rename stuff and add a couple missing imports

mnist_example.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python3
 
 from onn import *
-from onn.floats import *
+from onn.float import *
 from dotmap import DotMap
 
 lower_priority()

onn/__init__.py

@@ -5,20 +5,20 @@
 #           this is gonna take some work.
 
 from .activation import *
-from .floats import *
+from .float import *
 from .initialization import *
 from .layer import *
 from .learner import *
 from .loss import *
 from .math import *
 from .model import *
-from .nodes import *
+from .nodal import *
 from .optimizer import *
 from .parametric import *
 from .regularizer import *
 from .ritual import *
-from .util import *
+from .utility import *
-from .weights import *
+from .weight import *
 
 # this is similar to default behaviour of having no __all__ variable at all,
 # but ours ignores modules as well. this allows for `import sys` and such

onn/activation.py

@@ -3,7 +3,7 @@ import numpy as np
 # just for speed, not strictly essential:
 from scipy.special import expit as sigmoid
 
-from .floats import *
+from .float import *
 from .layer_base import *
 
 class Identity(Layer):

onn/layer.py

@@ -1,6 +1,6 @@
 from .layer_base import *
 from .initialization import *
-from .floats import *
+from .float import *
 
 # Nonparametric Layers {{{1
 

onn/layer_base.py

@@ -2,7 +2,7 @@ import numpy as np
 
 from collections import defaultdict, OrderedDict
 
-from .weights import *
+from .weight import *
 
 # used for numbering layers like Keras:
 _layer_counters = defaultdict(lambda: 0)

onn/learner.py

@@ -1,4 +1,4 @@
-from .floats import *
+from .float import *
 from .optimizer_base import *
 
 class Learner:

onn/loss.py

@@ -1,6 +1,6 @@
 import numpy as np
 
-from .floats import *
+from .float import *
 
 class Loss:
     def forward(self, p, y):

onn/model.py

@@ -1,8 +1,9 @@
 import sys
 
-from .floats import *
+from .float import *
-from .nodes import *
+from .nodal import *
 from .layer_base import *
+from .utility import *
 
 class Model:
     def __init__(self, nodes_in, nodes_out, loss=None, mloss=None, unsafe=False):

onn/optimizer.py

@@ -1,7 +1,8 @@
 import numpy as np
 
-from .floats import *
+from .float import *
 from .optimizer_base import *
+from .utility import *
 
 # some of the the following optimizers are blatantly lifted from tiny-dnn:
 # https://github.com/tiny-dnn/tiny-dnn/blob/master/tiny_dnn/optimizers/optimizer.h

onn/optimizer_base.py

@@ -1,6 +1,6 @@
 import numpy as np
 
-from .floats import *
+from .float import *
 
 class Optimizer:
     def __init__(self, lr=0.1):

onn/parametric.py

@@ -1,6 +1,6 @@
 import numpy as np
 
-from .floats import *
+from .float import *
 from .layer_base import *
 from .initialization import *
 

onn/regularizer.py

@@ -1,6 +1,6 @@
 import numpy as np
 
-from .floats import *
+from .float import *
 
 class Regularizer:
     pass

onn/ritual.py

@@ -1,6 +1,6 @@
 import numpy as np
 
-from .floats import *
+from .float import *
 from .initialization import *
 from .ritual_base import *
 

onn/ritual_base.py

@@ -1,7 +1,7 @@
 import types
 import numpy as np
 
-from .floats import *
+from .float import *
 
 class Ritual: # i'm just making up names at this point.
     def __init__(self, learner=None):