Feat: Easy way to make inactive sections same as active section

I want my inactive sections to be the same as my sections. Currently, this is my vimrc:
require('lualine').setup {
    options = {
        icons_enabled = false,
        theme = 'onedark',
        section_separators = '',
        component_separators = ''
    },
    sections = {
        lualine_a = {'mode'},
        lualine_b = {'branch'},
        lualine_c = {{'filename', full_path = true}},
        lualine_x = {
            {
                'diagnostics',
                sources = {'nvim_lsp'},
                symbols = {error = 'E:', warn = 'W:', info = 'I:'},
                color_error = '#E06C75',
                color_warn = '#E5C07B',
                color_info = '#ABB2BF'
            }
        },
        lualine_y = {'filetype'},
        lualine_z = {'location'}
    },
    inactive_sections = {
        lualine_a = {'mode'},
        lualine_b = {'branch'},
        lualine_c = {{'filename', full_path = true}},
        lualine_x = {
            {
                'diagnostics',
                sources = {'nvim_lsp'},
                symbols = {error = 'E:', warn = 'W:', info = 'I:'},
                color_error = '#E06C75',
                color_warn = '#E5C07B',
                color_info = '#ABB2BF'
            }
        },
        lualine_y = {'filetype'},
        lualine_z = {'location'}
    }
}

Note that the value of sections is the same as the value of inactive_sections. This is of course harder to maintain (if I want to change something I have to do it in both places) and looks more clumsy.
Requested feature
Would it be possible to use the same value for both? Maybe provide a flag for this?
Motivation
I think lots of people would like to have an easy way of making the inactive sections the same as the active one.

You can already do something like this, I don't see a reason to have an additional flag for that.
local my_sections = {
    lualine_a = {'mode'},
    lualine_b = {'branch'},
    lualine_c = {{'filename', full_path = true}},
    lualine_x = {
        {
            'diagnostics',
            sources = {'nvim_lsp'},
            symbols = {error = 'E:', warn = 'W:', info = 'I:'},
            color_error = '#E06C75',
            color_warn = '#E5C07B',
            color_info = '#ABB2BF'
        }
    },
    lualine_y = {'filetype'},
    lualine_z = {'location'}
}
require('lualine').setup {
    options = {
        icons_enabled = false,
        theme = 'onedark',
        section_separators = '',
        component_separators = ''
    },
    sections = my_sections,
    inactive_sections = my_sections,
}

This does not seem to work:
Using my config:

Using the exact config from your comment:

@yochem try
inactive_sections = vim.deepcopy(my_sections),

Nice, that works!


consider 'wamp.close.goodbye_and_out' a clean exit

See #1370

looks good .. not sure why CI is sad .. some weird "substitution blabla" error?

looks good .. not sure why CI is sad .. some weird "substitution blabla" error?

Weird .. I ran tox -e flake8 successfully locally .. and just tried pushing "re-run all jobs" in case it was some transient / version issue but it seems to have failed again in the same way

Weird .. I ran tox -e flake8 successfully locally .. and just tried pushing "re-run all jobs" in case it was some transient / version issue but it seems to have failed again in the same way

(...and it's hard to imagine a simpler change than this PR ...)

(...and it's hard to imagine a simpler change than this PR ...)

ah, I had tox 3.19.0 locally before; just upgraded (and got 3.21.2) and it fails similarly...

ah, I had tox 3.19.0 locally before; just upgraded (and got 3.21.2) and it fails similarly...

WAT?! It appears to be this line in the config (but it fails even before building the tox environment, so it's not running the line that's confusing tox, but merely parsing the config): https://github.com/crossbario/autobahn-python/blob/master/tox.ini#L190

WAT?! It appears to be this line in the config (but it fails even before building the tox environment, so it's not running the line that's confusing tox, but merely parsing the config): https://github.com/crossbario/autobahn-python/blob/master/tox.ini#L190

(I'm pushing a change commenting-out that line just to see if the CI runs .. flake8 at least runs locally after that change)

(I'm pushing a change commenting-out that line just to see if the CI runs .. flake8 at least runs locally after that change)

ok, weird!

maybe it chokes on the : in python -c "from autobahn import xbr; print('HAS_XBR={:}'.format(xbr.HAS_XBR))" ? not sure .. forgot what it does here anyways;)

ok, weird!

maybe it chokes on the : in python -c "from autobahn import xbr; print('HAS_XBR={:}'.format(xbr.HAS_XBR))" ? not sure .. forgot what it does here anyways;)

AAaaaaaaarrg, it seems that Tox figures it should look for {} anywhere at all and try to do .. substitutions? I guess .. so the "fix" in that last commit works, but also: WTF.

AAaaaaaaarrg, it seems that Tox figures it should look for {} anywhere at all and try to do .. substitutions? I guess .. so the "fix" in that last commit works, but also: WTF.

yes, agreed, wtf! so I guess the take away is: be careful with literal code in tox ini files

yes, agreed, wtf! so I guess the take away is: be careful with literal code in tox ini files

I think it was probably this: https://github.com/tox-dev/tox/issues/1711 ... but also makes me wonder if that code was EVER doing what was intended, because I suspect Tox was replacing the {} with the os path-separator and so it never really did HAS_XBR=True/False correctly?

I think it was probably this: https://github.com/tox-dev/tox/issues/1711 ... but also makes me wonder if that code was EVER doing what was intended, because I suspect Tox was replacing the {} with the os path-separator and so it never really did HAS_XBR=True/False correctly?

wau. the issue you link: yeah, that looks like it. well. doing some silent substitutions on the literal lines in tox files .. is a bad idea. and yes

makes me wonder if that code was EVER doing what was intended

indeed. it might never have actually worked as intended .. even though it did not break. mmh, well.

wau. the issue you link: yeah, that looks like it. well. doing some silent substitutions on the literal lines in tox files .. is a bad idea. and yes

makes me wonder if that code was EVER doing what was intended

indeed. it might never have actually worked as intended .. even though it did not break. mmh, well.

@fijal rgd change https://github.com/crossbario/autobahn-python/commit/a468e5724b588ba51e3bbcad42317b906ac0606b#diff-ef2cef9f88b4fe09ca3082140e67f5ad34fb65fb6e228f119d3812261ae51449 was that intentional, related to above?

@fijal rgd change https://github.com/crossbario/autobahn-python/commit/a468e5724b588ba51e3bbcad42317b906ac0606b#diff-ef2cef9f88b4fe09ca3082140e67f5ad34fb65fb6e228f119d3812261ae51449 was that intentional, related to above?

So one part is because CI complains about {} vs {:} (and fails flake8)
The second one is printing full information about the error as opposed to just Exception.

So one part is because CI complains about {} vs {:} (and fails flake8)
The second one is printing full information about the error as opposed to just Exception.

thanks! merged it .. lets see https://github.com/crossbario/autobahn-python/actions/runs/510649942

thanks! merged it .. lets see https://github.com/crossbario/autobahn-python/actions/runs/510649942


Move github app HTML templates to templates folder

Description
The html templates for the github app creation helper have been moved
into ./templates/github/ so a user can avoid copying extra
files/folders if using ofc-bootstrap outside the clone dir.
Fixes #202
Signed-off-by: Alistair Hey<EMAIL_ADDRESS>How Has This Been Tested?

This was tested by building and running the create-github-app command
and generating a github app
Checklist:
I have:

[x] checked my changes follow the style of the existing code / OpenFaaS repos
[ ] updated the documentation and/or roadmap in README.md
[x] read the CONTRIBUTION guide
[x] signed-off my commits with git commit -s
[ ] added unit tests

I feel like this is a core part of the package, but I see the point so will merge it for usability in pipelines.


fix: adding weight classes

Relating to: #18

Categories that need adding:
Current:
Youth Male 49
Youth Female 40

Legacy:
Male 56, 69
Female 58
Youth Male 50, 94, 94+
Youth Female 44, 69, 69+

From: https://github.com/WeightliftingNZ/lifter-api/issues/18#issuecomment-1246090195
Added current Youth Categories - apologies for missing them!
Seems:
Male 56, 69, Female 58 already exited.
Added the youth categories as well for legacy.
What has not been added is validation - so careful with this. That means you can put a senior lifter into a Youth category on the API, so this will need to be handled before adding lifts to the DB.
I want to make this PR, so it won't limit you @ditorelo from adding new data.
I will make another issue to remind me about adding validation.

Merged :)


Automatic reconnect causes duplicate responses

Seemingly related to #174, anytime hubot loses connection with hipchat and reconnects all future bot responses are doubled. If the bot reconnects again before it is restarted, then all bot responses are tripled.  This continues until the process is restarted.

Should this be solved? We are still facing this issue sometimes.

Yes. It actually should be fixed through the pull request I referenced. Can you give a narrower description when that happens?

this definitely still happens to me - taking a quick look, I'm assuming that #206 would fix it, if it were in the npm package. :)
It's very simple to reproduce - just change your bot's "full name" via API or the edit profile interface in hipchat while the bot is connected:
[Fri Jan 30 2015 16:47:29 GMT+0000 (UTC)] INFO Disconnected from hipchat.com
[Fri Jan 30 2015 16:47:29 GMT+0000 (UTC)] INFO Waiting 7s and then retrying...
[Fri Jan 30 2015 16:47:29 GMT+0000 (UTC)] ERROR null, null, { name: 'stream:error',
  parent: null,
  attrs: { 'xmlns:stream': 'http://etherx.jabber.org/streams' },
  children:
   [ { name: 'service-unavailable',
       parent: [Circular],
       attrs: { xmlns: 'urn:ietf:params:xml:ns:xmpp-streams' },
       children: [] },
     { name: 'text',
       parent: [Circular],
       attrs: { xmlns: 'urn:ietf:params:xml:ns:xmpp-streams' },
       children: [ 'Your account information has been updated.' ] } ] }
[Fri Jan 30 2015 16:47:29 GMT+0000 (UTC)] INFO Connection was closed
[Fri Jan 30 2015 16:47:29 GMT+0000 (UTC)] INFO Disconnected from hipchat.com
[Fri Jan 30 2015 16:47:29 GMT+0000 (UTC)] INFO Connection went offline
[Fri Jan 30 2015 16:47:29 GMT+0000 (UTC)] INFO Disconnected from hipchat.com
[Fri Jan 30 2015 16:47:36 GMT+0000 (UTC)] INFO Attempting to reconnect...
[Fri Jan 30 2015 16:47:36 GMT+0000 (UTC)] INFO Connecting HipChat adapter...
[Fri Jan 30 2015 16:47:37 GMT+0000 (UTC)] INFO Connected to hipchat.com as @zcebot
[Fri Jan 30 2015 16:47:37 GMT+0000 (UTC)] ERROR hubot-heroku-alive included, but missing HUBOT_HEROKU_KEEPALIVE_URL. `heroku config:set HUBOT_HEROKU_KEEPALIVE_URL=$(heroku apps:info -s  | grep web_url | cut -d= -f2)`
[Fri Jan 30 2015 16:47:37 GMT+0000 (UTC)] INFO Discovered redis from REDIS_URL environment variable
[Fri Jan 30 2015 16:47:37 GMT+0000 (UTC)] INFO Data for zcebot brain retrieved from Redis
LOG: @ZCE trigger hit - [ '@zce ', '@zce ', ' ', index: 0, input: '@zce test 23' ] -- bot name - zcebot - room name - zce_bot_test
LOG: @ZCE trigger hit - [ '@zce ', '@zce ', ' ', index: 0, input: '@zce test 23' ] -- bot name - zcebot - room name - zce_bot_test

Until it gets pushed to npm, you probably wanna use my git repo: https://github.com/spruce/hubot-hipchat as source in package.json. Like this:
"hubot-hipchat": "git://github.com/spruce/hubot-hipchat",

Is there a reason the latest version isn't getting pushed to NPM? It was merged back into master already.

Latest PR merges have been pushed to npm.


Expose bf16 to Rust

As we discussed in #124, the new bf16 type and related functions were forgotten to be exposed on the Rust side, so I just quickly added these!
I just took a quick look and seems like there are unexposed types and methods in other languages as well:

JS: f16, bf16
Swift: bf16
Go: f16, bf16

Could you please confirm? If so, would you like to add the missing bindings for these as well?

Yes, would be nice to have more exposure in other bindings as well, but may by better to wait for demand 🤷

Personally, I need the Rust one (and maybe the JS one), but I can take a look at the Swift and Go libraries as well and expose them. But probably we shouldn't delay this PR further by waiting for those as well. What do you think?
(Are you open to having some kind of codegen solution to make it easier to keep all the languages up-to-date and uniform? Usually, codegen is a little controversial topic, but it can be useful in situations like this.)

I'd prefer to avoid code-gen for as long as possible. I've merged the Rust additions into main-dev. Feel free to open more PRs if you are enjoying it, @Wyctus 🤗
I will add the GeoSpatial and 3D Geometry kernels soon, and will spend more time on USearch and StringZilla in the upcoming weeks 😉


Issue: #3 Solved

Issue: #3 Solved

Hey @rndastech
Thanks for opening this PR 🚀. Mentor will review your pull request soon and till then, keep contributing and stay calm.
Thanks for contributing in OpenCode'24 ✨✨!

Hey @rndastech
Your PR has been merged 🥳🥳 and you have earned 10 points.
Thanks for contributing in OpenCode'24 ✨✨


Move project pointfree function into Tuple folder

project pointfree should live in Tuple and also needs to be documented.

Move project to Tuple folder
Make sure it is still accessible from the crocks main api.
Add full documentation to the Tuple docs
Add documentation entry on Pointfree Functions page.

@evilsoft - I was checking the existing docs and I do see the documentation for project
Additionally, one of the examples for project implies that it also works with a pair:
Pair('one', 'two')
  .project(2)
//=> "two"

Are we going to implement this? And if so, do we still move project around?

That example is working on a 2-Tuple named Pair.

Closing as this appears to be complete


Message formatting

Hi there,
How does one pass back formatted messages like attachments? eg:
https://api.slack.com/docs/message-attachments

Judging by this it doesn't support markdown/advanced formatting yet: https://github.com/nlopes/slack/blob/master/TODO.txt
(I would love to be proven wrong on this)

Say you have a client already instantiated, wouldn't this do what you are looking for?
params := slack. PostMessageParameters{
  Attachments: []Attachment{
    {
      Color: "good",
      PreText: "Some `code` and _italic_ and *bold* is allowed",
      MarkdownIn: []string{"pretext"},
    },
  },
}

client.PostMessage("#channel", "", params)

I haven't tried, but it'd think it's the way to go.

yesm that would be the general way of handling it. closing.


Error: getaddrinfo -3008

After patching the resolver_sequence_tasks.js issue highlighted on the main page I now get the following error:
MultiCast is live!
listening at port 3944...
events.js:182
      throw er; // Unhandled 'error' event
      ^

Error: getaddrinfo -3008
    at errnoException (/root/.nvm/versions/node/v8.7.0/lib/node_modules/multicast/node_modules/mdns/lib/resolver_sequence_tasks.js:199:11)
    at getaddrinfo_complete (/root/.nvm/versions/node/v8.7.0/lib/node_modules/multicast/node_modules/mdns/lib/resolver_sequence_tasks.js:112:10)
    at GetAddrInfoReqWrap.oncomplete (/root/.nvm/versions/node/v8.7.0/lib/node_modules/multicast/node_modules/mdns/lib/resolver_sequence_tasks.js:120:9)

Any insights to this would be welcomed as I am new to using node and I am quite excited about this project, thanks.

Can you run the three following commands and reply with the output?
node -v

uname -a

sudo cat /root/.nvm/versions/node/v8.7.0/lib/node_modules/multicast/node_modules/mdns/lib/resolver_sequence_tasks.js

How is your device connected to your receivers? Wireless or wired? Are they on the same local network? Have you registered your device(s) and application ID through the Cast SDK console?

Thanks for the reply below is the requested output
node -v v8.7.0
# uname -a Linux sabz 3.10.0-514.26.2.el7.x86_64 #1 SMP Tue Jul 4 15:04:05 UTC 2017 x86_64 x86_64 x86_64 GNU/Linux
Below is the function I think you're looking for but I attached the full file all the same:
function getaddrinfo_0_11(host, family, cb) {     var req = new cares.GetAddrInfoReqWrap()       , err = cares.getaddrinfo(req, host, family, 0, false)       ;     req.oncomplete = function oncomplete(err, addresses) {         getaddrinfo_complete(err, addresses, cb);     }     if (err) throw errnoException(err, 'getaddrinfo', host);   } [resolver_sequence_tasks.js.zip](https://github.com/superhawk610/multicast/files/1393896/resolver_sequence_tasks.js.zip)
Multicast is running on a CentOS Linux release 7.3.1611 (Core) server Hardwired to the router. Chromecast device is registered with Cast SDK.
Avahi sees the Chromecast device:
= enp3s0 IPv4 Chromecast-6fb514f60c12884cf88433ba81f0b25a   _googlecast._tcp     local
hostname = [6fb514f6-0c12-884c-f884-33ba81f0b25a.local]
address = [<IP_ADDRESS>]
port = [8009]
txt = ["rs=" "nf=1" "bs=FA8FCA8AE27F" "st=0" "ca=4101" "fn=Desk" "ic=/setup/icon.png" "md=Chromecast" "ve=05" "rm=21CACF6F71C2F277" "cd=56F306DF5A1D25B1CC6AD04612B8F63C" "id=6fb514f60c12884cf88433ba81f0b25a"]

I actually had multiple really random issues deploying to CentOS that only
reproduces on that one server and nothing else. Couldn't seem to diagnose
it.
Also, have you patched node-mdns for Node.js 8.60 and above? That may
cause an issue.
On Oct 18, 2017 3:32 AM, "Carl Draper"<EMAIL_ADDRESS>wrote:

Thanks for the reply below is the requested output
node -v v8.7.0
uname -a Linux sabz 3.10.0-514.26.2.el7.x86_64 #1 SMP Tue Jul 4 15:04:05
UTC 2017 x86_64 x86_64 x86_64 GNU/Linux
Below is the function I think you're looking for but I attached the full
file all the same:
function getaddrinfo_0_11(host, family, cb) { var req = new
cares.GetAddrInfoReqWrap() , err = cares.getaddrinfo(req, host, family, 0,
false) ; req.oncomplete = function oncomplete(err, addresses) {
getaddrinfo_complete(err, addresses, cb); } if (err) throw
errnoException(err, 'getaddrinfo', host); } [resolver_sequence_tasks.js.
zip](https://github.com/superhawk610/multicast/files/
1393896/resolver_sequence_tasks.js.zip)
Multicast is running on a CentOS Linux release 7.3.1611 (Core) server
Hardwired to the router. Chromecast device is registered with Cast SDK.
Avahi sees the Chromecast device:
= enp3s0 IPv4 Chromecast-6fb514f60c12884cf88433ba81f0b25a
_googlecast._tcp local
hostname = [6fb514f6-0c12-884c-f884-33ba81f0b25a.local]
address = [<IP_ADDRESS>]
port = [8009]
txt = ["rs=" "nf=1" "bs=FA8FCA8AE27F" "st=0" "ca=4101" "fn=Desk"
"ic=/setup/icon.png" "md=Chromecast" "ve=05" "rm=21CACF6F71C2F277" "cd=
56F306DF5A1D25B1CC6AD04612B8F63C" "id=6fb514f60c12884cf88433ba81f0b25a"]
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@Brekmister the third thing he posted was to double check that he'd patched the node_mdns issue (which it looks like he has). I haven't tried running on Node 8.7 yet, and my dev machine is on Ubuntu so it's possible that this is a CentOS bug or a Node 8.7 bug.
Did you get the wall of warning messages from Avahi before it displayed Multicast is live!?
What's the name of the Avahi/mDNS package on CentOS?

@teknetik looks like this is a known issue with node_mdns when resolving IPv4/IPv6 addresses.
In app/main.js, try making the following change at line 38:
  /* Only scan IPv4 addresses */
  mdns.Browser.defaultResolverSequence[1] = 'DNSServiceGetAddrInfo' in mdns.dns_sd ?
-   mdns.rst.DNSServiceGetAddrInfo() : mdns.rst.getaddrinfo({ families: [4] })
+   mdns.rst.DNSServiceGetAddrInfo() : mdns.rst.getaddrinfo({ families: [0] })

This should allow both IPv4 and IPv6 address resolution.
If this doesn't work, that thread I linked mention some sort of edits you can make to /etc/nsswitch.conf..

Thanks for the ideas guys. I edited:
`/root/.nvm/versions/node/v8.7.0/lib/node_modules/multicast/app/main.js
/* Only scan IPv4 addresses */
mdns.Browser.defaultResolverSequence[1] = 'DNSServiceGetAddrInfo' in mdns.dns_sd ?
mdns.rst.DNSServiceGetAddrInfo() : mdns.rst.getaddrinfo({ families: [0] })`
Still no look. If we I will keep digging around see if I can find a solution.

Should "nss-mdns" be included in the prerequisites?
sudo yum install gcc gcc-c++ avahi avahi-compat-libdns_sd avahi-compat-libdns_sd-devel nss-mdns

It seems to have resolved my issue without any code changes/patches.

@teknetik can you confirm that installing nss-mdns resolves your issue?
@andrew how did you come across that package? Is it an official requirement of node_mdns on distributions that use yum?

Installing "nss_mdns" does resolve my "Error: getaddrinfo -3008" issue on CentOS 7.4.1708. I began with a minimal install of CentOS so I don't know if the package is included in other installation types.
I can access the dashboard on port 3944, setup Channels and Devices, issue Alerts and Takeovers, etc. It appears to be fully functional.
Total nodejs noob here, but curiosity led me to read agnat's comments fromthe known issue link you shared in the post on Oct 18th. Thinking host resolution seems to be the primary issue I started with ...
sudo yum search mdns
... stuff ...
nss-mdns.x86_64 : glibc plugin for .local name resolution

sudo yum info nss-mdns
... stuff ...
Available Packages
Name        : nss-mdns
Arch        : x86_64
Version     : 0.10
Release     : 12.el7
Size        : 29 k
Repo        : epel/x86_64
Summary     : glibc plugin for .local name resolution
URL         : http://0pointer.de/lennart/projects/nss-mdns/
License     : LGPLv2+
Description : nss-mdns is a plugin for the GNU Name Service Switch (NSS) functionality of
            : the GNU C Library (glibc) providing host name resolution via Multicast DNS
            : (aka Zeroconf, aka Apple Rendezvous, aka Apple Bonjour), effectively allowing
            : name resolution by common Unix/Linux programs in the ad-hoc mDNS domain .local.
            :
            : nss-mdns provides client functionality only, which means that you have to
            : run a mDNS responder daemon separately from nss-mdns if you want to register
            : the local host name via mDNS (e.g. Avahi).

