Merge pull request #303 from nouiz/test_sigm_opt

theano/tensor/nnet/tests/test_sigm.py

@@ -16,14 +16,18 @@ from theano.tensor.nnet.sigm import (
 class T_sigmoid(unittest.TestCase):
     def setUp(self):
         utt.seed_rng()
+
     def test_elemwise(self):
-        utt.verify_grad(sigmoid, [numpy.random.rand(3,4)])
+        utt.verify_grad(sigmoid, [numpy.random.rand(3, 4)])
+
 
 class T_softplus(unittest.TestCase):
     def setUp(self):
         utt.seed_rng()
+
     def test_elemwise(self):
-        utt.verify_grad(softplus, [numpy.random.rand(3,4)])
+        utt.verify_grad(softplus, [numpy.random.rand(3, 4)])
+
 
 class T_sigmoid_opts(unittest.TestCase):
 
@@ -50,31 +54,89 @@ class T_sigmoid_opts(unittest.TestCase):
     def test_exp_over_1_plus_exp(self):
         m = self.get_mode(excluding=['local_elemwise_fusion'])
 
-        x = T.dvector()
+        x = T.vector()
+        data = numpy.random.rand(54).astype(config.floatX)
 
         # tests exp_over_1_plus_exp
-        f = theano.function([x], T.exp(x)/(1+T.exp(x)), mode=m)
-        theano.printing.debugprint(f)
+        f = theano.function([x], T.exp(x) / (1 + T.exp(x)), mode=m)
         assert [node.op for node in f.maker.env.toposort()] == [sigmoid]
+        f(data)
+        f = theano.function([x], T.exp(x) / (2 + T.exp(x)), mode=m)
+        assert [node.op for node in f.maker.env.toposort()] != [sigmoid]
+        f(data)
+        f = theano.function([x], T.exp(x) / (1 - T.exp(x)), mode=m)
+        assert [node.op for node in f.maker.env.toposort()] != [sigmoid]
+        f(data)
+        f = theano.function([x], T.exp(x + 1) / (1 + T.exp(x)), mode=m)
+        assert [node.op for node in f.maker.env.toposort()] != [sigmoid]
+        f(data)
 
         # tests inv_1_plus_exp
-        f = theano.function([x], T.fill(x,1.0) / (1+T.exp(-x)), mode=m)
-        theano.printing.debugprint(f)
+        f = theano.function([x], T.fill(x, 1.0) / (1 + T.exp(-x)), mode=m)
         assert [node.op for node in f.maker.env.toposort()] == [sigmoid]
+        f(data)
+        f = theano.function([x], T.fill(x, 1.0) / (2 + T.exp(-x)), mode=m)
+        assert [node.op for node in f.maker.env.toposort()] != [sigmoid]
+        f(data)
+        f = theano.function([x], T.fill(x, 1.0) / (1 - T.exp(-x)), mode=m)
+        assert [node.op for node in f.maker.env.toposort()] != [sigmoid]
+        f(data)
+        f = theano.function([x], T.fill(x, 1.1) / (1 + T.exp(-x)), mode=m)
+        assert [node.op for node in f.maker.env.toposort()] != [sigmoid]
+        f(data)
 
         # tests inv_1_plus_exp with neg
-        f = theano.function([x], T.fill(x,-1.0) / (1+T.exp(-x)), mode=m)
+        f = theano.function([x], T.fill(x, -1.0) / (1 + T.exp(-x)), mode=m)
         assert [node.op for node in f.maker.env.toposort()] == [sigmoid,
                 theano.tensor.inplace.neg_inplace]
+        f(data)
+        f = theano.function([x], T.fill(x, -1.0) / (1 - T.exp(-x)), mode=m)
+        assert [node.op for node in f.maker.env.toposort()] != [sigmoid,
+                theano.tensor.inplace.neg_inplace]
+        f(data)
+        f = theano.function([x], T.fill(x, -1.0) / (2 + T.exp(-x)), mode=m)
+        assert [node.op for node in f.maker.env.toposort()] != [sigmoid,
+                theano.tensor.inplace.neg_inplace]
+        f(data)
+        f = theano.function([x], T.fill(x, -1.1) / (1 + T.exp(-x)), mode=m)
+        assert [node.op for node in f.maker.env.toposort()] != [sigmoid,
+                theano.tensor.inplace.neg_inplace]
+        f(data)
 
