backport to python2.4

theano/compile/sandbox/shared_randomstreams.py

@@ -4,8 +4,8 @@ __docformat__ = "restructuredtext en"
 import sys
 import numpy
 
-from ...gof import Container
-from ...tensor import raw_random
+from theano.gof import Container
+from theano.tensor import raw_random
 
 from sharedvalue import SharedVariable, shared_constructor, shared
 
@@ -64,7 +64,9 @@ class RandomStreams(object):
 
         :rtype: None
         """
-        seed = self.default_instance_seed if seed is None else seed
+        if seed is None:
+            seed = self.default_instance_seed
+
         seedgen = numpy.random.RandomState(seed)
         for old_r, new_r in self.random_state_variables:
             old_r_seed = seedgen.randint(2**30)

theano/compile/sandbox/tests/test_pfunc.py

@@ -141,13 +141,13 @@ class Test_pfunc(unittest.TestCase):
         # by default, shared are not mutable unless doing an explicit update
         f = pfunc([], [b_out], mode='FAST_RUN')
         assert (f() ==  numpy.arange(5) * 2).all()
-        assert all( b.value == numpy.arange(5))
+        assert numpy.all( b.value == numpy.arange(5))
 
         # using updates, b is now a mutable parameter
         f = pfunc([], [b_out], updates=[(b, b_out)], mode='FAST_RUN')
         assert (f() == numpy.arange(5)*2 ).all()
-        assert all( b.value == numpy.arange(5)*2) # because of the update
-        assert all( bval == numpy.arange(5)*2) # because of mutable=True
+        assert ( b.value == numpy.arange(5)*2).all() # because of the update
+        assert ( bval == numpy.arange(5)*2).all() # because of mutable=True
 
         # do not depend on updates being in-place though!
         bval = numpy.arange(5)
@@ -156,7 +156,7 @@ class Test_pfunc(unittest.TestCase):
         assert ( f() == numpy.arange(5)*2 ).all()
         assert (b.value == ((numpy.arange(5)*2)+3)).all() # because of the update
         # bval got modified to something...
-        assert not all(bval == numpy.arange(5))
+        assert not (bval == numpy.arange(5)).all()
         # ... but not to b.value !
         assert not (bval == b.value).all()
 

theano/compile/tests/test_debugmode.py

@@ -36,7 +36,10 @@ class BROKEN_ON_PURPOSE_StructuredDotCSC(gof.Op):
                 copy = False)
 #       TODO: todense() is automatic in 0.7.0, just remove the following line:
         z = a * b
-        out[0] = z+0.5 if self.py_offset else z #ERROR TO ADD THIS CRAPPY OFFSET
+        #ERROR TO ADD THIS CRAPPY OFFSET
+        if self.py_offset:
+            out[0] = z+0.5
+        else: out[0] = z 
 
     def c_code(self, node, name, (a_val, a_ind, a_ptr, a_nrows, b), (z,), sub):
         return """

theano/compile/tests/test_inplace_opt_for_value.py

@@ -42,7 +42,10 @@ class StochasticGradientDescent(module.FancyModule):
             raise ValueError('stepsize must be a scalar', stepsize)
 
         self.params = params
-        self.gparams = T.grad(cost, self.params) if gradients is None else gradients
+        if gradients is None:
+            self.gparams = T.grad(cost, self.params)
+        else:
+            self.gparams = gradients
 
         self.updates = dict((p, p - self.stepsize * g) for p, g in zip(self.params, self.gparams))
 

theano/compile/tests/test_module.py

@@ -695,6 +695,12 @@ def test_method_implicit_ticket_384():
         if not str(e).startswith('Tried to provide value for implicit input'):
             raise
 
+def get_mode():
+    if default_mode != 'DEBUG_MODE':
+        mode = default_mode
+    else: mode = 'FAST_RUN'
+    return mode
+
 def test_pickle():
     """Test that a module can be pickled"""
     M = Module()
@@ -704,7 +710,7 @@ def test_pickle():
     M.f = Method([a], a + M.x + M.y)
     M.g = Method([a], a * M.x * M.y)
 
-    mode = default_mode if default_mode != 'DEBUG_MODE' else 'FAST_RUN'
+    mode = get_mode()
     m = M.make(x=numpy.zeros((4,5)), y=numpy.ones((2,3)), mode=mode)
 
     m_dup = cPickle.loads(cPickle.dumps(m))
@@ -729,7 +735,7 @@ def test_pickle_aliased_memory():
     M.f = Method([a], a + M.x + M.y)
     M.g = Method([a], a * M.x * M.y)
 
-    mode = default_mode if default_mode != 'DEBUG_MODE' else 'FAST_RUN'
+    mode = get_mode()
     m = M.make(x=numpy.zeros((4,5)), y=numpy.ones((2,3)), mode=mode)
     m.y = m.x[:]
 

theano/gof/tests/test_opt.py

@@ -57,7 +57,10 @@ class MyOp(Op):
 
     def __hash__(self):
         #return hash(self.x if self.x is not None else id(self)) ^ hash(self.name)
-        return hash(self.x if self.x is not None else id(self)) 
+        if self.x is not None:
+            return hash(self.x)
+        else:
+            return id(self)
 
 
 op1 = MyOp('Op1')