Dataloader with concurrency improvements (from https://github.com/iarai/concurrent-dataloader)
Project description
PytorchConcurrentDataloader
Minimal version of the ConcurrentDataloader repository published to pip.
Setup
pip install pytorch-concurrent-dataloader
Usage
- replace
torch.utils.data.DataLoader
withpytorch_concurrent_dataloader.DataLoader
- pass new parameters for concurrent dataloading
from pytorch_concurrent_dataloader import DataLoader
dataloader = DataLoader(
# pass old parameters as usual
dataset=...,
batch_size=...,
num_workers=...,
# pass new parameters
num_fetch_workers=...,
)
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Close
Hashes for pytorch_concurrent_dataloader-0.0.3.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | df1256e155102e7ae6cfd84ec18b73a26b89f6a040e22319255a8abcdedaafc3 |
|
MD5 | 2d2b1cbf4832636e693fd7ded4355b6b |
|
BLAKE2b-256 | f5dc3cf53fcb784ae63d1ddd4087de7bfadfc5bf126ae342f95113540a02077f |
Close
Hashes for pytorch_concurrent_dataloader-0.0.3-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 75ac4fc7e99a78456864883381d4640f47315dcb95f2ead0be19ed965ceb0f1a |
|
MD5 | 725f513c5ef66dad962bcdd87637051f |
|
BLAKE2b-256 | b123b51e57576dfa0306fb2b69aca73c10970d4409793d80535486feda486e46 |