bump version

fix bug in function \theta for batchwise cosine similarity

README.md

@@ -456,7 +456,7 @@ python ./tasks/argmax_task.py -cuda 0 -lr 0.0001 -rnn_type lstm -memory_type dnc
 
 ## General noteworthy stuff
 
-1. SDNCs use the [FLANN approximate nearest neigbhour library](https://www.cs.ubc.ca/research/flann/), with its python binding [pyflann3](https://github.com/primetang/pyflann) and [FAISS](https://github.com/facebookresearch/faiss).
+1. SDNCs use the [FLANN approximate nearest neigbhour library](https://github.com/mariusmuja/flann), with its python binding [pyflann3](https://github.com/primetang/pyflann) and [FAISS](https://github.com/facebookresearch/faiss).
 
 FLANN can be installed either from pip (automatically as a dependency), or from source (e.g. for multithreading via OpenMP):
 

dnc/util.py

@@ -56,29 +56,23 @@ def cudalong(x, grad=False, gpu_id=-1):
     return t
 
 
-def θ(a, b, dimA=2, dimB=2, normBy=2):
-  """Batchwise Cosine distance
+def θ(a, b, normBy=2):
+  """Batchwise Cosine similarity
 
-  Cosine distance
+  Cosine similarity
 
   Arguments:
       a {Tensor} -- A 3D Tensor (b * m * w)
       b {Tensor} -- A 3D Tensor (b * r * w)
 
-  Keyword Arguments:
-      dimA {number} -- exponent value of the norm for `a` (default: {2})
-      dimB {number} -- exponent value of the norm for `b` (default: {1})
-
   Returns:
-      Tensor -- Batchwise cosine distance (b * r * m)
+      Tensor -- Batchwise cosine similarity (b * r * m)
   """
-  a_norm = T.norm(a, normBy, dimA, keepdim=True).expand_as(a) + δ
-  b_norm = T.norm(b, normBy, dimB, keepdim=True).expand_as(b) + δ
-
-  x = T.bmm(a, b.transpose(1, 2)).transpose(1, 2) / (
-      T.bmm(a_norm, b_norm.transpose(1, 2)).transpose(1, 2) + δ)
-  # apply_dict(locals())
-  return x
+  dot = T.bmm(a, b.transpose(1,2))
+  a_norm = T.norm(a, normBy, dim=2).unsqueeze(2)
+  b_norm = T.norm(b, normBy, dim=2).unsqueeze(1)
+  cos = dot / (a_norm * b_norm + δ)
+  return cos.transpose(1,2).contiguous()
 
 
 def σ(input, axis=1):

setup.py

@@ -22,7 +22,7 @@ with open(path.join(here, 'README.rst'), encoding='utf-8') as f:
 setup(
     name='dnc',
 
-    version='1.0.3',
+    version='1.1.0',
     description='Differentiable Neural Computer, for Pytorch',
     long_description=long_description,