[bug] When adding or removing lines, the mark positions are not updated.

I love this plugin!
But there's only one thing that prevents proper usage for me: if I paste code (for example) the marks don't move to their new line numbers. The marks in the gutter move, as expected, but the actual marks don't, they stay on the same line.
For example, suppose we have this code and add a mark:
  1 one
# 2 two|
  3 three

right now it works, navigating to the mark will take me to line 2 (the | shows where navigation takes me).
if I add some lines, I get something that looks like this:
  1 one
  2 one-a|
  3 one-b
  4 one-c
# 5 two
  6 three

so it looks like the mark moved down to line 5, but when I try to navigate to the mark, my cursor moves to line 2

@trusktr Sorry for the late response.
For most things, marks and signs behave similarly such as moving when you add/remove lines around the line with the mark/sign. However, when it comes deleting a line, vim treats the two differently; marks get removed while the sign persists. I don't know why vim chooses to do it this way.
To fix this, I ended up periodically comparing the line number of the mark and the sign and correcting it when a line gets moved.
Currently, there isn't a good API to figure out the line number a sign is located on (feel free to correct me in case this is no longer true) and hence I'm a little worried that my code might be a little resource-intensive. Please try it out and let me know in case of any issues.

Retracting this fix since it causes other issues (#144 and #145).

Had to retract the fix. Will try to figure out a better solution.

No prob, looking forward to it! This is one of my favorite plugins!
On Aug 17, 2017 4:48 PM, "Kartik Shenoy"<EMAIL_ADDRESS>wrote:

Had to retract the fix. Will try to figure out a better solution.
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After this retracting,  when adding or removing lines, vim keeps displaying anonying information as below in command window.
Error detected while processing function signature#sign#Refresh..signature#sign#Remove:
line   32:
E117: Unknown function: assert_true

I figured out it is due to the following change. Guess this is for debugging purpose?
+    call assert_true(len(l:arr) == 1, "Multiple marks found where one was expected")

Still looking forward to the fi for this, it's quite annoying. Most of the time, the marks only move a little ways off, so I can usually find my way.  So most of the time I can live with the mark being a few lines off, then navigating my way to the correct line.

This works fine in vim-bookmarks. Maybe you can look at how vim-bookmarks does it. Works perfectly there (add/remove lines, undo/redo, etc, anything you do, the marks move in the gutter and in the code).

Will do. Thanks :)

I thought I had somehow broken the plugin somewhere in my 1000-line vimrc - good to know I won't have to binary search to find the problem, haha
Anywho, this should be easily fixable with the TextChanged and TextChangedI events. Comparing the mark and sign positions for every pair on every edit isn't great, especially if it isn't straightforward to get sign positions (if it was, I assume this plugin would just use signs on the backend). . . If I get the time I'll look through the source and see if there's a way to get a list of marks below the changes.


Board Review: Event Hubs - Send batch API for collection of events

The Basics

Service team responsible for the client library: Event Hubs
Link to documentation describing the service: https://azure.microsoft.com/en-us/services/event-hubs/
Contact email (if service team, provide PM and Dev Lead): SeongJoon Kwak, Javier Fernandez & Shubha Vijayasarathy

About this client library

Name of the client library: azure-messaging-eventhub
Languages for this review: Python, Java, .NET, JS
Link to the service REST APIs: N/A

Background and alternatives considered
Event Hub producer client today requires users to create an EventBatch, tryAdd() events to the batch and send the batch when the user is ready or when the next event does not fit into a batch.
While this API is very helpful to ensure we build a batch that would meet the size restrictions of the AMQP link, it is cumbersome for cases where the customer is confident that their set of events does actually fit within the size restrictions. There has also been feedback that the client should be smart enough to do batching on its own without having the customer do it.
We explored a variety of options to provide a smart send feature to the customer which is captured in this gist.
We soon realized that each alternative resulted in us foregoing one section of the user base in favor of the other and had us making assumptions regarding the customer use cases. Therefore, we chose to rather provide tools to the customer and trust that they know their application best.
If they want to ensure that their batch is under the size limit, then they can use CreateBatch() that already exists. If they are confident they won't increase the limit, they can use send() that takes multiple events and throwing an exception if the batch size indeed increases the limit.
This issue is to propose the introduction of a new API to send events on the producer client that takes multiple events as input and throws an exception if the size of the resulting batch increases the size limits
Artifacts required (per language)
Java

API review
Sample code

Python

API with sample code

JavaScript

API with sample code

.NET

API
Sample code

Champion Scenarios
A champion scenario is a use case that the consumer of the client library is commonly expected to perform.  Champion scenarios are used to ensure the developer experience is exemplary for the common cases.  You need to show the entire code sample (including error handling, as an example) for the champion scenarios.

Champion Scenario:

Describe the champion scenario: Send a list of events that the user knows can fit within a single EventDataBatch.
Estimate the percentage of developers using the service who would use the champion scenario: Most developers will use it. We have also received feedback from customers to provide this capability.
Link to the code sample

Looks good to me for Java.

Please upload revision with the new PAIs to https://apiview.dev/Assemblies/Review/ef013a8cb7cc4f4c83cb6d1e64367bd1
But I took a look at the new API listing, and it looks good.

API listing is good here too.

Looks good for .NET

Added some comments to the Python examples. @annatisch, have you also gone over this?

Yup - I've also added a couple of comments, but so far look good to me.

@johanste - I think the comments have been addressed - I'm good with this.

Approved.

Closing this as the May update has this api shipped across all 4 languages


solving Tokenizer issue #4

solving Tokenizer issue #4 also on root web for doc libs: {site}/Shared Documents/Forms/template.dotx
Test case: create a template from root sp on prem web without managed path and provisioning this template to sp online site with managed path

Hi @braegelno5, I'm your friendly neighborhood Microsoft Pull Request Bot (You can call me MSBOT). Thanks for your contribution!
You've already signed the contribution license agreement. Thanks!
The agreement was validated by Microsoft and real humans are currently evaluating your PR.
TTYL, MSBOT;

Thx Torsten for this. We'll have a look on this during next week and hopefully will make to the December master merge (if not - delayed for January). Change is impacting all tokes, so even though it's a small change, we'll need to be careful on the verifying the fix.

Thanks Torsten! I just merged a slightly modified version of your PR into Core (PR #326). I will make sure you will receive the appropriate credits on the weekly call.


server.go:2161: http: multiple response.WriteHeader calls

Hi there,
Really appreciate your work. I'm getting weird errors like "server.go:2161: http: multiple response.WriteHeader calls" in my error log after normal looking GET requests to the index page. It's a been a bit hard to debug and replicate.
I know this may be outside the purview of the project, but if you have any pointers on where I can look to track this down, that would be really helpful.
Thanks!

Ah never mind, I figured it out. Thanks!

No problem.
I had created my own middleware that checks the URL and forwards the user if it's invalid using 	http.Redirect(...). The problem was there wasn't a "return" after that so there was further writing to the headers later on.

Ah, I gotcha. Thanks!


Change 'srv' to 'srv2'

Most servers these days will be running SMB2.0 at least by default, so Srv2 will be in use. The way the guide is currently written, if Srv does not exist (i.e. SMB1 is not installed on the server), then the LanManServer service fails to start.

@c4bler Thanks for your contribution, we'll proceed to handle the changes.

@c4bler The changes are live at https://learn.microsoft.com/en-us/troubleshoot/windows-server/backup-and-storage/file-shares-on-iscsi-devices-not-recreated. This PR will be closed.


Improve quality checks and lint the code

Issue: #38

@ziima
The available tox environments are now:

test:
Run all the Python/Django test environments.
check:
Run all the check environments.
parallel-test:
Run all the Python/Django test environments in parallel.
parallel-check:
Run all the check environments in parallel.
parallel-all:
Run all the environments in parallel.
build-docs:
Build the documentation locally.
check-setup:
Check that the package will be correctly installed and correctly rendered on PyPI.
check-bandit:
Run bandit tool on the code.
check-safety:
Check that the requirements versions do not have security vulnerabilities.
check-black:
Run black tool on the code.
check-isort:
Check the imports order.
check-pylint:
Check the code style.
check-docs-spell:
Check the spelling in the documentation.
check-docs-link:
Check that the links written in documentation are valid.
run-black:
Run black tool on the code.
run-isort:
Check the imports order.
run-bumpversion:
Check the imports order.
report:
Create coverage report.
clean:
Delete coverage report.
codacy:
Upload coverage report to codacy.

Also:

Configuration for tools has been moved in respective files in config directory. It was before all in setup.cfg.
Prospector has been changed for pylint. Pylint job is allowed to fail on CI.
MANIFEST.in has been simplified, and will reduce the size of the built packages.
Line length set to 120.
Pandas and Django sections removed from isort config.
Ran black and isort on the code.
Travis config updated to reflect the changes.

I'm not sure that moving the config files into config directory is a good move. For example various editor plugins will not find their configuration in there. I don't really mind using setup.cfg for these.

I think you generally can configure these plugins to give the location of the config file. I myself use PyCharm and you can configure your external tools and set up parameters for execution so everything is possible. However, I don't use any external tool in my IDE, so I reverted that back, just in case. Config is now in setup.cfg, except for black which has its config in pyproject.toml.

I'm not very favor of pylint for the number of false positives it produces. I can recommend flake8 instead.

I agree. Replaced pylint with flake8.

I have never thought about using tox for anything else but code checks and tests. What's your experience with using tox for code modification?

Actually a lot of people seem to use tox as some kind of make tool. So not only I'm used to write test environments and "check" environments, but also environments that will perform some action on the code. It usually works well and can reduce the friction for new contributors, as everything you need is in tox and tox takes care of installing the tools needed.

isort and black now conflict with each other on the trailing comma in imports... :confused:

Closing in favor of #45.


Azure Application Insights libraries for .NET Documentation - Broken link

"Application Insights Analytics with OpenSchema" link is broken

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

ID: 3628e326-be45-e441-eb62-627b721d3e70
Version Independent ID: e4e26910-eda8-a7f8-de42-150232c24a8b
Content: Azure Application Insights libraries for .NET - Azure for .NET Developers
Content Source: api/overview/azure/insights.md
Service: application-insights
GitHub Login: @CamSoper
Microsoft Alias: casoper

Thank you for your feedback.  Tagging and routing to the team best able to assist.

@reyang can you please forward to the appropriate person on the AppInsights team?

@reyang can you please forward to the appropriate person on the AppInsights team?

Sorry @pakrym I don't know the appropriate person.

https://github.com/Azure/azure-docs-sdk-dotnet/pull/2091


Added the Exponet calculator

Issue no #174
Description👨💻
Exponent Calculator: Which takes two numbers X and Y and then calculate XY.
Type of change📄

[X] New feature (non-breaking change which adds functionality)

How this has been tested✅
First I have tested it on my PC and It will work correctly on my PC.
Checklist✅

[X] My code follows the style guidelines of this project
[X] I have performed a self-review of my own code
[X] I have commented my code, particularly in hard-to-understand areas
[X] I have added demonstration in the form of GIF/video file
[X] I am an Open Source Contributor

Screenshots/GIF📷

@Rakesh9100, I have added the exponent calculator. Please Check it out and If It is fine then please merge to the main branch.

Pls keep your folder name as Exponent-Calculator by using hyphen.
Handle NaN value in the calculator as now when clicking on Calculate without entering any number, it is showing one which should not @Parmesh119

@Rakesh9100 Now please check it.

Good, Merged!! Congrats on getting your PR merged to this repo under SWOC S4 🎉🎉 @Parmesh119

@Rakesh9100, I also need your help regarding GSoC.
Can we talk on LinkedIn or on Twitter?


How to train it on another data set? how can I handle checkpoint?

Hi, kwotsin! Thanks for your work.
I want to train it on another data set (class number is 30 instead of 12). I thought I had changed related codes. But I met this error:
2018-01-11 17:23:22.187077: W tensorflow/core/framework/op_kernel.cc:1158] Invalid argument: Input to reshape is a tensor with 172800 values, but the requested shape has 4320000
I thought it may be caused by checkpoint? How can I deal with this problem?
The completed information is as follow:
========= Median Frequency Balancing Class Weights =========
[6.397542327061094e-05, 6.7097626201794152e-05, 0.024400273767542283, 0.041269401614453756, 5.5506352412896832e-05, 0.076635711324892844, 0.069381256179271614, 3.472654196521944e-05, 0.00042760164428717635, 0.00012440287198120186, 0.090233329139976615, 0.12489918060211183, 0.0013708685331902757, 6.0827765291491662e-05, 0.073240128809290553, 0.35775514055273316, 0.64257341685305103, 0.90968868010977944, 0.37688909228806228, 0.44248634385452756, 0.00042529101230680852, 0.30566376891079095, 0.28941152643298945, 3.9464190165066867e-05, 0.26421036878629223, 0.42250536299160169, 0.5089356784417215, 0.00024742224929701886, 0.47265314480960613, 0.0]
2018-01-11 17:22:23.528595: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2018-01-11 17:22:23.528689: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2018-01-11 17:22:23.528720: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2018-01-11 17:22:29.254935: I tensorflow/core/common_runtime/gpu/gpu_device.cc:940] Found device 0 with properties:
name: Tesla K40c
major: 3 minor: 5 memoryClockRate (GHz) 0.745
pciBusID 0000:02:00.0
Total memory: 11.17GiB
Free memory: 11.10GiB
2018-01-11 17:22:29.503633: W tensorflow/stream_executor/cuda/cuda_driver.cc:523] A non-primary context 0x1e106f80 exists before initializing the StreamExecutor. We haven't verified StreamExecutor works with that.
2018-01-11 17:22:29.504523: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:893] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2018-01-11 17:22:29.505315: I tensorflow/core/common_runtime/gpu/gpu_device.cc:940] Found device 1 with properties:
name: Tesla K40c
major: 3 minor: 5 memoryClockRate (GHz) 0.745
pciBusID 0000:84:00.0
Total memory: 11.17GiB
Free memory: 11.10GiB
2018-01-11 17:22:29.505448: I tensorflow/core/common_runtime/gpu/gpu_device.cc:832] Peer access not supported between device ordinals 0 and 1
2018-01-11 17:22:29.505491: I tensorflow/core/common_runtime/gpu/gpu_device.cc:832] Peer access not supported between device ordinals 1 and 0
2018-01-11 17:22:29.505540: I tensorflow/core/common_runtime/gpu/gpu_device.cc:961] DMA: 0 1
2018-01-11 17:22:29.505685: I tensorflow/core/common_runtime/gpu/gpu_device.cc:971] 0:   Y N
2018-01-11 17:22:29.505705: I tensorflow/core/common_runtime/gpu/gpu_device.cc:971] 1:   N Y
2018-01-11 17:22:29.505740: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1030] Creating TensorFlow device (/gpu:0) -> (device: 0, name: Tesla K40c, pci bus id: 0000:02:00.0)
2018-01-11 17:22:29.505779: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1030] Creating TensorFlow device (/gpu:1) -> (device: 1, name: Tesla K40c, pci bus id: 0000:84:00.0)
2018-01-11 17:22:34.391659: I tensorflow/core/common_runtime/gpu/pool_allocator.cc:247] PoolAllocator: After 1368 get requests, put_count=1100 evicted_count=1000 eviction_rate=0.909091 and unsatisfied allocation rate=1
2018-01-11 17:22:34.391731: I tensorflow/core/common_runtime/gpu/pool_allocator.cc:259] Raising pool_size_limit_ from 100 to 110
INFO:tensorflow:Starting standard services.
INFO:tensorflow:Starting queue runners.
INFO:tensorflow:Saving checkpoint to path ./log/original/model.ckpt
INFO:tensorflow:global_step/sec: 0
INFO:tensorflow:Epoch 1/300
INFO:tensorflow:Current Learning Rate: [0.00050000002]
INFO:tensorflow:global step 1: loss: 0.3121 (4.79 sec/step)    Current Streaming Accuracy: 0.0000    Current Mean IOU: 0.0000
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0000    Validation Mean IOU: 0.0000    (2.24 sec/step)
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0209    Validation Mean IOU: 0.0030    (1.10 sec/step)
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0207    Validation Mean IOU: 0.0028    (1.26 sec/step)
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0227    Validation Mean IOU: 0.0033    (1.23 sec/step)
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0220    Validation Mean IOU: 0.0035    (1.24 sec/step)
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0208    Validation Mean IOU: 0.0033    (1.28 sec/step)
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0201    Validation Mean IOU: 0.0033    (1.22 sec/step)
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0198    Validation Mean IOU: 0.0032    (1.25 sec/step)
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0197    Validation Mean IOU: 0.0032    (1.24 sec/step)
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0196    Validation Mean IOU: 0.0031    (1.21 sec/step)
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0197    Validation Mean IOU: 0.0031    (1.18 sec/step)
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0196    Validation Mean IOU: 0.0031    (1.21 sec/step)
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0196    Validation Mean IOU: 0.0031    (1.39 sec/step)
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0196    Validation Mean IOU: 0.0032    (1.23 sec/step)
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0196    Validation Mean IOU: 0.0032    (1.18 sec/step)
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0193    Validation Mean IOU: 0.0032    (1.16 sec/step)
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0191    Validation Mean IOU: 0.0031    (1.41 sec/step)
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0193    Validation Mean IOU: 0.0031    (1.26 sec/step)
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0195    Validation Mean IOU: 0.0032    (1.43 sec/step)
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0197    Validation Mean IOU: 0.0032    (1.32 sec/step)
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0202    Validation Mean IOU: 0.0033    (1.34 sec/step)
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0204    Validation Mean IOU: 0.0034    (1.33 sec/step)
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0203    Validation Mean IOU: 0.0034    (1.21 sec/step)
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0206    Validation Mean IOU: 0.0034    (1.36 sec/step)
2018-01-11 17:23:21.808311: W tensorflow/core/framework/op_kernel.cc:1158] Invalid argument: assertion failed: [all dims of 'image.shape' must be > 0.]
[[Node: assert_positive_11/assert_less/Assert/Assert = Assert[T=[DT_STRING], summarize=3, _device="/job:localhost/replica:0/task:0/cpu:0"](assert_positive_11/assert_less/All/_5795, assert_positive_11/assert_less/Assert/Assert/data_0)]]
INFO:tensorflow:Error reported to Coordinator: <class 'tensorflow.python.framework.errors_impl.InvalidArgumentError'>, assertion failed: [all dims of 'image.shape' must be > 0.]
[[Node: assert_positive_11/assert_less/Assert/Assert = Assert[T=[DT_STRING], summarize=3, _device="/job:localhost/replica:0/task:0/cpu:0"](assert_positive_11/assert_less/All/_5795, assert_positive_11/assert_less/Assert/Assert/data_0)]]
INFO:tensorflow:---VALIDATION--- Validation Accuracy: 0.0207    Validation Mean IOU: 0.0035    (1.19 sec/step)
2018-01-11 17:23:22.187077: W tensorflow/core/framework/op_kernel.cc:1158] Invalid argument: Input to reshape is a tensor with 172800 values, but the requested shape has 4320000
[[Node: Reshape_5 = Reshape[T=DT_UINT8, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/gpu:0"](batch_1/_5971, Reshape_5/shape)]]
2018-01-11 17:23:22.197319: W tensorflow/core/framework/op_kernel.cc:1158] Invalid argument: Input to reshape is a tensor with 172800 values, but the requested shape has 4320000
[[Node: Reshape_5 = Reshape[T=DT_UINT8, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/gpu:0"](batch_1/5971, Reshape_5/shape)]]
Traceback (most recent call last):
File "train_enet.py", line 340, in
run()
File "train_enet.py", line 337, in run
plt.savefig(photo_dir+"/image" + str(i))
File "/usr/lib64/python2.7/contextlib.py", line 35, in exit
self.gen.throw(type, value, traceback)
File "/usr/lib/python2.7/site-packages/tensorflow/python/training/supervisor.py", line 964, in managed_session
self.stop(close_summary_writer=close_summary_writer)
File "/usr/lib/python2.7/site-packages/tensorflow/python/training/supervisor.py", line 792, in stop
stop_grace_period_secs=self._stop_grace_secs)
File "/usr/lib/python2.7/site-packages/tensorflow/python/training/coordinator.py", line 389, in join
six.reraise(*self._exc_info_to_raise)
File "/usr/lib/python2.7/site-packages/tensorflow/python/training/queue_runner_impl.py", line 238, in _run
enqueue_callable()
File "/usr/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1063, in _single_operation_run
target_list_as_strings, status, None)
File "/usr/lib64/python2.7/contextlib.py", line 24, in exit
self.gen.next()
File "/usr/lib/python2.7/site-packages/tensorflow/python/framework/errors_impl.py", line 466, in raise_exception_on_not_ok_status
pywrap_tensorflow.TF_GetCode(status))
tensorflow.python.framework.errors_impl.InvalidArgumentError: assertion failed: [all dims of 'image.shape' must be > 0.]
[[Node: assert_positive_11/assert_less/Assert/Assert = Assert[T=[DT_STRING], summarize=3, _device="/job:localhost/replica:0/task:0/cpu:0"](assert_positive_11/assert_less/All/_5795, assert_positive_11/assert_less/Assert/Assert/data_0)]]

have you figured out how it works? I trained on my own dataset as well, but the accuracy is so low..

heollo, @changlinzhang @kwotsin  could you tell me how to use the files in the checkpoint folder as the pretrain model to train my own dataset?

I faced same problem.
In my case, I remade annotation images not including value of '255' and works.
https://github.com/DrSleep/tensorflow-deeplab-resnet/issues/107#issuecomment-325857231

@RobinHan24 I met the same problem.I have 10 classes,according my classes,I set the pixels of my label images to 0 to 9,then the problem fixed.I don't wither it is helpful for you?

thanks for this useful repo
hi everyone if anyone could help me out to solve this issue

the current code works for camvid dataset,
am facing a difficulty in training this ENet model with cityscapes dataset :
which i tried using https://github.com/mcordts/cityscapesScripts and got trained data,
now i would like to import this similar data in this code but states dimension miss match, could you please help me to fix this grey scale image insertion as i have 4types(color.png,instance.png,labeld.png,json.png,trainid.png) of labeling after training the data. how to choose anyone from this folder and import in this model
i tried for single type of images and got error:

InvalidArgumentError (see above for traceback): assertion failed: [labels out of bound] [Condition x < y did not hold element-wise:] [x (mean_iou/confusion_matrix/control_dependency:0) = ] [0 0 0...] [y (mean_iou/ToInt64_1:0) = ] [12]
[[node mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert (defined at /usr/local/lib/python2.7/dist-packages/tensorflow/contrib/metrics/python/ops/metric_ops.py:3561)  = Assert[T=[DT_STRING, DT_STRING, DT_STRING, DT_INT64, DT_STRING, DT_INT64], summarize=3, _device="/job:localhost/replica:0/task:0/device:CPU:0"](mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/Switch, mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/data_0, mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/data_1, mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/data_2, mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/Switch_1, mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/data_4, mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/Switch_2)]]
as i am beginner to this field so, hoping for suggestions to resolve this error.


Add cohesive Teleoperate Objective

This reworks teleoperation by using a single Objective that allows switching modes between the UI, vs. a bunch of disparate Objectives for each time of user control.
Critically, this allows teleoperation not only as a standalone UI interaction with the "Teleoperate Standalone" Objective, but as part of an Objective by bringing in "Teleoperate" as a subtree.
I'm not super married to the naming, and very open to suggestions.

NOTE: Integration tests failing here is expected because we're calling a new Behavior that's part of an upstream PR for this. I think it might be beneficial for me to maybe break that out and merge it first...


Icons not showing bundled in Angular

I have created a bundle file of some Icons as described in this article:
https://iconify.design/docs/icon-bundles/. Everything went fine with that. Now when I use those icons in a static HTML file like in the guide then everything works fine. If I start using the icons in for example a ngIf directive then they do not show, there is not error in the console. It just does not get replaced with the SVG. If I move away from the bundle file and to the online version then the icons start showing again.

Angular is a special case, it freaks out when something is happening to DOM.
I suggest to try Angular component instead: https://github.com/iconify/iconify-angular

Actually the documentation says that it works well with Angular and as mentioned it does work with the online version that is why I am confused.

Can you try replacing Iconify with files from attached package?
iconify-2.0.0-dev-20Mar20.zip
If you are using Iconify as NPM package, replace files from dist with attached files. If you are including Iconify remotely, link to iconify.min.js from attached file.
Attached file is early alpha of Iconify 2.0. It was completely rewritten from ground up and handles icons differently. Maybe it will solve issue.
You will also need to change bundle a bit. In bundle file replace SimpleSVG.addCollection with Iconify.addCollection. It was legacy code to support old version. I'll replace it in tools package soon.

I am sorry I was asked to move away from this task now, I hope I can get back to it not too long from today then I will give you some feedback. Thanks for looking into it


Very bad render/mesh - NeuS

I tested the 3D reconstruction on the batman sample example provided and the render video and .ply look terrible. Any advice?
https://github.com/Wi-sc/ViewFusion/assets/150967838/c1d30edb-dd8e-44b2-b6fc-0b146f0f5d63
https://github.com/Wi-sc/ViewFusion/assets/150967838/65cde044-6c71-4294-a5e2-87827006193b

Hi @hadillivvy ,
I just tested my code again, and it shouldn't be. Your problem is that the multi-view images are bad, not by the NeuS.
Can you provide more details? What model are you using? Have you checked the dataloader as the initial frame of the video seems broken?

Hey @hadillivvy ,
Thanks for the clarification. I have re-produced your issue on the batman image, while I have also run the pokeman images and the reconstruced 3d model looks well. So I think that is not a bug from the code.
I believe the issue here is because the batman is a thin and tall 3d object, with lots of details (cloak, belt, arms, masks, legs). We didn't focus on the NeuS training in our paper and the training scripts and weights are stolen from SyncDreamer. Maybe you can try to reduce the weight of eikonal loss for NeuS and have a try.
Sorry for the inconvenience. If you have any insights on this issue, just comment here. Let's make the model better!


Stream upload file in new version 5.16.0

Environment details

OS: MacOs
Node.js version: 16.8
npm version: 7.21.0
@google-cloud/storage version: 5.16.0

Steps to reproduce
Not working upload stream file as:
https://github.com/googleapis/nodejs-storage/blob/main/samples/streamFileUpload.js
Expected result
In version 5.15.6 works.

I'm not able to reproduce this locally. When I check out node-js storage and do the following:
cd samples
npm install
cd ..
node samples/streamFileUpload.js mybucket myfile

It works fine, and I can see that the file successfully uploads. Additionally, we have system tests that test that sample, and they're passing. Can you share your exact code so I can see if there's any problem with how you're doing it?

Closing due to inactivity. Please re-open with the requested information if this is still an issue.

@JesseLovelace file is uploading but not readable
Sample file attached
TestDeepak.pdf
Did exactly what you mentioned
cd samples
npm install
cd ..
node samples/streamFileUpload.js mybucket myfile
Thanks
Deepak


[MB-15068] show fadd details received from ghc prime

Jira ticket for this change
Summary
I verified that the data is properly handled both on the backend and frontend. The issue lied at the point in the go code where Domestic destination add'l SIT & Domestic destination SIT delivery are being automatically generated. Once I identified that, I hardcoded some customer contact information and it displayed properly for the TOO! :fiesta_parrot: So that looks like it's good to go, I would appreciate some input on whether or not I should leave that hardcoded customer contact info in my PR since this other ticket handles setting up inputs for the Prime to submit their own information for these currently auto-generated fields, otherwise the PR is just going to be some front end refactoring I did to clean up the JSX that displays this information along with small changes to the copy to match the AC for the ticket.
Setup to Run Your Code

💻 You will need to use three separate terminals to test this locally.
Terminal 1
Start the Storybook locally.
make storybook

Terminal 2
Start the UI locally.
make client_run

Terminal 3
Start the Go server locally.
make server_run

Additional steps

Access the S1TT3R move as a Prime user and add a new service item, selecting Destination SIT from the service item type dropdown.
Login as a TOO and access the same move
Navigate to the move task order tab and you should see the information being displayed at the bottom of the page

Verification Steps for Author
These are to be checked by the author.

[x] Have the Jira acceptance criteria been met for this change?

Verification Steps for Reviewers
These are to be checked by a reviewer.

Frontend

[ ] User facing changes have been reviewed by design.
[ ] There are no aXe warnings for UI.
[ ] This works in Supported Browsers and their phone views (Chrome, Firefox, IE, Edge).
[ ] There are no new console errors in the browser devtools
[ ] There are no new console errors in the test output
[ ] If this PR adds a new component to Storybook, it ensures the component is fully responsive, OR if it is intentionally not, a wrapping div using the officeApp class or custom min-width styling is used to hide any states the would not be visible to the user.

Backend

[ ] Code follows the guidelines for Logging
[ ] The requirements listed in Querying the Database Safely have been satisfied.

Screenshots

Warnings

:warning:
This PR does not include changes to unit tests, even though it affects app code.

Messages

:book:
:link: MB-15068

  Generated by :no_entry_sign: dangerJS against 946f9b21fdf34cfb992d0ab35db25712825641bf

Hey @ruizajtruss I find the A/C calls out the field like this

I don't see a review is requested anymore but I would have asked for changes.

Hey @ruizajtruss I find the A/C calls out the field like this
 I don't see a review is requested anymore but I would have asked for changes.

Yes, moved back to draft for some changes but I appreciate your comment. That screenshot looks different from what was listed in my ticket; so thank you for the clarification!


feat: add namedExports option to css modules config

Description
Currently cssPostPlugin is using hardcoded value (true) for namedExports to generate classes mapping.
In my project namedExports: true, duplicates the classes map file size generated based on css file.
NOTE: namedExports: true, is great to have when css file contains a lot of overrides for same css class. But if the css file has distinct classes it is not optimal to have namedExports
What is the purpose of this pull request?

[ ] Bug fix
[X] New Feature
[ ] Documentation update
[ ] Other

Before submitting the PR, please make sure you do the following

[x] Read the Contributing Guidelines.
[x] Read the Pull Request Guidelines and follow the Commit Convention.
[x] Check that there isn't already a PR that solves the problem the same way to avoid creating a duplicate.
[x] Provide a description in this PR that addresses what the PR is solving, or reference the issue that it solves (e.g. fixes #123).
[ ] Ideally, include relevant tests that fail without this PR but pass with it.

In my project namedExports: true, duplicates the classes map file size generated based on css file.

Would you expand this? I tested a bit but didn't find a case that happens.

@sapphi-red
ex. test.module.css
.classA {
  width: '100px';
}
.classB {
  width: '100px';
}
.classC {
  width: '100px';
}

test.tsx
import classes from './test.module.css';

export default function Test() {
  return <div className={`${classes.classA} ${classes.classB} ${classes.classC}`}>test
;
}

After build, output is test.js
import { jsx as a } from "react/jsx-runtime";
const c = "_classA_aar66_1", l = "_classB_aar66_5", t = "_classC_aar66_9", s = {
  classA: c,
  classB: l,
  classC: t
};
function _() {
  return /* @__PURE__ */ a("div", {
    className: `${s.classA} ${s.classB} ${s.classC}`,
    children: "test"
  });
}
export {
  _ as default
};

I want in output instead of
const c = "_classA_aar66_1", l = "_classB_aar66_5", t = "_classC_aar66_9", s = {
  classA: c,
  classB: l,
  classC: t
};

to have
const s = {
  classA: "_classA_aar66_1",
  classB: "_classB_aar66_5",
  classC: "_classC_aar66_9"
};

@sapphi-red Could you take a look on the provided example?

@patak-dev @sapphi-red
Guys, can you take a look on this change?

Ideally variable inlining is better to be done with minifier. But I guess this won't be supported soon.
Given that most users won't mix using default import and named import, I think it's better to change this part to:
dataToEsm(modules, {
  namedExports: true
  preferConst: true
}).replace(/^export default {.+$/, '') + dataToEsm(modules, {
  namedExports: false
  preferConst: true
})

rather than adding an option for this.


Inconsistency between Ollama REST API and CLI Model List causing model accessibility issues

Summary
There's a critical inconsistency between models listed via Ollama's REST API endpoint (curl http:// localhost:11434/api/tags) and the CLI command (ollama list). This leads to models being accessible through
only one interface (either CLI or Python client) despite being physically present in the system (see the logs at to view descrepency).
Description
Previously, Ollama had a consistent behaviour: all models were downloaded to .ollama\models\blobs, and both the CLI (ollama list) and REST API showed the same models. However, something has changed in how Ollama manages model storage, leading to a split in model accessibility between the CLI and REST API interfaces.
Timeline of Issue Discovery

Initial State (Before Issue):

All models were stored in .ollama\models\blobs
Models were accessible via both CLI and Python client
ollama list and REST API showed identical model lists

Issue Detection:

Noticed phi3:14b-medium-128k-instruct-q4_K_M was suddenly the only model visible in ollama list
Started redownloading needed models (hermes3 and qwen)
Later discovered via curl http://localhost:11434/api/tags that original models were still listed
Confirmed original model files still present in .ollama\models\blobs
However, newly downloaded models' files were not appearing in .ollama\models\blobs

Current Behaviour

Split Storage Behaviour:

Original models:

Still physically present in .ollama\models\blobs
Visible via REST API (curl http://localhost:11434/api/tags)
Accessible through Python client
Invisible to CLI (ollama list)

Newly downloaded models:

Stored in unknown location (not in .ollama\models\blobs)
Visible via CLI
Not accessible through Python client

Example of the Inconsistency:
# Using curl to query Ollama's REST API
curl http://localhost:11434/api/tags
{
    "models": [
        {
            "name": "qwen2.5:14b-instruct-q4_K_M",
            "model": "qwen2.5:14b-instruct-q4_K_M",
            "size":<PHONE_NUMBER>,
            "digest": "7cdf5a0187d5..."
        }
    ]
}

# Using Ollama CLI
ollama list
NAME                    ID              SIZE      MODIFIED
qwen2.5:14b            7cdf5a0187d5    9.0 GB    23 hours ago

Note that despite showing different model names, they reference the same model (same ID: 7cdf5a0187d5). Same happened with hermes3:latest.

Model accessibility is split between interfaces:

Python client (which uses the REST API):from ollama import Client
client = Client(host='http://localhost:11434')

messages = [{"role": "user", "content": "What is the capital of France?"}]
# Works - model name from REST API
client.chat(model="qwen2.5:14b-instruct-q4_K_M", messages=messages, format="json") # Success

# Fails - model name from CLI list
response = client.chat(model="qwen2.5:14b", messages=messages, format="json") # Fails with "model not found"

CLI:# Works - model name from CLI list
ollama run qwen2.5:14b  # Success

# Fails - model name from REST API
ollama run qwen2.5:14b-instruct-q4_K_M  # Attempted to redownload - completed in under a second which is obivously is not possible for a 9GB model but the fact that it had the same ID as the blob file means it just used the existing file (qwen2.5:14b). qwen2.5:14b redownloaded as expected despite qwen2.5:14b-instruct-q4_K_M being present in the blobs directory.

Redownloading models:

Models that maintain the same name in both interfaces (e.g., hermes3:latest) work across both interfaces after redownload
Models with different names (e.g., Qwen variants) maintain the split behaviour

I think the .ollama\models\blobs directory is no longer recognised by the CLI, although it is still utilised by the Python client. This discrepancy explains why the Python client can access the original models, while the CLI cannot.
Here's what happened in sequence:

I noticed my models were missing from the CLI, so I redownloaded models like hermes3 and qwen2.5:14b
Later, I discovered that my original model files were actually still present in the blobs directory
I then tried to run qwen2.5:14b-instruct-q4_K_M (the name of the model in the original blob file) , instead of calling the original version from the blobs directory, Ollama pointed to the newly downloaded qwen2.5:14b (hence why both share the same ID)

So it seems that Ollama is now storing models in a different directory.
Expected Behaviour

Ollama should maintain a single, consistent model storage location (traditionally .ollama\models\blobs)
Both CLI and REST API should:
Both REST API (curl http://localhost:11434/api/tags) and CLI (ollama list) should show the same list of models
Models should be accessible through both CLI and Python client
Ollama should store allmodels in the .ollama\models\blobs directory

System Information

OS: Windows 10
Original Models Location: C:\Users\Nason\.ollama\models\blobs
New Models Location: Unknown (not in traditional blob storage location)

Additional Notes

This appears to be a regression in Ollama's model storage management
The split between CLI and REST API suggests a fundamental change in how Ollama manages model storage
Despite the storage/accessibility issues, models function correctly when successfully accessed
The presence of original model files in blobs directory but invisibility to CLI suggests a broken link in Ollama's model registry system

Any advice or help on fixing this issue and getting back to the usual behaviour would be greatly appreciated.
Logs
Z:\nas\projects\deep_thinker> ollama list
NAME                                                          ID              SIZE      MODIFIED
hf.co/bartowski/deepthought-8b-llama-v0.01-alpha-GGUF:Q6_K    94820e8abf2f    6.6 GB    41 minutes ago
qwen2.5:14b                                                   7cdf5a0187d5    9.0 GB    22 hours ago
hermes3:latest                                                b5c6c7cb379d    4.7 GB    23 hours ago
phi3:14b-medium-128k-instruct-q4_K_M                          1372226c9b0b    8.6 GB    2 weeks ago

Z:\nas\projects\deep_thinker>curl http: //localhost:11434/api/tags
{
    "models": [
        {
            "name": "phi3:14b-medium-128k-instruct-q4_K_M",
            "model": "phi3:14b-medium-128k-instruct-q4_K_M",
            "modified_at": "2024-11-21T02:29:23.846191Z",
            "size":<PHONE_NUMBER>,
            "digest": "1372226c9b0b61f3c693ef9dc54ec646d4cd75347eca849a76a04de22e350517",
            "details": {
                "parent_model": "",
                "format": "gguf",
                "family": "phi3",
                "families": [
                    "phi3"
                ],
                "parameter_size": "14.0B",
                "quantization_level": "Q4_K_M"
            }
        },
        {
            "name": "qwen2.5:14b-instruct-q4_K_M",
            "model": "qwen2.5:14b-instruct-q4_K_M",
            "modified_at": "2024-10-22T06:01:07.5828927+01:00",
            "size":<PHONE_NUMBER>,
            "digest": "7cdf5a0187d5c58cc5d369b255592f7841d1c4696d45a8c8a9489440385b22f6",
            "details": {
                "parent_model": "",
                "format": "gguf",
                "family": "qwen2",
                "families": [
                    "qwen2"
                ],
                "parameter_size": "14.8B",
                "quantization_level": "Q4_K_M"
            }
        },
        {
            "name": "hermes3:latest",
            "model": "hermes3:latest",
            "modified_at": "2024-10-12T04:44:51.4633447+01:00",
            "size":<PHONE_NUMBER>,
            "digest": "b5c6c7cb379dae220c8525ae71c4f025f4f85157070d594318b1764c882b217d",
            "details": {
                "parent_model": "",
                "format": "gguf",
                "family": "llama",
                "families": [
                    "llama"
                ],
                "parameter_size": "8.0B",
                "quantization_level": "Q4_0"
            }
        },
        ...
        {
            "name": "gemma2:9b",
            "model": "gemma2:9b",
            "modified_at": "2024-07-19T17:45:43.0850279+01:00",
            "size":<PHONE_NUMBER>,
            "digest": "ff02c3702f322b9e075e9568332d96c0a7028002f1a5a056e0a6784320a4db0b",
            "details": {
                "parent_model": "",
                "format": "gguf",
                "family": "gemma2",
                "families": [
                    "gemma2"
                ],
                "parameter_size": "9.2B",
                "quantization_level": "Q4_0"
            }
        }
    ]
}

Note different time stamps for hermes3:latest.
Also note Phi's time stamps is from 2 weeks ago, it was the only model to survive whatever issue this is.

Testing models present in ollama list
Z:\nas\projects\deep_thinker>ollama run qwen2.5: 14b
>>> hi, tell me about yourself
Hello! I'm Qwen, an AI assistant developed by Alibaba Cloud. My purpose is to assist users like you in generating text on
various topics, answering questions, providing explanations, and helping with creative writing tasks. Whether you need
information, want to have a conversation, or are looking for assistance with something specific, feel free to ask me anything!

>>> /bye

Z:\nas\projects\deep_thinker>ollama run hf.co/bartowski/deepthought-8b-llama-v0.01-alpha-GGUF:Q6_K
>>> hi, tell me about yourself
The user has requested information about myself. This is a personal introduction task that requires crafting a concise
yet informative response about my background, interests, and personality."
  },
  {
    "step": 2,
    "type": "data_gathering",
    "thought": "I need to collect relevant information about myself. As an AI language model, I don't have personal
experiences or emotions, but I can provide information about my capabilities and the nature of my existence."
  },
  {
    "step": 3,
    "type": "synthesis",
    "thought": "Based on the gathered information, I'll create a comprehensive yet concise description of myself: 'I am
an AI language model designed to assist and communicate with humans. My purpose is to provide information, answer
questions, and engage in conversation based on my training data.'"
  },
  ...

So models from ollama list can be used with the CLI.
Testing a model only present in the api list
Z:\nas\projects\deep_thinker>ollama run gemma2: 9b
pulling manifest
pulling ff1d1fc78170...   0% ▕                                                                   ▏ 8.9 MB/5.4 GB  4.3 MB/s  21m12^
C

Z:\nas\projects\deep_thinker>
Z:\nas\projects\deep_thinker>ollama run mistral:v0.3
pulling manifest
pulling ff82381e2bea...   0% ▕                                                                                ▏ 2.3 MB/4.1 GB                  ^C

Models from the API list can NOT be used with the CLI.
Testing client
Gemma works fine through the python client
from ollama import Client

client = Client(host='http://localhost:11434')
response = client.chat(
    model="gemma2:9b",
    messages=[{"role": "user", "content": "What is the capital of France?"}],
)

response
{'model': 'gemma2:9b',
 'created_at': '2024-12-05T18:41:41.508362Z',
 'message': {'role': 'assistant',
  'content': '{\n\n  "capitalOfFrance": "Paris" \n\n}'},
 ...}

The new qwen2.5 does not work through the python client
 response = client.chat(
    model="qwen2.5:14b",
    messages=[{"role": "user", "content": "What is the capital of France?"}],
)

response
File c:\Users\Nason\anaconda3\envs\agent_studio\lib\site-packages\ollama\_client.py:74, in Client._request(self, method, url, **kwargs)
     72   response.raise_for_status()
     73 except httpx.HTTPStatusError as e:
---> 74   raise ResponseError(e.response.text, e.response.status_code) from None
     76 return response

ResponseError: model "qwen2.5:14b" not found, try pulling it first

The new deepthought-8b does not work through the python client
client = Client(host='http://localhost:11434')
response = client.chat(
    model="hf.co/bartowski/deepthought-8b-llama-v0.01-alpha-GGUF:Q6_K",
    messages=[{"role": "user", "content": "What is the capital of France?"}],
)

response
File c:\Users\Nason\anaconda3\envs\agent_studio\lib\site-packages\ollama\_client.py:74, in Client._request(self, method, url, **kwargs)
     72   response.raise_for_status()
     73 except httpx.HTTPStatusError as e:
---> 74   raise ResponseError(e.response.text, e.response.status_code) from None
     76 return response

ResponseError: model "hf.co/bartowski/deepthought-8b-llama-v0.01-alpha-GGUF:Q6_K" not found, try pulling it first

Old qwen2.5:14b does work through the python client
response = client.chat(
    model="qwen2.5:14b-instruct-q4_K_M",
    messages=[{"role": "user", "content": "What is the capital of France?"}],
)

response
{'model': 'qwen2.5:14b-instruct-q4_K_M',
 'created_at': '2024-12-05T19:59:09.3711764Z',
 'message': {'role': 'assistant',
  'content': 'The capital of France is Paris.'},
  ...}

So in summary the logs and testing demonstrate that the python client can access the original models but not the redownloaded models, and that the CLI can access the redownloaded models but not the original models.
OS
Windows
GPU
Nvidia
CPU
AMD
Ollama version
0.4.2

You are likely running two servers.  Do ollama -v and curl http://localhost:11434/api/version show the same results?  Have you previously installed ollama in WSL?  Does tasklist show any ollama processes?

Also try running this in a PowerShell in administrator mode:
netstat -bano | Select-String -Pattern 11434 -Context 0,1

Thanks for the speedy response. Tried killing any ollama servers running and starting back up but had no luck. I did install ollama in a wsl environment weeks ago, but I've not used that WSL enviroment in 2 weeks but have been using ollama daily until now.
(base) PS Z:\nas\projects\deep_thinker> Get-Process | Where-Object {$_.ProcessName -like 'ollama'} | kill
(base) PS Z:\nas\projects\deep_thinker>  taskkill /fi "imagename eq ollama app.exe"

INFO: No tasks running with the specified criteria.
(base) PS Z:\nas\projects\deep_thinker> ollama -v
ollama version is 0.4.2
(base) PS Z:\nas\projects\deep_thinker> curl http://localhost:11434/api/version

StatusCode        : 200
StatusDescription : OK
Content           : {"version":"0.4.2"}
RawContent        : HTTP/1.1 200 OK
                    Content-Length: 19
                    Content-Type: application/json; charset=utf-8
                    Date: Thu, 05 Dec 2024 20:46:16 GMT

                    {"version":"0.4.2"}
Forms             : {}
Headers           : {[Content-Length, 19], [Content-Type, application/json; charset=utf-8], [Date, Thu, 05 Dec 2024
                    20:46:16 GMT]}
Images            : {}
InputFields       : {}
Links             : {}
ParsedHtml        : mshtml.HTMLDocumentClass
RawContentLength  : 19

>   TCP    <IP_ADDRESS>:11434        <IP_ADDRESS>:0              LISTENING       38128
   [wslrelay.exe]

You have an ollama server running in a WSL container.

