Model performance issue

Hi,
I am trying to train a breakout game model using your batch-a3c code.
I am using a p2.xlarge instance (NVIDIA K80) and it has training been about 20-22 hours and it has completed about ~33m frames. From your graph, assuming each unit in x-axis is 10m training steps, at about 30-25m steps, it has achieved an average score of atleast 30-50. But my model unfortunately barely gets a 10 - its mostly still zeros. I am not sure why this happens.
I am using the same 80m steps and all the default params are the same.
These are the statistics at about ~34m frames.
Frames: 34300000; Policy_loss: -0.701535; Value_loss: 0.002712; Entrophy: 0.345996; V-value_avg:  0.439
Also, I should mention that I am using 16 acting agents so I believe the performance should be much better, correct?
Other doubts that I have are:
-Would it help to increase the queue length as the number of agents increase wouldn't this diversify the different experiences the agent can learn?
-During my training, I paused and resumed training once (at 6m steps) - since most of the code is dependent of the network weights and the number of train steps (obtained from the input args) - this shouldn't have had any effect on the training right?
-The total training steps is the one counted in the learn_proc() method right? each actor process's train steps progress much slower than the learn_proc() thread - is this normal?
-There is no stopping condition, so I am assuming the training ran for 80m steps as indicated by the message printed out by LearningAgent's learn() method.
I will let the training continue for another 10m steps and see if there are any performance changes.
Thank you!

Hi,
I found a small bug in code that could cause some agents to get stuck (choosing always the same action) and therefore stop them from generating useful experience. So my guess is that in your case after a while some, if not all, agents just got stuck. I pushed a fix already. Tested it for 6m iterations with 16 generating agent and was able to achieve average score of 10 points and 30 points after 10m iterations.
I don't know the spec of p2.xlarge instance but ~33m frames in 20-20h is quite slow. On my machine (i5-6600K, GTX1080) training for 80m frames took about 23h total, so thats strange.
Answering your questions.

According to paper (https://arxiv.org/pdf/1602.01783v2.pdf) it seems like number of acting agents shouldn't have significant impact on score, although it may speed up learning a lot. I would advice setting --processes to number of cores on your machine.
I haven't tested it but I think that making a queue bigger won't help. Mainly because with bigger queue there might be more old experience (if learning agent can't keep up).
I resumed training many times and with A3C it wasn't a problem but Q-learning methods may stop learning sometimes. There are some parameters in optimizer that I think should be saved (like momentum) with model. I'm not doing it now (will look into it).
Yes, total number of frames is counted in learn_proc and specifically by LearningAgent (it counts frames used for learning, not number of batches). Each generate_experience_proc should go slower.
There is no stopping condition, because I used it on local machine I just Ctrl+C to stop. This might be a little problematic when training on remote machine.

I hope it helps. If you have more questions feel free to ask. :)

Hi,
Thank you for your reply!
I guess the version of K80 that Aamazon uses has significantly lower clock speeds than a GTX1080 - that could probably explain why it's slow. But 80m frames in less than a day is blazing fast! Unfortunately I only have a GTX 660 on my desktop so, K80 is the only way to go for me at the moment.
Thanks for the fix! I will try it again with 16 agents and will let you know how it performs.
Both the machines I work with (PC and  EC2 instance) have quad core CPUs only. I will also try running with 4 agents and report score later on.
Your answers really helped me! :)
Your model (the 91m frames) for breakout and all other tests were conducted using the default params in your code correct? (i.e 4 process, lr, batch size etc..) - at least for a3c.

Hi,
In my case GPU usage was about ~30-35% and CPU always 100%, so I think it should work on your desktop quite well.
Yes, I used default parameters for Breakout model and tests. :)

Hi,
Sorry for the late reply!
I have tried running the updated train.py for a3c and I am still getting the same results! :(
Just to confirm, my library versions are:
Keras: 1.1.2
Theano: 0.8.2
numpy: 1.11.2
scipy: 0.18.1
I ran the exact same file (train.py) with the default parameters. I added some logging function to it.
Here is the log info from the 0th actor thread (inside generate_experience_proc method):
training_log_actor-0 (copy).txt
Here is the full log info from the learner thread:
full_log.txt
I ran this on my PC (NVIDIA GTX 660), and it completed about 19m frames in 13-14 hours.
Why is it that I am getting vastly lower performance with the same code in my computer?

Looks like something is wrong elsewhere. I suspect this Theano warning might have something to do with it.
Please do this four things:

upload any weight file
check model summary (in LearningAgent add self.train_net.summary())
check action set in Breakout-v0 (your entropy is different from mine (in my case it was ~0.36), which suggests you have more actions (I have four))
upgrade Theano to bleeding edge version if possible (pip install --upgrade --no-deps git+git://github.com/Theano/Theano.git)

I think that cuDNN might be a problem here. After upgrading to bleeding edge, run some simple convolutional network on mnist to confirm it is learning.
My library versions:
Keras: 1.1.1
Theano: 0.9.0.dev3
numpy: 1.11.2
scipy: 0.18.1
I hope we will figure it out soon. :)

Hi,
Thank you for the suggestions!

Uploaded model file
model-Breakout-v0-19250000.h5.zip
Learning Agent summary:

-My action set is set as default i.e env.action_space so I will set it as:
    if args.game == 'Breakout-v0' :
        action_space = Discrete(4)

(env.action_space for breakout returns Discrete(6))

Just upgraded it.

I will run the theano checks.
I will train for 15-20m steps and let you know the results!
About the theano warning, I have been testing another implementation of original DQN using lasagne (which uses only theano backend) - and I had no problems learning breakout and other games using it.

Don't change action_space because it may break something in gym. You can try using env.get_action_meanings() to see what actions are available to agent (my case: ['NOOP', 'FIRE', 'RIGHT', 'LEFT']) and post it here.
To make sure its not a problem with Keras try:
from keras.models import *
from keras.layers import *
from keras.datasets import mnist

x = Input(shape=(28, 28))
h = Reshape((1, 28, 28))(x)
h = Convolution2D(8, 3, 3, activation='relu')(h)
h = Convolution2D(8, 3, 3, activation='relu')(h)
h = Convolution2D(8, 3, 3, activation='relu')(h)
h = Flatten()(h)
y = Dense(10, activation='softmax')(h)

model = Model(x, y)
model.compile('rmsprop', 'sparse_categorical_crossentropy', metrics=['accuracy'])

(train_x, train_y), _ = mnist.load_data()
model.fit(train_x, train_y, nb_epoch=1)

Result:
Epoch 1/1
60000/60000 [==============================] - 4s - loss: 0.2332 - acc: 0.9416

I guess you should have about ~95% accuracy as well.

The action meanings in gym has always been like this for me:
['NOOP', 'FIRE', 'RIGHT', 'LEFT', 'RIGHTFIRE', 'LEFTFIRE']

So, in most of my experiments, I had to correct it to 4 or 3.
I installed gym using pip install 'gym[all]' and gym version is gym-0.7.1. How come your gym only returns 4 actions?
Also, there was a problem with the keras code.
Python 2.7.6 (default, Oct 26 2016, 20:30:19)
[GCC 4.8.4] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> from keras.models import *
Using Theano backend.
Using gpu device 0: GeForce GTX 660 (CNMeM is disabled, cuDNN 5105)
>>> from keras.layers import *
>>> from keras.datasets import mnist
>>> x = Input(shape=(28, 28))
>>> h = Reshape((1, 28, 28))(x)
>>> h = Convolution2D(8, 3, 3, activation='relu')(h)
>>> h = Convolution2D(8, 3, 3, activation='relu')(h)
>>> h = Convolution2D(8, 3, 3, activation='relu')(h)
>>> h = Flatten()(h)
>>> y = Dense(10, activation='softmax')(h)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/local/lib/python2.7/dist-packages/keras/engine/topology.py", line 491, in __call__
    self.build(input_shapes[0])
  File "/usr/local/lib/python2.7/dist-packages/keras/layers/core.py", line 727, in build
    name='{}_W'.format(self.name))
  File "/usr/local/lib/python2.7/dist-packages/keras/initializations.py", line 60, in glorot_uniform
    return uniform(shape, s, name=name)
  File "/usr/local/lib/python2.7/dist-packages/keras/initializations.py", line 33, in uniform
    return K.random_uniform_variable(shape, -scale, scale, name=name)
  File "/usr/local/lib/python2.7/dist-packages/keras/backend/theano_backend.py", line 141, in random_uniform_variable
    return variable(np.random.uniform(low=low, high=high, size=shape),
  File "mtrand.pyx", line 1565, in mtrand.RandomState.uniform (numpy/random/mtrand/mtrand.c:17319)
OverflowError: Range exceeds valid bounds

But after referencing this, I added:
from keras import backend as K
K.set_image_dim_ordering('th')

and I was able to execute the code.
Result:
60000/60000 [==============================] - 9s - loss: 0.3006 - acc: 0.9402

Maybe its because of different roms and/or version of gym (I'm using 0.5.6). Or maybe because right now I'm on Windows and I had to compile ALE and use lots of workarounds to make atari_py work at all. :)
So I think we found main issue. You can either use:
from keras import backend as K
K.set_image_dim_ordering('th')

at the begining of generate_experience_proc and learning_proc or set it permanently in .keras/keras.json with "image_dim_ordering": "th" if I'm correct.
Give it a try and let me know if that solves the issue. :)

Yes. I will give it a try and let you know!
The 4 actions that you get seems a bit weird tho. If you are using atari-py, it should return 6 actions as per the code here, but if you have compiled using the original ALE here - it has 4 actions as you have got. Maybe I need to update my .so files :)
Thanks for helping to solve the problem!  :)

Thats interesting. I wasn't aware of the difference between atari-py and ALE. I sort of compiled ALE and copied it to atari-py to make it work on Windows. :)

Hi,
I just let it run for another 14m epochs, but again I have the same problem! :(
The average is still 1.XX and the image ordering does not seem to be the problem here.
Model after 14m frames:
model-Breakout-v0-14000000.h5.zip
Score avg of actor 0:
training_log_actor-0.txt
Code I used for training:
train_updated_new -code.txt
Unfortunately I could not get the terminal output about loss/entrophy/etc. I closed the terminal before I could copy it. So, I resumed from the 14m frames checkpoint and let it run for a few mins. Here is the output:
Frames: 14005000; Policy-Loss:  -0.427857; Avg:  -0.019142 --- Value-Loss:   0.000391; Avg:   0.199642 --- Entropy: 0.346546; Avg: 0.346539 --- V-value; Min:  0Frames: 14010000; Policy-Loss:  -0.450229; Avg:  -0.013545 --- Value-Loss:   0.000488; Avg:   0.174907 --- Entropy: 0.346533; Avg: 0.346537 --- V-value; Min:  0Frames: 14015000; Policy-Loss:  -0.478949; Avg:  -0.012407 --- Value-Loss:   0.000597; Avg:   0.176477 --- Entropy: 0.346534; Avg: 0.346531 --- V-value; Min:  0.210; Max:  0.218; Avg:  0.213  7310> Best:    3; Avg:   1.00; Max:    3
  7318> Best:    3; Avg:   1.05; Max:    3
Frames: 14020000; Policy-Loss:  -1.874325; Avg:   0.470858 --- Value-Loss:   0.105481; Avg:   0.346848 --- Entropy: 0.346542; Avg: 0.346538 --- V-value; Min:  0.208; Max:  0.215; Avg:  0.211  7315> Best:    4; Avg:   1.24; Max:    4
  7312> Best:    5; Avg:   1.35; Max:    5
Frames: 14025000; Policy-Loss:  -0.457242; Avg:   0.031370 --- Value-Loss:   0.000610; Avg:   0.175511 --- Entropy: 0.346525; Avg: 0.346534 --- V-value; Min:  0.211; Max:  0.216; Avg:  0.214

At time point, it would be really helpful if somone else could run it on their comp and check it!

Hi,
Thought I would make a separate post for this.
I have trained for 10m frames and the average is now at 14-16! :)
Full log:
train_updated_new_v2.py full_log.txt
Actor-0 score averages:
training_log_actor-0.txt
10m train steps model:
model-Breakout-v0-10000000.h5.zip
I have created a few pull requests to make the code compatible with both python 2.x and 3.x and a few other changes to account for breakout's control changes. Review them if you can! :)
Thank you for helping to resolve this issue!  :)

Thank you guys. The future division import helped me on Python 2.7 as well.
I can also confirm the action_space=4 vs 6 makes not a difference, both have good results.
Tested on Keras_V2, gpu.cuda8.cudnn5110 Ubuntu 16.04 and OSX 10.12.3.


Refactor BytecodeFileHandler

BytecodeFileHandler is doing two jobs right now and is quite bloated, break it out into two classes again

Read/Save file
Encode/Decode data

Will also help with decoupling if read&save is not dependant on encode&decode.

Fixed by 959e98576c5f5ecc691f0d5776619b61e46dad30


test target should be in form of test-XXXX

rename e2e-test target to keep in sync with other test targets
https://github.com/vmware/docker-volume-vsphere/blob/master/vmdk_plugin/Makefile#L351
need to rename following targets and make them consistent with others.
e2e-test
e2e-test-runalways
e2e-test-runonce

/CC @msterin

That's easy- just revert the order as below :)
test-e2e
test-e2e-runalways
test-e2e-runonce

That's easy- just revert the order as below

That's a plan hence kept this as 0.5 point task.

Closing this since it is fixed now.


Updated dependencies and fixed issues Update/Redeploy a pod when Conf…

Updated dependencies and fixed issues Update/Redeploy a pod when ConfigMap or Secrets have changed #169 and Allow custom liveness/readiness probe #192
Closes #74

In values.yaml at Line 144, it says, ".. All values will only be created once during install!"
Is this still true?

@bmackinney: No, i forgot to remove that line. All settings are updatable now.
Thank you for pointing me to that little detail.
One thing: When I upgrade the deployment to latest version I get an error that the dependency for the database can't be updated. I need to check that. -- It must be caused by some change in the StatefulSets. :-(

Alright.. bug #224 is fixed and all dependencies in all charts are up-to-date now with #226. I upgraded all my deployments and it works like expected.


Flutter doctor crashes when xcode licenses not yet agreed to

This weekend I was providing assistance as @sobrienpdx tried to install Flutter on a brand new Mac laptop.  After installing xcode, but not yet running it for the first time, Flutter Doctor produced the following output:
$ flutter doctor

Agreeing to the Xcode/iOS license requires admin privileges, please run “sudo xcodebuild -license” and then retry this command.

Building flutter tool...
Doctor summary (to see all details, run flutter doctor -v):

Oops; flutter has exited unexpectedly.
Sending crash report to Google.
Error executing simctl: 69

Agreeing to the Xcode/iOS license requires admin privileges, please run “sudo xcodebuild -license” and then retry this command.

Failed to send crash report. Server responded with HTTP status code 400
Crash report written to .../flutter_01.log;
please let us know at https://github.com/flutter/flutter/issues.
$

Steps to Reproduce
(This is my best recollection of how the problem arose; launching xcode for the first time fixed the problem so I can't verify that this is a correct repro)

Acquire a fresh MacOS computer that has not yet had xcode run on it.
Download and install xcode using the App store, but do not open it.
Download and install Flutter.
Run "flutter doctor".

Logs
Contents of flutter_01.log:

Flutter crash report; please file at https://github.com/flutter/flutter/issues.
command
flutter doctor
exception
VersionCheckError: VersionCheckError: Command exited with code 69: git log -n 1 --pretty=format:%ad --date=iso
Standard error:
Agreeing to the Xcode/iOS license requires admin privileges, please run “sudo xcodebuild -license” and then retry this command.
#0      _runSync (package:flutter_tools/src/version.dart:491:5)
#1      FlutterVersion._latestGitCommitDate (package:flutter_tools/src/version.dart:129:12)
#2      FlutterVersion.frameworkCommitDate (package:flutter_tools/src/version.dart:120:37)
#3      FlutterVersion.frameworkDate (package:flutter_tools/src/version.dart:83:31)
#4      _FlutterValidator.validate (package:flutter_tools/src/doctor.dart:398:45)
<asynchronous suspension>
#5      Doctor.startValidatorTasks (package:flutter_tools/src/doctor.dart:105:56)
#6      Doctor.diagnose (package:flutter_tools/src/doctor.dart:183:42)
<asynchronous suspension>
#7      DoctorCommand.runCommand (package:flutter_tools/src/commands/doctor.dart:29:39)
<asynchronous suspension>
#8      FlutterCommand.verifyThenRunCommand (package:flutter_tools/src/runner/flutter_command.dart:372:18)
#9      _asyncThenWrapperHelper.<anonymous closure> (dart:async/runtime/libasync_patch.dart:77:64)
#10     _rootRunUnary (dart:async/zone.dart:1132:38)
#11     _CustomZone.runUnary (dart:async/zone.dart:1029:19)
#12     _FutureListener.handleValue (dart:async/future_impl.dart:129:18)
#13     Future._propagateToListeners.handleValueCallback (dart:async/future_impl.dart:642:45)
#14     Future._propagateToListeners (dart:async/future_impl.dart:671:32)
#15     Future._complete (dart:async/future_impl.dart:476:7)
#16     _SyncCompleter.complete (dart:async/future_impl.dart:51:12)
#17     _AsyncAwaitCompleter.complete.<anonymous closure> (dart:async/runtime/libasync_patch.dart:33:20)
#18     _rootRun (dart:async/zone.dart:1124:13)
#19     _CustomZone.run (dart:async/zone.dart:1021:19)
#20     _CustomZone.bindCallback.<anonymous closure> (dart:async/zone.dart:947:23)
#21     _microtaskLoop (dart:async/schedule_microtask.dart:41:21)
#22     _startMicrotaskLoop (dart:async/schedule_microtask.dart:50:5)
#23     _runPendingImmediateCallback (dart:isolate/runtime/libisolate_patch.dart:115:13)
#24     _RawReceivePortImpl._handleMessage (dart:isolate/runtime/libisolate_patch.dart:172:5)

flutter doctor
encountered exception: VersionCheckError: Command exited with code 69: git log -n 1 --pretty=format:%ad --date=iso
Standard error:

Agreeing to the Xcode/iOS license requires admin privileges, please run “sudo xcodebuild -license” and then retry this command.

