Strawman: FastAPI model server

This is potential design that could hit three interconnected birds with one stone:

🐣 #193
🐥 #205
🐔 #259

Those tickets contain user data and requirements. Please read them for context.
This is a strawman. It is most likely wrong. Please attack with your sharpest pitchforks!
Model definition
The model API is specified using Pydantic types in the predict function.
import cog
from pathlib import Path
from pydantic import Field
import torch

class Predictor(cog.Predictor):
    def setup(self):
        self.net = torch.load("weights.pth")

    def predict(
        self,
        input: Path = Field(..., title="Image to enlarge"),
        scale: float = Field(1.5, description="Factor to scale image by"),
    ) -> Path:
        """Run a single prediction on the model"""
        # ... pre-processing ...
        output = self.net(input)
        # ... post-processing ...
        return output

You could imagine some custom types like cog.Field if we need custom behavior, or don't want the extra import.
This predictor serves:
GET /predict
Takes a JSON object in request body:
{
  "input": "https://bucket.s3.amazon.com/...", # or "data:foo/bar;base64,..."
  "scale": 1.7,
}

Returns:
{
  "output": "https://bucket.s3.amazon.com/..."
}

Everything is JSON. Files are represented as URLs -- HTTP, cloud storage, data: URLs, or perhaps even file:// for mounted storage. This is for simplicity, so it can be represented sensibly in OpenAPI, and so more complex data structures can be represented.
If a more complex Pydantic object was defined as the return value, output would be a JSON object. The root object can also include other information about the run -- some prior art in #259 might be informative about what we want to include (metrics, etc).
Authentication and configuration for cloud storage needs some thought. It could specify a prefix for storing output files in the request.
GET /docs
A Swagger UI, generated automatically by FastAPI.
GET /openapi.json
An OpenAPI definition, generated automatically by FastAPI. This is used as the type definition. It contains a complete documentation of the HTTP API and entries like this to define the types for input/output:
{
  "components": {
    "schemas": {
      "Input": {
        "title": "Input",
        "required": [
          "input"
        ],
        "type": "object",
        "properties": {
          "input": {
            "title": "Image to enlarge",
            "type": "string",
            "format": "path"
          },
          "scale": {
            "title": "Scale",
            "type": "number",
            "description": "Factor to scale image by",
            "default": 1.5
          }
        }
      },
      "Output": ...
    }
  }
}

How this would be used for Replicate
We could either:

Integrate with existing redis queue worker.
Run a sidecar container that converts the current Redis API into HTTP.

Over time, we could define a queue API and include that in Cog. (Or leave it as an external system. See discussion in #259.)
Files
Files are represented as URLs. data:, http:, gcs:, s3:, etc.
This works well for input, but some way of specifying where output files go is required. Predictions could produce arbitrary output files (or should they be able to?) so some generic way of defining where multiple files can go is needed. For filesystem or bucket, this could be a prefix, and the prediction is responsible for naming files such that they don't collide.
Perhaps prediction requests could include the output path prefix:
{
  "input": {"image": "s3://predictions/1/input/image.jpg"},
  "output_path": "s3://predictions/1/output/",
}

~For Replicate, files could be fetched and uploaded from Cloud Storage using signed URLs with a prefix.~ Unfortunately signed URLs can't be made for prefixes. You can assign IAM permissions for a prefix, but that would mean a service account for each prediction, which is unwieldy.
Some potential solutions:

We use serving's existing file storage system
We send files directly back to replicate-web, bypassing serving's file storage system. Perhaps if
We use data URIs...?!

Future

An asynchronous API, where a job is started and you can query the status of the job. (This might be required for passing logs to Replicate?)
This request/response can be passed over a queue. The same type definition could be used.
How would do we support gRPC? Would we want to generate a generic protobuf schema that supports any kind of model, or generate one per-model somehow?
We might want a more FastAPI-like API instead of the class-based Predictor.
Custom URL routes on the FastAPI server. These might be namespaced under /extensions to preserve the stability of the top-level API.

Reflection
FastAPI is very HTTP + JSON centric. OpenAPI is too. This is optimal for simple use-cases, but using more advanced/efficient systems like gRPC or queues may feel like an impedance mismatch.
Implementation details
The predictor in the example above would be converted into a FastAPI method like this:
app = FastAPI()

class Input(BaseModel):
    input = Path = Field(..., title="Image to enlarge")
    scale = float = Field(1.5, description="Factor to scale image by")

@app.post("/predict")
async def predict(input: Input):
    # ...
    return Path(...)

We would need to come up with a custom Path handler that knows how to convert it into URLs or base64 encoded strings.

Thanks for putting this together!
Throwing some forks at this strawman:

FastAPI can return files as FileResponse or StreamingResponse. How would you return multiple files?

multipart/form-data seems like a reasonable approach (see https://github.com/replicate/cog/pull/328), but I'm not sure that's supported in FastAPI.

I assume FastAPI's StreamingResponse can handle files of arbitrary size, and only keeps small chunks in memory?
How would we implement progressive outputs?
How would we capture logs from setup() and predict()?
Would this API still allow you to import a cog.Predictor in a plain Python project and call p = Predictor(); p.setup(); p.predict(...)?
How can models be adapted for AI Platform, Cloud Dataflow, Seldon, etc., where k8s sidecars aren't applicable?

Can we design our API with plugin capabilities from the start, so we don't have to do another major redesign when we want to deploy Cog models on non-k8s targets?
Perhaps the queue worker could be implemented using some adapter pattern that lives outside of the main Predictor class?

FastAPI can return files as FileResponse or StreamingResponse. How would you return multiple files?

Everything is JSON. Files are represented as URLs -- HTTP, cloud storage, data: URLs, or perhaps even file:// for mounted storage.
This is for simplicity, so it can be represented sensibly in OpenAPI, and so more complex data structures can be represented.
We have user data here -- we fetch and store files on cloud storage, and two of our users is requesting it works this way too.
See GET /predict for more detail.

How would we implement progressive outputs?

An asynchronous API -- see "future". Lambdas could be used as they current are. In addition, we could represent progressive output as a list of outputs in the response so it is persistent and consistent.

How would we capture logs from setup() and predict()?

Like we currently do, with an asynchronous API I expect. See "future".

Would this API still allow you to import a cog.Predictor in a plain Python project and call p = Predictor(); p.setup(); p.predict(...)?

Yeah, I don't think anything's going to change there.

How can models be adapted for AI Platform, Cloud Dataflow, Seldon, etc., where k8s sidecars aren't applicable?

This is touched on in #259.

 You now want to classify all those images, as well as new images that come in to your service.
You find a permissively licensed image classifier model on Replicate that is perfect for this feature. You now want to download that model and run a massive batch job over all your existing images, as well as process new images that come in from your users.
You decide to use Cloud Dataflow for batch processing of existing images and AI Platform Serving for new images. How do you adapt the Cog model on Replicate so that it can be deployed on Dataflow and AI Platform?
As a thought experiment, how would you do this if the model were a simple trained scikit-learn model? In that case you could make two Docker images, one for Dataflow and one for AI Platform, that wrapped the scikit-learn model in a bit of boilerplate to implement the APIs. That boilerplate could be abstracted out into some "sklearn-deployment" library where you just pass a predictor and it figures it all out: sklearn_deployment.serve_ai_platform(my_sklearn_predictor).
If you want to read from GCS and write to BigTable, you could provide input and output handlers:
sklearn_deployment.serve_ai_platform(my_sklearn_predictor) \
    .with_input_handler(sklearn_deployment.google.cloud_storage) \
    .with_output_handler(sklearn_deployment.google.bigtable)

Since Cog models are tied to their environments, it's more complicated. But perhaps we (and the community) could provide Cog-aware libraries for serving Cog models in different environments, of which a FastAPI server is one instance.
Here's a strawman for this kind of architecture where the user provides a "server" class and input and output handlers in cog.yaml:
build:
  ...
predict: predict.py:Predictor
serve:
  server: FastAPI
  input_handler: google.gcs
  output_handler: google.big_table

This means that we'd be forced to decouple the model interface from the serving interface.

Agreed we should figure out a way of supporting multiple deployment environments. This is mostly relevant to #259 and discussed a bit in there, but I'll continue this here.
At a high-level, model packaging should be independent of model deployment. A researcher should be able to package a model and it should be able to be deployed anywhere.
This implies that the deployment configuration should happen after a model is packaged. In an ideal world, this would simply be done with a sidecar, where the standard interface on the researcher's model was translated into whatever system they have running.
But as you suggest, there are platforms like AI Platform where things need to be shipped as a single Docker container. So, at some point, we need some way adding a different interface inside a model that has already been created.
The question in my mind: does this abstraction live at the Python level or the HTTP level? You could imagine two ways of implementing this:

An additional Python library is added that imports Predictor translates it to the other API.
An additional binary entrypoint is added to the container that translates the HTTP API to the other API.

A few additional thoughts:

I wonder whether we can defer this, but keep it in mind. Right now our user needs are a queue-based API (for us and one user) and an asynchronous HTTP API, all of which are able to run sidecars. We could build for that, with some kind of more generic system in mind.
I wonder whether there is prior art here. What systems is this similar to?

Wheee we did this ages ago


Resize FullCalendar views to fill screens

Right now the month view on mobile doesn't take advantage of the portrait aspect ratio, so a lot of information is lost.
I've found a bit of info on resizing fullcalendar:

https://stackoverflow.com/questions/5191616/how-can-i-auto-fit-fullcalendar-into-a-specified-div-space
https://stackoverflow.com/questions/9982045/fullcalendar-resize-calendar-on-window-resize

Unless this is a quick fix, @audreywl, I think we should just wait until my ultra-responsive-calendar is in beta.


[zh] sync device-plugins.md

Sync with en.
content/zh-cn/docs/concepts/extend-kubernetes/compute-storage-net/device-plugins.md

Looks weird currently:

/lgtm
/approve


How to write fmp4?

Hello,
I am currently researching your Rust library and have come across the read_fragment_header() function in the Reader. However, I noticed that there doesn’t seem to be a corresponding function in the Writer for writing the header data.
Could you please provide some guidance on how to use the Writer to write the corresponding data? Is there a specific function or method that I should use, or is this functionality integrated into another function?
Thank you for your time and assistance.

how set mp4 flags like ffmpeg, for web video tag player? -movflags frag_keyframe+empty_moov+default_base_moof


Add documentation for the new config format

Closed this PR due to 6 months inactivity. Reopen if needed.


[Access Request]  page 41 "Sales Quote" EnableBillToCustomerNo

Could you please change the variable EnableBillToCustomerNo on the page  "Sales Quote" to protected that we can use this value for our own fields as property value?

Thanks for reporting this. We agree, and we’ll publish a fix asap, either in an update for the current version or in the next major release. Please do not reply to this, as we do not monitor closed issues. If you have follow-up questions or requests, please create a new issue where you reference this one.


9 - delay the display of keyboard statuses

When a player submits their row guess an animation that last 2.5 seconds is played so it slowly reveals the letters and if they have been successful or not.
However the keyboard letter statuses are displayed immediately.  The keyboard letter statuses should only be revealed once the animation of the tile letters has completed.

#25 :+1:


Update conferences2020.yml

https://twitter.com/brightonruby/status/1238407268141498368
https://mailchi.mp/27de177b76f0/its-going-to-have-to-be-different

Thanks for the update. Stay safe. Responsible decision.


Fix unsynchronized access to stats holder.record()

StatisticsHolder.record() is meant to be called as each operation
is finishing, to record the time spent, etc. It modifies the
underlying Histogram object, which is not thread safe. Under enough
load, strange errors crop up without the synch.

Do not merge this; it is too disruptive. I'll do a separate fix involving a per thread histogram and histogram aggregation instead.

OK, now this is correct. Or at least closer. Works wonderfully.

final added.


