to compile this code:

pub fn write_to_log(line: String) {
use std::fs::{File, OpenOptions};
let resFile = OpenOptions::new().read(true).write(true)
.append(true).open("log.log");
let mut file = match resFile {
Ok(f) => f,
Err(e) => panic!("file error: {}", e),
};
let _ = writeln!(&mut file, "{}", line);
}

fn main() {
write_to_log("Hello".to_string());
}

compiler prints this message:

<std macros>:2:20: 2:66 error: type `&mut std::fs::File` does not implement any method in scope named `write_fmt`
<std macros>:2 ( & mut * $ dst ) . write_fmt ( format_args ! ( $ ( $ arg ) * ) ) )
^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
<std macros>:2:66: 2:66 help: methods from traits can only be called if the trait is in scope; the following trait is implemented but not in scope, perhaps add a `use` for it:
<std macros>:2:66: 2:66 help: candidate #1: use `std::io::Write`
error: aborting due to previous error

I would expect it to point me to the fine and line where writeln! is used. Right now it very hard to find error location.

Issue 2:
<std macros>:4:19: 4:46 error: invalid reference to argument `1` (there is 1 argument)
<std macros>:4 write ! ( $ dst , concat ! ( $ fmt , "\n" ) , $ ( $ arg ) * ) ) ;
^~~~~~~~~~~~~~~~~~~~~~~~~~~

<std macros>:3:11: 3:38 error: invalid reference to argument `2` (there are 2 arguments)
<std macros>:3 print ! ( concat ! ( $ fmt , "\n" ) , $ ( $ arg ) * ) ) ;
^~~~~~~~~~~~~~~~~~~~~~~~~~~

I’d expect it to at least emit an in expansion of writeln! and in expansion of println! hints which it doesn’t currently.
Issue 1:
See three examples:

import tensorflow as tf

x = tf.constant(1.0)
x = tf.Print(x, ['x'])
y = tf.constant(2.0)
y = tf.Print(y, ['y'])
z = tf.constant(3.0)
z = tf.Print(z, ['z'])

with tf.Session() as sess:
print(sess.run([x,y,z]))

The sequence of output of tf.Print is indeterminate, which means sess.run don't executes tensors from left to right.

import tensorflow as tf

x = tf.constant(1.0)
x = tf.Print(x, ['x'])
y = tf.constant(2.0)
y = tf.Print(y, ['y'])
with tf.control_dependencies([x, y]):
z = tf.constant(3.0)
z = tf.Print(z, ['z'])

with tf.Session() as sess:
print(sess.run(z))

The sequence of x and y is indeterminate, which means control_dependencies don't executes tensors from left to right.

import tensorflow as tf

x = tf.constant(1.0)
x = tf.Print(x, ['x'])
y = tf.constant(2.0)
y = tf.Print(y, ['y'])
d = tf.constant(3.0)
d = tf.Print(d, ['d'])
with tf.control_dependencies([x, y]):
z = tf.add(d, 3.)
z = tf.Print(z, ['z'])

with tf.Session() as sess:
print(sess.run(z))

The sequence of x, y and d is indeterminate.

Is it intentional behavior or bug? I find that if the sequence is indeterminate, the program may get different result.

Another example I can't explain:

import tensorflow as tf

x = tf.placeholder(tf.float32, [])
y = tf.Variable(2.)
op = tf.assign(y, x)
op = tf.Print(op, ['op'])

with tf.control_dependencies([op]):
q = tf.Print(y, [y])

with tf.Session() as sess:
tf.global_variables_initializer().run()
print(sess.run([q], feed_dict={x: -1.0}))

The [op] is printed before [y], but q=2.0, why? If op is executed before y, y will be assigned by x, which means y=-1.0, and q should be -1.0.

Issue 2:
import tensorflow as tf

w = tf.Variable(0)
op1 = tf.assign(w, 1)
op2 = tf.assign(w, 2)
op_1 = tf.constant('op1')
op_2 = tf.constant('op2')

op1 = tf.Print(op1, [op_1])
op2 = tf.Print(op2, [op_2])

with tf.control_dependencies([op2]):
with tf.control_dependencies([op1]):
op = tf.no_op()

with tf.Session() as sess:
tf.global_variables_initializer().run()
sess.run(op)
print(sess.run(w))

It sometimes prints 1 and sometimes prints 2.

Another example:

import tensorflow as tf

w = tf.Variable(0)
op1 = tf.assign(w, 0)
op2 = tf.assign(w, 2)
op_1 = tf.constant('op1')
op_2 = tf.constant('op2')

op1 = tf.Print(op1, [op_1])
op2 = tf.Print(op2, [op_2])

with tf.control_dependencies([op1]):
op3 = tf.no_op()

with tf.control_dependencies([op3, op2]):
op4 = tf.no_op()

with tf.Session() as sess:
tf.global_variables_initializer().run()
sess.run(op4)
print(sess.run(w))

Sometimes 0 and sometimes 2.
Issue 1:
Hi guys,

I met an issue, I want to use Table View to show the table column, I succeed to create slice like this:

But when I use it into the dashboard, I get this error:

I found this error will happened no matter what table I use. Is it a bug?

PS: I just followed the doc to install the caravel : http://airbnb.io/caravel/installation.html#caravel-installation-and-initialization

Issue 2:
Within the SQL Editor section of SQL Lab, when you select the “+” icon beside the current tab to create a new query, the name of the query gets increased incrementally (see the image below) [except there is consistently a duplicate name for the first two].

However, if you select the “+“ icon on the top right of the web page beside the settings drop down and select “SQL query“, the names of the new queries do not increase incrementally. They are all just named "Untitled Query 2" (see the images below).

In the image above, the query tab in the far right was created using the "SQL query" button under the “+“ icon drop down on the top right of the page. As you can see, the query name was not increased incrementally.

How to reproduce the bug

Go to the SQL Editor page by selecting it from the main menu under the "SQL Lab" drop down.

You can immediately notice one of the bugs that occurs, the first untitled query will always be called "Untitled Query 2", never "Untitled Query 1".

Click on the "+" button next to the list of query tabs, it should properly increment the query tab names.

Select the “+“ icon on the top right of the web page beside the settings drop down, and then click "SQL query"

You will notice that the name of the newly created query is "Untitled Query 2". No matter how many times you complete step 4, it will never increment the new query tab names.

Expected results

When either the "+" button next to the query tabs or the "SQL query" button from the drop down is selected, they should both increment the name of the untitled query properly.

Actual results

When the "SQL query" button from the drop down is selected, the newly created query tabs are always named "Untitled Query 2". Also, the way the code is currently implemented, there will never be an "Untitled Query 1".

Screenshots

Please see the main summary for screenshots

Environment

operating system name and version: Ubuntu 20.04

browser type and version: Google Chrome (Version 97.0.4692.71)

superset version: Superset 1.4

python version: Python 3.8.12

node.js version: Node v14.16.1

any feature flags active: N/A

Checklist

Make sure to follow these steps before submitting your issue - thank you!

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

Additional context

Also, since discovering this bug, I have created a fix for it on my local fork. I will create a corresponding PR that fixes this bug (and link it to this issue).

#18951
Issue 1:
Coming from Python, I was really surprised to find that Julia has no way to execute code after a try block only if no exception/error was caught. Right now it seems the only way to get around this is something like:

try
maybe_raise_exception()
unrelated_stuff()
more_unrelated()
catch
stuff()
end

Whereas the Python code for this would read:

try:
maybe_raise_exception()
except SomeException:
stuff()
else:
unrelated_stuff()
more_unrelated()

It seems like bad practice to put code that we aren't worried about causing exceptions/errors in a try block so I'm interested in hearing what others have to say about this.

e: Alternatively you could do:

try
maybe_raise_exception()
noex = true
catch
stuff()
end
if noex
unrelated_stuff()
more_unrelated()
end

Although I do personally prefer the else syntax.

Issue 2:
master (70b6afa):

julia> isequal(Tuple{Vararg{Int, N}} where N)
julia> isequal(Tuple{Vararg{Int, N}} where N)
ERROR: TypeError: in new, expected DataType, got Type{Tuple{Vararg{Int64, N}} where N}
Stacktrace:
[1] Base.Fix2(f::typeof(isequal), x::Type{Tuple{Vararg{Int64}}})
@ Base ./operators.jl:1059
[2] isequal(x::Type)
@ Base ./operators.jl:1074
[3] top-level scope
@ none:1

1.6-rc1

julia> isequal(Tuple{Vararg{Int, N}} where N)
(::Base.Fix2{typeof(isequal), UnionAll}) (generic function with 1 method)

I confirmed this issue disappears after checking out to 3635f04, so I guess this is caused by 8fc5293 .

/cc @vtjnash
Issue 1:
It seems likely that 0.4 will see a transition to array views (#5556). This change will surely break some code, e.g., for anyone who was relying on the behavior of setindex! applied to the output of A[3:15, 7]. Perhaps we should take the occasion to simultaneously think about another (much worse) breakage.

As we've gotten less concerned about breaking Matlab compatibility (and as I've learned more about the wider scientific ecosystem), I've increasingly begun to wonder whether NumPy's slicing rules are the right way to go. It's very simple: if you index along a particular dimension with an AbstractVector, that dimension is retained; if you index with a scalar, that dimension is dropped. So for a 2d array A, A[:,:] produces 2d output, A[3,:] and A[:,3] both produce 1d output, and A[3:3,:], A[:,3:3] both produce 2d output. Note this scheme is type-stable, so AFAICT there are no performance gotchas.

But wow would it be a breaking change.

Issue 2:
I fixed complex dot(), but it still does not work correctly. I can't figure out what might be wrong. The only thing I can think of is that the C interface probably does not know how to return complex numbers.
Issue 1:
Consider:

using BenchmarkTools

struct Foo{T}
x::T
end

const m = [1,2,3]
const k = 1:3

@btime Foo(k);
@btime Foo(m);

Output:

julia> @btime Foo(k);

0.029 ns (0 allocations: 0 bytes)

julia> @btime Foo(m);
4.952 ns (1 allocation: 16 bytes)

It doesn't seem like Foo(m) should allocate when Foo(k) can avoid it.

Issue 2:
Add sum_kbn(itr) and sum_kbn(f, itr) methods.

https://discourse.julialang.org/t/why-sum-kbn-cant-sum-generators/1717/2