[BUG] RuntimeError: The detected CUDA version (12.1) mismatches the version that was used to compile PyTorch (11.8). Please make sure to use the same CUDA versions.

Describe the bug
I'm attempting to install auto-gptq into an environment with:
pip install auto-gptq

The error I get is the following:
File "C:\Users\domin\anaconda3\envs\local-gpt\Lib\site-packages\torch\utils\cpp_extension.py", line 387, in _check_cuda_version
          raise RuntimeError(CUDA_MISMATCH_MESSAGE.format(cuda_str_version, torch.version.cuda))
      RuntimeError:
      The detected CUDA version (12.1) mismatches the version that was used to compile
      PyTorch (11.8). Please make sure to use the same CUDA versions.

      [end of output]

  note: This error originates from a subprocess, and is likely not a problem with pip.
  ERROR: Failed building wheel for auto-gptq
  Running setup.py clean for auto-gptq
Failed to build auto-gptq
ERROR: Could not build wheels for auto-gptq, which is required to install pyproject.toml-based projects

I haven't been able to use my environment with dev or nightly pytorch versions compatible with cuda 12.1 so I was hoping to fix this issue on the AutoGPTQ side. I've checked the nvidia website at https://www.nvidia.com/download/find.aspx looking for an earlier driver version I could downgrade to that would work with cuda 11.8, but the earliest supported is 527.56, which according to https://docs.nvidia.com/deploy/cuda-compatibility/index.html is not compatible with cuda 11.8. I'm not entirely sure how the versioning works though, because despite this my pytorch version compiled with cuda 11.8 works fine with my 12.1 drivers, so I'm unsure why Auto-GPTQ doesn't.
Hardware details
My nvidia gpu and drivers are:
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 535.98                 Driver Version: 535.98       CUDA Version: 12.2     |
|-----------------------------------------+----------------------+----------------------+
| GPU  Name                     TCC/WDDM  | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |
|                                         |                      |               MIG M. |
|=========================================+======================+======================|
|   0  NVIDIA GeForce RTX 2070 ...  WDDM  | 00000000:29:00.0  On |                  N/A |
|ERR!    0C    P0             ERR! / 235W |   1071MiB /  8192MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+

Software version
The version of autogptq pip is attempting to install is:
Downloading auto_gptq-0.2.2.tar.gz (52 kB)

I have also encountered the same issue with:
auto-gptq 0.2.2+cu118

I have the following version of pytorch installed:
# Name                    Version                   Build  Channel
torch                     2.0.1+cu118              pypi_0    pypi
torchvision               0.15.2+cu118             pypi_0    pypi

I have cudatoolkit 11.8 installed:
# Name                    Version                   Build  Channel
cudatoolkit               11.8.0               hd77b12b_0

My python version is:
# Name                    Version                   Build  Channel
python                    3.11.3               he1021f5_1

An exhaustive list of all of the packages installed in the environment is:
# Name                    Version                   Build  Channel
accelerate                0.20.3                   pypi_0    pypi
aiohttp                   3.8.4                    pypi_0    pypi
aiosignal                 1.3.1                    pypi_0    pypi
anyio                     3.7.0                    pypi_0    pypi
async-timeout             4.0.2                    pypi_0    pypi
attrs                     23.1.0                   pypi_0    pypi
backoff                   2.2.1                    pypi_0    pypi
bitsandbytes              0.39.0                   pypi_0    pypi
bzip2                     1.0.8                he774522_0
ca-certificates           2023.05.30           haa95532_0
certifi                   2023.5.7                 pypi_0    pypi
cffi                      1.15.1                   pypi_0    pypi
charset-normalizer        3.1.0                    pypi_0    pypi
chromadb                  0.3.22                   pypi_0    pypi
click                     8.1.3                    pypi_0    pypi
clickhouse-connect        0.6.2                    pypi_0    pypi
colorama                  0.4.6                    pypi_0    pypi
cryptography              41.0.1                   pypi_0    pypi
cudatoolkit               11.8.0               hd77b12b_0
dataclasses-json          0.5.7                    pypi_0    pypi
datasets                  2.13.0                   pypi_0    pypi
dill                      0.3.6                    pypi_0    pypi
duckdb                    0.8.0                    pypi_0    pypi
et-xmlfile                1.1.0                    pypi_0    pypi
faiss-cpu                 1.7.4                    pypi_0    pypi
fastapi                   0.96.0                   pypi_0    pypi
filelock                  3.12.1                   pypi_0    pypi
frozenlist                1.3.3                    pypi_0    pypi
fsspec                    2023.6.0                 pypi_0    pypi
greenlet                  2.0.2                    pypi_0    pypi
h11                       0.14.0                   pypi_0    pypi
hnswlib                   0.7.0                    pypi_0    pypi
httptools                 0.5.0                    pypi_0    pypi
huggingface-hub           0.15.1                   pypi_0    pypi
idna                      3.4                      pypi_0    pypi
instructorembedding       1.0.1                    pypi_0    pypi
jinja2                    3.1.2                    pypi_0    pypi
joblib                    1.2.0                    pypi_0    pypi
langchain                 0.0.191                  pypi_0    pypi
libffi                    3.4.4                hd77b12b_0
llama-cpp-python          0.1.48                   pypi_0    pypi
lz4                       4.3.2                    pypi_0    pypi
markupsafe                2.1.3                    pypi_0    pypi
marshmallow               3.19.0                   pypi_0    pypi
marshmallow-enum          1.5.1                    pypi_0    pypi
monotonic                 1.6                      pypi_0    pypi
mpmath                    1.3.0                    pypi_0    pypi
multidict                 6.0.4                    pypi_0    pypi
multiprocess              0.70.14                  pypi_0    pypi
mypy-extensions           1.0.0                    pypi_0    pypi
networkx                  3.1                      pypi_0    pypi
nltk                      3.8.1                    pypi_0    pypi
numexpr                   2.8.4                    pypi_0    pypi
numpy                     1.24.3                   pypi_0    pypi
openapi-schema-pydantic   1.2.4                    pypi_0    pypi
openpyxl                  3.1.2                    pypi_0    pypi
openssl                   3.0.8                h2bbff1b_0
packaging                 23.1                     pypi_0    pypi
pandas                    2.0.2                    pypi_0    pypi
pdfminer-six              20221105                 pypi_0    pypi
pillow                    9.5.0                    pypi_0    pypi
pip                       23.1.2          py311haa95532_0
posthog                   3.0.1                    pypi_0    pypi
protobuf                  3.20.0                   pypi_0    pypi
psutil                    5.9.5                    pypi_0    pypi
pyarrow                   12.0.1                   pypi_0    pypi
pycparser                 2.21                     pypi_0    pypi
pydantic                  1.10.9                   pypi_0    pypi
python                    3.11.3               he1021f5_1
python-dateutil           2.8.2                    pypi_0    pypi
python-dotenv             1.0.0                    pypi_0    pypi
pytz                      2023.3                   pypi_0    pypi
pyyaml                    6.0                      pypi_0    pypi
regex                     2023.6.3                 pypi_0    pypi
requests                  2.31.0                   pypi_0    pypi
rouge                     1.0.1                    pypi_0    pypi
safetensors               0.3.1                    pypi_0    pypi
scikit-learn              1.2.2                    pypi_0    pypi
scipy                     1.10.1                   pypi_0    pypi
sentence-transformers     2.2.2                    pypi_0    pypi
sentencepiece             0.1.99                   pypi_0    pypi
setuptools                67.8.0          py311haa95532_0
six                       1.16.0                   pypi_0    pypi
sniffio                   1.3.0                    pypi_0    pypi
sqlalchemy                2.0.15                   pypi_0    pypi
sqlite                    3.41.2               h2bbff1b_0
starlette                 0.27.0                   pypi_0    pypi
sympy                     1.12                     pypi_0    pypi
tenacity                  8.2.2                    pypi_0    pypi
threadpoolctl             3.1.0                    pypi_0    pypi
tk                        8.6.12               h2bbff1b_0
tokenizers                0.13.3                   pypi_0    pypi
torch                     2.0.1+cu118              pypi_0    pypi
torchvision               0.15.2+cu118             pypi_0    pypi
tqdm                      4.65.0                   pypi_0    pypi
transformers              4.30.1                   pypi_0    pypi
typing-extensions         4.6.3                    pypi_0    pypi
typing-inspect            0.9.0                    pypi_0    pypi
tzdata                    2023.3                   pypi_0    pypi
urllib3                   1.26.6                   pypi_0    pypi
uvicorn                   0.22.0                   pypi_0    pypi
vc                        14.2                 h21ff451_1
vs2015_runtime            14.27.29016          h5e58377_2
watchfiles                0.19.0                   pypi_0    pypi
websockets                11.0.3                   pypi_0    pypi
wheel                     0.38.4          py311haa95532_0
xxhash                    3.2.0                    pypi_0    pypi
xz                        5.4.2                h8cc25b3_0
yarl                      1.9.2                    pypi_0    pypi
zlib                      1.2.13               h8cc25b3_0
zstandard                 0.21.0                   pypi_0    pypi

