ViroARSceneNavigator/ViroVRSceneNavigator from SideMenu based app

Hi,
Currently i'm working on an application which has side menu and there are list of mix of different types of scene like ARScenes , VRScenes and normal scenes like List, contact us, about us.
This is how i have created app structure.
Any sample would be great.
 const Drawer = DrawerNavigator(
  {
    Home: { screen: Home },
    SignUpScreen : {screen: SignUpScreen},
    HelloWorldScene : {screen: HelloWorldScene},
    HelloWorldSceneAR : {screen: HelloWorldSceneAR}
  },
  {
    initialRouteName: "Home",
    contentOptions: {
      activeTintColor: "#e91e63"
    },
    contentComponent: props => <SideBar {...props} />
  }
 );

  const AppNavigator = StackNavigator(
  {
    Drawer: { screen: Drawer },
    SignUpScreen : {screen: SignUpScreen},
    HelloWorldScene : {screen: HelloWorldScene},
    HelloWorldSceneAR : {screen: HelloWorldSceneAR},
  },
  {
    initialRouteName: "Drawer",
    headerMode: "none"
  }
  );

  export default () =>
  <Root>
    <AppNavigator />
  </Root>;

Thank you!

Hi @saad-ansari ,
Can you specify what problem are you facing? We have samples for both AR and VR scenes here https://github.com/viromedia/viro/tree/master/js. We don't have samples for how to structure your app for Drawer. For that we would recommend searching on react-native forums.
Thanks,

Hi @manbod
Thanks for the response. The only problem i'm facing is how to push from normal scene means not a  ViroScene to the AR/VR ViroScene. Like...
this.props.navigation.navigate(NormalScene) to ViroARSceneNavigator(ARScene)
Thanks,

Hi @saad-ansari, here is a link to a sample app with Normal Scene and Viro Scene. -> https://github.com/viromedia/ViroARSampleApp
Let us know if that helps or if you are still having issues.


Can't run Dreamer algos

Thanks for making this great repo.
I'm trying to run Dreamer-v2 and I can't get it to work.
Steps to reproduce:

Install from main (commit 0fae2a9fc990b0b53332eccd4ea7ecba435fa71f)
Install dependencies

python -m pip install -e .
python -m pip install opencv-python # Required for cartpole
python -m pip install gymnasium[atari, accept-rom-license] # Required for ALE
python -m pip install gymnasium[mujoco] # Required for Mujoco envs
python -m pip install mujoco==2.3.3 # To avoid mujoco version issue, see https://github.com/deepmind/mujoco/issues/833

System details:

Ubuntu 22.04
Python 3.9.17
Anaconda 3

Running PPO works.
Running Dreamer-v1 fails.
$ python sheeprl.py dreamer_v1 --env_id=CartPole-v1 --num_envs=1 --buffer_size=2 --per_rank_batch_size=1 --per_rank_sequence_length=1
/home/daniel/Documents/github/sheeprl/sheeprl/cli.py:23: UserWarning: This script was launched without the Lightning CLI. Consider to launch the script with `lightning run model ...` to scale it with Fabric
  warnings.warn(
You are using a CUDA device ('NVIDIA GeForce RTX 3070 Laptop GPU') that has Tensor Cores. To properly utilize them, you should set `torch.set_float32_matmul_precision('medium' | 'high')` which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision
Global seed set to 42
Missing logger folder: logs/dreamer_v1/2023-08-02_08-11-14/CartPole-v1_default_42_1690960274
/home/daniel/Documents/github/sheeprl/sheeprl/algos/dreamer_v1/dreamer_v1.py:584: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting to a tensor. (Triggered internally at ../torch/csrc/utils/tensor_new.cpp:245.)
  rewards = torch.tensor([rewards]).view(args.num_envs, -1).float()
Traceback (most recent call last):
  File "/home/daniel/Documents/github/sheeprl/sheeprl.py", line 4, in <module>
    run()
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/click/core.py", line 1157, in __call__
    return self.main(*args, **kwargs)
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/click/core.py", line 1078, in main
    rv = self.invoke(ctx)
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/click/core.py", line 1688, in invoke
    return _process_result(sub_ctx.command.invoke(sub_ctx))
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/click/core.py", line 1434, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/click/core.py", line 783, in invoke
    return __callback(*args, **kwargs)
  File "/home/daniel/Documents/github/sheeprl/sheeprl/cli.py", line 75, in wrapper
    command()
  File "/home/daniel/Documents/github/sheeprl/sheeprl/algos/dreamer_v1/dreamer_v1.py", line 594, in main
    rb.add(step_data[None, ...])
  File "/home/daniel/Documents/github/sheeprl/sheeprl/data/buffers.py", line 647, in add
    self._buf[env_idx].add(data[:, env_data_idx : env_data_idx + 1])
  File "/home/daniel/Documents/github/sheeprl/sheeprl/data/buffers.py", line 146, in add
    self._buf[idxes, :] = data_to_store
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/tensordict/tensordict.py", line 3133, in __setitem__
    self.set_at_(key, item, index)
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/tensordict/tensordict.py", line 3808, in set_at_
    _set_item(tensor_in, idx, value)
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/tensordict/utils.py", line 730, in _set_item
    tensor[index] = value
IndexError: tensors used as indices must be long, int, byte or bool tensors

Running Dreamer-v2 also fails.
$ python sheeprl.py dreamer_v2 --env_id=CartPole-v1 --num_envs=1
/home/daniel/Documents/github/sheeprl/sheeprl/cli.py:23: UserWarning: This script was launched without the Lightning CLI. Consider to launch the script with `lightning run model ...` to scale it with Fabric
  warnings.warn(
You are using a CUDA device ('NVIDIA GeForce RTX 3070 Laptop GPU') that has Tensor Cores. To properly utilize them, you should set `torch.set_float32_matmul_precision('medium' | 'high')` which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision
Global seed set to 42
Missing logger folder: logs/dreamer_v2/2023-08-02_08-09-04/CartPole-v1_default_42_1690960144
Traceback (most recent call last):
  File "/home/daniel/Documents/github/sheeprl/sheeprl.py", line 4, in <module>
    run()
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/click/core.py", line 1157, in __call__
    return self.main(*args, **kwargs)
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/click/core.py", line 1078, in main
    rv = self.invoke(ctx)
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/click/core.py", line 1688, in invoke
    return _process_result(sub_ctx.command.invoke(sub_ctx))
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/click/core.py", line 1434, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/click/core.py", line 783, in invoke
    return __callback(*args, **kwargs)
  File "/home/daniel/Documents/github/sheeprl/sheeprl/cli.py", line 75, in wrapper
    command()
  File "/home/daniel/Documents/github/sheeprl/sheeprl/algos/dreamer_v2/dreamer_v2.py", line 486, in main
    raise RuntimeError(f"There must be at least one valid observation.")
RuntimeError: There must be at least one valid observation

Running the Dreamer-v1 tests works. (The first 6 at least, I didn't wait for the others to finish.)
$ python -m pytest tests/test_algos -k test_dreamer_v1
======================================== test session starts ========================================
platform linux -- Python 3.9.17, pytest-7.3.1, pluggy-1.2.0
rootdir: /home/daniel/Documents/github/sheeprl
configfile: pyproject.toml
plugins: anyio-3.7.1, timeout-2.1.0, cov-4.1.0
collected 117 items / 99 deselected / 18 selected

tests/test_algos/test_algos.py ......

Running the Dreamer-v2 tests also works. (Again, only the first 6)
$ python -m pytest tests/test_algos/test_algos.py -k test_dreamer_v2
======================================== test session starts ========================================
platform linux -- Python 3.9.17, pytest-7.3.1, pluggy-1.2.0
rootdir: /home/daniel/Documents/github/sheeprl
configfile: pyproject.toml
plugins: anyio-3.7.1, timeout-2.1.0, cov-4.1.0
collected 114 items / 96 deselected / 18 selected

tests/test_algos/test_algos.py ......

After some further testing, I also can't run many of the other algorithms.
PPO continuous:
$ python sheeprl.py ppo_continuous --num_envs=1 --env_id=Walker2d-v4
/home/daniel/Documents/github/sheeprl/sheeprl/cli.py:23: UserWarning: This script was launched without the Lightning CLI. Consider to launch the script with `lightning run model ...` to scale it with Fabric
  warnings.warn(
You are using a CUDA device ('NVIDIA GeForce RTX 3070 Laptop GPU') that has Tensor Cores. To properly utilize them, you should set `torch.set_float32_matmul_precision('medium' | 'high')` which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision
Global seed set to 42
Missing logger folder: logs/ppo_continuous/2023-08-02_08-25-25/Walker2d-v4_default_42_1690961125
Traceback (most recent call last):
  File "/home/daniel/Documents/github/sheeprl/sheeprl.py", line 4, in <module>
    run()
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/click/core.py", line 1157, in __call__
    return self.main(*args, **kwargs)
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/click/core.py", line 1078, in main
    rv = self.invoke(ctx)
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/click/core.py", line 1688, in invoke
    return _process_result(sub_ctx.command.invoke(sub_ctx))
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/click/core.py", line 1434, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/click/core.py", line 783, in invoke
    return __callback(*args, **kwargs)
  File "/home/daniel/Documents/github/sheeprl/sheeprl/cli.py", line 75, in wrapper
    command()
  File "/home/daniel/Documents/github/sheeprl/sheeprl/algos/ppo_continuous/ppo_continuous.py", line 228, in main
    action, logprob, _ = actor.module(next_obs)
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/daniel/Documents/github/sheeprl/sheeprl/algos/ppo_continuous/agent.py", line 41, in forward
    x = self.model(obs)
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/daniel/Documents/github/sheeprl/sheeprl/models/models.py", line 118, in forward
    return self.model(obs)
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/torch/nn/modules/container.py", line 217, in forward
    input = module(input)
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/torch/nn/modules/linear.py", line 114, in forward
    return F.linear(input, self.weight, self.bias)
RuntimeError: mat1 and mat2 must have the same dtype

SAC:
$ python sheeprl.py sac --num_envs 1 --env_id Walker2d-v4
/home/daniel/Documents/github/sheeprl/sheeprl/cli.py:23: UserWarning: This script was launched without the Lightning CLI. Consider to launch the script with `lightning run model ...` to scale it with Fabric
  warnings.warn(
You are using a CUDA device ('NVIDIA GeForce RTX 3070 Laptop GPU') that has Tensor Cores. To properly utilize them, you should set `torch.set_float32_matmul_precision('medium' | 'high')` which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision
Global seed set to 42
Missing logger folder: logs/sac/2023-08-02_08-24-39/Walker2d-v4_default_42_1690961079
/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/torchmetrics/utilities/prints.py:42: UserWarning: The ``compute`` method of metric MeanMetric was called before the ``update`` method which may lead to errors, as metric states have not yet been updated.
  warnings.warn(*args, **kwargs)  # noqa: B028
Traceback (most recent call last):
  File "/home/daniel/Documents/github/sheeprl/sheeprl.py", line 4, in <module>
    run()
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/click/core.py", line 1157, in __call__
    return self.main(*args, **kwargs)
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/click/core.py", line 1078, in main
    rv = self.invoke(ctx)
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/click/core.py", line 1688, in invoke
    return _process_result(sub_ctx.command.invoke(sub_ctx))
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/click/core.py", line 1434, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/click/core.py", line 783, in invoke
    return __callback(*args, **kwargs)
  File "/home/daniel/Documents/github/sheeprl/sheeprl/cli.py", line 75, in wrapper
    command()
  File "/home/daniel/Documents/github/sheeprl/sheeprl/algos/sac/sac.py", line 251, in main
    rb.add(step_data.unsqueeze(0))
  File "/home/daniel/Documents/github/sheeprl/sheeprl/data/buffers.py", line 146, in add
    self._buf[idxes, :] = data_to_store
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/tensordict/tensordict.py", line 3133, in __setitem__
    self.set_at_(key, item, index)
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/tensordict/tensordict.py", line 3808, in set_at_
    _set_item(tensor_in, idx, value)
  File "/home/daniel/anaconda3/envs/sheeprl/lib/python3.9/site-packages/tensordict/utils.py", line 730, in _set_item
    tensor[index] = value
RuntimeError: Index put requires the source and destination dtypes match, got Float for the destination and Double for the source.

Hi @dtch1997, i will look into them.


Feature: Select Actions

Add other actions (not only launch apps) like:

no action
open app menu
show settings

no action

Possible since version 1.2.1

open app menu
show settings

Is currently being implemented


Update en.json

Danish keyboard

@netromnetrom Thank you for the contributions.  A couple of things regarding these changes:

You don't need individual pull requests for each commit.  You can do multiple commits in a single pull request.
All Pull Requests should be associated with a JIRA issue.  I believe there's already a JIRA issue for this, so the Pull Request just needs to be updated with the GUACAMOLE-XXX: tag on the front.
All commits also need to be tagged with the JIRA issue.

You can look at existing pull requests for examples of how to tag both the pull request itself and the individual commits.  You can also look at the following contribution guidelines:
http://guacamole.apache.org/open-source/


DMP-2884 ARM Synchronous Deletion - IU file deletion

JIRA link (if applicable)
https://tools.hmcts.net/jira/browse/DMP-2884
Change description
Added functionality to delete the batch IU file
Does this PR introduce a breaking change? (check one with "x")
[ ] Yes
[ x] No

Are there any tests (unit/int) that can be written to verify the new functionality?

I have updated the tests to cover this


Can't get it to log in; I put the client ID and key yet it does't log into it.

Or do I need to add devices one by one manually?

This does not seem to be a bug report, it is a question.  If you can phrase it more clearly you could post it in discussions.  But as it is, I would not expect anyone to be able to answer it, as it does not make a lot of sense in the context of this integration.


chore: Making chromadb package optional

Closes #30

#32  👈
main

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Join @tazarov and the rest of your teammates on  Graphite


sent GraphQL request without content type header and got error

Hi, I sent GraphQL request and got error Cannot read properties of undefined (reading 'launchesQuery')
GRAPHQL https://api.spacex.land/graphql

query launchesQuery($limit: Int!){
  launchesPast(limit: $limit) {
    mission_name
    launch_date_local
  }
}

{
    "limit": 10
}

Is it possible that httpYac can also support the GraphQL request without header Content-Type?
GraphQL syntax is without Content-Type header in built-in plugins HTTP Client of Jetbrain IDE.  It would be great to have support. Thank a lot :bowing_woman:
https://www.jetbrains.com/help/idea/http-client-in-product-code-editor.html#graphql

Yes, agree that should work the same. Feel free to create a bug in case of deviations. I don't use Intellij at all at the moment and you don't document changes so precisely in updates.
fixed and released in v6.11.3


Bug/293

fixes for memory leaks related to watches never ending

https://github.com/Comcast/kuberhealthy/issues/293#issuecomment-590119623 ):

merging this for now even though it does not fix #293


system.autoUpgrade: optionally allow rebooting the system on kernel change

Motivation for this change
new function for the module: Allows automatic reboots if the new generation uses a different kernel.
Things done

[x] Tested using sandboxing (nix.useSandbox on NixOS, or option sandbox in nix.conf on non-NixOS)
Built on platform(s)

[x] NixOS
[ ] macOS
[ ] other Linux distributions

[ ] Tested via one or more NixOS test(s) if existing and applicable for the change (look inside nixos/tests)
[ ] Tested compilation of all pkgs that depend on this change using nix-shell -p nix-review --run "nix-review wip"
[ ] Tested execution of all binary files (usually in ./result/bin/)
[ ] Determined the impact on package closure size (by running nix path-info -S before and after)
[x] Ensured that relevant documentation is up to date
[ ] Fits CONTRIBUTING.md.

The option has a description, so it should show up.
Default is false for allowReboot, so it should yield the same result as the current version, unless the allowReboot is enabled.
I don't think there's any test that can actually test an upgrade. I've ran it on nixos-19.03 channel and it does what it's supposed to, i.e. build the new generation, check if the kernel has changed. If the kernel is the same, it runs a switch. If the kernel has changed, it will boot into the new generation.

not sure who's the best to mention here, but probably @edolstra as the first and @danbst as the last contributor for that file?

I tried something similar but I took a different approach.
I always did a switch and then checked if the kernel has changed, if so I did a reboot.
I'm not sure if this has some drawbacks compared to your version, but it for sure has less cases as it is just a post step after the normal switch.

I'd love to have a test for this as well, but I have no idea where to start writing one, so I'll leave that open.
I'm testing this on my system right now, so please don't merge yet until I've verified it's working.
Just need the stable channel to have a kernel update.

So there was kernel update recently and the module worked just fine when hammered into 19.03, so I believe the PR is ready to be merged if there are no objections?


Updated put-file docs

Throughout our docs, we need to add a few specific updates for put-file:

-c flag should be removed everywhere
In https://pachyderm.readthedocs.io/en/latest/fundamentals/getting_data_into_pachyderm.html, the -r syntax shown is incorrect:

pachctl put-file <repo> <branch> -r <dir> should be pachctl put-file <repo> <branch> -r if <dir>
There may be other sections in this doc that are a bit out of date, so a quick review/test pass would be good since it's one of the first things users come across after deploying
┆Issue is synchronized with this Asana task

-c should.... be gone from all docs (other than cli help output)

grep -rnw './' -e '-c'
Binary file .//enterprise/dashboard.png matches
Binary file .//enterprise/enterprise.png matches
.//pachctl/pachctl_put-file.md:64:  -c, --commit                    DEPRECATED: Put file(s) in a new commit.
.//pachctl/pachctl_put-file.md:69:  -m, --message string            A description of this commit's contents (only allowed with -c)
.//pachctl/pachctl_mount.md:17:  -c, --commits []string   Commits to mount for repos, arguments should be of the form "repo:commit" (default [])
Binary file .//cookbook/cron1.png matches
Binary file .//custom_theme/static/fonts/fontawesome-webfont.eot matches
Binary file .//getting_started/montage-screenshot.png matches
Binary file .//getting_started/dashboard1.png matches
Binary file .//getting_started/dashboard3.png matches

fixed the -r flag.


