Another whitespace cleanup.

theano/compile/tests/test_debugmode.py

@@ -36,7 +36,7 @@ class BROKEN_ON_PURPOSE_Add(gof.Op):
         #ERROR TO ADD THIS CRAPPY OFFSET
         if self.py_offset:
             out[0] = z+0.5
-        else: out[0] = z 
+        else: out[0] = z
 
     def c_code(self, node, name, (a, b), (z,), sub):
         return """
@@ -75,7 +75,7 @@ class BROKEN_ON_PURPOSE_Add(gof.Op):
 # inconsistent is a invalid op, whose perform and c_code do not match
 inconsistent = BROKEN_ON_PURPOSE_Add(False)
 # off_by_half is a good op, that is different from theano.sparse.sd_csc
-off_by_half = BROKEN_ON_PURPOSE_Add(True) 
+off_by_half = BROKEN_ON_PURPOSE_Add(True)
 
 class WeirdBrokenOp(gof.Op):
     """
@@ -172,11 +172,11 @@ def test_badclinkeroutput():
     a = theano.tensor.dvector()
     b = theano.tensor.dvector()
 
-    f_good = theano.function([a, b], 
-            off_by_half(a, b), 
+    f_good = theano.function([a, b],
+            off_by_half(a, b),
             mode=debugmode.DebugMode(check_c_code=True))
-    f_inconsistent = theano.function([a,b], 
-            inconsistent(a, b), 
+    f_inconsistent = theano.function([a,b],
+            inconsistent(a, b),
             mode=debugmode.DebugMode(check_c_code=True))
 
     #this should evaluate with no error
@@ -189,7 +189,7 @@ def test_badclinkeroutput():
         return #TEST PASS
 
     assert False  #an error should have been detected
-        
+
 
 def test_badoptimization():
     @gof.local_optimizer([theano.tensor.add])
@@ -204,7 +204,7 @@ def test_badoptimization():
     a = theano.tensor.dvector()
     b = theano.tensor.dvector()
 
-    f = theano.function([a, b], a+b, 
+    f = theano.function([a, b], a+b,
             mode=debugmode.DebugMode(optimizer=opt, check_c_code=True))
 
     try:
@@ -235,8 +235,8 @@ def test_stochasticoptimization():
     b = theano.tensor.dvector()
 
     try:
-        f = theano.function([a, b], 
-                theano.tensor.add(a, b), 
+        f = theano.function([a, b],
+                theano.tensor.add(a, b),
                 mode=debugmode.DebugMode(optimizer=opt, check_c_code=True))
     except debugmode.StochasticOrder:
         return #TEST PASS

theano/compile/tests/test_inplace_opt_for_value.py

@@ -73,7 +73,7 @@ class TanhRnn(Op):
     This class implements the recurrent part of a recurrent neural network.
 
     There is not a neat way to include this in a more fine-grained way in Theano at the moment,
-    so to get something working, I'm implementing a relatively complicated Op that could be 
+    so to get something working, I'm implementing a relatively complicated Op that could be
     broken down later into constituents.
 
     Anyway, this Op implements recursive computation of the form:
@@ -81,7 +81,7 @@ class TanhRnn(Op):
     .. latex-eqn:
         z_t &= \tanh( z_{t-1} A + x_{t-1})
 
-    For z0 a vector, and x a TxM matrix, it returns a matrix z of shape (T+1, M), 
+    For z0 a vector, and x a TxM matrix, it returns a matrix z of shape (T+1, M),
     in which z[0] = z0.
 
     """
@@ -275,7 +275,7 @@ def test_WEIRD_STUFF():
     print rnn1.minimizer.step.maker.inputs
     print rnn2.minimizer.step.maker.inputs
 
-    
+
 
 #    for i in range(1,len(rnn1.minimizer.step.maker.inputs)):
 #        print "valid update:",theano.printing.pp(rnn1.minimizer.step.maker.inputs[i].update),
@@ -284,7 +284,7 @@ def test_WEIRD_STUFF():
 #        print rnn2.minimizer.step.maker.inputs[i].update.name
 #    print dir(rnn1.minimizer.step.maker.inputs[5].update)
 #    print dir(rnn2.minimizer.step.maker.inputs[5].update)
-    
+
 
 
     niter=3

theano/gof/tests/test_cc.py

@@ -24,7 +24,7 @@ class TDouble(Type):
         return """
         %(name)s = 0;
         %(name)s_bad_thing = malloc(100000);
-        //printf("Initializing %(name)s\\n"); 
+        //printf("Initializing %(name)s\\n");
         """ % locals()
 