My OS is Windows 10 Pro version 22H2
Expected behavior
AutoGPTQ installs successfully

Your installation issues seem unrelated to AutoGPTQ and more so related to PyTorch. Did you try downgrading your CUDA version to match your PyTorch CUDA version?
https://discuss.pytorch.org/t/install-pytorch-with-cuda-12-1/174294

Your installation issues seem unrelated to AutoGPTQ and more so related to PyTorch. Did you try downgrading your CUDA version to match your PyTorch CUDA version?
https://discuss.pytorch.org/t/install-pytorch-with-cuda-12-1/174294

I refer to this in the original post

I haven't been able to use my environment with dev or nightly pytorch versions compatible with cuda 12.1 so I was hoping to fix this issue on the AutoGPTQ side. I've checked the nvidia website at https://www.nvidia.com/download/find.aspx looking for an earlier driver version I could downgrade to that would work with cuda 11.8, but the earliest supported is 527.56, which according to https://docs.nvidia.com/deploy/cuda-compatibility/index.html is not compatible with cuda 11.8. I'm not entirely sure how the versioning works though, because despite this my pytorch version compiled with cuda 11.8 works fine with my 12.1 drivers, so I'm unsure why Auto-GPTQ doesn't.

It seems as though my gpu isn’t compatible with the driver versions necessary for cuda 11.8 and the program I’m running in the environment isn’t compatible with later cuda versions of pytorch. I was hoping there was a solution I hadn’t thought of.

I'm a bit confused.  According to your nvidia-smi output you're using an NVidia 2070?  Which is an old GPU and could use a much older version of the NVidia drivers.
FYI your nvidia-smi is reporting some errors, which makes me wonder if you have some issue there:

What is your exact GPU model name, and could you please link to whatever you're seeing suggesting that you can't use an NV driver older than 527?
However regardless of that it shouldn't be an issue anyway, because you definitely can use 11.8 with newer NV driver versions.  Eg here I am using CUDA toolkit 11.8 with NV driver 530.30, with no problems at all:
 root@22437ad3eef0:/workspace ᐅ nvidia-smi
Sat Jun 17 20:09:40 2023
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 530.30.02              Driver Version: 530.30.02    CUDA Version: 12.1     |
|-----------------------------------------+----------------------+----------------------+
| GPU  Name                  Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf            Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                                         |                      |               MIG M. |
|=========================================+======================+======================|
|   0  NVIDIA L40                      On | 00000000:81:00.0 Off |                    0 |
| N/A   25C    P8               34W / 300W|      2MiB / 46068MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+

+---------------------------------------------------------------------------------------+
| Processes:                                                                            |
|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |
|        ID   ID                                                             Usage      |
|=======================================================================================|
|  No running processes found                                                           |
+---------------------------------------------------------------------------------------+
 root@22437ad3eef0:/workspace ᐅ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2022 NVIDIA Corporation
Built on Wed_Sep_21_10:33:58_PDT_2022
Cuda compilation tools, release 11.8, V11.8.89
Build cuda_11.8.r11.8/compiler.31833905_0

I could be using (and have used) 11.6 even and it'd work.
So I'd suggest you install CUDA 11.8 with pytorch 2.0.1 and then everything will be fully supported.

The source I used for supported driver versions is https://www.nvidia.com/download/find.aspx, it seems like more older driver versions are available for Linux than Windows. My gpu is a 2070 super. I have cudatoolkit 11.8 and PyTorch compiled with cuda 11.8 already installed (see the original post) and they do work, as I stated in the original post, I can run code that uses PyTorch compiled with cuda 11.8 on my gpu that has cuda 12.1. The problem is that AutoGPTQ is giving me a version mismatch error, which is why I created an issue here and not on the PyTorch GitHub.

I am facing this exact issue. my understanding:

PyTorch ships with its own cuda runtime which is 11.7 as of this date. if someone tries to use torch it uses this runtime instead of whatever may be installed globally on the machine which is 12.1 in this case.
but when you try to build a cpp_extension then torch utils uses the global runtime and raises this error

Solutions:

install cuda 11 side by side. there are some blog posts how to do that although i did not try it
wait for pytorch to ship with cuda 12.1
redirect global paths to the cuda 11 that comes with pytorch. anyone know how to do this? where is the location of the cuda runtime that comes bundled with pytorch?

The source I used for supported driver versions is https://www.nvidia.com/download/find.aspx, it seems like more older driver versions are available for Linux than Windows. My gpu is a 2070 super. I have cudatoolkit 11.8 and PyTorch compiled with cuda 11.8 already installed (see the original post) and they do work, as I stated in the original post, I can run code that uses PyTorch compiled with cuda 11.8 on my gpu that has cuda 12.1. The problem is that AutoGPTQ is giving me a version mismatch error, which is why I created an issue here and not on the PyTorch GitHub.
Edit: Apologies for poor formatting, this was written on mobile as I’m away from my PC until tomorrow.

That link gives you the latest driver, not the only supported one.  The 2070 Super came out three years ago and can use any NV driver released in the last 3 years.
If you had CUDA toolkit 11.8 installed and pytorch 2.0.1 compiled with 11.8 then you have no problems, AutoGPTQ will compile fine.  But based on the what you said, you actually have CUDA toolkit 12.x installed + pytorch compiled with 11.x, and that won't work.
If you do have CUDA 11.8 installed as well then maybe your issue is that the installation can't find your CUDA toolkit 11.8 install.  If so then that's easy to solve, so let us know if that's the case when you're back at your PC.
Personally I would just remove CUDA toolkit 12.x, ensure 11.x is installed, build AutoGPTQ against CUDA 11.8, and then everything will be fine.  There's no pressing reason to use CUDA 12.x that I know of - no improvement in performance or anything.  11.8 supports all the latest GPUs like the 4090, L40, H100, etc.
@siddhsql  Installing CUDA toolkit 11.x is the option I would go with.  It's very quick and easy to do.
You can have them installed side by side as you say, and then specify which one is active via PATH and/or CUDA_HOME/CUDA_PATH environment variables.
I've never looked into the CUDA runtime in pytorch, and I wouldn't be comfortable suggesting hacking the pytorch install when there's an easy solution already.
I do agree that it's annoying to have this issue with being unable to compile new pytorch cpp_extensions. Maybe there is some other solution.  But I've always resolved it as described above and that's been easy to do.

Incidentally @mcgeochd you could also try just directly installing a pre-built wheel with eg:
pip install https://github.com/PanQiWei/AutoGPTQ/releases/download/v0.2.2/auto_gptq-0.2.2+cu118-cp310-cp310-linux_x86_64.whl

That would install the AutoGPTQ 11.8 wheel for Python 3.10 on Linux.  If you're using a different version of Python, or are on Windows, then you'd swap out the URL for one of the others listed here: https://github.com/PanQiWei/AutoGPTQ/releases/tag/v0.2.2
I don't know if that will work, but it's worth a try.  It will definitely install. The question will then be whether the extension will work.

Hi @TheBloke,
I'm not sure what cudatoolkit I should be looking for? I though it was the python package "cudatoolkit", I'm vaguely aware there's also an application with the same name that can be installed? Apologies for my confusion, this is my first foray into projects requiring cuda.
Also, just to clear up the OS, I'm on Windows 10 Pro.
In terms of cuda applications, I have:

My current cuda PATH variables are:

In terms of cuda python packages, I have:
(local-gpt) PS C:\Users\domin\Documents\Projects\Python\LocalGPT> conda list cudatoolkit
# packages in environment at C:\Users\domin\anaconda3\envs\local-gpt:
#
# Name                    Version                   Build  Channel
cudatoolkit               11.8.0               hd77b12b_0

I tried the precompiled wheel as well, I downgraded to python 3.10 from 3.11 and ran:
pip install https://github.com/PanQiWei/AutoGPTQ/releases/download/v0.2.2/auto_gptq-0.2.2+cu118-cp310-cp310-win_amd64.whl
Collecting auto-gptq==0.2.2+cu118
  Downloading https://github.com/PanQiWei/AutoGPTQ/releases/download/v0.2.2/auto_gptq-0.2.2+cu118-cp310-cp310-win_amd64.whl (703 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 703.9/703.9 kB 3.2 MB/s eta 0:00:00
Requirement already satisfied: accelerate>=0.19.0 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from auto-gptq==0.2.2+cu118) (0.20.3)
Requirement already satisfied: datasets in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from auto-gptq==0.2.2+cu118) (2.13.0)
Requirement already satisfied: numpy in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from auto-gptq==0.2.2+cu118) (1.24.3)
Requirement already satisfied: rouge in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from auto-gptq==0.2.2+cu118) (1.0.1)
Requirement already satisfied: torch>=1.13.0 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from auto-gptq==0.2.2+cu118) (2.0.1+cu118)
Requirement already satisfied: safetensors in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from auto-gptq==0.2.2+cu118) (0.3.1)
Requirement already satisfied: transformers>=4.26.1 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from auto-gptq==0.2.2+cu118) (4.30.1)
Requirement already satisfied: packaging>=20.0 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from accelerate>=0.19.0->auto-gptq==0.2.2+cu118) (23.1)
Requirement already satisfied: psutil in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from accelerate>=0.19.0->auto-gptq==0.2.2+cu118) (5.9.5)
Requirement already satisfied: pyyaml in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from accelerate>=0.19.0->auto-gptq==0.2.2+cu118) (6.0)
Requirement already satisfied: filelock in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from torch>=1.13.0->auto-gptq==0.2.2+cu118) (3.12.1)
Requirement already satisfied: typing-extensions in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from torch>=1.13.0->auto-gptq==0.2.2+cu118) (4.6.3)
Requirement already satisfied: sympy in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from torch>=1.13.0->auto-gptq==0.2.2+cu118) (1.12)
Requirement already satisfied: networkx in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from torch>=1.13.0->auto-gptq==0.2.2+cu118) (3.1)
Requirement already satisfied: jinja2 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from torch>=1.13.0->auto-gptq==0.2.2+cu118) (3.1.2)
Requirement already satisfied: huggingface-hub<1.0,>=0.14.1 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from transformers>=4.26.1->auto-gptq==0.2.2+cu118) (0.15.1)
Requirement already satisfied: regex!=2019.12.17 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from transformers>=4.26.1->auto-gptq==0.2.2+cu118) (2023.6.3)
Requirement already satisfied: requests in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from transformers>=4.26.1->auto-gptq==0.2.2+cu118) (2.31.0)
Requirement already satisfied: tokenizers!=0.11.3,<0.14,>=0.11.1 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from transformers>=4.26.1->auto-gptq==0.2.2+cu118) (0.13.3)
Requirement already satisfied: tqdm>=4.27 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from transformers>=4.26.1->auto-gptq==0.2.2+cu118) (4.65.0)
Requirement already satisfied: pyarrow>=8.0.0 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from datasets->auto-gptq==0.2.2+cu118) (12.0.1)
Requirement already satisfied: dill<0.3.7,>=0.3.0 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from datasets->auto-gptq==0.2.2+cu118) (0.3.6)
Requirement already satisfied: pandas in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from datasets->auto-gptq==0.2.2+cu118) (2.0.2)
Requirement already satisfied: xxhash in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from datasets->auto-gptq==0.2.2+cu118) (3.2.0)
Requirement already satisfied: multiprocess in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from datasets->auto-gptq==0.2.2+cu118) (0.70.14)
Requirement already satisfied: fsspec[http]>=2021.11.1 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from datasets->auto-gptq==0.2.2+cu118) (2023.6.0)
Requirement already satisfied: aiohttp in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from datasets->auto-gptq==0.2.2+cu118) (3.8.4)
Requirement already satisfied: six in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from rouge->auto-gptq==0.2.2+cu118) (1.16.0)
Requirement already satisfied: attrs>=17.3.0 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from aiohttp->datasets->auto-gptq==0.2.2+cu118) (23.1.0)
Requirement already satisfied: charset-normalizer<4.0,>=2.0 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from aiohttp->datasets->auto-gptq==0.2.2+cu118) (3.1.0)
Requirement already satisfied: multidict<7.0,>=4.5 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from aiohttp->datasets->auto-gptq==0.2.2+cu118) (6.0.4)
Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from aiohttp->datasets->auto-gptq==0.2.2+cu118) (4.0.2)
Requirement already satisfied: yarl<2.0,>=1.0 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from aiohttp->datasets->auto-gptq==0.2.2+cu118) (1.9.2)
Requirement already satisfied: frozenlist>=1.1.1 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from aiohttp->datasets->auto-gptq==0.2.2+cu118) (1.3.3)
Requirement already satisfied: aiosignal>=1.1.2 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from aiohttp->datasets->auto-gptq==0.2.2+cu118) (1.3.1)
Requirement already satisfied: idna<4,>=2.5 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from requests->transformers>=4.26.1->auto-gptq==0.2.2+cu118) (3.4)
Requirement already satisfied: urllib3<3,>=1.21.1 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from requests->transformers>=4.26.1->auto-gptq==0.2.2+cu118) (1.26.6)
Requirement already satisfied: certifi>=2017.4.17 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from requests->transformers>=4.26.1->auto-gptq==0.2.2+cu118) (2023.5.7)
Requirement already satisfied: colorama in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from tqdm>=4.27->transformers>=4.26.1->auto-gptq==0.2.2+cu118) (0.4.6)
Requirement already satisfied: MarkupSafe>=2.0 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from jinja2->torch>=1.13.0->auto-gptq==0.2.2+cu118) (2.1.3)
Requirement already satisfied: python-dateutil>=2.8.2 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from pandas->datasets->auto-gptq==0.2.2+cu118) (2.8.2)
Requirement already satisfied: pytz>=2020.1 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from pandas->datasets->auto-gptq==0.2.2+cu118) (2023.3)
Requirement already satisfied: tzdata>=2022.1 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from pandas->datasets->auto-gptq==0.2.2+cu118) (2023.3)
Requirement already satisfied: mpmath>=0.19 in c:\users\domin\anaconda3\envs\local-gpt\lib\site-packages (from sympy->torch>=1.13.0->auto-gptq==0.2.2+cu118) (1.3.0)
Installing collected packages: auto-gptq
Successfully installed auto-gptq-0.2.2+cu118
(local-gpt) PS C:\Users\domin\Documents\Projects\Python\LocalGPT> & C:/Users/domin/anaconda3/envs/local-gpt/python.exe c:/Users/domin/Documents/Projects/Python/LocalGPT/run_localGPT.py
Traceback (most recent call last):
  File "c:\Users\domin\Documents\Projects\Python\LocalGPT\run_localGPT.py", line 4, in <module>
    import torch
  File "C:\Users\domin\anaconda3\envs\local-gpt\lib\site-packages\torch\__init__.py", line 133, in <module>
    raise err
OSError: [WinError 126] The specified module could not be found. Error loading "C:\Users\domin\anaconda3\envs\local-gpt\lib\site-packages\torch\lib\torch_python.dll" or one of its dependencies.
(local-gpt) PS C:\Users\domin\Documents\Projects\Python\LocalGPT> conda list torch
# packages in environment at C:\Users\domin\anaconda3\envs\local-gpt:
#
# Name                    Version                   Build  Channel
torch                     2.0.1+cu118              pypi_0    pypi
torchvision               0.15.2+cu118             pypi_0    pypi
(local-gpt) PS C:\Users\domin\Documents\Projects\Python\LocalGPT> conda list python
# packages in environment at C:\Users\domin\anaconda3\envs\local-gpt:
#
# Name                    Version                   Build  Channel
llama-cpp-python          0.1.48                   pypi_0    pypi
python                    3.10.11              he1021f5_3
python-dateutil           2.8.2                    pypi_0    pypi
python-dotenv             1.0.0                    pypi_0    pypi

Related to this, is there a required version of CuDA that needs to be installed on my machine, or is any version fine?

In theory any 11.x or 12.x version is fine.
However pytorch currently only supports CUDA 11.x.  You can use pytorch with 12.x, but you either need to use a nightly build of pytorch 2.1, or compile your own pytorch 2.0.1.  AutoGPTQ works fine with pytorch 2.1 in my (brief) testing but not many people will be using that yet so it would be considered an untested and unsupported configuration.
Compiling pytorch 2.0.1 with CUDA 12.x support is another option, and I do that myself on one system.  But compiling pytorch does take a while to do, and there's a few steps to go through.
Therefore right now the recommended and supported version of CUDA is 11.8.
11.8 supports all the latest GPUs and to my knowledge there's no performance difference between 12.x and 11.8, so I don't know of any pressing reason to move off 11.8 until pytorch 2.1 officially releases.