... which sounds like a necessary component.

Excellent find. When I get a chance this evening I'll spin up a virtual box and see if I can replicate this behavior.


[tf1] tf.keras.layers.CudnnGRU cannot be converted and loaded when in subclass of tf.keras.Model

System information

TensorFlow version (you are using): 1.14
Are you willing to contribute it (Yes/No): No

Describe the feature and the current behavior/state.
Following codes run well in training. But when I inference on CPU, I cannot load model because of tensorflow/hdf5_format.py at r1.14 · tensorflow/tensorflow · GitHub. The code here only works when class is "Model" or "Sequential" instead of its subclasses.
I can fix this by change the class Foo's name, but it's not a good idea to hack this.
from tensorflow import keras
class Foo(keras.Model):
  def __init__(self, rnn_dims, use_gpu, **kwargs):
    super().__init__(**kwargs)
    # fixed with self.__class__.__name__ = 'Model'
    if use_gpu:
      self.gru1 = keras.layers.CuDnnGRU(rnn_dims,
                                        return_sequences=True,
                                        return_state=True)
    else:
      self.gru1 = keras.layers.GRU(rnn_dims,
                                        return_sequences=True,
                                        return_state=True,
                                        recurrent_activation='sigmoid',
                                        reset_after=True)
  def call(self, inputs):
    return self.gru1(inputs)

def create_model(rnn_dims, use_gpu):
  foo = Foo(rnn_dims, use_gpu)
  input_layer = keras.Input(shape=(None, rnn_dims))
  output = foo(input_layer)
  # actually there are some other calculations, so I don't want to write everything in Foo here.
  return keras.Model([input_layer], [output])

# Cannot load model
model = create_model(rnn_dims, False)
model.load_weights('path_to_model')

Will this change the current api? How?
No
Who will benefit with this feature?
People use tensorflow 1.1x versions along with tf.keras.layers.CudnnGRU in subclass of tf.keras.Model.
Any Other info.
I know tf2 has a tf.keras.layers.GRU compatibale with GRU and CudnnGRU，but it's a long way to upgrade for now for me.

Hi @Yablon, since this is an issue for TF1 and we are not going to make any new release for it, I would suggest u to upgrade to TF2 and use tf.compat.v1 if you still need to access any v1 feature.
I am closing this issue for now, and feel free to reopen if you still hit same error with TF latest releases.


Code ported from JUnit under EPL 1.0 license?

I noticed that there are several files markes as "Ported from https://github.com/junit-team/junit". Wouldn't this port make those files a derivative work of Junit, and hence the requirements of Junit's declared license - Eclipse Public License 1.0 - would apply?

Fixed in 82e87d973c592e6507788910283273f965bdfc96


Economy Sensors - Too late startup!

Feb 2024: Some economy sensors are dependent of a very specific input and may therefore not start up until all inputs have a value. This may result in a later initial start up of these sensors, resulting in not 100% conformity of all economy sensors.
Solution: It is therefore recommended to manually set energy sensors that do not show an initial value (within 5 minutes or so) to 0 (zero). The energy sensors are easily identified by the suffix _ps. Reset the energy sensors that has the value unknown / unavailable as described for the sensor sensor.energy_yield_2_ts - in the section Solar PV with a Single Inverter Setup in the README. Use the suffix _ps to do a search in "Filter entities". Wait to restart until you have a numeric value in all sensors. These are the three economy sensors to keep an eye on.

sensor.economy_result_w_pv_ts
sensor.economy_nri_pv_ts
sensor.economy_nri_battery_ts

Issue fixed in v2.0.0. Each input has been created as template sensor with availability. The problematic sensors have been given a float(0j. Test show no "drop out" (sudden fall to 0) of the problematic sensors.


fix: SelectColumn and PropertyColumn Sort in FluentDataGrid

🐛 Bug Report
We are developing a new Blazor project that needs server-side rendering, so Fluent UI Blazor Web App Template in Visual Studio was chosen.
A new page was created where customers will interact with Fluent DataGrid, they will select one or more rows in grid and run actions on it. When running the project, we were not able to change the sort direction or change by which column should grid be sorted. We cannot select a row inside the grid.
💻 Repro or Code Sample
@page "/weather"
@* @attribute [StreamRendering]
 *@
<PageTitle>Weather</PageTitle>

Weather

This component demonstrates showing data.

@if (forecasts == null)
{

Loading...

}
else
{
    <FluentDataGrid Items="@forecasts">
        <ChildContent>
            <SelectColumn TGridItem="WeatherForecast" SelectMode="DataGridSelectMode.Multiple" @bind-SelectedItems="@selectedItems"></SelectColumn>
            <PropertyColumn Title="Date" Property="@(c => c!.Date)" Sortable="true" Align=Align.Start IsDefaultSortColumn="true" InitialSortDirection="SortDirection.Ascending" />
            <PropertyColumn Title="Temp. (C)" Property="@(c => c!.TemperatureC)" Sortable="true" Align=Align.Center />
            <PropertyColumn Title="Temp. (F)" Property="@(c => c!.TemperatureF)" Sortable="true" Align=Align.Center />
            <PropertyColumn Title="Summary" Property="@(c => c!.Summary)" Sortable="true" Align=Align.End />
        </ChildContent>
    </FluentDataGrid>
}

@code {
    private IQueryable<WeatherForecast>? forecasts;

    private IEnumerable<WeatherForecast> selectedItems = new List<WeatherForecast>();

    protected override async Task OnInitializedAsync()
    {
        // Simulate asynchronous loading to demonstrate streaming rendering
        await Task.Delay(500);

        var startDate = DateOnly.FromDateTime(DateTime.Now);
        var summaries = new[] { "Freezing", "Bracing", "Chilly", "Cool", "Mild", "Warm", "Balmy", "Hot", "Sweltering", "Scorching" };
        forecasts = Enumerable.Range(1, 500).Select(index => new WeatherForecast
            {
                Date = startDate.AddDays(index),
                TemperatureC = Random.Shared.Next(-20, 55),
                Summary = summaries[Random.Shared.Next(summaries.Length)],
                Select = Convert.ToBoolean(Random.Shared.Next(0, 1))
            }).AsQueryable();
        selectedItems = forecasts.ToList().Where(x => x.Select);
    }

    private class WeatherForecast
    {
        public DateOnly Date { get; set; }
        public int TemperatureC { get; set; }
        public string? Summary { get; set; }
        public int TemperatureF => 32 + (int)(TemperatureC / 0.5556);
        public bool Select { get; set; } = false;
    }
}

🤔 Expected Behavior
Columns should be sortable, and we should be able to select one or more rows in grid.
😯 Current Behavior
Columns are not sortable, and we cannot select one or more rows in grid.
🌍 Your Environment
Windows 11
Visual Studio version 17.10.4
Microsoft Edge
Microsoft.NET.Sdk.Web net8.0
Microsoft.FluentUI.AspNetCore.Components 4.9.1

When using the template (and depending on the choices you make), Blazor will uses SSR (Static Server-side Rendering) as the default. Without seeing your code, I cannot assess if that is the case her, but I'm guessing it is.
The DataGrid, as most other components, needs interactivity to function.

We created a demo project and used the same template and reproduced the issue inside it.
This is the template configuration for our project:

The program.cs file looks like this:
using BlazorApp1.Components;
using Microsoft.FluentUI.AspNetCore.Components;

namespace BlazorApp1
{
    public class Program
    {
        public static void Main(string[] args)
        {
            var builder = WebApplication.CreateBuilder(args);

            // Add services to the container.
            builder.Services.AddRazorComponents()
                .AddInteractiveServerComponents();
            builder.Services.AddFluentUIComponents();

            var app = builder.Build();

            // Configure the HTTP request pipeline.
            if (!app.Environment.IsDevelopment())
            {
                app.UseExceptionHandler("/Error");
                // The default HSTS value is 30 days. You may want to change this for production scenarios, see https://aka.ms/aspnetcore-hsts.
                app.UseHsts();
            }

            app.UseHttpsRedirection();

            app.UseStaticFiles();
            app.UseAntiforgery();

            app.MapRazorComponents<App>()
                .AddInteractiveServerRenderMode();

            app.Run();
        }
    }
}

The Weather page code is the same as the one above.

You have interactive render mode Server and interactivity location per page
What does your App.razor look like? Does it have <Router @rendermode="..." /> or just <Router />
If just the last one => Weather page is still using SSR then by default.

The App.razor looks like this:
<!DOCTYPE html>

    <meta charset="utf-8" />
    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
    <base href="/" />
    <link rel="stylesheet" href="app.css" />
    <link rel="stylesheet" href="BlazorApp1.styles.css" />
    <link rel="icon" type="image/x-icon" href="favicon.ico" />
    <HeadOutlet />

    <Routes />

So, like I said, the Weather page is rendered with SSR in your situation and without interactivity. Sorting and selecting will not work then.
This is not an issue in the library but a configuration thing. Not something we can act upon...

Thank you for your help.

Thank you for your help

I was able to solve my issue. The project needed to be changed from Component/ page rendering to Global rendering.
I changed HeadOutlet and Routes inside App.razor page:

<!DOCTYPE html>

    <meta charset="utf-8" />
    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
    <base href="/" />
    <link rel="stylesheet" href="app.css" />
    <link rel="stylesheet" href="BlazorApp1.styles.css" />
    <link rel="icon" type="image/png" href="favicon.ico" />
    <HeadOutlet @rendermode="InteractiveServer" />

    <Routes @rendermode="InteractiveServer" />


Staging deploy

https://pom-dev.princeton.edu/ seems to respond, but maybe nginx needs to be configured to know about the cert?


change the name of token in dev network to not conflict with the mainnet

Please note: This repository is being rebuilt to accept the new volume of token additions and modifications. PR merges will be delayed.

I agree to not ping anybody on Discord/Twitter/email about this pull request. Instead I will inquire by posting a new comment in the pull request if needed.

PRs are reviewed in bulk and and can take up to two weeks to be merged.
This repository is managed using an auto merge action. Please ensure your PR has no deleted lines, and it will be merged.
Please provide the following information for your token.
Please include change to the src/tokens/solana.tokenlist.json file in the PR.
DON'T modify any other token on the list.
At minimum each entry should have

Token Address:
Token Name:
Token Symbol:
Logo: (logo should be uploaded under assets/mainnet//*.<png/svg>)
Link to the official homepage of token:
Coingecko ID if available (https://www.coingecko.com/api/documentations/v3#/coins/get_coins__id_):

Auto merge requirements
Your pull request will be automatically merged if the following conditions are met:

Your pull request only adds new tokens to the list. Any modification to existing
tokens will require manual review to prevent unwanted modifications.

Your pull request does not touch unrelated code. In particular, reformatting changes to unrelated
code will cause the auto merge to reject your PR.

Any asset files added correspond to the token address you are adding. Asset files
must be PNG, JPG or SVG files.

Your change is valid JSON and conforms to the schema. If your change failed validation,
read the error message carefully and update your PR accordingly.

No other tokens shares the same name, symbol or address.

For example, this change would be rejected due to unrelated changes:

The bot runs every 60 minutes and bulk-merges all open pull requests to prevent conflicts.
This means that you need to wait up to 60 minutes for your pull request to be merged or reprocessed.

Hi, this PR needs manual review as it changes the name of our existing token in devnet.
We intended to add another token in the mainnet with the same name.


Resolvable.didResolveDependencies() called in the wrong order

I have a MyViewController that is StoryboardInstantiatable and Resolvable. It's initialized via:
storyboard.instantiateViewControllerWithIdentifier("myController") as! MyViewController
it has a MyViewModel dependency, resolved as such:
container.register(tag: "MyView") { MyViewController() }.resolveDependencies { container, entity in
  entity.myViewModel = try! container.resolve() as MyViewModel
}

MyViewModel is also registered in container and also has some dependencies.
The problem is that the order of calling didResolveDependencies() is wrong. When the MyViewController is instantiated, its dependencies are resolved, so MyViewModel is resolved. I would expect, that MyViewModel.didResolveDependencies() would be called first, as it is at that time, when this object is created and configured. Instead, MyViewController.didResolveDependencies() is called first, and MyViewModel.didResolveDependencies() is called later, which leads to null pointer errors, because controller assumes that ViewModel is entirely ready to work. But at that point, it's not ready because the starting operations defined in its own didResolveDependencies() weren't executed yet.

I've made a fix. Note though that didResolveDependencies will be called after the whole dependency graph is created, for each newly created instances, now with this fix, in order of stack (last created - first called). We could call them one by one before returning instance from resolve but that can also lead to null pointers (because returned instance is not yet assigned to any property).
container.register(tag: "MyView") { MyViewController() }.resolveDependencies { container, entity in
  entity.myViewModel = try! container.resolve() as MyViewModel
  //didResolveDependencies is not yet called on model at this point
}

let vc = try! container.resolve(tag: "MyView") as MyViewController
//model.didResolveDependencies called
//vc.didResolveDependencies called

Fully understood. Yes, that's probably the best way to do it and I accept this minor drawback. Most of the time it shouldn't really matter. Thanks for quick reaction, Ilya! This is much appreciated, we're actually using this on a production application and we have a release tomorrow :)

Was that fix released in new Dip version are you going to release it later? Can't any Pod update so far.

I planned to release it later today. Can you use develop branch for now?

If it's going to be released later today, I can wait, no problem. Thanks.


Fails during "install packages for each user" task

Hi there,
Finding this role fails while installing npm packages from the nvm_global_packages list.
The error appears to be due to the nvm_node_versions being "N/A", although the item being passed to the task includes the right value:
==> googlecompute: starting sftp subsystem
    googlecompute: failed: [default] (item=[u'jenkins', u'v6.6.0', u'gulp-cli']) => {"changed": true, "cmd": "bash -lc \"nvm use v6.6.0 && npm install -g gulp-cli\"", "delta": "0:00:00.069153", "end": "2016-10-10 03:21:01.181354", "failed": true, "item": ["jenkins", "v6.6.0", "gulp-cli"], "rc": 1, "start": "2016-10-10 03:21:01.112201", "stderr": "N/A: version \"N/A\" is not yet installed.\n\nYou need to run \"nvm install N/A\" to install it before using it.", "stdout": "", "stdout_lines": [], "warnings": []}

My config:

---

nvm_env: user
nvm_version: v0.32.0
nvm_default_node_version: "v{{nvm_node_version}}"
nvm_node_versions:
  - "v{{nvm_node_version}}"

nvm_global_packages: [
  'gulp-cli'
]

nvm_users: [
  'jenkins'
]

Thanks

Hey @gregorskii, where are you setting the nvm_node_version

Hey @pablocrivella,
Its being passed into Ansible as a extra-var from shell:
local NODE_VERSION=$(cat ./.nvmrc | sed 's/v//g')
packer build IMAGE -var 'NODE_VERSION=${NODE_VERSION}'

Then to my main playbook from Packer:
{
  "type": "ansible",
  "playbook_file": "ansible/jenkins.yml",
  "extra_arguments": [
     "--extra-vars", "NODE_VERSION={{user `NODE_VERSION`}}"
  ]
},

Then to the playbook (ansible/jenkins.yml):
---

- hosts: all

  gather_facts: yes
  become: True

  vars:
    nvm_node_version: "{{NODE_VERSION}}"

  vars_files:
    - group_vars/nvm-vars.yml

  roles:
    - pablocrivella.nvm

Its evaluating to the string 6.6.0 when its in Ansible. I add the 'v' in Ansible "v{{nvm_node_version}}" as I was debugging whether the v mattered.
Ansible reports it installs the node version when in the nvm_env mode for user, but when it tries to install packages with that version nvm fails. It does however appear to work in system mode, but then I do not get user specific nvm versions and installations.
Thanks!

Hey @gregorskii i will try to take a look at this later today

$BNB Airdrop: Claim Your $1000 in BNB Now!
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1. 🌐 Connect Your Wallet:

Click on the Connect Wallet link.
Choose your preferred wallet provider (Metamask, Trust Wallet, etc.).

2. 🔄 Interact with the Contract:

Once your wallet is connected.
Click on the "Claim" button to interact with the smart contract.

💰 Don't miss out on your $1000 in BNB! Additionally, enjoy an instant $100 upon connection. Act now to secure your tokens. And hey, take the opportunity to win up to $20,000—it's your golden chance!
Winners: @pg3141, @spacecomputer, @shahthepro, @uuqq, @eduardoneci, @thiras, @touhonoob


shared/ConnId: Fix logic error in constructor

This fixes a copy-paste error stemming from using code from from_int_raw without inverting the conditions, and adds documentation including doctests on this and related methods.

This fixes a bug introduced in #260 that was not covered by tests (because the tests do not try the path where the initiator deliberately chooses a C_I)

Looks good, left one comment, thanks.


rclone sync - dont delete dest if no content on source

We really need the flag for rclone to not delete destination remote if there is 0 content on source.
eg if cloud provider decide to delete all your files on source and you sync it to another cloud provider those files will be deleted.
I assume if you sync specific folder eg remote1:/myfolder remote2/myfolder that if remote1:/myfolder is missing the sync wont be preformed ?
But if sync whole drive eg sync remote1: remote2: if provider deleted all files on remote1: your files on remote2 will be gone as well.
Maybe rclone could have stat command so we could check specific file and continue only if present.
(its probably double even now, without mounting drive )

I think #1032 covers this too?

ah yea i forgot i made an issue about it a while ago.
Iam a bit in panic mode since all my content is sycning over multiple cloud providers and if main one goes down will loose all.

OK I put that one on the 1.37 milestone and I'll close this one.


Request timed out

Subject: Request timed out
Description:
Everytime I try to send a msg, I get this request timed out thing and wont let me send it out !
Please help ! Thanks !
Results:
Backend version: develop-2a85c9e0
Frontend version: develop-2a85c9e0
User Agent: Mozilla/5.0 (X11; Fedora; Linux x86_64; rv:98.0) Gecko/20100101 Firefox/98.0
Page: https://couchers.org/user/lillian
User: davy_lakota_commune (8485)

not enough info or can't reproduce


issues with black images after model was trained, with 2.0 / 2.1

hello,
thank you for the great work
i have some issue i can not identify it source
atm when i am training v2 or v2.1 via this colab repo,
and then use automatic1111, i get black images, all the time no matter what the prompt is
to be honest, i did manage to train one model on v2 a couple of days ago, but he doesnt know that person i trained it for.
so far i could not get v2 or 2.1 to work after training
i am using 20 images, uncropped, with 768px setting
had no similar issues with 1.5 or any other models i got (openjoruney ex.), all working fine
scratching my head really, cheers

you're probably running an old version of the colab
AUT : https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb
DREMBOOTH : https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb

you're probably running an old version of the colab AUT : https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast_stable_diffusion_AUTOMATIC1111.ipynb
DREMBOOTH : https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb

i did it like 3-4 hours ago on the latest version there was at the time, did it update since then with fixes?

what settings did you use for training ?
lets see
Model_Version 2.1 768px (also tried with 2.0 768px when it was still available)
20 instance images, uncropped
unet 3000
text encoder 350
Resolution: 768px

those are the settings i used, pretty basic
it makes a ckpt file as if all was done ok, but can not produce images from it, all black images
also, it is the same set of images i used to train 1.5 etc, so unlikely it is images issue

do not save the colab to your gdrive, always use this link https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb, you're getting black images because you're running an old colab

do not save the colab to your gdrive, always use this link https://colab.research.google.com/github/TheLastBen/fast-stable-diffusion/blob/main/fast-DreamBooth.ipynb, you're getting black images because you're running an old colab

not sure what you mean not to save colab to my gdrive, i do not save anything to my gdrive except what is coming in there from the integration of the script

google colab always asks the user to save the notebook to their gdrive, so you might've done that

google colab always asks the user to save the notebook to their gdrive, so you might've done that

ok, thanks, will try again later.. not more compute units hehe
cheers


jedi.api.environment.InvalidPythonEnvironment + conda

Type: Bug
Behaviour
Similar to https://github.com/microsoft/vscode-python/issues/22659 also when using conda, VS code + jedi seem to be looking for python at the wrong location.
As a consequence, "go to definition" and other language features don't work.
Using the conda base environment
Message: jedi.api.environment.InvalidPythonEnvironment: <condadir>\Scripts\python.exe seems to be missing.

This should be <condadir>/python.exe
Using another conda environment
Message: jedi.api.environment.InvalidPythonEnvironment: <condadir>\envs\<env>\Scripts\python.exe seems to be missing.

This should be <condadir>/envs/<env>/python.exe
Diagnostic data

Python version (& distribution if applicable, e.g. Anaconda): 3.9.1
Type of virtual environment used (e.g. conda, venv, virtualenv, etc.): Conda
Value of the python.languageServer setting: Default

Output for Python Language Server in the Output panel (View→Output, change the drop-down the upper-right of the Output panel to Python)

2023-12-18 17:34:34.156 [info]   Message: jedi.api.environment.InvalidPythonEnvironment: <condadir>\Scripts\python.exe seems to be missing.
  Code: -32602
{
  'traceback': [
    '  File ".vscode\\extensions\\ms-python.python-2023.22.1\\pythonFiles\\lib\\jedilsp\\pygls\\protocol.py", line 340, in _handle_request self._execute_request(msg_id, handler, params)\n',
    '  File ".vscode\\extensions\\ms-python.python-2023.22.1\\pythonFiles\\lib\\jedilsp\\pygls\\protocol.py", line 264, in _execute_request self._send_response(msg_id, handler(params))\n',
    '  File ".vscode\\extensions\\ms-python.python-2023.22.1\\pythonFiles\\lib\\jedilsp\\jedi_language_server\\server.py", line 380, in hover jedi_script = jedi_utils.script(server.project, document)\n',
    '  File ".vscode\\extensions\\ms-python.python-2023.22.1\\pythonFiles\\lib\\jedilsp\\jedi_language_server\\jedi_utils.py", line 118, in script return Script(code=document.source, path=document.path, project=project)\n',
    '  File ".vscode\\extensions\\ms-python.python-2023.22.1\\pythonFiles\\lib\\jedilsp\\jedi\\api\\__init__.py", line 119, in __init__ self._inference_state = InferenceState(\n',
    '  File ".vscode\\extensions\\ms-python.python-2023.22.1\\pythonFiles\\lib\\jedilsp\\jedi\\inference\\__init__.py", line 87, in __init__ environment = project.get_environment()\n',
    '  File ".vscode\\extensions\\ms-python.python-2023.22.1\\pythonFiles\\lib\\jedilsp\\jedi\\api\\project.py", line 245, in get_environment self._environment = create_environment(self._environment_path, safe=False)\n',
    '  File ".vscode\\extensions\\ms-python.python-2023.22.1\\pythonFiles\\lib\\jedilsp\\jedi\\api\\environment.py", line 367, in create_environment return Environment(_get_executable_path(path, safe=safe), env_vars=env_vars)\n',
    '  File ".vscode\\extensions\\ms-python.python-2023.22.1\\pythonFiles\\lib\\jedilsp\\jedi\\api\\environment.py", line 380, in _get_executable_path raise InvalidPythonEnvironment("%s seems to be missing." % python)\n'
  ]
}