     def c_literal(self, data):
@@ -40,7 +40,7 @@ class TDouble(Type):
         %(name)s_bad_thing = NULL;
         //printf("Extracting %(name)s\\n");
         """ % dict(locals(), **sub)
-    
+
     def c_sync(self, name, sub):
         return """
         Py_XDECREF(py_%(name)s);
@@ -71,7 +71,7 @@ class MyOp(Op):
     def __init__(self, nin, name):
         self.nin = nin
         self.name = name
-    
+
     def make_node(self, *inputs):
         assert len(inputs) == self.nin
         inputs = map(as_variable, inputs)
@@ -98,28 +98,28 @@ class Binary(MyOp):
     def __init__(self):
         MyOp.__init__(self, 2, self.__class__.__name__)
 
-        
+
 class Add(Binary):
     def c_code(self, node, name, (x, y), (z, ), sub):
         return "%(z)s = %(x)s + %(y)s;" % locals()
     def impl(self, x, y):
         return x + y
 add = Add()
-        
+
 class Sub(Binary):
     def c_code(self, node, name, (x, y), (z, ), sub):
         return "%(z)s = %(x)s - %(y)s;" % locals()
     def impl(self, x, y):
         return -10 # erroneous (most of the time)
 sub = Sub()
-        
+
 class Mul(Binary):
     def c_code(self, node, name, (x, y), (z, ), sub):
         return "%(z)s = %(x)s * %(y)s;" % locals()
     def impl(self, x, y):
         return x * y
 mul = Mul()
-        
+
 class Div(Binary):
     def c_code(self, node, name, (x, y), (z, ), sub):
         return "%(z)s = %(x)s / %(y)s;" % locals()
@@ -185,7 +185,7 @@ def test_clinker_dups_inner():
     lnk = CLinker().accept(Env([x, y, z], [e]))
     fn = lnk.make_function()
     assert fn(1.0, 2.0, 3.0) == 8.0
-    
+
 
 
 ######################
@@ -254,7 +254,7 @@ def test_duallinker_mismatch():
 ################################
 # Test that failure code works #
 ################################
-        
+
 class AddFail(Binary):
     def c_code(self, node, name, (x, y), (z, ), sub):
         fail=sub['fail']

theano/gof/tests/test_link.py

@@ -32,7 +32,7 @@ class MyOp(Op):
         self.name = name
         if impl:
             self.impl = impl
-    
+
     def make_node(self, *inputs):
         assert len(inputs) == self.nin
         inputs = map(as_variable, inputs)
@@ -85,7 +85,7 @@ class TestPerformLinker:
         i[1].data = 2
         fn()
         assert o[0].data == 1.5
-        
+
     def test_function(self):
         x, y, z = inputs()
         e = mul(add(x, y), div(x, y))
@@ -130,7 +130,7 @@ class TestWrapLinker:
         nodes = []
         def wrap(i, node, th):
             nodes.append(node.op)
-            
+
         x, y, z = inputs()
         e = mul(add(x, y), div(x, y))
         fn, i, o = wrap_linker(Env([x, y, z], [e]), [PerformLinker(allow_gc=False)], wrap).make_thunk()
@@ -154,8 +154,8 @@ class TestWrapLinker:
         fn()
         assert nodes == [div, add, mul]
         assert o[0].data == 1.5
-        
 
 
 
-        
+
+

theano/tests/test_gradient.py

@@ -15,7 +15,7 @@ def _grad_sources_inputs(*args):
     return grad_sources_inputs(warn_type=False, *args)
 
 class test_grad_sources_inputs(unittest.TestCase):
-    def test_retNone1(self): 
+    def test_retNone1(self):
         """Test that it is not ok to return None from op.grad()"""
         class retNone(gof.op.Op):
             def make_node(self):
@@ -31,7 +31,7 @@ class test_grad_sources_inputs(unittest.TestCase):
             self.failUnless(e[0] is gradient._msg_retType)
             return
         self.fail()
-    def test_retNone1_b(self): 
+    def test_retNone1_b(self):
         """Test that it is ok to return [None] from op.grad()"""
         class retNone(gof.op.Op):
             def make_node(self, *inputs):
@@ -44,7 +44,7 @@ class test_grad_sources_inputs(unittest.TestCase):
         g = _grad_sources_inputs([(a.out, 1)], None)
         self.failUnless(not i in g)
 
-    def test_wrong_rval_len1(self): 
+    def test_wrong_rval_len1(self):
         """Test that it is not ok to return the wrong number of gradients"""
         class retNone(gof.op.Op):
             def make_node(self, *inputs):