Minimalistic & easy deployment of PyTorch models on AWS Lambda with C++
Project description
torchlambda is a tool to deploy PyTorch models on Amazon's AWS Lambda using AWS SDK for C++ and custom C++ runtime.
Using statically compiled dependencies whole package is shrunk to only 30MB.
Due to small size of compiled source code users can pass their models as AWS Lambda layers. Services like Amazon S3 are no longer necessary to load your model.
torchlambda has it's PyTorch & AWS dependencies always up to date because of continuous deployment run at 03:00 a.m.
every day.
| Docs | Deployment | Package | Python | PyTorch | Docker | CodeBeat | Images |
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Comparison with other deployment tools
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| Trait / Tool | torchlambda | fastai Lambda | KubeFlow | Tensorflow Serving |
|---|---|---|---|---|
| Autoscaling | :heavy_check_mark: | :heavy_check_mark: | with Kubernetes | with Kubernetes |
| Light/Heavy load | Light | Light | Heavy/Both | Both |
| GPU Support | :x: | :x: | :heavy_check_mark: | :heavy_check_mark: |
| Serverless | :heavy_check_mark: | :heavy_check_mark: | :x: | :x: |
| Required services | AWS Lambda | AWS Lambda, AWS S3 | Kubernetes Cluster & cloud provider | Deployable in various settings |
| Multiple frameworks | :x: | :x: | :heavy_check_mark: | :x: |
| Latest framework 1 | :heavy_check_mark: | :x: | :x: | :heavy_check_mark: |
| Version (higher more mature) | CD | N/A | 1.0 | 2.1.0 |
| Customizable dependencies 2 | :heavy_check_mark: | :x: | :x: | :x: |
| Deployment size 3 | ~30Mb | +1Gb | N/A | ~67Mb4 |
Table Of Contents
Footnotes
1. Support for latest version of it's main DL framework or main frameworks if multiple supported
2. Project dependencies are easily customizable. In torchlambda it would be user
specified build procedures for libtorch and AWS C++ SDK
3. Necessary size of code and dependencies to deploy model
4. Based on Dockerfile size
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