Expand public fields

Although this is not the most common scenario, there are some nice libraries that expose data as public (readonly) fields. This PR adds support for reading frame columns from public fields (this does not affect normal .NET classes with private fields).
[This is adding just one commit to the existing PR - so we need to merge that one first]

I updated this PR to match the latest version.
@hmansell @adamklein Would anybody object to merging this? (It is a fairly innocent change that just enables one more scenario that I came across. I think it does not realistically affect any existing code, because public fields are not very frequent - the only F# type I can think of is ref<'T>).

The build completed successfully but then failed when shutting down. Travis sometimes does that :-(

Looks good, nice scenario to support.


Hide/add new view to hierarchy

Hi!
First, I wonder, is there a way to hide messageInputView param, because for certain cases I don't need it.
And second - how to add another subviews in hierarchy? or just button?
Are there any legal way to di this things?
Thanks!

Hi @kharitonovAL, I will be working on implementing a simple way to hide the input view this weekend (fingers crossed).
With regard to adding subviews, where do you want to do this? In the InputView? The UICollectionView?

Closing due to lack of requirements


Add a function specifically for setting the chip select pin

I think the code would be more readable if whenever you set the chip select pin for SPI, you use a function with "chip select" in the name instead of just calling BSP_GPIO_Write_Pint()

This has been done in PR #200 with the minions driver.


fix: skip replacing secret data without ref prefix

What type of PR is this?

/kind bug
What this PR does / why we need it:
This PR fixes a bug of replacing secret ref prefix in kusion apply command, which skips the secret data without ref prefix.
Which issue(s) this PR fixes:

Fixes #
Special notes for your reviewer:
Does this PR introduce a user-facing change?

Additional documentation e.g., design docs, usage docs, etc.:

Pull Request Test Coverage Report for Build<PHONE_NUMBER>
Details

0 of 4 (0.0%)  changed or added relevant lines in 1 file are covered.
No unchanged relevant lines lost coverage.
Overall coverage decreased (-0.01%) to 54.208%

Changes Missing Coverage
Covered Lines
Changed/Added Lines
%

pkg/engine/operation/graph/resource_node.go
0
4
0.0%

Totals

Change from base Build<PHONE_NUMBER>:
-0.01%

Covered Lines:
9102

Relevant Lines:
16791

💛  - Coveralls


Prepare service extension that allow to easy instantiate authentication

Here we need to use extensions methods for service coleection and application start-up class

were added IServiceCollection & IApplicationBuilder extensions


"Giveth token" should be simply "GIV"

This is a semantic/grammar issue...I'm suggesting to replace "Giveth token" with "GIV"... as it is, it reads funny.
Should say: "This proposal is requesting 0 [GIV] out of 3,000,000 [GIV] currently in the common pool."

I think it makes sense to also say "Get GIV" in the header... rather than "Get Giveth token"

Let's default to use the symbol.
On the top menu bar we can sai: " Giveth  token from Honeyswap" or similar.


TFLite inference on iOS works with Metal GPU delegate but fails with CoreML delegate

Issue type
Bug
Have you reproduced the bug with TensorFlow Nightly?
Yes
Source
source
TensorFlow version
2.17.0
Custom code
Yes
OS platform and distribution
MacOS Sonoma 14.6
Mobile device
iPhone 12 Pro
Python version
3.12.4
Bazel version
7.2.1
GCC/compiler version
15.0.0
CUDA/cuDNN version
No response
GPU model and memory
Apple M3 Max 36GB
Current behavior?
I tested a TFLite model inference with the C API on iOS (code attached below). The code tries to initialize a CoreML delegate when it's available, otherwise, it falls back to Metal GPU delegate. It works fine with Metal GPU delegate when the CoreML delegate is commented out, but produces errors when CoreML delegate is enabled at the line:
 modelInterpreter = TfLiteInterpreterCreate(tfModel, options); // <-----Thread 1: signal. SIGABRT
The error from the log output is attached below. It looks like it has to do with the TFLite model. I also tested on other TFLite models, they all have the same error. Can someone help point out what the root cause is?
Standalone code to reproduce the issue
// Initialize model
    tfModel = TfLiteModelCreateFromFile(modelPath.c_str());

    TfLiteInterpreterOptions* options = TfLiteInterpreterOptionsCreate();
    TfLiteInterpreterOptionsSetNumThreads(options, 4);

