[improve][io] reduce dependencies of pulsar-io-common module

Motivation
pulsar-io-common is a module published as convenience for java connectors to help with loading configuration.
When a connectors declares it, it brings also pulsar-common which contains a lot of other transitive dependencies. (for example, Netty)
We can remove all the non necessary dependencies since it's trivial to replace their usage in the pulsar-io-common module.
Modifications

Removed pulsar-common and commons-lang dependecies and replaced with vanilla methods 100% compatible
Improve usage of the underlyng ObjectMapper used for read the config

Verifying this change

[x] Make sure that the change passes the CI checks.

Documentation

[ ] doc
[ ] doc-required
[x] doc-not-needed
[ ] doc-complete

Matching PR in forked repository

Codecov Report

Merging #19000 (14737bc) into master (feb3cb4) will decrease coverage by 9.57%.
The diff coverage is 5.26%.

@@             Coverage Diff              @@
##             master   #19000      +/-   ##
============================================
- Coverage     46.35%   36.78%   -9.58%
+ Complexity     8939     1956    -6983
============================================
  Files           597      209     -388
  Lines         56858    14406   -42452
  Branches       5905     1567    -4338
============================================
- Hits          26357     5299   -21058
+ Misses        27616     8532   -19084
+ Partials       2885      575    -2310

Flag
Coverage Δ

unittests
36.78% <5.26%> (-9.58%)
:arrow_down:

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files
Coverage Δ

...va/org/apache/pulsar/client/impl/ConsumerImpl.java
15.09% <0.00%> (+<0.01%)
:arrow_up:

...he/pulsar/client/impl/MultiTopicsConsumerImpl.java
22.80% <0.00%> (+0.01%)
:arrow_up:

...ache/pulsar/client/impl/ZeroQueueConsumerImpl.java
0.00% <0.00%> (ø)

...va/org/apache/pulsar/client/impl/ConsumerBase.java
21.51% <6.66%> (-0.42%)
:arrow_down:

...g/apache/pulsar/client/impl/ConnectionHandler.java
50.00% <0.00%> (-5.32%)
:arrow_down:

...va/org/apache/pulsar/client/impl/ProducerBase.java
32.69% <0.00%> (-1.93%)
:arrow_down:

...rg/apache/pulsar/broker/delayed/bucket/Bucket.java

.../pulsar/broker/service/BrokerServiceException.java

...va/org/apache/pulsar/broker/service/ServerCnx.java

...ar/broker/loadbalance/impl/BundleSplitterTask.java

... and 384 more


Calculator in C++

You have pulled all your commits into this Pull Request. If I merge this I would have to close others(439,437,441,437).
Do you want me to continue or you would open separate PR's for all the commits.

Please merge them as individual PR's and NOT as a single PR.
Thanks in advance.
On Sat, Oct 17, 2020 at 12:09 PM Amritansh Vajpayee <
<EMAIL_ADDRESS>wrote:

You have pulled all your commits into this Pull Request. If I merge this I
would have to close others(439,437,441,437).
Do you want me to continue or you would open separate PR's for all the
commits.
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/amritansh22/Data-Structures-and-Algorithms-in-cpp/pull/438#issuecomment-710761602,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/ANFO4UVKHHL2LDMEAZTTBU3SLE33ZANCNFSM4SUEPR2A
.

This is not possible. You have to open separate PR for them or revert commits in individual PR's

Okay i'll open separate PR's. For now you can merge them and close the
others as you have mentioned before.
On Sat, Oct 17, 2020 at 7:25 PM Amritansh Vajpayee<EMAIL_ADDRESS>wrote:

This is not possible. You have to open separate PR for them or revert
commits in individual PR's
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/amritansh22/Data-Structures-and-Algorithms-in-cpp/pull/438#issuecomment-710988662,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/ANFO4URYNVWI6V6YEXCRVITSLGO6DANCNFSM4SUEPR2A
.

Are you going to merge them? Like let me know if there are any corrections or any changes to be made.

@mirajkarsaurabh All your code files are in .txt format, please change them to c++


Fixes for test installers

Fix various installers, to get a clean make fmt-build

Backports from #200

Use new universal installer for Nodejs
install prettier-ruby and prettier-svelte plugins locally in /tmp
use newer prettier option --plugin= instead of --parser= for
prettier-ruby and prettier-svelte

Use standard local rust/rustfmt install for test setup instead of tarball (no longer available)

install locally, change permissions to make the install visible to all users, and then symlink
to the install dir and config in the global /etc/bash.bashrc so local test user will picks them up.

Change filename to download for nixfmt (now includes OS/arch)

There was initially no binary available when nixfmt was updated,
but the devs there were kind enough to provide one:
https://github.com/serokell/nixfmt/issues/139

We might also need to bump the base image version, it's currently 20.04 but that ships Emacs 26, which https://github.com/radian-software/apheleia/pull/215 dropped support for.

Closed in favor of #242

Closed in favor of #242


Compile scaling results for ClimaAtmos.jl on Derecho supercomputer

Compile scaling results for ClimaAtmos.jl on Derecho supercomputer

Here's more things that we could explore to mprove scaling:

MPICH_GPU_MANAGED_MEMORY_SUPPORT_ENABLED:

https://ncar-hpc-docs.readthedocs.io/en/latest/compute-systems/derecho/starting-derecho-jobs/derecho-job-script-examples-content/?h=set_gpu
# (Optional: Enable GPU managed memory if required.)
#   From ‘man mpi’: This setting will allow MPI to properly
#   handle unify memory addresses. This setting has performance
#   penalties as MPICH will perform buffer query on each buffer
#   that is handled by MPI)
# If you see runtime errors like
# (GTL DEBUG: 0) cuIpcGetMemHandle: invalid argument,
#  CUDA_ERROR_INVALID_VALUE
# make sure this variable is set
export MPICH_GPU_MANAGED_MEMORY_SUPPORT_ENABLED=1

Maybe with this we don't need JULIA_MEMORY_POOL="none" which would allow us to use the new allocator

CPU/GPU affinity

From the same page:

Binding MPI ranks to CPU cores can also be an important performance consideration for GPU-enabled codes, and can be done with the --cpu-bind option to mpiexec. For the above example using 2 nodes, 4 MPI ranks per node, and 1 GPU per MPI rank, binding each of the MPI ranks to one of the four separate NUMA domains within a node is likely to be optimal for performance. This could be done as follows:

mpiexec -n 8 -ppn 4 --cpu-bind verbose,list:0:16:32:48 ./set_gpu_rank ./executable_name

We should ensure that we are doing Device-to-Device communication, also when going across nodes (this might require fiddling with the RMDA protocol)

It would also be good to run a profiled run at least once to check why scaling drops


Provide the ability to pull missing buildtrees via the scheduler outside of user invoked bst pull & build

See original issue on GitLab
In GitLab by [Gitlab user @tpollard] on Nov 20, 2018, 15:29
Background
https://gitlab.com/BuildStream/buildstream/issues/494 has criteria which expects the buildstream scheduler to be able, as an example, to attempt to pull a missing artifact buildtree dir if that is the given content/config in which the bst workspace was initiated.
https://gitlab.com/BuildStream/buildstream/merge_requests/786/ Added the default behaviour of not downloading (with the ability to override) artifact buildtrees by default when directly spawning element pull jobs (element.py to artifactcache.py) via stream.py's construction of scheduler pull queues. As it stands the only two bst commands that utilise said pull queues are bst pull and build. These queues also provide the functionality to download the missing buildtree into an existing build artifact.
As it stands when attempting to use a buildtree anywhere else in the codebase, the assumption that it is or will be cached locally has to currently be skipped, warning the user as such if appropriate. The pullqueue scheduler creation should be made accessible to these instances (workspace buildtrees, pushing partial artifacts, staging buildtrees in sandbox as examples) via one api path to attempt the partial pull if appropriate.
Task description

Create a generic way for the pullqueue scheduler to be generated outside of bst pull/build which can be used throughout buildstream in instances where a cached buildtree is expected to be required
Implement into said instances as appropriate once available.

Acceptance Criteria
This will close the final point of https://gitlab.com/BuildStream/buildstream/issues/494

In GitLab by [Gitlab user @tpollard] on Nov 20, 2018, 15:30
marked this issue as related to #494

In GitLab by [Gitlab user @tpollard] on Nov 20, 2018, 15:31
marked this issue as related to #740

In GitLab by [Gitlab user @tristanvb] on Nov 27, 2018, 06:05
changed title from Provide the ability to pull missing buildtrees via the scheduler outside of user invoked bst pu{-sh-} & build to Provide the ability to pull missing buildtrees via the scheduler outside of user invoked bst pu{+ll+} & build

In GitLab by [Gitlab user @tristanvb] on Nov 27, 2018, 06:06
This should be blocker for 1.4

In GitLab by [Gitlab user @tpollard] on Nov 27, 2018, 15:54
https://gitlab.com/BuildStream/buildstream/merge_requests/873 adds api to artifactcache to query if an element contains a given subdir (buildtree), this may need to land as part of this issue. At the stream level if we're attempting to use a buildtree (i.e as 873 is doing, putting a buildtree into a workspace) then it will allow us to construct a pull queue for attempting to pull it if it's missing.

In GitLab by [Gitlab user @tpollard] on Nov 27, 2018, 16:00
This will be usable in cases where we know we explicitly want to attempt to have a buildtree (workspace open, push) as we can add a pullqueue for the given elements at the stream level as usual.  Later interactions that happen within element.py will prove to be more of an issue if not currently captured by current queue logic.

In GitLab by [Gitlab user @tpollard] on Nov 27, 2018, 16:40
Hi [Gitlab user @tristanvb] after assessing things, I think I'm going to go ahead with attempting to do this via a helper function to stream (_buildtree_required() maybe), which when queried will define if a specific command should call pull() internally to instantiate the creation of a pullqueue for buildtrees of elements where needed. It will do this by checking if current config (pull_buildtrees context) is set, and if the given artifact/s contain their buildtrees or not.
It was suggested I look at calling stream.pull() in cli.py where logic deemed it necessary to do so for commands such as workspace open, but I feel this logic is more suited to stream. The main reason being as it stands we don't currently query the artifact cache from cli.py. For instance in bst push & pull, we allow it to flow to stream.py before checking the artifactcache context for actual available remotes, rather than doing it directly in cli.py
Does this sound plausible? (I'm not against doing it in cli.py, I'm just trying to follow the current style (I think!))

