Refactor gravity initialization and update post-init conversion to use default tensor type

src/adam/parametric/pytorch/computations_parametric.py

@@ -23,9 +23,7 @@ def __init__(
         joints_name_list: list,
         links_name_list: list,
         root_link: str = None,
-        gravity: np.array = torch.tensor(
-            [0, 0, -9.80665, 0, 0, 0], dtype=torch.float64
-        ),
+        gravity: np.array = torch.tensor([0, 0, -9.80665, 0, 0, 0]),
     ) -> None:
         """
         Args:

src/adam/pytorch/computations.py

@@ -20,9 +20,7 @@ def __init__(
         urdfstring: str,
         joints_name_list: list = None,
         root_link: str = None,
-        gravity: np.array = torch.tensor(
-            [0, 0, -9.80665, 0, 0, 0], dtype=torch.float64
-        ),
+        gravity: np.array = torch.tensor([0, 0, -9.80665, 0, 0, 0]),
     ) -> None:
         """
         Args:

src/adam/pytorch/torch_like.py

@@ -17,9 +17,9 @@ class TorchLike(ArrayLike):
     array: torch.Tensor
 
     def __post_init__(self):
-        """Converts array to double precision"""
-        if self.array.dtype != torch.float64:
-            self.array = self.array.double()
+        """Converts array to the default type used in the library"""
+        if self.array.dtype != torch.get_default_dtype():
+            self.array = self.array.to(torch.get_default_dtype())
 
     def __setitem__(self, idx, value: Union["TorchLike", ntp.ArrayLike]) -> "TorchLike":
         """Overrides set item operator"""