Discrepancy between dev and build

Vue version
3.3.4
Link to minimal reproduction
https://github.com/pbgcommits/trainle-solver/commit/6b16ecd5f96a4b36ab38b0005f7f1f6c29d00081
Steps to reproduce
The faulty code can be found here. Code
You can see the line 142 which is bugged (red), and the line which works (green).
Open the minimal reproduction link. Input "belgrave", "5", and "5" into the fields. The expected table will not appear, and the following error will display:
TypeError: Cannot read properties of undefined (reading 'hintLines')
    at index-ceba6773.js:4:8528
    at Ei (index-ceba6773.js:1:24804)
    at index-ceba6773.js:4:8152
    at Object.a [as default] (index-ceba6773.js:1:16490)
    at default (index-ceba6773.js:8:248060)
    at ms (index-ceba6773.js:1:50234)
    at ne (index-ceba6773.js:1:48469)
    at og (index-ceba6773.js:1:48997)
    at Proxy.<anonymous> (index-ceba6773.js:8:247633)
    at kr (index-ceba6773.js:1:16802)

(The expected behaviour can be seen here by using the same input: Working link )
What is expected?
A table with a single row should appear upon valid submission of data. This should be consistent across the "npm run dev" environment and the "npm run build" build.
What is actually happening?
In the dev environment, the table drops down correctly, suggesting it will also work in build. (This can be seen by cloning the supplied repo, running npm run install, then npm run dev, then inputting the above input). However, in the build environment, the code runs into an error.
System Info
No response
Any additional comments?
No response

I've tried to reduce this reproduction down to a Playground:

Playground

You can toggle between DEV and PROD using the button at the top, yielding the error in production mode.
The original report is using 3.3.4. That Playground is using the latest main branch. The warning in development mode was added in 3.3.9 by #7866.

Thanks for the quick response time! Glad to see this has been fixed already :)


Benchmarking

See tickets LAB-823 and LAB-815 for description. Adds a method for extracting benchmark data from a PAM population, for specified combinations of data fields, dimensions, and aggregation functions.

@fredshone I have added trips by distance and duration bin benchmarks, as well as some other wrappers (hour and mode+purpose breakdowns)


Remove version: taers232c.GAMADV-XTD3 version 6.67.29

This version is older than what has been set in max-versions-to-keep by the publisher.
Microsoft Reviewers: Open in CodeFlow

URL: https://github.com/taers232c/GAMADV-XTD3/releases/download/v6.67.29/gamadv-xtd3-6.67.29-windows-x86_64.msi
OK
(Automated message - build 910)


Cryptomatte With Tiles

Hey Guys
I hope all is well you are having a great holiday. I have come across and issue when using cryptomatte, we deal with really large images for print and in order to get renders turned around we do a lot of tiles. I have noticed when we do the tiles and combine them all together in nuke we can use the cryptomatte gizmo without a problem, however, when we try to merge the metadata streams from all the exrs to create a flattened exr and that exr is read back in the gizmo no longer works. I suspect that when the tiles are merged and the gizmo is placed inline after the merge the original metadata streams can be parsed independently, but when we merge the metadata and make a single image somehow they do not play well together.
Has anyone else come across this?
Should i be looking to combine these images with something OpenExr Commandline?

when we try to merge the metadata streams from all the exrs to create a
flattened exr and that exr is read back in the gizmo no longer works.
Rings a bell
Are the resulting crypto aovs's in the flattened exr 32bit? If the metadata
and pixels are there, sounds like a bitdepth issue.
For mixed bit depth files, multipart exr's are the answer.
On Wed, Dec 13, 2017 at 3:48 PM, cjagman123<EMAIL_ADDRESS>wrote:

Hey Guys
I hope all is well you are having a great holiday. I have come across and
issue when using cryptomatte, we deal with really large images for print
and in order to get renders turned around we do a lot of tiles. I have
noticed when we do the tiles and combine them all together in nuke we can
use the cryptomatte gizmo without a problem, however, when we try to merge
the metadata streams from all the exrs to create a flattened exr and that
exr is read back in the gizmo no longer works. I suspect that when the
tiles are merged and the gizmo is placed inline after the merge the
original metadata streams can be parsed independently, but when we merge
the metadata and make a single image somehow they do not play well together.
Has anyone else come across this?
Should i be looking to combine these images with something OpenExr
Commandline?
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
https://github.com/Psyop/Cryptomatte/issues/54, or mute the thread
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.

That's a good point I have not checked the bitdepth that we are outputting. We are using the standard vray crypto and using the stock output at 16bit. I will try running with the 32 bit and multipart exr options. Thanks for the quick response. I will let you know what I find.

Also, see this ticket: https://github.com/Psyop/Cryptomatte/issues/36
(The issue in that ticket was fixed but extra metadata keys may be tripping you up)

@cjagman123 Did this work, can we close this?
Cryptomattes must be 32 bit, the ones written out of VRay are no exception.

Thanks Jonah
We did not realize that the exr was a multipart exr. I wrote out the tiles at a 32-bit exr and everything works as expected. Thank you.

Thanks, @cjagman123


add TemporalGPs 0.6

Codecov Report
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Additional details and impacted files
@@          Coverage Diff          @@
##            main     #75   +/-   ##
=====================================
  Coverage   7.89%   7.89%
=====================================
  Files         32      32
  Lines       2039    2039
=====================================
  Hits         161     161
  Misses      1878    1878

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Updating compat


Normalize code blocks

Pull Request Test Coverage Report for Build f5e7c59d7cd69837769c520655a0f1ac95aa1665-PR-7

40 of 40 (100.0%)  changed or added relevant lines in 1 file are covered.
No unchanged relevant lines lost coverage.
Overall coverage increased (+0.7%) to 96.569%

Totals

Change from base Build 7e8707bce914fa8c494e8f695d6ad2696fc2296e:
0.7%

Covered Lines:
197

Relevant Lines:
204

💛  - Coveralls


A member with the name 'name' already exists on 'OpenAI.Chat.Message'

Bug Report
The following error message occurs when attempting ChatEndpoint.GetCompletionAsync():
JsonSerializationException: A member with the name 'name' already exists on 'OpenAI.Chat.Message'. Use the JsonPropertyAttribute to specify another name.
I apologize if this is not the proper space to bring this up, I could not start a discussion in the Q&A section of the Discussions tab.
Overview
Upon looking through the source I see that in Message.cs there is a serialized field "name" as well as using the JsonPropertyAttribute to specify the public "Name" field to serialize as "name".  This might be causing the issue.
To Reproduce
The following code reproduces this problem on the "await api.ChatEndpoint.GetCompletionAsync(chatRequest);" line.
private async Task<string> SendMessage(string message)
{
    var api = new OpenAIClient(GPT_API_KEY);

    var messages = new List<Message>
    {
        new Message(Role.System, GPT_SYSTEM_ROLE),
        new Message(Role.User, message)
    };
    var chatRequest = new ChatRequest(messages, GPT_MODEL_ID);
    var response = await api.ChatEndpoint.GetCompletionAsync(chatRequest);
    var choice = response.FirstChoice;

    return choice.Message.Content.ToString();
}

Expected behavior
I would expect that error to not occur and for the GetCompletionAsync() to complete as expected.
Additional context
I am using this package in Unity 2022.3.10f1.

I don't understand. Are you using my official unity package or using the Nuget version in Unity?

Oh I'm sorry, yes I'm using that unity package. I must have posted on the wrong repo.

Created a new issue there: https://github.com/RageAgainstThePixel/com.openai.unity/issues/170


k3s: symlinks for kubectl crictl & ctr

Description of changes
These symlinks are added by the standard k3s installer and are useful for using these command line utilities more ergonomically. Rather than calling k3s kubectl ... users may now call kubectl ....
Things done

Built on platform(s)

[x] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

[ ] For non-Linux: Is sandbox = true set in nix.conf? (See Nix manual)
[x] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[x] Tested basic functionality of all binary files (usually in ./result/bin/)
23.05 Release Notes (or backporting 22.11 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module

[x] Fits CONTRIBUTING.md.

Thanks for the thoughtful response - agreed on preferring non-k3s installations of kubectl, crtictl, ctr. Dropped meta.priority to 5 for the various k3s packages

I took the liberty of re-basing, would be great if some could review it so we can get this merged.


Prompt only updates when zsh is first started

If I make changes or cd into a git repository, zsh does not register the difference (e.g. the changed files, or the fact that we're now in a git repo) until you launch zsh again.
For example, starting in a regular directory (/), then cding into a git repo ($HOME):
USER at HOST in  /
$ cd ~
USER at HOST in  ~
$ zsh
USER at HOST in  ~  (master↑2|✚2)
$

The same thing happens when you are already in a git repo, and changes are made:
USER at HOST in  ~/test  (master|✔)
$ touch test
USER at HOST in  ~/test  (master|✔)
$ zsh
USER at HOST in  ~/test  (master|…)
$ git add test
USER at HOST in  ~/test  (master|…)
$ zsh
USER at HOST in  ~/test  (master|●1)
$

I'm unsure if it's related, but the stock zsh ${git_branch} doesn't register changes for me. It only shows the branch. On some machines it works (all have the same exact config files), on others it doesn't.
Let me know if you need any config files, or environment variables, etc.
My .zshrc at the time of testing (prompt starts at line 33): https://github.com/zhimsel/dotfiles/blob/af3687d409e5bac1eb1c735076eaa79c2b7f0806/.zshrc

+1 Getting the same issue here. The git prompt is not updating whent changing directories.

Does it also not update for changes in the git status? (e.g. added a new file, or there are new unstaged changes) For me, it only displays what was present at the time zsh launched.

The __CURRENT_GIT_STATUS status does get updated properly on change of directory. Thought there is nothing invoking git_super_status to update the current PROMPT variable. The following manual updating of PROMP works for me.
In my .zshrc file
# Prompt
# Git
source ~/.zsh.d/zsh-git-prompt/zshrc.sh
PROMPT="%{$fg[green]%}%c $(git_super_status)%{$fg[red]%}~%{$fg[white]%}࿔ %{$reset_color%}"

autoload -U add-zsh-hook
add-zsh-hook chpwd update_prompt
function update_prompt() {
    PROMPT="%{$fg[green]%}%c $(git_super_status)%{$fg[red]%}~%{$fg[white]%}࿔ %{$reset_color%}"
}

Hm. I'll have to try that later. Thanks.

I think the same thing applies here, as in the other issue: https://github.com/olivierverdier/zsh-git-prompt/issues/55#issuecomment-77440662

@cevaris Your solution works, but only for when you change directories. If you stay in the same dir and just update git somehow (checking out a different branch, making commit, etc), the status is not reflected until you cd ..

Workaround in #55 (thanks @cevaris )

Closing issue (workaround in #55)


docker-machine vs sudo docker-machine

When I run
docker-machine active

I get the active machine.
If I run
sudo docker-machine active

I get "no active host found".
The same with
docker-machine inspect dinghy

and
sudo docker-machine dinghy

I am using dinghy to manage my docker environment on Mac OS X - and the dinghy command requires docker-machine to be elevated to sudo when running commands - but unfortunately the sudo and non-sudo commands return different results.
Is there anything I can change on my setup so that the same output is returned? Is something wrong on my end? Where can I change right etc to make this work properly? Or is this by design?

(Disclaimer: not a maintainer, might want to fact check me on some of this)
Machine operates on the user level by design. It stores a lot of state in ~/.docker/machine for each user, including which machines it has defined, certificates for connecting to them, etc. If dinghy requires everything to run as root, then the machine you're operating on must also be owned by the root user.
We have a similar problem in Dusty where we need some root privileges but also want to be able to use a non-root user's machine. We solved this by specifying the user who owned the machines and dropping privileges down to that user whenever we wanted to talk to Machine. Dinghy might need to implement this pattern to avoid having to run everything as root.

Ok awesome thank you.

Yes, Machine itself is not meant to be run as root.  I'd suggest if users need to sudo operations related to Machine (such as setting up NFS mounts) that they take a similar approach to what Vagrant has done by creating custom sudoers entries for those commands.


Variable x axis

This PR addresses #196. These changes should allow proper handling of TRACULA data with different numbers of nodes for each tract.

@arokem @richford @jyeatman @akeshavan There is a bit of redundant code that I should be able to turn into a couple of small functions, but wanted to get this out there in case anyone else wants to test the functionality before we meet.

Redundant code cleaned up with updates in ac0f1b3ccb6acbfcdf80b59f70197598f2d12cb4.

@anotherjoshsmith The axes look good and brushing works for me. There are a few issues I noticed:

[ ] Brushing on core fibers doesn't cover the entire fiber. This is my fault from a previous PR. No need to address it here as #215 addresses it.
[ ] The std and stderr shading areas are displayed on top of some of the subject lines, preventing selection. As described here, can we put the shading areas in one g element and the lines in another g element and then render the areas first and then the lines.
[ ] Sorting on a column is not saved in the querystring for me. The weird thing is it works for the AFQ generated data but when I switch to the stuff in the tracula_data folder, then the grouping and sorting is not saved on a page refresh with the querystring.

@anotherjoshsmith I created a PR against this branch on your fork to partially resolve the sorting issue. It's better but isn't completely fixed. The query string now saves an initial sort but if I click on a column twice, it won't save that on page refresh (weird). Again, this is all for the TRACULA generated data. Things work well for the AFQ generated data.

@anotherjoshsmith I pushed another commit to that PR that fixes the restoration of column sorting from the querystring. If you merge that PR, I think all that's left is to fix the std area shading issue listed above.

@richford Great, thanks! I'll check out your changes and take care of the std area issue.

@richford Most recent commit fixes layering of g elements. Let me know if I broke anything!

I found two errors, both of which are my fault I think. I submitted a PR on your branch to fix them. After that, I think it's good to go!


Add ActivityPub support

Is your proposal related to a problem?

I want the readers of my Wagtail based website will be able to follow my news on Mastodon and other federated platforms that support ActivityPub.
Describe the solution you'd like

Add support for ActivityPub in Wagtail so that it works out-of-the-box.
I'm no expert on the ActivityPub protocol, but I imagine that the functionality you could add in Wagtail with an integration with ActivityPub (in addition to an RSS bot) could basically be the ability to receive and track reactions (e.g. reply, boost, fav, bookmark) and maybe show threaded comments.
Describe alternatives you've considered

Wordpress already have a plugin to add ActivityPub support to already published website.

Drupal has ActivityPub support too.

Additional context

There are already some Django-based implementation of ActivityPub protocol for standalone servers (es: takahe or bookwyrm) but it would be very useful to add ActivtyPub support to an already published Wagtail based website.

So, as an alleged expert in this now, here's what I think the basic coverage of ActivityPub (i.e. sending posts to followers with only a single "account" you follow for the whole server) would entail:

A Follower model that tracks which ActivityPub Actors are following the server
A FanOut model that tracks which Actors have been delivered which posts
A background worker, like Takahē's Stator, that delivers Accept (for Follow) and Create.Note (for posts) messages to other Actors and which can handle retrying them
An Inbox view that accepts Follow messages from other users, and accepts and drops all the Create.Note messages that other servers are going to start sending you because they think you're more capable than you are.

I personally think that something like this would be better suited to be an external package. Maybe even starting as a blog post or two from anyone in the community.
While I agree that this capability would be awesome and I'm all for ActivityPub - this is not something that all sites would use and might not be suitable for Wagtail core.
It might be worth discussing what parts are missing that may be suitable for Wagtail. For example there is an existing RFC to add background workers to Wagtail - https://github.com/wagtail/rfcs/pull/72
I'll let other core team members add their thoughts and maybe experience with implementing something similar.

Thanks for your feedback.
I'm not a Wagtail or ActivityPub expert but I thought that integrating ActivitPub in Wagtail can be a great features that can attract more users and developers.
I opened this issue to start a discussion about this feature but I don't know if it can be implemented as an external package or not, I hope others can share their thoughts.

Thanks @pauloxnet - I 100% think this is a good discussion to have and agree that the more Wagtail can do for developers the better it is. However, some things are often best suited as an external package even if it may end up in core in the future.
Let's give others a week or so to give feedback and thoughts - we may end up moving this to a discussion not an issue from there.

I agree with you. Maybe this would be a starting point for an external package, if feasible.


Fix aliasing partial with viewModel, when set before upgrade.

https://github.com/Starcounter/starcounter-include/issues/21

Related to https://github.com/Starcounter/starcounter-include/issues/38

Did you test this in an app? For me KitchenSink navigation does not work after this change:
I am testing this by:

Run KitchenSink
Run CompositionProvider
In CompositionEditor, cd src/CompositionEditor
bower install starcounter-include#fix-aliasing-viewModel
bower install starcounter/starcounter-layout-html-editor#starcounter-include-3.x
Run CompositionEditor
Go to localhost:8080/kitchensink and try clicking on navigation in the left menu

:( I tested it with Products + Images
I think It's really the time to set up Polymer's Tattoo before proceeding with any changes to our frontend stack.

And integrate this tattoo with our teamcity somehow.


create AD file annotation view

Figured I would move this branch to our adkp/snowflake fork so it doesn't hang out here stagnating forever. https://github.com/adknowledgeportal/snowflake/tree/ad-annotation-view


confusing interface between qtls and quic-go for session tickets

quic-go encodes information into the session ticket and restores them on ClientSessionCache.Get(). However, qtls then decides if it uses the session ticket. We should not use the restored information if qtls decides not to use the ticket.

One option would be to extend the Get() method. Currently, it's
Get(sessionKey string) (session *ClientSessionState, ok bool)

We could add a callback as a return value, which would be called when the session ticket is actually used:
Get(sessionKey string) (session *ClientSessionState, used func(), ok bool)

Another option would be to decouple the ClientSessionCache from quic-go. We'd not wrap the Get and Put method anymore. Instead, we add two new functions to the qtls.Config:
GetAppDataForSessionTicket func() []byte
ProcessAppDataFromSessionTicket func([]byte)

It would then be qtls' responsibility to encode / decode the app data provided by quic-go into the session ticket, which quic-go would deal with serializing the values it wants to save.


[AutoPR apimanagement/resource-manager] Merge master in to keyvault_preview

Created to sync https://github.com/Azure/azure-rest-api-specs/pull/2681

Codecov Report

Merging #2203 into restapi_auto_keyvault_preview will increase coverage by 0.14%.
The diff coverage is n/a.

@@                        Coverage Diff                        @@
##           restapi_auto_keyvault_preview    #2203      +/-   ##
=================================================================
+ Coverage                           52.9%   53.04%   +0.14%
=================================================================
  Files                               4798     4798
  Lines                             120947   120487     -460
=================================================================
- Hits                               63982    63913      -69
+ Misses                             56965    56574     -391

Impacted Files
Coverage Δ

...azure/mgmt/cdn/operations/edge_nodes_operations.py
40% <0%> (-1.94%)
:arrow_down:

...e-mgmt-cdn/azure/mgmt/cdn/operations/operations.py
40% <0%> (-1.94%)
:arrow_down:

...e/mgmt/cdn/operations/resource_usage_operations.py
37.5% <0%> (-1.9%)
:arrow_down:

.../azure/mgmt/cdn/operations/endpoints_operations.py
9.84% <0%> (-1.72%)
:arrow_down:

...n/azure/mgmt/cdn/operations/profiles_operations.py
10.91% <0%> (-0.93%)
:arrow_down:

...e/mgmt/cdn/operations/custom_domains_operations.py
13.29% <0%> (-0.35%)
:arrow_down:

...dn/azure/mgmt/cdn/operations/origins_operations.py
19.54% <0%> (+1.14%)
:arrow_up:

...e-mgmt-cdn/azure/mgmt/cdn/cdn_management_client.py
76.54% <0%> (+8.12%)
:arrow_up:

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[Enhancement] Trinket slot positioning?

https://www.curseforge.com/minecraft/mc-mods/trinkets
Trinket's look weird on scaled limbs due to trinkets using the default player models positioning. This would be great to be able to set where trinket slots appear.

🥺

it would be cool to have custom trinket positioning but I don't think it's possible since more then one trinket can have different root parts but use the same slot


BDropdown changes v0.20.0

What you are trying to do. A clear and concise description of what you want to happen.
Hi, the new version v0.20.0 makes some changes to BDropdowns - what do they do? I've been looking through the code and I'm not sure what is going on - only that after the update I have some issues rendering my components contents/items, v0.19 had some issues but not this. I need to wrap my BDropdowns with <ClientOnly> tags now to get them to render their contents. Any input is appreciated! Many thanks.
What you have already tried. A clear and concise description of any alternative solutions or features you have considered.
Wrapping my BDropdowns in  <ClientOnly> tags which isn't ideal. Needed for page reloads.
Any error messages you are getting. If any, please list the errors you are getting.

This is thrown when clicking on the dropdown.
Environment (please complete the following information):

OS: linux Ubuntu v22.04
Package Version: 0.20.0
Npm/Yarn/Pnpm/Bun Version: yarn v1.22.19

@JagoEFP not 100% since no reproduction, but try setting teleport-to="#teleports" if you're using nuxt (if not create a div with id teleports to body)

I am in the same situation. Enclosing it in  tags or adding teleport-to=“#teleports” worked correctly.

@xvaara What do you think would have caused this issue?
It's important in SSR contexts to provide a stable teleport target. This is why nuxt added it in their release.
I initially added it to the nuxt module for global configuration to have it teleport to this location, but in relation to https://github.com/bootstrap-vue-next/bootstrap-vue-next/issues/1898 it wasn't able to inherit the style since its location in the dom was not a child element... I suppose if we were able to tell if a close parent had this class, we could selectively add it to the class list of the element, then automatically provide the stable teleport target that we need for our Teleport usage

I'm working on a pr that fixes a punch of nuxt ssr problems. I've run into some quite strange bugs/"features".

I've found same bug. I should wrap my dropdown with . I want to render the dropdown in SSR. Is there any solution? now?

I think vue 3.4.35 fixed the teleport bugs, I'll need to check.


[BUG] youtube always open in-app browser on iOS

To Reproduce

Run Example code in iOS
when app run, app open browser link of youtube

on youtube_player_mobile.dart function shouldOverrideUrlLoading it run url_launcher.launch

I have the same issue .... have you found a solution ?

I forked this repository and fix the bugs

you can see my git repository: https://github.com/pansitwattana/youtube_player_flutter/blob/014c7745280af8941b578574557b910bf140f950/packages/youtube_player_iframe/lib/src/players/youtube_player_mobile.dart#L138

Pleas make a PR :)

when is this gonna merge with the master branch?

Someone is opening PR here https://github.com/sarbagyastha/youtube_player_flutter/pull/420

any update on this?

Im using youtube_player_iframe Is this fixed there?

Still seeing this on 2.1.0 - Have a listing of Youtube videos, and when the screen builds it automatically opens every video in a browser window.
iOS 14.5
Flutter 2.2.3

Fixed with v2.2.2


Add unix_server to create a Unix server.

Based on #273 by @PrettyWood.

@PrettyWood Can you confirm this covers your use case in #273?

:+1: thanks a bunch !


Allow extending C++ StandardMethodCodec

The current C++ implementation of StandardMethodCodec/StandardMessageCodec doesn't allow client extensions, which is supported on other platforms, and require for compatibility with plugins that use it in their current implementations.
The approach I have in mind is:

Add one more type to EncodableValue for extensions, and have that extension type store a void* value along with function pointers for delete, copy, and optionally compare. Then there would be all the usual associated methods (IsExtension, ExtensionValue, etc.).
Make the serializer class subclassable, with a method that is called for reading and writing values when an extension type is encountered.

The reason for this approach rather than something subclassing based is that this should be something that would continue to work even if the codecs are moved into the libraries. We'll need to evaluate how onerous that ends up being to use; my hope is that it should be straightforward for someone extending to make an adapter that hides most of that complexity from most of the call sites.

The reason for this approach rather than something subclassing based is that this should be something that would continue to work even if the codecs are moved into the libraries.

I decided that moving codecs into the libraries was impractical, so subclassing is a viable option.


Mechanism for package authors to give auto-import hints

Apologies if this exists and I just couldn't find documentation on it. We have several in-house npm packages to offer common functionality across our codebases. Each of these packages defines subpath exports entries to directly target individual functions and components, in addition to getting everything from the root entry. To use an example with MUI, you can do either of these:
import { Grid } from '@mui/material';

or
import Grid from '@mui/material/Grid'`

The problem is, the auto-import completion rarely even lists the later, just the former, or sometimes, when it does go deeper, it tries to import the direct file (eg, @mui/material/node/Grid/Grid.js) instead of using the subpath export.
It would be very helpful if I, as a package author, could give weight to the exports so that I can tell vscode "this is actually the better path to use for suggesting this export."

Something in the same vein that I've been considering is the ability for package authors to specify a default name for namespace auto-imports (#52527, #23830).

Something in the same vein that I've been considering is the ability for package authors to specify a default name for namespace auto-imports (https://github.com/microsoft/TypeScript/issues/52527, https://github.com/microsoft/TypeScript/issues/23830).

Oh yes 🙏 this would be super awesome. In a similar vein... some consumers prefer namespace-based imports so it would be cool to have that configurable from the consuming side of things as well.

Is there any reason that you prefer the subpath export?

Hm, I didn't exactly have subpath exports/imports in mind. Just that in some codebases import * as React from 'react' is preferred. It would be cool if auto-importing useState could result in this:
// pre
useStat/*cursor*/

// post
import * as React from 'react'
React.useState/*cursor*/

Sorry, not you @Andarist, I meant that more as a question for @Twipped.

@RyanCavanaugh ohh, that might indeed solve it. I'll take a look today

I figured it out! I can actually solve for this, by defining a typesVersions entry in my package.json.
  "typesVersions": {
    "*": {
      "*": ["./dist/*.d.ts"]
    }
  },

This gets vscode to properly recommend the subpath export instead of the root export. Problem solved!

I figured it out! I can actually solve for this, by defining a typesVersions entry in my package.json.
  "typesVersions": {
    "*": {
      "*": ["./dist/*.d.ts"]
    }
  },

This gets vscode to properly recommend the subpath export instead of the root export. Problem solved!

I'm not sure how that would solve the issue (it doesn't for my case)


Sometimes app doesn't quit properly. (Windows)

It's not consistent, but sometimes when I exit Toggl Desktop, it disappears from system tray, but stays in processes.
What's more annoying is that I can't launch Toggl Desktop until I reboot or kill the process manually.
If I try to launch a new instance, while old one is running, sometimes I get an error (I didn't screenshot it, will add it if I encounter it again).

Similar issue to #2201 but on Windows

Probably issue with the syncing activity. We will have to start syncing activity on demand and keep it closed when not needed.

God, this is annoying. 😠
Happens to me almost every day now. Plz look into it.

the issue 2201 is already fixed but not released. If testing goes well we'll push the new version to beta tomorrow. Thank you for your patience.

Updated, now I get a crash instead of silent fail.
Sceenshot.


CORS web-browser error

Hello,
Using reverse proxy on web applications has started returning errors regarding "POST" requests. Here is an example of a console output:
Access to XMLHttpRequest at 'https://api.chatanywhere.cn//chat/completions' from origin '{...}' has been blocked by CORS policy: Request header field content-type is not allowed by Access-Control-Allow-Headers in preflight response.
Note: I have redacted the name of the website I use the API for (for personal reason), though if more detail is required I could try to provide it.
Is this an issue on the end of the website I am trying to access? I am not certain because previously (earlier today and the past few days), accessing web applications using the reverse proxy has worked perfectly fine. Moreover, the redacted website was one of these websites that had worked fine for me.
I have confirmed the API otherwise works on other applications (Such as Microsoft Visual Studio Code), but accessing these web applications is also an important part of what I'm seeking.
Thanks in advance for your help.

The issue has been resolved.


What are the recommended settings for pro account?

OS version: MacOS Big Sur 11.4
Editor: vscode
Editor version: 1.57.0
Programming language: ts, html, css
TabNine extension version: 3.4.5
Engine version: 3.4.29-40

Issue Details:
Could you please clarify which are the recommended settings for best autocompletion results?
Should the deep cloud and local model be turned on? Or only the cloud model?
What will be the difference?
I also have an older Win PC for work, which settings are best for a slower machine (i5 2,6ghz, 8gb ram)?
(Please add the recommended settings to your FAQ I googled so much and couldn't find any recommendations)
gz#1655

The cloud version eliminates 90% of CPU consumption and 70% of memory consumption.
The main difference is that the local model works offline and the cloud model is not.
There is no need for both cloud and local to be on. If you have a stable internet connection - I recommend the cloud version.


meta/redis: fix unlock on not-existed lock

closes #2323

Codecov Report

Merging #2325 (ee2a37c) into main (6dbc25b) will increase coverage by 0.07%.
The diff coverage is 0.00%.

@@            Coverage Diff             @@
##             main    #2325      +/-   ##
==========================================
+ Coverage   61.68%   61.75%   +0.07%
==========================================
  Files         137      137
  Lines       25400    25400
==========================================
+ Hits        15667    15685      +18
+ Misses       7906     7896      -10
+ Partials     1827     1819       -8

Impacted Files
Coverage Δ

pkg/meta/redis.go
71.83% <0.00%> (-0.05%)
:arrow_down:

pkg/meta/redis_lock.go
76.33% <0.00%> (+1.52%)
:arrow_up:

pkg/vfs/writer.go
78.64% <0.00%> (-1.02%)
:arrow_down:

pkg/meta/base.go
71.44% <0.00%> (-0.15%)
:arrow_down:

pkg/meta/sql.go
65.95% <0.00%> (+0.18%)
:arrow_up:

pkg/meta/tkv.go
76.53% <0.00%> (+0.53%)
:arrow_up:

pkg/meta/sql_lock.go
72.84% <0.00%> (+1.32%)
:arrow_up:

pkg/meta/tkv_lock.go
83.91% <0.00%> (+1.39%)
:arrow_up:

... and 1 more

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 6dbc25b...ee2a37c. Read the comment docs.


Update sbt-bloop to 1.4.8

Updates ch.epfl.scala:sbt-bloop from 1.4.2 to 1.4.8.
GitHub Release Notes - Version Diff
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!

Ignore future updates
Add this to your .scala-steward.conf file to ignore future updates of this dependency:
updates.ignore = [ { groupId = "ch.epfl.scala", artifactId = "sbt-bloop" } ]

labels: sbt-plugin-update, semver-patch

Superseded by #259.


update nlp config

Fix NLP config to be similarto what @asamant22 has in the notebook walkthrough https://colab.research.google.com/drive/1LAYtvxkUPsRQZpPPqQFDBSA3-mxFvEKE#scrollTo=35d40591.
Putting PR for visibility, might just force-merge this for efficiency

We have a lot of creds sprinkled around our notebooks rn


Rhys addgettingstarteddocs

Hi @RhysSchmidtke, I'm your friendly neighborhood Microsoft Pull Request Bot (You can call me MSBOT). Thanks for your contribution!

It looks like you're a Microsoft contributor (Rhys Schmidtke). If you're full-time, we DON'T require a Contribution License Agreement. If you are a vendor, please DO sign the electronic Contribution License Agreement. It will take 2 minutes and there's no faxing! https://cla.microsoft.com.

TTYL, MSBOT;


add option to shorten prompt print in log

For now, model get big context support, and there is scenario that prompt would be very long, if we also want to kept a eye over the incoming traffic, then there will be huge log created.

Actually, I changed the name back to "max_log_len" since for prompt string, it limits the number of characters instead of tokens.


AS3 does not currently support serverType "generic-host"

Environment

Application Services Version: 3.43.0
BIG-IP Version: 15.1.8

Summary
I'm preparing an AS3 JSON script in VSCode to deploy a GSLB configuration.
I have taken a fully configured GTM and converted the ucs using ACC.
I ran into this issue while going through the configuration of a Server as a generic host.
It appears that the 'serverType' will not accept "generic-host' as a valid value.
Steps To Reproduce
Steps to reproduce the behavior:

Submit the following declaration:

"rtp-gtm-only-external": {
                    "dataCenter": {
                        "use": "/Common/Shared/RTP"
                    },
                    "devices": [
                        {
                            "address": "<IP_ADDRESS>"
                        }
                    ],

                    "proberPool": {
                        "use": "/Common/rtp-prober-pool-psuedo-external"
                    },
                    "proberPreferred": "pool",
                    "serverType": "generic-host",    **<<<---- Here**

Observe the following error response:

While running my cursor over the highlighted value the message states:  "value must be "bigip"
Expected Behavior
The GTM configuration expects either 'generic-host" or "bigip" as valid values.  However the AS3 extension does not.
It Should accept "generic-host"
Actual Behavior
n/a

AND I just noticed that when I change the value for serverType to "bigip" it displays 'value must be "generic-host"
So, this is definitely a BUG

To further illustrate - the inconsistency appears on only two of the four servers that are reflected in the script.
Showing only two of the 4 - but the issue is illustrated.

Working on this issue with @Ronnie110755

Note:
"pathProbeEnabled": false,
"serviceCheckProbeEnabled": false,
"snmpProbeEnabled": false,.

Once removed its fine. Possible ACC logic issue when converting. Sending you a working JSON via email. Chat tomorrow.

Note:
"pathProbeEnabled": false,
"serviceCheckProbeEnabled": false,
"snmpProbeEnabled": false,.

Once removed its fine. Possible ACC logic issue when converting. Sending you a working JSON via email. Chat tomorrow.

Progressing through the updated JSON - dry runs look good with those parameters removed.

Issue resolved and can be closed. Will make improvements in ACC. Defaults not getting converted correctly


How to act linux alpine container as gateway for the host behind the proxy?

How to act linux alpine container as gateway for the host behind the proxy?

I don't quite understand your question, could you please elaborate?

https://raw.githubusercontent.com/ej52/proxmox/main/lxc/nginx-proxy-manager. is not working


Module install fails due to missing-localisation on Windows

I'm currently trying to install Azure on one of our Windows2012 VMs, but the install fails due to a missing localisation variable. If there's anymore information needed to identify the cause of this bug, leave a comment and I'll respond quickly.
It appears to be related to #1874
Steps to reproduce:
Run Install-Module Azure, Install-Module Azure-RM, Install-Module pester, or Find-Module on a particular machine. This doesn't occur on any of our companies other PCs / VMs.
Suspected cause
The cmdlet Install-Package from PowerShellGet as it makes several calls to methods on the variable $LocalizedData. I don't understand why $LocalizedData is undefined.
Expected behaviour
The module should be successfully installed.
Actual behaviour
The following errors occurs:
PS C:\Users\Administrator> install-module pester
WARNING: The variable '$LocalizedData' cannot be retrieved because it has not been set.
PackageManagement\Install-Package : The variable '$LocalizedData' cannot be retrieved because it has not been set.
At C:\Program Files\WindowsPowerShell\Modules\PowerShellGet\PSGet.psm1:1009 char:21
+ ...          $null = PackageManagement\Install-Package @PSBoundParameters
+                      ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
    + CategoryInfo          : InvalidOperation: (LocalizedData:String) [Install-Package], Exception
    + FullyQualifiedErrorId : VariableIsUndefined,Microsoft.PowerShell.PackageManagement.Cmdlets.InstallPackage

PS C:\Users\Administrator> install-module pester

Find-Module

Version    Name                                Repository           Description
-------    ----                                ----------           -----------
2.1.0      AzureRM.profile                     PSGallery            Microsoft Azure PowerShell - Profile credential ...
2.1.0      Azure.Storage                       PSGallery

PS C:\Users\Administrator>

Windows version
WindowsServer 2012
(Get-ItemProperty -Path c:\windows\system32\hal.dll).VersionInfo.FileVersion
6.3.9600.17196 (winblue_gdr.140601-1505)

PowerShell-version
PSVersion:                 5.0.10514.6
WSManStackVersion:         3
SerializationVersion:      <IP_ADDRESS>
CLRVersion:                4.0.30319.42000
BuildVersion:              10.0.10514.6
PSCompatibleVersions:      {1.0, 2.0, 3.0,4.0...}
PSRemotingProtocolVersion: 2.3

@ryangrannell From the error message, it looks like you have very old version of PowerShellGet. Please try with the latest version of PowerShellGet.  There’s a blog topic with the details here.


Add auto-assign workflow for issue comments

Resolves Issue #52

Hey @PranavMasekar I think it would be much better if we can add an in:triage label to it just like in Flutter repo, then the maintainers can decide whom to assign it. Also we are planning to expand the list of maintainers.


