Releases: lululxvi/deepxde
Releases · lululxvi/deepxde
DeepXDE v1.7.0
Areas of improvement
dde.icbc.PointSetBC
supports mini-batch- Bug fix
New APIs
- Backend paddle: Support
dde.nn.DeepONet
anddde.nn.DeepONetCartesianProd
API changes
- Change
dde.callback.PDEResidualResampler
todde.callback.PDEPointResampler
DeepXDE v1.6.2
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
anddde.nn.MIONetCartesianProd
support multiple merge operations
DeepXDE v1.6.1
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
New APIs
- Backend PyTorch adds
dde.nn.PODMIONet
- Backend PyTorch adds
dde.nn.MIONetCartesianProd
DeepXDE v1.6.0
Backend JAX supports PDE inverse problems.🎉🎉🎉
Areas of improvement
- Backend PyTorch supports l2 regularization
- Improve XLA jit
New APIs
- Add
dde.data.PDEOperatorCartesianProd
- Backend TensorFlow supports
dde.nn.PFNN
API changes
Model.train
:epochs
is replaced byiterations
- Merge
PIDeepONet
intoDeepONet
DeepXDE v1.5.1
Areas of improvement
- Bug fix:
dde.icbc.NeumannBC
fordde.geometry.Polygon
New APIs
- Add new geometry
dde.geometry.PointCloud
DeepXDE v1.5.0
Areas of improvement
- Support new loss "mean l2 relative error"
- Backend PyTorch supports
dde.nn.DeepONetCartesianProd
anddde.nn.PODDeepONet
- Backend PyTorch supports "step" LR decay
dde.callbacks.OperatorPredictor
supports backends tensorflow.compat.v1, tensorflow, pytorch, paddle- Fix
dde.config.set_random_seed
New APIs
- Add
dde.config.enable_xla_jit
anddde.config.disable_xla_jit
API changes
- Change
DDEBACKEND
toDDE_BACKEND
DeepXDE v1.4.0
DeepXDE supports a new backend PaddlePaddle.🎉🎉🎉
Areas of improvement
- Backend PyTorch supports
dde.nn.PFNN
- Backend TensorFlow 1.x enables XLA for GPU
DeepXDE v1.3.1
This is a bugfix release.
Areas of improvement
- Bug fix:
NeumannBC
andRobinBC
DeepXDE v1.3.0
Backend JAX supports ODE forward problems.🎉🎉🎉
Areas of improvement
- Backend TensorFlow supports
model.save
andmodel.restore
. - Backend TensorFlow uses
@tf.function(jit_compile=True)
for faster speed.
DeepXDE v1.2.0
DeepXDE supports physics-informed DeepONet.🎉🎉🎉
Areas of improvement
- Fix the issue when setting random seed via
dde.set_random_seed()
New APIs
- Support physics-informed DeepONet
- Add function spaces:
dde.data.PowerSeries
,dde.data.Chebyshev
,dde.data.GRF
,dde.data.GRF_KL
,dde.data.GRF2D
- Add
dde.data.PDEOperator
- Add
dde.nn.PIDeepONet
- Add function spaces: