Python exception when running buildstream twice in the same command

When I run bst show to show a diff between two projects (e.g. to do diff <(bst show ...) <(bst show ...)) I sometimes get exceptions - the stack trace of one is below.
I was using -C to switch to a different buildstream project, if that makes any difference.
I installed recently in a venv, through pip:
$ pip show buildstream
Name: BuildStream
Version: 2.3.0
Summary: A framework for modelling build pipelines in YAML
Home-page: https://buildstream.build
Author: The Apache Software Foundation
Author-email<EMAIL_ADDRESS>License: Apache License Version 2.0
Location: /home/john/src/project/.venv/lib64/python3.12/site-packages
Requires: Click, grpcio, Jinja2, pluginbase, protobuf, psutil, pyroaring, ruamel.yaml, ruamel.yaml.clib, setuptools, ujson
Required-by:

Traceback (modified only to hide project name):
Traceback (most recent call last):
  File "/home/john/src/project/.venv/bin/bst", line 8, in <module>
    sys.exit(cli())
             ^^^^^
  File "/home/john/src/project/.venv/lib64/python3.12/site-packages/click/core.py", line 1157, in __call__
    return self.main(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/john/src/project/.venv/lib64/python3.12/site-packages/buildstream/_frontend/cli.py", line 272, in override_main
    original_main(self, args=args, prog_name=prog_name, complete_var=None, standalone_mode=standalone_mode, **extra)
  File "/home/john/src/project/.venv/lib64/python3.12/site-packages/click/core.py", line 1078, in main
    rv = self.invoke(ctx)
         ^^^^^^^^^^^^^^^^
  File "/home/john/src/project/.venv/lib64/python3.12/site-packages/click/core.py", line 1688, in invoke
    return _process_result(sub_ctx.command.invoke(sub_ctx))
                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/john/src/project/.venv/lib64/python3.12/site-packages/click/core.py", line 1434, in invoke
    return ctx.invoke(self.callback, **ctx.params)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/john/src/project/.venv/lib64/python3.12/site-packages/click/core.py", line 783, in invoke
    return __callback(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/john/src/project/.venv/lib64/python3.12/site-packages/click/decorators.py", line 45, in new_func
    return f(get_current_context().obj, *args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/john/src/project/.venv/lib64/python3.12/site-packages/buildstream/_frontend/cli.py", line 631, in show
    with app.initialized():
         ^^^^^^^^^^^^^^^^^
  File "/usr/lib64/python3.12/contextlib.py", line 137, in __enter__
    return next(self.gen)
           ^^^^^^^^^^^^^^
  File "/home/john/src/project/.venv/lib64/python3.12/site-packages/buildstream/_frontend/app.py", line 250, in initialized
    self.context.artifactcache.preflight()
    ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/john/src/project/.venv/lib64/python3.12/site-packages/buildstream/_context.py", line 482, in artifactcache
    self._artifactcache = ArtifactCache(self)
                          ^^^^^^^^^^^^^^^^^^^
  File "/home/john/src/project/.venv/lib64/python3.12/site-packages/buildstream/_artifactcache.py", line 36, in __init__
    super().__init__(context)
  File "/home/john/src/project/.venv/lib64/python3.12/site-packages/buildstream/_assetcache.py", line 306, in __init__
    self.cas: CASCache = context.get_cascache()
                         ^^^^^^^^^^^^^^^^^^^^^^
  File "/home/john/src/project/.venv/lib64/python3.12/site-packages/buildstream/_context.py", line 709, in get_cascache
    self._cascache = CASCache(self.cachedir, casd=self.get_casd(), remote_cache=bool(self.remote_cache_spec))
                                                  ^^^^^^^^^^^^^^^
  File "/home/john/src/project/.venv/lib64/python3.12/site-packages/buildstream/_context.py", line 696, in get_casd
    self._casd = CASDProcessManager(
                 ^^^^^^^^^^^^^^^^^^^
  File "/home/john/src/project/.venv/lib64/python3.12/site-packages/buildstream/_cas/casdprocessmanager.py", line 109, in __init__
    self._logfile = self._rotate_and_get_next_logfile()
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/john/src/project/.venv/lib64/python3.12/site-packages/buildstream/_cas/casdprocessmanager.py", line 277, in _rotate_and_get_next_logfile
    os.remove(os.path.join(self._log_dir, logfile_to_delete))
FileNotFoundError: [Errno 2] No such file or directory: '/home/john/.cache/buildstream/logs/_casd/1727856548.523361.log'

diff <(bst show ...) <(bst show ...)
This may be running two buildstream instances in parallel, starting at the same time, which is likely the cause of the error.
buildstream doesn't support having more than one instance at a time, even though it mostly works. But such a race is probably worse.


feat: support LZW compression

The methods of the LZW decoder are based on the pseudo code from the spec:

Codecov Report

Merging #20 into master will increase coverage by 6.48%.
The diff coverage is 93.16%.

@@            Coverage Diff             @@
##           master      #20      +/-   ##
==========================================
+ Coverage   69.94%   76.43%   +6.48%
==========================================
  Files           8       10       +2
  Lines         396      505     +109
  Branches       71       83      +12
==========================================
+ Hits          277      386     +109
  Misses        119      119

Impacted Files
Coverage Δ

src/tiffDecoder.ts
81.63% <75.86%> (+0.48%)
:arrow_up:

src/lzw.ts
98.61% <98.61%> (ø)

src/horizontalDifferencing.ts
100.00% <100.00%> (ø)

src/tiffIfd.ts
52.38% <0.00%> (+4.76%)
:arrow_up:

Continue to review full report at Codecov.

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Bump Version

jira core and software to 7.7.1
jira servicedesk to 3.10.1

Signed-off-by: steigr<EMAIL_ADDRESS>

Thank you!
Note: You do not have to update the version number in the upgrade how-to. That version number is just exemplary!


Maintenance Test: tambo fixes for iOS 13

A maintenance patch has been made to address some issues with platform detection on iOS 13 that was causing problem with sound generation, see https://github.com/phetsims/tambo/issues/78.  The sims below all had this patch, and should be tested for correct sound generation.  The test should consist of two steps:

Make sure that sound is generated normally when the sim starts up, and isn't stalled until reset is pressed
Reload the sim, then before doing any other action, drag a finger in a non-interactive area of the sim, then test that sound generation works correctly.

Here is a list of the patched sims with links to the RCs:
build-a-fraction 1.0 (fix iOS 13 sound issues, see https://github.com/phetsims/tambo/issues/78)

[x] build-a-fraction 1.0.10-rc.2

circuit-construction-kit-dc 1.1 (fix iOS 13 sound issues, see https://github.com/phetsims/tambo/issues/78)

[x] circuit-construction-kit-dc 1.1.5-rc.2

circuit-construction-kit-dc-virtual-lab 1.1 (fix iOS 13 sound issues, see https://github.com/phetsims/tambo/issues/78)

[x] circuit-construction-kit-dc-virtual-lab 1.1.5-rc.2

coulombs-law 1.0 (fix iOS 13 sound issues, see https://github.com/phetsims/tambo/issues/78)

[x] coulombs-law 1.0.9-rc.2

diffusion 1.0 (fix iOS 13 sound issues, see https://github.com/phetsims/tambo/issues/78)

[x] diffusion 1.0.4-rc.2

energy-forms-and-changes 1.0 (fix iOS 13 sound issues, see https://github.com/phetsims/tambo/issues/78)

[x] energy-forms-and-changes 1.0.11-rc.2

fractions-equality 1.0 (fix iOS 13 sound issues, see https://github.com/phetsims/tambo/issues/78)

[x] fractions-equality 1.0.10-rc.2

fractions-intro 1.0 (fix iOS 13 sound issues, see https://github.com/phetsims/tambo/issues/78)

[x] fractions-intro 1.0.10-rc.2

fractions-mixed-numbers 1.0 (fix iOS 13 sound issues, see https://github.com/phetsims/tambo/issues/78)

[x] fractions-mixed-numbers 1.0.10-rc.2

friction 1.5 (fix iOS 13 sound issues, see https://github.com/phetsims/tambo/issues/78)

[x] friction 1.5.10-rc.2

gas-properties 1.0 (fix iOS 13 sound issues, see https://github.com/phetsims/tambo/issues/78)

[x] gas-properties 1.0.3-rc.2

gases-intro 1.0 (fix iOS 13 sound issues, see https://github.com/phetsims/tambo/issues/78)

[x] gases-intro 1.0.4-rc.2

graphing-lines 1.3 (fix iOS 13 sound issues, see https://github.com/phetsims/tambo/issues/78)

[x] graphing-lines 1.3.9-rc.2

graphing-quadratics 1.1 (fix iOS 13 sound issues, see https://github.com/phetsims/tambo/issues/78)

[x] graphing-quadratics 1.1.5-rc.2
[x] graphing-quadratics 1.1.5-rc.2 phet-io
[x] [graphing-quadratics 1.1.5-rc.2 phet-io Studio](https://phet-dev.colorado.edu/html/graphing-quadratics/1.1.5-rc.2/phet-io/wrappers/studio

graphing-slope-intercept 1.1 (fix iOS 13 sound issues, see https://github.com/phetsims/tambo/issues/78)

[x] graphing-slope-intercept 1.1.9-rc.2

isotopes-and-atomic-mass 1.1 (fix iOS 13 sound issues, see https://github.com/phetsims/tambo/issues/78)

[x] isotopes-and-atomic-mass 1.1.8-rc.2

john-travoltage 1.5 (fix iOS 13 sound issues, see https://github.com/phetsims/tambo/issues/78)

[x] john-travoltage 1.5.12-rc.2

masses-and-springs-basics 1.0 (fix iOS 13 sound issues, see https://github.com/phetsims/tambo/issues/78)

[x] masses-and-springs-basics 1.0.9-rc.2

molecule-shapes 1.2 (fix iOS 13 sound issues, see https://github.com/phetsims/tambo/issues/78)

[x] molecule-shapes 1.2.8-rc.2

molecule-shapes-basics 1.2 (fix iOS 13 sound issues, see https://github.com/phetsims/tambo/issues/78)

[x] molecule-shapes-basics 1.2.8-rc.2

ohms-law 1.4 (fix iOS 13 sound issues, see https://github.com/phetsims/tambo/issues/78)

[x] ohms-law 1.4.7-rc.2

resistance-in-a-wire 1.6 (fix iOS 13 sound issues, see https://github.com/phetsims/tambo/issues/78)

[x] resistance-in-a-wire 1.6.9-rc.2

wave-interference 2.0 (fix iOS 13 sound issues, see https://github.com/phetsims/tambo/issues/78)

[x] wave-interference 2.0.1-rc.2

waves-intro 1.0 (fix iOS 13 sound issues, see https://github.com/phetsims/tambo/issues/78)

[x] waves-intro 1.0.1-rc.2

Assigning to @ariel-phet for prioritization.  This was discussed in last Thursday's status meeting, and @kathy-phet seemed to feel like it was pretty high priority so that sound would work correctly in the iOS app.

There is another maintenance patch that is being done at this time that includes all of the sims above, so once the patch described in this GitHub issue has been verified, deploying of the sims listed in https://github.com/phetsims/QA/issues/432#issuecomment-542567431 should be deployed, and that will finish both maintenance releases.

Concurrent top priority with #440

QA is done

Thanks!


Phone call

Can one make a phone call using Raspberry Pi 4G/LTE Shield Kit? If so is there any examples of that I can look into?

Hello, There is no audio codec available on the Base Shield. So you cannot make voice calls.
But if the scenario is to trigger an event with a call you can use ATD; command to do so.

Thank you @saeedjohar for letting me know. This resolves the issue.


Bug on mapping for FetchOneToMany with complex entities in children and workaround

I have the following situation:
Table1:
Id
Field1
Table2
IdTable1 -> FK to Table1.Id
Child__UUID
Child__Type
ExtraData
class ObjTable1:
Id,
Field1
ChildEntities: List< ObjTable2 >
class ObjTable2
IdTable1
Child: TypedUUID
ExtraData
class TypedUUID
UUID
Type
FetchOneToMany< ObjTable1 >(arg => arg.ChildEntities, "SELECT Table1., Table2. FROM ... INNER JOIN...");
What happens it's that the field ExtraData it's not filled. BUT if I change the SQL sentence to "SELECT Table1.*, Table2.IdTable1, Table2.ExtraData, Table2.Child__UUID, Table2.Child__Type ---" then it works fine. The problem it's on ConvertFromOldConvention method of PropertyMapperNameConvention. More precisely on this line: var unusedPocoMembers = members.Where(x => !used.ContainsKey(x.PocoMember) && x.Level >= level). The problem it's the level filter. As before the ExtraData fields there are two fields that map to a complex object (TypedUUID), then the level it's increased and it's supposed that following fields will be of child entity.
In my case the workaround (put first non complex properties in the query) works because I only have one complex property but with more complex properties in the same object, there is a problem.

The most reliable way to write this query is using the following hints so that the sql would look like this. The other way only works for limited scenarios and supports the old way of doing it.
SELECT Table1.*, null npoco_ChildEntities, Table2.* ...

What ends up happening is the npoco_ChildEntities then ends up prefixing each value after it with "ChildEntities__" which leaves no ambiguity for the mapper.
Apologies for the delay.
Here is some of the crazyness
public void Test28()
{
    var data = Database.Fetch<Test28Class>("select 3 Id, 'Name' Name, 'dyn' Dynamic__Value1, 'dict' Dict__Value2, null npoco_Nest1__Dict2," +
                                           " 'dictnested' Value3, null npoco_Dict2__Value4, 'my string' S, 5 I, null npoco, 'oh my' DictHell__Key1__Dict2__Key2__S, 99 DictInt__ints," +
                                           " 'z' NestMe__Nested__Nest3__Z, 'dictsupernesed' NestMe__Nested__Dict4__MyKey__S").Single();
    Assert.AreEqual(3, data.Id);
    Assert.AreEqual("Name", data.Name);
    Assert.AreEqual("dyn", data.Dynamic.Value1);
    Assert.AreEqual("dict", data.Dict["Value2"]);
    Assert.AreEqual("dictnested", data.Nest1.Dict2["Value3"]);
    Assert.AreEqual("my string", data.Dict2["Value4"].S);
    Assert.AreEqual(5, data.Dict2["Value4"].I);
    Assert.AreEqual(99, data.DictInt["ints"]);
    Assert.AreEqual("oh my", data.DictHell["Key1"].Dict2["Key2"].S);
    Assert.AreEqual("z", data.NestMe.Nested.Nest3.Z);
    Assert.AreEqual("dictsupernesed", data.NestMe.Nested.Dict4["MyKey"].S);
}


Added role.

@rgarg24 Do we need to do anything for the keyboard on these or is just adding the role enough?

@natechadwick For this ticket, we just need to add the role. There is another ticket for keyboard. So, we need to do that also.


Transitions: Update filters for transitions page

Who is this PR for?
8th grade counselors, 9th grade counselors and assistant principals
What problem does this PR fix?
Folks can sort and search, but not obvious filter for starred / has a note / school.
What does this PR do?
Adds them.  Also updates default sort to "Starred for discussion?" and adjust the column widths.
Checklists
Which features or pages does this PR touch?

[x] Transitions

Does this PR use tests to help verify we can deploy these changes quickly and confidently?

[x] Included specs for changes
[x] Improved specs for existing code in need of better test coverage
[x] Manual testing made more sense here

selfie


hls: support generating streams with multiple audio tracks (#2728)

Fixes #2728
This allows to generate HLS playlists and streams with multiple audio tracks. The embedded HLS player was improved with a button, displayed in the top right corner of the screen, that allows to change the audio track.
This has been tested with Chrome and Firefox. There are still compatibility issues with iOS.
Nightly binaries
https://github.com/bluenviron/mediamtx/actions/runs/10980959304

Works great after few tests. Thank you!

It looks like there is compatibility with VLC Media Player, both desktop and mobile versions.
VLC doesn’t show any audio tracks, thus has no audio.

@m13253 the bug you mentioned is fixed with https://github.com/bluenviron/gohlslib/pull/204. Next time open a dedicated bug report.

Next time open a dedicated bug report.

Sorry about that! It turned out to be a different reason that I never considered.
Thanks for fixing it!


SYS1 Initializing RPI System

Creating some groundwork for the RPI system, specifically sensor multithreading and inter communication

Added sensor module, with AbstractSensor class and skeletons for RPI Cam Sensor, Ultrasonic sensor
Added logging (to console and file) and command line control over log level

temp closing till ready for review

 Here is an overview of what got changed by this pull request:

Issues
======
- Added 171

Complexity increasing per file
==============================
- bellboy/bellboy.py  5
- bellboy/LCD/I2CLCD1602.py  2
- bellboy/sensors.py  4
- bellboy/UltrasonicRanging.py  5
- bellboy/LCD/UltrasonicRanging.py  5
- bellboy/LCD/Adafruit_LCD1602.py  7
- bellboy/test/test_system.py  2
- bellboy/LCD/PCF8574.py  3

See the complete overview on Codacy


New diagnostics module : write error

Possible bug (?) cc @Sbozzolo
There seems to be an issue with the new diagnostics module in ClimaAtmos v0.17.2, when writing to a directory with existing <varname>.nc files (reproducible with any test cases, verified against box and plane configurations so far, run any of them 2x sequentially without manually cleaning the write path):
ERROR: LoadError: Could not compute diagnostic Air Potential Temperature: NCDatasets.NetCDFError(-101, "Opening path output/box_density_current_test/thetaa_inst.nc: NetCDF: HDF error")
Stacktrace:
 [1] error(s::String)
   @ Base ./error.jl:35
 [2] macro expansion
   @ ~/Research/Codes/ClimaAtmos.jl/src/solver/type_getters.jl:923 [inlined]
 [3] macro expansion
   @ ./timing.jl:501 [inlined]
 [4] macro expansion
   @ ~/Research/Codes/ClimaAtmos.jl/src/utils/utilities.jl:234 [inlined]
 [5] get_simulation(config::ClimaAtmos.AtmosConfig{Float32, CLIMAParameters.AliasParamDict{Float32}, Dict{Any, Any}, ClimaComms.SingletonCommsContext{ClimaComms.CPUSingleThreaded}})
   @ ClimaAtmos ~/Research/Codes/ClimaAtmos.jl/src/solver/type_getters.jl:894
 [6] top-level scope
   @ ~/Research/Codes/ClimaAtmos.jl/examples/hybrid/driver.jl:8
in expression starting at /Users/akshaysridhar/Research/Codes/ClimaAtmos.jl/examples/hybrid/driver.jl:8

caused by: NetCDF error: Opening path output/box_density_current_test/thetaa_inst.nc: NetCDF: HDF error (NetCDF error code: -101)
Stacktrace:
 [1] nc_open(path::String, mode::UInt16)
   @ NCDatasets ~/.julia/packages/NCDatasets/vRl1m/src/netcdf_c.jl:274
 [2] NCDatasets.NCDataset(filename::String, mode::String; format::Symbol, share::Bool, diskless::Bool, persist::Bool, memory::Nothing, attrib::Vector{Any})
   @ NCDatasets ~/.julia/packages/NCDatasets/vRl1m/src/dataset.jl:217
 [3] NCDataset
   @ ~/.julia/packages/NCDatasets/vRl1m/src/dataset.jl:177 [inlined]

   ...
   ...
   ...


Fix bug: no error message shown when deleting exercise in regime with duplicate index

I have changed the HashSet in AddRegimeCommand to integer because if hash Index, need to write hashCode() in Index.

What's the reason for not implementing the hashCode in Index?  You can just have it return the hash of the number

Is it like this?
public int hashCode() {
    Integer i =  new Integer(zeroBasedIndex);
    return i.hashCode();
}

Yes it looks something like that. Did your bug got resolved?

Yep


Error when Execute grunt build

I got an error (look at the picture bellow) when execute grunt build. Please help me, thank you

when execute grunt build command some issue occurred.

we have download file and paste folder  localhost xampp then again install python,grunt dependency package but not run apprtc please suggest proper sollution.


Error Cross Compiling on Linux AMD64 -> aarch64

/home/hortinstein/.cache/nim/cross_compile_d/@m..@s..@s.nimble@spkgs@szippy-0.10.3@szippy@sadler32_simd.nim.c:9:10:
fatal error: arm_neon.h: No such file or directory
    9 | #include "arm_neon.h"

I am getting the following issue when I try to compile, here is a reproduction:
https://github.com/hortinstein/cross_compile
nimble buildmobile

I do not know what config or requirements there are to make cross compiling from amd64 to arm64 work. Something is not correct now because the NEON header is not present for some reason for SIMD. I will not be working on this unless something changes and I need it personally as fighting with compiler config is not something I enjoy.


Analyzer fails to determine the right spot for "Wrap with widget" action in switch expression

Original issue in flutter-intellij: https://github.com/flutter/flutter-intellij/issues/6877

Hi, can someone still reproduce this? It works ok for me.


Is it applicable for any loss function?

Hi, thanks for the great work. I noticed the general usage is for categorical logits. Does it only work with categorical logits? I am working on a regression task with MSE using LLM, can I use it and how to?

+1

If you have a well-specified probabilistic model, then the GNB estimator will work as is. For example, suppose your probabilistic  model for $y|x$  is $N(\mu_{\theta}(x), \sigma_\theta^2(x)$ where $\mu_\theta$ and $\sigma_\theta$ are neural nets, then you can just use the same algorithm as is, at least in theory. This also works if the std of y|x is known
However, you simply have a MSE loss, but the standard deviation of y|x is not specified, then maybe some tricks are needed. We can only speculate without any theoretical or empirical evidence: maybe you can first estimate the std of y|x, and then sample Gaussian labels from the model using the output of the model as the mean, and the estimated std as the std. Hope this makes sense.


Fix CI failure when using println! and dbg

This pull request fixes an issue where the CI pipeline fails when there are println! or dbg statements in the code. The failure occurs because these statements are not allowed in the CI environment. To fix this, the code has been modified to remove or comment out the println! and dbg statements. This ensures that the CI pipeline runs successfully without any errors.
Fixes #4

結局、このPRを見る感じ、CIいらないんじゃないか説が出てきた
GPUの部分がテストできなくて色々こねくり回すぐらいなら、いらんのじゃないという

おけ、任せるわ


tools: Convert test-js-with-node to Python.

This is mostly a straight port from bash to Python, but we
rename the coverage option to --coverage and we add checks
for being in a venv and being correctly provisioned.
Fixes #4009.

Automated message from Dropbox CLA bot
@showell, it looks like you've already signed the Dropbox CLA. Thanks!

Nice, merged, thanks @showell!


add print tsfile specfic path

when users like me would like to analyse the specfic measurement data distribution of the tsfile file, it may help

Doc needed
Test needed
Don't we have such a similar tool?

Doc added
as the tool has just a main function, I think test can be skipped
we have TsFileSequenceRead, while the class print all the data in the tsfile. As far as I know, no other tools

as the tool has just a main function, I think test can be skipped

If no test, how to guarantee the main() is keeping maintained well?

we have TsFileSequenceRead(the tool currently does not provide script）, while the class print all the data in the tsfile. As far as I know, no other tools

see server/src/assembly/resources/tools/tsfileToolSet.

we have TsFileSequenceRead(the tool currently does not provide script）, while the class print all the data in the tsfile. As far as I know, no other tools

see server/src/assembly/resources/tools/tsfileToolSet.

Before I developed the tool, I had checked the scripts under the server dir. No tool can print out chunk data like this.

as the tool has just a main function, I think test can be skipped

If no test, how to guarantee the main() is keeping maintained well?

test added


Refined simplification logic

The simplification logic applies to non-root nodes as well. This new logic compresses the aggregate-projection nodes that are under an asynchronous aggregation node.

Codecov Report

Merging #256 into master will increase coverage by 0.27%.
The diff coverage is 100%.

@@            Coverage Diff             @@
##           master     #256      +/-   ##
==========================================
+ Coverage   73.26%   73.52%   +0.27%
==========================================
  Files         152      152
  Lines        9204     9238      +34
  Branches     1459     1464       +5
==========================================
+ Hits         6742     6791      +49
+ Misses       2090     2084       -6
+ Partials      372      363       -9

Impacted Files
Coverage Δ

.../verdictdb/coordinator/SelectQueryCoordinator.java
89.25% <ø> (ø)
:arrow_up:

...rg/verdictdb/core/querying/ExecutableNodeBase.java
92.55% <100%> (+0.34%)
:arrow_up:

...rying/simplifier/QueryExecutionPlanSimplifier.java
85.88% <100%> (ø)

...querying/simplifier/ConsolidatedExecutionNode.java
91.87% <100%> (ø)

...tdb/core/querying/ola/AsyncQueryExecutionPlan.java
89.45% <0%> (+0.48%)
:arrow_up:

...ictdb/core/querying/ola/AsyncAggExecutionNode.java
70.8% <0%> (+0.59%)
:arrow_up:

.../core/scrambling/FastConvergeScramblingMethod.java
90.97% <0%> (+1.21%)
:arrow_up:

...db/core/querying/ola/AggCombinerExecutionNode.java
97.15% <0%> (+1.43%)
:arrow_up:

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Paginated GraphQL calls use an XViewNode type as response

When  we declare a paginated data fetcher to return a view CatView, the type definitions that are generated for GraphQL will include 2 types (and more).

CatView (since this type exists as a view / java type)
CatViewNode - this type is introduced by the BP GraphQL type generation

The problem is, that a paginated call will return CatViewNodeViewConnection in the graphqls schema, which itself nests CatViewEdge which then nests CatViewNode.
The latter one CatViewNode should actually be CatView and those types are identical in the generated type definition, but they  are not the same.
The problem becomes more visible when the graphql client uses the schema to generate a client-sdk and uses types to deal with cache and flusing those.
Is there any reason we introduced XViewNode in the first place? The entire type seems redundant to me.
The code for that is in GraphQLEntityViewSupportFactory#addObjectTypeDefinition()
            nodeTypeName = objectType.getName() + "Node";
            edgeTypeName = objectType.getName() + "Edge";
            connectionTypeName = objectType.getName() + "Connection";
            pageInfoTypeName = "PageInfo";

See https://persistence.blazebit.com/documentation/1.6/entity-view/manual/en_US/#pagination-support for details about why this is this way. You can disable the relay schema parts by calling setDefineRelayTypes(false), setImplementRelayNode(false) and setDefineRelayNodeIfNotExist(false) on the GraphQLEntityViewSupportFactory

Thank you for the quick reply. I'am not sure i understand the article entirely.
Disabling
    graphQLEntityViewSupportFactory.setImplementRelayNode(false);
    graphQLEntityViewSupportFactory.setDefineRelayNodeIfNotExist(false);

Will lead to
core  |          * The field type 'PageInfo' is not present when resolving type 'AuditLogIdViewConnection' [@-1:-1]
core  |          * The field type 'PageInfo' is not present when resolving type 'ModerationPageModerationSettingEmbeddedIdViewConnection' [@-1:-1]
core  |          * The field type 'PageInfo' is not present when resolving type 'AttachmentExcerptViewConnection' [@-1:-1]

PageInfo is part of Connection
When using what you those options, what is the impact / burden. Does this mean we can no longer use the pagination implementation BP offers for GQL at all? Thanks for the clarification (and hopefully this will be helpful for others too)

You have to find a custom way to implement pagination which is not standardized.

Looking at the implementation, we could do that, seems quiet possible. But is there any technical reason you introduce an entirely new type for the node? This is not part of the spec and is not done usually https://www.apollographql.com/docs/technotes/TN0029-relay-style-connections/
Surely Connection and Edge are needed, but the inner node type could be just the EV we define as the projection, right? Is there really a technical need to introduce a new type for that?

I would love to work on that. As soon as the BP main branch has a working GQL integration again, blocked by #1707 , we will work on this.
AFAIU we would implement

a new flag defineRelayNodeTypes which is true by default
if enabled, XViewNode types are generated (current behavior)
if disabled, the actual XView type is used

Did i understand your idea correctly

a new flag defineRelayNodeTypes which is true by default

You can make it false by default and add a note about the backwards incompatible change in the CHANGELOG

if enabled, XViewNode types are generated (current behavior)

Correct

if disabled, the actual XView type is used

Yes, but also make sure that XView implements Node if isImplementRelayNode()

Yes, but also make sure that XView implements Node if isImplementRelayNode()
What does this mean? Cannot find a type /interface Node

i see
        if (!typeRegistry.getType("Node").isPresent() && isImplementRelayNode() && isDefineRelayNodeIfNotExist()) {
            List<FieldDefinition> nodeFields = new ArrayList<>(4);
            nodeFields.add(new FieldDefinition("id", new NonNullType(new TypeName("ID"))));
            addDefinition(typeRegistry, newInterfaceTypeDefinition("Node", nodeFields, null));
        }

Which basically Seem to represent
type Node {
  id: ID!
}

Right now, looking at our types, i cannot find this type nor i can see that the XViewNode type implement/extend of this. Could you explain a little on that detail?


Web View

New web view activity to show news' link.

What's a news link?

The essence of HackerNews (and Reddit) is a place for its user to share links from all over the web.
So, yeah.


Change Style to tree

I try to check if this library appropriate to my needs
I use newick string and get nice tree !
but I want to change the style:
the node of the tree get default color of pink and blue border - can I change the pink color or better hide the circle of node ?
the leaves of the tree get default color of blue and blue border - can I delete the blue border ?
the root get yellow color - can I change the yellow color or better hide the circle of node ?
I use glyphs to separate the data to groups, leaves  can belong to more 5 or 6 groups,  but the rectangles position on the label and hide the label,  I want some margin between the  rectangles  to the leaves label,  it is possible ?

Hi,
Thanks for using vue-phylogram.
For changing styles, for now, it's only possible by using the node style (https://github.com/lipme/vue-phylogram#node-styles). However, I'm adding a new option to define default colors. It will be ready in two weeks I think.
Glyphs overflow is clearly a bug, I'm going to fix it as soon as possible.
Ludo

Hi,
The last version of vue-phylogram now allows to specify default fill and outline colors for nodes and branches.
See the doc for more details. Also, you have a demo here to see all the features of vue-phylogram :
https://lipme.github.io/vue-phylogram/
Ludo

Hi, thank you for your help !!!
Ok,  I will wait for this - "Glyphs overflow is clearly a bug, I'm going to
fix it as soon as possible."
I have more issues, you send me a demo that i can check all function of the
tree,  I see there is some function that not work to me:
1 - when i hover on node or leaf nothing happens
2 - when I click on a node or leaf nothing happens,  in the demo I see the
branch and label color change of the selected nodes.
I am using nuxt 2, and the input string is newick  - can you explain to me
how  to use these events ?
בתאריך יום ה׳, 3 בנוב׳ 2022 ב-17:30 מאת lipme @.***
>:

Hi,
The last version of vue-phylogram now allows to specify default fill and
outline colors for nodes and branches.
See the doc for more details. Also, you have a demo here to see all the
features of vue-phylogram :
https://lipme.github.io/vue-phylogram/
Ludo
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Hi,
I have just tested the site with chrome and firefox and the hover (node size increases) and click (selection of the node) events look ok. Which browser do you use?
I think, it lacks the ":" before your props. Try :
:display-inner-nodes="false"

and
:display-inner-labels="false"

ן i am use chrome,
and i use in ":" in the props.
Can i show u in zoom ?
בתאריך יום שני, 7 בנובמבר 2022, מאת lipme @.***>:

Hi,
I have just tested the site with chrome and firefox and the hover (node
size increases) and click (selection of the node) events look ok. Which
browser do you use?
I think, it lacks the ":" before your props. Try :
:display-inner-nodes="false"
and
:display-inner-labels="false"
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I prefer not to use Zoom to fix issues :-).
Can you tell me if you found bugs in the demo website (https://lipme.github.io/vue-phylogram/) or in your own code ? If the bugs appear only in the app that you coded, please copy paste the code that involves vue-phylogram so that I can test it.

example of my code and newick tree
בתאריך יום ג׳, 8 בנוב׳ 2022 ב-10:38 מאת נריה סיון @.***
>:

The issue is in my project, I don't have options to click on nodes or
leaves to see the path of children's nodes and color them.
I see that options in the demo, to use these options I should use some
props or some events ? or something else ? or just add the newick string
props to the components ?
i use newick string and use nuxt 2 project
בתאריך יום ג׳, 8 בנוב׳ 2022 ב-8:49 מאת lipme <
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Closed #4 https://github.com/lipme/vue-phylogram/issues/4 as completed
via 9494934
https://github.com/lipme/vue-phylogram/commit/94949340425b3e97e242fc6d1debd60db408bca2
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ok, it helps !!
There are events like click and hover.
last question: I see that you can hide some nodes or paths by clicking. How
can I do that ?
בתאריך יום ג׳, 8 בנוב׳ 2022 ב-18:55 מאת lipme @.***
>:

Ok, it seems that nuxt misses some css...
Add
import 'vue-phylogram/dist/vue-phylogram.css'
at the beginning of the script part, it should fix the problem.
To handle events (click, hover, etc...), please read this comment :
#5 (comment)
https://github.com/lipme/vue-phylogram/issues/5#issuecomment-1306231573
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Can I choose the label color for the selected nodes by click ?  In my
project I color 2 groups of leaves by positive - green and negative by red,
when i click on a node the font labels of the leaves change to bold but the
color is red. Can I choose a different color ?
בתאריך יום ג׳, 8 בנוב׳ 2022 ב-19:41 מאת נריה סיון @.***
>:

ok, it helps !!
There are events like click and hover.
last question: I see that you can hide some nodes or paths by clicking.
How can I do that ?
בתאריך יום ג׳, 8 בנוב׳ 2022 ב-18:55 מאת lipme <
@.***>:

Ok, it seems that nuxt misses some css...
Add
import 'vue-phylogram/dist/vue-phylogram.css'
at the beginning of the script part, it should fix the problem.
To handle events (click, hover, etc...), please read this comment :
#5 (comment)
https://github.com/lipme/vue-phylogram/issues/5#issuecomment-1306231573
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You can collapse nodes by indicating nodes in the props :
https://github.com/lipme/vue-phylogram#collapse-nodes-from-props
Considering your last question, the default color for labels (selected or not) are now configurable in the defaultColors prop in the last version (3.3.0) of vue-phylogram.


Map the images/icons to the item

Is there a reason why the images/icons aren't mapped to the item/village/fish/etc... so two api calls wouldn't be necessary?
Just curious!

Hi,
The main reason the images/icons are separated is to make it clear for beginners. I know a lot of users are actually pretty new at this. Embedding the images in B64 within the response would both slow down the loading a lot for users and include useless data for people who only want the image/icon or the JSON response. Making a multipart response would also make it harder for these people. I'm nowhere near reaching a bottleneck on my end so I feel like this is the appropriate solution.
The API is also still under development, so such changes might come on the long run.
There is also the fact that a lot of app are already built on it this way which make drastic changes harder to implement (which is something I hadn't planned when I first created this).

I understand. I think my only issue is if one were making a list of villagers (which is easy to list via the /villagers/ endpoint, if someone wanted the icons of the villagers along with the name of the villager then it makes it more complex to then make a seperate call for each villager icon.
I understand the development/level of coding ability point as well. Just a thought

Maybe even adding the name prop instead of just file_name or id might be helpful too.

Sure, I'll add the English name for the villager endpoint in the coming days now that I reworked the back-end. Adding more languages wouldn't really be possible as some different villagers share the same name but in different languages.

Totally get that.
Second "enhancement" thought on this actually. Too keep the data steam low, and not break previous implementations maybe you could add an imageUri/iconUri to the item endpoints. (I can do this for you if you want! Since it would be kind of tedious). That way it's not importing the image bits but rather at least a quicker reference to the api call. So if say, I wanted to pull the villager with id: 24 the response might look like this
{
    "id": 24,
    "file-name": "brd01",
    "name": {
        "name-en": "Robin",
        "name-eneu": "Robin",
        "name-de": "Jule",
        "name-sp": "Aria",
        "name-spus": "Aria",
        "name-fr": "Robie",
        "name-frus": "Robie",
        "name-it": "Rossana",
        "name-nl": "Robin",
        "name-cn": "喳喳",
        "name-tw": "喳喳",
        "name-jp": "パーチク",
        "name-kr": "파틱",
        "name-ru": "Робин"
    },
    "personality": "Snooty",
    "birthday-string": "December 4th",
    "birthday": "4/12",
    "species": "Bird",
    "gender": "Female",
    "catch-phrase": "la-di-da",
    "image_uri": "https://acnhapi.com/images/villagers/24",
    "icon_uri": "https://acnhapi.com/icons/villagers/24"
}

and I can add the image_uri to the image component in my code and it would just fetch it when mounting.

I'll do that on Tuesday, thanks for the feedback.

I actually already did haha. wrote a small script to do the heavy lifting. Mind if I make a PR?

Fixed and uri keys added to all endpoints, will update the doc.


Highlighting

Support for highlights. Regex can be easily supported.

Note: this is already supported for the rsn itself


CPU execution of ops after gradient clipping on windows

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): Windows10
TensorFlow installed from (source or binary): Binary
TensorFlow version (use command below):1.5.0
Python version: 3.6
Bazel version (if compiling from source):N/A
GCC/Compiler version (if compiling from source):N/A
CUDA/cuDNN version:CUDA 9.0, cuDNN 7
GPU model and memory: Titan xp, 12gb
Exact command to reproduce: Script attached below

Describe the problem
Adding gradient clipping as follows places certain ops on the CPU greatly increasing training time on windows.
    grads = tf.gradients(loss, tf.trainable_variables())
    omnomed_grads, _ = tf.clip_by_global_norm(grads, 0.5)
    train_op = optimizer.apply_gradients(zip(omnomed_grads,  tf.trainable_variables()))

I worte a script  to perform a few tests:

OS
TF Version
Gradient clipping
Average runtime (m:s.ms)

Windows10
1.6
True
2:13.57

Windows10
1.6
False
0:16.24

Windows10
1.5
True
2:13.46

Windows10
1.5
False
0:16.52

Windows10
1.2
True
0:24.64

Windows10
1.2
False
0:23.80

Linux mint 18.1
1.5
True
0:23.45

Linux mint 18.1
1.5
False
0:21.29

Curiously the issue isn't present on TF1.2
Forcing operation placement on the GPU:
    with tf.device('/gpu:0'):
        grads = tf.gradients(loss, tf.trainable_variables())
        omnomed_grads, _ = tf.clip_by_global_norm(grads, 0.5)
        train_op = optimizer.apply_gradients(zip(omnomed_grads,  tf.trainable_variables()))

results in the following error on windows:
Cannot assign a device for operation 'gradients/softmax_cross_entropy_with_logits_grad/LogSoftmax': Could not satisfy explicit device specification '/device:GPU:0' because no supported kernel for GPU devices is available.
The error generated is similar to #2803 and #3118
Setting soft device placement in session configuration results in similar runtime.
Source code / logs
I have attached the device placement logs of windows 10 running TF 1.6 with and without gradient clipping as well as the device placement logs from Linux mint with gradient clipping
A few discrepancies with respect to op placement while gradient clipping are highlighted below:

Windows10
Linux mint

gradients/softmax_cross_entropy_with_logits_grad/LogSoftmax: (LogSoftmax): /job:localhost/replica:0/task:0/device:CPU:0
gradients/softmax_cross_entropy_with_logits_grad/LogSoftmax: (LogSoftmax): /job:localhost/replica:0/task:0/device:GPU:0

global_norm/L2Loss_6: (L2Loss): /job:localhost/replica:0/task:0/device:CPU:0
global_norm/L2Loss_6: (L2Loss): /job:localhost/replica:0/task:0/device:GPU:0

gradients/conv2d/Conv2D_grad/Conv2DBackpropFilter: (Conv2DBackpropFilter): /job:localhost/replica:0/task:0/device:CPU:0
gradients/conv2d/Conv2D_grad/Conv2DBackpropFilter: (Conv2DBackpropFilter): /job:localhost/replica:0/task:0/device:GPU:0

gradients/conv2d/BiasAdd_grad/BiasAddGrad: (BiasAddGrad): /job:localhost/replica:0/task:0/device:CPU:0
gradients/conv2d/BiasAdd_grad/BiasAddGrad: (BiasAddGrad): /job:localhost/replica:0/task:0/device:GPU:0

clip_by_global_norm/mul_8: (Mul): /job:localhost/replica:0/task:0/device:CPU:0
clip_by_global_norm/mul_8: (Mul): /job:localhost/replica:0/task:0/device:GPU:0

Nagging Assignee: It has been 14 days with no activity and this issue has an assignee. Please update the label and/or status accordingly.

Nagging Assignee @rmlarsen: It has been 14 days with no activity and this issue has an assignee. Please update the label and/or status accordingly.

Did you ever make any progress with this? I've had the same issue myself and it seems to be exactly this happening.

Sorry, haven't made any progress on this issue. I switched training of networks to Linux to mitigate the problem.

From: Jonas Adler<EMAIL_ADDRESS>Sent: Monday, March 12, 2018 7:36 PM
To: tensorflow/tensorflow
Cc: Dhruv Mohan; Author
Subject: Re: [tensorflow/tensorflow] CPU execution of ops after gradient clipping on windows (#16864)
Did you ever make any progress with this? I've had the same issue myself and it seems to be exactly this happening.
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Is there any chance for an update on this? This bug is basically rendering a lot of my old code un-usable since it takes weeks to run it. And dropping the clipping changes its behavior.

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Hi @Dhruv-Mohan ! 1.x versions are not supported any more. Have you checked this issue in 2.7 version onward? Thanks!


Audible  is playing from wrong time stamp

IMPORTANT: Before you create an issue, please take a look at our Issue Reporting Guide.
Briefly summarize your issue:-->
When we are asking Alexa to play a book from audible,it starts streaming the recently read book and then after a while if we pause it and then resume, it will read from wrong time stamp i.e., it will go 15-20 secs behind and starts playing.
What is the expected behavior?
Alexa should read the book from audible from  the timestamp that it is stopped.
What behavior are you observing?
Alexa starts reading the book 15-20 secs behind
Provide the steps to reproduce the issue, if applicable:
Ask to play Audible ("Alexa, play Audible")
Stop playing ("Alexa, stop")
Resume playing ("Alexa, resume Audible")
Check playing position

Tell us about your environment:
AVS SDK version 1.12.0
Tell us what hardware you're using:
SDM450
Tell us about your OS (Type & version):
Android P

Logcat_file
audible_avs_play_resume.txt

Hello @dipalisb,
I was able to reproduce your experience locally.  It appears that Alexa Service is sending an AudioPlayer.Play directive with an offset from well before the offset provided by the AudioPlayer PlaybackPaused and PlaybackStopped events sent to AVS when audible playback is paused.  We are investigating the source of this discrepancy.
That you for bringing this to our attention!
-SWH

Hello @dipalisb,
I have heard back from the Audible service team, and they indicate that this 15 second rewind is intentional.
I am closing this issue as the behavior is as expected/designed.  Please feel free to re-open this issue if it has been closed in error.
Thank you again,
-SWH


Additional resources is missing

It says above "For more information about both of these books, see Additional resources later in this topic."
There is no Additional resources chapter on this page.

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

ID: 5dcd8f18-dc4c-3780-7fda-f662ceba7890
Version Independent ID: 452ebf35-75b1-4b9e-2d06-b3e8da78e774
Content: CMMI process template artifacts - VSTS & TFS
Content Source: docs/work/work-items/guidance/cmmi-process.md
Product: devops
GitHub Login: @KathrynEE
Microsoft Alias: kaelli

Sorry, I accidentally opened this on the wrong page


fit() error

Hi,
The dataset used was like this:
import io
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import scipy.stats
import scipy.special
data = """Grain size (mm)	Spiders
0.245	absent
0.247	absent
0.285	present
0.299	present
0.327	present
0.347	present
0.356	absent
0.36	present
0.363	absent
0.364	present
0.398	absent
0.4	present
0.409	absent
0.421	present
0.432	absent
0.473	present
0.509	present
0.529	present
0.561	absent
0.569	absent
0.594	present
0.638	present
0.656	present
0.816	present
0.853	present
0.938	present
1.036	present
1.045	present
"""
df = pd.read_table(io.StringIO(data))
df.Spiders = df.Spiders == 'present'
df.head()

I am trying to perform the 'likelihood ratio test' to evaluate the regression model. it includes a null model and fitted model. in the null model, we do the below in fit()
CODE:
k1 = np.zeros_like(df['Spiders']).reshape(-1,1)
k2 = pd.DataFrame(k1, columns=['n'])
k3 = df['Spiders']
k4 = pd.DataFrame(k3)
k5 = k2.join(k4)
label='Spiders'
pred2 = task.fit(train_data=k5,label=label, hyperparameters={'LR':{}}, eval_metric='log_loss')

The above code basically takes a column of 'false' values(0's) as dependent variable and the independent variable label as 0's and 1's. But it gives me the following error, can u pls say why?
ERROR:
No output_directory specified. Models will be saved in: AutogluonModels/ag-20200621_121945/
Beginning AutoGluon training ...
AutoGluon will save models to AutogluonModels/ag-20200621_121945/
Train Data Rows:    28
Train Data Columns: 2
Preprocessing data ...
Here are the 2 unique label values in your data:  [False, True]
AutoGluon infers your prediction problem is: binary  (because only two unique label-values observed).
If this is wrong, please specify `problem_type` argument in fit() instead (You may specify problem_type as one of: ['binary', 'multiclass', 'regression'])

Warning: Updated label_count_threshold from 10 to 9 to avoid cutting too many classes.
Selected class <--> label mapping:  class 1 = True, class 0 = False
Train Data Class Count: 2
Feature Generator processed 28 data points with 0 features
Original Features:
Generated Features:
	int features: 0
All Features:
	int features: 0
	Data preprocessing and feature engineering runtime = 0.03s ...
AutoGluon will gauge predictive performance using evaluation metric: log_loss
This metric expects predicted probabilities rather than predicted class labels, so you'll need to use predict_proba() instead of predict()
To change this, specify the eval_metric argument of fit()
AutoGluon will early stop models using evaluation metric: log_loss
Fitting model: LinearModel ...
  File "/usr/local/lib/python3.6/dist-packages/autogluon/utils/tabular/ml/trainer/abstract_trainer.py", line 261, in train_and_save
    model = self.train_single(X_train, y_train, X_test, y_test, model, kfolds=kfolds, k_fold_start=k_fold_start, k_fold_end=k_fold_end, n_repeats=n_repeats, n_repeat_start=n_repeat_start, level=level, time_limit=time_limit)
  File "/usr/local/lib/python3.6/dist-packages/autogluon/utils/tabular/ml/trainer/abstract_trainer.py", line 246, in train_single
    model.fit(X_train=X_train, Y_train=y_train, X_test=X_test, Y_test=y_test, time_limit=time_limit, **model_fit_kwargs)
  File "/usr/local/lib/python3.6/dist-packages/autogluon/utils/tabular/ml/models/lr/lr_model.py", line 123, in fit
    X_train = self.preprocess(X_train, is_train=True, vect_max_features=hyperparams['vectorizer_dict_size'], model_specific_preprocessing=True)
  File "/usr/local/lib/python3.6/dist-packages/autogluon/utils/tabular/ml/models/lr/lr_model.py", line 72, in preprocess
    self.preprocess_train(X, feature_types, vect_max_features)
  File "/usr/local/lib/python3.6/dist-packages/autogluon/utils/tabular/ml/models/lr/lr_model.py", line 105, in preprocess_train
    self.pipeline = FeatureUnion(transformer_list=transformer_list)
  File "/usr/local/lib/python3.6/dist-packages/sklearn/pipeline.py", line 814, in __init__
    self._validate_transformers()
  File "/usr/local/lib/python3.6/dist-packages/sklearn/pipeline.py", line 845, in _validate_transformers
    names, transformers = zip(*self.transformer_list)
Warning: Exception caused LinearModel to fail during training... Skipping this model.
Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/autogluon/utils/tabular/ml/trainer/abstract_trainer.py", line 261, in train_and_save
    model = self.train_single(X_train, y_train, X_test, y_test, model, kfolds=kfolds, k_fold_start=k_fold_start, k_fold_end=k_fold_end, n_repeats=n_repeats, n_repeat_start=n_repeat_start, level=level, time_limit=time_limit)
  File "/usr/local/lib/python3.6/dist-packages/autogluon/utils/tabular/ml/trainer/abstract_trainer.py", line 246, in train_single
    model.fit(X_train=X_train, Y_train=y_train, X_test=X_test, Y_test=y_test, time_limit=time_limit, **model_fit_kwargs)
  File "/usr/local/lib/python3.6/dist-packages/autogluon/utils/tabular/ml/models/lr/lr_model.py", line 123, in fit
    X_train = self.preprocess(X_train, is_train=True, vect_max_features=hyperparams['vectorizer_dict_size'], model_specific_preprocessing=True)
  File "/usr/local/lib/python3.6/dist-packages/autogluon/utils/tabular/ml/models/lr/lr_model.py", line 72, in preprocess
    self.preprocess_train(X, feature_types, vect_max_features)
  File "/usr/local/lib/python3.6/dist-packages/autogluon/utils/tabular/ml/models/lr/lr_model.py", line 105, in preprocess_train
    self.pipeline = FeatureUnion(transformer_list=transformer_list)
  File "/usr/local/lib/python3.6/dist-packages/sklearn/pipeline.py", line 814, in __init__
    self._validate_transformers()
  File "/usr/local/lib/python3.6/dist-packages/sklearn/pipeline.py", line 845, in _validate_transformers
    names, transformers = zip(*self.transformer_list)
ValueError: not enough values to unpack (expected 2, got 0)
not enough values to unpack (expected 2, got 0)
No base models to train on, skipping weighted ensemble...

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-37-002c89d9f4c6> in <module>
      5 k5 = k2.join(k4)
      6 label='Spiders'
----> 7 pred2 = task.fit(train_data=k5,label=label, hyperparameters={'LR':{}}, eval_metric='log_loss')

/usr/local/lib/python3.6/dist-packages/autogluon/task/tabular_prediction/presets_configs.py in _call(**kwargs)
      7         @functools.wraps(f)
      8         def _call(**kwargs):
----> 9             return f(**g(**kwargs))
     10         return _call
     11     return _unpack_inner

/usr/local/lib/python3.6/dist-packages/autogluon/task/tabular_prediction/tabular_prediction.py in fit(train_data, label, tuning_data, time_limits, output_directory, presets, problem_type, eval_metric, stopping_metric, auto_stack, hyperparameter_tune, feature_prune, holdout_frac, num_bagging_folds, num_bagging_sets, stack_ensemble_levels, hyperparameters, num_trials, scheduler_options, search_strategy, search_options, nthreads_per_trial, ngpus_per_trial, dist_ip_addrs, visualizer, verbosity, **kwargs)
    586                     hyperparameter_tune=hyperparameter_tune, feature_prune=feature_prune,
    587                     holdout_frac=holdout_frac, num_bagging_folds=num_bagging_folds, num_bagging_sets=num_bagging_sets, stack_ensemble_levels=stack_ensemble_levels,
--> 588                     hyperparameters=hyperparameters, time_limit=time_limits_orig, save_data=cache_data, save_bagged_folds=save_bagged_folds, verbosity=verbosity)
    589
    590         predictor = TabularPredictor(learner=learner)

/usr/local/lib/python3.6/dist-packages/autogluon/utils/tabular/ml/learner/default_learner.py in fit(self, X, X_test, scheduler_options, hyperparameter_tune, feature_prune, holdout_frac, num_bagging_folds, num_bagging_sets, stack_ensemble_levels, hyperparameters, time_limit, save_data, save_bagged_folds, verbosity)
    101         self.save()
    102         trainer.train(X, y, X_test, y_test, hyperparameter_tune=hyperparameter_tune, feature_prune=feature_prune, holdout_frac=holdout_frac,
--> 103                       hyperparameters=hyperparameters)
    104         self.save_trainer(trainer=trainer)
    105         time_end = time.time()

/usr/local/lib/python3.6/dist-packages/autogluon/utils/tabular/ml/trainer/auto_trainer.py in train(self, X_train, y_train, X_test, y_test, hyperparameter_tune, feature_prune, holdout_frac, hyperparameters)
     31             if (y_test is None) or (X_test is None):
     32                 X_train, X_test, y_train, y_test = generate_train_test_split(X_train, y_train, problem_type=self.problem_type, test_size=holdout_frac, random_state=self.random_seed)
---> 33         self.train_multi_and_ensemble(X_train, y_train, X_test, y_test, models, hyperparameter_tune=hyperparameter_tune, feature_prune=feature_prune)

/usr/local/lib/python3.6/dist-packages/autogluon/utils/tabular/ml/trainer/abstract_trainer.py in train_multi_and_ensemble(self, X_train, y_train, X_test, y_test, models, hyperparameter_tune, feature_prune)
    503         self.train_multi_levels(X_train, y_train, X_test, y_test, models=models, hyperparameter_tune=hyperparameter_tune, feature_prune=feature_prune, level_start=0, level_end=self.stack_ensemble_levels)
    504         if len(self.get_model_names_all()) == 0:
--> 505             raise ValueError('AutoGluon did not successfully train any models')
    506
    507     def train_multi_levels(self, X_train, y_train, X_test, y_test, models: List[AbstractModel], hyperparameter_tune=True, feature_prune=False, level_start=0, level_end=0):

ValueError: AutoGluon did not successfully train any models

Note: This error doesn't occur if I use fit() using sklearn without using autogluon. But I want to implement using autogluon, please help!
Please help me to solve, thanks in advance!

A tip for future issues: Please use the code block functionality of GitHub when pasting code into your issue, this simplifies viewing and makes things look a lot cleaner. I have edited your original comment to use code blocks.

Oh sure, noted. Thanks. Waiting for your reply on the issue!

Your data transformation was not correct, and led to the 'n' column consisting of only 0 values. Since this is the only feature and it contains no information (thus getting filtered out during preprocessing), AutoGluon crashes.
This modified code works:
import io
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import scipy.stats
import scipy.special
from autogluon import TabularPrediction as task

data = """Grain size (mm)	Spiders
0.245	absent
0.247	absent
0.285	present
0.299	present
0.327	present
0.347	present
0.356	absent
0.36	present
0.363	absent
0.364	present
0.398	absent
0.4	present
0.409	absent
0.421	present
0.432	absent
0.473	present
0.509	present
0.529	present
0.561	absent
0.569	absent
0.594	present
0.638	present
0.656	present
0.816	present
0.853	present
0.938	present
1.036	present
1.045	present
"""
df = pd.read_table(io.StringIO(data))
# df.Spiders = df.Spiders == 'present'
# print(df.head())

# k1 = np.zeros_like(df['Spiders']).reshape(-1, 1)
# k2 = pd.DataFrame(k1, columns=['n'])
# k3 = df['Spiders']
# k4 = pd.DataFrame(k3)
# k5 = k2.join(k4)
label = 'Spiders'
pred2 = task.fit(train_data=df, label=label, hyperparameters={'LR': {}}, eval_metric='log_loss')

Code Output:
No output_directory specified. Models will be saved in: AutogluonModels/ag-20200623_003617/
Beginning AutoGluon training ...
AutoGluon will save models to AutogluonModels/ag-20200623_003617/
Train Data Rows:    28
Train Data Columns: 2
Preprocessing data ...
Here are the 2 unique label values in your data:  ['absent', 'present']
AutoGluon infers your prediction problem is: binary  (because only two unique label-values observed).
If this is wrong, please specify `problem_type` argument in fit() instead (You may specify problem_type as one of: ['binary', 'multiclass', 'regression'])
Warning: Updated label_count_threshold from 10 to 9 to avoid cutting too many classes.
Selected class <--> label mapping:  class 1 = present, class 0 = absent
Train Data Class Count: 2
Feature Generator processed 28 data points with 1 features
Original Features:
	float features: 1
	object features: 0
Generated Features:
	int features: 0
All Features:
	float features: 1
	object features: 0
	int features: 0
	Data preprocessing and feature engineering runtime = 0.04s ...
AutoGluon will gauge predictive performance using evaluation metric: log_loss
This metric expects predicted probabilities rather than predicted class labels, so you'll need to use predict_proba() instead of predict()
To change this, specify the eval_metric argument of fit()
AutoGluon will early stop models using evaluation metric: log_loss
Fitting model: LinearModel ...
	-0.5258	 = Validation log_loss score
	1.86s	 = Training runtime
	0.01s	 = Validation runtime
Fitting model: weighted_ensemble_k0_l1 ...
	-0.5258	 = Validation log_loss score
	0.01s	 = Training runtime
	0.0s	 = Validation runtime
AutoGluon training complete, total runtime = 1.95s ...

For future issues, please confirm that your data being sent into AutoGluon is correct before creating the issue, in order to save time.
Best,
Nick

No, to perform likelihood ratio test we use fit() with only zeros as train_data and dependent variable. This error doesn't occur when we do the same with scikit learn fit().

I understand what you mean now, sorry for misunderstanding. While this is technically a valid use-case, AutoML may not be the best solution to go about creating a null model. AutoGluon crashes because it filters out features which have all the same value across all rows, and since no features exist, no models can be trained. This could be changed in future to instead return a dummy model which just predicts a constant value.

Thank you!


Add git status functionality

Design Doc
Goal
Our goal is to have .status() surface useful information to the user.  Since status is inherently backward-looking, I expect users will approach it with two questions in mind:

Where did I start?
What did I do?

Did I create a new group?
Did I delete an existing?
Did I update an existing group?

Did I update attributes of this group?
Did I create a new array?
Did I delete an array?
Did I modify existing arrays?

Did I modify attributes?
Are these chunk modifications?

did I write new chunks?
did I delete existing chunks?
did I overwrite existing chunks?

How did I modify the chunks (if relevant)?

What fraction of the array was modified?
Did I append?
Did I write a region?

Wait, I didn't know I did that?

We should let the user interrogate the changeset to see what exact changes were made. E.g. you added an attribute to an array at this path.

What do I do next?

Commit!

Some things to be careful about:

Initial commit should not be confusing to the user.
Comparing two different status outputs should be easy

Information should be easy to scan, sorting is a good idea.

Information to surface

For Q1, we should surface VCS history information:
a. Repo bucket
b. Base Snapshot ID and commit time.
c. Do we need to surface a truncated commit message too?
d. Current branch

For Q2, we should surface information in the current ChangeSet:

new_groups, new_arrays
deleted_groups, deleted_arrays
updated_arrays -> zarr array metadata
updated_attributes -> group/array user attributes
set_chunks -> modified chunks (create/delete/overwrite)

For Q3,  we punt to later :)

For Q4, we should encourage the user to make a commit by saying loud and clear that these are "uncommitted changes" and will be lost (?).

How to surface
As a tree?
One particularly neat way to surface this information would be to show the hierarchy as tree. We could construct a tree for the snapshot + changeset: new-tree. Then iterate through the changeset and add information to the appropriate node of the tree. During diffing, if two nodes are in the same place, we examine the changeset for metadata, chunk modifications and annotate the new-tree appropriately. The diffed-tree structure could then be rendered to text in Rust, and transferred to Python for rendering with rich (for example)
As plain text?
We could simply output formatted lists of created/updated/deleted groups/arrays.

I'll add another option to "How to surface":

full structured list of changes.

That could help us in the future have an answer to 3.
Example:
struct Status(Vec<(Path, Vec[Change])>)

enum Change {
   ArrayCreated(ZarrMetadata),
   ArrayMetadataUpdated(ZarrMetadata),
   ChunksDeleted(Vec<ChunkIndices>),
   ChunksWritten(Vec<ChunkIndices>),
   GroupDeleted,
    ....
}

This would give us a high level language. Then we can build different types of formaters on top of it.

Ah nice, yes that makes sense.
I'm also thinking the formatting of the structure should live in Rust, and we may want to expose it through a CLI in the future?

We should probably design both status and transaction log as abstract data structures and then build ways to transform them into something for display in different contexts, e.g.

json
python class with a nice __repr__
rich formatted text for CLI
etc


chore: increase version

Coverage remained the same at 89.301% when pulling 27e186be054b22e02de140d1b2601cd1b66991ff on v2.4.1 into c8c20a046e9c2ea187fe2f511d5e2326d154025b on master.

Coverage remained the same at 89.301% when pulling 3ab0bf88267e05e817b8547b091b9545cbd11d52 on v2.4.1 into c8c20a046e9c2ea187fe2f511d5e2326d154025b on master.

Well that was fun...so this is actually v2.4.3 even though the branch says v2.4.1

Coverage decreased (-0.5%) to 88.839% when pulling b42ca0b5abcf90fc58c8fe96101c3fe7ee72ccd0 on v2.4.1 into c8c20a046e9c2ea187fe2f511d5e2326d154025b on master.

@homu r+

:pushpin: Commit b42ca0b has been approved by kbknapp

:hourglass: Testing commit b42ca0b with merge b027c65...

:sunny: Test successful - status


Interface auto exporting random items

Issue description:
When connecting an item duct to an interface and setting it to auto output via a servo the interface starts exporting random items from different mods.
What happens:
Random items are exported.
What you expected to happen:
Nothing.
Steps to reproduce:

connect an interface to a network containing items.
create a loop via item ducts from one side of the interface to another
Put a servo on one side and set it to auto export
...

Version (make sure you are on the latest version before reporting):

Minecraft: 1.12.2
Forge: <IP_ADDRESS>18
Refined Storage: 1.5.31

Does this issue occur on a server? [yes/no]
don't know
If a (crash)log is relevant for this issue, link it here:
[pastebin/gist/etc link here]
Here's a link to a video demonstrating.
https://youtu.be/3OAxzsv3AdY

It's not a bug, it's a feature.


Fix support data for browsers missing flex-basis

Support for the flex-basis property is an important part of the Intrinsic & Extrinsic Sizing in the CSS Box Sizing spec.
There's currently some inconsistency in the data where some browsers missing flex-basis show "partial support", while others are showing full support. This PR fixes the inconsistent data to mark browsers missing flex-basis support to consistently show "partial support". Additionally, this adds STP support for flex-basis (added in STP 140).

Ping?

Still needs more revisiting as mentioned in my previous comment, but I just confirmed support in Safari 16+ and have updated there appropriately.

Thank you!


fix the source code

maybe im dumb, but i kept getting this errors when im trying to build a solution:

It says something like "Der Namesoace "Photon (And so on)" wasnt found"

there is nothing to fix you just need to add references

To do that go on the right bar on the "References" option, right click it, select "Add References", once the references screen pops up on the bottom click "Browse" and go to this path "C:\Program Files (x86)\Steam\steamapps\common\1v1.LOL\1v1_LOL_Data\Managed", once you're there select these files showed in the image and add them, after that you should be able to build NetWare.

To do that go on the right bar on the "References" option, right click it, select "Add References", once the references screen pops up on the bottom click "Browse" and go to this path "C:\Program Files (x86)\Steam\steamapps\common\1v1.LOL\1v1_LOL_Data\Managed", once you're there select these files showed in the image and add them, after that you should be able to build NetWare.

ily man ♥

To do that go on the right bar on the "References" option, right click it, select "Add References", once the references screen pops up on the bottom click "Browse" and go to this path "C:\Program Files (x86)\Steam\steamapps\common\1v1.LOL\1v1_LOL_Data\Managed", once you're there select these files showed in the image and add them, after that you should be able to build NetWare.

it worked now ty man


Peering Request

Full Name
archelle louie datahan
ASN
150000
PeeringDB Integration

[X] My PeeringDB Entries are current
[X] Peer at ALL EXCHANGES (and skip the Peer Address(es) field below)

Peer Address(es)
peering Bgp ip v4 is <IP_ADDRESS>
peering Bgp ip v6 is 2401:8e80::21
for Ph Open IX Billateral Session
peering Bgp ip v4 is <IP_ADDRESS>
peering Bgp ip v6 is 2001:478:172::171
Multihop

[X] Multihop Peering Request

I've added the 2nd bilateral peering at PhOpenIX now. Just to note that the original bilateral we set up in May has been down for the last 4 days. And also your PeeringDB entry says you have two peering addresses at PhOpenIX. Is the original peering going away, or are you planning to bring it back up?
This is the status now:
Neighbor          V         AS   MsgRcvd   MsgSent   TblVer  InQ OutQ  Up/Down State/PfxRcd   PfxSnt Desc
<IP_ADDRESS>    4     150000     63236     23712        0    0    0 4d07h01m       Active        0 Data-Beam Business
<IP_ADDRESS>    4     150000         0         3        0    0    0    never       Active        0 Data-Beam Business
2001:478:172::170 4     150000     24351     23713        0    0    0 4d07h01m       Active        0 Data-Beam Business
2001:478:172::171 4     150000         0         3        0    0    0    never       Active        0 Data-Beam Business

Please let us know!
Also, is there any reason you are asking for multi-hop peering as well? We generally set those up for peers who are not present at Internet Exchange Points. Do let us know, please.

Hello thanks for setting up our 2nd peering. our first peering still up. just encountered foc break on field and still functioning.thnx!

both ipv4 and v6 on our 2nd peering now up.thanks!

Ok, understood, thanks for letting us know. Status now:
Neighbor          V         AS   MsgRcvd   MsgSent   TblVer  InQ OutQ  Up/Down State/PfxRcd   PfxSnt Desc
<IP_ADDRESS>    4     150000     63236     23712        0    0    0 4d07h14m       Active        0 Data-Beam Business
<IP_ADDRESS>    4     150000    289470        16 32203929    0    0 00:04:53       968579        0 Data-Beam Business
2001:478:172::170 4     150000     24351     23713        0    0    0 4d07h14m       Active        0 Data-Beam Business
2001:478:172::171 4     150000     68993        25 18150245    0    0 00:04:58       207738        0 Data-Beam Business

Thanks very much!

thanks!
Regards..
Mr. Archelle Louie Datahan
Data-Byte Computer Sales  & ServicesAeroCam Media-Low altitude Aerial Services
Aparente Street, Cor Salvani Street, Brgy City Hights,General Santos CityTel #<PHONE_NUMBER> or<PHONE_NUMBER>8
like us on Facebook!
http://facebook.com/databytegensanhttp://facebook.com/aerocammedia
On Saturday, September 7, 2024 at 05:02:15 PM GMT+8, Philip Smith<EMAIL_ADDRESS>wrote:

I've added the 2nd bilateral peering at PhOpenIX now. Just to note that the original bilateral we set up in May has been down for the last 4 days. And also your PeeringDB entry says you have two peering addresses at PhOpenIX. Is the original peering going away, or are you planning to bring it back up?
This is the status now:
Neighbor          V         AS   MsgRcvd   MsgSent   TblVer  InQ OutQ  Up/Down State/PfxRcd   PfxSnt Desc
<IP_ADDRESS>    4     150000     63236     23712        0    0    0 4d07h01m       Active        0 Data-Beam Business
<IP_ADDRESS>    4     150000         0         3        0    0    0    never       Active        0 Data-Beam Business
2001:478:172::170 4     150000     24351     23713        0    0    0 4d07h01m       Active        0 Data-Beam Business
2001:478:172::171 4     150000         0         3        0    0    0    never       Active        0 Data-Beam Business
Please let us know!
Also, is there any reason you are asking for multi-hop peering as well? We generally set those up for peers who are not present at Internet Exchange Points. Do let us know, please.
—
Reply to this email directly, view it on GitHub, or unsubscribe.
You are receiving this because you authored the thread.Message ID: @.***>


Connection pooling throws TypeLoadException in Oracle.DataAccess with OS authentication disabled

When Oracle.DataAccess populates the connection pool (e.g. Min Pool Size > 1 or multiple concurrent connections in the same connection pool), a TypeLoadException is thrown:
Could not load type 'System.Security.Principal.WindowsImpersonationContext' from assembly 'mscorlib, Version=<IP_ADDRESS>, Culture=neutral, PublicKeyToken=b77a5c561934e089'.
The WindowsImpersonationContext type and the WindowsIdentity.Impersonate() method have not been ported to .NET Core, but are referenced by the ODP.NET driver. ODP.NET ensures that the correct windows identity is impersonated for connection pooling when operating system authentication is enabled in the connection string (User ID=/).
However, the runtime error also occurs when OS authentication is not used, since the ODP.NET method for populating the pool still needs to be compiled with types unknown to the .NET Core runtime.

The unmanaged ODP.NET provider can now be loaded in a compatibility assembly load context to avoid the TypeLoadException in .NET Core. Operating system authentication is still not supported and throws a PlatformNotSupportedException.


added Hunter College Schools

added Hunter College Schools

@mehrkaurr First stage of verification passed, official domain for Hunter College Campus School is hunterschools.org as far as I verified. This is just an informational note. Pull request is still in the review. I appreciate your patience while waiting for the final decision.


⚡ [SUPPORT] : Rework Market with ReactQuery in LLM + CVS v3 on LL

📝 Description
Replace MarketProvider in LLM new Arch with ReactQuery hook like LLD

Introducing  LLM
Usage of TanstackQuery (ReactQuery)
Adding new part in Store dedicated to Market pages
Remove old stuff from Settings store to new Market store
Removal of MarketDataProvider from LLC

❓ Context

JIRA or GitHub link: LIVE-11751 LIVE-12816

✅ Checklist
Pull Requests must pass the CI and be code reviewed. Set as Draft if the PR is not ready.

[x] npx changeset was attached.
[ ] Covered by automatic tests.
[ ] Impact of the changes:

...

🧐 Checklist for the PR Reviewers

[ ] The code aligns with the requirements described in the linked JIRA or GitHub issue.
[ ] The PR description clearly documents the changes made and explains any technical trade-offs or design decisions.
[ ] There are no undocumented trade-offs, technical debt, or maintainability issues.
[ ] The PR has been tested thoroughly, and any potential edge cases have been considered and handled.
[ ] Any new dependencies have been justified and documented.
[ ] Performance considerations have been taken into account. (changes have been profiled or benchmarked if necessary)

/generate-screenshots

/generate-screenshots

LGTM !


Providing GPR shadow sets

raised by AIA group as potentially useful for fast interrupt group in email.

Providing GPR Shadow Sets.
The EIC has the ability to specify a GPR Shadow Set that the interrupt handler can use, w/o executing a GPR save/restore sequence in the handler. The EIC specifies the Shadow Set to be used by the hart. The tradeoff is eliminating the save/restore sequence against adding area/power for the shadow GPR sets, which is significant. Given the cost, the likelihood of this being a valuable architectural feature is low.

Seems to be a general trend away from this due to cost/power, especially for multiple preemption levels.  Software can save/restore only those registers needed. Handlers would be software-incompatible ( but difference could be constrained to trampoline code in software-vectored scheme if common ABI used for handlers).   For the class of cores using CLIC, probably explicit push/pop instructions are more useful than interrupt register banks.


Google map links not able to share in ios version :16.6.1 device

We are using this plugin to share the Google Map link to the application via the Google Map app(not Safari or other browsers). We are facing one issue like the map link being received as the null value in the listener. Also, the issue is coming 8 times out of 10.
Plugin version:
1.8.0
ios OS version:
16.6.1
Note: In other iOS OS versions it is working as expected.
@KasemJaffer

@KasemJaffer any updates on this?


Contribution Guidelines and Code of Conduct

I've added drafts of Contribution Guidelines and Code of Conduct.
Some things that should be resolved before these are accepted:

<EMAIL_ADDRESS>email alias should be set up, forwarding to the Code For Science Team
agree with Mozilla Science Lab who should be emailed for escalation of reports relating to Code of Conduct
someone from the Code For Science team should review the documents and see if they agree with them :-)

Some things which could be considered, but aren't necessary for acceptance:

consider using standard labels (e.g. Easy Pick) in the issues to mark out low hanging fruit for potential contributors

@npch do you know of a source of standard issue label names? I don't think I've seen any kind of standard before.

and I forgot to say thanks so much for this! A huge improvement to the repo :)

Love this COC @npch, I checked out your PR and made changes locally but don't have push permissions, so I'll add some suggestions here.

Under Reporting, feel free to list me as the Mozilla Science arbiter:

If your report is concerning a member of the Code For Science team, and you do not wish them to see the report, you may escalate your report by sending it directly to the independent arbiter, Mozilla Science Lab. You can email Aurelia at the Science Lab directly<EMAIL_ADDRESS>and she will reach out and handle your case with the unmost professionalism and discretion. If you're not comfortable emailing only Aurelia, you can reach out to the science lab team as a whole<EMAIL_ADDRESS>
Likewise, feel free to change the language if you think an alternate articulation is best.

I think @auremoser has made the changes mentioned above in the https://github.com/codeforscience/sciencefair/tree/documentation branch

Yes, sorry @blahah, if I messed that up, I checked out the PR but pushed the changes tithe master documentation branch and not the forked one :/ apparently.

@auremoser not at all, that's perfect because when we merge documentation into master it will mark this PR as merged and close it :)
You have come to a clearing in the repo. There are three items resting on the ground in the clearing:
🏆 🍪 🌵
A worn scrap of parchment is pinned to the ground in front of the items. it reads:

You may choose one item to take with you as you continue on your quest.
Choose wisely - a poor choice may lead to misery, while an apt choice will open the door to great riches.

Wow, well if it's survival we're going for I think the decision is obvious.
(after only 8 hours of contemplation)

@auremoser only 9 months late, but: 🌵

At long last, we're ready to merge this! Thanks so much @npch :)


js-test-repo to 0.0.6

Promote js-test-repo to version 0.0.6

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Special handling of functions that produce Optional output

A function that maps Foo to Optional<Bar> is like a shorthand for a Flux.filter() on the output of the flux function.

