Version 2.3.0
This branch of releases aims to provide a unified computing framework for brain simulation and brain-inspired computing.
New features
brainpy.BPTT
supportstrain_data
andtest_data
with general Python iterators. For instance, one can train a model with PyTorch dataloader or TensorFlow datasets.
import torchvision
from torch.utils.data import DataLoader
data = torchvision.datasets.CIFAR10("./CIFAR10", train=False, transform=torchvision.transforms.ToTensor())
loader = DataLoader(dataset=data, batch_size=4, shuffle=True, num_workers=0, drop_last=False)
# any generator can be used for train_data or test_data
trainer = bp.BPTT()
trainer.fit(loader)
-
Consolidated object-oriented transformation in
brainpy.math.object_transform
module. All brainpy transformations generate a newBrainPyObject
instance so that objects in brainpy can be composed hierarchically.brainpy.math.to_object()
transformation transforms a pure Python function into aBrainPyObject
. -
New documentation is currently online for introducing the consolidated BrainPy concept of object-oriented transformation.
-
Change
brainpy.math.JaxArray
tobrainpy.math.Array
.
Deprecations
brainpy.datasets
module is no longer supported. New APIs will be moved intobrainpy-datasets
package.brainpy.train.BPTT
no longer support to receive the train data[X, Y]
. Instead, users should provide a data generator such likepytorch
dataset ortensorflow
dataset.- The update function of
brainpy.math.TimeDealy
does not support receiving atime
index. Instead, one can update the new data by directly usingTimeDealy.update(data)
instead ofTimeDealy.update(time, data)
. - Fix the monitoring error of delay differential equations with
brainpy.integrators.IntegratorRunner
.
Bug Fixes
- Fix the bug on
One2One
connection. - Fix the bug in
eprop
example. - Fix
ij2csr
transformation error. - Fix test bugs
What's Changed
- fix eprop example error by @chaoming0625 in #305
- minor updates on API and DOC by @chaoming0625 in #306
- Add new optimizers by @chaoming0625 in #307
- add documentation of for random number generation by @chaoming0625 in #308
- consolidate the concept of OO transformation by @chaoming0625 in #309
- Upgrade documetations by @chaoming0625 in #310
- Ready for publish by @chaoming0625 in #311
Full Changelog: V2.2.4.0...V2.3.0