#0      _runSync (package:flutter_tools/src/version.dart:491:5)
#1      FlutterVersion._latestGitCommitDate (package:flutter_tools/src/version.dart:129:12)
#2      FlutterVersion.frameworkCommitDate (package:flutter_tools/src/version.dart:120:37)
#3      FlutterVersion.frameworkDate (package:flutter_tools/src/version.dart:83:31)
#4      _FlutterValidator.validate (package:flutter_tools/src/doctor.dart:398:45)
<asynchronous suspension>
#5      Doctor.startValidatorTasks (package:flutter_tools/src/doctor.dart:105:56)
#6      Doctor.diagnose (package:flutter_tools/src/doctor.dart:183:42)
<asynchronous suspension>
#7      _doctorText.<anonymous closure> (package:flutter_tools/runner.dart:194:26)
#8      AppContext.run.<anonymous closure> (package:flutter_tools/src/base/context.dart:142:29)
<asynchronous suspension>
#9      _rootRun (dart:async/zone.dart:1124:13)
#10     _CustomZone.run (dart:async/zone.dart:1021:19)
#11     _runZoned (dart:async/zone.dart:1516:10)
#12     runZoned (dart:async/zone.dart:1463:12)
#13     AppContext.run (package:flutter_tools/src/base/context.dart:141:18)
<asynchronous suspension>
#14     _doctorText (package:flutter_tools/runner.dart:193:19)
<asynchronous suspension>
#15     _createLocalCrashReport (package:flutter_tools/runner.dart:171:32)
<asynchronous suspension>
#16     _handleToolError (package:flutter_tools/runner.dart:126:33)
<asynchronous suspension>
#17     run.<anonymous closure> (package:flutter_tools/runner.dart:63:20)
<asynchronous suspension>
#18     AppContext.run.<anonymous closure> (package:flutter_tools/src/base/context.dart:142:29)
<asynchronous suspension>
#19     _rootRun (dart:async/zone.dart:1124:13)
#20     _CustomZone.run (dart:async/zone.dart:1021:19)
#21     _runZoned (dart:async/zone.dart:1516:10)
#22     runZoned (dart:async/zone.dart:1463:12)
#23     AppContext.run (package:flutter_tools/src/base/context.dart:141:18)
<asynchronous suspension>
#24     runInContext (package:flutter_tools/src/context_runner.dart:42:24)
<asynchronous suspension>
#25     run (package:flutter_tools/runner.dart:50:10)
#26     main (package:flutter_tools/executable.dart:52:9)
<asynchronous suspension>
#27     main (file:///Users/shaunnaobrien/development_tools/flutter/packages/flutter_tools/bin/flutter_tools.dart:8:3)
#28     _startIsolate.<anonymous closure> (dart:isolate/runtime/libisolate_patch.dart:287:32)
#29     _RawReceivePortImpl._handleMessage (dart:isolate/runtime/libisolate_patch.dart:171:12)

Duplicate of #16427


added brush size indicator cursor

Remove the images.

Overall looks really clean. There's a bunch of small things but (other than the editorview getting a little big) it's good overall.
After the fixes, :shipit:

Closing pull request and moving it to lukemetz/Paranormal


Update Places and Orgs “organizations”

Automatically generated by Netlify CMS

@corbamtb Thank you Steve! The changes are live


RFC: use atomic instructions for propagating simple node outputs

This follows a similar approach to the earlier work by Derek Murray
(change ID I9058c55898079cb3ab6011513b4468ddb293f59f) and allows using
atomic operations on the pending counts. It extends that work to also
apply to graphs that include control/merge nodes (eg the 'wide_deep'
model in the tf models repo)
The approach here is to note that even in a graph that has control/merge
nodes, it's likely that many nodes do not have any merge/control
outputs. There's already a fast path for this case with simpler logic,
and that simple logic has the advantage of only accessing the pending
count in one spot where it decrements the incoming pending values. Only
the last such decrementer propagates the output and activates the node.
Given this, we can use atomic operations for all such "fast path" nodes
and avoid holding an exclusive lock. We fall back to the exclusive lock
for any nodes that have slow-path outputs. As a conservative measure,
this patch acquires the shared lock for the fast path, though it may
not be necessary.
The other bit in this patch is the management of the 'outstanding_ops'
member. In order to allow concurrent completion of ops without the
exclusive lock, this also becomes atomic. Simply making it atomic is
sufficient but leaves a lot of performance on the table. This patch
batches the updates of this variable so that each op completion only
touches it at most once, and no-ops out in the case that the pending op
count doesn't need to be modified (eg when an op completion activates
exactly one downstream node).
I benchmarked this change using tensorflow-models/official/r1/wide_deep
and collecting the distribution of "steps/sec" reported using commands
like:
  # switch to new code
  $ python -u  census_main.py -ebe=20  -te 20 -mt wide 2>&1 | tee /tmp/before/wide.txt
  # switch to new code
  $ python -u  census_main.py -ebe=20  -te 20 -mt wide 2>&1 | tee /tmp/after/wide.txt

... for the 'wide', 'wide_deep', and 'deep' models. I then exported the
'steps/second' metrics to TSV with:
  $ grep 'tensorflow:global_step/sec' \
    /tmp/{before,after}/*.txt | perl -p  -e \
    's,/tmp/(.+)/(.+).txt:.*?([\d\.]+)$,$1 $2 $3,g' > /tmp/data.tsv

Mean steps/sec are as follows on my AMD Ryzen 9 3900X desktop (12
physical cores, 'performance' CPU governor enabled):
Before:
    model   steps/sec
----------------------
      deep  888.2449
      wide  778.8037
 wide_deep  635.0198

After:
    model   steps/sec   improvement
-----------------------------------
      deep  929.8955  (+4%)
      wide  989.9900  (+27%)
 wide_deep  780.8842  (+22%)

A few notes worth considering:
Using atomic operations has some fixed overhead compared to non-atomics,
and particularly when the cache line being operated on is in M
"modified" state in another core. This increased latency of operating on
a cache-line in remote M state (aka "HitM" access) is also true with
non-atomic operations, but non-atomics can potentially allow for
instruction level parallelism and pipeline multiple such accesses
together, whereas atomics do not on current x86 architectures[1]. So,
there is possibly a cross-over point on some graph shapes where the
mutex-based synchronization with non-atomic operations actually beats
the atomic-based implementation here.
That said, the current code path for the non-atomic (mutex-protected)
case is complex/branchy enough that it's not clear that any significant
pipelining of reads can actually occur without some more explicit
unrolling, etc.
It's also worth noting that, in uncontended cases, the atomics will be
slower than the non-atomics. However, this is unlikely an issue in real
workloads, considering that these code paths are only uncontended when
the actual work of op execution dominates the runtime. In other words,
this is only a perf bottleneck when it's under contention, and a small
regression for uncontended cases is likely in the noise.
[1] https://spcl.inf.ethz.ch/Publications/.pdf/atomic-bench.pdf

Mingsheng, I believe you're the right person to be reviewing or finding a reviewer for current runtime changes too? Looks like an interesting optimization but definitely not my area of expertise.

@rmlarsen Can you please review this PR ? Thanks!

@rmlarsen Can you please review this PR ? Thanks!

@toddlipcon This PR failed on some of our tests ( see one of the stack traces below). It is unclear to me what the cause may be. Could you please look into this?
 Will update the PR once fixed.

@toddlipcon  Can you please check @rmlarsen's comments and keep us posted ? Thanks!

Spent a little time digging into the issue the afternoon. The problem seems to be a race when decrementing the num_outstanding_ops in FrameState::IterationState. Specifically, you can get a race like:
Initially: IterationState::num_outstanding_ops == 1, FrameState::num_pending_inputs == 1
T1: decrements num_outstanding_ops from 1->0, but hasn't yet acquired the FrameState::mu_ mutex.
T2: one of the pending inputs is completed, which increments num_outstanding_ops to 1 and decrements num_pending_inputs to 0.
T2: the newly scheduled op is completed, and now we decrement num_outstanding_ops from 1->0
Now both threads proceed to acquire FrameState::mu_ and see that the Iteration is complete (and the frame is complete too). They both think they were "responsible" for completing the frame because they were the thread to decrement num_outstanding_ops. But, really, we need to make the check for the other conditions of IsIterationDone() atomically with the decrement.
Fixing this by putting all the AdjustOutstandingOps logic under a mutex again makes it correct but probably would cancel out a lot of the performance gain. I'm thinking through a few other options and will try to circle back on this patch at some point, but not sure exactly when. I'm happy to prioritize it more highly if you think the performance benefits are substantial to an important class of workloads, but otherwise might be more of a back-burner task for me.

Actually had an idea to try out and it seems to have fixed the problem locally. The num_outstanding_ops structure is now adjusted while holding the shared_mutex on the hot path (which was already held, so there isn't any new lock acquisition in the common case). I check the IsIterationDone() while holding the shared lock. Since any enter/exit nodes would acquire the exclusive lock while modifying the other conditions for IsIterationDone() I think the shared lock is sufficient.
Would it be possible to re-run the test suite? I don't have access to RBE or anything and I think it would take a couple days to run it all on my desktop. Otherwise, I'll be a Googler in a couple weeks and can probably figure out how to run them.

BTW I was able to re-run the benchmarks and still seeing similar improvements of the branch relative to master.
Here "after-ub" is with the "undefined behavior" version of the code that reinterpret_casts to atomic when atomics are necessary, and "after" is the current version of this PR that uses atomic all the time. There's a slight loss in performance by not using the reinterpret_cast trick, but the current PR is still a good improvement relative to master on my machine.

model
run
throughput
vs baseline

deep
before
875.9

deep
after-ub
909.0
+3.9%

deep
after
897.2
+2.5%

wide
before
776.5

wide
after-ub
975.8
+25.7%

wide
after
927.6
+19.5%

wide_deep
before
625.5

wide_deep
after-ub
768.6
+22.9%

wide_deep
after
760.4
+21.6%

@toddlipcon thanks a lot for your patience. This is a very exciting improvement to the core of TensorFlow. Much appreciated!

I'm submitting this via the Google-internal submission flow instead of github PR. Closing here.


Changes required for GCP VPC site creation

This branch will remain open until memes/terraform-google-volterra modules pass their tests.
Closes #81

Closing PR as release 1.0.7 seems to be addressing most use cases.


