Return primitives when possible

phiml/backend/_backend.py

@@ -194,6 +194,17 @@ def auto_cast(self, *tensors, bool_to_int=False, int_to_float=False) -> list:
             tensors = [self.cast(t, result_type) for t in tensors]
         return tensors
 
+    def auto_cast1(self, tensor):
+        if isinstance(tensor, (bool, Number)):
+            return tensor
+        dtype = self.dtype(tensor)
+        if dtype.kind in {int, bool}:
+            return tensor
+        result_type = combine_types(dtype, fp_precision=self.precision)
+        if result_type.bits == dtype.bits:
+            return tensor
+        return self.cast(tensor, result_type)
+
     def __str__(self):
         return self.name
 

phiml/math/_magic_ops.py

@@ -283,7 +283,7 @@ def stack(values: Union[Sequence[PhiTreeNodeType], Dict[str, PhiTreeNodeType]],
         return values[0]
 
 
-def concat(values: Sequence[PhiTreeNodeType], dim: Union[str, Shape], /, expand_values=False, **kwargs) -> PhiTreeNodeType:
+def concat(values: Sequence[PhiTreeNodeType], dim: Union[str, Shape], expand_values=False, **kwargs) -> PhiTreeNodeType:
     """
     Concatenates a sequence of `phiml.math.magic.Shapable` objects, e.g. `Tensor`, along one dimension.
     All values must have the same spatial, instance and channel dimensions and their sizes must be equal, except for `dim`.

phiml/math/_tensors.py

@@ -1240,7 +1240,7 @@ def native(self, order: Union[str, tuple, list, Shape] = None, force_expand=True
         if order is None:
             assert len(self._shape) <= 1, f"When calling Tensor.native() or Tensor.numpy(), the dimension order must be specified for Tensors with more than one dimension, e.g. '{','.join(self._shape.names)}'. The listed default dimension order can vary depending on the chosen backend. Consider using math.reshaped_native(Tensor) instead."
             if len(self._names) == len(self._shape):
-                return self.backend.auto_cast(self._native)[0]
+                return self.backend.auto_cast1(self._native)
             assert len(self._names) == 0  # shape.rank is 1
             return self.backend.tile(self.backend.expand_dims(self.backend.auto_cast(self._native)[0]), (self._shape.size,))
         if isinstance(order, str):
@@ -1251,6 +1251,8 @@ def native(self, order: Union[str, tuple, list, Shape] = None, force_expand=True
         return self._reshaped_native(groups)
 
     def _reshaped_native(self, groups: Sequence[Shape]):
+        if not groups:
+            return self.backend.auto_cast1(self._native)
         perm = []
         slices = []
         tile = []