Tensorflow TypeError

What version of tensorflow tensor2tensor require?
I'm using the tensorflow-gpu version 1.2.1
I just run:
pip install tensor2tensor && t2t-trainer \
  --generate_data \
  --data_dir=~/t2t_data \
  --problems=translate_ende_wmt32k \
  --model=transformer \
  --hparams_set=transformer_base_single_gpu \
  --output_dir=~/t2t_train/base

I got the error:
INFO:tensorflow:Performing local training and evaluation.
WARNING:tensorflow:From /usr/local/lib/python2.7/dist-packages/tensorflow/contrib/learn/python/learn/monitors.py:268: __
init__ (from tensorflow.contrib.learn.python.learn.monitors) is deprecated and will be removed after 2016-12-05.
Instructions for updating:
Monitors are deprecated. Please use tf.train.SessionRunHook.
INFO:tensorflow:batching_scheme = {'boundaries': [8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 22, 24, 26, 28, 30,
33, 36, 39, 42, 46, 50, 55, 60, 66, 72, 79, 86, 94, 103, 113, 124, 136, 149, 163, 179, 196, 215, 236], 'window_size': 72
0, 'max_length': 256, 'batch_sizes': [240, 180, 180, 180, 144, 144, 144, 120, 120, 120, 90, 90, 90, 90, 80, 72, 72, 60,
60, 48, 48, 48, 40, 40, 36, 30, 30, 24, 24, 20, 20, 18, 18, 16, 15, 12, 12, 10, 10, 9, 8, 8], 'shuffle_queue_size': 270}
Traceback (most recent call last):
  File "/usr/local/bin/t2t-trainer", line 87, in <module>
    tf.app.run()
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/app.py", line 48, in run
    _sys.exit(main(_sys.argv[:1] + flags_passthrough))
  File "/usr/local/bin/t2t-trainer", line 83, in main
    schedule=FLAGS.schedule)
  File "/usr/local/lib/python2.7/dist-packages/tensor2tensor/utils/trainer_utils.py", line 301, in run
    exp.train_and_evaluate()
    self._map_func.add_to_graph(ops.get_default_graph())
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/function.py", line 619, in add_to_graph
    self._create_definition_if_needed()
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/data/python/framework/function.py", line 167, in _create_definition_if_needed
    outputs = self._func(*inputs)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/data/python/ops/dataset_ops.py", line 1427, in tf_map_func
    flattened_ret = [ops.convert_to_tensor(t) for t in nest.flatten(ret)]
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 676, in convert_to_tensor
    as_ref=False)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 741, in internal_convert_to_tensor
    ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/constant_op.py", line 113, in _constant_tensor_conversion_function
    return constant(v, dtype=dtype, name=name)
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/constant_op.py", line 102, in constant
    tensor_util.make_tensor_proto(value, dtype=dtype, shape=shape, verify_shape=verify_shape))
  File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/tensor_util.py", line 462, in make_tensor_proto
    "supported type." % (type(values), values))
TypeError: Failed to convert object of type <type 'dict'> to Tensor. Contents: {'inputs': <tf.Tensor 'SparseToDense:0' shape=(?,) dtype=int64>, 'targets': <tf.Tensor 'SparseToDense_1:0' shape=(?,) dtype=int64>}. Consider casting elements to a supported type.

same here - it seems more a problem where a python dict (name: tensor) is provided instead of a tensor...
(not sure it is a problem with my registered problem though - but it was working well with version 1.1.9)

same problem with 1.2.1.  Another problem occurs with version 1.1.9.

Have you tried upgrading to Tensorflow 1.3?

I changed to another stable t2t version, now it works well with 1.2.1

@mtu  :
by 'I changed to another stable t2t' you mean you just updated tensor2tensor code?

@mirkobronzi changed to an earlier version,not the latest one

Is this resolved in T2T 1.2.2 with TF 1.3?

I see the error with TF 1.3 built on python 2.7
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/tensor_util.py", line 462, in make_tensor_proto
"supported type." % (type(values), values))
TypeError: Failed to convert object of type <type 'dict'> to Tensor. Contents: {'inputs': <tf.Tensor 'SparseToDense:0' shape=(?,) dtype=int64>, 'targets': <tf.Tensor 'SparseToDense_1:0' shape=(?,) dtype=int64>}. Consider casting elements to a supported type.
after invoking
levinth@c2k-144-linux:~/tensor2tensor$ t2t-trainer \

--data_dir=$DATA_DIR
--problems=$PROBLEM
--model=$MODEL
--hparams_set=$HPARAMS
--output_dir=$TRAIN_DIR

this worked fine
t2t-datagen --data_dir=$DATA_DIR --tmp_dir=$TMP_DIR --problem=$PROBLEM

I get a different error:
t2t-trainer   --generate_data   --data_dir=~/t2t_data   --problems=translate_ende_wmt32k   --model=transformer   --hparams_set=transformer_base_single_gpu   --output_dir=~/t2t_train/base
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcublas.so locally
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcudnn.so locally
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcufft.so locally
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcuda.so.1 locally
I tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcurand.so locally
Traceback (most recent call last):
File "/home/dan/.local/bin/t2t-trainer", line 38, in
from tensor2tensor.utils import trainer_utils
File "/home/dan/.local/lib/python2.7/site-packages/tensor2tensor/utils/trainer_utils.py", line 27, in
from tensor2tensor.data_generators import all_problems  # pylint: disable=unused-import
File "/home/dan/.local/lib/python2.7/site-packages/tensor2tensor/data_generators/all_problems.py", line 22, in
from tensor2tensor.data_generators import algorithmic
File "/home/dan/.local/lib/python2.7/site-packages/tensor2tensor/data_generators/algorithmic.py", line 28, in
from tensor2tensor.data_generators import problem
File "/home/dan/.local/lib/python2.7/site-packages/tensor2tensor/data_generators/problem.py", line 31, in
from tensor2tensor.utils import metrics
File "/home/dan/.local/lib/python2.7/site-packages/tensor2tensor/utils/metrics.py", line 23, in
from tensor2tensor.layers import common_layers
File "/home/dan/.local/lib/python2.7/site-packages/tensor2tensor/layers/common_layers.py", line 30, in
from tensor2tensor.utils import expert_utils as eu
File "/home/dan/.local/lib/python2.7/site-packages/tensor2tensor/utils/expert_utils.py", line 398, in
initializer=tf.zeros_initializer(),
TypeError: zeros_initializer() takes at least 1 argument (0 given)

I cannot reproduce this. The Travis CI tests demonstrate that the commands you seem to be running work fine. Please make sure you're running TensorFlow 1.3 and the latest version of Tensor2Tensor.
Please provide the command line you use (without env vars - use actual values)


Switching audio track in Safari stops and stalls playback for DASH streams

Have you read the FAQ and checked for duplicate open issues?
Yes
What version of Shaka Player are you using?
v2.5.8 in production, v3.0.9 while checking if the issue was resolved in a later version
Can you reproduce the issue with our latest release version?
Yes
Can you reproduce the issue with the latest code from master?
Yes
Are you using the demo app or your own custom app?
Custom.
If custom app, can you reproduce the issue using our demo app?
Yes
What browser and OS are you using?
Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_6) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/14.0.2 Safari/605.1.15
We see the same behavior on Safari on iPad.
For embedded devices (smart TVs, etc.), what model and firmware version are you using?
What are the manifest and license server URIs?

https://www.dropbox.com/s/148qbja0yy43x1r/180124b4c8175216ae0e3bdc.zip?dl=0
https://shakadebug.s3.eu-central-1.amazonaws.com/dash/stream.mpd
What configuration are you using?  What is the output of player.getConfiguration()?

{
    "drm": {
        "retryParameters": {
            "maxAttempts": 2,
            "baseDelay": 1000,
            "backoffFactor": 2,
            "fuzzFactor": 0.5,
            "timeout": 0
        },
        "servers": {},
        "clearKeys": {},
        "advanced": {},
        "delayLicenseRequestUntilPlayed": false,
        "logLicenseExchange": false,
        "updateExpirationTime": 1
    },
    "manifest": {
        "retryParameters": {
            "maxAttempts": 2,
            "baseDelay": 1000,
            "backoffFactor": 2,
            "fuzzFactor": 0.5,
            "timeout": 0
        },
        "availabilityWindowOverride": null,
        "disableAudio": false,
        "disableVideo": false,
        "disableText": false,
        "defaultPresentationDelay": 0,
        "dash": {
            "clockSyncUri": "",
            "ignoreDrmInfo": false,
            "xlinkFailGracefully": false,
            "ignoreMinBufferTime": false,
            "autoCorrectDrift": true,
            "initialSegmentLimit": 1000,
            "ignoreSuggestedPresentationDelay": false,
            "ignoreEmptyAdaptationSet": false
        },
        "hls": {
            "ignoreTextStreamFailures": false,
            "useFullSegmentsForStartTime": false
        }
    },
    "streaming": {
        "retryParameters": {
            "maxAttempts": 2,
            "baseDelay": 1000,
            "backoffFactor": 2,
            "fuzzFactor": 0.5,
            "timeout": 0
        },
        "rebufferingGoal": 2,
        "bufferingGoal": 10,
        "bufferBehind": 30,
        "ignoreTextStreamFailures": false,
        "alwaysStreamText": false,
        "startAtSegmentBoundary": false,
        "smallGapLimit": 0.5,
        "jumpLargeGaps": false,
        "durationBackoff": 1,
        "forceTransmuxTS": false,
        "safeSeekOffset": 5,
        "stallEnabled": true,
        "stallThreshold": 1,
        "stallSkip": 0.1,
        "useNativeHlsOnSafari": true,
        "inaccurateManifestTolerance": 2
    },
    "offline": {
        "usePersistentLicense": true
    },
    "abr": {
        "enabled": true,
        "defaultBandwidthEstimate": 10000000,
        "switchInterval": 8,
        "bandwidthUpgradeTarget": 0.85,
        "bandwidthDowngradeTarget": 0.95,
        "restrictions": {
            "minWidth": 0,
            "maxWidth": null,
            "minHeight": 0,
            "maxHeight": null,
            "minPixels": 0,
            "maxPixels": null,
            "minFrameRate": 0,
            "maxFrameRate": null,
            "minBandwidth": 0,
            "maxBandwidth": null
        }
    },
    "preferredAudioLanguage": "en",
    "preferredTextLanguage": "",
    "preferredVariantRole": "",
    "preferredTextRole": "",
    "preferredAudioChannelCount": 2,
    "restrictions": {
        "minWidth": 0,
        "maxWidth": null,
        "minHeight": 0,
        "maxHeight": null,
        "minPixels": 0,
        "maxPixels": null,
        "minFrameRate": 0,
        "maxFrameRate": null,
        "minBandwidth": 0,
        "maxBandwidth": null
    },
    "playRangeStart": 0,
    "playRangeEnd": null
}

What did you do?

Playback the stream, then switch to a different audio track.
What did you expect to happen?
The playback to continue. The same manifest and player configuration works on Chrome and Firefox.
What actually happened?

The playback stopped and is stuck buffering/seeking:
[Log] Found variant with audio and video content, so filtering out audio-only content. (application.js, line 105795)
[Log] codecs – "avc1-mp4a" – "avg bandwidth" – 2200054.4 (application.js, line 105479)
[Log] init: completed initial Stream setup (application.js, line 105608)
[Log] Calling switch_(), bandwidth=324140 kbps (application.js, line 105505)
[Log] switch_ (application.js, line 105864)
[Log] (audio:11) – "buffered to end of presentation" (application.js, line 105637)
[Log] (video:1) – "buffered to end of presentation" (application.js, line 105637)
[Log] switch: Stream (video:1) already active (application.js, line 105618)
[Log] switch: switching to Stream (audio:5) (application.js, line 105617)
[Log] (audio:5) – "clearing buffer" (application.js, line 105665)
[Log] (audio:5) – "cleared buffer" (application.js, line 105666)
[Log] (all): seeked: buffered seek: presentationTime=26.070636705 (application.js, line 105624)
[Log] (audio:5) – "buffered to end of presentation" (application.js, line 105637)
[Log] Stall detected at 26.0706367 for 1.003999948501587 seconds. (application.js, line 105577)
[Log] Seeking forward 0.1 seconds to break stall. (application.js, line 105577)
[Log] (all): seeked: buffered seek: presentationTime=26.170636700000003 (application.js, line 105624)
[Log] Stall detected at 26.1706367 for 1.001000165939331 seconds. (application.js, line 105577)
[Log] Seeking forward 0.1 seconds to break stall. (application.js, line 105577)
[Log] (all): seeked: buffered seek: presentationTime=26.2706367 (application.js, line 105624)

We are getting the same results when using a HLS stream. Playback works until you switch to a different audio track. https://www.dropbox.com/s/f604y1rer3dussn/hls.zip?dl=0

Hi @dsander
Ideally, we require a hosted manifest link and media content for a repro.
Do you think you can provide that? If you have privacy concerns, you can send the info to<EMAIL_ADDRESS>You can check if the issue reproduces with the latest master by trying it on our nightly demo page (under the "CUSTOM CONTENT" tab).

Hi @ismena,
sharing wasn't the problem CORS is the annoying part 😄
DASH: https://shakadebug.s3.eu-central-1.amazonaws.com/dash/stream.mpd
HLS: https://shakadebug.s3.eu-central-1.amazonaws.com/hls/master.m3u8 (we don't normally work with HLS, I am also getting errors on Chrome, but even without audio playback Safari has the same behavior of stopping playback when switching the audio track)
I didn't see any difference with the nightly player.

Confirmed.  It also seems to take a long time to start, which we should look into.  It may be a platform bug since we have content buffered, but the video refuses to move.

I reproduced the same problem on some models of WebOS 3.5, but not all ...

I ran into this issue also.  I was hunting around to find a duplicate before I created a new bug, and it appears I have found one.  In my particular test I tested on safari and switching audio tracks fails, but tried in edge on win10 and it works.  I chose these two browsers because the video is HEVC and won't work anywhere else, but if you want another test asset that duplicates the issue (and one with lots of test audio tracks): https://content.uplynk.com/2e881c1059bd47cfbd2844c40ec9931b.mpd?sstart=5

Can you test with v4.3.4? Thanks!

Sadly it still does not work on macOS 13.1 with Safari Version 16.2 (186<IP_ADDRESS>.5) using v4.3.4 (uncompiled) from https://shaka-player-demo.appspot.com.
Chrome has no issues switching the audio tracks in the DASH stream https://shakadebug.s3.eu-central-1.amazonaws.com/dash/stream.mpd

The problem still occurs in Safari 17 (in my case it is reproducible 50% of the time)

Sorry, I can not test this any more because we switched from DASH to HLS proxies. With HLS playback switching the audio tracks isn't an issue in Safari.


Missing links and dead sites

I looked through the current webring links and found the following issues:

theiceshelf.com (dead site) - I can't find the name of the original owner so please tag them if you know them
@simbolo (dead site)
@cblgh (missing webring link)
@jda0 (missing webring link)

Please update your sites as soon as possible. I will temporarily comment out the dead sites just to keep the webring working. Just submit a pull request when it's ready. Thank you :)

@joshavanier not sure why my site is greyed out, but cblgh.org works and links correctly

@cblgh Oh that's just the CSS styling for visited links. Where's the webring link on your site?

ahhh, i completely missed the part where that was a requirement. i'll fix it today :)

Le 4 févr. 2019 à 10:57, ジョシュ<EMAIL_ADDRESS>a écrit :
I looked through the current webring links and found the following issues:
theiceshelf.com (dead site) - I can't find the name of the original owner so please tag them if you know them
@simbolo (dead site)
@cblgh (missing webring link)
@jda0 (missing webring link)
Please update your sites as soon as possible. I will temporarily comment out the dead sites just to keep the webring working. Just submit a pull request when it's ready. Thank you :)
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub, or mute the thread.

@joshavanier the webrink link is under networks on the far left. The link is clearer on the redesigned version I’ll be pushing today.


Auto old part taxation

Background
Implementation in electronic invoice complex, as no comparable case on TypeCode level
Objective
'Worldwide data exchange desired and mapping of taxes of other countries necessary'
Challenges
'Tax and invoice compliant mapping of two tax rates'
Open Questions
'Code list designed very restrictively. Opening of the code list required or new code to be included'
Approaches
'Workaround not permissible according to BMF'
Further Procedure
'CoSIT: New TaxCategoryCode in preparation. Change request at UNECE level. Code usable for 4) and 5) Xrechnung: Implementation within the extension --> Implementation in ZUGFeRD EXTENDED (?)
Update: Workaround published in XRechnung FAQ'

Seems to be Margin Scheme; See #4


ComfyUI + Flux AI training(ai-toolkit)

Credits: https://github.com/ostris/ai-toolkit, https://github.com/comfyanonymous/ComfyUI
@dusty-nv I've updated Pytorch and their libraries, and opencv and bitsandbytes required for FLUX.
Now pytorch has heterogeneus memory with +12.2 so you can use swap

finally @dusty-nv  ai-toolkit is working

Thank you good sir @johnnynunez!  even added CUDA 12.6 🤣
I added some comments to your PR about changing the default versions of cuDNN and OpenCV.  After resolving those, should be g2g to merge 👍


Clicking Virtual Console sound buttons too fast breaks the program

Describe the bug
If you click a virtual console sound button then quickly click it again, the button you click beomes highlighted and you cannot unclick it. The sound you activated will continue playing and you cannot stop it. If you press any other buttons, they will highlight, but nothing will be triggered. If you attempt to return to design mode, the software will freeze up. To fix it you have to close and relaunch the software.
From what I can tell, the conflict happens because you're clicking the button again before the sound actually starts playing.
To Reproduce

add a sound function and a scene or two
assign everything you created to buttons
click the sound button then quickly click it again (before the sound starts playing)

Expected behavior
The software should remain stable.
Desktop (please complete the following information):

OS: Windows 11
QLC+ Version 4.12.8 (It also occurse in 4.12.7)
hardware setup: Acer Laptop with a DMX USB input

Hey, I'm afraid you want things QLC+ is not designed for.
In general QLC+ is not primarily an audio player. For that, I suggest to use dedicated softwares.
Sorry but I won't pick this up.

Ah, no worries. I think I found a workaround anyway.
On Sat, Oct 28, 2023 at 5:20 AM Massimo Callegari @.***>
wrote:

Closed #1470 https://github.com/mcallegari/qlcplus/issues/1470 as
completed.
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Use mina_version_compiled in test_executive

Problem: test_executive uses wrong version of mina_version virtual package, for that reason [UNKNOWN] was used in generation of testnet id instead of short commit id.
Explain how you tested your changes:

[ ] Confirm successful execution of intg tests

Checklist:

[x] Dependency versions are unchanged

Notify Velocity team if dependencies must change in CI

[ ] Modified the current draft of release notes with details on what is completed or incomplete within this project
[x] Document code purpose, how to use it

Mention expected invariants, implicit constraints

[x] Tests were added for the new behavior

Document test purpose, significance of failures
Test names should reflect their purpose

[x] All tests pass (CI will check this if you didn't)
[x] Serialized types are in stable-versioned modules
[x] Does this close issues? None

To check whether some other executables need to have a correct mina version used I used the following two commands (on georgeee/granular-nix):
nix build --show-trace --verbose .?submodules=1#info.deps --out-link deps.json

However by analyzing usages of Mina_version module, most of these executables seem to have inherited usage of mina_version from its usage in:

Logging metadata, in internal_trace, error_json, transaction_snark and blockchain_snark
Status/error reporting service (node_error_service, node_status_service)
Part of node status (mina_lib)
Graphql's version endpoint

Apps generate_keypair and validate_keypair are two notable exceptions, so I'm committing a change for them too.
Also committing changes to signer as it's user-facing application and logging with a version is important.
For all of the other apps my reasoning is that it's alright to keep them "unversioned" with an eye to remove the implicit dependency in future.

Created a reversion PR instead: #15863


Add gas canisters

Add gas canister to refill the air horn, The gas canister has limited use.

This feature is related to #2.

The integration of a gas canister aimed to solve the problem of the magazine of the Air Horn, for the moment the Air Horn can have a single use


Update Dockerfile - #1542

What was the problem?
This PR resolves #1542
How was it solved?
Update the existing dockerfiles
How was it tested?
By running existing test cases. No new testcases failed after adding the changes.

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.

can you sign the commit @vardan10 ? you need to configure the GPG and git commit -S -m while committing

Done.


Madison/new form queries

We should add python types to convert the results of the new queries back into. And also add unit tests. See for example: https://github.com/IndicoDataSolutions/indico-client-python/blob/master/indico/queries/datasets.py#L53


Long filename, player window is too narrow to see entire filename

This makes it impossible to select which files on a playlist I want to play.
See attached jpg

Thanks!

+1 lets keep track of this on #13


Update to v0.2.2

Comments on pull requests will not trigger Registrator, as it is disabled. Please try commenting on a commit or issue.


RenderBox was not laid out: RenderRepaintBoundary#31887 relayoutBoundary=up1 NEEDS-PAINT

Steps to Reproduce

Run flutter create bug.
Update the files as follows: ...
...

Expected results:
Actual results:

Logs

Hi @marqueetest
Please reply original issue with more details
Closing as duplicate of https://github.com/flutter/flutter/issues/84429


[Prankcast] Tags are no longer a JSON list

IMPORTANT: PRs without the template will be CLOSED
Description of your pull request and other information

At some point in the last week the tags field has changed from a JSON list to a string. This caused the extractor to fail:

ERROR: [PrankCast] 1380: 1380: Failed to parse JSON (caused by JSONDecodeError("Expecting value in '': line 1 column 1 (char 0)")); please report this issue on  https://github.com/yt-dlp/yt-dlp/issues?q= , filling out the appropriate issue template. Confirm you are on the latest version using  yt-dlp -U

I've changed the tests to reflect this change and updated the extractor to no longer try to parse the string into JSON.
I'm not sure if it would be better to try and "convert" the string into a list manually (replacing commas with the proper formatting for a list) or just leave it as it is. If converting it to a list would be preferred let me know and I'll change it.
Fixes #
Template

Before submitting a pull request make sure you have:

[X] At least skimmed through contributing guidelines including yt-dlp coding conventions
[X] Searched the bugtracker for similar pull requests
[X] Checked the code with flake8 and ran relevant tests

In order to be accepted and merged into yt-dlp each piece of code must be in public domain or released under Unlicense. Check all of the following options that apply:

[X] I am the original author of this code and I am willing to release it under Unlicense
[ ] I am not the original author of this code but it is in public domain or released under Unlicense (provide reliable evidence)

What is the purpose of your pull request?

[X] Fix or improvement to an extractor (Make sure to add/update tests)
[ ] New extractor (Piracy websites will not be accepted)
[ ] Core bug fix/improvement
[ ] New feature (It is strongly recommended to open an issue first)

Done, I've changed it to a try_call


[Unsafe][WIP] Using memmap'd data directly for CPU tensor storage, instead of copying.

Blocking questions:

Is it safe to std::mem::forget the tensor? Is that all we need to do? What about the other fields of tensor?
Is the Vec::from_raw_parts_mut usage safe?

Yeah I'm thinking to make this opt-in, because you're exactly right that you'd be paying for disk reads every forward call. Perhaps we can add something like --mmap-limit-for-model which defaults to 0

@coreylowman eventually the forward pass would warm up the cache as needed. I am trying to think of a use case where mmap() is superior here. The use of mmap() or not, depends on the holistic system. Either way, after the cache is warmed up, mmap() won't have much impact.
The advantage in my opinion is to mmap(), and then not lazily load, but force load the stuff that matters. That way you get instant memory mapping of the model, but can load the important stuff as needed, reducing what the user sees as "load-screen" lag.


Setting ClientId dynamically at runtime

Hi All,
Is there any way to dynamically set the ClientId at runtime for openId connect?
The reason for this is to support different client ids for each tenant in my app but using the same instance and single db for all the tenants. I tried to change the clientId in the event handlers like: OnRedirectToIdentityProvider but it doesn't work as the token validation process seems to take the clientId from the options at the initial config always.
I also tried to use OpenIdConnectPostConfigureOptions, but again didn't work.
Thanks for your support.

I'm developing a Spring boot application where the authentication server is IdentityServer4. I have cloned this code and ran the identity server in my Linux. I tried to get access token via client credentials grant type and for the sample client id like "m2m" or "client" it always throws invalid client. As I'm very new to Dot net framework couldn't find out how to load sample clients and users for setting up a development environment. If you could share some info, it would be of great help.
Thanks in advance


Solution for https://github.com/rkokkelk/homey-wear/issues/1

Only add supported devices to the list

Should commit to Develop Branch, not Master, sorry

Hi thank you for the PR. But it is fine to make the PR for the master branch, develop is currently in a none stable situation and I would prefer to release this bugfix as soon as possible.
However in your PR you put 2 commits, the second one is not required for the bugfix and which changes a lot of variables, which can have an unspecified impact on the app and would require a lot more testing. Could you therefore please remove this commit from this PR, and maybe create a separate PR for those issues.
In your fix you specified just to skip all devices which do not contain the required capabilities. Although this is appropriated, I'm thinking this might result in confusion in the users to why certain favorite devices are not listed in the app. I prefer a solution which shows all devices but which show a pop-up indicating this device is not supported or a greyed out device.


Bug report: Closing informational overlay removes input data

Describe the bug
When loading data from a file through the "Open file as input" button a informational overlay box gets displayed:

Closing this overlay removes also the input data that was just imported.
To Reproduce
Steps to reproduce the behaviour or a link to the recipe / input used to cause the bug:

Go to https://gchq.github.io/CyberChef/
Click on 'Open file as input'
Chose any local file, size is not relevant
Close the informational overlay by pressing the X in the top right corner
Observe the now empty input and output text boxes

Expected behaviour
I expected that the loaded input data stays in the input text box after closing the overlay box.
Desktop (if relevant, please complete the following information):

OS: macOS
Browser: Chrome 81
CyberChef version: 9.20.3

Hi @roman-mueller, this is intended behaviour. We don't actually load the file data fully into the input box since the file could be huge. We display a preview of it behind the file overlay for purely aesthetic reasons, but it is only loaded fully into memory. Input files are not intended to be editable, so therefore closing the file overlay would have no purpose. The close button is there to clear the file from the input.


Current handlebars dependency version is vulnerable to prototype pollution

Overview
Versions of handlebars prior to 4.0.14 are vulnerable to Prototype Pollution. Templates may alter an Objects' prototype, thus allowing an attacker to execute arbitrary code on the server.
Remediation
For handlebars 4.1.x upgrade to 4.1.2 or later. For handlebars 4.0.x upgrade to 4.0.14 or later.
https://www.npmjs.com/advisories/755

This will be fixed in the next release, the fix has been merged to master in #1019


deployment: add a homebrew formula

This is now available with v0.4.0:
https://github.com/hbagdi/homebrew-deck
🎉


All Feature Classes, Feature Datasets and GDBs Need Metadata (Pro)

From @conklinbd on May 29, 2014 21:38
In Pro all Feature Classes, Feature Datasets and GDBs need item metadata. We need to test to determine if this makes the GDB incompatible with 10.X clients before we completely implement.

Copied from original issue: ArcGIS/military-features-pro-data_RETIRED_DONT_USE#10

From @csmoore on October 29, 2014 15:2
I'm not able to view GDB metadata on the project pane with recent builds (I am using 1566 now but did see it in last week's build also) - can anyone repro with a build from the last week?

@csmoore and @abouffard - I can draft some text for the metadata.

Note: Editing GDB Meta data in Pro does not appear to affect compatibility with 10.X (shows up in "Item Description" there)

I do notice that when I add the feature class with metadata in Pro, the metadata doesn't seem to be added/transferred to the layer's metadata, so that might be a bug/oversight.

Here is a sample of the updated/added feature class item description (ArcMap 10.x) / metadata (Pro).

Looks good to me.

:+1:

I like the thumbnails, that's a nice touch.
I see that the GDB and the feature dataset don't have Descriptions, just Summaries. Seems like they could have both.
Also, the Summary text:
Military Features Military Overlay is a template for creating a geodatabase of military features for Planning, Operations, and Intelligence use. It contains ArcGIS feature templates that let you quickly create Military Features based on MIL-STD-2525D.
seems slightly off - at least currently, the GDB contains feature classes for use in creating the various MIL-STD-2525D features, but it doesn't contain feature templates

I'll correct those 2 issues & recommit (I am actually never sure how the summary/description differ or why they are 2 separate metadata fields)

Feedback addressed in https://github.com/csmoore/military-features-data/commit/1fa4acf5ae73ab3fb7c61cd9fc81b21a8001b76f

Verified Fixed.Pull #77 merged.


use slice predicates and add missing explicit triggers to pkg/addr

Doing this now will require a medium-sized refactor which is not the best idea at the moment. When we do this though, we should also have a way to retrieve access to a single cell of a slice to avoid so many outline blocks


Connection unrecoverables after RabbitMQ server restart

Hi,
we restarted our rabbitmq server for a maintenance and logstash clients started to write in the log file this string:
[2016-12-30T13:42:32,108][ERROR][logstash.outputs.rabbitmq] Error while publishing. Will retry. {:message=>"#method<connection.close>(reply-code=320, reply-text=CONNECTION_FORCED - broker forced connection closure with reason 'shutdown', class-id=0, method-id=0)", :exception=>MarchHare::ChannelAlreadyClosed, :backtrace=>["/usr/share/logstash/vendor/bundle/jruby/1.9/gems/march_hare-2.20.0-java/lib/march_hare/exceptions.rb:121:in `convert_and_reraise'", "/usr/share/logstash/vendor/bundle/jruby/1.9/gems/march_hare-2.20.0-java/lib/march_hare/channel.rb:980:in `converting_rjc_exceptions_to_ruby'", "/usr/share/logstash/vendor/bundle/jruby/1.9/gems/march_hare-2.20.0-java/lib/march_hare/channel.rb:978:in `converting_rjc_exceptions_to_ruby'", "/usr/share/logstash/vendor/bundle/jruby/1.9/gems/march_hare-2.20.0-java/lib/march_hare/channel.rb:606:in `basic_publish'", "/usr/share/logstash/vendor/bundle/jruby/1.9/gems/march_hare-2.20.0-java/lib/march_hare/exchange.rb:77:in `publish'", "/usr/share/logstash/vendor/bundle/jruby/1.9/gems/logstash-output-rabbitmq-4.0.4-java/lib/logstash/outputs/rabbitmq.rb:54:in `publish'", "org/jruby/RubyProc.java:281:in `call'", "/usr/share/logstash/vendor/bundle/jruby/1.9/gems/logstash-codec-json-3.0.2/lib/logstash/codecs/json.rb:42:in `encode'", "/usr/share/logstash/vendor/bundle/jruby/1.9/gems/logstash-output-rabbitmq-4.0.4-java/lib/logstash/outputs/rabbitmq.rb:47:in `receive'", "/usr/share/logstash/logstash-core/lib/logstash/outputs/base.rb:92:in `multi_receive'", "org/jruby/RubyArray.java:1613:in `each'", "/usr/share/logstash/logstash-core/lib/logstash/outputs/base.rb:92:in `multi_receive'", "/usr/share/logstash/logstash-core/lib/logstash/output_delegator_strategies/legacy.rb:19:in `multi_receive'", "/usr/share/logstash/logstash-core/lib/logstash/output_delegator.rb:42:in `multi_receive'", "/usr/share/logstash/logstash-core/lib/logstash/pipeline.rb:297:in `output_batch'", "org/jruby/RubyHash.java:1342:in `each'", "/usr/share/logstash/logstash-core/lib/logstash/pipeline.rb:296:in `output_batch'", "/usr/share/logstash/logstash-core/lib/logstash/pipeline.rb:252:in `worker_loop'", "/usr/share/logstash/logstash-core/lib/logstash/pipeline.rb:225:in `start_workers'"]}
The solution was restart the logstash service.
We use:

Ubuntu 14.04
Logstash 5.1.1 (package from apt)
logstash-output-rabbitmq 4.0.4

The logstash configuration is set with the heartbeat parameter, like bottom:
    rabbitmq {
        exchange => "logstash"
        exchange_type => "topic"
        host => "XXX.XXX.XXX.XXX"
        port => "XXXX"
        user => "user"
        password => "password"
        key => ""
        ssl => true
        heartbeat => "5"
    }

Can you help us please?

Another thing that I observed was the name of directory of march_hare.
I understood about this that it is the client used from logstash-output-rabbitmq to connect to rabbitmq.
On the servers with logstash that they are not able to reconnect the plugin seems has name march_hare-2.20.0-java, on a server windows 2012 R2 that was able to reconnect was called march_hare-2.15.0-java.
I don't know if this can help you.

Hi,
can anyone help us please?

@kavat it looks like you shutdown your rabbitmq cluster with rabbitmqctl. Is that correct? Did the error message ever go away?

Hi @andrewvc ,
I restarted my RabbitMQ with reboot command.
I continued see the error until I restarted logstash service.
Why has not logstash client retried the connection and it has entered into this error log infinite loop?

Hi @andrewvc,
In the next days we have to restart out rabbitmq server and we are worried about this.
Have my informations helped you in your analysis? Have you got any news?
Sorry but we need a urgent fix or workaround.

Any news?

@kavat AFAIK rabbitmqctl has no reboot command, you can stop and start it. I assume you're using an init script?
At any rate, I just tested it with a manual start and a rabbitmqctl stop and everything worked great.
The logstash config I used was: bin/logstash -e "input { stdin {} } output { rabbitmq { exchange => foobar exchange_type => fanout host => localhost} }"
I'll need a detailed reproducible test case to go any further with this.
It might even make sense to upload a virtualbox VM demonstrating this error.
Given that others haven't reported this error I am leaning toward this being an environment issue. RabbitMQ is very finicky to setup and there is a large amount of variation between environments.

I've reboot the entire linux server rabbitmq, with the command via ssh reboot.
The server went down and the client started to write in log
[2016-12-30T13:42:32,108][ERROR][logstash.outputs.rabbitmq] Error while publishing. Will retry. {:message=>"#method<connection.close>(reply-code=320, reply-text=CONNECTION_FORCED - broker forced connection closure with reason 'shutdown', class-id=0, method-id=0)", :exception=>MarchHare::ChannelAlreadyClosed, :backtrace=>["/usr/share/logstash/vendor/bundle/jruby/1.9/gems/march_hare-2.20.0-java/lib/march_hare/exceptions.rb:121:in convert_and_reraise'", "/usr/share/logstash/vendor/bundle/jruby/1.9/gems/march_hare-2.20.0-java/lib/march_hare/channel.rb:980:inconverting_rjc_exceptions_to_ruby'", "/usr/share/logstash/vendor/bundle/jruby/1.9/gems/march_hare-2.20.0-java/lib/march_hare/channel.rb:978:in converting_rjc_exceptions_to_ruby'", "/usr/share/logstash/vendor/bundle/jruby/1.9/gems/march_hare-2.20.0-java/lib/march_hare/channel.rb:606:inbasic_publish'", "/usr/share/logstash/vendor/bundle/jruby/1.9/gems/march_hare-2.20.0-java/lib/march_hare/exchange.rb:77:in publish'", "/usr/share/logstash/vendor/bundle/jruby/1.9/gems/logstash-output-rabbitmq-4.0.4-java/lib/logstash/outputs/rabbitmq.rb:54:inpublish'", "org/jruby/RubyProc.java:281:in call'", "/usr/share/logstash/vendor/bundle/jruby/1.9/gems/logstash-codec-json-3.0.2/lib/logstash/codecs/json.rb:42:inencode'", "/usr/share/logstash/vendor/bundle/jruby/1.9/gems/logstash-output-rabbitmq-4.0.4-java/lib/logstash/outputs/rabbitmq.rb:47:in receive'", "/usr/share/logstash/logstash-core/lib/logstash/outputs/base.rb:92:inmulti_receive'", "org/jruby/RubyArray.java:1613:in each'", "/usr/share/logstash/logstash-core/lib/logstash/outputs/base.rb:92:inmulti_receive'", "/usr/share/logstash/logstash-core/lib/logstash/output_delegator_strategies/legacy.rb:19:in multi_receive'", "/usr/share/logstash/logstash-core/lib/logstash/output_delegator.rb:42:inmulti_receive'", "/usr/share/logstash/logstash-core/lib/logstash/pipeline.rb:297:in output_batch'", "org/jruby/RubyHash.java:1342:ineach'", "/usr/share/logstash/logstash-core/lib/logstash/pipeline.rb:296:in output_batch'", "/usr/share/logstash/logstash-core/lib/logstash/pipeline.rb:252:inworker_loop'", "/usr/share/logstash/logstash-core/lib/logstash/pipeline.rb:225:in `start_workers'"]}
Also when the server recover itself the log continue to append the string before.
Is it clear now?

@kavat I already tried rebooting the server, didn't get the same error. What you've submitted is not a sufficient test case.
If you can create a VM image that demonstrates this effect I'd be glad to take a look.

I'am having the same error logstash can't recover rabbitmq connection after restarting rabbitmq-server
RabbitMQ connection was closed! {XXXX} :automatic_recovery=>true, :cause=>com.rabbitmq.client.ShutdownSignalException: connection error; protocol method: #method<connection.close>(reply-code=320, reply-text=CONNECTION_FORCED - broker forced connection closure with reason 'shutdown', class-id=0, method-id=0)}

Today i've encountered the same issue, is there any workaround?


refactor: bulk issuance template list response changes

What

Removed logic to check schema already exists for W3C
Changed template list response
Added validation for empty attribute

Why are we removing logic for checking if schema exists for w3c?


Table column dynamic icon text

I would like to be able to add dynamic text to the icon inside the table.

With the current implementation I can only add static text.
😯 Problem to Solve
It would help my development for the move assets feature as it requires a column in which we need to display a dynamic icon each having a different text depending on results.
💁 Proposed Solution
One solution I see would be to make the mapped property available inside the template, this would help development as we could simply define any custom template we need.
Another one I notice would be to accept different keys for icon and text.
I am sure there are some other approaches as well. I am looking forward to a solution.
📋 Tasks

[ ]

@ni-saradei we brainstormed ideas for this with the Nimble team and came up with some quesitons.

Is anything stopping you from creating a nimble-mapping-icon element for each possible string? Some of those elements could map to the same icon but different strings. This is possible today without any new additions to Nimble. This approach would also work well for localization as the app could leverage its infrastructure for translating those strings whereas populating them from the backend via a table record field might be harder to localize.

We're also curious about the nature of these strings. Are they critical information or just background info? How long will the strings typically be? If they are important or lengthy we might want to consider moving the information out of the tooltip and instead displaying it in a separate text column or creating a new column type that shows an icon and text.

@ni-saradei we brainstormed ideas for this with the Nimble team and came up with some quesitons.

Is anything stopping you from creating a nimble-mapping-icon element for each possible string? Some of those elements could map to the same icon but different strings. This is possible today without any new additions to Nimble. This approach would also work well for localization as the app could leverage its infrastructure for translating those strings whereas populating them from the backend via a table record field might be harder to localize.
We're also curious about the nature of these strings. Are they critical information or just background info? How long will the strings typically be? If they are important or lengthy we might want to consider moving the information out of the tooltip and instead displaying it in a separate text column or creating a new column type that shows an icon and text.

Thank you for the suggestion, I created a nimble-mapping-icon for each case. I didn't want to do this initially as we would need to maintain the messages/codes in two places.


Improve feature-card-9.html

Need to improve this component on \feature card\src\feature-card-9.html
Improvements required :
Increase icon size and make it blue
Any reference image?

Any external reference?
You can checkout this one for better understanding.

I think this is compeleted


[Users] Delete a Scheduler

Need to review existing code to make sure that the param filtering matches the API docs
https://marketplace.zoom.us/docs/api-reference/zoom-api/users/userschedulerdelete

Implemented here: https://github.com/kyleboe/zoom_rb/blob/main/lib/zoom/actions/user.rb#L42


Create Navbar

for easy accessibility for clients using app we should include:

home
my workouts
my recipes
create a profile icon that when the client clicks on this it will take them to a "my profile" page where it shows them all the information they originally inputted.

NavBar at top of page


fine tuning

Hi,
is it possible to fine-tune the model on a custom dataset?

If you want to fine tune the model on a different dataset, you can do that without any coding by naming the model checkpoints accordingly.

Copy the trained model to
MODEL_DIR/models/model.ckpt-1.*
Copy the config file and change the model_dir to MODEL_DIR, the starting_iter to 1 in the config file, and the data entries to point to your new data.

There are other ways to do this in code using the restore_from_checkpoint method, if you need finer grained control of what is restored from the checkpoint.

I am getting below error
**INFO:niftynet: stopping sampling threads
Traceback (most recent call last):
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1334, in _do_call
return fn(*args)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1319, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1407, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Assign requires shapes of both tensors to match. lhs shape= [3,3,61,256] rhs shape= [3,3,3,61,9]
[[{{node save/Assign_19}} = Assign[T=DT_FLOAT, class=["loc:@DenseVNet/conv/conv/w"], use_locking=true, validate_shape=true, device="/job:localhost/replica:0/task:0/device:GPU:0"](DenseVNet/conv/conv/w/Adam_1, save/RestoreV2/_39)]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 1546, in restore
{self.saver_def.filename_tensor_name: save_path})
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 929, in run
run_metadata_ptr)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1152, in _run
feed_dict_tensor, options, run_metadata)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1328, in _do_run
run_metadata)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/client/session.py", line 1348, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Assign requires shapes of both tensors to match. lhs shape= [3,3,61,256] rhs shape= [3,3,3,61,9]
[[node save/Assign_19 (defined at /home/NiftyNet/niftynet/engine/handler_model.py:109)  = Assign[T=DT_FLOAT, class=["loc:@DenseVNet/conv/conv/w"], use_locking=true, validate_shape=true, device="/job:localhost/replica:0/task:0/device:GPU:0"](DenseVNet/conv/conv/w/Adam_1, save/RestoreV2/_39)]]
Caused by op 'save/Assign_19', defined at:
File "net_segment.py", line 8, in
sys.exit(main())
File "/home/NiftyNet/niftynet/init.py", line 142, in main
app_driver.run(app_driver.app)
File "/home/NiftyNet/niftynet/engine/application_driver.py", line 197, in run
SESS_STARTED.send(application, iter_msg=None)
File "/usr/local/lib/python3.5/dist-packages/blinker/base.py", line 267, in send
for receiver in self.receivers_for(sender)]
File "/usr/local/lib/python3.5/dist-packages/blinker/base.py", line 267, in
for receiver in self.receivers_for(sender)]
File "/home/NiftyNet/niftynet/engine/handler_model.py", line 109, in restore_model
var_list=to_restore, save_relative_paths=True)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 1102, in init
self.build()
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 1114, in build
self._build(self._filename, build_save=True, build_restore=True)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 1151, in _build
build_save=build_save, build_restore=build_restore)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 795, in _build_internal
restore_sequentially, reshape)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 428, in _AddRestoreOps
assign_ops.append(saveable.restore(saveable_tensors, shapes))
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 119, in restore
self.op.get_shape().is_fully_defined())
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/state_ops.py", line 221, in assign
validate_shape=validate_shape)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/gen_state_ops.py", line 61, in assign
use_locking=use_locking, name=name)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/util/deprecation.py", line 488, in new_func
return func(*args, **kwargs)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 3274, in create_op
op_def=op_def)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 1770, in init
self._traceback = tf_stack.extract_stack()
InvalidArgumentError (see above for traceback): Assign requires shapes of both tensors to match. lhs shape= [3,3,61,256] rhs shape= [3,3,3,61,9]
[[node save/Assign_19 (defined at /home/NiftyNet/niftynet/engine/handler_model.py:109)  = Assign[T=DT_FLOAT, class=["loc:@DenseVNet/conv/conv/w"], use_locking=true, validate_shape=true, device="/job:localhost/replica:0/task:0/device:GPU:0"](DenseVNet/conv/conv/w/Adam_1, save/RestoreV2/_39)]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "net_segment.py", line 8, in
sys.exit(main())
File "/home/NiftyNet/niftynet/init.py", line 142, in main
app_driver.run(app_driver.app)
File "/home/NiftyNet/niftynet/engine/application_driver.py", line 197, in run
SESS_STARTED.send(application, iter_msg=None)
File "/usr/local/lib/python3.5/dist-packages/blinker/base.py", line 267, in send
for receiver in self.receivers_for(sender)]
File "/usr/local/lib/python3.5/dist-packages/blinker/base.py", line 267, in
for receiver in self.receivers_for(sender)]
File "/home/NiftyNet/niftynet/engine/handler_model.py", line 110, in restore_model
saver.restore(tf.get_default_session(), checkpoint)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 1582, in restore
err, "a mismatch between the current graph and the graph")
tensorflow.python.framework.errors_impl.InvalidArgumentError: Restoring from checkpoint failed. This is most likely due to a mismatch between the current graph and the graph from the checkpoint. Please ensure that you have not altered the graph expected based on the checkpoint. Original error:
Assign requires shapes of both tensors to match. lhs shape= [3,3,61,256] rhs shape= [3,3,3,61,9]
[[node save/Assign_19 (defined at /home/NiftyNet/niftynet/engine/handler_model.py:109)  = Assign[T=DT_FLOAT, class=["loc:@DenseVNet/conv/conv/w"], use_locking=true, validate_shape=true, device="/job:localhost/replica:0/task:0/device:GPU:0"](DenseVNet/conv/conv/w/Adam_1, save/RestoreV2/_39)]]
Caused by op 'save/Assign_19', defined at:
File "net_segment.py", line 8, in
sys.exit(main())
File "/home/NiftyNet/niftynet/init.py", line 142, in main
app_driver.run(app_driver.app)
File "/home/NiftyNet/niftynet/engine/application_driver.py", line 197, in run
SESS_STARTED.send(application, iter_msg=None)
File "/usr/local/lib/python3.5/dist-packages/blinker/base.py", line 267, in send
for receiver in self.receivers_for(sender)]
File "/usr/local/lib/python3.5/dist-packages/blinker/base.py", line 267, in
for receiver in self.receivers_for(sender)]
File "/home/NiftyNet/niftynet/engine/handler_model.py", line 109, in restore_model
var_list=to_restore, save_relative_paths=True)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 1102, in init
self.build()
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 1114, in build
self._build(self._filename, build_save=True, build_restore=True)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 1151, in _build
build_save=build_save, build_restore=build_restore)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 795, in _build_internal
restore_sequentially, reshape)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 428, in _AddRestoreOps
assign_ops.append(saveable.restore(saveable_tensors, shapes))
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/training/saver.py", line 119, in restore
self.op.get_shape().is_fully_defined())
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/state_ops.py", line 221, in assign
validate_shape=validate_shape)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/ops/gen_state_ops.py", line 61, in assign
use_locking=use_locking, name=name)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/util/deprecation.py", line 488, in new_func
return func(*args, **kwargs)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 3274, in create_op
op_def=op_def)
File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/framework/ops.py", line 1770, in init
self._traceback = tf_stack.extract_stack()
InvalidArgumentError (see above for traceback): Restoring from checkpoint failed. This is most likely due to a mismatch between the current graph and the graph from the checkpoint. Please ensure that you have not altered the graph expected based on the checkpoint. Original error:
Assign requires shapes of both tensors to match. lhs shape= [3,3,61,256] rhs shape= [3,3,3,61,9]
[[node save/Assign_19 (defined at /home/NiftyNet/niftynet/engine/handler_model.py:109)  = Assign[T=DT_FLOAT, class=["loc:@DenseVNet/conv/conv/w"], use_locking=true, validate_shape=true, device="/job:localhost/replica:0/task:0/device:GPU:0"](DenseVNet/conv/conv/w/Adam_1, save/RestoreV2/_39)]]
**

This appears to be caused by creating a network based on data with a different dimensionality than the one being loaded from the checkpoint. If you want to train on a 2D dataset the weights of some convolution would have a 4D dimension (ie. shape= [3,3,61,256])  whereas those being loaded from the zoo would have 5D (ie. shape= [3,3,3,61,9]).

@ericspod  Is it possible to add new layers in between and fine-tune the model on a custom dataset?

@koriavinash1 I'm afraid not, at least not trivially. The models are loaded from the zoo as checkpoints so you can't really have a different model with new layers load data from that.


please update for flutter

Hi create a flutter plugin to publish display streams

For discussion or idea, please ask in discord.
This issue will be eliminated, see #2716


Index operation

Description
[Add option to open index, set index status to block write on split page to make the index ready for split]
Issues Resolved
[List any issues this PR will resolve]
Check List

[X] Commits are signed per the DCO using --signoff

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.
For more information on following Developer Certificate of Origin and signing off your commits, please check here.

Codecov Report

Merging #378 (55d35b6) into index-operation (e93d5f9) will increase coverage by 0.20%.
The diff coverage is n/a.

@@                 Coverage Diff                 @@
##           index-operation     #378      +/-   ##
===================================================
+ Coverage            56.85%   57.06%   +0.20%
===================================================
  Files                  215      215
  Lines                 7011     7024      +13
  Branches              1127     1131       +4
===================================================
+ Hits                  3986     4008      +22
+ Misses                2741     2739       -2
+ Partials               284      277       -7

Impacted Files
Coverage Δ

.../pages/Indices/containers/IndicesActions/index.tsx
69.82% <0.00%> (-0.82%)
:arrow_down:

...s/components/SplitIndexFlyout/SplitIndexFlyout.tsx
86.66% <0.00%> (+23.70%)
:arrow_up:

Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here.


Update doc for mix and match discount line groups

This is the old repo for D365 Commerce documents. We'll add a new page in dynamics-365-unified-operations-public repo.


Hide tracebacks by default for most types of error

For user errors (specifying wrong file, nonexistent filename, [...]) you should see a clean error message, not a huge traceback.

replace --hide-traceback option by UserError which don't show the traceback by default

done


Why is the process stuck?

Why does this step get stuck before the test loads the model？Unable to run further down。

This step stops after that.

The CUDA version is too high。

CUDA版本太高。

What version of CUDA is needed here？


Add back README.md to the dist version?

README.md contains useful information for new comers, it is a super-slim documentation, so even if I usually prefer excluding documentation from dist versions, for this package ,I would consider having it bundled with the dist version as well. What do you think?

mmmh you're making a point but at the same time, I'm balanced between 2 waters. Since the README file is available online, I don't see the point of having it in vendor/. I personally never go in vendor/ for checking the documentation.
If you don't mind, I would prefer to keep the dist as small as possible.

It is no problem if you keep the current behavior :) However let me tell you what I did yesterday.
Yes, it is available online therefore I constantly jump between PHPStorm and a web browser tab to see the extra context that is not available in the code. PHPStorm nicely jumped to the class definition (that opened vendor/... instantly in project browser due to my PHPStorm settings) and then I realize, "Hey, if README.md would be here, I could just pin tab in PHPStorm and never look back to my browser.".
I was also surprised that this was my methodology discovering what is available in this package and what is not.
So maybe this could be a DX improve... maybe I was doing something special.
By the way, thank you for this package! :muscle:

You're making a valid point, but I prefer to keep it as it is.

By the way, thank you for this package! 💪

Thanks! Curious to learn why you're using it!

Atm, I am trying to build (again) a memory and performance efficient lazy list implementation for Drupal 10+ that also holds Drupal dearest changeability information in it, so bubbling up a list of entities and listing specific cacheability information at the call site becomes super simple and easy with this approach. Less magic in upper layers...
The Collection seemed and overkill for this, but these underlying building blocks helped a lot.

Interesting!
Yeah loophp/collection is huge and not efficient for small amount of items. I should build a more efficient version of it, but then I would avoid making it immutable. Maybe this is something I should do.

Hm, I think you were referring to something else with immutability, but that also reminded me that I may need to build an immutable version of \Drupal\Core\Cache\CacheableMetadata (again) to ensure it does not poison my collection.

Yeah... but using immutable objects means creating a new instance at each single least modification, I'm not sure if this is a good idea for a caching object.

haha enjoy! Writing loophp/collection and loophp/iterators were the thing I really enjoyed in PHP, hope you'll have fun too in your quest! Drupal needs improvements ;)

Thank you! :grimacing:


Added CMD cheatsheet

added cmd cheatsheet with the most commonly used cmd commands.

Hello @dmanocha464
Thanks for your contribution.
Let's connect ->
GitHub -> @Suryansh1720001 (Follow)
LinkedIn -> https://www.linkedin.com/in/suryanshprajapati17
Also, Star the repo ⭐


[Docs] Code of Conduct contact method placeholder

Someone has forgoten to replace the contact method placeholder in the Code of Conduct.

https://github.com/k8s-at-home/charts/commit/32af5c7326703a4a72617565d707fb86f28b6aad


chore: move api into dependencies in integration tests

Integration tests require the OTel API. Therefore move it into dependencies section and remove the peer-dependency.

EasyCLA tells I miss CLA authorization. No idea what I did that this got lost. If I click on above link to get authorized the result is an internal server error.
Any hints welcome...

I'm not sure what's wrong with the CLA check. I'll try to find out more

@Flarna looks like the email associated with that commit is a yahoo.de email. Most of your other commits appear to use the users.noreply.github.com email provided by github.

/easycla


Trouble Registering With Bitnami Parse-Server AWS Image

Hello,
I am presently trying to connect to the parse-server instance from my Bitnami Parse-Server AWS Image.
However, I noticed the register()  function requires a rest_key parameter. To get this, I went to the /opt/bitnami/apps/parse/htdocs/server.js file in the image, and saw the following variables:
var api = new ParseServer({
    databaseURI: "mongodb://root:WcbKujWVdiX2@<IP_ADDRESS>:27017/bitnami_parse",
    cloud: "./node_modules/parse-server/lib/cloud-code/Parse.Cloud.js",
    appId: "APP_ID",
    masterKey: "MASTER_KEY",
    fileKey: "FILE_KEY",
    serverURL: "http://<IP_ADDRESS>:80/parse"
});

I tried passing both the masterKey and fileKey variables as the rest_key argument for the function, and received the following error in both instances:
Traceback (most recent call last):
  File "/anaconda3/lib/python3.7/site-packages/parse_rest/connection.py", line 140, in execute
    response = urlopen(request, timeout=CONNECTION_TIMEOUT)
  File "/anaconda3/lib/python3.7/urllib/request.py", line 222, in urlopen
    return opener.open(url, data, timeout)
  File "/anaconda3/lib/python3.7/urllib/request.py", line 531, in open
    response = meth(req, response)
  File "/anaconda3/lib/python3.7/urllib/request.py", line 641, in http_response
    'http', request, response, code, msg, hdrs)
  File "/anaconda3/lib/python3.7/urllib/request.py", line 569, in error
    return self._call_chain(*args)
  File "/anaconda3/lib/python3.7/urllib/request.py", line 503, in _call_chain
    result = func(*args)
  File "/anaconda3/lib/python3.7/urllib/request.py", line 649, in http_error_default
    raise HTTPError(req.full_url, code, msg, hdrs, fp)
urllib.error.HTTPError: HTTP Error 410: Parse.com has shutdown - https://parseplatform.github.io/

I also tried adding a restAPIKey argument in the server.js file above, rebooting my instance, and then passing it in as the arg. Unfortunately, that led to no difference in result.
Any guidance would be appreciated, thanks.

hi @michaelyma12
This is a parse-server issue. You need to instantiate parse-server with options including restApiKey.
https://github.com/parse-community/parse-server#client-key-options


.unpack on an Archive should handle GNU extensions

https://github.com/alexcrichton/tar-rs/blob/0cc93a7/src/archive.rs#L109
(someone hit this - https://users.rust-lang.org/t/tar-rs-failed-to-iterate-over-archive-when-unpacking-tar/4442)

Oh that's actually an old TODO, this should be handled by the entries iterator (the GNU extensions). I'll comment on that thread though.


clearStoredFiles doesn't work as expected

Type of issue

[ ] Bug report

Uploader type

[ ] Traditional

Note: Support requests cannot be accepted due to lack of time.

Bug Report
Fine Uploader version
5.15.4
Browsers where the bug is reproducible
Google chrome
Operating systems where the bug is reproducible
iOS 10.13.2
All relevant Fine Uploader-related code that you have written
    new qq.FineUploader({
        element: document.getElementById('template-manual-trigger'),
        template: 'qq-template-manual-trigger',
        multiple: false,
        autoUpload: false,
        validation: {
            allowedExtensions: [ 'jpeg', 'jpg', 'png' ],
            itemLimit: 1
        },
        callbacks: {
            onValidateBatch() {
                if (this._netUploadedOrQueued > 1) {
                    this.clearStoredFiles();
                    this._netUploadedOrQueued = 1;
                }
            }
       }
  });

Your Fine Uploader template markup (if using Fine Uploader UI and the issue is UI-related)
Couldn't put HTML here

Detailed explanation of the problem
I have " itemLimit: 1". So I need to clean the previous image if I try to upload one more (a simple upload box for an avatar). I use the method "clearStoredFiles" and the image is reseted, it's ok. But when I try to upload one more I've got an error box with the text "Too many items (2) would be uploaded. Item limit is 1.". I decided to rewrite a private field "_netUploadedOrQueued" manually and it works correctly. But it seems like a hack than a right way to resolve the problem.

So I need to clean the previous image if I try to upload one more

You cannot do this using clearStoredFiles - that clears out files that have not yet been uploaded, to be used only when autoUpload is set to false. You can reset though.


[BUG] Error on wallet load

Describe the bug
I see to bugs on the deployment :

Endpoint /api/properties don't exist
Endpoint for subgraph don't exist (hosted service has been disabled)

Screenshots

Good news ! Can you make a PR to hydrate it ?


Dark mode hide data when applied in some of the application pages

In some pages of the application some data can be hidden due to color changes while using the Dark mode.

The map legend in "single-line-map" doesn't show correctly in dark mode.
In line profile page some of the data will not show correctly in dark mode.

I'll take it if that's ok.
I also see that it needs to be translated.

Hi @YuvalMasada are you still up for it? Do you need any help?


sort the clusters by descending order of decimal part in dynamicDivideReplicas

…ynamicDivideReplicas
Signed-off-by: Garrybest<EMAIL_ADDRESS>
What type of PR is this?
What this PR does / why we need it:
Which issue(s) this PR fixes:

Fixes #526
Special notes for your reviewer:

Seems we need to improve the algorithm for dynamic assigner as well.

That's right... The decimal could be negative when scale down, so retrieving abs of decimal is correct.


Installer Bugs for Geometry Dash version 2.2

Geode Issue

[X] I confirm that this bug is NOT related to a mod but directly to Geode Loader itself.

Platform
Windows
SDK commit
No response
Geode Version
v.2.0.0-beta.25
Mods Installed
BetterEdit v6.3.3, Click Between Frames v1.0.9, Globed v1.3.7
Expected Behavior
The mods will work as they normally do.
Actual Behavior
The mods show an error sign, and do not work.
Steps to Reproduce
I started up Geometry Dash, and the mods showed that there were some errors.
Additional Information
I do not know how this was caused, there were no mods that needed to be updated, and i haven't done anything weird on the game. I just started up the game.

You have to install the mods these mods depend on so get node ids and custom keybinds


update China/Taiwan testdata

You must at the same time also update supplier_test.cc in which the KeyDepth* test cases use the data you're changing.

Updated supplier_test.cc also.


TEST

What problem does this PR solve?
Issue Number: ref https://github.com/pingcap/tiflash/issues/6809
Problem Summary:
What is changed and how it works?
Check List
Tests

[ ] Unit test
[ ] Integration test
[ ] Manual test (add detailed scripts or steps below)
[ ] No code

Side effects

[ ] Performance regression: Consumes more CPU
[ ] Performance regression: Consumes more Memory
[ ] Breaking backward compatibility

Documentation

[ ] Affects user behaviors
[ ] Contains syntax changes
[ ] Contains variable changes
[ ] Contains experimental features
[ ] Changes MySQL compatibility

Release note

None

/run-sanitizer-test tsan

/run-sanitizer-test tsan

/run-sanitizer-test tsan

/run-sanitizer-test tsan

/run-sanitizer-test tsan

/run-sanitizer-test tsan

/run-sanitizer-test tsan

/run-sanitizer-test tsan


ValueError raised in FunctionLogger when target density is zero

Raising issue as part of JOSS review https://github.com/openjournals/joss-reviews/issues/5428
The code block
https://github.com/acerbilab/pyvbmc/blob/b7c6e381be75dd508ac9663825fd77ed8885816d/pyvbmc/function_logger/function_logger.py#L148-L156
raises a ValueError when the value returned by the function is non-scalar, non-finite or non-real. When the function corresponds to the logarithm of the target density, this excludes the target density taking value zero, and so it's logarithm being negative infinity. I imagine this might be a constraint implied by using a Gaussian process to fit to the log target density evaluations, so this check probably makes sense, but as it implies a (weak) constraint on the class of posterior distributions that can be targeted it may be worth explicitly mentioning this is disallowed in the documentation, and/or suggesting workarounds (possibly outputting a large in magnitude but finite negative value as a proxy for negative infinity?). I imagine some common cases where users might want to use a target density which may take exactly evaluate to zero are: (i) when the prior has support only on a subset of the specified domain but this doesn't correspond to a simple Cartesian product of intervals as covered by the lower / upper bound options, (ii) observation noise from some truncated distribution is assumed which will mean the likelihood may evaluate to zero, (iii) the model involves a numerical solver which may fail to converge for some choices of the parameters, for which a common resolution would be to output a target density of zero to exclude these regions of parameter space from posterior (I hit against this in the latter case when trying out PyVBMC with a model which involves solving a system of ordinary differential equations for which the solver fails to converge for some parameter settings).
As a sidenote, I might be wrong but I think the np.any call in the condition expression to the if block is not needed. np.any would usually be used on an array of boolean values. Here if f_val_orig is not a scalar and so not np.isscalar(f_val_orig) evaluates to True then because of the short-circuit evaluation semantics of or then the whole expression will evaluate to True without evaluating the not np.isfinite(f_val_orig) and not np.isreal(f_val_orig) parts of the expression. If instead f_val_orig is a scalar then both np.isfinite(f_val_orig) and not np.isfinite(f_val_orig) will output scalars I believe and the overall expression will therefore always evaluate to either (scalar) True or False without the need for np.any.

Thanks for the comment! This is actually a non-trivial issue to deal with when working with surrogate models of the log-density.
The original VBMC algorithm does not deal with Infs and NaNs, assuming the output of the log-density is always well-behaved. This is indeed a limitation, for now we should probably mention it more explicitly in the documentation (besides the FAQ), as you also suggest above:

it may be worth explicitly mentioning this is disallowed in the documentation

As for future plans, we do want to address the issues of zero-density (or NaNs)
A naive workaround of outputting an arbitrary large negative number will break the GP surrogate, but a heuristic dynamical approach that sets this value based on the current observed values might work, combined with (fake) observation noise that informs (Py)VBMC not to take that observation too seriously (for the latter, see this preprint, Section 3.5 on noise shaping).
In an ideal world, we should use a logistic non-Gaussian likelihood for the GP model that informs the GP surrogate that the observation is below a threshold. However, introduction of non-Gaussian likelihoods requires approximate inference for the GP, which is a major modification of the algorithm and a separate research project in itself.

Thanks @lacerbi for the detailed explanation. Having something slightly more prominent in the documentation I think would be good though I did end up finding the relevant FAQ so not essential.
Out of interest, in terms of the possible longer term fixes, is the latter approach you suggest of informing the GP surrogate the target is below a threshold in a similar vein to that used by the authors of the GPry package / paper employ for this issue of simultaneously fitting a classifier (they use a support vector machine) which partitions the latent space into regions with well-defined target (log density) values and those with non-finite / non-defined values? That seemed an interesting idea but I haven't had a chance to try out GPry yet to see how well it works in practice.

Thanks @matt-graham - I am aware of the GPRy approach but we have not tried it out it - it is an interesting idea that might work in practice, and was planning to also give it a try.
Still, it remains an ad hoc heuristic since it doesn't really include the measurement into the GP surrogate; the SVM and the GP model are entirely distinct. For example, not sure how it avoids that whole areas of parameter space are ruled out just because one or two computations failed; or that the acquisition function would keep trying to go to the border of the unfeasible region (since it was a good region before, it likely remains a good region now; the GP has not changed, unless e.g. some additional heuristic "repulsion" term is added to the acquisition function).
The approach I was talking about would be more principled (but, of course, more costly), in that you do include the observation in the GP model, but instead of making it a standard observation with Gaussian likelihood, you make it a "censored" observation that just informs the model that "the observed value is somewhere below this threshold", where the threshold could be some low density value (but not insanely low). The point is that we just want to log-density to be very low, we don't care about its exact value. However, a censored-observation model is non-Gaussian so it requires approximate inference for the GP, which is a pain.
I have been thinking about this for a very long time (since the original VBMC paper more or less), but never got to it mostly because implementing it in MATLAB was out of the question (no autodiff). Incidentally, a recent paper worked out a nice way to implement censored observations in GP models, exactly along the lines we have been thinking about (not for VBMC of course; they just present it for general GP regression): https://link.springer.com/article/10.1007/s11222-023-10225-3

Regarding the extraneous np.any call, you are correct @matt-graham: It has been removed in pull #140.

Thanks @Bobby-Huggins and for the additions to the documentation making the requirements for the target log density function more visible. Closing this as now resolved from my perspective.


Dynamic Captions with DataSource

Hey, not sure if this is an issue, but I've been trying to get DataSource from the page https://photoswipe.com/data-sources/ working with the Dynamic Caption plugin  for a few days, but nothing I try has worked. Is it possible?
My goal is to have one image open up when clicked revealing an album or gallery of other images with their own captions or at least one general caption for all of them. This works using the code from the DataSource page and using an image instead of button and adding the id of the button to the image, but no captions.
Has anyone tried this before? Any hints would be greatly appreciated! Thanks.

Use captionContent option, it should return the caption HTML text, you may parse the data however you wish in it. This may help - https://github.com/dimsemenov/photoswipe-dynamic-caption-plugin/issues/10

Thank you so much!