not sure how to handle this local variation, letters following cutter

In my catalog, sometimes letter suffixes have been added to cutters.
Say, BA 101.1 A123a
Note the a on the end. It doesn't have to be a, and sometimes is more than one letter.
This definitely isn't standard LC call numbering, it's a variation. Local catalogers aren't sure how common this practice might be. The Stanford call number parsing code doesn't handle it, I don't think. Bill Dueber's parsing code doesn't parse it 'correctly', although it doesn't reject it.
I need to handle it somehow. It doesn't matter too much to me if the letters are treated correctly for sorting, or just ignored as if they weren't there. But currently, the letters cause the call number not to match the initial regex and be rejected entirely.
I'm not really sure what to do.  Modifying Lcsort to handle this local variation doesn't feel good; but neither does forking Lcsort to my own custom version. I can't figure out any good way to make Lcsort locally customizable -- there'd have to be an option for changing the regex AND an option for supplying custom logic for turning the cutter into a sortkey. It could be done, but would be a lot of work and make the code a lot more complicated. It would be a lot easier to simply make Lcsort handle my local variation out of the box, but yeah, it feels not great.  But I'm leaning to that just because it would make things easier for me at least, and I don't think would cause any problems for anyone else.
Any thoughts or advice?

Added wrinkle that might justify adding cutter-letter-suffix recognition to the main Lcsort:
NLM call numbers look a lot like LC call numbers, but differ in some ways. One way they appear to differ is that cutters sometimes have letter suffixes (for serials only, I think).
http://www.nlm.nih.gov/tsd/cataloging/trainingcourses/classification/mod9_050.html
Adding recognition of letter suffixes in cutters is necessary for parsing NLM call numbers (I'm not sure if it's sufficient as well as necessary, but I think it might be).
Man, call numbers are a mess.
I'm inclined to submit a PR where letter suffixes on cutters are recognized -- I don't care too much if they wind up sorting 'correctly', or the letter suffixes are just ignored. "Correctly" means A123a sorts after A123 but before A1231 or A124.  "Ignore" would mean sort A123a just like A123, it's not determined which comes first, the suffix just gets stripped. Either is fine with me.

Bah, nevermind, NLM diverges in several other ways too.

I think suffixes like the one in the example you mentioned are fairly common practice. We have them also, but usually they are part of the "extra" portion so they don't interpreted as another cutter. I think in this case a suffix that appears as part of a cutter should be put into the extra.

Thansk for the feedback!
It's not as easy as "putting it in the extra", for my use case.  "The extra" is at the end of the entire call number, but in my case at least, these extra letters can be internal.
QA 101.1 A101zz  B202

Note the zz is the kind of suffix I'm talking about.
I'll probably submit a PR for it anyway though, see what we think. I may give up and ignore those suffixes -- it's really tricky to actually have them sort 'correctly', I've been trying, at some point I'll give up and decide it's good enough if QA 101.1 A101zz B202 just sorts exactly the same as QA 101.1 A101 B202 -- right now, it doesn't parse at all.

Actually I think it is as easy as "putting in the extra." The hard part I believe is being able to capture the suffixes (which it sounds like you need to do either way). However, if you can do that, moving it to the end of the extra (or maybe the beginning of the extra?) would give you the desired result.
$ cn1 = Lcsort.normalize("QA 101.1 A101 B202") => "QA<PHONE_NUMBER>A101B202"
$ cn2 = Lcsort.normalize("QA 101.1 A101 B205") => "QA<PHONE_NUMBER>A101B205"

Imagine a function that gives you the captured suffix and the call number with such suffix removed:
$ suffix, cn_stripped = capture_suffix("QA 101.1 A101zz B202")
$ cn3 = Lcsort.normalize(cn_stripped) + suffix => "QA<PHONE_NUMBER>A101B202zz"
$ [cn1, cn2, cn3].sort => [cn1, cn3, cn2]

Hm, I think that woudln't actually sort correctly. Here's a proper sort order:

QA 101.1 A101
QA 101.1 A101a
QA 101.1 A101b
QA 101.1 A101 B101

I don't think your approach would result in that sort order?  Although frankly at this point I'd be happy to simply strip/ignore the suffix, and treat QA 101.1 A101a as sorting identically to QA 101.1 A101, as opposed to not parsing. Which would be fairly easy to implement as built-in to lcsort.
REALLY I'm considering just ignoring it entirely at this point and letting those call numbers simply be rejected, oh well. There are so many idiosyncratic call numbers we have falling through the cracks anyway, I think maybe that's just how it's gonna be.

Still not quite sure what to do with all this -- I'm considering whether we want to turn the code into actual object-oriented class, so you'd do something like this:
normalizer = LCSort.new
normalizer.normalize(call_number)
That would make it easier to provide configuration options to parse in different ways. Maybe:
normalizer.allow_letter_suffixes!
# or
normalizer.extend(LCSort::AllowLetterSuffixes)

Although I'm not sure most users will actually want configuration. It might provide cleaner code either way, even if we don't (initially) provide configuration.  I might benchmark to make sure it doesn't slow things down though, I need performance from this library.
I definitely also want to handle the "date or other number" that can appear before a cutter, as in JK1359 46th .M4 or QA 101 1990 .A101.  That is standard LC.
It's unclear how adding those will effect the 'bottomout' option. We need more tests for bottomout, and to think about what we actually want to support. I wonder if bottomout actually only needs to be supported for classifications (eg QA 101.1) and not for subsequent cutter numbers. I asked Bill Dueber about use cases for bottomout including cutters, but he couldn't remember for sure. If we only support bottomout for class numbers, generated sortkeys can get significantly simpler, we don't need to pad all the cutters.
I also want to make this thing be able to handle NLM call numbers, which are MOSTLY like LC, but have some different allowable patterns in cutters. I'm still figuring out

Hey @tampakis, I've got some ideas for some fairly major refactors

Change the way the normalized strings are constructed a bit, to better accomodate the enhancements we want
Make the whole thing object-oriented  (Lcsort.new.normalize(foo)) to hypothetically allow some easier customization for different local rules.

Since I have a bunch of stuff I want to work on or experiment with, I've made my own fork and am doing my work there, currently in a branch: https://github.com/jrochkind/lcsort/tree/object_oriented
I'm happy to give you commit rights on my fork if it would make any kind of collaboration easier. Feel free to put a watch on that repo to see my work as it progresses.
I also plan to share my changes back when I'm doing; I'm not trying to go off with a permanent fork, I just wanted to do a bunch of work to see where it gets me, in a repo I have commit rights to.

Sounds good. I'll watch that repo and see how I can help.

Hey @tampakis, I've done some MAJOR overhaul of lcsort, over in https://github.com/jrochkind/lcsort/tree/object_oriented
I think it does everything I need now, and has a README.
Do you want to merge it back in here? Would you consider adding me as a committer here?
It does not yet handle your lowercase x as a cutter prefix to be ignored. I wonder if your org locally is maybe simply using that x as an alternative to ., and you could pre-process to just turn them into standard . by something simple like gsub(/x([A-Z])/, ".\1", or something like that?

@jrochkind this looks awesome! I just give you admin rights on this repository. Submit a PR and I'll merge.

FYI, our local call number browse is live, eg here

:+1:


Support array type during intersection

The change is motivated by https://github.com/colinhacks/zod/issues/636.
It should be possible to intersect schemas that consist of common fields, even
in the common fields are defined via z.array. Prior to the current change it
was only possible to intersect primitives/objects.

@colinhacks any chance to take a 👁

Great PR, merged in 3.9.8 👍


Travis County, TX

The data can be downloaded here: https://data.austintexas.gov/Geodata/Address-Points/bpa2-q2tj
although this is on the cities open data portal, it covers the county.  If we are missing anything in the region, we can look at the surrounding counties (here: http://regional-data.capcog.opendata.arcgis.com/datasets?q=property&sort_by=relevance ) or I was told individual cities there : sunset valley, lakeway, roundrock, cedar park - all maintain their own address data.  So its all over the place...  Tonight I'll download all of Texas and do some analysis against US TIGER Places and see where we are missing data.  If anyone has questions/ concerns let me know.  Thanks

The Austin, TX data can be found in this source here:
https://github.com/openaddresses/openaddresses/blob/4061df1d4af774d8c8fb0402d6353f47285384d0/sources/us/tx/city_of_austin.json

@iandees I was looking for data for all of Travis County, TX as per http://davidchiles.org/2016/11/21/Progress-on-OpenAddresses.html saying we are missing Travis County - and after several phone calls - that is where they told me the data was.  I opened, panned around, and the county seems full (even overlaps to the county to the north of it).  I have to do some analysis tonight to see what cities we have data for and what ones are missing.  I usually trust the interactive map right on OA - but sometimes things don't plot.  not trying to make more work where we don't need it - just trying to make sure we account for major metros/ big counties.

(The interactive map on openaddresses.io is still out of date)

I'm going to close this issue; after looking into our sources and looking at the data, we have a top-notch dataset for Travis county/ Austin (*although it is in the city of Austin's open data portal, has coverage for the majority of Travis County).  I created the issue ticket because of the article here: http://davidchiles.org/2016/11/21/Progress-on-OpenAddresses.html but should have looked at the data first.  I believe we have coverage for Travis County based on the data here: https://github.com/openaddresses/openaddresses/blob/4061df1d4af774d8c8fb0402d6353f47285384d0/sources/us/tx/city_of_austin.json


Tony/54_escape_characters

Pull Request Details
What issue does this PR address

Add support for escaped left and right brackets.

Link to associated issue: #54

Checklist
Complete the check-list below to ensure your branch is ready for PR.
Flutter Style Guide: https://survivor.togaware.com/gnulinux/flutter-style.html

[x] Screenshots included in linked issue
[ ] Changes adhere to the team style and coding guideline
[x] No confidential information
[x] No duplicated content
[x] No lint check errors related to your changes (make prep or flutter analyze lib)
[ ] Pre-exisiting lint errors noted: [HERE]
[x] Tested on at least one device

[ ] Android Phone
[ ] Android Emulator
[ ] Chrome on Android
[ ] Chrome
[ ] iOS
[ ] Linux
[x] MacOS
[ ] Windows

[x] Added 2 reviewers (or 1 for private repositories then they add another)

Finalising
Once PR discussion is complete and 2 reviewers have approved:

[ ] Merge dev into the branch
[ ] Resolve any conflicts
[ ] Add one line summary into CHANGELOG.md
[ ] Bump appropriate version number in pubspec.yaml
[ ] Push to git repository and review
[ ] Merge PR into dev

I am getting the following error.

I am getting the following error.

Hi @anushkavidanage, thank you for your feedback. Could you share your markdown code for this question? I'll analyse the reason. Thank you very much.

Here's the markdown code.
3. The following are two groups of checkboxes. This is Question 3. Multiple
   options can be selected.

%% Checkbox(Question 3,1,"Option 1 This is a long option that may wrap to the
next line if it needs to. When wrapping it does so indented to align the
paragraph. This example also demonstrates the use of escape characters, such
as \".")

%% Checkbox(Question 3,2,"Option 2. If you choose this option, you will need to
answer another follow-up question.",Hidden 3)

%% Checkbox(Question 3,3,"Option 3")

%% Checkbox(Question 3,4,"Option 4 (details about option 4)")

%% Checkbox(Question 3,5,"Option 5")

%% Checkbox(Question 3,6,"Option 6")

%% Hidden-Begin(Hidden 3)
This is a follow-up question for Option 2.
%% InputML(Question 3.2)
%% Hidden-End

Here's the markdown code.
3. The following are two groups of checkboxes. This is Question 3. Multiple
   options can be selected.

%% Checkbox(Question 3,1,"Option 1 This is a long option that may wrap to the
next line if it needs to. When wrapping it does so indented to align the
paragraph. This example also demonstrates the use of escape characters, such
as \".")

%% Checkbox(Question 3,2,"Option 2. If you choose this option, you will need to
answer another follow-up question.",Hidden 3)

%% Checkbox(Question 3,3,"Option 3")

%% Checkbox(Question 3,4,"Option 4 (details about option 4)")

%% Checkbox(Question 3,5,"Option 5")

%% Checkbox(Question 3,6,"Option 6")

%% Hidden-Begin(Hidden 3)
This is a follow-up question for Option 2.
%% InputML(Question 3.2)
%% Hidden-End

Hi @anushkavidanage, thank you for sharing your markdown code. I think you can use escape characters ( and ) to represent the brackets as below.
%% Checkbox(Question 3,4,"Option 4 \(details about option 4\)")

In this ticket (#54), I defined 3 escape characters '(', ')' and '"' to represent '(', ')' and '"' respectively, because using these 3 characters directly may cause parsing problems.

Thanks for the clarification Tony. That worked. Thanks.

Hi Tony, using the markdown code below, I got \( and \) as shown in the screenshot, is that expected behaviour?
%% Dropdown(Dropdown Menu)
- Option 1 \(Hello\)
- Option 2
- Option 3
- Option 4

Hi Tony, using the markdown code below, I got \( and \) as shown in the screenshot, is that expected behaviour?
%% Dropdown(Dropdown Menu)
- Option 1 \(Hello\)
- Option 2
- Option 3
- Option 4

Hi @cdawei, the escape characters are just designed for radio buttons and checkboxes. Because after the %% Radio command and the %% Checkbox command, there is an argument list, which uses brackets and quotation marks to mark the beginning and the end of the argument list and the string inside it.

Hi @cdawei, the escape characters are just designed for radio buttons and checkboxes. Because after the %% Radio command and the %% Checkbox command, there is an argument list, which uses brackets and quotation marks to mark the beginning and the end of the argument list and the string inside it.

Thanks Tony for clarifying. If this is clearly described in the user manual then all good.

Hi @cdawei, the escape characters are just designed for radio buttons and checkboxes. Because after the %% Radio command and the %% Checkbox command, there is an argument list, which uses brackets and quotation marks to mark the beginning and the end of the argument list and the string inside it.

Thanks Tony for clarifying. If this is clearly described in the user manual then all good.

Thanks @cdawei. I updated the README file.


How many apps use Swift in 2019?

https://blog.andrewmadsen.com/post/182862756395/how-many-apps-use-swift-in-2019
作者分析了App Store中前100名App使用Swift和Objective-C的情况。
Objective-C还远未消亡。

https://gist.github.com/armadsen/477d9a1d6d61dac37f8336fdf58981d4


xwayland: create one selection window per selection source

This allows multiple data transfers to happen at the same time, and removes the need for a transfer queue.

Closing in favor of https://github.com/swaywm/wlroots/issues/1497.

Closing in favor of https://github.com/swaywm/wlroots/issues/1497.


Fix golint issues in select_disk.go

Following file has a lint issue:
 maya/cmd/maya-apiserver/spc-watcher/select_disk.go
The lint  issue is :
Line 118: warning: error should be the last type when returning multiple items (golint)
Line 222: warning: error should be the last type when returning multiple items (golint)
Line 242: warning: error should be the last type when returning multiple items (golint)

Help Links :
Contributors guide

I am unable to fix the sign-off should I create another pull request?

#707 fixed this!

https://github.com/openebs/maya/pull/707 Fixes this!


Blurry Font and Ripple Effect Menu Bar!

This same thing happens on Atom, Visual Studio and Light Table, Brackets its fine.
Text is very distorted and blurry and it gets better if I hover with a mouse over part of a text (only that part gets better) if I don't move the mouse that area gets bad again, also the menu bar gets something like Ripple effect or like a page is opening and its moving, could someone explain why this happens?!
OS: Windows 10 Pro 1151

It sounds like a bad video driver or card to me, especially since this is happening in multiple applications. Can you reproduce the problem in Chrome?

@lee-dohm No I can't repro on Chrome, chrome is fine, I'm using Radeon Graphics Crimson Edition Drivers, if I can't repro on chrome hat means the problem is in Electron

We haven't seen anything like this. Can you reproduce this on another computer?

Maybe related to #10185.
For me some parts of the text are blurry others aren't as bad. But on the whole font rendering is very, very bad.

@damieng can you work your font magic here?

Electron uses DirectWrite hardware graphics acceleration and I suspect these new Radeon drivers are applying some additional processing effects without realizing what the result will be. Very few apps do this today although Chrome does I suspect they have opted Chrome out of things.
I'd try going into the Chrome folder on your machine and copying the chrome.exe and launching that to see if the new copy has distorted text (drivers tend to opt apps out based on the filename of the executable).
These new Radeon drivers do let you specify 3D options for specific apps according to http://www.anandtech.com/show/9811/amd-crimson-driver-overview/4 so I'd recommend adding atom.exe to that and turning off a bunch of options to see if it improves. (I don't have an AMD card to repro with as I use Nvidia)
I suspect this is going to be a Radeon driver bug they're going to want to address as it's going to affect more and more apps using DirectWrite.

Based on some more research I think the specific setting you want to disable for atom.exe (and potentially other EXE's that use Electron) is to disable Morphological Anti-Aliasing (MLAA)

I'm using an Nvidia and intel GPU.  @damieng  How can i disable  Morphological Anti-Aliasing (MLAA)?

@musmo are you seeing exact same effect? Can you post a screen shot from yours too?

bottom paragraph blurry top not blurry

That's actually a different issue relating I think to sign pixel positioning. I'll see if I can find the issue number for the other one and link it here.

Given other reports I've seen online referring to AMD drivers, this kind of text effect and the need to disable MLAA I'm going to close this bug. Please re-open if this does not solve your issue @jack-dev


[BUG] GitHub Enterprise Cloud is not supported

Describe the bug
Most likely GitHub Cloud and GitHub Enterprise Cloud need to be treated differently.
Log and Stack trace
Status code 401,"{"error":{"code":"unauthorized","message":"Your account type is not currently supported","details":"Your account type is not currently supported"}}"

The exact same granular token scope for my other account works fine.
Expected behavior
The GitHub Model does also work for GitHub Enterprise Cloud users.
Please complete the following information:

LangChain4j version: 0.36.0
LLM(s) used: GitHub Copilot

Additional context
Just to link a bug in a project which is using langchain4j: https://github.com/Blarc/ai-commits-intellij-plugin/issues/286

cc @jdubois @agoncal

I don't think there's a specific authentication mechanism for GitHub Enterprise Cloud, could you check at https://docs.github.com/en/enterprise-cloud@latest/github-models/prototyping-with-ai-models if you can access them directly, without using LangChain4j ?


and  tags don't work

Hi there,
I'm trying to use jekyll-scholar to automate the bibliography section and I found out that when generated, the HTML tags  and  are there but are never displayed in the screen. I tested in both Firefox and Chrome in case it was an issue with the browser but the result is the same.
This also happens if I write literal HTML tags in the index.md, they appear in the source code of the HTML but they are not rendered in the screen.
Any idea why this could be?
Thank you in advance,
Xabi
PS: this is the link to the jekyll-scholar issue https://github.com/inukshuk/jekyll-scholar/issues/242

you should specify a styling for i and b elements in the CSS file you use.
All styles are cleared at the top of the default CSS, and no italic or bold tag is specified.


query by location not working in GEP 10.2.2

Queries based on location are not working for me.
I am using the adapters, transports and so on provided on the Twitter for Geoevent tutorial published in August 2014.
I am using the 10.2.2 version of the geoevent processor extension.

@luisbausalopez - apologies for the delay in response. I would recommend that you configure a Filter in your GeoEvent Service which references a GeoFence to discard any Geolocated tweets which are outside a given area of interest. I've had issues using the Twitter API to query for tweets based on location.

@rsunderman - Thanks for the reply. That is exactly what I am currently doing, but unfortunately that won't work for me because that means I only get the Tweets corresponding to a specific query (i.e. containing some keywords) and afterwards filtered by location, and not ALL the tweets within the area of interest.


Dashboard name restrictions

Make sure dashboard name will not have conflict with routes.

playground
status

will never conflict with existed routes now


Containers, Wrappers and Managers for Application

All base classes for interaction with UI and Android Services are complete. This effectively closes #13. These changes introduce

MinimalPokemon: smaller class to perform quick viewing operations.
PokedexManager: for handling the currently selected Pokemon and its information.
PokedexAssetFactory: class with static methods for asset retrieval
IMediaPlayer and ITTSEngineWrapper: interfaces for OS resources used in audio playback
CentralAudioPlayer and TTSController: the realization of the above interfaces
PokedexArrayAdapter: UI container that extends "ArrayAdapter" for interacting with customized rows
Partial asset list incorporation to apk build, but includes most Pokemon Sprites and Cries
Small UI changes, pending a larger, more thorough redesign

Good catch on the details @minicole, would not have easily noticed the typos


Fix 'NoneType' Error on jupyter notebooks

Some objects don't return anything for getmodule(), e.g., jupyter notebook.
While I am using it on jupyter notebooks, the code throws an Error:
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-13-720eba80f94f> in <module>()
     87
     88 @register_trainer
---> 89 class Trainer(BaseTrainer):
     90     def __init__(self, model,
     91                  train_dataloader, val_dataloader, loss_fn, optimizer, device=torch.device('cpu'), trainer_kwargs={'max_epochs': 10}):

~/anaconda3/lib/python3.7/site-packages/nni/retiarii/utils.py in register_trainer(cls)
    117     """
    118     frm = inspect.stack()[1]
--> 119     module_name = inspect.getmodule(frm[0]).__name__
    120     return _blackbox_cls(cls, module_name, 'full')
    121

AttributeError: 'NoneType' object has no attribute '__name__'

In this case, we can use getsourcefile to get the name of the current cell in the jupyter notebook, for example, <ipython-input-14-f75f6173b0d5> means the 14th cell and the subsequent programs can run normally.

I found that this problem is related to the framework design. The core of the problem is that we have to generate different codes according to the user's settings and manage their operation. To solve the problem of "how to find the location of custom modules (including custom blackbox_module, Trainer, etc.) in the generated code", I made a lot of changes, but I am not sure whether they can cover many scenarios, so I don’t submit and respect the choices of existing developers.
Now, NNI's codes depend on two main ideas, i.e., hard-code definition and dynamic inspect. They are not robust, but it is indeed a simple and clear method. In this situation, we need users to create a new module when they need to custom new blackbox_module, Trainer, etc. (not able to finish the definition process in a single file). For example, if we try to custom a layer as follows:
import random

import nni.retiarii.nn.pytorch as nn
import torch.nn.functional as F
from nni.retiarii.utils import blackbox_module
from nni.retiarii.experiment import RetiariiExeConfig, RetiariiExperiment
from nni.retiarii.strategies import RandomStrategy
from nni.retiarii.trainer import PyTorchImageClassificationTrainer

# from layer.sequential import LayerChoiceSequential

import nni.retiarii.nn.pytorch as nn
from nni.retiarii.utils import blackbox_module

@blackbox_module
class LayerChoiceSequential(nn.Module):
    def __init__(self, m):
        super().__init__()
        self.m = nn.Sequential(m)

    def forward(self, x):
        return self.m(x)

class Net(nn.Module):
    def __init__(self, hidden_size):
        super(Net, self).__init__()
        self.conv1 = nn.Conv2d(1, 20, 5, 1)
        self.conv2 = nn.Conv2d(20, 50, 5, 1)
        self.fc1 = nn.LayerChoice([
            LayerChoiceSequential(nn.Linear(4*4*50, hidden_size)),
            nn.Linear(4*4*50, hidden_size, bias=False)
        ])
        self.fc2 = nn.Linear(hidden_size, 10)

    def forward(self, x):
        x = F.relu(self.conv1(x))
        x = F.max_pool2d(x, 2, 2)
        x = F.relu(self.conv2(x))
        x = F.max_pool2d(x, 2, 2)
        x = x.view(-1, 4*4*50)
        x = F.relu(self.fc1(x))
        x = self.fc2(x)
        return F.log_softmax(x, dim=1)

if __name__ == '__main__':
    base_model = Net(128)
    trainer = PyTorchImageClassificationTrainer(base_model, dataset_cls="MNIST",
                                                dataset_kwargs={"root": "data/mnist", "download": True},
                                                dataloader_kwargs={"batch_size": 32},
                                                optimizer_kwargs={"lr": 1e-3},
                                                trainer_kwargs={"max_epochs": 1})

    simple_startegy = RandomStrategy()

    exp = RetiariiExperiment(base_model, trainer, [], simple_startegy)

    exp_config = RetiariiExeConfig('local')
    exp_config.experiment_name = 'mnist_search'
    exp_config.trial_concurrency = 2
    exp_config.max_trial_number = 10
    exp_config.training_service.use_active_gpu = False

    exp.run(exp_config, 7081 + random.randint(0, 100))

the generated code would be:
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim

=== look here ===
import __main__
=== look here ===
import nni

class _model(nn.Module):
    def __init__(self):
        super().__init__()
        self.__conv1 = nni.retiarii.nn.pytorch.nn.Conv2d(in_channels=1, out_channels=20, kernel_size=5, stride=1)
        self.__conv2 = nni.retiarii.nn.pytorch.nn.Conv2d(in_channels=20, out_channels=50, kernel_size=5, stride=1)
        === look here ===
        self.__fc1 = __main__.LayerChoiceSequential()
        === look here ===
        self.__fc2 = nni.retiarii.nn.pytorch.nn.Linear(in_features=128, out_features=10)
...

Obviously, it did not meet our expectations. But we can create a new module and folder for the custom layer, so that it can be generated normally. For example, in the main.py (a jupyter notebook) we can do:
import random

import nni.retiarii.nn.pytorch as nn
import torch.nn.functional as F
from nni.retiarii.utils import blackbox_module
from nni.retiarii.experiment import RetiariiExeConfig, RetiariiExperiment
from nni.retiarii.strategies import RandomStrategy
from nni.retiarii.trainer import PyTorchImageClassificationTrainer

from layer.sequential import LayerChoiceSequential

class Net(nn.Module):
    def __init__(self, hidden_size):
        super(Net, self).__init__()
        self.conv1 = nn.Conv2d(1, 20, 5, 1)
        self.conv2 = nn.Conv2d(20, 50, 5, 1)
        self.fc1 = nn.LayerChoice([
            LayerChoiceSequential(nn.Linear(4*4*50, hidden_size)),
            nn.Linear(4*4*50, hidden_size, bias=False)
        ])
        self.fc2 = nn.Linear(hidden_size, 10)

    def forward(self, x):
        x = F.relu(self.conv1(x))
        x = F.max_pool2d(x, 2, 2)
        x = F.relu(self.conv2(x))
        x = F.max_pool2d(x, 2, 2)
        x = x.view(-1, 4*4*50)
        x = F.relu(self.fc1(x))
        x = self.fc2(x)
        return F.log_softmax(x, dim=1)

if __name__ == '__main__':
    base_model = Net(128)
    trainer = PyTorchImageClassificationTrainer(base_model, dataset_cls="MNIST",
                                                dataset_kwargs={"root": "data/mnist", "download": True},
                                                dataloader_kwargs={"batch_size": 32},
                                                optimizer_kwargs={"lr": 1e-3},
                                                trainer_kwargs={"max_epochs": 1})

    simple_startegy = RandomStrategy()

    exp = RetiariiExperiment(base_model, trainer, [], simple_startegy)

    exp_config = RetiariiExeConfig('local')
    exp_config.experiment_name = 'mnist_search'
    exp_config.trial_concurrency = 2
    exp_config.max_trial_number = 10
    exp_config.training_service.use_active_gpu = False

    exp.run(exp_config, 7081 + random.randint(0, 100))

and finish the definition in layer/sequential.py:
import nni.retiarii.nn.pytorch as nn
from nni.retiarii.utils import blackbox_module

@blackbox_module
class LayerChoiceSequential(nn.Module):
    def __init__(self, m):
        super().__init__()
        self.m = nn.Sequential(m)

    def forward(self, x):
        return self.m(x)

In this way, it will be all good.

I found that this problem is related to the framework design. The core of the problem is that we have to generate different codes according to the user's settings and manage their operation. To solve the problem of "how to find the location of custom modules (including custom blackbox_module, Trainer, etc.) in the generated code", I made a lot of changes, but I am not sure whether they can cover many scenarios, so I don’t submit and respect the choices of existing developers.
Now, NNI's codes depend on two main ideas, i.e., hard-code definition and dynamic inspect. They are not robust, but it is indeed a simple and clear method. In this situation, we need users to create a new module when they need to custom new blackbox_module, Trainer, etc. (not able to finish the definition process in a single file). For example, if we try to custom a layer as follows:
import random

import nni.retiarii.nn.pytorch as nn
import torch.nn.functional as F
from nni.retiarii.utils import blackbox_module
from nni.retiarii.experiment import RetiariiExeConfig, RetiariiExperiment
from nni.retiarii.strategies import RandomStrategy
from nni.retiarii.trainer import PyTorchImageClassificationTrainer

# from layer.sequential import LayerChoiceSequential

import nni.retiarii.nn.pytorch as nn
from nni.retiarii.utils import blackbox_module

@blackbox_module
class LayerChoiceSequential(nn.Module):
    def __init__(self, m):
        super().__init__()
        self.m = nn.Sequential(m)

    def forward(self, x):
        return self.m(x)

class Net(nn.Module):
    def __init__(self, hidden_size):
        super(Net, self).__init__()
        self.conv1 = nn.Conv2d(1, 20, 5, 1)
        self.conv2 = nn.Conv2d(20, 50, 5, 1)
        self.fc1 = nn.LayerChoice([
            LayerChoiceSequential(nn.Linear(4*4*50, hidden_size)),
            nn.Linear(4*4*50, hidden_size, bias=False)
        ])
        self.fc2 = nn.Linear(hidden_size, 10)

    def forward(self, x):
        x = F.relu(self.conv1(x))
        x = F.max_pool2d(x, 2, 2)
        x = F.relu(self.conv2(x))
        x = F.max_pool2d(x, 2, 2)
        x = x.view(-1, 4*4*50)
        x = F.relu(self.fc1(x))
        x = self.fc2(x)
        return F.log_softmax(x, dim=1)

if __name__ == '__main__':
    base_model = Net(128)
    trainer = PyTorchImageClassificationTrainer(base_model, dataset_cls="MNIST",
                                                dataset_kwargs={"root": "data/mnist", "download": True},
                                                dataloader_kwargs={"batch_size": 32},
                                                optimizer_kwargs={"lr": 1e-3},
                                                trainer_kwargs={"max_epochs": 1})

    simple_startegy = RandomStrategy()

    exp = RetiariiExperiment(base_model, trainer, [], simple_startegy)

    exp_config = RetiariiExeConfig('local')
    exp_config.experiment_name = 'mnist_search'
    exp_config.trial_concurrency = 2
    exp_config.max_trial_number = 10
    exp_config.training_service.use_active_gpu = False

    exp.run(exp_config, 7081 + random.randint(0, 100))

the generated code would be:
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim

=== look here ===
import __main__
=== look here ===
import nni

class _model(nn.Module):
    def __init__(self):
        super().__init__()
        self.__conv1 = nni.retiarii.nn.pytorch.nn.Conv2d(in_channels=1, out_channels=20, kernel_size=5, stride=1)
        self.__conv2 = nni.retiarii.nn.pytorch.nn.Conv2d(in_channels=20, out_channels=50, kernel_size=5, stride=1)
        === look here ===
        self.__fc1 = __main__.LayerChoiceSequential()
        === look here ===
        self.__fc2 = nni.retiarii.nn.pytorch.nn.Linear(in_features=128, out_features=10)
...

Obviously, it did not meet our expectations. But we can create a new module and folder for the custom layer, so that it can be generated normally. For example, in the main.py (a jupyter notebook) we can do:
import random

import nni.retiarii.nn.pytorch as nn
import torch.nn.functional as F
from nni.retiarii.utils import blackbox_module
from nni.retiarii.experiment import RetiariiExeConfig, RetiariiExperiment
from nni.retiarii.strategies import RandomStrategy
from nni.retiarii.trainer import PyTorchImageClassificationTrainer

from layer.sequential import LayerChoiceSequential

class Net(nn.Module):
    def __init__(self, hidden_size):
        super(Net, self).__init__()
        self.conv1 = nn.Conv2d(1, 20, 5, 1)
        self.conv2 = nn.Conv2d(20, 50, 5, 1)
        self.fc1 = nn.LayerChoice([
            LayerChoiceSequential(nn.Linear(4*4*50, hidden_size)),
            nn.Linear(4*4*50, hidden_size, bias=False)
        ])
        self.fc2 = nn.Linear(hidden_size, 10)

    def forward(self, x):
        x = F.relu(self.conv1(x))
        x = F.max_pool2d(x, 2, 2)
        x = F.relu(self.conv2(x))
        x = F.max_pool2d(x, 2, 2)
        x = x.view(-1, 4*4*50)
        x = F.relu(self.fc1(x))
        x = self.fc2(x)
        return F.log_softmax(x, dim=1)

if __name__ == '__main__':
    base_model = Net(128)
    trainer = PyTorchImageClassificationTrainer(base_model, dataset_cls="MNIST",
                                                dataset_kwargs={"root": "data/mnist", "download": True},
                                                dataloader_kwargs={"batch_size": 32},
                                                optimizer_kwargs={"lr": 1e-3},
                                                trainer_kwargs={"max_epochs": 1})

    simple_startegy = RandomStrategy()

    exp = RetiariiExperiment(base_model, trainer, [], simple_startegy)

    exp_config = RetiariiExeConfig('local')
    exp_config.experiment_name = 'mnist_search'
    exp_config.trial_concurrency = 2
    exp_config.max_trial_number = 10
    exp_config.training_service.use_active_gpu = False

    exp.run(exp_config, 7081 + random.randint(0, 100))

and finish the definition in layer/sequential.py:
import nni.retiarii.nn.pytorch as nn
from nni.retiarii.utils import blackbox_module

@blackbox_module
class LayerChoiceSequential(nn.Module):
    def __init__(self, m):
        super().__init__()
        self.m = nn.Sequential(m)

    def forward(self, x):
        return self.m(x)

In this way, it will be all good.

In a conclusion, I believe that the existing design makes some sense, but it is not very robust and users need to follow a template project architecture. I will close this PR, if you have other questions, feel free to reopen it.

In a conclusion, I believe that the existing design makes some sense, but it is not very robust and users need to follow a template project architecture. I will close this PR, if you have other questions, feel free to reopen it.

@tczhangzhi thanks a lot for reporting this issue and kindly providing your solution:).
First, by design we allow blackbox_module class to be put in the "main" python file. thanks for reporting the bug.
Second, in v2.0 non-serializable input argument of blackbox_module class is not supported. various input argument types will be supported in v2.1.
for your example, you can make the following two changes:
(1) update the "utils.py" as follows:
module_name = inspect.getmodule(frm[0]).__name__
if module_name == '__main__':
    main_file_path = Path(inspect.getsourcefile(frm[0]))
    if main_file_path.parents[0] != Path('.'):
        raise RuntimeError(f'you are using "{main_file_path}" to launch your experiment, '
                           f'please launch the experiment under the directory where "{main_file_path.name}" is located.')
    module_name = main_file_path.stem

we should handle blackbox_module in the "main" python file specially.
(2) modify your script as follows:
# definition
@blackbox_module
class LayerChoiceSequential(nn.Module):
    def __init__(self, in_proj, out_proj):
        super().__init__()
        self.m = nn.Sequential(nn.Linear(in_proj, out_proj))

    def forward(self, x):
        return self.m(x)

# instantiation
self.fc1 = nn.LayerChoice([
            LayerChoiceSequential(4*4*50, hidden_size)
            nn.Linear(4*4*50, hidden_size, bias=False)
])

encourage you to update your pr accordingly, or you have better solutions feel free to tell us:)

@tczhangzhi thanks a lot for reporting this issue and kindly providing your solution:).
First, by design we allow blackbox_module class to be put in the "main" python file. thanks for reporting the bug.
Second, in v2.0 non-serializable input argument of blackbox_module class is not supported. various input argument types will be supported in v2.1.
for your example, you can make the following two changes:
(1) update the "utils.py" as follows:
module_name = inspect.getmodule(frm[0]).__name__
if module_name == '__main__':
    main_file_path = Path(inspect.getsourcefile(frm[0]))
    if main_file_path.parents[0] != Path('.'):
        raise RuntimeError(f'you are using "{main_file_path}" to launch your experiment, '
                           f'please launch the experiment under the directory where "{main_file_path.name}" is located.')
    module_name = main_file_path.stem

we should handle blackbox_module in the "main" python file specially.
(2) modify your script as follows:
# definition
@blackbox_module
class LayerChoiceSequential(nn.Module):
    def __init__(self, in_proj, out_proj):
        super().__init__()
        self.m = nn.Sequential(nn.Linear(in_proj, out_proj))

    def forward(self, x):
        return self.m(x)

# instantiation
self.fc1 = nn.LayerChoice([
            LayerChoiceSequential(4*4*50, hidden_size)
            nn.Linear(4*4*50, hidden_size, bias=False)
])

encourage you to update your pr accordingly, or you have better solutions feel free to tell us:)

@tczhangzhi thanks a lot for reporting this issue and kindly providing your solution:).
First, by design we allow blackbox_module class to be put in the "main" python file. thanks for reporting the bug.
Second, in v2.0 non-serializable input argument of blackbox_module class is not supported. various input argument types will be supported in v2.1.
for your example, you can make the following two changes:
(1) update the "utils.py" as follows:
module_name = inspect.getmodule(frm[0]).__name__
if module_name == '__main__':
    main_file_path = Path(inspect.getsourcefile(frm[0]))
    if main_file_path.parents[0] != Path('.'):
        raise RuntimeError(f'you are using "{main_file_path}" to launch your experiment, '
                           f'please launch the experiment under the directory where "{main_file_path.name}" is located.')
    module_name = main_file_path.stem

we should handle blackbox_module in the "main" python file specially.
(2) modify your script as follows:
# definition
@blackbox_module
class LayerChoiceSequential(nn.Module):
    def __init__(self, in_proj, out_proj):
        super().__init__()
        self.m = nn.Sequential(nn.Linear(in_proj, out_proj))

    def forward(self, x):
        return self.m(x)

# instantiation
self.fc1 = nn.LayerChoice([
            LayerChoiceSequential(4*4*50, hidden_size)
            nn.Linear(4*4*50, hidden_size, bias=False)
])

encourage you to update your pr accordingly, or you have better solutions feel free to tell us:)

Thanks for your fast and detailed reply and producing a warning for users is a wise choice. I totally agree with it and look forward to a better NNI.

@tczhangzhi thanks a lot for reporting this issue and kindly providing your solution:).
First, by design we allow blackbox_module class to be put in the "main" python file. thanks for reporting the bug.
Second, in v2.0 non-serializable input argument of blackbox_module class is not supported. various input argument types will be supported in v2.1.
for your example, you can make the following two changes:
(1) update the "utils.py" as follows:
module_name = inspect.getmodule(frm[0]).__name__
if module_name == '__main__':
    main_file_path = Path(inspect.getsourcefile(frm[0]))
    if main_file_path.parents[0] != Path('.'):
        raise RuntimeError(f'you are using "{main_file_path}" to launch your experiment, '
                           f'please launch the experiment under the directory where "{main_file_path.name}" is located.')
    module_name = main_file_path.stem

we should handle blackbox_module in the "main" python file specially.
(2) modify your script as follows:
# definition
@blackbox_module
class LayerChoiceSequential(nn.Module):
    def __init__(self, in_proj, out_proj):
        super().__init__()
        self.m = nn.Sequential(nn.Linear(in_proj, out_proj))

    def forward(self, x):
        return self.m(x)

# instantiation
self.fc1 = nn.LayerChoice([
            LayerChoiceSequential(4*4*50, hidden_size)
            nn.Linear(4*4*50, hidden_size, bias=False)
])

encourage you to update your pr accordingly, or you have better solutions feel free to tell us:)

Thanks for your fast and detailed reply and producing a warning for users is a wise choice. I totally agree with it and look forward to a better NNI.

Many thanks to @QuanluZhang, I believe his idea may be the best practice to solve the location problem of the custom module.
There are two types of problem:

module_name is set to __main__ while defining blackbox_module in the entry python file. And @QuanluZhang has worked it out.
inspect.getmodule(frm[0]) is set to None while defining blackbox_module or trainer in the .ipynb file. It is easy to understand, cause inspect cannot attach an exact file_name IPython environment on the fly. Questions are the same when users try to use string to define modules and instance them with ModuleType and exec. However, as @QuanluZhang said, producing a warning for users is a wise choice. So we follow his suggestion and produce a user-friendly Error to make users understand what he should do.

Many thanks to @QuanluZhang, I believe his idea may be the best practice to solve the location problem of the custom module.
There are two types of problem:

module_name is set to __main__ while defining blackbox_module in the entry python file. And @QuanluZhang has worked it out.
inspect.getmodule(frm[0]) is set to None while defining blackbox_module or trainer in the .ipynb file. It is easy to understand, cause inspect cannot attach an exact file_name IPython environment on the fly. Questions are the same when users try to use string to define modules and instance them with ModuleType and exec. However, as @QuanluZhang said, producing a warning for users is a wise choice. So we follow his suggestion and produce a user-friendly Error to make users understand what he should do.


Need to be able change version of Alloy that is used with Appc CLI

As a developer,
I want to be able to be able to use a different version (or custom build) of Alloy when using the Appcelerator CLI,
So that I can be able to patch urgent issues and critical defects while waiting for a new version of Alloy

With the old build system (Titanium or Ti), I could simply run npm install -g alloy@versionx to get a different or custom build of Alloy used with a build. Now with the new build system (Appcelerator or Appc), A specific version of Alloy is bundled with the Appcelerator Platform and there is not a simple way to change it on all our developer and build machines.
If there is known way of doing this already, please let us know!
We have an Enterprise license and this is critical for us right now as we have a memory leak that we need to patch in Alloy and get it into production quickly.
Associated JIRA Ticket:  https://jira.appcelerator.org/browse/AC-661
Workaround
@FokkeZB  proposed adding a global hook that contains this:
delete process.env.ALLOY_PATH;

https://jira.appcelerator.org/browse/TIMOB-20512

@brentonhouse if you'd like to contain this within the adamantium project you could install a global CLI hook as part of installing the global Alloy CLI. See how TiShadow does the same:
https://github.com/dbankier/TiShadow/blob/master/package.json#L47

@FokkeZB Maybe even create a parameter that could enable/disable it so that you could compile using "real" alloy if you wanted to.

That's probably not going to happen anymore as Alloy is being refactored.

Couldn't I look for a paramter in cli:go hook and then conditionally execute delete process.env.ALLOY_PATH; depending on what the parameter value was?   Are these being refactored as well?

All of CLI tooling is getting refactored, but of course until then you can introduce a option (like TiShadow does --express) to trigger the global CLI to be used.

ah, gotcha.   I will try to keep up w/ the changes to adapt.


Feature Request: LBRY app on PortableApps.com

Is your feature request related to a problem? Please describe.
I have a Windows machine without Administrator rights, I can't install LBRY app.
Describe the solution you'd like
Try deploying LBRY Desktop to PortableApps (which doesn't require admin privileges under Windows).
Moreover, it allows users to easily take along an USB stick with LBRY app as well. 👍
See Official Website
Describe alternatives you've considered
Create a binary that doesn't require admin rights?
Additional context
Blocked by (I don't have admin access):

It doesn't fit in the roll-out procedure

Jeremy


Update sync-health.md - Tenant Association Key clarity

Add clarity around the Tenant Association Key: it no longer needs to be copied anywhere, the client/report sync process will pick it up automatically.
Add a space and formatting to .plist to make it clearer.

@MikePlumleyMSFT
PR has been copyedited and is ready for final review, could you please check and merge? Thanks!

@webash note that we would not include instructions on things not to do - such as not copying the key.


Updated Logo and Responsiveness

#Fix: 213
I have updated the logo and responsiveness of the website.
@anuragverma108 Please check now if the logo is seen.

Logo is only visible in light mode & not in dark mode. Fix this & raise PR again


Connot show any webcam output

Hi i am a student, i have a problem , there's no output or show any panel of webcam in my netbeans...this is my codes
package pkg123;
import com.github.sarxos.webcam.Webcam;
import java.io.File;
import java.io.IOException;
import javax.imageio.ImageIO;

public class Main {

    public static void main(String[] args) throws IOException{
  Webcam webcam = Webcam.getDefault();
webcam.open();
ImageIO.write(webcam.getImage(), "PNG", new File("123.PNG"));
    }

}

And this is the output when i run the file
11:23:09.475 [main] INFO  com.github.sarxos.webcam.Webcam - WebcamDefaultDriver capture driver will be used
11:23:09.487 [webcam-discovery-service] DEBUG c.g.s.w.d.b.WebcamDefaultDriver - Searching devices
11:23:12.366 [webcam-discovery-service] DEBUG c.g.s.w.d.b.WebcamDefaultDriver - Found device Lenovo EasyCamera 0
11:23:12.374 [main] DEBUG com.github.sarxos.webcam.WebcamLock - Lock Webcam Lenovo EasyCamera 0
11:23:12.386 [atomic-processor-1] INFO  c.g.s.webcam.ds.cgt.WebcamOpenTask - Opening webcam Lenovo EasyCamera 0
11:23:12.386 [atomic-processor-1] DEBUG c.g.s.w.d.b.WebcamDefaultDevice - Opening webcam device Lenovo EasyCamera 0
11:23:12.386 [atomic-processor-1] DEBUG c.g.s.w.d.b.WebcamDefaultDevice - Webcam device 0 starting session, size java.awt.Dimension[width=176,height=144]
11:23:12.649 [atomic-processor-1] DEBUG c.g.s.w.d.b.WebcamDefaultDevice - Webcam device session started
11:23:12.651 [atomic-processor-1] WARN  c.g.s.w.d.b.WebcamDefaultDevice - Different size obtained vs requested - [176x144] vs [160x120]. Setting correct one. New size is [160x120]
11:23:12.656 [atomic-processor-1] DEBUG c.g.s.w.d.b.WebcamDefaultDevice - Clear memory buffer
11:23:12.975 [atomic-processor-1] DEBUG c.g.s.w.d.b.WebcamDefaultDevice - Webcam device com.github.sarxos.webcam.ds.buildin.WebcamDefaultDevice@e1b93e5 is now open
11:23:12.976 [main] DEBUG com.github.sarxos.webcam.Webcam - Webcam is now open Lenovo EasyCamera 0
11:23:13.125 [shutdown-hook-1] INFO  c.g.sarxos.webcam.WebcamShutdownHook - Automatic Lenovo EasyCamera 0 deallocation
11:23:13.125 [shutdown-hook-1] INFO  com.github.sarxos.webcam.Webcam - Disposing webcam Lenovo EasyCamera 0
11:23:13.138 [atomic-processor-1] DEBUG c.g.s.w.d.b.WebcamDefaultDevice - Disposing webcam device Lenovo EasyCamera 0
11:23:13.138 [atomic-processor-1] DEBUG c.g.s.w.d.b.WebcamDefaultDevice - Closing webcam device
11:23:13.307 [shutdown-hook-1] DEBUG com.github.sarxos.webcam.Webcam - Webcam disposed Lenovo EasyCamera 0
BUILD SUCCESSFUL (total time: 4 seconds)

Hi @cezzynahurt,
I'm glad you were able to find the problem by yourself :) Happy hacking!

Thank you sarxos :)


Code Generation!!!

To do: To be determined...

[ ] Add printf support and ignore that undefined reference at semantic stage (or initially add it to function table)


circuit.insert into a specific place

Maybe I'm doing something wrong, but I'm trying to insert an operation into an existing moment on an existing qubit for which I know to be idle. I'm using circuit.insert. But it won't put it at the i I specify. Rather, it will slide my gate as left as possible near index i

This is probably because the default value for the optional strategy parameter is cirq.InsertStrategy.EARLIEST.  Is earliest the most intuitive for the insert method?

Sorry, I should have mentioned that I tried changing the strategy to INLINE. I observed the same behavior. Upon further digging it looks like (under the inline strategy) it subtracts 1 from the index you pass in and puts the operation there; which seems surprising at best.

The behaviour is expected as far as the current InsertStrategy definitions are concerned.

InsertStrategy.INLINE: Attempts to add the operation to insert into the moment just before the desired insert location. But, if there’s already an existing operation affecting any of the qubits touched by the operation to insert, a new moment is created instead.

Therefore to achieve the desired effect, we would have to specify index + 1 with insert strategy INLINE.
Currently, there is no insert strategy which directly inserts into an existing moment at index i if possible, else creates a new moment / starts scanning backwards.

This reason for this is to make it act the way list.insert does, in that the index that you're refering to is the divider between the two indices. So if you say to insert at index 5, you mean between offsets 4 and 5. So the insert is logically before offset 5 if you say 5.
I agree that this is confusing sometimes. I've confused myself with it. I'm not sure what's best to do.

Maybe instead of insert i, you could do circuit[i] += op.

would this need to throw an exception if the operation cannot be added to the moment?

it should raise if it won't fit

The list metaphor makes sense if you're doing insert(moment) (because Circuit is like a List[Moment]) but it really breaks down since we're inserting a thing that goes into a list element
What if we only allow inserting moments? and then have a .place(op) to put in an operation (and/or use the syntax you suggest of circuit[i] += op). Would this break too much existing code?

circuit[i] += op currently works as expected. We can also use circuit.batch_insert_into([(moment_index, operation)]) to achieve the exact same thing.
IIUC, it would break a lot of code if we just allow inserting moments. There will also be inconsistencies with other methods like insert_into_range, insert_at_frontier, batch_insert etc., all of which are for inserting operations in the circuit.

I agree that we have to continue supporting circuit.insert(index, operation).

Marking the issue resolved.


Pip File provided has a small error

For this section:
pip install streamlit ollama googlesearch-python newpaper3k
It is a newspaper not newpaper, fix this it would help run and make it better

thanks for noticing the typo, will fix. as for lxml shouldn't it be installed with newspaper3k?

will fix, thanks


Use /usr/bin/env python instead of /usr/bin/python (python2)

I did a few more things here.

[x] Refactored the Cell_Fabric_FinFET__Mock/Align_primitives.py file to make it even smaller (good work before getting it to the state before this change.)
[x] Refactored the command line parsing using argparser do that we can call it easily from inside a python script (not just at the command line)
[x] Added some tests that check for shorts and opens on certain layers. Fixed up a relative path issue so the test work run in both the CellFabric directory (CI) and the CellFabric/Cell_Fabric_FinFET__Mock directory
[x] Fixed a few shorts and opens (usually by removing incorrect names)

What I want to do:

[ ] Remove the files that aren't used anymore. If a file is still used let's include a simple short/open checking test.
[ ] Remove the remaining duplication (I think fabric_NMOS.py and fabric_PMOS.py are very similar.)

@parijatm I got rid of all the shorts and the only opens seem to be on layers we don't care about (although I'm checking by netname and not layer.
Why don't you get rid of the duplication in fabric_NMOS and fabric_PMOS? That way you can look at the tests I've done.

@arvuce22 Arvind, can you remove the python files that are no longer needed in the CellFabric/Cell_Fabric_FinFET__Mock directory? You can do it in the branch/pull request.

Sure! I will fix this today.
On Tue, Aug 13, 2019 at 11:25 AM Steve Burns<EMAIL_ADDRESS>wrote:

@arvuce22 https://github.com/arvuce22 Arvind, can you remove the python
files that are no longer needed in the CellFabric/Cell_Fabric_FinFET__Mock
directory? You can do it in the branch/pull request.
—
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Reply to this email directly, view it on GitHub
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.

Why don't you get rid of the duplication in fabric_NMOS and fabric_PMOS? That way you can look at the tests I've done.

Got rid of the duplication but left the UnitCell classes in the original files so that we don't have to fix all the library dependencies. May want to think about co-locating primitive generators at some point so that it is easier for a user to read through (and for us to document).


Remove light-client specific GRANDPA block import

Currently we have separate instances of BlockImport for dealing with GRANDPA logic for full and light nodes. Initially the full node used to call into the runtime when importing a block (to fetch authorities IIRC). This is no longer the case and the light client can just use the regular GrandpaBlockImport (I've tested and it works). Is there any reason why we need to have separate handling for the light client and use finality proofs (instead of just regular justifications as in the full node).
cc @svyatonik

For example, in BABE we have no special handling for the light client and just use the same BabeBlockImport.

@andresilva Could you please guide me from where I can start looking into the code?

@ayushmishra2005 I already have these changes done in a branch, this issue was more for tracking discussion on this change.


pull request 35 updates implemented on the server

Ensure that updates from David's recent pull request (no. 35) are implemented on the server.

Added new source_type UKESM1-StratTrop to CCMI2022_CV.json

Updated source attribute for CNRM-MOCAGE in CCMI2022_CV.json


[SPARK-33282][test] Verify labeler for globs with leading slash

A few recent tests of the labeler have failed. One of my theories is that the leading slash is causing problems. This change should be labeled INFRA if the leading slash is not a problem. If it is, then that's most likely a problem in the config which affected the STRUCTURED STREAMING and the DSTREAM tests.

Once I merged in this PR that removes leading slashes, it appears that this PR should work (as evidenced by other changes working): https://github.com/kbendick/spark/pull/22
I'll merge in my local master, rerun the tests, and then update the PR for upstream once I've verified this patch.


Set Up Workflow Management in Cloud Cockpit

Tutorials: https://developers.sap.com/tutorials/cp-starter-ibpm-employeeonboarding-1-setup.html
Step1 : If user has two subaccounts in trial landscape then after selecting the workflow Booster, the below popup comes, where one has to select the subaccount in which the required entitlements for the Booster have been added.

A note can be added for the above case. With one subaccount the flow works as mentioned.

this is fixed now


Where can I find the "List of available fields" and "How to use it" in creating custom divi module?

Problem Description
This is not a bug or issue. Just a feedback and what to be pointed in the right direction.

I can't find a list of available fields that can be used in the custom module creation. ex. select option for the number of columns, a layout of display and etc.

I can't find a documentation on how to use each field. ex. "categories"
'include_categories' => array(              'label' => esc_html__('Include Categories', 'et_builder'),              'type' => 'categories',              'option_category' => 'basic_option',              'description' => esc_html__('Select the categories that you would like to include in the feed.', 'et_builder'),              'toggle_slug' => 'main_content',              'computed_affects' => array(                  '__projects',              ),              'taxonomy_name' => 'project_category',          ),

How to populate select options dynamically for a specific field. ex. Post Type field -> array('page', 'post', 'projects') etc.

Hope you can point me in the right direction thanks.
Steps To Reproduce
n/a
Screenshot and/or gif
n/a

QA Checklist
Reporter

[ ] Helpful title used

Helpful title format: Scope(s) :: One Sentence To Describe The Issue
Example: VB :: Floating Toolbar :: Jumps To Top Of Page

[x] Detailed description
[ ] Steps to reproduce included
[ ] Support Ticket URL included
[ ] Image and/or gif

Developer

[ ] Steps to reproduce proven solved
[ ] Test included and coverage acceptable and all Tests passing?
[ ] PR description has layman's description of problem and solution and "Areas Affected" listed/explained?
[ ] PR branch includes latest commits from master branch (at the time of checking)?
[ ] Estimated points on issue
[ ] Proper code documentation and conventions?
[ ] Proper RTL appearance
[ ] i18n used if applicable
[ ] Ajax/Form used? Nonce used? Perms checked? All user input sanitized and validated? Intentional unsanitized/unescaped functions used?
[ ] Database saved/updated? Data sanitized and validated?
[ ] Variable output properly escaped and validated?

Peer Review

[ ] PR branch includes latest commits from master branch (at the time of checking)?
[ ] Steps to reproduce proven solved
[ ] Affected areas are tested and ok
[ ] Proper code documentation and conventions
[ ] Proper RTL appearance
[ ] i18n used if applicable
[ ] Test(s) included and coverage acceptable
[ ] Ajax/Form used? Nonce used? Perms checked? All user input sanitized and validated? Intentional unsanitized/unescaped functions used?
[ ] Database saved/updated? Data sanitized and validated?
[ ] Variable output properly escaped and validated?

Quality Assurance

[ ] All tests passed on CircleCI.
[ ] Steps to reproduce passed, the fix works.
[ ] No errors in console or output
[ ] Affected areas are tested and ok
[ ] The fix does not change a customer's website in any surprising or unintended way

[ ] If Divi's design is adjusted, settings are migrated gracefully and invisibly

Design Review

[ ] UI is to spec
[ ] UX is to spec
[ ] Design is to spec
[ ] No surprising visual changes to a customer's website will be experienced after updating

[ ] Any/all visual changes are migrated gracefully

Dev Review

[ ] Test(s) included and coverage acceptable
[ ] Ajax/Form used? Nonce used? Perms checked? All user input sanitized and validated? Intentional unsanitized/unescaped functions used?
[ ] Database saved/updated? Data sanitized and validated?
[ ] Variable output properly escaped and validated?
[ ] i18n used if applicable
[ ] Implementation acceptable, DRY, Scaleable, future safe
[ ] Best practices used, cleverness and grokage, ES6 use, etc.

Sorry for the delayed response! You can find documentation for the field types here. To populate select options dynamically you must do that from within your module's get_fields() method before returning the array of fields. I hope that helps :smiley:

This list doesn't seem complete. I see other modules using types like "upload", "upload-gallery" or "computed", which are not documented in the provided link. Is there a complete list anywhere or a non-minified code file where I can see all available types?

Sorry for the delayed response! You can find documentation for the field types here. To populate select options dynamically you must do that from within your module's get_fields() method before returning the array of fields. I hope that helps 😃

Hi. Can you please tell where I can find a description such fields types like tiny_mce and which else exist (full list)?
Thanks.

I would also like to know. I notice a field type 'upload' but do not see any documentation on it?

I would also like to know. I notice a field type 'upload' but do not see any documentation on it?

This list doesn't seem complete. I see other modules using types like "upload", "upload-gallery" or "computed", which are not documented in the provided link. Is there a complete list anywhere or a non-minified code file where I can see all available types?

Always not a complete documentation ?


Encryption

Encrypt Message Passing in Mirage
Overview
While Mirage does not store data, the messages currently pass through the server in plain text. To enhance security, we need to implement encryption for these messages.
Task
Your objective is to encrypt the message passing so that messages are only decrypted on the client side.
Requirements

Implement encryption for messages transmitted through the server.
Ensure that messages are decrypted exclusively on the client side.

Questions or Claims
If you have any doubts or would like to be assigned to this issue, please comment below.

Note
This is part of Hacktoberfest! Let's make Mirage more secure together!

Hi @KorryKatti ,
Can you assign me this issue?

Hi @KorryKatti ,
Can you assign me this issue?

sure

Thank you, I added a PR for this

Thank you, I added a PR for this

will test and merge soon , thanks for the PR

solved at #38


Added ground-to-image notebook using vector math.

Tested it with (undistorted) 512,512 and 100,100.
Ping me on gitter if you have any questions.
Process to get XYZ values for a specific Line,Sample:

Modify MdisNacSensorModel::imageToGround to not use the distortion model (comment out the setFocalPlane() call).
Modify MdisNacSensorModelTest imageToGround1 with the line,sample you want.
Re-make.
Run the tests (./runTests).
The non-truth output for imageToGround1 test shows the resulting XYZ.
Update the notebook to use that XYZ as input to its groundToImage function.

This looks really sweet!  +100.  I am digesting now.


where is "Web components: basics" source code?

i need to review Web components: basics website source code.

It's here https://github.com/open-wc/open-wc/tree/master/packages/codelabs/src/basics.

@LarsDenBakker , your link just let me see some markdown file and images, but i want to know how is your site laid out, ui, router.....?


Very small perf tweak to help box2

@keybase/react-hackers
Small tweak to intersperseFn which is used by Box2 when you ask for gaps.
On my machine it makes box2 with 100 children 10% faster. In practice it probably won't be so dramatic since I don't think we use box2 with a lot of children and gap. When the children count is small it's basically the same thing as the reduce version.
It does have fewer allocations which could help with GC /shrug

@MarcoPolo the letterSpacing in storyshots was fixed in master

Proof of correctness: https://runkit.com/marcopolo/5cbfdc169fa32800123da8fe


Adding fonctionality to support cookie for secure sites authentication

Is there a way to add the support of cookie file in the request header?
The cURL request must look like that:
curl 'https://<IP_ADDRESS>/rest/v1/banner/post_auth' -H 'Cookie: id=550orR9UL-Q3yBx4IWOwNQ==; user=eyJ1c2VyIjoiYWRtaW4iLCJsZXZlbCI6MTUsInR5cGUiOiJMT0NBTCIsIm1ldGhvZCI6IkxPQ0FMIn0='
The cookie is is obtained via first login URL(user/password in POST):
https://<IP_ADDRESS>/rest/v1/login
Thank you

Hi,
I have the same problem and there is no clear information about it.
Anyone can give an example?

Could you give me a sample how to code that with a cookie file as input ?

You can set (static) custom header values in the config, but the value of the header can not be read from an external file.

i add cookies like this:
  headers:
    Cookie: "session=xxxxxxxxxx"


MINOR: Error log, should be use log4j

@xinzhuxiansheng please create a new issue and relate to this PR.


[KYUUBI #1840] Minor fix for general_incubator_vote script

Why are the changes needed?

How was this patch tested?

[ ] Add some test cases that check the changes thoroughly including negative and positive cases if possible

[ ] Add screenshots for manual tests if appropriate

[ ] Run test locally before make a pull request

Codecov Report

Merging #1841 (ea9b0ff) into master (fecbd70) will not change coverage.
The diff coverage is n/a.

@@            Coverage Diff            @@
##             master    #1841   +/-   ##
=========================================
  Coverage     59.62%   59.62%
  Complexity      271      271
=========================================
  Files           275      275
  Lines         13782    13782
  Branches       1763     1763
=========================================
  Hits           8218     8218
  Misses         4862     4862
  Partials        702      702

Impacted Files
Coverage Δ

...rg/apache/kyuubi/engine/trino/TrinoStatement.scala
64.70% <0.00%> (-1.18%)
:arrow_down:

...rc/main/scala/org/apache/spark/ui/EnginePage.scala
79.87% <0.00%> (+0.30%)
:arrow_up:

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thanks, merging to master


Segmentation Fault when rekeying the database

As before, I was playing around with the SQLiteShell (linux 64bit). I'm facing "Segmentation Fault" error when trying to rekey the database file.
Below the steps I used:
SQLite version 3.32.0 2020-04-29 01:09:46
Use ".open FILENAME" to reopen on a persistent database.
sqlite> .open file.db
sqlite> pragma key='rr';
ok
sqlite> CREATE TABLE contacts (contact_id INTEGER PRIMARY KEY,first_name TEXT NOT NULL,last_name TEXT NOT NULL,email TEXT NOT NULL UNIQUE, phone TEXT NOT NULL UNIQUE);
sqlite> select 1 from sqlite_master;
sqlite> pragma rekey='rrr';
Erreur de segmentation

Thanks for taking the time to test and to report bugs. I really appreciate that.
Most likely I introduced a bug while adapting the code to use the database filename to identify a database file handle. I will look into this.

Commit 4a6783368442d3cf4047e9911ed6442420888ce4 should fix the issue.
The bug was introduced in course of implementing the pragma handling. If the key length is given as -1 it is assumed that the string is zero-terminated and that the key length should be determined from the string length. This was not done for function sqlite3_rekey_v2. Thus, the key length of -1 was interpreted as an unsigned integer - that is, 4 GB password ... :boom:.
Now, function sqlite3_rekey_v2 (just as function sqlite3_key_v2) calculates the key length from the string length, if the key length was specified as -1.

Thank you ! It seams to be working now.


[Feature Request] None throwing connectivity-check

I have a case where I do not care for the reason of connectivity issues. I just need to know whether or not i am able to connect, that's it.
Maybe another option, as shown below could be a plausible option?
namespace Neo4j.Driver;

public interface IDriver
{
    public Task<bool> TryVerifyConnectivityAsync();
}

@WhatzGames Thank you for you suggestion, I have had this on my personal backlog to implement for good while. I think what we will do is something like Task<bool> TryGetServerInfoAsync(out IServerInfo)

That would be nice. If i recall it correctly, asynchronous operations  do not allow out parameters


closing video

The video plan as I understand it:

Explain basic approach of hedgehog-plutus-simple
Admit that it never made it to the point of usefulness
Summarize psm maintenance
Demmo new plutarch support in psm

Ideally find an existing demo but writing one shouldn't be that bad if it comes to that


github: improve pull request template

Release note default to None.
Rephrase checklist.
More about issue links.

This closes #11142 .
Signed-off-by: tison<EMAIL_ADDRESS>Release note
None

@TomShawn no. #11142 proposes to set it default to None. If it's rejected, I tend to close this PR as rejected.


Passthrough drive into dsm?

I use pve to run a vm ，then install docker into the vm.

the 32G drive used to the system of debian. and the 256G server used to mount into the dsm.
so in current architecturel, i cant direct use pve vitrual disk into the dsm， data.img is a virtualdisk into another virtualdisk.
question: can i mount pve vm like pve do in my phyics device https://pve.proxmox.com/wiki/Passthrough_Physical_Disk_to_Virtual_Machine_(VM)

updated:
edit disk args like this， and passthrough the disk, the volume showing up,  it's works,.

but i dont think the direct mount physics disk is a good idea, in my "physics" device, actually is a pve virutal disk, store on a zfs array, so the data is safe.

So the problem is solved?

so, their are also need some feature in the script, like mount iscsi drive  direct to kvm and dynamic mount multi num of disks.

thx a lot , i will try it later.

but, their are also another idea， perhaps we can define the vdsm by shell script, rather use env variable. like below.
# their are some shell init some functions like add_disk, mount device.

#define disk part

add_diak("/storage/system.img")
add_disk("/storage/data.img")
add_disk("/dev/sdc1")

# define passthrough
add_device("/dev/nvidia0")

use shell script to combine qemu params mayebe a workable solutaion for custom device.
maybe i can try it by myself, if interest it.

yeah, for most of users, the env define is good, but in my opinion, is hard to maintenance, their are hard code all of it, so use env command to call the function like add_disk or add_device in preset, and for pro user, just mount a single file by docker-compose, like mount /storage.
    volumes:
      - ./vdsm.sh:/vdsm/vdsm.sh

the vdsm.sh also store outside the docker, like /storage volume, it will not take effect for current user,  but keep the api stablize and open some "inner" function to pro user, will give more freedom to use it.

But first, can you confirm this works in your case:
        environment:
            DEVICE: "/dev/vdc1"
        devices:
            - /dev/vdc1

not OP, but this works wonderfully... Thank you! Any chance we can pass through multiple-devices?

cool... thx!
Sorry, to hijack... but do yo know of any way how to setup this up behind a reverse-proxy...
I have caddy successfully configured with nas.example.com -> <IP_ADDRESS>, but it only shows a blue screen saying "DSM is located at <IP_ADDRESS>" and redirects me to the IP instead.

Oh man... thank you so much for this one... I totally didn't see that you mentioned this.

You are my hero! it works!


improvement(common-utils): remove deprecated internal APIs

Breaking Changes
internal APIs that were moved to @fluidframewrk/client-utils have been removed. All were @internal and should not cause external issues.
Additionally clears up a warning (or error) where types are improperly stated for Buffer.
Reviewer Guidance
No changeset has been authored for this breaking change per https://github.com/microsoft/FluidFramework/wiki/Changesets#adding-a-changeset-to-a-pr that says contact @tylerbutler for independent packages. Draft until resolved.

nothing in here should be used by client any more. we should just move whatever server need to server, and then delete the package and never release again

nothing in here should be used by client any more. we should just move whatever server need to server, and then delete the package and never release again

Good to know. I wrote this in response to FF Teams - Webpack issues with latest FFX packages. So, sounds like the fix for that is what you describe.


apps/x509: fix use and documentation of -CAserial and -CAcreateserial for 1.1.1

This backports the essence of #18373.

Merged to 1.1.1 - thanks @hlandau and @t8m


Naming convention change in repo

opensearch-project/security-dashboards-plugin pull request intake form
Please provide as much details as possible to get feedback/acceptance on your PR quickly

Category: (Enhancement, New feature, Bug fix, Test fix, Refactoring, Maintenance, Documentation)
Enhancement

Github Issue # or road-map entry, if available:

Description of changes:
Rename identifiers to align with OpenSearch naming convention

Why these changes are required?

What is the old behavior before changes and new behavior after changes? (Please add any example/logs/screen-shot if available)

Testing done: (Please provide details of testing done: Unit testing, integration testing and manual testing)
Unit tests, integration tests and manual tests

TO-DOs, if any: (Please describe pending items and provide Github issues# for each of them)

Is it backport from main branch? (If yes, please add backport PR # and commits #)

By making a contribution to this project, I certify that:
(a) The contribution was created in whole or in part by me and I
have the right to submit it under the open source license
indicated in the file; or
(b) The contribution is based upon previous work that, to the best
of my knowledge, is covered under an appropriate open source
license and I have the right under that license to submit that
work with modifications, whether created in whole or in part
by me, under the same open source license (unless I am
permitted to submit under a different license), as indicated
in the file; or
(c) The contribution was provided directly to me by some other
person who certified (a), (b) or (c) and I have not modified
it.
(d) I understand and agree that this project and the contribution
are public and that a record of the contribution (including all
personal information I submit with it, including my sign-off) is
maintained indefinitely and may be redistributed consistent with
this project or the open source license(s) involved.
By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.
For more information on following Developer Certificate of Origin and signing off your commits, please check here.

Codecov Report

Merging #764 (41877e7) into main (33d56ed) will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##             main     #764   +/-   ##
=======================================
  Coverage   72.08%   72.08%
=======================================
  Files          87       87
  Lines        1902     1902
  Branches      241      241
=======================================
  Hits         1371     1371
  Misses        477      477
  Partials       54       54

Impacted Files
Coverage Δ

...lugins/security-dashboards-plugin/public/plugin.ts
0.00% <0.00%> (ø)

...y-dashboards-plugin/public/services/shared-link.ts
26.31% <0.00%> (ø)

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feat: enable migration from longhorn to openebs

What this PR does / why we need it:
Migrates data from Longhorn to OpenEBS during upgrades if there is no longhorn version selected.
Which issue(s) this PR fixes:
Fixes #58505
Does this PR introduce a user-facing change?
feat: automatic migrates data from Longhorn to OpenEBS

https://github.com/replicatedhq/kURL-testgrid/pull/143 needs to go in first.

Part of this code has been migrated to https://github.com/replicatedhq/kURL/pull/3915. I am setting this back to a Draft while that is not merged.


IngestionService integration test

Codecov Report

:exclamation: No coverage uploaded for pull request base (ingestion_config@5431e9a). Click here to learn what that means.
The diff coverage is 100%.

@@                 Coverage Diff                 @@
##             ingestion_config    #6117   +/-   ##
===================================================
  Coverage                    ?   83.17%
  Complexity                  ?    12601
===================================================
  Files                       ?     1453
  Lines                       ?    47539
  Branches                    ?     5844
===================================================
  Hits                        ?    39542
  Misses                      ?     5274
  Partials                    ?     2723

Impacted Files
Coverage Δ
Complexity Δ

sql/src/main/java/io/crate/plugin/SQLPlugin.java
100% <ø> (ø)
16 <0> (?)

sql/src/main/java/io/crate/plugin/SQLModule.java
100% <100%> (ø)
2 <0> (?)

...o/crate/metadata/rule/ingest/IngestionService.java
100% <100%> (ø)
16 <3> (?)

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Clarify error message in Checkboxes component

A user commented on Slack that their team was confused whether to use single quotes or double quotes to refer to checkboxes in error messages.
On the checkboxes component, error messages are presented as quotes, which creates confusion when the error message itself contains a quote (quotes with quotes). Best practice (according to grammar and the style guide) is to use double quotes within single quotes, but the inconsistency is causing confusion.
This PR proposes using a quote block to avoid using quote marks.

@CharlotteDowns Hope you don't mind giving a review!
I wanted to check, do we have a block quote style on our website? Like, is the blank indent it's doing in the preview correct?

@CharlotteDowns I've added the inset styling, could have a look and help make another review?


Connection Status always showed as "Disconnected"

I'm trying to run a basic demo with the web-based studio but it always showed "Connection Status: Disconnected".
Here is what I have gone through so far:
I created a bootable iso following this instruction: (https://github.com/AmberInside/Amber_AI_ROS2/wiki/AMBER-B1-Wiki-&-How). I was able to get into the Ubuntu system.
When trying to boot the robot, I did the following things in order:

plug the PSU (110V as I'm in US), the small green led on PSU is on
I released the e-stop of the robot. I can see each motor has a dimed red led on and motors are stiffed
I wait a few sec and then plugin the host PC (the wooded box), wait for it to boot
I login the system and run the two scripts following this (https://github.com/AmberInside/Amber_AI_ROS2/wiki/Launch-AMBER-Studio,-web-based-controller-for-AMBER-B1)
I then jump to the <IP_ADDRESS>:85
It showed disconnected and refresh doesn't help.

Can you let me know if I'm doing anything wrong and how to fix this?

I've also tried the b1 program in the directory of '/home/amber/b1_demo/b1' and it works. The robot moves. So it has to be something with the web interface.

Yes I tried that.
https://user-images.githubusercontent.com/1237408/153736076-4c8ca381-7377-4a8f-bda8-510e3706aa88.MOV

Upload the Information View screenshot of Web Based Robotic Studio.
Then follow the steos below:
1, Keep the B1 and Master power on
2, Restart Ubuntu and try again.

Thx it works this time. I have to keep the e-stop in the released mode, restart the Ubuntu, and then run the 2 scripts and get to the web browser.


Remove version: Tencent.COSBrowser version 2.8.5

[Automated] It returns code over 400 in all urls
Microsoft Reviewers: Open in CodeFlow

URL: https://cos5.cloud.tencent.com/cosbrowser/cosbrowser-setup-2.8.5.exe
Response status code does not indicate success: 404 (Not Found).
(Automated message - build 896)


Fix non-uniform requirements across CUDA versions causing solver error

Follow-up of #27...

Checklist

[ ] Used a personal fork of the feedstock to propose changes
[ ] Bumped the build number (if the version is unchanged)
[ ] Reset the build number to 0 (if the version changed)
[ ] Re-rendered with the latest conda-smithy (Use the phrase @conda-forge-admin, please rerender in a comment in this PR for automated rerendering)
[ ] Ensured the license file is being packaged.

Hi! This is the friendly automated conda-forge-linting service.
I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.

@conda-forge-admin, please rerender

@conda-forge-admin, please rerender

Hi! This is the friendly automated conda-forge-linting service.
I wanted to let you know that I linted all conda-recipes in your PR (recipe) and found some lint.
Here's what I've got...
For recipe:

The build section contained an unexpected subsection name. f is not a valid subsection name.

Hi! This is the friendly automated conda-forge-linting service.
I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.


Unable to add metric variable

I am attempting to install Grafana on an OCI instance in us-phoenix-1. I have done with Instance Principals and with OCI cli config and I reach a similar error each time. My dynamic group has manage all-resources as does my OCI cli user (to ensure there is no permission issue).
When I create a new dashboard, there are no variables and metrics offered in the pull down with OCI as the data source.

So I proceed to create variables like it says in templating in using.md. I can successfully input region, compartment, and namespace but I cannot input the metric variable. On my instance with OCI CLI credentials, I don't even get any errors in the log /var/log/grafana/grafana.log with debug level set.

t=2020-07-01T17:29:46+0000 lvl=dbug msg="Scheduling update" logger=alerting.scheduler ruleCount=0
t=2020-07-01T17:29:56+0000 lvl=dbug msg="Scheduling update" logger=alerting.scheduler ruleCount=0
t=2020-07-01T17:30:06+0000 lvl=dbug msg="Scheduling update" logger=alerting.scheduler ruleCount=0
t=2020-07-01T17:30:16+0000 lvl=dbug msg="Scheduling update" logger=alerting.scheduler ruleCount=0
t=2020-07-01T17:30:26+0000 lvl=dbug msg="Scheduling update" logger=alerting.scheduler ruleCount=0
t=2020-07-01T17:30:36+0000 lvl=dbug msg="Scheduling update" logger=alerting.scheduler ruleCount=0
t=2020-07-01T17:30:46+0000 lvl=dbug msg="Scheduling update" logger=alerting.scheduler ruleCount=0
t=2020-07-01T17:30:56+0000 lvl=dbug msg="Scheduling update" logger=alerting.scheduler ruleCount=0
t=2020-07-01T17:31:05+0000 lvl=dbug msg="Found old rendered image to delete" logger=cleanup deleted=0 kept=0
t=2020-07-01T17:31:05+0000 lvl=dbug msg="Deleted expired snapshots" logger=cleanup rows affected=0
t=2020-07-01T17:31:05+0000 lvl=dbug msg="Deleted old/expired dashboard versions" logger=cleanup rows affected=0
t=2020-07-01T17:31:05+0000 lvl=dbug msg="Deleted expired login attempts" logger=cleanup rows affected=0
t=2020-07-01T17:31:05+0000 lvl=dbug msg="Checking for updates" logger=plugins
t=2020-07-01T17:31:06+0000 lvl=dbug msg="Scheduling update" logger=alerting.scheduler ruleCount=0
t=2020-07-01T17:31:15+0000 lvl=dbug msg="Updating last user_seen_at" logger=context userId=1 orgId=1 uname=admin user_id=1
t=2020-07-01T17:31:15+0000 lvl=dbug msg="Updating last user_seen_at" logger=context userId=1 orgId=1 uname=admin user_id=1
t=2020-07-01T17:31:16+0000 lvl=dbug msg="Scheduling update" logger=alerting.scheduler ruleCount=0
t=2020-07-01T17:31:26+0000 lvl=dbug msg="Scheduling update" logger=alerting.scheduler ruleCount=0
t=2020-07-01T17:31:36+0000 lvl=dbug msg="Scheduling update" logger=alerting.scheduler ruleCount=0
On my instance with Instance principals I do get errors when trying to add the namespaces variable.

t=2020-07-01T17:32:56+0000 lvl=eror msg="Request Completed" logger=context userId=1 orgId=1 uname=admin method=POST path=/api/tsdb/query status=500 remote_addr=<IP_ADDRESS> time_ms=164 size=34 referer="http://<IP_ADDRESS>:3000/d/T9U2NVMGz/oci-general?editview=templating&orgId=1"
t=2020-07-01T17:32:57+0000 lvl=eror msg="Metric request error" logger=context userId=1 orgId=1 uname=admin error="rpc error: code = Unknown desc = list metrircs failed(monitoring.ListMetricsDetails) { Name= Namespace= ResourceGroup= DimensionFilters=map[] GroupBy=[namespace] SortBy= SortOrder= }\n: list metrircs failed: Service error:NotAuthorizedOrNotFound. Authorization failed or requested resource not found.. http status code: 404. Opc request id: 49b31281c2212480d3b75fc8ebd81a7b/EB712F9DE066F221D7304966E35A3137/EDB93052BCF1C54B828036E17D9CDAAA" remote_addr=<IP_ADDRESS>
t=2020-07-01T17:32:57+0000 lvl=eror msg="Request Completed" logger=context userId=1 orgId=1 uname=admin method=POST path=/api/tsdb/query status=500 remote_addr=<IP_ADDRESS> time_ms=171 size=34 referer="http://<IP_ADDRESS>:3000/d/T9U2NVMGz/oci-general?editview=templating&orgId=1"
t=2020-07-01T17:32:58+0000 lvl=eror msg="Metric request error" logger=context userId=1 orgId=1 uname=admin error="rpc error: code = Unknown desc = list metrircs failed(monitoring.ListMetricsDetails) { Name= Namespace= ResourceGroup= DimensionFilters=map[] GroupBy=[namespace] SortBy= SortOrder= }\n: list metrircs failed: Service error:NotAuthorizedOrNotFound. Authorization failed or requested resource not found.. http status code: 404. Opc request id: 17296bcb11a498cc1cee262544eaf34c/9BD34B545739A9FB80C956C54050EC71/CF75419E97A8A6B3CA24C2F9A40097AC" remote_addr=<IP_ADDRESS>
t=2020-07-01T17:32:58+0000 lvl=eror msg="Request Completed" logger=context userId=1 orgId=1 uname=admin method=POST path=/api/tsdb/query status=500 remote_addr=<IP_ADDRESS> time_ms=166 size=34 referer="http://<IP_ADDRESS>:3000/d/T9U2NVMGz/oci-general?editview=templating&orgId=1"
I have someone gotten past that once and then got the same error with MEtrics as I did on my OCI CLI instance.
Any help would be appreciated. Instance Principals is running Grafana v7.0.4, OCI CLI instance is running Grafana v7.0.5. Both are running OCI Grafana Plugin v1.1.1

Note all of these problems appear to go away with Grafana v6.7.4.
Did something big change with Grafana v7? I did have to allow unsigned data sources with v7 but I dont know what else would have changed. Have you verified this with Grafana v7.x.x? If not, it should be documented to use the older versions of Grafana.

I've gotten Grafana 6 to work. I'm just curious if Oracle plans on the data source supporting Grafana 7.

I see the updates support 7. I will close this


[Fix](point query) add query options for short circuit queries

Some options like be_exec_version needed for functions
Proposed changes
Issue Number: close #xxx

Further comments
If this is a relatively large or complex change, kick off the discussion at<EMAIL_ADDRESS>by explaining why you chose the solution you did and what alternatives you considered, etc...

run buildall

run buildall

run buildall

run buildall


Osmcha doesn't visualize any changesets

I'm submitting a bug report_
Brief Description

Osmcha doesn't visualize any changesets for about last one day (oldest changesets are OK)
What is the motivation / use case for this feature?

Trying to visualize changesets from my filters
What  is the current behaviour, (attach relevant screenshots) ?

It waits about ine minute, then I get rose screen and this error message:

What  is the expected behaviour ?

Good visualization
When does this occur ?

Always
How do we replicate the issue ?

Any changeset for last day

Please tell us about your environment:

Windows 10, ANY browser.
Other Information / context:

Is seems it stopped updating 4-5 days ago. Old changesets are still displaying normally.

For me it stoppt 2 days ago. The connection sto osm the api seams to be broken.- only changeset are listed without any data detail. So the tag indexing does also not work, That means, one can filter by location or by time but not by tags.

from the OSM US slack:

No other update has been provided.

It appears to be fully caught up now and map diffs are loading properly for changesets going back ~3 days. Thanks for the fix!

The issue on overpass is solved now. Sorry for the disruption.


(REST Speech-to-text) How do you differentiate pronScore, Accuracy Score, and Fluency Score?

The docs are unclear: https://docs.microsoft.com/en-us/azure/cognitive-services/speech-service/rest-speech-to-text#response-parameters
Fluency is a part of accuracy, and accuracy is a part of fluency. I don't understand what the difference is in the calculation/production of these two scores. The explanations are single lines that essentially say "x is x".
Also the pronScore is based on these two scores and "weighted" - weighted how? weighted towards what?
Forgive me if I've posted this issue in the wrong place!

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: 11673bc9-9062-278d-c5b8-84b05f2b81be
Version Independent ID: 29347a63-de63-4ff0-5a62-149ab31d1b7e
Content: Speech-to-text API reference (REST) - Speech service - Azure Cognitive Services
Content Source: articles/cognitive-services/Speech-Service/rest-speech-to-text.md
Service: cognitive-services
Sub-service: speech-service
GitHub Login: @yinhew
Microsoft Alias: yinhew

@crevulus
Thanks for the feedback! We are currently investigating and will update you shortly.

@crevulus Thanks again for the feedback.
We will improve the document to make it more meaningful to help customer understand the API more easily.
For your questions, let me answer here.
About the difference between accuracy and fluency:
The accuracy score indicates the sounds accuracy of phonemes toward native pronunciation.
We calculate it on phoneme level first, and word level and full text level accuracy score is aggregated from phoneme level accuracy score.
The fluency score indicates the speech fluency of the given speech towards native speaking naturalness such as break, silence duration. It cares inter-word part. This is different from accuracy score.
The completeness score is calculated by the ratio of non-mispronunciation words towards reference text input.
For pronScore, it's the overall score which is aggregated from accuracy score, fluency score and completeness score. It's calculated by accuracyScore * X% + fluencyScore * Y% + completenessScore * Z%. There could be adjustment on the weight so we don't share it here.
In the future we will introduce more dimensions like prosody score and aggregate it into pronScore. You can also calculate the over all score with your customized weight.
Please let me know if you have further questions.

Thanks for the feedback. It was very thorough.
Prosody score would be very useful for my purposes! Please keep me updated, and you can close this ticket if you wish.

@crevulus
We will now proceed to close this thread. If there are further questions regarding this matter, please respond here and @YutongTie-MSFT and we will gladly continue the discussion.

Revised public-facing content will appear at this address within 24 hours:
https://docs.microsoft.com/en-us/azure/cognitive-services/speech-service/rest-speech-to-text
#sign-off

@yinhew , thanks for the detailed explaination. I wonder if you have time to help me to better understand the **fluency score**:
Like you mentioned:

The fluency score indicates the speech fluency of the given speech towards native speaking naturalness such as break, silence duration. It cares inter-word part. This is different from accuracy score.

Is there a way for you to share more details of how exactly the fluency score is calculated? For example, I have the follow alignment result of a recording:
silence 0-0.1s
I       0.1-0.3s
break   0.3-0.6s
like    0.7-1.7s # the speaker pronounced the word 'like' longer than most of the native speaker.
it      1.7-2.0s
silence 2.0-2.3s

What is the fluency score for this case? And how it is calculated?
P.S.: only a rough idea of the calculation procedure is fine with me, no specific parameter is needed.
Thanks.

@weiwchu @YutongTie-MSFT I'm also very interested in your reply to @weiwchu 's query. Would be useful to know for our product.

Why have we closed this thread?
It's not been answered yet!

Why have we closed this thread?
It's not been answered yet!

@sourabharsh and @crevulus and others who are interested in this topic, let me share my thoughts with you on this:
(Important things first, I created a group for discussing speech assessment questions and problems, I will see if I can answer most of them for you guys during weekends or evening time. And please free free to post your questions. I have a PhD in speech, and my thesis is on pitch estimation and speech analysis.
https://groups.google.com/g/speech-assessment
Anyone is welcomed to join and discuss.)
Fluency is a very subjective concept compared to recognition accuracy or detection precision. I have been doing research on speech assessment for some years. My feeling (just my thoughts) is that this domain lacks of definitions of metrics, e.g. what type of speech is considered as 'native' speech? However, It is perfectly fine, for many aspects of speech assessment are still regarded as open domain by research community.
So the fact I understand is that different firms have to have their own understanding of fluency and have their own implementation.
There a few ways of estimating fluency:
Method 1: have teachers labeling a lot of recordings with fluency scores from 0-100 (at least 10k+), then build a model for predicting the score from features (you can check linear/logistic regression, xgboost, ... ), the features could be raw mfcc, or state-level posteriors.
Method 2: still have teachers labeling a few recordings with fluency scores from 0-100 (maybe just 100 samples), but just define a function with expert knowledge, and manually tune the parameters in it (this may surprise you, a lot of firms use method 2 indeed).
Thanks,
Wei

@sourabharsh and @crevulus and others who are interested in this topic, let me share my thoughts with you on this:
(Important things first, I created a group for discussing speech assessment questions and problems, I will see if I can answer most of them for you guys during weekends or evening time. And please free free to post your questions. I have a PhD in speech, and my thesis is on pitch estimation and speech analysis.
https://groups.google.com/g/speech-assessment
Anyone is welcomed to join and discuss.)
Fluency is a very subjective concept compared to recognition accuracy or detection precision. I have been doing research on speech assessment for some years. My feeling (just my thoughts) is that this domain lacks of definitions of metrics, e.g. what type of speech is considered as 'native' speech? However, It is perfectly fine, for many aspects of speech assessment are still regarded as open domain by research community.
So the fact I understand is that different firms have to have their own understanding of fluency and have their own implementation.
There a few ways of estimating fluency:
Method 1: have teachers labeling a lot of recordings with fluency scores from 0-100 (at least 10k+), then build a model for predicting the score from features (you can check linear/logistic regression, xgboost, ... ), the features could be raw mfcc, or state-level posteriors.
Method 2: still have teachers labeling a few recordings with fluency scores from 0-100 (maybe just 100 samples), but just define a function with expert knowledge, and manually tune the parameters in it (this may surprise you, a lot of firms use method 2 indeed).
Thanks,
Wei

@weiwchu
Thanks a lot for taking time and explaining that to me!
I am definitely connecting with you on your said group. :)

@weiwchu
Thanks a lot for taking time and explaining that to me!
I am definitely connecting with you on your said group. :)