vcpkg install failure

getting this when installing from the vcpkg install mentioned in the official documentation:
-- Found external ninja('1.10.2').
-- Configuring x64-windows
CMake Error at scripts/cmake/vcpkg_execute_required_process.cmake:96 (message):
    Command failed: "C:/Program Files/Microsoft Visual Studio/2022/Professional/Common7/IDE/CommonExtensions/Microsoft/CMake/Ninja/ninja.exe" -v
    Working Directory: C:/src/vcpkg/buildtrees/openimageio/x64-windows-rel/vcpkg-parallel-configure
    Error code: 1
    See logs for more information:
      C:\src\vcpkg\buildtrees\openimageio\config-x64-windows-CMakeCache.txt.log
      C:\src\vcpkg\buildtrees\openimageio\config-x64-windows-CMakeCache.txt.log
      C:\src\vcpkg\buildtrees\openimageio\config-x64-windows-out.log

Call Stack (most recent call first):
  installed/x64-windows/share/vcpkg-cmake/vcpkg_cmake_configure.cmake:238 (vcpkg_execute_required_process)
  ports/openimageio/portfile.cmake:43 (vcpkg_cmake_configure)
  scripts/ports.cmake:147 (include)

error: building openimageio:x64-windows failed with: BUILD_FAILED
Please ensure you're using the latest port files with `git pull` and `vcpkg update`.
Then check for known issues at:
    https://github.com/microsoft/vcpkg/issues?q=is%3Aissue+is%3Aopen+in%3Atitle+openimageio
You can submit a new issue at:
    https://github.com/microsoft/vcpkg/issues/new?template=report-package-build-failure.md&title=[openimageio]+Build+error
Include '[openimageio] Build error' in your bug report title, the following version information in your bug description, and attach any relevant failure logs from above.
    vcpkg-tool version: 2022-07-21-a0e87e227afb536c62188c11ad029954f28fdb22
    vcpkg-scripts version: acc3bcf76 2022-08-15 (2 weeks ago)

You can also use the prefilled template from C:\src\vcpkg\installed\vcpkg\issue_body.md.

Running the failed command manually, seems to be a version conflict with Imath.
--     PNG_INCLUDE_DIRS = C:/src/vcpkg/installed/x64-windows/include;C:/src/vcpkg/installed/x64-windows/include
--     PNG_LIBRARIES = optimized;C:/src/vcpkg/installed/x64-windows/lib/libpng16.lib;debug;C:/src/vcpkg/installed/x64-windows/debug/lib/libpng16d.lib;optimized;C:/src/vcpkg/installed/x64-windows/lib/zlib.lib;debug;C:/src/vcpkg/installed/x64-windows/debug/lib/zlibd.lib
-- Found BZip2 1.0.8
--     BZIP2_INCLUDE_DIR = C:/src/vcpkg/installed/x64-windows/include
--     BZIP2_INCLUDE_DIRS = C:/src/vcpkg/installed/x64-windows/include
--     BZIP2_LIBRARIES = optimized;C:/src/vcpkg/installed/x64-windows/lib/bz2.lib;debug;C:/src/vcpkg/installed/x64-windows/debug/lib/bz2d.lib
-- Not using Freetype -- disabled
-- Found OpenColorIO 2.1.2
--     OPENCOLORIO_LIBRARIES = OpenColorIO::OpenColorIO
CMake Error at src/cmake/externalpackages.cmake:172 (message):
  OpenColorIO and OpenEXR use incompatible versions of Imath.  You cannot use
  openimageio[opencolorio] for this configuration.
Call Stack (most recent call first):
  CMakeLists.txt:141 (include)

What could be the issue? Is there something incompatible with my environment? Are the official docs from https://opencolorio.readthedocs.io/en/latest/quick_start/installation.html#installation outdated? Was there a recent breakage?
Also the link to "homebrew homepage"  is broken on that page.

Hello @xchen31u,
Could you list the steps that you have done? e.g. the commands that you did, etc.
Are you trying to install OpenColorIO with Vcpkg or are you trying to build it from source?

Hi,
I'm trying to install OCIO following the instructions. The command is:
vcpkg install openimageio[opencolorio,tools]:x64-windows --recurse

bump!

Hi @xchen31u. This is an issue with vcpkg’s repository currently having incompatible versions of Imath and OpenEXR. I am looking to see if I can help move OpenEXR’s update forward to fix it.

You can install both ports at the same time, but you can't use them at the same time.
For this reason, you currently cannot install openimageio[opencolorio] with the latest versions of these ports, because opencolorio was updated to use the new imath while openimageio still uses the outdated openexr.

https://github.com/microsoft/vcpkg/pull/26513#issuecomment-1227053580

Thanks @EvanAW !
Would using brew mitigate this issue?
Or using another platform such as linux / mac?

Recent testing shows that this now succeeds:
vcpkg install openimageio[opencolorio]:x64-windows --recurse
But the install with the tools option (needed to get oiiotool) still fails due to a QT problem:
vcpkg install openimageio[opencolorio,tools]:x64-windows --recurse
However, that is a problem that doesn't seem to have anything to do with OCIO and would be more appropriately logged to vcpkg or oiio.
I don't want to remove it from our installation page, since it is in theory a valid option.  Hopefully it will be fixed on their side soon.


[#166590] Check if user has already email-confirmed (Improve)

Code already checks if user has email confirmed, however, in this case it allowed the requester to email-confirm three times.
Relevant request: https://accounts.wmflabs.org/acc.php?action=zoom&id=166590
[Community]	email-confirmed	42 minutes ago
[Community]	email-confirmed	42 minutes ago
[Community]	email-confirmed	42 minutes ago

Pegging this for newinternal since it's low priority and sounds like something that would be easier to do there.  Sorry Simon.  :P Ping #232

possibe race condition here?

@stwalkerster How do you mean?

The check already exists, yet it failed to fire in this case. The likely answer is the check succeeded on all three requests before all three of them marked it as email confirmed, then all three sent the IRC notifications and made the log entries - a standard race condition.
My theory is backed up by the fact that all three log entries occurred at the same second. Unfortunately, I believe MySQL discards fractional seconds on storage.

Hmm.  It doesn't sound like this would be terribly easy to solve, unless your optimistic locking would also cover this.

It should, yeah, but it may introduce the problem of errors being thrown instead. I'm fairly sure I've already handled that case, but I'm gonna leave this open for now as a reminder to check it.


Timing null in server

The timing can be null when playing, despite the player has actually send this data.

May be resolved by commit 0f7148382df4a845478edfe30cc7686cbdeeb135.


prime fileld example in tests

Could you give an example of using prime field in tests/test_aurora_snark.cpp? In addition to GF(64)?

Thats already done in https://github.com/scipr-lab/libiop/blob/master/libiop/tests/snark/test_aurora_snark.cpp#L66!

Thanks again for the quick response!
Xiang

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Subject: Re: [scipr-lab/libiop] prime fileld example in tests (#40)
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np!


Drop dist from git repo

Fixes #231, if this is what you meant :-)

It requires a second part, which is publishing to S3 or something on builds so we do have this output.  @fivetanley may have time to help, as he did it for RSVP.js

Cool! What about something like https://unpkg.com/?

@sotojuan oh, I have not seen that before. Looks like it would solve the issue.

@sotojuan actually a quick read yields:

All you need to do is include your UMD build in your npm package (not your repo, that's different!).

Which seems like what we are attempting to avoid.

Hey, I probably won't be able to work on this so I'm closing the PR. Sorry!


Improve TWAP Queries to not require pool id

Background
Current TWAP Queries, regardless of the quote denom and base denom, require specification of pool id in the query(https://github.com/osmosis-labs/osmosis/blob/main/proto/osmosis/twap/v1beta1/query.proto#L37-L58)
This is unnecessary for the base asset - quote asset pairs that have an obvious or a single twap pair.
Suggested Design
Suggested design is that we make the pool id optional for the query, when a query has been given, check in state if we have one pair for the given base asset and quote asset pair. If so, great we use that pool as the twap and return results, if not and multiple pools registered for the base asset and quote asset pair exists, return an error specifying that pool id should be specified.
Acceptance Criteria

Improve TWAP Queries to not require pool id
Test cases have been added

@AlpinYukseloglu yeah, right now, anyone trying to query twap needs to query or know before hand on the pool id as well as the base and quote denom, which creates an extra overhead on the queries

I see, thanks!


feat: add batch delete requests

make batchAddRequests method to correspond with API
move retries and parallelization into method batchAddRequestsWithRetries
add batchDeleteRequests

During implementation, I realized that client should be a thin wrapper around API. I decided to move parallelization and retries of unprocessedRequest into a separate method. I'm even thinking to move batchAddRequestsWithRetries into Apify SDK. What do you think? @B4nan

I think we moved past the "thin wrapper" idea when we released version 1. The client should simplify integration of Apify. To me, the function without the retries is a bit useless, because you have to understand API internals very well to be able to implement the retries. What's the use-case for having the non-retrying function?

Agreed with Ondra, from the SDK standpoint, we expect the client to handle retries, we even use it to get the rate limit stats for autoscaling. All the other methods are handling this (and there is no other *WithRetries method), why should we have a single outlier that don't. I'd keep just one public method that handles all, number of retries should be configurable from outside - if you pass 0 retries, you have the simplified version without them.

What's the use-case for having the non-retrying function?

I have in mind mainly SDK, that it will make sense that SDK will handle autoscaling based on unprocessRequests.
But I got your points that you can handle autoscaling based on a number of retries and if it will be not enough we can introduce a new stat for request queue which SDK can use.

SDK will handle autoscaling based on unprocessRequests.

SDK autoscales based on 429 errors from API. If API does not return 429s, SDK will not downscale. I would not introduce additional complexity to this on the SDK level. Either the batch function needs to autoscale on its own or return 429s.

How do we handle the problem where a user starts pushing a lot of batches to the API and only learns that the API is overloaded 2 minutes later when the exponential backoff on the backend runs out of retries?
I still think that the optimal throughput needs to be handled in the client, based on some immediate information from the API. But even if I ignore that, to be able to properly autoscale on the SDK level, we need to know that the API is overloaded early. After the the two minutes of silence, where the SDK will be scaling up (unless CPU caps it) it could easily send tens of thousands of requests to the API. Then it would get most of them back as unprocessed and the cycle would start over.
Has there been any development in this?

How do we handle the problem where a user starts pushing a lot of batches to the API and only learns that the API is overloaded 2 minutes later when the exponential backoff on the backend runs out of retries?
I still think that the optimal throughput needs to be handled in the client, based on some immediate information from the API. But even if I ignore that, to be able to properly autoscale on the SDK level, we need to know that the API is overloaded early. After the the two minutes of silence, where the SDK will be scaling up (unless CPU caps it) it could easily send tens of thousands of requests to the API. Then it would get most of them back as unprocessed which would save to stats as a lot of rate limit errors and after that the process would start over.

@mnmkng We are passing the message to the SDK early - there are no retries on the server, and the client increases the stats.rateLimitErrors after each HTTP call if there are still some unprocessed requests. So the autoscaled pool in SDK will know about the rate limiting immediately when it reads those client stats, which it does once per second.
Conceptually, I agree that it would be nice if the client handled this autoscaling itself, so even other tools than the SDK can benefit from it, but since we have the scaling logic in the SDK, let's use that for now, since the client is used through the SDK the most, by far.

@fnesveda so just to double check, this is not true:

DynamoDB may return a list of unprocessed requests (we need to measure how often) and the server will be automatically retrying those with exponential backoff for up to 2 minutes. After this period if there is anything unprocessed it will be returned to the client to retry it client-side.

@mnmkng Yup, not anymore, we decided to remove the server-side retries, so that the client gets the rate limit errors as soon as possible. We forgot to remove the mention in Notion, sorry.


fix(deps): update terraform terraform-ibm-modules/observability-agents/ibm to v1.26.0

This PR contains the following updates:

Package
Type
Update
Change

terraform-ibm-modules/observability-agents/ibm (source)
module
minor
1.25.4 -> 1.26.0

Release Notes

terraform-ibm-modules/terraform-ibm-observability-agents (terraform-ibm-modules/observability-agents/ibm)
v1.26.0
Compare Source
Features

deps: update icr.io/ext/logdna-agent docker tag to v3.10.0-20240620.7524d812f60db3d2 (#354) (2c17d18)

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:tada: This PR is included in version 1.9.1 :tada:
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chore(main): release 0.0.6

:robot: I have created a release beep boop
0.0.6 (2024-09-26)
Features

add make for cjs-module-lexer (30f0e7e)

This PR was generated with Release Please. See documentation.

:robot: Release is at https://github.com/mhdawson/wasm-builder/releases/tag/v0.0.6 :sunflower:


oauth/oidc: token expiration policy attribute name

Attribute name is invalid: documentation says timeToLive and cas search for timeToKill
https://github.com/apereo/cas/blob/b1a805429dcff00415a9a3b7d8ebfa6d01809afc/support/cas-server-support-oauth-services/src/main/java/org/apereo/cas/support/oauth/services/DefaultRegisteredServiceOAuthAccessTokenExpirationPolicy.java#L31
https://github.com/apereo/cas/blob/b1a805429dcff00415a9a3b7d8ebfa6d01809afc/support/cas-server-support-oauth-services/src/main/java/org/apereo/cas/support/oauth/services/DefaultRegisteredServiceOAuthRefreshTokenExpirationPolicy.java#L29

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.


Align Demo and Website styling

Aligning the demo-page with the overall website styling.
Also see https://github.com/highlightjs/hljs_org/pull/2
Changes

Use same fonts as website ("PT Sans" for text, "Consolas" for code)
before

after

Use CSS scrollbars and remove "perfect-scrollbar"

Align link and text colors
Set min-width on content
Use thin scrollbar for code (on Firefox)

Checklist

[x] ~Added markup tests~, N/A, only demo website changes
[x] ~Updated the changelog at CHANGES.md~ No changes to the library
[x] ~Added myself to AUTHORS.txt, under Contributors~ Already there 😉

I'll fetch this local to play with later, but it's probably fine. :)  Nice to see perfect scrollbar die.

@Hirse Thanks so much!  I made a few small tweaks here and there.


Custom PCH storage location

Is there a way to specify the pch storage location? It seems to default to /tmp. The problem is we only have a small /tmp space on our servers that are used by multiple developers. As such, it fills up quickly with pch files and then causes problems system wide. Please let me know if there is a way to change that or consider adding this option in a future version.
EDIT: Looks like setting TMPDIR to a different location is  a way to control that location. But still, would be good to have an explicit way of changing that just for clangd.

I know it can't be done this way now, but it should be either an arg to clangd (like --tmpdir or an environment variable like CLANGD_TMPDIR. It should also be a setting in .clangd.
Clangd already respects OS specific locations for its config file, so it could also use something like $XDG_CACHE_DIR/clangd on linux for example. This could be the default location.

See also discussion in https://github.com/llvm/llvm-project/issues/65029


[Performance] Setup a microbenchmark to monitor non-gemm kernel performance

We need a Microbenchmark to check the performance regularly, guarantee there is no huge regression after some changes.
Currently we already have 130+ triton none-gemm kernels extracted from pytorch E2E models: https://github.com/intel/intel-xpu-backend-for-triton/tree/liyang/micro-benchmark/benchmark/inductor_kernels
There are several points that need to be decided:

The scope of the benchmark
kernel number, kernel categories, ...
The baseline
who will the benchmark perf data compare to. This should have an agreement with pytorch team.
The automated checking strategy.

We need to provide a powerful compare method to confirm Triton's performance is good. like: E2E/kernels compare to PVC + IPEX/NV platform,

We need to provide a powerful compare method to confirm Triton's performance is good. like: E2E/kernels compare to PVC + IPEX/NV platform,

Yes. Given the fused Triton kernels from PyTorch E2E models, to setup the benchmark, we should decide

a convincing methodology to monitor kernel performance
For PyTorch models, they calculate the speedup ratio, which is graph mode (using Triton) / eager mode, then compare speedup ratio gap towards CUDA.
But for Triton kernel only, it's hard to map Inductor generated Triton kernel to eager mode operations. It's unrealistic to reproduce each Triton kernel on other libraries like oneDNN, XeTLA, to do the comparison on the same Intel platform.
So, an initial proposal in my mind is, comparing the kernel performance with CUDA. We can make categories on kernels, for memory-bound, computation-bound ... kernels, we apply suitable scaling factors onto performance data to narrow down the hardware differences. This needs more discussion.
the target and plan on the execution
We should know how much performance data is our target? the scope of kernels? will the kernel be change with PyTorch update? Do kernel analysis would be effort-taking, we don't want to do it back and forth.

When above points are resolved, maybe we can consider add this non-gemm benchmark to https://github.com/intel/intel-xpu-backend-for-triton/issues/879 and tracked by CI or nightly.

This microbenchmark purpose is to check performance regressions.

Split this ticket into the two: base (existing kernels - softmax) and additions (generalized / standalone reduction kernels).

Split this ticket into the two: base (existing kernels - softmax) and additions (generalized / standalone reduction and atomic add kernels).

2 issues are filed to track these 2 step:

https://github.com/intel/intel-xpu-backend-for-triton/issues/999
https://github.com/intel/intel-xpu-backend-for-triton/issues/1000

Propose to set the issue as an umbrella issue, will create some sub-issue to track details.


Broken with the recent file on next.js

Previous version was working fine with next.js. Somehow I think the update on the model on Cloudfront is making this fail.

I've done the following:

Download the raw zip https://github.com/GantMan/nsfw_model/releases/tag/1.1.0
Copy and paste the contents of web_model_quantized in my own s3 directory.
Try to use that link

Results in the following error:
Error: layer: Improper config format: {"node":[{"name":"input","op":"Placeholder","attr":{"shape":{"shape":{"dim":[{"size":"-1"},{"size":"224"},{"size":"224"},{"size":"3"}]}},"dtype":{"type":"DTFLOAT"}}},{"name":"StatefulPartitionedCall/sequential/keras_layer/StatefulPartitionedCall/StatefulPartitionedCall/StatefulPartitionedCall/predict/MobilenetV2/Conv/Conv2D_weights","op":"Const","attr":{"value":{"tensor":{"dtype":"DTFLOAT","tensorShape":{"dim":[{"size":"3"},{"size":"3"},{"size":"3"},{"size":"48"}]}}},"dtype":{"type":"DTFLOAT"}}},{"name":"StatefulPartitionedCall/sequential/keras_layer/StatefulPartitionedCall/StatefulPartitionedCall/StatefulPartitionedCall/predict/MobilenetV2/expanded_conv_14/expand/Conv2D_bn_offset","op":"Const","attr":{"value":{"tensor":{"dtype":"DTFLOAT","tensorShape":{"dim":[{"size":"1344"}]}}},"dtype":{"type":"DTFLOAT"}}},{"name":"StatefulPartitionedCall/sequential/keras_layer/StatefulPartitionedCall/StatefulPartitionedCall/StatefulPartitionedCall/predict/MobilenetV2/Conv/Conv2D_bn_offset","op":"Const","attr":{"value":{"tensor":{"dtype":"DTFLOAT","tensorShape":{"dim":[{"size":"48"}]}}},"dtype":{"type":"DTFLOAT"}}},{"name":"StatefulPartitionedCall/sequential/keras_layer/StatefulPartitionedCall/StatefulPartitionedCall/StatefulPartitionedCall/predict/MobilenetV2/expanded_conv/depthwise/depthwise_weights","op":"Const","attr":{"value":{"tensor":{"dtype":"DTFLOAT","tensorShape":{"dim":[{"size":"3"},{"size":"3"},{"size":"48"},{"size":"1"}]}}},"dtype":{"type":"DTFLOAT"}}},{"name":"StatefulPartitionedCall/sequential/keras_layer/StatefulPartitionedCall/StatefulPartitionedCall/StatefulPartitionedCall/predict/MobilenetV2/expanded_conv/depthwise/depthwise_bn_offset","op":"Const","attr":{"value":{"tensor":{"dtype":"DTFLOAT","tensorShape":{"dim":[{"size":"48"}]}}},"dtype":{"type":"DTFLOAT"}}},{"name":"StatefulPartitionedCall/sequential/keras_layer/StatefulPartitionedCall/StatefulPartitionedCall/StatefulPartitionedCall/predict/MobilenetV2/expanded_conv/project/Conv2D_weights","op":"Const","attr":{"value":{"tensor":{"dtype":"DTFLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"48"},{"size":"24"}]}}},"dtype":{"type":"DTFLOAT"}}},{"name":"StatefulPartitionedCall/sequential/keras_layer/StatefulPartitionedCall/StatefulPartitionedCall/StatefulPartitionedCall/predict/MobilenetV2/expanded_conv/project/Conv2D_bn_offset","op":"Const","attr":{"value":{"tensor":{"dtype":"DTFLOAT","tensorShape":{"dim":[{"size":"24"}]}}},"dtype":{"type":"DTFLOAT"}}},{"name":"StatefulPartitionedCall/sequential/keras_layer/StatefulPartitionedCall/StatefulPartitionedCall/StatefulPartitionedCall/predict/MobilenetV2/expanded_conv_1/expand/Conv2D_weights","op":"Const","attr":{"value":{"tensor":{"dtype":"DTFLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"24"},{"size":"144"}]}}},"dtype":{"type":"DTFLOAT"}}},{"name":"StatefulPartitionedCall/sequential/keras_layer/StatefulPartitionedCall/StatefulPartitionedCall/StatefulPartitionedCall/predict/MobilenetV2/expanded_conv_14/depthwise/depthwise_weights","op":"Const","attr":{"value":{"tensor":{"dtype":"DTFLOAT","tensorShape":{"dim":[{"size":"3"},{"size":"3"},{"size":"1344"},{"size":"1"}]}}},"dtype":{"type":"DTFLOAT"}}},{"name":"StatefulPartitionedCall/sequential/keras_layer/StatefulPartitionedCall/StatefulPartitionedCall/StatefulPartitionedCall/predict/MobilenetV2/expanded_conv_1/expand/Conv2D_bn_offset","op":"Const","attr":{"value":{"tensor":{"dtype":"DTFLOAT","tensorShape":{"dim":[{"size":"144"}]}}},"dtype":{"type":"DTFLOAT"}}},{"name":"StatefulPartitionedCall/sequential/keras_layer/StatefulPartitionedCall/StatefulPartitionedCall/StatefulPartitionedCall/predict/MobilenetV2/expanded_conv_1/depthwise/depthwise_weights","op":"Const","attr":{"value":{"tensor":{"dtype":"DTFLOAT","tensorShape":{"dim":[{"size":"3"},{"size":"3"},{"size":"144"},{"size":"1"}]}}},"dtype":{"type":"DTFLOAT"}}},{"name":"StatefulPartitionedCall/sequential/keras_layer/StatefulPartitionedCall/StatefulPartitionedCall/StatefulPartitionedCall/predict/MobilenetV2/expanded_conv_1/depthwise/depthwise_bn_offset","op":"Const","attr":{"value":{"tensor":{"dtype":"DTFLOAT","tensorShape":{"dim":[{"size":"144"}]}}},"dtype":{"type":"DTFLOAT"}}},{"name":"StatefulPartitionedCall/sequential/keras_layer/StatefulPartitionedCall/StatefulPartitionedCall/StatefulPartitionedCall/predict/MobilenetV2/expanded_conv_1/project/Conv2D_weights","op":"Const","attr":{"value":{"tensor":{"dtype":"DTFLOAT","tensorShape":{"dim":[{"size":"1"},{"size":"1"},{"size":"144"},{"size":"32"}]}}},"dtype":{"type":"DTFLOAT"}}},{"name":"StatefulPartitionedCall/sequential/keras_layer/StatefulPartitionedCall/StatefulPartitionedCall/StatefulPartitionedCall/predict/MobilenetV2/expanded_conv_14/depthwise/depthwise_bn_offset","op":"Const","attr":{"value":{"tensor":{"dtype":"DTFLOAT","tensorShape":{"dim":[{"size":"1344"}]}}},"dtype":{"type":"DTFLOAT"}}},{"name":"StatefulPartitionedCall/sequential/keras_layer/StatefulPartitionedCall/StatefulPartitionedCa'className' and 'config' must set.

