A lot of implementations for backend [paddle](https://www.paddlepaddle.org.cn/en)! Feel free to use backend paddle.🎉🎉🎉
Areas of improvement
- `dde.nn.FNN` supports defining activation functions for each layer - `dde.geometry.PointCloud` supports boundary points and normals - Bug fix
New APIs
- Backend PyTorch: Support `dde.nn.DeepONet`
1.7.2
Areas of improvement
- Add `dde.icbc.PointSetOperatorBC` - `dde.callbacks.OperatorPredictor` can be used during training - Backend PyTorch: `dde.icbc.PointSetBC` supports multi-component outputs - Bug fix
1.7.1
Areas of improvement
- `dde.data.TripleCartesianProd` and `dde.data.QuadrupleCartesianProd` support mini-batch for both branch and trunk nets - Backend TensorFlow 1.x: L-BFGS dumps trainable variables and test loss
- Backend paddle: Support `dde.nn.DeepONet` and `dde.nn.DeepONetCartesianProd`
API changes
- Change `dde.callback.PDEResidualResampler` to `dde.callback.PDEPointResampler`
1.6.2
Areas of improvement
- Set Hammersley as the default point sampling for PINN - Improve point sampling of `dde.geometry.GeometryXTime.random_points` - `dde.callback.ModelCheckpoint` supports monitoring test loss - PyTorch backend: `dde.nn.PODMIONet` and `dde.nn.MIONetCartesianProd` support multiple merge operations
1.6.1
Areas of improvement
- Backend TensorFlow 1.x `dde.nn.DeepONet` supports customized branch - Fix `Triangle.on_boundary` for float32 - Bug fix: a few issues of float64 - Many documentation improvements