new long[] {2, 3} // shape
        );
IValue result = mod.forward(IValue.from(data), IValue.from(3.0));
Tensor output = result.toTensor();
System.out.println("shape: " + Arrays.toString(output.shape()));
System.out.println("data: " + Arrays.toString(output.getDataAsFloatArray()));
```
Learn more about how to use PyTorch from Java here, and see the full Javadocs API documentation here.
For the full 1.4 release notes, see here.
Domain Libraries
PyTorch domain libraries like torchvision, torchtext, and torchaudio complement PyTorch with common datasets, models, and transforms. We’re excited to share new releases for all three domain libraries alongside the PyTorch 1.4 core release.
torchvision 0.5
The improvements to torchvision 0.5 mainly focus on adding support for production deployment including quantization, TorchScript, and ONNX. Some of the highlights include: