Simplify and optimize Util.falsey?

I noticed that there was a new utility function that encapsulated the JMESPath rules for false. It's great that an important definition like that is not repeated over and over again.
However, I think the implementation for an often used function like this needs to take performance into account. Using literals in Ruby is problematic since they're allocated on each call, leading to unnecessary garbage being created.
I rewrote the code to avoid allocations, and also simplified it slightly.
These are benchmarks for a few different inputs before these changes (the full benchmark code is below).
                                     user     system      total        real
true                             0.450000   0.010000   0.460000 (  0.458666)
false                            0.120000   0.000000   0.120000 (  0.118656)
{}                               0.440000   0.000000   0.440000 (  0.437886)
[]                               0.730000   0.000000   0.730000 (  0.739866)
["a"]                            0.960000   0.000000   0.960000 (  0.968578)
{"a"=>"b"}                       1.080000   0.000000   1.080000 (  1.085161)
#<Object:0x007fe6c4088c90>       0.460000   0.010000   0.470000 (  0.462774)
nil                              0.090000   0.000000   0.090000 (  0.095598)
#<struct Foo one=nil, two=nil>   0.850000   0.000000   0.850000 (  0.848883)
#<struct Foo one=1, two=2>       0.860000   0.000000   0.860000 (  0.866559)

And these are the numbers with the changes applied:
                                     user     system      total        real
true                             0.340000   0.000000   0.340000 (  0.341450)
false                            0.090000   0.000000   0.090000 (  0.088636)
{}                               0.160000   0.000000   0.160000 (  0.159498)
[]                               0.170000   0.000000   0.170000 (  0.166334)
["a"]                            0.470000   0.000000   0.470000 (  0.479173)
{"a"=>"b"}                       0.630000   0.000000   0.630000 (  0.637846)
#<Object:0x007fddd204bdb8>       0.360000   0.010000   0.370000 (  0.367299)
nil                              0.090000   0.000000   0.090000 (  0.093467)
#<struct Foo one=nil, two=nil>   0.540000   0.000000   0.540000 (  0.543378)
#<struct Foo one=1, two=2>       0.530000   0.000000   0.530000 (  0.536465)

Notice especially the difference for the non-empty array hash cases. Checking that a hash is empty is much better than checking whether or not it is equal to another hash.
The benchmarks of course don't capture the most important aspect of this, GC pressure.
This is the full benchmark code:
Foo = Struct.new(:one, :two)

Benchmark.bmbm do |x|
  [
    true,
    false,
    {},
    [],
    ['a'],
    {'a' => 'b'},
    Object.new,
    nil,
    Foo.new,
    Foo.new(1, 2),
  ].each do |thing|
    x.report(thing.inspect) { 1_000_000.times { JMESPath::Util.falsey?(thing) } }
  end
end

We're have systems that are doing thousands, of not tens of thousands of JMESPath searches per second, so every little bit of performance counts.

Thanks for the tuning work. This should be part of the 1.3 release shortly.


Implement Tofino-specific TDI target

Move Tofino-specific files from bin/tdi to bin/tdi/tofino and from lib/tdi to lib/tdi/tofino.

Change 'tdi' in file names to 'tofino'.
Change 'Tdi' in class names to 'Tofino'.
Update Bazel build files.

Signed-off-by: Derek G Foster<EMAIL_ADDRESS>

Did you get a chance to compile against the SDE? We will need to modify the build instructions in the README.

Did you get a chance to compile against the SDE? We will need to modify the build instructions in the README.

I've built against the Tofino SDE using both CMake and Bazel. I've also run the Bazel regression tests (bazel test //stratum/hal/lib/tdi/tofino:all --define target-tofino).
We'll want to create a separate README document for DPDK, to allow for differences in such things as setup procedures and how one obtains the SDE. These will become increasingly divergent when we add support for MEV.


ModalNavigator leads to crash

If you use ModalNavigator inside iOS you got need event loop error

Fixed in 1.3


CopyForwarding - small redesign to fix bugs.

Copy forwarding was designed with some assumptions about symmetry of
operations. If copy_value/destroy_value are expanded somewhere for a given
value, then they should be expanded everywhere. The pass took a conservative
approach to SIL patterns that were guaranteed safe, and bailed out on unknown
patterns. However, due to some over-aggressive code factoring, the assumption
wasn't being checked in one corner case.
This redesign makes a clear distinction between the requirements for forward
vs. backward propagation.
Fixes rdar://35646292 Swift CI: resilience bot seg faults in
stdlib/RangeReplaceable.swift.gyb

@swift-ci test.

@aschwaighofer I need a CCC review. This is a lot of code to review in one diff. Rather than figure it out on you own I can give you a walk through.

@swift-ci test.

Build failed
Swift Test Linux Platform
Git Sha - 2aa112f024a349d611b87db37fa71268e930cd59

Build failed
Swift Test OS X Platform
Git Sha - 2aa112f024a349d611b87db37fa71268e930cd59

@aschwaighofer I added a related commit to this PR based on your in person review. Ok for CCC?

4.1 CCC Info
Explanation: At -O, the CopyForwarding optimization pass could shrink
the lifetime of a copied value so that it us destroyed before a load
(use-after-free).
Scope: The SIL pattern was exposed by compiling in resilience mode. However, I can't guarantee the the problem only occurs in resilience mode.
Radar: rdar://problem/35646292 Swift CI: resilience bot seg faults in stdlib/RangeReplaceable.swift.gyb
Risk: The fix is a large change to make the pass more robust, hopefully fixing a category of bugs rather thean just a specific case. A large change could have introduced new bugs.
Testing: New unit tests are added. The resilience bot was failing and now passes. No change in benchmarks. All of the usual testing/living on is useful and important here.
4.1 PR https://github.com/apple/swift/pull/13407

@swift-ci nominate
Explanation: At -O, the CopyForwarding optimization pass could shrink
the lifetime of a copied value so that it us destroyed before a load
(use-after-free).
Scope: The SIL pattern was exposed by compiling in resilience mode. However, I can't guarantee the the problem only occurs in resilience mode.
Origin: The bug has been present for years but is only exposed in resilience mode.
Radar: rdar://problem/35646292 Swift CI: resilience bot seg faults in stdlib/RangeReplaceable.swift.gyb
Risk: The fix is a large change to make the pass more robust, hopefully fixing a category of bugs rather thean just a specific case. A large change could have introduced new bugs.
Testing: New unit tests are added. The resilience bot was failing and now passes. No change in benchmarks. All of the usual testing/living on is useful and important here.


Fix multiple potential race condtions due to improper mutex usage.

This PR contains fixes for potential race conditions due to improper mutex usage in the hash table class.

Superseded by recent decisions.


Mouse actions on prompt generates error on one-cli execution

Found a bug? Please fill out the sections below. 👍
Issue Summary
A summary of the issue.
Steps to Reproduce the Problem

type one workspace change
when the prompt comes up with a list,  hit any part of the prompt with mouse cursor.
error:
Traceback (most recent call last):
File "/usr/local/bin/one", line 8, in
sys.exit(main())
File "/usr/local/lib/python3.8/site-packages/one/main.py", line 5, in main
cli()
File "/usr/local/lib/python3.8/site-packages/click/core.py", line 829, in call
return self.main(*args, **kwargs)
File "/usr/local/lib/python3.8/site-packages/click/core.py", line 782, in main
rv = self.invoke(ctx)
File "/usr/local/lib/python3.8/site-packages/click/core.py", line 1259, in invoke
return _process_result(sub_ctx.command.invoke(sub_ctx))
File "/usr/local/lib/python3.8/site-packages/click/core.py", line 1259, in invoke
return _process_result(sub_ctx.command.invoke(sub_ctx))
File "/usr/local/lib/python3.8/site-packages/click/core.py", line 1066, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "/usr/local/lib/python3.8/site-packages/click/core.py", line 610, in invoke
return callback(*args, **kwargs)
File "/usr/local/lib/python3.8/site-packages/one/commands/workspace.py", line 38, in change
f.write('WORKSPACE=' + answers['workspace'] + '\n')
KeyError: 'workspace'

Any other relevant information. For example, why do you consider this a bug and what did you expect to happen instead?
Specifications

Version: Run one --version:   one, version 0.5.1
Platform: (macOS / Linux):  macOs
Installation method: (Binary / PyPI):  PyPI

same here

Hi @Renatovnctavares and @lzrocha, can you share the one.yaml file?

Found that this is an error in the lib PyInquirer that prompts the questions, they already fixed it but still no new release.
https://github.com/CITGuru/PyInquirer/issues/41

When they release the new version from master we will just need to update the module and replace:
answers['workspace']
# to
answers.get('workspace', 'default')


Unknown CMake command "idf_component_optional_requires". (IDFGH-7882)

IDF 4.3
IDE: Visual Studio Code
Using latest IDF on Visual Studio Code
When building pre_encrypted_ota from examples folder:
URL: https://github.com/espressif/esp-idf/tree/master/examples/system/ota/pre_encrypted_ota
Expected Behavior
Build example
Actual Behavior
CMake Error from esp/esp-idf/examples/common_components/protocol_examples_common/CMakeLists.txt:20 (idf_component_optional_requires):
Unknown CMake command "idf_component_optional_requires".
Steps to reproduce

git clone repository: https://github.com/espressif/esp-idf/tree/master/examples/system/ota/pre_encrypted_ota
Build project

Hi @5abina, it seems that you are trying to compile an example from the master branch of this repository with IDF v4.3. In most cases this combination won't work, since examples are generally not backwards compatible. You have to use examples from the same version of ESP-IDF as the one you have installed.

Hello @igrr. Thank you for your help.
I have just built a binary using tools from the master branch. The problem has been solved.
Kind regards
Daniel

Thanks for reporting, and glad to hear the issue has been solved, feel free to reopen.


Error with "textarea" element type (OSX / Chrome 37)

For some reason if the "textarea" field is selected it is wiping out the data associated with anything stored in that field. Setting it back to just "text" seems to solve the issue but the input area isnt ideal.
Screencast:
http://youtu.be/KwoXbfOXy9w

Would love to see this fixed!

@dereklieu This is still an issue, unfortunately.

@dereklieu Ignore the last comment. Had not run gulp. https://github.com/prose/prose/pull/862 fixes the textarea issue for me, e.g.:
https://github.com/phillipadsmith/starter/commits/gh-pages/_posts/2015-08-08-test-metadata-save.md

Textarea fields are working as of #862 and deployed to prose.io.


Model usage

Hello!
I have recently came across this work and I am curious about the usage of the model. Can you give a demo for english language?
Thank you!

Hello! I have recently came across this work and I am curious about the usage of the model. Can you give a demo for english language? Thank you!

You can first pre-train a English GBERT using the following command

python monolingual_GBERT_pretrain/GBERT_pretraining.py --pretraining language eng

This produces a vocabulary and a GBERT checkpoint. The tokenizer uses torchtext tokenizer. you can refer to the code of GBERT_pretraining.py to implement GBERT for other usages.

You can then train a GBERT based G2P model using the pre-trained GBERT checkpoint, such as GBERT-finetuning model or GBERT-attention model, the command is

python monolingual_G2P_model/GBERT_finetuning.py --hyperparameter

The hyperparameters are given in the Implement Details part of the Readme.md file, you can use our given hyperparameters to reproduce our experimental results, or tune these hyperparameters for your G2P dataset.

I understood your pre-training and fine-tuning recipes as they were very well-structured and concise. Using them, I successfully created the pytorch model for english.
The problem I am facing now is in inferencing.
As I am new to the field, I have taken help from some articles on how to load a pytorch model for inferencing
([https://stackoverflow.com/questions/49941426/attributeerror-collections-ordereddict-object-has-no-attribute-eval])
As you can see in the article's answer, for inferencing we require the class which defines the structure of the model. But in your fine-tuning training file, there are many classes. I chose Seq2Seq() for the same but it's giving the following error:
Traceback (most recent call last):
File "model_test.py", line 10, in
model = Seq2Seq()
TypeError: init() missing 4 required positional arguments: 'decoder', 'trg_pad_idx', 'output_dim', and 'device'
This the code which I have written for inferencing:
`import torch
from monolingual_G2P_model.GBERT_finetuning import Seq2Seq
PATH = './monolingual_medium_resource/torch_models/g2p-model_eng_without_g2p_dev_and_test_word_Transformer_with_BERT_pretrain_Encoder_batch_size256_gelu_hid_dim128_new_pretrain.pt'
model = Seq2Seq()
model.load_state_dict(torch.load(PATH))
model.eval()`
Moreover, when I import the GBERT_finetuning file, it begins to train the model again as the code for training is global and not under any method.
My ultimate use case is to generate a phonetic expansion for any given input word using the model which I have generated. Can you provide some suggestion regarding the same?

I understood your pre-training and fine-tuning recipes as they were very well-structured and concise. Using them, I successfully created the pytorch model for english. The problem I am facing now is in inferencing. As I am new to the field, I have taken help from some articles on how to load a pytorch model for inferencing ([https://stackoverflow.com/questions/49941426/attributeerror-collections-ordereddict-object-has-no-attribute-eval])
As you can see in the article's answer, for inferencing we require the class which defines the structure of the model. But in your fine-tuning training file, there are many classes. I chose Seq2Seq() for the same but it's giving the following error:
Traceback (most recent call last):
  File "model_test.py", line 10, in <module>
    model = Seq2Seq()
TypeError: __init__() missing 4 required positional arguments: 'decoder', 'trg_pad_idx', 'output_dim', and 'device'

This the code which I have written for inferencing:
import torch
from monolingual_G2P_model.GBERT_finetuning import Seq2Seq

PATH = './monolingual_medium_resource/torch_models/g2p-model_eng_without_g2p_dev_and_test_word_Transformer_with_BERT_pretrain_Encoder_batch_size256_gelu_hid_dim128_new_pretrain.pt'

model = Seq2Seq()
model.load_state_dict(torch.load(PATH))
model.eval()

Moreover, when I import the GBERT_finetuning file, it begins to train the model again as the code for training is global and not under any method. My ultimate use case is to generate a phonetic expansion for any given input word using the model which I have generated. Can you provide some suggestion regarding the same?

To load the Se2seq model, You are required to add this part code to your code, which will initialize the model parameters.
For loading the GBERT_fintuning module, you need to reorganize the code of GBERT_finetuning.py, put the preprocessing and checkpoint loading code into a init method, the inference code in some function and load. Because our code is mainly used for academic purpose.
An advice for using our model for phonetic expansion is to pre-train our GBERT with larger dictionary or train our GBERT_finetuning model with larger G2P dataset to improve the open domain G2P performance, since our model is only pre-trained with ~10k dictionary and trained with 8k G2P dataset, you may find our model not work well for any given input words.

This is really helpful. Thanks a lot :)


No support for lights on the Alienware Steam Machine

gamerOS currently doesn't support changing the color and intensity of the lights on the outside of the Alienware Steam Machine. On SteamOS this does work.

I can implement this later, since I know how it works. For now it isn't high on the priority list, though, especially since I'm currently seeing kernel panics on SteamOS because of this.

#57 solves this issue


add custom repr to Place and GooglePlacesSearchResult

I just came across this project. Thanks to all of you who've been putting it together. As I start using it, I'll see if there are ways I can help out.
One thing I noticed is that the Place and GooglePlacesSearchResult classes don't override object's repr. I know it's a minor aesthetic thing, but it would be nice to have.
For Place it could look something like <Place name=[obj.name]> (using the name attribute). What do you think?

Hey scottcode - Please feel free to submit a pull request to the development branch for this. It's a useful feature for sure.


NAT rules for ExternalCIDR (4/4)

Description
This PR adds a new controller that reconciles the resource NatMapping. It ensures the appropriate set of NAT rules for supporting ExternalCIDR traffic is in place and updated.

/ok-to-test

/rebase

/rebase


Camera not updating position

Do you want to request a feature or report a bug?
Bug

What is the current behavior?
Camera position not changing, rotation changes but doesn't look like it is working
If the current behavior is a bug, please provide the steps to reproduce.
Open location based example from ar-js github, allow camera and location

https://ar-js-org.github.io/AR.js-Docs/location-based-aframe/

Please mention other relevant information such as the browser version, Operating System and Device Name
Browser version: Chrome 111.0.5563.57
Operating System: Android 13
Device name: Samsung Galaxy Note20 5G
What is the expected behavior?
Object should not be fixed to camera and camera should update it's position
I don't know why is this happening, tried multiple examples.
Also i've seen that DeviceOrientationControls from Three.js is deprecated from version 0.133. I don't know if that causes an issue, should i build npm packages. Also , i don't know if attribute look-controls does anything when using phone camera or it is only for VR but in inspect of the example code a-camera gets attribute look-controls-enabled:"false".

Are you using the latest from Ar.js? Does this live example works for you?


Epinio/namespace validation

Summary
Fixes https://github.com/epinio/ui/issues/111

Looks good! I wonder if we should have a look at this, when the form is invalid the Create button it's still actionable, we might want to disable it?

Agree, I forgot to to do the change!


consider releasing output data?

Hi, since code-davinci-002 is deprecated by openai, I wonder will you consider release your output data run by your codex_gsm8k_complex.ipynb script, whose outputs on GSM8K test set are definitely important to many researchers.

Agree!


Enable tests for all JSON white space normalization

This fixes https://github.com/rapidsai/cudf/issues/15280
This depends on https://github.com/rapidsai/cudf/pull/16759

build


run_game.py Attribute Error

Hi,
I use pypy3-2.4.0 on windows and no success to install curse on it. I have try the run_game.py script but I have some error.
PS C:\hearthbreaker-master\hearthbreaker-master> pypy .\run_games.py
Traceback (most recent call last):
File ".\run_games.py", line 57, in
do_stuff()
File ".\run_games.py", line 52, in do_stuff
game = Game([deck1, deck2], [RandomAgent(), RandomAgent()])
File "C:\hearthbreaker-master\hearthbreaker-master\hearthbreaker\engine.py", line 58, in init
self.players = [Player("one", decks[play_order[0]], agents[play_order[0]], self),
File "C:\hearthbreaker-master\hearthbreaker-master\hearthbreaker\engine.py", line 316, in init
self.hero = deck.hero.create_hero(self)
AttributeError: 'int' object has no attribute 'create_hero'

Hi Olivier,
Seems like curses and pypy don't work together on windows.  You could POSSIBLY compile it together yourself, but that's going to be tricky.  Hearthbreaker runs much faster on Cython anyhow.
For your other error, I've uploaded a fix that ought to solve your problem.


Fix/typesupport override

Fix duplication in "%s_type_support.cpp" package name when trying to build c_ros2_interface() and cpp_ros2_interface() versions of the same message

Solved in https://github.com/EddyGharib/rules_ros2/pull/6


Make the first-level left nav items clickable

Description:
Need to make the first-level left nav items clickable. Currently, those pages aren't getting indexed due to this. For example, we should have the URL https://wso2.com/ballerina/vscode/docs/get-started for it to be indexed.
Upgrading to the latest MKDocs Material theme will sort this. For example, see https://wso2.com/asgardeo/docs/get-started/.
Instructions for upgrading can be found in https://squidfunk.github.io/mkdocs-material/upgrade/.
Suggested Labels:

Suggested Assignees:

Affected Product Version:
OS, DB, other environment details and versions:
Steps to reproduce:
Related Issues:

Closing as this is not applicable in the new docs moved to the Ballerina website at: https://ballerina.io/learn/vs-code-extension/


Build/Install Fail

I followed the reference from there ,  on ubuntu 14.04 x64

download the project from github 2) mvn install  (mvn2 actually)

But error jumped out when building
Downloading: http://oss.sonatype.org/content/repositories/postgis-releases/com/sun/jersey/jersey-bundle/1.8/je[8/1821]
dle-1.8.pom
[INFO] Unable to find resource 'com.sun.jersey:jersey-bundle:pom:1.8' in repository sonatype-postgis-releases (http://
oss.sonatype.org/content/repositories/postgis-releases)
Downloading: http://repo1.maven.org/maven2/com/sun/jersey/jersey-bundle/1.8/jersey-bundle-1.8.pom
21K downloaded  (jersey-bundle-1.8.pom)
Downloading: http://maven.glassfish.org/content/groups/glassfish/com/sun/jersey/jersey-project/1.8/jersey-project-1.8.
pom
178b downloaded  (jersey-project-1.8.pom)
[WARNING] *** CHECKSUM FAILED - Checksum failed on download: local = '81ffbd1712afe8cdf138b570c0fc9934742c33c1'; remote = '
<title>301' - RETRYING
Downloading: http://maven.glassfish.org/content/groups/glassfish/com/sun/jersey/jersey-project/1.8/jersey-project-1.8.
pom
178b downloaded  (jersey-project-1.8.pom)
[WARNING] *** CHECKSUM FAILED - Checksum failed on download: local = '81ffbd1712afe8cdf138b570c0fc9934742c33c1'; remot
e = '
<title>301' - IGNORING
[INFO] ------------------------------------------------------------------------
[ERROR] BUILD ERROR
[INFO] ------------------------------------------------------------------------
[INFO] Cannot build project dependency tree for project: MavenProject: org.n52.oss:service:0.6 @ /root/OpenSensorSearc
h/service/pom.xml

Not a v4.0.0 POM. for project com.sun.jersey:jersey-project at /root/.m2/repository/com/sun/jersey/jersey-project/1.8/
jersey-project-1.8.pom
[INFO] ------------------------------------------------------------------------

When fetching POM from https://maven.java.net/content/groups/glassfish/com/sun/jersey/jersey-project/1.8/jersey-project-1.8.pom . In web browser this page returns a 404 page.
But in your folder of your PC, after mvn install , actually you've gotten a file
file jersey-project-1.8.pom looks like:

<title>301 Moved Permanently</title>

301 Moved Permanently

nginx

Obviously this is not a XML file. And the building procedure has been stopped from here.
How to fix this? Or any ideas about the https://maven.java.net/content/groups/glassfish/com/sun/jersey/jersey-project/1.8/jersey-project-1.8.pom  ?

As if the problem is solved. I replace the file with this one http://download.java.net/maven/2/com/sun/jersey/jersey-project/1.8/jersey-project-1.8.pom  I think there should be a fix to this.

Can you post your maven settings file, please?
Also, please update the code and run mvn clean install again.

Actually there is not a settings.xml in the folder /root/.m2/ . And I have not change the default settings yet. It's a brand-new mvn.
Yet I have found this https://maven.apache.org/settings.html , but I haven't known what to change to fix this.
I did
mvn clean install And another error came out:
[INFO] Parsing Dependencies for: Open Sensor Search Parent Project                                            [31/138]
[INFO] Parsing Dependencies for: Open Sensor Search common classes
[INFO] Parsing Dependencies for: SIR JSON Bindings
[INFO] Parsing Dependencies for: SIR common classes
[WARNING] Missing POM for org.n52.sensorweb:52n-xml-wrs-v101:jar:1.1.6-SNAPSHOT
[WARNING] Missing POM for org.n52.sensorweb:52n-xml-sir-v032:jar:1.1.6-SNAPSHOT
[WARNING] Missing POM for org.n52.sensorweb:52n-xml-sor-v031:jar:1.1.6-SNAPSHOT
[WARNING] Missing POM for org.n52.sensorweb:52n-xml-sps-v100:jar:1.1.6-SNAPSHOT
[WARNING] Missing POM for org.n52.sensorweb:52n-xml-sos-v100:jar:1.1.6-SNAPSHOT
[WARNING] Missing POM for org.n52.sensorweb:52n-xml-kml-v220:jar:1.1.6-SNAPSHOT
[WARNING] Failed to find license info for: org.n52.sensorweb:52n-xml-wrs-v101:jar:1.1.6-SNAPSHOT:compile
[WARNING] Failed to find license info for: org.n52.sensorweb:52n-xml-sir-v032:jar:1.1.6-SNAPSHOT:compile
[WARNING] Failed to find license info for: org.n52.sensorweb:52n-xml-sor-v031:jar:1.1.6-SNAPSHOT:compile
[WARNING] Failed to find license info for: org.n52.sensorweb:52n-xml-sps-v100:jar:1.1.6-SNAPSHOT:compile
[WARNING] Failed to find license info for: org.n52.sensorweb:52n-xml-sos-v100:jar:1.1.6-SNAPSHOT:compile
[WARNING] Failed to find license info for: org.n52.sensorweb:52n-xml-kml-v220:jar:1.1.6-SNAPSHOT:compile
[INFO] Parsing Dependencies for: Open Sensor Search Service
[INFO] Parsing Dependencies for: Open Sensor Search Website
[INFO] Parsing Dependencies for: AR Open Sensor Search Service
[INFO] Parsing Dependencies for: SOR common
[INFO] Parsing Dependencies for: Sensor Observable Registry
[ERROR] Failed to find Licenses for the following dependencies:
[ERROR]         org.n52.sensorweb:52n-xml-kml-v220:jar:1.1.6-SNAPSHOT:compile
[ERROR]         org.n52.sensorweb:52n-xml-sir-v032:jar:1.1.6-SNAPSHOT:compile
[ERROR]         org.n52.sensorweb:52n-xml-sor-v031:jar:1.1.6-SNAPSHOT:compile
[ERROR]         org.n52.sensorweb:52n-xml-sos-v100:jar:1.1.6-SNAPSHOT:compile
[ERROR]         org.n52.sensorweb:52n-xml-sps-v100:jar:1.1.6-SNAPSHOT:compile
[ERROR]         org.n52.sensorweb:52n-xml-wrs-v101:jar:1.1.6-SNAPSHOT:compile
[ERROR] Try adding them to a 'licenseMapping' file.
[ERROR] A stub license-mapping.xml file containing the unresolved dependencies has been written to: /root/OpenS[2/138]
arch/target/license-mappings.xml
[INFO] ------------------------------------------------------------------------
[INFO] Reactor Summary:
[INFO]
[INFO] Open Sensor Search Parent Project ................. FAILURE [5.057s]
[INFO] Open Sensor Search common classes ................. SKIPPED
[INFO] SIR JSON Bindings ................................. SKIPPED
[INFO] SIR common classes ................................ SKIPPED
[INFO] SOR common ........................................ SKIPPED
[INFO] Sensor Observable Registry ........................ SKIPPED
[INFO] Open Sensor Search Service ........................ SKIPPED
[INFO] Open Sensor Search Website ........................ SKIPPED
[INFO] AR Open Sensor Search Service ..................... SKIPPED
[INFO] ------------------------------------------------------------------------
[INFO] BUILD FAILURE
[INFO] ------------------------------------------------------------------------
[INFO] Total time: 5.990s
[INFO] Finished at: Wed Jun 10 17:12:11 UTC 2015
[INFO] Final Memory: 13M/170M
[INFO] ------------------------------------------------------------------------
[ERROR] Failed to execute goal org.jasig.maven:maven-notice-plugin:1.0.6:check (check-notice) on project parent: Faile
d to find Licenses for 6 artifacts -> [Help 1]
[ERROR]
[ERROR] To see the full stack trace of the errors, re-run Maven with the -e switch.
[ERROR] Re-run Maven using the -X switch to enable full debug logging.
[ERROR]
[ERROR] For more information about the errors and possible solutions, please read the following articles:
[ERROR] [Help 1] http://cwiki.apache.org/confluence/display/MAVEN/MojoFailureException

Just as it indicated, "[ERROR] Failed to find Licenses for the following dependencies: ", there has something to do with the Licenses.   This is different from the previous jersey error but it's still about the Licences.

Can you please attach the contents of the file mentioned in the error logs:
[ERROR] A stub license-mapping.xml file containing the unresolved dependencies has been written to: /root/OpenS[2/138] arch/target/license-mappings.xml


跑deepctr样例，auc只有0.5， 提示no gradient found

对deepctr样例，做了微小的改动，打印出auc，结果发现，auc一直在0.5上不去，同时还会提示全连接层的参数没有梯度，请问这是咋回事？
输出信息：

[WARNING]: no gradient found for var:dense/kernel under scope: , maybe not used?
[WARNING]: no gradient found for var:dense/bias under scope: , maybe not used?
[WARNING]: no gradient found for var:dense_1/kernel under scope: , maybe not used?
[WARNING]: no gradient found for var:dense_1/bias under scope: , maybe not used?
[WARNING]: no gradient found for var:dense_2/kernel under scope: , maybe not used?
[WARNING]: no gradient found for var:dense_2/bias under scope: , maybe not used?
loss:0.6931536,auc:0.50344515
loss:0.69737524,auc:0.49663246
loss:0.8758856,auc:0.50528824
……

改过后代码如下：

def train():
    batch = reader.read()
    sess = xdl.TrainSession()
    emb1 = xdl.embedding('emb1', batch['sparse0'], xdl.TruncatedNormal(stddev=0.001), 8, 1024, vtype='hash')
    emb2 = xdl.embedding('emb2', batch['sparse1'], xdl.TruncatedNormal(stddev=0.001), 8, 1024, vtype='hash')
    loss, auc, y = model(batch['deep0'], [emb1, emb2], batch['label'])
    train_op = xdl.SGD(0.5).optimize()
    log_hook = xdl.LoggerHook([loss,auc], "loss:{0},auc:{1}", 1)
    sess = xdl.TrainSession(hooks=[log_hook])
    while not sess.should_stop():
        sess.run(train_op)

@xdl.tf_wrapper()
def model(deep, embeddings, labels):
    input = tf.concat([deep] + embeddings, 1)
    fc1 = tf.layers.dense(
        input, 128, kernel_initializer=tf.truncated_normal_initializer(
            stddev=0.001, dtype=tf.float32))
    fc2 = tf.layers.dense(
        fc1, 64, kernel_initializer=tf.truncated_normal_initializer(
            stddev=0.001, dtype=tf.float32))
    fc3 = tf.layers.dense(
        fc2, 32, kernel_initializer=tf.truncated_normal_initializer(
            stddev=0.001, dtype=tf.float32))
    y = tf.layers.dense(
        input, 1, kernel_initializer=tf.truncated_normal_initializer(
            stddev=0.001, dtype=tf.float32))
    loss = tf.losses.sigmoid_cross_entropy(labels, y)

    y_pred = tf.sigmoid(y)
    _, auc = tf.metrics.auc(labels=labels, predictions=y_pred)

    return loss, auc, y

train()

模型写错了
y = tf.layers.dense(
input, 1, kernel_initializer=tf.truncated_normal_initializer(
stddev=0.001, dtype=tf.float32))
另外训练数据是完全随机生成的，请使用真实数据验证

模型写错了
y = tf.layers.dense(
input, 1, kernel_initializer=tf.truncated_normal_initializer(
stddev=0.001, dtype=tf.float32))
另外训练数据是完全随机生成的，请使用真实数据验证

模型写错了
y = tf.layers.dense(
input, 1, kernel_initializer=tf.truncated_normal_initializer(
stddev=0.001, dtype=tf.float32))
另外训练数据是完全随机生成的，请使用真实数据验证

不好意思，上面的代码是我调试的时候，忘记改回来了。问题181能否帮忙看看：https://github.com/alibaba/x-deeplearning/issues/181

模型写错了
y = tf.layers.dense(
input, 1, kernel_initializer=tf.truncated_normal_initializer(
stddev=0.001, dtype=tf.float32))
另外deepctr这个例子主要是说明api用法，训练数据是完全随机生成的，不保证收敛效果

我又想了下，即使是随机生成的数据，也不该每次auc都是0.5吧，我自己构造了个样本数据，里面有2条样本，其中1条是负样本，另1条是正样本，连续训练100个epochs，batch：2， 按理肯定会过拟合的，可是，auc依然是0.5。
样本数据：

skey1|gkey1|sparse0@759:0.762162,548:0.101924,716:0.194687,421:0.264081,261:0.404047,385:0.499228,449:0.959710,324:0.599362,731:0.446862;sparse1@546:0.951531,432:0.898802,\
105:0.783065,857:0.471639|deep0@0.662782,0.342298,0.468571,0.718452,0.713778,0.163456,0.887874,0.960262,0.044802,0.853923,0.400626,0.711758,0.221172,0.688655,0.571846,0.91\
1907,0.302197,0.677726,0.610022,0.452376,0.974598,0.304923,0.926549,0.402046,0.137225,0.083297,0.956003,0.084375,0.474048,0.183849,0.023845,0.262389,0.094568,0.385041,0.60\
4758,0.807893,0.546411,0.263949,0.620935,0.662830,0.221174,0.947233,0.609922,0.458325,0.163481,0.514653,0.258731,0.243340,0.949402,0.715515,0.525947,0.075673,0.805997,0.89\
9717,0.344329,0.145784,0.130369,0.234209,0.653809,0.297923,0.356226,0.412527,0.986982,0.645392,0.447851,0.945122,0.698532,0.270804,0.824928,0.355763,0.949162,0.339264,0.03\
5675,0.889754,0.001660,0.881021,0.087891,0.798518,0.472960,0.926075,0.475933,0.680346,0.125074,0.389097,0.480265,0.447326,0.554875,0.913568,0.213271,0.072741,0.928426,0.43\
3917,0.437505,0.196376,0.288154,0.271000,0.271465,0.677179,0.148842,0.208836,0.258478,0.554515,0.271461,0.493273,0.263461,0.014935,0.378840,0.726748,0.601786,0.327549,0.36\
7978,0.210795,0.902559,0.990410,0.990561,0.203781,0.976384,0.529055,0.439665,0.979978,0.919847,0.628117,0.531591,0.559527,0.854383,0.567795,0.669983,0.131906,0.810021,0.45\
7204,0.362367,0.241847,0.259656,0.095626,0.066626,0.639766,0.264775,0.555648,0.450152,0.721681,0.886644,0.001726,0.037867,0.024443,0.223571,0.082423,0.138201,0.767822,0.55\
4831,0.122466,0.142976,0.508260,0.504362,0.967684,0.447289,0.653109,0.651150,0.712938,0.553411,0.832021,0.061552,0.590981,0.704351,0.847320,0.522703,0.585140,0.965691,0.96\
2297,0.600640,0.508416,0.461186,0.252704,0.672691,0.631777,0.460096,0.574279,0.726332,0.429794,0.212263,0.237247,0.759556,0.078822,0.932726,0.200260,0.420823,0.578012,0.61\
4804,0.543419,0.448529,0.292871,0.238784,0.565181,0.316637,0.884232,0.672599,0.583305,0.608038,0.217691,0.100539,0.430582,0.476008,0.724872,0.480458,0.252887,0.330800,0.81\
4417,0.081829,0.570468,0.336623,0.598733,0.356824,0.500899,0.294857,0.760062,0.451524,0.641034,0.087247,0.289112,0.864109,0.854319,0.093764,0.378239,0.075818,0.455410,0.10\
4947,0.316122,0.462723,0.420934,0.647593,0.916033,0.684150,0.219117,0.449281,0.940042,0.845376,0.572261,0.072145,0.046971,0.692016,0.404238,0.668091,0.983969,0.686270,0.16\
3032,0.064395,0.463078,0.170263,0.834831,0.521397,0.390686,0.855010,0.123449,0.766170,0.223663,0.076849,0.653404|0|1544094735
skey2|gkey2|sparse0@856:0.352409,953:0.663148,523:0.722702,99:0.187631,753:0.935152,746:0.576277,458:0.820544,962:0.843274,325:0.527312,163:0.092034,620:0.242616,984:0.1610
33,166:0.154479,842:0.875578;sparse1@515:0.208188,1019:0.591209,145:0.156365,605:0.997317,1021:0.940796,729:0.273456,1005:0.047435,433:0.377895,1003:0.431236,500:0.032101,5
56:0.318865,145:0.522828,221:0.465735,685:0.818602,77:0.669590|deep0@0.999240,0.440470,0.047516,0.430420,0.634393,0.204206,0.665262,0.337837,0.169835,0.089634,0.878299,0.11
1705,0.523178,0.397379,0.832842,0.916505,0.390858,0.765615,0.332115,0.320150,0.951650,0.246418,0.512040,0.749791,0.673629,0.535592,0.865059,0.583392,0.691534,0.559879,0.246
394,0.822141,0.191856,0.138813,0.977759,0.104353,0.643541,0.891259,0.387623,0.138292,0.287816,0.773174,0.577388,0.399102,0.661399,0.436638,0.247339,0.000672,0.343219,0.2713
45,0.483667,0.311244,0.595922,0.712664,0.177472,0.232139,0.686599,0.857067,0.745553,0.588793,0.775999,0.510141,0.002143,0.174302,0.393704,0.840412,0.946845,0.016176,0.84112
9,0.698696,0.022466,0.431059,0.038136,0.526626,0.002277,0.137417,0.853434,0.192572,0.495922,0.832388,0.056398,0.564264,0.424322,0.520221,0.358680,0.811522,0.269201,0.204860
,0.697190,0.815236,0.587757,0.628998,0.290156,0.128817,0.977050,0.951258,0.501323,0.977213,0.705750,0.926940,0.904108,0.891195,0.229011,0.194533,0.544853,0.837290,0.627977,
0.806972,0.838957,0.867092,0.192085,0.943976,0.931445,0.915464,0.136756,0.966073,0.165868,0.208994,0.303334,0.992627,0.080906,0.722388,0.315930,0.413592,0.613303,0.562165,0
.844661,0.125174,0.963790,0.434821,0.734555,0.375568,0.309204,0.406794,0.928774,0.183238,0.905576,0.656561,0.300933,0.189950,0.558191,0.842550,0.747929,0.393342,0.866781,0.
298084,0.114384,0.530025,0.934307,0.026605,0.224099,0.074621,0.373608,0.696212,0.384710,0.658822,0.071645,0.514396,0.968043,0.660373,0.380076,0.062846,0.835793,0.160011,0.9
72219,0.552067,0.852591,0.498116,0.467868,0.871608,0.558435,0.296820,0.606116,0.869073,0.521347,0.962195,0.555587,0.718314,0.014050,0.584082,0.540957,0.390047,0.281304,0.02
6981,0.814965,0.136477,0.696427,0.486134,0.173861,0.349167,0.985647,0.426176,0.523973,0.942895,0.862479,0.206533,0.215264,0.095748,0.811125,0.339203,0.185293,0.321666,0.950
192,0.602032,0.185758,0.147267,0.725569,0.275365,0.454471,0.293140,0.850988,0.407612,0.778952,0.788696,0.849566,0.776480,0.259140,0.723711,0.859693,0.268434,0.498420,0.7846
41,0.465112,0.339739,0.813121,0.181796,0.996655,0.796091,0.264137,0.762158,0.731558,0.932281,0.776534,0.151321,0.153504,0.940771,0.205348,0.301515,0.098815,0.396543,0.83577
1,0.861178,0.180162,0.364074,0.570220,0.055760,0.072960,0.578157,0.777676,0.435500,0.865028,0.283787,0.616606,0.019386,0.217615,0.463562|1|1544094735


inbreast.py error

Hi Wentao - I'm making progress but now get the following error in inbreast.py at line 158:
for train, test in skf.split(x,y):
Error:
File "C:\Python35\lib\site-packages\sklearn\utils\validation.py", line 126, in
num_samples
" a valid collection." % x)
peError: Singleton array array(dict_values([0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1
1, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0,
, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 0
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 0,
0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0,
, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0
0, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 1,
, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0
0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0,
0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0,
, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0
0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,
, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1]), dt
e=object) cannot be considered a valid collection.

Hi, I think you should check the x, y shape in for train, test in skf.split(x,y):. Make sure it is consistent with your skf.split function. You know, these packages are always updating. Some interfaces may be changing. I think it will be easy to fix. Good luck. If you cannot fix it, tell me specific problems and more informations, I will spend some time on it. Thanks!

Thanks Wentao - I will let you know how I get on and much appreciated if
you can help get it working in Keras 2.0.
David
On 25 May 2017 at 20:51, Wentao Zhu<EMAIL_ADDRESS>wrote:

Hi, I think you should check the x, y shape in for train, test in
skf.split(x,y):. Make sure it is consistent with your skf.split function.
You know, these packages are always updating. Some interfaces may be
changing. I think it will be easy to fix. Good luck. If you cannot fix it,
tell me specific problems and more informations, I will spend some time on
it. Thanks!
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Hi Wentao, I have downgraded to keras 1.2 hoping it would help but I still get the same error message in for train, test in skf.split(x,y): and can't get pass this point.
David

BTW I have upgraded back to Keras 2.0 since I need it for other projects but I guess the error is based on something else though! It would be great if you could get an updated version working please?

check the skf version and skf.split function. You can just check the usage of the function as http://scikit-learn.org/stable/modules/cross_validation.html. Hope it helps you.

Hi Wentao,
I've spent some time looking at the error:
for train, test in skf.split(x,y): in run_cnn_k_new.py
In the usage description both x and y structure are the same as those input
here. The only thing I can think of is that mydict created from readLabel()
is formatting in a way skf.split() does not like when fed
into cvsplitenhance(fold, totalfold, mydict, valfold=valfold)
I can't see the difference between in data structure in their example and
the one here?
David
On 30 May 2017 at 20:55, Wentao Zhu<EMAIL_ADDRESS>wrote:

check the skf version and skf.split function. You can just check the usage
of the function as http://scikit-learn.org/stable/modules/cross_
validation.html. Hope it helps you.
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
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or mute the thread
https://github.com/notifications/unsubscribe-auth/ATg8ZHUftqbX4jEZGC2lEBMHYw-WvBxFks5r_HQcgaJpZM4NmXAq
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You can use type(x), type(y) to get the type of x, y easily. If it is consist with that of split(), you can send me email and I can help you debug if it is okay for you.

I get for type x, y:
<class 'dict_keys'>
<class 'dict_values'>
Does that help?

From the following document, x, y should be of numpy array like type.
http://scikit-learn.org/stable/modules/generated/sklearn.model_selection.StratifiedKFold.html#sklearn.model_selection.StratifiedKFold
split(X, y, groups=None)[source]
Generate indices to split data into training and test set.
Parameters:

X : array-like, shape (n_samples, n_features)

    Training data, where n_samples is the number of samples and n_features is the number of features.

    Note that providing y is sufficient to generate the splits and hence np.zeros(n_samples) may be used as a placeholder for X instead of actual training data.

y : array-like, shape (n_samples,)

    The target variable for supervised learning problems. Stratification is done based on the y labels.

groups : object

    Always ignored, exists for compatibility.

Returns:

train : ndarray

    The training set indices for that split.

test : ndarray

    The testing set indices for that split.

OK so far I have had to make the following changes to inbreast.py to update to Python 3:
In:
def cvsplitenhance(fold, totalfold, mydict, valfold=-1):
y2 = np.fromiter(iter(mydict.values()), dtype=int)
x2 = np.fromiter(iter(mydict.keys()), dtype=int)
for train, test in skf.split(x2,y2):
In:
def loaddataenhance(fold, totalfold, valfold=-1, valnum=60):
mydictkey = list(mydict.keys())
mydictvalue = list(mydict.values())
Also change xrange to range where applicable.
Now there is a problem with encoding/decoding the pickle files at:
im = cPickle.load(inputfile)
Error:
UnicodeDecoderError: 'ascii' codec can't decode byte 0xac in position 0: ordinal not in range(128)
I'm using 64-bit Windows 8.0 and when I use print(sys.getdefaultencoding()) I get utf-8
Any ideas how to solve this one?

It appears that forcing encoding='latin1' fixes the codec problem. That is:
im = cPickle.load(inputfile, encoding='latin1')
Also, all occurrences of W_regularizerl1l2() should be changed to W_regularizerl1_l2() in the model defs

Hi Wentao,
Error when running: run_cnn_k_new.py:
Negative dimension size caused by subtracting 11 from 3 for 'conv_1/convolution' with input shape: [?,3,227,227], [11,11,227,96]
I guess this is a dim_ordering issue between tensorflow and theano (i'm using tf backend) do you know a way to change this I've tried a few things but still crashes?
David

Hi Wentao,
Solved quite a lot of the problems and been updating on Github for anyone
else using the software to make the appropriate changes where necessary.
You can check the comments and let me know if you think the changes should
have correctly solved the errors in inbreast.py using Keras 2 and Python
3.5.
I now get an error when running: run_cnn_k_new.py:
Negative dimension size caused by subtracting 11 from 3 for
'conv_1/convolution' with input shape: [?,3,227,227], [11,11,227,96]
I guess this is a dim_ordering issue between tensorflow and theano (i'm
using tf backend) do you know a way to change this I've tried a few things
but still crashes?
David
On 2 June 2017 at 18:05, Wentao Zhu<EMAIL_ADDRESS>wrote:

From the following document, x, y should be of numpy array like type.
http://scikit-learn.org/stable/modules/generated/sklearn.model_selection.
StratifiedKFold.html#sklearn.model_selection.StratifiedKFold
split(X, y, groups=None)[source]
Generate indices to split data into training and test set.
Parameters:
X : array-like, shape (n_samples, n_features)
Training data, where n_samples is the number of samples and n_features is the number of features.

Note that providing y is sufficient to generate the splits and hence np.zeros(n_samples) may be used as a placeholder for X instead of actual training data.

y : array-like, shape (n_samples,)
The target variable for supervised learning problems. Stratification is done based on the y labels.

groups : object
Always ignored, exists for compatibility.

Returns:
train : ndarray
The training set indices for that split.

test : ndarray
The testing set indices for that split.

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Yes.  Check your keras configure file. If the channel is the last dimension, change it to the first dimension. I think it will be ok because you can see [?,3,227,227], the channel is the first dimension. Or you can do minor change to the input data. Thanks!

I changed the "image_data_format line" in the keras.json config file:
"backend": "tensorflow",
"epsilon": 1e-07,
"image_data_format": "channels_first",
"floatx": "float32"
But now the program just hangs at:
conv_1 = Convolution2D(96, 11, 11,subsample=(4,4),activation='relu',
W_regularizer=l1_l2(l1=l1factor, l2=l2factor),
name='conv_1')(inputs)
in def AlexNet() without any clue to error just stalls wont go any further?
Any ideas?
On 3 June 2017 at 18:43, Wentao Zhu<EMAIL_ADDRESS>wrote:

Yes. Check your keras configure file. If the channel is the last
dimension, change it to the first dimension. I think it will be ok because
you can see [?,3,227,227], the channel is the first dimension. Or you can
do minor change to the input data. Thanks!
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Restart, if the problem exists, it probably be the keras bug. Then you need to swap the input data axis to fit the data into channel last. Make sure your keras configure be channel last. Then run again.

ive changed this:
inputs = Input(shape=(3,227,227)) to:
inputs = Input(shape=(227,227,3)) so it is consistent with tensorflow channel_last but still same problem of it hanging. Any other ideas? Its a shame I think I'm almost there!

I recommend you to use theano because you are running in windows.

What do I need to change to run theano? I think ive tried this in the past
and got some issues with 64-bit not installed?
On 3 June 2017 at 21:38, Wentao Zhu<EMAIL_ADDRESS>wrote:

I recommend you to use theano because you are running in windows.
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Tensorflow does not support windows well. I think maybe it is the reason.

I get the following error (see attached).
Any ideas?
On 3 June 2017 at 21:56, Wentao Zhu<EMAIL_ADDRESS>wrote:

Tensorflow does not support windows well. I think maybe it is the reason.
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Hi Wentao,
Just a quick one:
How can I look at one of the train o test images? Can you do this with a
pickle file or do we access the images elsewhere? I just wnt to see what
they look like before going into the neural network.
Regards
David
On 3 June 2017 at 21:56, Wentao Zhu<EMAIL_ADDRESS>wrote:

Tensorflow does not support windows well. I think maybe it is the reason.
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 Good luck!
Best,
Wentao

I totally agree Wentao!
On 5 June 2017 at 00:54, Wentao Zhu<EMAIL_ADDRESS>wrote:

Hi David,
If I were you, I will spend a week to learn python first. Good luck!
Best,
Wentao
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I finally got the scripts working and running: run_cnn_k_mysparsemil_new.py

Hi Wentao,
I'm running: run_cnn_k_mysparsemil_new.py and getting output (see attached):

Do you recognise the Keras warning?

Is it correct that acc & val_acc are all 0.7561 and other parameters are
0.00 e.g. prec, etc? I have actually ran it for over 50 epochs and still
the same pattern?

Also, what is the main difference between mil, mymil and mysparsemil
scripts?
Thanks
David
On 5 June 2017 at 00:54, Wentao Zhu<EMAIL_ADDRESS>wrote:

Hi David,
If I were you, I will spend a week to learn python first. Good luck!
Best,
Wentao
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You need to debug. Try to run more epochs may be better.

OK - what is the main differences between mil, mymil and mysparsemil
scripts? Its hard to see from the code?

mil is the max pooling based mil. Please read the readme file
run_cnn_k_new.py is used for alex net. run_cnn_k_mil_new.py is used for max pooling based deep mil. run_cnn_k_mysparsemil_new.py is used for sparse deep mil. run_cnn_k_mymil_new.py is used for label assignment based deep mil. Here we finetuned weights from max pooling based deep mil.

Hi Wentao,
Can you explain in more detail the following functions in the
ImageGenerator please:
featurewise_center=False,  # set input mean to 0 over the dataset
samplewise_center=False,  # set each sample mean to 0
featurewise_std_normalization=False,  # divide inputs by std of the dataset
samplewise_std_normalization=False,  # divide each input by its std
zerosquare=True,
zerosquareh=noises,
zerosquarew=noises,
zerosquareintern=0.0
What are noises? Do you think these augmentations make a large difference?
Why did you not use the standard image generators but create your own?
David
On 11 June 2017 at 17:33, Wentao Zhu<EMAIL_ADDRESS>wrote:

mil is the max pooling based mil. Please read the readme file
run_cnn_k_new.py is used for alex net. run_cnn_k_mil_new.py is used for
max pooling based deep mil. run_cnn_k_mysparsemil_new.py is used for sparse
deep mil. run_cnn_k_mymil_new.py is used for label assignment based deep
mil. Here we finetuned weights from max pooling based deep mil.
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Hi Wentao,
Do you have the code snippets that created the segmentation patches from
the paper in Figure 4?
Thanks
David
On 11 June 2017 at 18:48, david jones<EMAIL_ADDRESS>wrote:

Hi Wentao,
Can you explain in more detail the following functions in the
ImageGenerator please:
featurewise_center=False,  # set input mean to 0 over the dataset
samplewise_center=False,  # set each sample mean to 0
featurewise_std_normalization=False,  # divide inputs by std of the
dataset
samplewise_std_normalization=False,  # divide each input by its std
zerosquare=True,
zerosquareh=noises,
zerosquarew=noises,
zerosquareintern=0.0
What are noises? Do you think these augmentations make a large difference?
Why did you not use the standard image generators but create your own?
David
On 11 June 2017 at 17:33, Wentao Zhu<EMAIL_ADDRESS>wrote:

mil is the max pooling based mil. Please read the readme file
run_cnn_k_new.py is used for alex net. run_cnn_k_mil_new.py is used for
max pooling based deep mil. run_cnn_k_mysparsemil_new.py is used for sparse
deep mil. run_cnn_k_mymil_new.py is used for label assignment based deep
mil. Here we finetuned weights from max pooling based deep mil.
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I finally got the scripts working and running: run_cnn_k_mysparsemil_new.py
What do you edit??

What do you mean edit?

I now get an error when running: run_cnn_k_new.py:
Negative dimension size caused by subtracting 11 from 3 for
'conv_1/convolution' with input shape: [?,3,227,227], [11,11,227,96]

You should make sure the input size as [?,3,227,227]. You can easily do this by resizing image at the first step.

Thank you wentao, I do appreciate the quick response.

Hi, I am unable to solve the error
Negative dimension size caused by subtracting 11 from 3 for
'conv_1/convolution' with input shape: [?,3,227,227], [11,11,227,96]
Where should I resize the image?

TypeError                                 Traceback (most recent call last)
 in ()
23     X_test_test_extend[i,:,:,2] = rex
24   X_test_test = X_test_test_extend
---> 25   alexmodel = convnet('alexnet', weights_path='alexnet_weights.h5', heatmap=False, l1=l1factor, l2=l2factor)
26   model = convnet('alexnet', outdim=2, l1=l1factor, l2=l2factor)
27   if pretrain:
3 frames
/content/customlayers.py in f(X)
16         square = K.square(X)
17         extra_channels = K.spatial_2d_padding(K.permute_dimensions(square, (0,2,3,1))
---> 18                                               , (0,half))
19         extra_channels = K.permute_dimensions(extra_channels, (0,3,1,2))
20         scale = k
TypeError: Exception encountered when calling layer "convpool_1" (type Lambda).
object of type 'int' has no len()
Call arguments received:
• inputs=tf.Tensor(shape=(None, 9, 9, 96), dtype=float32)
• mask=None
• training=None
I am getting this error after changing dimensions. How to solve?


patronictl do not work after fresh build

With freshly build images, "patronictl list" returns:
]$ patronictl list
Traceback (most recent call last):
  File "/usr/local/lib/python3.9/site-packages/patroni/ctl.py", line 45, in <module>
    from ydiff import markup_to_pager, PatchStream  # pyright: ignore [reportMissingModuleSource]
ImportError: cannot import name 'PatchStream' from 'ydiff' (/usr/local/lib/python3.9/site-packages/ydiff.py)

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/usr/local/bin/patronictl", line 5, in <module>
    from patroni.ctl import ctl
  File "/usr/local/lib/python3.9/site-packages/patroni/ctl.py", line 47, in <module>
    from cdiff import markup_to_pager, PatchStream  # pyright: ignore [reportMissingModuleSource]
ModuleNotFoundError: No module named 'cdiff

@ermajn did you used the latest release?
https://github.com/cybertec-postgresql/CYBERTEC-pg-container/releases/tag/V0.7.0-rc3

@ermajn Check the latest RC and you will see, that this is already included.
Merge in Main will take place when the release is published later this week


[Core] Rename Manager.entityVersionName

This hopefully reduces the ambiguity where this method could be considered to be in the same area as the displayName methods, and ties it more closely with its counterpart - entityVersions.
Closes https://github.com/TheFoundryVisionmongers/OpenAssetIO/issues/118.

[consider] CODING_STANDARDS.md uses Test_ManagerInterface_entityVersionName as an example.

Looks good, other than the example in CODING_STANDARDS.md which we might want to change.

Good spot @feltech, thanks - forgot to grep that folder! Fixed here.


Prod beta to stable

Description:
Production beta to Production Stable push
Received ACK from team here
Jira cards included in the release:
RHIROS-488
RHIROS-489
RHIROS-487
RHIROS-490
RHIROS-519

Codecov Report

Merging #98 (88efc55) into prod-stable (0b8b836) will decrease coverage by 0.14%.
The diff coverage is 8.69%.

:exclamation: Current head 88efc55 differs from pull request most recent head d04eae6. Consider uploading reports for the commit d04eae6 to get more accurate results

@@               Coverage Diff               @@
##           prod-stable      #98      +/-   ##
===============================================
- Coverage        11.63%   11.48%   -0.15%
===============================================
  Files               29       29
  Lines              447      470      +23
  Branches            95       98       +3
===============================================
+ Hits                52       54       +2
- Misses             366      384      +18
- Partials            29       32       +3

Impacted Files
Coverage Δ

...rc/Components/SystemDetail/RecommendationsTable.js
76.19% <ø> (ø)

src/Routes.js
0.00% <ø> (ø)

src/Routes/RosPage/RosPage.js
0.00% <0.00%> (ø)

src/constants.js
100.00% <100.00%> (ø)

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 0b8b836...d04eae6. Read the comment docs.

Thanks @PreetiW! Please mark statuses on JIRAs & announce it on ros channel once changes available in PROD.


Distributed training (PyTorch) proof-of-concept with Flask and PeerJS communication

This builds on PR #16 with a very basic proof-of-concept of 2 peers training a model and communicating.
It works like this: a model is trained locally with Pytorch and periodically serves its parameters (as JSON) over localhost using a Flask app. The peer on the same host machine where the model is being trained makes periodic requests for the parameters and sends them to another peer using PeerJS.
The flow of data in one direction looks like this:
|Pytorch| ---> |localhost| ---> |local peer| ---> (internet) ---> |remote peer|

(Disclaimers) The code is not very elaborate/stable, it is just meant as a demonstration and I did not test it with a remote peer. The neural network that gets trained is also pretty basic and is artificially slowed down with sleep statements.
To test it follow these steps (the order doesn't really matter).

Start the Flask web app. The model takes a few minutes to train, so you should execute the subsequent steps within this time in order to have some meaninfgul communication.

cd local_webapp
export FLASK_APP=webapp.py
flask run --port 5001

Open peerjs-backend/local_peerjs_interface.html in 2 tabs and open the console in both tabs
On the left tab, type in left, right for "Username" and "Receiver", then click Register
On the right tab, type in right for "Username" (don't fill in the "Receiver" field) and click Register.

Now in the console of the right tab you should see that the data from the peer on the left tab is periodically received.

@martinjaggi should we remove this because it is quite slow/unstable? Alternatively, we could move it to experiments. What do you think?

yes let's move it to experiments

Closing this because it was move to experiments with 65004cb


Not able to deposit ATOM into savers

Prerequisites
Asgardex with ATOM
Expected Behavior
Expect deposits to savers to work
Current Behavior
Cannot deposit because the "earn" button remains grayed out.
Steps to Reproduce

Have ATOM in Asgardex
Go to wallets page and locate ATOM
Press the "Earn" button for ATOM
Enter an amount to deposit (leaving a balance of 6 ATOM)
"Earn" button cannot be clicked (still greyed)

Also tried with ETH and had the same issue.
Related issues https://github.com/asgardex/asgardex-desktop/issues/424 https://github.com/asgardex/asgardex-desktop/issues/416
Possible Solution
Your Environment - Release Version (skip if not using a release version)

ASGARDEX desktop version: 1.22.8 (from GH deb file)
Operating system and version: Debian testing

fixing, thanks 👍

Can confirm this is working in 1.22.9. Thanks.


Errors in examples for addDays, addHours

Evening Microsoft
The examples for the addN functions are not consistent and do not match observed behavior.
To validate, I created a flow that sent an e-mail calling the functions per the examples:

The resulting e-mail body (bold are those that the result doesn't match the docs)
Add Days:
addDays('2018-03-15T13:00:00Z', 10) = 2018-03-25T13:00:00.0000000Z
addDays('2018-03-15T00:00:00Z', -5) = 2018-03-10T00:00:00.0000000Z
Add Hours:
addHours('2018-03-15T00:00:00Z', 10) = 2018-03-15T10:00:00.0000000Z
addHours('2018-03-15T15:00:00Z', -5) = 2018-03-15T10:00:00.0000000Z
Add Minutes:
addMinutes('2018-03-15T00:10:00Z', 10) = 2018-03-15T00:20:00.0000000Z
addMinutes('2018-03-15T00:20:00Z', -5) = 2018-03-15T00:15:00.0000000Z
Add Seconds:
addSeconds('2018-03-15T00:00:00Z', 10) = 2018-03-15T00:00:10.0000000Z
addSeconds('2018-03-15T00:00:30Z', -5) = 2018-03-15T00:00:25.0000000Z
Thanks!
Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: 03aa9e88-7fa0-56ab-f794-58f0c37b6d7a
Version Independent ID: 25c5ef5c-6ba4-f5ff-f94b-8f2818ec2feb
Content: Reference guide for functions in expressions - Azure Logic Apps
Content Source: articles/logic-apps/workflow-definition-language-functions-reference.md
Service: logic-apps
GitHub Login: @ecfan
Microsoft Alias: estfan

Looks like subtractFromTime has an error as well. Colon instead of period separating the milliseconds in the first example

Hello @nonodename,
Thank you for your feedback! We will review and update as appropriate.

Hi @nonodename,
Thanks for finding this issue! I've queued up an update to fix the problem.

@nonodename, the update should be live Wed morning 11:00 AM Pacific Time.

Great - thanks for working through this.

Hello @ecfan, Thank you for working on this!


Add progressbar to new Media details zoom activity

Summary:
When it is a DSLR image with a big size, it took some time for it to be displayed. But user is looking at a black screen during this time. Instead there should be an progressbar.
Progressbar should appear after image from media details is clicked until image is being loaded.

@neslihanturan I have understanding of the custom ZoomableDraweeView which I added so can I work on this?

Go for it @kbhardwaj123 :)


python312Packages.llama-cpp-python: init at 0.3.1

unlike previous attempt https://github.com/NixOS/nixpkgs/pull/268712
this uses bundled version of llama-cpp, also tested CUDA support

Things done

Built on platform(s)

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

For non-Linux: Is sandboxing enabled in nix.conf? (See Nix manual)

[ ] sandbox = relaxed
[ ] sandbox = true

[ ] Tested, as applicable:

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

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[ ] Tested basic functionality of all binary files (usually in ./result/bin/)
24.11 Release Notes (or backporting 23.11 and 24.05 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module

[ ] Fits CONTRIBUTING.md.

Add a :+1: reaction to pull requests you find important.

Thanks for the work !
Can you explain the motivations behind switching to the bundled version of llama-cpp ?
The package looks much simpler than the previous version that used patches on llama-cpp, but lacks support for other back-ends (OpenCL, ROCm).

Trying to build with Cuda results in the version error:
llama-cpp-python>   /nix/store/slx40i35cmd7kb3wvdqzckfww8smcy6s-cuda_nvcc-12.2.140/include/crt/host_config.h:143:2:
llama-cpp-python>   error: #error -- unsupported GNU version! gcc versions later than 12 are
llama-cpp-python>   not supported! The nvcc flag '-allow-unsupported-compiler' can be used to
llama-cpp-python>   override this version check; however, using an unsupported host compiler
llama-cpp-python>   may cause compilation failure or incorrect run time execution.  Use at your
llama-cpp-python>   own risk.

Thanks for the work !
Can you explain the motivations behind switching to the bundled version of llama-cpp ?
The package looks much simpler than the previous version that used patches on llama-cpp, but lacks support for other back-ends (OpenCL, ROCm).

I am not the author but the code refers to the llama.cpp's examples subdirectory which is not included in nixpkg.llama-cpp. For instance https://github.com/abetlen/llama-cpp-python/blob/7403e002b8e033c0a34e93fba2b311e2118487fe/CMakeLists.txt#L110.

@hoh

Can you explain the motivations behind switching to the bundled version of llama-cpp ?

llama-cpp and llama-cpp-python often get out of sync, so using llama-cpp from nixpkgs requires either breaking lama-cpp-python or not updating llama-cpp
@alexvorobiev CUDA support builds without any overrides, do you change default cuda in your overlays ?

@alexvorobiev CUDA support builds without any overrides, do you change default cuda in your overlays ?

I have to use CUDA 12.2 for now, could that be the issue?

yes, it seems to only build with 12.4  ( which is default in nixpkgs )

@alexvorobiev I've fixed cuda build, tested with 12_3, 12_2, 12_1, 12_0, 11_8 ( stopped here )

@alexvorobiev I've fixed cuda build, tested with 12_3, 12_2, 12_1, 12_0, 11_8 ( stopped here )

Thank you!

This pull request has been mentioned on NixOS Discourse. There might be relevant details there:
https://discourse.nixos.org/t/nix-development-environment-for-python-ai-llama-3-1/56143/3

This pull request has been mentioned on NixOS Discourse. There might be relevant details there:
https://discourse.nixos.org/t/nix-development-environment-for-python-ai-llama-3-1/56143/4

Unsure if there are any outstanding issues, but best to merge instead of leaving the PR for a long time, so have merged and will try to use it and identify any outstanding issues.


docs(samples): adding speech quickstart and snippets for v2

Description
Fixes #
Note: Before submitting a pull request, please open an issue for discussion if you are not associated with Google.
Checklist

[x] I have followed Contributing Guidelines from CONTRIBUTING.MD
[ ] Tests pass:   go test -v ./.. (see Testing)
[x] Code formatted:   gofmt (see Formatting)
[ ] Vetting pass:   go vet (see Formatting)
[ ] These samples need a new API enabled in testing projects to pass (let us know which ones)
[ ] These samples need a new/updated env vars in testing projects set to pass (let us know which ones)
[ ] This sample adds a new sample directory, and I updated the CODEOWNERS file with the codeowners for this sample
[ ] This sample adds a new Product API, and I updated the Blunderbuss issue/PR auto-assigner with the codeowners for this sample
[x] Please merge this PR for me once it is approved

updated

Updated as requested. Please review. Thank you

@muncus  Need your review. Thanks in Advance


Enhancement: Rename the whitty fla files

You need to rename the whitty fla fils in the "flashFiles"

nevermind i found them


Case inside "Quoted Identifier" is syntax-highlighted as case keyword and start of block. Ditto begin, end, etc.?

TSIA really:

Name: AL Language
Id: ms-dynamics-smb.al
Description: AL development tools for Dynamics 365 Business Central
Version: 9.0.615906
Publisher: Microsoft
VS Marketplace Link: https://marketplace.visualstudio.com/items?itemName=ms-dynamics-smb.al

Try enabling semantic highlighting
https://youtu.be/cTc0kYFsAr0?t=312

It was already enabled:

Not sure whether this may make a difference, but set it up for AL Language only (as shown in the video with time stamp).
And I am assuming that there is no other setting overriding your user setting?

Thanks, adding it in an "[AL]" group means I actually get the highlighting, but it doesn't fix the issue with case.
Trying a couple more, it looks like some other keywords are affected by this too, e.g. begin and end. Probably there is just missing code to stop trying to highlight anything specially within identifiers.

I can confirm this issue.
I am having the exact same problem with Quted identifiers like "begin", "end", "case" etc.

It is there because with the latest version of VSCode the setting "editor.bracketPairColorization.enabled" is enabled by default.
As a mitigation you should disable it in settings.

Sure, thanks - but is there a way that al.configuration.json can define what a "quoted identifier" is and then use "notIn" to avoid highlighting such words within identifiers?

Unfortunately, this is a bug in VSCode's bracket colorization feature and AL and we can't fix it on the AL side. VSCode has not considered the case that a bracket keyword may also be a word that is part of a language's syntax.
Begin and end are identified as brackets in al.configuration.json. From what I could figure out the colorization feature considers that only two kinds of code ranges should not have colorization on brackets, comments and strings. AL identifiers inside "" are neither of the two. At the same time, they are defined inside the grammar of the language which is why if you use a keyword inside a quoted identifier it will not appear highlighted.

There is no option to define that brackets should not be recognized in other syntax, so we can't override the behavior.
Here's a funny example where I've said that {"codeunit", "report"} is a bracket pair. VSCode is not smart enough to figure out that codeunit by itself is a keyword and not a bracket:

Thus there are two options:

Remove begin/end from brackets and thus remove support for bracket colors for these keywords altogether.
Accept this bug and file a bug on the editor so that they don't highlight syntax elements defined in the language grammar.

Since "begin" and "end" are much more rarely used inside quoted identifier as compared to brackets, I think we can go with #2 and depend on VSCode to make the feature a bit smarter.

@BazookaMusic Thanks for the investigation and write-up! Are the AL team going to file the bug with VSC?

I have created the issue here:
https://github.com/microsoft/vscode/issues/167062

Many thanks!


Report URLs of pending status checks

This PR allows hoff to report the target_url of pending builds, giving users an indication of which job hoff is waiting for. This is shown both as a comment on the PR, and an additional link in the headline for pull requests where a CI URL is available (i.e. pending and failed jobs, since we don't currently keep the URL of succeeded jobs).
Screenshots:

I'm slightly unsure if this will actually go off in practice. This info is given when the build status changes to pending with a non-null target_url, but I have no concrete intuition for when this would occur in practice. I'm hoping when the status check starts it will change the state from BuildPending Nothing to BuildPending (Just url).
Closes #26
Closes #109

I'm slightly unsure if this will actually go off in practice. This info is given when the build status changes to pending with a non-null target_url, but I have no concrete intuition for when this would occur in practice. I'm hoping when the status check starts it will change the state from BuildPending Nothing to BuildPending (Just url).

For this, I think GitHub sends a BuildPending hook again with the build URL when it gets one.  But I think you've already figured this out because I saw your changes on send-webhook which deal with this.

Btw, I reverted the broken merge of yesterday.  So feel free to rebase and merge this into master now if you like.
I saw this created a few conflicts with your files (as your change was already based on top of mine).  I'm sorry about that :pensive:.  I reviewed the conflicts though, and they seem to be not major.  :-)

Okay, the rebase was mostly mechanical apart from the handleBuildStatusChanged which was a little different after the revert for some reason. I changed the PR to be in the style of the reverted version so give it a once over in case anything dumb crept in

@OpsBotPrime merge on friday

Pull request approved for merge by @alex-mckenna, rebasing now.

Rebased as b4994cabf047f6cdedc1433018f46a2d54d0391b, waiting for CI …


Problem copying and pasting text with line breaks

Steps to Reproduce

Execute flutter run example on the code sample
Copy some text with more than one line to the clipboard
Try pasting any input in Flutter

Expected results:
That the text kept the line breaks
Actual results:
On the web, pasted text loses line breaks, even when the input has maxLines greater than 1

Code sample

TextFormField(maxLines: 3)

Logs

[✓] Flutter (Channel beta, 2.8.0-3.2.pre, on Mac OS X 10.15.7 19H1419 darwin-x64, locale pt-BR)
    • Flutter version 2.8.0-3.2.pre at /Users/reni/Downloads/Programas/flutter
    • Upstream repository https://github.com/flutter/flutter.git
    • Framework revision 2901cd7208 (7 weeks ago), 2021-11-18 11:15:09 -0800
    • Engine revision bcc2b7f12c
    • Dart version 2.15.0 (build 2.15.0-268.18.beta)

[✓] Android toolchain - develop for Android devices (Android SDK version 29.0.2)
    • Android SDK at /Users/reni/Library/Android/sdk
    • Platform android-31, build-tools 29.0.2
    • ANDROID_HOME = /Users/reni/Library/Android/sdk
    • Java binary at: /Applications/Android Studio.app/Contents/jre/jdk/Contents/Home/bin/java
    • Java version OpenJDK Runtime Environment (build 11.0.8+10-b944.6916264)
    • All Android licenses accepted.

[!] Xcode - develop for iOS and macOS (Xcode 12.4)
    • Xcode at /Applications/Xcode.app/Contents/Developer
    ! Flutter recommends a minimum Xcode version of 13.0.0.
      Download the latest version or update via the Mac App Store.
    • CocoaPods version 1.10.0

[✓] Chrome - develop for the web
    • Chrome at /Applications/Google Chrome.app/Contents/MacOS/Google Chrome

[✓] Android Studio (version 4.2)
    • Android Studio at /Applications/Android Studio.app/Contents
    • Flutter plugin can be installed from:
      🔨 https://plugins.jetbrains.com/plugin/9212-flutter
    • Dart plugin can be installed from:
      🔨 https://plugins.jetbrains.com/plugin/6351-dart
    • Java version OpenJDK Runtime Environment (build 11.0.8+10-b944.6916264)

[✓] VS Code (version 1.63.2)
    • VS Code at /Applications/Visual Studio Code.app/Contents
    • Flutter extension version 3.29.0

[✓] Connected device (2 available)
    • macOS (desktop) • macos  • darwin-x64     • Mac OS X 10.15.7 19H1419 darwin-x64
    • Chrome (web)    • chrome • web-javascript • Google Chrome 96.0.4664.110

! Doctor found issues in 1 category.

Hi @ReniDelonzek , Thanks for filing the issue. I am not able to reproduce the issue. on stable 2.8.1 Are you seeing this issue in chrome browser? Let me know if I am missing anything.
https://user-images.githubusercontent.com/31410839/148190861-b417d6b5-07cd-4c89-b138-91d6a56350e6.mov

code sample
import 'package:flutter/material.dart';

void main() {
  runApp(const MyApp());
}

class MyApp extends StatelessWidget {
  const MyApp({Key? key}) : super(key: key);

  @override
  Widget build(BuildContext context) {
    return MaterialApp(
      theme: ThemeData(
          textSelectionTheme: const TextSelectionThemeData(
        selectionColor: Colors.red,
      )),
      home: const MyHomePage(),
    );
  }
}

class MyHomePage extends StatefulWidget {
  const MyHomePage({Key? key}) : super(key: key);

  @override
  State<MyHomePage> createState() => _MyHomePageState();
}

class _MyHomePageState extends State<MyHomePage> {
  @override
  Widget build(BuildContext context) {
    return Scaffold(
      body: Center(
        child: TextFormField(
          maxLines: 3,
        ),
      ),
    );
  }
}

flutter doctor -v
[✓] Flutter (Channel stable, 2.8.1, on macOS 12.1 21C52 darwin-arm, locale en-GB)
    • Flutter version 2.8.1 at /Users/mahesh/Documents/flutter
    • Upstream repository https://github.com/flutter/flutter.git
    • Framework revision 77d935af4d (3 weeks ago), 2021-12-16 08:37:33 -0800
    • Engine revision 890a5fca2e
    • Dart version 2.15.1

[✓] Android toolchain - develop for Android devices (Android SDK version 31.0.0)
    • Android SDK at /Users/mahesh/Library/Android/sdk
    • Platform android-31, build-tools 31.0.0
    • ANDROID_HOME = /Users/mahesh/Library/Android/sdk
    • Java binary at: /Applications/Android Studio.app/Contents/jre/jdk/Contents/Home/bin/java
    • Java version OpenJDK Runtime Environment (build 11.0.8+10-b944.6916264)
    • All Android licenses accepted.

[✓] Xcode - develop for iOS and macOS (Xcode 13.1)
    • Xcode at /Applications/Xcode.app/Contents/Developer
    • CocoaPods version 1.10.2

[✓] Chrome - develop for the web
    • Chrome at /Applications/Google Chrome.app/Contents/MacOS/Google Chrome

[✓] Android Studio (version 4.2)
    • Android Studio at /Applications/Android Studio.app/Contents
    • Flutter plugin can be installed from:
      🔨 https://plugins.jetbrains.com/plugin/9212-flutter
    • Dart plugin can be installed from:
      🔨 https://plugins.jetbrains.com/plugin/6351-dart
    • Java version OpenJDK Runtime Environment (build 11.0.8+10-b944.6916264)

[✓] IntelliJ IDEA Community Edition (version 2021.2.1)
    • IntelliJ at /Applications/IntelliJ IDEA CE.app
    • Flutter plugin version 60.1.4
    • Dart plugin version 212.5080.8

[✓] VS Code (version 1.63.2)
    • VS Code at /Applications/Visual Studio Code.app/Contents
    • Flutter extension version 3.32.0

[✓] Connected device (4 available)
    • Redmi K20 Pro (mobile) • <IP_ADDRESS>:5555                     • android-arm64  • Android 11 (API 30)
    • iPhone 13 Pro (mobile) • 0FA2FB93-2A89-4FDB-8293-DF66188F1E54 • ios            • com.apple.CoreSimulator.SimRuntime.iOS-15-0
      (simulator)
    • macOS (desktop)        • macos                                • darwin-arm64   • macOS 12.1 21C52 darwin-arm
    • Chrome (web)           • chrome                               • web-javascript • Google Chrome 96.0.4664.110

• No issues found!

Thanks

H @maheshmnj, I investigated further here and found that the problem only occurs when we set keyboardType: TextInputType.text, please test it on your machine too.
However, it works fine if we define keyboardType as: TextInputType.multiline. Is it mandatory to set it to multiline in these cases?

Thanks for the info @ReniDelonzek, I am able to reproduce the issue withkeyboardType: TextInputType.text the line break formatting is lost on the web while it works fine on Desktop.
MacOS Desktop TextInputType.text ✅
https://user-images.githubusercontent.com/31410839/148334308-e60bc6b6-0bb4-4fa3-a2f8-8d502eabc454.mov
Web

TextInputType.multiline ✅
TextInputType.text  ❌

However, it works fine if we define keyboardType as: TextInputType.multiline. Is it mandatory to set it to multiline in these cases?
I think formatting should be retained regardless of the KeyboardType, But I may be wrong considering How line breaks are calculated on the web and Desktop. Lets wait for further insights from the team.

flutter doctor -v
[✓] Flutter (Channel stable, 2.8.1, on macOS 12.1 21C52 darwin-arm, locale en-GB)
    • Flutter version 2.8.1 at /Users/mahesh/Documents/flutter
    • Upstream repository https://github.com/flutter/flutter.git
    • Framework revision 77d935af4d (3 weeks ago), 2021-12-16 08:37:33 -0800
    • Engine revision 890a5fca2e
    • Dart version 2.15.1

[✓] Android toolchain - develop for Android devices (Android SDK version 31.0.0)
    • Android SDK at /Users/mahesh/Library/Android/sdk
    • Platform android-31, build-tools 31.0.0
    • ANDROID_HOME = /Users/mahesh/Library/Android/sdk
    • Java binary at: /Applications/Android Studio.app/Contents/jre/jdk/Contents/Home/bin/java
    • Java version OpenJDK Runtime Environment (build 11.0.8+10-b944.6916264)
    • All Android licenses accepted.

[✓] Xcode - develop for iOS and macOS (Xcode 13.1)
    • Xcode at /Applications/Xcode.app/Contents/Developer
    • CocoaPods version 1.10.2

[✓] Chrome - develop for the web
    • Chrome at /Applications/Google Chrome.app/Contents/MacOS/Google Chrome

[✓] Android Studio (version 4.2)
    • Android Studio at /Applications/Android Studio.app/Contents
    • Flutter plugin can be installed from:
      🔨 https://plugins.jetbrains.com/plugin/9212-flutter
    • Dart plugin can be installed from:
      🔨 https://plugins.jetbrains.com/plugin/6351-dart
    • Java version OpenJDK Runtime Environment (build 11.0.8+10-b944.6916264)

[✓] IntelliJ IDEA Community Edition (version 2021.2.1)
    • IntelliJ at /Applications/IntelliJ IDEA CE.app
    • Flutter plugin version 60.1.4
    • Dart plugin version 212.5080.8

[✓] VS Code (version 1.63.2)
    • VS Code at /Applications/Visual Studio Code.app/Contents
    • Flutter extension version 3.32.0

[✓] Connected device (4 available)
    • Redmi K20 Pro (mobile) • <IP_ADDRESS>:5555                     • android-arm64  • Android 11 (API 30)
    • iPhone 13 Pro (mobile) • 0FA2FB93-2A89-4FDB-8293-DF66188F1E54 • ios            • com.apple.CoreSimulator.SimRuntime.iOS-15-0
      (simulator)
    • macOS (desktop)        • macos                                • darwin-arm64   • macOS 12.1 21C52 darwin-arm
    • Chrome (web)           • chrome                               • web-javascript • Google Chrome 96.0.4664.110

• No issues found!

[✓] Flutter (Channel master, 2.9.0-1.0.pre.224, on macOS 12.1 21C52 darwin-arm, locale en-GB)
    • Flutter version 2.9.0-1.0.pre.224 at /Users/mahesh/Documents/flutter_master
    • Upstream repository https://github.com/flutter/flutter.git
    • Framework revision a0f8937b7c (2 days ago), 2022-01-03 04:15:18 -0500
    • Engine revision 8f53bbfde0
    • Dart version 2.16.0 (build 2.16.0-134.0.dev)
    • DevTools version 2.9.2

[✓] Android toolchain - develop for Android devices (Android SDK version 31.0.0)
    • Android SDK at /Users/mahesh/Library/Android/sdk
    • Platform android-31, build-tools 31.0.0
    • ANDROID_HOME = /Users/mahesh/Library/Android/sdk
    • Java binary at: /Applications/Android Studio.app/Contents/jre/jdk/Contents/Home/bin/java
    • Java version OpenJDK Runtime Environment (build 11.0.8+10-b944.6916264)
    • All Android licenses accepted.

[✓] Xcode - develop for iOS and macOS (Xcode 13.1)
    • Xcode at /Applications/Xcode.app/Contents/Developer
    • CocoaPods version 1.10.2

[✓] Chrome - develop for the web
    • Chrome at /Applications/Google Chrome.app/Contents/MacOS/Google Chrome

[✓] Android Studio (version 4.2)
    • Android Studio at /Applications/Android Studio.app/Contents
    • Flutter plugin can be installed from:
      🔨 https://plugins.jetbrains.com/plugin/9212-flutter
    • Dart plugin can be installed from:
      🔨 https://plugins.jetbrains.com/plugin/6351-dart
    • Java version OpenJDK Runtime Environment (build 11.0.8+10-b944.6916264)

[✓] IntelliJ IDEA Community Edition (version 2021.2.1)
    • IntelliJ at /Applications/IntelliJ IDEA CE.app
    • Flutter plugin version 60.1.4
    • Dart plugin version 212.5080.8

[✓] VS Code (version 1.63.2)
    • VS Code at /Applications/Visual Studio Code.app/Contents
    • Flutter extension version 3.32.0

[✓] Connected device (4 available)
    • Redmi K20 Pro (mobile) • <IP_ADDRESS>:5555                     • android-arm64  • Android 11 (API 30)
    • iPhone 13 Pro (mobile) • 0FA2FB93-2A89-4FDB-8293-DF66188F1E54 • ios            • com.apple.CoreSimulator.SimRuntime.iOS-15-0
      (simulator)
    • macOS (desktop)        • macos                                • darwin-arm64   • macOS 12.1 21C52 darwin-arm
    • Chrome (web)           • chrome                               • web-javascript • Google Chrome 96.0.4664.110

[✓] HTTP Host Availability
    • All required HTTP hosts are available

• No issues found!

To fix this, we probably need to always use a <textarea> element even in single-line cases.

I am also getting weird bug when I can't copy anything to the Android, on iOS it works fine, not sure if it's related. Flutter 2.8.1 stable.


Unplugging my phone does not kill flutter run

I'm not sure, but I thought flutter run was resident as long as it was connected to an app on the phone.

What is the lifecycle intention of flutter run and its relationship to the app on the phone?

cc @mit-mit

@danrubel can you take a look?

This is probably related to https://github.com/flutter/flutter/issues/5448 and https://github.com/flutter/flutter/issues/5185 and https://github.com/flutter/flutter/issues/4508 and https://github.com/flutter/flutter/issues/4497 and https://github.com/flutter/flutter/issues/4165
That is, looks like we might want to define some new semantics for the commands in our tools. :)
cc @mit-mit something you want to take a crack at?

I tried flutter run with Android, with iOS, and with the simulator. If I unplugged the device or quit the simulator, the flutter run command properly terminated in each situation.
Can you give me more details on how I can repro this situation?
Were there exceptions?

Try flutter run --release.
Apologies, I wasn't specific in the original description. Will update.

Yes, apparently the --release flag changes the behavior.


Odd heading behavior in one case (when hr follows)

Could you explain why the second line is interpreted as a h2?

http://spec.commonmark.org/0.24/#setext-headings
because spec says to do so :) ?

That's a good reason :)


[BACKLOG-19596] Auto-save generated meta injection ktrs in the repo, when connected

@pentaho/r2d2

Build Completed
:fire: This pull request has some issues. It would be preferable to fix them in order for it to be just perfect. See below for more details. Some links are also available below for further assistance in addressing those issues.
Build Commands
mvn -Dsurefire.runOrder=alphabetical -B -fn -f 'pom.xml' -pl 'plugins/meta-inject' -P '!assemblies' -amd clean install && mvn -B -f 'pom.xml' -pl 'plugins/meta-inject' -P '!assemblies' -amd site

Cleanup Commands
mvn -B -f 'pom.xml' -pl 'plugins/meta-inject' -P '!assemblies' -amd build-helper:remove-project-artifact

Changed files
  plugins/meta-inject/pom.xml
  plugins/meta-inject/src/main/java/org/pentaho/di/trans/steps/metainject/MetaInject.java
  plugins/meta-inject/src/test/java/org/pentaho/di/trans/steps/metainject/MetaInjectTest.java

Unit Test Coverage
These statistics help you identify how your changes have affected the coverage of the following files. If a file is not in this list, then its coverage was not affected by your changes. To get some help interpreting these metrics, please refer to Jacoco's documentation.

:warning: Coverage Changes: -15.9% (click to expand)
org.pentaho.di.trans.steps.metainject.MetaInject

Branch Change: -49.8% :small_red_triangle_down:
Complexity Change: -43.4% :small_red_triangle_down:
Instruction Change: -58.7% :small_red_triangle_down:
Line Change: -65.3% :small_red_triangle_down:
Method Change: -84.6% :small_red_triangle_down:

org.pentaho.di.trans.steps.metainject.MetaInjectData

Complexity Change: -100% :small_red_triangle_down:
Instruction Change: -100% :small_red_triangle_down:
Line Change: -100% :small_red_triangle_down:
Method Change: -100% :small_red_triangle_down:

org.pentaho.di.trans.steps.metainject.MetaInjectMeta

Complexity Change: -0.9% :small_red_triangle_down:
Instruction Change: -0.1% :small_red_triangle_down:
Line Change: -0.3% :small_red_triangle_down:
Method Change: -1.6% :small_red_triangle_down:

org.pentaho.di.trans.steps.metainject.SourceStepField

Branch Change: -37.5% :small_red_triangle_down:
Complexity Change: -18.1% :small_red_triangle_down:
Instruction Change: -43.3% :small_red_triangle_down:
Line Change: -17.7% :small_red_triangle_down:
Method Change: -14.3% :small_red_triangle_down:

org.pentaho.di.trans.steps.metainject.TargetStepAttribute

Branch Change: -50% :small_red_triangle_down:
Complexity Change: -7.7% :small_red_triangle_down:
Instruction Change: -34.3% :small_red_triangle_down:
Line Change: -19% :small_red_triangle_down:
Method Change: -11.1% :small_red_triangle_down:


How to run this framework

Hi Sir,
I have cloned Test.Automation.ProjectExample.Features.  How to run this framework?
Here are steps i followed.

Copied Test.Automation.ProjectExample.Features.zip into my local drive
Unzipped Test.Automation.ProjectExample.Features into my local drive
Open Visual studio Enterprise 2015 --> Click on Open project --> Opened Test.Automation.ProjectExample.Features file -->Then I see Test.Automation.ProjectExample.Features under Class View of Visual studio
Click on Run button ( I need to do something here before click on run button, But i don't know what to do)

I see below error
A project with an output type of class library cannot be started directly.
In order to debug this project , add an executable project to this solution which references the library project . Set the executable project as the startup project._
How to add an executable project to this solution?
Could you please send me sample executable project to see how it is running.  This is the first time I'm using Visual studio. Could you please help me with detailed steps.
Thanks :)

I updated README file.


[Bug] Index-based access to VSS instances, e.g. Vehicle.Cabin.Seat.Row(1).Pos(2). ..., not offered by generated model

Some month ago we introduced the automated vehicle model generation from the json-based model specification referenced in the AppManifest. This was done under the assumption that json-based VSS specification is semantically identical to vspec-based origin of the vehicle signal catalog (except file separation, of course).
But unfortunately it isn't: In the vss.json all kind of instances, e.g. like instances of Seats, are expanded and the information that the different seats in Row1 Pos1 and Row2 Pos3 are instances of a single Seat definition is lost.
This leads to the problem that the functions that should offer index based access to instances are not generated as part of the model like they would if using model generation from vspec files. The index-based access functions enable iteration over, for example, the rows of seats and seats per row; means allows for something like this: Vehicle.Cabin.Seat.Row(row_idx).Pos(pos_idx).Position
Unfortunately, we also cannot easily move back to use vspec files for model generation as Digital.Auto is working on json base, only.
We are currently working hard on a solution for this.

Solution proposal for COVESA: https://github.com/COVESA/vss-tools/pull/293

Erik Jaegerval provided a quick prototype with PR https://github.com/COVESA/vss-tools/pull/293 showing two possible solutions:

Keeping instance expansion but adding a flag for expanded branches
Add a flag --no-expand to the vspec2json (or in general: vspec2x.py) of the VSS tooling to discard instance expansion and instead keeping the instance information in the generated output files.
JSON examples are included for both. We should check if any of the approaches would fit our needs, and Erik will mention it on VSS meetings so they can start thinking about it as well.

I provided a PoC fix of our model-generator for solution (i), that restores the original instance information (from vspec files). This has limitations in cases where the expanded flag isn't correctly set and also for the case that an instances (or some) have "special" attributes, which is allowed by the VSS specification.
I also tried solution (ii) with our model-generator and it works "out-of-the-box". Means, no fixes in the model-generator needed.
Solution (ii) would be preferred, as it keeps the original information of the vspec files in the JSON file.

I also thought about a PoC that recognizes expanded instances just by comparing children of a branch and rating them as instances of a common definition if they contain equal (grand) children.
Unfortunately, this would have even more limitations than the PoC identifying instances based on the expanded flag: There could be branches consisting of a single instance only (in model for specific vehicles, e.g. roadsters having only row1 of seats). But still an index-based access function must be available as developers would expect that when writing vehicle independent apps.

Currently, we are in discussion with digital.auto, if the proposed solution (ii) (see above) would also fit for them.


Bug: $getSelection() does not work inside the shadow DOM.

Lexical version:
latest
Steps To Reproduce
When I use Lexical inside a shadow DOM, I find that $getSelection() does not work, and I am unable to retrieve the selected content.
Link to code example:
https://stackblitz.com/edit/facebook-lexical-j9ccrm
The current behavior
$getSelection() does not work inside the shadow DOM.
The expected behavior
To be able to use FloatingTextFormatToolbarPlugin inside the shadow DOM.

Selections and contentEditable don't really work very well in shadow DOM, you should put the editor in light DOM if you want it to work cross-platform without hacks. See also https://github.com/facebook/lexical/issues/2119


Best distro for gaming is a very subjective matter. I dont think it is fixable

Second google hit (tomsguide) seems pretty decent list. They even tested two entries on that list.
 You cannot choose for them.

When I google the "best linux distro for gaming" I get two top results, and the toms guide one is absolute garbage. Listing Manjaro, Garuda and Drauger instead of the mainstream distributions like Fedora or openSUSE is really terrible advice. No one should follow that advice at all, it is close to being completely worthless.

The list includes Ubuntu, Manjaro and PopOS. Those are pretty popular, but as I said before, this is a very subjective issue.
It could be great for me, garbage for you and it is fine. They are professional reviewers, let them make their own list.

And of those three, I would only recommend one. A lot of LTTs issues came from insisting on using Manjaro or Pop. When you recommend a distro, you recommend everything about it. Infrastructure, bug triage, upstream connections, responsiveness to bug reports. If you claim that Manjaro or Pop does a better job at this than Fedora, backed by Red Hat and openSUSE then you are way too biased, and a simple look at my avatar shows that I am not a fan of either of those distributions.
These niche distributions are okay-ish if you recommend to someone who already know what they're doing, but they are complete garbage compared to the bigger ones. And you need to put away your own preference and bias when you recommend.

I totally agree and I would personally not recommend PopOS or even less Manjaro. For a beginner I would choose Ubuntu from that list as it easier/has less rough edges than Debian (my personal favorite). I am still frustrated they didn't include Ubuntu on their tests as the user base is larger and it would be easier to get help from the community. But again, even if we both agree, that would be subjective. We would need a poll of some kind to get more people represented or some an objective benchmark to rank them.

Here is a poll with 15k votes. https://strawpoll.com/z57pyrzxw/r
It is funny because the results are almost exactly the opposite of what I would recommend.
Anyway, I think people answers from what they are using or what is best for their own instead of thinking what would would work best for a linux beginner that wants to play games and other basic stuff.

I think the problem is to ask the right question. For advanced users wanting to get extra FPS, probably gentoo is a good option, For someone coming from windows and want a quick painless transition to their favorite games probably is not.
The gaming part can probably be boiled down to 1. support for proprietary drivers OOTB (sorry debian) and 2. Include key software on the default app stores such as steam, lutris, OBS, etc.
I think we can make a table (in the wiki perhaps?) listing the key features for most distros and let users decide.

Here is a draft/attempt on an objective table to help new linux gamers choose their right distro:
https://github.com/fleshin/ltt-linux-challenge-issues/wiki/Best-distro-for-gamers-transitioning-to-Linux-for-the-first-time
After some polishing/accuracy checking we could merge into this same repo.
Please, let me know comments, corrections, etc Thanks!

@fleshin Lenovo laptops can officially come with Fedora pre-installed nowadays. Just a small correction

Happy to hear that, table is updated now...  Thanks for the info!

BTW, anyone knows any source for estimated user base for each distro?
This is the hardest piece of info to get...

@fleshin Most distros don't collect telemetry by default. You could try the Steam Hardware Survey (click on "Linux Version"), but the results are biased because some distro users are more likely to use Steam and opt into the survey than others.


Updated zend-expressive-helpers version to 2.0

In terms of functionality related to this component, nothing has changed.  However, to ensure that the component works with Expressive RC6, it needs access to the 2.0 release of zend-expressive-helpers.

Closing; I can make this work with either version.