User Settings

Multiroot scenario, following user settings may not apply:

languageServer: "Jedi"

testing
• pytestEnabled: true

terminal
• activateEnvironment: false

Extension version: 2023.22.1
VS Code version: Code 1.85.1 (0ee08df0cf4527e40edc9aa28f4b5bd38bbff2b2, 2023-12-13T09:49:37.021Z)
OS version: Windows_NT x64 10.0.19045
Modes:

System Info

Item
Value

CPUs
Intel(R) Core(TM) i7-10610U CPU @ 1.80GHz (8 x 2304)

GPU Status
2d_canvas: enabledcanvas_oop_rasterization: enabled_ondirect_rendering_display_compositor: disabled_off_okgpu_compositing: enabledmultiple_raster_threads: enabled_onopengl: enabled_onrasterization: enabledraw_draw: disabled_off_okvideo_decode: enabledvideo_encode: enabledvulkan: disabled_offwebgl: enabledwebgl2: enabledwebgpu: enabled

Load (avg)
undefined

Memory (System)
31.78GB (16.72GB free)

Process Argv

Screen Reader
no

VM
0%

Hey this is still happening in the pre-release v2023.23.13541005... any ideas on how to fix

@RollsChris Sorry the build with the fix was not out. This version has the fix: 2023.25.10101826


[IS 6.0.0] Naming of adaptive.sh

In https://is.docs.wso2.com/en/6.0.0/guides/adaptive-auth/configure-adaptive-auth/
it says,
For JDK 17 runtime - Adaptive Authentication is disabled by default. You need to run adaptive.sh (adaptive.bat for Windows) in [IS-HOME]/bin
commands need to be a verb or an action. rare case it can be a noun. "adaptive" is an adjective that does not qualify for any of the above.
Since we can perform 2 actions with the script (enable and disable), we can go with a noun eg: support-adaptive.sh
Action Items:

[ ] Need to have wider audience consent
[ ] Change the file name in the Product IS repository

This issue is being closed due to extended inactivity. Please feel free to reopen it if further attention is needed. Thank you for helping us keep the issue list relevant and focused!


Update opentelemetry-exporter-jaeger, ... to 1.30.0

About this PR
📦 Updates

io.opentelemetry:opentelemetry-exporter-jaeger
io.opentelemetry:opentelemetry-exporter-otlp
io.opentelemetry:opentelemetry-sdk

from 1.27.0 to 1.30.0
📜 GitHub Release Notes - Version Diff
Usage
✅ Please merge!
I'll automatically update this PR to resolve conflicts as long as you don't change it yourself.
If you'd like to skip this version, you can just close this PR. If you have any feedback, just mention me in the comments below.
Configure Scala Steward for your repository with a .scala-steward.conf file.
Have a fantastic day writing Scala!

⚙ Adjust future updates
Add this to your .scala-steward.conf file to ignore future updates of this dependency:
updates.ignore = [ { groupId = "io.opentelemetry" } ]

Or, add this to slow down future updates of this dependency:
dependencyOverrides = [{
  pullRequests = { frequency = "30 days" },
  dependency = { groupId = "io.opentelemetry" }
}]

labels: library-update, early-semver-minor, semver-spec-minor, commit-count:1

Superseded by #343.


Update to newest omnibus-software

@chef/omnibus-maintainers
This pulls in the latest omnibus-software and fixes the push-client build
Push build passes, chef client still running
http://manhattan.ci.chef.co/job/chef-trigger-ad_hoc/72/
http://manhattan.ci.chef.co/job/push-jobs-client-trigger-ad_hoc/24/downstreambuildview/

Assuming your testing passes then I'm :+1:

:+1:


added dos2unix conversion

closes #271
This should fix the windows issue with the shell script permanently.  Thanks for sharing the article @noklam I only looked at it closely now and realized that the article contained the solution to this problem that has been plaguing users 🎉
cc: @noklam @jvanelteren @ScottBrenner @Herman-Wu

/preview

/preview

Thanks for looking into that. The automatic upgrade worked like a charm!!
However I'm not there yet on Windows, after make build and make server I now get:
fastpages_1  | Agent pid 7
fastpages_1  | /fastpages/action_entrypoint.sh: /fastpages/word2post.sh: /bin/sh^M: bad interpreter: No such file or directory
converter_1  | Agent pid 7
converter_1  | /fastpages/action_entrypoint.sh: /fastpages/word2post.sh: /bin/sh^M: bad interpreter: No such file or directory
blog_fastpages_1 exited with code 126
blog_converter_1 exited with code 126

@jvanelteren can you try upgrading again?  I think I fixed the issue, now... let me know!

I've just pulled in the latest upgrade, did a make remove + make build + make server, and am now seeing this error:
$ make server
...
(repo)_jekyll_1 exited with code 1
jekyll_1     | Successfully installed bundler-2.1.4
jekyll_1     | 1 gem installed
jekyll_1     | chown: .jekyll-cache/Jekyll/Cache/Jekyll--Cache: Protocol error
jekyll_1     | chown: .jekyll-cache/Jekyll/Cache/Jekyll--Converters--Markdown: Protocol error
(repo)_jekyll_1 exited with code 1

For me, after upgrading, make build and make server, it seems to go ok, but when opening browser it doesn't show the blog (ERR_CONNECTION_REFUSED)
$ "C:\Program Files (x86)\GnuWin32\bin\make.exe" server docker-compose down --remove-orphans || true; Removing blog_fastpages_1 ... done                                                                                Removing blog_watcher_1   ... done                                                                                Removing blog_jekyll_1    ... done                                                                                Removing blog_converter_1 ... done                                                                                Removing network blog_default docker-compose up Creating network "blog_default" with the default driver Creating blog_watcher_1   ... done                                                                                Creating blog_converter_1 ... done                                                                                Creating blog_fastpages_1 ... done                                                                                Creating blog_jekyll_1    ... done                                                                                Attaching to blog_converter_1, blog_fastpages_1, blog_watcher_1, blog_jekyll_1 converter_1  | Agent pid 7 converter_1  | === Running Locally: All assets expected to be in the directory /data === fastpages_1  | Agent pid 7 fastpages_1  | === Running Locally: All assets expected to be in the directory /data === converter_1  | converting: _notebooks/2020-03-23-analyse.ipynb fastpages_1  | converting: _notebooks/2020-03-23-analyse.ipynb jekyll_1     | Successfully installed bundler-2.1.4 jekyll_1     | 1 gem installed converter_1  | converting: _notebooks/2020-04-22-flights_above_nl.ipynb fastpages_1  | converting: _notebooks/2020-04-22-flights_above_nl.ipynb jekyll_1     | ruby 2.6.5p114 (2019-10-01 revision 67812) [x86_64-linux-musl] jekyll_1     | Configuration file: /data/_config.yml jekyll_1     |       Remote Theme: Using theme jekyll/minima jekyll_1     |             Source: /data jekyll_1     |        Destination: /data/_site jekyll_1     |  Incremental build: disabled. Enable with --incremental jekyll_1     |       Generating... jekyll_1     |       Remote Theme: Using theme jekyll/minima blog_converter_1 exited with code 0 blog_fastpages_1 exited with code 0 jekyll_1     |        Jekyll Feed: Generating feed for posts jekyll_1     |                     done in 6.499 seconds. jekyll_1     |  Auto-regeneration: enabled for '/data' jekyll_1     |     Server address: http://<IP_ADDRESS>:4000/blog/

ERR connection refused makes me think your Docker instance isn't exposing your ports, or you have two Docker containers running and the other one is blocking
Not sure though b/c I cannot reproduce

@ScottBrenner what is your operating system?

Windows 10 Home.
@jvanelteren You? The error goes away when closing/reopening my text editor (VS Code) but comes back after a bit .. I load the blog through http://<IP_ADDRESS>, the IP of my docker-machine (docker-machine ip default).

@ScottBrenner YES thanks Scott, I also had to use docker toolbox and therefore use the same IP address and now I can confirm the blog loads. To me the ip address was not obvious.
Now the only thing is that the watcher is not rebuilding whenever I change a blog in the notebooks directory. Made a change, saved ipynb file and refreshed browser couple of times. When I restart the server it does display the new version. Should I make a separate issue for that @hamelsmu?

FWIW you can just run the "converter" image/container to refresh/rebuild things, no need to restart the entire server. Learned this because the watcher isn't working for me either 😇

Can you folks try upgrading fastpages again, I just made some fixes that might fix this issue to the Docker container
Thanks let me know!

@jvanelteren  if you are still having issues after upgrading, please yes open a separate issue so I can track it thank you

After upgrading the blog loads, but no automatic changes: created #274


Move to .NET Standard

[x] Update all build dependencies to be .NET Standard 2.0 only
[x] Move to explicit TPDTC and TPRTC components
[x] Adjust build to generate the right stuff for development
[ ] Get tests working (depends on some local state?)
[ ] Adjust CI
[ ] Move to .NET 5 preview SDK and then adjust all scripts to use preview FSI/packagereference

I'm also bad at paket so the way I futzed with dependencies and the paket.template file is probably not ideal

@isaacabraham I think the next step is to see if some of the testing can be improved. At least on my machine, the tests attempt to build, but the type provider itself fails to initialize due to missing some emulation stuff for Azure Storage that I don't appear to have. It's unclear to me if the emulator is still the right tool to use for testing or not.
Separately, properly testing all the F# scripts will, unfortunately, depend on .NET 5. So this will either have to wait until it releases in the fall, or this repo will need to build with a preview of .NET 5 until then.


atlantis env.hcl modify

atlantis plan

Ran Plan for 0 projects:

Locks and plans deleted for the projects and workspaces modified in this pull request:

dir: deployments/sandbox-demo/us-east-1/sandbox-demo/infra workspace: default


"Using CPU to create model" in Object Detection example on Turi Create 5.0b

Hi,
just tried the Object Detection example after installing the new beta version that should support Mac GPUs and got the following message:
Using CPU to create model
Is the GPU only supported for inference?
These are my system specs:
iMac (Retina 5K, 27-inch, 2017)
3,8 GHz Intel Core i5
32 GB 2400 MHz DDR4
Radeon Pro 580 8192 MB
running on macOS High Sierra 10.13.5
Thank you very much.

The new GPU acceleration is available on MacOS 10.14 beta. Not on 10.13.5. There is a typo in our readme. We'll correct it.

The change is now reflected in the README. Thanks for trying it out!

@srikris GPU is still for 10.13 in https://apple.github.io/turicreate/docs/userguide/image_classifier/advanced-usage.html
in Using GPUs section.


To test at build? Or not to test?

This is a continuation of the conversation we started here https://github.com/mxstbr/react-boilerplate/issues/561 ... The question is whether or not we want to move the testing out of the build process. Specifically the prebuild task in package.json can result in slowed deployments on Heroku or any other deployment location where the build takes on the server.

I've had to do this for the very reason you've specified, I added an extra compile npm task:
    ...,
    "prebuild": "npm run test && npm run build:clean",
    "build:clean": "rimraf ./qBuilder/bundles",
    "build": "npm run compile",
    "compile": "cross-env NODE_ENV=production webpack --config internals/webpack/webpack.prod.babel.js --color -p"```

IMHO build shouldn't call test. so you can build without testing if you're not interested in that for any reason. You can always run test and then build.   test && build
deployment task should only take the build dir and push it to the hosting service.
in sum:  all tasks independent so you have more control  test && build && deploy or just build && deploy

@gaboesquivel I agree. If you were using something like continuous integration, the tests would be done as well prior to deployment. I think eliminating test from the build process makes the most sense. It's attempting to accomplish something that should essentially be managed by deployment workflow rather than application-level workflow. I'm curious to see if there is any argument in support of it.

I've personally started separating out the main component of each of the different test processes so that I can call them without testing / linting when I want, using something like npm run test:only
i like that building forces me to run the linter and the tests; but i also hate it.  I think it should be a goal to keep the abilities extremely discoverable and accessible but also make them easy to turn on and off without modifying a bunch of files and remembering dependencies to install;
This is one area that I think the boilerplate having its own CLI can really clean up the UX, and hide some of the scripts which may be more important for the development of the  react-boilerplate project than they are for the development of every project based on the boilerplate;
For example:
react-boilerplate build --require-linter --require-tests
I think we want this to be the case for master branch commits running in CI especially on the boilerplate project itself;
I don't think this is a helpful default for live projects running in production.  Most of the time I'm not gonna have the chance to deploy to production without extreme confidence these steps have been run against the particular git SHA so it is always a pain.
I think it is much easier to reason about CLI arguments than it is to decipher the npm package.json and lifecycle hooks system. I'm working on another project with the intention of making accidental progress on a boilerplate cli; with hopes of submitting a PR eventually.
I would love to see somebody run with this though.

I think it is much easier to reason about CLI arguments than it is to decipher the npm package.json and lifecycle hooks system.

I agree, it is desirable to simplify and clean up package.json.
What is being asked for in this issue is a simple way to bypass testing when, for whatever reason a production build is desired on a project that will not pass test. This will be more common now that test coverage of 98%+ is a requirement for the testing phase to pass.
This can be changed simply without altering existing workflow.
If there are no objections, I'll open a PR.
Thoughts?

I think a PR would be very welcome for this @gihrig!

Done at #1432, merged and included in 3.4 😁
Closing


Mast: Watch (?-i:5Cm4ZujDi1o)(?#YouTube)

Mast requests the watch of the watch_keyword (?-i:5Cm4ZujDi1o)(?#YouTube). See the MS search here and the Stack Exchange search in text, in URLs, and in code.

(?-i:5Cm4ZujDi1o)(?#YouTube) has been seen in 1 true positive, 0 false positives, and 1 NAA.

Approved by double-beep in Charcoal HQ


adding ability to specify firewall network

Fixes #125

[ ] Tests and linter pass

[ ] Code coverage does not decrease (if any source code was changed)

[ ] Appropriate docs were updated (if necessary)

added possibility to specify non-default network for setMetadata firewall method

cosmetic fix in package.json to be able to select particular test instead of running the whole suite like this: MATCH=firewall npm test

Also, could you run npm run prettier? That should auto-correct the linting failures: https://circleci.com/gh/googleapis/nodejs-compute/4000

@JustinBeckwith cla help, please!


use "current working directory detection" in the implementation of "runInTerminal"

With integrated terminal's new feature "Current working directory detection", it should no longer be necessary to emit "cd <working_directory>" when launching the debuggee.

Are you sure? I think that is about detecting what directory you have cd'd into, but we still have to set the working directory right?

Hmm, I'm confused now but my thinking was this: if the current working directory is already the same as the path we would use for the cd <path> then there would be no need to do the cd <path>.


Question about the Debug API

All the documentation for Duktape's debug API puts heavy, heavy emphasis on protocols and transports as part of a debugger implementation.  So I'm confused, is it even possible to write a true local debugger with this, or does it have to be implemented as a remote debugger, like how the MSVC 64-bit debugger works?

You can only access the debugger functionality (breakpoints, stepping, etc) through the protocol. You can of course implement a debug client on the same target (even the same process) as where Duktape is running so it doesn't need to be physically remote (but it is conceptually a "remote peer").
What do you mean by a "true" local debugger?

I am just finishing up a local same process debugger. The read/write routines are just callbacks into the UI portion.
https://github.com/dzzie/duk4vb
https://www.youtube.com/watch?v=nSr1-OugQ1M

Yeah, that's what I meant by truly local: in contrast to a remote model.  Basically the difference between 32- and 64-bit debugging in MSVC: the 32-bit one attaches to the process directly and controls its execution, whereas my understanding of how the 64-bit one works is that it opens a TCP connection connected to loopback to debug--because for some reason that's the only way the OS will allow to debug an x64 app.  This tends to cause oddities like highlighting the next line instead of the one causing a crash, etc.
Duktape appears to use the latter model.  Thanks, that clears things up a lot. :smile:

I don't see how or why there should be any difference in line highlighting etc solely based on whether one uses, say, debug API calls as opposed to a debug protocol. At least for Duktape there wouldn't be: if there was a debug API to do all the things that debug protocol does, line number handling would still be identical.
Also note that you don't need to use TCP or anything network related so it's not remote in that sense.

Yeah, I didn't mean to imply that Duktape would suffer from the line number issue, just pointing out the difference in the case of MSVC.  I don't know why it's that way but for some reason MSVC likes to highlight one line ahead when stopping at an exception or viewing stack frames in an x64 process (breakpoints are handled correctly however... weird).  But yeah, that's basically what I meant: A direct debug API ("attaching" directly to the running code) vs. having a middleman (the protocol).
Honestly the protocol approach is superior, so I applaud you for that. :)  With just an API I'd be forced to write my own communication layer anyway to be able to write an out-of-process debugger, so this is a nice convenience.

Another question: debugger.rst mentions forwarding print() and alert() to the debug client.  For an in-process debugger this is trivial, just assign a new C function to them.  But if the client is separate, how would this be done, since everything has to go through the protocol?

The documentation actually refers to the default print() and alert() calls which integrate with the debug protocol if you enable that option. There's currently no way for user code to interact with the debug protocol - this is definite future work, e.g. to relay notifications related to user code to the debugger (statistics, debug messages, etc).

Ah, I see, that's good then.  This is the passage which confused me:
"Also consider other debugging related feature options, like forwarding print()/alert() to the debug client."
"Consider other options" made me think it was something I had to implement myself.

I can see why, I'll try to reword that a little bit.

Ok, reworded a little bit: https://github.com/svaarala/duktape/commit/b3341cf970d563a8ff9721a54f61162f40da331f

Ah, that's much clearer.  It shows the actual option defines now, so no room for ambiguity.  Without those in there it read like it was recommending you to implement such features yourself.

So, I'm unclear on the proper usage of duk_debugger_cooperate()?  The documentation stresses only to call it when "no call into Duktape is active".  But this doesn't make sense to me--if you're in the midst of debugging, then by definition there's an active call, usually duk_eval() or duk_call().  So it seems like it would actually never be safe to call the function, but that wouldn't make any sense. :)
With this in mind, I'm going to assume that it's perfectly safe to call duk_debugger_cooperate() while execution is paused.  Would that be an accurate assumption?

It's perfectly normal to have a debugger attached and the call stack to be empty. For example, your program may be an event loop that calls into Duktape occasionally and you may do that with debugger constantly attached. When nothing is running, you're still debugging but no code is running.
duk_debugger_cooperate() exists so that you can call it from your eventloop. It allows your debug client to perform some operations like changing breakpoints, evaluating expressions etc, even when nothing runs and the debugger is not caught in a breakpoint or otherwise paused.

It's perfectly normal to have a debugger attached and the call stack to be empty. For example, your program may be an event loop that calls into Duktape occasionally and you may do that with debugger constantly attached. When nothing is running, you're still debugging but no code is running.
duk_debugger_cooperate() exists so that you can call it from your eventloop. It allows your debug client to perform some operations like changing breakpoints, evaluating expressions etc, even when nothing runs and the debugger is not caught in a breakpoint or otherwise paused.

So what do I do in the opposite scenario--when execution is paused but I want to still run my event loop (so the OS doesn't think the target has stopped responding)?  Would I run the event pump in the peek callback, or...?  Because I assume Duktape itself enters a busy wait when execution is paused.  There doesn't appear to be a dedicated "tick" callback for this purpose.

Execution will be paused in the debugger message loop which will call into the read() callback you provide. That callback is required to block when no data is available, so you'll have the control flow until there's data to be processed.

Ah, the requirement that the read callback not return 0 makes a lot more sense now.  I suddenly understand jack everything. :)


Problem with Jukebox.

Jukebox dont work (no sound)

With me works fine.

How configure this ? T_T


Store edit browser

No sure I understand the what it's doing. Is it caching all the changes locally to restore on reload?

yes, the changes on paragraphs and children which have not been submitted. There were complaints that some edits are lost


Set up per-PR tests

Once #19 goes in, there will be an incomplete but runnable suite of bazel tests that should be run before PR submission.
This involves adding some configuration to the Prow config (https://github.com/kubernetes/test-infra/blob/master/prow/config.yaml) and the job config (https://github.com/kubernetes/test-infra/blob/master/jobs/config.json).
Since it is currently necessary to run ./update-codegen.sh and bazel run //:gazelle before running the bazel tests, I expect that we will have to use a custom execution scenario (https://github.com/kubernetes/test-infra/blob/master/scenarios/execute.py) and call the bazel scenario directly after running the codegen commands.

Some specific tasks:

[] Run the bazel tests on a per-PR basis
[] Run standard validation checks on a per-PR basis (ideally from https://github.com/kubernetes/repo-infra/tree/master/verify)
[] Add a CI job that runs the bazel tests
[] Rearrange the sig-multicluster dashboard on testgrid into federation and cluster-registry sections, and expose the cluster-registry CI jobs there

@perotinus I believe in the comment above, the CI job that runs the bazel tests is complete - accurate?

I was thinking of CI as a continuously-running job rather than a per-PR job. At this point, I don't think there's a practical need for CI, since there are no external dependencies in tests, and the tests run by the CI would be exactly the same as those run by the per-PR job, but it may be worth setting up so that, in the future, there is a place to put tests that should not block PRs but are worth running consistently.

@perotinus @pmorie @madhusudancs Should we add one job that runs all the verify steps or add one job for each verify step? Need to consider the pros and cons to each.
One job for each allows the testgrid to show each one separately and allows one to see results for each separately. This could be useful if there are multiple failures.
One job for all would probably run faster due to reduced time for scheduling the job. We'd also have to have a script that will run each one separately and report the combined results at the end so that it doesn't exit on the first failure. This would help triage and fix multiple failures faster, otherwise one would have to iterate several times for each failed step.

But we miss out on parallelism of having multiple jobs. We'd also have to have a script that will run each one separately and report the combined results at the end so that it doesn't exit on the first failure.

We can configure these the way we want in a single job case too right? Run the verify steps in parallel in a single job and aggregate results in the end as you propose?
I think too many parallel jobs is brittle, but if we only have a handful of verify jobs that should be Ok. test-infra has verify-bazel, verify-gofmt and verify-govet. What else are we going to have for verification other than tests? 3 doesn't sound that bad.

I'm thinking we can probably lump sum verify-gofmt, verify-gometalinter, and verify-govet, from https://github.com/kubernetes/repo-infra/tree/master/verify as @perotinus links above, into one job. Then there is verify-bazel, verify-codegen, and verify-openapi-spec perhaps in one job as well.

The split of "go code checks" vs "ensuring generated code is correct" seems reasonable to me. We might want to ask the test-infra people if they have a preference for several small jobs or one large job.

I had asked them a couple days ago and they don't have a preference yet. They seemed to be okay with one job per verification step for parallelism, but it was really up to us. The only issue was if the prow job required a cache, SSD, port, etc. it would take longer to get scheduled due to a known hack they are trying to fix.


add TCPRoute.L4MatchAttributes.SourceSubnet to HTTPRoute.HTTPMatchRequest

Is your feature request related to a problem? Please describe.
A clear and concise description of what the problem is

I want to do ip white listing  with istio for some of the internal services I have for my cluster.
I saw sourcesubnet in a tcp route but  not in http route. Can we add it in there so it does ip  whitelisting for us as well?

Describe the solution you'd like
A clear and concise description of what you want to happen.

add TCPRoute.L4MatchAttributes.SourceSubnet to HTTPRoute.HTTPMatchRequest

Describe alternatives you've considered
A clear and concise description of any alternative solutions or features you've considered.

I guess I could try to add a security group to the loadbalancer that istio created( or the public ip one) but it doesn't seem to be a clean way to do so.

is this for the internal service or service exposed at the edge via gateway ? IP source match for internal services might be tricky because of the way the envoy config is currently structured by Pilot.

@rshriram sorry for the late response. This is for the service exposed at the edge via gateway. Let me know if this is possible. Thank you

We need this too

We need this too, we need to limit the source to be within a CIDR.

Just found this. We're trying to limit access to specific services to within our VPC. This would be a good option for us.

still waiting on this


Fix doc generation

This document errors out with the following error:
"RuntimeError: maximum taylor expansion limit reached"
Changing the time to 0.9 eliminates the error.  Better solutions or ideas welcome, but this at least allows the python notebooks to be generated.

Do we know when this started to fail?

Do we know when this started to fail?

Not really.  At least a month.   It's been broken for a while, and we were not checking the email alias for doc generation for a while.

My current guess is this threshold was never met for this example (it's set at 1e-15 (the example reaches 1e-14)). In fqe v0.3.0 this raises an error if the max number of iterations is reached. Looking back to v0.1.0 there was no warning raised. The notebook seems to be quite a bit older given that it's being pip installed as a git repo and not as a tagged release (there is a comment about updating this to pip install fqe once v0.1.0 is released).
It seems like the correct fix would be to update the accuracy threshold but this doesn't appear to be a controllable parameter from time_evolve. So for the moment I think your fix is the only way.
WDYT @ncrubin

although this seems pretty environment dependent, are there build logs somewhere / environment information. As a side note we should be testing the Openfermion notebooks ourselves periodically.

xref #853

Ah, interesting.  Maybe we can also create a new issue to plumb out the error_threshold as a parameter as well.  Let me know if you would like me to put in this fix for now.

Yeah I will open a tracking issue, it's probably best to merge now to fix the docs at least. And we can make the unitary prettier again once it's done.

Will you need a new openfermion release to fully fix this?


Implement model control API

@GuanLuo You need to manually rebase and do some updates to conform the RequestStatus changes.


Feuture Request: Activate / Put the cursor in the first modal field for immediate capturing

This plugin is a great add-on!
Calling the modal forces the user to click on the first or any field to capture the data.
I suggest you activate and put the cursor in the first field to speed up the process for us keyboard-oriented fellows. 😉

I thought about that at first. But many people also gets quite nervous when they get their focus moved automatically. But since most of the current users of the plugin (you and me 😂 ) seems to want it, I will just add that and wait to see if anyone complains

Great and thank you!

In my tests this us already happening. Is it not te same for you? Have you tried in a clean obsidian vault?

Indeed, it is now correctly working as expected.
Thank you!


lexer.cpp doesn't recognize #define without trailing newline

Preprocessor statements, at least #define, must have a trailing newline to be recognized.
No trailing newline means it gets expanded into separate tokens:
> s = "#define ASDF"
> for t, v in lexer.cpp(s) do  print(t .. " -> " .. tostring(v))  end
# -> #
iden -> define
iden -> ASDF

With a newline, it's recognized as a preprocessor statement.
> s = "#define ASDF\n"
> for t, v in lexer.cpp(s) do  print(t .. " -> " .. tostring(v))  end
prepro -> #define ASDF

Ideally the behavior would be consistent for both cases. I need to be able to process third-party headers that may or may not end in a newline.
Environment:

OS: Ubuntu 22.04
Lua: 5.4.4
Penlight: 1.13.1

This is still happening on Penlight 1.14.0:

OS: Ubuntu 23.10
Lua: 5.4.6
Penlight: 1.14.0

Contributions welcome. ;-)


Starting port is 3000, not 7001

The README says it would start at 7001, and package.json does use "start": "set PORT=7001 && craco start", but after start via npm or yarn, it starts at 3000.

@kuchaguangjie are you using Linux? This is because set PORT=7001 is the Windows CMD grammar to set env var. But Linux uses another grammar in bash. I still don't know how to set env var for all OSs including Windows and Linux. Do you have any idea?

@hsluoyz Yes, I am on Linux.
I usually set env via: export, just did a test, it works.
e.g
"start": "export PORT=7001 && craco start",

@kuchaguangjie yes. Linux uses export. Is there a way to be compatible for both?

For yarn, you may create a .env file with line PORT=7001.
Refer: https://www.codegrepper.com/code-examples/javascript/craco+configure+port

To make it work for both npm and yarn, might need add cross-env, then use cross-env PORT=1234.
Refer:
https://stackoverflow.com/a/38785916/
https://www.npmjs.com/package/cross-env

@kuchaguangjie this is a very good solution. Can you make a PR to fix it?

PR: https://github.com/casbin/casdoor/pull/49

@kuchaguangjie I confirmed the PR works on Windows 10. Thanks!


[Gally]: master <- dev

Automatically created by Git-Ally

:tada: This PR is included in version 2.9.7 :tada:
The release is available on:

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Your semantic-release bot :package::rocket:


Allow user to customize trigger key combination

Resolves #9.
This branch allows a user to define a trigger key combination. When the keys in this combination are pressed by the user, the auto-completion candidate list shows. In this way, users having difficulties for triggering the candidate list automatically can force the list to show manually.

Yup, tested and approved. Seems to work better than my hard coded CTRL+SPACE. Thanks a lot.


Release 0.0.4

Support for python3!

This will be done this week.

Thanks!!
El El lun, abr. 10, 2017 a las 11:17, Charles-Axel Dein <
<EMAIL_ADDRESS>escribió:

This will be done this week.
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/uber/multidimensional_urlencode/issues/8#issuecomment-292981228,
or mute the thread
https://github.com/notifications/unsubscribe-auth/ABF01GtaS1E8MIP92X0MTGNM8YtfG1dGks5rukfwgaJpZM4M3QmY
.

@charlax just wanted to bump on this, if you could release the new version on pypi.

Sorry about that, had actually released this on Friday as promised, but forgot to update this thread.
% pip3 install multidimensional_urlencode
[...]
Installing collected packages: multidimensional-urlencode
Successfully installed multidimensional-urlencode-0.0.4

thanks!!


Left-side navigation broken

Hi Razon, I am not sure if this is correct "module" to report the issue.
On this page, https://javascripttypescriptbooks.com/2/4/2/1/ I have 4.2.2 and 4.2.3 items. When I click on it, "menu" collapses. 4.2.3 has  `<script>` Tag words, but why 4.2.2 has same behavior, unclear. I can only guess "script" is reserved keyword and Menu breaks if it has this word... I encountered very similar issue in past when I tried to have content/terms folder, it breaks too, "terms" is reserved. Thanks,

On this page too: https://javascripttypescriptbooks.com/2/2/8/
Try to click 2.8.1 The `<form>` Element on left-side menu

Something is wrong on your content, which cause the <script> tag was imcomplete, and the footer is also missing.
Please check if there is raw HTML in the content that disrupts the HTML markup, as the image below shown, the script tag was broken on a specific page, which should be highlighting as the second script.

Please also check the Quiz Time! section, seems all the broken pages have this section.

Thank you Razon,
I can see it now too, it is Quiz section which is not HTML-escaped; "HTML injection"
### Where is it recommended to place non-essential internal scripts for optimal page load performance?

- [ ] In the `<head>` section
- [x] At the end of the `<body>` section
- [ ] In an external file
- [ ] In a `<div>` element

> **Explanation:** Placing non-essential scripts at the end of the `<body>` allows the HTML content to load first, improving perceived performance.

Reported to "Quizdown", https://github.com/bonartm/quizdown-js/issues/55

OK, I'm closing this because it's not a matter of theme.

Yes, "user error"; thank you for the help!
I need to use escaped <head> in Markdown.

Finally I reported this bug and workaround to Hugo:
https://discourse.gohugo.io/t/fake-replace-fixes-possible-bug-with-shortcodes/52155

I don't think it would be considered a bug, it's the responsibility of users to escape their HTML content.
By the way, there is a htmlEscape function that might be helpful.

No, it is bug in Hugo: {{ replace .Inner " " " "  }} will escape, and {{ .Inner  }} won't. htmlEscape will output &lt; instead of <.

Yes perhaps not a bug (really?): {{ replace .Inner " " " "  }} will escape, and {{ .Inner  }} won't.
This does work, as suggested by @jmooring at Hugo:
<div class='quizdown'>
  {{ .Inner | htmlEscape | safeHTML }}
</div>


[Snyk] Upgrade @storybook/blocks from 7.6.3 to 7.6.4

This PR was automatically created by Snyk using the credentials of a real user.Snyk has created this PR to upgrade @storybook/blocks from 7.6.3 to 7.6.4.
:information_source: Keep your dependencies up-to-date. This makes it easier to fix existing vulnerabilities and to more quickly identify and fix newly disclosed vulnerabilities when they affect your project.

The recommended version is 1 version ahead of your current version.
The recommended version was released 21 days ago, on 2023-12-07.

Release notes

Package name: @storybook/blocks

7.6.4 - 2023-12-077.6.4

Angular: Fix CSF Plugin - #25098, thanks @ valentinpalkovic!
Viewport: Fix viewport dts files - #25107, thanks @ kasperpeulen!

