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This package contains a pure-python class that wraps a list of dataloaders and allows to iterate over them in a random order.
This repository contains an hyper-simple wrapper class that allows to iterate over a list of dataloaders in a transparent way.
pip install list-dataloaders
or directly from the repository:
pip install git+https://github.com/MorenoLaQuatra/list-dataloaders.git
from list_dataloaders import ListDataLoaders
list_dataloaders = []
train_dl1 = DataLoader(...)
train_dl2 = DataLoader(...)
train_dl3 = DataLoader(...)
list_dataloaders.append(train_dl1)
list_dataloaders.append(train_dl2)
list_dataloaders.append(train_dl3)
train_dls = ListDataLoaders(list_dataloaders)
for batch in train_dls:
print(batch)
The main class ListDataLoaders
has the following parameters:
dataloaders
: the list of dataloaders to iterate oververbose
: if True, prints the number of samples in each dataloader (default: False)weight_by_num_samples
: if True, the probability of sampling a dataloader is proportional to the number of samples in the dataloader (default: True)This project is licensed under the terms of the MIT license.
If you encounter any problems, please file an issue along with a detailed description.
FAQs
This package contains a pure-python class that wraps a list of dataloaders and allows to iterate over them in a random order.
We found that list-dataloaders demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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Product
Socket now supports Scala and Kotlin, bringing AI-powered threat detection to JVM projects with easy manifest generation and fast, accurate scans.
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