@TheBloke I installed cudatoolkit 11.8 and its the main one pointed to on my path at the moment:

But I'm still getting the same error. Is there anything else I need to do?
RuntimeError:
      The detected CUDA version (12.1) mismatches the version that was used to compile
      PyTorch (11.8). Please make sure to use the same CUDA versions.

      [end of output]

  note: This error originates from a subprocess, and is likely not a problem with pip.
  ERROR: Failed building wheel for auto-gptq
  Running setup.py clean for auto-gptq
Failed to build auto-gptq
ERROR: Could not build wheels for auto-gptq, which is required to install pyproject.toml-based projects

@TheBloke I installed cudatoolkit 11.8 and its the main one pointed to on my path at the moment:   But I'm still getting the same error. Is there anything else I need to do?
RuntimeError:
      The detected CUDA version (12.1) mismatches the version that was used to compile
      PyTorch (11.8). Please make sure to use the same CUDA versions.

      [end of output]

  note: This error originates from a subprocess, and is likely not a problem with pip.
  ERROR: Failed building wheel for auto-gptq
  Running setup.py clean for auto-gptq
Failed to build auto-gptq
ERROR: Could not build wheels for auto-gptq, which is required to install pyproject.toml-based projects

I had the same problem, heres how i fixed it.     The problem is the CUDA_PATH was still referencing 12.1, even though i fixed all the settings on the windows side.  This problem persisted through newly opened terminals too.
I closed out conda/closed all my VS code instances, and reopened VS Code and it worked.
If you run "env" in the terminal look at what path CUDA_PATH is set to.

