Added Count Op

theano/typed_list/basic.py

@@ -27,6 +27,9 @@ class _typed_list_py_operators:
     def reverse(self):
         return Reverse()(self)
 
+    def count(self, elem):
+        return Count()(self, elem)
+
     #name "index" is already used by an attribute
     def ind(self, elem):
         return Index()(self, elem)
@@ -274,3 +277,35 @@ class Index(Op):
 
     def __str__(self):
         return self.__class__.__name__
+
+
+class Count(Op):
+
+    def __eq__(self, other):
+        return type(self) == type(other)
+
+    def __hash__(self):
+        return hash(type(self))
+
+    def make_node(self, x, elem):
+        assert isinstance(x.type, TypedListType)
+        assert x.ttype == elem.type
+        return Apply(self, [x, elem], [T.scalar()])
+
+    def perform(self, node, (x, elem), (out, )):
+        """
+        inelegant workaround for ValueError: The truth value of an
+        array with more than one element is ambiguous. Use a.any() or a.all()
+        being thrown when trying to remove a matrix from a matrices list
+        """
+        if isinstance(elem, numpy.ndarray):
+            out[0] = 0
+            for y in range(x.__len__()):
+                if numpy.array_equal(x[y], elem):
+                    out[0] += 1
+            out[0] = numpy.asarray([out[0]])
+        else:
+            out[0] = numpy.asarray([x.count(elem)])
+
+    def __str__(self):
+        return self.__class__.__name__

theano/typed_list/tests/test_basic.py

@@ -9,7 +9,7 @@ from theano.tensor.type_other import SliceType
 from theano.typed_list.type import TypedListType
 from theano.typed_list.basic import (GetItem, Insert,
                                       Append, Extend, Remove, Reverse,
-                                      Index)
+                                      Index, Count)
 from theano.tests import unittest_tools as utt
 
 
@@ -396,7 +396,7 @@ class test_index(unittest.TestCase):
         mySymbolicMatricesList = TypedListType(T.TensorType(
                                 theano.config.floatX, (False, False)))()
 
-        z = mySymbolicNestedMatricesList.ind(mySymbolicMatricesList)
+        z = Index()(mySymbolicNestedMatricesList, mySymbolicMatricesList)
 
         f = theano.function([mySymbolicNestedMatricesList,
                              mySymbolicMatricesList], z)
@@ -406,3 +406,53 @@ class test_index(unittest.TestCase):
         y = rand_ranged_matrix(-1000, 1000, [100, 101])
 
         self.assertTrue(f([[x, y], [x, y, y]], [x, y]) == 0)
+
+
+class test_count(unittest.TestCase):
+
+    def test_sanity_check(self):
+        mySymbolicMatricesList = TypedListType(T.TensorType(
+                                theano.config.floatX, (False, False)))()
+        myMatrix = T.matrix()
+
+        z = Count()(mySymbolicMatricesList, myMatrix)
+
+        f = theano.function([mySymbolicMatricesList, myMatrix], z)
+
+        x = rand_ranged_matrix(-1000, 1000, [100, 101])
+
+        y = rand_ranged_matrix(-1000, 1000, [100, 101])
+
+        self.assertTrue(f([y, y, x, y], y) == 3)
+
+    def test_interface(self):
+        mySymbolicMatricesList = TypedListType(T.TensorType(
+                                theano.config.floatX, (False, False)))()
+        myMatrix = T.matrix()
+
+        z = mySymbolicMatricesList.count(myMatrix)
+
+        f = theano.function([mySymbolicMatricesList, myMatrix], z)
+
+        x = rand_ranged_matrix(-1000, 1000, [100, 101])
+
+        y = rand_ranged_matrix(-1000, 1000, [100, 101])
+
+        self.assertTrue(f([x, y], y) == 1)
+
+    def test_non_tensor_type(self):
+        mySymbolicNestedMatricesList = TypedListType(T.TensorType(
+                                theano.config.floatX, (False, False)), 1)()
+        mySymbolicMatricesList = TypedListType(T.TensorType(
+                                theano.config.floatX, (False, False)))()
+
+        z = Count()(mySymbolicNestedMatricesList, mySymbolicMatricesList)
+
+        f = theano.function([mySymbolicNestedMatricesList,
+                             mySymbolicMatricesList], z)
+
+        x = rand_ranged_matrix(-1000, 1000, [100, 101])
+
+        y = rand_ranged_matrix(-1000, 1000, [100, 101])
+
+        self.assertTrue(f([[x, y], [x, y, y]], [x, y]) == 1)