Introduce param data/modules, regularizers, and T transforms (#67)

* Add parameter management module with bijective transforms and state containers

* Bump version to 0.1.6 and update changelog with new features, improvements, breaking changes, and bug fixes

Author: chaoming0625

braintools/__init__.py

@@ -14,7 +14,7 @@
 # ==============================================================================
 
 
-__version__ = "0.1.5"
+__version__ = "0.1.6"
 __version_info__ = tuple(map(int, __version__.split(".")))
 
 from . import conn
@@ -34,10 +34,17 @@
 from ._spike_operation import __all__ as operation_all
 
 __all__ = [
-              'conn', 'input', 'init',
-              'file', 'metric', 'visualize',
-              'optim', 'tree', 'quad',
-              'surrogate', 'param',
+              'conn',
+              'input',
+              'init',
+              'file',
+              'metric',
+              'visualize',
+              'optim',
+              'tree',
+              'quad',
+              'surrogate',
+              'param',
           ] + encoder_all + operation_all
 
 del encoder_all, operation_all

braintools/init/_init_basic.py

@@ -444,7 +444,7 @@ def __init__(
         self.unit = unit
 
     def __call__(self, size, **kwargs):
-        rng = kwargs.get('rng', brainstate.random)
+        rng = kwargs.get('rng', np.random)
         mean, unit = u.split_mantissa_unit(self.mean)
         std = u.Quantity(self.std).to(unit).mantissa
 

braintools/optim/_optax_optimizer.py

@@ -3553,7 +3553,7 @@ class Rprop(OptaxOptimizer):
         >>> # Setup for batch learning
         >>> model = brainstate.nn.Sequential(
         ...     brainstate.nn.Linear(100, 50),
-        ...     brainstate.nn.Tanh(),
+        ...     brainstate.nn.TanhT(),
         ...     brainstate.nn.Linear(50, 10)
         ... )
         >>>

braintools/param/__init__.py

@@ -13,13 +13,21 @@
 # limitations under the License.
 # ==============================================================================
 
-from ._base import *
-from ._base import __all__ as base_all
+from ._data import *
+from ._data import __all__ as data_all
+from ._module import *
+from ._module import __all__ as module_all
+from ._regularization import *
+from ._regularization import __all__ as reg_all
 from ._state import *
 from ._state import __all__ as state_all
 from ._transform import *
 from ._transform import __all__ as transform_all
 
-__all__ = state_all + transform_all + base_all
+__all__ = state_all + transform_all + reg_all + module_all + data_all
 
-del transform_all, base_all, state_all
+del transform_all
+del state_all
+del reg_all
+del module_all
+del data_all