Issues with 'az network dns zone import'

Issues with 'az network dns zone import':

Supports the --location parameter.  As with 'create', this should be removed since there is only one supported value, 'global'.

remove location param and default to global

Fixed by PR #1122.


Top1 Acc on ImageNet

Thanks @taoyang1122 for sharing this great repo.
For the result of 67.8% you got for linear classification on pre-trained feature model by SimSiam, is it by the last (90-th) epoch model or the best epoch model?

It is the last epoch model.

It is the last epoch model.

Interesting, what I got is only 65.316% (1 trial). I do not think I changed anything. Can you repeat your results at your end, @taoyang1122 ? Thanks.

Interesting, what I got is only 65.316% (1 trial). I do not think I changed anything. Can you repeat your results at your end, @taoyang1122 ? Thanks.

I can repeat the results.
Can you report your setting and environment? And are you using my provided pre-trained model to do linear evaluation or you first do unsupervised pretraining then do linear evaluation? If you do first do unsupervised pretraining, maybe you can try directly do linear evaluation with my provided model to see which stage went wrong.

I can repeat the results.
Can you report your setting and environment? And are you using my provided pre-trained model to do linear evaluation or you first do unsupervised pretraining then do linear evaluation? If you do first do unsupervised pretraining, maybe you can try directly do linear evaluation with my provided model to see which stage went wrong.

Thanks for the response.
I did both simsiam pretraining and linear classifier trainining at my side.
Indeed, it is a good idea to use your pretrained model. I will do.
The below is the config I used. I use the DP version instead of DDP version which I failed to get work on my machine. Not sure if this is the problem.
| python3 main_simsiam_DP.py
  | --aug-plus
  | --cos
  | -a resnet50
  | --lr 0.1
  | -p 100
  | --epochs 100
  | --batch-size 512
  | # --dist-url 'tcp://localhost:10001'
  | # --multiprocessing-distributed
  | # --world-size 1
  | # --rank 0 \

Thanks for the response.
I did both simsiam pretraining and linear classifier trainining at my side.
Indeed, it is a good idea to use your pretrained model. I will do.
The below is the config I used. I use the DP version instead of DDP version which I failed to get work on my machine. Not sure if this is the problem.
| python3 main_simsiam_DP.py
  | --aug-plus
  | --cos
  | -a resnet50
  | --lr 0.1
  | -p 100
  | --epochs 100
  | --batch-size 512
  | # --dist-url 'tcp://localhost:10001'
  | # --multiprocessing-distributed
  | # --world-size 1
  | # --rank 0 \

For training the linear classification, I used the same config as yours (again I commented DDP):
python3 main_lincls.py
  | -a resnet50
  | --lr 1.6
  | --cos
  | --epochs 90
  | --batch-size 4096
  | -p 100
  | --pretrained /gpfs-volume/train_logs/simsiam/simsiam_checkpoint_0099.pth.tar
  | # --dist-url 'tcp://localhost:10001'
  | # --multiprocessing-distributed
  | # --world-size 1
  | # --rank 0 \

For training the linear classification, I used the same config as yours (again I commented DDP):
python3 main_lincls.py
  | -a resnet50
  | --lr 1.6
  | --cos
  | --epochs 90
  | --batch-size 4096
  | -p 100
  | --pretrained /gpfs-volume/train_logs/simsiam/simsiam_checkpoint_0099.pth.tar
  | # --dist-url 'tcp://localhost:10001'
  | # --multiprocessing-distributed
  | # --world-size 1
  | # --rank 0 \

Sorry, although I implemented the DP version, I didn't really test its performance. The paper says it uses syncBN so maybe DP will cause some issues.
I will remove the DP version, sorry for the confusion. You can try to get the DDP working and I think that should reproduce the results.

Sorry, although I implemented the DP version, I didn't really test its performance. The paper says it uses syncBN so maybe DP will cause some issues.
I will remove the DP version, sorry for the confusion. You can try to get the DDP working and I think that should reproduce the results.

I see. Thanks for letting me know this. It is great to know the reason. I will check the DDP version again.

I see. Thanks for letting me know this. It is great to know the reason. I will check the DDP version again.

DDP version is still a problem for my machine. I often got this error. @taoyang1122 Do you have this issue before? or there are special requirements for cuda driver and package version? Thanks!
-- Process 0 terminated with the following error:
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/torch/multiprocessing/spawn.py",                                                                                line 19, in wrap
fn(i, *args)
File "/home/user/SimSiam_ImageNet/mlp_main_simsiam_ddp.py", line 300, in main                                                                                worker
train(train_loader, model, optimizer, epoch, args)
File "/home/user/SimSiam_ImageNet/mlp_main_simsiam_ddp.py", line 340, in train
z1, p1 = model(images[0])
File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/module.py", line                                                                                541, in call
result = self.forward(*input, **kwargs)
File "/usr/local/lib/python3.7/site-packages/torch/nn/parallel/distributed.py"                                                                                , line 442, in forward
output = self.module(*inputs[0], **kwargs[0])
File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/module.py", line                                                                                541, in call
result = self.forward(*input, **kwargs)
File "/home/user/SimSiam_ImageNet/models/simsiam.py", line 77, in forward
z = self.projection(x)
File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/module.py", line                                                                                541, in call
result = self.forward(*input, **kwargs)
File "/home/user/SimSiam_ImageNet/models/simsiam.py", line 27, in forward
x = self.l1(x)
File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/module.py", line                                                                                541, in call
result = self.forward(*input, **kwargs)
File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/container.py", l                                                                                ine 92, in forward
input = module(input)
File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/module.py", line                                                                                541, in call
result = self.forward(*input, **kwargs)
File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/batchnorm.py", l                                                                                ine 429, in forward
self._check_input_dim(input)
File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/batchnorm.py", l                                                                                ine 417, in _check_input_dim
.format(input.dim()))
ValueError: expected at least 3D input (got 2D input)

DDP version is still a problem for my machine. I often got this error. @taoyang1122 Do you have this issue before? or there are special requirements for cuda driver and package version? Thanks!
-- Process 0 terminated with the following error:
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/torch/multiprocessing/spawn.py",                                                                                line 19, in wrap
fn(i, *args)
File "/home/user/SimSiam_ImageNet/mlp_main_simsiam_ddp.py", line 300, in main                                                                                worker
train(train_loader, model, optimizer, epoch, args)
File "/home/user/SimSiam_ImageNet/mlp_main_simsiam_ddp.py", line 340, in train
z1, p1 = model(images[0])
File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/module.py", line                                                                                541, in call
result = self.forward(*input, **kwargs)
File "/usr/local/lib/python3.7/site-packages/torch/nn/parallel/distributed.py"                                                                                , line 442, in forward
output = self.module(*inputs[0], **kwargs[0])
File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/module.py", line                                                                                541, in call
result = self.forward(*input, **kwargs)
File "/home/user/SimSiam_ImageNet/models/simsiam.py", line 77, in forward
z = self.projection(x)
File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/module.py", line                                                                                541, in call
result = self.forward(*input, **kwargs)
File "/home/user/SimSiam_ImageNet/models/simsiam.py", line 27, in forward
x = self.l1(x)
File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/module.py", line                                                                                541, in call
result = self.forward(*input, **kwargs)
File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/container.py", l                                                                                ine 92, in forward
input = module(input)
File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/module.py", line                                                                                541, in call
result = self.forward(*input, **kwargs)
File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/batchnorm.py", l                                                                                ine 429, in forward
self._check_input_dim(input)
File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/batchnorm.py", l                                                                                ine 417, in _check_input_dim
.format(input.dim()))
ValueError: expected at least 3D input (got 2D input)

No, I don't have this issue. Seems that there is some problem with the input dimension, maybe you can print the input dimension to the encoder and input dimension to the projection MLP to see if it is reasonable.
My Pytorch is 1.7.1, CUDA=11.1, python=3.7, torchvision=0.8.2

No, I don't have this issue. Seems that there is some problem with the input dimension, maybe you can print the input dimension to the encoder and input dimension to the projection MLP to see if it is reasonable.
My Pytorch is 1.7.1, CUDA=11.1, python=3.7, torchvision=0.8.2

Thanks for giving the config of your machine.
Mine is: torch=1.3.0, CUDA=10.1.243, python=2.7.12,  torchvision=0.4.1
Quite away from your config.
As you suggested, I print the shape for the project MLP and it is indeed 2D: batch x feat_dim (2048). It is also the same 2D shape for the DP version. The input looks fine to me. This may be caused by different PyTorch versions. Thanks still!

Thanks for giving the config of your machine.
Mine is: torch=1.3.0, CUDA=10.1.243, python=2.7.12,  torchvision=0.4.1
Quite away from your config.
As you suggested, I print the shape for the project MLP and it is indeed 2D: batch x feat_dim (2048). It is also the same 2D shape for the DP version. The input looks fine to me. This may be caused by different PyTorch versions. Thanks still!

