re-activating layer-wise actf

Author: ehsanhaghighat

SciANN.egg-info/PKG-INFO

@@ -1,6 +1,6 @@
 Metadata-Version: 2.1
 Name: SciANN
-Version: 0.6.8.4
+Version: 0.6.8.5
 Summary: A Keras/Tensorflow wrapper for scientific computations and physics-informed deep learning using artificial neural networks.
 Home-page: https://github.com/sciann/sciann
 Author: Ehsan Haghighat

sciann/__init__.py

@@ -41,7 +41,7 @@
 __credits__ = []
 __url__ = "http://github.com/sciann/sciann]"
 __license__ = "MIT"
-__version__ = "0.6.8.4"
+__version__ = "0.6.8.5"
 __cite__ = \
     '@article{haghighat2021sciann, \n' +\
     '    title={SciANN: A Keras/TensorFlow wrapper for scientific computations and physics-informed deep learning using artificial neural networks}, \n' +\

sciann/functionals/functional.py

@@ -83,10 +83,18 @@ def Functional(
     if not all([isinstance(n, int) for n in hidden_layers]):
         raise TypeError("Enter a list of integers as the third input assigning layer widths, e.g. [10,10,10]. ")
     # prepare kernel initializers.
-    activations, def_biasinit, def_kerinit = \
-        prepare_default_activations_and_initializers(
-        len(hidden_layers) * [activation] + [output_activation]
-    )
+    if isinstance(activation, list) and isinstance(activation[0], list):
+        assert len(activation) == len(hidden_layers), \
+            'to specify activation per layer, make sure len(activation)==len(hidden_layer).'
+        activations, def_biasinit, def_kerinit = \
+            prepare_default_activations_and_initializers(
+            activation + [output_activation]
+        )
+    else:
+        activations, def_biasinit, def_kerinit = \
+            prepare_default_activations_and_initializers(
+            len(hidden_layers) * [activation] + [output_activation]
+        )
     if kernel_initializer is None:
         kernel_initializer = def_kerinit
     elif isinstance(kernel_initializer, (float, int)):

setup.py

@@ -15,7 +15,7 @@
 
 setup(
     name='SciANN',
-    version='0.6.8.4',
+    version='0.6.8.5',
     description='A Keras/Tensorflow wrapper for scientific computations and physics-informed deep learning using artificial neural networks.',
     long_description=long_description,
     author='Ehsan Haghighat',