mirror of https://github.com/hpcaitech/ColossalAI
32 lines
987 B
Markdown
32 lines
987 B
Markdown
# Comparison of Large Batch Training Optimization
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## 🚀Quick Start
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Run with synthetic data
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```bash
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colossalai run --nproc_per_node 4 train.py --config config.py -s
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```
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## Prepare Dataset
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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`.
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The dataset will be downloaded to `colossalai/examples/tutorials/data` by default.
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If you wish to use customized directory for the dataset. You can set the environment variable `DATA` via the following command.
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```bash
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export DATA=/path/to/data
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```
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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.
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## Run on 2*2 device mesh
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```bash
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# run with cifar10
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colossalai run --nproc_per_node 4 train.py --config config.py
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# run with synthetic dataset
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colossalai run --nproc_per_node 4 train.py --config config.py -s
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```
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