In GitLab by [Gitlab user @tpollard] on Nov 28, 2018, 10:07
assigned to [Gitlab user @tpollard]

In GitLab by [Gitlab user @tpollard] on Nov 28, 2018, 16:26
mentioned in merge request !978

In GitLab by [Gitlab user @juergbi] on Nov 30, 2018, 14:10
closed via merge request !978

In GitLab by [Gitlab user @juergbi] on Nov 30, 2018, 14:10
mentioned in commit ad293ed38b5d9d72432ac882901a3c28b720069b


[AutoRelease] t2-network-2024-06-11-97046(can only be merged by SDK owner)

https://github.com/Azure/sdk-release-request/issues/2048
Recording test fail, detailed info is in pipeline log(search keyword FAILED)!!!
BuildTargetingString
azure-mgmt-network
Skip.CreateApiReview
true

issue link:https://github.com/Azure/sdk-release-request/issues/2048


Crash while parsing JSON command

Backtrace
{"id":"24cc8dda5d1983c21d5ff1fb5f1470f6","target":"page$ac1b788632cd57ac91c222ca40f42df8","name":"invokeMethod","params":["evaluate",null],"response":{"0":{"ALLOW_KEYBOARD_INPUT":1,"ATTRIBUTE_NODE":2,"CDATA_SECTION_NODE":4,"COMMENT_NODE"
:8,"DOCUMENT_FRAGMENT_NODE":11,"DOCUMENT_NODE":9,"DOCUMENT_POSITION_CONTAINED_BY":16,"DOCUMENT_POSITION_CONTAINS":8,"DOCUMENT_POSITION_DISCONNECTED":1,"DOCUMENT_POSITION_FOLLOWING":4,"DOCUMENT_POSITION_IMPLEMENTATION_SPECIFIC":32,"DOCUME
NT_POSITION_PRECEDING":2,"DOCUMENT_TYPE_NODE":10,"ELEMENT_NODE":1,"ENTITY_NODE":6,"ENTITY_REFERENCE_NODE":5,"NOTATION_NODE":12,"PROCESSING_INSTRUCTION_NODE":7,"TEXT_NODE":3,"accessKey":"","addEventListener":null,"align":"","appendChild":
null,"attributes":{"0":{"ATTRIBUTE_NODE":2,"CDATA_SECTION_NODE":4,"COMMENT_NODE":8,"DOCUMENT_FRAGMENT_NODE":11,"DOCUMENT_NODE":9,"DOCUMENT_POSITION_CONTAINED_BY":16,"DOCUMENT_POSITION_CONTAINS":8,"DOCUMENT_POSITION_DISCONNECTED":1,"DOCUM
ENT_POSITION_FOLLOWING":4,"DOCUMENT_POSITION_IMPLEMENTATION_SP

SyntaxError: Unexpected end of JSON input
    at Object.parse (native)
    at Liner.<anonymous> (/usr/src/app/node_modules/phantom/lib/phantom.js:144:36)
    at emitOne (events.js:96:13)
    at Liner.emit (events.js:188:7)
    at readableAddChunk (_stream_readable.js:176:18)
    at Liner.Readable.push (_stream_readable.js:134:10)
    at Liner.Transform.push (_stream_transform.js:128:32)
    at Liner.flush [as _flush] (/usr/src/app/node_modules/linerstream/index.js:26:10)
    at Liner.<anonymous> (_stream_transform.js:118:12)
    at Liner.g (events.js:291:16)

I do not have a solid repro now. Happens intermittently, looks like for some reason there is a newline midway through the command and Liner breaks it there, which causes invalid JSON. For now, I will start catching exceptions there and try to see if indeed there is a continuation in the next line or whether it's PhantomJS crashing or anything along those lines.
Environment
OS: Docker image node:6.9-slim based on Debian
Phantom: 2.1.21 (npm install phantomjs)

I'm getting the same issue. Any advises ?

It was OOM in my case. Bumping memory limit and adding swap memory helped in my case.


Share Config for Cifar10 eps != 1

Hi,
In the paper https://arxiv.org/pdf/2204.13650.pdf, the following plot is presented:

.
However, the configs associated https://github.com/deepmind/jax_privacy/tree/main/experiments/image_classification/configs only have CIFAR10 for stop_training_at_epsilon = 1.
I am curious what the config that acheived SOTA looks like. Is the only change the "stop_training_at_epsilon" was set to a larger number, in order to generated the plots in the paper (I presume 8). Or are other values are different, such as std_relative=10.

If possible, could you share how std_relative=10. was selected?
and if this config was the config used for the SOTA CIFAR-10 results.

Hi, all the hyper-parameters are reported in appendix C.5 of the paper, their values should be straightforward to plug into the existing config files.


add api to map cid to multiadress suffexed with cid on any node

so if i have cid, i can map to adress to download from peer (via external proxy adress or other)

existing apis (so also hard to read these without examples of input out puts):
-- Download file `cid` from IPFS node `from` and save it to `node`
func get_from(node: PeerId, cid: CID, from: Multiaddr) -> IpfsGetResult
... seems returns local path

-- Get externally available multiaddress of IPFS's HTTP RPC endpoint (usually on port 5001)
func get_external_api_multiaddr(node: PeerId) -> IpfsMultiaddrResult
.. not cid specific - need to merge somehow values - error prone.

assuming above do not cover next:
--- gets download link via proxy for give CID
get_from_external_api_multiaddr(node: PeerId, cid: CID) -> IpfsMultiaddrResult
read it as part `IpfsFluence` path utility


Refactor boundary condition types

Purpose
Refactor boundary condition types.
What we had in place was a little confusing (you could either pass a NamedTuple with values of type "AbstractSoilBC" or something of type "AbstractSoilBC" as your boundary condition), had very little unification between how we handled BC between soil +soil co2, and had nested named tuples for models with only a single boundary condition needed.
I was also finding it very hard to use the RichardsAtmosDrivenBC in PR #511 due to the design.
After this PR, we would have:
Instead of:
boundary_fluxes = (top = RichardsAtmosDrivenFluxBC(), bottom = (water = WaterFluxBC(),))

you now have
boundary_fluxes = (top = RichardsAtmosDrivenFluxBC(), bottom = WaterFluxBC()).

instead of
boundary_fluxes = (top = (water = MoistureBC(), bottom = (water = WaterFluxBC(),))

you now have
boundary_fluxes = (top = MoistureBC(), bottom = WaterFluxBC())

instead of :
boundary_fluxes = (top = (water = MoistureBC(), heat = TemperatureBC()), bottom = (water = WaterFluxBC(), heat = HeatFluxBC(),))

you now have:
boundary_fluxes = (top = WaterHeatBC(; water = MoistureBC(), heat = TemperatureBC()),
                   bottom = WaterHeatBC(; water = WaterFluxBC(), heat = HeatFluxBC()))

instead of
boundary_fluxes = (top = AtmosDrivenFluxBC(), bottom = (water = WaterFluxBC(), heat = HeatFluxBC(),))

now, we would have
boundary_fluxes = (top = AtmosDrivenFluxBC(), bottom = WaterHeatBC(; water = WaterFluxBC(), heat = HeatFluxBC()))

To-do
review
Content
This PR refactors the code so that

You can make types of AbstractWaterBC which can be used for RichardsModel or for the water equation in the EnergyHydrologyModel. All of our old BC types are now subtyped from this.
You can also define types of AbstractHeatBC for the soil heat equation. All of our old BC types are now subtyped from this.
To create BC for the EnergyHydrologyModel, you can combined an AbstractHeat and AbstractWater BC if these are treated independently, or use a BC that indicates that the water and heat BC are set in way that depend on each other. The former is a WaterHeatBC <: AbstractEnergyHydrologyBC, the second has one example currently: AtmosDrivenFluxBC <: AbstractEnergyHydrologyBC. (change: introduce WaterHeatBC struct instead of using a NamedTuple, introduce abstract type)
The SoilCO2 model follows the same conventions as RichardsModel (single equation, single BC).
Since boundary condition types may require additional variables, all PDE models now use and extend the boundary_var methods instead of this being done haphazardly/only for soil.
I removed the nested named tuples with redundant information for soil co2 and richards equation. This means we specify BC like top = WaterFluxBC() and not top = (;water = WaterFluxBC()))
soil_boundary_fluxes now updates in place (easy change to make but not directly related to this PR)

Review checklist
I have:

followed the codebase contribution guide: https://clima.github.io/ClimateMachine.jl/latest/Contributing/
followed the style guide: https://clima.github.io/ClimateMachine.jl/latest/DevDocs/CodeStyle/
followed the documentation policy: https://github.com/CliMA/policies/wiki/Documentation-Policy
checked that this PR does not duplicate an open PR.

In the Content, I have included

relevant unit tests, and integration tests,
appropriate docstrings on all functions, structs, and modules, and included relevant documentation.

[x] I have read and checked the items on the review checklist.

@juliasloan25 investigating cleaning up BC here....will tag for a review if it pans out!

I added a tutorial for soil boundary conditions! good call. it'll help us down the line too :D


Fix broken URLs

URL checker was down temporarily but #2659 brings it back up again.
At the moment, there are a lot of broken URLs - https://github.com/pybamm-team/PyBaMM/actions/runs/4090861650/jobs/7054568267 - which should be fixed.
Most of them originate from the documentation revamp, some of them are false alarms, and some of them are from external repositories/sources.

Started working on it #2656

@Saransh-cpp
How do we know where these links were used?
Then we can replace it with the correct link like in #2656

You can use the search feature of your IDE (VSCode has a great search functionality).
Alternatively, you can use CLI tools like grep (UNIX) and findstr (Windows). For example -
cd PyBaMM
grep -nr the/url/you/want/to/search     # -r -> recursive, -n -> print line numbers

Something similar should work for findstr as well.

Thank you for that. Used findstr and found the file location of missing links which can be viewed from Google Sheet-PyBaMM Link Fixes


Update README.md (fixes#36)

A few months ago, I encountered the issue described in #36. After that day, I tried several times to solve the problem without success, so I gave up. This week, I attempted to install again on a freshly formatted Arch Linux system with all the dependencies installed, but I faced the same issue. Upon further investigation, I discovered that the problem was related to my DNS, which was unable to resolve "level3.blizzard.com" to an IP address. After changing the DNS to Google's and clearing my laptop's DNS cache, I run ./craft.sh again and it installed without any problems. I changed my DNS back to automatic and tried to install again, but encountered the same error: "Temporary failure in name resolution." So, I'm certain that the issue was the DNS.
In that case, I updated the README to include information about the issue and assist potential individuals who have faced or will face this problem :D
I also removed the '$' character in the places where the code should be copied, to make it easier for users to copy and paste using the icon or manually.
This is my first contribution, so I apologize for any mistakes.

oh nice, thanks for figuring that out. I remember I've added this line --cdn "http://level3.blizzard.com/tpr/hs" in the script to use this level3 cdn because it greatly increased download speed for my location. you can also try to remove this parameter and check if it helps or force another cdn that's better for your location


Remove dependency on Basic Auth

Make Basic Authentication a configuration option. Rather than assume that the API is going to use it maybe have a configuration that allows different types of authentication.

No longer an issue since with version .13 you don't need any configuration at all.


feat: Use thiserror 2.0

Minimal changes to update miette to use thiserror 2.0 and re-export core::error::Error as StdError now instead of the potentially custom implementation from miden_thiserror.
I'm guessing that the no-std branch was used to publish current miden-miette so I branched off of that.
The changes in this PR are successful (with warnings):

cargo check --no-default-features
cargo check --features std

cargo check --all-features does not work but it does not work on the no-std branch for the same reasons, so I assume this somehow fine.
I did a test run in a miden-vm PR to see if these changes pass CI and they do: https://github.com/0xPolygonMiden/miden-vm/actions/runs/12081536640

Since the build in miden-vm passed, I believe this should be good to go and after merging, we can release this.
Not entirely sure whether this is technically a breaking change or not. It really only affects no-std configurations and here the previous copy of core::error::Error was replaced by the actual core::error::Error, so the differences should be basically none.
But maybe there is a subtle difference. I'm also guessing it doesn't matter very much because we are the only users of this crate, and so we could go with the safe option of bumping the major version. Then no miden-vm dependency of <= 0.11 pulls this new release and we're definitely fine.


Logic App Workflow Assistant is not working

Describe the Bug with repro steps
Go to your Logic App workflow and click on Assistant.
Ask a query
Error pops up with below:
Sorry, something went wrong. Please try again.
chat-session-id:BB15EEC8-BC6E-4D57-8465-151B4DE50A58
What type of Logic App Is this happening in?
Standard (Portal)
Which operating system are you using?
Windows
Did you refer to the TSG before filing this issue? https://aka.ms/lauxtsg
No
Workflow JSON

Screenshots or Videos
No response
Browser
Chrome
Additional context
No response

Hi @MisbahAfreen thanks for raising this issue. I will close this issue as duplicated of https://github.com/Azure/LogicAppsUX/issues/6266. Can you verify if it's working here: https://aka.ms/emacanary?


Frames very dark at low light

I'm not fully sure if I get the way how the IR cameras and emitters on Laptops work correctly.  When running sudo howdy test however with only artificial lighting in my room I can only see the lights in my room. The rest is completely black. By putting a mirror in front of the camera I can confirm that the IR emitter is flashing. Also running https://github.com/EmixamPP/linux-enable-ir-emitter told me my IR emitter is already working fine.
Now is my expectation to be able to use face detection at low light wrong or do I need to fix the IR emitter?
My setup:
Linux Mint 21
howdy 2.6.1
Lenovo Yoga 16ACH6
lsusb
Bus 004 Device 001: ID 1d6b:0003 Linux Foundation 3.0 root hub
Bus 003 Device 003: ID 04f2:b6cb Chicony Electronics Co., Ltd Integrated Camera
Bus 003 Device 002: ID 0489:e0cd Foxconn / Hon Hai Wireless_Device
Bus 003 Device 001: ID 1d6b:0002 Linux Foundation 2.0 root hub
Bus 002 Device 001: ID 1d6b:0003 Linux Foundation 3.0 root hub
Bus 001 Device 001: ID 1d6b:0002 Linux Foundation 2.0 root hub

Anyone has any idea on this?


build: generalize Dockerfiles and reuse common build steps

Closes: #1685
What is the purpose of the change
Reuse common Docker build steps across all Dockerfiles
Testing and Verifying
Tested by:
docker image rm -f $(docker image ls -aq)

make docker-build-setup

make docker-build-builder

make docker-build-debug

make docker-build-e2e-init-chain

make docker-build-e2e-init-node

Documentation and Release Note

Does this pull request introduce a new feature or user-facing behavior changes? no
Is a relevant changelog entry added to the Unreleased section in CHANGELOG.md? no
How is the feature or change documented? not applicable

cc @niccoloraspa

I think this breaks the docker CI: https://github.com/osmosis-labs/osmosis/blob/main/.github/workflows/docker.yml

I understand the idea behind the PR, but I have mixed feelings about it.
Personally I prefer to keep Dockerfile flat and self-contained, and splitting a Dockerfile  in 3 to favour reusability I think creates confusion.
We have made a lot of progress in reducing the number of Dockerfiles and this creates 2 additional Dockerfiles that we have to mantain.
I think the correct approach would be to remove the
Also the:

tests/localosmosis/mainnet_state/Dockerfile-stateExport will be removed soon

I think the correct approach would be to remove the e2e Dockerfile favouring the re-use of the main Dockerfile.

I have mixed feelings about this PR.
I don't think splitting the main Dockerfile into 3 to favor re-usability is the right approach. We have made a lot of progress in reducing the number of Dockerfiles, and this creates 2 additional Dockerfiles that we have to maintain.
I think the right approach would be to re-use the main Dockerfile in e2e.
The tests/localosmosis/mainnet_state/Dockerfile-stateExport will be removed soon.

I prefer Dockerfile to be as flat and self-contained as possible.
A Dockerfile is like a contract between you and the users who run it. The simplicity favours the transparency.

I don't think splitting the main Dockerfile into 3 to favor re-usability is the right approach. We have made a lot of progress in reducing the number of Dockerfiles, and this creates 2 additional Dockerfiles that we have to maintain.

The core issue this is solving is that there are several Docker files that utilize the same logic.
As a result, when one gets updated, all other Dockerfiles aren't. They end up going out of sync. For example, both init.Dockerfile and Dockerfile-stateExport are out of sync from the main one. It also happened so that not all Dockerfiles being updated broke scripts and tests for us in the past. That's why encapsulating common Docker logic is useful.
Additionally, it is an overhead to update them in multiple places every time.
Analogous to how we encapsulate duplicated code into functions, we should do the same with Dockerfile for the same reasons of them going out of sunc and having to update them in multiple places.

this creates 2 additional Dockerfiles that we have to maintain.

I think it is easier to maintain 2 extra Dockerfiles that are reused by 3 others rather than having 3 Dockerfiles with the same logic.
In the former case, one change would need to be made to 1 file, and in the latter case to 3 files.

I think the right approach would be to re-use the main Dockerfile in e2e

In e2e, we are running a script, not an osmosisd binary. Same as in the state export Dockerfile. However, the setup logic is exactly the same.
It is not possible to utilize the main dockerfile as a builder because its last build step is a runner.

FYI the tests/localosmosis/mainnet_state/Dockerfile-stateExport will also be removed soon.

That's great! In that case, it would be possible to consolidate setup.Dockerfile and builder.Dockerfile into one.
Currently, I still think that this change introduces an improvement rather than additional overhead. Please let me know what you think

I generally agree with the assesment that there should really just be one "build" dockerfile, and other things should just use that if they have extra steps.

Analogous to how we encapsulate duplicated code into functions, we should do the same with Dockerfile for the same reasons of them going out of sunc and having to update them in multiple places.

Modularity's great but for me, keeping the main Dockerfile transparent and self-contained is a priority over the rest.
Also, keep in mind that Dockerfile-stateExport will leave only:

the main Dockerfile
the e2e init.Dockerfile

Afaik, these two only share the "setup" part (downloading CosmWasm and some packages). I think the intersection would be too small to justify splitting them.

Analogous to how we encapsulate duplicated code into functions, we should do the same with Dockerfile for the same reasons of them going out of sunc and having to update them in multiple places.

Modularity's great but, for me, keeping the main Dockerfile transparent and self-contained is a priority over the rest.
Also, keep in mind that removing the Dockerfile-stateExport leaves only:

the main Dockerfile
the e2e init.Dockerfile

Afaiu, these two only share the "setup" part (downloading CosmWasm and some packages) and then they continue to build their own binary. I think the intersection would be too small to justify splitting them.
P.S. You can run scripts with the main Dockerfile if needed. This is what localOsmosis is doing: https://github.com/osmosis-labs/osmosis/blob/main/tests/localosmosis/docker-compose.yml#L17

Sounds good, thanks! Let me try running the script via a different entrypoint. If that works, we can drop this common builder.
I do think, however, that it is inevitable to end up splitting them as the system grows and new Dockerfiles continue requiring custom functionality on top of the builder


key_pair module reports incorrect latest version

Description
The terraform init process errors with The newest available version is 2.0.3; according to the releases, the latest version is 2.2.1.
% make init
terraform init -get=true -backend=true -reconfigure

Initializing the backend...

Successfully configured the backend "s3"! Terraform will automatically
use this backend unless the backend configuration changes.
Initializing modules...
╷
│ Error: Unresolvable module version constraint
│
│   on key-pair.tf line 9:
│    9: module "key_pair" {
│
│ There is no available version of module "registry.terraform.io/terraform-aws-modules/key-pair/aws" (key-pair.tf:9) which matches the given version constraint. The newest available version is 2.0.3.
╵

[X] ✋ I have searched the open/closed issues and my issue is not listed.

Versions
module "key_pair" {
  source  = "terraform-aws-modules/key-pair/aws"
  version = "~> 2.2.1"
...
}

Terraform version:

% tf version
Terraform v1.7.5
on darwin_arm64

Provider version(s):

provider registry.terraform.io/hashicorp/aws v5.47.0
provider registry.terraform.io/hashicorp/cloudinit v2.3.4
provider registry.terraform.io/hashicorp/helm v2.13.1
provider registry.terraform.io/hashicorp/kubernetes v2.29.0
provider registry.terraform.io/hashicorp/null v3.2.2
provider registry.terraform.io/hashicorp/time v0.11.1
provider registry.terraform.io/hashicorp/tls v4.0.5

Reproduction Code [Required]

Steps to reproduce the behavior:
Workspaces: no
Clear Cache: yes
Steps to Reproduce

Create module like

module "key_pair" {
  source  = "terraform-aws-modules/key-pair/aws"
  version = "~> 2.2.1"

  key_name_prefix    = local.name
  create_private_key = true

  tags = local.tags
}

terraform init
ERROR

The newest available version is 2.0.3.

Expected behavior
The module initializes.
Actual behavior
The module failed init for the version number.

module "key_pair" {
  source  = "terraform-aws-modules/key-pair/aws"
  version = "~> 2.2.1"  # 2.0.3 does not satisfy this condition
...
}

You should use version = "~> 2.0" or similar.

@bryantbiggs  Good tips, thank you. I did not have -upgrade in there; that helped.
@antonbabenko, updated the version to reflect suggested. But, version = "~> 2.0" doesn't get me to 2.2.1.
In this case, I've upgraded all modules (using the same method) but only the key_pair errors; not sure why the others worked without it then 🤔
Any ideas?

There is no module terraform-aws-modules/key-pair/aws with version 2.2.1 (only 2.0.3 - https://registry.terraform.io/modules/terraform-aws-modules/key-pair/aws/latest )

The link was miss-documented in the code 😞 it's always the details.


refactor: use testutil.SystemTest for getting project ids

There were some lingering references of getting the test project via os.Getenv. This switches the remaining non-main tests to use testutil.SystemTest(t).ProjectID instead.

This is intentional -- that way, we can avoid having golang-samples as a dependency in the go.mod for the sample functions and apps.


The repository should be moved to the Pull App organization

IMO, it'd be better if this repository would be moved to the Pull App organization.
It makes more sense for the repository to be in the organization.
Thanks. 🙂

Thanks for opening the issue. There are no plans to move at this time. We'll update this issue if this changes in the future.


Field Customizer context does not provide access to the list

Category

[x] Bug

Describe the bug
Neither the FieldCustomizerContext nor the IFieldCustomizerCellEventParameters objects provide any mechanism to identify the list the field being rendered belongs to.
There is a context.pageContext property which has a list: SPList property. There is a lot of example code out there using this property but it only works by accident. If the field is being rendered on a standard list view page then context.pageContext.list will happen to point to the list that the field belongs to. But, if the field is being rendered in a list web part on a site page then pageContext.list will be the Site Pages library.
Steps to reproduce

Create a Field Customizer and attach it to a list
Add a List web part to a Site Page
Use a debugger to break in your onRenderCell method
Try to find the identity of the source list in any of the available data.

Expected behavior
There should be some sort of list property on the context or the event identifying the list the field belongs to.
Environment details (development & target environment)
Sharepoint Framework 1.11.0
TypeScript 3.3.4

I found a partial workaround. event.listItem contains a FileRef property that can be used to work out the list URL.
This works for my specific use case
private getListUrlFromEvent(event: IFieldCustomizerCellEventParameters): string {
    const fileRef: string = event.listItem.getValueByName('FileRef');
    const i = fileRef ? fileRef.lastIndexOf('/') : -1;
    return i >= 0 ? fileRef.substring(0,i): null;
}

The URL processing would need more work to handle a library with folders.

Hello @IvanTheBearable - sorry for the long delay, missed this one due to issues with the tagging.
You can access the list view accessor using this.context.tryGetListView(). Currently this object provides access to the columns only.
But we're actively working to provide additional context in there:

basic list info
view info
rows
selected rows
filters and sorting

We're planning to ship it in one of the upcoming releases.
If you have any other ideas for enhancements, please post them to one of the following discussions:

Command Sets
Field Cutomizers
Application Customizers


Cleanup type parsing

Implementation of the suggested cleanup of type parsing from #474

Updated with proper implementation of type resolving. Somebody should probably check this out

Looks good to me


Consider adding Profile entry point in Getting Started

Can we add a Profile entry point in Welcome Start. Something like this (wording in progress):

I have discussed with @bhavyaus and her main concerns are that since we are adding remote entries we might end up with too many (6 total).
@sandy081 and me believe this is an important entry point for new users to choose between some built-in profiles. For example, this way users could easy choose to setup their VS Code for data science. We will soon have other built-in profiles (Java, Text Editor, Cloud...)

After discussion within the team we agreed that we would add this as a step in the "Get Started with VS Code" walkthrough.
@bhavyaus how do you suggest we proceed, is it ok if I just add this? What step do you think this should be?
@daviddossett could you help with an illustration for the walkthrough?

I like the outcome of adding profiles in the walk through

I like the idea too but I would also argue that these built-in walkthroughs already feel quite heavy given the # of steps. What, if any, could we consider swapping out here?
cc @digitarald for walkthrough research insights.
I can help with the artwork, yes.

Actually, chewing on this a bit more, I wonder if Profiles makes sense as an entry in the very first walkthrough. That's a pretty advanced feature to be seeing in the first 30 seconds. How likely are we to think that brand new users will be interested in profiles?

@daviddossett good questions. @bhavyaus informed me that we are already cleaning up the built-in walkthrough. Bhavya what steps did you consider to remove?
Our vision is that profiles can help brand new users setup VS Code in a particular way. So yes, it is an advanced topic underneath, but we wish that built-in profiles are useful for new users - and the fact that is uses profiles is just an implementation detail. What do you think about this?

Could we include this as a step in the Learn the Fundamentals walkthrough and highlight the ability to use existing profiles or tweak it and create new ones.
This video https://code.visualstudio.com/docs/introvideos/basics could also be updated to include Profiles as a basic steppingstone in setting up.

@bhavyaus that works for me
@sandy081 what do you think? Bhavya checked and these two walkthroughs are equally popular among our users.
fyi @burkeholland for potentially including built-in profiles in videos.

Sounds good

Moving to next milestone since this depends on us integrating Built-in profiles in VS Code.

Closing as done 👏  Thank you @bhavyaus !

Verification Steps:

Open the walkthrough Learn the Fundamentals
Verify that there exists a step to Try Profiles.


Implement compact config formatters

resolves #238

@Sadaf-A This feature will be available once we release the next version of CLI, I assume it will happen in the next few days.

@Sadaf-A This feature will be available once we release the next version of CLI, I assume it will happen in the next few days.

awesome!


test: fixup windows tests

fix intermittent failure in test-clock-time-get.
avoid window popups that cause any failed test to just hang until test times out

@cjihrig on the optimization front I used the value in assert to try to avoid that, but agreed not 100% sure what I have will fool all compilers. Seems to work now, possibly because by default we compile in debug mode.


Update zio, zio-test, zio-test-sbt to 2.0.0-RC4

Updates

dev.zio:zio
dev.zio:zio-test
dev.zio:zio-test-sbt

from 2.0.0-RC1 to 2.0.0-RC4.
GitHub Release Notes - Version Diff
I'll automatically update this PR to resolve conflicts as long as you don't change it yourself.
If you'd like to skip this version, you can just close this PR. If you have any feedback, just mention me in the comments below.
Configure Scala Steward for your repository with a .scala-steward.conf file.
Have a fantastic day writing Scala!

Ignore future updates
Add this to your .scala-steward.conf file to ignore future updates of this dependency:
updates.ignore = [ { groupId = "dev.zio" } ]

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

Superseded by #183.


wget-parser: init at 2.0.0

Description of changes
wget-parser is a tool to format as JSON the output of a wget spider scan. It is useful to scan a website for dead links.
Things done

Built on platform(s)

[X] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

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

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

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[X] Tested basic functionality of all binary files (usually in ./result/bin/)
22.05 Release Notes (or backporting 21.11 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module
[ ] (Release notes changes) Ran nixos/doc/manual/md-to-db.sh to update generated release notes

[X] Fits CONTRIBUTING.md.

Result of nixpkgs-review pr 165945 run on x86_64-linux 1

1 package built:

wget-parser

I'm closing this issue as there hasn't been any development for some time. Feel free to reopen with answers to reviewers.


Missing tasks for distinct options cwd

When I hit "Ctrl + Shift + B" I see only one of my tasks. Further my launch.json can not find all task just the last on in the list. It seems the tasks are somehow unique by type and script and only the last from the tasks.json attached below is visible. If I change the script fields to watch1, watch2, watch3 all three tasks appear. Now these execute npm scripts in different directories and if I comment out 2 out of 3, the one remaining works fine.
I have the following tasks.json:
// See https://go.microsoft.com/fwlink/?LinkId=733558
// for the documentation about the tasks.json format
{
  "version": "2.0.0",
  "tasks": [
    {
      "label": "Kendo Extension Watch",
      "type": "npm",
      "script": "watch",
      "problemMatcher": "$tsc-watch",
      "isBackground": true,
      "presentation": {
        "reveal": "always",
        "panel": "dedicated"
      },
      "group": "build",
      "options": {
        "cwd": "${workspaceFolder}/kendo-vscode-extensions/src/extension"
      }
    },
    {
      "label": "Blazor Extension Watch",
      "type": "npm",
      "script": "watch",
      "problemMatcher": "$tsc-watch",
      "isBackground": true,
      "presentation": {
        "reveal": "always",
        "panel": "dedicated"
      },
      "group": "build",
      "options": {
        "cwd": "${workspaceFolder}/blazor-vscode-extensions/src/extension"
      }
    },
    {
      "label": "ASP.NET Core Watch",
      "type": "npm",
      "script": "watch",
      "problemMatcher": "$tsc-watch",
      "isBackground": true,
      "presentation": {
        "reveal": "always",
        "panel": "dedicated"
      },
      "group": "build",
      "options": {
        "cwd": "${workspaceFolder}/aspnet-core-vscode-extensions/src/extension"
      }
    }
  ]
}

I would expect Ctrl + Shift + B to list all three, and to be able to use them in the launch.json. The temporary workaround is to make unique npm script names in each of the subfolders.

This is intended. An npm task is identified by the script and path properties. The path property is the path to the folder containing the package.json that the script is in.
Perhaps you could use inputs?
{
	// See https://go.microsoft.com/fwlink/?LinkId=733558
	// for the documentation about the tasks.json format
	"version": "2.0.0",
	"tasks": [
		{
			"label": "Kendo Extension Watch",
			"type": "npm",
			"script": "watch",
			"problemMatcher": "$tsc-watch",
			"isBackground": true,
			"presentation": {
				"reveal": "always",
				"panel": "dedicated"
			},
			"group": "build",
			"options": {
				"cwd": "${workspaceFolder}/${input:locaion}/src/extension"
			}
		}
	],
	"inputs": [
		{
			"id": "location",
			"type": "pickString",
			"description": "Select which location to build",
			"options": [
				"kendo-vscode-extensions",
				"blazor-vscode-extensions",
				"aspnet-core-vscode-extensions"
			]
		}
	]
}

@alexr00 Thank you,
Adding path seems to work and now all my tasks appear in the list. Path's tooltip says it is the path to the folder containing the package.json, but if I don't set the options.cwd as well it seems VSCode still resolves the package.json file located at the root open folder in the IDE.


External hostname vs hostname

I'm running into a similar issue as https://github.com/SUSE/Portus/issues/774 when trying to run portus in docker compose and Docker for Mac.
It's clear from the logs that "hostname" needs to be configured to the service specified in the registry.  However, in the web UI, when you click advanced, it says:
Portus uses the hostname field to communicate with the registry, but this may be on an internal network and inaccessible to the client. Clients may connect to the registry by a name different to the hostname above, for example if it is behind a reverse proxy. This field must be set to prevent Portus from ignoring registry events originating from this external hostname.

In the docker-compose setup though, this hostname is not what portus should use to communicate with the registry.  It should instead use "registry" under docker-compose v2.
It seems(?) like the web-ui should be changed to have two fields:

Service name
Address to talk to the registry on.

Agreed.

Is this resolved with the "External Registry Name" field that's now available in the registry settings under "Show Advanced"? I'm not sure if this was available at the time this issue was opened.

I think so. Moreover, things have changed in Portus (e.g. docker-compose setup). so this might not be relevant anymore.
@schancel I'll close this issue, but feel free to re-open it if you think this still applies 😉


ocamlPackages.gapi-ocaml: 0.4.2 → 0.4.3

Description of changes
Fixes & compatibility with latest yojson: https://github.com/astrada/gapi-ocaml/releases/tag/v0.4.3
cc maintainer @bennofs.
Things done

Built on platform(s)

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

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

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

[x] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[ ] Tested basic functionality of all binary files (usually in ./result/bin/)
22.11 Release Notes (or backporting 22.05 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module
[ ] (Release notes changes) Ran nixos/doc/manual/md-to-db.sh to update generated release notes

[x] Fits CONTRIBUTING.md.

@GrahamcOfBorg build google-drive-ocamlfuse


Removed unnecessary else

Removing unnecessary else because of return statement

Nice job, Kolya! @JenyaFTW @artemkaxdxd what do you think about it?


Documentation out of date

Hey,
I'm a long time rails developer but have been forced to work with ASP, so I went the MVC 3 way and found your package. However the docs on the site and on github seem to be out of date, github gets me closer to actually working but both cases I get issues.
Following Github instructions I get:
The type Routes doesn't have a static method named Start
Following the website, I get:
'Routes' does not implement inherited abstract member 'RestfulRouting.RouteSet.Map(RestfulRouting.IMapper)'
Hard to figure out what's happening when my .net knowladge is limited.

Wow, thanks for the offer but a few more hours last night I was able to get it working.
The docs I'm referring to is the README file on github (under basic usage) and the website under the basic example (http://stevehodgkiss.github.com/restful-routing/#example).
NOTE: in the README on github, the basic usage example, your attribute being passed in is type Mapper and it should be IMapper.
Also, just wondering if the Restful Routing comes with a better way to do ActionLinks?

Ok I'll take a look at the README and fix that.
Yeah Action links are not really fun in asp.net mvc. There is currently no implementation of rails link methods in Restful Routing. I've seen Rob Conery try to do it, but it always seems weird to me in the context of asp.net mvc. If you come up with a way I'd love to see it.
On Oct 7, 2011, at 2:20 PM, Andrew Kalek wrote:

Wow, thanks for the offer but a few more hours last night I was able to get it working.
The docs I'm referring to is the README file on github (under basic usage) and the website under the basic example (http://stevehodgkiss.github.com/restful-routing/#example).
NOTE: in the README on github, the basic usage example, your attribute being passed in is type Mapper and it should be IMapper.
Also, just wondering if the Restful Routing comes with a better way to do ActionLinks?
--
Reply to this email directly or view it on GitHub:
https://github.com/stevehodgkiss/restful-routing/issues/40#issuecomment-2324891

I'm just trying to get this project done and get back to Rails (and my sanity), so I doubt I'll come up with a way. However I did see somewhere some docs for better routing, maybe in MVCcontrib or somewhere, however it was a few weeks ago and it seems ASP.net community makes it super hard to find docs for MVC 3 (vs MVC or MVC2).
Will post if I find anything.
Thanks for the quick replys,
Andrew

yep, no problem


Allow release workflow write access to create GH releases

Issue #, if available:
The "Create Release" step in the release workflow fails with Error: Resource not accessible by integration. This is because the workflow's permissions for the repository content (includes creating release on the repo) is set to read which overwrites the default repo setting.
Description of changes:
Setting the contents permission to write to enable this workflow to create a draft release. I was able to test this change on my personal repo here: https://github.com/srprash/Workflow_Test/actions/runs/1609080628
By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.

I think since continuous-build doesn't need any write permissions, it's safe to keep contents:read to override the default "read/write" permission. This way its permissions are restricted.

I’m okay with it either way, but if we’re going for restrictive we should probably update the repo settings instead and still delete any permissions that the workflow doesn’t explicitly need (i.e. the continuous-build.yml workflow which doesn’t explicitly need to read the repo contents).


I wonder how many evenings it will take me to find information about PropertyChanged.

Microsoft documentation is next-to-worthless. 'Can't find anything.

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

ID: 9de402a5-a78c-3cfe-f9b1-443a3401574b
Version Independent ID: 4488127d-8fe9-eef6-c665-106b493f93fd
Content: Xamarin.Forms CollectionView - Xamarin
Content Source: docs/xamarin-forms/user-interface/collectionview/index.md
Product: xamarin
Technology: xamarin-forms
GitHub Login: @davidbritch
Microsoft Alias: dabritch

Hi @LJ9999
I recommend you read and understand the following: https://docs.microsoft.com/xamarin/xamarin-forms/xaml/xaml-basics/data-bindings-to-mvvm


{} vs {{}} vs ⦃⦄

We should explain the difference between {} and {{}} and ⦃⦄. I think section 2.8 (Implicit Arguments) is to early, but maybe we can add a new section in chapter 5 or 8 (More on Implicit Arguments?). There we can also briefly mention [] (with a forward reference to chapter 9) and explain !foo, which is currently unexplained, I believe (The only mention seems to be the sentence "Remember that the exclamation mark adds implicit arguments as necessary" in section 4.2).
I'll try to write something up along these lines, but I'd like some input whether to put this in chapter 5 or 8.

I'll try to write something up along these lines, but I'd like some input whether to put this in chapter 5 or 8.

That would be great!

I agree. As to where to put it, I am not sure.
I try to imagine a reader working through the tutorial, starting with chapter 1, and learning to use the system. Too much technical information early on will overwhelm them, but we want them to have the information when it is useful.
In this case, either chapter 5 or 8 seems fine.


Event UI: Question List/Queue

1. Please briefly explain what it is you coded
Restyled question list and queue based on Figma design.
Nodes referenced:

Question queue
Question list (Note that I didn't add a play/pause button since I was unsure of how it would function and I thought it would be a different feature to be done in a separate PR)

2. Please briefly explain your approach (new components added? modified? removed?)
Use a combination of Material UI components to restyle question list and queue. Modified some mutations to allow variables to be used in certain components (i.e. last name for question cards, enqueue/dequeue functionality for upcoming questions, etc.) Created a separate component for the current question to be displayed at the top of the event sidebar.
3. Any packages added/updated/removed
N/A
(Optional) 4. Any feature recommendations/insights/questions/comments/etc.?

It looks and works well. Just two minor changes I'd like you to make. I think the current question should be excluded from the previous tab and the order of previous questions should be reversed so the last question asked would be at the top and oldest would be at the bottom.


Optimization for automatic variable merging

Version and Platform (required):

Binary Ninja Version: 3.6.4764-dev, 1e8f4a9b
OS: macos
OS Version: 14.2
CPU Architecture: arm64

In the example below there are 4 DEVICE_OBJECT* variable. Notice one of them does not even have a variable definition in the decompiler output (14008a012), which could be another bug.

When I manually merge those variables like this:

This is the output I got:

I expect BN to get rid of the variable assignations at 14008a077, 14008a0d8, 14008a0e0. Furthermore, I expect BN to do this merging for me automatically.
Issue can be reproduced at 14008a000 for this binary:
HEVD.zip

Related to #4761


merge new version

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@zmyer: PR needs rebase.

Instructions for interacting with me using PR comments are available here.  If you have questions or suggestions related to my behavior, please file an issue against the kubernetes/test-infra repository.

Hi @zmyer. Thanks for your PR.
I'm waiting for a istio member to verify that this patch is reasonable to test. If it is, they should reply with /ok-to-test on its own line. Until that is done, I will not automatically test new commits in this PR, but the usual testing commands by org members will still work. Regular contributors should join the org to skip this step.
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what is this ?
going to close it as it looks like an error. in general please provide a description and/or an issue # for all PRs


C Stack smashing from inside python when using tensorflow

I am trying to implement Fully Connected Convolutional Network in python using tensorflow and I am getting a Stack Smashing error in one of the Convolution operators. I have checked and all the filter sizes match up and are perfectly in sync with the layer shapes. I did my research on the error and found that this error is caused when you overflow the alloted buffer but I cant see any place where I exceed this buffer and the most weird part is that it's running for 10 layers (7 convolutions and 3 max pool ones of the VGG network) and crashing on the next convolution.
(Posted this on Stack Overflow and was told that this error is due to a bug in tensorflow and hence should be posted here. The reason I was told was that the stack smashing is happening in the C++ code and not the python code and I havent written any C++ code myself so the most likely place for the error to have happened is inside tensorflow)
The error I get is:
-> _, loss_value = sess.run([train_op, loss],feed_dict=feed_dict) (Pdb) c I tensorflow/core/kernels/logging_ops.cc:79] Shape of input image: [1 375 1242 3] I tensorflow/core/kernels/logging_ops.cc:79] Shape of conv1_1[1 375 1242 64] I tensorflow/core/kernels/logging_ops.cc:79] Shape of conv1_2[1 375 1242 64] I tensorflow/core/kernels/logging_ops.cc:79] Shape of pool1[1 188 621 64] I tensorflow/core/kernels/logging_ops.cc:79] Shape of conv2_1[1 188 621 128] I tensorflow/core/kernels/logging_ops.cc:79] Shape of conv2_2[1 188 621 128] I tensorflow/core/kernels/logging_ops.cc:79] Shape of pool2[1 94 311 128] I tensorflow/core/kernels/logging_ops.cc:79] Shape of conv3_1[1 94 311 256] I tensorflow/core/kernels/logging_ops.cc:79] Shape of conv3_2[1 94 311 256] I tensorflow/core/kernels/logging_ops.cc:79] Shape of conv3_3[1 94 311 256] I tensorflow/core/kernels/logging_ops.cc:79] Shape of pool3[1 47 156 256] *** stack smashing detected ***: python terminated Aborted (core dumped)
Here is the relevant part of my code:
`class FCN8VGG:
def __init__(self, vgg16_npy_path=None):
    if vgg16_npy_path is None:
        path = sys.modules[self.__class__.__module__].__file__
        # print path
        path = os.path.abspath(os.path.join(path, os.pardir))
        # print path
        path = os.path.join(path, "vgg16.npy")
        print(path)
        vgg16_npy_path = path

    self.data_dict = np.load(vgg16_npy_path).item()
    self.wd = 5e-4
    print("npy file loaded")
def build(self, rgb, train=True, num_classes=14, random_init_fc8=True,
          debug=True):
    """
    Build the VGG model using loaded weights
    Parameters
    ----------
    rgb: image batch tensor
        Image in rgb shap. Scaled to Intervall [0, 255]
    train: bool
        Whether to build train or inference graph
    num_classes: int
        How many classes should be predicted (by fc8)
    random_init_fc8 : bool
        Whether to initialize fc8 layer randomly.
        Finetuning is required in this case.
    debug: bool
        Whether to print additional Debug Information.
    """
    # Convert RGB to BGR

    with tf.name_scope('Processing'):
        #import pdb;pdb.set_trace()
        red, green, blue = tf.split(3, 3, rgb)
        # assert red.get_shape().as_list()[1:] == [224, 224, 1]
        # assert green.get_shape().as_list()[1:] == [224, 224, 1]
        # assert blue.get_shape().as_list()[1:] == [224, 224, 1]
        bgr = tf.concat(3, [
            blue - VGG_MEAN[0],
            green - VGG_MEAN[1],
            red - VGG_MEAN[2],
        ])

        if debug:
            bgr = tf.Print(bgr, [tf.shape(bgr)],
                           message='Shape of input image: ',
                           summarize=4, first_n=1)

    self.conv1_1 = self._conv_layer(bgr, "conv1_1")
    self.conv1_2 = self._conv_layer(self.conv1_1, "conv1_2")
    self.pool1 = self._max_pool(self.conv1_2, 'pool1', debug)

    print("Pool1 layer ready")

    self.conv2_1 = self._conv_layer(self.pool1, "conv2_1")
    self.conv2_2 = self._conv_layer(self.conv2_1, "conv2_2")
    self.pool2 = self._max_pool(self.conv2_2, 'pool2', debug)
    self.conv3_1 = self._conv_layer(self.pool2, "conv3_1")
    self.conv3_2 = self._conv_layer(self.conv3_1, "conv3_2")
    self.conv3_3 = self._conv_layer(self.conv3_2, "conv3_3")
    self.pool3 = self._max_pool(self.conv3_3, 'pool3', debug)

    print("Pool 3 layer ready")
    #pdb.set_trace()
    self.conv4_1 = self._conv_layer(self.pool3, "conv4_1")
    self.conv4_2 = self._conv_layer(self.conv4_1, "conv4_2")
    self.conv4_3 = self._conv_layer(self.conv4_2, "conv4_3")
    self.pool4 = self._max_pool(self.conv4_3, 'pool4', debug)

    print("Pool 4 layer ready")
    #pdb.set_trace()
    self.conv5_1 = self._conv_layer(self.pool4, "conv5_1")
    self.conv5_2 = self._conv_layer(self.conv5_1, "conv5_2")
    self.conv5_3 = self._conv_layer(self.conv5_2, "conv5_3")
    self.pool5 = self._max_pool(self.conv5_3, 'pool5', debug)

    print("Pool 5 layer ready")
    #pdb.set_trace()
    self.fc6 = self._fc_layer(self.pool5, "fc6")

    if train:
        self.fc6 = tf.nn.dropout(self.fc6, 0.5)

    self.fc7 = self._fc_layer(self.fc6, "fc7")
    if train:
        self.fc7 = tf.nn.dropout(self.fc7, 0.5)

    if random_init_fc8:
        self.score_fr = self._score_layer(self.fc7, "score_fr",
                                          num_classes)
    else:
        self.score_fr = self._fc_layer(self.fc7, "score_fr",
                                       num_classes=num_classes,
                                       relu=False)

    self.pred = tf.argmax(self.score_fr, dimension=3)

    self.upscore2 = self._upscore_layer(self.score_fr,
                                        shape=tf.shape(self.pool4),
                                        num_classes=num_classes,
                                        debug=debug, name='upscore2',
                                        ksize=4, stride=2)
    self.score_pool4 = self._score_layer(self.pool4, "score_pool4",
                                         num_classes=num_classes)
    self.fuse_pool4 = tf.add(self.upscore2, self.score_pool4)
    self.upscore4 = self._upscore_layer(self.fuse_pool4,
                                        shape=tf.shape(self.pool3),
                                        num_classes=num_classes,
                                        debug=debug, name='upscore4',
                                        ksize=4, stride=2)
    self.score_pool3 = self._score_layer(self.pool3, "score_pool3",
                                         num_classes=num_classes)
    self.fuse_pool3 = tf.add(self.upscore4, self.score_pool3)

    self.upscore32 = self._upscore_layer(self.fuse_pool3,
                                         shape=tf.shape(bgr),
                                         num_classes=num_classes,
                                         debug=debug, name='upscore32',
                                         ksize=16, stride=8)

    self.pred_up = tf.argmax(self.upscore32, dimension=3)

def _max_pool(self, bottom, name, debug):
    pool = tf.nn.max_pool(bottom, ksize=[1, 2, 2, 1], strides=[1, 2, 2, 1],
                          padding='SAME', name=name)

    if debug:
        pool = tf.Print(pool, [tf.shape(pool)],
                        message='Shape of %s' % name,
                        summarize=4, first_n=1)
    return pool

def _conv_layer(self, bottom, name):
    with tf.variable_scope(name) as scope:
        filt = self.get_conv_filter(name)
        conv = tf.nn.conv2d(bottom, filt, [1, 1, 1, 1], padding='SAME')

        conv = tf.Print(conv, [tf.shape(conv)], message='Shape of %s' % name, summarize=4, first_n=1)

        conv_biases = self.get_bias(name)
        bias = tf.nn.bias_add(conv, conv_biases)
        if relu:
            bias = tf.nn.relu(bias)
        _activation_summary(bias)

        if debug:
            bias = tf.Print(bias, [tf.shape(bias)],
                            message='Shape of %s' % name,
                            summarize=4, first_n=1)
        return bias`

The driver tensorflow code has this command which produces the error:

` _, loss_value = sess.run([train_op, loss],feed_dict=feed_dict)`

Where loss is the tensorflow op for:

`def loss(logits, labels):
"""Calculate the loss from the logits and the labels.

Args:
  logits: Logits tensor, float - [batch_size, height, width, NUM_CLASSES].  Must be unsclaed and unsoftmaxed.
  labels: Labels tensor, int32 - [batch_size, height, width].

Returns:
  loss: Loss tensor of type float.
"""
with tf.name_scope('loss'):
    reshaped_logits = tf.reshape(logits, [-1, 14])  # shape [batch_size*height*width, 14]
    reshaped_labels = tf.reshape(labels, [-1])  # shape [batch_size*height*width]   #Need fix size images for this
    loss = tf.nn.sparse_softmax_cross_entropy_with_logits(reshaped_logits, reshaped_labels)
return loss   `

And training is the driver training function:

`def training(loss, learning_rate):
  """Sets up the training Ops.

  Creates a summarizer to track the loss over time in TensorBoard.

  Creates an optimizer and applies the gradients to all trainable variables.

  The Op returned by this function is what must be passed to the
  `sess.run()` call to cause the model to train.

  Args:
    loss: Loss tensor, from loss().
    learning_rate: The learning rate to use for gradient descent.

  Returns:
    train_op: The Op for training.
  """
  # Add a scalar summary for the snapshot loss.
  tf.scalar_summary(loss.op.name, loss)
  # Create the gradient descent optimizer with the given learning rate.
  #optimizer = tf.train.GradientDescentOptimizer(learning_rate)
  optimizer = tf.train.AdamOptimizer(1e-6)
  # Create a variable to track the global step.
  print("Setting step size to 1e-6 for Adam Optimizer")
  global_step = tf.Variable(0, name='global_step', trainable=False)
  # Use the optimizer to apply the gradients that minimize the loss
  # (and also increment the global step counter) as a single training step.
  print("Running optimizer")
  train_op = optimizer.minimize(loss, global_step=global_step)
  return train_op `

The debug log from the building of the network is: This contains details of filter and layer shapes etc.
`Layer name: conv1_1
Layer shape: (3, 3, 3, 64)
INFO:tensorflow:Created variable conv1_1/filter:0 with shape (3, 3, 3, 64) and init <function _initializer at 0x7fcc27c85ed8>
2016-06-30 14:15:53,939 INFO Created variable conv1_1/filter:0 with shape (3, 3, 3, 64) and init <function _initializer at 0x7fcc27c85ed8>

INFO:tensorflow:Created variable conv1_1/biases:0 with shape (64,) and init <function _initializer at 0x7fcc27c85ed8>
2016-06-30 14:15:53,944 INFO Created variable conv1_1/biases:0 with shape (64,) and init <function _initializer at 0x7fcc27c85ed8>
Layer name: conv1_2
Layer shape: (3, 3, 64, 64)

INFO:tensorflow:Created variable conv1_2/filter:0 with shape (3, 3, 64, 64) and init <function _initializer at 0x7fcc27c96488>
2016-06-30 14:15:53,952 INFO Created variable conv1_2/filter:0 with shape (3, 3, 64, 64) and init <function _initializer at 0x7fcc27c96488>

INFO:tensorflow:Created variable conv1_2/biases:0 with shape (64,) and init <function _initializer at 0x7fcc27c96488>
2016-06-30 14:15:53,956 INFO Created variable conv1_2/biases:0 with shape (64,) and init <function _initializer at 0x7fcc27c96488>
Pool1 layer ready
Layer name: conv2_1
Layer shape: (3, 3, 64, 128)

INFO:tensorflow:Created variable conv2_1/filter:0 with shape (3, 3, 64, 128) and init <function _initializer at 0x7fcc27c9dc08>
2016-06-30 14:15:53,967 INFO Created variable conv2_1/filter:0 with shape (3, 3, 64, 128) and init <function _initializer at 0x7fcc27c9dc08>

INFO:tensorflow:Created variable conv2_1/biases:0 with shape (128,) and init <function _initializer at 0x7fcc27c9dc08>
2016-06-30 14:15:53,972 INFO Created variable conv2_1/biases:0 with shape (128,) and init <function _initializer at 0x7fcc27c9dc08>
Layer name: conv2_2
Layer shape: (3, 3, 128, 128)

INFO:tensorflow:Created variable conv2_2/filter:0 with shape (3, 3, 128, 128) and init <function _initializer at 0x7fcbb3012488>
2016-06-30 14:15:53,980 INFO Created variable conv2_2/filter:0 with shape (3, 3, 128, 128) and init <function _initializer at 0x7fcbb3012488>

INFO:tensorflow:Created variable conv2_2/biases:0 with shape (128,) and init <function _initializer at 0x7fcbb2f8af50>
2016-06-30 14:15:53,985 INFO Created variable conv2_2/biases:0 with shape (128,) and init <function _initializer at 0x7fcbb2f8af50>
Pool 2 layer ready
Layer name: conv3_1
Layer shape: (3, 3, 128, 256)

INFO:tensorflow:Created variable conv3_1/filter:0 with shape (3, 3, 128, 256) and init <function _initializer at 0x7fcbb3012488>
2016-06-30 14:15:53,995 INFO Created variable conv3_1/filter:0 with shape (3, 3, 128, 256) and init <function _initializer at 0x7fcbb3012488>

INFO:tensorflow:Created variable conv3_1/biases:0 with shape (256,) and init <function _initializer at 0x7fcbb1a7cb90>
2016-06-30 14:15:54,000 INFO Created variable conv3_1/biases:0 with shape (256,) and init <function _initializer at 0x7fcbb1a7cb90>
Layer name: conv3_2
Layer shape: (3, 3, 256, 256)

INFO:tensorflow:Created variable conv3_2/filter:0 with shape (3, 3, 256, 256) and init <function _initializer at 0x7fcbb3012488>
2016-06-30 14:15:54,010 INFO Created variable conv3_2/filter:0 with shape (3, 3, 256, 256) and init <function _initializer at 0x7fcbb3012488>

INFO:tensorflow:Created variable conv3_2/biases:0 with shape (256,) and init <function _initializer at 0x7fcbb3012488>
2016-06-30 14:15:54,015 INFO Created variable conv3_2/biases:0 with shape (256,) and init <function _initializer at 0x7fcbb3012488>
Layer name: conv3_3
Layer shape: (3, 3, 256, 256)

INFO:tensorflow:Created variable conv3_3/filter:0 with shape (3, 3, 256, 256) and init <function _initializer at 0x7fcbb1a8aaa0>
2016-06-30 14:15:54,024 INFO Created variable conv3_3/filter:0 with shape (3, 3, 256, 256) and init <function _initializer at 0x7fcbb1a8aaa0>

INFO:tensorflow:Created variable conv3_3/biases:0 with shape (256,) and init <function _initializer at 0x7fcbb1a8aaa0>
2016-06-30 14:15:54,029 INFO Created variable conv3_3/biases:0 with shape (256,) and init <function _initializer at 0x7fcbb1a8aaa0>
Pool 3 layer ready
Layer name: conv4_1
Layer shape: (3, 3, 256, 512)

INFO:tensorflow:Created variable conv4_1/filter:0 with shape (3, 3, 256, 512) and init <function _initializer at 0x7fcbb1a4c7d0>
2016-06-30 14:15:54,043 INFO Created variable conv4_1/filter:0 with shape (3, 3, 256, 512) and init <function _initializer at 0x7fcbb1a4c7d0>

INFO:tensorflow:Created variable conv4_1/biases:0 with shape (512,) and init <function _initializer at 0x7fcbb1a4c7d0>
2016-06-30 14:15:54,048 INFO Created variable conv4_1/biases:0 with shape (512,) and init <function _initializer at 0x7fcbb1a4c7d0>
Layer name: conv4_2
Layer shape: (3, 3, 512, 512)

INFO:tensorflow:Created variable conv4_2/filter:0 with shape (3, 3, 512, 512) and init <function _initializer at 0x7fcbb1a12500>
2016-06-30 14:15:54,063 INFO Created variable conv4_2/filter:0 with shape (3, 3, 512, 512) and init <function _initializer at 0x7fcbb1a12500>

INFO:tensorflow:Created variable conv4_2/biases:0 with shape (512,) and init <function _initializer at 0x7fcbb1a12500>
2016-06-30 14:15:54,068 INFO Created variable conv4_2/biases:0 with shape (512,) and init <function _initializer at 0x7fcbb1a12500>
Layer name: conv4_3
Layer shape: (3, 3, 512, 512)

INFO:tensorflow:Created variable conv4_3/filter:0 with shape (3, 3, 512, 512) and init <function _initializer at 0x7fcbb19d89b0>
2016-06-30 14:15:54,083 INFO Created variable conv4_3/filter:0 with shape (3, 3, 512, 512) and init <function _initializer at 0x7fcbb19d89b0>

INFO:tensorflow:Created variable conv4_3/biases:0 with shape (512,) and init <function _initializer at 0x7fcbb19d89b0>
2016-06-30 14:15:54,088 INFO Created variable conv4_3/biases:0 with shape (512,) and init <function _initializer at 0x7fcbb19d89b0>
Pool 4 layer ready
Layer name: conv5_1
Layer shape: (3, 3, 512, 512)

INFO:tensorflow:Created variable conv5_1/filter:0 with shape (3, 3, 512, 512) and init <function _initializer at 0x7fcbb199f6e0>
2016-06-30 14:15:54,103 INFO Created variable conv5_1/filter:0 with shape (3, 3, 512, 512) and init <function _initializer at 0x7fcbb199f6e0>

INFO:tensorflow:Created variable conv5_1/biases:0 with shape (512,) and init <function _initializer at 0x7fcbb199f6e0>
2016-06-30 14:15:54,108 INFO Created variable conv5_1/biases:0 with shape (512,) and init <function _initializer at 0x7fcbb199f6e0>
Layer name: conv5_2
Layer shape: (3, 3, 512, 512)

INFO:tensorflow:Created variable conv5_2/filter:0 with shape (3, 3, 512, 512) and init <function _initializer at 0x7fcbb1961488>
2016-06-30 14:15:54,122 INFO Created variable conv5_2/filter:0 with shape (3, 3, 512, 512) and init <function _initializer at 0x7fcbb1961488>

INFO:tensorflow:Created variable conv5_2/biases:0 with shape (512,) and init <function _initializer at 0x7fcbb18daf50>
2016-06-30 14:15:54,127 INFO Created variable conv5_2/biases:0 with shape (512,) and init <function _initializer at 0x7fcbb18daf50>
Layer name: conv5_3
Layer shape: (3, 3, 512, 512)

INFO:tensorflow:Created variable conv5_3/filter:0 with shape (3, 3, 512, 512) and init <function _initializer at 0x7fcbb1961488>
2016-06-30 14:15:54,141 INFO Created variable conv5_3/filter:0 with shape (3, 3, 512, 512) and init <function _initializer at 0x7fcbb1961488>

INFO:tensorflow:Created variable conv5_3/biases:0 with shape (512,) and init <function _initializer at 0x7fcbb1961488>
2016-06-30 14:15:54,146 INFO Created variable conv5_3/biases:0 with shape (512,) and init <function _initializer at 0x7fcbb1961488>
Pool 5 layer ready
Layer name: fc6
Layer shape: [7, 7, 512, 4096]

INFO:tensorflow:Created variable fc6/weights:0 with shape (7, 7, 512, 4096) and init <function _initializer at 0x7fcbb186b5f0>
2016-06-30 14:15:54,435 INFO Created variable fc6/weights:0 with shape (7, 7, 512, 4096) and init <function _initializer at 0x7fcbb186b5f0>

INFO:tensorflow:Created variable fc6/biases:0 with shape (4096,) and init <function _initializer at 0x7fcbb186b5f0>
2016-06-30 14:15:54,438 INFO Created variable fc6/biases:0 with shape (4096,) and init <function _initializer at 0x7fcbb186b5f0>
Layer name: fc7
Layer shape: [1, 1, 4096, 4096]

INFO:tensorflow:Created variable fc7/weights:0 with shape (1, 1, 4096, 4096) and init <function _initializer at 0x7fcbb189fed8>
2016-06-30 14:15:54,492 INFO Created variable fc7/weights:0 with shape (1, 1, 4096, 4096) and init <function _initializer at 0x7fcbb189fed8>

INFO:tensorflow:Created variable fc7/biases:0 with shape (4096,) and init <function _initializer at 0x7fcbb189fed8>
2016-06-30 14:15:54,495 INFO Created variable fc7/biases:0 with shape (4096,) and init <function _initializer at 0x7fcbb189fed8>

INFO:tensorflow:Created variable score_fr/weights:0 with shape (1, 1, 4096, 14) and init <function _initializer at 0x7fcbb186b5f0>
2016-06-30 14:15:54,506 INFO Created variable score_fr/weights:0 with shape (1, 1, 4096, 14) and init <function _initializer at 0x7fcbb186b5f0>

INFO:tensorflow:Created variable score_fr/biases:0 with shape (14,) and init <function _initializer at 0x7fcbb186b5f0>
2016-06-30 14:15:54,510 INFO Created variable score_fr/biases:0 with shape (14,) and init <function _initializer at 0x7fcbb186b5f0>

INFO:tensorflow:Created variable upscore2/up_filter:0 with shape (4, 4, 14, 14) and init <function _initializer at 0x7fcbb17a48c0>
2016-06-30 14:15:54,525 INFO Created variable upscore2/up_filter:0 with shape (4, 4, 14, 14) and init <function _initializer at 0x7fcbb17a48c0>

INFO:tensorflow:Created variable score_pool4/weights:0 with shape (1, 1, 512, 14) and init <function _initializer at 0x7fcbb17a48c0>
2016-06-30 14:15:54,536 INFO Created variable score_pool4/weights:0 with shape (1, 1, 512, 14) and init <function _initializer at 0x7fcbb17a48c0>

INFO:tensorflow:Created variable score_pool4/biases:0 with shape (14,) and init <function _initializer at 0x7fcbb17a48c0>
2016-06-30 14:15:54,540 INFO Created variable score_pool4/biases:0 with shape (14,) and init <function _initializer at 0x7fcbb17a48c0>

INFO:tensorflow:Created variable upscore4/up_filter:0 with shape (4, 4, 14, 14) and init <function _initializer at 0x7fcbb16c0aa0>
2016-06-30 14:15:54,555 INFO Created variable upscore4/up_filter:0 with shape (4, 4, 14, 14) and init <function _initializer at 0x7fcbb16c0aa0>

INFO:tensorflow:Created variable score_pool3/weights:0 with shape (1, 1, 256, 14) and init <function _initializer at 0x7fcbb16c0aa0>
2016-06-30 14:15:54,566 INFO Created variable score_pool3/weights:0 with shape (1, 1, 256, 14) and init <function _initializer at 0x7fcbb16c0aa0>

INFO:tensorflow:Created variable score_pool3/biases:0 with shape (14,) and init <function _initializer at 0x7fcbb16c0aa0>
2016-06-30 14:15:54,570 INFO Created variable score_pool3/biases:0 with shape (14,) and init <function _initializer at 0x7fcbb16c0aa0>

INFO:tensorflow:Created variable upscore32/up_filter:0 with shape (16, 16, 14, 14) and init <function _initializer at 0x7fcbb15eb758>
2016-06-30 14:15:54,585 INFO Created variable upscore32/up_filter:0 with shape (16, 16, 14, 14) and init <function _initializer at 0x7fcbb15eb758>`

Been stuck on this for quite some time and cant figure out whats wrong... Any help will be appreciated :)

Is this still occurring (try the 0.10RC for example).  If it is still occurring, it will be difficult to help you any further without you providing a self-contained reproducible test case. I understand these errors are frustrating.

Automatically closing due to lack of recent activity. Please reopen when additional becomes available.


Headings ids are inconsistent

All headings must have an id attribute, which is formed from the content of the heading. The format of this id attribute is inconsistent.
Sometimes it uses - and is suffixed with _0:

Getting Started

And sometimes, it uses _:

Setup of your site project

id attributes must use a consistent pattern (it's recommended to use - and don't suffix with _0), so that they are predictable.

Fixed with #18


Proxy clean-up

What should be done?

Make the polling time of a request for available workers configurable from the configuration file.
Update Pingora to 0.4

How should it be done?

We should add a new field to the ProxyConfig struct to keep track of the polling time for available workers in the configuration file, and then keep track of the value with a new field in LoadBalancer, that way we can access the value in each request to perform the sleep. Default poll time should be 20 ms.
Update Pingora and Pingora-related crates to 0.4 version in the Cargo.toml of the miden-tx bin. In the changelog of the version no breaking change seems to appear so it should work out of the box.

When is this task done?

We can consider it done when a user can set manually any polling time in the configuration file.
All pingora crates are using 0.4.

Additional context
No response

Close because it is in the wrong repository.


Relocate Intro Videos

#2831 I observed that introductory videos which are to introduce a new comer to the community, the library and what the community stands for, was located at after the lists of tutorials, making them appear below the fold.
This means that a new comer would have to scroll down before finding out 'who' the community is.
I suggested relocating the videos to come above the fold, so a new comer sees them first.
@bebatut suggested that we make them stay on a right column and keep the tutorials on the left column.
We decided to go with that and I worked on the modification. I also took responsiveness into consideration across large, medium and small screens.

It looks quite nice:

Some comments

Maybe the right column could be a bit smaller than the left one

I would put "Galaxy Tips & Tricks", "Data Science Survival Kit" and maybe "Galaxy for Developers and Admins" in the left column below

Maybe putting "How to contribute?" and "Galaxy for Contributors and Instructors" below the videos

Some content has disappear (the news, tweets, the hall of fame):

It seems that there is a conflict on the file you edited with the current version of the file in GitHub. Have you ever solved git conflicts? Can you try to solve the conflict? Do you need help?

I like this as well, perhaps we can add the news and tweets on the right column as well, perhaps under the first video? I think it would be nice to have the news feed more prominent as it announced new tutorials, or updates interesting for contributors.
So maybe all the tutorials on the left, and in the right column something like:

"Welcome to the GTN" video
News feed (we can play around with the number of items to show)
"Join the community" Video
Tweets
Hall of Fame
Map of GTN

Depending on how long the left column with tutorials gets, we can match it on the right, and have the rest of the above list below the two columns if needed.
and I agree with @bebatut that perhaps the left column could be a bit wider than the right
What do you think?

I have made a second commit, taking into consideration all our suggestions. It is also responsive and looks beautiful too! Our new comers and normal users can have the best experience too :)

@Chinonyemildred could you post some screenshots here? That way everybody can have a look and give their opinion/suggestions etc :)

It looks like this right now:

I feel like the News are a bit too big. Maybe changing the font size to have it same as the other elements
I would put the GTN tweets below the Galaxy video
The Galaxy Training Network maps and the Contributor Hall of Fame should probably be side by side
The text in the section "Acknowledgement und funding" should not be centered

@Chinonyemildred could you try with these suggestions and post screenshots? Thanks

Okay, that means I'll go to that html file to edit the font size right?

Indirectly. The styling will be done in CSS, and we might have to override the CSS coming from bootstrap (we can help with that) What you can do in that file however, is change the number of news items to show from 6 to maybe 4 or 5 to save on some space?
P.S. I would try to resolve the merge conflict sooner rather than later, sometimes the longer you wait the harder it gets (again, if you need help with this just let us know! they can be a bit tricky if you're not used to them)
And a final tiny general git tip: try to make your commit message more descriptive, stating what you've done ("moved news section" etc, rather than "Relocate Videos" for every commit), helps you and us keep track of what was done in which commit.
Let me know if you would like me to do any of these things, I can add a commit to your PR as well that you can work further on.

Thank you so much @shiltemann. I really need help with the git conflict. Can you help me please? I tried but I haven't experienced this before so I don't know how to resolve it accurately.
Thanks for this suggestion, I'll reduce the number of items....this should work some magic!
Thank you so much :)

@shiltemann I still feel confused, so I might need to study this aspect of git. At the same time, I wouldn't want to still leave this conflict open, please if you don't mind, can you help me resolve it?
I'm so thankful for your guidance ❤

I will look into the failing test too

awesome! One more suggestion: the tagline under the first video is more related to the second video, maybe remove it, or change to something like "watch the video below to find out more about the GTN" or something, what do you think?

Maybe remove the word "Galaxy" from the title here so it fits on one line?

Thanks @Chinonyemildred for the changes there. It looks nice!
In there :

We use different headlines:

Welcome to the Galaxy Training!
Welcome to the GTN!

But we never explained what does GTN stand for

@shiltemann it looks nice, it still retained its weight which give it some emphasis yet keeping the balance.....,❤❤
@bebatut we can do the explanation in the tagline beneath WELCOME TO GTN: 'Watch the video to find out about Galaxy Training Network'. My worry may be the length of the sentence (it may break into two lines). I guess of it does, I can just edit it to 'Find out about Galaxy Training Network'.
What do you think?

ooh yay, excited to merge this! Thanks so much @Chinonyemildred, great work!


[Backend] link influncers list of each with their respective analytics page

when a logged in brand will see influncers list then he can click on any influcners and go to their analytics page and can connect on that request influcencer

@RohitGupta1237  can you please assign this to me.


Pods should allow running other pods as applications

Pods currently only allow running applications backed up by ACI images. This is nice, but it makes it difficult to pack complex applications in multiple containers.
Instead, if pods allowed to specify applications as a pod instance, it would be possible to pack complex applications in multi levels. First, applications requiring multiple service to run together might run as the innermost pods, and the application themselves could interact as the outermost pod.
Example running multiple level applications could be:

HTTP service for a given host

reverse proxy for the following two applications
HTTP application 1

HTTP server
Database

HTTP application 2

HTTP server
Database
Processing agent

Mail service (grouping the different services that need to be configured together)

SMTP service
IMAP service

On the host, you'll just configure the execution of two pods: the HTTP pod and the Mail pod. They will recursively execute the Mail services and theHTTP reverse proxy, along with both HTTP applications and their database.

This is kind of an interesting idea but very underdefined and raises a tonne of questions. For example, what namespaces are shared between the top-level pods? Can isolators be applied at every level? How many levels of nesting are allowed? What about pod lifecycle? (#276)


[OZ][N-07]:BIT Token Address Is Used Instead of MNT Token Address

Describe the bug
The bridge contracts have specific logic to handle MNT tokens but the L1StandardBridge
contract currently associates the BIT token with the L2 Mantle token. Consider reusing the
existing variable to identify the MNT token address.
Note that the L2 token also still references the BIT token and should be updated accordingly.

Yes, after our official Mantle token deployed on Ethereum, we will change it from BIT to MNT.


files.retrieveContent only returns strings, and not bytes/binary data

Confirm this is a Node library issue and not an underlying OpenAI API issue

[X] This is an issue with the Node library

Describe the bug
See this issue for the python library. I don't see an equivalent method to with_raw_response in the node sdk.
To Reproduce
const content = await openai.files.retrieveContent("file-id");

fs.writeFile("image.png", content, (err) => {
  if (err) {
    console.log(err);
  }
});

This saves a corrupt file, though the file can be downloaded from the playground without a problem.
Code snippets
No response
OS
windows 11
Node version
Node.js v20.9.0
Library version
"openai": "^4.16.1"

This has been fixed in the v4.17.1 release, you can now use client.files.content() instead.

To anybody facing this...
const file = await openai.files.content(file_id)
await fs.writeFile('./my_image.png', file.body, 'binary')

Nevertheless, I can't understand why you deprecate things so quickly.

I can't understand why you deprecate things so quickly.

openai.files.retrieveContent() will continue to work until the next major version, it's just documented as deprecated to help developers find the new one, which is much more useful (binary contents as text isn't ideal).

Sure, I just saw this as a bug, don't really understand why is not retrieveContent anymore.

Changing the behavior of retrieveContent to return a response instead of a string would be a breaking change.

Is there a way we can get it with including the output file name? Im using the code interpreter API, and I want the user to be able to download the file generated, but it seems I have to specify a file name with an extension to save it?

For that I believe you want openai.files.retrieve
On Sat, Nov 11 2023 at 12:02 AM, salvinoto @.***>
wrote:

Is there a way we can get it with including the output file name? Im using
the code interpreter API, and I want the user to be able to download the
file generated, but it seems I have to specify a file name with an
extension to save it?
—
Reply to this email directly, view it on GitHub
https://github.com/openai/openai-node/issues/464#issuecomment-1806688689,
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.
You are receiving this because you commented.Message ID:
@.***>

A few things. Thanks @pcaselas for the code but since the response.body is a PassThrough that does not work. Here is an example for folks that does.
const response = await openai.files.content(fileID);
const writeStream = fs.createWriteStream("./my_image.png");
response.body.pipe(writeStream);

Second, I noticed the commit to add content has no tests. So I had to figure this out on my own. https://github.com/openai/openai-node/commit/7c7bfc2fad5a786c9172110e90c9566a943e49f9

Thank you for sharing! Further examples of streaming responses are available here: https://github.com/openai/openai-node/blob/master/examples/audio.ts


Add directx BitmapFont to accelerate text

Added new BitmapFont class that supports faster DirectX 8 text rendering by using bitmap font glyphs as textures in GPU batch processing (seeing negligible fps hit now)
Added map support for BitmapFont including font selection
Added some Arial spritefont sizes in uifiles/zeal/fonts
Added some util classes in directx.h for stashing state
Cleaned up map labels and added a '+' marker with label

Hold on merging this one.  I had two hard lock ups tonight in raids.  I did merge in all of the other changes, so not sure what the source is. I also may have had a "dirty gpu".  But wait until I get some more run time on it.

I fixed some resource release issues.  I didn't see anything else obviously wrong and it was stable on a test server. I should be able to test again tomorrow night.


tiny typo

https://github.com/0atman/BrainMade-org/blob/e5c2de53d12396cad8996c0285b846d726310281/src/main.rs#L182
Absolutely love your message and have shared this page to tons of people. I just noticed a small typo that could distract people from the awesomeness
"I don't need 100% human made, I perhaps need 90% human made. Three ~example~ examples may make my thinking clearer:"
Happy to make a PR but just wanted to let you know

Thank you! It seems trivial, but a PR would be great help to my workload, thank you!


v1.4 doc updates

I just pushed final (from my perspective) edits to the R and python library docs. Build is here:
https://docs.airr-community.org/en/doc-1.4-fixes/
I made one actual change to the interface functions in the libraries, which was to rename the adf argument to model under the reasoning that the name and purpose of DataFile may change in v2.0. I don't love the name model, but it will let us convert it from a boolean to a string so we can do stuff like model="DataFile", model="Manifest", etc for different use cases without breaking backwards compatibility for the default behavior (which is currently what's in DataFile). I don't know what we'll do with all that for v2.0 - just trying to future proof against argument name changes.


Suggestion: Update to .NET 4.6.2

My main reason:
https://github.com/microsoftgraph/ConsoleApp-DeltaQuery-DotNet-Sample/blob/master/Client/packages.config#L3
This is a very, very old version of ADAL. Tested with 3.14.1, one necessary code change in Client.cs line no 168:
AuthenticationResult authenticationResult = authenticationContext.AcquireToken(this.protectedResourcePrincipalId, clientCred);
to
AuthenticationResult authenticationResult = authenticationContext.AcquireTokenAsync(this.protectedResourcePrincipalId, clientCred).GetAwaiter().GetResult();

Updated to MSAL . Thanks :)


Add setting to substitute substrings in description_head for item attributes

Codecov Report

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The diff coverage is 0.00%.

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##             master      #2   +/-   ##
========================================
  Coverage          ?   0.00%
========================================
  Files             ?       3
  Lines             ?     117
  Branches          ?       0
========================================
  Hits              ?       0
  Misses            ?     117
  Partials          ?       0

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mlx/jira_interaction.py
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Thanks!

I cannot merge, can you reassign please?

@Ben2022  you can go to diff->review->approve :wink:


[Medium] Locator name selecting leads to warning appearance and disabled Save button

JDN v 3.1.157
Back-end v 2022-03-30-06.47.33
Chrome

open any webpage
open JDN tab
new page object
generate
open any locator Edit menu
select the name in the Name container
unselect

AR: warning and disabled Save button

ER: if there are no changes, there should be no warning and no button status changes

can't reproduce