Changed comments to docstrings where necessary in theano/gof/tests

theano/gof/tests/test_cmodule.py

-# We don't have real tests for the cache, but it would be great to make them!
-#
-# But this one tests a current behavior that isn't good: the c_code isn't
-# deterministic based on the input type and the op.
+"""
+We don't have real tests for the cache, but it would be great to make them!
+
+But this one tests a current behavior that isn't good: the c_code isn't
+deterministic based on the input type and the op.
+"""
 from __future__ import absolute_import, print_function, division
 
 import numpy as np

theano/gof/tests/test_compute_test_value.py

@@ -19,7 +19,9 @@ from theano.tensor.basic import _allclose
 
 # Used in TestComputeTestValue.test_no_perform
 class IncOneC(Op):
-    # An Op with only a C (c_code) implementation
+    """
+    An Op with only a C (c_code) implementation
+    """
     __props__ = ()
 
     def make_node(self, input):
@@ -332,7 +334,9 @@ class TestComputeTestValue(unittest.TestCase):
 
     def test_no_c_code(self):
         class IncOnePython(Op):
-            # An Op with only a Python (perform) implementation
+            """
+            An Op with only a Python (perform) implementation
+            """
             __props__ = ()
 
             def make_node(self, input):

theano/gof/tests/test_graph.py

@@ -256,20 +256,21 @@ class TestToposort:
 class TestIsSameGraph(unittest.TestCase):
 
     def check(self, expected, debug=True):
-        # Core function to perform comparison.
-        #
-        # :param expected: A list of tuples (v1, v2, ((g1, o1), ..., (gN, oN)))
-        # with:
-        #     - `v1` and `v2` two Variables (the graphs to be compared)
-        #     - `gj` a `givens` dictionary to give as input to `is_same_graph`
-        #     - `oj` the expected output of `is_same_graph(v1, v2, givens=gj)`
-        #
-        # :param debug: If True, then we make sure we are testing both
-        # implementations of `is_same_graph`.
-        #
-        # This function also tries to call `is_same_graph` by inverting `v1` and
-        # `v2`, and ensures the output remains the same.
+        """
+        Core function to perform comparison.
 
+        :param expected: A list of tuples (v1, v2, ((g1, o1), ..., (gN, oN)))
+        with:
+            - `v1` and `v2` two Variables (the graphs to be compared)
+            - `gj` a `givens` dictionary to give as input to `is_same_graph`
+            - `oj` the expected output of `is_same_graph(v1, v2, givens=gj)`
+
+        :param debug: If True, then we make sure we are testing both
+        implementations of `is_same_graph`.
+
+        This function also tries to call `is_same_graph` by inverting `v1` and
+        `v2`, and ensures the output remains the same.
+        """
         for v1, v2, go in expected:
             for gj, oj in go:
                 r1 = is_same_graph(v1, v2, givens=gj, debug=debug)

theano/gof/tests/test_op.py

@@ -71,8 +71,7 @@ MyOp = MyOp()
 
 
 class NoInputOp(Op):
-
-    # An Op to test the corner-case of an Op with no input.
+    """An Op to test the corner-case of an Op with no input."""
     __props__ = ()
 
     def make_node(self):
@@ -160,7 +159,7 @@ class TestMakeThunk(unittest.TestCase):
 
     def test_no_c_code(self):
         class IncOnePython(Op):
-            # An Op with only a Python (perform) implementation
+            """An Op with only a Python (perform) implementation"""
             __props__ = ()
 
             def make_node(self, input):
@@ -197,7 +196,7 @@ class TestMakeThunk(unittest.TestCase):
 
     def test_no_perform(self):
         class IncOneC(Op):
-            # An Op with only a C (c_code) implementation
+            """An Op with only a C (c_code) implementation"""
             __props__ = ()
 
             def make_node(self, input):
@@ -237,8 +236,7 @@ class TestMakeThunk(unittest.TestCase):
 
     def test_no_make_node(self):
         class DoubleOp(Op):
-            # An Op without make_node
-
+            """An Op without make_node"""
             __props__ = ()
 
             itypes = [T.dmatrix]