Version 2.3.8

This release continues to add support for improving the usability of BrainPy.

New Features

1. New data structures for object-oriented transformations.
   • NodeList and NodeDict for a list/tuple/dict of BrainPyObject instances.
   • ListVar and DictVar for a list/tuple/dict of brainpy data.
2. Clip transformation for brainpy initializers.
3. All brainpylib operators are accessible in brainpy.math module. Especially there are some dedicated operators for scaling up the million-level neuron networks. For an example, see example in Simulating 1-million-neuron networks with 1GB GPU memory
4. Enable monitoring GPU models on CPU when setting DSRunner(..., memory_efficient=True). This setting can usually reduce so much memory usage.
5. brainpylib wheels on the Linux platform support the GPU operators. Users can install GPU version of brainpylib (require brainpylib>=0.1.7) directly by pip install brainpylib. @ztqakita

What's Changed

• Fix bugs and add more variable structures: ListVar and DictVar by @chaoming0625 in #345
• add CI for testing various models by @chaoming0625 in #346
• Update docs and tests by @chaoming0625 in #347
• Fix `Runner(jit=False)`` bug by @chaoming0625 in #348
• Compatible with jax>=0.4.7 by @chaoming0625 in #349
• Updates by @chaoming0625 in #350
• reconstruct BrainPy by merging brainpylib by @ztqakita in #351
• Intergate brainpylib operators into brainpy by @chaoming0625 in #352
• fix brainpylib call bug by @chaoming0625 in #354
• Enable memory-efficient DSRunner by @chaoming0625 in #355
• fix Array transform bug by @chaoming0625 in #356

Full Changelog: V2.3.7...V2.3.8