ModuleNotFoundError: No module named 'packaging' in pytorch-lightning 1.2.9 #7178
Comments
|
https://github.com/PyTorchLightning/pytorch-lightning/blob/1.2.9/requirements.txt#L1 |
|
I checked the tarball for 1.2.9 on PyPI using the following script: # Fetch tarball for 1.2.9 from PyPi
curl https://files.pythonhosted.org/packages/09/b6/16e6e2247c0ac56461a0f98ed6055287320f035cc1d6effce36f3acb1f58/pytorch-lightning-1.2.9.tar.gz --output pytorch-lightning-1.2.9.tar.gz
tar -xvzf pytorch-lightning-1.2.9.tar.gz
# Check file contents
echo =======================================
cat pytorch-lightning-1.2.9/pytorch_lightning/utilities/imports.py | head -n 30
echo =======================================
cat pytorch-lightning-1.2.9/requirements.txtThis outputs: ...
=======================================
# Copyright The PyTorch Lightning team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""General utilities"""
import importlib
import operator
import platform
from importlib.util import find_spec
import torch
+ from packaging.version import Version
from pkg_resources import DistributionNotFound
def _module_available(module_path: str) -> bool:
"""
Check if a path is available in your environment
>>> _module_available('os')
True
=======================================
# the default package dependencies
numpy>=1.16.6
torch>=1.4
future>=0.17.1 # required for builtins in setup.py
# pyyaml>=3.13
PyYAML>=5.1, !=5.4.* # OmegaConf requirement >=5.1
tqdm>=4.41.0
fsspec[http]>=0.8.1
tensorboard>=2.2.0, !=2.5.0 # 2.5.0 GPU CI error: 'Couldn't build proto file into descriptor pool!'
torchmetrics==0.2.0
|
|
yeah it seems we made a mistake when we did resolve after cherry-picking, let us fix it very quick |
|
My bad. @Borda Should I do a PR to the release branch? |
|
well at first place we shall check ho it was possible that all tests passed and we did not find catch it |
|
@Borda Thanks for the quick fix 👍 |
|
@harupy just test for |
|
@Borda Confirmed the issue has been fixed! Thanks! |
🐛 Bug
Please reproduce using the BoringModel
To Reproduce
This docker file outputs:
Expected behavior
pytorch_lightningcan be installed without any additional dependencies.Environment
Note:
Bugs with codeare solved faster !Colab Notebookshould be madepublic!IDE: Please, use our python bug_report_model.py template.Colab Notebook: Please copy and paste the output from our environment collection script (or fill out the checklist below manually).You can get the script and run it with:
conda,pip, source):Additional context
The text was updated successfully, but these errors were encountered: