sagemaker-training-toolkit
torchlambda
| sagemaker-training-toolkit | torchlambda | |
|---|---|---|
| 1 | 2 | |
| 470 | 123 | |
| 2.8% | - | |
| 6.3 | 0.0 | |
| about 1 month ago | over 2 years ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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sagemaker-training-toolkit
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Distributed training with Horovod/MPI
I'm using sagemaker-training-toolkit to attempt hyperparameter optimization and trying to take advantage of all the cores on each machine using their MPI options (which uses Horovod with MPI to my understanding). I'm pretty new to this space and can't find anything that describes in somewhat lay-terms how training works in this distributed model. With AllReduce, how often does the reduce happen? I'm trying to figure out if all training threads are training a shared model such that every thread is training on the "latest" version of the model.
torchlambda
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AWS lambda inference taking 3s even after warmup
Ok I see. Have you maximized the ram in the lambdas? Since performance scale with ram. I have been using torchlambda.
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[D] Anyone deploy DL models with AWS Lambda? Trying to estimate costs
I don't think aws lambda has gpu support. We use torchlambda to static build the deployment. You end up with a small binary
What are some alternatives?
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