add Integer type casting when loading yaml file

What type of PR is this?
(REQUIRED)

bug

What this PR does / why we need it:
(REQUIRED)

Latest v2 release (2.24.1) resolved this https://github.com/urfave/cli/issues/1592
But also we cannot load the Uint64 flag because the casting error
The integer from yaml file is unmarshaled to the int about lower than<PHONE_NUMBER>854775807 regardless of the flag type
This PR can accept even the integer that can be casted to the flag type
IsSet()

The IsSet() returns true after loaded from yaml about all the flags except the slice flags
This PR can return true about slice flag type also

Which issue(s) this PR fixes:
(REQUIRED)

#1592

Special notes for your reviewer:
(fill-in or delete this section)

Testing
(fill-in or delete this section)

Release Notes
(REQUIRED)

@urfave/cli I am not watching it closely, but is there an API to type cast and report errors for just any type? The specificity of int64 sound like something that should not come out of the box for generic command line handling library.

@kjeom Can you add some tests in altsrc for this condition ?

@dearchap please finish your review


support for cert with DNS SANs in permissive mtls mode

This PR implements the proposal discussed in Connecting non Istio clients in Permissive mTLS mode
It adds an additional filter chain with filter chain match set to transport_protocol: tls in order to allow connections from non Istio mTLS clients to be terminated at the Istio Proxy sidecar instead of being handled by the application container
@costinm @incfly Please help review
/cc @sureshvis

@mdhume: PR needs rebase.

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A question on taxonomy of Arvicola cantianus. Is it valid or is it Arvicola terrestris cantianus?

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Show details
Write a comment…
indre.zliobaite Nov 20, 2023 3:37 PM
Lars curatorial: Arvicola cantianus is the version we go with, merge the subspecies in.
1
Reply • Delete
indre.zliobaite Dec 9, 2022 11:33 AM
@larsvandenhoekostende1 Any news on this? Is Tesakov active these days?
Reply • Delete
indre.zliobaite Oct 28, 2021 1:32 PM
what is a chronospecies in this case?
Reply • Delete
hispanomys Jun 25, 2021 4:45 PM
Agree
Reply • Delete
Lars van den Hoek Ostende Jun 17, 2021 1:22 PM
But cantianus should be recognized as a separate chronospecies (which was the original question
Reply • Delete
hispanomys Jun 17, 2021 12:38 PM
Ok, so better leave it as it is for the moment
Reply • Delete
Lars van den Hoek Ostende Jun 17, 2021 10:58 AM
terrestris was recognized as a more northern species. I don't think the synonymy (also recognized in Mammals species of the World) has reached the palaeontological world yet.
Reply • Delete
hispanomys Jun 17, 2021 9:24 AM
Lars you know arvicolids are not my favourite rodents and I have never worked with them. Currently most zoologists recognize Arvicola terrestris as a junior synonym of Arvicola amphibius, so there is no more 'terrestris' in the extant faunas. I am unaware if this has been applied to fossils as well. Perhaps Alexey should check.
Ah! My reference for the synonymy is the nice volume 'Handbook of Mammals of the World. Vol. 7', but I did not make a research to find out who synonymized these two species.
Reply • Delete
Lars van den Hoek Ostende Sep 25, 2020 11:00 AM
Nowadays the tendency is to make cantianus a species of its own. Its validity has been challenged and mosbachensis is actually the same species. We need a comment of Alexey Tesakov on this.


Copies of extensions after update - no deleting previous extension

I noticed that in my catlog .vscode\extensions exist many versions after update, eg.
ms-python.python-2018.3.1
ms-python.python-2018.4.0
ms-python.python-2018.5.0

VSCode Version: 1.24.0  / from .zip

OS Version:W7 x64 SP1

Steps to Reproduce:

Just do some update of extension as new version
Run extension manager, update to new version

Is this normal?
Why update not deleting previous?

Maybe we need some list of instaled plugins. Not only dir /p

@ManPython We do the extensions clean up during the start up of VS Code. So restarting the VS Code will remove the outdated extensions.


chore: update running-locally.md - corrects protoc install command

According to the doc which is currently linked in - one is to install protoc via brew install protobuf, and not via brew install protoc.
Checklist:

[ ] Either (a) I've created an enhancement proposal and discussed it with the community, (b) this is a bug fix, or (c) this is a chore.
[ ] The title of the PR is (a) conventional, (b) states what changed, and (c) suffixes the related issues number. E.g. "fix(controller): Updates such and such. Fixes #1234".
[ ] I've signed the CLA.
[ ] I have written unit and/or e2e tests for my change. PRs without these are unlikely to be merged.
[ ] My builds are green. Try syncing with master if they are not.
[ ] My organization is added to USERS.md.

 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.

/review @alexec


regression: akka-http is in a separate repository now

as of https://github.com/akka/akka/pull/21690
for now I will freeze at an earlier commit

wip PR https://github.com/scala/community-builds/pull/371


Automated cherry pick of #4141: huawei sync instance offset bugfix

Cherry pick of #4141 on release/2.12.
#4141: huawei sync instance offset bugfix

Codecov Report

:exclamation: No coverage uploaded for pull request base (release/2.12@651ded2). Click here to learn what that means.
The diff coverage is n/a.

@@              Coverage Diff               @@
##             release/2.12   #4144   +/-   ##
==============================================
  Coverage                ?   6.88%
==============================================
  Files                   ?     501
  Lines                   ?   84784
  Branches                ?       0
==============================================
  Hits                    ?    5834
  Misses                  ?   78456
  Partials                ?     494

Flag
Coverage Δ

#aFlag
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/lgtm

/approve


Add ETL pipeline blog post

This PR adds a new blog post about the new ETL pipeline, table and view versioning.
These changes can be previewed on my fork:
https://critzo.github.io/m-lab.github.io/blog/etl_pipeline_new_bqtables/
Pre-merge note: this PR should not be merged into master until the tables and views have been renamed by @gfr10598 or other team member.
@georgiamoon PTAL?

This change is

@gfr10598 Requested your review on this so you can give a last look at the content for accuracy, as well as to approve once the tables and views have been named/renamed/created. Thanks!

Review status: 0 of 3 files reviewed at latest revision, all discussions resolved.

Comments from Reviewable

@gfr10598 A condition of publishing this post is that the tables and views are created/named as expressed in the post (and in the list below). Could you comment on this PR once those are published? Thanks.

measurement-lab.legacy.ndt (data ~ 2015-01-01 - 2017-05-10)
measurement-lab.legacy.ndt_pre2015 (data ~ 2009-02-18 - 2014-12-31)
measurement-lab.public.ndt_v3.1 (data ~ 2017-05-01 - present)
All NDT data views:

ndt_all_v3.1 (data ~ 2009-02-18 - present)
ndt_all_current (data ~ 2009-02-18 - present)
ndt_all_legacysql_v3.1 (data ~ 2009-02-18 - present)

Separate views for NDT download and upload tests:

ndt_downloads_v3.1 (data ~ 2009-02-18 - present)
ndt_uploads_v3.1 (data ~ 2009-02-18 - present)

measurement-lab.public.traceroute_v3.1 (data ~ 2017-09-08 - present)
measurement-lab.public.sidestream_v3.1 (data ~ 2017-09-08 - present)
measurement-lab.public.npad_v3.1 (data ~ 2009-02-18 - present)

Closing this PR since work on the new tables/views is still not done and the post will need to be updated more once things are finalized.


Test coverage for 'BigBedToBed'

At least the pure parts of BigBedToBed should be covered. This includes:
RTreeOffset
RTreeInterval

We can then use example1.bb to test:
RTreeIndex#findOverlappingBlocks
RTreeIndex#findOverlaps
BPlusTree#traverse
BPlusTree#find

Partially done in de48c8e1af92d39bd4cc37aed4163f6c85ff59ae.


High CPU usage when a specific log appear

error-2023-01-03031327Z-82e00bfb-6139-4f2b-959d-3ac743d40669.zip
Our server facing high CPU usage(maybe infinite loop) when a specific log appear.
elmah/api/new-errors?id will pending and never end.
just unzip and put that xml to log folder will reproduce the problem.
elmahcore version : v2.1.2

Also running into this; only a server reboot seems to fix it.


Nazareth report card

ask firstname and lastname in separate steps, and save in separate fields in 3P
store all personal data in userdata in every step of the report card flow (so also in the rat/cat sub flows) such that they only have to type it once (firstname/lastname/phone number/address).

related issue https://github.com/our-city-app/plugin-3P-integration/issues/3


Added => Isomorphic.js

Assigned Issue Number ?
#1682
Location of the file(s) ?
Algorithms/String-Algorithm/Isomorphic.js
Checklist

[ YES] I've followed the contributing guidelines
[ YES] The content added isn't directly copied from any sources like gfg, tutorialpoint, etc.
[ NO] Input has been taken dynamically.
[ YES] I've referred the correct issue number.
[ YES] Comments have been added
[ YES] I've  synced-up my forked repo.
[ YES] Ain't pushing from the main branch.

@ahampriyanshu Okay!


Metrics not exported when multiple exporters are present

What version of OpenTelemetry are you using?
    "@opentelemetry/api": "1.7.0",
    "@opentelemetry/auto-instrumentations-node": "0.40.2",
    "@opentelemetry/exporter-metrics-otlp-grpc": "0.46.0",
    "@opentelemetry/exporter-metrics-otlp-proto": "0.46.0",
    "@opentelemetry/exporter-prometheus": "0.47.0",
    "@opentelemetry/host-metrics": "0.34.1",
    "@opentelemetry/sdk-node": "0.46.0",

What version of Node are you using?
v21.5.0
What did you do?
My use case is that the instrumentation shall use two separate exporters to export to two different endpoints. However, the data only gets exported via the first configured exporter. The second exporter receives an empty list of scope metrics in the export function.
Here is a sample application that reproduces the issue:
monitoring.js:
const { HostMetrics } = require('@opentelemetry/host-metrics');
const { PrometheusExporter } = require('@opentelemetry/exporter-prometheus');
const { NodeSDK } = require("@opentelemetry/sdk-node")
const { PeriodicExportingMetricReader, ConsoleMetricExporter } = require("@opentelemetry/sdk-metrics");
const { metrics } = require('@opentelemetry/api');

const exporter = new PrometheusExporter(
  {
    startServer: true
  }, () => {
    console.log('prometheus scrape endpoint: http://localhost:9464/metrics')
  }
);

const sdk = new NodeSDK({
    metricReader: exporter
});

sdk.start();

const hostMetrics = new HostMetrics({ name: 'example-host-metrics' });
hostMetrics.start();

const periodicReader = new PeriodicExportingMetricReader({
    exportIntervalMillis: 5000,
    exporter: new ConsoleMetricExporter() // this will never print any of the host metrics
});

metrics.getMeterProvider().addMetricReader(periodicReader) // expecting this to be the one global meter provider

app.js:
const express = require('express')
const app = express()

app.get('/', function (req, res) {
  res.send('Hello World')
})

app.listen(3000)

start via: node -r ./monitoring.js app.js
What did you expect to see?
Metrics being exported to two different endpoints via two different exporters.
What did you see instead?
Only the first exporter receiving a list of scope metrics while the second one receives an empty list. Thus, nothing gets exported via the second exporter.
Additional context

This was actually never intended to be used in that way and it's a problem with how we designed the Metrics SDK (see https://github.com/open-telemetry/opentelemetry-js/issues/4112#issuecomment-1705416081) as it actually looks like this could work. To work around this, we could add a feature the @opentelemetry/sdk-node so that multiple readers can be added on SDK creation.
Also note that this is actually getting the API type of the MeterProvider which does not advertise having such a method.

Is there any workaround available for the time being?

A workaround may be to call addMetricReader() before creating any instruments (in the example above, do something like this):
const { HostMetrics } = require('@opentelemetry/host-metrics');
const { PrometheusExporter } = require('@opentelemetry/exporter-prometheus');
const { NodeSDK } = require("@opentelemetry/sdk-node")
const { PeriodicExportingMetricReader, ConsoleMetricExporter } = require("@opentelemetry/sdk-metrics");
const { metrics } = require('@opentelemetry/api');

const exporter = new PrometheusExporter(
  {
    startServer: true
  }, () => {
    console.log('prometheus scrape endpoint: http://localhost:9464/metrics')
  }
);

const sdk = new NodeSDK({
    metricReader: exporter
});

sdk.start();

// Add metric reader before using host metrics
const periodicReader = new PeriodicExportingMetricReader({
    exportIntervalMillis: 5000,
    exporter: new ConsoleMetricExporter() // this will never print any of the host metrics
});

metrics.getMeterProvider().addMetricReader(periodicReader) // expecting this to be the one global meter provider

// Start up host metrics after registering the MetricReader
const hostMetrics = new HostMetrics({ name: 'example-host-metrics' });
hostMetrics.start();

this would cause the instruments in HostMetrics to be created AFTER registering the MetricReader.


Fix Loss Function to Improve Model Convergence for AutoEncoder

Description
This PR addresses an issue in the dfencoder model related to its convergence behavior. Previously, the model exhibited difficulty in converging when trained exclusively with numerical features.
This PR fixes the way different loss types are combined in the model's loss function to ensure that backpropagation works correctly.
Note: This may alter the exact values resulting from calling fit() on the model. Before, categorical features were weighted much higher than binary or numerical categories (all numerical features shared a combined weight of 1, all binaries features shared a combined weight of 1, and each categorical feature had a weight of 1). Now all features are weighted equally which may impact the trained weights.
Closes #1455

/ok to test

/merge


Extend the set of possible UI values for diver profile in order to reach the model limits

In particular height, weight & age

Done in https://github.com/wildbits/lead/commit/21b18b76bd8f3a8d23f89a4be74ee8a862d238ed


Better solved the dropout problem on the latent space to still apply …

…dropout to further layers

Codecov Report

Merging #194 into master will increase coverage by 0.04%.
The diff coverage is 100%.

@@            Coverage Diff             @@
##           master     #194      +/-   ##
==========================================
+ Coverage   89.06%   89.11%   +0.04%
==========================================
  Files          30       30
  Lines        2186     2195       +9
==========================================
+ Hits         1947     1956       +9
  Misses        239      239

Impacted Files
Coverage Δ

scvi/models/vae.py
86.41% <100%> (ø)
:arrow_up:

scvi/models/modules.py
100% <100%> (ø)
:arrow_up:

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Codecov Report

Merging #194 into master will increase coverage by 0.04%.
The diff coverage is 100%.

@@            Coverage Diff             @@
##           master     #194      +/-   ##
==========================================
+ Coverage   89.06%   89.11%   +0.04%
==========================================
  Files          30       30
  Lines        2186     2195       +9
==========================================
+ Hits         1947     1956       +9
  Misses        239      239

Impacted Files
Coverage Δ

scvi/models/vae.py
86.41% <100%> (ø)
:arrow_up:

scvi/models/modules.py
100% <100%> (ø)
:arrow_up:

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Closed until we figure out the source of the numerical unstability


Fail to deal with external  schemata

Hallo,
We have faced the following problem during the validation of some json files:
The Validation of the  CVE-2018-0171-modified.json file  with  csaf_json_schema.json schema throws an Error:
/vulnerabilities/0/scores/0/cvss_v3: did not match any of the specified OneOf schemas  and thus this valid document is classified as invalid.
Validator confirms the validity of this file against this schema also.
It seems that something goes wrong when processing oneOf  on #ref external schemata.
Tested with qri-io/jsonschema v0.2.1 und go v1.17.1

Minimizing the linked schema and json file in the last comment by removing some attributes and adjusting the usage example to use these minimized files like following:

import (
	"context"
	"encoding/json"
	"fmt"
	"github.com/qri-io/jsonschema"
)

func main() {
ctx := context.Background()

var schemaData = []byte(`{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "$id": "https://docs.oasis-open.org/csaf/csaf/v2.0/csaf_json_schema.json",
  "title": "Common Security Advisory Framework",
  "description": "Representation of security advisory information as a JSON document.",
  "type": "object",
  "properties": {
    "scores": {
      "title": "List of scores",
      "description": "contains score objects for the current vulnerability.",
      "type": "array",
      "minItems": 1,
      "items": {
        "title": "Score",
        "description": "specifies information about (at least one) score of the vulnerability and for which products the given value applies.",
        "type": "object",
        "properties": {
          "cvss_v2": {
            "$ref": "https://www.first.org/cvss/cvss-v2.0.json"
          },
          "cvss_v3": {
            "oneOf": [
              {
                "$ref": "https://www.first.org/cvss/cvss-v3.0.json"
              },
              {
                "$ref": "https://www.first.org/cvss/cvss-v3.1.json"
              }
            ]
          }
        }
      }
    }
  }
}`)

rs := &jsonschema.Schema{}
if err := json.Unmarshal(schemaData, rs); err != nil {
		panic("unmarshal schema: " + err.Error())
	}

var valid = []byte(`{
  "scores": [
    {
      "cvss_v3": {
        "version": "3.0",
        "baseScore": 9.8,
        "baseSeverity": "CRITICAL",
        "vectorString": "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H"
      }
    }
  ]
}`)

errs, err := rs.ValidateBytes(ctx, valid)
if err != nil {
	panic(err)
	}
if len(errs) > 0 {
	fmt.Println(errs[0].Error())
	}
}

Throws the error: /scores/0/cvss_v3: {"baseScore":9.8,"ba... did not match any of the specified OneOf schemas

This excerpt from debug output indicates that the problem is not being able to resolve a ref.
[Ref] Validating
[AddError] Error: failed to resolve schema for ref #/definitions/scoreType
[Schema] Validating
[AddError] Error: schema is nil
[AddSubErrors] Error: failed to resolve schema for ref #/definitions/scoreType
[AddSubErrors] Error: schema is nil

Furthermore, there is a warning earlier in the debug output that leads to the root cause.
[Schema] WARN: 'definitions' is not supported and will be ignored

Validation is failing because the schema being used is written to comply with JSON Schema draft-07 and qri-io/jsonschema primarily targets JSON Schema 2019-09. Specifically, between revisions, the functionality associated with the "definitions" keyword was moved to the new "$defs" keyword. See issue #97 for more discussion.
For this particular case, registering the "definitions" keyword with the "$def" keyword handler before any validation occurs, as shown below, should allow for your provided test case to validate as expected.
jsonschema.RegisterKeyword("definitions", jsonschema.NewDefs)


[terra-progress-bar] A11Y updates

Summary

A11y improvements for progress-bar
Added visually hidden component under progress bar to provider context and status update of progress
Updated test example

Closes #
Deployment Link

https://terra-core-deployed-pr-#.herokuapp.com/
Testing

Additional Details

Thank you for contributing to Terra.
@cerner/terra

Fails

:no_entry_sign:
Please include a CHANGELOG entry for each changed package this PR. Looks like a CHANGELOG is missing for:

terra-core-docs
terra-progress-bar

  Generated by :no_entry_sign: dangerJS against ae781077fe8e88a43e2b2e49496ae61ee312da6a

@saket2403 This test example was updated https://github.com/cerner/terra-core/blob/1369ca1fa31dc917949bcacdac79a2ae76ea3d02/packages/terra-core-docs/src/terra-dev-site/test/progress-bar/ProgressBarDefault.test.jsx to demonstrate use of aria-live for status and context. There are no other visual changes except label.

@saket2403 This test example was updated https://github.com/cerner/terra-core/blob/1369ca1fa31dc917949bcacdac79a2ae76ea3d02/packages/terra-core-docs/src/terra-dev-site/test/progress-bar/ProgressBarDefault.test.jsx to demonstrate use of aria-live for status and context. There are no other visual changes.

On the terra ui site user will not get to see the test page. So update an example under docs

@saket2403 This test example was updated https://github.com/cerner/terra-core/blob/1369ca1fa31dc917949bcacdac79a2ae76ea3d02/packages/terra-core-docs/src/terra-dev-site/test/progress-bar/ProgressBarDefault.test.jsx to demonstrate use of aria-live for status and context. There are no other visual changes.

On the terra ui site user will not get to see the test page. So update an example under docs

Added in https://github.com/cerner/terra-core/pull/3729/commits/939a686a704ec03d5cd822534de2938882ac8a7f

+1 with translation changes

Added translations in https://github.com/cerner/terra-core/pull/3729/commits/275881a93eb1ce6482513517be5401ca6d82fddb


5537 move host and port for groups api inside org metadata api config section

This closes #5537.
@azamorano CR this, please.
@viddo add host and port params to org_metadata_api as you can see in the example if you want organization creation to work as expected :-)

:+1:


[Bug] Android APP Runtime & Initialization failure

🐛 Bug
This Check fails in android apk

MLCChat failed
Stack trace:
org.apache.tvm.Base$TVMError: InternalError: Check failed: (fload_exec.defined()) is false: TVM runtime cannot find vm_load_executable
Stack trace:
File "/Users/workspace/stacks/mlc-llm/cpp/llm_chat.cc", line 161
at org.apache.tvm.Base.checkCall(Base.java:173)
at org.apache.tvm.Function.invoke(Function.java:130)
at ai.mlc.mlcllm.ChatModule.reload(ChatModule.java:43)
at ai.mlc.mlcchat.AppViewModel$ChatState$mainReloadChat$1$2.invoke(AppViewModel.kt:633)
at ai.mlc.mlcchat.AppViewModel$ChatState$mainReloadChat$1$2.invoke(AppViewModel.kt:631)
at ai.mlc.mlcchat.AppViewModel$ChatState.callBackend(AppViewModel.kt:534)
at ai.mlc.mlcchat.AppViewModel$ChatState.mainReloadChat$lambda$3(AppViewModel.kt:631)
at ai.mlc.mlcchat.AppViewModel$ChatState.$r8$lambda$JJKpoRMMpp77FzXKA0o00i8lgRA(Unknown Source:0)
at ai.mlc.mlcchat.AppViewModel$ChatState$$ExternalSyntheticLambda3.run(Unknown Source:8)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:487)
at java.util.concurrent.FutureTask.run(FutureTask.java:264)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:644)
at java.lang.Thread.run(Thread.java:1012)

Error message:
InternalError: Check failed: (fload_exec.defined()) is false: TVM runtime cannot find vm_load_executable
Stack trace:
File "/Users/workspace/stacks/mlc-llm/cpp/llm_chat.cc", line 161
To Reproduce
Steps to reproduce the behavior:

Compile android apk
All the json are pushed to hugging face
Weights (params_.*bin) are pushed using adb

Expected behavior

Environment

Platform (e.g. WebGPU/Vulkan/IOS/Android/CUDA): Android
Operating system (e.g. Ubuntu/Windows/MacOS/...): MacOS
Device (e.g. iPhone 12 Pro, PC+RTX 3090, ...)
How you installed MLC-LLM (conda, source): source
How you installed TVM-Unity (pip, source): source
Python version (e.g. 3.10): 3.9
GPU driver version (if applicable):
CUDA/cuDNN version (if applicable):
TVM Unity Hash Tag (python -c "import tvm; print('\n'.join(f'{k}: {v}' for k, v in tvm.support.libinfo().items()))", applicable if you compile models):
Any other relevant information:

Additional context

@junrushao @tqchen
suspecting tvm unity commit : bd3e8bb9cf33512a9da7af5d6854161131d8a6ac

Hey, I think this error is because the system_lib_prefix field might not be set correctly. Can you share what command you used for compilation? And you mlc-chat-config.json and app-config.json files as well?

Hello @Kartik14 , here is the requested info
Compile commands
python3 /Users/workspace/stacks/mlc-llm/python/mlc_chat/main.py convert_weight models/custom-mistral --quantization q4f16_1 -o dist/custom-mistral-q4f16_1
python3 /Users/workspace/stacks/mlc-llm/python/mlc_chat/main.py gen_config models/custom-mistral --quantization q4f16_1 --conv-template mistral_default -o dist/custom-mistral-q4f16_1 --sliding-window-size 1024 --prefill-chunk-size 128
python3 /Users/workspace/stacks/mlc-llm/python/mlc_chat/main.py compile dist/custom-mistral-q4f16_1/mlc-chat-config.json --device android -o dist/custom-mistral-q4f16_1/custom-mistral-q4f16_1-android.tar
MLC-CHAT-CONFIG
{   "model_type": "mistral",   "quantization": "q4f16_1",   "model_config": {     "hidden_size": 4096,     "intermediate_size": 20000,     "num_attention_heads": 32,     "num_hidden_layers": 16,     "rms_norm_eps": 1e-05,     "vocab_size": 32000,     "position_embedding_base": 10000.0,     "context_window_size": -1,     "num_key_value_heads": 8,     "head_dim": 128,     "sliding_window_size": 1024,     "prefill_chunk_size": 128,     "attention_sink_size": 4,     "tensor_parallel_shards": 1   },   "vocab_size": 32000,   "context_window_size": -1,   "sliding_window_size": 1024,   "prefill_chunk_size": 128,   "attention_sink_size": 4,   "tensor_parallel_shards": 1,   "mean_gen_len": 128,   "max_gen_len": 512,   "shift_fill_factor": 0.3,   "temperature": 0.7,   "repetition_penalty": 1.0,   "top_p": 0.95,   "conv_template": "mistral_default",   "pad_token_id": 2,   "bos_token_id": 1,   "eos_token_id": 2,   "tokenizer_files": [     "tokenizer.model",     "tokenizer.json",     "tokenizer_config.json"   ],   "version": "0.1.0"
APP CONFIG JSON
{   "model_libs": [     "custom-mistral-q4f16_1"   ],   "model_list": [     {       "model_url": "https://huggingface.co/User/custom-mistral-q4f16_1/",       "local_id": "custom-mistral-q4f16_1",       "model_lib_path": "custom-mistral-q4f16_1/custom-mistral-q4f16_1-android.tar",       "model_lib": "custom-mistral-q4f16_1"     }   ] }

You need to replace custom-mistral-q4f16_1 in model_libs and model_lib field with mistral_q4f16_1.
Basically, the model_libs and model_lib fields in app-config.json needs to match the system-lib-prefix argument in mlc-chat compile command which by default is set to <model-type>_<quantization>(from mlc-chat-config.json file)

Do you mean something like this
{
"model_libs": [
"mistral_q4f16_1"
],
"model_list": [
{
"model_url": "https://huggingface.co/User/custom-mistral-q4f16_1/",
"local_id": "custom-mistral-q4f16_1",
"model_lib_path": "custom-mistral-q4f16_1/custom-mistral-q4f16_1-android.tar",
"model_lib": "mistral_q4f16_1"
}
]
}
This is diff flow as compared to earlier, I think because of refactoring.
Does this mean that app tries to identify supported model template using "mistral_q4f16_1"  ?

Yes, It is different from earlier logic. Sorry for the confusion, we are in the midst of switching to a new workflow leading to these issues.

Yes, It is different from earlier logic. Sorry for the confusion, we are in the midst of switching to a new workflow leading to these issues.

Thank you very much. It works with your suggestion.
Where can I see all the default model_lib template names for supported models?
Thank you for your contributions.

You can check this file for different model types.

app-config.json：
{
"model_list": [
{
"model_url": "https://huggingface.co/mlc-ai/minicpm_q4f16_1-MLC/",
"model_lib": "minicpm_q4f16_1",
"estimated_vram_bytes":<PHONE_NUMBER>,
"model_id": "minicpm_q4f16_1"
}
],
"model_lib_path_for_prepare_libs": {
"minicpm_q4f16_1": "prebuilt_lib/minicpm_q4f16_1/MiniCPM-2b-q4f16_1-android.tar"
}
}
mlc-chat-config.json：
{
"model_type": "minicpm",
"quantization": "q4f16_1",
......}
with the same Error message:
InternalError: Check failed: (fload_exec.defined()) is false: TVM runtime cannot find vm_load_executable
Stack trace:
File "/opt/mlc-llm/cpp/llm_chat.cc", line 163
What should I do?


Not able to run ptan.ignite when custom events inherit from enum.Enum

Whenever I use ptan.ignite and call EpisodeFPSHandler().attach(engine), I get a NotImplementedError:
File "../common.py", line 159, in setup_ignite
ptan_ignite.EpisodeFPSHandler().attach(engine)
File "../venv/lib/python3.6/site-packages/ptan/ignite.py", line 80, in attach
engine.add_event_handler(EpisodeEvents.EPISODE_COMPLETED, self)
File "../venv/lib/python3.6/site-packages/ignite/engine/engine.py", line 269, in add_event_handler
if event_name not in self._allowed_events:
File "../venv/lib/python3.6/site-packages/ignite/engine/events.py", line 124, in __eq__
raise NotImplementedError
From what I see, ptan.ignite's custom event classes, EpisodeEvents and PeriodEvents, inherit from enum.Enum and they do get registered to the ignite Engine and they are in the ignite's Engine._allowed_events, however they don't become CallableEventWithFilter objects for some reason. I was able to fix the issue by making the custom event classes inherit from EventEnum in ignite.engine:
from ignite.engine import EventEnum
class EpisodeEvents(EventEnum):
class PeriodEvents(EventEnum):
I don't know why I had the issue, I was wondering if was because of some ignite update or something, but I thought you should know.
Thanks.

I had this same issue and concluded that PTAN is written to work with Ignite v0.3 but the latest Ignite is v0.41.  Downgrading to Ignite 0.3 solved it for me.

Had same issue, used same solution as demkejon001. Unfortunately I wasted time figuring it out for myself instead of checking here.... but it was good practice. Given that ignite is in active development, I didn't want to revert.

I am using new Ignite, it looks custom events should be inherit from EventEnum:
diff --git a/ptan/ignite.py b/ptan/ignite.py
index 65746f8..17eb11d 100644
--- a/ptan/ignite.py
+++ b/ptan/ignite.py
@@ -5,9 +5,9 @@ from typing import Optional
from ignite.engine import Engine, State
from ignite.engine import Events
from ignite.handlers.timing import Timer
+from ignite.engine.events import EventEnum

-class EpisodeEvents(enum.Enum):
+class EpisodeEvents(EventEnum):
EPISODE_COMPLETED = "episode_completed"
BOUND_REWARD_REACHED = "bound_reward_reached"
BEST_REWARD_REACHED = "best_reward_reached"
@@ -103,7 +103,7 @@ class EpisodeFPSHandler:
self._timer.reset()
-class PeriodEvents(enum.Enum):
+class PeriodEvents(EventEnum):
ITERS_10_COMPLETED = "iterations_10_completed"
ITERS_100_COMPLETED = "iterations_100_completed"
ITERS_1000_COMPLETED = "iterations_1000_completed"

Fixed with 0.7 release (which supports torch 1.7)


feat: add exec command args for xlinectl lock command

Please briefly answer these questions:

what problem are you trying to solve? (or if there's no problem, what's the motivation for this change?)
https://github.com/xline-kv/Xline/issues/823

what changes does this pull request make?
Added exec command support to xlinectl lock command. Updated the README with new examples for lock.

are there any non-obvious implications of these changes? (does it break compatibility with previous versions, etc)
No

Additional comments:
I'm not sure how to test the exec command args. I thought of two solutions:

Extend LockRequest or Test Case Representation: Add a way to represent the exec commands that should be executed after the lock is acquired. This could be a new field in the LockRequest struct or a separate structure linked to the test case.
Modify the Test Case: Adjust the test case in macros.rs to include the exec commands as part of the expected outcome.

Sorry for the late response. I really appreciate your interest about Xline and the contribution you've made.
I've reviewd your code logic, it's natural and clear.
However, recently we did a major change about this xlinectl lock command, you can refer to the #820.
In essence, the lock usage is changed from :  client.lock_client().lock(req).await?;
to : let mut xutex = Xutex::new().await?; let xutex_guard = xutex.lock_unsafe().await?
So you may update your repo and make corresponding change, especially the :
pub(crate) async fn execute(client: &mut Client, matches: &ArgMatches) -> Result<()> .
And for the test, we have a validation test in the: Xline/scripts/validation_test.sh, you can add your test case here.
If you have any questions, feel free to ask.

@CrystalAnalyst Thanks for the feedback. I'll close this pull request and create a new PR after pulling the recent changes.


Encoding autoguess - weird case

Testing #23322

Enable autoGuessEncoding
Open QuietLight.tmTheme in the vscode repo
It's guessed to be EUC-JP, apparently because of a ü character on line 6. Other than that, it includes only ASCII characters

I can't make the same thing happen in another file by inserting ü characters so I don't know whether it's a jschardet bug or whether our confidence threshold is too low.

https://github.com/aadsm/jschardet/issues/29


Add make test and other small cleanups

remove some very unused things from the Makefile, and add a make test target

LGTM

LGTM
@SvenDowideit if you're going to do updates for other repositories, you may want to add https://github.com/docker/docker/commit/9552e24af6151eaef07a481a1125059141d01f75 (or a variation thereof)

good idea :)


bugfix for dale-autowrap, wrong name storage_class

With the llvm-3.5 branch of c2ffi (https://github.com/rpav/c2ffi), the attribute is 'storage_class', whereas with later versions, it became 'storage-class'.  It's been updated now to support both key values.


Clusteriing version 3 - using only URls

Additional points: study about n-grams and fingerprinting. how it works to identify candidates.

https://github.com/hhundiwala/hierarchical-clustering/blob/master/Hierarchical Clustering Explanation.ipynb


Scrollable on Tabs component

It is possible to show scrollbar on tabs component when its has overflow? just like table component.
For example, I've use tabs component with many tab lists and the tab is overflowing

Tabs can be vertical and horizontal, when you're on small screen. You should never use horizontal mode, instead vertical.

still overflow when I user orientation="vertical"

Then use something else like docs offer.


Could not determine artifacts for com.github.corouteam:GlideToVectorYou:v2.0.0: Skipped due to earlier error

Keep getting the following error. Using dependency in Kotlin.

same,
https://blog.gradle.org/jcenter-shutdown#:~:text=On February 3 2021%2C JFrog,disruptions to your build pipelines.

@rtusiime if you change the package name to from corouteam to 2coffees1team it should work
When you click on the jitpack link in the readme.md it redirects you to 2coffees1team/GlideToVectorYou not corouteam/GildeToVectorYou even if it exists.

The artifact host has been changed to https://jitpack.io/#2coffees1team/GlideToVectorYou. Replace
com.github.corouteam:GlideToVectorYou:v2.0.0 to com.github.2coffees1team:GlideToVectorYou:v2.0.0

New artefact host still broken :(


add support for spark 2

spark 2 was just released...

Yep, I'll publish an official 2.0.0-compatible release as soon as we do a corresponding release for spark-avro. In the meantime, though, I believe that you should be able to use the 2.0.0-preview1 release of spark-redshift with the official Spark 2.0.0 release (it should be binary-compatible).

I've just released spark-redshift 2.0.0 to Maven Central and Spark Packages: https://github.com/databricks/spark-redshift/releases/tag/v2.0.0


Where to download jar file?

I'm a python guy so i don't really know the way to build jar file. Could you please tell me where i can get jar file.
Thank you very much.

Hi @maimike, we just recently published this to Maven Central. Check this out: https://github.com/spark-redshift-community/spark-redshift/issues/19
(basically add this to your pom)
<dependency>
  <groupId>io.github.spark-redshift-community</groupId>
  <artifactId>spark-redshift_2.11</artifactId>
  <version>4.0.0</version>
</dependency>


[Bug] PBC Gaussian density fitting error

Hi,
I tried to run a KUHF calculation with GDF on NiO (script attached in the end) and found the result unreasonable with the newest version of PySCF (1.7.1, dev branch). The Coulomb energy before the first step is already wrong (hugely negative):
E1 = (-207.04191083733718-5.041242320816222e-15j)  E_coul = (-59690.45792242636-8.909573202319806e-15j)
init E= -60136.8594748064

While running with an older version 1.6a, I got more reasonable initial energy and the final result also looks correct:
E1 = (-207.04205342072396-4.96541211509103e-15j)  E_coul = (48.666098213393646+1.033424591200558e-18j)
init E= -397.73559675008
...
converged SCF energy = -368.770742845341

I also tried to read in the GDF integrals generated from PySCF 1.6a, and run KUHF using PySCF 1.7.1. The result is correct and consistent with PySCF 1.6a. So the problem should happen at the GDF part (?), where PySCF 1.6a drops more auxiliary basis functions than PySCF 1.7.1 due to linear dependency.
Is this error coming from the change of default threshold in GDF or the change of other pieces of code?
Thank you!
Tianyu
from pyscf.pbc import df, scf, gto
from pyscf.pbc.lib import chkfile
import numpy

cell         = gto.Cell()
cell.atom    = '''
Ni     0.000   0.000   0.000
Ni     4.170   4.170   4.170
O      2.085   2.085   2.085
O      6.255   6.255   6.255
'''
cell.basis   = 'gth-dzvp-molopt-sr'
cell.pseudo  = 'gth-pade'
cell.a       = [[4.170,2.085,2.085],[2.085,4.170,2.085],[2.085,2.085,4.170]]
cell.spin    = 0
cell.verbose = 5
cell.max_memory = 50000
cell.build()

gdf = df.GDF(cell, kpts=cell.make_kpts([3,3,3]))
gdf._cderi_to_save = 'gdf_ints_333.h5'
gdf.build()

kmf = scf.KUHF(cell, kpts = cell.make_kpts([3,3,3])).density_fit()
kmf.with_df = gdf
kmf.with_df._cderi = 'gdf_ints_333.h5'
dm = kmf.get_init_guess()

aoind = cell.aoslice_by_atom()
dm[0,:,aoind[0][2]:aoind[0][3], aoind[0][2]:aoind[0][3]] = 0
dm[0,:,aoind[1][2]:aoind[1][3], aoind[1][2]:aoind[1][3]] = 2 * dm[0,:,aoind[1][2]:aoind[1][3], aoind[1][2]:aoind[1][3]]

dm[1,:,aoind[0][2]:aoind[0][3], aoind[0][2]:aoind[0][3]] = dm[1,:,aoind[0][2]:aoind[0][3], aoind[0][2]:aoind[0][3]] * 2
dm[1,:,aoind[1][2]:aoind[1][3], aoind[1][2]:aoind[1][3]] = 0

kmf.chkfile = 'afm_gdf_333.chk'
kmf.kernel(dm)
print('S^2 = %s, 2S+1 = %s' % kmf.spin_square())

I cannot reproduce this error as of the commit 702d304053cfdedca5a5859a01d895b19477da29 in dev branch. The initial Coulomb energy is 48.650381399 .

@zhutianyu1991 Did updating to the latest commit fix this?

I still got the same error even using the commit @sunqm mentioned. Maybe the error is related to my Python packages or MKL?

