Installation Error
thanks for great work!
I followed the readme instructions to clone a GitHub project on my server, created a virtual environment, installed the correct versions of torch and pytorch-scatter, and installed other pip packages.
However, I encountered the following error during pip install -v .
RuntimeError: Error compiling objects for extension error: subprocess-exited-with-error
× python setup.py bdist_wheel did not run successfully. │ exit code: 1 ╰─> See above for output.
note: This error originates from a subprocess, and is likely not a problem with pip.
full command: /root/miniconda3/envs/nr3d/bin/python -u -c '
exec(compile('"'"''"'"''"'"'
This is
- It imports setuptools before invoking setup.py, to enable projects that directly
import from
distutils.coreto work with newer packaging standards. - It provides a clear error message when setuptools is not installed.
- It sets
sys.argv[0]to the underlyingsetup.py, when invokingsetup.pyso setuptools doesn'"'"'t think the script is-c. This avoids the following warning: manifest_maker: standard file '"'"'-c'"'"' not found". - It generates a shim setup.py, for handling setup.cfg-only projects. import os, sys, tokenize
try:
import setuptools
except ImportError as error:
print(
"ERROR: Can not execute setup.py since setuptools is not available in "
"the build environment.",
file=sys.stderr,
)
sys.exit(1)
file = %r sys.argv[0] = file
if os.path.exists(file):
filename = file
with tokenize.open(file) as f:
setup_py_code = f.read()
else:
filename = "
exec(compile(setup_py_code, filename, "exec"))
'"'"''"'"''"'"' % ('"'"'/root/autodl-tmp/neuralsim/nr3d_lib/setup.py'"'"',), "
Hello, I have encountered the same problem as you. May I ask if you have resolved it
Hello, I have encountered the same problem as you. May I ask if you have resolved it
For this issue, the problem originated from initially renting a 4090 on a cloud server, but the environment recommended in the README, CUDA 11.3, does not support 4090. The solution is to switch to a 3090 or install a higher version of CUDA.
Additionally, I found that Lotd could not compile. The solution was to revert the project version to the one from August-September last year, and then follow the instructions in the README to successfully compile it.