Merge branch 'master' of https://github.com/brainpy/BrainPy

.github/workflows/CI-models.yml

@@ -32,7 +32,6 @@ jobs:
           python-version: ${{ matrix.python-version }}
       - name: Install dependencies
         run: |
-          pip install taichi-nightly -i https://pypi.taichi.graphics/simple/
           if [ -f requirements-dev.txt ]; then pip install -r requirements-dev.txt; fi
           pip uninstall brainpy -y
           python setup.py install
@@ -80,7 +79,6 @@ jobs:
         python-version: ${{ matrix.python-version }}
     - name: Install dependencies
       run: |
-        pip install taichi-nightly -i https://pypi.taichi.graphics/simple/
         if [ -f requirements-dev.txt ]; then pip install -r requirements-dev.txt; fi
         pip uninstall brainpy -y
         python setup.py install
@@ -130,7 +128,6 @@ jobs:
     - name: Install dependencies
       run: |
         python -m pip install numpy>=1.21.0
-        pip install taichi-nightly -i https://pypi.taichi.graphics/simple/
         python -m pip install -r requirements-dev.txt
         python -m pip install tqdm brainpylib
         pip uninstall brainpy -y

brainpy/_src/dnn/activations.py

@@ -840,10 +840,10 @@ class Softplus(Layer):
       >>> output = m(input)
   """
   __constants__ = ['beta', 'threshold']
-  beta: int
-  threshold: int
+  beta: float
+  threshold: float
 
-  def __init__(self, beta: int = 1, threshold: int = 20) -> None:
+  def __init__(self, beta: float = 1, threshold: float = 20.) -> None:
     super().__init__()
     self.beta = beta
     self.threshold = threshold

brainpy/_src/math/activations.py

@@ -298,7 +298,7 @@ def leaky_relu(x, negative_slope=1e-2):
   return jnp.where(x >= 0, x, negative_slope * x)
 
 
-def softplus(x, beta=1, threshold=20):
+def softplus(x, beta: float = 1., threshold: float = 20.):
   r"""Softplus activation function.
 
   Computes the element-wise function
@@ -315,12 +315,12 @@ def softplus(x, beta=1, threshold=20):
   Parameters
   ----------
   x: The input array.
-  beta: the :math:`\beta` value for the Softplus formulation. Default: 1
-  threshold: values above this revert to a linear function. Default: 20
+  beta: the :math:`\beta` value for the Softplus formulation. Default: 1.
+  threshold: values above this revert to a linear function. Default: 20.
 
   """
   x = x.value if isinstance(x, Array) else x
-  return jnp.where(x > threshold, x * beta, 1 / beta * jnp.logaddexp(beta * x, 0))
+  return jnp.where(x > threshold / beta, x, 1 / beta * jnp.logaddexp(beta * x, 0))
 
 
 def log_sigmoid(x):

requirements-dev.txt

@@ -7,7 +7,7 @@ matplotlib
 msgpack
 tqdm
 pathos
-taichi
+taichi==1.7.0
 
 # test requirements
 pytest

requirements-doc.txt

@@ -5,7 +5,7 @@ matplotlib
 numpy
 scipy
 numba
-taichi
+taichi==1.7.0
 
 # document requirements
 pandoc