CDN is down :  FetchError: request to https://d1zv2aa70wpiur.cloudfront.net/tfjs_quant_nsfw_mobilenet/model.json failed, reason: getaddrinfo ENOTFOUND d1zv2aa70wpiur.cloudfront.net
My logs :
2023-12-22T09:05:19.835173+00:00 app[web.1]: ><EMAIL_ADDRESS>start
2023-12-22T09:05:19.835173+00:00 app[web.1]: > node server.js
2023-12-22T09:05:19.835173+00:00 app[web.1]:
2023-12-22T09:05:20.269873+00:00 app[web.1]: 2023-12-22 09:05:20.269767: I tensorflow/core/util/util.cc:169] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2023-12-22T09:05:20.305057+00:00 app[web.1]: 2023-12-22 09:05:20.304914: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 AVX512F AVX512_VNNI FMA
2023-12-22T09:05:20.305060+00:00 app[web.1]: To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2023-12-22T09:05:20.503512+00:00 app[web.1]:
2023-12-22T09:05:20.503513+00:00 app[web.1]: /app/node_modules/@tensorflow/tfjs-core/node_modules/node-fetch/lib/index.js:1491
2023-12-22T09:05:20.503515+00:00 app[web.1]: reject(new FetchError(`request to ${request.url} failed, reason: ${err.message}`, 'system', err));
2023-12-22T09:05:20.503515+00:00 app[web.1]: ^
2023-12-22T09:05:20.505376+00:00 app[web.1]: FetchError: request to https://d1zv2aa70wpiur.cloudfront.net/tfjs_quant_nsfw_mobilenet/model.json failed, reason: getaddrinfo ENOTFOUND d1zv2aa70wpiur.cloudfront.net
2023-12-22T09:05:20.505378+00:00 app[web.1]: at ClientRequest.<anonymous> (/app/node_modules/@tensorflow/tfjs-core/node_modules/node-fetch/lib/index.js:1491:11)
2023-12-22T09:05:20.505380+00:00 app[web.1]: at ClientRequest.emit (node:events:513:28)
2023-12-22T09:05:20.505381+00:00 app[web.1]: at TLSSocket.socketErrorListener (node:_http_client:494:9)
2023-12-22T09:05:20.505381+00:00 app[web.1]: at TLSSocket.emit (node:events:513:28)
2023-12-22T09:05:20.505381+00:00 app[web.1]: at emitErrorNT (node:internal/streams/destroy:157:8)
2023-12-22T09:05:20.505381+00:00 app[web.1]: at emitErrorCloseNT (node:internal/streams/destroy:122:3)
2023-12-22T09:05:20.505384+00:00 app[web.1]: at processTicksAndRejections (node:internal/process/task_queues:83:21) {
2023-12-22T09:05:20.505386+00:00 app[web.1]: type: 'system',
2023-12-22T09:05:20.505386+00:00 app[web.1]: errno: 'ENOTFOUND',
2023-12-22T09:05:20.505386+00:00 app[web.1]: code: 'ENOTFOUND'
2023-12-22T09:05:20.505386+00:00 app[web.1]: }
2023-12-22T09:05:20.606437+00:00 heroku[web.1]: Process exited with status 1
2023-12-22T09:05:20.628032+00:00 heroku[web.1]: State changed from starting to crashed

You can download the model here:  https://github.com/infinitered/nsfwjs/tree/master/example/nsfw_demo/public/quant_mid
And point it at your own server.  I'll see what's up with cloudfront and report back.

Ok, I paid the AWS bill 😄
To stop this in the future host your own copy:
https://github.com/infinitered/nsfwjs?tab=readme-ov-file#host-your-own-model


Incompatible shapes error and bullet #5 DID NOT fix that

Hi there, I encountered a  Incompatible shapes: [1,1595,513] vs. [1,640,513] Error during training and the ALMIGHTY bullet #5 can not fix that. This error is raised when I calculate the L1 loss between linear_target and linear_output. I am not quite fimiliar with the whole structure of the network, so is there something I missed cause I really can't figure out which part decides the total length of the linear_output?
Any suggestion on how to fix that, why would it happen, or is there anyone else who has same problem?
Part of my training log:
(uploading strangely went worng,have to paste it)
Exiting due to exception: Incompatible shapes: [1,1545,513] vs. [1,620,513]
[[Node: model/optimizer/gradients/model/loss/sub_1_grad/BroadcastGradientArgs = BroadcastGradientArgs[T=DT_INT32, _device="/job:localhost/replica:0/task:0/device:CPU:0"](model/optimizer/gradients/model/loss/sub_1_grad/Shape, model/optimizer/gradients/model/loss/sub_1_grad/Shape_1)]]
Caused by op 'model/optimizer/gradients/model/loss/sub_1_grad/BroadcastGradientArgs', defined at:
File ".\train.py", line 202, in
main()
File ".\train.py", line 198, in main
train(log_dir, args)
File ".\train.py", line 74, in train
model.add_optimizer(global_step)
File "D:\projects\tacotron\models\tacotron.py", line 174, in add_optimizer
gradients, variables = zip(*optimizer.compute_gradients(self.loss))
File "C:\Users\max\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\training\optimizer.py", line 514, in compute_gradients
colocate_gradients_with_ops=colocate_gradients_with_ops)
File "C:\Users\max\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\ops\gradients_impl.py", line 596, in gradients
gate_gradients, aggregation_method, stop_gradients)
File "C:\Users\max\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\ops\gradients_impl.py", line 779, in _GradientsHelper
lambda: grad_fn(op, *out_grads))
File "C:\Users\max\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\ops\gradients_impl.py", line 398, in _MaybeCompile
return grad_fn()  # Exit early
File "C:\Users\max\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\ops\gradients_impl.py", line 779, in
lambda: grad_fn(op, *out_grads))
File "C:\Users\max\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\ops\math_grad.py", line 889, in _SubGrad
rx, ry = gen_array_ops.broadcast_gradient_args(sx, sy)
File "C:\Users\max\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 812, in broadcast_gradient_args
"BroadcastGradientArgs", s0=s0, s1=s1, name=name)
File "C:\Users\max\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "C:\Users\max\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\util\deprecation.py", line 454, in new_func
return func(*args, **kwargs)
File "C:\Users\max\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 3155, in create_op
op_def=op_def)
File "C:\Users\max\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 1717, in init
self._traceback = tf_stack.extract_stack()
...which was originally created as op 'model/loss/sub_1', defined at:
File ".\train.py", line 202, in
main()
[elided 0 identical lines from previous traceback]
File ".\train.py", line 198, in main
train(log_dir, args)
File ".\train.py", line 73, in train
model.add_loss()
File "D:\projects\tacotron\models\tacotron.py", line 149, in add_loss
l1 = tf.abs(self.linear_targets - self.linear_outputs)
File "C:\Users\max\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\ops\math_ops.py", line 850, in binary_op_wrapper
return func(x, y, name=name)
File "C:\Users\max\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\ops\gen_math_ops.py", line 8769, in sub
"Sub", x=x, y=y, name=name)
File "C:\Users\max\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "C:\Users\max\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\util\deprecation.py", line 454, in new_func
return func(*args, **kwargs)
File "C:\Users\max\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 3155, in create_op
op_def=op_def)
File "C:\Users\max\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\framework\ops.py", line 1717, in init
self._traceback = tf_stack.extract_stack()

I have fixed this problem, close this issue now.


AWS Centos7.2 after reboot could not start

I installed rexray on the Ec2 instance:
$ uname -a
Linux ip-10-0-8-100.ec2.internal 3.10.0-327.4.4.el7.x86_64 #1 SMP Tue Jan 5 16:07:00 UTC 2016 x86_64 x86_64 x86_64 GNU/Linux

after each reboot I see next in logs:
https://gist.github.com/miry/2905e9eac75f5f716c14
but it works if I run manually.

Can you verify that "rexray env" returns the correctly configured
credentials for AWS?
It is best to run rexray interactively before trying to start it as a
service.
rexray volume -l debug
On Monday, January 25, 2016, Dr. Pr. Michael Nikitochkin <
<EMAIL_ADDRESS>wrote:

I installed rexray on the Ec2 instance:
$ uname -a
Linux ip-10-0-8-100.ec2.internal 3.10.0-327.4.4.el7.x86_64 #1 SMP Tue Jan 5 16:07:00 UTC 2016 x86_64 x86_64 x86_64 GNU/Linux
And in logs I see next
https://gist.github.com/miry/2905e9eac75f5f716c14
—
Reply to this email directly or view it on GitHub
https://github.com/emccode/rexray/issues/268.

@clintonskitson yes it works fine from the interactive. And service started correctly from the bash. I use /etc/rexray/config.yml to keep aws credentials.

So this is the output when you run "rexray start -l debug"?
On Monday, January 25, 2016, Dr. Pr. Michael Nikitochkin <
<EMAIL_ADDRESS>wrote:

@clintonskitson https://github.com/clintonskitson yes it works fine
from the interactive. And service started correctly from the bash. I use
/etc/rexray/config.yml to keep aws credentials.
—
Reply to this email directly or view it on GitHub
https://github.com/emccode/rexray/issues/268#issuecomment-174618577.

@miry I do see your question for clearly now.  So during the init startup of REX-Ray on Centos 7.2, REX-Ray fails to start properly.  It is upon a manual start that it starts running.  I need to see about replicating this.

I fixed the systemctl service:
[Unit]
Description=rexray
Before=docker.service

[Service]
Restart=always
RestartSec=30
EnvironmentFile=/etc/rexray/rexray.env
ExecStartPre=/usr/bin/rexray env
ExecStart=/usr/bin/rexray start -l debug -f
ExecReload=/bin/kill -HUP $MAINPID
KillMode=process

[Install]
WantedBy=docker.service

Thanks @miry!
Pulling the original file below.
[Unit]
Description=rexray
Before=docker.service

[Service]
EnvironmentFile={{.EnvFile}}
ExecStart={{.RexrayBin}} start -f
ExecReload=/bin/kill -HUP $MAINPID
KillMode=process

[Install]
WantedBy=docker.service

Very interesting, sot he ExecStartPre looks to be your fix?  @akutz any ideas here?

The fix is always restart. And I added interval 30 secs. So on boot I still has problem with loading driver, but at least the service tries to start again after 30 secs. and it success.

@miry That makes more sense.  Different drivers may have dependencies on networking, etc to be functioning properly to be able to initialize.  Having this restart makes sense to overcome some of the unknown there in terms of dependencies not being ready.

PR https://github.com/emccode/rexray/pull/272


RegistrationID doesn't seems right!

Hi!
I am trying to send push notifications with your plugin. Everything works well on Android, but on iOS the registration is successful, but I can't send notifications to the registered device (I am using PHP)
Expected Behaviour
Receive a registrationID with only hexadecimal characters
Actual Behaviour
RegistrationID contains not only hexadecimal characters.
registrationID received from registration callback:
dBCNCs9v2jY:APA91bFovRcUkhwAeL8_9sIVx7Quck6AWEipB9GDS8rZMKAMbERn0WTVHFrpBFvQ0I1l44OdkPi5XPwDSuQcGRTz-N3CjCXclovC__7kJiYDtfT8RhsfFDrANcFjD_5DzNMThaip8Nb1
Reproduce Scenario (including but not limited to)
Only follow the step by step configuration in docs.
Steps to Reproduce
Only follow the step by step configuration in docs.
Platform and Version (eg. Android 5.0 or iOS 9.2.1)
iOS 9.3.2 on iPhone 5S
Cordova CLI version and cordova platform version
cordova --version 6.0.0

Plugin version
cordova plugin version 1.6.3

Sample Push Data Payload
$body['aps'] = array( 'alert' => $message, 				'badge' => 1, 		 				'sound' => 'default', 				'content-available' => 1 				); 			$body['type'] = $type;
Sample Code that illustrates the problem
`var options = {};
options.android = {
senderID: app.android_sender_id,
};
options.ios = {
senderID: app.ios_sender_id,
alert: true,
badge: true,
sound: true,
gcmSandbox: false,
};
app.push = PushNotification.init(options);
app.push.on('registration', function(data){
alert(data.registrationId);
};`

@ngystvn90 well you are registering your app with GCM on iOS but you are trying to send your push data to APNS directly. If you want to use GCM on iOS you need to send your push payload to GCM which then forwards to APNS which delivers to your device.

Yes, you were right. I removed the senderID: app.ios_sender_id, from the ios options. I regenerated my *.pem and now I am able to get notifications in development. I hope everything will be okey in production as well. Thank you for pointing me to the right direction. Cheers!


add runtime storage permission using customARFragment

I want to add WRITE_EXTERNAL_STORAGE permission also in ARFragment . so how can i do that??
i have made a CustomArfragment which extends ARFragment and looks like this
ublic class CustomARFragment extends ArFragment {
@Override
protected Config getSessionConfiguration(Session session) {
Config config = new Config(session);
config.setPlaneFindingMode(Config.PlaneFindingMode.HORIZONTAL);
return config;
}
}

@ishaang10
Override get additional permissions() method in your custom ARFragment class which can handle your permission at run time. Here Below, I showed you an example of that. Try that one.
    @Override
    public String[] getAdditionalPermissions() {
        String[] additionalPermissions = super.getAdditionalPermissions();

        int permissionLength = additionalPermissions != null ? additionalPermissions.length : 0;

        String[] permissions = new String[permissionLength + 1];

        permissions[0] = Manifest.permission.WRITE_EXTERNAL_STORAGE;

        if (permissionLength > 0) {
            System.arraycopy(additionalPermissions,
                    0,
                    permissions,
                    1,
                    additionalPermissions.length);
        }

        return permissions;

        //return super.getAdditionalPermissions();
    }

thanks a lot sir...!!!


Allow phpunit v4.8 and above for compatibility with PHP 5.5.

This fixes the compatibility issue mentioned by @oanhnn in #35
Composer was set to require phpunit 5.4 and above, but phpunit 5.4 only supports PHP 5.6+, but Slim 3 support PHP 5.5. The test examples are compatible with phpunit v4, so I have altered composer.json to use the maximum possible version between 4.8 and 6.

3.1.1 released with this fix.


Ob/v3

Passes tests (had to adopt the snapshot a little bit by removing metadata that we don't ahve anymore)


FlatList scroll implementation is not full

I have a typical use-case, I need to scroll to a certain position in a FlatList that does have different elements size. How can I scroll to a certain element since I can't calculate the height of each element?
And the documentation has something like this on every function related to scrolling:

Note: cannot scroll to locations outside the render window without specifying the
getItemLayout prop.
*/

Please, advice is there any way to scroll to the custom height item.

In 0.43.4，You can scroll to locations without specifying the getItemLayout prop, however its performance is not good. I believe the performance issue is the reason why now it must be used along with getItemLayout.

This issue looks like a question that would be best asked on StackOverflow.
StackOverflow is amazing for Q&A: it has a reputation system, voting, the ability to mark a question as answered. Because of the reputation system it is likely the community will see and answer your question there. This also helps us use the GitHub bug tracker for bugs only.
Will close this as this is really a question that should be asked on StackOverflow.

Anyone have any idea with this issue?


google telephonic quiz round questions

These questions are based on my recent experience of interview with Google.

Microsoft Internship Questions were asked during Campus Recruitment in Feb 2019

#33  I have updated the requested changes @rishabh115

@all-contributors please add @tanaytoshniwal  for code


Fix scala maven repos

Description
The Maven Repo of Linux GPU and MacOS CPU were interchanged in the Scala package installation page. So made the necessary changes.

Thanks for noticing and submitting a fix!


 And death to you open source fanboys for promoting them.
Hope ya'll have a tragic life & painful death.
And one other thing....
There is no such thing as "software" "engineering" or "social" "engineering".  Stop being disrespectful to Engineering. You know nothing about what Engineering entails. Engineering means designing, building and producing real mechanical systems, like turbojets and vehicular engines. It has nothing to do with scriptkiddies sitting behind a keyboard and writing code. Software dev is easy and for kids. And it has absolutely nothing to do with a serious and real subject like
Engineering (Mechanical Engineering is the ONLY Engineering). Quit making false claims against engineering.

 And death to
you open source fanboys for promoting them.
Hope ya'll have a tragic life & painful death.
And one other thing....
There is no such thing as "software" "engineering" or "social"
"engineering".  Stop being
disrespectful to Engineering. You know nothing about what Engineering
entails. Engineering means designing, building and producing real
mechanical systems, like turbojets and vehicular engines. It has nothing to
do with scriptkiddies sitting behind a keyboard and writing code. Software
dev is easy and for kids. And it has absolutely nothing to do with a
serious and real subject like
Engineering (Mechanical Engineering is the ONLY Engineering). Quit making
false claims against engineering.
—
Reply to this email directly, view it on GitHub
https://github.com/MentalOutlaw/dwm/issues/5, or unsubscribe
https://github.com/notifications/unsubscribe-auth/AN4J3OZ3BL2YDQTX3ZJRL4LWQ7MDJANCNFSM6AAAAAATS3JNDM
.

I recommend 100mg of lithium or Zoloft once a day. Do not take it orally together with magnesium as it may alter the absorption of the medication. Also no grape fruit juice as it may do the same.


Experimental Feature?

When I run the Set-PnPHomeSite command, I get the following error:
"Set-PnPHomeSite : The requested operation is part of an experimental feature that is not supported in the current
environment."
I was under the impression this was pushed.  Am I just too early, or is there really an issue?

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

ID: 12da9c12-7eff-f43f-67ff-d667d12847d4
Version Independent ID: bf90101d-939a-08b0-79fd-1032f00eccc7
Content: Set-PnPHomeSite (sharepoint-pnp)
Content Source: sharepoint/sharepoint-ps/sharepoint-pnp/Set-PnPHomeSite.md
GitHub Login: @techwriter40
Microsoft Alias: kirks

@officedocsbot assign @yogkumgit

Hello @Anonimiss Thanks for your feedback.
PnP cmdlets as you might know, are a community-driven effort and are constantly evolving, the documentation for the PnP cmdlets is directly synchronized from the source code in this repo so if a new cmdlet is created there, there will be an article here, even though the feature can be experimental and in development. So there is no really an issue, it is just not ready yet.
Hope this information helps you. Thanks again

@get-itips  Thank you very much for the contribution and sharing this explanation. @Anonimiss
Hope this comment is helpful for you. Thanks for taking out some time to open the issue. Appreciate and encourage you to do the same in future also.


Submission of RandomGenerator class?

Is the RandomGenerator class required for submission on CodeCrunch too?

No.

Got it, thanks!

nope you cant send class files through codeCrunch anyways


dev mode?

is it possible to use this with dev mode or can it only be used once the astro app is built?

Because it is middleware it is necessary to build your project and include it in a hono server. You can still use astro dev mode normally as it provides you with a server and the HMR.

Okay but without the middleware locals isnt populated.


[CELEBORN-645][REFACTOR] Refine logic about handle HeartbeatFromWorkerResponse

What changes were proposed in this pull request?
Refine the logic here to make it easier understand.
Why are the changes needed?
Does this PR introduce any user-facing change?
How was this patch tested?

ping @RexXiong


CFFL

CFFL

Linter check found the following problems:
The following problems have been found:
ERROR: /tmp/abs_81hcskxagi/clone/recipe/meta.yaml:16: pip_install_args: pip install should be run with --no-deps.
ERROR: /tmp/abs_81hcskxagi/clone/recipe/meta.yaml:22: host_section_needs_exact_pinnings: Packages in host must have exact version pinnings, except python build tools.
ERROR: /tmp/abs_81hcskxagi/clone/recipe/meta.yaml:22: missing_wheel: For pypi packages, wheel should be present in the host section
ERROR: /tmp/abs_81hcskxagi/clone/recipe/meta.yaml:46: missing_dev_url: The recipe is missing a dev_url
WARNING: /tmp/abs_81hcskxagi/clone/recipe/meta.yaml:46: missing_description: The recipe is missing a description
ERROR: /tmp/abs_81hcskxagi/clone/recipe/meta.yaml:46: missing_license_family: The recipe is missing the about/license_family key.
Errors were found

Linter check found the following problems:
The following problems have been found:
ERROR: /tmp/abs_8cu_b44v6p/clone/recipe/meta.yaml:16: pip_install_args: pip install should be run with --no-deps.
ERROR: /tmp/abs_8cu_b44v6p/clone/recipe/meta.yaml:22: missing_wheel: For pypi packages, wheel should be present in the host section
ERROR: /tmp/abs_8cu_b44v6p/clone/recipe/meta.yaml:22: host_section_needs_exact_pinnings: Packages in host must have exact version pinnings, except python build tools.
ERROR: /tmp/abs_8cu_b44v6p/clone/recipe/meta.yaml:46: missing_license_family: The recipe is missing the about/license_family key.
ERROR: /tmp/abs_8cu_b44v6p/clone/recipe/meta.yaml:46: missing_dev_url: The recipe is missing a dev_url
WARNING: /tmp/abs_8cu_b44v6p/clone/recipe/meta.yaml:46: missing_description: The recipe is missing a description
Errors were found


[Improvements] Fix partially the throtteling bug and added the required field to the operator crd.