Thank you! That worked for installing auto-gptq! I've just encountered a new issue though, I created a new venv and did a fresh install using pip install -r requirements.txt and tried to run run_localGPT.py, but there's an issue with a circular reference including sentencepiece?
(local-gpt2) PS C:\Users\domin\Documents\Projects\Python\LocalGPT> pip install -r requirements.txt
Requirement already satisfied: langchain==0.0.191 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from -r requirements.txt (line 2)) (0.0.191)
Requirement already satisfied: chromadb==0.3.22 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from -r requirements.txt (line 3)) (0.3.22)
Requirement already satisfied: llama-cpp-python==0.1.48 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from -r requirements.txt (line 4)) (0.1.48)
Requirement already satisfied: pdfminer.six==20221105 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from -r requirements.txt (line 5)) (20221105)
Requirement already satisfied: InstructorEmbedding in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from -r requirements.txt (line 6)) (1.0.1)
Requirement already satisfied: sentence-transformers in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from -r requirements.txt (line 7)) (2.2.2)
Requirement already satisfied: faiss-cpu in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from -r requirements.txt (line 8)) (1.7.4)
Requirement already satisfied: huggingface_hub in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from -r requirements.txt (line 9)) (0.15.1)
Requirement already satisfied: transformers in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from -r requirements.txt (line 10)) (4.30.0)
Requirement already satisfied: protobuf==3.20.0 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from -r requirements.txt (line 11)) (3.20.0)
Collecting auto-gptq
  Downloading auto_gptq-0.2.2.tar.gz (52 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 52.7/52.7 kB 2.8 MB/s eta 0:00:00
  Preparing metadata (setup.py) ... done
Requirement already satisfied: urllib3==1.26.6 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from -r requirements.txt (line 15)) (1.26.6)
Requirement already satisfied: accelerate in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from -r requirements.txt (line 16)) (0.20.3)
Requirement already satisfied: bitsandbytes in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from -r requirements.txt (line 17)) (0.39.0)
Requirement already satisfied: click in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from -r requirements.txt (line 18)) (8.1.3)
Requirement already satisfied: openpyxl in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from -r requirements.txt (line 21)) (3.1.2)
Requirement already satisfied: numexpr<3.0.0,>=2.8.4 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from langchain==0.0.191->-r requirements.txt (line 2)) (2.8.4)
Requirement already satisfied: PyYAML>=5.4.1 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from langchain==0.0.191->-r requirements.txt (line 2)) (6.0)
Requirement already satisfied: dataclasses-json<0.6.0,>=0.5.7 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from langchain==0.0.191->-r requirements.txt (line 2)) (0.5.7)
Requirement already satisfied: requests<3,>=2 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from langchain==0.0.191->-r requirements.txt (line 2)) (2.31.0)
Requirement already satisfied: aiohttp<4.0.0,>=3.8.3 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from langchain==0.0.191->-r requirements.txt (line 2)) (3.8.4)
Requirement already satisfied: numpy<2,>=1 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from langchain==0.0.191->-r requirements.txt (line 2)) (1.24.3)
Requirement already satisfied: tenacity<9.0.0,>=8.1.0 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from langchain==0.0.191->-r requirements.txt (line 2)) (8.2.2)
Requirement already satisfied: async-timeout<5.0.0,>=4.0.0 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from langchain==0.0.191->-r requirements.txt (line 2)) (4.0.2)
Requirement already satisfied: pydantic<2,>=1 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from langchain==0.0.191->-r requirements.txt (line 2)) (1.10.9)
Requirement already satisfied: SQLAlchemy<3,>=1.4 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from langchain==0.0.191->-r requirements.txt (line 2)) (2.0.15)
Requirement already satisfied: openapi-schema-pydantic<2.0,>=1.2 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from langchain==0.0.191->-r requirements.txt (line 2)) (1.2.4)
Requirement already satisfied: clickhouse-connect>=0.5.7 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from chromadb==0.3.22->-r requirements.txt (line 3)) (0.6.1)
Requirement already satisfied: typing-extensions>=4.5.0 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from chromadb==0.3.22->-r requirements.txt (line 3)) (4.6.3)
Requirement already satisfied: hnswlib>=0.7 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from chromadb==0.3.22->-r requirements.txt (line 3)) (0.7.0)
Requirement already satisfied: uvicorn[standard]>=0.18.3 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from chromadb==0.3.22->-r requirements.txt (line 3)) (0.22.0)
Requirement already satisfied: pandas>=1.3 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from chromadb==0.3.22->-r requirements.txt (line 3)) (2.0.2)
Requirement already satisfied: posthog>=2.4.0 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from chromadb==0.3.22->-r requirements.txt (line 3)) (3.0.1)
Requirement already satisfied: fastapi>=0.85.1 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from chromadb==0.3.22->-r requirements.txt (line 3)) (0.96.0)
Requirement already satisfied: duckdb>=0.7.1 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from chromadb==0.3.22->-r requirements.txt (line 3)) (0.8.0)
Requirement already satisfied: cryptography>=36.0.0 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from pdfminer.six==20221105->-r requirements.txt (line 5)) (41.0.1)
Requirement already satisfied: charset-normalizer>=2.0.0 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from pdfminer.six==20221105->-r requirements.txt (line 5)) (3.1.0)
Requirement already satisfied: tqdm in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from sentence-transformers->-r requirements.txt (line 7)) (4.65.0)
Requirement already satisfied: torch>=1.6.0 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from sentence-transformers->-r requirements.txt (line 7)) (2.0.1)
Requirement already satisfied: torchvision in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from sentence-transformers->-r requirements.txt (line 7)) (0.15.2)
Requirement already satisfied: scikit-learn in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from sentence-transformers->-r requirements.txt (line 7)) (1.2.2)
Requirement already satisfied: scipy in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from sentence-transformers->-r requirements.txt (line 7)) (1.10.1)
Requirement already satisfied: nltk in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from sentence-transformers->-r requirements.txt (line 7)) (3.8.1)
Requirement already satisfied: sentencepiece in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from sentence-transformers->-r requirements.txt (line 7)) (0.1.99)
Requirement already satisfied: filelock in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from huggingface_hub->-r requirements.txt (line 9)) (3.12.0)
Requirement already satisfied: packaging>=20.9 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from huggingface_hub->-r requirements.txt (line 9)) (23.1)
Requirement already satisfied: fsspec in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from huggingface_hub->-r requirements.txt (line 9)) (2023.5.0)
Requirement already satisfied: regex!=2019.12.17 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from transformers->-r requirements.txt (line 10)) (2023.6.3)
Requirement already satisfied: safetensors>=0.3.1 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from transformers->-r requirements.txt (line 10)) (0.3.1)
Requirement already satisfied: tokenizers!=0.11.3,<0.14,>=0.11.1 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from transformers->-r requirements.txt (line 10)) (0.13.3)
Collecting datasets
  Downloading datasets-2.13.1-py3-none-any.whl (486 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 486.2/486.2 kB 3.0 MB/s eta 0:00:00
Collecting rouge
  Downloading rouge-1.0.1-py3-none-any.whl (13 kB)
Requirement already satisfied: psutil in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from accelerate->-r requirements.txt (line 16)) (5.9.5)
Requirement already satisfied: colorama in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from click->-r requirements.txt (line 18)) (0.4.6)
Requirement already satisfied: et-xmlfile in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from openpyxl->-r requirements.txt (line 21)) (1.1.0)
Requirement already satisfied: frozenlist>=1.1.1 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from aiohttp<4.0.0,>=3.8.3->langchain==0.0.191->-r requirements.txt (line 2)) (1.3.3)
Requirement already satisfied: yarl<2.0,>=1.0 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from aiohttp<4.0.0,>=3.8.3->langchain==0.0.191->-r requirements.txt (line 2)) (1.9.2)
Requirement already satisfied: aiosignal>=1.1.2 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from aiohttp<4.0.0,>=3.8.3->langchain==0.0.191->-r requirements.txt (line 2)) (1.3.1)
Requirement already satisfied: multidict<7.0,>=4.5 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from aiohttp<4.0.0,>=3.8.3->langchain==0.0.191->-r requirements.txt (line 2)) (6.0.4)
Requirement already satisfied: attrs>=17.3.0 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from aiohttp<4.0.0,>=3.8.3->langchain==0.0.191->-r requirements.txt (line 2)) (23.1.0)
Requirement already satisfied: certifi in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from clickhouse-connect>=0.5.7->chromadb==0.3.22->-r requirements.txt (line 3)) (2023.5.7)
Requirement already satisfied: lz4 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from clickhouse-connect>=0.5.7->chromadb==0.3.22->-r requirements.txt (line 3)) (4.3.2)
Requirement already satisfied: zstandard in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from clickhouse-connect>=0.5.7->chromadb==0.3.22->-r requirements.txt (line 3)) (0.21.0)
Requirement already satisfied: pytz in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from clickhouse-connect>=0.5.7->chromadb==0.3.22->-r requirements.txt (line 3)) (2023.3)
Requirement already satisfied: cffi>=1.12 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from cryptography>=36.0.0->pdfminer.six==20221105->-r requirements.txt (line 5)) (1.15.1)
Requirement already satisfied: marshmallow<4.0.0,>=3.3.0 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from dataclasses-json<0.6.0,>=0.5.7->langchain==0.0.191->-r requirements.txt (line 2)) (3.19.0)
Requirement already satisfied: typing-inspect>=0.4.0 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from dataclasses-json<0.6.0,>=0.5.7->langchain==0.0.191->-r requirements.txt (line 2)) (0.9.0)
Requirement already satisfied: marshmallow-enum<2.0.0,>=1.5.1 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from dataclasses-json<0.6.0,>=0.5.7->langchain==0.0.191->-r requirements.txt (line 2)) (1.5.1)
Requirement already satisfied: starlette<0.28.0,>=0.27.0 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from fastapi>=0.85.1->chromadb==0.3.22->-r requirements.txt (line 3)) (0.27.0)
Requirement already satisfied: python-dateutil>=2.8.2 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from pandas>=1.3->chromadb==0.3.22->-r requirements.txt (line 3)) (2.8.2)
Requirement already satisfied: tzdata>=2022.1 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from pandas>=1.3->chromadb==0.3.22->-r requirements.txt (line 3)) (2023.3)
Requirement already satisfied: backoff>=1.10.0 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from posthog>=2.4.0->chromadb==0.3.22->-r requirements.txt (line 3)) (2.2.1)
Requirement already satisfied: six>=1.5 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from posthog>=2.4.0->chromadb==0.3.22->-r requirements.txt (line 3)) (1.16.0)
Requirement already satisfied: monotonic>=1.5 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from posthog>=2.4.0->chromadb==0.3.22->-r requirements.txt (line 3)) (1.6)
Requirement already satisfied: idna<4,>=2.5 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from requests<3,>=2->langchain==0.0.191->-r requirements.txt (line 2)) (3.4)
Requirement already satisfied: greenlet!=0.4.17 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from SQLAlchemy<3,>=1.4->langchain==0.0.191->-r requirements.txt (line 2)) (2.0.2)
Requirement already satisfied: sympy in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from torch>=1.6.0->sentence-transformers->-r requirements.txt (line 7)) (1.12)
Requirement already satisfied: jinja2 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from torch>=1.6.0->sentence-transformers->-r requirements.txt (line 7)) (3.1.2)
Requirement already satisfied: networkx in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from torch>=1.6.0->sentence-transformers->-r requirements.txt (line 7)) (3.1)
Requirement already satisfied: h11>=0.8 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from uvicorn[standard]>=0.18.3->chromadb==0.3.22->-r requirements.txt (line 3)) (0.14.0)
Requirement already satisfied: python-dotenv>=0.13 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from uvicorn[standard]>=0.18.3->chromadb==0.3.22->-r requirements.txt (line 3)) (1.0.0)
Requirement already satisfied: httptools>=0.5.0 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from uvicorn[standard]>=0.18.3->chromadb==0.3.22->-r requirements.txt (line 3)) (0.5.0)
Requirement already satisfied: websockets>=10.4 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from uvicorn[standard]>=0.18.3->chromadb==0.3.22->-r requirements.txt (line 3)) (11.0.3)
Requirement already satisfied: watchfiles>=0.13 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from uvicorn[standard]>=0.18.3->chromadb==0.3.22->-r requirements.txt (line 3)) (0.19.0)
Collecting multiprocess
  Downloading multiprocess-0.70.14-py310-none-any.whl (134 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 134.3/134.3 kB 2.7 MB/s eta 0:00:00
Collecting dill<0.3.7,>=0.3.0
  Downloading dill-0.3.6-py3-none-any.whl (110 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 110.5/110.5 kB 1.6 MB/s eta 0:00:00
  Downloading pyarrow-12.0.1-cp310-cp310-win_amd64.whl (21.5 MB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 21.5/21.5 MB 6.7 MB/s eta 0:00:00
Collecting xxhash
  Downloading xxhash-3.2.0-cp310-cp310-win_amd64.whl (30 kB)
Requirement already satisfied: joblib in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from nltk->sentence-transformers->-r requirements.txt (line 7)) (1.2.0)
Requirement already satisfied: threadpoolctl>=2.0.0 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from scikit-learn->sentence-transformers->-r requirements.txt (line 7)) (3.1.0)
Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from torchvision->sentence-transformers->-r requirements.txt (line 7)) (9.5.0)
Requirement already satisfied: pycparser in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from cffi>=1.12->cryptography>=36.0.0->pdfminer.six==20221105->-r requirements.txt (line 5)) (2.21)
Requirement already satisfied: anyio<5,>=3.4.0 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from starlette<0.28.0,>=0.27.0->fastapi>=0.85.1->chromadb==0.3.22->-r requirements.txt (line 3)) (3.7.0)
Requirement already satisfied: mypy-extensions>=0.3.0 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from typing-inspect>=0.4.0->dataclasses-json<0.6.0,>=0.5.7->langchain==0.0.191->-r requirements.txt (line 2)) (1.0.0)
Requirement already satisfied: MarkupSafe>=2.0 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from jinja2->torch>=1.6.0->sentence-transformers->-r requirements.txt (line 7)) (2.1.3)
Requirement already satisfied: mpmath>=0.19 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from sympy->torch>=1.6.0->sentence-transformers->-r requirements.txt (line 7)) (1.3.0)
Requirement already satisfied: sniffio>=1.1 in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from anyio<5,>=3.4.0->starlette<0.28.0,>=0.27.0->fastapi>=0.85.1->chromadb==0.3.22->-r requirements.txt (line 3)) (1.3.0)
Requirement already satisfied: exceptiongroup in c:\users\domin\appdata\local\programs\python\python310\lib\site-packages (from anyio<5,>=3.4.0->starlette<0.28.0,>=0.27.0->fastapi>=0.85.1->chromadb==0.3.22->-r requirements.txt (line 3)) (1.1.1)
Using legacy 'setup.py install' for auto-gptq, since package 'wheel' is not installed.
Installing collected packages: xxhash, rouge, pyarrow, dill, multiprocess, datasets, auto-gptq
  Running setup.py install for auto-gptq ... done
Successfully installed auto-gptq-0.2.2 datasets-2.13.1 dill-0.3.6 multiprocess-0.70.14 pyarrow-12.0.1 rouge-1.0.1 xxhash-3.2.0

[notice] A new release of pip available: 22.2.1 -> 23.1.2
[notice] To update, run: python.exe -m pip install --upgrade pip
(local-gpt2) PS C:\Users\domin\Documents\Projects\Python\LocalGPT> & C:/Users/domin/anaconda3/envs/local-gpt/python.exe c:/Users/domin/Documents/Projects/Python/LocalGPT/run_localGPT.py
Traceback (most recent call last):
  File "C:\Users\domin\anaconda3\envs\local-gpt\lib\site-packages\transformers\utils\import_utils.py", line 1084, in _get_module
    return importlib.import_module("." + module_name, self.__name__)
  File "C:\Users\domin\anaconda3\envs\local-gpt\lib\importlib\__init__.py", line 126, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
  File "<frozen importlib._bootstrap>", line 1050, in _gcd_import
  File "<frozen importlib._bootstrap>", line 1027, in _find_and_load
  File "<frozen importlib._bootstrap>", line 992, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 241, in _call_with_frames_removed
  File "<frozen importlib._bootstrap>", line 1050, in _gcd_import
  File "<frozen importlib._bootstrap>", line 1027, in _find_and_load
  File "<frozen importlib._bootstrap>", line 1006, in _find_and_load_unlocked
  File "<frozen importlib._bootstrap>", line 688, in _load_unlocked
  File "<frozen importlib._bootstrap_external>", line 883, in exec_module
  File "<frozen importlib._bootstrap>", line 241, in _call_with_frames_removed
  File "C:\Users\domin\anaconda3\envs\local-gpt\lib\site-packages\transformers\models\__init__.py", line 15, in <module>
    from . import (
  File "C:\Users\domin\anaconda3\envs\local-gpt\lib\site-packages\transformers\models\mt5\__init__.py", line 29, in <module>
    from ..t5.tokenization_t5 import T5Tokenizer
  File "C:\Users\domin\anaconda3\envs\local-gpt\lib\site-packages\transformers\models\t5\tokenization_t5.py", line 24, in <module>
    import sentencepiece as spm
  File "C:\Users\domin\anaconda3\envs\local-gpt\lib\site-packages\sentencepiece\__init__.py", line 13, in <module>
    from . import _sentencepiece
ImportError: cannot import name '_sentencepiece' from partially initialized module 'sentencepiece' (most likely due to a circular import) (C:\Users\domin\anaconda3\envs\local-gpt\lib\site-packages\sentencepiece\__init__.py)

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "c:\Users\domin\Documents\Projects\Python\LocalGPT\run_localGPT.py", line 5, in <module>
    from auto_gptq import AutoGPTQForCausalLM
  File "C:\Users\domin\anaconda3\envs\local-gpt\lib\site-packages\auto_gptq\__init__.py", line 1, in <module>
    from .modeling import BaseQuantizeConfig
  File "C:\Users\domin\anaconda3\envs\local-gpt\lib\site-packages\auto_gptq\modeling\__init__.py", line 1, in <module>
    from ._base import BaseGPTQForCausalLM, BaseQuantizeConfig
  File "C:\Users\domin\anaconda3\envs\local-gpt\lib\site-packages\auto_gptq\modeling\_base.py", line 16, in <module>
    from transformers import AutoConfig, AutoModelForCausalLM, PreTrainedModel
  File "<frozen importlib._bootstrap>", line 1075, in _handle_fromlist
  File "C:\Users\domin\anaconda3\envs\local-gpt\lib\site-packages\transformers\utils\import_utils.py", line 1074, in __getattr__
    module = self._get_module(self._class_to_module[name])
  File "C:\Users\domin\anaconda3\envs\local-gpt\lib\site-packages\transformers\utils\import_utils.py", line 1086, in _get_module
    raise RuntimeError(
RuntimeError: Failed to import transformers.models.auto because of the following error (look up to see its traceback):
cannot import name '_sentencepiece' from partially initialized module 'sentencepiece' (most likely due to a circular import) (C:\Users\domin\anaconda3\envs\local-gpt\lib\site-packages\sentencepiece\__init__.py)
(local-gpt2) PS C:\Users\domin\Documents\Projects\Python\LocalGPT>

This error appeared in one of Kaggle Docker images: they released a version with CUDA too high for some of torch-based libs. The subsequent release made a little downgrade, closing the gap. Hence, fixing this error is sometimes the matter of finding the right docker image:
base) maciej.skorski@shared-notebooks:~$ docker images
REPOSITORY                        TAG       IMAGE ID       CREATED        SIZE
gcr.io/kaggle-gpu-images/python   latest    87983e20c290   4 weeks ago    48.1GB
gcr.io/kaggle-gpu-images/python   <none>    2b12fe42f372   2 months ago   50.2GB
(base) maciej.skorski@shared-notebooks:~$ docker run --runtime nvidia --rm -it 2b12fe42f372 nvcc --version # older image has incompatibility against PyTorch

nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2023 NVIDIA Corporation
Built on Mon_Apr__3_17:16:06_PDT_2023
Cuda compilation tools, release 12.1, V12.1.105
Build cuda_12.1.r12.1/compiler.32688072_0
(base) maciej.skorski@shared-notebooks:~$ docker run --runtime nvidia --rm -it 87983e20c290 nvcc --version # newer image is OK

nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2022 NVIDIA Corporation
Built on Wed_Sep_21_10:33:58_PDT_2022
Cuda compilation tools, release 11.8, V11.8.89
Build cuda_11.8.r11.8/compiler.31833905_0


changing the hx.set_reference_unit() value in example.py doesn't do anything

I'm working with a 3kg load cell and when I run example.py with hx.set_reference_unit(1)
it outputs:
55372
55334
55426
55433
55350
55411
55342
55459
55441
55514
55469
55432
55462
55399
adding 2kg to the load cell changes the output to:
1347015
1347079
1347217
1347085
1347154
1347143
1347165
1347071
1347179
1347080
1347089
1347133
1347182
1346994
1347174
1347168
1347150
1347136
1347186
1347048
1347081
1347139
1347240
i used hx.set_reference_unit(673) since 1347126/2000=673
but the output does not change after running
please help :(

I have the same problem. The values don't change when chaning the reference_unit.

A major refactoring was just merged. Could you pull the changes and test again? Thanks.
Also, please post your test code.

i did
with a reference_unit=1 i got:
-31422
-31384
-31430
-31389
-59393
-31356
-31453
-31389
-31483
-31436
-31376
-31413
-31406
-31436
-31414
-31404
and with reference_unit=92 or any other number:
-31428
-31387
-31373
-31353
-31350
-31430
-31414
-31385
-31417
-31376
-31406

@Takrem1 Could you post your code, please? Thanks!

i used the example.py

I'll update README.md and example.py this weekend to make it clearer.
Meanwhile, in example.py your getting the raw value from HX711 using hx.read_long(). Comment that one and uncomment hx.get_weight(5).
So, change this:
# Prints the weight. Comment if you're debbuging the MSB and LSB issue.
# val = hx.get_weight(5)
val = hx.read_long()
print val

To this:
# Prints the weight. Comment if you're debbuging the MSB and LSB issue.
val = hx.get_weight(5)
# val = hx.read_long()
print val

Same issue.  I'm for sure registering changes through the load cell with example.py however these values are still just erroneous long numbers because the set reference unit is having apparently no effect whatsoever up the output?

Hey @rirons, are you using example.py? Did you modify any lines?

Using example.py.  Other than the reference unit everything is as downloaded.
From: tatobari<EMAIL_ADDRESS>Sent: Wednesday, February 27, 2019 4:33 PM
To: tatobari/hx711py<EMAIL_ADDRESS>Cc: rirons<EMAIL_ADDRESS>Mention<EMAIL_ADDRESS>Subject: Re: [tatobari/hx711py] changing the hx.set_reference_unit() value in example.py doesn't do anything (#18)
Hey @rirons https://github.com/rirons , are you using example.py? Did you modify any lines?
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub https://github.com/tatobari/hx711py/issues/18#issuecomment-468087518 , or mute the thread https://github.com/notifications/unsubscribe-auth/AqMP1KOX0JHuwTlYrP5wwc6me_d8VR6Hks5vRyOugaJpZM4aycA8 .  https://github.com/notifications/beacon/AqMP1EeMaiOSgOl9LSBrxOHB2P4W76K-ks5vRyOugaJpZM4aycA8.gif

This email has been checked for viruses by Avast antivirus software.
https://www.avast.com/antivirus

Please, read my comment just above your first one on this thread.


cannot access container. when run a container Status is Restarting

When trying to access docker image of container. it's show like
Running Command:
docker exec -it 720152f2c447 /bin/bash
Response:
Error response from daemon: Container 720152f2c447290596d2b8bc94775df1d9c863df141b48b420f9e6979f898cf6 is restarting, wait until the container is running. still it's not running.
I getting this error using docker in windows os.  can any one help me to fix errors.

Hi @sridharchary !
It is possible that gProfiler is failing to start, and the container was run with --restart=always, hence it keeps restarting.
Can you please run docker logs --tail 1000 720152f2c447 and post the output here? This will help understanding why the container restarts.