Elasticsearch-curator to be able to curate logs depending on % of drive used

Current implementation of elasticsearch-curator allows to use days for deleting logs.
kind: configuration/elasticsearch-curator
title: "ElasticSearch curator"
name: default
specification:
  indices_retention_days: 30
  debian_curator_version: "5.5.4_amd64"
  redhat_curator_version: "5.5.4-1.x86_64"

Introduce functionality to allow user to specify percentage of hard disk to use for logs.
Like:
indices_drive_usage_percent: 60%

There is no easy method to implement indices deleting based on % of disk usage, since ES Curator do not provide such functionality out of the box. In order to provide flexible and easy to maintain configuration of ES Curator cron jobs, it was decided to fully based on ES Curator filters. Among them, there is a filter of type space, which allows to retain indices based on disk consumption. See PR #763.


chore: import repository https://github.com/serverless-bot-726/twitter-dashboard-ui.git

this commit will trigger a pipeline to generate the CI/CD configuration which will create a second commit on this Pull Request before it auto merges

[APPROVALNOTIFIER] This PR is NOT APPROVED
This pull-request has been approved by:
To complete the pull request process, please assign
You can assign the PR to them by writing /assign  in a comment when ready.
The full list of commands accepted by this bot can be found here.

Needs approval from an approver in each of these files:

OWNERS

Approvers can indicate their approval by writing /approve in a comment
Approvers can cancel approval by writing /approve cancel in a comment

/approve


[BUG] Problem Pre-populating form text fields on page 2

Environment

Formio.js version: 4.0.0-rc.7
Frontend framework: ReactJS
Browser: Chrome
Browser version: Chrome 75

Steps to Reproduce

Create a form in form.io with Display as Wizard.
Make the form having multiple pages.
Have a textfield in the first page, and another textfield in the second page.
Embed the form in a React app (create react app)
Have a submission data with the two textfield (For the first and second page).

Expected behavior
Both textfield should have a value that is passed through submission
Observed behavior
Only the text field in the First Page has a value.
JSON format of the form:
https://lznmvamfenxirgd.form.io/reactformsimple
Here is a screenshot of the UI.

Here is a code snippet of how I embedded the Form component of Form.IO
import React, { useEffect, useState } from 'react';
import { Form } from 'react-formio';

const App = () => {
  return (
    <div style={{ marginLeft: '50px', marginRight: '50px', marginTop: '50px' }}>
      <Form src={FORM_IO_URL}
        submission={{
          data: {
            firstPageTextField: 'First Page Value',
            secondPageTextField: 'Second Page Value',
          }
        }}
      />
    </div>
  );
}

PS: Other input fields such as Checkbox and Radio Field on the second page doesn't have any problem.
Thank you

This issue is resolved on the latest version of formio.js (4.4.2).


[HaskellNG] Missing glib >=<IP_ADDRESS> && <0.14

While trying to build gio, I get "Missing glib >=<IP_ADDRESS> && <0.14". I use the following system:
haskellEnvDemo definition
    haskellEnvDemo = pkgs.haskellngPackages.ghcWithPackages (p: with p; [
      gio
    ]);

bleeding definition
NIX_PATH=$NIX_PATH:bleeding=/root/nixpkgs

alias bleeding='nix-env -f "<bleeding>"'

[root@brainstorm:~/nixpkgs]# git log | head -n 1
commit 02e7a4d403798f3bdfe92283066f227732f886c8

missing glib >=<IP_ADDRESS> && <0.14
λ bleeding -iA haskellEnvDemo
replacing old ‘ghc-7.8.4’
installing ‘ghc-7.8.4’
download-from-binary-cache.pl: binary cache ‘http://hydra.cryp.to’ is not trusted (please add it to ‘trusted-binary-caches’ in /etc/nix/nix.conf)
these derivations will be built:
  /nix/store/f3rcx1x3nn2sa5pc4mbllifi4znk27hf-haskell-gio-<IP_ADDRESS>.drv
  /nix/store/pn0s67xzydv7z0k2s3vx1kfxj06slww6-ghc-7.8.4.drv
building path(s) ‘/nix/store/25mx4pgpvpcsn7qhldsllbypy180q48r-haskell-gio-<IP_ADDRESS>’
building /nix/store/25mx4pgpvpcsn7qhldsllbypy180q48r-haskell-gio-<IP_ADDRESS>
setupCompilerEnvironmentPhase
Building with /nix/store/cq4qqjii3s9ghr6p59kkrdf44wnyhpp4-ghc-7.8.4.
unpacking sources
unpacking source archive /nix/store/rm6jrh3nhdra3z9i2anc3frqiiq7kn2k-gio-<IP_ADDRESS>.tar.gz
source root is gio-<IP_ADDRESS>
patching sources
jailbreakPhase
compileBuildDriverPhase
setupCompileFlags: -package-db=/tmp/nix-build-haskell-gio-<IP_ADDRESS>.drv-0/package.conf.d -j1
[1 of 2] Compiling SetupWrapper     ( SetupWrapper.hs, /tmp/nix-build-haskell-gio-<IP_ADDRESS>.drv-0/SetupWrapper.o )
[2 of 2] Compiling Main             ( Setup.hs, /tmp/nix-build-haskell-gio-<IP_ADDRESS>.drv-0/Main.o )
Linking Setup ...
configuring
configureFlags: --verbose --prefix=/nix/store/25mx4pgpvpcsn7qhldsllbypy180q48r-haskell-gio-<IP_ADDRESS> --libdir=$prefix/lib/$compiler --libsubdir=$pkgid --with-gcc=cc --package-db=/tmp/nix-build-haskell-gio-<IP_ADDRESS>.drv-0/package.conf.d --ghc-option=-optl=-Wl,-rpath=/nix/store/25mx4pgpvpcsn7qhldsllbypy180q48r-haskell-gio-<IP_ADDRESS>/lib/ghc-7.8.4/gio-<IP_ADDRESS> --enable-split-objs --disable-library-profiling --enable-shared --enable-library-vanilla --enable-executable-dynamic --enable-tests --extra-include-dirs=/nix/store/5b38bh8arsmn8dxyk0cxl8fy73wyq6sb-glib-2.42.1/include --extra-lib-dirs=/nix/store/5b38bh8arsmn8dxyk0cxl8fy73wyq6sb-glib-2.42.1/lib --extra-include-dirs=/nix/store/1wckfzjh15azhw5bxrbrsbzrjklmsr82-pcre-8.36/include --extra-lib-dirs=/nix/store/1wckfzjh15azhw5bxrbrsbzrjklmsr82-pcre-8.36/lib --extra-include-dirs=/nix/store/a2p5i9hb5hpqssh7vp402r6n9slfayqx-zlib-1.2.8/include --extra-lib-dirs=/nix/store/a2p5i9hb5hpqssh7vp402r6n9slfayqx-zlib-1.2.8/lib --extra-include-dirs=/nix/store/ryh3xlyylb59awppkpd1q9kzbpb8d870-libffi-3.0.13/include --extra-lib-dirs=/nix/store/ryh3xlyylb59awppkpd1q9kzbpb8d870-libffi-3.0.13/lib --extra-lib-dirs=/nix/store/ryh3xlyylb59awppkpd1q9kzbpb8d870-libffi-3.0.13/lib64
[1 of 2] Compiling Gtk2HsSetup      ( Gtk2HsSetup.hs, dist/setup-wrapper/Gtk2HsSetup.o )
[2 of 2] Compiling Main             ( SetupMain.hs, dist/setup-wrapper/Main.o )
Linking dist/setup-wrapper/setup ...
Configuring gio-<IP_ADDRESS>...
setup: At least the following dependencies are missing:
glib >=<IP_ADDRESS> && <0.14
builder for ‘/nix/store/f3rcx1x3nn2sa5pc4mbllifi4znk27hf-haskell-gio-<IP_ADDRESS>.drv’ failed with exit code 1
cannot build derivation ‘/nix/store/pn0s67xzydv7z0k2s3vx1kfxj06slww6-ghc-7.8.4.drv’: 1 dependencies couldn't be built
error: build of ‘/nix/store/pn0s67xzydv7z0k2s3vx1kfxj06slww6-ghc-7.8.4.drv’ failed

Just in case,
gio' = doJailbreak pkgs.haskellngPackages.gio;
haskellEnvDemo = pkgs.haskellngPackages.ghcWithPackages (p: with p; [
  gio'
]);