[test] add reclaim policy test

What type of PR is this?
/kind test

What this PR does / why we need it:
Add an e2e test to confirm CSI can delete volume after claim is deleted in default delete reclaim policy.
Which issue(s) this PR fixes:

Fixes #
Requirements:

[x] uses conventional commit messages

[ ] includes documentation
[ ] adds unit tests
[ ] tested upgrade from previous version

Special notes for your reviewer:
Release note:
none

Pull Request Test Coverage Report for Build<PHONE_NUMBER>

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage remained the same at 77.662%

Totals

Change from base Build<PHONE_NUMBER>:
0.0%

Covered Lines:
817

Relevant Lines:
1052

💛  - Coveralls


Use common story arguments

Part of #202
This is another refactor to reuse storybook arguments across stories. This will make it easier for us to refactor attributes to give them consistent names and values in #202.
This is a no-op. Storybook should work the same in chromatic.
We'll merge this into dev, then merge dev into 2.0.0-alpha1 to make the uxds 2.0 easier to develop.

It looks like some items don't have the same options to follow specially on the sizes and colors. We might need to add the missing options or just create different parameter option for those cases. For example the spinner size is not working with all the options.

@jedgar1mx the differing size arguments was a bug. Some components don't support lg or xl. I fixed that issue.
The differing color arguments was just some missing configurations. AFAIK all the components that gained color options in this PR support those options. E.g. <cod-spinner data-background-color="accent-secondary"/> works OK. See the demo here: https://is.gd/JN4pid


Retrying bulkMutation failures in batch.

Retries are now done as a batch in BulkMutation.
Shared code from BatchExecutor and BigtableBufferedMutator moved to BulkMutation.

Thanks for the catch with retryId.  I somehow removed that with my last PR.  I just submitted a fix for that issue.  I also added handling for a generic RuntimeException.  PTAL.

LGTM


bash completion for detach events

ref #22898, #23244
ping @sdurrheimer for zsh completion

LGTM 🐠
/cc @thaJeztah @runcom

LGTM


"No Notes Connections Found on Canvas" when groups used

EDIT: Oh... Assign Properties by Group was off by default. This was unexpected and added some confusion here! Understand that the behavior below happened with "Assign Properties by Group" disabled and that there's still some strange behavior going on that i can't explain.
Referring to the third example here:

Properties are assigned to both notes based on their groups. However, when I try to do something similar...

...and hit "Append Properties to Notes", the error "No Notes Connections found on Canvas" appears.
Doing this, instead, does give me the property I want in my note, but is not how I wish to lay out my information.

I attempted to then put it in a group called Status that's linked to In Progress, but strangely this made the property field name "cards" and it shows two card names, "|" and "In Progress".

Quite strangely, I was able to get the desired behavior here where it set the status to In Progress.

However, upon adding and removing a few groups and going back to "Append Properties in Note", it again said "No Notes Connections Found on Canvas".

I'm creating a new issue that details my issue better since this one's a mess.


Fixed indexing but partials calculations have empty columns?

The inversion fails with a singular matrix error. I assume this is due to some columns being all zeros, and this seems to be the case from some of the troubleshooting I placed into the bottom of the solver code block, but I can't figure it out. Looks like there are zero columns corresponding to the first few columns of TDE partials (63, 64, 65…) but then when I try to check that matrix of partials itself, it's not reporting any zero columns, so clearly my Python inexperience is causing some issues here. But, if the TDE partials indeed contain some all-zero columns, I'm not sure how to fix that.
Any ideas?

I'm merging this.
@jploveless From your description this sounds like a matrix assembly issue likely focused on estimation.operator?

It looks like most of the estimation.operators matrix is empty right now, so that's something to go on!

Okay, I think I have some indexing suspicions about inserting the TDE
partials into estimation.operators, and I will try to check that out soon.
On Wed, Feb 9, 2022 at 10:54 PM Brendan Meade @.***>
wrote:

It looks like most of the estimation.operators matrix is empty right now,
so that's something to go on!
[image: spy(estimation operator)]
https://user-images.githubusercontent.com/4225359/153334024-9b38b9fc-2f66-4da0-9d02-4214bd60bf58.png
—
Reply to this email directly, view it on GitHub
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REVIEW: harmonize web tutorial with JOSS manuscript examples

(Part of JOSS review https://github.com/openjournals/joss-reviews/issues/6027)
Both the web documentation and the JOSS manuscript include examples for running PROSPECT under a number of scenarios. The web documentation appears to be less recent than the manuscript.
As it stands, I cannot execute the first line in the tutorial:
library(prospect)
LRT_default <- PROSPECT(SpecPROSPECT)

It looks like this throws an error that checks for whether to run PROSPECT-D or PROSPECT-PRO:
Error in if (!LMA == 0 & (PROT > 0 | CBC > 0)) {: argument is of length zero
Traceback:

1. PROSPECT(SpecPROSPECT)

This example should be updated so it executes properly. Other examples that specify the minimum default arguments succeed, but this documented snippet doesn't.
There are many additional examples provided in the JOSS manuscript that users would benefit from having in the web docs. As a user, I am most interested in the inversion methods, and example inversion code is included in the manuscript but not in the web docs. I recommend updating the web docs to include this deeper set of code examples, as it is difficult (at the moment, impossible) to copy code snippets from the manuscript and run them to verify execution.

@earth-chris thank you for raising this issue. This should now be fixed in prospect 1.5.0.
The code and web documentation are now up-to-date. Please tell me if any error remains.

thanks for the fix! i can execute the example code with no issues.


ci(travis): update to node 10

:tada: This PR is included in version 1.3.0 :tada:
The release is available on GitHub release
Your semantic-release bot :package::rocket:


ResultsViz: end times of the plots should line up

It is hard (esp. for longer plots) to accurately match up the logs because their end times are different.  Normalizing their end-times would make visual inspection faster and easier.

Might not be required anymore, since we've got zoomable plots with d3?


Icon classes are not detected at runtime

Context
I have a custom component that takes a Vue component builder as a prop, to be used for on-demand list rendering in the DOM, depending on the viewport size. If nothing is provided, a default builder is used, generating numeric icons on the fly.

Looks like this

withDefaults(defineProps<P>(), {
  right: (i: number) => <CommonCell icon={`i-ri:number-${i}`}/>
})

The cell is just a basic container, nothing fancy:

SFC

<template>
  <div class="cell" flex justify-center items-center>
    <slot>
      <div :class="icon" />
    </slot>
  </div>
</template>

<script setup lang='ts'>
  interface P { icon?: string }
  withDefaults(defineProps<P>(), { icon: 'i-ri:checkbox-multiple-blank-line' })
</script>

Expectation
Have the component class parsed and processed at runtime or during the compilation process, detect any matches, download what's needed, and generate the CSS required for that icon to pop up in the DOM.

Intended usage

<component
  v-for="i in 2"
  :is="right(i)"
/>

Reality
Nothing is detected, CSS classes are empty, no icons to be found on the page. 🤷🏻♂
Research
A few other issues here, relating to dynamic imports, have mentioned safelist-s and manual collection specification. Couldn't quite figure out what to indicate, where precisely and how exactly, though. Any additional pointers would be appreciated.
Workaround
Manually create 'fake' attributes to trick the detector into thinking that the icons are to be used. Quite an annoying thing to do, and only possible for a relatively small (8 icons, in my case) set of these. Utterly impractical for anything bigger.

Current usage

<component
  v-for="i in 2"
  :is="right(i)"
  icons="i-ri:number-1 i-ri:number-2"
/>

<template v-if="smPlus">
  <component
    v-for="i in 2"
    :is="right(i+2)"
    icons="i-ri:number-3 i-ri:number-4"
  />
</template>

<template v-if="mdPlus">
  <component
    v-for="i in 2"
    :is="right(i+4)"
    icons="i-ri:number-5 i-ri:number-6"
  />
</template>

It does look a bit nicer with the auto-preview though, I'll give you that:

--
Is there anything that I'm missing here? Or would it require some inner refactoring?

https://github.com/unocss/unocss#scanning


Vue support

Plan for Vue support has already been mentioned. I've created this issue as a tracker.
Once completed, it might be worth checking whether it works in Nuxt (SSR) too?

You can try https://www.npmjs.com/package/@vt7/vue-number-flow.
In Nuxt I tried and got an error, I checked if there was a problem in esm-env
https://github.com/barvian/number-flow/blob/4fe9cebbfcddd992b27896585558357b65b806d6/packages/number-flow/src/ssr.ts#L1

Haven't had a chance to try it out yet, but in my opinion a Nuxt module instead of having to create a plugin would provide better DX :)

@barvian any update?

It's almost there, I just need to convert the examples on the site and do/write more tests 👍

By the way, if anybody knows a solution for this it'd be very helpful! https://discord.com/channels/325477692906536972/1299071468533055541

Just pushed @number-flow/vue (👉 docs). Please let me know if you experience any issues!

Just tested and it works perfectly! Great job @barvian


Failed prop type: "deprecatedVariants" is read-only in Typography

Just updated to v3.2.1 and am getting the following error in console:
Failed prop type: "deprecatedVariants" is read-only in Typography (created by WithStyles(Typography))
Any ideas?

[x] This is not a v0.x issue.
[x] I have searched the issues of this repository and believe that this is not a duplicate.

Your Environment

Tech
Version

Material-UI
v3.2.1

Failed prop type: "deprecatedVariants" is read-only in Typography (created by WithStyles(Typography)) in WithStyles(Typography) (created by FormControlLabel) in label (created by FormControlLabel) in FormControlLabel (created by WithStyles(FormControlLabel)) in WithStyles(FormControlLabel) (created by CreateTaskBase)

Also getting this for a seemingly benign use of Typography.

update typography variant

@biggreenbubble what do you mean?

Too update variants follow this instruction:
https://material-ui.com/style/typography/#migration-to-typography-v2
However I have updated variants and still got this issue.

Likewise.

+1

We located the issue and have a potential fix pending for review. Please don't spam this thread with "+1". This just floods notifications for everyone subscribed to this issue. You can use the reactions feature instead.

The upstream issue should be fixed with https://github.com/oliviertassinari/babel-plugin-transform-react-remove-prop-types/pull/167. We need to release it now.

can not solve the problem, the console continues to indicate the following warning:
Warning: Failed prop type: "deprecatedVariants" is read-only....
could you help me please?  #Thanks..

@JulianPovedaM The fix is not released yet. We can't offer a solution other than manually editing your node_modules.
One solution could be to clone, build locally and link in your app since the fix in the babel plugin is already released. But please don't ask in this thread how to do this. This is out of scope for this issue.

Will this go out in a patch release or in 3.4.0? If it's a patch release, any time frame estimates?

1-2 hours.

v3.2.2 was released, let me know if it's all good :).

All good on my side too!

I had 3.2.1 that I installed yesterday, and  got here from a google search to find out that 3.2.2 is out! First time I get to an issue right as it gets fixed! Good Job.

@oliviertassinari I'm actually confused here. I get the same warning and is spite of the 3.2.2 it still shows:
const theme = createMuiTheme({
  typography: {
    useNextVariants: true
  },
  palette: {
    primary: {
      main: "#50c9c3",
      light: "#87fcf6",
      dark: "#009893",
      contrastText: "#000000"
    },
    secondary: {
      main: "#80d8ff",
      light: "#b5ffff",
      dark: "#49a7cc",
      contrastText: "#000000"
    }
  }
});

I had a look at the code: here:https://github.com/mui-org/material-ui/blob/b895ee783b13a50d4ab0a92c2ea15c2ff7f1e8ae/packages/material-ui/src/styles/createTypography.js#L38
It seems that calling createTypography (called by createMuiTheme) will always yield this warning once useNextVariants is set to true which per https://material-ui.com/style/typography/#migration-to-typography-v2 is recommended. Am I missing something?

@jraoult Please post the warning message.
The warning message in the code you linked will only trigger if the condition is false.

@oliviertassinari I'm having an error while using Typography and it's saying Cannot read property 'useNextVariants' of undefined. I'm not using material-ui theme. I've set my own theme using another package and also written window.__MUI_USE_NEXT_TYPOGRAPHY_VARIANTS__ = true; inside my HTML page.
Seems there's a condition inside Typography.js that doesn't check null refrence for theme.

We require for the theme to have a certain shape. If a 3rd party package wants to create themes for this library it should match the shape. Full shape: https://github.com/mui-org/material-ui/blob/994c376bb2d07d70b67182be60afd4ad7e247478/packages/material-ui/src/styles/createMuiTheme.d.ts#L30-L43


fix(docz,docz-theme-default): remove react & react-dom from dependencies

Description
fixes #923

https://github.com/pedronauck/docz/pull/882 aims to solve the same issue. I made a comment there to solve it like you did here, @MunifTanjim. But it seems @saimonmoore hasn't updated his PR yet.
@MunifTanjim I guess you also should remove react, react-dom from gatsby-theme-docz's dependencies.

Also, you should update the installation instructions in README.md now that react and react-dom need to be installed as peers.

I guess you also should remove react, react-dom from gatsby-theme-docz's dependencies.

Already did.

Also, you should update the installation instructions in README.md now that react and react-dom need to be installed as peers.

Done!

Hm, I can't see that you've changed anything for gatsby-theme-docz. Are you confusing it with docz-theme-default? gatsby-theme-docz doesn't even have any peerDependencies, so I think they need to be added there and removed from dependencies.

Hm, I can't see that you've changed anything for gatsby-theme-docz. Are you confusing it with docz-theme-default?

You are absolutely right 😲 So sorry about that.

gatsby-theme-docz doesn't even have any peerDependencies, so I think they need to be added there and removed from dependencies.

Done! :sweat_smile:

Merged manually into feat/gatsby.


Homebridge not starting because of host value error

@lprhodes Since last update I get this:
Homer-MacMini:~ homer$ homebridge
[3/14/2018, 8:36:01 PM] Loaded plugin: homebridge-broadlink-rm
[3/14/2018, 8:36:01 PM] Registering platform 'homebridge-broadlink-rm.BroadlinkRM'
[3/14/2018, 8:36:01 PM] ---
[3/14/2018, 8:36:01 PM] Loaded config.json with 0 accessories and 1 platforms.
[3/14/2018, 8:36:01 PM] ---
[3/14/2018, 8:36:01 PM] Loading 1 platforms...
[3/14/2018, 8:36:01 PM] [Broadlink RM] Initializing BroadlinkRM platform...
[CONFIG ERROR] Numeric values should look like this: "host": <IP_ADDRESS> not this "host": "<IP_ADDRESS>"
I went to the config file and remove the " " from the ip numbers and got this:
Homer-MacMini:~ homer$ homebridge
[3/14/2018, 8:32:30 PM] Loaded plugin: homebridge-broadlink-rm
[3/14/2018, 8:32:30 PM] Registering platform 'homebridge-broadlink-rm.BroadlinkRM'
[3/14/2018, 8:32:30 PM] ---
[3/14/2018, 8:32:30 PM] There was a problem reading your config.json file.
[3/14/2018, 8:32:30 PM] Please try pasting your config.json file here to validate it: http://jsonlint.com
[3/14/2018, 8:32:30 PM]
/usr/local/lib/node_modules/homebridge/lib/server.js:207
throw err;
^
SyntaxError: Unexpected token . in JSON at position 391
at JSON.parse ()
at Server._loadConfig (/usr/local/lib/node_modules/homebridge/lib/server.js:201:19)
at new Server (/usr/local/lib/node_modules/homebridge/lib/server.js:57:38)
at module.exports (/usr/local/lib/node_modules/homebridge/lib/cli.js:26:16)
at Object. (/usr/local/lib/node_modules/homebridge/bin/homebridge:17:22)
at Module._compile (module.js:635:30)
at Object.Module._extensions..js (module.js:646:10)
at Module.load (module.js:554:32)
at tryModuleLoad (module.js:497:12)
at Function.Module._load (module.js:489:3)

This is fixed in v3.2.3


I will start editing again once the English text has caught up.

I will restart editing once the English text has caught up. Currently, I am waiting for more text to appear for smart pointers and beyond.

Those we can close this issue, please close it.
Because dangling issues do drain human energy.

Very well, I will close this issue. I was waiting from some update from the project, but it has not come yet.

On Sat, Aug 05, 2023 at 09:45:18AM -0700, Tanish-Eagle wrote:

... I was waiting from some update from the project, but it has not come yet.

Advice: State clearly what update you need.
Preferable in an open (or re-opened) issue.
And take ownership of it.
Groeten
Geert Stappers
Has no idea what is blocking Tanish-Eagle
and want to go beyond it, to go a next challenge.
Silence is hard to parse

I was waiting for more text to appear on the smart pointers and beyond, but currently there is nothing there. As a result, I could not perform my editing duties. That is what blocking me.

On Sun, Aug 06, 2023 at 11:28:01AM -0700, Tanish-Eagle wrote:

I was waiting for more text to appear on the smart pointers and beyond,
but currently there is nothing there. As a result, I could not perform
my editing duties. That is what blocking me.

Acknowlege.
Thanks for closing the issue.
Thanks for explaining what is needed at your side.
For what it is worth:
Doing is much better as talking about what will be done.
Groeten
Geert Stappers
Silence is hard to parse


During maxreflectionlength downgrade, try divide&conquer with larger fanout

https://github.com/dionyziz/rupture/blob/develop/backend/breach/strategy.py#L244


Fix bug in Rectangle copying functionality

The former code failed to correctly copy source rectangles whose x == 0, returning a Rectangle with { x: nan... }. It might also be worthwhile to put some checks in place to ensure NaN is never possible as the values for any of the rectangle properties.

yes, good point, we could check the arguments and throw an error if it's not what we expect.
Thanks for the PR! (I just added a regression test)


feat(587): Add lastCommitMessage to parsed hook

Context
I'd like to implement the skipping builds feature (screwdriver-cd/screwdriver#587)
I've already changed scm-github and scm-bitbucket module to do it (screwdriver-cd/scm-github#64 , screwdriver-cd/scm-bitbucket#40)
Objective
This PR adds lastCommitMessage to the result of parseHook.
References

issue: screwdriver-cd/screwdriver#587
webhook spec: https://docs.gitlab.com/ce/user/project/integrations/webhooks.html

Hi @catto, thanks for this enhancement.  Before I can merge, can you help to rebase?

@bdangit I have fixed the conflict. Would you check it please?


Using ssh-agent on Windows?

Is it possible to use deployer with ssh-agent on Windows?
When I am connecting with identityFile('~/.ssh/id_rsa.pub', '~/.ssh/id_rsa', 'MyStrongPassword') it's ok. Deployment is successful.
But it's not secure to store MyStrongPassword here. I am trying to use forwardAgent() and all I get is:
Warning: fsockopen(): unable to connect to unix://C:/Users/8523~1/AppData/Local/Temp/ssh-lZz6mszVrxCO/agent.2700:0 (Unable to find the socket transport "unix" - did you forget to enable it when you configured PHP?) in path\to\vendor\deployer\phpseclib\phpseclib\System\SSH\Agent.php on line 97

Notice: Unable to connect to ssh-agent (Error 11073052: Unable to find the socket transport "unix" - did you forget to enable it when you configured PHP?) in path\to\vendor\deployer\phpseclib\phpseclib\System\SSH\Agent.php on line 99

[RuntimeException]
 Unable to login with the provided credentials.

I am using https://msysgit.github.io/ and ssh-agent works great. I just typing "ssh user@hostname" and connection is successful.
Also I can use "pageant" agent (Putty). It works great too.

Error 11073052: Unable to find the socket transport "unix" - did you forget to enable it when you configured PHP?

Couldn't find any information about unix sockets on Windows.

Is it possible to use unix sockets on Windows? [I think answer is NO]
Is it possible to use another socket transport to connect to ssh-agent on Windows?

I have exact same problem on Windows.
@frutality

When I am connecting with identityFile('~/.ssh/id_rsa.pub', '~/.ssh/id_rsa', 'MyStrongPassword') it's ok.

I even could not deploy with identityFile().
When using identityFile(), how could deployment server be authenticated by git server? Did you upload private key to deployment server?

Why is this closed? I'm having same issue.

using windows
everything works with putty+pageant
everything works with ssh+ssh-agent
deployer doesn't work, same error as described above.

stream_get_transports() returns
string (3) "tcp"
string (3) "udp"
string (3) "ssl"
string (5) "sslv3"
string (5) "sslv2"
string (3) "tls"
string (7) "tlsv1.0"
string (7) "tlsv1.1"
string (7) "tlsv1.2"

How exactly do I "enable unix:// socket transport" in my php.ini in windows?
If unix:// transport is not available, maybe you could implement some other way of using ssh-agent (or pageant) - the way default utilites like ssh do it.

@dima-stefantsov this issue is out of date.
You can make a new issue if you have problem.
Please show me your enviroment.
Current i am using forward agent success on windows (git bash + ssh-agent).

Hi @oanhnn, thanks for your reply.
With stream_get_transports() I have shown that I don't have unix:// transport available/installed. That is certainly the reason it fails for me.
I am using latest wamp on windows, php 5.6 or 7.0.8. Since it works for you, you must have unix:// transport. How do I get one?

Problem with ssh in php is what native extension ext-ssh for php does not support this, and pure php implementation of ssh (phpseclib) supports it only on unix-like systems.
So here a few way to solve this issue:

Implement forwardAgent in ext-ssh.
Add windows support to phpseclib.
Or add new ssh transport to deployer.

I'm going to do last one in next v4. But do not know then it will be done.

Reopened in #808


Upgrade to 0.93

Checklist

[x] Used a personal fork of the feedstock to propose changes
[x] Reset the build number to 0 (if the version changed)
[x] Re-rendered with the latest conda-smithy (Use the phrase @conda-forge-admin, please rerender in a comment in this PR for automated rerendering)

Hi! This is the friendly automated conda-forge-linting service.
I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.

@conda-forge-admin, please rerender

@conda-forge-admin, please rerender

@conda-forge-admin, please rerender

bld.bat should be in the recipe directory.

@jakirkham My bad. Thanks!

No worries. Looks like you were already fixing it 🙂

@conda-forge-admin, please re-render.

Maybe we can disable the static library on Windows? Or do we need that for things downstream of this package?

Let me create a patch for removing static libs from the build.

@conda-forge-admin, please rerender

Looks like Python 3.6 and 3.7 now pass! 😄
Python 3.8 fails, but this appears to be related to a known issue finding DLLs ( https://github.com/conda-forge/python-feedstock/issues/307 ). We've seen this before in llvmlite where we added a small patch to include the right search path ( https://github.com/conda-forge/llvmlite-feedstock/pull/44 ), which fixed the issue there. Maybe we can do something similar here?

@jakirkham Thanks! Hopefully the new fix will fix the DLL path issue.

@jakirkham It worked! Thanks a lot!

Great thanks for working on this @hcho3! 😀


can't select GPU

hi,
in cyclesOption nodes, I can see both cuda and optix options in "device" choice but both are not selectable
I've tried to install cuda, like for older version, it's make no changes, I'm still not able to select gpu rendering
If I put device on "Multi", then I can select my 7 GPU in Multidevice settings but the render crash gaffer with segmentation fault
WARNING : MeshAlgo : Variable "N" has unsupported interpolation type - not generating normals. E1003 10:50:04.943858 174090 bvh.cpp:122] Requested unsupported BVH layout.
any idea why ?
specs:
OS : Centos 7.8
NVIDIA Drivers : 450.80.02 - Cuda version 11.0
gafferCycles 0.22.0
gaffer <IP_ADDRESS>

I've tried both BHV2 and EMBREE in bhv settings

Hi @Kaiz3rTool
I don't have an Nvidia card currently in a convenient way to test this so no ETA, but all the kernels are built and packaged for Cycles to detect and use without needing Cuda installed, and I am not seeing anything obvious that has changed since the previous version of Cycles in this regard.
BVH setting shouldn't be needed here, but BVH2 is what GPUs should use automatically. Is this choosing device or multi-device? Multi-device needs revisiting eventually when I have the hardware to test.
Cheers

hi, the strange things is that cards are detected as I see it in device but i can't select them
about BHV, it's in multidevice as I can't select cuda or optix in device
also I have seen that Optix denoising doesn't works so I guess is a global problem with Nvidia GPU support
cheers

Can you just test from Session->Device just the GPU itself and not multi-device, does that work? I don't have the hardware here to get multi-device to work smoothly, someone else will need to send patches in or I get the hardware somehow.

The denoise thing is new code to manage different device render/denoise compatibility eg. CPU render + Optix denoise, I've got some code which might solve that one that I found was added to the Blender addon, just I can't test it locally.

hey, I can't as the GPU is greyed

If it's helps, I can maybe create remote login on my server to let you test. I need to see how it's doable to us
to be certain the problem is not from our server, I've tried in blender and with blender benchmark, both cuda and optix works as expected

That is strange, never seen the UI have those greyed out before. Can you run this in the script editor for me?
import GafferCycles

for device in GafferCycles.devices:
    print("Type: %s - ID: %s" % (device["type"], device["id"]))

Also is that an existing CyclesOptions node in a loaded scene? Can you try re-creating that node to see if that fixes things?

here is the log from the command
Type: CUDA - ID: CUDA_GeForce RTX 2080 Ti_0000:1a:00 Type: CUDA - ID: CUDA_GeForce RTX 2080 Ti_0000:1b:00 Type: CUDA - ID: CUDA_GeForce RTX 2080 Ti_0000:3d:00 Type: CUDA - ID: CUDA_GeForce RTX 2080 Ti_0000:88:00 Type: CUDA - ID: CUDA_GeForce RTX 2080 Ti_0000:89:00 Type: CUDA - ID: CUDA_GeForce RTX 2080 Ti_0000:b1:00 Type: CUDA - ID: CUDA_GeForce RTX 2080 Ti_0000:b2:00 Type: OPTIX - ID: CUDA_GeForce RTX 2080 Ti_0000:1a:00_OptiX Type: OPTIX - ID: CUDA_GeForce RTX 2080 Ti_0000:1b:00_OptiX Type: OPTIX - ID: CUDA_GeForce RTX 2080 Ti_0000:3d:00_OptiX Type: OPTIX - ID: CUDA_GeForce RTX 2080 Ti_0000:88:00_OptiX Type: OPTIX - ID: CUDA_GeForce RTX 2080 Ti_0000:89:00_OptiX Type: OPTIX - ID: CUDA_GeForce RTX 2080 Ti_0000:b1:00_OptiX Type: OPTIX - ID: CUDA_GeForce RTX 2080 Ti_0000:b2:00_OptiX Type: CPU - ID: CPU Type: MULTI - ID: MULTICUDA_GeForce RTX 2080 Ti_0000:1a:00CUDA_GeForce RTX 2080 Ti_0000:1b:00CUDA_GeForce RTX 2080 Ti_0000:3d:00CUDA_GeForce RTX 2080 Ti_0000:88:00CUDA_GeForce RTX 2080 Ti_0000:89:00CUDA_GeForce RTX 2080 Ti_0000:b1:00CUDA_GeForce RTX 2080 Ti_0000:b2:00CUDA_GeForce RTX 2080 Ti_0000:1a:00_OptiXCUDA_GeForce RTX 2080 Ti_0000:1b:00_OptiXCUDA_GeForce RTX 2080 Ti_0000:3d:00_OptiXCUDA_GeForce RTX 2080 Ti_0000:88:00_OptiXCUDA_GeForce RTX 2080 Ti_0000:89:00_OptiXCUDA_GeForce RTX 2080 Ti_0000:b1:00_OptiXCUDA_GeForce RTX 2080 Ti_0000:b2:00_OptiXCPU
I have tried to recreate the node a couple of times or open it in different older scene, still greyed

Alright I think I know what it might be, just simply a huge amount of the same card (nice setup!)
https://github.com/boberfly/GafferCycles/blob/master/python/GafferCyclesUI/CyclesOptionsUI.py#L471

On this line in python, can you change:
	for device in GafferCycles.devices :
		presetNames.append( "%s - %s" % ( device["type"], device["description"] ) )

To:
	index = 0
	for device in GafferCycles.devices :
		presetNames.append( "%02i - %s - %s" % ( index, device["type"], device["description"] ) )
		index += 1

And see if the box isn't greyed out but rather lists all of your cards?
Cheers

hey,
thanks for the fix, not greyed anymore and it's work nicely with both Optix and Cuda
all cards are listed as in multidevice,
yeah this server is quite funny, next step is to founda way to render on all GPUs on deadline :)
Thanks !

Re-opening until I patch the source code ;)


Split munki recipes into download+munki where applicable

Some of your .munki recipes actually do the work of downloading the app in addition to just importing it into Munki. Would be excellent to have discrete .download recipes to use as the ParentRecipe for your .munki recipe, and this would allow others to create .pkg and other recipes based on the .download as well.
Here's a list of recipes that fit into this category:

GoogleTalkPlugin/GoogleTalkPlugin.munki.recipe
Handbrake/Handbrake.munki.recipe
iTerm2/iTerm2.munki.recipe
Panic/Coda.munki.recipe
Panic/Coda2.munki.recipe
Panic/Transmit.munki.recipe
Panic/Unison.munki.recipe
PrimateLabs/Geekbench2.munki.recipe
PrimateLabs/Wiinote.munki.recipe

Interested? Of course I'd help.

