Drop backward compatibility for Torch 1.13 (#1948)

* Drop backward compatibility for Torch 1.13

* Fix lint errors

nerfstudio/cameras/camera_utils.py

@@ -25,8 +25,6 @@ from jaxtyping import Float
 from numpy.typing import NDArray
 from torch import Tensor
 
-from nerfstudio.utils.misc import torch_compile
-
 _EPS = np.finfo(float).eps * 4.0
 
 
@@ -407,7 +405,7 @@ def _compute_residual_and_jacobian(
     return fx, fy, fx_x, fx_y, fy_x, fy_y
 
 
-@torch_compile(dynamic=True, mode="reduce-overhead", backend="eager")
+@torch.compile(dynamic=True, mode="reduce-overhead", backend="eager")
 def radial_and_tangential_undistort(
     coords: torch.Tensor,
     distortion_params: torch.Tensor,

nerfstudio/model_components/scene_colliders.py

@@ -22,7 +22,6 @@ import torch
 from jaxtyping import Float
 from torch import Tensor, nn
 
-from nerfstudio.utils.misc import torch_compile
 from nerfstudio.cameras.rays import RayBundle
 from nerfstudio.data.scene_box import SceneBox
 
@@ -109,7 +108,7 @@ class AABBBoxCollider(SceneCollider):
         return ray_bundle
 
 
-@torch_compile(dynamic=True, mode="reduce-overhead")
+@torch.compile(dynamic=True, mode="reduce-overhead")
 def _intersect_with_sphere(
     rays_o: torch.Tensor, rays_d: torch.Tensor, center: torch.Tensor, radius: float = 1.0, near_plane: float = 0.0
 ):

nerfstudio/utils/math.py

@@ -21,8 +21,6 @@ import torch
 from jaxtyping import Bool, Float
 from torch import Tensor
 
-from nerfstudio.utils.misc import torch_compile
-
 
 def components_from_spherical_harmonics(
     levels: int, directions: Float[Tensor, "*batch 3"]
@@ -199,7 +197,7 @@ def expected_sin(x_means: torch.Tensor, x_vars: torch.Tensor) -> torch.Tensor:
     return torch.exp(-0.5 * x_vars) * torch.sin(x_means)
 
 
-@torch_compile(dynamic=True, mode="reduce-overhead", backend="eager")
+@torch.compile(dynamic=True, mode="reduce-overhead", backend="eager")
 def intersect_aabb(
     origins: torch.Tensor,
     directions: torch.Tensor,

nerfstudio/utils/misc.py

@@ -158,13 +158,3 @@ def strtobool(val) -> bool:
     FMI https://stackoverflow.com/a/715468
     """
     return val.lower() in ("yes", "y", "true", "t", "on", "1")
-
-
-if hasattr(torch, "compile"):
-    # PyTorch 2.0+
-    torch_compile = torch.compile
-else:
-    # PyTorch 1.x
-    def torch_compile(*args, **kwargs):
-        """Fall back to jit script if using pytorch 1.x, args ignored"""
-        return torch.jit.script