Description
Added some minor updates to the CRDs to support the missing security flag.
I also reduced the api requests.

Relevant issues/tickets

closes #603
closes #460

Type of change
I removed the throtteling a little bit by not asking for all api-resources in the cluster which are stable.
Now I reduced it only to the apiGroupVersion which reduces the request amount by huge margin.
This should mostly remove the throtteling messages.

[X] Bug fix (non-breaking change which fixes an issue)

Checklist

[X] Verified independently on a cluster by reviewer
[ ] Verified against an OpenShift Cluster.

Hi @Cellebyte as mentioned in https://github.com/grafana-operator/grafana-operator/issues/603 there is no point in enabling DisableInitialAdminCreation since we use the admin user to create dashboards.
Try this change locally and add a dashboard and I'm rather sure it shouldn't work.
The partial solution if minimizing the API calls Is more interesting though.
So if you update the PR to only include that we could take a look at that part
@pb82 have started to look at number of API requests as well so I will let him look at that part.

Hi @Cellebyte as mentioned in #603 there is no point in enabling DisableInitialAdminCreation since we use the admin user to create dashboards. Try this change locally and add a dashboard and I'm rather sure it shouldn't work.
The partial solution if minimizing the API calls Is more interesting though. So if you update the PR to only include that we could take a look at that part
@pb82 have started to look at number of API requests as well so I will let him look at that part.

I reverted the changes I did to the CRD.
I only left the fix for the API Requests.

@NissesSenap is this now ready to merge?

@Cellebyte i'll give it a try and merge early next week, thanks a lot for the contribution!


Storage class for s3

Closes #9
The following PR implements the AwsS3Storage for use with AWS. Similar to LocalStorage, the AWS trait allows retrieving objects, formatting their urls, and determining their sizes.
The trait uses a BufReader<Cursor<Bytes>> Streamable type to implement AsyncRead and AsyncSeek. Currently this requires reading the entire contents of the S3 object into memory for get operations, and does not use a byte stream. There doesn't appear to be a ready-made type (such as tokio StreamReader) that implements both AsyncRead and AsyncSeek for byte streams, however I don't think it would be too hard to make one.
Urls are retrieved as presigned s3 urls. There is also the get_retrieval_type function which determines whether an object in immediately retrievable, or stored in longer-term storage and cannot be accessed right away.
Still to do is connecting the AwsS3Storage for use in the actual server, and allowing it to be configured. This could be part of a different issue, as currently server configuration is done using environment variables, which gets a bit messy when there is more structured configuration options. It may be better to transition to using config files like htsget-refserver.

Should we close this one, and I'll open another PR for the storage http server, as it's a separate issue? @brainstorm

Should we close this one, and I'll open another PR for the storage http server, as it's a separate issue in #73? @brainstorm

If by close you mean merge, yes please go ahead and open a new PR for #73. Thx!

If by close you mean merge, yes please go ahead and open a new PR for #73. Thx!

Yes, that's what I meant!


What is mask_score?

Hello, you have done a very great job on cell segmentation. I want to use the coco_evaluation.py you public to evaluate the performance of my model. I have read your code but have a question:
What does mask_score(here replace score) mean in the code ? Is it IoU of (pred instance ) and (gt instance) for each instance in a image?
Thank you for answering my question!

Hi there @XunDejin, we are delighted to hear that people such as you are using the LIVECell resources.
The evaluation script is based on work done by youngwanLEE in his CenterMask2 repo but modified by us to evaluate many more instances per image.
The mask_score is a metric that i think is introduced in the CenterMask2 code and is defined as box scores * maskiou per instance. You can find the code that calculates and attaches the score to each instance here.
I hope that gave you some clarity.

Thank you very much for answering my question!
I will study and try it.


Longevity test runner doesn't use NGINX Plus image

Running longevity tests using:
 make start-longevity-test PLUS_ENABLED=true

with vars.env like below:
TAG=edge
PREFIX=<redacted>/nginx-gateway-fabric
NGINX_PREFIX=<redacted>/nginx-gateway-fabric/nginx
NGINX_PLUS_PREFIX=<redacted>/nginx-gateway-fabric/nginx-plus

wrongly uses NGINX_PREFIX image:
make start-longevity-test PLUS_ENABLED=true
START_LONGEVITY=true /Library/Developer/CommandLineTools/usr/bin/make nfr-test
NFR=true bash scripts/run-tests-gcp-vm.sh
vars.env                                                                                100% 1024    23.0KB/s   00:00
go test -v ./suite -ginkgo.label-filter "nfr" -ginkgo.label-filter "longevity-setup" -ginkgo.v -args --gateway-api-version=1.0.0  \
        --gateway-api-prev-version=1.0.0  --image-tag=edge --version-under-test= \
        --plus-enabled=true --ngf-image-repo=<redacted>/nginx-gateway-fabric --nginx-image-repo=<redacted>/nginx \

When running GKE-based tests, you need to set the variable in the vars.env file. The make target variables are not propagated to the VM.

@sjberman  my bad, should have included in the description:
PLUS_ENABLED=true

However, note how it propagated to --plus-enabled=true  in the ginkgo output

NGINX_PREFIX also needs to specify the correct image


docs: Fix broken nav links

Sidebar nav items weren't using Gatsby's Link, so weren't picking up the pathPrefix in the config and were 404ing. This should fix that. (But note that for some reason yarn build failed for me locally so I can't validate this fix.)

Incidentally, looks like the logo at the site root isn't picking up the font anymore for some reason:

I see the same issue at https://astroturf.netlify.app/ so I don't think it's related to the prefix.

lol the svg must contain actual text, not a path, that's silly. will fix

Cool! Sidebar links still 404 for me unfortunately -- not sure if there's CI for the site set up or if there's a manual build step currently


add option to set gym http server url

Enable non standard gym http server location via command line options

Great, nice work. This should allow for starting up multiple communication channels as well. You may have already done this, but would you mind running:
https://github.com/twitter/torch-twrl/blob/master/test/test-gym.lua
with a server started, to make sure that all passes...
It is not included in github travis checks as it would fail if the server wasn't started, but it should help show us that this change passes and can be squash and merged no problem.
Please let me know if there are any questions.
K


What security methods are used in the migrator to protect data during migration?

We are evaluating whether this is a solution for us and for our Info Sec crew to approve we need to see some security details for this app.
Where may I find those? Or can you send to me?
Thanks!

Hi @rrobertsor
I will paste all of the security details available below. If you can any further specific questions, feel free to comment and I'll answer to the best of my ability :)
Development details

Which programming language is used?
.NET Framework (C#)

Are third party components or plugins used?
Here is a list of the top-level NuGet packages used by the solution as of 2023-09-03:

Top-level Package
Version

Atlassian.SDK
12.1.0

AutoFixture
4.11.0

AutoFixture.AutoNSubstitute
4.11.0

coverlet.collector
3.1.2

Microsoft.NET.Test.Sdk
16.5.0

Microsoft.TeamFoundationServer.Client
16.153.0

Newtonsoft.Json
13.0.1

NSubstitute
4.2.1

NUnit
3.12.0

NUnit.Analyzers
3.3.0

NUnit3TestAdapter
4.2.1

System.IO.Abstractions
17.0.11

Does the application use web services or APIs?
The solution uses the following web APIs:

Azure DevOps Services/Server REST API (https://learn.microsoft.com/en-us/rest/api/azure/devops)
Jira REST API (https://developer.atlassian.com/server/jira/platform/rest-apis/)
Azure Applications Insights API for telemetry (Can be turned off)

Network security

How will data integrity be ensured during the migration?

The integrity of the Jira data is ensured by the tool.
Project reader access is sufficient in Jira.

How do you ensure the security of data during migration?

The data will be exported to disk. If necessary, the migration should be carried out on an on-premises environment to ensure full compliance. If so, the customer needs to provision an environment.

Does the solution have encryption in transit? (SSL/TLS)
https is supported for all network traffic.

Does the solution have encryption at rest? (file or disk)
The tool does not provide any encryption at rest service.

Does the solution have encryption/obfuscation while processing? (P2PE)
The tool does not provide any P2PE service.

Has the code base gone through a static code review for OWASP top 10 and/or SANS25?
The tool frequently undergoes OWASP top 10 static code analysis through Sonarqube.

Has the app gone through a DAST or other dynamic testing?
No

Are there any hard-coded passwords within the code base?
No

Does the application have the ability to prevent duplicate concurrent sessions per user?
No

Does the application have the ability to limit the total number of active sessions?
No

Does the application have the ability to automatically tear down/terminate sessions and logout after a defined time is exceeded?
No

Does the application validate ALL input, regardless of the source, when it crosses a trust boundary?
The application validates any user input parameters and configuration for the purpose of ensuring that the program can execute normally.

Is the application SAML 2.0 compatible? Is the application able to integrate with Active Directory?
The application does not integrate with Active Directory or SAML. The user will instead provide their API tokens for the respective services in order to authenticate.


[release-1.5] Fix GOBUILDFLAGS usage in codecov scripts

This is an automated cherry-pick of #22178

@googlebot I consent.


Transfer nft script is added

Resolves #209

Checklist before requesting a review

[x] I have added documentation to README
[x] I have performed a self-review of my code
[x] I have tested this new feature or change on devnet and verified that it works


FLANN lib cannot be found when compiling pcl

I was trying to compile pcl (Windows) from source since vcpkg is currently not able to install it. So what I did was I installed flann from vcpkg and linked it to install pcl.
pcl> mkdir build
pcl> cd build
cmake .. -DCMAKE_TOOLCHAIN_FILE=C:\Users\XXX\source\vcpkg\scripts\buildsystems\vcpkg.cmake -DVCPKG_TARGET_TRIPLET=x64-windows-static -G "Visual Studio 15 2017 Win64"
-- The C compiler identification is MSVC 19.16.27026.1
-- The CXX compiler identification is MSVC 19.16.27026.1
-- Check for working C compiler: C:/Program Files (x86)/Microsoft Visual Studio/2017/Community/VC/Tools/MSVC/14.16.27023/bin/Hostx86/x64/cl.exe
-- Check for working C compiler: C:/Program Files (x86)/Microsoft Visual Studio/2017/Community/VC/Tools/MSVC/14.16.27023/bin/Hostx86/x64/cl.exe -- works
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Detecting C compile features
-- Detecting C compile features - done
-- Check for working CXX compiler: C:/Program Files (x86)/Microsoft Visual Studio/2017/Community/VC/Tools/MSVC/14.16.27023/bin/Hostx86/x64/cl.exe
-- Check for working CXX compiler: C:/Program Files (x86)/Microsoft Visual Studio/2017/Community/VC/Tools/MSVC/14.16.27023/bin/Hostx86/x64/cl.exe -- works
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Detecting CXX compile features
-- Detecting CXX compile features - done
-- Found PkgConfig: C:/Users/XXXXX/Downloads/cmake-3.13.3-win64-x64/bin/pkg-config.exe (found version "0.26")
-- Performing Test HAVE_MM_MALLOC
-- Performing Test HAVE_MM_MALLOC - Failed
-- Performing Test HAVE_POSIX_MEMALIGN
-- Performing Test HAVE_POSIX_MEMALIGN - Failed
-- Performing Test HAVE_SSE4_2_EXTENSIONS
-- Performing Test HAVE_SSE4_2_EXTENSIONS - Success
-- Performing Test HAVE_SSE4_1_EXTENSIONS
-- Performing Test HAVE_SSE4_1_EXTENSIONS - Success
-- Performing Test HAVE_SSSE3_EXTENSIONS
-- Performing Test HAVE_SSSE3_EXTENSIONS - Success
-- Performing Test HAVE_SSE3_EXTENSIONS
-- Performing Test HAVE_SSE3_EXTENSIONS - Success
-- Performing Test HAVE_SSE2_EXTENSIONS
-- Performing Test HAVE_SSE2_EXTENSIONS - Success
-- Performing Test HAVE_SSE_EXTENSIONS
-- Performing Test HAVE_SSE_EXTENSIONS - Success
-- Found OpenMP_C: -openmp (found version "2.0")
-- Found OpenMP_CXX: -openmp (found version "2.0")
-- Found OpenMP: TRUE (found version "2.0")
-- Found OpenMP
-- Looking for pthread.h
-- Looking for pthread.h - not found
-- Found Threads: TRUE
-- Checking for module 'eigen3'
--   No package 'eigen3' found
-- Found Eigen: C:/Users/XXXXx/source/vcpkg/installed/x64-windows-static/include/eigen3 (Required is at least version "3.1")
-- Eigen found (include: C:/Users/XXXXX/source/vcpkg/installed/x64-windows-static/include/eigen3, version: 3.3.7)
-- Checking for module 'flann>=1.7.0'
--   Found flann, version 1.9.1
CMake Error at C:/Program Files/CMake/share/cmake-3.13/Modules/FindPackageHandleStandardArgs.cmake:137 (message):
  Could NOT find FLANN (missing: FLANN_LIBRARIES) (Required is at least
  version "1.7.0")
Call Stack (most recent call first):
  C:/Program Files/CMake/share/cmake-3.13/Modules/FindPackageHandleStandardArgs.cmake:378 (_FPHSA_FAILURE_MESSAGE)
  cmake/Modules/FindFLANN.cmake:111 (find_package_handle_standard_args)
  C:/Users/XXXXXX/source/vcpkg/scripts/buildsystems/vcpkg.cmake:266 (_find_package)
  CMakeLists.txt:290 (find_package)

 -- Found flann, version 1.9.1
Could NOT find FLANN (missing: FLANN_LIBRARIES)

cmake/Modules/FindFLANN.cmake:111
most likely the library name does not match
libflann.liib flann.lib libflann-1.9.lib, etc.

I think this issue is resolved. Please reopen this issue if it's still exists.
Thanks.

 -- Found flann, version 1.9.1
Could NOT find FLANN (missing: FLANN_LIBRARIES)

cmake/Modules/FindFLANN.cmake:111
most likely the library name does not match
libflann.liib flann.lib libflann-1.9.lib, etc.

How to solve this problem, please?


500 Internal Server Error / on 304 response and empty ReadableStream

It seems there is inconsistency between CF and Miniflare. PoC code:
addEventListener('fetch', function(event) {
  event.respondWith(handleRequest(event.request))
})
async function handleRequest(request) {
  let url = new URL(request.url)
  const res = await fetch(`http://origin.cloudtest.it${url.pathname}`, {headers: {"if-modified-since": "Wed, 12 Jan 2022 10:43:29 GMT"}})
  return new Response(res.body, {
    headers: {
      ...Object.fromEntries(res.headers),
      "x-workers-hello": "Hello from Cloudflare Workers"
    },
    status: res.status,
    statusText: res.statusText
  })
}

Throws the following error:
GET /bigfiles/256m 500 Internal Server Error (98.22ms)
[mf:err] GET /bigfiles/256m: TypeError: Response with null body status cannot have body
    at new Response (/Users/lukes/labs/cf-workers/sandbox-lukasz-testing/node_modules/undici/lib/fetch/response.js:160:15)
    at new Response (/Users/lukes/labs/cf-workers/sandbox-lukasz-testing/node_modules/@miniflare/core/src/standards/http.ts:556:13)
    at handleRequest (/Users/lukes/labs/cf-workers/sandbox-lukasz-testing/index.js:22:10)
    at processTicksAndRejections (node:internal/process/task_queues:96:5)
    at EventTarget.[kDispatchFetch] (/Users/lukes/labs/cf-workers/sandbox-lukasz-testing/node_modules/@miniflare/core/src/standards/event.ts:359:13)
    at Server.<anonymous> (/Users/lukes/labs/cf-workers/sandbox-lukasz-testing/node_modules/@miniflare/http-server/src/index.ts:167:20)

The origin server returns 304 response with no body (as expected). The reason of the error is that res.body is a ReadableStream which is empty but the object itself is not, therefore the undici library doesn't like it and throws an error (304 responses don't have response body).
I was sitting on the fence if this should be reported here or maybe to the dependency's maintainer. In fact, the object type could be detected to behave properly. WDYT?

if you are happy with the proposal I can create a PR?


update jquery visualize and add the jquery/visualize asset

fix #1836

After playing a bit with 5.7 and visualize, it seems that either the version shipped was heavily modified or just old, and was plainly broken with 5.7 (probably coming from incompatibilities with latest jquery and our current styling).
As a result, it was simply unusable, so I went ahead and updated to the last version on github available here:
https://github.com/filamentgroup/jQuery-Visualize
(graph now work once again).

Thanks!


[DEMO] Completion Features

Config completion
PHP:
https://github.com/yaegassy/coc-laravel/assets/188642/3ccf8f43-25e7-4c67-8a13-c0e23ab1a581
Blade:
https://github.com/yaegassy/coc-laravel/assets/188642/59c26c21-b18a-40aa-bedc-21cea5639d8f

Env completion
PHP:
https://github.com/yaegassy/coc-laravel/assets/188642/f0a0bd29-958e-4dbc-9fa8-b5dfc50d796c
Blade:
https://github.com/yaegassy/coc-laravel/assets/188642/6cb32ff8-e1ca-4f32-90e5-58740a09b145

Validation completion
https://github.com/yaegassy/coc-laravel/assets/188642/8c775e92-e642-4cfa-9d20-a85a60fff981

Route completion
PHP:
https://github.com/yaegassy/coc-laravel/assets/188642/15854a8a-28cf-400c-92fb-79adfe0abfe6
Blade:
https://github.com/yaegassy/coc-laravel/assets/188642/47e61640-314e-40cd-90aa-09781ad7dd71

View completion
PHP:
https://github.com/yaegassy/coc-laravel/assets/188642/9305144a-9527-495b-a96a-1aa510633640
Blade:
https://github.com/yaegassy/coc-laravel/assets/188642/0a1cbfea-691b-4e8f-bf9a-fe29168f7862

Middleware completion
https://github.com/yaegassy/coc-laravel/assets/188642/5e17383b-d386-426b-a55f-7c79783e9de9

Guard completion
PHP:
https://github.com/yaegassy/coc-laravel/assets/188642/5787c49c-fffa-46d3-8fca-2f345c7bedfa
Blade:
https://github.com/yaegassy/coc-laravel/assets/188642/699b2db7-82eb-448d-b90f-274c21124b4a

Translation Completion
Blade:
https://github.com/yaegassy/coc-laravel/assets/188642/2350f3c1-9211-4c80-a0ea-59bbc49223b5

ComponentTag Completion
https://github.com/yaegassy/coc-laravel/assets/188642/09b143d8-b066-4279-b70c-85aa589aa79d

ComponentProps Completion
https://github.com/yaegassy/coc-laravel/assets/188642/43221895-4166-49c1-bd75-7adc01d5aa15

PHP Function Completion
https://github.com/yaegassy/coc-laravel/assets/188642/e98757bd-5c0b-4089-842f-5b6609503c5d

Method directive parameter Completion
https://github.com/yaegassy/coc-laravel/assets/188642/539ae7ba-11a7-4fd4-9f65-ef2ec40d040a

Component Completion
https://github.com/yaegassy/coc-laravel/assets/188642/f64d207e-82db-48ac-8ea3-41f7497996cf

Directive completion
https://github.com/yaegassy/coc-laravel/assets/188642/14c87529-8534-45ee-9cfe-3631d99415fd

Livewire tag completion
https://github.com/yaegassy/coc-laravel/assets/188642/31655790-7ab5-4aa5-8431-c163a076a5c6

Livewire action completion
https://github.com/yaegassy/coc-laravel/assets/188642/3ff0072c-2fae-40ae-a5c4-074b2c2678b9

Livewire event completion
https://github.com/yaegassy/coc-laravel/assets/188642/e85c8aab-cb3e-4271-86b1-9312c7af2007

Livewire directive completion
https://github.com/yaegassy/coc-laravel/assets/188642/596dee19-310e-4392-8171-490a1808dfd8

Livewire property completion
https://github.com/yaegassy/coc-laravel/assets/188642/b3999196-4757-4043-925f-3f3c9d5c76b8

PHP Class Completion

Contents of completion items

Standard class obtained by parsing phpstorm-stubs. By default standard, date, and Core are parsed. Can be changed by setting laravel.stubs.useStubs.
Class obtained by parsing the vendor directory. This includes class, interface, trait, and enum, You can also exclude a specific vendor in the laravel.project.excludeVendors settings.

https://github.com/yaegassy/coc-laravel/assets/188642/91f5fc92-9fcd-48fc-a88c-535a06535bca

PHP Scope Resolution completion
https://github.com/yaegassy/coc-laravel/assets/188642/6f8994eb-647a-465e-8f4c-1d3c42d07ad2

PHP Variable completion
this completion feature of variables or objects defined in inline-php region (<?php ... ?>) and php-directive region (@php ... @endphp) in the blade file. Variables defined above the current cursor position are targeted.
The details that are displayed when a completion item is selected are displayed using PHP reflection in the case of an object to identify what kind of object it is.
As a side note, there are other php-related regions in the blade file besides inline-php and php-directive, but I thought that I wouldn't define variables there, so I don't support them at the moment. The processing also needs a bit of work.
https://github.com/yaegassy/coc-laravel/assets/188642/daaa98a8-da33-4808-a3da-243b4d9ffeec

PHP Object Member completion
https://github.com/yaegassy/coc-laravel/assets/188642/156c20dd-e822-4d74-8171-1fc33906bca0

Eloquent Model Field completion
https://github.com/yaegassy/coc-laravel/assets/188642/ac007274-c5fd-4448-87c7-806a9042971c

View Reference Variable completion
This feature completes the variables specified in the view function of the php file with the blade file. Variables passed in with method can also be completed.
Unfortunately, the use of the compact function cannot be completed at this time.
https://github.com/yaegassy/coc-laravel/assets/188642/19771bed-3efa-485d-bc46-733679bd84f7


Export EC public key failed when curve is SM2

OS: Fedora 36 x86_64
Version: OpenSSL 3.1.0-dev  (Library: OpenSSL 3.1.0-dev ), commit_id: c267588fd400593c090ebb24643c2be5158bfbcc
    $ util/wrap.pl ./apps/openssl ec -in ../test/SM2.pem -pubout
read EC key
unable to enable public key encoding
4097499DAE7F0000:error:030000A3:digital envelope routines:EVP_PKEY_set_params:invalid key:crypto/evp/p_lib.c:2342:

I have tried other supported curve, and it works well
    $ util/wrap.pl ./apps/openssl ec -in ../test/prime256v1.pem -pubout
read EC key
writing EC key
-----BEGIN PUBLIC KEY-----
***
-----END PUBLIC KEY-----
    ```

Could you please check that Fedora OpenSSL version is not built with no-sm2? I think sm2 is not supported.

I build it from source code from github, not fedora buildin openssl
and genpkey or sign with SM2 is normal
$ ./util/wrap.pl apps/openssl genpkey -algorithm EC -pkeyopt 'ec_paramgen_curve:SM2'
-----BEGIN PRIVATE KEY-----
MIGHAgEAMBMGByqGSM49AgEGCCqBHM9VAYItBG0wawIBAQQgFv+e2Cz/7OdbyYvg
7QZcOBskWXWXQpE0eOgZRw7U5lShRANCAATDgbHsY6rJc1ojwOrmz4n39M3lTKlA
lzujBugqkttsULNOWqDftS4L4XBmw1KHEXxWleRyHBDr8ajXWrK7MPAV
-----END PRIVATE KEY-----
$ ./util/wrap.pl apps/openssl dgst -sign ../test/SM2.pem -hex ../cert/file
EC-SM3(../cert/file)= 304402204e350566ad77a897788ae1fe387310ffcc6a092b75d74198bb335a9dab180b3d02200a23c7e64c7f450372b1bd3c6bbb521802501b7c7b6f1b8ef83b512fdc182bc5

This is not platform specific..
This works just fine though.
./apps/openssl pkey -in SM2.pem -pubout


[flutter_tools][plugins] generated registerWith guards against re-regitration

This is for handling the case where the PluginRegistry was kept alive by a background service, and is now being used again for a new foreground activity.

How would the new foreground activity communicate with an already registered plugin?

The PluginRegistry is owned by the FlutterNativeView here https://github.com/flutter/engine/blob/master/shell/platform/android/io/flutter/view/FlutterNativeView.java#L24. FlutterNativeViews are recycled when an app overrides createFlutterNativeView in its MainActivity. See: https://github.com/flutter/plugins/blob/master/packages/android_alarm_manager/example/android/app/src/main/java/io/flutter/androidalarmmanagerexample/MainActivity.java

Avoiding calling GeneratedPluginRegistrant would require doing something like:
public class MainActivity extends FlutterActivity {
  ...
  @Override
  protected void onCreate(Bundle savedInstanceState) {
    super.onCreate(savedInstanceState);
    if (super.freshlyCreatedPluginRegistry()) {
      GeneratedPluginRegistrant.registerWith(this);
    }
  }
  ...
}

which seemed awkward to me. Instead, this change makes GeneratedPluginRegistrant.registerWith() idempotent w.r.t. the same PluginRegistry.

OK. But we should be able to avoid asking basically the same question for each plugin. What about generating
public final class GeneratedPluginRegistrant {
  public static void registerWith(PluginRegistry registry) {
    if (alreadyRegisteredWith(registry)) {
      return;
    }
    // as before
  }

  private static boolean alreadyRegisteredWith(PluginRegistry registry) {
    final String key = GeneratedPluginRegistrant.class.getCanonicalName();
    if (registry.hasPlugin(key)) {
      return true;
    }
    registry.registrarFor(key);
    return false;
  }
}

Alternatively add that state to PluginRegistry along the lines of:
  private boolean pluginsHaveBeenRegistered = false;
  public boolean shouldRegisterAgain() {
    if (!pluginsHaveBeenRegistered) {
      pluginsHaveBeenRegistered = true;
      return false;
    }
    return true;
  }

Thanks. Went with @mravn-google's suggestion.


Recreate Benchmarks on A100

Hey all,
Very interesting work! I am trying to recreate some of the results you have in table 1.
Do you happen to have the script + audio used on hand? I am having trouble matching it on my machine:
from whisper_jax import FlaxWhisperPipline
import jax.numpy as jnp
import time
import librosa

SAMPLING_RATE = 16000
audio, sr = librosa.load('test_audio.mp3', sr=SAMPLING_RATE)

# instantiate pipeline in bfloat16
pipeline = FlaxWhisperPipline("openai/whisper-large-v2", dtype=jnp.float16, batch_size=32)

print("Warmup compiling forward pass")
text = pipeline(audio)

start_time = time.time()
for i in range(10):
    print(f"Go iter {i}")
    text = pipeline(audio)
end_time = time.time()
print(text)
print(f"Took {end_time - start_time} s")

# Took<PHONE_NUMBER>9210815 s

test_audio.mp3 is a 13 min ted talk clip. I get about 30s per transcription iteration with this. Could be a bunch of things, but just want to know if this code would expect to give the benchmark results under optimal config.

This looks more or less correct! The benchmarks we ran were from a bunch of YouTube videos (I can give you the URLs), and transcription time is somewhat dependent on audio file. This slower transcription time could be because Whisper is getting caught in a hallucination in one of the batches, causing it to generate till it hits max length (448 tokens).
You could check whether the text has repetitions, or try instantiating the pipeline with a lower max length (we set it to 128 and got complete transcriptions):
# instantiate pipeline in bfloat16
pipeline = FlaxWhisperPipline("openai/whisper-large-v2", dtype=jnp.float16, batch_size=32, max_length=128)

reproduced the hallucination with this audio file on Huggingface

it's impressively fast
but 16G memory seems not enough for statement jax = FlaxWhisperPipline("openai/whisper-large-v2", dtype=jnp.bfloat16, batch_size=16), how much memory does it require to instantiate the pipeline?

Also worth making sure your audio is already at 16kHz so that we don't resample in the Flax Whisper pipeline (which can be lengthy for long audio files)

The absolute transcription time is somewhat dependent on audio sample - since it's proportional to number of tokens generated, it'll depend on speaking rate, propensity to hallucinate, speech:silence ratio, etc. Since we what we really care about is the relative time between systems (rather than necessarily the absolute ones), it would be cool to benchmark with the same audio file using OpenAI's Whisper and Transformer's Whisper on GPU to see what we're aiming for

One more question to do some fair comparisons across libraries. If I am reading the codebase correctly, this is doing a greedy search (e.g. beam_size=1).

Correct!

Finally, it might be good to just have the audio you used to benchmark. @sanchit-gandhi can you direct me to the youtube video?

Hi,
On CPU only system (no TPU/GPU), the following deteriorates the overall performance. For a <10 min audio, it consumes almost 25% more time.

SAMPLING_RATE = 16000
audio, sr = librosa.load('test_audio.mp3', sr=SAMPLING_RATE)

I guess there are quite a few parameters to be tuned to achieve good/best performance, and improper tuning can worsen the situation 🤔


CI should work for scheduled runs

Currently, scheduled workflows are skipped.
I don't know any drawbacks of the change proposed in this PR, but if there are any we can either use the same pattern as in ParquetSharp (https://github.com/G-Research/ParquetSharp/blob/master/.github/workflows/ci.yml#L24).

I think I'd be more inclined to go with the other approach (adding github.event_name == 'schedule' to the conditions) to avoid losing the ability to have the CI workflow run when pushing to a feature branch, before a PR is opened.

I think I'd be more inclined to go with the other approach (adding github.event_name == 'schedule' to the conditions) to avoid losing the ability to have the CI workflow run when pushing to a feature branch, before a PR is opened.

All right, makes sense


UTF8 symbols oversized in module/text, but not in module/script

Describe the issue
UTF8 symbols load, but font size is too large and I see no way of decreasing it. There are no errors in the logs, even with -l info enabled. It shouldn't be a font issue, as the symbols appear. They're just oversized. There is also a default bg and fg set which I cannot seem to override.
I also included my script block for spotify because I also use utf8 symbols here as prefix for the song title. And it's working fine here. If you want to test the tool for some reason: pip install spotify-cli-linux
To Reproduce
A minimal but complete config with which the problem occurs:
[colors]
background = #030303
background-alt = #444
foreground = #dfdfdf
foreground-alt = #555
primary = #ffb52a
secondary = #e60053
alert = #bd2c40

[bar/example]
monitor = ${env:MONITOR:HDMI1}
width = 100%
height = 27
fixed-center = false
bottom = true

background = ${colors.background}
foreground = ${colors.foreground}

line-size = 3
line-color = #f00

border-size = 0
border-color = #00000000

font-0 = fixed:pixelsize=10;1
font-1 = unifont:fontformat=truetype:size=8:antialias=false;0
font-2 = Noto Color Emoji:fontformat=truetype:size=3:antialias=false;0

modules-center = spotify-status spotify-prev spotify-playpause spotify-next

override-redirect = true

cursor-click = pointer
cursor-scroll = ns-resize

[module/spotify-status]
type = custom/script
exec = spotifycli --status

format = <label>
label = %output%

interval = 5

scroll-down = amixer set Master 5%-
scroll-up = amixer set Master 5%+

format-prefix = "♫ "
format-prefix-foreground = ${colors.foreground}

[module/spotify-prev]
type = custom/text

content = ⏮
content-padding = 1
click-left = spotifycli --prev

content-background = ${colors.background}
content-foreground = ${colors.foreground}

[module/spotify-playpause]
type = custom/text

content = ⏯
click-left = spotifycli --playpause

content-background = ${colors.background}
content-foreground = ${colors.foreground}

[module/spotify-next]
type = custom/text

content = ⏭
content-padding = 1
click-left = spotifycli --next

content-background = ${colors.background}
content-foreground = ${colors.foreground}

List any other steps needed to reproduce the issue besides starting polybar with the config you posted above.
Polybar Log
Post everything polybar outputs to the terminal when you run it and the issue occurs below
* Loading config: /home/f3bruary/.config/polybar/config
* Environment var ${MONITOR} is undefined, using defined fallback value "HDMI1"
* Loaded monitor HDMI1 (1920x1080+0+0)
* Bar geometry: 1920x27+0+1053; Borders: 0,0,0,0
error: module/xbacklight: Could not get data (err: XCB_NAME (15))
error: Disabling module "xbacklight" (reason: Not supported for "HDMI1")
warn: pulseaudio: using default sink alsa_output.pci-0000_00_1b.0.analog-stereo
* Starting application
* Starting module/powermenu
* Starting module/spotify-status
* Starting module/spotify-prev
* module/spotify-status: Invoking shell command: "spotifycli --status"
* Starting module/spotify-playpause
* Starting module/spotify-next
* Starting module/filesystem
* Starting module/pulseaudio
* Starting module/cpu
* Starting module/wlan
* Starting module/eth
* Starting module/battery
* Starting module/temperature
* Starting module/date
* Entering event loop (thread-id=1)
* Eventqueue worker (thread-id=13)
* Configured DPI = 96x96
* Loaded font "fixed:pixelsize=10" (name=DejaVu Sans, offset=1, file=/usr/share/fonts/TTF/DejaVuSans.ttf)
* Loaded font "unifont:fontformat=truetype:size=8:antialias=false" (name=DejaVu Sans, offset=0, file=/usr/share/fonts/TTF/DejaVuSans.ttf)
* Loaded font "Noto Color Emoji:fontformat=truetype:size=3:antialias=false" (name=Noto Color Emoji, offset=0, file=/usr/share/fonts/noto/NotoColorEmoji.ttf)
* Bar window: 0x7c00002
* Disabling tray manager (reason: missing `tray-position`)
* module/powermenu: Rebuilding cache
* module/spotify-status: Rebuilding cache
* module/spotify-prev: Rebuilding cache
* module/spotify-playpause: Rebuilding cache
* module/spotify-next: Rebuilding cache
* module/filesystem: Rebuilding cache
* module/pulseaudio: Rebuilding cache
* module/cpu: Rebuilding cache
* module/wlan: Rebuilding cache
* module/eth: Rebuilding cache
* module/battery: Rebuilding cache
* module/temperature: Rebuilding cache
* module/date: Rebuilding cache
* Redrawing bar window
* module/spotify-status: Rebuilding cache
* Redrawing bar window
* module/battery: Rebuilding cache
* module/temperature: Rebuilding cache
* Redrawing bar window
* module/cpu: Rebuilding cache
* module/battery: Rebuilding cache
* module/temperature: Rebuilding cache
* Redrawing bar window

Screenshots
If applicable, add screenshots to help explain your problem.

Environment:

WM: XFCE4
Distro: Manjaro 'Micah'
Output of polybar -vvv:

polybar 3.4.3

Features: +alsa +curl +i3 +mpd +network(libnl) +pulseaudio +xkeyboard

X extensions: +randr (+monitors) +composite +xkb +xrm +xcursor

Build type: Release
Compiler: /usr/bin/c++
Compiler flags: -D_FORTIFY_SOURCE=2 -march=x86-64 -mtune=generic -O2 -pipe -fstack-protector-strong -fno-plt -Wall -Wextra -Wpedantic -O3 -DNDEBUG
Linker flags: -Wl,-O1,--sort-common,--as-needed,-z,relro,-z,now

https://github.com/polybar/polybar/wiki/Known-Issues#huge-emojis
For emojis, changing the size doesn't seem to do anything, you need to change the scale property of your emoji font.


Update patches

Issue #, if available:
Description of changes:
By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.

Will be updated separately.


Implement new concurrency limit mechanism for the CloudWatch client

This PR implements a new concurrency mechanism for the CloudWatch client. For this, the client is decoupled of how the concurrency is limited, and two implementations are provided:

a single limit limiter, which is the current implementation
one that keeps one limit per api call

The second one will allow us to take full advantage of the rate limits imposed by AWS into each api.

@cristiangreco what do you think of the latest changes here?


Remove Test Skips

Description
Various unit tests are being skipped for various reasons. We need to reevaluate those being skipped and fix where needed.

/azp run Steeltoe.All


Hooking inline function

Hello,
I want to hook a function that in the C source code it is indeed a function, but when compiled it is inlined by compiler optimizations.
What are my options to hook this function?
Thanks

I know this is old, but this is an easy one to respond to.  You cannot detour an inlined function.  At a simple level, an inlined function is pretty much just copying and pasting the code into where the function is called. Is has no signature that you can hook into.


Not possible to view load of full year

In the LES Showcase buurtbatterij - overzicht ( https://moses.energytransitionmodel.com/testing_grounds/471 ) it is not possible to switch viewing the load from the first week of January to the whole year.
(Sorry Chael, I forgot who I could assign to this, so I assigned you.)

When I first click another week and then whole year it loads the whole year. When I click whole year first nothing changes.

When I select the node MSR4 Buurtbatterij I can select weeks for the load, but it doesn't want to show me the load for a whole year.


Please provide parameters for sebbo2002/ble2mqtt docker

Hello,
Please provide more data how to run docker ble2mqtt. How to change data/log folder.

@orzechszek I don't know what data you are hoping for here, maybe you can be a little more specific. All available environment variables are documented in the readme. There is no data or log folder.


Syndicus building list

Syndici should be able to see their assigned buildings

I'm pretty that this can be done by making the /buildings only return the buildings a syndicus has access to. This way, the current admin building views should work completely without any modification, as the endpoint is the same.


CHAIN_ID env var is wrong when running make test-chunk-prove

I am trying to run make test-chunk-prove but getting this error: CHAIN_ID env var is wrong. chain id in trace 534351, CHAIN_ID 53077
The full trace is:
running 1 test
2023-10-03T13:51:27.882740624+00:00 INFO prover::utils - git version 7ddaf92
2023-10-03T13:51:27.882767635+00:00 INFO prover::utils - short git version 7ddaf92
2023-10-03T13:51:27.882777676+00:00 INFO chunk_tests - Initialized ENV and created output-dir chunk_tests_output_multi_20231003_135127
2023-10-03T13:51:27.882851200+00:00 INFO integration::test_util - using mode "default", testing with "./tests/extra_traces/new.json"
2023-10-03T13:51:27.882903014+00:00 INFO integration::test_util - test cases traces: ["./tests/extra_traces/new.json"]
2023-10-03T13:51:27.886142221+00:00 INFO chunk_tests - Loaded chunk trace
2023-10-03T13:51:27.886170983+00:00 INFO prover::zkevm::circuit::l2_builder - check capacity of block traces, num_block 1, num_tx 1, tx total len 36
test test_chunk_prove_verify ... FAILED

failures:

---- test_chunk_prove_verify stdout ----
thread 'test_chunk_prove_verify' panicked at 'called `Result::unwrap()` on an `Err` value: CHAIN_ID env var is wrong. chain id in trace 534351, CHAIN_ID 53077

Could set export CHAIN_ID=534351 then run make test-chunk-prove.

That fixed it, thank you!


Shaka and iPadOS

Have you read the FAQ and checked for duplicate open issues?
yes
What version of Shaka Player are you using?
latest
Can you reproduce the issue with our latest release version?
yes
Can you reproduce the issue with the latest code from master?
yes
Are you using the demo app or your own custom app?
both
If custom app, can you reproduce the issue using our demo app?
yes
What browser and OS are you using?
iPadOS 14.3
For embedded devices (smart TVs, etc.), what model and firmware version are you using?
What are the manifest and license server URIs?
any
What did you do?
I am very sure, that DASH Playback on iPadOS (13+) worked fine, when iPadOS was released. Nevertheless, currently, any DASH Manifest leads to an Exception in Shaka. I am not sure, if Apple changed something or something in Shaka changed. I admit, its been a while, that I last checked that, but I am absolutely sure (and our Code was built for that), that DASH Content was no Problem with iPadOS 13.
Anyway - as I couldnt make any Content work via DASH on iPadOS, I decided to try HLS, which for sure works fine. But still, I cannot force SHAKA to use MSE for that, it always uses the "native" Implementation.
I know, there is a Setting "useNativeHlsOnSafari", but this does not seem to have an effect. At least, the Video src is still the HLS URL itself and no Blob and getVariantTracks() is still empty.
What did you expect to happen?
I initially expected, that DASH works on iPadOS.
If thats not possible, I would like to use HLS via MSE .
What actually happened?

DASH does not work at all (but maybe thats intended)
HLS always uses native Integration, not EME and ignores "useNativeHlsOnSafari"

What error are you seeing?  Do you have any device logs?  It works fine for me on iOS 14.0.  We'll ignore useNativeHlsOnSafari if the device doesn't have MSE, so it's possible something happened and MSE is detected as not supported.

What error are you seeing?  Do you have any device logs?  It works fine for me on iOS 14.0.  We'll ignore useNativeHlsOnSafari if the device doesn't have MSE, so it's possible something happened and MSE is detected as not supported.

@shaka-bot reopen
Hi there and sorry I did not notice that more early :)
We have this Issue a lot again and all kind of Versions.
First of all - DASH should work on iPadOS 13+, or am I wrong?
At least - visiting the SHAKA Demo Player Page with an iPad only shows HLS Links, no DASH at all.
If I try it anyway with a custom Manifest - SHAKA responds with Media Error (4).
But i am 100% sure, that this worked without any Issues - as iPadOS claims to me macOS since v13, it offers all Possibilities, that the macOS Safari offers - including DASH Support.
Or am I wrong here?
Thanks,
Christoph

And then coming back to native HLS on iPadOS:
I start the Player with this Config:
"{"preferredAudioLanguage":"auto","abr":{"enabled":true,"switchInterval":6},"manifest":{"disableText":true},"streaming":{"smallGapLimit":1,"jumpLargeGaps":true,"ignoreTextStreamFailures":true,"useNativeHlsOnSafari":false}}"
and the Manifest:
https://nq-p01.akamaized.net/5d3a9aac-d32f-48ef-bc83-2f68d8d239c8/1694021_src.ism/Manifest(format=m3u8-cmaf)
and still - the  Object uses this Manifest as src, so we use "native HLS" here. as this is a new iPad with latest iPadOS (14.4), MSE should be available there.

And at the very last - I can confirm this Behavious on various iPads on iPadOS 13,14-14.4 on our Players and Shaka Dev. I cannot see the Usage of MSE anywhere, its always native HLS.
Is there anything else I can provide to figure out why this happens? Or am I missing something here?

You can check window.MediaSource in JavaScript.  This will be present if MSE is supported, otherwise we can't use MSE and only native HLS will be supported.  We can only play DASH content if MSE is available.


Use Python for build scripts

Currently there are 2 different languages used for the build scripts (batch and bash). There are some problems with these languages that Python can solve, for example requiring a script be run from a certain directory for correct behaviour.

I think we have some which generate samples or build files. These are not used often, generally only once or twice when you want to set up a build. The rest is CMake.
Which scripts do you think will benefit the more being ported to python?


ML training data generator

I added a simple notebook to synthetically generate a training dataset for machine learning using Landsat imagery.  This will be used for machine learning examples.

@ebo Thanks!
I'll take a look shortly and I'm looking forward to the other notebooks that will accompany it.


Maths Quiz Game

I would like to contribute to this project by adding a maths quiz game for fun,
please assign this project addition to me @urvashi-code1255 @Vishal-raj-1
I am a GSSOC'21 participant and I am excited to contribute to this project

@urvashi-code1255 I like to work on this issue. Please Assign me

@Saumya-07 You have already assigned two issues so I am assigning this to @balarka135

Thank you for assigning me. I will update you tomorrow about my project status.

@urvashi-code1255 I build the math game already. But after several tries

I am unable to link the image or gif with the Project section on the page. I attached a screenshot for your reference. pls, help me.Thank you


Kernel dies when trying to plot after fitting NN

Any time I train a NN (using tensorflow with keras) and attempt to plot (matplotlib) the loss history of the fit model, the kernel dies. I do not think it is code because running different code from different validated sources (links below) causes the same problem.
Also, it appears to be specific to tensorflow/keras and matplotlib. If I run an sklearn model and then plot it works fine.
example links:
https://github.com/chrisalbon/notes/blob/master/docs/deep_learning/keras/visualize_loss_history.ipynb
https://machinelearningmastery.com/tutorial-first-neural-network-python-keras/
Tried fixes:

Restarting comp
Removing keras and matplotlib
Rolling back matplotlib to a previous version (3.02)
Updating python 3.6 to 3.71
Uninstalling python and anaconda from comp and re-installing 6. Running code in different browser (safari and chrome)

Important
I believe it has something to do with my installation. I sent the notebook and data to someone else with the same exact comp and setup and it worked fine. However, this isn't an isolated incident, as its been reported on stack before.
https://stackoverflow.com/questions/55833399/unable-to-plot-after-keras-fit-called
I've also tried running the py file through the command line to retrieve errors, but nothing happens (no error, no indication that the file is running). Other py files run fine though.
current versions
python - 3.71
matplotlib - 3.0.3
keras - 2.2.4
tensorflow - 1.13.1

@thorrester I just ran the example and I am not getting any error. I suspect the problem is in installation . Can you please clean your environment and reinstall Keras and Tensorflow and see if it works. Thanks!

Seemed to work! Thanks!


Changing requirements.txt to resolve dependency error

for some reason travis pull request check are stuck and I can't merge unless these checks pass. I will close this PR without merging but will bring in these changes separately through a local branch merge.