[readme] Update README.md

.github/workflows/CI.yml

@@ -79,6 +79,8 @@ jobs:
           if [ -f requirements-dev.txt ]; then pip install -r requirements-dev.txt; fi
           pip uninstall brainpy -y
           python setup.py install
+          pip install jax==0.4.30
+          pip install jaxlib==0.4.30
       - name: Test with pytest
         run: |
           cd brainpy

README.md

@@ -49,6 +49,19 @@ We provide a Binder environment for BrainPy. You can use the following button to
 
 [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/brainpy/BrainPy-binder/main)
 
+## Brain Dynamics Programming Ecosystem
+
+We are building an ecosystem for bain dynamics programming (BDP), evolving from our previously experimental [BrainPy package](https://github.com/brainpy/BrainPy).
+
+The BDP ecosystem is a collection of tools, libraries, and frameworks that can be used to build brain dynamics models and applications.
+
+The BDP ecosystem is designed to be modular, so you can use as much or as little of it as you need.
+
+The details for this ecosystem please see: https://ecosystem-for-brain-dynamics.readthedocs.io/
+
+We welcome contributions from the community, so if you have an idea for a new tool or library, please let us know! Please email us at: <[email protected]>.
+
+
 
 ## Ecosystem
 

brainpy/_src/dnn/tests/test_activation.py

@@ -4,6 +4,7 @@
 import brainpy.math as bm
 
 
+
 class Test_Activation(parameterized.TestCase):
 
   @parameterized.product(

brainpy/_src/dnn/tests/test_conv_layers.py

@@ -1,12 +1,17 @@
 # -*- coding: utf-8 -*-
+import platform
 
 import jax.numpy as jnp
+import pytest
 from absl.testing import absltest
 from absl.testing import parameterized
 
 import brainpy as bp
 import brainpy.math as bm
 
+if platform.system() == 'Darwin':
+  pytest.skip('skip Mac OS', allow_module_level=True)
+
 
 class TestConv(parameterized.TestCase):
   def test_Conv2D_img(self):

brainpy/_src/math/op_register/ad_support.py

@@ -41,9 +41,14 @@ def _standard_jvp(jvp_rules, primitive: Primitive, primals, tangents, **params):
       r = tuple(rule(t, *primals, **params))
       tangents_out.append(r)
       assert tree_util.tree_structure(r) == tree
-  return val_out, functools.reduce(_add_tangents,
+  try:
+    return val_out, functools.reduce(_add_tangents,
                                    tangents_out,
-                                   tree_util.tree_map(lambda a: ad.Zero.from_value(a), val_out))
+                                   tree_util.tree_map(lambda a: ad.Zero.from_primal_value(a), val_out))
+  except:
+    return val_out, functools.reduce(_add_tangents,
+                                     tangents_out,
+                                     tree_util.tree_map(lambda a: ad.Zero.from_value(a), val_out))
 
 
 def _add_tangents(xs, ys):