I can reproduce Tianyu's error. The problem comes from the code that takes into account the k-point symmetry of the Coulomb metric integral, specifically:
`        # The k-point k' which has (k - k') * a = 2n pi. Metric integrals have the
# symmetry S = S
uniq_kptji_ids = kconserve_indices(-kpt)
log.debug1("Symmetry pattern (k - %s)*a= 2n pi", kpt)
log.debug1("    make_kpt for uniq_kptji_ids %s", uniq_kptji_ids)
for uniq_kptji_id in uniq_kptji_ids:
if not done[uniq_kptji_id]:
make_kpt(uniq_kptji_id, cholesky_j2c)
done[uniq_kptji_ids] = True
    # The k-point k' which has (k + k') * a = 2n pi. Metric integrals have the
    # symmetry S = S*
    uniq_kptji_ids = kconserve_indices(kpt)
    log.debug1("Symmetry pattern (k + %s)*a= 2n pi", kpt)
    log.debug1("    make_kpt for %s", uniq_kptji_ids)
    cholesky_j2c = conj_j2c(cholesky_j2c)
    for uniq_kptji_id in uniq_kptji_ids:
        if not done[uniq_kptji_id]:
            make_kpt(uniq_kptji_id, cholesky_j2c)
    done[uniq_kptji_ids] = True`

in pbc/df/df.py.
If I turn off the above code and compute Coulomb metric integral for each k point, the I can get the correct answer. @sunqm may have an idea what the problem is.
Xing

Hi all,
After some test on MnO, I found that the source of the errors is from the reciprocal space grid(mydf.mesh) in computing J2C integral. The real space summation part preserves the both two types of periodic symmetry quite well but the reciprocal part breaks it. Once I increased the mesh, the periodic symmetry in J2c are well preserved(norm difference becomes 1e-16 while default mesh gives 1e-6 ) and gives correct coulomb energy.
I think increasing the default mesh will fix this but since it has some system/basis dependence, adding some warning when periodic symmetry is broken might be useful to the users. @sunqm

@yangcal could you test the system again using the latest commit? I suspect the error in j2c is caused by the inconsistency between the parity symmetry of mesh and parity symmetry in k-points. This problem is handled in the latest commit

Hi Qiming,
The latest commit did fix the issue. MnO calculations now does not crash. However, when I try to increase the mesh from the current default [11,11,11] to [25,25,25], I see the SCF energy differs by almost 1 Hartree. Seems the integrals are not converged with the default mesh.

@yangcal could you test the system again using the latest commit? I suspect the error in j2c is caused by the inconsistency between the parity symmetry of mesh and parity symmetry in k-points. This problem is handled in the latest commit

@sunqm  Can you explain the error measure in aft.estimate_eta_for_ke_cutoff and aft.estimate_ke_cutoff_for_eta? The non-convergence is mostly from the j2c integrals, but these functions does not seem to take any information on the auxiliary basis set.


Custom OPS with registering gradient functions error in eager backprop

System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow): Yes
OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Centos
Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:
TensorFlow installed from (source or binary): PIP
TensorFlow version (use command below): 2.0.0-beta1
Python version: 3.6.9
Bazel version (if compiling from source):
GCC/Compiler version (if compiling from source):
CUDA/cuDNN version: V10.0.130 / V7.0.5
GPU model and memory: NVIDIA TITAN Xp

Describe the current behavior
If I run the code with directly
2019-08-06 11:32:33.687311: E tensorflow/stream_executor/cuda/cuda_driver.cc:1003] failed to synchronize the stop event: CUDA_ERROR_ILLEGAL_ADDRESS: an illegal memory access was encountered
2019-08-06 11:32:33.687356: E tensorflow/stream_executor/gpu/gpu_timer.cc:78] Invalid argument: error recording CUDA event on stream 0x7fce8a062590: CUDA_ERROR_ILLEGAL_ADDRESS: an illegal memory access was encountered
2019-08-06 11:32:33.687558: F ./tensorflow/core/kernels/reduction_gpu_kernels.cu.h:644] Non-OK-status: CudaLaunchKernel( ColumnReduceKernel<IN_T, T*, Op>, grid_dim, block_dim, 0, cu_stream, in, (T*)temp_storage.flat<int8_t>().data(), extent_x, extent_y, op, init) status: Internal: an illegal memory access was encountered
Aborted (core dumped)

If I run the code with cuda-memcheck --binary-patching no python train_simple.py
Traceback (most recent call last):
  File "train_simple.py", line 71, in <module>
    grads = tape.gradient(loss, model.trainable_variables)
  File "/media/disk1/fordata/web_server/kangfu/anaconda3/envs/tensorflow-gpu/lib/python3.6/site-packages/tensorflow/python/eager/backprop.py", line 1002, in gradient
    unconnected_gradients=unconnected_gradients)
  File "/media/disk1/fordata/web_server/kangfu/anaconda3/envs/tensorflow-gpu/lib/python3.6/site-packages/tensorflow/python/eager/imperative_grad.py", line 76, in imperative_grad
    compat.as_str(unconnected_gradients.value))
  File "/media/disk1/fordata/web_server/kangfu/anaconda3/envs/tensorflow-gpu/lib/python3.6/site-packages/tensorflow/python/eager/backprop.py", line 137, in _gradient_function
    return grad_fn(mock_op, *out_grads)
  File "/media/disk4/fordata/web_server/kangfu/HDRNet-TF/hdrnet_ops.py", line 24, in _bilateral_slice_grad
    grid_tensor, guide_tensor, input_tensor, grad, has_offset=has_offset)
  File "<string>", line 355, in bilateral_slice_apply_grad
  File "<string>", line 3, in raise_from
tensorflow.python.framework.errors_impl.InternalError: Failed launch BilateralSliceApplyGradKernel. [Op:BilateralSliceApplyGrad]

Describe the expected behavior
The code should calculate gradient properly without error. The custom ops run correctly in inferring mode, however, it throws bug during model.fit or below:
with tf.GradientTape() as tape:
    output = model(_full_res)
    loss = tf.keras.losses.mse(output, _full_res)
grads = tape.gradient(loss, model.trainable_variables)

Code to reproduce the issue
I define the custom ops like below:
REGISTER_KERNEL_BUILDER(Name("BilateralSlice").Device(DEVICE_GPU), BilateralSliceOp);
REGISTER_KERNEL_BUILDER(Name("BilateralSliceGrad").Device(DEVICE_GPU), BilateralSliceGradOp);
REGISTER_KERNEL_BUILDER(Name("BilateralSliceApply").Device(DEVICE_GPU), BilateralSliceApplyOp);
REGISTER_KERNEL_BUILDER(Name("BilateralSliceApplyGrad").Device(DEVICE_GPU), BilateralSliceApplyGradOp);

It seems like the custom ops not work OK in eager mode
Other info / logs
Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached.

In order to expedite the trouble-shooting process, please provide a code snippet to reproduce the issue reported here. Thanks!

@ravikyram I commit the code used to reproduce the error in https://github.com/MKFMIKU/Tensorflow-Bug-Reproduce.
To get the error, you can:
git clone https://github.com/MKFMIKU/Tensorflow-Bug-Reproduce.git
cd Tensorflow-Bug-Reproduce
make
python run.py

then it outputs:
2019-08-08 17:50:50.689623: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudnn.so.7
2019-08-08 17:50:51.605504: E tensorflow/stream_executor/cuda/cuda_driver.cc:1003] failed to synchronize the stop event: CUDA_ERROR_ILLEGAL_ADDRESS: an illegal memory access was encountered
2019-08-08 17:50:51.605560: E tensorflow/stream_executor/gpu/gpu_timer.cc:78] Invalid argument: error recording CUDA event on stream 0x7fe3505d0550: CUDA_ERROR_ILLEGAL_ADDRESS: an illegal memory access was encountered
2019-08-08 17:50:51.605661: F ./tensorflow/core/kernels/reduction_gpu_kernels.cu.h:605] Non-OK-status: CudaLaunchKernel(ColumnReduceMax16ColumnsKernel<IN_T, T*, Op>, grid_dim, block_dim, 0, cu_stream, in, (T*)temp_storage.flat<int8_t>().data(), extent_x, extent_y, op, init) status: Internal: an illegal memory access was encountered
Aborted (core dumped)

@MKFMIKU
I am trying to reproduce the issue with your instructions.
I am able to run the below two commands:
git clone https://github.com/MKFMIKU/Tensorflow-Bug-Reproduce.git
cd Tensorflow-Bug-Reproduce
but make command is throwing some error

Thanks!

