fix conflicts

brainpy/_src/dynsys.py

@@ -10,7 +10,7 @@
 
 from brainpy import tools, math as bm
 from brainpy._src.initialize import parameter, variable_
-from brainpy._src.mixin import SupportAutoDelay, Container, ReceiveInputProj, DelayRegister, global_delay_data
+from brainpy._src.mixin import SupportAutoDelay, Container, SupportInputProj, DelayRegister, global_delay_data
 from brainpy.errors import NoImplementationError, UnsupportedError
 from brainpy.types import ArrayType, Shape
 from brainpy._src.deprecations import _update_deprecate_msg
@@ -70,7 +70,7 @@ def update(self, x):
   return func
 
 
-class DynamicalSystem(bm.BrainPyObject, DelayRegister, ReceiveInputProj):
+class DynamicalSystem(bm.BrainPyObject, DelayRegister, SupportInputProj):
   """Base Dynamical System class.
 
   .. note::

brainpy/_src/math/object_transform/base.py

@@ -141,6 +141,8 @@ def fun(self):
            # that has been created.
            a = self.tracing_variable('a', bm.zeros, (10,))
 
+    .. versionadded:: 2.4.5
+
     Args:
       name: str. The variable name.
       init: callable, Array. The data to be initialized as a ``Variable``.

brainpy/_src/math/random.py

@@ -22,7 +22,7 @@
 __all__ = [
   'RandomState', 'Generator', 'DEFAULT',
 
-  'seed', 'default_rng', 'split_key',
+  'seed', 'default_rng', 'split_key', 'split_keys',
 
   # numpy compatibility
   'rand', 'randint', 'random_integers', 'randn', 'random',
@@ -1258,6 +1258,8 @@ def split_keys(n):
   internally by `pmap` and `vmap` to ensure that random numbers
   are different in parallel threads.
 
+  .. versionadded:: 2.4.5
+
   Parameters
   ----------
   n : int
@@ -1267,6 +1269,15 @@ def split_keys(n):
 
 
 def clone_rng(seed_or_key=None, clone: bool = True) -> RandomState:
+  """Clone the random state according to the given setting.
+
+  Args:
+    seed_or_key: The seed (an integer) or the random key.
+    clone: Bool. Whether clone the default random state.
+
+  Returns:
+    The random state.
+  """
   if seed_or_key is None:
     return DEFAULT.clone() if clone else DEFAULT
   else:

brainpy/_src/mixin.py

@@ -1,6 +1,5 @@
 import numbers
 import sys
-import warnings
 from dataclasses import dataclass
 from typing import Union, Dict, Callable, Sequence, Optional, TypeVar, Any
 from typing import (_SpecialForm, _type_check, _remove_dups_flatten)
@@ -28,12 +27,15 @@
   'ParamDesc',
   'ParamDescInit',
   'AlignPost',
-  'SupportAutoDelay',
   'Container',
   'TreeNode',
   'BindCondData',
   'JointType',
   'SupportSTDP',
+  'SupportAutoDelay',
+  'SupportInputProj',
+  'SupportOnline',
+  'SupportOffline',
 ]
 
 global_delay_data = dict()
@@ -47,59 +49,6 @@ class MixIn(object):
   pass
 
 
-class ReceiveInputProj(MixIn):
-  """The :py:class:`~.MixIn` that receives the input projections.
-
-  Note that the subclass should define a ``cur_inputs`` attribute.
-
-  """
-  cur_inputs: bm.node_dict
-
-  def add_inp_fun(self, key: Any, fun: Callable):
-    """Add an input function.
-
-    Args:
-      key: The dict key.
-      fun: The function to generate inputs.
-    """
-    if not callable(fun):
-      raise TypeError('Must be a function.')
-    if key in self.cur_inputs:
-      raise ValueError(f'Key "{key}" has been defined and used.')
-    self.cur_inputs[key] = fun
-
-  def get_inp_fun(self, key):
-    """Get the input function.
-
-    Args:
-      key: The key.
-
-    Returns:
-      The input function which generates currents.
-    """
-    return self.cur_inputs.get(key)
-
-  def sum_inputs(self, *args, init=0., label=None, **kwargs):
-    """Summarize all inputs by the defined input functions ``.cur_inputs``.
-
-    Args:
-      *args: The arguments for input functions.
-      init: The initial input data.
-      **kwargs: The arguments for input functions.
-
-    Returns:
-      The total currents.
-    """
-    if label is None:
-      for key, out in self.cur_inputs.items():
-        init = init + out(*args, **kwargs)
-    else:
-      for key, out in self.cur_inputs.items():
-        if key.startswith(label + ' // '):
-          init = init + out(*args, **kwargs)
-    return init
-
-
 class ParamDesc(MixIn):
   """:py:class:`~.MixIn` indicates the function for describing initialization parameters.
 
@@ -208,13 +157,6 @@ def get_data(self):
     return init
 
 
-class SupportAutoDelay(MixIn):
-  """``MixIn`` to support the automatic delay in synaptic projection :py:class:`~.SynProj`."""
-
-  def return_info(self) -> Union[bm.Variable, ReturnInfo]:
-    raise NotImplementedError('Must implement the "return_info()" function.')
-
-
 class Container(MixIn):
   """Container :py:class:`~.MixIn` which wrap a group of objects.
   """
@@ -550,8 +492,71 @@ def get_delay_var(self, name):
     return global_delay_data[name]
 
 
+class SupportInputProj(MixIn):
+  """The :py:class:`~.MixIn` that receives the input projections.
+
+  Note that the subclass should define a ``cur_inputs`` attribute.
+
+  """
+  cur_inputs: bm.node_dict
+
+  def add_inp_fun(self, key: Any, fun: Callable):
+    """Add an input function.
+
+    Args:
+      key: The dict key.
+      fun: The function to generate inputs.
+    """
+    if not callable(fun):
+      raise TypeError('Must be a function.')
+    if key in self.cur_inputs:
+      raise ValueError(f'Key "{key}" has been defined and used.')
+    self.cur_inputs[key] = fun
+
+  def get_inp_fun(self, key):
+    """Get the input function.
+
+    Args:
+      key: The key.
+
+    Returns:
+      The input function which generates currents.
+    """
+    return self.cur_inputs.get(key)
+
+  def sum_inputs(self, *args, init=0., label=None, **kwargs):
+    """Summarize all inputs by the defined input functions ``.cur_inputs``.
+
+    Args:
+      *args: The arguments for input functions.
+      init: The initial input data.
+      **kwargs: The arguments for input functions.
+
+    Returns:
+      The total currents.
+    """
+    if label is None:
+      for key, out in self.cur_inputs.items():
+        init = init + out(*args, **kwargs)
+    else:
+      for key, out in self.cur_inputs.items():
+        if key.startswith(label + ' // '):
+          init = init + out(*args, **kwargs)
+    return init
+
+
+class SupportAutoDelay(MixIn):
+  """``MixIn`` to support the automatic delay in synaptic projection :py:class:`~.SynProj`."""
+
+  def return_info(self) -> Union[bm.Variable, ReturnInfo]:
+    raise NotImplementedError('Must implement the "return_info()" function.')
+
+
 class SupportOnline(MixIn):
-  """:py:class:`~.MixIn` to support the online training methods."""
+  """:py:class:`~.MixIn` to support the online training methods.
+
+  .. versionadded:: 2.4.5
+  """
 
   online_fit_by: Optional  # methods for online fitting
 
@@ -563,7 +568,10 @@ def online_fit(self, target: ArrayType, fit_record: Dict[str, ArrayType]):
 
 
 class SupportOffline(MixIn):
-  """:py:class:`~.MixIn` to support the offline training methods."""
+  """:py:class:`~.MixIn` to support the offline training methods.
+
+  .. versionadded:: 2.4.5
+  """
 
   offline_fit_by: Optional  # methods for offline fitting
 
@@ -573,6 +581,8 @@ def offline_fit(self, target: ArrayType, fit_record: Dict[str, ArrayType]):
 
 class BindCondData(MixIn):
   """Bind temporary conductance data.
+
+
   """
   _conductance: Optional
 

brainpy/mixin.py

@@ -1,9 +1,9 @@
 
 from brainpy._src.mixin import (
   MixIn as MixIn,
-  ReceiveInputProj as ReceiveInputProj,
+  SupportInputProj as SupportInputProj,
   AlignPost as AlignPost,
-  AutoDelaySupp as AutoDelaySupp,
+  SupportAutoDelay as SupportAutoDelay,
   ParamDesc as ParamDesc,
   ParamDescInit as ParamDescInit,
   BindCondData as BindCondData,

docs/quickstart/installation.rst

@@ -78,8 +78,8 @@ BrainPy relies on `JAX`_. JAX is a high-performance JIT compiler which enables
 users to run Python code on CPU, GPU, and TPU devices. Core functionalities of
 BrainPy (>=2.0.0) have been migrated to the JAX backend.
 
-Linux & MacOS
-^^^^^^^^^^^^^
+Linux
+^^^^^
 
 Currently, JAX supports **Linux** (Ubuntu 16.04 or later) and **macOS** (10.12 or
 later) platforms. The provided binary releases of `jax` and `jaxlib` for Linux and macOS
@@ -108,6 +108,7 @@ If you want to install JAX with both CPU and NVidia GPU support, you must first
     # Note: wheels only available on linux.
     pip install --upgrade "jax[cuda11_pip]" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html
 
+
 Alternatively, you can download the preferred release ".whl" file for jaxlib
 from the above release links, and install it via ``pip``:
 
@@ -121,14 +122,46 @@ from the above release links, and install it via ``pip``:
 
     Note that the versions of jaxlib and jax should be consistent.
 
-    For example, if you are using jax==0.4.15, you would better install
-jax==0.4.15.
+    For example, if you are using jax==0.4.15, you would better install jax==0.4.15.
+
+
+MacOS
+^^^^^
+
+If you are using macOS Intel, we recommend you first to install the Miniconda Intel installer:
+
+1. Download the package in the link https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.pkg
+2. Then click the downloaded package and install it.
+
+
+If you are using the latest M1 macOS version, you'd better to install the Miniconda M1 installer:
+
+
+1. Download the package in the link https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-arm64.pkg
+2. Then click the downloaded package and install it.
+
+
+Finally, you can install `jax` and `jaxlib` as the same as the Linux platform.
+
+.. code-block:: bash
+
+   pip install --upgrade "jax[cpu]"
+
+
 
 Windows
 ^^^^^^^
 
-For **Windows** users, `jax` and `jaxlib` can be installed from the community supports.
-Specifically, you can install `jax` and `jaxlib` through:
+For **Windows** users with Python >= 3.9, `jax` and `jaxlib` can be installed
+directly from the PyPi channel.
+
+.. code-block:: bash
+
+   pip install jax jaxlib
+
+
+For **Windows** users with Python <= 3.8, `jax` and `jaxlib` can be installed
+from the community supports. Specifically, you can install `jax` and `jaxlib` through:
 
 .. code-block:: bash
 
@@ -141,7 +174,8 @@ If you are using GPU, you can install GPU-versioned wheels through:
    pip install "jax[cuda111]" -f https://whls.blob.core.windows.net/unstable/index.html
 
 Alternatively, you can manually install you favourite version of `jax` and `jaxlib` by
-downloading binary releases of JAX for Windows from https://whls.blob.core.windows.net/unstable/index.html .
+downloading binary releases of JAX for Windows from
+https://whls.blob.core.windows.net/unstable/index.html .
 Then install it via ``pip``:
 
 .. code-block:: bash
@@ -180,8 +214,9 @@ For windows, Linux and MacOS users, ``brainpylib`` supports CPU operators.
 For CUDA users, ``brainpylib`` only support GPU on Linux platform. You can install GPU version ``brainpylib``
 on Linux through ``pip install brainpylib`` too.
 
+
 Installation from docker
-========================
+------------------------
 
 If you want to use BrainPy in docker, you can use the following command
 to install BrainPy:
@@ -190,8 +225,9 @@ to install BrainPy:
 
    docker pull ztqakita/brainpy
 
+
 Running BrainPy online with binder
-==================================
+----------------------------------
 
 Click on the following link to launch the Binder environment with the
 BrainPy repository: