Add a_tensor.squeeze() interface as numpy

theano/tensor/tests/test_extra_ops.py

@@ -286,6 +286,20 @@ class SqueezeTester(utt.InferShapeTester):
 
             utt.verify_grad(self.op, [data])
 
+    def test_var_interface(self):
+        # same as test_op, but use a_theano_var.squeeze.
+        for shape, broadcast in zip(self.shape_list, self.broadcast_list):
+            data = numpy.random.random(size=shape).astype(theano.config.floatX)
+            variable = tensor.TensorType(theano.config.floatX, broadcast)()
+
+            f = theano.function([variable], variable.squeeze())
+
+            expected = numpy.squeeze(data)
+            tested = f(data)
+
+            assert tested.shape == expected.shape
+            assert numpy.allclose(tested, expected)
+
 
 class TestRepeatOp(utt.InferShapeTester):
     def _possible_axis(self, ndim):

theano/tensor/var.py

@@ -585,7 +585,19 @@ class _tensor_py_operators:
 
     def choose(self, a, choices, out=None, mode='raise'):
         """Construct an array from an index array and a set of arrays to choose from."""
-        return theano.tensor.basic.choose(self, a, choices, out=None, mode='raise')
+        return theano.tensor.basic.choose(self, a, choices, out=None,
+                                          mode='raise')
+
+    def squeeze(self):
+        """Remove broadcastable dimensions from
+        the shape of an array.
+
+        It returns the input array, but with the
+        broadcastable dimensions removed. This is
+        always `x` itself or a view into `x`.
+        """
+        return theano.tensor.extra_ops.squeeze(self)
+
 
 class TensorVariable(_tensor_py_operators, Variable):
     """Subclass to add the tensor operators to the basic `Variable` class."""