use assert in example code snippets, and not == followed by True

edward/util/random_variables.py

@@ -376,8 +376,7 @@ def get_ancestors(x, collection=None):
   >>> b = Normal(mu=a, sigma=1.0)
   >>> c = Normal(mu=0.0, sigma=1.0)
   >>> d = Normal(mu=tf.mul(b, c), sigma=1.0)
-  >>> set(ed.get_ancestors(d)) == set([a, b, c])
-  True
+  >>> assert set(ed.get_ancestors(d)) == set([a, b, c])
   """
   if collection is None:
     collection = random_variables()
@@ -429,8 +428,7 @@ def get_children(x, collection=None):
   >>> b = Normal(mu=a, sigma=1.0)
   >>> c = Normal(mu=a, sigma=1.0)
   >>> d = Normal(mu=c, sigma=1.0)
-  >>> set(ed.get_children(a)) == set([b, c])
-  True
+  >>> assert set(ed.get_children(a)) == set([b, c])
   """
   if collection is None:
     collection = random_variables()
@@ -483,8 +481,7 @@ def get_descendants(x, collection=None):
   >>> b = Normal(mu=a, sigma=1.0)
   >>> c = Normal(mu=a, sigma=1.0)
   >>> d = Normal(mu=c, sigma=1.0)
-  >>> set(ed.get_descendants(a)) == set([b, c, d])
-  True
+  >>> assert set(ed.get_descendants(a)) == set([b, c, d])
   """
   if collection is None:
     collection = random_variables()
@@ -537,8 +534,7 @@ def get_parents(x, collection=None):
   >>> b = Normal(mu=a, sigma=1.0)
   >>> c = Normal(mu=0.0, sigma=1.0)
   >>> d = Normal(mu=tf.mul(b, c), sigma=1.0)
-  >>> set(ed.get_parents(d)) == set([b, c])
-  True
+  >>> assert set(ed.get_parents(d)) == set([b, c])
   """
   if collection is None:
     collection = random_variables()
@@ -589,8 +585,7 @@ def get_siblings(x, collection=None):
   >>> a = Normal(mu=0.0, sigma=1.0)
   >>> b = Normal(mu=a, sigma=1.0)
   >>> c = Normal(mu=a, sigma=1.0)
-  >>> ed.get_siblings(b) == [c]
-  True
+  >>> assert ed.get_siblings(b) == [c]
   """
   parents = get_parents(x, collection)
   siblings = set()
@@ -622,8 +617,7 @@ def get_variables(x, collection=None):
   >>> a = tf.Variable(0.0)
   >>> b = tf.Variable(0.0)
   >>> c = Normal(mu=tf.mul(a, b), sigma=1.0)
-  >>> set(ed.get_variables(c)) == set([a, b])
-  True
+  >>> assert set(ed.get_variables(c)) == set([a, b])
   """
   if collection is None:
     collection = tf.global_variables()