         # tests double inv_1_plus_exp with neg
         # (-1)(exp(x)) / (1+exp(x))(1+exp(-x))
         # = (-1)/(1+exp(-x)) * exp(x)/(1+exp(x))
         # = - (sigm(x) * sigm(x))
-        f = theano.function([x], (T.fill(x,-1.0)*T.exp(x)) / ((1+T.exp(x))*(1+T.exp(-x))), mode=m)
-        theano.printing.debugprint(f)
+        f = theano.function([x], (T.fill(x, -1.0) * T.exp(x)) /
+                            ((1 + T.exp(x)) * (1 + T.exp(-x))), mode=m)
         assert [node.op for node in f.maker.env.toposort()] == [sigmoid,
                 T.mul, theano.tensor.inplace.neg_inplace]
+        f(data)
+        f = theano.function([x], (T.fill(x, -1.1) * T.exp(x)) /
+                            ((1 + T.exp(x)) * (1 + T.exp(-x))), mode=m)
+        assert [node.op for node in f.maker.env.toposort()] != [sigmoid,
+                T.mul, theano.tensor.inplace.neg_inplace]
+        f(data)
+        f = theano.function([x], (T.fill(x, -1.0) * T.exp(x)) /
+                            ((2 + T.exp(x)) * (1 + T.exp(-x))), mode=m)
+        assert [node.op for node in f.maker.env.toposort()] != [sigmoid,
+                T.mul, theano.tensor.inplace.neg_inplace]
+        f(data)
+        f = theano.function([x], (T.fill(x, -1.0) * T.exp(x)) /
+                            ((1 + T.exp(x)) * (2 + T.exp(-x))), mode=m)
+        assert [node.op for node in f.maker.env.toposort()] != [sigmoid,
+                T.mul, theano.tensor.inplace.neg_inplace]
+        f(data)
+        f = theano.function([x], (T.fill(x, -1.0) * T.exp(x)) /
+                            ((1 + T.exp(x)) * (1 + T.exp(x))), mode=m)
+        assert [node.op for node in f.maker.env.toposort()] != [sigmoid,
+                T.mul, theano.tensor.inplace.neg_inplace]
+        f(data)
+        f = theano.function([x], (T.fill(x, -1.0) * T.exp(x)) /
+                            ((1 + T.exp(x)) * (2 + T.exp(-x))), mode=m)
+        assert [node.op for node in f.maker.env.toposort()] != [sigmoid,
+                T.mul, theano.tensor.inplace.neg_inplace]
+        f(data)
 
     def test_1msigmoid(self):
         if not register_local_1msigmoid:
@@ -84,13 +146,12 @@ class T_sigmoid_opts(unittest.TestCase):
         x = T.fmatrix()
 
         # tests exp_over_1_plus_exp
-        f = theano.function([x], 1 - T.exp(x)/(1+T.exp(x)), mode=m)
-        theano.printing.debugprint(f)
-        assert [node.op for node in f.maker.env.toposort()] == [tensor.neg, sigmoid_inplace]
+        f = theano.function([x], 1 - T.exp(x) / (1 + T.exp(x)), mode=m)
+        assert [node.op for node in f.maker.env.toposort()] == [
+            tensor.neg, sigmoid_inplace]
 
         # tests inv_1_plus_exp
-        f = theano.function([x], 1 - T.fill(x,1.0) / (1+T.exp(-x)), mode=m)
-        theano.printing.debugprint(f)
+        f = theano.function([x], 1 - T.fill(x, 1.0) / (1 + T.exp(-x)), mode=m)
         assert [node.op for node in f.maker.env.toposort()] == [tensor.neg,
                 sigmoid_inplace]
 
