| title | order | snippet | summary-home | featured-home |
|---|---|---|---|---|
Mobile (Experimental) |
4 |
```python
## Save your model
torch.jit.script(model).save("my_mobile_model.pt")
## iOS prebuilt binary
pod ‘LibTorch’
## Android prebuilt binary
implementation 'org.pytorch:pytorch_android:1.3.0'
## Run your model (Android example)
Tensor input = Tensor.fromBlob(data, new long[]{1, data.length});
IValue output = module.forward(IValue.tensor(input));
float[] scores = output.getTensor().getDataAsFloatArray();
```
|
PyTorch supports an end-to-end workflow from Python to deployment on iOS and Android. It extends the PyTorch API to cover common preprocessing and integration tasks needed for incorporating ML in mobile applications. |
false |
PyTorch supports an end-to-end workflow from Python to deployment on iOS and Android. It extends the PyTorch API to cover common preprocessing and integration tasks needed for incorporating ML in mobile applications.