Bingo, that was the issue.
(base) PS Z:\nas\projects\deep_thinker> ollama list
NAME                                                          ID              SIZE      MODIFIED
qwen2.5:14b-instruct-q4_K_M                                   7cdf5a0187d5    9.0 GB    3 hours ago
qwen2.5:14b                                                   7cdf5a0187d5    9.0 GB    25 hours ago
hermes3:latest                                                b5c6c7cb379d    4.7 GB    25 hours ago
phi3:14b-medium-128k-instruct-q4_K_M                          1372226c9b0b    8.6 GB    2 weeks ago
(base) PS Z:\nas\projects\deep_thinker> wsl --list --verbose
  NAME                   STATE           VERSION
* Ubuntu-22.04           Running         2
  docker-desktop         Running         2
  docker-desktop-data    Running         2
(base) PS Z:\nas\projects\deep_thinker> wsl --shutdown
(base) PS Z:\nas\projects\deep_thinker>
(base) PS Z:\nas\projects\deep_thinker> ollama list
NAME                                    ID              SIZE      MODIFIED
phi3:14b-medium-128k-instruct-q4_K_M    1372226c9b0b    8.6 GB    2 weeks ago
qwen2.5:14b-instruct-q4_K_M             7cdf5a0187d5    9.0 GB    6 weeks ago
llama3.2:1b                             baf6a787fdff    1.3 GB    7 weeks ago
hermes3:latest                          b5c6c7cb379d    4.7 GB    7 weeks ago
nomic-embed-text:latest                 0a109f422b47    274 MB    2 months ago
mistral-nemo:latest                     4b300b8c6a97    7.1 GB    4 months ago
llama3.1:latest                         a340353013fd    4.7 GB    4 months ago
mistral:v0.3                            f974a74358d6    4.1 GB    4 months ago
llama3-groq-tool-use:latest             55065f5d86c6    4.7 GB    4 months ago
deepseek-coder-v2:latest                8577f96d693e    8.9 GB    4 months ago
gemma2:9b                               ff02c3702f32    5.4 GB    4 months ago


add an API to import an executable+runfiles

This PR implements #64.  This is probably a work in progress concerning the API.
The feature here allows one to import to the scratch workspace an executable that was compiled outside of the scratch workspace.
The motivation is testing rules.  @ittaiz it might be of interest to you because, for instance, it allows you to import the scala compiler for testing the scala rules.  Having the download cache, this PR and copying all the *.bzl files is probably sufficient to have an integration test running.

I’m actually unclear about the motivation since bazel works with source dependencies and IIUC this means the scratch workspace doesn’t depend on this executable via source but on it’s outputs.
Is this only for better performance?
If I can copy the bzl files do I have to do the above?
@damienmg you also mentioned this feature, what scenario did you have in mind?

I re-read #64 and it indeed sounds like the main motivation is performance. I'm completely not belittling it but I want to understand if there are additional motivations?

One point, of course, is performance, because if you can avoid recompiling a compiler for every one of your test cases, that could be great.  This is not something that can be accomplished in general by just copying the runfiles of the binary to the workspace.  With the JVM, it's a bit simpler because jars are easier to move around, and you could imagine a java_import of a fat (deploy) jar.
However, this proposal is also about convenience.  With it, you don't have to import all the dependencies that you declare in the WORKSPACE, your BUILD files or your source files.  You don't have to maintain a new way to build the executable just for your integration tests.  In my opinion, it simplifies the writing of integration tests a lot.
It focuses on executables with runfiles because when you implement a rule for a language in Bazel, you often have a modified compiler laying around (to have a Bazel worker, for code coverage, to resolve file names). In integration tests, your goal is to check how this compiler behaves with your Skylark rules, so wouldn't it make sense to have this executable already built?


Not triggering boole when in middle of the word.

Hi,
Something small I've noticed lately. When I am standing on the (for example) a of false and inc or decr boole, it doesn't do anything.
When there is another true / false after it on the same line, then it will jump to the next one and toggle it.
When I stand on the first letter of the word however, then the behavior works as intended.
Wouldn't it make sense when the cursor is inside the word itself that it changes the actual word. instead of jumping to the next match?
Cheers.

thanks for the bug report and comments. I am working on this now.

It works! Thanks a lot 💪🏼


nix build .#urbit

Given bazel usage, is it possible to wrap this new build system in the flake.nix file to provide a nix build .#urbit command?
This would be intended for one-off usage while integrating urbit into other projects, or for easy global installations with nix-env or nix profile, it doesn't need to be fast/incremental as the current bazel-based build system seems great for active development.
As a starting point, we could add the following to the flake.nix outputs:
      packages = {
        urbit = pkgs.stdenv.mkDerivation {
          pname = "urbit";
          version = "2.5";
          src = ./.;
          buildInputs = with pkgs; [
            toolchain
          ]
          ++ (with pkgs; [
            autoconf
            automake
            bazel_5
            binutils # for `nm`
            jdk11_headless
            libtool
            m4
          ]);
          buildPhase = ''
            bazel build :urbit
            cp bazel-bin/pkg/vere/urbit $out/bin
          '';

The buildInputs use the same build toolchain dependencies as the devShells, and running nix build .#urbit seems to kick-off in a way that suggests dependencies are available. But, as is, it fails with:
       > FATAL: mkdir('/homeless-shelter/.cache/bazel/_bazel_nixbld'): (error: 13): Permission denied
I assume, if we could prevent bazel from caching incremental builds, then we could stop it from accessing the shared cache in $HOME. But I'm not familiar with bazel & maybe this kind of configuration isn't possible.
Is this rabbit hole worth exploring? Is there any chance that such a nix expression would ever work?
Thank you in advance for any feedback/guidance you all could provide.

This is a lot harder than it seems.

Also: nixpkgs has a recent version of vere. Might make more sense to just use that.

I wouldn't put too much work into anything that adds a dependency on bazel or
involves delving too much into the bazel build system. We have plans to
eventually get away from it.

@barter-simsum what are you planning to move to?

@ilyakooo0 a secret third thing

@barter-simsum it'd be useful to me to know what build system you guys are moving to, as I'm trying to get a build working against a custom toolchain (cosmopolitan libc, specifically.)


pip install fails

Installation fails if you don't have one or some of the following packages:

python2.7-dev
libevent-dev

The error: error: command 'x86_64-linux-gnu-gcc' failed with exit status 1
I would put in a PR to add this info to the README but I don't know which one fixed it or if it was both and don't want to put false info in it so figured I'd at least leave this here

You're right the detailed instructions in the readme should have that information.
Feel free to make a PR. If not, I'll make the necessary changes later tonight when I get home. Thanks!

Readme is now updated.
Thanks for reporting it. :umbrella:


there is no metadata in the h5 file of the Raw virtual reality demonstration dataset (VR_demos_raw)

there is no metadata, which caused we can't read the content to reolay the demonstration, such as task, task_id and scene. All the content is none.
Traceback (most recent call last):
File "e:\pythonprojects\iGibson\iGibson\demo_replaying_example.py", line 370, in
main()
File "e:\pythonprojects\iGibson\iGibson\demo_replaying_example.py", line 361, in main
replay_demo(in_demo_file, **args_dict)
File "e:\pythonprojects\iGibson\iGibson\demo_replaying_example.py", line 231, in replay_demo
env = iGibsonEnv(
File "e:\pythonprojects\iGibson\iGibson\igibson\envs\igibson_env.py", line 62, in init
super(iGibsonEnv, self).init(
File "e:\pythonprojects\iGibson\iGibson\igibson\envs\env_base.py", line 108, in init
self.load()
File "e:\pythonprojects\iGibson\iGibson\igibson\envs\igibson_env.py", line 263, in load
super(iGibsonEnv, self).load()
File "e:\pythonprojects\iGibson\iGibson\igibson\envs\env_base.py", line 170, in load
scene = InteractiveIndoorScene(
File "e:\pythonprojects\iGibson\iGibson\igibson\scenes\igibson_indoor_scene.py", line 143, in init
self.scene_tree = ET.parse(self.scene_file)
File "E:\anaconda\envs\igibson\lib\xml\etree\ElementTree.py", line 1202, in parse
tree.parse(source, parser)
File "E:\anaconda\envs\igibson\lib\xml\etree\ElementTree.py", line 584, in parse
source = open(source, "rb")
FileNotFoundError: [Errno 2] No such file or directory: 'E:\pythonprojects\iGibson\iGibson\igibson\data/ig_dataset\scenes\Ihlen_0_int\urdf\Ihlen_0_int_task_None_None_0_fixed_furniture.urdf'

oh i know, the name of the definition is not the same. But there is other question:
Traceback (most recent call last):
File "e:\pythonprojects\iGibson\iGibson\demo_replaying_example.py", line 370, in
main()
File "e:\pythonprojects\iGibson\iGibson\demo_replaying_example.py", line 361, in main
replay_demo(in_demo_file, **args_dict)
File "e:\pythonprojects\iGibson\iGibson\demo_replaying_example.py", line 245, in replay_demo
log_reader = IGLogReader(in_demo_file, log_status=False)
File "e:\pythonprojects\iGibson\iGibson\igibson\utils\ig_logging.py", line 564, in init
self.total_frame_num = self.hf["frame_data"].shape[0]
File "h5py_objects.pyx", line 54, in h5py._objects.with_phil.wrapper
File "h5py_objects.pyx", line 55, in h5py._objects.with_phil.wrapper
File "E:\anaconda\envs\igibson\lib\site-packages\h5py_hl\group.py", line 357, in getitem
oid = h5o.open(self.id, self._e(name), lapl=self._lapl)
File "h5py_objects.pyx", line 54, in h5py._objects.with_phil.wrapper
File "h5py_objects.pyx", line 55, in h5py._objects.with_phil.wrapper
File "h5py\h5o.pyx", line 189, in h5py.h5o.open
KeyError: "Unable to synchronously open object (object 'frame_data' doesn't exist)"


Binwalk not working (High priority)

When the container (autodyne-em1) is started, I see the following error. I did some investigation, and it looks like the file fw_dev_data/firmware-analysis-toolkit/firmadyne/sources/extractor/extractor.py is unable to extract *.bin image into the tar and place it in the /opt/firmadyne/images/*.tar.gz dir. And this might be due to the python versions issue. As the default python in the container is python2, it is unable to run this script using python2. Without this, nothing will work, please help resolving it. I will try my best on what I can do. Thanks and following is the traceback:
 *  Executing task in folder testenvironment: docker logs --tail 1000 -f 0459631a829f1d84ba5c1d9f8965a38ac893a6d9233ef589c0b750e2213ba14c

+ export PGPASSWORD=firmadyne
+ PGPASSWORD=firmadyne
+ export USER=firmadyne
+ USER=firmadyne
+ sleep 5
+ '[' '!' -z '' ']'
+ exec /opt/firmadyne/autodyne-0.5a.sh netgear 1.bin
+ socat TCP-LISTEN:5432,fork TCP:<IP_ADDRESS>:5432
Changing Directory...
Setting netgear for /opt/firmadyne/samples/1.bin
Here is basename 1.bin
>> Database Image ID: 1

/opt/firmadyne/samples/1.bin
>> MD5: 904d495563ba7c21a0478777b33fd11d
>> Tag: 1
>> Temp: /tmp/tmp3XnvHT
>> Status: Kernel: True, Rootfs: False, Do_Kernel: False,                 Do_Rootfs: True
>> Recursing into archive ...
>> Recursing into compressed ...
>> Cleaning up /tmp/tmp3XnvHT...
tar: /opt/firmadyne/images/1.tar.gz: Cannot open: No such file or directory
tar: Error is not recoverable: exiting now
tar: /opt/firmadyne/images/1.tar.gz: Cannot open: No such file or directory
tar: Error is not recoverable: exiting now
tar: /opt/firmadyne/images/1.tar.gz: Cannot open: No such file or directory
tar: Error is not recoverable: exiting now
ImageID: 1
Arch: default architecture guessed
mipseb
Extracting filesystem and building QEMU image for sample 1...
Traceback (most recent call last):
  File "./scripts/tar2db.py", line 101, in <module>
    main()
  File "./scripts/tar2db.py", line 98, in main
    process(iid, infile)
  File "./scripts/tar2db.py", line 69, in process
    (files, links) = getFileHashes(infile)
  File "./scripts/tar2db.py", line 12, in getFileHashes
    t = tarfile.open(infile)
  File "/usr/lib/python3.6/tarfile.py", line 1573, in open
    return func(name, "r", fileobj, **kwargs)
  File "/usr/lib/python3.6/tarfile.py", line 1638, in gzopen
    fileobj = gzip.GzipFile(name, mode + "b", compresslevel, fileobj)
  File "/usr/lib/python3.6/gzip.py", line 163, in __init__
    fileobj = self.myfileobj = builtins.open(filename, mode or 'rb')
FileNotFoundError: [Errno 2] No such file or directory: '/opt/firmadyne/images/1.tar.gz'
starting emulator for sample 1...

@compsecdirect hi, can you please help me resolve this python deps issue

@compsecdirect anything please?

We can't really troubleshoot issues like these without more context, like which firmware image is used.
If you exec into the docker image, and run /opt/firmadyne/autodyne-0.5a.sh netgear 1.bin after placing the 1.bin into the samples folder; what is the output of that anbd which firmware file are you using, with a download location?
We also see similar issues with this project, but please don't spam comments in issues requesting help as the initial issue is sufficient.

My apologies, but the issue seemed like it was a wrong samples-out dir and the python version issue. But fixed the issue once and for all by making the samples and samples-out dir automatically generated and fixed the python version issue too: https://github.com/compsecdirect/autodyne/pull/2


Add "requires javascript" message when javascript isn't enabled?

This is kind of a niche issue, but since not everyone has javascript enabled globally, it might be good to display a message about chaise requiring javascript instead in that case. This seems to be pretty standard for other javascript-dependent applications. Currently chaise just looks like a blank screen in non-javascript-enabled browsers.

This is done in this commit. We're going to show a error modal when Javascript is not available.


TextureProgress Error bad polygon

Godot version:
Godot 3.0.1-RC1
Issue description:
TextureProgress not working well when using Clockwise Fill mode , it's not rendering if reaching some value and there is an Error say : bad polygon
Minimal reproduction project:
TestProgressTexture.zip

I am experiencing the same issue with the counter clockwise fill mode. Setting the min value to 0 and max value to 1, with a step of .01 will disallow me from using values greater than ~.63

@Jcozman For me this solution not working in my project it's still give me the same error
and why this issue not set as bug ?

Duplicate of #17102.
No need to reopen an issue when there is one already. An issue not labelled as "bug" just means that no issue triager had time to look at it yet.


Glowsilk Cocoon can't be blown up by explosions

https://i.imgur.com/c3Wp6Yw.png

This is intended to align with the hardness of the cocoon. It is meant to be a netherite-like material. This is also to allow for explosion mining for it without fear of destroying it.


who can use box-flex

https://developer.mozilla.org/en-US/docs/Web/CSS/box-flex

box-flex was a property used in the old Flexbox implementation an has been superseded by the properties at https://caniuse.com/#feat=flexbox


Max ESS Detection with lugsail fails when input is block-averaged

Fix this by using instead finding the minimum estimated standard error.

Closing as method is deprecated.


Docking branch available for testing

The docking branch has been ported, it's based on the last 1.77
https://user-images.githubusercontent.com/8225057/46300244-80708900-c5a3-11e8-8365-f89cfd06080e.gif
Known bug: problems by loading properly the windows position from the ini file
Original issue
I'll be glad to gather feedbacks

On linux, using the GNOME DE, running on wayland:

[ ] With the ini file present, all windows spawn on the bottom right of the screen (video 1)
[ ] Many actions will result in the same JVM crash (crash) (video 1 and video 2)

Returning a undocked window back to the main window
Closing a undocked window
Rarely, opening a undocked window (I've only had this happen with context menus)

[ ] The native 'closing animation' is visible, creating a non-seamless transition from undocked -> docked. (video 1)
[ ] Dragging a docked window out of the main window will undock it, but will also stop dragging the window (video 2)
[ ] About 1 in 5 tries, instead of a JVM crash, the message *** buffer overflow detected ***: terminated appears. (video 3)

Here's a list of JVM crashes I ran into while testing. They appear to all be more or less the same, but most have a slightly different call stack.

Thanks for the list
ini bug fixed
I had a couple of commit still locals, could you give a try to the rest?

I don't experience your crashes.
I can replicate n4, the dragging issue
Ubuntu 19.04

Are you running a wayland or xorg session? On the login screen, as I recall, there should be a button on the bottom right that allows you to choose which session to log into. The crashes I experience are on wayland (with XWayland enabled, but that should be on by default).
For the latest commits, I actually can't run the docking branch anymore:
Exception in thread "main" java.lang.NoSuchFieldError: DockingEnable
	at examples.ImGuiOpenGL3.<init>(opengl3.kt:92)
	at examples.Opengl3Kt.main(opengl3.kt:30)
	at examples.Opengl3Kt.main(opengl3.kt)

Not sure why this happens. IDEA is able to navigate to DockingEnable just fine.
A (black) window will spawn and shortly after close with the above error message.

The default, xorg
Try delete cache and rebuild

The default, xorg

Can you try on wayland instead?

Try deleting the cache and rebuild

This worked - but all previous bugs (aside from ini thing) are still there.

Sure, I tried right now
no crashes bringing windows inside/outside my main window.
I'm on Ubuntu 19.10 and Intel UHD Graphics 620 (nuc)
Which distro and gpu are you using?

I'm using Arch linux with vanilla GNOME. I have an i5-8250U with integrated graphics.

@zeroeightysix
Spasi

Currently, the choice between X11 and Wayland cannot be made at runtime, GLFW must be built to support one or the other. That's why lwjgl-glfw-natives-linux.jar includes two binaries. LWJGL defaults to X11. You can use -Dorg.lwjgl.glfw.libname=glfw_wayland (or call Configuration.GLFW_LIBRARY_NAME.set("glfw_wayland") before initializing GLFW) to enable the shared library that supports Wayland.

Running with the wayland flag causes the following error: /usr/lib/jvm/java-11-openjdk/bin/java: symbol lookup error: /tmp/lwjglridan/3.2.3-build-13/libglfw_wayland.so: undefined symbol: __wrap_memcpy
Presumably related to https://github.com/LWJGL/lwjgl3/issues/543 or https://github.com/LWJGL/lwjgl3/issues/557?
However, I tried launching again and the JVM crashes are gone! I have no clue why, but I'm not going to question it either. Problem 3 and 4 (native animation, dragging) persist.

[ ] Windows run away when docked. (video)


CommandList Scroll To View On keyDown

Added to the ability to Scroll the active or selected item into view when using keydown events

@stavast thank you very much @stavast that's a very nice thing to have...

@sereneinserenade Thanks for the update! The smooth scrolling is really looking great 🚀 🚀


Add ES6-style snippets

What would it take to make the build on AppVeyor pass ? The error seems to come from the fact that Chocolatey is prompting the user, of course it doesn't exist on CI. Should it be merged anyway, since the tests pass on Travis ?

Hi, Travis is enough! Thanks for contributing!

Nice !
Do you know when you'll make a new release of the package ?

I think I'll add some more ES6 snippets today and also apply some fixes to existing ones.

Ok, good to know. Thanks for your package btw, it works very well.

New version published and webpage updated to contain new snippets.

:+1:

I just updated to 0.12.1 and the ES6 snippets are not working. Is there some extra thing to do on the key binding or something?

Just edited the /

I made it work by editing snippets/Javascript(JSX).cson
commentend in line 81
  # React >0.13 (ES6)
  # ".source.js":

and reindented the lines for ES6
also I changed the snippet for rcc6 for this
    prefix: 'rcc6'
    body: 'import React from \'react\';\n\nclass $1 extends React.Component{\n\trender () {\n\t\treturn (\n\t\n\t\t);\n\t}\n}\n\nexport default ${1};\n'

I made it work by editing the file sippets/JavaScritp (JSX).cson
comment the line 80
79   # React >0.13 (ES6)
80   # ".source.js":

and change the name of all the ES6 snippets from React: ...  to  ReactES6: ....
"ReactES6: componentDidMount() { ... }":
"ReactES6: componentDidUpdate(pp, ps) { ... }":
"ReactES6: componentWillMount() { ... }":
"ReactES6: componentWillReceiveProps(np) { ... }":

also I changed the rcc6 body to:
    prefix: 'rcc6'
    body: 'import React from \'react\';\n\nclass $1 extends React.Component{\n\trender () {\n\t\treturn (\n\t\n\t\t);\n\t}\n}\n\nexport default ${1};\n'


Documentation Revamp

What does this PR do?
This PR is an attempt at revamping the documentation, and include recent changes on the architecture (notably middleware).
Motivation
We want people to spend more time on the disco dancefloor.

Additional Notes
Some sections are still work in progress (marked todo in the title), others are already reviewable.
We're aware that this is quite a huge PR ... and we're not even sorry for that.
(If it's OK, we'll rebase later since the history is not relevant)
Co-authored-by: jbdoumenjou<EMAIL_ADDRESS>

FYI, to support this branch once it will be merged, a PR to structor had been sent: https://github.com/containous/structor/pull/4 .
Test scenarios (on my fork of course):

✅  This PR's branch is merged on a master branch, and we build the next v1.7.x tag. We can build with the structor from https://github.com/containous/structor/pull/4
⌚  This PR's branch is on a branch named v15.0 and a tag v15.0.0 is created on this branch.

Everything is ready to go in structor, this PR can be merged from the point of view of the plumbing/tooling.


[GOBBLIN-1410] Bump lombok to 1.18.16 for compatibility with Java 11

Dear Gobblin maintainers,
Please accept this PR. I understand that it will not be reviewed until I have checked off all the steps below!
JIRA

[x] My PR addresses the following Gobblin JIRA issues and references them in the PR title. For example, "[GOBBLIN-XXX] My Gobblin PR"

https://issues.apache.org/jira/browse/GOBBLIN-1410

Description

[x] Here are some details about my PR, including screenshots (if applicable):
Lombok version 1.18.10 is required for compatibility with Java 11, so bumping it because there are downstream consumers of gobblin that are migrating to java 11 that require it.

Tests

[x] My PR adds the following unit tests OR does not need testing for this extremely good reason:
./gradlew build passed

Commits

[x] My commits all reference JIRA issues in their subject lines, and I have squashed multiple commits if they address the same issue. In addition, my commits follow the guidelines from "How to write a good git commit message":

Subject is separated from body by a blank line
Subject is limited to 50 characters
Subject does not end with a period
Subject uses the imperative mood ("add", not "adding")
Body wraps at 72 characters
Body explains "what" and "why", not "how"

@htran1 please review/merge, thanks

LGTM

Codecov Report

Merging #3245 (49e524a) into master (30bc46d) will decrease coverage by 3.48%.
The diff coverage is n/a.

:exclamation: Current head 49e524a differs from pull request most recent head 918922f.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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Verify that "Petrești" is listed in the dropdown menu when searched

Description:
"Petrești" should appear in the dropdown menu with correct spelling and locality information.
Preconditions:
The website is up and running.

Step 1
Type "Petrești" in the search bar.
Expected results:
The dropdown is listing "Petrești" as the first location in the dropdown menu.

Step 2
Observe the dropdown menu.
Expected results:
"Petrești" is displayed and selectable from the dropdown menu.


New message received - last message still showing in message list

I have the windows bluebubbles app open all the time.
I often receive "one time codes" from places I login to
I receive a notification from bb saying for example "your onetime code is 5678"
but when I look over to the bluebubbles app without clicking into the actual chat, the preview in the messages list still shows the last onetime code from that site "your onetime code is 1234"
In other words, the messages list doesnt show the LATEST message for that chat

Came here to write a similar issue. Bumping this.


Style geolocation popup

I was wondering if there is a way to style the component that shows the geolocation on the camera overlay.
Where is the styling found for this component?
Example:
geoLocations: [
{
  latitude: 1.2345,
  longitude:<PHONE_NUMBER>,
  name: "Location name"
}

I was able to get this to come up on our test app but we would like to style the popup better to better match my apps layout. Please let me know if this is possible!
Thanks!

Yes it is possible. Add your styled popup background images here cordova-plugin-ar/src/ios/ARKit/Images and rename the image values in MarkerView.m this file under Plugins folder.


Add a How-To Guide

How to write to a .gdf file with symmetry planes

Get inspiration from https://pandas.pydata.org/docs/getting_started/index.html


[POI] Use choice prompt for POI selection & prompt user for current location if they are missing the IPA.Location event

Description
Bug Fixes
Fix #783 where "fix KEYWORD" utterances were mapped to None.
Conversational Experience
Close ##572: use the ChoicePrompt when POIs are displayed to allow a user to select by name, address, number, & ordinal.
Close ##755: if IPA.location event is not sent, the VA will prompt user for their current location. This runs an Azure Maps fuzzy query on their entire response and asks users to select the best match. The bot then continues to their original intent (find POI, find parking, route to...).

Updated responses for improved speak properties
Updated POI card with route info card

Testing Steps

User: Send utterance to trigger POI
Bot: Where are you now?
User: Send location like an address or description "city center plaza in bellevue"
Bot: look up with fuzzy search and send choice prompt
User: select option and continue with normal dialog
Validate with new uploaded sample transcript
Checklist

[X] I have commented my code, particularly in hard-to-understand areas
[X] I have added or updated the appropriate unit tests
[X] I have tested any new/updated dialogs using Speech in the emulator to ensure the Speak property is set to enable a high quality speech-first experience and the appropriate InputHints are set correctly.
[X] All languages have been updated
[X] You have tested deployment with your new models

Looks good, the location prompt is pretty clever in that if I say "city center plaza in bellevue" or "chippenham in the UK" it works but if I'm (lazy) and just say Seattle or London it says

Which one is a little confusing as it's not giving me any options, so perhaps a try again or something? If there is a easy way to get seattle, london, berlin, etc. working that would be great or we have this as a known issue.

Added a simple change to the appsettings.json file as the secret config entry had an old name

@darrenj it looks like just a city name like "Seattle" is captured as a Cancel intent. Opened #943 to track it. Afterwards, we may need to filter properly (it probably doesn't come back as a POI or Street Address type from Azure Maps, but that will require us to follow through the steps that it is rendered correctly)


Compile the generated client in Javascript

Explore if it is possible to use Dart JS compiler to generate a client for Javascript. An advantage here is that the client can then be used on the web or in React.
It seems somewhat tricky to do this, but can also be a fun challenge. There are some starting pointers here:
https://pub.dev/packages/js

Have you considered generating a typescript client? Not sure it would be possible to use dart web interop to do that.

Yes! We have discussed this, I think it would make sense if we create a bespoke JS client to also add the type definitions.
The compiling route as discussed in this issue turned out to be pretty difficult, and would in the end mean that we more or less would have to define the entire interface manually anyway.


Can't built with paru on Archlinux

I think I should report this issue on github because the PKGBUILD seems to be no problem.
I can't built with this error:
+ chmod -R g-w,a-w src/ /home/djw/.cache/paru/clone/yabsnap/pkg/yabsnap/usr/share/yabsnap
++ which selinuxenabled
+ mkdir -p /home/djw/.cache/paru/clone/yabsnap/pkg/yabsnap/usr/bin
+ ln -sf /usr/share/yabsnap/yabsnap.sh /home/djw/.cache/paru/clone/yabsnap/pkg/yabsnap/usr/bin/yabsnap
+ chmod 755 /home/djw/.cache/paru/clone/yabsnap/pkg/yabsnap/usr/bin/yabsnap
chmod: 无法对悬空符号链接 '/home/djw/.cache/paru/clone/yabsnap/pkg/yabsnap/usr/bin/yabsnap' 进行操作==> 错误： 在 package() 中发生一个错误。    正在放弃...
错误: 未能构建 'yabsnap-2.0.2-1':

The ln -sf /usr/share/yabsnap/yabsnap.sh $PKGDIR/usr/bin/yabsnap shold be ln -sf $PKGDIR/usr/share/yabsnap/yabsnap.sh $PKGDIR/usr/bin/yabsnap or removing /? There seems to be a missing point here and yabsnap-git in AUR has the same error.

Thanks for filing this.
Should be resolved in commits d93c9a43f5f7b97852255da90a82caf6d672acf2 and 1447070a1ed5589fbf2866e99af368f71077124a.
Would you kindly try to update to v2.0.4?
I think the chmod on symlink was an error, since it's unnecessary on symlinks. Also it was failing because the target (which should point to the file in actual root) did not yet exist when paru compiles it.
Looks like paru caught an edge case that yay missed.

Thanks,it has been fixed after updating to v2.0.4

Glad to hear it!


Add .rustfmt.toml

Resolves #11

as far as I know, edition is set to the package.edition in Cargo.toml by default.
https://github.com/rust-lang/rustfmt/blob/master/Configurations.md#edition

Why not set newline_style to Unix to prevent CSRF code from being commited.
https://github.com/rust-lang/rustfmt/blob/master/Configurations.md#newline_style


Arduino libraries not found

I'm trying to use Arduino based libraries within the light example.
I followed the install guide here: https://docs.espressif.com/projects/arduino-esp32/en/latest/esp-idf_component.html , but installed the library globally under /esp-idf/components, and it seems to work as I can compile the sample_project in esp-idf/examples/get-started folder.
My project is located in esp-matter/examples, and when I try to include Arduino.h it says "fatal error: Arduino.h: No such file or directory"
I also set "CONFIG_FREERTOS_HZ" in sdkconfig to 1000 (as required by arduino-esp32)
I can find the Arduino Component now under menuconfig (and also tried ticking the box within compatibility options to "Include headers across components as before IDF v4.0" -> made no difference)
Still getting the error that Arduino.h can't be found.
Using ESP-IDF: v4.4.2
Any ideas how Arduino can be correctly added to an esp-matter project?

Hi @bernch1nv,
I tried the steps you mentioned above and was able to compile the example given here by creating a sample project in esp-matter/examples.
Using IDF Branch: release/v4.4
Is there any other library that you are using with Arduino ?

@SuGlider maybe you can provide some help.

@bernch1nv -

I followed the install guide here: https://docs.espressif.com/projects/arduino-esp32/en/latest/esp-idf_component.html , but installed the library globally under /esp-idf/components, and it seems to work as I can compile the sample_project in esp-idf/examples/get-started folder.

The libraries shall not go under /esp-idf/components.
An example of folder strucuture is https://github.com/SuGlider/RainMaker_as_Arduino_Component
It is a RainMaker Arduino Project as IDF component.
You should clone Matter in the /yourProject/components
Then you shall add its components to the CMakeList.txt of the project:
# The following lines of boilerplate have to be in your project's
# CMakeLists in this exact order for cmake to work correctly
cmake_minimum_required(VERSION 3.5)

set(EXTRA_COMPONENT_DIRS components/esp-matter/components)

include($ENV{IDF_PATH}/tools/cmake/project.cmake)
project(arduino_matter_test)

I was reading the code from https://github.com/espressif/esp-matter/blob/main/examples/light/main/app_main.cpp and it does have a app_main() function.
Is that code that you want to use and add to it  some Arduino API calls?

My goal is to have the device operating (based on a hw-switch) in either Wifi AP-mode for configuration purposes, or in matter-"mode". As I have the AP-mode part already written using libraries like ESPAsyncWebserver, AsyncTCP etc. which are based on arduino-esp32 I somehow need the Arduino.h file in there

How is the project structured in the folders?
Is Arduino cloned to the /components folder of your project?

Matter has its own commissioning methods.
WiFi credentials shall be passed to the Matter device using the BLE commissioning secure protocol.
@bernch1nv - What is AP-mode used for in your project?
Matter devices will use WiFi for IPv6 communications over the Matter network.

When I opened this issue, as described I installed arduino globally under {$home}/esp-idf/components (with the intention to being able to use it by multiple projects)
esp-matter was installed under {$home}/esp-matter (so everything should be like the development guide says)
Project was located under {$home}/esp-matter/examples/my_project (which was just a copy of the light example)
This is where i tried to include Arduino.h in my_project/main/app_main.cpp and got that error.
Right now I just removed my existing esp-matter installation, and moved my project to {$home}/esp-projects/my_project
There I now cloned the esp-matter repo into my_project/components/esp-matter, as suggested by @SuGlider
And also cloned arduino in there.
I did not adapt the CMakeLists.txt file though, because i think the current set EXTRA_COMPONENTS_DIRS looks fine for me, as it uses the ESP_MATTER_PATH variable.
With this setup, I now get the Error "Failed to resolve component 'app_reset'"
@RoCorbera AP-mode is hosting a webapp for configuration purposes, for variables that cannot be known in production yet.
But like I said, I want to make it either operating in AP-mode OR matter-mode. The only thing the both modes share would be some variables in NVS.

With this setup, I now get the Error "Failed to resolve component 'app_reset'", because esp-matter does not contain a CMakeLists.txt file

app_reset is in Examples/Common, not as a component.
https://github.com/espressif/esp-matter/tree/5ff7d0d7fa9e93d248b557f0c4eee2a7df5410d8/examples/common/app_reset
In the other Matter examples, the CMakeLists.txt adds the common folder to the sources and includes.
https://github.com/espressif/esp-matter/blob/5ff7d0d7fa9e93d248b557f0c4eee2a7df5410d8/examples/light_switch/CMakeLists.txt
You may need to add this folder to your project and fix your project's CMakeLists.txt to add it.

@bernch1nv - I've built the esp-matter/examples/light example with an extra line #include <Arduino.h> as requested.
In order to get it done, I followed these steps:

clone https://github.com/espressif/esp-idf.git in ~/esp-idf
run git checkout v4.4.2 on esp-idf
run git submodule update --init on esp-idf
run esp-idf/install.sh and esp-idf/export.sh
check idf version with idf.py --version - it shall display v4.4.2
clone https://github.com/espressif/esp-matter.git in a separated folder like ~/esp-matter
run esp-matter/install.sh and esp-matter/export.sh
go to esp-matter/components and git clone --recursive https://github.com/espressif/arduino-esp32.git arduino there
go to esp-matter/components/arduino and edit CMakeLists.txt on line 227 to remove -DESP32 at https://github.com/espressif/arduino-esp32/blob/master/CMakeLists.txt#L227
go to esp-matter/examples/light/main and edit CMakeLists.txt to include arduino to the  PRIV_REQUIRES_LIST
https://github.com/espressif/esp-matter/blob/main/examples/light/main/CMakeLists.txt#L1
set(PRIV_REQUIRES_LIST arduino device esp_matter esp_matter_console route_hook app_reset)
go to esp-matter/examples/light and run idf.py build to check and verify that it builds correctly
add #include <Arduino.h> to line 19 of esp-matter/examples/light/main/app_main.cpp at https://github.com/espressif/esp-matter/blob/main/examples/light/main/app_main.cpp#L19
in esp-matter/examples/light  run idf.py build again.
There will be an error of Conflict with INADDR_NONE

To fix this error there are a couple possibilitites:

Change the name of INADDR_NONE variable from cores/esp32 and in the WiFi Library.
https://github.com/espressif/arduino-esp32/blob/master/cores/esp32/IPAddress.cpp#L125
https://github.com/espressif/arduino-esp32/blob/master/cores/esp32/IPAddress.h#L95
https://github.com/espressif/arduino-esp32/blob/master/libraries/WiFi/src/WiFiAP.cpp#L50
https://github.com/espressif/arduino-esp32/blob/master/libraries/WiFi/src/WiFiSTA.cpp#L54
https://github.com/espressif/arduino-esp32/blob/master/libraries/WiFi/src/WiFiGeneric.cpp#L86

OR Change the esp-matter file esp-matter/connectedhomeip/connectedhomeip/src/inet/IPAddress.h
https://github.com/espressif/connectedhomeip/blob/87bee4de25886ba00f1a177cd0f8791a48528a1f/src/inet/IPAddress.h#L51
it shouldn't include lwip/inet.h and instead just define two symbols that will be enough to compile it.
Change the line 51 of esp-matter/connectedhomeip/connectedhomeip/src/inet/IPAddress.h to:

//#include <lwip/inet.h>
#define INET6_ADDRSTRLEN  46
#define INET_ADDRSTRLEN   16

Finally, just run idf.py build in the esp-matter/examples/light example and it will get it done fine.

First of all thanks for these detailed instructions! I followed your steps, but idf.py build still fails for me as I got to the point of changing CONFIG_FREERTOS_HZ already.
What I can see marked as faied:
[877/1546] Building C object esp-idf/a...32.dir/cores/esp32/esp32-hal-cpu.c.obj
FAILED: esp-idf/arduino-esp32/CMakeFiles/__idf_arduino-esp32.dir/cores/esp32/esp32-hal-cpu.c.obj

In file included from /home/chbe/esp-idf/components/arduino-esp32/cores/esp32/esp32-hal-cpu.c:22:
/home/chbe/esp-idf/components/soc/esp32/include/soc/rtc.h:22:14: error: expected identifier or '(' before numeric constant
 #define MHZ (1000000)
              ^~~~~~~
/home/chbe/esp-idf/components/arduino-esp32/cores/esp32/esp32-hal-cpu.c:47:16: note: in expansion of macro 'MHZ'
 const uint32_t MHZ = 1000000;
                ^~~
[880/1546] Building C object esp-idf/a...2.dir/cores/esp32/esp32-hal-gpio.c.obj
FAILED: esp-idf/arduino-esp32/CMakeFiles/__idf_arduino-esp32.dir/cores/esp32/esp32-hal-gpio.c.obj

/home/chbe/esp-idf/components/arduino-esp32/cores/esp32/esp32-hal-gpio.c: In function '__pinMode':
/home/chbe/esp-idf/components/arduino-esp32/cores/esp32/esp32-hal-gpio.c:102:24: error: 'rtc_gpio_desc' undeclared (first use in this function); did you mean 'rtc_io_desc'?
     uint32_t rtc_reg = rtc_gpio_desc[pin].reg;
                        ^~~~~~~~~~~~~
                        rtc_io_desc
/home/chbe/esp-idf/components/arduino-esp32/cores/esp32/esp32-hal-gpio.c:102:24: note: each undeclared identifier is reported only once for each function it appears in
[881/1546] Performing build step for 'chip_gn'
[1/716] stamp obj/mbedtls/mbedtls.stamp

@bernch1nv

/home/chbe/esp-idf/components/arduino-esp32/cores/esp32/esp32-hal-cpu.c:47:16: note: in expansion of macro 'MHZ'
const uint32_t MHZ = 1000000;

It seems that the folders are not setup as I instructed.
You have Arduino cloned in the IDF folder instead.
Please delete the whole esp-idf/components/arduino-esp32/ from your IDF envionment.
You should have something like this:
 /myProj
     |
     +-- esp-idf-v4.4.2/                  ==> cloned from esp-idf.git + checkout v4.4.2 + install.sh + export.sh
     |
     +-- esp-matter/                      ==> cloned from esp-matter.git
     +-- esp-matter/components/arduino    ==> cloned from arduino-esp32.git and modified as instructed
     +-- esp-matter/examples/light        ==> add "Arduino.h" and necessary sdkconfig/CMakeLisit.txt changes

@bernch1nv - Please let me know if this issue is solved. Thanks,

So the first time I tried this I didn't remove arduino under esp-idf/components, you're right.
Now the build runs as described when including Arduino.h, thanks for that!
However now I just tried to establish a wifi in AP mode, to see if this is really working, but I get this error:
/home/chbe/.espressif/tools/xtensa-esp32-elf/esp-2021r2-patch3-8.4.0/xtensa-esp32-elf/bin/../lib/gcc/xtensa-esp32-elf/8.4.0/../../../../xtensa-esp32-elf/bin/ld: esp-idf/arduino/libarduino.a(WiFiGeneric.cpp.obj):(.literal._Z16wifiLowLevelInitb+0x24): undefined reference to `esp_netif_create_default_wifi_ap'
/home/chbe/.espressif/tools/xtensa-esp32-elf/esp-2021r2-patch3-8.4.0/xtensa-esp32-elf/bin/../lib/gcc/xtensa-esp32-elf/8.4.0/../../../../xtensa-esp32-elf/bin/ld: esp-idf/arduino/libarduino.a(WiFiGeneric.cpp.obj): in function `wifiLowLevelInit(bool)':
/home/chbe/esp-matter/components/arduino/libraries/WiFi/src/WiFiGeneric.cpp:624: undefined reference to `esp_netif_create_default_wifi_ap'
collect2: error: ld returned 1 exit status
ninja: build stopped: subcommand failed.
ninja failed with exit code 1

@bernch1nv
OK, now it is another issue.
This issue is related to the linker that can't find the function in the object files.
It may happen a often along your project development and it will demand that you compare your Matter MyProj sdkconfig with the Arduino default sdkconfig and then find what you need to add to your project sdkconfig in order to build it.
The Arduino default sdkconfig file is in
https://github.com/espressif/arduino-esp32/blob/master/tools/sdk/esp32/sdkconfig
You can change it to the target SoC of your project in the sdk/esp32xxxx/ folder.
For this specific issue with  softAp() you must add CONFIG_ESP_WIFI_SOFTAP_SUPPORT=y to your sdkconfig file.
You may want to add it to the sdkconfig.defaults in order to make it global for any SoC, but then, please don't forget to delete the previous sdkconfig file in the project folder in order to force rebuilding it again.
I added this line to my sdkconfig and it builds fine.
You shall have in mind that mixing Matter Code and Framework with Arduino Code and Framework won't be easy.
Each one initializes NVS, PSRAM, LwIP, BLE, etc. in a different way.
Compiling doesn't mean that it will run...

@bernch1nv - I made it work and start SoftAP with this code:
extern "C" void app_main()
{

    esp_err_t ard_err = nvs_flash_init();
    if(ard_err == ESP_ERR_NVS_NO_FREE_PAGES || ard_err == ESP_ERR_NVS_NEW_VERSION_FOUND){
        const esp_partition_t* partition = esp_partition_find_first(ESP_PARTITION_TYPE_DATA, ESP_PARTITION_SUBTYPE_DATA_NVS, NULL);
        if (partition != NULL) {
            ard_err = esp_partition_erase_range(partition, 0, partition->size);
            if(!ard_err){
                ard_err = nvs_flash_init();
            } else {
                printf("ARDUINO :: Failed to format the broken NVS partition!");
            }
        } else {
            printf("ARDUINO :: Could not find NVS partition");
        }
    }
    if(ard_err) {
        printf("ARDUINO :: Failed to initialize NVS! Error: %u", ard_err);
    }

    Serial.begin(115200);
    Serial.println();

    const char* ssid = "examplewifissid";
    const char* password = "tenonezero";
    Serial.print("Setting soft-AP ... ");
    WiFi.mode(WIFI_AP);                //Configure Access Point mode
    Serial.println(WiFi.softAP(ssid, password) ? "Ready" : "Failed!");    //Password length minimum 8 char

    Serial.print("Soft-AP IP address = ");
    Serial.println(WiFi.softAPIP());

    Serial.println("======================================");
}

OUTPUT:
Setting soft-AP ... I (918) wifi:wifi driver task: 3ffdb8fc, prio:23, stack:6656, core=0
I (922) wifi:wifi firmware version: eeaa27d
I (922) wifi:wifi certification version: v7.0
I (922) wifi:config NVS flash: enabled
I (925) wifi:config nano formating: disabled
I (929) wifi:Init data frame dynamic rx buffer num: 32
I (933) wifi:Init management frame dynamic rx buffer num: 32
I (939) wifi:Init management short buffer num: 32
I (943) wifi:Init dynamic tx buffer num: 32
I (947) wifi:Init static rx buffer size: 1600
I (951) wifi:Init static rx buffer num: 4
I (955) wifi:Init dynamic rx buffer num: 32
I (960) wifi_init: rx ba win: 6
I (963) wifi_init: tcpip mbox: 32
I (967) wifi_init: udp mbox: 6
I (970) wifi_init: tcp mbox: 6
I (974) wifi_init: tcp tx win: 5744
I (978) wifi_init: tcp rx win: 5744
I (982) wifi_init: tcp mss: 1440
I (986) wifi_init: WiFi IRAM OP enabled
I (991) wifi_init: WiFi RX IRAM OP enabled
I (997) phy_init: phy_version 4670,719f9f6,Feb 18 2021,17:07:07
I (1100) wifi:mode : softAP (84:0d:8e:e3:b2:19)
I (1102) wifi:Total power save buffer number: 16
I (1102) wifi:Init max length of beacon: 752/752
I (1104) wifi:Init max length of beacon: 752/752
I (3028) wifi:Total power save buffer number: 16
Ready
Soft-AP IP address = <IP_ADDRESS>
======================================

@SuGlider now this works, guess I can close this issue now.
Hope I don't run too much into conflicts as I plan to not have matter code run simultaneously with the Arduino/SoftAP code, but we will see.
Thanks for your support!