@ravikyram Seems like you don't have nvcc in your environment. The nvidia-cuda-toolkit should be installed before run make.

@MKFMIKU,
Is this still an issue? Could you please upgrade to TensorFlow v2.3 and check if you are still facing the error?

git clone https://github.com/MKFMIKU/Tensorflow-Bug-Reproduce.git
cd Tensorflow-Bug-Reproduce
make

Also while trying to reproduce the issue, on running the make step I am facing an error stating Makefile:28: recipe for target 'build/bilateral_slice.cu.o' failed. Please find the gist of it here. Thanks!

It is solved after upgrade

@MKFMIKU I encounter the same problem and it fails on tf2. How did you solve it?


fix(theme): change the dark theme default background color to transparent

Checklist

[x] npm test passes
[ ] benchmarks are included
[ ] commit message follows commit guidelines
[ ] documents are updated

Description of change

change dark theme default color from '#141414' to 'transparent'.

fix: #6164

Pull Request Test Coverage Report for Build<PHONE_NUMBER>
Details

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage increased (+0.007%) to 86.373%

Totals

Change from base Build<PHONE_NUMBER>:
0.007%

Covered Lines:
10322

Relevant Lines:
11575

💛  - Coveralls

另外，官网主题 demo 中需要增加一行：

document.getElementById('container').style.background = '#141414';

CI好像挂了，我本地检查下啥情况

https://github.com/antvis/component/pull/318/files#diff-85d875b86904ac041094f85658fb11c5bc0ed6624d0967ae038b2edffd3cd522
可能是这里带来的，你本地删除截图，然后重新生成吧


Connecting two metadata tables

Hi, thanks for the insights from this study. I'm wondering whether you have the metadata link between clinical-challenge-study-data.xlsx and the sequencing mutational metadata (which cow, dpi, Ct value, tissue, inoculation route, etc.).

@tungwinxp I've updated the repo to include a spreadsheet that has the information requested (minus inoculation route - though this is in the clinical challenge study data spreadsheet). If you have any questions, please reopen this issue and I can address it.


Write QA checklist

Testing

[ ]  Browser test: IE 9-11, Chrome, Firefox, Safari (current versions)
[ ]  Device testing: iPhone (3.5", 4", 4.7"), Android (multiple), iPad.
[ ]  Test with JS turned off
[ ]  Test with CSS turned off
[ ]  Stress test using Blitz.io
[ ]  PC / old display check

Accessibility

[ ]  WAI-ARIA roles
[ ] Keyboard navigation
[ ] Proper form markup
[ ] Color contrast check
[ ] Image alt tags
[ ] Go through 508 checklist

##Content

[ ] Spell-check and grammar check
[ ] Retina quality assets
[ ] SEO tags
[ ] Check all links
[ ] Warning for old browsers
[ ] 404 error page
[ ] Favicon
[ ] Footer - directs to Bocoup.com

Functionality

[ ] Schema.org semantics?
[ ] Confirm Google Analytics working
[ ] Optimization and Validation

Cleanup CSS

[ ] Delete unused files
[ ] Consolidate CSS and JS requests
[ ] Lint JS
[ ] Lint CSS
[ ] Validate HTML
[ ] Optimize images

looks good @susanjrobertson @pamela-drouin ?

Looks good!
On Wed, Sep 7, 2016 at 8:53 AM, iamjessklein<EMAIL_ADDRESS>wrote:

looks good @susanjrobertson https://github.com/susanjrobertson
@pamela-drouin https://github.com/pamela-drouin ?
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Looks good and I'll be working on test over the next few days.

Great closing this issue.


Dark mode functionality

Added CSS to make the website compatible with dark mode.  Button size and some text font size adjusted to be responsive to the layout.

Merged PR to enable dark mode functionality.


Phone number validation is still broken

Phone numbers of length less than 10 is being accepted.
The front end validation ensures that the text box accepts only digits 0-9 (as well as + - and . )
The phone field in the models have max_length = 10, so it addresses the concern of the upper limit.
The problem can be fixed by adding a RegexValidator on the phone.CharField. The regex can be ^[0-9]{10}$
I've tried this and it works. However, in the case of the request page, when regex validation fails on the backend, the "Allow Location - നിങ്ങളുടെ സ്ഥലം കൊടുക്കുക" help modal pops up again (because the user is redirected back to the request page itself). It can be extremely confusing to the user.
Thoughts, anyone?

Working on it with Django Validators.

@clasick Like?


Add queuing system that supports gapless playback

I know we've discussed this, but even a simple single entry queue (next up) would be an acceptable solution, could even just be the same api call.
SAPlayer.shared.startRemoteAudio(withRemoteUrl: remoteUrl, beginMode: .immedatiely)
beginMode is an enum with immediately, next
It's then up to the user application to implement the queue and queue logic.
The existing startRemoteAudio just becomes a wrapper around the new api call.
SAPlayer.shared.startRemoteAudio(withRemoteUrl: remoteUrl {
self.startRemoteAudio(withRemoteUrl: remoteUrl, beginMode: .immediately)
}

@jw1540 made a PR #72 but need to cherry pick out because the PR had many changes in one


Fix up examples in src/schema/README.md to not use outdated schema paths

I also developed a script to catch those no longer valid paths used. I think it is worth adding it on CI

[ ] find where in CI we produce that json dump of the schema, and add there running this script to ensure that all paths in README.md are valid
(maybe elsewhere) decide if we should not choose simpler example or may be make it fuller (give example of secondary dereference)

I found where schema.org is produced -- in RTD, but there in env there is no jq so RTD succeeds but log says
tools/no-bad-schema-paths.sh: line 19: jq: command not found
meta.context.context: not reachable
tools/no-bad-schema-paths.sh: line 19: jq: command not found
objects.columns: not reachable
tools/no-bad-schema-paths.sh: line 19: jq: command not found
objects.common_principles: not reachable
tools/no-bad-schema-paths.sh: line 19: jq: command not found

moreover -- RTD succeeds! so that would not be appropriate place.  we need to do it in another CI

yeay -- it worked, removing TEMP commit:


Support for multi-arch images of keptn components (ARM)

Is your feature request related to a problem? Please describe.
Currently, keptn docker images are not built for multi-arch support.
Describe the solution you'd like
Add arm64 and amd64 support for the docker images using docker buildx. Currently, amd64 is supported, but not arm64
Describe alternatives you've considered
A clear and concise description of any alternative solutions or features you've considered.
Additional context
Add any other context or screenshots about the feature request here.

cc: @jetzlstorfer

I've already looked at this at

https://github.com/keptn/gh-action-build-docker-image/issues/1
and PR https://github.com/keptn/keptn/pull/3055

At this point it's not feasible to build ARM containers/images using docker buildx, as the build process takes multiple times longer using buildx (we are talking several hours instead of 30 minutes).
If we get an ARM/ARM64 based GH Action Runner the story might be different.

If we get an ARM/ARM64 based GH Action Runner the story might be different.

Is it taking the same time after making the pipelines parallel for AMD and ARM?

Due to our mono-repo our CI already consists of many parallel steps (unit tests, building docker images, building CLI for multiple architectures, ...).
Adding parallel steps for Docker Builds will block other steps like unit tests and building the CLI.
In addition, just building images for ARM/ARM64 is not the whole story. Those images also need to be e2e/integration tested, etc...
If the use-case is that someone needs a one-time build, then it's absolutely possible to do that by cloning the repo, checking out the respective branch/tag, and running make build-docker locally.

@christian-kreuzberger-dtx, I thought the ARM support would be good for the community. Currently, I don't have this requirement. You may close this issue if you want. Thanks.

One more way is to use more than one CI tool(circleCI + GitHub workflow) to reduce pipeline time. But this will create an overhead to manage two CI tool.

I thought the ARM support would be good for the community

Long-term, yes. We can leave the issue open, such that people can comment on it or upvote it if they have this requirement.