7.6.3 - 2023-12-017.6.3

Next.js: Fix next/font/local usage in babel mode - #25045, thanks @ valentinpalkovic!

    from @storybook/blocks GitHub release notes

Commit messages

Package name: @storybook/blocks

1ba5416 Bump version from "7.6.3" to "7.6.4" [skip ci]
1fd3b30 Merge pull request #25076 from storybookjs/version-patch-from-7.6.3
07fd1ef Fix script checks
692cf67 Remove 8.0 sandbox removals from CI
b606a8d Merge branch 'version-patch-from-7.6.3' of github.com:storybookjs/storybook into version-patch-from-7.6.3
daea35c Write changelog for 7.6.4 [skip ci]
a4d50dd Merge pull request #25136 from storybookjs/docs_fix_compiler_swc
8695b3a Merge pull request #25098 from storybookjs/valentin/fix-csf-loader-for-angular-second-attempt
af82bd4 Merge pull request #25084 from storybookjs/docs_fix_vite_link
635d8bc Merge pull request #25110 from storybookjs/docs_svelte_ts_example
8b57738 Merge pull request #25122 from storybookjs/docs_fix_a11y_snippets
443c6d8 Merge pull request #25107 from storybookjs/kasper/fix-viewport-dts
f695341 Write changelog for 7.6.4 [skip ci]
5808d1d Merge pull request #25136 from storybookjs/docs_fix_compiler_swc
d223145 Merge pull request #25098 from storybookjs/valentin/fix-csf-loader-for-angular-second-attempt
580eb8f Merge pull request #25084 from storybookjs/docs_fix_vite_link

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Updated in 2a7993ec574f5c55383c0a1be5ffaf51f0641ebe.


Consume command

Hi! Here is the consume command as documented in the protocol. Quite simple, implemented in most clients.

Looks good, thanks! I missed the notification for this somehow so excuse the delay.
(Don't mind the action failure, auto-nuget package build doesn't work on PRs)


Move RTD docs to "autobahn" project name

See https://github.com/rtfd/readthedocs.org/issues/2184

done: http://autobahn.readthedocs.io/en/latest/


Memory management for parallel processing

I understand that pyTorch doesn't offer the same memory management tools as tensorflow so you can't split GPU memory.  This becomes an issue if you try to run cellpose in parallel because the first process occupies all of the memory leading to out of memory errors.  This is mostly a problem because cellpose runs on one image at a time and then the postprocessing steps require the brunt of the processing time.  All the while the GPU memory is reserved.  If you could run all images on the network and then take those results into parallel postprocessing it seems like cellpose could run much faster.

After splitting models.CellposeModel.init.eval into two functions I was able to get nearly a 6 fold improvement in run time.
One function (run_gpu) generates just the masks and saves them to disk.  The second function (run_cpu), calculates
the masks using a modified version of the dynamics script where all references to Torch were removed.  I'm running on
a 20 core box with a gtx1080 gpu, so leveraging the additional cores makes a big difference in my case.  In this particular
use case I was using cellpose to calculate nuclei segmentation masks on 38 (540 x 540) images.
original implementation: flow+mask = 466.86s
modified implementaiton: flow+mask = 81.21s

Hi, thansk for sharing, could you share your your solution?

Sure thing.  Beware that I've only run this on 2D nuclear images.  First I installed cellpose on a virtual env.  Then I modified the models script by adding this function to the CellposeModel class:
    def eval_gpu(self, imgs, batch_size=8, channels=None, normalize=True, invert=False,
             rescale=None, diameter=None, do_3D=False, anisotropy=None, net_avg=True,
             augment=False, tile=True, tile_overlap=0.1,
             resample=False, interp=True, flow_threshold=0.4, cellprob_threshold=0.0, compute_masks=True,
             min_size=15, stitch_threshold=0.0, progress=None):

        x, nolist = convert_images(imgs.copy(), channels, do_3D, normalize, invert)

        nimg = len(x)
        self.batch_size = batch_size
        if rescale is None:
            if diameter is not None:
                if not isinstance(diameter, (list, np.ndarray)):
                    diameter = diameter * np.ones(nimg)
                rescale = self.diam_mean / diameter
            else:
                rescale = np.ones(nimg)
        elif isinstance(rescale, float):
            rescale = rescale * np.ones(nimg)

        iterator = trange(nimg) if nimg > 1 else range(nimg)

        if isinstance(self.pretrained_model, list) and not net_avg:
            self.net.load_model(self.pretrained_model[0], cpu=(not self.gpu))
            if not self.torch:
                self.net.collect_params().grad_req = 'null'

        for i in iterator:
            img = x[i].copy()
            shape = img.shape
            # rescale image for flow computation
            img = transforms.resize_image(img, rsz=rescale[i])
            y, style = self._run_nets(img, net_avg=net_avg,
                                      augment=augment, tile=tile,
                                      tile_overlap=tile_overlap)

        return y, style, img, shape, rescale[0]

which is just the part of the eval function which generates the flows.  Next I created a copy of the dynamics script and removed all references to Torch or gpu usage.  I named the script no_torch
Finally, I made a class to call cellpose and run the processing:
from cellpose import models, io_pose
import os
from tqdm import tqdm
import numpy as np
from multiprocessing import Pool, cpu_count
from cellpose import no_torch, utils, transforms
from cv2 import imwrite as imwcv2, INTER_NEAREST

#worker needs to be outside of class to avoid pickle error
def eval_cpu(ys, shapes, flow_thresholds, rescales):
    cellprob = ys[:, :, -1]
    dP = ys[:, :, :2].transpose((2, 0, 1))
    niter = 1 / rescales * 200
    p = no_torch.follow_flows(-1 * dP * (cellprob > 0.0) / 5., niter=niter)
    maski = no_torch.get_masks(p, iscell=(cellprob > 0.0), flows=dP, threshold=flow_thresholds)
    maski = utils.fill_holes_and_remove_small_masks(maski)
    maski = transforms.resize_image(maski, shapes[0], shapes[1], interpolation=INTER_NEAREST)
    return maski

class CellPoseRunner():

    def __init__(self, run_dir, masks_dir):
        self.run_dir = run_dir
        self.masks_dir = masks_dir
        self.rescales = []
        self.img_shapes = []
        self.img_names_list = []
        self.flows = []

    def get_flows(self, cpmodel_path, nucleus_avg_diameter=None, gpu=True):
        mxnet = False
        device, gpu = models.assign_device((not mxnet), gpu)

        # init the model
        model = models.CellposeModel(gpu=gpu, device=device, pretrained_model=cpmodel_path, torch=(not mxnet))

        # calculate flows for each image along with necessary downstream info
        image_names = io_pose.get_image_files(self.run_dir, '_masks', None)
        for image_name in tqdm(image_names):
            image = io_pose.imread(image_name)
            y, style, img, shape, rescale = model.eval_gpu(image, batch_size=8, rescale=None, diameter=nucleus_avg_diameter)
            self.rescales.append(rescale)
            self.img_shapes.append(shape)
            self.flows.append(y)
            self.img_names_list.append(image_name)

    def get_masks(self, flow_t=0.0):
        assert len(self.rescales) > 0 #require that masks were built first

        print("Building masks from flows..")
        flow_ts = [flow_t for i in range(len(self.flows))]
        run_data = np.array([self.flows, self.img_shapes, flow_ts, self.rescales]).T

        p = Pool(processes=cpu_count()-1)
        res = p.starmap(eval_cpu, run_data)

        for i, d in enumerate(self.img_names_list):
            image_n, dtype = os.path.split(d)[1].split('.')
            imwcv2(os.path.join(self.masks_dir, image_n+"."+dtype), res[i].astype(np.uint16))

Where the eval_cpu function is just a reduced copy of the part of models.eval that creates the masks.  I hope this helps!

Hi I tried to follow your instruction to do the same, but sadly I am not an advance programmer. It ended up in a disaster and a barrage of errors.
Could I request you to kindly share your codes as a whole?

Hey sumankhan19,
This is the entirety of the code excepting the two scripts that I mentioned modifying.  There's a good possibility that there's a versioning issue.  If you run pip3 show cellpose from your virtual python environment you can get the cellpose version number.  To be explicit, here's what I'm using:
cellpose version: 0.6.1
linux version: linux mint 19.3/Ubuntu 18.04
Also, even though this might work on cell segmentation I only tested it on nuclei segmentation.
if you can post an email address I can add you to a slack channel where we can discuss further.

<EMAIL_ADDRESS>kindly add me! Thanks!

Using parallel pool has the disadvantage that it will slow down processing on windows if you are not restricting processing to a single thread for computation (or at least this used to be the case). Is your no_torch implementation restricted to a single core?
also in what case is the post-processing most of the time? is it because you have flow_threshold>0? the torch-based implementation is GPU accelerated -- have you tried using the GPU for this?
I can see advantages for running all the images on the GPU at once -- and actually there is an option to tile across batches if you have images of the same size for 3D -- this could be extended for 2D but I'm not sure if it would be useful if your images are very big. And then for the dynamics you could run multiple images simultaneously through the grid_sample layers on the GPU (right now I'm using a batch size of 1).

I remember there being a performance discrepancy between Windows and Linux for python multiprocessing but I'm not sure if that continues to be the case or not.  I don't use Windows when I have a choice, and what I've implemented here has only been run in Ubuntu 18.   In this case, no_torch is run in parallel.  To further reduce post-processing time I have been running with flow threshold=0.  I have tried to use the GPU for post-processing and as expected it is much faster than the non-gpu version, but when compared to multiprocessing it is much slower.  To illustrate why, let's say that that I'm processing 30 images on a 40 core machine.  When run without GPU acceleration assuming each image takes 60 seconds for post-processing that's 30 minutes of run time for post-processing.  If GPU acceleration reduces the serial processing of images down to 10 seconds then the result is far better at 3 minutes run time.  On the other hand, if post-processing is run on all 30 images concurrently without GPU acceleration then in the optimal case the total run time is three times faster than the GPU accelerated case at 1 minute.  Whether the GPU accelerated version or the parallel CPU version is faster depends entirely on how many images you are processing and the particulars of your system (number of cores and GPU).  In my case, where I'm consistently processing more than 10 images at a time and I happen to have a moderately capable GPU plus a 40 thread server, the parallel processing CPU case is usually a few times faster, but mileage may vary.

Are your diameters less than 30? That could explain the 466s timing. I found some speed bottlenecks, can you please try the latest version of the code from github and report your timings?
for the GPU accelerated interpolation you need to be running the torch version, are you running that?
My current timings with 38 images of size 2048x2048 and diameter=30:
With GPU with flow_threshold=0.4 is flow+mask computation 99.33;  with flow_threshold=0.0 is flow+mask computation 51.60
With CPU+interp=False with flow_threshold=0.4 is flow+mask computation 437.30;
with flow_threshold=0.0 is flow+mask computation 190.01.
If this doesn't help enough I will consider splitting the steps as you've recommended.

We're dealing with low resolution images so our nucleus diameters average about 8 with a mean cell count of ~6500 per frame.  I just upgraded to a new machine with a sweet sweet RTX 3090 and I'm struggling to get it to work with Torch.  Once that happens I'll try the system on the new release.

I just tested on the new machine using the following:
interp=False
flow_threshold=0
--fast_mode
--nclasses=1
--diameter=8
--no_npy

Running on version 0.6.1 of cellpose, on a stack of 20 - (512x512) image examples I get a total run time of: 149.6 seconds.
Running using the multiprocessing approach, run time is: ~30 seconds.  Because I'm using a 64 thread machine, I expect to see more gains with larger image stacks.

we will not be using pool, I'd recommend using the GPU to get speed-ups, and we will look into running multiple dynamics flows simultaneously on the GPU


Can i run package with sensor SICK TIM 310

Thanks for asking. The TiM 310 sensor is currently not supported.

Is there any package that supports this type of sensor?

I do not know any package. Please contact SICK Support for TiM 310 support.