Added log1p Op

theano/scalar/basic.py

@@ -1178,6 +1178,18 @@ class Log10(UnaryScalarOp):
         return "%(z)s = log10(%(x)s);" % locals()
 log10 = Log10(upgrade_to_float, name = 'log10')
 
+class Log1p(UnaryScalarOp):
+    """ log(1+x) """
+    def impl(self, x):
+        return numpy.log1p(x)
+    def grad(self, (x,), (gz,)):
+        return [gz / (1+x)]
+    def c_code(self, node, name, (x, ), (z, ), sub):
+        if node.inputs[0].type in complex_types:
+            raise NotImplementedError('type not supported', type)
+        return "%(z)s = log1p(%(x)s);" % locals()
+log1p = Log1p(upgrade_to_float, name = 'log1p')
+
 class Exp(UnaryScalarOp):
     def impl(self, x):
         return numpy.exp(x)

theano/tensor/basic.py

@@ -1437,6 +1437,10 @@ def log2(a):
 def log10(a):
     """base 10 logarithm of a"""
 
+@_scal_elemwise
+def log1p(a):
+    """log(1+a)"""
+
 @_scal_elemwise
 def sgn(a):
     """sign of a"""

theano/tensor/inplace.py

@@ -100,6 +100,10 @@ def inv_inplace(a):
 def log_inplace(a):
     """base e logarithm of a (inplace on a)"""
 
+@_scal_inplace
+def log1p_inplace(a):
+    """log(1+a)"""
+
 @_scal_inplace
 def log2_inplace(a):
     """base 2 logarithm of a (inplace on a)"""

theano/tensor/tests/test_basic.py

@@ -444,6 +444,17 @@ Log10InplaceTester = makeBroadcastTester(op = inplace.log10_inplace,
                                           grad = _grad_broadcast_unary_positive,
                                           inplace = True)
 
+Log1pTester = makeBroadcastTester(op = log1p,
+                                  expected = numpy.log1p,
+                                  good = _good_broadcast_unary_positive,
+                                  grad = _grad_broadcast_unary_positive)
+Log1pInplaceTester = makeBroadcastTester(op = inplace.log1p_inplace,
+                                         expected = numpy.log1p,
+                                         good = _good_broadcast_unary_positive,
+                                         grad = _grad_broadcast_unary_positive,
+                                         inplace = True)
+
+
 SqrtTester = makeBroadcastTester(op = sqrt,
                                    expected = numpy.sqrt,
                                    good = _good_broadcast_unary_positive,
@@ -1088,9 +1099,7 @@ class test_bitwise(unittest.TestCase):
         self.failUnless(numpy.all(v == (~l)), (l, r, v))
 
 
-
 class T_add(unittest.TestCase):
-
     def setUp(self):
         utt.seed_rng()
 
@@ -1118,7 +1127,6 @@ class T_add(unittest.TestCase):
         utt.verify_grad(add, [numpy.random.rand(3, 5), numpy.random.rand(3, 1)])
 
 class T_exp(unittest.TestCase):
-
     def test_grad_0(self):
         utt.verify_grad(exp, [
             numpy.asarray([[ 1.5089518 ,  1.48439076, -4.7820262 ],