Simplify more

Author: NeilGirdhar

src/array_api_extra/_lib/_funcs.py

@@ -383,18 +383,18 @@ def one_hot(
     xp: ModuleType,
 ) -> Array:  # numpydoc ignore=PR01,RT01
     """See docstring in `array_api_extra._delegation.py`."""
-    x_size = _compat.size(x)
-    if x_size is None:  # pragma: no cover
-        # This cannot be tested because there is no way to create an array with abstract
-        # size today.  However, it is blocked for the sake of type-checking and
-        # future-proofing since x.size is allowed to be None according to the
-        # specification.
-        msg = "x must have a concrete size."
-        raise TypeError(msg)
     # TODO: Benchmark whether this is faster on the NumPy backend:
+    # x_size = _compat.size(x)
+    # if x_size is None:  # pragma: no cover
+    #     # This cannot be tested because there is no way to create an array with abstract
+    #     # size today.  However, it is blocked for the sake of type-checking and
+    #     # future-proofing since x.size is allowed to be None according to the
+    #     # specification.
+    #     msg = "x must have a concrete size."
+    #     raise TypeError(msg)
     # x_flattened = xp.reshape(x, (-1,))
     # out = xp.zeros((x.size, num_classes), dtype=dtype, device=_compat.device(x))
-    # out = at(out)[xp.arange(x_size), x_flattened].set(1)
+    # out = at(out)[xp.arange(x.size), x_flattened].set(1)
     # out = xp.reshape(out, (*x.shape, num_classes))
     range_num_classes = xp.arange(num_classes, dtype=x.dtype, device=_compat.device(x))
     return x[..., xp.newaxis] == range_num_classes