text:
Search results 0

The script has worked fine until yesterday..
Now the script returns 0 results..
How to debug the script? Maybe Google has detected the scraping

or maybe google has changed the data structure?

Have tried the script from 3-4 different IP adresses and all returns 0
$positions = $page->getPositions();

same thing here.
No result

Ok, let me check very soon

Ok, google replaced  with  in its DOM. It should be ok for now. Please let me know it some errors still happen, I dont have much time to test now because of summertime.
Thanks

it's seems ok for me
Thanks

In my tests there are local listings in the natural listings now.
I tried to rewrite const NATURAL_QUERY to exclude li[@id = 'lclbox'] but I failed.
My test query: "cafe berlin"
-> natural listings on page 1 (15 are 5 too much):
1: http://www.berlin.de/cafes/
2: http://www.berlin.de/cafes/stadtteile/
3: http://www.berlin.de/bars/adressen/bar/cafe-commune-0d1ab041fbae2cc0a7f4503ae944708a.html
4: http://www.schwarzescafe-berlin.de/
5: https://plus.google.com/110132661049009362940/about?hl=de&socfid=web:lu:unknown:localgroupedresult&socpid=1
6: http://www.cafeeinstein.com/
7: http://www.einsteinudl.com/
8: http://www.literaturhaus-berlin.de/
9: http://www.oliv-cafe.de/
10: http://www.cafe-butter.de/
11: http://www.cremeguides.com/de/berlin-kategorien/food-in-berlin/cafes-kuchen-kaffee-in-berlin/
12: http://www.top10berlin.de/de/cat/essen-267/cafes-fuer-kaffeeliebhaber-567
13: http://www.yelp.de/c/berlin/cafe
14: http://www.visitberlin.de/de/erleben/essen-trinken/cafes
15: http://www.cafe-k.com/

Is there is already a solution?

authors: LiloBzH clarkk gsouf radolfi

repo: gsouf/google-url


text:
WIP: Bump babel, eslint and jest

Hello. First of all, thank you for the great tool, oao.
I found babel-pollyfill is out of date.
I update to new major version of babel. And I also updated eslint and jest due to babel-eslint and babel-jest.
All tests was passed. But I got a problem.
Eslint conflicts with prettier.
Which one takes priority? Or should we use something like eslint-config-prettier?

Coverage increased (+0.2%) to 79.173% when pulling b63631132c78b51dfc55550888285662527090d8 on otariidae:babel7 into 27a77aa3b06c3da6fa9129283992d9fb3b73bfce on guigrpa:master.

Coverage increased (+0.2%) to 79.173% when pulling b63631132c78b51dfc55550888285662527090d8 on otariidae:babel7 into 27a77aa3b06c3da6fa9129283992d9fb3b73bfce on guigrpa:master.

Thanks a lot!

source: gharchive/pull-request

authors: coveralls guigrpa otariidae

repo: guigrpa/oao

license: mit

license_type: permissive

license_source: bigquery


text:
Email with a single letter as tld (example@mail.a) passes validation.

What kind of issue is this? (put 'x' between the square brackets)

[ ] Question. This issue tracker is not the place for questions. If you want to ask how to do
something, or to understand why something isn't working the way you expect it to, use
http://stackoverflow.com/questions/ask .
Provide working code, starting from http://codepen.io/marcandre/pen/jqbzyN?editors=101.
We monitor the tag parsley.js.

[x] Bug report. If you’ve found a bug, you must provide a minimal example in a CodePen,
starting from http://codepen.io/marcandre/pen/jqbzyN?editors=101 .

[ ] Feature Request. Make sure there's no good way to do what you want first;
consider asking on http://stackoverflow.com/questions/ask first.

I noticed that an email adress with one character after the last dot will be validated as true. For example example@email.a. As far as I know that should be a minimum of two?
You can see it here: http://codepen.io/erik127/pen/XKWWaJ?editors=101

Single letter TLDs are technically valid. We don't aim to validate that the TLD actually exist.
See also: http://stackoverflow.com/questions/7411255/is-it-possible-to-have-one-single-character-top-level-domain-name

Ah ok. Thanks for the quick response.

source: gharchive/issue


text:
Approach for building custom validator including Ajax Validation

Two out of three fields are required with pattern validation. Once two fields have been filled Ajax call will happen carrying the data from both fields to verify the content. Depending on response the both fields will be validated.

There's no easy way to handle dependencies right now. I'm closing this, please follow #694 if interested in future developments.

authors: marcandre nileshku


text:
Poor quality of "06_Stats/Wind_Stats" exercise

The link at step 2 is wrong, as it leads to github, not the data
Steps 4 and 5 are confusing, because they depend on the way the step 3 is solved. I didn't do a mistake described in solutions and spent some time figuring out what these steps are about.
The solution to step 7 is wrong, it should be:
data.shape[0] - data.isnull().sum() or better data.notnull().sum().
The solution to step 8 is wrong: the mean value does not equal to the mean of means. The right solution is:
data.fillna(0).values.flatten().mean()
The solution to step 9 seems a bit verbose. What's wrong with describe(percentiles=[])?
The solution to step 11 seems ok, but is too verbose as well. Pandas favors one-liners where possible:
data.loc[data.index.month == 1].mean()
The solutions to steps 12, 13 and 14 are absolutely wrong. It has nothing to do with "yearly/monthly frequency", but selects individual rows from the data frame. The right solution looks like:
data.groupby(data.index.to_period('A')).mean()
Step 15 is confusing, because that's "monthly frequency" that step 13 was about. The distinction should be better clarified in both steps. And the solution is wrong again. Here's what it should be:
data.groupby(data.index.to_period('M')).mean().head()

Overall, 11 out of 16 are either wrong or misleading. On top of that, the bulk of this notebook belongs to "Time series analysis"

@maxim5 Thank you for the valid inputs. It would be great if you could make a PR in order to improve the quality of it.

@guipsamora
I did few days ago. Please have a look.

@maxim5 thank you, I implemented your suggestions. Thanks for the massive PRs @TakaakiFuruse and sorry for taking to long to merge them, I just moved to Germany and started working he so I had other priorities. Feel free to collaborate on this repo!

authors: TakaakiFuruse guipsamora maxim5

license_source: github-api


text:
Added nil-check for _accountKit

If using getAccount before initializing _accountKit the callbacks were never called. Added nil check to trigger callback when not initialized.

Doesn't really solve the issue :(

repo: gurisko/cordova-plugin-accountkit


text:
[WIP] Add support for pullRequestGetCommits in GitlabRepoAdapter

This PR is a WIP for the #581 issue. For the moment it can't be merged because the Gitlab API library can't retrieve merge request commits.
I've submitted a PR here: m4tthumphrey/php-gitlab-api#139.
When the PR will be merged and a version released, we can increment dependency number in composer.json and merge that one.
I've also added a new flag --with-commits on the pull-request:show command.

Hello,
Since the #632 has been merged and the composer.json updated to use the gitlabapi library v7.14.0, I've rebased this PR and removed the WIP status.
It can be merged if everything is ok :smile:.

repo: gushphp/gush


text:
Testando

Dia 29/11/22

Testando no seu teste kkkkkk

authors: MaxxamRS angelocsdev

repo: gustavoguanabara/git-github

license: MIT


text:
Opening 'biometric' settings on Android is crashing application

Hello,I installed the plugin to open biometrics (touchID/faceID) device settings from an Angular+ionic App. On IOS, everything works smooth by using the 'touch' option. For Android, however, I experienced a couple of issues:

'security' option does not always redirect to the correct settings section (ex. privacy)
'biometric' options is even making App crashing on some devices.
Have you ever experienced something like this and/or know what the issue could be?

Tech stack:
"@ionic/angular": "^6.0.9"
"cordova-open-native-settings": "^1.5.5"
"@awesome-cordova-plugins/open-native-settings": "^5.37.3"

See #57, 'biometric' fails on Android 13.

authors: Anthreon minduch

repo: guyromb/cordova-open-native-settings


text:
Can't Rent a Hotel?

First off, this plugin seems amazing. Honestly. I only have one issue. When doing the command /ht rent (HotelName) (room number) An Error message saying Invalid Hotel Room Number or Name comes in the chat? The Hotel Name on my server is StonyBrook. So there for when doing the command /ht rent StonyBrook 1 should rent  room "1" that I've set in my hotel. Its not working tho for some reason?? Advice?? I also get an error now when removing and creating a hotel in the same place!!!!! an internal error! The plugin doesn't recognize I removed the previous hotel for a new one to take its spot!

I will look into this, but it's very likely I will not release a bugfix version of Hotels for this but instead go straight to version 1.0.0

What can I do to fix this? Im running everything correctly

What version of the plugin are you using? What version of bukkit/spigot?

Im using 0.6.3 and Im ussing Paper spigot 1.9.4

you can come join my server XeraNetwork.com and see for youself maybe Im doing something wrong?

There was a bug in an older version of Hotels in which this would happen, if you have updated the old hotel region could have stayed so try doing /rg list and looking for the hotel-hotelName region and the hotel-hotelName-roomNum regions (with the hotelName being the name of the old hotel that wasn't fully deleted) and then doing /rg del hotel-hotelName and /rg del hotel-hotelName-roomNum

@JetSlayer Is the issue still present?

@JetSlayer Can you try with the test version of Hotels 1.0.0?

license: unlicense


text:
ReAdd cooldowns

Hello,
I installed OCM on my server, but now i want to test some plugin without him (OCM) but I can't get back the cooldown of 1.9. I have removed in my plugin folder the .jar file and the folder.
I really need to get back the cooldown (true 1.9 cooldown).
Please, could you help me?

What version did you do this with? It's supposed to remove the cooldown when you log out/ do /ocm reload

The server is on 1.10.2, i can't do /ocm reload because i've deleted the plugin. There are 5 maps on the server and all have the same problem, all sword we craft or give or take in the creative inventory don't have cooldown.

