mirror of https://github.com/tracel-ai/burn.git
24 lines
1.1 KiB
Markdown
24 lines
1.1 KiB
Markdown
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# MNIST
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The example is showing you how to:
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* Define your own custom module (MLP).
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* Create the data pipeline from a raw dataset to a batched multi-threaded fast DataLoader.
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* Configure a learner to display and log metrics as well as to keep training checkpoints.
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The example can be run like so:
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```bash
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git clone https://github.com/burn-rs/burn.git
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cd burn
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# Use the --release flag to really speed up training.
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echo "Using ndarray backend"
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cargo run --example mnist --release --features ndarray # CPU NdArray Backend - f32 - single thread
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cargo run --example mnist --release --features ndarray-blas-openblas # CPU NdArray Backend - f32 - blas with openblas
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cargo run --example mnist --release --features ndarray-blas-netlib # CPU NdArray Backend - f32 - blas with netlib
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echo "Using tch backend"
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export TORCH_CUDA_VERSION=cu113 # Set the cuda version
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cargo run --example mnist --release --features tch-gpu # GPU Tch Backend - f16
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cargo run --example mnist --release --features tch-cpu # CPU Tch Backend - f32
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```
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