WhereIsAI/github-issue-similarity huggingface dataset:
Issue 1:
https://k8s-gubernator.appspot.com/build/kubernetes-jenkins/logs/ci-kubernetes-soak-gce-test/84/

Failed: BeforeSuite {Kubernetes e2e suite}

/go/src/k8s.io/kubernetes/_output/dockerized/go/src/k8s.io/kubernetes/test/e2e/e2e.go:165
Dec 6 12:00:03.528: Error waiting for all pods to be running and ready: 3 / 33 pods in namespace "kube-system" are NOT in RUNNING and READY state in 10m0s
POD NODE PHASE GRACE CONDITIONS
fluentd-cloud-logging-bootstrap-e2e-minion-group-ccml bootstrap-e2e-minion-group-ccml Running [{Initialized True 0001-01-01 00:00:00 +0000 UTC 2016-12-06 04:58:32 -0800 PST } {Ready False 0001-01-01 00:00:00 +0000 UTC 2016-12-06 04:59:35 -0800 PST } {PodScheduled True 0001-01-01 00:00:00 +0000 UTC 2016-12-06 04:58:32 -0800 PST }]
kube-proxy-bootstrap-e2e-minion-group-ccml bootstrap-e2e-minion-group-ccml Running [{Initialized True 0001-01-01 00:00:00 +0000 UTC 2016-12-06 04:58:32 -0800 PST } {Ready False 0001-01-01 00:00:00 +0000 UTC 2016-12-06 04:58:32 -0800 PST } {PodScheduled True 0001-01-01 00:00:00 +0000 UTC 2016-12-06 04:58:32 -0800 PST }]
node-problem-detector-v0.1-r97lg bootstrap-e2e-minion-group-ccml Running [{Initialized True 0001-01-01 00:00:00 +0000 UTC 2016-12-06 04:58:25 -0800 PST } {Ready False 0001-01-01 00:00:00 +0000 UTC 2016-12-06 04:58:37 -0800 PST } {PodScheduled True 0001-01-01 00:00:00 +0000 UTC 2016-12-06 04:58:32 -0800 PST }]

/go/src/k8s.io/kubernetes/_output/dockerized/go/src/k8s.io/kubernetes/test/e2e/e2e.go:135

Previous issues for this test: #26135 #26236 #27920 #28492 #29970 #30075 #32980 #33313 #35444 #37814

Issue 2:
https://k8s-gubernator.appspot.com/build/kubernetes-jenkins/logs/kubernetes-e2e-gce-scalability/10992/

Failed: BeforeSuite {Kubernetes e2e suite}

/go/src/k8s.io/kubernetes/_output/dockerized/go/src/k8s.io/kubernetes/test/e2e/e2e.go:158
Sep 23 11:26:08.874: Error waiting for all pods to be running and ready: 1 / 418 pods in namespace "kube-system" are NOT in the desired state in 10m0s
POD NODE PHASE GRACE CONDITIONS
node-problem-detector-v0.1-dwpq2 e2e-scalability-minion-group-i5cw Pending [{Initialized True 0001-01-01 00:00:00 +0000 UTC 2016-09-23 11:12:13 -0700 PDT } {Ready False 0001-01-01 00:00:00 +0000 UTC 2016-09-23 11:12:13 -0700 PDT ContainersNotReady containers with unready status: [node-problem-detector]} {PodScheduled True 0001-01-01 00:00:00 +0000 UTC 2016-09-23 11:16:54 -0700 PDT }]

/go/src/k8s.io/kubernetes/_output/dockerized/go/src/k8s.io/kubernetes/test/e2e/e2e.go:128

Previous issues for this test: #26135 #26236 #27920 #28492 #29970 #30075 #32980 #33313
Issue 1:
Make sure these boxes are checked before submitting your issue - thank you!

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

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

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

when table include number type columns and the value is null , The TableViz cannot display this table when these columns be selected in NOT GROUPED BY

Superset version

0.26.3 On centos7 + Python 3.6.5

Expected results

Actual results

Unexpected error.

Steps to reproduce

Table DDL:

CREATE TABLE testt ( id int(11) NOT NULL AUTO_INCREMENT, name varchar(255) DEFAULT NULL, value int(255) DEFAULT NULL, PRIMARY KEY (id) ) ENGINE=InnoDB AUTO_INCREMENT=5 DEFAULT CHARSET=utf8;

Data:

id
name
value

1
aaa
1

2
bbb

3
ccc
3

4
ddd

And choose these three columns in TableViz's NOT GROUPED BY selector.

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

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

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

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

Superset version

0.26.3

Expected results

Table View chart to load when column data contains NULL's. In previous versions it would display NULL's as 0's.

Actual results

Unexpected Error is thrown and subsequently the table did not load.

Steps to reproduce

Create a table view with a data set that has a column that contains some data and the rest NULL.

Select column with NULL data in NOT GROUPED BY section.

Run Query and see "Unexpected Error"

It seems this problem only exists with multiple rows of a column containing NULL data. I can load one row with NULL data in columns. As soon as I load more rows I get "Unexpected Error".
Issue 1:
Jon Daly opened SPR-7062 and commented

Would like a replacement for @Valid that could take group classes for JSR-303 validation. Right now only the default group class of JSR-303 Constraints is run for the @Valid.

Please refer to this forum thread for more detail: http://forum.springsource.org/showthread.php?p=292566

Reference URL: http://forum.springsource.org/showthread.php?p=292566

Issue Links:

SWF-1453 Support JSR303 Validation Groups for Webflow View States ("is depended on by")

#11039 Support for validation groups in @Valid used by spring MVC ("duplicates")

18 votes, 14 watchers

Issue 2:
Chris Widhelm opened SPR-2002 and commented

When calling ServletRequestUtils.getRequiredStringParameters or ServletRequestUtils.getStringParameters the following chunk of code throws a ServletRequestBindingException if there is an empty String as one of the parameter values. I would argue that an empty String is a value when dealing with a String.

protected final void validateRequiredParameter(String name, Object parameter)
throws ServletRequestBindingException {

if (parameter == null) {
throw new ServletRequestBindingException("Required " + getType() + " parameter '" + name
+ "' is not present");
}
if ("".equals(parameter)) {
throw new ServletRequestBindingException("Required " + getType() + " parameter '" + name
+ "' contains no value");
}
}

Attachments:

ServletRequestUtilsTest.java (986 bytes)

Issue Links:

#6686 ServletRequestUtils.getStringParameters behaviour with empty (not null) Strings is unintuitive ("duplicates")
Issue 1:
I have tried all the methods but did not succeed to make a batch processing of images in Go Tensorflow.

I have been following this test case for the inception model. I tried many things but did not work.

https://github.com/tensorflow/tensorflow/blob/master/tensorflow/go/example_inception_inference_test.go#L199

Could anyone help me? I really appreciate any help.

Issue 2:
Please make sure that this is a bug. As per our GitHub Policy, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:bug_template

System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow): Yes

OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Windows 10

TensorFlow installed from (source or binary): Binary

TensorFlow version (use command below): tensorflow-gpu 1.14.0

Python version: 3.6.7

CUDA/cuDNN version: 10

GPU model and memory: GTX1060M

Describe the current behavior

Wrapping a model in a TimeDistributed layer creates duplicate nodes in the graph. If we follow the docs (link) and create a simple Dense Model wrapped in a TD Layer:

inner_input = keras.layers.Input((2,))
dense = keras.layers.Dense(2, activation='relu')(inner_input)
inner_model = keras.Model(inputs=inner_input, outputs=dense)

full_input = keras.layers.Input((2,2))
td_2 = keras.layers.TimeDistributed(inner_model)(full_input)
model = keras.models.Model(full_input, td_2)
model.compile('SGD', 'mse')

You end up with this:

Firstly, if you follow the documentation approach you end up with an additional Dense Layer (Bottom Left). This eats up memory, and happens because you build the inner model then rebuild it again when you build the TimeDistributed model. This can be avoided by parameterizing your model (link), but it can be a very painful workaround if your model is complex. But for demonstrations sake, here's the model as an object:

class InnerModel(keras.Model):
def __init__(self):
super(InnerModel, self).__init__()

self.dense = keras.layers.Dense(2, activation='relu')

def call(self, inputs, training=None, mask=None):
out = self.dense(inputs)
return out

def compute_output_shape(self, input_shape):
return (input_shape[0], 2)

input = keras.layers.Input((2,2))
td_model = InnerModel()
time_dist = keras.layers.TimeDistributed(td_model)(input)
model = keras.models.Model(input, time_dist)
model.compile('SGD', 'mse')

Here's the improved graph:

So the additional Dense layer is gone, but there are still two dense layers inside. They have different contents too.

Describe the expected behavior

If you compare to what you get if you just wrap the Dense layer itself:

full_input = keras.layers.Input((2,2,2))
td_2 = keras.layers.TimeDistributed(keras.layers.Dense(2, activation='relu'))(full_input)
model = keras.models.Model(full_input, td_2)
model.compile('SGD', 'mse')

I'd expect wrapping a model should result in a very similar looking graph to wrapping a layer

Code to reproduce the issue

Full code for creating the graphs:

https://gist.github.com/LukeBolly/0efeca3db275dee97c5f0fbf1f400b5a
Issue 1:
Issue originally made by James Koshigoe (jameslk)

Bug information

Babel version: 6.6.5

Node version: v4.2.1

npm version: 2.14.7

Options

"babel-preset-es2015": "^6.6.0"

...

"presets": ["es2015"]

Input code

export var i = 0;
i++;

Description

When I try to run the following code:

export var i = 0;
i++;

I see the following error:

TypeError: test.js: undefined is not iterable!
at TypeError (native)
at module.exports.require.getIterator ([removed]/node_modules/babel-preset-es2015/node_modules/babel-plugin-transform-es2015-modules-commonjs/node_modules/babel-runtime/node_modules/core-js/library/modules/core.get-iterator.js:5:40)
at Object.UpdateExpression ([removed]/node_modules/babel-preset-es2015/node_modules/babel-plugin-transform-es2015-modules-commonjs/lib/index.js:132:125)
at NodePath._call ([removed]/.nvm/versions/node/v4.2.1/lib/node_modules/babel-cli/node_modules/babel-core/node_modules/babel-traverse/lib/path/context.js:63:18)
at NodePath.call ([removed]/.nvm/versions/node/v4.2.1/lib/node_modules/babel-cli/node_modules/babel-core/node_modules/babel-traverse/lib/path/context.js:47:17)
at NodePath.visit ([removed]/.nvm/versions/node/v4.2.1/lib/node_modules/babel-cli/node_modules/babel-core/node_modules/babel-traverse/lib/path/context.js:93:12)
at TraversalContext.visitQueue ([removed]/.nvm/versions/node/v4.2.1/lib/node_modules/babel-cli/node_modules/babel-core/node_modules/babel-traverse/lib/context.js:152:16)
at TraversalContext.visitSingle ([removed]/.nvm/versions/node/v4.2.1/lib/node_modules/babel-cli/node_modules/babel-core/node_modules/babel-traverse/lib/context.js:115:19)
at TraversalContext.visit ([removed]/.nvm/versions/node/v4.2.1/lib/node_modules/babel-cli/node_modules/babel-core/node_modules/babel-traverse/lib/context.js:184:19)
at Function.traverse.node ([removed]/.nvm/versions/node/v4.2.1/lib/node_modules/babel-cli/node_modules/babel-core/node_modules/babel-traverse/lib/index.js:135:17)

Issue 2:
Issue originally made by Justin Johansson (justinjohansson)

Bug information

Babel version: 6.11.4 (babel-core 6.13.2)

Node version: v6.4.0

npm version: v6.4.0

Input code

Bug shows up when transpiling following input code with ES2015 CommonJS module transform plugin.

/* file: bar.js */

export { yy, zz };

var yy = 0;
var zz = yy++;

Description

Bug is apparent by visual inspection of code in babel-plugin-transform-es2015-modules-commonjs/src/index.js line 122 in UpdateExpression:

let newPaths = path.replaceWithMultiple(t.sequenceExpression(nodes));
for (const newPath of newPaths) this.requeueInParent(newPath);

replaceWithMultiple is a method which always returns undefined. The following for/in statement will therefore always throw an exception as follows:

babel -d dist src
TypeError: src/bar.js: Cannot read property 'Symbol(Symbol.iterator)' of undefined
at Object.UpdateExpression
Issue 1:
I'm trying to create an application that registers events on key presses. The registering works fine, and the events are triggered properly, but the keypress isnt passed forwards onto the OS for any other program to process.

Yes I'm using single character ('x' etc.), and obviously there are security implications of this (no I'm not writing anything malicious), but it would still be nice to be able to bind to keys and them still pass to other programs on the OS.

Any help would be great, sorta forgot to check this was possible before I started developing the rest of it 👍

Issue 2:
Not sure if this is the intended outcome, but wasnt what I expected;

if I register 'ctrl+c' or 'ctrl+x' as a global shortcut, the system will only listen to that function and not run the default copy/cut-function. I was hoping to bind my listener as an addition to the default function..
Issue 1:
https://k8s-gubernator.appspot.com/build/kubernetes-jenkins/logs/ci-kubernetes-e2e-gci-gke-pre-release/77/

Failed: [k8s.io] Kubelet [Serial] [Slow] [k8s.io] regular resource usage tracking resource tracking for 100 pods per node {Kubernetes e2e suite}

/go/src/k8s.io/kubernetes/_output/dockerized/go/src/k8s.io/kubernetes/test/e2e/kubelet_perf.go:279
Dec 6 08:12:34.311: Memory usage exceeding limits:
node gke-bootstrap-e2e-default-pool-33fbefd8-5f1z:
container "kubelet": expected RSS memory (MB) < 83886080; got 87023616
/go/src/k8s.io/kubernetes/_output/dockerized/go/src/k8s.io/kubernetes/test/e2e/kubelet_perf.go:154

Previous issues for this test: #26982 #33994 #34035 #35399

Issue 2:
https://k8s-gubernator.appspot.com/build/kubernetes-jenkins/logs/kubernetes-soak-continuous-e2e-gce/6512/

Failed: [k8s.io] Kubelet [Serial] [Slow] [k8s.io] regular resource usage tracking resource tracking for 100 pods per node {Kubernetes e2e suite}

/go/src/k8s.io/kubernetes/_output/dockerized/go/src/k8s.io/kubernetes/test/e2e/kubelet_perf.go:278
Sep 7 04:56:39.012: Memory usage exceeding limits:
node jenkins-e2e-minion-group-4yze:
container "kubelet": expected RSS memory (MB) < 83886080; got 85123072
/go/src/k8s.io/kubernetes/_output/dockerized/go/src/k8s.io/kubernetes/test/e2e/kubelet_perf.go:153

Previous issues for this test: #26982
Issue 1:
The following program calls 'fail!()', but still results in an exit code of zero:

fn main () {
os::args();
fail!();
}

Here's what it looks like:

jclements-09740:~/clements/projects/rust-experimenting clements> rustc ./foo.rs && ./foo && echo "done"
Running /usr/local/bin/rustc:
warning: no debug symbols in executable (-arch x86_64)
rust: task failed at 'explicit failure', ./foo.rs:3
done

Commenting out the call to "os::args()" produces the expected output:

jclements-09740:~/clements/projects/rust-experimenting clements> rustc ./foo.rs && ./foo && echo "done"
Running /usr/local/bin/rustc:
warning: no debug symbols in executable (-arch x86_64)
rust: task failed at 'explicit failure', ./foo.rs:3
rust: domain main @0x7fdd91815e10 root task failed

... note the extra line of output, and the lack of the "done" message, indicating a nonzero exit code.

Issue 2:
fn main() {
os::args();
assert!(false);
}

Causes the program to return with exit status 0. Thankfully removing os::args() makes it return with nonzero, but it appears that at any point after the invocation of os::args() an assertion failure will cause an exit status of 0.

I ran this against a compiler built at e51ec26
Issue 1:
I'm submitting a ... (check one with "x")

[ x] bug report => search github for a similar issue or PR before submitting
[ ] feature request
[ ] support request => Please do not submit support request here, instead see https://github.com/angular/angular/blob/master/CONTRIBUTING.md#question

Current behavior

When a directive is attached to the DOM via @HostBinding decorator, it seems to not be active.

import { Component, Directive, ElementRef, HostBinding } from '@angular/core';

@Directive({
selector: '[ui-color]',
})
export class ColorDirective {
constructor(el: ElementRef) {
el.nativeElement.style.backgroundColor = 'red';
}
}

@Component({
selector: 'test-cmp',
template: `Should be red`,
})
export class TestComponent {
@HostBinding('attr.ui-color') color = '';
}

@Component({
selector: 'my-app',
template: `
<test-cmp></test-cmp>
<div ui-color>Should be red</div>
`,
})
export class AppComponent {}

//Two text lines should be red

The problem is also reproduced with modules: angular/flex-layout#76

Expected behavior

Directive should be active when injected via @HostBinding decorator.

Minimal reproduction of the problem with instructions

https://plnkr.co/edit/j5MSVP5pIRjTTK9D2LsS

What is the motivation / use case for changing the behavior?

Please tell us about your environment:

Angular version: 2.0.X | 4.0.X

Browser: [all ]

Language: [all]

Issue 2:
Possible bug with slice in alpha.55 and beta 0 … was there a change with slice recently?

The app gets a list and then slices them. No changes are made on load.

The app works without slice.

// cc @wardbell
Issue 1:
Bug summary

When using Jupyter notebook and matplotlib.pyplot with setting %matplotlib notebook,

the plots generated only show the top left corner. One can pan and see the remaining section of the plot.

Using %matplotlib inline does not have the same problem.

Code for reproduction

##any plotting code will do, a simple example is attached

import matplotlib.pyplot as plt

%matplotlib notebook

x = np.arange(10)

y = x

plt.plot(x,y)

Outcome

I am posting another user's stackoverflow result, as he already attached the outcome:

https://stackoverflow.com/questions/63106366/matplotlib-notebook-magic-in-jupyter-notebook-partial-plot

Matplotlib version

Operating system: ubuntu 20.04.1

Matplotlib version: '3.3.0'

Matplotlib backend (print(matplotlib.get_backend())): nbAgg

Python version: 3.8.2

Jupyter version (if applicable): 6.1.1

Other libraries:

pip3, by having --user flag

Issue 2:
Bug report

Bug summary

A simple 3D scatter plot is not working on jupyter notebook when %matplotlib notebook is enabled. However, it is working for %matplotlib inline

An extremely large, blank window appears that spans beyond the page.

Code for reproduction

%matplotlib notebook

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

A = np.random.random((100,3))
fig = plt.figure()
ax = Axes3D(fig)
ax.scatter(A[:,0], A[:,1], A[:,2])
plt.show()

Actual outcome

Expected outcome

Expecting a 3D scatter plot of A.

Matplotlib version

Operating system: posix Darwin 19.6.0

Matplotlib version: 3.3.0

Matplotlib backend (print(matplotlib.get_backend())): nbAgg

Python version: 3.7.5

Jupyter version (if applicable):

jupyter core : 4.6.3

jupyter-notebook : 6.0.3

qtconsole : 4.7.5

ipython : 7.16.1

ipykernel : 5.3.4

jupyter client : 6.1.6

jupyter lab : not installed

nbconvert : 5.6.1

ipywidgets : 7.5.1

nbformat : 5.0.7

traitlets : 4.3.3

Other libraries: numpy 1.19.1, scipy 1.5.2
Issue 1:
On beta, this container (which still has a message which says "output will go here"), no longer shows the challenges' output:

Instead, we only see the notification that the tests are running or have completed:

Are we doing away with showing the challenge output or is this unintentional? If we are, we need to change that default message. But I think we should still show it, it's nice to have that tangible feedback.

cc/ @freeCodeCamp/moderators Anyone know anything about this? I might have missed a previous issue.

Issue 2:
The instructions ask us to change the second child of div with class="well", but the exercise is validate when you change div class="target" element.
Issue 1:
Problem description

Since upgrading from material-ui 0.14.4 to 0.15.1 I'm noticing my SelectField component is not rendering MenuItems. This could be due to the two warnings i'm seeing (related to #4594), but those are warnings, not errors.

Steps to reproduce

import MuiThemeProvider from 'material-ui/styles/MuiThemeProvider';
import SelectField from 'material-ui/SelectField';
import MenuItem from 'material-ui/MenuItem';

var Example = React.createClass({
render: function() {

return (
<MuiThemeProvider>
<SelectField floatingLabelText="Rendering">
<MenuItem value={1} primaryText="Not rendering" />
</SelectField>
</MuiThemeProvider>
);
}
});

module.exports = Example;

Versions

Material-UI: 0.15.1

React: 15.2.0

Browser: Chrome 50.0.2661.75 (64-bit)

Issue 2:
Problem description

I can't open the SelectField,that is it is not useful to click SelectField.But My code is just referred to http://www.material-ui.com/#/components/select-field

Could you give me some suggestions?

Steps to reproduce

1.I write a div that contains a SelectField

<div>
<SelectField
floatingLabelText="sex"
value={this.props.pageData.newUser == undefined?"1":this.props.pageData.newUser.sex}
onChange={(event, index, value) => {
let tempPageData = this.props.pageData;
tempPageData.newUser.sex = value;
this.props.changePageData(tempPageData);
}}
>
<MenuItem value="1" primaryText="man"/>
<MenuItem value="2" primaryText="woman"/>
</SelectField>
</div>

The default value of SelectField is "1"

2.The Page shows as follows:

Versions

Material-UI: ^0.15.0

React: ^15.0.1

Browser: google cherome
Issue 1:
System information (version)

OpenCV => 4.1.2（Ubuntu18.04），4.2（Win10 64bit)

Operating System / Platform => Linux, Win

Compiler => gcc7.5(linux), Visual Studio 2019(Win10)

Tensorflow => 2.1

Detailed description

I want to convert keras model to .pb file and load it using dnn.readNetFromTensorflow() , and I got an error like the title shows ( same error in Ubuntu18.04 with opencv 4.1.2):

error: OpenCV(4.2.0) E:\ScientificComputing\opencv-4.2.0\modules\dnn\src\tensorflow\tf_io.cpp:42: error: (-2:Unspecified error) FAILED: ReadProtoFromBinaryFile(param_file, param). Failed to parse GraphDef file: my_model/saved_model.pb in function 'ReadTFNetParamsFromBinaryFileOrDie'

Can someone tell me the best way to load a keras model (tf version is 2.1)? I tried the solution in issue #13728 , but didn't work for me.

Steps to reproduce

import tensorflow as tf
import cv2
from cv2 import dnn
import numpy as np
import matplotlib.pyplot as plt
import os
print(tf.__version__)
print(cv2.__version__)
model = tf.keras.applications.mobilenet.MobileNet(weights=None)
model.save('my_model', save_format='tf')

net = dnn.readNetFromTensorflow('my_model/saved_model.pb')

In tf2.1, the save method using argument save_format='tf' will generate files like below:

Issue 2:
I encountered a discrepancy between the documentation (found here) and the actual behavior of the cv::log function. Though the documentation says that log(0) will evaluate it to roughly -700, printing it indicates that it is -inf. Is this the intended behavior?

Please state the information for your system

OpenCV version: 3.1.0

Host OS: Mac OS X 10.10.5

Duplicate of #4982