Hi @taoyang1122 I try to use the simsiam model you shared in google drive, named unsuperivsed_petrained.tar. Is it the last epoch output? I cannot load it. Any preprocess needed?
Error is below:
checkpoint = torch.load(args.pretrained, map_location="cpu")
File "/usr/local/lib/python3.7/site-packages/torch/serialization.py", line 426, in load
return _load(f, map_location, pickle_module, **pickle_load_args)
File "/usr/local/lib/python3.7/site-packages/torch/serialization.py", line 599, in _load
raise RuntimeError("{} is a zip archive (did you mean to use torch.jit.load()?)".format(f.name))
RuntimeError: /gpfs-volume/train_logs/simsiam/taoyang_pretrained.tar is a zip archive (did you mean to use torch.jit.load()?)

Hi @taoyang1122 I try to use the simsiam model you shared in google drive, named unsuperivsed_petrained.tar. Is it the last epoch output? I cannot load it. Any preprocess needed?
Error is below:
checkpoint = torch.load(args.pretrained, map_location="cpu")
File "/usr/local/lib/python3.7/site-packages/torch/serialization.py", line 426, in load
return _load(f, map_location, pickle_module, **pickle_load_args)
File "/usr/local/lib/python3.7/site-packages/torch/serialization.py", line 599, in _load
raise RuntimeError("{} is a zip archive (did you mean to use torch.jit.load()?)".format(f.name))
RuntimeError: /gpfs-volume/train_logs/simsiam/taoyang_pretrained.tar is a zip archive (did you mean to use torch.jit.load()?)

I can try to rename it to unsupervised_pretrained.pth.tar.

I can try to rename it to unsupervised_pretrained.pth.tar.

After renamed to .pth.tar at my side, I still cannot load it with the same error.

After renamed to .pth.tar at my side, I still cannot load it with the same error.

That's weird, I don't have such issue. I don't know if it caused by the pytorch version.

That's weird, I don't have such issue. I don't know if it caused by the pytorch version.

Sorry. The problem may be at my side. I can load it on another server. Thanks.

Sorry. The problem may be at my side. I can load it on another server. Thanks.

@taoyang1122 With the pre-trained model you provided and the same parameters (below), I can reach a very similar result for linear evaluation: 67.778%.
| -a resnet50
  | --lr 1.6
  | --cos
  | --epochs 90
  | --batch-size 4096
  | -p 100
  | --pretrained ./taoyang_pretrained.pth.tar
  | --dist-url 'tcp://localhost:10001'
  | --multiprocessing-distributed
  | --world-size 1
  | --rank 0 \

@taoyang1122 With the pre-trained model you provided and the same parameters (below), I can reach a very similar result for linear evaluation: 67.778%.
| -a resnet50
  | --lr 1.6
  | --cos
  | --epochs 90
  | --batch-size 4096
  | -p 100
  | --pretrained ./taoyang_pretrained.pth.tar
  | --dist-url 'tcp://localhost:10001'
  | --multiprocessing-distributed
  | --world-size 1
  | --rank 0 \

Great! You can try to fix the DDP issue and that should be able to reproduce the results from scratch.

Great! You can try to fix the DDP issue and that should be able to reproduce the results from scratch.

How much time did it cost for reproducing this result on ImageNet?


Faster processing

Dear Kelly,
'plotboxpos' works perfect for me.
The problem for me is, it is for my purpose the bottleneck in respect to processing time.
Two of the main time consuming statements are:
temp = axes('Units', 'Pixels', 'Position', pos, 'Visible', 'off', 'parent', hparent);
and
delete(temp);
Both statement use about 60% of the processing time.
Attached you will find a faster Version. It is about 5 times faster in Matlab R2016a and, surprise,  7 times faster in Matlab R2020a.
Changes are only at the end of the code.
May be you want to implement that changes in an updated version.
Best regards from Germany,
Peter
plotboxpos.zip

the next largest processing load is on line 30:
axisPos  = getpixelposition(h);%Takes on my PC with 6000 runs 1.49 seconds
If you replace it by:
set(h,'units','Pixels');
axisPos  = get(h,'Position');
set(h,'units',currunit);
you gain 30% of time . The three lines take with 6000 runs 1.04 seconds


Logger for every request?

Hi I was just wondering if there's a current solution for logging all http requests made to a restivus api?
Thanks!

closing this as I discovered https://github.com/RocketChat/Rocket.Chat/blob/develop/packages/rocketchat-api/server/api.js


fix circular objects in json reporter. Closes #2433

In #2433, @boneskull recommended using jsonStringify() from ./lib/utils, but that function isn't exported by the utils module, and more importantly it isn't actually circular-reference safe.
Instead, I took the custom replacer from this StackOverflow post and added it to the reporter's invocation of JSON.stringify.
The test for this issue is mostly a copy of the 1st json reporter test. It has fewer asserts because there's no way to test for the change to the object that is made by the replacer, but the test does fail without the additional code.

Nice one. I'm not a big fan of the duplication though. Should this be put in its own reusable util function?

There's no duplication here? This one reporter is the only spot I'm aware of with this problem.

IMHO if the version in our util component isn't actually circular-safe we should fix it (or make it a reference to a dependency that's safe), and if it isn't exported it should be, so other components such as reporters can just call on the util function.

hmm, yes, it seems canonicalize() is circular-safe, which is what I thought I was pointing you to.  oops.  but that function is for displaying diffs.

It would seem a public API to output JSON--while avoiding circular references--would be helpful to reporter implementations.  That's tangential to #2433.
Looking more closely at the JSON reporter, it already purports to kill circular references.  The bug is that it doesn't actually succeed in doing this.
The JSON stream reporter works because it doesn't attempt to "stringify" an Error--it just yanks the message and stack properties out.
I think what this PR should do is actually very fine-tuned to this bug.  @jeversmann Can you instead modify errorJSON() or clean() to skip objects it's already seen?
I don't know what the "best" implementation would look like here, but we should retain as much of the Error as is feasible.  We shouldn't take the easy way out and do what the JSON stream reporter does. That would would be a breaking change, and not a bug fix.

I moved the circular object logic into a helper function that's called in clean so it behaves according to the comment above it.
The 'gotcha' here is that Error objects don't JSON.stringify correctly, so formatting test.err is a two-step process which might behave strangely if a test throws an object that isn't an instanceof Error but contains one or more Errors as children. The suggested fix seems to be defining Error.prototype.toJSON but that seems like overkill unless the current method causes problems for anyone.

...might behave strangely if a test throws an object that isn't an  instanceof Error  but contains one or more  Error s as children.

I thought Mocha doesn't accept non-Error failures in the first place?

The problem in #2433 deals specifically with an object whose prototype chain contains Error, but the test I wrote to provoke the circular parsing problem just throws a regular object with a circular reference in it.
I can modify the test to build the thrown object from an Error but the code to handle printing it shouldn't change.

Yeah, I'm not too concerned with having a test that focuses on the circular reference thing without worrying about rigging up a "real" Error; I just wasn't sure how the comment about handling the case of Error as a member of non-Error objects was relevant. Sorry for any confusion!

@boneskull This is still labeled as pr-needs-work, but I think I've addressed the feedback.
The bot is right that this PR has become stale, but #2433 is still around, so I'd rather merge this in.

@jeversmann thanks for the heads-up.  someone will take a look at this, maybe even me!

Hey! I've stumbled upon this situation myself and the proposed commits seem to resolve the issue for me.
Do you plan on merging this pull request sometime? Is this PR missing anything that prevents it from being mergable?

continued in #3318.  thanks

landed in https://github.com/mochajs/mocha/commit/741b0bd4eff23b2388b605c8f4cda99d2d7ea38a


hmc-351: add dockerfile for local dev

This PR resolves https://github.com/Mirantis/hmc/issues/351 by adding Dockerfile to allow local update/ development on the docs code base.

Hi @a13x5 ,  I accidentally delete my fork, will re-issue a similar PR with the correction, soon.


As a user, I should see at least one result for all possible filters

Some filters on the site don't return any results. On the Items page, selecting the "Quest Items" filter does not match any items.

Estimated Time: 2 hours


Fix a bug in non-English character handling

Convert unicode formatted characters into normal java characters using Properties#{put,get}.
Specify chartset to write in explicitly and in the pom.xml for safety (basically, this doesn't fix the problem by itself, though).
Improve a handling of unnamed module name.

This fixed Issue-#19


Ticino showing on map even though it is inactive

Search for "Ticino" dojo in Switzerland, it doesn't show up in the list beneath the map but it does appear on the map, even though it is inactive! http://zen.coderdojo.com/dojo/ch/ticino/ticino/ticino

@tangentfairy Hi, I've submitted a pull request to fix this issue, just dawned on me that I maybe should have lifted the issue 1st, Apologies.

Thanks @orrwil - I tested it and it works. I'm just wondering if you managed to test this locally?
I see that you have forked cp-zen-platform but not cp-local-development.

@tangentfairy I'm a bit new to a lot of this so might have made a few errors along the way. I originally just cloned cp-local-development to my laptop. I did get the local setup running, although there were some errors populating the db and I had to run the script (dojos.sql) again manually.  I was able to successfully test my change locally but my commits were producing errors, that I assumed were configuration issues, so I ended up submitting the change from another computer. Hope this makes sense?

@orrwil I see - if you still have problems then make sure to join the Gitter! Thank you for the pull request :)

This is live now, thank you!