text:
401_CNN.py

I run it on WIN10.I have gotten the mnist.But when I run it,it says "RuntimeError: Dataset not found. You can use download=True to download it"

first, make sure that your conda is setup properly with the right environment
for that, check that which conda, which pip and which python points to the
right path. From a clean conda env, this is what you need to do
conda create --name maskrcnn_benchmark
source activate maskrcnn_benchmark
this installs the right pip and dependencies for the fresh python
conda install ipython
maskrcnn_benchmark and coco api dependencies
pip install ninja yacs cython matplotlib
follow PyTorch installation in https://pytorch.org/get-started/locally/
we give the instructions for CUDA 9.0
conda install pytorch-nightly -c pytorch
install torchvision
cd ~/github
git clone https://github.com/pytorch/vision.git
cd vision
python setup.py install
install pycocotools
cd ~/github
git clone https://github.com/cocodataset/cocoapi.git
cd cocoapi/PythonAPI
python setup.py build_ext install
install PyTorch Detection
cd ~/github
git clone https://github.com/facebookresearch/maskrcnn-benchmark.git
cd maskrcnn-benchmark
the following will install the lib with
symbolic links, so that you can modify
the files if you want and won't need to
re-build it
python setup.py build develop
or if you are on macOS
MACOSX_DEPLOYMENT_TARGET=10.9 CC=clang CXX=clang++ python setup.py build develop

您好，      您的邮件已收到。陈通宝广东工业大学

你好，你的邮件已收到，稍后将会查看，尽快给你回复。

repo: MorvanZhou/PyTorch-Tutorial


text:
Merge pull request #4 from Mostafa-MR/main

Main to Mostafa

renamed a branch

source: gharchive/pull-request

license: MIT

license_type: permissive

license_source: github-api


text:
Issue with download_gbif() finding Taxon.tsv.

When I run download_gbif() I run into the following issue:
> download_gbif()
Your current download timeout is set to 60 seconds.
Temporarily setting the download timeout to 1800 seconds.
trying URL 'https://hosted-datasets.gbif.org/datasets/backbone/current/backbone.zip'
Content type 'application/zip' length 971465842 bytes (926.5 MB)
==================================================
downloaded 926.5 MB

GBIF backbone taxonomy has been downloaded.
Error in download_gbif() :
  Error saving Taxon.tsv. Consider raising an issue on Github.
In addition: Warning message:
In utils::unzip(tf, files = c(file.path("backbone", "Taxon.tsv")),  :
  requested file not found in the zip file

Just downloading the file manually now to see if it's an issue with capitalization.

Following up, the file is there and capitalized as expected.
And:
R version 4.3.1 (2023-06-16)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 23.10

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.23.so;  LAPACK version 3.11.0

locale:
 [1] LC_CTYPE=en_CA.UTF-8       LC_NUMERIC=C
 [3] LC_TIME=en_CA.UTF-8        LC_COLLATE=en_CA.UTF-8
 [5] LC_MONETARY=en_CA.UTF-8    LC_MESSAGES=en_CA.UTF-8
 [7] LC_PAPER=en_CA.UTF-8       LC_NAME=C
 [9] LC_ADDRESS=C               LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_CA.UTF-8 LC_IDENTIFICATION=C

time zone: America/Vancouver
tzcode source: system (glibc)

attached base packages:
[1] stats     graphics  grDevices datasets  utils     methods   base

other attached packages:
[1] taxonbridge_1.2.2 purrr_1.0.2       dplyr_1.1.2       neotoma2_1.0.2

loaded via a namespace (and not attached):
 [1] raster_3.6-23      htmlwidgets_1.6.2  lattice_0.21-8     bspm_0.3.10
 [5] tzdb_0.4.0         vctrs_0.6.3        tools_4.3.1        crosstalk_1.2.0
 [9] generics_0.1.3     curl_5.0.2         parallel_4.3.1     stats4_4.3.1
[13] tibble_3.2.1       proxy_0.4-27       fansi_1.0.4        pkgconfig_2.0.3
[17] KernSmooth_2.23-22 satellite_1.0.4    leaflet_2.1.2      assertthat_0.2.1
[21] webshot_0.5.5      uuid_1.1-1         lifecycle_1.0.3    compiler_4.3.1
[25] stringr_1.5.0      progress_1.2.2     munsell_0.5.0      terra_1.7-39
[29] codetools_0.2-19   htmltools_0.5.6    class_7.3-22       pillar_1.9.0
[33] crayon_1.5.2       tidyr_1.3.0        classInt_0.4-9     gtools_3.9.4
[37] tidyselect_1.2.0   digest_0.6.33      stringi_1.7.12     sf_1.0-14
[41] fastmap_1.1.1      grid_4.3.1         colorspace_2.1-0   cli_3.6.1
[45] magrittr_2.0.3     base64enc_0.1-3    utf8_1.2.3         leafem_0.2.0
[49] e1071_1.7-13       withr_2.5.0        readr_2.1.4        prettyunits_1.1.1
[53] scales_1.2.1       bit64_4.0.5        sp_2.0-0           lubridate_1.9.2
[57] timechange_0.2.0   httr_1.4.7         bit_4.0.5          png_0.1-8
[61] hms_1.1.3          mapview_2.11.0     rlang_1.1.1        Rcpp_1.0.11
[65] glue_1.6.2         DBI_1.1.3          geojsonsf_2.0.3    vroom_1.6.3
[69] jsonlite_1.8.7     R6_2.5.1           units_0.8-3

It seems like the issue is the line:

files <- utils::unzip(tf, files = c(file.path("backbone",
"Taxon.tsv")), exdir = td)

Where it is trying to pull a file backbone out of the zip file, but when the file was downloaded it was downloaded to a temporary file tf.
I was able to correct it by replacing the line with:

files <- utils::unzip(tf, files = "Taxon.tsv", exdir = td)

TODO: Change package maintainer

I'm guessing this means you don't want to manage the package anymore? :)

Taxonbridge is not actively maintained. However, it still belongs to the ongoing MoultDB project about moulting in the Arthropoda. If you’d like to contribute to its development @SimonGoring, and I hope you do, please contact the principal investigator @marcrr. In the meantime, I’ll let CRAN know that I’m no longer the maintainer.

Hello @SimonGoring, I will be the new maintainer of this package. I will update the code as soon as possible. Thank you for your feedback

source: gharchive/issue

authors: MicheleRoar SimonGoring Werner0

repo: MoultDB/taxonbridge


text:
Manual segmentation end up with index error

Hello!
I faced strange bug. In a paticular moment I wasn't able to stop outlining a cell. I pressed “enter” to make a “cell” out of this dotted line and then delete it. But I wasn't able to do this either. "Ctrl+z" option led to removing previously outlined cells. Then I decided to save file and get out of the programme.
After reentering cellpose gave this message.
7 (1150, 1150, 3)
Traceback (most recent call last):
File "cellpose\menus.py", line 21, in
File "cellpose\io.py", line 542, in _load_seg
File "cellpose\gui.py", line 1168, in draw_masks
IndexError: index 229 is out of bounds for axis 0 with size 229
And all options doesn't work properly (even zoom). Previously outlined cells "partially" disappeared. Partially because they appears after user click on the place where they were outlined.
It took too much time to create this segmentation. So, could you tell me how to fix this problem? And how to safe all segmented cells or at least larger part?

I got this problem one more time on the other file. This time I was able to screenshot the initial error.

sorry I'm not sure what the error is here, but your _seg.npy file may be weirdly formatted now. you can load the masks in python and save them as a tif and then load them back in the gui and try to save them again
import numpy as np
from cellpose.io import imsave

dat = np.load('/path/name_seg.npy', allow_pickle=True).item()
imsave('masks.tif', dat['masks'].squeeze())

do you have any idea what you did before it stopped working? sorry it's hard to know without running the gui myself.
please also upgrade to the latest version pip install cellpose --upgrade

(or upgrade to the latest v1.0 version pip install cellpose==1.0.2)

authors: carsen-stringer i-v-e

repo: MouseLand/cellpose


text:
[INSTALL]

Install problem
Having issues with basic installation of Cellpose. Steps 1-5 ran well I believe. Getting the same error in step 6 every time I try. "Preparing metadata (pyproject.tom1) did not run successfully."
Environment info
Name                    Version                   Build  Channel
bzip2                     1.0.8                h620ffc9_4
ca-certificates           2023.01.10           hca03da5_0
cellpose                  2.2.2                    pypi_0    pypi
fastremap                 1.13.5                   pypi_0    pypi
filelock                  3.12.0                   pypi_0    pypi
imagecodecs               2023.3.16                pypi_0    pypi
jinja2                    3.1.2                    pypi_0    pypi
libffi                    3.4.4                hca03da5_0
llvmlite                  0.40.0                   pypi_0    pypi
markupsafe                2.1.2                    pypi_0    pypi
mpmath                    1.3.0                    pypi_0    pypi
natsort                   8.3.1                    pypi_0    pypi
ncurses                   6.4                  h313beb8_0
networkx                  3.1                      pypi_0    pypi
numba                     0.57.0                   pypi_0    pypi
numpy                     1.24.3                   pypi_0    pypi
opencv-python-headless    4.7.0.72                 pypi_0    pypi
openssl                   1.1.1t               h1a28f6b_0
pip                       23.0.1          py310hca03da5_0
python                    3.10.11              hc0d8a6c_2
readline                  8.2                  h1a28f6b_0
roifile                   2023.5.12                pypi_0    pypi
scipy                     1.10.1                   pypi_0    pypi
setuptools                67.8.0          py310hca03da5_0
sqlite                    3.41.2               h80987f9_0
sympy                     1.12                     pypi_0    pypi
tifffile                  2023.4.12                pypi_0    pypi
tk                        8.6.12               hb8d0fd4_0
torch                     2.0.1                    pypi_0    pypi
tqdm                      4.65.0                   pypi_0    pypi
typing-extensions         4.6.2                    pypi_0    pypi
tzdata                    2023c                h04d1e81_0
wheel                     0.38.4          py310hca03da5_0
xz                        5.4.2                h80987f9_0
zlib                      1.2.13               h5a0b063_0
Unfortunately I struggle with all things coding and this is the best I can do. Any help would be much appreciated.

Hi,
Please share the details of your system. What OS are you working on? Are you following the conda install instructions in our docs?

Hello,
Yes, I am following the doc.
My OS is MacOS Ventura 13.3.1
Thank you

On Jun 1, 2023, at 11:53 AM, Michael Rariden @.***> wrote:
Hi,
Please share the details of your system. What OS are you working on? Are you following the conda install instructions in our docs?
—
Reply to this email directly, view it on GitHub https://github.com/MouseLand/cellpose/issues/722#issuecomment-1572530211, or unsubscribe https://github.com/notifications/unsubscribe-auth/BAH6BHYRBCRCRIDKAWOUY63XJDJLPANCNFSM6AAAAAAYXGRFE4.
You are receiving this because you authored the thread.

Hi NWood4,
Sorry for the delay. Were you able to install successfully? Based on your error it may be that your conda setup is incorrect. Are there any other outputs that we can use to debug your install?

Hi there, Thankfully I got it installed and working!Thank you!On Aug 24, 2023, at 19:51, Michael Rariden @.***> wrote:
Hi NWood4,
Sorry for the delay. Were you able to install successfully? Based on your error it may be that your conda setup is incorrect. Are there any other outputs that we can use to debug your install?
—Reply to this email directly, view it on GitHub, or unsubscribe.You are receiving this because you authored the thread.Message ID: @.***>


text:
Plugins

I would like to propose a plugin system for Moya.
MoyaProvider can now be initialized with a set of Plugins.  A Plugin receives callbacks to perform side effects wherever a request is sent or received.
For example, a plugin may be used to

log network requests
hide and show a network avtivity indicator
inject additional information into a request

This kind of tackles #144 as well, as the number of additional closures is now much lower and can be initialized with an arbitrary number of plugins
I have also added plugins for the existing CredentialClosure and NetworkActivityClosure to make it easy for everyone to adopt this change. Maybe we should also try to build a plugin from the Logger in #235?
Would love to get some feedback on the idea or how to make this even more generic for everyone to use (I'm not super happy with the subclassing approach). :heart:

Actually, this should be merged into develop.
Continued in #238.

repo: Moya/Moya

license: mit

license_source: bigquery


text:
cant cmpile

error: use of ‘auto’ in lambda parameter declaration only available with ‘-std=c++14’ or ‘-std=gnu++14’

waht linux are you using? seems like you need newer cpp. what compiler are you using?

authors: AVert Mozer

repo: Mozer/talk-llama-fast


text:
Win Banner Appears on Mobile Devices

Win Banner Appears on Mobile Devices

https://github.com/Mr-MikeRoss/Color-Racer/pull/60

repo: Mr-MikeRoss/Color-Racer


text:
Readme update

Is your feature request related to a problem? Please describe.

Read me update, adding sponsor links
Describe the solution you'd like

Describe alternatives you've considered

Additional context

PR #81

repo: MrGreensWorkshop/MrGreen-JekyllTheme


text:
html2pdf wordspacing problem and an error so open to Adobe Reader

Hello
I am currently encountering a problem when generating my PDF via the script html2Pdf provided in version 1.3.4. Indeed, html2pdf generates a concise space between words as if the text was jutified. Has anyone ever encountered this problem and is there a solution to it?
Looking forward to reviewing

Well, I give up! The script correctly generates (except this dark history of wordspacing) the pdf in an iframe (Chrome and firefox) but generates an error when opening the PDF in Adobe Reader! I think Html2Pdf is not the solution!
To try to understand, I reduced my code to a simple text without HTML tag and I am left with a single word to display
I.V.A.: xxx est assujetti à la T.V.A. Délai de règlement : à réception de la facture.
I do not understand what's going on and I'm wasting time trying to do things unsuccessfully.

Hello
After many attempts, my wordspaccing problem was due to the unsupported font (Helvetica).
For the opening problem in Adobe, I came across this issue  and my problem was corrected by applying the fix

repo: MrRio/jsPDF


text:
Feature requests: Getting the current x/y position while creating a pdf

Feature requests,
i like to have a function that returns the x and y coordinates which gives the right bottom position of the last added element.
This would help me add text below a table for instance

Partly duplicate of #2926.

This feature would be really helpful. I find it very difficult to render a large dynamic PDF with this Library. As you have no way of controlling where content is rendered with dynamic html-content. I get a lot of data and turn it to html snippets via handlebars. Converting these snippets into a nicely layoutet pdf is almost impossible.

authors: HackbrettXXX a-somesan nielsnl68


text:
MudListItem: Replace Avatar and AvatarClass with AvatarContent

Description
The Avatar parameter was just an icon with a circle background nothing more. It didn't live up to the expectation of an actual avatar. By removing it and making AvatarContent a renderfragment it is now much more potent at the cost of brevity in the markup which I hope isn't that big of an issue.
Before:

After:

How Has This Been Tested?

Types of changes

[ ] Bug fix (non-breaking change which fixes an issue)
[ ] New feature (non-breaking change which adds functionality)
[x] Breaking change (fix or feature that would cause existing functionality to not work as expected)

Checklist

[x] The PR is submitted to the correct branch (dev).
[x] My code follows the code style of this project.
[ ] I've added relevant tests.

Added to v7.0.0 Migration Guide #8447

repo: MudBlazor/MudBlazor


text:
Divide the menu between hot and cold beverages

The menu currently has a very general mention of drinks, no real separation between hot and cold beverages, or even the option to add additional flavors to them
Assign this issue to me

@karanharshey assigned


text:
Make Regular Member Help

Eliminates typo, slightly tightens wording of help text for Make Regular Member

coverage: 93.467%. remained the same
when pulling b0e87b03fbee3f5ec348a4c22950142830e521d1 on 2494-describe-make-regular-member
into 4d95d2c18e31be48bb725a10b501f0c38bfda75d on main.

authors: JoeCohen coveralls

repo: MushroomObserver/mushroom-observer


text:
Remove conferences

Removes all code and tables related to Conferences.
It's unused, but must be maintained if we keep it. (E.g., in Rails updates, we'll need, at a minimum, to deal with routes.)  Because of impending update to Rails 5.0, I decided to ditch it. I think cost of maintainance > hypothetical future usefulness.
Also see following email chain:

On Sat, Aug 12, 2017 at 2:14 PM, Joseph Cohen jdcohenesq@gmail.com wrote:
Nathan:
Could I delete the Conference code (controller, models, tests, views)?

Nathan Wilson to me, Jason Aug 13
I guess. Doesn't seem worth worrying about and some day it might be useful, but I don't really care.
-Nathan

I will let this PR sit until Monday or Tuesday. If there are no objections, I'll merge it into master (and ror-5, which catalyzed this PR).


text:
Add Password Strength Validation to Signup Form

This pull request addresses the issue of weak password validation in the SignupForm component.
The implementation includes a validation function isPasswordValid() to check if the password meets the specified criteria before submitting the form. If the password does not meet the requirements, an appropriate error message is displayed using the toast library.
This pull request introduces password strength validation to ensure that users create strong passwords meeting the following criteria:
At least 8 characters long
Contains at least one uppercase letter
Contains at least one lowercase letter
Contains at least one number
Contains at least one special character
@Muskansahuincredible please review this pull request.please let me know any changes required.Thank you ,once again for assigning me this issue

@techmannih can you please label level to this pull request.


text:
Updated footer copy

Updated footer copy to match MyCryptoHQ/MyCrypto description at Jordans request

[ ] Jordan to review build

LGTM 👍
ty @409H

repo: MyCryptoHQ/landing


text:
css-like theme classes assignable to UI elements

Is your feature request related to a problem? Please describe.
Currently I have to describe the theme for each element individually(using prototypes) or using the class / default descriptor. In a GUI with large amount of differently themed widgets it gets cumbersome.
Describe the solution you'd like
I'd like to be able to assign multiple theme css-like "classes" directly to a UI element.
Describe alternatives you've considered
The same could be achieved by allowing multiple prototypes and using them to style the element with an individual theme (via object_id), but it would require an unnecessary step.
This may be a bad place to ask, but it is somewhat related - is it intentional that multiple UI elements can have the same object_id?

Had a start on implementing this, but would like to hear feedback in case I'm doing it all wrong.

It seems good to me.
The only thing I see that you could perhaps think about is the naming - since it's possible to pass both an id of the object and of the class perhaps the parameter and the named tuple would be better called something like theming id to avoid confusion?

I did think about that, but it would break the code of anyone using the current 'object_id' parameter as a keyword, so I thought I'd leave it for compatibility reasons.

You could always add a new parameter, but keep object_id as is to preserve compatibility. A deprecation warning should be enough to make people switch over to the new one, so that object_id could be removed in some future version..

Been pondering this again today (while doing the washing up).
It's quite tricky to manage deprecation of keyword parameters in python - especially the way I began with this project where parameters are, in the vast majority, optionally keyword or positional. If I add a new one on the end with a new name, and then later remove one from further up the order then the very act of removing one will also affect everyone using positional parameters to create elements and not in an immediately obvious way.
The other difficulty is that the IDs are used mostly for theming, but also optionally for events (because it seemed pointless having two types of object ID) so naming them theming IDs doesn't cover their dual role in the GUI.

I have to say I haven't thought about it this way - I guess deprecation is harder to handle than I thought. Now I understand why they added keyword only arguments in Python 3.8.

Yep, I'm hoping to start using them more in the future for option type stuff - though I think they are actually valid in all versions of python 3? Just not Python 2.

authors: MyreMylar ylenard


text:
Explorer: list of transactions interacting with the smart contracts

On Package page, show a list of transactions that call the entry functions (i.e. public (script)) defined in the package.
The fullnode needs to support indexing transactions by Package, Module, and Function.

@bwann52 - could you spec this out a bit more? What would this look like (not from a UI standpoint, but more about what the data is.) The current description is a bit vague in my mind.

Hey @mystenmark , is there any update on this issue?

I can have a look at this, later this week.

repo: MystenLabs/sui


text:
"sui start" panic (main branch 1.29)

Steps to Reproduce Issue
(1) Build sui binary from main branch (currently 1.29.0-f6f2584c5072 )
(2) env RUST_LOG=error sui start --network.config /home/olet/suibase/workdirs/localnet/config/network.yaml
network.yaml is attached ( network.yaml.txt )
Expected Result
"sui start" to normally start and keep running.
Actual Result
A panic

This problem is not happening with devnet branch 1.28.1 (and many older versions).
The error message shows a path that includes the file "network.yaml" which is not a directory (it is the file specified with --network-config), could this be the problem?
System Information
ubuntu, rustc 1.75
Tests with 1.29 is my own cargo build, while 1.28.1 was the precompiled Mysten binaries ( sui-devnet-v1.28.1-ubuntu-x86_64.tgz )

Thanks for reporting this. I've made some changes to sui start that might be causing this. I'll look into it now, but would help me to know:

where is your genesis blob stored (folder relative to localnet/config/network.yaml). I assume it is in home/olet/suibase/workdirs/localnet
where are the previous DBs stored: are they in the home/olet/suibase/workdirs/localnet? Do you see a full_node_db there?

When testing, my script delete and regenerate "everything" from scratch. So in the case of testing 1.29, it does not reach the point of creating full_node_db.
(1) The blob is in /home/olet/suibase/workdirs/localnet/config

(2) Will follow up in a few minutes about where full_node_db is created when testing with 1.28.1

I see, in this case, I think you might just get away with passing the folder instead of the actual network file
sui start --network.config ~/suibase/workdirs/localnet/config.

But I will fix it asap so that it accepts the network.yaml config file as it used to.

Thanks. No rush to fix for me... as long it works as used to in devnet/testnet branch :smile:
Just FYI, specifying just the directory did not work:

Going on a tangent about full_node_db (can create another issue as needed?)
With 1.28.1, it is created in ~/.sui/sui_config ( it might have always work that way and never noticed).
This is inconsistent with all the rest being created in ~/suibase/workdirs/localnet/config

Thanks for the detailed info! I'll try to put up a fix today.

More info related to full_node_db:

thanks @mario4tier. I am not fully sure how suibase does stuff, particularly, why it creates another config-default folder to store the DBs.
I have a PR up that should fix the issue you have. If you have a chance to build the sui binary from that branch https://github.com/MystenLabs/sui/pull/18469 and try it locally, let me know if you still encounter issues.
Thanks for your patience here!

It works (tested with latest 1.29 branch + changes to sui_command.rs)
About DBs location
One key design choice for Suibase is to not interfere with the Mysten Labs official installation. So the Suibase localnet should not depend or even "touch" ~/.sui
That design allows to support a distinct set of binaries/repos/config/keystore for each network. The users/app can then operate localnet/devnet/testnet/mainnet concurrently... there is no "switch env" for Suibase users.
To keep things clean, all files related to a network are kept in a single place (e.g. ~/suibase/workdirs/testnet). full_node_db is the only exception right now...
I tried to modify the fullnode.yaml with an absolute path like done in network.yaml, but it did not work (still created in ~/.sui/sui_config ).
In short, ideally, Suibase would benefit from being able to specify the full_node_db path (but it is not breaking anything right now).


text:
Fix object lookup in gas computation

Description
@gdanezis suggested the change implemented here (if we got it right) which would fix the issue with gas computation and partly for conservation that is bugging us.
We change calls to get_object to use get_object_by_key and remove panic for version checks.
We have the version already at the point we call so we can use it and be more precise and correct.
The change ended up being more intrusive that we wanted because of traits implementation.
We would love more eyes on this to make sure things are correct
Test Plan
Existing tests

If your changes are not user-facing and not a breaking change, you can skip the following section. Otherwise, please indicate what changed, and then add to the Release Notes section as highlighted during the release process.
Type of Change (Check all that apply)

[ ] user-visible impact
[ ] breaking change for a client SDKs
[ ] breaking change for FNs (FN binary must upgrade)
[ ] breaking change for validators or node operators (must upgrade binaries)
[ ] breaking change for on-chain data layout
[ ] necessitate either a data wipe or data migration

Release notes

Assuming we add back the panics/invariant violations, there should be no behavior change here other than not crashing in some cases where we previously crashed.

Isn't his a behavior change? By the way, crash is not the right word here because previously we would return ExecutionError instead of panic, but now we may execute successfully. This could lead to a fork for sure.

As @lxfind said, this could immediately cause a fork if we change panic to execution error or vis versa

Got it + yes, good point

ok I'll look at this in the morning, not sure what all the comments are implying.
If anybody wants to take it and move forward I'd appreciate.

please take a look and let me know.
I have removed some of the changes because I had applied them to gas legacy which should be left alone.
I have gated the new checks behind a protocol change. I am gating at version 4, is that correct? should it be 3?
Left few comments on the feedback, please review

authors: bmwill dariorussi lxfind sblackshear


text:
Change Type of 'Order' From "String" To "Boolean"

hi. i'm jihwan from south korea.
while i making a Wallet with '@mysten/sui.js', i found a little problem.
whenever i used a function 'provider.getTransactionsForAddress()', i got error everytime.
the error was '{code: -32602, message: 'invalid type: string "Descending", expected a boolean at line 1 column 12'}'
so i cheched Sui Docs and Sui SDK source code, finally i got it what problem is.
the problem is 'Type of Ordeing object'
Sui Docs say " descending_order :  - query result ordering, default to false (ascending order), oldest record first."
but my sdk source is "export declare type Ordering = 'Ascending' | 'Descending';"
therefore that function not working.
finally i change to Type of Order Object.
please check my commit
thanks.

#6004 please check this error @oJshua @huitseeker @tfiala @palango

Hi @DevJihwan thanks for the PR and welcome to Sui :)
Which version of TS-SDK are you using? We have changed the ordering in getTransactionsForAddress to boolean a while ago.
https://github.com/MystenLabs/sui/blob/ef4a949f3d9b980461830bba908b72c8abbf1b77/sdk/typescript/src/providers/json-rpc-provider.ts#L481

authors: DevJihwan patrickkuo


text:
[checkpoints] Correctly read last checkpoint on epoch boundary.

This PR changes how last checkpoint is read on epoch boundary. Previously we relied on internal builder table, checkpoint_summary to read last checkpoint. This is not correct however, since on the checkpoint boundary this might not be updated fully, also this table will be empty if new validator joins in the epoch.
In this PR we change it:
(1) checkpoint_summary is renamed and move to epoch store
(2) Across epoch boundary certified_checkpoint table is used to get last checkpoint of previous epoch.

Do you have a theory why we haven't seen any problem from private testnet yet?

Do you have a theory why we haven't seen any problem from private testnet yet?

My guess is Narwhal instances live long enough so that every validator receives all information through it, in which case this issue does not surface

authors: andll lxfind


text:
🛑 OARC Cloudlog (M0OUK) is down

In 6b79ee9, OARC Cloudlog (M0OUK) (https://cloudlog.oarc.uk/M0OUK/) was down:

HTTP code: 500
Response time: 7437 ms

Resolved: OARC Cloudlog (M0OUK) is back up in 5c4b7ed after 5 minutes.

repo: MysterAitch/oarc-monitor


text:
Define User Journeys

💡 Description

Define set of user journeys for our community.

Prioritized five journeys -
Have begun to describe the workflow in a what user see/what user does framework
https://www.figma.com/file/wzRO1Hr3bkykHVxOpVLQSX/User-Journeys?node-id=0%3A1

authors: edwardbarraza jordanpadams


text:
Implement Initial Search Results Page and Associated Components

💡 Description

📆 01/2024 status: Deferring these landing pages to next build. This website delivery spans several builds, so no impact on delivery. No review from SWG needed.

New designs expected for product types.

Merged in https://github.com/NASA-PDS/portal-wp/pull/20

repo: NASA-PDS/portal-wp-tasks


text:
Externalise functions which provide hmac/md5/crc32 functions

into a separate set of utils.
This allows us to provide custom implementation of these functions if libz or openssl is unavailable (i.e. embedded)

Coverage increased (+0.09%) to 82.594% when pulling 8fa59f96cc5470a46c3a646bfc4a8614f29307d0 on imont:external-deps into 2caeda2a524fc6d0da0295756a18ea08b6bf3bc4 on NATTools:master.

authors: SStorm coveralls

repo: NATTools/stunlib


text:
Bugfix: wind boundary

TYPE: bug fix
KEYWORDS: wind field, boundary conditions
SOURCE: Soren Rasmussen, NCAR
DESCRIPTION OF CHANGES: Boundary conditions of the wind fields causes significant answer changes. The calculation of the the halo region bounds was slightly off for the wind fields.
ISSUE: The GitHub Issue that this PR addresses. For issue number 123, it would
be Fixes #123
Checklist

[ ] Closes issue #xxxx (An issue must exist or be created to be closed. The
issue describes and documents the problem and general solution, the PR
describes the technical details of the solution.)
[ ] Tests added (unit tests and/or regression/integration tests)
[X] Backwards compatible
[ ] Requires new files? If so, how to generate them.
[ ] Fully documented

The following are plots displaying the difference between a run of the develop branch (labeled as upstream) with one image and the upstream with 36 images. Additionally the difference of the upstream with one image vs the Wind PR with 36 images. The upstream branch run with 1 image serves as the baseline and presumably "correct" run.
The equations used are listed below. The max along the level axis is used, after the absolute value function has been applied so that any negative values are also considered for the max function.
abs((ds1.var[t,:,:,:] - ds2.var[t,:,:,:])).max(axis=0)

1 image upstream vs 36 image upstream

1 image upstream vs 36 image wind PR

(abs((ds1.var[t,:,:,:] - ds2.var[t,:,:,:])/ds1.var[t,:,:,:])).max(axis=0)

1 image upstream vs 36 image upstream

1 image upstream vs 36 image wind PR

Ok, I think what happened was my “upstream base case” directory was accidentally overwritten with “wind_fix base case” so I thought it was working. Here are current results

The first is upstream 1 vs 36 images

The second is wind_fix 1 vs 36 images, with halo of 1 for both

The third is wind_fix 1 vs 36 images with halo of 3 for the 36 images

The fourths is upstream 1 image vs wind_fix 1 image

Ran a test and the difference in upstream 1 image vs wind_fix 1 image is due to the corr_factor changes. The PR looks good to go, these runs were done with a single wind iteration, rather than the default 100. Will run tests again with 50 and 100 wind iterations to see the results

change map = (old-new) / old
Fractional change in precipitation over a ~6month period changes are <5%, mostly <1%, with the "biggest" changes being a decrease on top of mountains, and an increase in valleys (that is a good thing).  Other changes seem randomly distributed.

authors: gutmann scrasmussen

repo: NCAR/icar


text:
Fix Nuget Readme rendering

Describe the bug
As seen on https://www.nuget.org/packages/NCronJob#readme-body-tab, the html trickery doesn't play well with nuger.org markdown rendering engine.

Yeah we could have a separate README.md just for nuget - not sure why <h1> and stuff doesn't work.
The img src should probably use the github.com/NcronJob-Dev/... URL instead of a relative one.

Basically we are blocked by: https://github.com/NuGet/NuGetGallery/issues/8644

authors: linkdotnet nulltoken

repo: NCronJob-Dev/NCronJob


text:
auto close after posting

This PR is not supposed to be merged, but is just an example of how to rely on Near.View cache invalidation implemented in this PR to the VM, to detect when the editor can be closed after creating a post.
https://youtu.be/xbxX3DVHFno
@Megha-Dev-19

hey @petersalomonsen, thanks for the PR
I have incorporated the logic here

repo: NEAR-DevHub/neardevhub-bos


text:
Team member with permission owner cannot delete datasets

Describe the bug
I have created a team and invited someone. This person got the right "owner" and I would expect this member to have the same rights as the creator of the team. If this member tries to delete a project, this person gets an 403 This Action is Unothorized
Interestingly, the owner has the right can read and/or update project, study and dataset information and the Collaborator has the same description.
What is the difference between the two? BTW: Project/study/dataset -> Project/sample/spectrum/a.
My use case having someone with the same rights as the creator is to curate data on behalf of someone. I created the team, a member joins, uploads data, I curate the data and the member publishes it. After that, I leave the team as  a creator but the joined other member with permissions owner may continue in using this team.
Expected behavior
Member added to team as owner has the same permission level as the person who created a team.
Best,
Tillmann

Closing this issue for now. Please reopen if the issue still persists

I can access the project settings of a project in Team IPB Halle now:

However, I cannot delete a project..

..although I have the permission level "owner":


text:
Prevent teams to be deleted unless projects associated with the team are deleted

We should not let the user be able to delete their team if the team has projects associated with it.
Resolves null team issue
Attempt to read property "personal_team" on null - Projects

Duplicate #101

I am not allowed to delete a team that has projects associated with it.

But I was also not able to delete it after deleting the projects

Updated the message to be more clear. For recently deleted projects, the user has to wait for a cool-off of 30 days for the project to be deleted permanently.


text:
InputNumber does not keep cursor position on editing with formatter

Reproduction link
https://stackblitz.com/edit/ng-zorro-antd-start-a2uaty
Steps to reproduce

Default value is 100
Click before the '1' to add the number '2' : current value is now 2100

What is expected?
The cursor should be between '2' and '1'
What is actually happening?
The cursor is now at the end of the value, after the last '0'

Environment
Info

ng-zorro-antd
8.5.2

Browser
Chrome version 79.0.3945.88

Any plan for a fix ?

Is there any plans for a fix on this :(

Potentially related: With a formatter, you cannot type a decimal, regardless of any other option (parser, min/max, precision, etc).

authors: AGYmag celluj34 dsouzadyn sebcam

repo: NG-ZORRO/ng-zorro-antd


text:
[ISSUE] Repeated taxon numbers

Template for isues/tickets in DigiApp
What is the issue ?
There is an issue with the NHMA taxonomy and taxonnumbers – there are repeated taxon
numbers, which should not happen (e.g., number 16 appears twice in the database).
This is a huge issue and I don't fully understand it myself, needs discussion

Why is it needed/relevant ?
# Explain the need, relevance.
# Give scenario(s) of why and when this could be relevant.

Estimate level of effort required.
# easy
# difficult
# hard

What is the expected acceptable result.
#  How to approach it?
#  Give a clear approach/potential solution on how to resolve it.
#  What steps would be required to do this ?
#  It might also be an idea to put some pseudocode if relevant.

What could be the challenges ?
Is there a potential risk to this.
Could it affect another part of the project.

What test are required ?
New tests/Could include reference to the existing test
What documentation required?
Could refer to existing documentation and changes in relevant doc files.
Remarks

In the case of taxon number 16, these seems to be synonyms: https://www.gbif.org/species/9578719

Synonyms do not in themselves constitute an actual issue, since these would be sorted in Specify or in any case GBIF, and both accepted names and synonyms should be available. However, if the app consistently chooses the synonym to populate the taxon fields instead of the accepted name, that would need to be mitigated somehow.

After conferring with @bhsi-snm and then @PipBrewer the easiest solution is going back to the question why the taxon numbers are repeated in the first place. This seems like a mismatch during import.

Reduced the number of re-used taxon numbers to 130, but there are still some cases where a single taxon number actually was assigned to multiple taxa:

Solution could be to integrate the secondary (serial?) number into the taxon number and advise digitizers to be mindful of and use that one. However, it's unclear whether this would work in practice.

Note: Fix is invalid, because some of the species were assigned to new genera so the full names don't match. I will need to redo this

Note: After close investigation the previous was actually correct in removing the taxon number from certain species (like Acalypta gracilis) and that was not because the species were assigned to new genera, but rather because the file I was supplied with processed taxon-sortnr pairs had incorrectly assigned these taxon numbers to those species in question.
However, a different problem was discovered where there was a limited number of cases where the genus name was not added to the full name, which lead to the SQL script (MassDigitizer/sql/specify/UpdateSetTaxonNumber.sql) failing to add those taxon numbers to the taxa in question, since it relied on full name (binomial). The latter file is now fixed by having redone the binomial full name in those cases.
Then the script MassDigitizer/sql/ExtractTaxonNames.sql could be run again resulting in a now correct MassDigitizer/sql/editions/NHMA/entomology/Species-Batch1.sql

authors: FedorSteeman bhsi-snm

repo: NHMDenmark/Mass-Digitizer


text:
Support for multiple manifests

Hi there! Thank you for this plugin :)
Is there a chance to add support for multiple manifests?
I have this structure of my _data/meta.js:
require('dotenv').config()

module.exports = {
  env: process.env.NODE_ENV,
  url: process.env.URL || 'http://localhost:8080',
  en: {
    title: 'title',
    description: 'description',
  },
  ru: {
    title: 'тайтл',
    description: 'описание',
  },
}

And with this structure, I don't see any way to provide metadata to manifestData object to generate multiple manifests and associate them with the corresponding templates. Much appreciated for any help!

Came up with this solution as a workaround.
// .eleventy.js

...
eleventyConfig.addPlugin(faviconsPlugin, {
  generateManifest: false,
})

// _layouts/manifest.njk

{
  "lang": "{{ lang }}",
  "dir": "{{ dir or 'ltr' }}",
  "short_name": "{{ meta[lang].title }}",
  "name": "{{ meta[lang].title }}",
  "description": "{{ meta[lang].description }}",
  "orientation": "{{ 'any' }}",
  "scope": "{{ '/' }}",
  "start_url": "{{ '/' }}",
  "theme_color": "{{ '#090d11' }}",
  "background_color": "{{ '#090d11' }}",
  "display": "{{ 'standalone' }}",
  // copy from plugin once
  "icons": [
      { "src": "/icon-192.png", "type": "image/png", "sizes": "192x192" },
      { "src": "/icon-512.png", "type": "image/png", "sizes": "512x512" }
   ]
}

// _layouts/base.njk

...

// needs eleventy i18n plugin for locale url filter
<link rel="manifest" href="{{ "/site.webmanifest" | locale_url }}"">

// make for each lang
// example: en/manifest.njk

---
permalink: /{{ lang }}/site.webmanifest
layout: manifest
eleventyExcludeFromCollections: true
---

repo: NJAldwin/eleventy-plugin-gen-favicons


text:
Jhove 1.29

Dobrý den,
na wiki-Instalace se píše, že minimální podporovaná verze JHOVE je verze 1.29. Tu se mi ale nedaří nikde nalézt. Na GitHubu k JHOVE jsem narazil jen na verzi 1.28 a pre-release verzi 1.30.
Děkuji

Testoval jsem v CLI verzi KV 2.4.1, že JHOVE 1.28 funguje. Patrně se tedy jedná o překlep v dokumentaci.
@rzeh4n Prosím, mohl byste potvrdit, že se jedná o překlep?

Ano, je to verze 1.28. Doplním na https://github.com/NLCR/komplexni-validator/wiki/Instalace

repo: NLCR/komplexni-validator


text:
Socket timed out for Slurm adaptor

I've got the following error after submitting a couple of jobs to the queue. BTW the error occurs occasionally during builds on Travis CI.
slurm adaptor: Could not run command "scontrol" with stdin "null" arguments "[show, config]" at "nl.esciencecenter.xenon.adaptors.schedulers.JobQueueScheduler@142bb68f". Exit code = 1 Output:  Error output: slurm_load_ctl_conf error: Socket timed out on send/recv operation
Error submitting jobscript (exit code 1):
00:10:14.463 [main] DEBUG nl.esciencecenter.xenon.adaptors.schedulers.ScriptingScheduler - creating sub scheduler for slurm adaptor at local://
00:10:14.471 [main] DEBUG nl.esciencecenter.xenon.adaptors.schedulers.JobQueueScheduler - Creating JobQueueScheduler for Adaptor local with multiQThreads: 4 and pollingDelay: 1000
00:10:14.473 [main] DEBUG nl.esciencecenter.xenon.adaptors.schedulers.JobQueueScheduler - local: Submitting job
00:10:14.473 [main] DEBUG nl.esciencecenter.xenon.adaptors.schedulers.JobQueueScheduler - local: Created Job local-0
00:10:14.475 [main] DEBUG nl.esciencecenter.xenon.adaptors.schedulers.JobQueueScheduler - local: Submitting job to queue unlimited
00:10:14.475 [main] DEBUG nl.esciencecenter.xenon.adaptors.schedulers.JobQueueScheduler - local: Waiting for interactive job to start.
00:10:16.487 [main] DEBUG nl.esciencecenter.xenon.adaptors.schedulers.JobQueueScheduler - local: getJobStatus for job local-0
00:10:16.488 [main] DEBUG nl.esciencecenter.xenon.adaptors.schedulers.JobQueueScheduler - local: findJob for job local-0
00:10:16.488 [main] DEBUG nl.esciencecenter.xenon.adaptors.schedulers.JobQueueScheduler - local: findJob for job local-0
00:10:16.488 [main] DEBUG nl.esciencecenter.xenon.adaptors.schedulers.JobQueueScheduler - local: findJob for job local-0
00:10:16.488 [main] DEBUG nl.esciencecenter.xenon.adaptors.schedulers.JobQueueScheduler - local: findJob for job local-0
00:10:16.488 [main] DEBUG nl.esciencecenter.xenon.adaptors.schedulers.JobQueueScheduler - local: cleanupJob for job local-0
00:10:16.488 [main] DEBUG nl.esciencecenter.xenon.adaptors.schedulers.JobQueueScheduler - local: cleanupJob for job local-0
00:10:16.488 [main] DEBUG nl.esciencecenter.xenon.adaptors.schedulers.JobQueueScheduler - local: cleanupJob for job local-0
00:10:16.489 [main] DEBUG nl.esciencecenter.xenon.adaptors.schedulers.RemoteCommandRunner - CommandRunner took 2016 ms, executable = scontrol, arguments = [show, config], exitcode = 1, stdout:
stderr:
slurm_load_ctl_conf error: Socket timed out on send/recv operation

Interestingly, after restarting the Travis build this error disappeared.

The socket timeout is actually produced by slurm itself, Xenon just reports is back.
Apparently there is some race condition that occurs every now and then where a part slurm is not yet running? (or has already disappeared).

authors: arnikz jmaassen

repo: NLeSC/xenon-cli


text:
Disable apk caching to reduce image size

Avoid storing ~1.4M of /var/cache/apk/ files in the image which are not needed. Pkg installation still works without them.

Cc: @wk

Makes perfect sense to me (can also be done at the clean-up stage as apk cache clean as well).

repo: NLnetLabs/routinator


text:
upgrade Csproj tests, remove old nuget restore

fixes #2

Unfortunately all current tests has  [Ignore("Ignore")] :(

anyway, this works:


text:
Create LICENSE.md

BSD 3-clause license added

changing the suggested MIT in #35 to BSD 3-clause as suggested.

repo: NOAA-CEFI-Portal/cefi-portal


text:
Intel compilers: add Intel's cmake module

Intel compilers: add Intel's cmake module
Additions
-Intel compilers: add Intel's cmake module
Removals

Changes

Testing

Compiled and tested with OneAPI 2022.3

Screenshots
Notes

Todos

Checklist

[X] PR has an informative and human-readable title
[X] Changes are limited to a single goal (no scope creep)
[X] Code can be automatically merged (no conflicts)
[X] Code follows project standards (link if applicable)
[X] Passes all existing automated tests
[X] Any change in functionality is tested
[X] New functions are documented (with a description, list of inputs, and expected output)
[X] Placeholder code is flagged / future todos are captured in comments
[X] Visually tested in supported browsers and devices (see checklist below :point_down:)
[X] Project documentation has been updated (including the "Unreleased" section of the CHANGELOG)
[X] Reviewers requested with the Reviewers tool :arrow_right:

Testing checklist
Target Environment support

[X] Linux

Test failure Realization config path extern/sloth/test/data/sloth_realization.json not readable...does not compute.

repo: NOAA-OWP/SLoTH


text:
ZGRID, called by the scat2gridlaplace functions has workspace limited to 50000 pts

Reported by Ansley B Manke on 26 Aug 2008 18:10 UTC
Steve Guimond reported this:
use "/home/porter/ansley/ans_ferret/users/guimond/scat_laplace_dat.nc"
sh dat
currently SET data sets:
1> ./scat_laplace_dat.nc  (default)
name     title                             I         J         K         L
XX       XX                               1:960     1:367     ...       ...
YY       YY                               1:960     1:367     ...       ...
DBZ      DBZ                              1:960     1:367     ...       ...
let nxx = xsequence(xx)
let nyy = xsequence(yy)
let ndbz = xsequence(dbz)
def axis/x=-240:240:0.5 nx
def axis/y=-240:240:0.5 ny
let sgrid = scat2gridlaplace_xy(nxx,nyy,ndbz,x[gx=nx],y[gy=ny], 5., 5)
fill sgrid
Segmentation fault
The scat2gridlaplace functions call zgrid, which is under ppl/plotlib and is
also used in the PPLUS contouring code.  It declares two work arrays
zpij(50000),knxt(50000)

The data in this example has 960*367 = 352367 points so the code eventually
overwrites memory and causes the crash.

At least we should put in a test for exceeding the memory, and a useful error
message

or could make a version of zgrid to be called by the scat2gridlaplace
functions, that would be passed work arrays allocated at run time. Since these
functions were originally written as ef's we have the work-array-allocation
capability right there to use.

Migrated-From: http://dunkel.pmel.noaa.gov/trac/ferret/ticket/1590

Comment by ansley.b.manke on 27 Apr 2012 19:36 UTC
As suggested above in the report, the current versions of scat2gridlaplace* call a version of zgrid which use work arrays allocated in the external functions framework.

repo: NOAA-PMEL/Ferret

license: Unlicense


text:
subspan modulo fails for CONTOUR when region is set

Reported by andrew wittenberg on 28 Apr 2009 20:49 UTC
CONTOUR (or FILL) doesn't work properly with a subspan modulo axis, unlike SHADE.  And we get different CONTOUR results if the subspan modulo axis coordinates are supplied on the positive vs. the negative modulo branch.  (See plots.)
    NOAA/PMEL TMAP
    FERRET v6.196
    Linux(g77) 2.4.21-32 - 03/19/09
    28-Apr-09 16:38

yes? use coads_climatology
yes? let a = sst[save/clob/file=a.nc a
LISTing to file a.nc
yes? can var a
yes? use a
yes? set reg/x=125e:70w
yes? shade/x=-360:360 a
yes? cont/ov/x=-360:360 a
    NOAA/PMEL TMAP
    FERRET v6.196
    Linux(g77) 2.4.21-32 - 03/19/09
    28-Apr-09 16:35

yes? use coads_climatology
yes? let b = sst[x=-240:-76,y=-2:2@ave](x=120:284,y=-2:2@ave]
yes?)
yes? save/clob/file=a.nc b
LISTing to file b.nc
yes? can var b
yes? use b
yes? set reg/x=125e:70w
yes? shade/x=-360:360 b
yes? cont/ov/x=-360:360 b
Migrated-From: http://dunkel.pmel.noaa.gov/trac/ferret/ticket/1659

Comment by andrew.wittenberg on 28 Apr 2009 20:54 UTC
(Properly formatted version.)
CONTOUR (or FILL) doesn't work properly with a subspan modulo axis, unlike SHADE.  And we get different CONTOUR results if the subspan modulo axis coordinates are supplied on the positive vs. the negative modulo branch. (See plots.)
        NOAA/PMEL TMAP
        FERRET v6.196
        Linux(g77) 2.4.21-32 - 03/19/09
        28-Apr-09 16:38

yes? use coads_climatology
yes? let a = sst[save/clob/file=a.nc a
 LISTing to file a.nc
yes? can var a
yes? use a
yes? set reg/x=125e:70w
yes? shade/x=-360:360 a
yes? cont/ov/x=-360:360 a

        NOAA/PMEL TMAP
        FERRET v6.196
        Linux(g77) 2.4.21-32 - 03/19/09
        28-Apr-09 16:35

yes? use coads_climatology
yes? let b = sst[x=-240:-76,y=-2:2@ave](x=120:284,y=-2:2@ave]
yes?)
yes? save/clob/file=b.nc b
 LISTing to file b.nc
yes? can var b
yes? use b
yes? set reg/x=125e:70w
yes? shade/x=-360:360 b
yes? cont/ov/x=-360:360 b

Comment by andrew.wittenberg on 28 Apr 2009 20:55 UTC
See also #1487.

Comment by ansley.b.manke on 2 May 2009 03:13 UTC
in SHADE, the routine gets the horizontal and vertical coordinates from Ferret via a call to BOX_BOUNDS.  This is necessary because the shade command needs the box edges. It also has the effect that it gets the correct coordinates for the piece of the modulo axis when it is subspan modulo.
CONTOUR just computes the coordinates of the axis using delta-x (for regularly-spaced axes).  If instead I make a routine similar to BOX_BOUNDS, namely BOX_CENTERS, to get the coordinates using calls to TM_WORLD, then the correct coordinates are used. Fixes the plots regardless of how the subspan axis was defined.
(Fixed in ppl/plot/plotz.F and new routine box_centers.F)

Attachment from andrew.wittenberg on 28 Apr 2009 20:50 UTC
plot_positive.gif
REPLACE THIS TEXT WITH UPLOADED FILE ./attachments/TRAC_1659_GIT_931/plot_positive.gif

Attachment from andrew.wittenberg on 28 Apr 2009 20:50 UTC
plot_negative.gif
REPLACE THIS TEXT WITH UPLOADED FILE ./attachments/TRAC_1659_GIT_931/plot_negative.gif


text:
Code Generator providing incorrect sscapi.h - Matlab code generation fails

See discussion at https://sam.nrel.gov/forum/forum-sdk/4788-matlab-and-ssc-library.html

To fix, include the latest sscapi.h file into the x64 folder with the ssc.dll file in the distribution and then MATLAB will find the exported function.
For completeness, please add sscall('unload'); to the beginning of the generated Matlab code to ensure the correct ssc.dll is loaded; e.g.
clear
ssccall('unload');
ssccall('load');

repo: NREL/SAM


text:
Fix typo bug in System Sizing macros

Description
Change variable 'montn' to 'mount'
Note: this fix hasn't been tested
Type of change

[x] Bug fix (non-breaking change which fixes an issue)
[ ] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
[ ] This change requires a documentation update

Checklist:
If you have added a new compute module in a SSC pull request related to this one, be sure to check the Process Requirements.

[x] My code follows the style guidelines of this project
[ ] I have performed a self-review of my own code
[ ] I have commented my code, particularly in hard-to-understand areas
[ ] I have made corresponding changes to the documentation
[ ] My changes generate no new warnings
[ ] I have added tests that prove my fix is effective or that my feature works
[ ] New and existing unit tests pass locally with my changes
[ ] Any dependent changes have been merged and published in downstream modules
[ ] I have checked my code and corrected any misspellings

Please also fix the typo in .../macros/PV battery/System Sizing.lk

Other typo?

Please also fix the typo in .../macros/PV battery/System Sizing.lk

@cpaulgilman please clarify, I still don't see the typo you're asking me to fix. I've scoured the graphic to find it unsuccessfully. Can you point it out ?

Please also fix the typo in .../macros/PV battery/System Sizing.lk

@cpaulgilman please clarify, I still don't see the typo you're asking me to fix. I've scoured the graphic to find it unsuccessfully. Can you point it out ?

The typo is fixed in both copies of the script. Thank you.

authors: cpaulgilman luzpaz


text:
filter by road classes doesn't sync with the rtree input plugin

this issue imported from the internal repo
r-tree pre-processing maps coordinates to vertex ids on the map. if the user chooses a frontier model that restricts some links, the r-tree will not know of these restrictions. as a result, when the road class frontier model ignores TomTom's "restricted links" (road class 7), the denver beer run test case fails, as the origin or destination must have been pegged to vertices that are only connected via restricted links:
[frontier]
type = "road_class"
road_class_file = "data/tomtom_metro_denver_network/edges-road-class-enumerated.txt.gz"
valid_road_classes = ["1", "2", "3", "4", "5", "6"]  # ignore 7, "restricted road"

{
        "error": "no path exists between vertices 57209 and 356583",
        "request": {
            "destination_name": "Comrade Brewing Company",
            "destination_vertex": 356583,
            "destination_x": -104.9009913,
            "destination_y": 39.6757025,
            "energy_cost_coefficient": 0.0,
            "origin_name": "NREL",
            "origin_vertex": 57209,
            "origin_x": -105.1710052,
            "origin_y": 39.7402804
        }
    },

some possible solutions:

make an edge-oriented rtree that is built based on the DirectedGraph or otherwise knows the list of valid edges

may require passing the DirectedGraph or the SearchApp in the InputPlugin constructor

promote map matching algorithms from InputPlugin to its own component of SearchApp, where we can build it based on the combination of the frontier model and the directed graph
~modify the a star priority values so they are a tuple of (-int(cost * f), -road_class) where f is some factor such as 100~

no longer possible since we removed road class annotations from Edge
requires a lower-bound on cost values, which is practical if cost is utility-based
cast to integers in order to make an equality check possible
follows the road network hierarchy as a tie breaker, using higher-priority links when the costs are equivalent

the first solution may be best, but i'm finding it still may make my life complicated with my sub-project of creating a MEP tool using compass.
my problem is transit, but i think this applies to any mode which only has access to a subset of links. for a transit MEP search, i want to be able to 1) walk on road network links, 2) ride transit on transit links. i also want one instance of CompassApp to serve search for 4 travel modes - walk, bike, transit, drive - and so i want them all to share the same Graph instance and just have different traversal models. for this, the search algorithm needs

all edges for all modes to exist
some way for the traversal model to know which edges are valid
some way for the frontier model to know which edges are valid for a given traversal model
some way for the map matching rtree to know which edges are valid for a given traversal model

so, my problems:

frontier models in this case should change with the traversal model
rtree input plugin happens without having a way to know which edges are valid for the query

just thinking out loud here, trying to think about the options...

instead of having one CompassApp, have one for each mode and handle switching at the main.rs entry point, but sharing the Graph between each app
make an edge-based rtree, and share the &SearchApp as an argument to the InputPlugin
extend the vertex rtree with a "departure search" which runs from the nearest vertex to the nearest valid edge

but we would need an "arrival search" too

all of these solutions sound spooky to me right now. hopefully with some more iteration a better way forward will become more clear.

i like the edge rtree idea the best. working back from the implementation, the input plugin would have an rtree of edges, a Box<[T]> of length $|E|$ with road class information, and a set of valid road classes HashSet<T>. it would probably build a nearest neighbor iterator (or maybe this one so we can still have a distance tolerance) and take from the iterator until it finds an edge with a valid road class.
this means we would load the road class information twice (doubling the RAM for a large dataset) and depend on the user to make sure their input plugin and frontier configuration have matching road class parameters, both of which sound a bit sloppy.
i like the design we have, so maybe this sloppyness is worth it, but maybe there's something we could fix to make it possible to share these data dependencies.

wondering here, does the list of valid road classes come from

the input plugin configuration
the query
both? input plugin, but can be overridden by the query?

repo: NREL/routee-compass


text:
[Feature]: new page under devops for terraform

Is your feature request related to a problem? Please describe.
https://www.nsccbpit.tech/devops
create the page for the subject, connect it to the card.
On the page provide all information and resources related to the concerned topic such as tutorials, documentation, youtube channels, articles, courses etc.
Describe the solution you'd like
No response
Describe alternatives you've considered
No response
Additional context
No response

assigned to @Shruti700

resolved

repo: NSCC-BPIT/NSCC-BPIT-Website


text:
Feature/kho 175/user roles

Checklist

[X] I have performed a self-review of my code
[X] I have reached out to another developer to review my code
[X] New and existing unit tests pass locally with my changes
[X] All Lint and CI checks are passing

Pressing the browser back button in the assignment creation flow should have the same functionality as pressing your custom "previous" button imo

There should also be a loading state when clicking "finish" in the assignment creation flow

can't accept assignment still:
"api error: 500 GitHub API Request Error: api error: 500 GitHub API Request Error: POST https://api.github.com/repos/NUSpecialProjects/NUSpecialProjects-Kennys Coding Classroom-test/forks: 404 Not Found []"
looks like an issue with the urlencoding of "-"

authors: kennybc ntietje1 sebytremblay


text:
Pin pyarrow version for integration tests

Pin pyarrow version for integration tests.
The pip install 'feast<0.20' command is installing the latest version of pyarrow (currently 10.0.1). This is incompatibile with the current version of cudf.
Follow-up
The container we're testing with already has pyarrow installed. So a follow-up action would be to figure out why the existing pyarrow version is not being detected and take any actions required for this to be found.

import pyarrow; pyarrow.__version__ reports 8.0.0.

However, pip show pyarrow doesn't report anything.
Suggesting that the pyarrow installation is incomplete (missing the dist-info directory)

rerun tests

This error about no such file while trying to save the merlin schema when the model is saved is because keras uses the tf.io in-memory filesystem which I think is a tensorflow io feature (I've not seen ram:// used outside of this context at least) when trying to pickle a model. And to use this RAM filesystem, you can't use regular python file io functionality it seems. We'll need to use tf.io functions to write things into this in-memory filesystem.
This looks like it's been replaced in TF 2.11 by a regular regular temporary directory on disk. However, since we currently aim to support versions back to TF 2.8, will need to handle both cases now.
The reason this has only appeared now? Until recently we weren't testing the ability to pickle a TF Merlin Model.   The recent change in systems to use the executor triggered this to be checked now https://github.com/NVIDIA-Merlin/systems/pull/255 since it relies on cloudpickle to save the model artifact.

This PR on models https://github.com/NVIDIA-Merlin/models/pull/930 should fix the error we're getting from the notebook test when trying to serialize the model

rerun tests

rerun tests

repo: NVIDIA-Merlin/Merlin


text:
[BUG] BinaryClassificationTask prediction does not return one score per session with summary_type='mean'

Bug description
When we train a BinaryClassificationTask and then do
prediction = trainer.predict(eval_paths[0])
prediction

this does not return prediction scores.
In addition, we are able to set  trainer.args.predict_top_k, but we should not be able to do that for BC Task, since this is particularly designed for NextItem Prediction task.
Steps/Code to reproduce bug
Expected behavior
we should be getting a probability score per session.
Environment details

Transformers4Rec version:
Platform:
Python version:
Huggingface Transformers version:
PyTorch version (GPU?):
Tensorflow version (GPU?):

Additional context
using merlin-pytorch:22.12 with the latest main branches pulled.

closing since https://github.com/NVIDIA-Merlin/Transformers4Rec/pull/641 fixing the bug.


text:
[BUG] Weight-tying does not work due to emb_dim mismatch because dim  arg does not work properly in Embeddings func

Bug description
I get the following error when I want to apply weight-tying in session-based task with XLNET architecture. The reason of that when we set dim as a custom embedding dimension (or a custom dictionary)  it does not apply this. It still tries to apply heuristic approach and calculate emd dim from cardinality, therefore this creates a mistmatch.
---------------------------------------------------------------------------
---------------------------------------------------------------------------
InvalidArgumentError                      Traceback (most recent call last)
Cell In [21], line 39
     35 optimizer = tf.keras.optimizers.Adam(
     36     learning_rate=0.005
     37 )
     38 model.compile(run_eagerly=False, optimizer=optimizer)
---> 39 model.fit(loader, batch_size=1024, epochs=5)

File /usr/local/lib/python3.8/dist-packages/merlin/models/tf/models/base.py:899, in BaseModel.fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing, train_metrics_steps, pre, **kwargs)
    896     self._reset_compile_cache()
    897     self.train_pre = pre
--> 899 out = super().fit(**fit_kwargs)
    901 if pre:
    902     del self.train_pre

File /usr/local/lib/python3.8/dist-packages/keras/utils/traceback_utils.py:67, in filter_traceback.<locals>.error_handler(*args, **kwargs)
     65 except Exception as e:  # pylint: disable=broad-except
     66   filtered_tb = _process_traceback_frames(e.__traceback__)
---> 67   raise e.with_traceback(filtered_tb) from None
     68 finally:
     69   del filtered_tb

File /usr/local/lib/python3.8/dist-packages/merlin/models/tf/models/base.py:1179, in Model.call(self, inputs, targets, training, testing, output_context)
   1176     outputs, context = self._call_child(self.pre, outputs, context)
   1178 for block in self.blocks:
-> 1179     outputs, context = self._call_child(block, outputs, context)
   1181 if self.post:
   1182     outputs, context = self._call_child(self.post, outputs, context)

File /usr/local/lib/python3.8/dist-packages/merlin/models/tf/models/base.py:1208, in Model._call_child(self, child, inputs, context)
   1205 if any(isinstance(sub, ModelBlock) for sub in child.submodules):
   1206     del call_kwargs["features"]
-> 1208 outputs = call_layer(child, inputs, **call_kwargs)
   1209 if isinstance(outputs, Prediction):
   1210     targets = outputs.targets if outputs.targets is not None else context.targets

File /usr/local/lib/python3.8/dist-packages/merlin/models/tf/utils/tf_utils.py:437, in call_layer(layer, inputs, *args, **kwargs)
    433         call_fn = type(layer).call
    435         filtered_kwargs = filter_kwargs(filtered_kwargs, call_fn, **_k)
--> 437 return layer(inputs, *args, **filtered_kwargs)

File /usr/local/lib/python3.8/dist-packages/merlin/models/tf/outputs/base.py:136, in ModelOutput.__call__(self, inputs, *args, **kwargs)
    133     inputs = tf_utils.call_layer(self.pre, inputs, **kwargs)
    135 # super call
--> 136 outputs = super(ModelOutput, self).__call__(inputs, *args, **kwargs)
    138 if self.post:
    139     outputs = tf_utils.call_layer(self.post, outputs, **kwargs)

File /usr/local/lib/python3.8/dist-packages/merlin/models/tf/outputs/base.py:114, in ModelOutput.call(self, inputs, training, testing, **kwargs)
    113 def call(self, inputs, training=False, testing=False, **kwargs):
--> 114     return tf_utils.call_layer(
    115         self.to_call, inputs, training=training, testing=testing, **kwargs
    116     )

File /usr/local/lib/python3.8/dist-packages/merlin/models/tf/utils/tf_utils.py:437, in call_layer(layer, inputs, *args, **kwargs)
    433         call_fn = type(layer).call
    435         filtered_kwargs = filter_kwargs(filtered_kwargs, call_fn, **_k)
--> 437 return layer(inputs, *args, **filtered_kwargs)

File /usr/local/lib/python3.8/dist-packages/merlin/models/tf/outputs/classification.py:330, in EmbeddingTablePrediction.call(self, inputs, training, **kwargs)
    329 def call(self, inputs, training=False, **kwargs) -> tf.Tensor:
--> 330     logits = tf.matmul(inputs, self.table.table.embeddings, transpose_b=True)
    331     logits = tf.nn.bias_add(logits, self.bias)
    333     return logits

InvalidArgumentError: Exception encountered when calling layer "embedding_table_prediction_4" (type EmbeddingTablePrediction).

Matrix size-incompatible: In[0]: [1024,48], In[1]: [23272,32] [Op:MatMul]

Call arguments received by layer "embedding_table_prediction_4" (type EmbeddingTablePrediction):
  • inputs=tf.Tensor(shape=(1024, 48), dtype=float32)
  • training=False
  • kwargs={'testing': 'False', 'features': {'f_47_list_seq': '<tf.RaggedTensor [[[3],\n  [3],\n  [3]], [[2],\n         [4],\n         [4]], [[3],\n                [9],\n                [9]], ..., [[2]], [[3],\n                                   [3],\n                                   [3]], [[8]]]>', 'f_68_list_seq': '<tf.RaggedTensor [[[3],\n  [2],\n  [2]], [[5],\n         [23],\n         [2]] , [[3],\n                 [11],\n                 [3]] , ..., [[25]], [[3],\n                                      [3],\n                                      [3]], [[10]]]>', 'item_id_list_seq': '<tf.RaggedTensor [[[1929],\n  [328],\n  [116]] , [[9228],\n            [3787],\n            [8778]], [[2527],\n                      [4350],\n                      [1782]], ..., [[9587]], [[267],\n                                               [100],\n                                               [100]], [[4722]]]>', 'item_id_last': 'tf.Tensor(shape=(1024, 1), dtype=int32)'}}

Steps/Code to reproduce bug

First of all, please generate the syntethic data set and process with NVT. you can use this code

Once you generate the train set, run the code below to repro the error

EMBED_DIM = 48
embeds = {'item_id_list_seq':EMBED_DIM,
          'f_47_list_seq': 16,
          'f_68_list_seq': 16
         }

inputs = mm.InputBlockV2(
        train.schema.select_by_name(
        ['item_id_list_seq', 'f_47_list_seq', 'f_68_list_seq']
    ),
        embeddings=mm.Embeddings(train.schema.select_by_name(['item_id_list_seq', 'f_47_list_seq', 'f_68_list_seq']
                                                            ),
                                 sequence_combiner=None,
                                 dim=embeds
                                )
)

model = mm.Model(
    inputs,
    mm.MLPBlock([EMBED_DIM]),
    mm.XLNetBlock(
        d_model=EMBED_DIM,
        n_head=8,
        n_layer=2,
        post='sequence_mean',
    ),
    mm.CategoricalOutput(
        to_call=inputs["categorical"][item_id_name],
        target="purchase_id_first"
    ),
)

loader = mm.Loader(train, batch_size=1024, transform=mm.ToTarget(train.schema, "purchase_id_first", one_hot=True))

optimizer = tf.keras.optimizers.Adam(
    learning_rate=0.005
)
model.compile(run_eagerly=False, optimizer=optimizer)
model.fit(loader, batch_size=1024, epochs=1)

The specified embedding dim is ignored because you are using the deprecated embeddings arg, which was renamed to categorical. I have added a deprecation warning and also updated tests in #880

authors: gabrielspmoreira rnyak

repo: NVIDIA-Merlin/models


text:
Asv test support

These changes add support for benchmarking leveraging the Air Speed Velocity framework to display benchmarks over time. This will be extremely helpful in catch regressions in performance while also ensuring any new changes do not adversely affect our selected benchmarks.

rerun tests

rerun tests

rerun tests

rerun tests

repo: NVIDIA/NVTabular


text:
enable SP in mixtral-8x7b

Avoid triggering raise ValueError( ValueError: When using expert parallelism and tensor parallelism, sequence parallelism must be used, since both EP & TP are enabled.

Also enabled sequence_parallel for mixtral & mistrla

repo: NVIDIA/NeMo-Framework-Launcher


text:
generation does not stop correctly

model：codellama/CodeLlama-7b-Python-hf
build code：
python build.py --model_dir /docker_storage/CodeLlama-7b-Python-hf/ --dtype float16 \     --remove_input_padding --use_gpt_attention_plugin float16 --use_gemm_plugin float16 \     --enable_context_fmha --output_dir codellama_7b --rotary_base 1000000 --vocab_size 32016
run code：
python run.py --max_output_len=512 --tokenizer_dir /docker_storage/CodeLlama-7b-Python-hf/ --engine_dir codellama_7b --input_text "# language: Python\n# write a bubble sort function\n"
output：
`Output: "\ndef bubble_sort(array):\n    n = len(array)\n    for i in range(n):\n        swapped = False\n        for j in range(0, n-i-1):\n            if array[j] > array[j + 1]:\n                array[j], array[j + 1] = array[j + 1], array[j]\n                swapped = True\n        if swapped == False:\n            return array\n\n\n# test the function\narray = [6, 20, 8, 19, 56, 23, 87, 49, 41, 54]\nprint(bubble_sort(array))"
}
def test_get_code_snippet_from_file(self):
    code_snippet = get_code_snippet_from_file(self.file_path)
    self.assertEqual(code_snippet, self.code_snippet)

def test_get_code_snippet_from_file_with_invalid_file_path(self):
    with self.assertRaises(FileNotFoundError):
        get_code_snippet_from_file("invalid_file_path")

def test_get_code_snippet_from_file_with_invalid_file_extension(self):
    with self.assertRaises(ValueError):
        get_code_snippet_from_file("invalid_file_extension.txt")

def test_get_code_snippet_from_file_with_invalid_file_content(self):
    with self.assertRaises(ValueError):
        get_code_snippet_from_file(self.invalid_file_path)

def test_get_code_snippet_from_file_with_invalid_file_content_with_no_code(self):
    with self.assertRaises(ValueError):
        get_code_snippet_from_file(self.invalid_file_path_with_no_code)

def"`

expected result：
"\ndef bubble_sort(array):\n    n = len(array)\n    for i in range(n):\n        swapped = False\n        for j in range(0, n-i-1):\n            if array[j] > array[j + 1]:\n                array[j], array[j + 1] = array[j + 1], array[j]\n                swapped = True\n        if swapped == False:\n            return array\n\n\n# test the function\narray = [6, 20, 8, 19, 56, 23, 87, 49, 41, 54]\nprint(bubble_sort(array))"
so, the generation seems does not stop correctly.

There’s a bug, we don’t pass the proper end token, that is going to be fixed when we push an update to the dev (main) branch at the end of this week. Sorry for the inconvenience.

There’s a bug. We don’t pass the proper end token, that is going to be fixed when we push an update to the dev (main) branch at the end of this week. Sorry for the inconvenience.

ok，thx for the quick response

@gesanqiu , that's correct, the buffer is pre-filled and run.py shows the entire sequence without stoping to the 1st EOS token. We plan to fix that in the future.

There’s a bug. We don’t pass the proper end token, that is going to be fixed when we push an update to the dev (main) branch at the end of this week. Sorry for the inconvenience.

hi jdemouth，i use the latest code in main branch, this problem seems still existed. The generation doesn't stop correctly.

I was facing this issue as well. I replicated the behavior of adding "" until the max_token when using run.py.
I also used the same engine and trt-llm backend to set up a triton server. When I use curl -X POST http://localhost/v2/models/ensemble/generate -d '{"text_input": "..", "max_tokens": 128, "top_k":1} to generate text, it outputs unrelated text after what the generation should be, until the max token number specified. I'm not sure if this is also due to this TRT-LLM bug. I'm currently able to pass an "end_id" explicitly in the curl request to avoid this issue though.

Any update here? Same problem last for few weeks.

Any update here? Same problem last for few weeks.

Try the latest main?

This isn't fixed yet, still can't stop generating when passing eos_token

The "stop words" works in run.py but does not work in triton server.

Mark

authors: Linzecong VeryVery abacaj jdemouth-nvidia sc-gr spongezz thendwk

repo: NVIDIA/TensorRT-LLM


text:
🐛 [Bug] Docker build fails while building libtorchtrc

Bug Description
Error during torch tensorrt installation inside a docker container using the provided docker image file. The following error is thrown while building the libtorchtrc. Is there a version mismatch somewhere in the current docker file?
ERROR: /workspace/torch_tensorrt/src/cpp/bin/torchtrtc/BUILD:10:10: Compiling cpp/bin/torchtrtc/main.cpp failed: (Exit 1): gcc failed: error executing command /usr/bin/gcc -U_FORTIFY_SOURCE -fstack-protector -Wall -Wunused-but-set-parameter -Wno-free-nonheap-object -fno-omit-frame-pointer -g0 -O2 '-D_FORTIFY_SOURCE=1' -DNDEBUG -ffunction-sections ... (remaining 66 argument(s) skipped)

Use --sandbox_debug to see verbose messages from the sandbox
cpp/bin/torchtrtc/main.cpp: In function 'int main(int, char**)':
cpp/bin/torchtrtc/main.cpp:464:22: error: 'struct torch_tensorrt::torchscript::CompileSpec' has no member named 'strict_types'
  464 |     compile_settings.strict_types = true;
      |                      ^~~~~~~~~~~~
cpp/bin/torchtrtc/main.cpp:590:22: error: 'struct torch_tensorrt::torchscript::CompileSpec' has no member named 'max_batch_size'
  590 |     compile_settings.max_batch_size = args::get(max_batch_size);

To Reproduce
Steps to reproduce the behavior:

Run git clone https://github.com/NVIDIA/Torch-TensorRT.git
cp Torch-TensorRT
Run docker build -f docker/Dockerfile -t torch_trt:21.10 .

No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda'
running bdist_wheel
Extracting Bazel installation...
Starting local Bazel server and connecting to it...
Loading:
Loading: 0 packages loaded
Loading: 0 packages loaded
Analyzing: target //:libtorchtrt (1 packages loaded, 0 targets configured)
Analyzing: target //:libtorchtrt (35 packages loaded, 75 targets configured)
INFO: Analyzed target //:libtorchtrt (43 packages loaded, 2934 targets configured).
INFO: Found 1 target...
[0 / 91] [Prepa] Creating source manifest for @rules_pkg//:build_tar ... (9 actions, 0 running)
[1,145 / 1,328] Compiling core/util/logging/TorchTRTLogger.cpp; 0s processwrapper-sandbox ... (63 actions, 62 running)
[1,147 / 1,328] Compiling core/lowering/passes/view_to_reshape.cpp; 1s processwrapper-sandbox ... (63 actions, 62 running)
[1,147 / 1,328] Compiling core/lowering/passes/view_to_reshape.cpp; 3s processwrapper-sandbox ... (63 actions running)
[1,147 / 1,328] Compiling core/lowering/passes/view_to_reshape.cpp; 4s processwrapper-sandbox ... (64 actions running)
[1,148 / 1,328] Compiling core/lowering/passes/view_to_reshape.cpp; 8s processwrapper-sandbox ... (64 actions, 63 running)
[1,157 / 1,328] Compiling core/lowering/passes/unpack_var.cpp; 10s processwrapper-sandbox ... (64 actions, 61 running)
[1,189 / 1,328] Compiling core/lowering/passes/unpack_var.cpp; 12s processwrapper-sandbox ... (63 actions, 62 running)
[1,208 / 1,328] Compiling core/lowering/passes/module_fallback.cpp; 14s processwrapper-sandbox ... (64 actions, 63 running)
[1,210 / 1,328] Compiling core/conversion/converters/converter_util.cpp; 16s processwrapper-sandbox ... (64 actions running)
[1,214 / 1,328] Compiling core/conversion/converters/converter_util.cpp; 19s processwrapper-sandbox ... (64 actions running)
[1,224 / 1,328] Compiling core/conversion/converters/converter_util.cpp; 23s processwrapper-sandbox ... (64 actions running)
[1,241 / 1,328] Compiling core/plugins/impl/normalize_plugin.cpp; 21s processwrapper-sandbox ... (64 actions running)
[1,248 / 1,328] Compiling core/plugins/impl/interpolate_plugin.cpp; 25s processwrapper-sandbox ... (64 actions, 63 running)
[1,313 / 1,328] Compiling core/conversion/converters/impl/layer_norm.cpp; 23s processwrapper-sandbox ... (10 actions running)
ERROR: /workspace/torch_tensorrt/src/cpp/bin/torchtrtc/BUILD:10:10: Compiling cpp/bin/torchtrtc/main.cpp failed: (Exit 1): gcc failed: error executing command /usr/bin/gcc -U_FORTIFY_SOURCE -fstack-protector -Wall -Wunused-but-set-parameter -Wno-free-nonheap-object -fno-omit-frame-pointer -g0 -O2 '-D_FORTIFY_SOURCE=1' -DNDEBUG -ffunction-sections ... (remaining 66 argument(s) skipped)

Use --sandbox_debug to see verbose messages from the sandbox
cpp/bin/torchtrtc/main.cpp: In function 'int main(int, char**)':
cpp/bin/torchtrtc/main.cpp:464:22: error: 'struct torch_tensorrt::torchscript::CompileSpec' has no member named 'strict_types'
  464 |     compile_settings.strict_types = true;
      |                      ^~~~~~~~~~~~
cpp/bin/torchtrtc/main.cpp:590:22: error: 'struct torch_tensorrt::torchscript::CompileSpec' has no member named 'max_batch_size'
  590 |     compile_settings.max_batch_size = args::get(max_batch_size);
      |                      ^~~~~~~~~~~~~~
Target //:libtorchtrt failed to build
Use --verbose_failures to see the command lines of failed build steps.
INFO: Elapsed time: 64.339s, Critical Path: 29.80s
INFO: 1323 processes: 1131 internal, 192 processwrapper-sandbox.
FAILED: Build did NOT complete successfully
FAILED: Build did NOT complete successfully
using CXX11 ABI build
building libtorchtrt
The command '/bin/sh -c ./docker/dist-build.sh' returned a non-zero code: 1

Expected behavior
A successfully installed docker image supporting Torch-TensorRT.
Environment

Build information about Torch-TensorRT can be found by turning on debug messages

Torch-TensorRT Version (e.g. 1.0.0): 1.0.0
PyTorch Version (e.g. 1.0): 1.10
CPU Architecture: x86_64
OS (e.g., Linux): Ubuntu 20.04
How you installed PyTorch (conda, pip, libtorch, source): docker
Build command you used (if compiling from source): docker build -f docker/Dockerfile -t torch_trt:21.10 .
Are you using local sources or building from archives:
Python version: 3.8
CUDA version: 11.4
GPU models and configuration: NVIDIA RTX A6000
Any other relevant information: Base NVIDIA container image for PyTorch = 21.10

There was a PR that broke master, should be fixed now. Please reopen if you still have errors

Hello, Thank you for the reply. I pulled the latest changes, made sure all the cuda and device drivers are installed properly before trying again. Unfortunately, it fails at the same step albeit with a different error.
Step 18/34 : RUN ./docker/dist-build.sh --verbose
 ---> Running in a4da0d642cb0
No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda'
running bdist_wheel
Extracting Bazel installation...
Starting local Bazel server and connecting to it...
Loading:
Loading: 0 packages loaded
Loading: 0 packages loaded
Analyzing: target //:libtorchtrt (1 packages loaded, 0 targets configured)
INFO: Analyzed target //:libtorchtrt (43 packages loaded, 2934 targets configured).

INFO: Found 1 target...
[0 / 47] [Prepa] Expanding template external/rules_pkg/build_tar ... (3 actions, 0 running)
[1,145 / 1,328] Compiling core/util/trt_util.cpp; 0s processwrapper-sandbox ... (63 actions, 62 running)
[1,147 / 1,328] Compiling core/util/trt_util.cpp; 1s processwrapper-sandbox ... (64 actions, 63 running)
[1,148 / 1,328] Compiling core/util/trt_util.cpp; 2s processwrapper-sandbox ... (64 actions, 63 running)
[1,148 / 1,328] Compiling core/util/trt_util.cpp; 3s processwrapper-sandbox ... (64 actions running)
[1,149 / 1,328] Compiling core/util/trt_util.cpp; 8s processwrapper-sandbox ... (64 actions, 63 running)
[1,157 / 1,328] Compiling core/util/trt_util.cpp; 10s processwrapper-sandbox ... (64 actions, 63 running)
[1,180 / 1,328] Compiling core/conversion/converters/converter_util.cpp; 12s processwrapper-sandbox ... (64 actions, 63 running)
[1,184 / 1,328] Compiling core/conversion/converters/converter_util.cpp; 15s processwrapper-sandbox ... (64 actions running)
ERROR: /workspace/torch_tensorrt/src/core/conversion/converters/BUILD:51:11: Compiling core/conversion/converters/impl/element_wise.cpp failed: (Exit 1): gcc failed: error executing command /usr/bin/gcc -U_FORTIFY_SOURCE -fstack-protector -Wall -Wunused-but-set-parameter -Wno-free-nonheap-object -fno-omit-frame-pointer -g0 -O2 '-D_FORTIFY_SOURCE=1' -DNDEBUG -ffunction-sections ... (remaining 60 argument(s) skipped)

Use --sandbox_debug to see verbose messages from the sandbox
core/conversion/converters/impl/element_wise.cpp: In lambda function:
core/conversion/converters/impl/element_wise.cpp:347:104: error: 'kSIGN' is not a member of 'nvinfer1::UnaryOperation'; did you mean 'kSIN'?
  347 |                       auto sign = ctx->net->addUnary(*tmp_div->getOutput(0), nvinfer1::UnaryOperation::kSIGN);
      |                                                                                ^~~~~
      |                                                                                kSIN
[1,187 / 1,328] Compiling core/conversion/converters/converter_util.cpp; 18s processwrapper-sandbox ... (63 actions running)
Target //:libtorchtrt failed to build
Use --verbose_failures to see the command lines of failed build steps.
INFO: Elapsed time: 29.663s, Critical Path: 19.19s
INFO: 1250 processes: 1190 internal, 60 processwrapper-sandbox.
FAILED: Build did NOT complete successfully
FAILED: Build did NOT complete successfully
using CXX11 ABI build
building libtorchtrt
The command '/bin/sh -c ./docker/dist-build.sh --verbose' returned a non-zero code: 1

I tracked the issue to this line inside the dist-build.sh
MAX_JOBS=1 LANG=en_US.UTF-8 LANGUAGE=en_US:en LC_ALL=en_US.UTF-8 \
	       python3 setup.py bdist_wheel --use-cxx11-abi $* || exit 1

I have the same error, using PyTorch NGC with 21.10 version as a base container

I also meet the same error, with the base container 21.11

authors: david-montalvoo heluocs narendasan tridivb

repo: NVIDIA/Torch-TensorRT


text:
Add support for multi-query and grouped-query attention

This PR adds support for multi-query attention (MQA) and grouped-query attention (GQA). Specifically, it enables the use of MQA and GQA in FlashAttention() and UnfusedDotProductAttention. MQA and MHA are special cases of GQA, i.e. when num_gqa_groups=1 and num_heads. GQA only applies to keys and values, not queries.

/te-ci

/te-ci

/te-ci

/te-ci

/te-ci

Hi, overall LGTM with only one small thing. I see @ksivaman mentioned that this PR uses a PR in MegatronLM as a reference. The main difference I see is that in TE you use a Q projection and a KV projection while in megatron it's packed to be a single QKV projection matrix. Is there any particular reasons why you separate them? I think it would be better if the implementations are consistent so that people don't need to convert checkpoints back and forth. especially because I see megatron core uses some TE layers internally.

Hi @blahBlahhhJ ,
With MQA and GQA, the kv projection size might be different from the query projection size. That itself isn't a problem for the projection gemm, but when we do ColumnParallel and the split of parameters (into q, k, v, in TE), the q_projection_size + 2 * kv_projection_size might not divide well by 3. To be safe and to make the TP balancing easier (I'm sure we can parallelize it too with a non-balanced TP situation, if we really want to do it), I coded the projection as Q and KV rather than QKV.

authors: blahBlahhhJ cyanguwa ksivaman

repo: NVIDIA/TransformerEngine


text:
Support building using the manylinux docker image.

Two changes:

libpython is only required for embedded python, not for python extensions.
tell cmake explicitly to use the current interpreter (and includes)

See related issues:

https://gitlab.kitware.com/cmake/cmake/-/issues/20425
https://github.com/pypa/manylinux/issues/484

/te-ci

/te-ci

The errors are unrelated and they also showed up in the 1/12 nightly build.

authors: lpetre ptrendx timmoon10


text:
GEFS select variables

Earth2Studio Pull Request
Description

Checklist

[ ] I am familiar with the Contributing Guidelines.
[ ] New or existing tests cover these changes.
[ ] The documentation is up to date with these changes.
[ ] The CHANGELOG.md is up to date with these changes.
[ ] An issue is linked to this pull request.

Dependencies

/blossom-ci


text:
Early versions of TensorFlow (e.g. 1.9) do not have a version attribute

I am getting  AttributeError for tf 1.9, saying that tensorflow doesn't have "version" as attribute.
Can you help?

Hi @SageAgastya,
I assume that you're attempting to apply the patch function from the PyPI distribution. We have paused development in the middle of a major update and will not be able to make changes to the PyPI distribution anytime soon. However, even if version 1.9 of TensorFlow had a version attribute, and therefore didn't exit with a TypeError for that reason, the patch code would proceed to exit with another TypeError and a message saying, "No patch available for version 1.9 of TensorFlow".
The patch function is not intended to be executed on any NGC TensorFlow containers nor on versions of stock TensorFlow earlier than 1.14 and is designed to throw a TypeError if that is attempted.
I hope this helps. I'm going to close this issue, but I'm happy to continue this discussion, if you wish.
Duncan

Actually, I'm going to leave this open so that it serves as a marker to possibly address this issue in a future release. We could check if there is a version attribute and if there is none then we could assume that the TensorFlow version is earlier than 1.14.

Thank you, @SageAgastya, for bringing this to my attention.

authors: SageAgastya duncanriach

repo: NVIDIA/framework-determinism


text:
/run/nvidia-persistenced/socket: no such device or address

Hi,
we are currently setting up a new cluster deployment environment with slurm, pyxis and enroot.
Our machines have DGX OS installed.
Container images like centos
srun --container-image=centos grep PRETTY /etc/os-release
finish without a problem. GPU Based images like
srun --container-image=nvcr.io/nvidia/tensorflow:22.08-tf2-py3 /bin/bash
experiencing a problem during startup
nvidia-container-cli: mount error: file creation failed: /raid/enroot-data/user-9011/pyxis_59.0/run/nvidia-persistenced/socket: no such device or address
[ERROR] /raid/enroot//hooks.d/98-nvidia.sh exited with return code 1

I think it is some misconfiguration, but at the moment I am not able to spot it.

Hi @matyro. Could you file an issue at https://github.com/NVIDIA/enroot instead as they may have a better idea as to what is happening here. If there is an issue with the NVIDIA Container CLI then please update this issue with the relevant context.

Thanks @matyro. As a matter of interest, which version of libnvidia-container-tools is being used?

Hi, not the newest release:
nvidia-container-cli -V
cli-version: 1.7.0
lib-version: 1.7.0
build date: 2021-11-30T19:53+00:00
build revision: f37bb387ad05f6e501069d99e4135a97289faf1f
build compiler: x86_64-linux-gnu-gcc-7 7.5.0
build platform: x86_64
build flags: -D_GNU_SOURCE -D_FORTIFY_SOURCE=2 -DNDEBUG -std=gnu11 -O2 -g -fdata-sections -ffunction-sections -fstack-protector -fno-strict-aliasing -fvisibility=hidden -Wall -Wextra -Wcast-align -Wpointer-arith -Wmissing-prototypes -Wnonnull -Wwrite-strings -Wlogical-op -Wformat=2 -Wmissing-format-attribute -Winit-self -Wshadow -Wstrict-prototypes -Wunreachable-code -Wconversion -Wsign-conversion -Wno-unknown-warning-option -Wno-format-extra-args -Wno-gnu-alignof-expression -Wl,-zrelro -Wl,-znow -Wl,-zdefs -Wl,--gc-sections

Updating to the newest system available did not help:
enroot start -e NVIDIA_VISIBLE_DEVICES=all --root --rw cuda_root
nvidia-container-cli: container error: stat failed: /raid/enroot-data/cuda_root/proc/12474: no such file or directory
[ERROR] /etc/enroot/hooks.d/98-nvidia.sh exited with return code 1

root@ml2ran03:~# nvidia-container-cli -V
cli-version: 1.10.0
lib-version: 1.10.0
build date: 2022-06-13T10:39+00:00
build revision: 395fd41701117121f1fd04ada01e1d7e006a37ae
build compiler: x86_64-linux-gnu-gcc-7 7.5.0
build platform: x86_64
build flags: -D_GNU_SOURCE -D_FORTIFY_SOURCE=2 -DNDEBUG -std=gnu11 -O2 -g -fdata-sections -ffunction-sections -fplan9-extensions -fstack-protector -fno-strict-aliasing -fvisibility=hidden -Wall -Wextra -Wcast-align -Wpointer-arith -Wmissing-prototypes -Wnonnull -Wwrite-strings -Wlogical-op -Wformat=2 -Wmissing-format-attribute -Winit-self -Wshadow -Wstrict-prototypes -Wunreachable-code -Wconversion -Wsign-conversion -Wno-unknown-warning-option -Wno-format-extra-args -Wno-gnu-alignof-expression -Wl,-zrelro -Wl,-znow -Wl,-zdefs -Wl,--gc-sections

@matyro this doesn't show the same error creating /run though, or are the error messages in fact identical?

As per https://github.com/NVIDIA/enroot/issues/138#issuecomment-1267746598 can you confirm that /proc is mounted into the container correctly when starting without GPUs? (i.e. enroot start --root --rw cuda_root).

You are right, it seems proc was not mounted correctly
root@ml2ran03:/# ll /
total 84
drwxrwxr-x 17 root root  4096 Oct  4 19:29 ./
drwxrwxr-x 17 root root  4096 Oct  4 19:29 ../
-rw-r--r--  1 root root     0 Oct  6 13:01 .lock
-rw-r--r--  1 root root 16047 Aug  8 21:08 NGC-DL-CONTAINER-LICENSE
lrwxrwxrwx  1 root root     7 Aug  1 13:22 bin -> usr/bin/
drwxr-xr-x  2 root root  4096 Apr 15  2020 boot/
drwxr-xr-x  2 root root  4096 Oct  5 10:17 dev/
drwxrwxr-x 36 root root  4096 Oct  4 18:57 etc/
drwxr-xr-x  2 root root  4096 Apr 15  2020 home/
lrwxrwxrwx  1 root root     7 Aug  1 13:22 lib -> usr/lib/
lrwxrwxrwx  1 root root     9 Aug  1 13:22 lib32 -> usr/lib32/
lrwxrwxrwx  1 root root     9 Aug  1 13:22 lib64 -> usr/lib64/
lrwxrwxrwx  1 root root    10 Aug  1 13:22 libx32 -> usr/libx32/
drwxr-xr-x  2 root root  4096 Aug  1 13:22 media/
drwxr-xr-x  2 root root  4096 Aug  1 13:22 mnt/
drwxr-xr-x  2 root root  4096 Aug  1 13:22 opt/
drwxr-xr-x  2 root root  4096 Apr 15  2020 proc/
drwx------  2 root root  4096 Oct  5 17:46 root/
drwxr-xr-x  5 root root  4096 Aug  1 13:25 run/
lrwxrwxrwx  1 root root     8 Aug  1 13:22 sbin -> usr/sbin/
drwxr-xr-x  2 root root  4096 Aug  1 13:22 srv/
drwxr-xr-x  3 root root  4096 Oct  5 10:17 sys/
drwxrwxrwt  2 root root  4096 Aug  1 13:25 tmp/
drwxr-xr-x 13 root root  4096 Aug  1 13:22 usr/
drwxr-xr-x 11 root root  4096 Aug  1 13:25 var/

Hi @matyro with regards to the error related to /run/nvidia-persistenced/socket after seeing similar behaviour in https://github.com/NVIDIA/nvidia-docker/issues/1690 I was able to reproduce this locally (by including the -v /var/run:/var/run flag when starting a docker container.
I have updated the "mount" code in libnvidia-container to check whether a file exists before creating it in
https://gitlab.com/nvidia/container-toolkit/libnvidia-container/-/merge_requests/187.
Are you in a position to test this patch?

We are currently having a hardware problem on one of our nodes and are in contact with enterprise support. When the hardware exchange is done next week we will have a spare node available and should be able to run some tests.

The machine is back, what is the simplest way to test it now?
I already cloned the repository and switched the branch to your MR.

Running make -f mk/docker.mk ubunut18.04-amd64 from the libnvidia-container repo root should generate debian packages in ./dist/ubuntu18.04/amd64 (replace this with your distro of choice).
You can then install the deb files directly by: sudo dpkg -i dist/ubuntu18.04/amd64/libnvidia-container1_1.12.0~rc.1-1_amd64.deb dist/ubunut18.04/amd64/libnvidia-container-tools_1.12.0~rc.2-1_amd64.deb
This will then be available system-wide. You can confirm the commit used to build the nvidia-container-cli by running:
nvidia-container-cli --version

A (forced) reinstall of the libnvidia-container1 and libnvidia-container-tools packages from our public repos should restore the state.

Hi,
I deployed the fixed file today on our test machine and enroot is now working fine.
GPUs are limited to the selected device.

Thanks for the confirimation @matyro. That's good news,
I'm not sure how srun interacts with the NVIDIA container stack to provide the isolation. Do you have a link to their documentation on this?

https://slurm.schedmd.com/gres.html#GPU_Management
In the slurm Job CUDA_VISIBLE_DEVICES is set correctly. But even directly on the node
CUDA_VISIBLE_DEVICES=0 nvidia-smi
shows all GPUs

Since nvidia-smi uses the low-level NVIDIA Management Library under the hood, I don't think it checks CUDA_VISIBLE_DEVICES to filter the list. This seems like an issue with how enroot is being triggered (through pyxis) when invoking srun.
For clarification, the NVIDIA container stack uses the NVIDIA_VISIBLE_DEVICES environment variable in the container to determine which devices to inject. This is processed specifically by the NVIDIA Container Runtime Hook and is (as far as I am aware) not applicable to enroot directly.

Everything works now, and I think the problem can be closed from my side.
The only remaining question would be if there is an estimated date when the patched libnvidia-container will be available directly in DGX OS.
Thanks for your help
Dominik

Thanks @matyro. Our current timeline is to release the final version including this fix at the start of December. It should be picked up for distribution through the DGX repos shortly after that.
Note that we will release an rc.2 with these changes between now and then and this will be installable through our public experimental repositories.

@matyro sorry for the delayed response from my end. We have released 1.12.0-rc.2 including this fix. Once the final version is released (still at the start of december), that should be picked up by the DGX repositories.

@matyro v1.12.0 has now been released. Sorry for the delay on this.
Please reopen the issue if you're still having problems.

authors: elezar matyro

repo: NVIDIA/libnvidia-container


text:
[submodule-sync] bot-submodule-sync-branch-23.06 to branch-23.06 [skip ci] [bot]

submodule-sync to create a PR keeping thirdparty/cudf up-to-date.
HEAD commit SHA: cb71b80ff1829047f3939b20af8d1dd20f691d82, cudf commit SHA: https://github.com/rapidsai/cudf/commit/f6abfddbb66fbde2d2f27d743f2de3e5a7c9a8c8
This PR will be auto-merged if test passed. If failed, it will remain open until test pass or manually fix.

HEAD commit SHA: cb71b80ff1829047f3939b20af8d1dd20f691d82, CUDF commit SHA: https://github.com/rapidsai/cudf/commit/f6abfddbb66fbde2d2f27d743f2de3e5a7c9a8c8
Test passed: True

SUCCESS - auto-merge

repo: NVIDIA/spark-rapids-jni


text:
[submodule-sync] bot-submodule-sync-branch-22.10 to branch-22.10 [skip ci] [bot]

submodule-sync to create a PR keeping thirdparty/cudf up-to-date.
HEAD commit SHA: ec3ceb97f1a9d256d01df75e8384c0be0982cf76, cudf commit SHA: https://github.com/rapidsai/cudf/commit/ba4f7153c66fcbe684412eabb22635d7b8fb2149
This PR will be auto-merged if test passed. If failed, it will remain open until test pass or manually fix.

HEAD commit SHA: ec3ceb97f1a9d256d01df75e8384c0be0982cf76, CUDF commit SHA: https://github.com/rapidsai/cudf/commit/ba4f7153c66fcbe684412eabb22635d7b8fb2149
Test passed: True

SUCCESS - auto-merge