What version of the plugin did you have before?
How did you 'delete' the plugin? Because any normal way of removing it shouldn't cause this problem

it was the 1.1.0 version of the plugin. I've deleted the .jar in the server's FTP, in the plugin folder, and right click and click "delete", same with the folder OCM with the config file.

All versions of the plugin are compatible with 1.10. I meant did you stop the server before removing the plugin or not?

i've first remove the plugin, then i've restart, maybe i have to readd the plugin and do /ocm disable or something like this ?

Did you turn the server off before removing the plugin?

no

May I ask how you managed to remove it then? Did you use plugman?

no, i removed it when the server was online, then i've stop it and restart

Well that was your problem then. You should have either turned the server off or turned the modules off in the config then done /ocm reload before removing the .jar
The way to fix it now is to use the OCMFixer plugin created by Rayzr522. Read carefully the instructions on the page on how to fix it. Once you've run the commands you can remove that plugin.

Thanks, solved. ^^


text:
Support for old codehaus-hosted versions

For archival purposes, it would be good if gvm could install really old, codehaus-hosted versions of Groovy.
Archive.org maintains copies of some of these, e.g. v1.0:
http://web.archive.org/web/20150508090325/http://dist.codehaus.org/groovy/distributions/

We currently only rely on binaries found in BinTray. If these libraries are ported over to BinTray, we would be happy to point to them from GVM.

I haven't used BinTray before, but it sounds great!
How do we add these legacy versions to BinTray?

The guys at bintray need to add them. Maybe raise a request with them
directly?
On Wed, 26 Aug 2015 15:52 Andrew Pennebaker notifications@github.com
wrote:

I haven't used BinTray before, but it sounds great!
How do we add these legacy versions to BinTray?
—
Reply to this email directly or view it on GitHub
https://github.com/gvmtool/gvm-cli/issues/350#issuecomment-135048573.

Can we close this issue?

authors: marc0der marcoVermeulen mcandre

repo: gvmtool/gvm-cli


text:
Append DSL Issue : Adds text in between instead of at the end (gwen-web-2.29.0)

I am using below sequence of steps
And  I execute javascript "$("div.sidebar-container i.fa-search").closest(".filter").find("input").val("Item Allow Recalculation Of Amounts Flag")"

And  I append " " to search attribute textbox on data format

Currently the append dsl adds space in between. In earlier gwen version (2.26.5), it use to work correctly, adding space at the end of the text.

Fixed in release 2.29.1

repo: gwen-interpreter/gwen-web


text:
README

README
User Story
As a boot camp student,
I want the prework notes to be structured on a webpage,
So that I can easily find and read the information.
Acceptance Criteria
GIVEN the prework project repository,
WHEN I view the README for the repository,
THEN I can see a professional README that provides information on the project and how to use it

Changes to the README files has been completed as outlined in the acceptance Criteria.


text:
feat: 实现外排序算法

const input = fs.createReadStream(inputFile); // 输入文件流
const output = fs.createWriteStream(outputFile); // 输出文件流

await externalSort(input, output, {
  maxHeap: 1024 * 1024,
});

Codecov Report

:exclamation: No coverage uploaded for pull request base (main@1455b83). Click here to learn what that means.
The diff coverage is n/a.

@@           Coverage Diff            @@
##             main        #1   +/-   ##
========================================
  Coverage        ?   100.00%
========================================
  Files           ?         4
  Lines           ?       114
  Branches        ?         0
========================================
  Hits            ?       114
  Misses          ?         0
  Partials        ?         0

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 1455b83...26f896e. Read the comment docs.

authors: codecov-io gxcsoccer

repo: gxcsoccer/external-sorting


text:
Support autojump in popup SelectView

For now, only support autojump when the popup is closed, and not inside the menu popup itself.
Note that autojump fires the select callback, while popup mode previously only fired the submit callback.

Thanks for the work!

authors: bgilbert gyscos

repo: gyscos/cursive


text:
🛑 Undertale社区维基 测试站 - UTCWIKIT is down

In 4933586, Undertale社区维基 测试站 - UTCWIKIT (https://test.utcwiki.com) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Undertale社区维基 测试站 - UTCWIKIT is back up in 18ad322 after 17 minutes.

repo: gzombiejun/upptime


text:
🛑 Undertale社区项目路线图 - UTCPRP is down

In 5cb95c1, Undertale社区项目路线图 - UTCPRP (https://road.utcwiki.com) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Undertale社区项目路线图 - UTCPRP is back up in a7e1189 after 14 minutes.


text:
Windows CUDA GPU support

I followed the instructions but couldn't get the GPU to be recognised....kept getting BLAS=0
I had to compile llama-cpp-python anyway for another environment so I did that for h2ogpt and it worked.
I installed all the requirements
then uninstalled llama-cpp-python
then installed llama-cpp-python forcing a compile for CUDA.
It works but... I still get
python generate.py --base_model=llama --model_path_llama=llama-2-7b-chat.Q3_K_S.gguf --prompt_type=zephyr --max_seq_len=4096

No GPUs detected

[I then get a ton(!) of langchain messages about deprecation ]
then further down

ggml_init_cublas: found 1 CUDA devices

llm_load_tensors: offloading 32 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloaded 33/33 layers to GPU

and

AVX = 1 | AVX_VNNI = 0 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 0 | VSX = 0 | MATMUL_INT8 = 0

Inference makes the GPU sweat and CPU relax so I know it's using the GPU.
so 2 questions

how is the install really supposed to work for Windows CUDA?  I have 12.3 and install instructions reference 12.1 (eg. index and wheels are 121) - does that matter?
Why the message no gpus found (or what kind find the gpu) at the beginning when later it (llama-cpp-python?) does find it?

Yes, the llama_cpp_python wheels are specific.  I would have people always compile that, but that brings extra dependencies.
The No GPUs detected means torch had issue with finding GPUs. This won't directly affect llama_cpp_python.  You can just do in your env:

   import torch
   print(torch.cuda.is_available())

Should say fails, which is messed up.

It does come back with

False

I'm redownloading torch with CUDA support now but while it's doing that (slow) I checked another environment and here torch comes back with

True

(which I kinda knew already because been using torch with CUDA before).  So not sure what happened here.  Hopefully reinstall works and I'll put it down to one of those things.
Any chance for a quick explanation when h2ogpt uses Torch and when llama-cpp-python?

okay did:

the reinstall (quick start) this time with the constraints
requirements_optional_gpt4all failed with

ERROR: llama_cpp_python_cuda-0.2.26+cu121avx-cp310-cp310-win_amd64.whl is not a supported wheel on this platform.
as expected, so I pip installed llama_cpp_python myself having it compile for my system

wouldn't start due to

ModuleNotFoundError: No module named 'librosa'
so as reported elsewhere I have to pip install librosa

successful start, torch sees GPU and llama_cpp sees GPU

inference now has a huge pause (slow, several secs) before streaming out the output.  CPU not used, GPU is....still slow compared to the first environment I cobbled h2ogpt together on (same model, same parameters, same prompts, max 1 sec pause before streaming).  Don't know enough to debug so just leaving my findings here fwiw.

If you only do:
pip install llama_cpp_python

then it won't install the GPU version.
Check this for which env to set: https://github.com/abetlen/llama-cpp-python?tab=readme-ov-file#supported-backends

yes, I took it for granted that I had set the CUBLAS arguments correctly - I should have been more explicit but I think I found the issue.  And I'm kind of glad I had it (and found it) as it brings another question.
so my original cobbled together quickstart h2ogpt install with fast prompt eval, visible GPU usage, fast output gave me this:

Starting get_model: llama
ggml_init_cublas: GGML_CUDA_FORCE_MMQ:   yes   <-----
ggml_init_cublas: CUDA_USE_TENSOR_CORES: no      <-----
ggml_init_cublas: found 1 CUDA devices:
llm_load_tensors: using CUDA for GPU acceleration   <-----
llm_load_tensors: system memory used  =   53.82 MiB
llm_load_tensors: VRAM used           = 2757.30 MiB   <-----
llm_load_tensors: offloading 32 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloaded 33/33 layers to GPU
AVX = 1 | AVX2 = 0 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 0 | NEON = 0 | ARM_FMA = 0 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 0 | SSSE3 = 0 | VSX = 0 |

my install with requirement constraints and GPU compiled llama-cpp-python with slow prompt eval, but still visible GPU usage and fast output gave me this:

Starting get_model: llama
Failed to listen to n_gpus: No module named 'llama_cpp_cuda'  <-----
ggml_init_cublas: GGML_CUDA_FORCE_MMQ:   no <-----
ggml_init_cublas: CUDA_USE_TENSOR_CORES: yes <-----
ggml_init_cublas: found 1 CUDA devices:
<no lines about GPU acceleration, VRAM used, etc>
llm_load_tensors: offloading 32 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloaded 33/33 layers to GPU
<AVX2=1, FMA=1, F16C=1, SSE3=1 which were not set in the original>
AVX = 1 | AVX_VNNI = 0 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 0 | VSX = 0 | MATMUL_INT8 = 0 |

both models are were using a relatively small GGUF model for ease of experimenting.
I managed to figure out that requirements_optional_gpt4all.txt was not being run and that means
llama_cpp_python_cuda @ https://github.com/jllllll/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda-0.2.26+cu121avx-cp310-cp310-win_amd64.whl was not installed
It wouldn't run because in the new environment I has python 3.11 (!)
Once I substituted that command for
`llama_cpp_python_cuda @ https://github.com/jllllll/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda-0.2.26+cu121avx-cp311-cp311-win_amd64.whl
it installed and I finally got the output of the original install.  So installing this wheel had some impact which changed the differences of the outputs of generate.py
I admit I'm picking stuff up as I go along but I'd love to know:

either GGML_CUDA_FORCE_MMQ set to yes or CUDA_USE_TENSOR_CORES set to no gives me faster prompt eval.  Which is it and why?
1.1 what do GGML_CUDA_FORCE_MMQ and CUDA_USE_TENSOR_CORES do?
1.2 can they both be set to yes?

Maybe AVX2=1, FMA=1, F16C=1, SSE3=1 is responsible for the slower prompt eval.

because llama-cpp-python-cuda is installed does that mean llama-cpp-python not enough?  what does llama-cpp-python-cuda do?  I don't have it installed in my other llama-cpp-python environments
3.1 I mean I saw llama-cpp-python get compiled with CUDA support and without the llama-cpp-python-cuda wheel I still get BLAS support, and GPU is clearly used.
3.2 how to compile llama-cpp-python-cuda (so I can get my compilation to decide what features my system has) because if I don't specify the wheel pip can't find it

I know it's a lot but partly I'm saving my results so far, partly leaving this searchable for future users, partly asking for info :)

Yes, if user has GPUs, we look for llama_cpp_cuda as that's the name of the module from jlllll.  But if we don't find, we try the llama_cpp still, because like here they may have installed manually.
It's good question, maybe other options are required for good speed.
This is how jllllll compiles:
https://github.com/jllllll/llama-cpp-python-cuBLAS-wheels/blob/89862684fa6d409f54d6e54d0dbd630b3f84f053/.github/workflows/build-wheels-oobabooga.yml#L192
I don't think avx matters, AVX2 is default.
Maybe 0.2.26 vs. latest llama_cpp_python is an issue.  Latest is 0.2.55.
You could try:
pip uninstall llama_cpp_python llama_cpp_python_cuda -y
CMAKE_ARGS="-DLLAMA_CUBLAS=on" pip install llama_cpp_python==0.2.26

so the same version is used.

What I tried:
(h2ogpt) jon@pseudotensor:~/h2ogpt$ CMAKE_ARGS="-DLLAMA_CUBLAS=on" pip install llama_cpp_python==0.2.26
Looking in indexes: https://pypi.org/simple, https://download.pytorch.org/whl/cu123, https://huggingface.github.io/autogptq-index/whl/cu123
Collecting llama_cpp_python==0.2.26
  Using cached llama_cpp_python-0.2.26-cp310-cp310-manylinux_2_35_x86_64.whl
Requirement already satisfied: typing-extensions>=4.5.0 in /home/jon/miniconda3/envs/h2ogpt/lib/python3.10/site-packages (from llama_cpp_python==0.2.26) (4.9.0)
Requirement already satisfied: numpy>=1.20.0 in /home/jon/miniconda3/envs/h2ogpt/lib/python3.10/site-packages (from llama_cpp_python==0.2.26) (1.26.4)
Requirement already satisfied: diskcache>=5.6.1 in /home/jon/miniconda3/envs/h2ogpt/lib/python3.10/site-packages (from llama_cpp_python==0.2.26) (5.6.3)
DEPRECATION: textract 1.6.5 has a non-standard dependency specifier extract-msg<=0.29.*. pip 24.1 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of textract or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063
Installing collected packages: llama_cpp_python

Then ran:
python generate.py --base_model=llama

which uses llama-2-7b-chat.Q6_K.gguf by default
Then I see only large CPU usage, and slow response like you see.  So something is wrong.

the cached copy maybe CPU only?  when you generate do you get BLAS=1?

Yes, if user has GPUs, we look for llama_cpp_cuda as that's the name of the module from jlllll. But if we don't find, we try the llama_cpp still, because like here they may have installed manually.
It's good question, maybe other options are required for good speed.
This is how jllllll compiles:
https://github.com/jllllll/llama-cpp-python-cuBLAS-wheels/blob/89862684fa6d409f54d6e54d0dbd630b3f84f053/.github/workflows/build-wheels-oobabooga.yml#L192
I don't think avx matters, AVX2 is default.
Maybe 0.2.26 vs. latest llama_cpp_python is an issue. Latest is 0.2.55.
You could try:
pip uninstall llama_cpp_python llama_cpp_python_cuda -y
CMAKE_ARGS="-DLLAMA_CUBLAS=on" pip install llama_cpp_python==0.2.26

so the same version is used.

Yes, their docs aren't great.  I had documented this before, but only in isolated place.  Updated the new docs with this, which works:
pip uninstall llama_cpp_python llama_cpp_python_cuda -y
export LLAMA_CUBLAS=1
export CMAKE_ARGS="-DLLAMA_CUBLAS=on -DCMAKE_CUDA_ARCHITECTURES=all"
export FORCE_CMAKE=1
pip install llama_cpp_python==0.2.26 --force-reinstall --no-cache-dir

Thanks!

For windows do:
pip uninstall llama_cpp_python llama_cpp_python_cuda -y
set CMAKE_ARGS=-DLLAMA_CUBLAS=on -DCMAKE_CUDA_ARCHITECTURES=all
set LLAMA_CUBLAS=1
set FORCE_CMAKE=1
pip install llama_cpp_python==0.2.26 --force-reinstall --no-cache-dir

I updated readme_windows with this.

Maybe 0.2.26 vs. latest llama_cpp_python is an issue. Latest is 0.2.55.
You could try:
pip uninstall llama_cpp_python llama_cpp_python_cuda -y
CMAKE_ARGS="-DLLAMA_CUBLAS=on" pip install llama_cpp_python==0.2.26

so the same version is used.

well what do you know!!!
I checked my HWINFO and I have AVX2, SSE-3, and FMA available on the CPU so the 2nd environment is closer to the system spec.  However, I tried your suggestion.
You suggested to uninstall both, then only install one: llama-cpp-python.  Which is what I did.
On generate py I got:

Starting get_model: llama
Failed to listen to n_gpus: No module named 'llama_cpp_cuda'
ggml_init_cublas: GGML_CUDA_FORCE_MMQ:   no
ggml_init_cublas: CUDA_USE_TENSOR_CORES: yes
ggml_init_cublas: found 1 CUDA devices:

llama_cpp_cuda error (as to be expected as it was uninstalled)
then the No, Yes not consistent with the original, fast prompt eval environment :(

llm_load_tensors: using CUDA for GPU acceleration
llm_load_tensors: system memory used  =   53.82 MiB
llm_load_tensors: VRAM used           = 2757.30 MiB
llm_load_tensors: offloading 32 repeating layers to GPU
llm_load_tensors: offloading non-repeating layers to GPU
llm_load_tensors: offloaded 33/33 layers to GPU

that's looking better and more consistent with the original, fast prompt eval model :)
Finally I see this the proper use of the CPU features and BLAS=1 !!

AVX = 1 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 0 | VSX = 0 |

but the proof is in the running of the model.... and it's a fast prompt eval, minimal CPU usage, fast output  !!!
so what changed:

not using llama_cpp_python
self-compiled version of llama-cpp-python 0.2.26

so good call on the suggestion (thanks!) but I'm at a lost to explain the variations I've seen. python and dependencies eh?
would love to understand the reason behind using llama-cpp-python-cuda over just llama-python-cpp (of course compiled for cuda)?

set LLAMA_CUBLAS=1

I've never used that so far in compiling llama-cpp-python.  What does set LLAMA_CUBLAS=1 do?

Actually 0.2.55 is much faster:
Linux:
pip uninstall llama_cpp_python llama_cpp_python_cuda -y
export LLAMA_CUBLAS=1
export CMAKE_ARGS="-DLLAMA_CUBLAS=on -DCMAKE_CUDA_ARCHITECTURES=all"
export FORCE_CMAKE=1
pip install llama_cpp_python==0.2.55 --force-reinstall --no-cache-dir

Windows the equivalent is:
pip uninstall llama_cpp_python llama_cpp_python_cuda -y
set CMAKE_ARGS=-DLLAMA_CUBLAS=on -DCMAKE_CUDA_ARCHITECTURES=all
set LLAMA_CUBLAS=1
set FORCE_CMAKE=1
pip install llama_cpp_python==0.2.55 --force-reinstall --no-cache-dir

Metal equivalent is:
pip uninstall llama_cpp_python llama_cpp_python_cuda -y
export LLAMA_CUBLAS=1
export CMAKE_ARGS="-DLLAMA_METAL=on"
export FORCE_CMAKE=1
pip install llama_cpp_python==0.2.55 --force-reinstall --no-cache-dir

ok so final tests and llama_cpp-python-cuda seems to be the culprit.
if I uninstall llama_cpp-python-cuda everything speeds up - regardless if I use llama-cpp-python==0.024 or ==0.2.55
also it seems that llama_cpp-python-cuda sets GGML_CUDA_FORCE_MMQ: yes and after its removal CUDA_USE_TENSOR_CORES: is set to yes instead.  From a (very) quick search GGML_CUDA_FORCE_MMQ: yes is for older HW and TENSOR_CORES are preferred.  So that's odd behaviour.
Anyway, I now have a working h2ogpt with GPU support and acceptable performance on Windows, and I've got some more insights into under the hood stuff.  Now I'll be focussing on the features of h204gpt.  Thanks again for staying the course, it was helpful bouncing off your comments and suggestions.
I am still curious though why llama-cpp-python-cuda is used at all.

For me 0.55 is much faster than 0.26.  So I recommend sticking with .55.
llama-cpp-python-cuda is built by jllll as prebuilt wheels so user doesn't have to build them, which may require installing some things or taking time.  It also allows for separate CPU and GPU use with same installation, since each package will be used separately if using CUDA or not.


text:
Assegnato un nuovo spreasheet ad ogni nuovo utente

closes #7
Non sono totalmente soddisfatto, dacci un'occhiata tu @Arkango
Ho scoperto che il bug di gspread che sposta ogni nuova riga più a destra è legato alla presenza di celle vuote tra le righe da aggiungere. Tuttavia pare che il problema non compaia se la prima riga del worksheet non contiene celle vuote. Per questo motivo, come workaround, ho aggiunto la riga:
self.worksheet.append_row(['Timestamp', 'Activity', 'Valence', 'Arousal', 'Status', 'Notes'],"RAW")

C'è anche un altro bug che impedisce di condividere lo spreadsheet se lo si fa subito dopo la creazione del file. Ho provato ad aggiungere una funzione che aspetta che il file sia effettivamente creato, ma niente.
Come workaround ho aggiunto una sleep() di qualche secondo.
Ad ogni modo, lo spreadsheet viene condiviso con le mail che si trovano nel file data/sharelist.txt. Le mail devono essere inserite una per ogni riga.

del fatto che le celle vadano, sempre più a destra non lo avevo rilevato personalmente.
Per la questione dovresti lavorare con un evento e funzioni di callback

del fatto che le celle vadano, sempre più a destra non lo avevo rilevato personalmente.

ecco un esempio: https://docs.google.com/spreadsheets/d/1iXJJD6Nzq-BfYvqx4mlOVhNNGQxjrIVDkW4-gJvRu1k/edit?usp=sharing

Per la questione creazione dile condivisione dovresti lavorare con un evento e funzioni di callback

purtroppo le funzionalità della libreria gspread sono relativamente limitate

Il problema dello sleep() è che non potevo avere la certezza che al termine di esso la condivisione avrebbe funzionato.
Ho più o meno risolto catturando l'errore generato dalla mancata condivisione e ritentando fino a quando non si supera 10 tentativi (per evitare cicli infiniti nel caso di email non valide).


text:
botdotpng

Your checklist for this pull request
Author name
Author: Kai

About your game
What is your game about?
Teaching a robot to reach it's flag by placing arrows

How do you play your game?
WASD - Move Cursor
I - Spawn in bot
J - Rotate an arrow
K - Cycle though the tutorial text
L - Changes a tile (turns an empty tile into an arrow, and back, or if you have unlocked conditionals, it will cycle between normal, conditional, or empty)

Code
Check off the items that are true.

[x] The game was made using the Sprig editor.
[x] The game is placed in the in the /games directory.
[x] The game runs without errors.
[x] The code is significantly different from all other games in the Sprig gallery (except for games labeled "demo").
[x] The name of the file/game contains only alphanumeric characters, -s, or _s.
[x] The game name is not the same as the others from gallery

Image (If an image is used)

[ ] The image is in the /games/img directory.
[ ] The name of the image matches the name of your file.

Thanks for your PR!

despite being called 'dotpng' the art isn't very good

I also have no reason why I called it that..

Great job with this project- this was really interesting to play with. I'm approving it, and you should see it in the gallery next week.
If you're a teenager, you can request a free Sprig console at this link and join our online Slack community to chat with other people making Sprig games.

Thank you so much! I updated the branch so it can merge, I'm not sure if sprig maintainers have edit access to my branch.

authors: mavdotjs recursiveforte

repo: hackclub/sprig


text:
[크레센도] 해커톤 앱 제출

제목
팀 앱 제출 2차
팀 이름
크레센도
팀 리포지토리
https://github.com/hackersground-kr/hg-crescendo-server

git 환경 설정 내용이 없습니다.

repo: hackersground-kr/hackers-ground


text:
Feature: Support for Scribus SLA format

Would it be possible to autogenerate a Scribus .sla using HackMyResume?

Yes, assuming an .sla text/XML format under the hood, HMR could generate it. This would require a template but not much in the way of code. If this interests you, and you have a sample handy, we can tear off an experimental theme.

Added to https://github.com/hacksalot/HackMyResume/blob/dev/ROADMAP.md. Thanks!

authors: hacksalot luzpaz

repo: hacksalot/HackMyResume


text:
fix(engine/deps): preserve definitions order whenever possible

In most of the backends, a top-level definition should come prior to it's use. This is not true in Rust.
Thus, we need to sort the items so that item a comes before it is used in another item b.
We used to do that with a topological sort with the ocamlgraph library. But since this topological sort operated on a graph, we were loosing the original order of items.
This commit now:

construct a the transtive closure of the dependency graph
use this closure to stable sort the items

The comparison function is defined as follows (g denotes the transitive closure):

if there is an edge a ⟶ b in g and an edge b ⟶ a, we are in a recursive bundle, hence we return 0: a equals b
if there is an edge a ⟶ b in g, we return -1
if there is an edge b ⟶ a in g, we return 1
otherwise there is no relation between a and b, we return 0

The run for this PR on libcrux is there:

https://github.com/cryspen/libcrux/actions/runs/12068668021/job/33654275770

https://github.com/hacspec/hax/issues/771

repo: hacspec/hax


text:
🛑 GeekNews - https://news.hada.io is down

In 4342360, GeekNews - https://news.hada.io (https://news.hada.io) was down:

HTTP code: 0
Response time: 0 ms

Resolved: GeekNews - https://news.hada.io is back up in d6457f7.

repo: hada-io/upptime


text:
FileNotFoundError: [Errno 2] No such file or directory: 'ffmpeg': 'ffmpeg'

Describe the bug
I use Odoo 14, with docker
In docker file:
RUN pip3 install python-ffmpeg-video-streaming
When I get the above error, I have more: RUN pip3 install ffmpeg-python but can't
Logs
2023-06-09 09:36:03,411 1 INFO djc root: /mnt/extra-addons/djc_library/static/files/slide/95/mov_bbb.mp4
2023-06-09 09:36:03,412 1 INFO djc root: <ffmpeg_streaming.input.Input object at 0x7f0d2c354978>
2023-06-09 09:36:03,413 1 INFO djc root: <ffmpeg_streaming.media.DASH object at 0x7f0d2c330ba8>
2023-06-09 09:36:03,415 1 INFO djc root: [Errno 17] File exists: '/mnt/extra-addons/djc_library/static/files/slide/95'
2023-06-09 09:36:03,416 1 INFO djc root: ffmpeg running command: ffmpeg -y -i /djc_library/static/files/slide/95/mov_bbb.mp4 -c:v libx264 -c:a aac -bf 1 -keyint_min 25 -g 250 -sc_threshold 40 -use_timeline 1 -use_template 1 -init_seg_name mov_bbb_init$RepresentationID$.$ext$ -media_seg_name mov_bbb_chunk$RepresentationID$_$Number%05d$.$ext$ -f dash -map 0 -s:v:0 256x144 -b:v:0 95k -b:a:0 64k -map 0 -s:v:1 426x240 -b:v:1 150k -b:a:1 94k -map 0 -s:v:2 640x360 -b:v:2 276k -b:a:2 128k -map 0 -s:v:3 854x480 -b:v:3 750k -b:a:3 192k -map 0 -s:v:4 1280x720 -b:v:4 2048k -b:a:4 320k -map 0 -s:v:5 1920x1080 -b:v:5 4096k -b:a:5 320k -map 0 -s:v:6 2560x1440 -b:v:6 6144k -b:a:6 320k -map 0 -s:v:7 3840x2160 -b:v:7 17408k -b:a:7 320k -strict -2 /mnt/extra-addons/djc_library/static/files/slide/95/mov_bbb.mpd
2023-06-09 09:36:03,422 1 ERROR djc odoo.http: Exception during JSON request handling.
Traceback (most recent call last):
File "/usr/lib/python3/dist-packages/odoo/addons/base/models/ir_http.py", line 237, in _dispatch
result = request.dispatch()
File "/usr/lib/python3/dist-packages/odoo/http.py", line 696, in dispatch
result = self._call_function(**self.params)
File "/usr/lib/python3/dist-packages/odoo/http.py", line 370, in _call_function
return checked_call(self.db, *args, **kwargs)
File "/usr/lib/python3/dist-packages/odoo/service/model.py", line 94, in wrapper
return f(dbname, *args, **kwargs)
File "/usr/lib/python3/dist-packages/odoo/http.py", line 358, in checked_call
result = self.endpoint(*a, **kw)
File "/usr/lib/python3/dist-packages/odoo/http.py", line 919, in call
return self.method(*args, **kw)
File "/usr/lib/python3/dist-packages/odoo/http.py", line 544, in response_wrap
response = f(*args, **kw)
File "/usr/lib/python3/dist-packages/odoo/addons/web/controllers/main.py", line 1370, in call_kw
return self._call_kw(model, method, args, kwargs)
File "/usr/lib/python3/dist-packages/odoo/addons/web/controllers/main.py", line 1362, in _call_kw
return call_kw(request.env[model], method, args, kwargs)
File "/usr/lib/python3/dist-packages/odoo/api.py", line 399, in call_kw
result = _call_kw_multi(method, model, args, kwargs)
File "/usr/lib/python3/dist-packages/odoo/api.py", line 386, in _call_kw_multi
result = method(recs, *args, **kwargs)
File "/mnt/extra-addons/djc_library/models/slide_channel.py", line 451, in write
chanel = super().write(values)
File "/usr/lib/python3/dist-packages/odoo/addons/website_slides/models/slide_channel.py", line 416, in write
res = super(Channel, self).write(vals)
File "/usr/lib/python3/dist-packages/odoo/addons/mail/models/mail_thread.py", line 322, in write
result = super(MailThread, self).write(values)
File "/usr/lib/python3/dist-packages/odoo/addons/rating/models/rating_mixin.py", line 82, in write
result = super(RatingMixin, self).write(values)
File "/usr/lib/python3/dist-packages/odoo/addons/mail/models/mail_activity.py", line 788, in write
return super(MailActivityMixin, self).write(vals)
File "/usr/lib/python3/dist-packages/odoo/addons/website/models/mixins.py", line 205, in write
return super(WebsitePublishedMixin, self).write(values)
File "/usr/lib/python3/dist-packages/odoo/models.py", line 3681, in write
field.write(self, vals[fname])
File "/usr/lib/python3/dist-packages/odoo/fields.py", line 3057, in write
return self.write_batch([(records, value)])
File "/usr/lib/python3/dist-packages/odoo/fields.py", line 3078, in write_batch
return self.write_real(records_commands_list, create)
File "/usr/lib/python3/dist-packages/odoo/fields.py", line 3233, in write_real
comodel.browse(command[1]).write(command[2])
File "/mnt/extra-addons/djc_library/models/slide_slide.py", line 390, in write
self.local_file(self)
File "/mnt/extra-addons/djc_library/models/slide_slide.py", line 465, in local_file
dash.output(file_path.replace('.mp4', '.mpd'))
File "/usr/local/lib/python3.7/dist-packages/ffmpeg_streaming/_media.py", line 93, in output
self.run(ffmpeg_bin, monitor, **options)
File "/usr/local/lib/python3.7/dist-packages/ffmpeg_streaming/_media.py", line 121, in run
asyncio.run(self.async_run(ffmpeg_bin, monitor, **options))
File "/usr/lib/python3.7/asyncio/runners.py", line 43, in run
return loop.run_until_complete(main)
File "/usr/lib/python3.7/asyncio/base_events.py", line 584, in run_until_complete
return future.result()
File "/usr/local/lib/python3.7/dist-packages/ffmpeg_streaming/_media.py", line 112, in async_run
self._run(ffmpeg_bin, monitor, **options)
File "/usr/local/lib/python3.7/dist-packages/ffmpeg_streaming/_media.py", line 105, in _run
with Process(self, command_builder(ffmpeg_bin, self), monitor, **options) as process:
File "/usr/local/lib/python3.7/dist-packages/ffmpeg_streaming/_process.py", line 58, in init
self.process = _p_open(commands, **options)
File "/usr/local/lib/python3.7/dist-packages/ffmpeg_streaming/_process.py", line 29, in _p_open
return subprocess.Popen(shlex.split(commands), **options)
File "/usr/lib/python3.7/subprocess.py", line 775, in init
restore_signals, start_new_session)
File "/usr/lib/python3.7/subprocess.py", line 1522, in _execute_child
raise child_exception_type(errno_num, err_msg, err_filename)
Exception
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/usr/lib/python3/dist-packages/odoo/http.py", line 652, in _handle_exception
return super(JsonRequest, self)._handle_exception(exception)
File "/usr/lib/python3/dist-packages/odoo/http.py", line 317, in _handle_exception
raise exception.with_traceback(None) from new_cause
FileNotFoundError: [Errno 2] No such file or directory: 'ffmpeg': 'ffmpeg'

you need to install ffmpeg into your docker file like :
RUN apt-get update && apt-get install -y  ffmpeg


text:
Test cases using shapely

This PR contains:

[X] a new test-case for the benchmark

[X] I hereby confirm that NO LLM-based technology (such as github copilot) was used while writing this benchmark

[ ] new dependencies in requirements.txt

[ ] The environment.yml file was updated using the command conda env export > environment.yml

[ ] new generator-functions allowing to sample from other LLMs
[ ] new samples (sample_....jsonl files)
[ ] new benchmarking results (..._results.jsonl files)
[ ] documentation update
[ ] bug fixes

Related github issue (if relevant): closes #0
Short description:

Including Point and polygon operations using shapely.

How do you think will this influence the benchmark results?

This will add polygon related operations to benchmark results.

Why do you think it makes sense to merge this PR?

Extra test case

Fantastic @pr4deepr ! I tested them and they work very well. I'm going to merge them into the branch with new test-cases.
Thank you!

repo: haesleinhuepf/human-eval-bia


text:
Enhance docstrings

Enhance docstrings of the library so that it follows one of the three major styles (probably Google's one). Related to Issue #54.
The update will be reflected in version 4.2.0, which will be released shortly after 2024-10-01, the scheduled date of Python 3.13 release.

The implementation of this feature has been done in version 5.0.0.


text:
A Nativescript app template for use with tns create --template

The Nativescript CLI can create applications using a template. Instead of having the user using degit, give them the option to use one of these templates. An example template is here
https://github.com/shirakaba/tns-template-blank-react
They are published as a npm package.

Rosen Vladimirov walked me through the process of creating a template here: https://github.com/NativeScript/nativescript-cli/issues/4964

Sweet, thanks for the info

This has been done: https://www.npmjs.com/package/tns-template-blank-svelte

authors: halfnelson shirakaba

repo: halfnelson/svelte-native


text:
Feature Request: Autocomplete

Hi guys,
What about implementing autocomplete support?

Any news about this?

Thanks for reporting @JozefCipa!
I just checked out UI and UX designs for auto complete out there, and I think it's hard to create a generic and good looking auto complete feature in the library.
So I won't be able to implement this feature but I'm open for PRs that can deliver good looking and generic solutions here.

authors: JozefCipa halilb jonathanpalma

repo: halilb/react-native-textinput-effects


text:
typos error  in fallback and typos error in owner sender

hello sir
i got error in specific line in online remix editior

The code was written in a lower version of Solidity then the current
version. Lower the version of solidity being compiled to 0.4.23 and it will
work fine.
On Fri, Jul 5, 2019 at 1:41 AM ethereumbigvena notifications@github.com
wrote:

hello sir
i got error in specific line in online remix editior
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You are receiving this because you are subscribed to this thread.
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or mute the thread
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.

hello
when i connect metamask to myetherwallet
contract is  not deploying due to byte code error


text:
Multiple elm-package.json files

This plugin looks awesome but it crashes when I try to use it. The reason is that my project does not have a elm-package.json at the root of the folder. That's because I have two Elm projects, one for server-side, one for client-side, and some common source code.
├── client
│   ├── [some Elm code]
│   └── elm-package.json
├── server
│   ├── [some Elm code]
│   └── elm-package.json
└── src
    └──  [some common Elm code]

Is there any chance for the plugin to search for elm-package.json files inside subdirectories and support several Elm projects at once? Maybe with some ignored folders (either based on .gitignore or from plugin settings)

Hi, what did you mean by "it crashes"?  Were there error notifications or console errors?

This is what I get right after enabling elmjutsu on my project (atom is opened at the root of the folder, not inside client nor server). Using 2.10.1, I'm having some internet issues and failed to update to last version. Will try again tomorrow.

Ah, I see.  Did you open a .elm file in the src directory (which does not have an elm-package.json)?  When you open a .elm file, Elmjutsu will search for an elm-package.json in that directory or the parent directories.   Elmjutsu will treat the directory (where elm-package.json was found) as the "project directory" and needs to read elm-package.json for info about imports and such.  I don't know how to solve this elegantly right now :disappointed: Suggestions are welcome!

Yeah, you're right... I can see a way to do that either. So I tried to create a "fake" elm-package.json at the root of the project with all dependencies from both client and server but I got a new error.

Hi, do you have a sample project that I can use to replicate the issue?

Hi, does the new directory structure look like this?
├── client
│   └── [some Elm code]
├── server
│   └── [some Elm code]
└── src
    └──  [some common Elm code]
└── elm-package.json

Yes, exactly. I will try to do the sample project this weekend.
Le 19 janv. 2017 8:47 AM, "halohalospecial" notifications@github.com a
écrit :
Hi, does the new directory structure look like this?
├── client
│   └── [some Elm code]
├── server
│   └── [some Elm code]
└── src
└──  [some common Elm code]
└── elm-package.json
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https://github.com/notifications/unsubscribe-auth/ABN1neAW3qpKcT1QcLH5ak1j83IzjmZ3ks5rTxT3gaJpZM4LcFHd
.

Doing the sample project, I realized I had a wrong configuration in the project (one wrong source-directories in the elm-package.json). Fixing it fixed the Atom error.
There is only one thing that's not working but that's ok because I don't see any way how it could. It's the autocompletion when both client and server have the same module inside their respective folders exposing the same API (for example, a logger implementation) which is imported inside the common Elm code. Using the top level elm-package.json, there is no way to know which one is used.
Thanks again for the plugin!

authors: halohalospecial pauldijou

repo: halohalospecial/atom-elmjutsu


text:
⚠ ClamAV has degraded performance

In 72fa9e4, ClamAV (https://spamassassin.apache.org/) experienced degraded performance:

HTTP code: 200
Response time: 87 ms

Resolved: ClamAV performance has improved in bfc6ce7.

repo: hamboneZA/caffeine


text:
⚠ ClamAV has degraded performance

In 6a0275d, ClamAV (https://spamassassin.apache.org/) experienced degraded performance:

HTTP code: 200
Response time: 252 ms

Resolved: ClamAV performance has improved in d14f65a after 5 minutes.


text:
⚠ ClamAV has degraded performance

In d852366, ClamAV (https://spamassassin.apache.org/) experienced degraded performance:

HTTP code: 200
Response time: 46 ms

Resolved: ClamAV performance has improved in 2dce96d.


text:
⚠ ClamAV has degraded performance

In 9b4f285, ClamAV (https://spamassassin.apache.org/) experienced degraded performance:

HTTP code: 200
Response time: 190 ms

Resolved: ClamAV performance has improved in 0b15e41.


text:
⚠ ClamAV has degraded performance

In 7f3a05b, ClamAV (https://spamassassin.apache.org/) experienced degraded performance:

HTTP code: 200
Response time: 54 ms

Resolved: ClamAV performance has improved in 92cef9a.


text:
⚠ ClamAV has degraded performance

In b7bbfea, ClamAV (https://spamassassin.apache.org/) experienced degraded performance:

HTTP code: 200
Response time: 588 ms

Resolved: ClamAV performance has improved in 8f37d7f.


text:
⚠ ClamAV has degraded performance

In a34e118, ClamAV (https://spamassassin.apache.org/) experienced degraded performance:

HTTP code: 200
Response time: 141 ms

Resolved: ClamAV performance has improved in 90cb71f.


text:
How can i write list?

Hello, how i can write like this:
this.items = db.list('news', ref => ref.orderByChild('time').limitToFirst(25)).valueChanges(); ?

