Theano pairwise function

pairwise/pairwise_theano.py

@@ -0,0 +1,37 @@
+
+import theano
+import theano.tensor as TT
+
+from pairwise_python import pairwise_python_inner_broadcasting
+
+def pairwise_theano_tensor_prepare(dtype):
+    X = TT.matrix(dtype=str(dtype))
+    dists = TT.sqrt(
+        TT.sum(
+            TT.sqr(X[:, None, :] - X),
+            axis=2))
+    rval = theano.function([X],
+            theano.Out(dists, borrow=True),
+            allow_input_downcast=True)
+    rval.__name__ = 'pairwise_theano_tensor_' + dtype
+    return rval
+
+def pairwise_theano_blas_prepare(dtype):
+    X = TT.matrix(dtype=str(dtype))
+    X_norm_2 = (X ** 2).sum(axis=1)
+    dists = TT.sqrt(2 * X_norm_2 - TT.dot(X, X.T))
+    rval = theano.function([X],
+            theano.Out(dists, borrow=True),
+            allow_input_downcast=True)
+    rval.__name__ = 'pairwise_theano_blas_' + dtype
+    return rval
+
+
+benchmarks = (
+    pairwise_theano_tensor_prepare('float32'),
+    pairwise_theano_tensor_prepare('float64'),
+    pairwise_theano_blas_prepare('float32'),
+    pairwise_theano_blas_prepare('float64'),
+)
+
+

run_benchmarks.py

@@ -2,7 +2,10 @@
 # License: MIT
 from __future__ import print_function
 
-from collections import OrderedDict
+try:
+    from collections import OrderedDict
+except:
+    from ordereddict import OrderedDict
 import json
 import os
 import traceback