If you are using WSL 2, this might be related.

@Jongy thanks for response.
I am not using WSL 2. executing from power shell using docker command.
the out of logs are look like below image.

If you are using WSL 2, this might be related.

it's worked --disable-pids-check.
but not sync with gprofiler   site.

I see. When you use docker run in Windows, the Docker container actually runs on the WSL (or WSL2) that runs on your system.
This solves the issue. I will add a word on it in the documentation. Will update here once that's done.
I see that you've opened https://github.com/Granulate/gprofiler/issues/364 to discuss the data issue, I am closing this issue which was about starting the profiler, and we'll continue discussing there.


Bugfix, code tags were broken.

Spotted this, hoping it will fix. Haven't built it locally.

Yeah I know barely anything about rst, no idea about a note directive.

This is what it looks like using a note directive (which might be a sphinx extension).
I think  this is what we want so happy to commit and push it if you agree.

Found another weird quirk on a different page.

https://docs.flamegpu.com/guide/2-model-definition/2-environment.html#macro-environmental-properties

From the rst it looks like this link was just never inserted. I'll chuck it into this PR along with the note directive


update design arch and user story

This change is

Coverage remained the same at 84.832% when pulling e474f7c130484572010482a2047a280853a4d1d1 on Update-Developer-Guide into a4209c92d3c48cf950e9198fc33e0907c2839697 on master.

Coverage remained the same at 85.127% when pulling 7e3a423e6dfddbe97ca2ff877fa310ce57462740 on Update-Developer-Guide into 4f54937a08b3bf70c7ebb9f3fa02dd70fe069891 on master.


Pyicloud updated their code to be 2sa instead of 2fa. Fixing on this end as well

Ah, great. Could you please add a callable(requires_2sa) line to provide backwards compatibility with previous versions of pyicloud? Thanks!

okay, it's pushed.

Whoops, I gave you the wrong suggestion. We needed to use hasattr instead of callable. I pushed the fix: 43026e6b3f18d75b3b628ad58ff3190df59d05fa
Thanks for letting me know about that change!


Address long compilation time in RBDAs for models with many DoFs

After an extensive debugging, I noticed that the RBDAs requires long compilation time, especially when the number of DoFs is high (> 20). I believe that the problem might be related to this piece of code:
https://github.com/ami-iit/jaxsim/blob/d7cfcc6b7c8aab3528a5c81e3a67f157dddade27/src/jaxsim/api/kin_dyn_parameters.py#L387-L393
which uses a plain Python for-loop with enumerate. Moreover, the supported_joint_motion uses enum.IntEnum which is not completely compatible with JAX.
Therefore, the idea is to find a valid JAX-compatible alternative, eventually constructing a custom enum class that automatically handles the enum as integers, which are compatible with JAX arrays.
C.C. @diegoferigo @xela-95

I believe that the problem might be related to this piece of code

Yes this is correct. The current structure that defines a joint type (either as a JointType enum or a JointDescriptor pytree) prevents structuring that list comprehension either as a vmap transformation or jax.lax.scan statement. If a model has many joints (it's not important their type), the logic of the supported_joint_motion function is copied over and over, and JAX has to compile a huge piece of code. It starts to be noticeable for models with more than 20/25 DoFs.
I already spent more time than I want to admit trying to find a clean and general solution to this problem. Originally we had single-axis joints (Rx, Ry, etc.) in addition to generic revolute/prismatic joints like R and P (that require the joint axis as metadata). The way to support both of them until now prevented replacing the problematic list comprehension. However, in https://github.com/ami-iit/jaxsim/pull/137, I've recently removed many of the original joint types so that the supported_joint_motion function could be compiled only for R and P. Note that F is never used.
I've performed multiple attempts by developing jit- and vmap-compatible enums, refactoring the JointDescriptor class, etc. None of the attempts gave me something that worked fine, and the implementation ended up being too complicated to maintain.
At this point, since this is becoming a bottleneck, I believe that resorting to a more custom / hardcoded solution and introducing few assumptions is the way to go. I will propose something in the next comment.

I propose to make the following assumption:

JaxSim only supports revolute and prismatic joints.

This is already the case, but the previous structure allowed a simple inclusion of other joint types, and I wanted at some point to add a FreeFloating joint so that we could remove in our RBDAs all the if/else statement related to fixed-base / floating-base models. For the time being, I think we can live happy with only these two joint types, that are those required by probably 99% of the models out there.

Here below my proposal:

Remove the JointType enum and replace it with the following class: class JointType:
   Fixed: jtp.Int = jnp.array(0, dtype=int)
   Revolute: jtp.Int = jnp.array(1, dtype=int)
   Prismatic: jtp.Int = jnp.array(2, dtype=int)

In this way, JointDescriptor becomes a propert vmappable pytree since joint_type is a jax-compatible leaf. The same applies to JointGenericAxis that is the class used to implement prismatic/revolute joints.
I would not change, at least in this first iteration, JointModel.joint_types. I think that making it non-static doesn't give us any noticeable improvement. With 2) in place, I believe that things can be vectorized elsewhere.
Modify supported_joint_motion as<EMAIL_ADDRESS>def supported_joint_motion(
    joint_type: jtp.IntLike, joint_position: jtp.FloatLike, **kwargs
) -> tuple[jtp.Matrix, jtp.Array]:

where the axis metadata necessary for R and P is passed as kwarg and unpacked in the chained jax.lax.cond statements that will replace the match/case (it cannot be plain if/else sequence if we want jit support over the joint_type integer).
Replace the problematic list comprension with something similar to the following:pre_H_suc_and_S = jax.vmap(supported_joint_motion)(
   jnp.array([j.joint_type for j in self.joint_model.joint_types[1:]], dtype=int),
   jnp.array(joint_positions).astype(float),
   jnp.array([j.axis for j in self.joint_model.joint_types[1:]], dtype=float)
)

In other works, my proposal is to only support joints that can be modeled as JointGenericAxis. In this way, we can vectorize over a unique pytree structure.

This implementation prevents the definition of other joint types where the motion subspace S is not a (6, 1) array (and the joint angle is not a scalar, in general). Again, if needed, we can think of a proper solution for that in the future.

In the end I kept the support for fixed joints and separated JointType from JointGenericAxis. Furthermore, I rewrote the JointType class so that its values get interpreted as plain integers, which simplifies a lot the computation on the JAX side. (https://github.com/ami-iit/jaxsim/commit/51ea173aa8792e4da5c5e12c188c010d7ebe6121)
Then, I added a couple of minor changes here (https://github.com/ami-iit/jaxsim/commit/0d636d9c5d7d0a1d82965406b1c9a32e9013413b) and finally used vmap to speed up the computation of the joint transforms and the motion subspaces in https://github.com/ami-iit/jaxsim/commit/a6ddcd2ffe7c03180189c6baa7a3becc22c17381.
I will add some benchmarks soon

Great! I'm glad that the pattern worked fine. I'm not fully convinced on the metaclass though. I'll review the PR as soon as it's ready.

Benchmarks reported in https://github.com/ami-iit/jaxsim/pull/153#issuecomment-2112687460


Async Queries sometimes stuck in PENDING (Fails to pass task to worker)

