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[Quality] Better warning when c++ binaries failed to be imported #2541

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merged 1 commit into from
Nov 6, 2024
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[Quality] Better warning when c++ binaries failed to be imported #2541

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31 changes: 26 additions & 5 deletions torchrl/_extension.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,9 @@
import importlib.util
import warnings

from packaging.version import parse
from torchrl import __version__


def is_module_available(*modules: str) -> bool:
"""Returns if a top-level module with :attr:`name` exists *without** importing it.
Expand All @@ -24,8 +27,26 @@ def _init_extension():
return


EXTENSION_WARNING = (
"Failed to import torchrl C++ binaries. Some modules (eg, prioritized replay buffers) may not work with your installation. "
"If you installed TorchRL from PyPI, please report the bug on TorchRL github. "
"If you installed TorchRL locally and/or in development mode, check that you have all the required compiling packages."
)
def _is_nightly(version):
parsed_version = parse(version)
return parsed_version.local is not None


if _is_nightly(__version__):
EXTENSION_WARNING = (
"Failed to import torchrl C++ binaries. Some modules (eg, prioritized replay buffers) may not work with your installation. "
"You seem to be using the nightly version of TorchRL. If this is a local install, there might be an issue with "
"the local installation. Here are some tips to debug this:\n"
" - make sure ninja and cmake were installed\n"
" - make sure you ran `python setup.py clean && python setup.py develop` and that no error was raised\n"
" - make sure the version of PyTorch you are using matches the one that was present in your virtual env during "
"setup."
)

else:
EXTENSION_WARNING = (
"Failed to import torchrl C++ binaries. Some modules (eg, prioritized replay buffers) may not work with your installation. "
"This is likely due to a discrepancy between your package version and the PyTorch version. Make sure both are compatible. "
"Usually, torchrl majors follow the pytorch majors within a few days around the release. "
"For instance, TorchRL 0.5 requires PyTorch 2.4.0, and TorchRL 0.6 requires PyTorch 2.5.0."
)
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