setitem in-place operator tests (#4577)

* tests and error

* rename to in-place

* add a note

* more comments

* more comments

* disable folded advanced setitem tests for now

test/imported/test_indexing.py

@@ -1094,6 +1094,8 @@ class TestIndexing(unittest.TestCase):
       r[zero]
     numpy_testing_assert_equal_helper(r, r[...])
 
+  # TODO fancy setitem
+  '''
   def test_setitem_scalars(self):
     zero = Tensor(0, dtype=dtypes.int64)
 
@@ -1121,6 +1123,7 @@ class TestIndexing(unittest.TestCase):
     # TODO: weird inaccuracy Max relative difference: 3.85322971e-08
     # numpy_testing_assert_equal_helper(9.9, r)
     np.testing.assert_allclose(9.9, r, rtol=1e-7)
+  '''
 
   def test_basic_advanced_combined(self):
     # From the NumPy indexing example
@@ -1518,7 +1521,10 @@ class TestNumpy(unittest.TestCase):
   def test_broaderrors_indexing(self):
     a = Tensor.zeros(5, 5)
     self.assertRaises(IndexError, a.__getitem__, ([0, 1], [0, 1, 2]))
+    # TODO: fancy setitem
+    '''
     self.assertRaises(IndexError, a.contiguous().__setitem__, ([0, 1], [0, 1, 2]), 0)
+    '''
 
   # TODO out of bound getitem does not raise error
   '''

test/test_setitem.py

@@ -42,6 +42,41 @@ class TestSetitem(unittest.TestCase):
     assert not t.lazydata.st.contiguous
     with self.assertRaises(AssertionError): t[1] = 5
 
+  def test_setitem_inplace_operator(self):
+    t = Tensor.arange(4).reshape(2, 2).contiguous()
+    t[1] += 2
+    np.testing.assert_allclose(t.numpy(), [[0, 1], [4, 5]])
+
+    t = Tensor.arange(4).reshape(2, 2).contiguous()
+    t[1] -= 1
+    np.testing.assert_allclose(t.numpy(), [[0, 1], [1, 2]])
+
+    t = Tensor.arange(4).reshape(2, 2).contiguous()
+    t[1] *= 2
+    np.testing.assert_allclose(t.numpy(), [[0, 1], [4, 6]])
+
+    # NOTE: have to manually cast setitem target to least_upper_float for div
+    t = Tensor.arange(4, dtype=dtypes.float).reshape(2, 2).contiguous()
+    t[1] /= 2
+    np.testing.assert_allclose(t.numpy(), [[0, 1], [1, 1.5]])
+
+    t = Tensor.arange(4).reshape(2, 2).contiguous()
+    t[1] **= 2
+    np.testing.assert_allclose(t.numpy(), [[0, 1], [4, 9]])
+
+    t = Tensor.arange(4).reshape(2, 2).contiguous()
+    t[1] ^= 5
+    np.testing.assert_allclose(t.numpy(), [[0, 1], [7, 6]])
+
+  @unittest.expectedFailure
+  def test_setitem_consecutive_inplace_operator(self):
+    t = Tensor.arange(4).reshape(2, 2).contiguous()
+    t[1] += 2
+    t = t.contiguous()
+    # TODO: RuntimeError: must be contiguous for assign ShapeTracker(views=(View(shape=(2,), strides=(1,), offset=2, mask=None, contiguous=False),))
+    t[1] -= 1
+    np.testing.assert_allclose(t.numpy(), [[0, 1], [3, 4]])
+
   # TODO: implement fancy setitem
   @unittest.expectedFailure
   def test_fancy_setitem(self):

tinygrad/tensor.py

@@ -824,6 +824,8 @@ class Tensor:
     if not isinstance(v, (Tensor, float, int, bool)): raise TypeError(f"can't set a {type(v).__name__} to a Tensor")
     if not isinstance(v, Tensor): v = Tensor(v, device=self.device, dtype=self.dtype)
     if self.requires_grad or v.requires_grad: raise NotImplementedError("setitem with requires_grad is not supported")
+    if isinstance(indices, (Tensor, list)) or (isinstance(indices, tuple) and any(isinstance(i, (Tensor, list)) for i in indices)):
+      raise NotImplementedError("Advanced indexing setitem is not currently supported")
 
     assign_to = self.realize().__getitem__(indices)
     # NOTE: contiguous to prevent const folding.