Results in
replacing old ‘ghc-7.8.4’
installing ‘ghc-7.8.4’
download-from-binary-cache.pl: binary cache ‘http://hydra.cryp.to’ is not trusted (please add it to ‘trusted-binary-caches’ in /etc/nix/nix.conf)
these derivations will be built:
  /nix/store/0qh4jfkfyn8cn0rc9c0r715pbmqc6f1g-haskell-language-c-0.4.7.drv
  /nix/store/zayh0gkdxv6gbmblfzz3dnck469rf5y4-haskell-newtype-0.2.drv
  /nix/store/np0gkq4ypn4f060d513p78p6bdzp0hk8-haskell-constraints-<IP_ADDRESS>.drv
  /nix/store/z74xdy8rr901mhpn8y32mn12sqr15xc7-haskell-lifted-async-<IP_ADDRESS>.drv
  /nix/store/di75nskpdyfg3s9flvl27qmbqwjmrh54-haskell-shelly-1.6.0.drv
  /nix/store/4paji8w16n8bszj00x48c9gc5yzjm07f-c2hs-0.21.1.drv
  /nix/store/bxz380wr6v8g02nl18n620hirf7ss3sh-haskell-ncurses-0.2.11.drv
  /nix/store/wrf8sll3z1jvphfp1z7ij9ayp0gywjpi-haskell-gio-<IP_ADDRESS>.drv
  /nix/store/2vmcyrb4blh5l7j6qr15c2xhnl4d32v0-ghc-7.8.4.drv
building path(s) ‘/nix/store/ayq1h7zcvyd7p5bjpc7qy2wz3j5qlnrn-haskell-gio-<IP_ADDRESS>’
building path(s) ‘/nix/store/8yxbf9mai1q945y8wyws208n353wx536-haskell-language-c-0.4.7’
building path(s) ‘/nix/store/sxvhi3f57c6sf5w34w1qzdm6p2s0hbvv-haskell-newtype-0.2’
building /nix/store/8yxbf9mai1q945y8wyws208n353wx536-haskell-language-c-0.4.7
setupCompilerEnvironmentPhase
Building with /nix/store/cq4qqjii3s9ghr6p59kkrdf44wnyhpp4-ghc-7.8.4.
building /nix/store/sxvhi3f57c6sf5w34w1qzdm6p2s0hbvv-haskell-newtype-0.2
setupCompilerEnvironmentPhase
Building with /nix/store/cq4qqjii3s9ghr6p59kkrdf44wnyhpp4-ghc-7.8.4.
building /nix/store/ayq1h7zcvyd7p5bjpc7qy2wz3j5qlnrn-haskell-gio-<IP_ADDRESS>
setupCompilerEnvironmentPhase
Building with /nix/store/cq4qqjii3s9ghr6p59kkrdf44wnyhpp4-ghc-7.8.4.
unpacking sources
unpacking source archive /nix/store/5gdd3i336kazi25mhmr435xk7d123j16-language-c-0.4.7.tar.gz
source root is language-c-0.4.7
patching sources
jailbreakPhase
compileBuildDriverPhase
setupCompileFlags: -package-db=/tmp/nix-build-haskell-language-c-0.4.7.drv-0/package.conf.d -j1
unpacking sources
unpacking source archive /nix/store/xpsfyhva3g4gk288xn7z4n9kjr41w3sg-newtype-0.2.tar.gz
unpacking sources
source root is newtype-0.2
unpacking source archive /nix/store/rm6jrh3nhdra3z9i2anc3frqiiq7kn2k-gio-<IP_ADDRESS>.tar.gz
patching sources
jailbreakPhase
source root is gio-<IP_ADDRESS>
compileBuildDriverPhase
patching sources
setupCompileFlags: -package-db=/tmp/nix-build-haskell-newtype-0.2.drv-0/package.conf.d -j1
jailbreakPhase
Running jailbreak-cabal to lift version restrictions on build inputs.
compileBuildDriverPhase
setupCompileFlags: -package-db=/tmp/nix-build-haskell-gio-<IP_ADDRESS>.drv-0/package.conf.d -j1
[1 of 1] Compiling Main             ( Setup.hs, /tmp/nix-build-haskell-language-c-0.4.7.drv-0/Main.o )
[1 of 1] Compiling Main             ( Setup.hs, /tmp/nix-build-haskell-newtype-0.2.drv-0/Main.o )
[1 of 2] Compiling SetupWrapper     ( SetupWrapper.hs, /tmp/nix-build-haskell-gio-<IP_ADDRESS>.drv-0/SetupWrapper.o )
Linking Setup ...
Linking Setup ...
[2 of 2] Compiling Main             ( Setup.hs, /tmp/nix-build-haskell-gio-<IP_ADDRESS>.drv-0/Main.o )
Linking Setup ...
configuring
configureFlags: --verbose --prefix=/nix/store/ayq1h7zcvyd7p5bjpc7qy2wz3j5qlnrn-haskell-gio-<IP_ADDRESS> --libdir=$prefix/lib/$compiler --libsubdir=$pkgid --with-gcc=cc --package-db=/tmp/nix-build-haskell-gio-<IP_ADDRESS>.drv-0/package.conf.d --ghc-option=-optl=-Wl,-rpath=/nix/store/ayq1h7zcvyd7p5bjpc7qy2wz3j5qlnrn-haskell-gio-<IP_ADDRESS>/lib/ghc-7.8.4/gio-<IP_ADDRESS> --enable-split-objs --disable-library-profiling --enable-shared --enable-library-vanilla --enable-executable-dynamic --enable-tests --extra-include-dirs=/nix/store/5b38bh8arsmn8dxyk0cxl8fy73wyq6sb-glib-2.42.1/include --extra-lib-dirs=/nix/store/5b38bh8arsmn8dxyk0cxl8fy73wyq6sb-glib-2.42.1/lib --extra-include-dirs=/nix/store/1wckfzjh15azhw5bxrbrsbzrjklmsr82-pcre-8.36/include --extra-lib-dirs=/nix/store/1wckfzjh15azhw5bxrbrsbzrjklmsr82-pcre-8.36/lib --extra-include-dirs=/nix/store/a2p5i9hb5hpqssh7vp402r6n9slfayqx-zlib-1.2.8/include --extra-lib-dirs=/nix/store/a2p5i9hb5hpqssh7vp402r6n9slfayqx-zlib-1.2.8/lib --extra-include-dirs=/nix/store/ryh3xlyylb59awppkpd1q9kzbpb8d870-libffi-3.0.13/include --extra-lib-dirs=/nix/store/ryh3xlyylb59awppkpd1q9kzbpb8d870-libffi-3.0.13/lib --extra-lib-dirs=/nix/store/ryh3xlyylb59awppkpd1q9kzbpb8d870-libffi-3.0.13/lib64
configuring
configureFlags: --verbose --prefix=/nix/store/8yxbf9mai1q945y8wyws208n353wx536-haskell-language-c-0.4.7 --libdir=$prefix/lib/$compiler --libsubdir=$pkgid --with-gcc=cc --package-db=/tmp/nix-build-haskell-language-c-0.4.7.drv-0/package.conf.d --ghc-option=-optl=-Wl,-rpath=/nix/store/8yxbf9mai1q945y8wyws208n353wx536-haskell-language-c-0.4.7/lib/ghc-7.8.4/language-c-0.4.7 --enable-split-objs --disable-library-profiling --enable-shared --enable-library-vanilla --enable-executable-dynamic --enable-tests
configuring
configureFlags: --verbose --prefix=/nix/store/sxvhi3f57c6sf5w34w1qzdm6p2s0hbvv-haskell-newtype-0.2 --libdir=$prefix/lib/$compiler --libsubdir=$pkgid --with-gcc=cc --package-db=/tmp/nix-build-haskell-newtype-0.2.drv-0/package.conf.d --ghc-option=-optl=-Wl,-rpath=/nix/store/sxvhi3f57c6sf5w34w1qzdm6p2s0hbvv-haskell-newtype-0.2/lib/ghc-7.8.4/newtype-0.2 --enable-split-objs --disable-library-profiling --enable-shared --enable-library-vanilla --enable-executable-dynamic --enable-tests
[1 of 2] Compiling Gtk2HsSetup      ( Gtk2HsSetup.hs, dist/setup-wrapper/Gtk2HsSetup.o )
Configuring newtype-0.2...
Dependency base >=3.0 && <6: using base-<IP_ADDRESS>
Configuring language-c-0.4.7...
Flags chosen: separatesyb=True, usebytestrings=True, splitbase=True
Dependency array -any: using array-<IP_ADDRESS>
Dependency base ==4.*: using base-<IP_ADDRESS>
Dependency bytestring >=0.9.0: using bytestring-<IP_ADDRESS>
Dependency containers -any: using containers-<IP_ADDRESS>
Dependency directory -any: using directory-<IP_ADDRESS>
Dependency filepath -any: using filepath-<IP_ADDRESS>
Dependency pretty -any: using pretty-<IP_ADDRESS>
Dependency process -any: using process-<IP_ADDRESS>
Dependency syb -any: using syb-0.4.4
[2 of 2] Compiling Main             ( SetupMain.hs, dist/setup-wrapper/Main.o )
Linking dist/setup-wrapper/setup ...
/nix/store/cq4qqjii3s9ghr6p59kkrdf44wnyhpp4-ghc-7.8.4/bin/ghc --info
Using Cabal-<IP_ADDRESS> compiled by ghc-7.8
Using compiler: ghc-7.8.4
Using install prefix:
/nix/store/sxvhi3f57c6sf5w34w1qzdm6p2s0hbvv-haskell-newtype-0.2
Binaries installed in:
/nix/store/sxvhi3f57c6sf5w34w1qzdm6p2s0hbvv-haskell-newtype-0.2/bin
Libraries installed in:
/nix/store/sxvhi3f57c6sf5w34w1qzdm6p2s0hbvv-haskell-newtype-0.2/lib/ghc-7.8.4/newtype-0.2
Private binaries installed in:
/nix/store/sxvhi3f57c6sf5w34w1qzdm6p2s0hbvv-haskell-newtype-0.2/libexec
Data files installed in:
/nix/store/sxvhi3f57c6sf5w34w1qzdm6p2s0hbvv-haskell-newtype-0.2/share/x86_64-linux-ghc-7.8.4/newtype-0.2
Documentation installed in:
/nix/store/sxvhi3f57c6sf5w34w1qzdm6p2s0hbvv-haskell-newtype-0.2/share/doc/x86_64-linux-ghc-7.8.4/newtype-0.2
Configuration files installed in:
/nix/store/sxvhi3f57c6sf5w34w1qzdm6p2s0hbvv-haskell-newtype-0.2/etc
No alex found
Using ar found on system at:
/nix/store/wr5c9d4mjb4c7gqvpv2qzg2z4h4lry17-binutils-2.23.1/bin/ar
No c2hs found
No cpphs found
No ffihugs found
Using gcc version 4.8.4 given by user at:
/nix/store/ng41cx2qbqmr81b4cvxvm9qi80kbasv0-gcc-wrapper-4.8.4/bin/cc
Using ghc version 7.8.4 found on system at:
/nix/store/cq4qqjii3s9ghr6p59kkrdf44wnyhpp4-ghc-7.8.4/bin/ghc
Using ghc-pkg version 7.8.4 found on system at:
/nix/store/cq4qqjii3s9ghr6p59kkrdf44wnyhpp4-ghc-7.8.4/bin/ghc-pkg
No greencard found
Using haddock version 2.14.3 found on system at:
/nix/store/cq4qqjii3s9ghr6p59kkrdf44wnyhpp4-ghc-7.8.4/bin/haddock
No happy found
No hmake found
Using hpc version 0.67 found on system at:
/nix/store/cq4qqjii3s9ghr6p59kkrdf44wnyhpp4-ghc-7.8.4/bin/hpc
Using hsc2hs version 0.67 found on system at:
/nix/store/cq4qqjii3s9ghr6p59kkrdf44wnyhpp4-ghc-7.8.4/bin/hsc2hs
Using hscolour version 1.20 found on system at:
/nix/store/1x496nh8iyy1264vczbqjfawhq4glv29-hscolour-1.20.3/bin/HsColour
No hugs found
No jhc found
Using ld found on system at:
/nix/store/ng41cx2qbqmr81b4cvxvm9qi80kbasv0-gcc-wrapper-4.8.4/bin/ld
No lhc found
No lhc-pkg found
No nhc98 found
No pkg-config found
Using ranlib found on system at:
/nix/store/wr5c9d4mjb4c7gqvpv2qzg2z4h4lry17-binutils-2.23.1/bin/ranlib
Using strip found on system at:
/nix/store/wr5c9d4mjb4c7gqvpv2qzg2z4h4lry17-binutils-2.23.1/bin/strip
Using tar found on system at:
/nix/store/k9ama576yfrfx1837rg4rrilma8pnwks-gnutar-1.27.1/bin/tar
No uhc found
building
/nix/store/cq4qqjii3s9ghr6p59kkrdf44wnyhpp4-ghc-7.8.4/bin/ghc --info
Using Cabal-<IP_ADDRESS> compiled by ghc-7.8
Using compiler: ghc-7.8.4
Using install prefix:
/nix/store/8yxbf9mai1q945y8wyws208n353wx536-haskell-language-c-0.4.7
Binaries installed in:
/nix/store/8yxbf9mai1q945y8wyws208n353wx536-haskell-language-c-0.4.7/bin
Libraries installed in:
/nix/store/8yxbf9mai1q945y8wyws208n353wx536-haskell-language-c-0.4.7/lib/ghc-7.8.4/language-c-0.4.7
Private binaries installed in:
/nix/store/8yxbf9mai1q945y8wyws208n353wx536-haskell-language-c-0.4.7/libexec
Data files installed in:
/nix/store/8yxbf9mai1q945y8wyws208n353wx536-haskell-language-c-0.4.7/share/x86_64-linux-ghc-7.8.4/language-c-0.4.7
Documentation installed in:
/nix/store/8yxbf9mai1q945y8wyws208n353wx536-haskell-language-c-0.4.7/share/doc/x86_64-linux-ghc-7.8.4/language-c-0.4.7
Configuration files installed in:
/nix/store/8yxbf9mai1q945y8wyws208n353wx536-haskell-language-c-0.4.7/etc
Using alex version 3.1.4 found on system at:
/nix/store/4ks4ncx8pqlm8d94vcsq6xgb8rc7gvx9-alex-3.1.4/bin/alex
Using ar found on system at:
/nix/store/wr5c9d4mjb4c7gqvpv2qzg2z4h4lry17-binutils-2.23.1/bin/ar
No c2hs found
No cpphs found
No ffihugs found
Using gcc version 4.8.4 given by user at:
/nix/store/ng41cx2qbqmr81b4cvxvm9qi80kbasv0-gcc-wrapper-4.8.4/bin/cc
Using ghc version 7.8.4 found on system at:
/nix/store/cq4qqjii3s9ghr6p59kkrdf44wnyhpp4-ghc-7.8.4/bin/ghc
Using ghc-pkg version 7.8.4 found on system at:
/nix/store/cq4qqjii3s9ghr6p59kkrdf44wnyhpp4-ghc-7.8.4/bin/ghc-pkg
No greencard found
Using haddock version 2.14.3 found on system at:
/nix/store/cq4qqjii3s9ghr6p59kkrdf44wnyhpp4-ghc-7.8.4/bin/haddock
Using happy version 1.19.5 found on system at:
/nix/store/gppfm8wagd5xy4k5fsb7mkr1zcxi11qw-happy-1.19.5/bin/happy
No hmake found
Using hpc version 0.67 found on system at:
/nix/store/cq4qqjii3s9ghr6p59kkrdf44wnyhpp4-ghc-7.8.4/bin/hpc
Using hsc2hs version 0.67 found on system at:
/nix/store/cq4qqjii3s9ghr6p59kkrdf44wnyhpp4-ghc-7.8.4/bin/hsc2hs
Using hscolour version 1.20 found on system at:
/nix/store/1x496nh8iyy1264vczbqjfawhq4glv29-hscolour-1.20.3/bin/HsColour
No hugs found
No jhc found
Using ld found on system at:
/nix/store/ng41cx2qbqmr81b4cvxvm9qi80kbasv0-gcc-wrapper-4.8.4/bin/ld
No lhc found
No lhc-pkg found
No nhc98 found
No pkg-config found
Using ranlib found on system at:
/nix/store/wr5c9d4mjb4c7gqvpv2qzg2z4h4lry17-binutils-2.23.1/bin/ranlib
Using strip found on system at:
/nix/store/wr5c9d4mjb4c7gqvpv2qzg2z4h4lry17-binutils-2.23.1/bin/strip
Using tar found on system at:
/nix/store/k9ama576yfrfx1837rg4rrilma8pnwks-gnutar-1.27.1/bin/tar
No uhc found
building
Building newtype-0.2...
Preprocessing library newtype-0.2...
Building language-c-0.4.7...
Preprocessing library language-c-0.4.7...
[1 of 1] Compiling Control.Newtype  ( Control/Newtype.hs, dist/build/Control/Newtype.o )
In-place registering newtype-0.2...
haddockPhase
Running Haddock for newtype-0.2...
Running hscolour for newtype-0.2...
Preprocessing library newtype-0.2...
Preprocessing library newtype-0.2...
Configuring gio-<IP_ADDRESS>...
setup: At least the following dependencies are missing:
glib -any
builder for ‘/nix/store/wrf8sll3z1jvphfp1z7ij9ayp0gywjpi-haskell-gio-<IP_ADDRESS>.drv’ failed with exit code 1
cannot build derivation ‘/nix/store/2vmcyrb4blh5l7j6qr15c2xhnl4d32v0-ghc-7.8.4.drv’: 1 dependencies couldn't be built
error: build of ‘/nix/store/2vmcyrb4blh5l7j6qr15c2xhnl4d32v0-ghc-7.8.4.drv’ failed

@peti rocks. :green_heart:

Thanks for the bug report. :smile:


Vendor RSpec::Matchers::BuiltIn::BaseMatcher.

This is in aid of moving RSpec Rails off RSpec expectations private API.
Going forward, it would be cool to refactor this base matcher to not be
a total and direct copy of RSpec Expectations' implementation, and
rather an implementation of the matcher API that rails needs, but for
right now this was the fastest route to green.
Going forward in to RSpec 4, it's good to flag that this might cause breakage,
given that the internal matcher API might change. I'd say that the matcher API
is mostly stable enough at this point, so I'm not hugely concerned.
@myronmarston, @jonrowe, @benoittgt do you predict the RSpec matchers API
changing drastically enough in RSpec 4 to cause this to be problematic?
One thing that I'd note here is that I think it'd be cool if we had a really
good step by step guide for implementing the matcher protocol from scratch, as
opposed to using custom matchers or inheriting from base matcher. Right now
there's no obvious human readable documentation for that. Maybe that's
something I could find a new contributor to do?

This looks good to me, as long as the base matcher implements the published protocol (which it obviously does as its been lifted from ourselves) it will continue to work, if we do change any part of that protocol we'd have to go through a deprecation and warning process anyway so I can't see it changing any time soon!


Changed to more modern and more used user-agents.

PR #7 has updated the user-agent. I will close this.


mec15xxevb_assy6853:running tests/kernel/workq/work_queue_api/ failed

Describe the bug
During run tests/kernel/workq/work_queue_api/ in test test_work_submit_to_multipleq assertion failed.
To Reproduce
Steps to reproduce the behavior:

west build -p -b mec15xxevb_assy6853 tests/kernel/workq/work_queue_api/
west flash
See the error in the console output
or
sanitycheck --hardware-map ~/mec1.file --device-testing -T tests/kernel/workq/work_queue_api/ -vv
See the error

Expected behavior
Test should pass
Impact
Test suite fails
Logs and console output
DEBUG   - DEVICE: *** Booting Zephyr OS build zephyr-v2.4.0-634-g53cc090c39a5  ***
DEBUG   - DEVICE: Running test suite workqueue_api
~~~
DEBUG   - DEVICE: ===================================================================
DEBUG   - DEVICE: START - test_work_submit_to_multipleq
DEBUG   - DEVICE:
DEBUG   - DEVICE: Assertion failed at WEST_TOPDIR/zephyr/tests/kernel/workq/work_queue_api/src/main.c:277: twork_submit_multipleq: k_delayed_work_pending(&new_work) is false
DEBUG   - DEVICE:
DEBUG   - DEVICE: FAIL - test_work_submit_to_multipleq
~~~

Environment (please complete the following information):

OS: Linux Ubuntu 18.04.4 LTS
Toolchain Zephyr SDK 0.11.4
Commit SHA or Version used 53cc090

close as possible duplicate of  #29329


chore: upgrate to polkadot-0.9.26

Task linked: CU-2p79uye Upgrade to polkadot-v0.9.26

Closing in favor of #463


At least don't crash on startup.

We will probably need a "please select your Overload directory" for first time setup.

It expects to be run out of the Overload Level Editor directory, where these errors don't occur. But for the purposes of debugging it's still kind of a nuisance; if it used the working directory rather than the location of the executable, maybe?


cuda out of memory

I have the  problem that the terminal show that CUDA out of menmory when I run "python main.py --is_sim --method 'reactive' --experience_replay --save_visualizations". However everything is ok when I run "python main.py --is_sim --push_rewards --experience_replay --explore_rate_decay --save_visualizations". Do you know this is why?
Thank you!

You're having the same issue as here. I am not sure what gpu specifications you are running it on, but theres a chance yours cannot handle the backpropagation. The only way I found to run the reactive net was to comment/edit the lines they described in this link.
https://github.com/andyzeng/visual-pushing-grasping/issues/70

I have an interesting observation. You only encounter this problem when using the argument "--method 'reactive'", which only changes the network model. So I think the root of this problem is not lack of GPU memory (I use 3080 with 12GB memory, equal to that of Titan X). There might be something wrong with the reactive net model.

It's a memory leak problem. The GPU memory usage increases per iteration. So no better how large memory your device has, the program will Eat It Up. I think it has something to do with the computation graph of the reactive_net, which caused the memory leak issue.


Allow calculation of standard errors with categorical data

Closes #514
This PR allows the std_errors and covariance_matrix method of glum.GeneralizedLinearRegressor to accept a pandas.DataFrame, now allowing the same X data used in fitting the model.
In particular, the calculation of the covariance matrix did not allow for all tabmat matrices. When X is a  tabmat.CategoricalMatrix, tabmat.SplitMatrix, or pandas.DataFrame with categorical or sparse data, the matrices used for further calculations were not supported in the calculation of the standard errors.
Further, this PR fixes a small errror where the nonrobust standard errors of a GLM with the binomial family and logit link were calculated incorrectly. The input argument of get_one_over_variance only affected a calculation for the binomial distribution with logit link.
Tests have been added for the calculation of standard errors with categorical data and dataframes. Tests for the standard errors of additional models, with the binomial distribution (with logit link) and poisson (with log link) have also been added.
Note:
I have kept the current test of the standard errors against statsmodels' OLS for now, but since I am also testing a GLM with Gaussian distribution and identity link, we may consider removing that one. I built most of the tests based on the regression_data fixture, but I am happy to restructure them as well!
Checklist

[x] Add further tests for different types of input data (dataframes, tabmat matrices)
[x] Added a CHANGELOG.rst entry

@DavidMeesterQC, I just released a new version of tabmat with multiply capabilities and a drop_first argument for CategoricalMatrix. Let me know if you need help integrating those in this PR.
FYI, it might take a few hours for the new tabmat version to become available on conda-forge.

@MarcAntoineSchmidtQC, @DavidMeesterQC, what's up here?

@MarcAntoineSchmidtQC, @DavidMeesterQC, what's up here?

This is ready for review 😄


merge upstream/master, remove a lot of unneeded code

merge upstream/master
takes out a lot of unused files and listeners, improving load times
changes from background page to background scripts
removes web_accessible_resources to fix https://github.com/brave/browser-laptop/issues/8365

sorry this is a large change. 32cac6d is the main non-merge diff.

Note that this depends on https://github.com/brave/browser-laptop/pull/8366 for PDFJS loading in the current tab.
Once that PR is merged and released, we should wait a while before doing a PDFJS release because this will not be compatible with previous versions of Brave.

@bsclifton you can run gulp chromium, then copy build/chromium to the location of pdf.js in your dev profile. ex: ~/Library/Application\ Support/brave-development/Extensions/jdbefljfgobbmcidnmpjamcbhnbphjnb/1.7.428/


Error: traces below the line

How to fix this error?

What is the font?

Cantarell - System font of Arch LInux.
I did Install powerline-fonts... So, Cantarell is not compatible?

Nothing! Cantarell is not compatible. Roboto Mono sounds good! ;)


Added support for FriendlyName to xCertReq - Fixes #44

This PR primarily adds support for specifying the Friendly Name of new certificates created using xCertReq.
It also makes style and other changes for consistency and HQRM compatibility.

xCertReq:

Added FriendlyName parameter to xCertReq.
Changed exceptions to be raised using New-InvalidOperationException from PSDscResources.
Changed integration tests to use Config Data instead of value in config to support
additional tests.
Converted unit tests to use Get-InvalidOperationRecord in CommonTestHelper.
Improved unit test style to match standard layout.
Minor corrections to style to be HQRM compliant.

Corrected all makrdown rule violations in README.MD.
Added markdownlint.json file to enable line length rule checking in VSCode
with MarkdownLint extension
installed.

This change is

Hi @johlju or @bgelens - if either of you have any downtime (I know you don't :grin:) would you mind looking over this PR for me? No rush at all- I just don't have anyone else maintaining this repo so have no official reviewers to check my code.
This is a smallish change but I did fix some existing style issues.

@PlagueHO I trade with you ;) Can you see if you have a good idea for my problem here https://github.com/PowerShell/xSQLServer/issues/641 while I review your PR tomorrow :smile:

@johlju - it's a deal :grin:
I've looked into this now though and haven't managed to get much more than a bad work around. Looks like we've got the same problem in a couple of resources as well. Maybe the DSC Team can offer some suggestions?

Nice cleanup in the tests :)

Reviewed 10 of 10 files at r1.
Review status: all files reviewed at latest revision, all discussions resolved.

Comments from Reviewable

Awesome! Thanks @johlju - and yep - I've been trying to clean everything up with each PR.


State change causes the src to download again

wheneveri tap on the increase quantity button and the state of quantity increases in short the state of the screen changes
the model is downloaded again.
https://user-images.githubusercontent.com/87603317/178215735-a8fbd1d2-0643-4236-b359-735a34dcce06.mp4

You must use a listener to update only your changeable widget, setState() when called rebuild the tree on the actual view.
In other words, rebuild ModelViewer again.


Return an empty collection when where(:foo => []) is given

The previous behaviour was to return everything! This is now consistent with ActiveRecord and avoids a needless request.
The new behaviour is not applied to has_one associations as they currently seem to ignore the where method entirely.

hi @chewi I've just got commit access on this repo and plan to get back on track with maintenance over time - will be in touch soon!

Rebased.

Rebased again.

And again!


@import url(//xxxxx.com?a=b); doesn't work

I would like to reference an external css in a schema-agnostic way (http/https)
@import url(//fonts.googleapis.com/css?family=Trocchi);
As a result I'm getting an "Invalid characters in path" exception, as dotLess is trying to parse it as a system file path.
@import url(//xxxxx.com);       // Works
@import url(//xxxxx.com?a=b);        // Doesn't work

Seems to work in the current release.


New OpenIdMetadata signing keys will not be picked up for up to 5 days

Versions
What package version of the SDK are you using.
4.9
(the rest is irrelevant)
Describe the bug
If MSFT adds a new signing key to the OpenIdMetadata it will not be picket up for 5 days and fail Directline Speech connections.
The issue seems to be in OpenIdMetadata: https://github.com/microsoft/botbuilder-js/blob/60ff913ea0199afb7e5ff96f6ebf25648a75479b/libraries/botframework-connector/src/auth/openIdMetadata.ts#L26
On incoming requests, JwtTokenExtractor will validate the JWT token using the cached public keys loaded via OpenIdMetadata.
MSFT adding (and using!) a new signing key will not be picked up for up to 5 days, which means that if a new signing key is being used, L42/43 will not find it in the cached keys and return undefined, which in turn fails OpenIdMetadata L98 (https://github.com/microsoft/botbuilder-js/blob/60ff913ea0199afb7e5ff96f6ebf25648a75479b/libraries/botframework-connector/src/auth/jwtTokenExtractor.ts#L98).
To Reproduce
Steps to reproduce the behavior:
Currently not reproducible as there's no new signing key. But the description should explain how it works.
Expected behavior
My suggestion would be to always check if the signing key actually exists in the cache and refresh the tokens if it doesn't. Only then can you be sure that the signing key is completely invalid.
Screenshots

Additional context
We saw this issue on Saturday for a few hours and restarting our service fixed the issue as it refreshed the memory cache.
[bug]

@alopix  Thank you for the detailed description, and raising this issue.
We are working on a fix, and will keep you updated.

@EricDahlvang can you also prepare a cherry-pick for the R9 branch?

@alopix we've merged a fix.  I'll let you know when this is released.

This fix has been released with https://www.npmjs.com/package/botbuilder/v/4.9.3


How does lstm-parser handle pre-trained word embeddings?

Hi,
First of all, thank you very much for sharing this excellent dependency parser. I am using your parser as part of my MSc thesis on improving dependency parsing of Norwegian language using pre-trained word embeddings, and I have a question regarding lstm-parser's handling of pre-trained embeddings which I cannot find the answer to in your article.
From my understanding, there are several different approaches to using pre-trained word embeddings in dependency parsers. UDPipe/Parsito has the option of either using the embeddings directly as feature vectors for each word in the vocabulary, or using the pre-trained embeddings as a basis for the training of internal form-embeddings used by the parser. So my question is: how does lstm-parser utilise the pre-trained embeddings internally?
Kind regards,
Henrik H. Løvold
LTG group at Uni. of Oslo

Take a look at section 3.3 http://aclweb.org/anthology/P/P15/P15-1033.pdf
Thanks !
Miguel

Thank you, that answers my question!


[FEATURE] Investigate GetXAttr performance

Description
Looking at CPU profiles for a couple of containers, it seems that GetXAttr is consistently showing up as a non-trivial amount of the soci-snapshotter's runtime. Specifically it is n.IsOpaque() which checks for the existance of a whiteout in the metadata db:
https://github.com/awslabs/soci-snapshotter/blob/6dcfca7bc0c70b00a5f23813d468379d6fbc8de5/fs/layer/node.go#L288-L293
example profiles:

It's possible that this is a red herring and what we're actually seeing is just that GetXAttr is a very common, so we should be careful how much effort we put into this before validating that we're seeing benefit.
Describe the solution you'd like
We should investigate whether there is a way we can reduce the cost of n.IsOpaque().
We could possibly move the opaqueness to a property of the node itself rather than pushing it down into the metadata db. A good first step might be to try this and compare benchmarks to see if it has an effect.
Describe any alternative solutions/features you've considered
No response
Any additional context or information about the feature request
No response

Copying some context

Ok, I finally got around to testing how this interacts with OverlayFS. The answer is that OverlayFS handles deleted files by creating "whiteouts" in higher layers. For example, if a lower layer has dir/file then a higher layer can delete it by containing a file named dir/.wh.file. This works with the change.
For directories, overlayfs has an "opaque" xattr (trusted.overlay.opaque=y) which treats all files as deleted rather than having to explicitly create a whiteout file for each. In containers, this is encoded as a special .wh..wh..opq file in a higher layer (.e.g. to delete all files in /bin a higher layer would contain /bin/.wh..wh..opq). So it's possible for the container image to contain an opaque directory with no xattrs. This change will disable xattrs and the directory will be populated at runtime.
An example:
FROM alpine:latest

RUN mkdir /dir && touch /dir/file1 /dir/file2 /dir/file3
RUN touch /dir/.wh..wh..opq

Without Soci:
# ls /dir
#

With SOCI:
# ls /dir
file1 file2 file3
#

The image spec says that whiteouts should be explicit, but to be spec compliant we must accept opaque directories. At a minimum, we should look for .wh..wh..opq files when determining if a layer has xattrs.

https://github.com/awslabs/soci-snapshotter/pull/718#issuecomment-1875759931

Taking a step back and considering #971, I think the real issue we have is that checking opaqueness is expensive. Each check goes through bbolt to see if a file exists. Since the lower layers are immutable, I think we could probably just push opaqueness up into the in-memory nodes.
I'm going to run some quick hard-coded benchmarks (normal, disableXattrs hard coded to true, isOpaque hard coded to false) to see how that compares.

https://github.com/awslabs/soci-snapshotter/pull/718#issuecomment-1875766120

TL;DR GetXAttrs is an expensive operation and should be avoided unless necessary. Full testing and results on changes can be found here: https://github.com/awslabs/soci-snapshotter/pull/1021#issuecomment-2010966698
Operations that normally made significant calls to GetXAttrs would take up a nontrivial amount of CPU seconds due to checking if isOpaque is true. #1021 fixed this by not making these calls on a layer-level unless the directory had opaque directories.
While we may want further iteration of this (i.e. see if we can make it more granular to avoid the call more often), the question and immediate problem at hand have been resolved, so this can be closed.


Add vendor specific command line options

Seagate raw data isn't accurate. Therefore -v is required. See https://www.truenas.com/community/threads/seagate-ironwolf-smart-test-raw_read_error_rate-seek_error_rate.68634/post-470741

Hi and thanks for mentioning this issue. As the source you provide seems rather old I am not convinced to make an exception for Segate. I'm also not sure if there are only drives concerned that are old or if this is a general "Segate" problem. Feel free to convince me that this is a general problem. Otherwise this this info might help someone to understand wrong error rates. So I added it to the README:
https://github.com/micha37-martins/S.M.A.R.T-disk-monitoring-for-Prometheus/pull/24/commits/73600ac546418537c2d6ff6fee0472ecabd13300

Hi. Thank you for your work. This issue is still valid. I bought two Seagate IronWolf NAS 12TB and smart still shows abnormally high values for "Seek_Error_Rate" and "Raw_Read_Error_Rate":

SMART Attributes Data Structure revision number: 10
Vendor Specific SMART Attributes with Thresholds:
ID# ATTRIBUTE_NAME          FLAG     VALUE WORST THRESH TYPE      UPDATED  WHEN_FAILED RAW_VALUE
  1 Raw_Read_Error_Rate     0x000f   084   064   044    Pre-fail  Always       -       241341296
  3 Spin_Up_Time            0x0003   092   092   000    Pre-fail  Always       -       0
  4 Start_Stop_Count        0x0032   100   100   020    Old_age   Always       -       11
  5 Reallocated_Sector_Ct   0x0033   100   100   010    Pre-fail  Always       -       0
  7 Seek_Error_Rate         0x000f   074   060   045    Pre-fail  Always       -       25607460

however, if I put these values here https://s.i.wtf/, it shows 0 errors
=== START OF INFORMATION SECTION ===
Model Family:     Seagate IronWolf
Device Model:     ST12000VN0007-2GS116
Serial Number:    ZJV60FWR
LU WWN Device Id: 5 000c50 0c3046680
Firmware Version: SC60
User Capacity:    12,000,138,625,024 bytes [12.0 TB]
Sector Sizes:     512 bytes logical, 4096 bytes physical
Rotation Rate:    7200 rpm
Form Factor:      3.5 inches
Device is:        In smartctl database 7.3/5528
ATA Version is:   ACS-3 T13/2161-D revision 5
SATA Version is:  SATA 3.1, 6.0 Gb/s (current: 6.0 Gb/s)
Local Time is:    Mon Sep 23 09:37:38 2024 CEST
SMART support is: Available - device has SMART capability.
SMART support is: Enabled

I have the same problem. How we can modify the script?
Thanks.

@DenisBY @dynux90
I see this is annoying behavior and I created a workaround for you. But I need your support as I do not have a Seagate drive. Please test the "seagate_special" branch.

@micha37-martins does this works when we have both HDD from Seagate and SSD from other vendors?

@dynux90 I cannot test it but maybe you can verify that it works for your Seagate and then I try to implement a switch for mixed setups that have Seagate and other vendor(s).

@micha37-martins the modified version does not work, even is not getting the smart attributes.
i tried this code instead and its working in process_device():
`# Get and parse SMART information
local info_json
info_json=$(/usr/sbin/smartctl -i -j -d "${type}" "${disk}")
parse_smartctl_info_json "${disk}" "${type}" "${info_json}"
local model_name
model_name=$(echo "$info_json" | jq -r '.model_name // empty')
Get and parse SMART attributes
local attributes_json
if [[ "$model_name" == ST* ]]; then
attributes_json=$(/usr/sbin/smartctl -A -j -d "${type}" -v 1,raw48:54 -v 7,raw48:54 "${disk}")
else
attributes_json=$(/usr/sbin/smartctl -A -j -d "${type}" "${disk}")
fi    `

@dynux90 Thanks for testing and your suggestion. I would still keep the flag to somehow separate the code for this kind of edge case. Feel free to check the change to seagate_special branch:
https://github.com/micha37-martins/S.M.A.R.T-disk-monitoring-for-Prometheus/blob/5a50a63dc28e1fb63c6c404a97832503f851a1b3/src/smartmon.sh#L316

I now added the seagate special to the main branch.


How to set generate_dataset_from_dir parameters properly for more diverse and more samples?

Hi guys, newbie here. I have a few questions regarding the data generation. I am using "generate_dataset_from_dir" to generate the dataset from a large .xls file consisting few thousands items of product info. Right now I can't set the “use_self_instruct” to True, it's giving me errors. And with default parameter values, it only generates fixed amount of new data samples. for example: for 5 data points in my excel file, it only generates 5 questions. currently my code looks like this:
from xturing.datasets import InstructionDataset
from xturing.model_apis.openai import Davinci, ChatGPT

engine = ChatGPT("*************************************************8")
dataset = InstructionDataset.generate_dataset_from_dir(path="data/",
                                                       engine=engine,
                                                       use_self_instruct=False,
                                                       chunk_size=8000,
                                                       num_instructions = 10,
                                                       num_instructions_for_finetuning = 5,
                                                       num_prompt_instructions = 1,
                                                       num_samples_per_chunk=5)
dataset.save("./my_generated_dataset")
[print(i) for i in dataset] # print the generated dataset

My questions are as follows:

What is the correct way to "set use_self_instruct" to "True" to get more diverse and samples?
What do these parameters exactly mean? - num_instructions, num_instructions_for_finetuning, num_prompt_instructions, num_samples_per_chunk.
For a dataset containing let's say 2000 items that have info related to its price, brand, type, topic, category, description etc, how many instruct data are enough to fine-tune a LLama 7b model? and how should I set these (num_instructions, num_instructions_for_finetuning, num_prompt_instructions, num_samples_per_chunk) parameters to generate maximum and enough numbers of new samples?

Any useful insight, suggestion is greatly appreciated.

