Add slice parameter type checking to disallow Tensor usage for slices (…

…tinygrad#6967)

* add support for single el tensors for slices

* rm trailing spaces

* cleanup long lines

* remove tensor in slice support, add comprehensive err msg

* cleanup getitem, add slice type check

* Edit err message

test/test_ops.py

@@ -1236,6 +1236,7 @@ def test_slice_errors(self):
     with self.assertRaisesRegex(IndexError, "out of bounds"): a[1, -4]
     with self.assertRaisesRegex(IndexError, "single ellipsis"): a[..., ...] # IndexError: only single ellipsis
     with self.assertRaises(ValueError): a[::0, 1] # no 0 strides
+    with self.assertRaises(TypeError): a[:Tensor([3]), 1] # Tensor can't be used as a slice parameter
     with self.assertRaises(IndexError): b[:] # slice cannot be applied to a 0-dim tensor
 
   def test_slice_ellipsis(self):

tinygrad/tensor.py

@@ -1063,6 +1063,9 @@ def _getitem(self, indices, v: Optional[Tensor] = None) -> Tensor:
       indices_filtered[dim] = ((index, index+1), 1) if index >= 0 else ((size+index, size+index+1), 1)
     for dim in type_dim[slice]:
       if (index := indices_filtered[dim]).step == 0: raise ValueError(f"{index=} on {dim=} cannot have 0 as step")
+      if not all(isinstance(x, (int, type(None))) for x in (index.start, index.stop, index.step)):
+        raise TypeError(f"Unsupported slice for dimension {dim}. Expected slice with integers or None, got slice("
+                        f"{', '.join(type(x).__name__ for x in (index.start, index.stop, index.step))}).")
       s, e, st = index.indices(self.shape[dim])
       indices_filtered[dim] = ((0, 0) if (st * (e - s)) < 0 else (s, e) if st > 0 else (e+1, s+1), st)
     # skip all Tensor dims for basic indexing