check for 0-length axes to avoid error with numpy.max; also unit test

theano/tensor/basic.py

@@ -7289,8 +7289,9 @@ def tensordot(a, b, axes = 2):
                              (a.ndim, len(a_axes)))
 
         # check that a_axes doesn't contain an axis greater than or equal to
-        # a's dimensions.
-        if numpy.max(numpy.array(a_axes)) >= a.ndim:
+        # a's dimensions. also check if len > 0 so numpy.max won't raise an
+        # error.
+        if len(a_axes) > 0 and numpy.max(numpy.array(a_axes)) >= a.ndim:
             raise ValueError('axes[0] contains dimensions greater than or '
                              'equal to a.ndim (a.ndim=%i, max(axes[0])=%i).' %
                              (a.ndim, numpy.max(numpy.array(a_axes))))
@@ -7303,8 +7304,9 @@ def tensordot(a, b, axes = 2):
                              (b.ndim, len(b_axes)))
 
         # check that b_axes doesn't contain an axis greater than or equal to
-        # b's dimensions.
-        if numpy.max(numpy.array(b_axes)) >= b.ndim:
+        # b's dimensions. also check if len > 0 so numpy.max won't raise an
+        # error.
+        if len(b_axes) > 0 and numpy.max(numpy.array(b_axes)) >= b.ndim:
             raise ValueError('axes[1] contains dimensions greater than or '
                              'equal to b.ndim (b.ndim=%i, max(axes[1])=%i).' %
                              (b.ndim, numpy.max(numpy.array(b_axes))))

theano/tensor/tests/test_basic.py

@@ -5541,7 +5541,13 @@ class test_tensordot(unittest.TestCase):
         # Test matrix-matrix
         amat = matrix()
         bmat = matrix()
-        for axes in 0, (1, 0), [1, 0], (1, (0, )), ((1, ), 0), ([1], [0]):
+        for axes in [0,
+                     (1, 0),
+                     [1, 0],
+                     (1, (0, )),
+                     ((1, ), 0),
+                     ([1], [0]),
+                     ([], [])]:
             c = tensordot(amat, bmat, axes)
             f3 = inplace_func([amat, bmat], c)
             aval = rand(4, 7)