Merge pull request #5456 from affanv14/indexwork

theano/tensor/tests/test_var.py

@@ -26,6 +26,19 @@ def test_numpy_method():
                             np.nan_to_num(fct(data)))
 
 
+def test_empty_list_indexing():
+    ynp = np.zeros((2, 2))[:, []]
+    znp = np.zeros((2, 2))[:, ()]
+    data = [[0, 0], [0, 0]]
+    x = tt.dmatrix('x')
+    y = x[:, []]
+    z = x[:, ()]
+    fy = theano.function([x], y)
+    fz = theano.function([x], z)
+    assert_equal(fy(data).shape, ynp.shape)
+    assert_equal(fz(data).shape, znp.shape)
+
+
 def test_copy():
     x = tt.dmatrix('x')
     data = np.random.rand(5, 5)

theano/tensor/var.py

@@ -501,6 +501,10 @@ class _tensor_py_operators(object):
             args[ellipsis_at: ellipsis_at + 1] = (
                 [slice(None)] * (self.ndim - (len(args) - 1 - new_axes)))
 
+        # Force input to be int64 datatype if input is an empty list or tuple
+        # Else leave it as is if it is a real number
+        args = tuple([numpy.array(inp, dtype=numpy.int64)
+                      if(inp == [] or inp == ()) else inp for inp in args])
         # Convert python literals to theano constants
         args = theano.tensor.subtensor.make_constant(args)
         # Determine if advanced indexing is needed or not