add more functions to docs

docs/source/nn.rst

@@ -383,6 +383,15 @@ Sparse layers
 .. autoclass:: Embedding
     :members:
 
+Distance functions
+----------------------------------
+
+:hidden:`PairwiseDistance`
+~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. autoclass:: PairwiseDistance
+    :members:
+
 
 Loss functions
 ----------------------------------
@@ -774,6 +783,15 @@ Dropout functions
 
 .. autofunction:: dropout
 
+Distance functions
+----------------------------------
+
+:hidden:`pairwise_distance`
+~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. autofunction:: pairwise_distance
+
+
 Loss functions
 --------------
 

docs/source/torch.rst

@@ -160,6 +160,8 @@ BLAS and LAPACK Operations
 .. autofunction:: addr
 .. autofunction:: baddbmm
 .. autofunction:: bmm
+.. autofunction:: btrifact
+.. autofunction:: btrisolve                  
 .. autofunction:: dot
 .. autofunction:: eig
 .. autofunction:: gels

torch/nn/functional.py

@@ -639,7 +639,7 @@ def pairwise_distance(x1, x2, p=2, eps=1e-6):
 
         Shape:
             - Input: :math:`(N, D)` where `D = vector dimension`
-            - Output: :math:`(N, 1)
+            - Output: :math:`(N, 1)`
 
         >>> input1 = autograd.Variable(torch.randn(100, 128))
         >>> input2 = autograd.Variable(torch.randn(100, 128))

torch/nn/modules/distance.py

@@ -16,7 +16,7 @@ class PairwiseDistance(Module):
 
         Shape:
             - Input: :math:`(N, D)` where `D = vector dimension`
-            - Output: :math:`(N, 1)
+            - Output: :math:`(N, 1)`
 
         >>> pdist = nn.PairwiseDistance(2)
         >>> input1 = autograd.Variable(torch.randn(100, 128))