When using async queries in SQL Lab, after couple of executions the same query stucks in PENDING state.
I have checked the logs of Superset Node and Worker and it seems that superset node fails pass data/task to worker, but without any errors or signs.
Superset Node logs:
...
Triggering query_id: 74
2022-09-20 23:51:12,129:INFO:superset.sqllab.command:Triggering query_id: 74
Query 74: Running query on a Celery worker
2022-09-20 23:51:12,381:INFO:superset.sqllab.sql_json_executer:Query 74: Running query on a Celery worker
Triggering query_id: 75
2022-09-20 23:55:40,069:INFO:superset.sqllab.command:Triggering query_id: 75
Query 75: Running query on a Celery worker
2022-09-20 23:55:40,084:INFO:superset.sqllab.sql_json_executer:Query 75: Running query on a Celery worker
Unable to load SQLAlchemy dialect <class 'pyhive.sqlalchemy_hive.HiveDialect'>: module 'pyhive.sqlalchemy_hive' has no attribute 'HiveHTTPDialect'
2022-09-20 23:56:55,495:WARNING:superset.db_engine_specs:Unable to load SQLAlchemy dialect <class 'pyhive.sqlalchemy_hive.HiveDialect'>: module 'pyhive.sqlalchemy_hive' has no attribute 'HiveHTTPDialect'
Unable to load SQLAlchemy dialect <class 'pyhive.sqlalchemy_hive.HiveDialect'>: module 'pyhive.sqlalchemy_hive' has no attribute 'HiveHTTPSDialect'
2022-09-20 23:56:55,495:WARNING:superset.db_engine_specs:Unable to load SQLAlchemy dialect <class 'pyhive.sqlalchemy_hive.HiveDialect'>: module 'pyhive.sqlalchemy_hive' has no attribute 'HiveHTTPSDialect'
Unable to load SQLAlchemy dialect <class 'pyhive.sqlalchemy_presto.PrestoDialect'>: No module named 'sqlalchemy_trino'
2022-09-20 23:56:56,326:WARNING:superset.db_engine_specs:Unable to load SQLAlchemy dialect <class 'pyhive.sqlalchemy_presto.PrestoDialect'>: No module named 'sqlalchemy_trino'
<IP_ADDRESS> - - [20/Sep/2022:23:56:56 +0000] "GET /superset/sqllab/ HTTP/1.1" 200 27759 "https://bi-910848238944.iomete.com/superset/welcome/" "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/16.0 Safari/605.1.15"
/app/superset/views/core.py:2351: FutureWarning: 'pyarrow.deserialize' is deprecated as of 2.0.0 and will be removed in a future version. Use pickle or the pyarrow IPC functionality instead.
  return self.results_exec(key)
Triggering query_id: 76
2022-09-20 23:57:10,277:INFO:superset.sqllab.command:Triggering query_id: 76
Query 76: Running query on a Celery worker
2022-09-20 23:57:10,293:INFO:superset.sqllab.sql_json_executer:Query 76: Running query on a Celery worker
Triggering query_id: 77
2022-09-20 23:57:14,854:INFO:superset.sqllab.command:Triggering query_id: 77
Query 77: Running query on a Celery worker
2022-09-20 23:57:14,869:INFO:superset.sqllab.sql_json_executer:Query 77: Running query on a Celery worker
...

WORKER Logs:
...
User information: uid=0 euid=0 gid=0 egid=0

  warnings.warn(RuntimeWarning(ROOT_DISCOURAGED.format(
Query 75: Executing 1 statement(s)
[2022-09-20 23:55:40,233: INFO/ForkPoolWorker-1] Query 75: Executing 1 statement(s)
Query 75: Set query to 'running'
[2022-09-20 23:55:40,234: INFO/ForkPoolWorker-1] Query 75: Set query to 'running'
Query 75: Running statement 1 out of 1
[2022-09-20 23:55:40,452: INFO/ForkPoolWorker-1] Query 75: Running statement 1 out of 1
[2022-09-20 23:57:01,469: WARNING/ForkPoolWorker-1] /app/superset/sql_lab.py:328: FutureWarning: 'pyarrow.default_serialization_context' is deprecated as of 2.0.0 and will be removed in a future version. Use pickle or the pyarrow IPC functionality instead.
  pa.default_serialization_context()
[2022-09-20 23:57:01,469: WARNING/ForkPoolWorker-1] /app/superset/sql_lab.py:161: FutureWarning: 'pyarrow.serialize' is deprecated as of 2.0.0 and will be removed in a future version. Use pickle or the pyarrow IPC functionality instead.
  return execute_sql_statements(
Query 75: Storing results in results backend, key: 848dbe03-0e9c-462a-a59d-a0bd3c44fbfb
[2022-09-20 23:57:01,470: INFO/ForkPoolWorker-1] Query 75: Storing results in results backend, key: 848dbe03-0e9c-462a-a59d-a0bd3c44fbfb
Query 77: Executing 1 statement(s)
[2022-09-20 23:57:14,909: INFO/ForkPoolWorker-1] Query 77: Executing 1 statement(s)
Query 77: Set query to 'running'
[2022-09-20 23:57:14,909: INFO/ForkPoolWorker-1] Query 77: Set query to 'running'
Query 77: Running statement 1 out of 1
[2022-09-20 23:57:15,105: INFO/ForkPoolWorker-1] Query 77: Running statement 1 out of 1
Query 77: Storing results in results backend, key: 25229e25-7d5f-455e-8447-e0ec47b622a6
[2022-09-20 23:57:15,979: INFO/ForkPoolWorker-1] Query 77: Storing results in results backend, key: 25229e25-7d5f-455e-8447-e0ec47b622a6

As you can see from logs, Query 74/76 logs does not exists in worker, only in superset master node

Don't care anymore

@Shisir99 I haven't used Superset recently and haven't checked the new versions. When this issue was first reported, I was unable to find any workarounds...

Hello, still face the same issue here, any update?


Multi-component selection

Should be able to select and move multiple components/gates. Should also be able to move all connected wires and/or individual wire nodes.

Multi-component + wire selection has been implemented (will appear in v0.12). No wire editing at the moment (will be moved to a new issue).


refactor(libraries/tipipeline/vars): refactor prow.checkoutRefs

replace hardcode composing repo url with repo_link field.
Signed-off-by: wuhuizuo<EMAIL_ADDRESS>

passed in https://do.pingcap.net/jenkins/job/pingcap/job/tidb/job/ghpr_build/21727/


[CI] Add dependabot, use newer workflows, use concurrency groups

Codecov Report
All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 92.48%. Comparing base (062ff51) to head (7789ee8).
Report is 1 commits behind head on master.

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Additional details and impacted files
@@           Coverage Diff           @@
##           master     #260   +/-   ##
=======================================
  Coverage   92.48%   92.48%
=======================================
  Files           7        7
  Lines         386      386
=======================================
  Hits          357      357
  Misses         29       29

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.

Tagging https://github.com/UCL-ARC/green-team/issues/76 to record evidence of reducing unnecessary CI usage


GlobeSurfaceTile uses TileBoundingBox (from 3d-tiles)

For #3177
Cherry-picking the changes from #3387 into master.

Looks good.


Windows Build working with cuda 10.1 and vs2019

I am only writing this as an issue as I got tensorflow with win 10 building with cuda 10.1 and vs2019 .
I am not sure if my changes can be general, they seem to work for me and I can train MNIST on GPU. The cuda changes could be relevant, the others might be working only for my system config.
Please make sure that this is a build/installation issue. As per our GitHub Policy, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:build_template
System information

OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Windows 10
Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:
TensorFlow installed from (source or binary): source
TensorFlow version: 2.0a
Python version: 3.6.5
Installed using virtualenv? pip? conda?: pip
Bazel version (if compiling from source): 20
GCC/Compiler version (if compiling from source): visual studo 2019
CUDA/cuDNN version: 10.1/7
GPU model and memory: gtx 1080 ti , 4gv

Describe the problem
Cannot compile tensorflow 2.0 alpha on windows with cuda 10.1, and visual studio 2019
Provide the exact sequence of commands / steps that you executed before running into the problem

Hardlinked visual studio 2019 as 2017 with mklink
modified bazel scripts and stream operators as in : https://github.com/atemysemicolon/tensorflow/commit/54faf06d5c10e8875b9ce36b941004aceb44c8b9
Compiles

Any other info / logs

Visual 2019 does not seem to be supported by older versions of Bazel. Bazel 24.1 causes compilation issues using nvcc. However, cheating bazel into thinking 2019 is 2017 is good enough - by hardlinking the 2019 folder to 2017 in C:\Program Files\Microsoft Visual Studio..
I had to modify bazel to not generate workspaces for mac and linux,
The most important one seems to be the modification in cuda_10_0.inc in tensorflow/stream_executer/cuda/...

TensorFlow supports CUDA 10.0 (TensorFlow >= 1.13.0). Please refer this link and let us know in case of any clarification. Thanks!

This guide is for 10.1 , not 10

Unfortunately, none of the TensorFlow versions officially support CUDA 10.1. As of now we have to build TensorFlow version>=1.13.0 using CUDA 10.0. Thanks!

Automatically closing due to lack of recent activity. Please update the issue when new information becomes available, and we will reopen the issue. Thanks!

I thought only when someone builds it , it could be officially supported xd


_ prefixed variables are still public despite being indicated as private by the _

Well as you probably saw, I haven't respected any nomenclatures. It could be indeed interesting to add this rule. And even add a tslint parser for verify future added code


Cannot delete PostgreSQL database

Running either clean-postgres-database-file.sh in the docker-compose directory or docker compose down --volumes does not properly destroy the database. How would one go about deleting the database file?

@Andrew-Chen-Wang Hi, the database file was mounted at /var/lib/illa/database/postgresql, you can delete this folder manually. (the clean-postgres-database-file.sh do the same thing.)
And if you changed the following configs, the postgres database file will be generated in the new folder you defined.
ILLA_HOME_DIR=/var/lib/illa
PG_VOLUMN=${ILLA_HOME_DIR}/database/postgresql

You can delete by yourself.

Issue closed due to no feedback over 5 days.