I have spiked it recently and can't seem to see much value at the moment.
For example, if user provides a signature of Function<Foo, Optional<Bar>>, then even if we filter implicitly, the signature of the function won't change and user will still receive Optional which (if he/she doesn't know about "our" filtering) then would still be interrogated/filtered by such user.
Anyway, i think it needs more time to bake.

I am going to close it as part of the clean up of old issue that get no traction. Feel free to reopen or open new one with more details


Invoke-RefreshGraphTokens "client_id" incorrect

Within $refreshbody on line 418 of GraphRunner.ps1, the "client_id" is not set to the $ClientID parameter. It is instead set to a static value. This throws an error if the refreshToken uses a different ClientID than the static value and you attempt setting the ClientID parameter when using Invoke-RefreshGraphTokens.
Current:
        "client_id" = "d3590ed6-52b3-4102-aeff-aad2292ab01c"
Recommendation:
        "client_id" = $ClientID
https://github.com/dafthack/GraphRunner/blob/main/GraphRunner.ps1#L418

Fixed!! Thank you.


oap alarm config can support i18n？

Please answer these questions before submitting your issue.

Why do you submit this issue?
[ ] Question or discussion
[ ] Bug
[ ✓ ] Requirement
[ ] Feature or performance improvement

Question

What do you want to know?

Bug

Which version of SkyWalking, OS, and JRE?

Which company or project?

What happened?
If possible, provide a way to reproduce the error. e.g. demo application, component version.

Requirement or improvement

Please describe your requirements or improvement suggestions.

Right now, it can't. You could consider to contribute it. But the question would be, how to determine the language?

@wu-sheng its a good idea.

We could continue once you have real solution.


Some Matrix & String Questions

1) Implement strStr()
2)  1D array to 2D array
 3) Determine matrix can be obtained by rotation or not
4) Available captures for rook

@aritra-tech can i get this issue assigned plz

Sure @CS50X-RGB


Configuration Issue

Hello. I'm running into this issue in Program.cs > CreateHostBuilder() after adding the services.AddWidgetFilter() service registration to startup.cs and attempting to run the application. Does the WidgetFilter service have a required configuration for ApplicationUser that is different from that of the vanilla Kentico 13 .Net Core installation? This appears to be the case as I've not added any special configuration pertaining to Microsoft.AspNetCore.Identity.UserManager. Thank you!
Inner Exception 1:
InvalidOperationException: Error while validating the service descriptor 'ServiceType: XperienceCommunity.WidgetFilter.IWidgetPermissionFilter Lifetime: Scoped ImplementationType: XperienceCommunity.WidgetFilter.WidgetPermissionFilter': Unable to resolve service for type 'Microsoft.AspNetCore.Identity.UserManager`1[Kentico.Membership.ApplicationUser]' while attempting to activate 'XperienceCommunity.WidgetFilter.WidgetPermissionFilter'.
Inner Exception 2:
InvalidOperationException: Unable to resolve service for type 'Microsoft.AspNetCore.Identity.UserManager`1[Kentico.Membership.ApplicationUser]' while attempting to activate 'XperienceCommunity.WidgetFilter.WidgetPermissionFilter'.

Yes you need to set up authentication, as the filter has role based filtering.
You can see an example from our baseline below, look to the authentication section.
https://github.com/HBSTech/Kentico13CoreBaseline/blob/master/MVC/MVC/App_Start/StartupConfig.cs

Yes you need to set up authentication, as the filter has role based filtering.
You can see an example from our baseline below, look to the authentication section.
https://github.com/HBSTech/Kentico13CoreBaseline/blob/master/MVC/MVC/App_Start/StartupConfig.cs

Thanks for the pointer. I thought it was something like that. I'll go by the example and hopefully won't need to bother you on this anymore. I appreciate your responsiveness and direction. -Dave


Create RohanKumarSingh.md

Hi, I'm closing this as no updates in two weeks; feel free to reopen if you sign the CLA. Thanks!


docs(ssr): fix typo

"tot his" to "to this"

:tada: This PR is included in version 3.3.0 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

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SSLHandshakeException getting after build jdk8 for linux x86

I built the jdk8u312 for Linux x86 using https://github.com/adoptium/temurin-build and when I trying to using on the app in my CentOS7 x64, I'm getting this issue:

But if I use the JRE from  https://github.com/adoptium/temurin8-binaries/releases/download/jdk8u302-b08/OpenJDK8U-jre_x64_linux_hotspot_8u302b08.tar.gz I don't get the issue.
Before build the binaries I the script for creating new certs:  https://github.com/adoptium/temurin-build/blob/0829acbf6e6118b8afe50e5a554e2c144cfa7999/security/README.md
and then run this command ./makejdk-any-platform.sh -J /usr/lib/jvm/java-1.7.0-openjdk --custom-cacerts true --build-variant hotspot jdk8u
Am I doing something wrong?  I suspect that could be a flag that I'm missing or something like that on the build process

I made this issue before: https://github.com/adoptium/temurin-build/issues/2783, but It was closed even before waiting for my answer or waiting for confirmation that is working/fixing now

Reopened the original


2.x – Rename "Getting Started Theme" to "Learn Timber Theme"

Ticket: https://github.com/timber/learn-timber-theme/issues/1
Issue
"Learn Timber Theme" is a clearer name than "Getting Started Theme"
Solution
Let’s rename it.
Impact
None.
Usage Changes
None.
Considerations
None.
Testing
I tested the composer create-project command. It works.

Please add timber/getting-started-theme to Composer "replace".

Please add timber/getting-started-theme to Composer "replace".

@szepeviktor I didn’t know about that one, will do 👍

@jarednova The hase been renames: so Merge or merge!


Fix vulnerabilities

This release fixes the following vulnerabilities by updating dependencies:

Vulnerability CVE-2024-23342 in transitive dependency via localstack to ecdsa.
Vulnerability CVE-2024-5206 in dependency scikit-learn versions below 1.5.0 caused by sensitive data leakage.
Vulnerability CVE-2024-37891 in transitive dependency via boto3 to urllib3 in versions below 2.2.2 caused by proxy-authorization request header not to be stripped during cross-origin redirects.
Vulnerability CVE-2024-35195 in dependency requests in versions below 2.32.0 caused by requests Session object not verifying requests after making first request with verify=False.

The release ignores the following vulnerabilities

Vulnerability CVE-2024-33663 in transitive dependency via localstack to python-jose 3.3.0 caused by algorithm confusion with OpenSSH ECDSA keys as there is no newer version of python-jose available and the dependency only affects tests.

Blocked by https://github.com/exasol/script-languages-container-tool/issues/216

Blocked until releases of TE and SME arepublished to pypi


i18n(fr): update guides/media/cloudinary.mdx

Description (required)
Adds changes from #9550 and #9659 to the French translation of guides/media/cloudinary.mdx

Related issues & labels (optional)

Suggested label: i18n

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OSSM-2152: Initial support for 2.4

What's the strategy_v2_4 used for ? Should we deprecate maistra v1 apis in 2.4 operator ?

IDK. This is just an initial port of 2.4 so that we have initial builds for it in brew. Further improvements (like dropping support for 1.1, 2.0, etc), updating SDK, etc will come after this PR is merged.


Optimize performance for large datasets

I am trying to analyze a 500MB csv file and rendering time takes minutes on a strong Windows machine. Sometimes the plot will render the first time in a few minutes, but never again (if I change the x-axis for example). Is it possible to launch this tool without analyzing/rendering by default? That way I can choose my options and then render once? Also, is anyone working on improving the performance of this tool?

Hi @drewkerwin, thanks for the feedback. When creating a chart, we create a dependency graph of all the variables used to specify the layout. We keep this graph in memory to facilitate a more responsive interaction when a user changes a slider for example, we don't recompute the entire layout, just the parts that change based on the slider value:

As you've noticed, this optimization becomes a liability for large datasets, as it consumes more resources. In these cases, we would need to opt to degrade interactivity, and recompute the entire layout.

Thank you @danmarshall, also note that a little pre-processing in python to reduce the size of the CSV help a great deal...e.g. extracting only the relevant columns into a modified CSV.


Runtime type checking

What do you guys think about adding a type system to some of the endpoints...?
The tcomb project is a very cool runtime type checking system similar to flow. It might make it easier to reason about the flow of the code.

We're adding Flow: https://github.com/gaearon/redux/pull/254
Does this help? It's not runtime but will help doc-wise.

Yeah, compile-time is safer than runtime checks anyways.

Can try out https://github.com/babel-plugins/babel-plugin-flow-comments as well now


[-Wsign-compare] warning fixes batch 14

@mihaimaruseac

@mihaimaruseac

@mihaimaruseac  int64 changed to `int64_t.

Closing as it has been handled by new PRs.


The models would be evaluated as incoherent.

I found an issue that consequence models would be evaluated as incoherent.
There are 2 cases.

API call for gathering dataset for evaluation of coherent. (Due to security issue, stop api call & empty dataset return.)
OPENAI api key expired.

These are sample examples of what I am saying.
Thanks

Can you please provide specific details on why this would differ from https://github.com/impel-intelligence/dippy-bittensor-subnet/issues/73 ?
Also there is no direct proof of these claims:
OPENAI api key expired -> if this were the case, all coherence evaluations would be failing
API call for gathering dataset for evaluation of coherent. (Due to security issue, stop api call & empty dataset return.) -> please provide a specific code solution if this is the case, otherwise we can address this as part of https://github.com/impel-intelligence/dippy-bittensor-subnet/issues/64 . I have updated the title to better reflect the root cause

I don't think it's because of openai api key or API call expiration.
As you can see on above image, if the models are submitted at once in a very short time, the validators would be glitched.
In that case, there's probability to pass the models' evaluation.

It could be.
I found another possibility.
What if the validators' openai request exceeds limit?
In that case, it's truely possible to get 0 coherent score.

Some clarification:

I believe there is some confusion regarding receiving a real coherence score of 0 vs what appears to be a coherence score of 0. In the code, there is a minimum threshold of 0.95. Any coherence score that falls below (ie. 0.9444....) would be marked down to 0
Given the above, the real core issue here is not a specific error in the API (which is monitored), but rather the specific variance of the score.

Addressed via this issue: https://github.com/impel-intelligence/dippy-bittensor-subnet/issues/64
There have been no erroneous incoherent model errors in the past 24 hours of scoring since the change was applied.


fix: style updates and bugfixes for multi y axis

Overview
Bugfix for multi y axis not a number display.
Style fixes for multi y axis legend. Fix spacing and font sizing.
Legal
This project is available under the Apache 2.0 License.

Looks good!