@Gorniv Thank you for posting the very issue here and it is a good one.
AngularFire Lite does not complicate things so when you want to read data from the realtime database you have to remember only one function that you are going to use 99% of the time which is the read function which you should pass it the reference to the database.
the functions returns the actual data when you give it the absolute path to the data (example: string)
    this.database = this.db.read('hellolist/hellodata');
    this.database.subscribe((data) => {
      console.log(data); // console logs the string stored in the database
      this.databaseData = data;
    });

and returns an object when you give it the absolute path to a data list.
    this.database = this.db.read('hellolist');
    this.database.subscribe((data) => {
      console.log(data); // console logs an object containing hellodata and other key value pairs
      this.databaseData = data;
    });

everything works if you simply want to use that data but as it is but as you know the ngFor does not support looping over objects so this is a great reminder to add support for ngFor which will be fixed in the next very few days. So thank you for posting this issue as this helps improving the library

@Gorniv Thank you for posting the very issue here and it is a good one.
AngularFire Lite does not complicate things so when you want to read data from the realtime database you have to remember only one function that you are going to use 99% of the time which is the read function which you should pass it the reference to the database.
the functions returns the actual data when you give it the absolute path to the data (example: string)
    this.database = this.db.read('hellolist/hellodata');
    this.database.subscribe((data) => {
      console.log(data); // console logs the string stored in the database
      this.databaseData = data;
    });

and returns an object when you give it the absolute path to a data list.
    this.database = this.db.read('hellolist');
    this.database.subscribe((data) => {
      console.log(data); // console logs an object containing hellodata and other key value pairs
      this.databaseData = data;
    });

everything works if you simply want to use that data but as it is but as you know the ngFor does not support looping over objects so this is a great reminder to add support for ngFor which will be fixed in the next very few days. So thank you for posting this issue as this helps to improve the library

@Gorniv Fixed it! 🎉
now you can use the *ngFor directive with async pipe if you pass a path pointing to a list in your real-time database to the read function. so now you can do the following to iterate over a list:
1. Inject the AngularFire Lite database service:
  constructor(public db: AngularFireLiteDatabase) {}
2. reference the list of data in your real-time database by passing its path to the read function
this.items = this.db.read('news');
3. then you iterate over all the data and print it in your template like this:

{{item}}

again thank you for posting this issue and if you have any feature request please open an issue here and I will try my best to add it in few days or in few hours if that is possible.

authors: Gorniv hamedbaatour

repo: hamedbaatour/angularfire-lite


text:
Add cashflow queries

(Also includes some auto-formatting changes)

Also a question about the need to specify date range params by default, as the rest of the Monarch gql calls don't require them and have default behavior.

You are right, the dates in the gql are optional, but it doesn't give predictable results. it returns the cashflow for the previous month when no dates specified. I think setting defaults to the current month keeps it predictable for the caller (e.g. Home Assistant) so they don't need to pass start_date, end_date to get latest cashflow data

repo: hammem/monarchmoney


text:
Add link to Dan Nguyen's journalism-syllabi repository

Just came across this, seems like an excellent addition.
https://github.com/dannguyen/journalism-syllabi

Computer-Assisted Reporting and Data Journalism Syllabuses
This is a collection of computational and data journalism courses for which there is a publicly available homepage or syllabus suitable for others to use as a guiding reference, i.e. basically anything that shows up in a Google search for syllabus + computational/data/research + journalism / computer assisted reporting.
Data/computational journalism is still a relatively new field, so it can be hard to know what's possible to fit in a curriculum. Hopefully, the 230+ course syllabuses – and in many cases, open source code/data repos – listed here can provide  helpful guidance!
Jump to the list of 230+ courses

https://github.com/simonw/datasette

An open source multi-tool for exploring and publishing data
Datasette is a tool for exploring and publishing data. It helps people take data of any shape or size and publish that as an interactive, explorable website and accompanying API.
Datasette is aimed at data journalists, museum curators, archivists, local governments, scientists, researchers and anyone else who has data that they wish to share with the world.

https://github.com/uwdata/visualization-curriculum

I'm not sure where to link to it since it's tangential to the doc. I'm closing the issue for now, though I might still add the links if I think of where to put them.

repo: hangtwenty/dive-into-machine-learning


text:
Underscore symbol pattern doesn't compile

Clang 5.0
Regular expression with single underscore _ does not compile.
But something like [_] compiles.
#include <ctre/include/ctre.hpp>

int main(int, char**)
{
  using namespace ctre::literals;
  "_"_ctre.match("_");
  return 0;
}

In file included from ctre_test/main.cpp:1:
In file included from ctre/include/ctre.hpp:4:
ctre/include/ctre/literals.hpp:55:2: error: static_assert failed due to requirement 'tmp()' "Regular Expression contains syntax error."
        static_assert(tmp(), "Regular Expression contains syntax error.");
        ^             ~~~~~
main.cpp:6:6: note: in instantiation of function template specialization 'ctre::literals::operator""_ctre<char, '_'>' requested here
  "_"_ctre.match("_");
     ^

Fixed in 6dd786b4f0572f5052efda61d055aa16a003b413

authors: hanickadot kroburg


text:
人名识别不准确

林军和大壮从侧门，被两个警察带进了市场旁边的一个大院内，随即直接进了办公楼里。
“这派出所挺大啊？”林军看着狭长的走廊，表情有些惊愕的说了一句。
“大哥，这是市局七处！”男警察斜眼回了一句。
市公安局第七刑侦大队，俗称七处，部门职责是主抓特大重点案件。
“咋给我们带这儿来了？”林军听后一愣。
“来，左边一个，右边一个，靠着暖气站好！”女警冲着林军和大壮，俏脸面无表情的说道。
二人听到这话，也没争辩，随后各自靠着暖气站了下来。而女警走进办公室取了两幅手铐，随即将二人分别铐在暖气管子上说道：“等着吧，一会派出所过来取你们俩。”
林军右手被铐上时,正好与女警脸对脸，随即他双眼本能的打量了女警一下。
她的长相有些特别，长发披肩，五官精致，但鼻梁很高，眼窝较深，一双灵动的大眼睛非常夺目。看着有点不像汉人五官，而是有点像史密斯夫妇中的安吉丽娜.茱莉！
女警身段挺直，个子起码一米七左右，上半身套着一件紧身的半袖警服衬衫，领口扣子系的一丝不苟。她下半身穿着黑蓝色宽松的长裤，脚上蹬着一双平底的黑色瓢鞋，整个人的气质给人一种充满活力，英姿飒爽的感觉。
“哎，郑警官，我俩这就是喝多了瞎闹腾，犯不上在你这儿占地方。你给我俩松开，我俩一块去派出所和解了得了。”大壮此刻已经有点被揍的醒酒了，他左手捂着还在淌血的嘴唇，随即含糊不清的喊道。
“闭上你的嘴，呆着！”女警厌恶的扫了他一眼，随后冲收发室喊道：“李叔，帮忙看一下，一会把他们交给派出所就行。”
“好叻！”　收发室的大爷回了一句。
随后女警踩着平底鞋就上了楼，而跟他一起的那个男警察转身再次去了市场，继续去给加班的同事买盒饭。
走廊内，工作人员来回穿梭，而林军和大壮相互对视了一眼。
“操你玛，你等出去的！我让你知道，你打我的那一酒瓶子有多无知！”大壮看着林军小声骂道。
林军将头扭过去，根本没回话。
......
四十分钟以后，派出所一个民警，带着一个二十六七的青年，并肩走进了走廊。民警进来以后，就直接走进了办公室，而青年腋下夹着包，脖子上挂着佛牌，手里搓着珠子冲大壮骂道：“一天净他妈给我惹事儿！”
“涛，你看他给我干的，嘴唇子都整豁豁了。”大壮指着自己的嘴唇子说道。
“你闭嘴吧！”青年回了一句，随后朝着民警走进的办公室走去。
二十分钟以后，民警和青年走了出来。
“王涛，谁是你朋友啊？”民警虎着脸，背手问道。
“就他！”叫王涛的青年指了指大壮。
民警扫了一眼林军和大壮，随即皱眉问道：“就这点破事儿，还用我调解啊？用验伤吗？”
“我不用！”大壮思考了一下，干脆的回道。
“我也不用！”林军扫了一眼三人，也面无表情的回道。
“真不用啊？”民警冲着林军再次问道。
“不用。”林军毫不犹豫的摇了摇头。
“打开，走吧！”民警随手拿着钥匙交给了王涛。
王涛接过钥匙，将大壮的铐子打开，然后又将钥匙扔给了林军。
“谭哥，麻烦了，明儿请你吃饭啊。”王涛笑着冲民警说道。
“轻点嘚瑟比啥都强，走吧，走吧。”民警淡然的摆了摆手。
“那我走了，谭哥！”
王涛冲民警打了个招呼，随后带着大壮扬长而去。林军摘下手铐以后，竖起大拇指冲民警说道：“这案子办的真利索！”
“你还有事儿啊？”民警回头，面无表情的问道。
“呵呵，没事儿。”林军放下手铐，随即头也不回的走出了七处。
.......
一个半小时以后，时间接近晚上七点多。
林军刚刚收拾完自己的小摊，并将烧烤用具放在了张小乐的三轮子上。
“今天不出了？”
张小乐站在一旁，张嘴问道。
“还出啥出，货都让他踩了。”林军有点心烦的回道。
“行，那我跟你把东西送回去。”张小乐穿着工作服，挺仗义的回了一句。
“不用了，你卖货吧，车借我用用就行。”林军骑上三轮子，咧嘴一笑说道。
“要不今天你别送了，东西直接扔我这儿得了。”张小乐明显有点担心的说道。
“呵呵。”林军一笑，也没多说，骑车就走了。
．．．．．．．
市场后方的小路上，林军健硕有力的双腿蹬着人力三轮车，顺着灯光昏暗的街道一路前行。
“咚咚咚！”
距离存放烧烤用具的车棚，还有一半路程时，小路对面突然泛起一阵农用三轮子的声响。
“吱嘎！”
林军踩了一脚刹车，右脚点地，眯着眼睛向前方望去。
“就那个傻Ｂ，一会给我往死怼他！”骑在三轮子上的大壮，满嘴漏风的大吼了一句。
大壮喊完，对方三轮车距离林军不超过二十米远后停滞，几乎同时，一副极为震撼的画面出现在林军眼中！
农用三轮子是摩托式的，马力很小，具体大小也就跟路边拉黑活的那种“摩的”差不多，而这车的车斗载重量，估计也就能拉几袋百斤重的大米。
但今天这个农用三轮子却突破了极限，就不足一米半长的车斗，竟然宛若春运火车车厢一般，拥挤得往下跳人！
一个，两个，三个.......
数秒过后，车斗之上竟然跳下来七个成年人！七个啊！天知道他们是怎么挤上去的，此场景即使跟印度三哥PK一下，那他妈也不差啥了！
“我操！”林军数着对方跳下来的人，脸色被雷的有点惊愕。
“呼啦啦！”
大壮跳下摩托车，右手从车斗中抽出一把片刀，随即带着七个人，手里拿着铁棍子，镐把子，镰刀，还有街头斗殴中百年难得一见的炉钩子等异样凶器，蜂拥着冲向林军。
“咣当当！”
林军下车，在自知无法躲避这场斗殴之时，立马回手从三轮车上抽出一根半米长的空心钢管，随后眉头都没皱一下，迈步就冲向人群。
双方碰见，基本没有废话，直接就开怼。
对方一个老农，抡着镰刀直接刨向林军，而林军侧身一闪，右臂摆动幅度很小，但右手攥着的钢管却闪电般的抽在了老农的手腕上。
当的一声，老农本能一缩手，林军手持钢管对着他脑袋，眨眼间就抽了三下，直接将其放倒。
其余众人冲上，林军左手抓过一人的脖领子，宛若拎着鸡崽子一般，直接将其摆在身前，随即他身体晃了一下，右手攥着钢管，对着旁边的大壮，反手就抽了过去！
“嘭！”
钢管抽在大壮嘴上，他疼的一蹦半米高。
“噼里啪啦！”
对方砸下来的武器，根本无处躲避的干在林军和对方那人的身上。
“往他手上砍！就照一万块钱干他了！”大壮捂着嘴，跳脚吼道。
林军额头，胳膊开始冒血，他左胳膊一甩，右腿一扫，直接将抓着的汉子绊倒。
“操你玛，我拿枪说话，拿刀吃饭的时候，你们还蹲地沟垄里唱东方红呢！”林军根本没管其他人，双手攥着钢管，胳膊卯足劲的往抡了数下。
“嘭！”
“嘭！”
“嘭！”
三声脆响，在林军身下这人的脑袋上，脖子上，后背上接连响起！
“呼啦啦！”
林军心黑手狠的干完这三下，人群顿时散开，众人看着他稍微有那么点犯怵！
“唰唰！”
与此同时，街口处有四台出租车匆忙赶来，这些车支着远光灯，停在路边。
“咣当！”
车门推开，张小乐扯脖子喊道：“军，谁他妈要干你啊？”
大壮团伙一看街口停了四台出租车，同时双眼又被大灯晃的看不清楚张小斌带来多少人，所以，他们第一时间掉头就跑，连能拉七个人的神奇农用三轮子都扔下了。
“咣当！”
林军脸不红气不喘的将钢管扔进自己的三轮车，随后伸手熟练的摸了一下后背。手指碰触皮肤，他感觉出后背没有刀伤，但回头再看右臂的时候，一个不足半指长的刀口，流着血，而皮肉已经翻开了。
“没事儿吧？”张小乐呼哧带喘的跑过来问道。
“没事儿，胳膊上划了一下。”林军拿起车上的餐巾纸，一下抽出了半盒的厚度堵在了伤口上，随即扭头冲着张小乐问道：“你都带谁过来的？”
“带个屁，四台出租车全是空的，现在的人，能借给你钱，就算好哥们了，哪有还能帮忙干仗的？”张小乐随口回了一句。
“谢了，乐乐！”林军愣了一下，随即认真的说道。
“谢的事儿回头再说，走吧，上医院看看！”张小乐拉着林军，继续说道：“他们这帮人，全是周边农村的，相互都认识，一会说不定叫来多少人！”
“他们跟谁玩的？”林军思考一下，直接问道。
“你要干啥啊？”张小乐一愣。
“这点破事儿不整明白了，我看是没完没了了。”林军低头回道。
“军，犯得上吗？”张小乐一听这话，顿时沉默几秒后皱眉问道。
“干都干了，你说咋整？今天要是没个结果，那明天我还能不能干活了？”林军简洁明了的回了一句，随即再次问道：“他们是跟谁玩的？”
“王涛。”张小乐思考了一下，随后还是如实相告。
“二十多岁，脖子上挂着佛牌儿，没事儿手里还愿意搓着珠子，是他吗？”林军脑中瞬间想起在七处走廊碰见的那个青年。
“对！”
“他不行，段位太低，他上面还有人吗？”林军摇头再问。
“大哥，你太狂点了吧？”张小乐愣了一下，随即惊愕的问道。
“这事儿跟你说不明白，一个段位，一个谈法！”林军干脆的回道。
“……王涛是跟满北伐玩的！”
“他在哪儿？”
“满北伐是整建筑的，手里有车队，人好像在江北望江别苑的三期工地里呢！”张小乐回了一句。
“谢了，你帮我把东西送回去，回来请你吃饭！”林军听完以后拍了拍张小乐的肩膀，随即转身就走。
两分钟以后，林军单人单骑，打了一辆出租车，直奔江北望江别苑。
这样一段文本，识别人名结果是：[林军, 史密斯, 安吉丽娜, 茱莉, 郑警官, 李叔, 操你玛, 都整豁, 王涛, 瑟比, 张小乐, 米高, 钱干他, 黑手, 张小斌, 连能拉, 都带谁]
请问识别出的这些不准确的，应该怎样才能尽量排除？

这些大量使用方言和网络用语的网络小说建议使用CRFSegment。
[嘴唇子, 都, 整, 豁豁, 了]

CRFSegment为什么比较适合呢？试过了，比较准确，但是不是很全。

这涉及到底层模型原理了，请查一下论文。

authors: hankcs xiyangzp

repo: hankcs/HanLP


text:
Bool header filter icons are mixed up

The icons for the header filter boolean options are mixed up. See figures below. This is a problem with panel and we should probably report the issue to them, but perhaps we can fix it ourselves.
"False" shows all

"True" shows selected

And having neither shows the ones that are not selected

In summary False == all, True == True and all == False

This bug is present even on their example on their documentation website. See "Client-side filtering" on this page https://panel.holoviz.org/reference/widgets/Tabulator.html

This is a Panel issue so we wont fix it

repo: hannamlmv/tseda


text:
Error when presenting HelpCentre

Hey,
Trying to update an older Titanium app, I came across your module for Intercom (which is ideal) - however I am getting the following error when trying to present the help centre, or messenger:
[INFO]  [Intercom] ERROR - Cannot present Messenger because no user is registered - you need register a user first -> Showing fallback error screen. Debug info: { has_identity: 1, has_user: 1, has_user_identification: 0 }
I have used the Intercom.registerUser function in the prior line, I noticed another project after googling suggested to the person to use the newer 14 SDK - I wondered if you have either came across this issue, or have plans to update to SDK 14?
Thanks in advance!

Just a note that it seems to work if I call Intercom.registerUser() without any data, but obviously that means that it's not being linked to the user?

repo: hansemannn/titanium-intercom


text:
Russian translation

Hi!
I made a russian tranlation for your mod. Currently as a resoource pack. Could you integrate it inside the mod?
tomes-of-experience-0.0.4-ru.zip

Thanks for contributing this translation! I'll put it into the mod with the next release

Thank you! If you add some more text in the next release, you can ask me to translate.

Implemented in #32

authors: alvlasov hanskroner

repo: hanskroner/tomes-of-experience


text:
新需求?

如果一个sheet里,有页头,OK用cell+part.
接下来是表体,list.OK用table.
那问题来了.如果这时候我还有页脚.
其中又有parameter.这时候就不能正确format了.
因为记录到页脚parameter的point都是旧的.(list 行数未知)
这个问题可能也很常见.可以考虑扩展一下.

不存在这个问题。ExcelReport中存在处理这个问题的机制。

.

authors: JsonRuby hanzhaoxin

repo: hanzhaoxin/ExcelReport


text:
NETWORK ERROR DUE TO HIGH TRAFFIC. PLEASE REGENERATE OR REFRESH THIS PAGE.[Usage]

Describe the issue
Issue:
NETWORK ERROR DUE TO HIGH TRAFFIC. PLEASE REGENERATE OR REFRESH THIS PAGE.
when trying to use as instructed in the demo instructions

how to deal with this？

Have you solved the problem yet?

authors: Coldermyy sivang xiaomatiaobugao

repo: haotian-liu/LLaVA


text:
using Jetson Nx  error

(torch_env) inspur@inspur-desktop:~/torch_long/yolact_edge$ python eval.py --trained_model=/home/inspur/torch_long/yolact/weights/yolact_edge_54_800000.pth --score_threshold=0.3 --top_k=100 --image=/home/inspur/torch_long/yolact/1.jpg:output_image.png
Config not specified. Parsed yolact_edge_config from the file name.
[02/01 11:33:58 yolact.eval]: Loading model...
/home/inspur/torch_long/torch_env/lib/python3.6/site-packages/torch/jit/_recursive.py:165: UserWarning: 'lat_layers' was found in ScriptModule constants,  but it is a non-constant submodule. Consider removing it.
" but it is a non-constant {}. Consider removing it.".format(name, hint))
/home/inspur/torch_long/torch_env/lib/python3.6/site-packages/torch/jit/_recursive.py:165: UserWarning: 'pred_layers' was found in ScriptModule constants,  but it is a non-constant submodule. Consider removing it.
" but it is a non-constant {}. Consider removing it.".format(name, hint))
/home/inspur/torch_long/torch_env/lib/python3.6/site-packages/torch/jit/_recursive.py:165: UserWarning: 'downsample_layers' was found in ScriptModule constants,  but it is a non-constant submodule. Consider removing it.
" but it is a non-constant {}. Consider removing it.".format(name, hint))
[02/01 11:34:08 yolact.eval]: Model loaded.
[02/01 11:34:08 yolact.eval]: Converting to TensorRT...
Traceback (most recent call last):
File "eval.py", line 1241, in
convert_to_tensorrt(net, cfg, args, transform=BaseTransform())
File "/home/inspur/torch_long/yolact_edge/utils/tensorrt.py", line 76, in convert_to_tensorrt
calibration_dataset = pull_calib_dataset(calib_images)
File "/home/inspur/torch_long/yolact_edge/utils/tensorrt.py", line 63, in pull_calib_dataset
calibration_dataset = torch.stack(images)
RuntimeError: stack expects a non-empty TensorList
########################
Who can answer me?

You did not download the calibration images for INT8 conversion. See here.

You did not download the calibration images for INT8 conversion. See here.

Thanks for your quick reply, we have solved this problem, but there is another problem when running  eval.py.

[02/01 16:13:45 yolact.eval]: Loading model...
[02/01 16:13:54 yolact.eval]: Model loaded.
[02/01 16:13:54 yolact.eval]: Converting to TensorRT...
[02/01 16:15:08 yolact.eval]: Converting backbone to TensorRT...
[TensorRT] ERROR: FAILED_ALLOCATION: std::bad_alloc
Traceback (most recent call last):
File "eval.py", line 1241, in
convert_to_tensorrt(net, cfg, args, transform=BaseTransform())
File "/home/inspur/torch_long/yolact_edge/utils/tensorrt.py", line 152, in convert_to_tensorrt
net.to_tensorrt_backbone(cfg.torch2trt_backbone_int8, calibration_dataset=calibration_dataset, batch_size=args.trt_batch_size)
File "/home/inspur/torch_long/yolact_edge/yolact.py", line 1571, in to_tensorrt_backbone
self.trt_load_if("backbone", trt_fn, [x], int8_mode, batch_size=batch_size)
File "/home/inspur/torch_long/yolact_edge/yolact.py", line 1554, in trt_load_if
self.save_trt_cached_module(module, module_name, int8_mode, batch_size=batch_size)
File "/home/inspur/torch_long/yolact_edge/yolact.py", line 1545, in save_trt_cached_module
torch.save(module.state_dict(), module_path)
File "/home/inspur/torch_long/torch_env/lib/python3.6/site-packages/torch/nn/modules/module.py", line 902, in state_dict
hook_result = hook(self, destination, prefix, local_metadata)
File "/home/inspur/torch_long/torch_env/lib/python3.6/site-packages/torch2trt-0.1.0-py3.6-linux-aarch64.egg/torch2trt/torch2trt.py", line 419, in _on_state_dict
state_dict[prefix + "engine"] = bytearray(self.engine.serialize())
TypeError: 'NoneType' object is not iterable
段错误 (核心已转储)

Can you help me?

Did you install the TensorRT and PyTorch with the version in INSTALL.md? If not, what is the version you are using? Can you try running without TensorRT (--disable_tensorrt) and use FP16 only (--use_fp16_tensorrt)?

Did you install the TensorRT and PyTorch with the version in INSTALL.md? If not, what is the version you are using? Can you try running without TensorRT (--disable_tensorrt) and use FP16 only (--use_fp16_tensorrt)?

Yes, I  installed, but for some modules, I didn't follow the INSTALL.md strictly due to Jetson NX (Maybe this is the cause.).  Some modules have been installed with the JetPack4.4.1, as follows:

When I try to run without  TensorRT (--disable_tensorrt) or use FP16 only (--use_fp16_tensorrt), all things are OK but one error:
#######
$ python3 eval.py --disable_tensorrt --trained_model=./weights/yolact_edge_54_800000.pth
Config not specified. Parsed yolact_edge_config from the file name.
loading annotations into memory...
Done (t=1.35s)
creating index...
index created!
[02/01 16:59:11 yolact.eval]: Loading model...
[02/01 16:59:19 yolact.eval]: Model loaded.
Processing Images  ██████████████████████████████   4952 /   4952 (100.00%)     1.86 fps
Saving data...
[02/01 17:44:18 yolact.eval]: Calculating mAP...
[02/01 17:44:50 yolact.eval]:
|  all  |  .50  |  .55  |  .60  |  .65  |  .70  |  .75  |  .80  |  .85  |  .90  |  .95  |
-------+-------+-------+-------+-------+-------+-------+-------+-------+-------+-------+-------+
box | 31.92 | 51.90 | 49.68 | 46.80 | 43.39 | 39.47 | 34.08 | 27.17 | 18.04 |  7.82 |  0.85 |
mask | 29.59 | 47.78 | 45.46 | 42.78 | 39.51 | 35.57 | 31.11 | 25.21 | 17.86 |  9.06 |  1.60 |
-------+-------+-------+-------+-------+-------+-------+-------+-------+-------+-------+-------+
Segmentation fault (core dumped)
#######

You provided the log for --disable_tensorrt, and please confirm it is working for FP16 with --use_fp16_tensorrt. If this is the case, could you try calibrating INT8 with less images with cfg.torch2trt_max_calibration_images (e.g. set to 5).

You provided the log for --disable_tensorrt, and please confirm it is working for FP16 with --use_fp16_tensorrt. If this is the case, could you try calibrating INT8 with less images with cfg.torch2trt_max_calibration_images (e.g. set to 5).

It works after setting cfg.torch2trt_max_calibration_images to 5, no more Segmentation fault (core dumped) error. But for 10, the error occurs again, which is interesting. Anyway, it works, thanks for your patience.
For NX, I get around 13~14 fps using yolact_edge_mobilenetv2_54_800000.pth, which is incredible. However,  taking into the hardware differences between NX and Xavier, the fps is supposed to being higher, I guess. Is there any setting to achieve this? Thanks.

I took a look at this website about the NX and AGX comparison.
It seems that NX has less RAM as well as CPU/GPU cores than AGX. The former might account for your previous OOM issue on calibration with cfg.torch2trt_max_calibration_images=100 but runs fine with five-image calibration.
The latter might suggests why it has inferior FPS than what we have on paper (correct me if the observation is wrong, thanks).
Btw, how do you measure the FPS, using --benchmark or using a video?

authors: haotian-liu weiluonika


text:
dxf Load Exception

Hello
i get an exception on loading a dxf file, because the WidthFactor is set to 300. it's possible to ignore such errors on loading?
rgds
public double WidthFactor
{
get { return this.widthFactor; }
set
{
if (value < 0.01 || value > 100.0)
throw new ArgumentOutOfRangeException(nameof(value), value, "The Text width factor valid values range from 0.01 to 100.");
this.widthFactor = value;
}
}
or
if (degree < 1 || degree > 10)
throw new ArgumentOutOfRangeException(nameof(degree), degree, "The spline degree valid values range from 1 to 10.");

If an out of range value of the WidthFactor of a TextStyle, like in many other similar parameters, is found during while loading a file, the default 1.0 will be used instead. Is your netDxf up to date?
If you are curious check the DxfReader class source code, for the case 41 of the TextStyle read method (line 1955) the default value 1.0 is given for an out of range width factor.
case 41:
    widthFactor = this.chunk.ReadDouble();
    if (widthFactor < 0.01 || widthFactor > 100.0)
        widthFactor = 1.0;
    this.chunk.Next();
    break;

The last case you showed about the spline degree is a worse scenario, if the degree of the spline is out of range you cannot just give the default value of 3, since the list of control points and/or knot values will not correlate.
Daniel

repo: haplokuon/netDxf


text:
Strongly statically typed?

On type_system.asciidoc there's the following sentence:

These aspects of the Erlang type system, strongly statically typed
with an order on the types puts some constraints on the implementation
of the language.

Given what is previously written in the chapter saying that Erlang is strongly statically typed confuses me. Is it really correct?

No. It should say dynamically typed.
I have fixed it now.
Thanks.

authors: alexandrejbr happi

repo: happi/theBeamBook


text:
inline alts need newline

to duplicate: paste the below grammar into ohm-editor, case 0: no error, case 1: uncomment "Thing1a rule" -> parse error in grammar
severity: low
workaround: always include newline after inline "-- ..." alternate declaration

testGrammar {
Main = Thing0a Thing0a
Thing0 =
| A
| B
Thing1 =
| A -- a
| B -- b
Thing0a = | A | B
// Thing1a = | A -- a | B -- b
A = "a"
B = "b"
}

Hi @guitarvydas,
This is how we intended the syntax of "case labels" to work, and our motivation was to keep grammars readable. I would argue that
Thing1
  = A -- a
  | B -- b

is much more readable than
Thing1a = A -- a | B -- b

Now, I understand this may be more heavy-handed than you might like. And it would be great if we could produce a nicer error message for your example. But I don't think it's a good reason to relax the syntax.
Do you disagree?

I don’t disagree, but it wasn’t obvious from the documentation.
I found a (single) edge-case where it made sense to collapse the grammar and have something like Thing1a on one line, but, I usually I don’t do this.
thanks
pt

On Apr 19, 2022, at 1:20 PM, Alessandro Warth @.***> wrote:
Hi @guitarvydas https://github.com/guitarvydas,
This is how we intended the syntax of "case labels" to work, and our motivation was to keep grammars readable. I would argue that
Thing1
= A -- a
| B -- b
is much more readable than
Thing1a = A -- a | B -- b
Now, I understand this may be more heavy-handed than you might like. And it would be great if we could produce a nicer error message for your example. But I don't think it's a good reason to relax the syntax.
Do you disagree?
—
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authors: alexwarth guitarvydas

repo: harc/ohm