Hi, any news on this feature ? It could be nice to try Keptn on K3S running on RPi 4

IMO it is a roadmap candidate. Arm is becoming more and more popular server architecture, including the K8s clusters. And also new Apple workstations. Creating preview packaging is relatively easy (we did it in Jenkins), having test automation is more tricky.
IMO a roadmap candidate. Maybe the same for RISC-V

I managed to get a PoC working in this PR here: https://github.com/keptn/keptn/pull/7365

any news on this feature ?

do you think it is possible to have this feature for https://github.com/keptn/keptn/milestone/59

Hi @nlamirault !
We can't provide an official version of Keptn with ARM support because not all of our dependencies are supported on ARM.
We use Bitnami's MongoDB Helm chart as a database and bitnami does not provide any ARM mongo images.
This is why we don't have ARM support yet in Keptn.

@mowies it's not possible to use the Bitnami Helm chart and change the Docker image to use the official Mongo Docker image ?
https://hub.docker.com/_/mongo

No, unfortunately that's not so easy to do. Bitnami has lots of custom stuff in it's images in addition to their custom chart.

Given the limitation of Bitnami, I will close this issue. Please, reopen it if the situation changes.


Added module Test.Cardano.Ledger.EraBuffet

The module Test.Cardano.Ledger.EraBuffet makes the module
Test.Cardano.Ledger.ShelleyMA.TestEra obsolete, so it has been removed.
The new module Test.Cardano.Ledger.EraBuffet supplies pieces that can
be used to create new Eras or specialize the Shelley, Allegra, and Mary Eras.
The pieces come in 3 flavors 1) Crypto,  2) Era's, 3) Type families.
Several examples are given.

you need to still remove TestEra.hs - otherwise, thanks for the buffet!


Crash when reading a response on filtered / proxied network

Hello there, I'm getting a crash with version 7.8.0 of the Flurry SDK. This was also happening in prior SDK versions as well.
Here's the stack trace:
#0. Crashed: com.apple.main-thread
0  Educreations                   0x17001f130 (Missing)
1  Educreations                   0x10032425c avro_resolved_union_writer_set_branch +<PHONE_NUMBER>
2  Educreations                   0x1002cb908 FlurryAvroread_value +<PHONE_NUMBER>
3  Educreations                   0x1002cb5e8 FlurryAvroread_value +<PHONE_NUMBER>
4  Educreations                   0x1002cb804 FlurryAvroread_value +<PHONE_NUMBER>
5  Educreations                   0x1002cb5e8 FlurryAvroread_value +<PHONE_NUMBER>
6  Educreations                   0x1002cb804 FlurryAvroread_value +<PHONE_NUMBER>
7  Educreations                   0x1002cb804 FlurryAvroread_value +<PHONE_NUMBER>
8  Educreations                   0x10033679c FlurryAvroavro_read_data +<PHONE_NUMBER>
9  Educreations                   0x1002c9a48 -[FlurryPulseResponse parsePulseResponse:] +<PHONE_NUMBER>
10 Educreations                   0x10031b5ac -[FlurryPulseRequest requestSuccessful:withResponse:] +<PHONE_NUMBER>
11 Educreations                   0x10032c29c -[FlurryConnectionDelegate connectionDidFinishLoading:] +<PHONE_NUMBER>
12 CFNetwork                      0x18480176c __65-[NSURLConnectionInternal _withConnectionAndDelegate:onlyActive:]_block_invoke + 80
13 CFNetwork                      0x1848016fc -[NSURLConnectionInternal _withConnectionAndDelegate:onlyActive:] + 200
14 CFNetwork                      0x184801870 -[NSURLConnectionInternal _withActiveConnectionAndDelegate:] + 56
15 CFNetwork                      0x184728788 ___ZN27URLConnectionClient_Classic26_delegate_didFinishLoadingEU13block_pointerFvvE_block_invoke + 96
16 CFNetwork                      0x184726678 ___ZN27URLConnectionClient_Classic18_withDelegateAsyncEPKcU13block_pointerFvP16_CFURLConnectionPK33CFURLConnectionClientCurrent_VMaxE_block_invoke_2 + 108
17 libdispatch.dylib              0x182e4d1c0 _dispatch_client_callout + 16
18 libdispatch.dylib              0x182e58b24 _dispatch_block_invoke_direct + 376
19 CFNetwork                      0x1847dee98 RunloopBlockContext::_invoke_block(void const*, void*) + 36
20 CoreFoundation                 0x183e9d9a8 CFArrayApplyFunction + 68
21 CFNetwork                      0x1847ded7c RunloopBlockContext::perform() + 136
22 CFNetwork                      0x1847e00a4 MultiplexerSource::perform() + 312
23 CFNetwork                      0x1847dfe10 MultiplexerSource::_perform(void*) + 64
24 CoreFoundation                 0x183f72278 __CFRUNLOOP_IS_CALLING_OUT_TO_A_SOURCE0_PERFORM_FUNCTION__ + 24
25 CoreFoundation                 0x183f71bc0 __CFRunLoopDoSources0 + 524
26 CoreFoundation                 0x183f6f7c0 __CFRunLoopRun + 804
27 CoreFoundation                 0x183e9e048 CFRunLoopRunSpecific + 444
28 GraphicsServices               0x185921198 GSEventRunModal + 180
29 UIKit                          0x189e70818 -[UIApplication _run] + 684
30 UIKit                          0x189e6b550 UIApplicationMain + 208
31 Educreations                   0x1001d404c main (main.m:14)
32 libdispatch.dylib              0x182e805b8 (Missing)

Many of our users are on school networks, which often have filters and proxies in place. In one instance of this crash, I know that the response to our own server, has a text/html content type getting returned. That often means the user's connection is proxied through some intermediate service on the network. So I'm guessing that Flurry is also getting back an unexpected text/html response.
I'd love to have this fixed, as this is our biggest crash right now. Otherwise, I'm going to have to remove Flurry from our app.

Thanks @streeter.  Definitely an unusual use case.  I will chat with our SDK folks and see how we will approach this.

Hi @rollinsio, any update on this? I saw that version 7.8.1 was released. Was hoping to see what the changelog was but [https://developer.yahoo.com/flurry/docs/releasenotes/archived-releasenotes/ios/] wasn't updated.

@streeter will look into the change logs getting updated.  I don't believe that your issue has been resolved.  It is proving very challenging to reproduce.  I will touch base with the SDK team again to chat about it.

Hi @rollinsio - I think if your team checks that the content type returned is what they're expecting as a response, you'll be fine. For instance, here is how AFNetworking is validating the response's content type: https://github.com/AFNetworking/AFNetworking/blob/master/AFNetworking/AFURLResponseSerialization.m#L115-L133
That way you aren't trying to process the response with bad data.

HI @rollinsio, just wondering if this has received any attention.

@streeter this is, unfortunately, not something we're going to actively address. We will likely be moving to pinning at some point, which would be in the opposite direction.

Ok, pinning is fine. That wouldn't prevent this issue though. If you've pinned to a particular server, you could still receive an invalid response type. And checking that response type is actually JSON, before parsing that JSON would be a good way to prevent crashes. Say that the flurry servers have an issue, and do not return JSON – I'd think you'd want to ensure the client handles that gracefully.


Automator: update<EMAIL_ADDRESS>in<EMAIL_ADDRESS>

Generated by Automator - 2022-12-08T06:46:14+00:00

@istio-testing: The following test failed, say /retest to rerun all failed tests or /retest-required to rerun all mandatory failed tests:

Test name
Commit
Details
Required
Rerun command

integ-security-multicluster_istio_release-1.16
5a7e6d0c74ccbd1b8f4c1f12d8b99d8394be33b7
link
true
/test integ-security-multicluster

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

/retest


Open URI on new tab

With the new Obsidian version have been introduced the tabs, it would be useful to have an option to open an URI on a new tab

There's already an parameter openmode for this https://vinzent03.github.io/obsidian-advanced-uri/concepts/navigation_parameters#open-mode