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-0.0.6.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | babbcf6ba8a57705043a17fbdbf892c830a343432072f21d63cd6462432422cf |
|
MD5 | 8bd5706a314eaccff7902f6fdbba9f8c |
|
BLAKE2b-256 | 2a1d386e9010bf26f47cee85743d212bc5df213d773638af10c39e8581843e85 |
Close
Hashes for pytorch_concurrent_dataloader-0.0.6-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5ecb438a4fb5a38df1a1d868b6dbb5e9f48de4779b789c253084e4e985f56957 |
|
MD5 | 7c4ca4c41727185c39e791a7720f31ad |
|
BLAKE2b-256 | 0fd5325f6b9562efefe3206d7a1d6d82c58ad45b8522e1528ecce72b18d03a76 |