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

theano/scan_module/tests/test_scan.py

@@ -55,16 +55,18 @@ type_eps = {'float64': 1e-7,
 
 
 class multiple_outputs_numeric_grad:
-    # WRITEME
+    """WRITEME"""
     def __init__(self, f, pt, ndarray_mask=None, eps=None):
-        # Return the gradient of f at pt.
-        #
-        # This function computes the gradient by a one-sided finite differences
-        # of a fixed step size (eps).
-        #
-        # It is assumed that f(...) will return a scalar.
-        # :param eps: the stepsize for the finite differencing. None means
-        # input dtype-dependent. See `type_eps`.
+        """
+        Return the gradient of f at pt.
+
+        This function computes the gradient by a one-sided finite differences
+        of a fixed step size (eps).
+
+        It is assumed that f(...) will return a scalar.
+        :param eps: the stepsize for the finite differencing. None means
+        input dtype-dependent. See `type_eps`.
+        """
 
         def prod(inputs):
             rval = 1
@@ -123,13 +125,15 @@ class multiple_outputs_numeric_grad:
 
     @staticmethod
     def abs_rel_err(a, b, eps=1.0e-10):
-        # Return a small number when a and b are close, relative to how big
-        # they are
+        """
+        Return a small number when a and b are close, relative to how big they are
+        """
         return abs(a - b) / (abs(a) + abs(b) + eps)
 
     def max_err(self, _g_pt):
-        # Return the biggest relative error between g_pt and self.gx
-
+        """
+        Return the biggest relative error between g_pt and self.gx
+        """
         g_pt = []
         for i in xrange(len(_g_pt)):
             if self.ndarray_mask[i]:
@@ -4527,19 +4531,18 @@ class T_Scan(unittest.TestCase):
 
 
 class ScanGpuTests:
-    # This class defines a number of tests for Scan on GPU as well as a few
-    # helper functions for these tests. The GPU tests defined in this class are
-    # independant of the GPU backend used. Because of this, a class inheriting
-    # from ScanGpuTests should define the following attributes and methods to
-    # make the tests run on a specific backend :
-    # - self.gpu_backend : Reference to the backend module
-    # - self.mode_with_opt : Compilation mode to force usage of the gpu backend
-    # - self.is_scan_on_gpu(node) : Method to determine is a scan node has been
-    #                               moved to run on a gpu under the specific
-    #                               backend. Returns a boolean.
-
-    # as test_one_sequence_one_output_weights, but on the gpu
-    # This first version test the first case in the optimizer to the gpu.
+    """
+    This class defines a number of tests for Scan on GPU as well as a few
+    helper functions for these tests. The GPU tests defined in this class are
+    independant of the GPU backend used. Because of this, a class inheriting
+    from ScanGpuTests should define the following attributes and methods to
+    make the tests run on a specific backend :
+    - self.gpu_backend : Reference to the backend module
+    - self.mode_with_opt : Compilation mode to force usage of the gpu backend
+    - self.is_scan_on_gpu(node) : Method to determine is a scan node has been
+                                  moved to run on a gpu under the specific
+                                  backend. Returns a boolean.
+    """
     def test_one_sequence_one_output_weights_gpu1(self):
 
         def f_rnn(u_t, x_tm1, W_in, W):
@@ -4869,8 +4872,10 @@ class ScanGpuTests:
 
 
 class T_Scan_Gpuarray(unittest.TestCase, ScanGpuTests):
-    # This class takes the gpu tests for scan that are defined in
-    # class ScanGpuTests and runs them using the gpuarray backend.
+    """
+    This class takes the gpu tests for scan that are defined in
+    class ScanGpuTests and runs them using the gpuarray backend.
+    """
 
     def __init__(self, *args, **kwargs):
         from theano import gpuarray

theano/scan_module/tests/test_scan_opt.py

@@ -12,9 +12,11 @@ mode = theano.compile.mode.get_mode(config.mode)
 
 
 class TestGaussNewton(unittest.TestCase):
-    # Regression test for code exhibiting various optimization errors.
-    # This test case is based on code by Sigurd Spieckermann.
+    """
+    Regression test for code exhibiting various optimization errors.
 
+    This test case is based on code by Sigurd Spieckermann.
+    """
     def setUp(self):
         self.rng = np.random.RandomState(utt.fetch_seed())
 
@@ -134,10 +136,12 @@ class GaussNewtonMatrix(object):
 
 
 class TestPushOutScanOutputDot(object):
-    # Test class for the PushOutScanOutput optimizer in the case where the inner
-    # function of a scan op has an output which is the result of a Dot product
-    # on a non-sequence matrix input to scan and a vector that is the result of
-    # computation in the inner function.
+    """
+    Test class for the PushOutScanOutput optimizer in the case where the inner
+    function of a scan op has an output which is the result of a Dot product
+    on a non-sequence matrix input to scan and a vector that is the result of
+    computation in the inner function.
+    """
 
     def test_dot_not_output(self):
         # Test the case where the vector input to the dot is not already an
@@ -264,9 +268,11 @@ class TestPushOutScanOutputDot(object):
 
 
 class TestPushOutSumOfDot():
-    # Test case for the PushOutScanOutput optimizer in the case where the scan
-    # is used to compute the sum over the dot products between the corresponding
-    # elements of two list of matrices.
+    """
+    Test case for the PushOutScanOutput optimizer in the case where the scan
+    is used to compute the sum over the dot products between the corresponding
+    elements of two list of matrices.
+    """
 
     def test_machine_translation(self):
         # This test case comes from https://github.com/rizar/scan-grad-speed and