// CoreML delegate
    const TfLiteCoreMlDelegateOptions coreMLOptions = {
        .enabled_devices = TfLiteCoreMlDelegateAllDevices
    };
    tfDelegate = TfLiteCoreMlDelegateCreate(&coreMLOptions);
    if (tfDelegate == NULL) {
        // Fall back to GPU delegate
        const TFLGpuDelegateOptions gpuOptions = {
          .allow_precision_loss = true,
          .wait_type = TFLGpuDelegateWaitType::TFLGpuDelegateWaitTypePassive,
          .enable_quantization = true
        };

        tfDelegate = TFLGpuDelegateCreate(&gpuOptions);
    }

    TfLiteInterpreterOptionsAddDelegate(options, tfDelegate);

    modelInterpreter = TfLiteInterpreterCreate(tfModel, options); // <-----Thread 1: signal. SIGABRT
    TfLiteInterpreterOptionsDelete(options);

Relevant log output
coreml_version must be 2 or 3. Setting to 3.
Initialized TensorFlow Lite runtime.
INFO: Initialized TensorFlow Lite runtime.
CoreML delegate: 50 nodes delegated out of 55 nodes, with 6 partitions.
INFO: CoreML delegate: 50 nodes delegated out of 55 nodes, with 6 partitions.

[libprotobuf FATAL google/protobuf/io/zero_copy_stream_impl_lite.cc:334] CHECK failed: (count) <= (buffer_used_):  Can't back up over more bytes than were returned by the last call to Next().
libc++abi: terminating due to uncaught exception of type google::protobuf::FatalException: CHECK failed: (count) <= (buffer_used_):  Can't back up over more bytes than were returned by the last call to Next().

@AdvaitDongre Thanks for your suggestions.

The tensorflow I have is version 2.17.0. I built it from source using bazel. For my tflite model, the format is "TensorFlow Lite v3". I think they should be compatible with CoreML delegate.
I think Protobuf library is included in the tensorflow package as third-party APIs, should I upgrade/downgrade myself?
I have tried your code, the app still crashes at the line:
modelInterpreter = TfLiteInterpreterCreate(tfModel, options); // <-----Thread 1: signal. SIGABRT
with the error:

[libprotobuf FATAL google/protobuf/io/zero_copy_stream_impl_lite.cc:334] CHECK failed: (count) <= (buffer_used_):  Can't back up over more bytes than were returned by the last call to Next().
libc++abi: terminating due to uncaught exception of type google::protobuf::FatalException: CHECK failed: (count) <= (buffer_used_):  Can't back up over more bytes than were returned by the last call to Next().

okay, it seems the main problem is related to protobuf, firstly try rebuilding your tensorflow lite and go for a version 3.19.... like 3.19.1, since it seems to work well with tensorflow 2.17.0, i feel like that would definitely do the work

@AdvaitDongre Can you elaborate on how i can change the version of Protobuf? Some configure file in the tensorflow package?

have you used pip or manually cloned the repo in your system?

@AdvaitDongre I just downloaded the source zip file for 2.17.0 and built it with Bazel locally. I haven't used pip or cloned the repo.

you should try changing the protobuf dependency in the WORKSPACE file before building tensorflow again
you should try this code (given by GPT):
wget https://github.com/protocolbuffers/protobuf/releases/download/v3.19.1/protobuf-all-3.19.1.tar.gz
tar -xzf protobuf-all-3.19.1.tar.gz
cd protobuf-3.19.1
./configure
make
sudo make install
cd ..

update this desired section, you might need to modify the
http_archive(
    name = "com_google_protobuf",
    urls = ["https://mirror.bazel.build/github.com/protocolbuffers/protobuf/archive/v3.19.1.tar.gz"],
    strip_prefix = "protobuf-3.19.1",
    sha256 = "a0d1a16ef23a15761a216c6dc7c7857b22f6b88ff52e19adad0c703f4b69e4b4",
)

now for sha256 file you'll need to run this command in your terminal
sha256sum protobuf-all-3.19.1.tar.gz

and then paste that thing in the sha256.
and then you can clean and rebuild the tensorflow lite

@AdvaitDongre Thanks for your suggestion. I downgraded the Protobuf from 3.21.9 to 3.19.2. The crash is gone.

You're welcome, and I think you should close it, if you have any other issues feel free to ask


Migrate from unittest to pytest

It's what all the cool kids are using.

Done. Not a new version because this only affects testing.


What doew the operator '<>' mean?

Is there any differences between '<>' and ':='?

Hi there,
Thank you for your interest in Chisel! <> is a bulk-connect operator; you can find out more about it here: https://github.com/freechipsproject/chisel3/wiki/Interfaces-Bulk-Connections#bulk-connections
Please feel free to open a new issue if you experience any bugs.


Clean OSX-related files (e.g., DS_Store)

They should not be uploaded to github.
Use .gitignore. See example here:
https://github.com/neuropoly/spinalcordtoolbox/blob/master/.gitignore

Done in #79


Mark constants as final

mypy (don't know about pyright) treats Delete = "Delete" as Delete: str = "Delete" for backwards compatibility, see https://mypy.readthedocs.io/en/stable/literal_types.html#declaring-literal-variables.
Delete: Final = "Delete" is the same as Delete: Literal["Delete"] = "Delete".

No worries.  I need to fix some type errors anyway.

Thanks!


Fix problems encountered during migration @MCH [DO NOT MERGE YET]

The new convention for the Fortran Interface is:
A n-dimensional fortran array (n<=4) will be written as a n-dimensional field by serialbox (no interpretation of size=1 as non-existent dimension). If a dimension does not exist we pass -1 in the strides and 0 in the dimensions from the FortranWrapper to C.

@chovyy Do you want to have a look if these changes make problems in the way you use serialbox?

@havogt I added the option --module= to pp_ser.py to specify extra module for use statement generation.
You can use the option like the following example. If more than one module, just use a , to separate the module names.
./pp_ser.py --module=cosmo_ppser lmorg.f90

I'm think of a way to extract the shortcuts from pp_ser.py but I have no good solution for the moment.

launch jenkins

Which decision exactly? The -1 or removing the masked/hidden dimension?

launch jenkins


UPDATE:  MAPIEv1 Backend -  Split .fit into .fit_single_estimator and fit_multi_estimator

…_multi_estimators
Description
Please include a summary of the change and which issue is fixed. Please also include relevant motivation and context. List any dependencies that are required for this change.
Fixes #(issue)
Type of change

New feature Non-breaking change which adds functionality

How Has This Been Tested?
Please describe the tests that you ran to verify your changes. Provide instructions so we can reproduce. Please also list any relevant details for your test configuration

[ ] Test A
[ ] Test B

Checklist

[ ] I have read the contributing guidelines
[ ] I have updated the HISTORY.rst and AUTHORS.rst files
[ ] Linting passes successfully : make lint
[ ] Typing passes successfully : make type-check
[ ] Unit tests pass successfully : make tests
[ ] Coverage is 100% : make coverage
[ ] Documentation builds successfully and without warnings : make doc

Codecov Report
All modified and coverable lines are covered by tests :white_check_mark:

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Additional details and impacted files
@@          Coverage Diff           @@
##             v1      #545   +/-   ##
======================================
  Coverage      ?   100.00%
======================================
  Files         ?        62
  Lines         ?      6001
  Branches      ?       951
======================================
  Hits          ?      6001
  Misses        ?         0
  Partials      ?         0

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Update creating-viz-plugins.mdx

SUMMARY
An error stating that the current environment lacks a feature required by the generator appears while trying to use the Yeoman generator @superset-ui/superset to create a custom Superset plugin. (See #26352)
BEFORE/AFTER SCREENSHOTS OR ANIMATED GIF

TESTING INSTRUCTIONS

ADDITIONAL INFORMATION

[ ] Has associated issue:
[ ] Required feature flags:
[ ] Changes UI
[ ] Includes DB Migration (follow approval process in SIP-59)

[ ] Migration is atomic, supports rollback & is backwards-compatible
[ ] Confirm DB migration upgrade and downgrade tested
[ ] Runtime estimates and downtime expectations provided

[ ] Introduces new feature or API
[ ] Removes existing feature or API

Can you please fill out the PR description template?

Thanks @visharavana for the PR. Could you please complete the PR description? This helps to provide the necessary context to the reviewers.

@rusackas @john-bodley I updated the description.

I think it is not quite right and the correct solution is to install yo@4 installed of the latest version.
The command
npm i -g yo

installs version 5.0 of the CLI tool yo.
If you try to scaffold a plugin with this version you get the error:
yo @superset-ui/superset

Error @superset-ui/superset Current environment doesn't provide some necessary feature this generator needs.

And i did not find any way to investigate these lacking "necessary feature".
Reverting to previous version solves the error:
npm i -g yo@4
yo @superset-ui/superset

# you get the prompts to create the boilerplate code

If you install the @superset-ui/superset-generator on npmjs.com you'll run into errors eventually.
The blog post says :

It is recommended to use the version of the template that ships with the version of Superset you are using. This can be installed by doing the following

Issue #27496 is most relevant here.
https://www.npmjs.com/package/@superset-ui/core and https://www.npmjs.com/package/@superset-ui/chart-controls are out of sync with master on Github.
To use the most recent capabilities the workaround is to use
"@superset-ui/chart-controls": "file:/home/qleroy/superset/superset-frontend/packages/superset-ui-chart-controls",
"@superset-ui/core": "file:/home/qleroy/superset/superset-frontend/packages/superset-ui-core",

but using local files for a custom plugin will prevent it from publishing it to npm

Thank you @qleroy that makes sense. @visharavana would you want to update the files/docs accordingly?
We should obviously pay off this debt at some point and either make things compatible with v5, or try a different approach if the generator is too tedious to maintain weill.

Thank you @qleroy that makes sense. @visharavana would you want to update the files/docs accordingly?
We should obviously pay off this debt at some point and either make things compatible with v5, or try a different approach if the generator is too tedious to maintain weill.

Thank you @rusackas, yes, I want to update the documents. "npm i -g @superset-ui/generator-superset", this is working quite well for me. Instead of any other approaches please try this.

@visharavana
Have you tried
npm i -g yo@4
cd superset-frontend/packages/generator-superset
npm i
npm link

If you install "npm i -g @superset-ui/generator-superset" you should not be able to build the plugin because there is a bug in the template.
If you use

@visharavana Have you tried
npm i -g yo@4
cd superset-frontend/packages/generator-superset
npm i
npm link

If you install "npm i -g @superset-ui/generator-superset" you should not be able to build the plugin because there is a bug in the template.
If you use

@qleroy Ok, I understand. Thanks for clarifying the bug in the template.

@qleroy Hi Quentin,
Thanks for the analysis, I've tried npm i -g yo@4, but still getting the following error:

Can I upgrade node to 18.x? As per the Superset doc, Node.js version must be 16.
Thank you.

@mvsenin do you manage to (globally) install any npm package at all?
Your error "yodoctor permission denied" means it requires administrative privileges.
Your problem should be related to your npm installation.

Any update on this ?

Hi @qleroy,
Whenever I try to install the generator using the source from the repo I get warnings of multiple packages complaining about an unsupported engine due to the node version. I've tried with node versions 16.20.2, 18.20.4 and 20.11.1 and all the times npm complains about the same but with different packaged depending on which node version I'm using. Should I just ignore those warnings? Which should be the most appropriate node version to use? the docs says to use Node 16 for creating my own plugins, but in the Dockerfile I see that Node 18 is being used to build the superset image.

Thanks.


Input image exceeds pixel limit

libvips is designed to handle any malicious input without crashing, and the same should applies to sharp as well.
Unfortunately, you don't seem to propagate the errors detected in the worker thread.
I see things like:
Error: Input image exceeds pixel limit

and Node just dies with exit code 1.

Yes I know that exists. Removing/widening the limit means you may suffer from DoS, which is a more serious problem. So that's not a solution.

And please not edit the title to alter the purpose of this issue. The lack of the error handling is the point.

"Unfortunately, you don't seem to propagate the errors detected in the worker thread."

Are you referring to Node worker threads? If so, please see #1297

No, I'm referring to the libuv tasks you spawn.

Thanks for confirming, please can you provide a code sample that fails in the manner you describe?

After some debugging, I found that ts-node was absorbing the cause message (error event on stream) and I found the way to fix it. Sorry for the disruption.

@ishitatsuyuki can you please share a way you fixed it?

Sorry I don't remember anything from 4 years ago. You might want to fiddle with ts-node as the past me said.