Hi @Purulence666 ,

What is your error when setting use_self_instruct =True
You can check out our documentation to understand these parameters: https://xturing.stochastic.ai/datasets/generate
The generate_dataset_from_dir focus on generating question answering data from plain text data. You can use generate_dataset method to generate diverse tasks given the some examples in the seed_tasks.json file


add support for rgb overlays

Resolves #1730.
Change log

Adds support for visualizing RGB segmentations in the App
Adds support for RGB segmentations in evaluate_segmentations()
Adds support for passing RGB mask targets to objects_to_segmentations()
Adds a new transform_segmentations() utility to transform existing masks between grayscale <> RGB

Example usage
import fiftyone as fo
import fiftyone.zoo as foz
import fiftyone.utils.labels as foul

mask_targets = {"#FF6D04": "person", "#499CEF": "cat", "#6D04FF": "dog"}

dataset = foz.load_zoo_dataset(
    "coco-2017",
    split="validation",
    label_types=["segmentations"],
    classes=["person", "cat", "dog"],
    label_field="instances",
    max_samples=25,
    only_matching=True,
)

foul.objects_to_segmentations(
    dataset,
    "instances",
    "segmentations",
    mask_targets=mask_targets,
)

dataset.default_mask_targets = mask_targets

# Test in-database RGB segmentations in App
session = fo.launch_app(dataset)

foul.export_segmentations(
    dataset, "segmentations", "/tmp/segmentations", overwrite=True
)

# Test on-disk RGB segmentations in App
session.refresh()

# Test evaluating RGB segmentations
dataset.rename_sample_field("segmentations", "ground_truth")
dataset.clone_sample_field("ground_truth", "predictions")

results1 = dataset.evaluate_segmentations(
    "predictions", gt_field="ground_truth", mask_targets=mask_targets
)
results1.print_report()

results2 = dataset.evaluate_segmentations("predictions", gt_field="ground_truth")
results2.print_report()

# Convert to grayscale
targets_map = {"#FF6D04": 1, "#499CEF": 2, "#6D04FF": 3}
foul.import_segmentations(dataset, "ground_truth")
foul.transform_segmentations(dataset, "ground_truth", targets_map)
foul.transform_segmentations(
    dataset, "predictions", targets_map, update_mask_targets=True
)

# Edit grayscale values
foul.transform_segmentations(
    dataset, "predictions", {1: 70, 2: 140, 3: 210}, update_mask_targets=True
)

# Convert back to RGB
foul.transform_segmentations(
    dataset, "predictions", {70: "#FF6D04", 140: "#499CEF", 210: "#6D04FF"}
)

@sashankaryal how's this PR coming? A couple things I noticed when testing just now:

The tooltip does not render correctly when viewing a dataset without mask targets explicitly defined in the App (does not consistency appear; and when it does seems to be showing the wrong data?)

I also noticed that pixel values that do not appear in the provided mask_targets are currently being rendered. Is that intentional? Or are you planning to switch to the currently documented behavior that pixels not in masks_targets are not rendered? After testing just now and experiencing the current behavior, I'm thinking it could be fine to go ahead and always render all non-zero classes and just show pixel value when a label is not available.
I can see value both ways:

If only mask_targets are painted, it would give a simple way to change what is rendered by editing mask_targets
If all non-zero values are painted, then there is never any confusion why user's data is not appearing

Addressed in the new commits


Cant get result

Hi,
This library is very useful to me. this demo working fine. but i was facing issue in above andorid version of lolipop.
please help me.

Was this resolved?


Fix ory respository name.

Description
This PR fixes the repository name of ory.sh in the repo-values.yaml that has been incorrectly set to smallstep causing errors locating the smallstep and ory packages.

@mattfarina: it looks like the issue is not fully resolved.
Now on https://hub.helm.sh/charts smallstep appears only once, before it was appearing twice, and ory is there, it wasn't before. But if you click on smallstep https://hub.helm.sh/charts/smallstep the only chart visible is smallstep/oathkeeper, and that chart is not in smallstep repo, the chart is part of ory.
Looking at helm/hub yaml, I cannot see anything wrong, so my guess is that is some kind of caching issue in the server running https://hub.helm.sh


Add Save list entry in the cart DB.

This PR detect the save type with more games.

Excellent work, thanks!


Autocomplete does not work for "cascading?" imports

VSCode Version: 1.41
OS Version: Windows 10

Steps to Reproduce:
(react native app)

import { Notifications} from 'expo';
verify there's no autocomplete
import * as Permissions from 'expo-permissions';
verify autocomplete works.

What's going on here? I come from C# VS background, so if the thing's imported autocomplete just works. Why does it depend on the way you import it?

Does this issue occur when all extensions are disabled?: Yes

Sorry, not a best place to report it. It seems all the other editors I've tried behaved in the same way. Unrelated to VS Code, it was just really weird.


Code Helper opens too many files when opening a project

Upon opening a project, Code Helper opens an excessive number of files simultaneously. Checking lsof -p ${pid} output at a random point, it's reading over 4500 files, mostly in vendor/bundler/** (this is a Ruby project). On OSX, kern.maxfiles is set to 12,288 and kern.maxfilesproc to 10,240. At the point I was able to run lsof, I'm guessing Code Helper had already closed many of the files it had opened.
I've added this directory to files.watcherExclude, which I believed would exempt these files from this behavior, but is apparently not the case.
The specific process causing the problem:
/Applications/Visual Studio Code.app/Contents/Frameworks/Code Helper.app/Contents/MacOS/Code Helper /Applications/Visual Studio Code.app/Contents/Resources/app/out/bootstrap --type=extensionHost

VSCode Version: Code 1.14.2 (cb82febafda0c8c199b9201ad274e25d9a76874e, 2017-07-19T23:22:50.650Z)
OS Version: Darwin x64 16.7.0
Extensions:

Extension
Author (truncated)
Version

EditorConfig
Edi
0.9.4

gitignore
cod
0.5.0

githistory
don
0.2.2

proto
pet
0.0.2

Ruby
reb
0.12.1

RustyCode
sav
0.19.1

org-mode
too
0.1.3

gitblame
wad
2.0.2

better-align
wwm
1.1.6

Steps to Reproduce:

Create a project with hundreds of thousands of files spread throughout subdirectories.
Open the project from the command line (code .).

Reproduces without extensions: Yes

I think this --type=extensionHost is implying that it's an extension doing this? Are you sure you tried launching with --disable-extensions?

You might be right. I didn't completely shut down Code before launching without extensions, I'll attempt to reproduce again and ensure it's not extension-related.

I have the same issue even when all extensions are disabled.
When viewed Activity Monitor, the 'Code Helper' process has a huge number of threads (around 620 for me.) Inspecting the 'Code Helper' process and opening the 'Open Files and Ports' tab lists out a huge number of files open by the program (in my case it's around 8400).
I can't use any terminal commands when it's open -- it gives me varying errors including 'Login incorrect' and 'too many files open in system.' It also breaks most web browsers including Chrome, Firefox and Safari.

@stouset Please let us know what happens with --disable-extensions.

Bug disappears. I'll file with the relevant extension, thanks.


Add tests for embedding last capability in capabilityChain in proof

Add tests for embedding last capability in capabilityChain in proof and ensure this is a viable option considering graph data model, etc.

This has landed.


libMoz2D.dll not designed to run on Windows or has an error

After trying several version of GT, being the last 0.6.62 I get the sabe errocode 0xc000012f with libMoz2D.dll . The error says that the dll is not designed to run on Windows or has an error.

Is there another source I can get the dll from?

Please install Visual C++ Redistributable for Visual Studio 2015 64bit
We will ship MSVCR140.dll together with libMoz2D.dll soon

I had the 2017 redist installed, so I had to uninstall them to be able to install the 2015 redist. After installing them and rebooting my machine I keep getting the same error.

Where can I find the instructions to try to generate the dll again?

@rcpacheco May we ask you to use Dependency Walker to check what dependencies are not satisfied? We test libMoz2D.dll on a fresh and clean installation of Windows 10 and Visual C++ redistributable appears to be the only required dependency.
Here is a video walkthrough of how to find missing dependencies. Could you take a screenshot of the left pane with dependencies from the app after opening libMoz2D.dll?
https://drive.google.com/open?id=1GND1CRU6UL6dX0kqfGIHqD9ljRaPyoot
Thank you

This is the error I get while trying to open the dll with dependency walker.

Downloaded GT v0.6.63 and got the same error

What Windows version do you have?

I'm using windows 10

build 67 has the DLLs fixed.
GToolkit starts but I get the error below:

build 67 has the DLLs fixed.
GToolkit starts but I get the error below:

the error was due to parallels folders, the gt window is still white

I got something simillar with build67

Progress! Now resizing the window should help 👍

Almost there, but still something not working

Upon starting the GT logo shows, I get these erros and then the Pharo Logo is shown and the black windows. The account has write acces to that directory.

I tried build68 on Windows 7 and no errors showed up.

Tried build 69, but got the same result  :'(

@rcpacheco what happens when you try to resize a black window with gt in the title? Does the content appear?

Ohhh yes :D when I expand the black box the menue apears and the I click again its header and takes back its normal size. The Logo is still Pahro's but not GT. I clicked all the menu options and they seem to work ok.

I've been playing with the image and it looks good. Nevertheless, even saving the imagen once the menu is showing, upon restart the menu gets black. Resizing solves the problem again.

Just to test the build, I tried to change the Desktop Logo using Settings. Upon clicking the file selector I got an "Use UIManager default chooseExistingFileReference:extensions:path:preview: instead" error. Do you think is related or relevant to this issue?  I tried to copy the error message from the inspector, but could not make copy paste from the inspector. Is that correct? Also I see that the buttons do not have hints? Is that also the expected behaviour ?

I


SSLEOFError when phone connects to wifi

general information:
flashed device: CASALUX Wifi LED RGB Light Strip (TYWE3S chip)
operating system: Raspberry Pi 3B+ with Raspberry Pi OS bullseye (headless) and its internal wifi chip
issue
I tried to flash the device when I got an timeout:
Timed out while waiting for the device to (re)connect
Searching for errors in the logs I found this error in the smarthack-psk.log:
new client on port 443 from <IP_ADDRESS>:46220
could not establish sslpsk socket: [SSL: NO_SHARED_CIPHER] no shared cipher (_ssl.c:1123)
don't panic this is probably just your phone!
new client on port 443 from <IP_ADDRESS>:46232
could not establish sslpsk socket: EOF occurred in violation of protocol (_ssl.c:1123)
Traceback (most recent call last):
  File "/home/pi/tuya-convert/scripts/./psk-frontend.py", line 61, in new_client
    ssl_sock = sslpsk.wrap_socket(s1,
  File "/usr/local/lib/python3.9/dist-packages/sslpsk/sslpsk.py", line 110, in wrap_socket
    sock.do_handshake()
  File "/usr/lib/python3.9/ssl.py", line 1309, in do_handshake
    self._sslobj.do_handshake()
ssl.SSLEOFError: EOF occurred in violation of protocol (_ssl.c:1123)

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/pi/tuya-convert/scripts/./psk-frontend.py", line 112, in <module>
    main()
  File "/home/pi/tuya-convert/scripts/./psk-frontend.py", line 108, in main
    p.data_ready_cb(s)
  File "/home/pi/tuya-convert/scripts/./psk-frontend.py", line 80, in data_ready_cb
    self.new_client(_s)
  File "/home/pi/tuya-convert/scripts/./psk-frontend.py", line 72, in new_client
    if "NO_SHARED_CIPHER" in e.reason or "WRONG_VERSION_NUMBER" in e.reason or "WRONG_SSL_VERSION" in e.reason:
TypeError: argument of type 'NoneType' is not iterable

solution
This error was caused by my phone and not the device and shouldn't matter for the flashing process. The first error is catched but the second error (throwed because e.reason seems to be None) not so it prevents the flashing process from working properly for the next connected devices. So I tried just preventing this error by inserting the following after line 71 in the new_client-function in psk-frontend.py:
[...]
except ssl.SSLError as e:
	print("could not establish sslpsk socket:", e)
	# added following 2 lines:
	if e.reason == None:
		return
	if "NO_SHARED_CIPHER" in e.reason or "WRONG_VERSION_NUMBER" in e.reason or "WRONG_SSL_VERSION" in e.reason:
		print("don't panic this is probably just your phone!")
[...]

Because the more detailed error message is not at all important for the flashing process, this change shouldn't effect it.
After this small change everything worked and I successfully flashed my device.
I hope this issue may help others who get the same error.

Hi @Sarius121,
I´m not as deep into this as you, but I found the same error in my smarthack-psk.log for the issue I did report here:
https://github.com/ct-Open-Source/tuya-convert/issues/1022
Would you mind taking a look and give your opinion if that might be related? For sure I will simply try to add your lines to see if that makes a difference ... I guess it would be interesting to understand why this exception is happening for 3 of my 5 devices (tried all to flash in the same setup).
Thanks!

Hi, I think our issue must be a differnent one - as much as I can say from our logs there is no other devices other than the phone ever connecting ... the exception we see in our log at the end seems to come from an interrupt ...
Out of curiosity I tried your modification but it did not make any difference - just the exception not showing up in my log anymore ...
My guess ...

Hi @MacSass,
the error in your smarthack-psk.log seems to be exactly the same and also seems to be triggered by your phone. But if you still get a timeout after adding the two lines and not getting this exact error anymore the problem is probably somewhere else.

the exception we see in our log at the end seems to come from an interrupt

As far as I understand the program, this interrupt is just the consequence of the timeout and not directly related to an error so your problem is probably not related to an error in the smarthack-psk part of the program.

Thanks @Sarius121 - yes I tend to agree with you - some other reason seems to prevent the device from re-connecting with IP <IP_ADDRESS>, but I´m not clear yet on what could be causing this ... I keep searching ...


[pm] Sprint 9 May 2016

2 week sprint. We approx follow: https://github.com/rgrp/project-management/blob/master/project-delivery.md#the-sprint-process-and-key-concepts
Sprint Goal
Sprint Backlog

And now this sprint has ended.


ERROR `/assets/fonts/dotx-icons.ttf' not found.

As the title says,  ERROR `/assets/fonts/dotx-icons.ttf' not found. Where do I get it?

#8 I created a pull request to solve this issue.

Pull request has been added to the repo. Your issue should be solved.


Need to ensure we use lower-case gRPC header keys

This might be a no-op, but please double check. Filing this issue just in case.
We need to ensure that all headers used for gRPC are written in lower-case. Please review this Pull Request for reference of what needs to be updated.
Again, perhaps this doesn't apply to your language. Feel free to comment and close the issue (after you double checking).

We don't explicitly set any gRPC header. @garrettjonesgoogle do you?

Our code doesn't have any uppercase text that it puts in the header. We should probably do a more thorough audit of the headers that are passed.

Not even user-agent ?

We set the user agent via a call to GAX, not setting the header key directly. I logged the headers of a request to PubSub and the user-agent related headers look fine, keys are: user-agent and x-google-apis-agent.

Can the issue be closed?


tools/nuttx-gdbinit: No such file or directory

I flowed this qemugdb document to debug the nuttx binary.
When I inputd the below command, there was a error message in the gdb window.
gdb-multiarch -ix tools/nuttx-gdbinit nuttx
I searched the tools directory, and I couldn't find the nuttx-gdbinit file the this directory. I can find this file in the older nuttx version, so whether there is a new document about the qemugdb?
Thanks for your help!

The script change to https://github.com/apache/nuttx/blob/master/tools/gdb

The script change to https://github.com/apache/nuttx/blob/master/tools/gdb

@anjiahao1 could you please fix https://nuttx.apache.org/docs/latest/guides/qemugdb.html ?
Since nuttx-gdbinit doesn't exist anymore, the documentation currently is useless!

The script change to https://github.com/apache/nuttx/blob/master/tools/gdb

@anjiahao1 could you please fix https://nuttx.apache.org/docs/latest/guides/qemugdb.html ?
Since nuttx-gdbinit doesn't exist anymore, the documentation currently is useless!

pr 12187 fixed it.


[Task]: Address Management View

📝 Task description
The Cardano DevKit Tauri app requires an address management view that provides an overview of all used addresses, including their ADA and native token balances. This view should show all wallets that have been topped up or that have more than zero ADA.
Component
ui
Steps to complete
No response
Additional context
Blocked by #7

#7 has been done.


fix: apply :global() to whole selector + add strict mode

Fixing some issues when combining (pseudo)class selectors, ex: .test.test-2 {}, p.test { ... } , .test:over { ... }, etc...

@adrien-k  Thank you for your contribution. I updated the code so that it would work in some other scenarios  such as:

Being used along other global selectors

Active

Being used in a media query or nested rules (for sass)

Active

Anything else you'd think of ?

@micantoine That looks like a way better approach 👍. Thank you for the fix and for the lib.


docs: Fix link to Paper Pages in Models FAQ

Hey,
this PR introduces a small improvement on the Models FAQ page and fixes the link to Paper Pages site.

The docs for this PR live here. All of your documentation changes will be reflected on that endpoint.


Event request : OnAfterSetPaymentLine

A customer wants to choose the vendor bank account on the purchase invoice. This should can be the preferred bank account, but they can change it manually.
Can there be an event after 'onvalidate account no' on T2000001
or afterSetpaymLine on R2000019 ?
thx

Closing requests ad no information have been provided. Please create new request with required information.


Configuration validation segfaults with cluster_type configured for Redis

Title: Configuration validation segfaults with cluster_type configured for Redis
Description:
When trying to validate a configuration with the CLI envoy -c /etc/envoy/redis.yaml --mode validate it segfaults. Even though the validate segfaults. When running without the --mode validate flag it works as expected.
Repro steps:
My current configuration is like this:

redis.yaml
static_resources:
  listeners:
  - name: redis_listener
    address:
      socket_address:
        address: <IP_ADDRESS>
        port_value: 6379
    filter_chains:
    - filters:
      - name: envoy.filters.network.redis_proxy
        typed_config:
          "@type": type.googleapis.com/envoy.extensions.filters.network.redis_proxy.v3.RedisProxy
          stat_prefix: redis_stats
          settings:
            op_timeout: 5s
            enable_hashtagging: true
            enable_redirection: true
            enable_command_stats: true
            dns_cache_config:
              name: redis_cache
              dns_lookup_family: V4_ONLY
              dns_refresh_rate: 300s
              dns_min_refresh_rate: 30s
          prefix_routes:
            catch_all_route:
              cluster: redis_cluster

  clusters:
  - name: redis_cluster
    cluster_type:
      name: envoy.clusters.redis
      typed_config:
        "@type": type.googleapis.com/google.protobuf.Struct
    connect_timeout: 5s
    lb_policy: CLUSTER_PROVIDED
    load_assignment:
      cluster_name: redis_cluster
      endpoints:
      - lb_endpoints:
        - endpoint:
            address:
              socket_address:
                address: elasticache-endpoint
                port_value: 6379
    typed_extension_protocol_options:
      envoy.filters.network.redis_proxy:
        "@type": type.googleapis.com/envoy.extensions.filters.network.redis_proxy.v3.RedisProtocolOptions
        auth_password:
          inline_string: "12345678"
    transport_socket:
      name: envoy.transport_sockets.tls
      typed_config:
        "@type": type.googleapis.com/envoy.extensions.transport_sockets.tls.v3.UpstreamTlsContext

I've done some search through the documentation and some closed issues to come up with the above configuration, but when I try to validate it with the CLI, it segfaults. I'm using the Docker image envoyproxy/envoy:contrib-v1.32-latest for my current setup. I just copy the above configuration to the container and try to start envoy with the CLI.
If I change the cluster_type to a type: STRICT_DNS and the lb_policy to ROUND_ROBIN, everything continues to work AND the CLI can validate the configuration.

redis.yaml - with type: STRICT_DNS and lb_policy: ROUND_ROBIN
static_resources:
  listeners:
  - name: redis_listener
    address:
      socket_address:
        address: <IP_ADDRESS>
        port_value: 6379
    filter_chains:
    - filters:
      - name: envoy.filters.network.redis_proxy
        typed_config:
          "@type": type.googleapis.com/envoy.extensions.filters.network.redis_proxy.v3.RedisProxy
          stat_prefix: redis_stats
          settings:
            op_timeout: 5s
            enable_hashtagging: true
            enable_redirection: true
            enable_command_stats: true
            dns_cache_config:
              name: redis_cache
              dns_lookup_family: V4_ONLY
              dns_refresh_rate: 300s
              dns_min_refresh_rate: 30s
          prefix_routes:
            catch_all_route:
              cluster: redis_cluster

  clusters:
  - name: redis_cluster
    connect_timeout: 5s
    type: STRICT_DNS
    lb_policy: ROUND_ROBIN
    load_assignment:
      cluster_name: redis_cluster
      endpoints:
      - lb_endpoints:
        - endpoint:
            address:
              socket_address:
                address: elasticache-endpoint
                port_value: 6379
    typed_extension_protocol_options:
      envoy.filters.network.redis_proxy:
        "@type": type.googleapis.com/envoy.extensions.filters.network.redis_proxy.v3.RedisProtocolOptions
        auth_password:
          inline_string: "12345678"
    transport_socket:
      name: envoy.transport_sockets.tls
      typed_config:
        "@type": type.googleapis.com/envoy.extensions.transport_sockets.tls.v3.UpstreamTlsContext

Admin and Stats Output:
Envoy haven't actually started when this strange behavior happens, so the only output is the CLI validate:

Envoy CLI validate
root@envoy-cc48545bb-pmnl9:/# vim /etc/envoy/redis.yaml
root@envoy-cc48545bb-pmnl9:/# envoy -c /etc/envoy/redis.yaml --mode validate
[2024-12-11 23:16:46.436][11677][info][main] [source/server/server.cc:879] runtime: {}
[2024-12-11 23:16:46.437][11677][info][config] [source/server/configuration_impl.cc:168] loading tracing configuration
[2024-12-11 23:16:46.437][11677][info][config] [source/server/configuration_impl.cc:124] loading 0 static secret(s)
[2024-12-11 23:16:46.437][11677][info][config] [source/server/configuration_impl.cc:130] loading 1 cluster(s)
[2024-12-11 23:16:46.438][11677][info][config] [source/server/configuration_impl.cc:138] loading 1 listener(s)
[2024-12-11 23:16:46.440][11677][info][config] [source/server/configuration_impl.cc:154] loading stats configuration
configuration '/etc/envoy/redis.yaml' OK
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:127] Caught Segmentation fault, suspect faulting address 0x220
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:111] Backtrace (use tools/stack_decode.py to get line numbers):
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:112] Envoy version: a0504e87c5a246cb097b37049b1e4dc7706c2a90/1.32.2/Clean/RELEASE/BoringSSL
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:114] Address mapping: 5d3e70c4b000-5d3e747c5000 /usr/local/bin/envoy
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:121] #0: [0x7ce643148520]
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:121] #1: [0x5d3e725d135e]
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:121] #2: [0x5d3e72f903ee]
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:121] #3: [0x5d3e72f90219]
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:121] #4: [0x5d3e733d035c]
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:121] #5: [0x5d3e733cf550]
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:121] #6: [0x5d3e72f8febf]
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:121] #7: [0x5d3e70cd8b16]
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:121] #8: [0x5d3e7236c490]
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:121] #9: [0x5d3e7236b1fa]
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:121] #10: [0x5d3e7237803c]
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:121] #11: [0x5d3e72380073]
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:121] #12: [0x5d3e723767e1]
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:121] #13: [0x5d3e72368ea2]
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:121] #14: [0x5d3e70cd290c]
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:121] #15: [0x5d3e70cd294e]
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:121] #16: [0x5d3e725da280]
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:121] #17: [0x5d3e7255ad4d]
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:121] #18: [0x5d3e7255a5d9]
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:121] #19: [0x5d3e72547d95]
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:121] #20: [0x5d3e7251929b]
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:121] #21: [0x5d3e72519a3e]
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:121] #22: [0x5d3e70c4b14c]
[2024-12-11 23:16:46.441][11677][critical][backtrace] [./source/server/backtrace.h:121] #23: [0x7ce64312fd90]
Segmentation fault (core dumped)

Checking the above error with the -dev Docker image, has the same problem:

Envoy CLI validate -dev version
root@envoy-d9c55694c-crsgh:/# envoy -c /etc/envoy/redis.yaml --mode validate
[2024-12-11 23:29:14.911][796][info][main] [source/server/server.cc:889] runtime: {}
[2024-12-11 23:29:14.912][796][info][config] [source/server/configuration_impl.cc:173] loading tracing configuration
[2024-12-11 23:29:14.912][796][info][config] [source/server/configuration_impl.cc:124] loading 0 static secret(s)
[2024-12-11 23:29:14.912][796][info][config] [source/server/configuration_impl.cc:130] loading 1 cluster(s)
[2024-12-11 23:29:14.913][796][info][config] [source/server/configuration_impl.cc:140] loading 1 listener(s)
[2024-12-11 23:29:14.915][796][info][config] [source/server/configuration_impl.cc:156] loading stats configuration
configuration '/etc/envoy/redis.yaml' OK
[2024-12-11 23:29:14.915][796][critical][backtrace] [./source/server/backtrace.h:127] Caught Segmentation fault, suspect faulting address 0x220
[2024-12-11 23:29:14.915][796][critical][backtrace] [./source/server/backtrace.h:111] Backtrace (use tools/stack_decode.py to get line numbers):
[2024-12-11 23:29:14.915][796][critical][backtrace] [./source/server/backtrace.h:112] Envoy version: 602a2b97a54435c38cb5bacf133b9984d2212498/1.33.0-dev/Clean/RELEASE/BoringSSL
[2024-12-11 23:29:14.915][796][critical][backtrace] [./source/server/backtrace.h:114] Address mapping: 5dce9d1ac000-5dcea0d92000 /usr/local/bin/envoy
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #0: [0x7b2633dfb520]
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #1: [0x5dce9eb2e6b2]
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #2: [0x5dce9eb2dc43]
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #3: [0x5dce9f54d764]
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #4: [0x5dce9f54d589]
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #5: [0x5dce9f95d58c]
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #6: [0x5dce9f95c780]
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #7: [0x5dce9f54d22f]
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #8: [0x5dce9d236f56]
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #9: [0x5dce9e8c24a0]
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #10: [0x5dce9e8c120a]
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #11: [0x5dce9e8ce05c]
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #12: [0x5dce9e8d6093]
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #13: [0x5dce9e8cc801]
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #14: [0x5dce9e8beeb2]
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #15: [0x5dce9d230d3c]
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #16: [0x5dce9d230d7e]
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #17: [0x5dce9eb36960]
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #18: [0x5dce9eab784d]
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #19: [0x5dce9eab70d9]
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #20: [0x5dce9eaa4815]
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #21: [0x5dce9ea768ab]
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #22: [0x5dce9ea7704e]
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #23: [0x5dce9d1ac11c]
[2024-12-11 23:29:14.916][796][critical][backtrace] [./source/server/backtrace.h:121] #24: [0x7b2633de2d90]

Config:
Included on the Repro steps.
Logs:
Same as above.
Call Stack:
The above on Repro steps is all I have.

cc @mattklein123

cc @phlax do we provide a image that with unstripped binnary or with debug file? Then @L30Bola could produces more helpful stack.

there is the debug container https://hub.docker.com/r/envoyproxy/envoy/tags?name=debug

With that debug image, should I just re-run the same tests (and maybe save some file or even the entire output) or do I need to add any additional flag on the CLI?


Try bun:test

10 times faster than AVA at this point, comparable output
… etc

✓ isUserSettings NO https://github.com/sindresorhus/refined-github/actions/new
✓ isUserSettings NO https://github.com/refined-github/github-url-detection/actions
✓ isUserSettings NO https://github.com/refined-github/github-url-detection/actions/workflows/demo.yml
✓ isUserSettings NO https://github.com/refined-github/github-url-detection/actions/workflows/esm-lint.yml
✓ isUserSettings NO https://github.com/new
✓ isUserSettings NO https://github.com/organizations/npmhub/repositories/new
✓ isUserSettings NO https://github.com/fregante/browser-extension-template/generate
✓ is404
✓ is500
✓ isPRCommit404
✓ isPRFile404

716 |                   }
717 |           }
718 |   }
719 |
720 |   if (typeof url === 'string') {
721 |           url = new URL(url, location.origin);
            ^
TypeError: Type error
      at ./index.ts:721:8
      at ./index.test.ts:151:15
✗ getRepositoryInfo

 12058 pass
 1 fail
 Ran 12059 tests across 1 files [1350.00ms]

the error is probably wrong and I'm not going to investigate

Ignore parts related to https://github.com/refined-github/github-url-detection/pull/126


Fix #606 Use endpoint ID

Pull Request Test Coverage Report for Build 307

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage remained the same at 50.545%

Totals

Change from base Build 305:
0.0%

Covered Lines:
3549

Relevant Lines:
5941

💛  - Coveralls

@compulim Please put descriptions into the PRs. This should include the link to the Issue.
Note also that if the description is correct, GitHub will autoclose associated issues.
https://blog.github.com/2013-05-14-closing-issues-via-pull-requests/

@compulim Also, code changes mean a unit should have changed. Please add a test to validate this behavior.

Added unit tests

Merged even though the coverage is dropped because:

Our code change should not drop coverage (it's a property name change)
We introduced more unit tests in the code path, it should keep the coverage or increase it

So I think the coverage report is bugged for this PR.


Find & fix root cause of 'html-pipeline' issue

First spotted by Tim Blair in April (https://github.com/alphagov/govuk-developer-docs/commit/e9541eb4d01d1fb4b883041ca211613086618641), html-pipeline 2.11.0 causes issues with ASCII/UTF-8 processing:
Error processing resource for index: apis/search/faceted-search.html
"\xE2" from ASCII-8BIT to UTF-8
 govuk-developer-docs/.bundle/gems/commonmarker-0.19.0/lib/commonmarker.rb:26:in `encode'

We pinned html-pipeline to 2.5.0 in https://github.com/alphagov/govuk-developer-docs/pull/1818/commits/6f81229297ab2a3107b317313de8101c1898a7a7, but should investigate the root cause and fix it.

We saw a very similar error here: https://github.com/alphagov/govuk-developer-docs/pull/2575/commits/d95bcbd509b92b0da14af36d3bf49a962f3b5c10 - but with a different stack trace.


Unable to launch project in chrome which created using angular-cli

Bug Report or Feature Request (mark with an x)
Bug Report: Issue is only in Chrome

Versions.
@angular/cli: 1.0.5
node: 6.9.1
os: win32 x64
@angular/common: 4.1.3
@angular/compiler: 4.1.3
@angular/core: 4.1.3
@angular/forms: 4.1.3
@angular/http: 4.1.3
@angular/platform-browser: 4.1.
@angular/platform-browser-dynam
@angular/router: 4.1.3
@angular/cli: 1.0.5
@angular/compiler-cli: 4.1.3
Repro steps.
create an angular project using angular-CLI as mentioned in  https://angular.io/docs/ts/latest/cli-quickstart.html
Run ng serve
access application using http://localhost:4200/
The log given by the failure.
This site can’t be reached
localhost refused to connect.
Mention any other details that might be useful.
Able to access in Firefox without issues
In IE after uncommenting  the below lines in polyfills worked fine
/** IE9, IE10 and IE11 requires all of the following polyfills. **/
import 'core-js/es6/symbol';
import 'core-js/es6/object';
import 'core-js/es6/function';
import 'core-js/es6/parse-int';
import 'core-js/es6/parse-float';
import 'core-js/es6/number';
import 'core-js/es6/math';
import 'core-js/es6/string';
import 'core-js/es6/date';
import 'core-js/es6/array';
import 'core-js/es6/regexp';
import 'core-js/es6/map';
import 'core-js/es6/set';

@sitaram676 Is there any error you are getting? Try closing and reopening the chrome or incognito mode and see if it works.

I have the same issue. It works in chrome incognito, but not in regular chrome

I am facing same issue. I have even enabled localhost on my windows machine. <IP_ADDRESS> port is working. but localhost:4200 is still not working (not even in incognito mode).


release v0.2.1

The "no unit" feature is in main (and I've merge a few docs fixes and the call_on_dataset refactor) so I'd like to issue a release soon.
If there are no urgent bug fixes I'd issue the release tomorrow (if there is, please feel free to add a checklist to this comment).

the release is on PyPI and will be on conda-forge once the bot notices.


Test/fix Linux permissions for installing

https://github.com/NetSparkleUpdater/NetSparkle/blob/957d131b3e3f724ad3d020da46d239248ba95dc0/src/NetSparkle/SparkleUpdater.cs#L1257
How does sudo work here? Do we even need sudo? Does Linux pop open a thing asking for the password? (I doubt it.) Do we need to pop open a terminal and run things in there (aka make the process not silent so that they can be prompted for their password)? I'm not as familiar with how Linux works, plus there are so many distributions...
Links:

https://askubuntu.com/questions/515292/how-to-get-gui-sudo-password-prompt-without-command-line

There is a way to install linux packages without root by installing it with --force-not-root (https://askubuntu.com/questions/339/how-can-i-install-a-package-without-root-access).
But there may be a lot of problems with dependencies (https://stackoverflow.com/questions/18858412/errors-installing-a-deb-without-sudo-root).
Unfortunately a lot of distributions are not automatically popping up a graphical password prompt (or even have one).
I think the safest way is to open a separate terminal window with the sudo command (i've seen this method in the wild).
The terminal will then ask the user for the password. The problem with this is you have to find out which terminal emulator is used.
For that it is advised to go through a list of known terminal emulators (https://superuser.com/questions/1153988/find-the-default-terminal-emulator).
With the known terminal emulator (here urxvt) and the $SHELL variable (already used in SparkleUpdater.cs) you can open a new terminal window:
urxvt -e $SHELL -c "sudo echo hello world"
The much more unsafe method is to ask for the password from the SparkleUpdater and pass it as a parameter to the sudo command (https://superuser.com/questions/67765/sudo-with-password-in-one-command-line). But i think its very unwise to hold it in the application memory.


Run tests on PRs (needs review)

I'm not familiar with GitHub Actions but this should do it, please review.
Just so that problems can be fixed by the PR creator before merging.
See 89612a5 and 90fbfe4

I think that the checks are listed here means that it works. :)

Yep, thanks! 💪


Discussion: should namespaces be applied to normal properties too?

Namespaces are originally designed for link-relations and action names since these have a history of using URIs for identifiers.
The same idea could as well be applied to API data such that it becomes possible to mix data from different sources without name collisions (much like XML namespaces). That might though be too complicated to be worth it.
Example:
{
  "@namespaces":
  {
    "n1": { name: "acme.inc" },
    "n2": { name: "sultan.inc" }
  },

  "n1:Title": "Title for Acme data",
  "n2:Title": "Title for Sultan data",
  ...
}

One could also simply use sub-properties:
{
  "acme.inc":
  {
    "title: "Title for Acme data"
  },
  "sultan.inc":
  {
    "title: "Title for Sultan data"
  },
  ...
}

One thing I noticed with Mason is a lack of specifying the link relation type for embedded resources. That's where something like this would come in handy. However, when it comes to using IANA-registered link relations, the problem still remains since there's no need for a URI.
This is likely all moot given issue #19 though.


Compile Luau with optimizations enabled since C++ compilers perform important stack layout optimizations.
We support up to 1000 nesting depth in optimized builds (controlled by FInt::LuauRecursionLimit)
If compiling with optimizations is not possible, you can lower the value of FInt::LuauRecursionLimit.
Another options is of course to increase the thread stack size.

Is there an API for setting the LuauRecursionLimit FValue? I can set it by iterating over the value list but maybe there's an API call for that.

You can place LUAU_FASTINT(LuauRecursionLimit) in the outer scope of the file and then use FInt::LuauRecursionLimit.value = 500;.

I would also suggest that overflowing the stack is still an issue that should be fixed, even if it happens without optimisations.

Many of the algorithms used by parser, compiler and type inference are recursive in nature and we do not plan to rework that.

Maybe the default depth should be 256 or something.

We always had a limit of 1000 and there already exists code that works only with this limit.
To preserve backwards compatibility, we do not plan to ever lower this limit.