In this tutorial, we will learn the solutions on how to fix the Modulenotfounderror: no module named ‘pytorch_lightning’.
The Python error no module named ‘pytorch_lightning’ occur because the python interpreter cannot find the installed pytorch_lighting in your system. Furthermore, the error occurs if the pytorch_lighting is installed yet it is not in the correct environment.
Also read: Modulenotfounderror: no module named ‘config’
What is PyTorch Lightning?
The PyTorch Lightning is the profound learning structure for professional Artificial Intelligence researchers and the machine learning engineers who used the greatest resilience without compromising performance at scale. The lightning expand as your projects go from opinion to paper or production.
How to fix the no module named ‘pytorch_lightning’?
Time needed: 3 minutes
Here are the solutions to fix the error no module named ‘pytorch_lightning’ in your windows, Anaconda
- Solution 1: Install pytorch_lightning
Step 1: Install the pytorch_lightning in windows
This is the command to install the pytorch_lightning in windows:“ pip install pytorch-lightning “
If the above code is executed it will install the pytorch library.
Step 2: Adding Imports
import os
import torch
from torch import nn
import torch.nn.functional as F
from torchvision.datasets import MNIST
from torch.utils.data import DataLoader, random_split
from torchvision import transforms
import pytorch_lightning as plAfter you import this command it will solve the error you entered.
- Solution 2: conda install pytorch lightning
The following command below is the command for the installation pytorch_lightning module in Anaconda.
“ conda install -c conda-forge pytorch-lightning “
Diagnostic checklist for “No module named ‘pytorch_lightning'”
- Verify pip install target. Run
pip show pytorch_lightning— if not installed, runpip install pytorch_lightning. - Check the active Python interpreter.
which python(mac/Linux) orwhere python(Windows). Both pip and python must point to the same environment. - Check virtual environment activation. If you use venv/conda, activate before installing:
source .venv/bin/activate. - Rule out uppercase/lowercase. Python imports are case-sensitive:
import PyPDF2notimport pypdf2. - Rule out the pip-vs-package-name mismatch. Some packages install under a different name than you import (e.g.
pip install beautifulsoup4→import bs4).
Installing pytorch_lightning — deep learning framework
# Standard pip install pip install pytorch_lightning # With CUDA support (Linux/Windows with GPU) # PyTorch: use the selector at https://pytorch.org/get-started/locally/ # TensorFlow: pip install tensorflow[and-cuda] # CPU-only install pip install pytorch_lightning --index-url https://download.pytorch.org/whl/cpu
Common causes for missing deep-learning modules
- CUDA / cuDNN version mismatch. GPU wheels are pinned to a CUDA version. Check the framework’s install page for your CUDA.
- Python version too new. PyTorch/TensorFlow support the latest Python by a few weeks. Pin to 3.11 or 3.12 if 3.13 fails.
- M1/M2 Mac Metal build. Apple silicon needs Metal-specific wheels (torch has these).
- Notebook kernel mismatch. Jupyter may pick a different Python. Install with
%pip install pytorch_lightning.
Working code example
import pytorch_lightning
print(pytorch_lightning.__version__)
# For PyTorch: verify CUDA
# import torch
# print(torch.cuda.is_available())
# For TensorFlow: verify GPUs
# import tensorflow as tf
# print(tf.config.list_physical_devices('GPU'))
Best practices
- Use conda for deep learning. It manages CUDA + cuDNN alongside Python packages — much smoother than pip alone.
- Pin the framework + CUDA version. Deep learning models are very version-sensitive.
- Consider Docker. NVIDIA publishes CUDA-ready base images that make setup trivial.
Official documentation
Frequently Asked Questions
What is Python ModuleNotFoundError and what causes it?
ModuleNotFoundError (a subclass of ImportError) is raised when Python cannot find the module you tried to import. Common causes: the package isn’t installed (pip install missing), wrong virtual environment activated, typo in module name, or Python can’t find your local module on the import path. The error message names exactly which module is missing.
How do I fix ‘ModuleNotFoundError: No module named X’?
Run pip install X first. If that succeeds but you still get the error, check which Python you’re using (which python OR python –version) vs which pip (which pip OR pip –version), they must match. Common gotcha: pip points to system Python 3.9 but you’re running python3.11 in a venv. Inside the venv, use python -m pip install X to be sure pip matches the active Python.
Why does my code work in one environment but not another?
Different Python versions or different installed packages. To diagnose: pip freeze > requirements.txt on the working environment, then pip install -r requirements.txt on the broken one. Use virtualenv (python -m venv venv) or conda for every project to avoid system-wide package collisions.
Is ModuleNotFoundError the same as ImportError?
ModuleNotFoundError is a subclass of ImportError added in Python 3.6. It specifically means ‘no such module exists.’ Plain ImportError covers a wider set: module exists but a name inside it can’t be imported (e.g. ‘cannot import name X from Y’). except ImportError catches both; except ModuleNotFoundError catches only the missing-module case.
Where can I find more ModuleNotFoundError fixes?
Browse the ModuleNotFoundError reference hub for 198+ specific module fixes (TensorFlow, Flask, Django, pandas, numpy, etc.). For related issues see ImportError. For broader Python setup see Python Tutorial hub.
Conclusion
To conclude, if you encountered this error Modulenotfounderror: no module named ‘pytorch_lightning’ the above solutions is the best way to solve your error.
Adones Evangelista
Programmer & Technical Writer at PIES IT Solution
Adones Evangelista is a programmer and writer at PIES IT Solution, author of over 900 tutorials and error-fix guides at itsourcecode.com. Specializes in JavaScript, Django, Laravel, and Python error debugging covering ValueError, TypeError, AttributeError, ModuleNotFoundError, and RuntimeError, plus C/C++ and PHP capstone projects for BSIT students.
Expertise: JavaScript · Python · Django · Laravel · Error Debugging · C/C++
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