[Bug]: "Reset on submit" is not working in Input Widget

Is there an existing issue for this?

[X] I have searched the existing issues

Current Behavior
After adding some input and submit (press enter), the old text is not getting removed even if Reset on Submit option is Enabled

Steps To Reproduce

Add input widget to canvas
Enable Reset on Submit option from property pane
Add some text and hit enter
Observe that older text is still present in the widget

Environment
Production
Version
Cloud

Hey @sbalaji1192 this is not working for me in production as well. It's working for currency widget but not for the input widget, can you check this?
Also can we add this in our regression cases if it's not there.

@chandannkumar @dilippitchika Not able to repro on release and prod - https://www.loom.com/share/88866ea7055a485ebfeba8cd1ae156c0

It is now observed that Text gets reset on submit if onSubmit action is handled and if onSubmit is not handled then text is unable to reset on Pressing Enter, though Reset on submit is enabled
@dilippitchika  is this a expected behavior? Does Reset on Submit have any limitations or dependent on any other actions?

This is the expected behavior, the problem was weirdly even that was not working for me, when I was demoing.
Closing this issue for now as it's not reproducible anymore.


Updated README.md

Updated README.md

@googlebot I signed it!
On Tue, Jun 16, 2020 at 2:48 PM googlebot<EMAIL_ADDRESS>wrote:

Thanks for your pull request. It looks like this may be your first
contribution to a Google open source project (if not, look below for help).
Before we can look at your pull request, you'll need to sign a Contributor
License Agreement (CLA).
📝 Please visit https://cla.developers.google.com/
https://cla.developers.google.com/ to sign.
Once you've signed (or fixed any issues), please reply here with @googlebot
I signed it! and we'll verify it.
What to do if you already signed the CLA Individual signers

It's possible we don't have your GitHub username or you're using a
different email address on your commit. Check your existing CLA data
https://cla.developers.google.com/clas and verify that your email is
set on your git commits
https://help.github.com/articles/setting-your-email-in-git/.

Corporate signers

Your company has a Point of Contact who decides which employees are
authorized to participate. Ask your POC to be added to the group of
authorized contributors. If you don't know who your Point of Contact is,
direct the Google project maintainer to go/cla#troubleshoot (Public
version https://opensource.google/docs/cla/#troubleshoot).
The email used to register you as an authorized contributor must be
the email used for the Git commit. Check your existing CLA data
https://cla.developers.google.com/clas and verify that your email is
set on your git commits
https://help.github.com/articles/setting-your-email-in-git/.
The email used to register you as an authorized contributor must
also be attached to your GitHub account
https://github.com/settings/emails.

ℹ Googlers: Go here
https://goto.google.com/prinfo/https%3A%2F%2Fgithub.com%2Fgoogle%2Fplayhvz%2Fpull%2F174
for more info.
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/google/playhvz/pull/174#issuecomment-644643892, or
unsubscribe
https://github.com/notifications/unsubscribe-auth/AND67DZ4SOJ2GKRDKWUTVOLRW42FXANCNFSM4N7NSWJA
.


Terminating Error on Write-HtmlReportSection

TerminatingError(Write-HtmlReportSection): "Cannot convert argument "value", with value: (with a typical 8-char ConfigMgr identifier).  It appears to be seeing those as a number and trying to convert it to System.Double.  This is for a site that uses site code "001", so collections have ID's like "001000DF" etc.

fixed in 1.0.22


Audio-driven head pose

Hi, thank you for sharing your work.
I notice that this method requires a driving video, as in the argument setting in line 591, ./inference/real3d_infer.py:
parser.add_argument("--drv_pose", default='data/raw/examples/May_5s.mp4', type=str) # data/raw/examples/May_5s.mp4

Please help me on how to use the predicted pose from the A2M.
Thank you.

If drv_audio_name is set to be an audio file, the drv_pose only provides camera pose (i.e. translation & rotation), and the A2M module will predict expression from the given audio.

Ok, thanks.


fix(cleanTypstSource): take baseNameOf path to match typst.toml

Closes #19

Thanks! I also wrote a test for this in dfe38fa30a9700b938cefe4bed951128be08be4c, which is now passing.


[3.7] Travis builds are broken with PHP 7.4

Affected Version
3.7.x
Description
The Travis builds are broken due to a list of deprecations that have been introduced recently into PHP 7.4. We have a bit of patching to do to fix them up, but shouldn't be much work.
Steps to Reproduce
https://travis-ci.org/silverstripe/silverstripe-framework/jobs/577129681

Fixed now: https://travis-ci.org/github/silverstripe/silverstripe-framework/builds/669700308
Thanks @kinglozzer


[QUESTION] Generation throughput in my experiment much lower than that reported

Question
Hello, it is very nice to see this interesting work.
However, when trying to implement results in Table 4, the throughput using ShadowKV is much lower than that reported.
As shown in the table below, throughput using vanilla KV cache is similar to that reported. But that using ShadowKV is much lower.

Model
Context (K)
Full Attention (tokens / s)
ShadowKV (tokens / s)
Gain

GLM-4-9B-1M (4 KV heads)
60
223 (12)
358 (50)
1.61x

GLM-4-9B-1M (4 KV heads)
122
114 (6)
182 (25)
1.60 x

Yi-9B-200K (4 KV heads)
60
192.74 (10)
336.11 (42)
1.74 x

Yi-9B-200K (4 KV heads)
122
94.83 (5)
167.24 (21)
1.76 x

Yi-9B-200K (4 KV heads)
244
43.83 (2)
75.20 (10)
1.72 x

I wonder whether this is due to environment difference or my implementing mistakes.
Environment
Driver: 550.54.14
CUDA: 12.4
Python: 3.10.0
transformers: 4.43.1
torch: 2.3.1
OS: Ubuntu, x86_64, 22.04.2 LTS
Device: A single NVIDIA A100 80GB

Command
python test/e2e.py --model_name "THUDM/glm-4-9b-chat-1m" --datalen "122k"

Looking forward to hearing from you.

Thanks for being interested in ShadowKV.
Based on your reported numbers, it is highly likely that your is bounded by PCIe.
ShadowKV offloads and stream in V through PCIe.
Full attention directly uses GPU DRAM and gets similar numbers, meaning your clock frequency is similar.
ShadowKV gets faster dull attention, meaning the computation part highly likely correct,
but worse than Table 4, implying your PCIe might be too slow.
Table 4 is measured using A100 SXM4 having PCIe with 31.5GB/s theoretical bandwidth single directional (which is mentioned in Figure 1).
The practical/measured bandwidth should be at least 24-26 GB/s, single directional.
There might be several reasons that make your PCIe slow, including your mother chipset, lower generation of PCIe, traffic, or using different A100 PCIe card instead of A100 SXM4.
I will suggest you run a micro-benchmarking testing your PCIe bandwidth or H2D bandwidth to check your PCIe bandwidth.
There is a tuning knob in kernels/copy.cub that can adapt different PCIe to reach a reasonable/practical speed of PCIe.
However, it won't make your streaming-in V faster than your PCIe physical speed.

Thanks for your reply.
By running bandwidthTest, I get the following result.
[CUDA Bandwidth Test] - Starting...
Running on...

  Device 0: NVIDIA A100 80GB PCIe
  Quick Mode

  Host to Device Bandwidth, 1 Device(s)
  PINNED Memory Transfers
    Transfer Size (Bytes)        Bandwidth(MB/s)
    33554432                     7831.1

  Device to Host Bandwidth, 1 Device(s)
  PINNED Memory Transfers
    Transfer Size (Bytes)        Bandwidth(MB/s)
    33554432                     9095.4

  Device to Device Bandwidth, 1 Device(s)
  PINNED Memory Transfers
    Transfer Size (Bytes)        Bandwidth(MB/s)
    33554432                     1416320.9

Result = PASS

NOTE: The CUDA Samples are not meant for performance measurements. Results may vary when GPU Boost is enabled.

I have to say that I am not a specialist in this field.
Does it mean my bandwidth is too small by comparing 7GB/s or 9GB/s with 24-26GB/s?

Most of the servers now are using PCIe 4.0, maxing out at 32 GB/s in a 16-lane slot.

@A-LinCui  We suggest that you use below script (lstopo command) to check your PCIE topo connection on your machine.
# install dependencies
sudo apt update -y && sudo apt install zsh tmux file libnet-ifconfig-wrapper-perl/oldstable -y
sudo apt install graphviz hwloc -y

env

WORKDIR=/your/work/path
mkdir -p $WORKDIR
sudo chown -R root:root ${WORKDIR}

pushd ${WORKDIR}
# mkdir on mounts
lshw -numeric -class display &> gpu-info
lstopo-no-graphics  --of txt > lstopo.txt
hwloc-ls hwloc.png
nvidia-smi -q > nvidia_smi_q.txt

@A-LinCui We suggest that you use below script (lstopo command) to check your PCIE topo connection on your machine.
# install dependencies
sudo apt install graphviz hwloc -y

env

WORKDIR=/your/work/path
mkdir -p $WORKDIR
sudo chown -R root:root ${WORKDIR}

pushd ${WORKDIR}
# mkdir on mounts
lshw -numeric -class display &> gpu-info
lstopo-no-graphics  --of txt > lstopo.txt
hwloc-ls hwloc.png
nvidia-smi -q > nvidia_smi_q.txt

Let me mention slightly more about the above script.
In your situation, slower PCIe could come from 1) lower generation of PCIe of your mother board or 2) plugging-in a wrong PCIe slot with fewer lanes.
The latter could be more possible, since PCIe gen4 has been there for a while.
The above script is helping detect your PCIe topology and show how many lanes for each PCIe card in your system.
If the PCIe slot is wrong, you can simply re-plug your A100 to a right one with 16 lanes.
For detecting PCIe generation, you can use Linux commands like lspci or dmidecode.
If it happened to be the first case, you might want to replace your mother board to a better one that can really fully utilize A100 well.

Thanks. I get it. I just find I'm using PCIe gen3.


Add rbxgameasset to asset url types

Changes
Adds rbxgameasset to the documentation.
Posted from the old game asset content page.
Checks
By submitting your pull request for review, you agree to the following:

[X] This contribution was created in whole or in part by me, and I have the right to submit it under the terms of this repository's open source licenses.
[X] I understand and agree that this contribution and a record of it are public, maintained indefinitely, and may be redistributed under the terms of this repository's open source licenses.
[X] To the best of my knowledge, all proposed changes are accurate.

I made some minor edits, particularly that the "URL" needs to omit the file format (such as just /Potion and not /Potion.png). Thanks for the contribution!


Work around frontend losing precision for Longs

DUN DUN DUN
[info] - OpaqueId serialisation roundtrip 169ms
[info]  [0] Property test failed on try 2 with seed Seed.fromBase64("UI8U1U9_IoA9x5ZBSyBwwIEeCSKnBIsHnDnk2EPAgjD=") and input -5475331890968884720 (modules/scalacheck/src/weaver/scalacheck/Checkers.scala:191)
[info]
[info]  [1] assertion failed (modules/shared/src/test/scala/JsonCodecsTest.scala:36)
[info]  [1]
[info]  [1] result == id
[info]  [1] |      |  |
[info]  [1] |      |  -5475331890968884720
[info]  [1] |      false
[info]  [1] -5475331890968884000

I think in the shared module we need to represent OpaqueId as backed by something that doesn't lose precision by going through JSON.parse.
Or perhaps override the codec to serialise Longs as String?

Done in #22


Use $this for fluent interface

see Shardj/zf1-future#302

This PR may not be complete. I have replaced only the docs where there was a comment with "fluent" or "fluent interface" etc.
I suspect phpstan will find some other occurrences, but I don't have time for that right now.

Seems UnitTest fails 8.1.4/8.2.1 b/c #305.