@@ -107,23 +168,19 @@ class T_sigmoid_opts(unittest.TestCase):
         x, y = tensor.vectors('x', 'y')
 
         f = theano.function([x], sigmoid(-x) * tensor.exp(x), mode=m)
-        theano.printing.debugprint(f)
         match(f, [sigmoid])
 
         f = theano.function([x], sigmoid(x) * tensor.exp(-x), mode=m)
-        theano.printing.debugprint(f)
         match(f, [tensor.neg, sigmoid])
 
         f = theano.function([x], -(-(-(sigmoid(x)))) * tensor.exp(-x), mode=m)
-        theano.printing.debugprint(f)
         match(f, [tensor.neg, sigmoid, tensor.neg])
 
         f = theano.function(
                 [x, y],
-                (sigmoid(x) * sigmoid(-y) * -tensor.exp(-x) * tensor.exp(x * y) *
-                 tensor.exp(y)),
+                (sigmoid(x) * sigmoid(-y) * -tensor.exp(-x) *
+                 tensor.exp(x * y) * tensor.exp(y)),
                 mode=m)
-        theano.printing.debugprint(f)
         match(f, [sigmoid, tensor.mul, tensor.neg, tensor.exp, sigmoid,
                   tensor.mul, tensor.neg])
 
@@ -136,6 +193,7 @@ class T_sigmoid_opts(unittest.TestCase):
         """
         x, y, z, t = tensor.vectors('x', 'y', 'z', 't')
         exp = tensor.exp
+
         def ok(expr1, expr2):
             trees = [parse_mul_tree(e) for e in (expr1, expr2)]
             perform_sigm_times_exp(trees[0])
@@ -170,32 +228,36 @@ class T_sigmoid_opts(unittest.TestCase):
 class T_softplus_opts(unittest.TestCase):
     def setUp(self):
         if theano.config.mode == 'FAST_COMPILE':
-            m = theano.compile.mode.get_mode('FAST_RUN').excluding('local_elemwise_fusion')
+            m = theano.compile.mode.get_mode('FAST_RUN').excluding(
+                'local_elemwise_fusion')
         else:
-            m = theano.compile.mode.get_default_mode().excluding('local_elemwise_fusion')
+            m = theano.compile.mode.get_default_mode().excluding(
+                'local_elemwise_fusion')
         self.m = m
         utt.seed_rng()
+
     def test_logsigm_to_softplus(self):
         x = T.vector()
 
         out = T.log(sigmoid(x))
-        f = theano.function([x],out,mode=self.m)
+        f = theano.function([x], out, mode=self.m)
         topo = f.maker.env.toposort()
-        print topo
-        assert len(topo)==3
+        assert len(topo) == 3
         assert isinstance(topo[0].op.scalar_op, theano.scalar.Neg)
-        assert isinstance(topo[1].op.scalar_op, theano.tensor.nnet.sigm.ScalarSoftplus)
+        assert isinstance(topo[1].op.scalar_op,
+                          theano.tensor.nnet.sigm.ScalarSoftplus)
         assert isinstance(topo[2].op.scalar_op, theano.scalar.Neg)
         f(numpy.random.rand(54).astype(config.floatX))
 
     def test_log1msigm_to_softplus(self):
         x = T.vector()
 
-        out = T.log(1-sigmoid(x))
-        f = theano.function([x],out,mode=self.m)
+        out = T.log(1 - sigmoid(x))
+        f = theano.function([x], out, mode=self.m)
         topo = f.maker.env.toposort()
-        assert len(topo)==2
-        assert isinstance(topo[0].op.scalar_op, theano.tensor.nnet.sigm.ScalarSoftplus)
+        assert len(topo) == 2
+        assert isinstance(topo[0].op.scalar_op,
+                          theano.tensor.nnet.sigm.ScalarSoftplus)
         assert isinstance(topo[1].op.scalar_op, theano.scalar.Neg)
         f(numpy.random.rand(54).astype(config.floatX))
 
@@ -206,11 +268,12 @@ class T_softplus_opts(unittest.TestCase):
 
         x = T.vector()
 
-        out = T.log(1+T.exp(x))
-        f = theano.function([x],out,mode=self.m)
+        out = T.log(1 + T.exp(x))
+        f = theano.function([x], out, mode=self.m)
         topo = f.maker.env.toposort()
-        assert len(topo)==1
-        assert isinstance(topo[0].op.scalar_op,theano.tensor.nnet.sigm.ScalarSoftplus)
+        assert len(topo) == 1
+        assert isinstance(topo[0].op.scalar_op,
+                          theano.tensor.nnet.sigm.ScalarSoftplus)
         f(numpy.random.rand(54).astype(config.floatX))