Federated Learning Simulator (FLSim) is a flexible, standalone core library that simulates FL settings with a minimal, easy-to-use API. FLSim is domain-agnostic and accommodates many use cases such as vision and text.
BSD 3-Clause "New" or "Revised" License
249
stars
58
forks
source link
Problem with "from flsim.utils.example_utils import DataLoader, DataProvider" #56
ValueError: mutable default <class 'flsim.utils.timing.training_duration_distribution.PerExampleGaussianDurationDistributionConfig'> for field duration_distribution_generator is not allowed: use default_factory
This error comes from the line: "from flsim.utils.example_utils import DataLoader, DataProvider"
To Reproduce
:warning: We cannot help you without you sharing reproducible code. Do not ignore this part :)
Steps to reproduce the behavior:
1.
2.
3.
I try to run the tutorials and examples provided in the codebase but this problem persists.
wget https://raw.githubusercontent.com/pytorch/pytorch/master/torch/utils/collect_env.py
# For security purposes, please check the contents of collect_env.py before running it.
python collect_env.py
PyTorch Version (e.g., 1.0):
OS (e.g., Linux):
How you installed PyTorch (conda, pip, source):
Build command you used (if compiling from source):
Hi @minhquang20VU Did u fix this? Or can u share the complete error message, it's hard to debug based on only this message. But it's something related @dataclass and default, here is a stackoverflow post fyi
🐛 Bug
ValueError: mutable default <class 'flsim.utils.timing.training_duration_distribution.PerExampleGaussianDurationDistributionConfig'> for field duration_distribution_generator is not allowed: use default_factory
This error comes from the line: "from flsim.utils.example_utils import DataLoader, DataProvider"
To Reproduce
1. 2. 3. I try to run the tutorials and examples provided in the codebase but this problem persists.
Expected behavior
Environment
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