These recipes were all written before parents existed.  I don't have the
need or any of these changes as I only use Munki, but would accept a pull
request which properly made them.
On Fri, Oct 2, 2015 at 1:57 AM, Elliot Jordan<EMAIL_ADDRESS>wrote:

Some of your .munki recipes actually do the work of downloading the app in
addition to just importing it into Munki. Would be excellent to have
discrete .download recipes to use as the ParentRecipe for your .munki
recipe, and this would allow others to create .pkg and other recipes based
on the .download as well.
Here's a list of recipes that fit into this category:

GoogleTalkPlugin/GoogleTalkPlugin.munki.recipe
Handbrake/Handbrake.munki.recipe
iTerm2/iTerm2.munki.recipe
Panic/Coda.munki.recipe
Panic/Coda2.munki.recipe
Panic/Transmit.munki.recipe
Panic/Unison.munki.recipe
PrimateLabs/Geekbench2.munki.recipe
PrimateLabs/Wiinote.munki.recipe

Interested? Of course I'd help.
—
Reply to this email directly or view it on GitHub
https://github.com/autopkg/keeleysam-recipes/issues/49.

--
Samuel Keeley


Support non-breaking spaces in function names.

[closes #21]
This change would allow a function name with non-breaking spaces to display correctly in pretty print output.

This looks good, but please add a test to prove that output is correct.

@ecrmnn - Added a test.

Thanks. I'm currently on vacation, but I'll look at this when I get home.


Problem with CUDA backend

I have compiled AdaptiveCpp with CUDA backend enabled and this code works with no problem:
#include<iostream>
#include<sycl/sycl.hpp>

using namespace sycl;

int main(){
    queue gpu_q{gpu_selector_v};
    std::cout << "device: "<< gpu_q.get_device().get_info<info::device::name>() << std::endl;
    return 0;
}

output:
device: NVIDIA GeForce RTX 3070 Laptop GPU

But when I run the following code:
#include<iostream>
#include<array>

#include<sycl/sycl.hpp>

using namespace sycl;

int main(){
    constexpr int size = 10000;
    std::array<int, size> data;

    queue gpu_q{gpu_selector_v};

    std::cout << "device: "<< gpu_q.get_device().get_info<info::device::name>() << std::endl;

    buffer B{data};

    gpu_q.submit([&](handler& h){
        accessor A{B, h};
        h.parallel_for(size, [=](auto& idx){
            A[idx] = idx;
        });
    });

    host_accessor A{B};

    for(size_t i=0; i<size; ++i)
        if (i%100 == 0)
            std::cout << "A[" << i << "] = " << A[i] << std::endl;

    return 0;
}

I get this error:
device: NVIDIA GeForce RTX 3070 Laptop GPU
[AdaptiveCpp Error] from /home/amirabbas/acpp/AdaptiveCpp/include/hipSYCL/glue/llvm-sscp/jit.hpp:277 @ compile(): jit::compile: Encountered errors:
0: LLVMToPtx: Could not find CUDA libdevice bitcode library

[AdaptiveCpp Error] from /home/amirabbas/acpp/AdaptiveCpp/src/runtime/cuda/cuda_queue.cpp:702 @ submit_sscp_kernel_from_code_object(): cuda_queue: Code object construction failed
[AdaptiveCpp Error] accessor [host]: Aborting synchronization, runtime error list is non-empty
============== hipSYCL error report ==============
hipSYCL has caught the following unhandled asynchronous errors:

   0. from /home/amirabbas/acpp/AdaptiveCpp/include/hipSYCL/glue/llvm-sscp/jit.hpp:277 @ compile(): jit::compile: Encountered errors:
0: LLVMToPtx: Could not find CUDA libdevice bitcode library

   1. from /home/amirabbas/acpp/AdaptiveCpp/src/runtime/cuda/cuda_queue.cpp:702 @ submit_sscp_kernel_from_code_object(): cuda_queue: Code object construction failed
terminate called after throwing an instance of 'hipsycl::sycl::exception'
  what():  from /home/amirabbas/acpp/AdaptiveCpp/include/hipSYCL/glue/llvm-sscp/jit.hpp:277 @ compile(): jit::compile: Encountered errors:
0: LLVMToPtx: Could not find CUDA libdevice bitcode library

Aborted (core dumped)

I'm on Ubuntu 24.04 and using CUDA 12.2 . Is it a problem with my CUDA installation? with AdaptiveCpp installation or it's about my code?
Thanks.

Is it a problem with my CUDA installation? with AdaptiveCpp installation or it's about my code?

It's about your setup, not about your code. It looks for the libdevice.10.bc file, which comes as part of CUDA and provides implementations of math function builtins. This file is supposed to be in $CUDA_ROOT/nvvm/libdevice.
My guess is that perhaps you have installed CUDA with some distribution packages. Some Linux distributions package CUDA differently - it's impossible for us take into account each and every distribution's conventions, since they all think they know it better. I recommend using the official CUDA installer or packages from NVIDIA.

It's working now after I installed CUDA from NVIDIA.


Update Set-AntiPhishPolicy.md

Removing parameters that are not applicable or available WW yet

OPS Build status updates of commit 93b1bc4:
:clock10: Preparing: average preparing time is 1 min(s) 13 sec(s)

OPS Build status updates of commit 93b1bc4:
:white_check_mark: Validation status: passed

File
Status
Preview URL
Details

exchange/exchange-ps/exchange/advanced-threat-protection/Set-AntiPhishPolicy.md
:white_check_mark:Succeeded
View (exchange-ps)

For more details, please refer to the build report.
Note: If you changed an existing file name or deleted a file, broken links in other files to the deleted or renamed file are listed only in the full build report.

OPS Build status updates of commit 88a2628:
:clock10: Preparing: average preparing time is 1 min(s) 13 sec(s)

OPS Build status updates of commit 88a2628:
:clock10: Incremental building: average incremental building time is 12 min(s) 23 sec(s)


kube-batch 0.4.1 release

Is this a BUG REPORT or FEATURE REQUEST?:
/kind feature
Description:

[ ] Release Notes
[x] Doc updates (#623)

@thandayuthapani , would you help to draft CHANGES for 0.4.1 based on release-0.4 branch?

Hi @k82cn , it seems kubesigs/kube-batch:v0.4.1 has not been pushed https://hub.docker.com/r/kubesigs/kube-batch/tags. All docs that reference it will fail.

@hex108 , yes, I'll upload it ASAP; sorry for the confusion :)

Image was uploaded, close this issue :)


Tasks are not restarting nor scaling

Hi
I am very new to Mesos/Marathon - I am following the following set of tutorials
https://open.mesosphere.com/advanced-course/using-the-marathon-gui/
When i start a task (command python -m SimpleHTTPServer $PORT) , it starts up correctly , but if i restart this task or try to scale up from 1 ==> 2 , It hangs up waiting on deployment. There is no logs and no way to tell what is going on.
Here is a screen shot of where is is stuck:

We'll need to see your app's complete JSON definition and it would help to share how may agents and the resources they each have (and the roles to which they belong).

Here is the complete json definition for my application
{
"id": "/http-simple",
"cmd": "python -m SimpleHTTPServer $PORT",
"cpus": 1,
"mem": 32,
"disk": 0,
"instances": 1,
"healthChecks": [
{
"path": "/",
"protocol": "HTTP",
"portIndex": 0,
"gracePeriodSeconds": 300,
"intervalSeconds": 60,
"timeoutSeconds": 20,
"maxConsecutiveFailures": 3,
"ignoreHttp1xx": false
}
],
"portDefinitions": [
{
"port": 10000,
"protocol": "tcp",
"labels": {}
}
]
}

@rupamroy: See here what Waiting means: https://mesosphere.github.io/marathon/docs/waiting.html
You probably run out of resources?

@rupamroy Are you using DC/OS from dcos.io ?
Where is python installed on your agents? When you a {{which python}} does it show {{/opt/mesosphere/bin/python}}? If so, please try specifying the full path to the python interpreter and change {{SimpleHTTPServer}} to {{http.server}} since we install and use python3 by default.

@rupamroy I'm assuming you got past this issue. I ran into as well and @aquamatthias hit the nail on the head for me.  I was previously working with DC/OS v1.7 which OOTB set Marathon application defaults to CPU usage of 0.1. When working through the https://open.mesosphere.com/advanced-course/using-the-marathon-gui/ tutorial I failed to immediately notice that Marathon application defaults to 1 CPU for the application. Once I changed it to 0.1 for the simple python server I was able to scale out as per the tut.

Note: This issue has been migrated to https://jira.mesosphere.com/browse/MARATHON-2556. For more information see https://groups.google.com/forum/#!topic/marathon-framework/khtvf-ifnp8.


fix(deis-slugbuilder.yaml): use repo_name instead of deis-slugbuilder

so the builder script can replace it with the git sha, and no collisions occur
Fixes #41

is there substitution happening here that wasn't happening before? :)

or is there another related PR for this

@bacongobbler my understanding is that the above is replaced by this:
https://github.com/deis/builder/blob/master/rootfs/etc/confd/templates/builder#L115

yep, what @technosophos said. he's a faster typer than me ;)

okay, we just weren't using it before.

we were, then I got my hands on it and broke everything! sorry @smothiki


Allow LPLayerNorm to support self.bias=None

We are experimenting with removing all biases from our MosaicGPT models. When we do so with torch.nn.LayerNorm it works, but with LPLayerNorm it fails. This just adds a check on if self.bias is None.

@bandish-shah there is a moderate likelihood that our MosaicGPT in examples will need this feature, so until this patch is released in Composer, we likely cannot tag a release of Examples against it (or we will need to maintain a second branch or something like that)
Basically this might be worth an 0.13.2, if you have other stuff you want to get in there.

@abhi-mosaic Can you please add a unit test ensuring this works? Similarly, can you please add the same fix and unit test to LowPrecisionGroupNorm? it's probably something simple like extending existing models they use in unit tests to have a flag for bias or not (with default on).

Basically this might be worth an 0.13.2, if you have other stuff you want to get in there.

We do have a lot of checkpointing fixes coming in this week....

Basically this might be worth an 0.13.2, if you have other stuff you want to get in there.

@abhi-mosaic let's hold off, there are other fixes in progress.  We can target the 0.13.2 hot patch for late next week.

Thanks @nik-mosaic !!!


Remove lombok

Why?

Idiot, useless library.

This doesn’t just remove lombok

Idiot, useless library.

^ is not an appropriate way to behave or have reasonable discussion.


 I was wondering if you could take the time to also add support for counting semaphores rather than just binary ones.

No plans, it shouldn't be hard to modify though. You will have counting semaphores in C++20 (https://en.cppreference.com/w/cpp/thread/counting_semaphore).


⚠ Thumbnails API Endpoint has degraded performance

In dd0e7a3, Thumbnails API Endpoint (https://thumbnails.roblox.com/v1/assets?assetIds=82738847&format=Png&isCircular=false&size=30x30) experienced degraded performance:

HTTP code: 200
Response time: 4885 ms

Resolved: Thumbnails API Endpoint performance has improved in cf64d74.


don't show seconds on webpage for race schedule times

oh i thought the referenced commit would have closed this


Refactor: switch to ring library

Description
A long time ago we moved away from the ring crate to a constellation of pure-rust cryptographic libraries. We did the switch because the ring library did not build for certain architectures (like s390x and webassembly).
This limitation has been addressed by latest versions of the library. Moreover, we have recently reintroduced the ring dependency to implement TUF trustroots.
Moving back to ring would reduce the list of dependencies we have, making the codebase easier to understand and to maintain.
I think these are the dependencies we should be able to remove:

ecdsa
ed25519
ed25519-dalek
elliptic-curve
p256
p384
pkcs1
pkcs8
rsa

@jleightcap: awesome, who should assign this issue to?

I still think we should drop the pure-rust libraries and support either ring or aws-lc-rs

It seems that aws-lc-rs is finicky for Windows builds. Since they are drop-in replacements, I think it would be a good idea to provide a feature for selecting between them.


MRG: Better Qt info

This PR

Fixes a minor bug with our OSX install instructions
Improves our mne.sys_info() to give the PyQt5 version, where relevant. This can help debug OSX problems.

thx @larsoner


Unable to start KingPhisherServer

Issue Description
I received below error:
ERROR    failed to bind server to address (socket error #98)
ERROR    socket error #98 (Address already in use)
Traceback (most recent call last):
File "/opt/king-phisher/king_phisher/server/build.py", line 159, in server_from_config
server = KingPhisherServer(config, plugin_manager, handler_klass, addresses=addresses, ssl_certfile=ssl_certfile, ssl_keyfile=ssl_keyfile)
File "/opt/king-phisher/king_phisher/server/server.py", line 757, in init
super(KingPhisherServer, self).init(handler_klass, *args, **kwargs)
File "/usr/local/lib/python3.5/dist-packages/advancedhttpserver.py", line 1694, in init
server = server_klass((address[0], address[1]), handler_klass, config=self.__config)
File "/usr/local/lib/python3.5/dist-packages/advancedhttpserver.py", line 666, in init
super(ServerNonThreaded, self).init(*args, **kwargs)
File "/usr/lib/python3.5/socketserver.py", line 440, in init
self.server_bind()
File "/usr/local/lib/python3.5/dist-packages/advancedhttpserver.py", line 682, in server_bind
super(ServerNonThreaded, self).server_bind(*args, **kwargs)
File "/usr/lib/python3.5/http/server.py", line 138, in server_bind
socketserver.TCPServer.server_bind(self)
File "/usr/lib/python3.5/socketserver.py", line 454, in server_bind
self.socket.bind(self.server_address)
OSError: [Errno 98] Address already in use
CRITICAL server failed to build with error: socket error #98 (Address already in use)
INFO     unloading 0 plugins
Reproduction Steps
I tried executing below command to start king-phisher server:
./KingPhisherServer -L INFO -f server_config.yml
Environment Details
Host OS:  Kali 2016 R2 32-Bit
King Phisher Version: Latest Version

@str4n63r Please review the FAQ for Socket failed to bind issue.
This gennerally occurs when you have an instance of apache or ngix already running on the system, stop and disable these service for the duration that you are utilizing the KingPhisherServer.

Thank you @wolfthefallen. That solved my issue.

@str4n63r No problem, Happy Phishing!


Long Integers in the data gets changed

I am having an issue in the PDF417 barcode. Suppose i pass a string which has a long number in it at some place barcode is generated but that value of string is getting changed.
e.g string,
30|1|756645355|02112015|1319|111111111w1111111111111111111w|1111111111111w111111111111111w|g|
The long string of 1's is not readable in barcode. Or changed to some other value

Thanks for the report, should be fixed by 9bf6e09


AMBARI-23873. Upgrade history arrow does not indicate downwards when …

…expanded
What changes were proposed in this pull request?
Upgrade history arrow does not indicate downwards when expanded
How was this patch tested?
manually
Please review Ambari Contributing Guide before opening a pull request.

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Test PASSed.

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Upgrade @types/uuid package to dependency

closes #387

I think some part of nests uses version 9 of uuid. Maybe we can upgrade this package to have it consistent?

decided to stay with v10


Type imports do not follow rules from import/order

I have the import/order rule set up with the following configuration:
		"import/order": ["error", {
			"groups": [	"builtin", "index", "external", "internal", "sibling", "parent", "type"],
			"newlines-between": "always",
			"alphabetize": { "order": "asc", "caseInsensitive": true }
		}],

And I expected the groups rule to be applied to type imports, however this doesn't seem the case and these imports seem to just get sorted alphabetically. Here's an example:
// Sorted type imports by import/order
import type { Command } from "../../lib/imports"
import type { WithId } from "mongodb"

Expected sorting following the order external -> internal
import type { WithId } from "mongodb"
import type { Command } from "../../lib/imports"

As I understand this may be seen as expected behavior for some people, I believe this fix could be introduced as a boolean option for the rule that would come disabled by default.

They should be sorted by specifier. The import names have no bearing on the sorting.
I definitely agree that it makes sense to, within the group "type", sort everything by groups as well. It'd probably be best to do this under an option, yes.

Ah sorry for my misunderstanding! Is there any documentation on what each one of the groups mean so that I can try to configure my rule better?
Glad to know you agree with this though, looking forward to seeing this in a future release!

I don't think there's any way to configure it for what you want, at the moment. The best path forward is a PR adding the option you want :-)


fix: make watch

What?
Fix make watch, some files were deleted

@menduz, can we merge it to master?

Merging this PR because we need it ASAP.


Reversed trend in /:owner/:repo/timeseries/watchers and possibly incorrect number

Looking at http://twitter.augurlabs.io/api/unstable/rails/rails/timeseries/watchers I think that the trend of watchers and the dates have been reversed i.e. watchers decrease with time. Maybe it's a bug.

After reversing the trend, I believe the number does not relate to the actual number of watchers on https://github.com/rails/rails

Hi @OrkoHunter,
/:owner/:repo/timeseries/watchers returns only the new watchers in that time period, instead of the total number of watchers in that time period. This is why the count goes up and down, and why the number =/=  the total number of watchers. If you want, I can look into adding a gross watchers and a net watchers endpoint.

Oh! Thanks @ccarterlandis for telling me about this. I did not expect the watchers endpoint to give the difference. Although that is a helpful metric. I wish it remains, but having the trend of the actual number will be helpful as well. (Not urgent in any way).

@OrkoHunter sure thing! If it's okay with you, I'll mark this as closed. If you want to open an issue detailing the new endpoints you'd like to see, that'd be very helpful! If you're busy, I can do it as well.

Sure, this is closed! I will open an issue shortly.

Ref - #153


December doc plan

Following doc updates are needed for Jan 11 release

[x] update how to azdev-ify in dev hub  (@hhunter-ms ) - done

Dependency on release in Jan. Point to release branch: release-azd-updates

[x] #1149

PR in DevHub: MicrosoftDocs/azure-dev-docs-pr#3957

[x] #1212

PR in DevHub: MicrosoftDocs/azure-dev-docs-pr#3983

[x] #1227

PR in DevHub: MicrosoftDocs/azure-dev-docs-pr#3842

[x] #1281

PR for DevHub: MicrosoftDocs/azure-dev-docs-pr#3842

[x] #1283

PR in DevHub: MicrosoftDocs/azure-dev-docs-pr#3973

[x] #1286

PR in DevHub: MicrosoftDocs/azure-dev-docs-pr#3978

[x] Updates for MSI install

[x] PR in DevHub: https://github.com/MicrosoftDocs/azure-dev-docs-pr/pull/4028

Push from release-azd-updates branch to live on 1/11/23:

[x] PR: MicrosoftDocs/azure-dev-docs-pr#4042

FYI, release branch: https://github.com/MicrosoftDocs/azure-dev-docs-pr/tree/release-azd-updates

I reviewed all PRs.  They look good to me.

Completed and merged.