notwa/optim
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

add/remove comments and fix code style

Browse Source
This commit is contained in:
Connor Olding 2017-08-02 03:59:15 +00:00
parent 8b3b8d8288
commit f28e8d3a54
1 changed files with 4 additions and 8 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

12
onn_core.py
View File

@ -482,6 +482,7 @@ class Layer:
_layer_counters[kind] += 1
self.name = "{}_{}".format(kind, _layer_counters[kind])
self.unsafe = False # disables assertions for better performance
# TODO: allow weights to be shared across layers.
def __str__(self):
return self.name
@ -851,6 +852,7 @@ class Model:
self.make_weights()
for node in self.nodes:
node.unsafe = unsafe
# TODO: handle the same layer being in more than one node.
@property
def ordered_nodes(self):
@ -978,6 +980,7 @@ class Model:
class Ritual: # i'm just making up names at this point.
def __init__(self, learner=None, loss=None, mloss=None):
# TODO: store loss and mloss in Model instead of here.
self.learner = learner if learner is not None else Learner(Optimizer())
self.loss = loss if loss is not None else Squared()
self.mloss = mloss if mloss is not None else loss
@ -1069,13 +1072,6 @@ class Ritual: # i'm just making up names at this point.
self.bn += 1
if gen:
# TODO: pass self as an argument to the generator.
# ...is there a pythonic way of doing that?
# as it turns out, there is! (untested code)
# in the generator: model = yield
# yield dostuff(model)
# in here: generator.send()
# stuff = next(generator)
batch_inputs, batch_outputs = next(generator)
batch_size = batch_inputs.shape[0]
# TODO: lift this restriction
@ -1087,7 +1083,7 @@ class Ritual: # i'm just making up names at this point.
batch_outputs = outputs[bi:bi+batch_size]
self._train_batch(batch_inputs, batch_outputs, b, batch_count,
test_only, return_losses == 'both', return_losses)
test_only, return_losses=='both', return_losses)
prev_batch_size = batch_size