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train.py |
README.md
Handson 4: Comparison of Large Batch Training Optimization
Prepare Dataset
We use CIFAR10 dataset in this example. You should invoke the donwload_cifar10.py
in the tutorial root directory or directly run the auto_parallel_with_resnet.py
.
The dataset will be downloaded to colossalai/examples/tutorials/data
by default.
If you wish to use customized directory for the dataset. You can set the environment variable DATA
via the following command.
export DATA=/path/to/data
You can also use synthetic data for this tutorial if you don't wish to download the CIFAR10
dataset by adding the -s
or --synthetic
flag to the command.
Run on 2*2 device mesh
# run with cifar10
colossalai run --nproc_per_node 4 train.py --config config.py
# run with synthetic dataset
colossalai run --nproc_per_node 4 train.py --config config.py -s