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Distributed support cifar (#1301)
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@@ -48,3 +48,17 @@ Note this was run on an M1 Macbook Pro with 16GB RAM.
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At the time of writing, `mlx` doesn't have built-in learning rate schedules.
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We intend to update this example once these features are added.
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## Distributed training
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The example also supports distributed data parallel training. You can launch a
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distributed training as follows:
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```shell
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$ cat >hostfile.json
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[
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{"ssh": "host-to-ssh-to", "ips": ["ip-to-bind-to"]},
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{"ssh": "host-to-ssh-to", "ips": ["ip-to-bind-to"]}
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]
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$ mlx.launch --verbose --hostfile hostfile.json main.py --batch 256 --epochs 5 --arch resnet20
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```
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