Formatting fixes.

Author: shauryadNv

source/isaaclab_tasks/isaaclab_tasks/contrib/deploy/cable_insertion/config/displayport_rizon_4s/joint_pos_env_cfg.py

@@ -48,7 +48,9 @@
 
 _SOCKET_ROOT = compute_socket_root(_GEOMETRY_POS, _SOCKET_ROT)
 _PLUG_ROOT, _PLUG_ROT = compute_plug_pose(
-    _GEOMETRY_POS, _SOCKET_ROT, z_clearance=_PLUG_CLEARANCE_Z,
+    _GEOMETRY_POS,
+    _SOCKET_ROT,
+    z_clearance=_PLUG_CLEARANCE_Z,
 )
 
 # DisplayPort plug insertion length (blade engagement along the insertion axis)

source/isaaclab_tasks/isaaclab_tasks/contrib/deploy/cable_insertion/config/displayport_rizon_4s/ros_inference_env_cfg.py

@@ -35,7 +35,9 @@
 
 _HUBBLE_SOCKET_ROOT = compute_socket_root(_HUBBLE_GEOMETRY_POS, _HUBBLE_SOCKET_ROT)
 _HUBBLE_PLUG_ROOT, _HUBBLE_PLUG_ROT = compute_plug_pose(
-    _HUBBLE_GEOMETRY_POS, _HUBBLE_SOCKET_ROT, z_clearance=_HUBBLE_PLUG_CLEARANCE_Z,
+    _HUBBLE_GEOMETRY_POS,
+    _HUBBLE_SOCKET_ROT,
+    z_clearance=_HUBBLE_PLUG_CLEARANCE_Z,
 )
 
 
@@ -133,9 +135,7 @@ def __post_init__(self):
 
 
 @configclass
-class Rizon4sGravDisplayportInsertionNoJointVelROSInferenceEnvCfg(
-    Rizon4sGravDisplayportInsertionROSInferenceEnvCfg
-):
+class Rizon4sGravDisplayportInsertionNoJointVelROSInferenceEnvCfg(Rizon4sGravDisplayportInsertionROSInferenceEnvCfg):
     """ROS inference config for the velocity-free joint-space policy.
 
     Identical deployment setup to

source/isaaclab_tasks/isaaclab_tasks/contrib/deploy/cable_insertion/config/displayport_rizon_4s/task_space_env_cfg.py

@@ -53,8 +53,12 @@
 _DAMPING_RATIO_TRANS = 35.0 / (2.0 * math.sqrt(300.0))  # ~1.010
 _DAMPING_RATIO_ROT = 1.1 / (2.0 * math.sqrt(30.0))  # ~0.100
 _DAMPING_RATIO = (
-    _DAMPING_RATIO_TRANS, _DAMPING_RATIO_TRANS, _DAMPING_RATIO_TRANS,
-    _DAMPING_RATIO_ROT, _DAMPING_RATIO_ROT, _DAMPING_RATIO_ROT,
+    _DAMPING_RATIO_TRANS,
+    _DAMPING_RATIO_TRANS,
+    _DAMPING_RATIO_TRANS,
+    _DAMPING_RATIO_ROT,
+    _DAMPING_RATIO_ROT,
+    _DAMPING_RATIO_ROT,
 )
 
 # Production action_scale = [0.01]*6 for both position and rotation

source/isaaclab_tasks/isaaclab_tasks/contrib/deploy/cable_insertion/displayport_insertion_env_cfg.py

@@ -62,6 +62,7 @@ def _quat_mul(q1_xyzw, q2_xyzw):
         w1 * w2 - x1 * x2 - y1 * y2 - z1 * z2,
     )
 
+
 # ---------------------------------------------------------------------------
 # USD body-frame offsets (DisplayPort asset geometry)
 # ---------------------------------------------------------------------------
@@ -114,7 +115,9 @@ def compute_plug_pose(geometry_pos, socket_rot, z_clearance=0.0):
 
 _SOCKET_ROOT_POS = compute_socket_root(_INSERTION_POINT, _DEFAULT_SOCKET_ROT)
 _PLUG_ROOT_POS, _DEFAULT_PLUG_ROT = compute_plug_pose(
-    _INSERTION_POINT, _DEFAULT_SOCKET_ROT, z_clearance=0.033,
+    _INSERTION_POINT,
+    _DEFAULT_SOCKET_ROT,
+    z_clearance=0.033,
 )
 
 ##

source/isaaclab_tasks/isaaclab_tasks/contrib/deploy/cable_insertion/insertion_env.py

@@ -25,7 +25,6 @@
 from __future__ import annotations
 
 import torch
-
 import warp as wp
 
 from isaaclab.envs import ManagerBasedRLEnv

source/isaaclab_tasks/isaaclab_tasks/contrib/deploy/mdp/events.py

@@ -11,6 +11,7 @@
 from typing import TYPE_CHECKING
 
 import torch
+import warp as wp
 
 import isaaclab.utils.math as math_utils
 from isaaclab.managers import EventTermCfg, ManagerTermBase, SceneEntityCfg
@@ -763,9 +764,7 @@ def __call__(
         # Write gripper STATE at ``hand_hold_width`` (fingers just touching the
         # plug, no mesh overlap) and set the TARGET to ``hand_close_width``
         # (fully closed) so the actuator drive squeezes around the plug.
-        self.gripper_joint_setter_func(
-            joint_pos, list(range(num_reset_envs)), self.finger_joints, self.hand_hold_width
-        )
+        self.gripper_joint_setter_func(joint_pos, list(range(num_reset_envs)), self.finger_joints, self.hand_hold_width)
         self.robot_asset.write_joint_position_to_sim_index(position=joint_pos, env_ids=env_ids)
         self.robot_asset.write_joint_velocity_to_sim_index(velocity=joint_vel, env_ids=env_ids)
 
@@ -824,9 +823,7 @@ def __init__(self, cfg: EventTermCfg, env: ManagerBasedEnv):
 
         self.normal_pose_range: dict = cfg.params.get("normal_pose_range", {})
 
-        self.identity_quat = torch.tensor(
-            [0.0, 0.0, 0.0, 1.0], device=env.device, dtype=torch.float32
-        )
+        self.identity_quat = torch.tensor([0.0, 0.0, 0.0, 1.0], device=env.device, dtype=torch.float32)
 
     def _current_at_goal_prob(self, env: ManagerBasedEnv) -> float:
         """Return the at-goal probability for the current training progress.
@@ -835,11 +832,7 @@ def _current_at_goal_prob(self, env: ManagerBasedEnv) -> float:
         between ``anneal_start_iter`` and ``anneal_end_iter``. Returns the
         constant ``at_goal_prob`` when annealing is not fully configured.
         """
-        if (
-            self.at_goal_prob_final is None
-            or self.anneal_end_iter is None
-            or not self.num_steps_per_env
-        ):
+        if self.at_goal_prob_final is None or self.anneal_end_iter is None or not self.num_steps_per_env:
             return self.at_goal_prob
 
         current_iter = env.common_step_counter / float(self.num_steps_per_env)
@@ -875,7 +868,10 @@ def __call__(
         socket_offset_batch = self.socket_insertion_offset.unsqueeze(0).expand(num_envs, -1)
         id_quat_batch = self.identity_quat.unsqueeze(0).expand(num_envs, -1)
         kp_origin_w, _ = math_utils.combine_frame_transforms(
-            socket_pos, socket_quat, socket_offset_batch, id_quat_batch,
+            socket_pos,
+            socket_quat,
+            socket_offset_batch,
+            id_quat_batch,
         )
 
         # Insertion axis in world frame (rotated by socket orientation)
@@ -917,7 +913,9 @@ def __call__(
             num_at_goal = int(at_goal_local.numel())
             if num_at_goal > 0:
                 depth_rand = torch.rand(num_at_goal, 1, device=env.device)
-                goal_kp_pos = kp_origin_w[at_goal_local] + depth_rand * insertion_axis_w[at_goal_local] * self.insertion_length
+                goal_kp_pos = (
+                    kp_origin_w[at_goal_local] + depth_rand * insertion_axis_w[at_goal_local] * self.insertion_length
+                )
 
                 # Convert keypoint position to plug root position
                 plug_pos[at_goal_local] = goal_kp_pos - plug_kp_in_world[at_goal_local]

source/isaaclab_tasks/isaaclab_tasks/contrib/deploy/mdp/observations.py

@@ -10,6 +10,7 @@
 from typing import TYPE_CHECKING
 
 import torch
+import warp as wp
 
 from isaaclab.managers import ManagerTermBase, ObservationTermCfg, SceneEntityCfg
 from isaaclab.utils.math import combine_frame_transforms, matrix_from_quat

source/isaaclab_tasks/isaaclab_tasks/contrib/deploy/mdp/rewards.py

@@ -609,15 +609,13 @@ def __init__(self, cfg: RewardTermCfg, env: ManagerBasedRLEnv):
             torch.tensor(rot_offset_2, device=env.device, dtype=torch.float32).unsqueeze(0).repeat(env.num_envs, 1)
         )
 
-        self.identity_quat = (
-            torch.tensor([[0.0, 0.0, 0.0, 1.0]], device=env.device, dtype=torch.float32).repeat(env.num_envs, 1)
+        self.identity_quat = torch.tensor([[0.0, 0.0, 0.0, 1.0]], device=env.device, dtype=torch.float32).repeat(
+            env.num_envs, 1
         )
 
         self.keypoint_computer = _compute_keypoint_distance(cfg, env)
 
-    def _get_kp_frames(
-        self, env: ManagerBasedRLEnv
-    ) -> tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor]:
+    def _get_kp_frames(self, env: ManagerBasedRLEnv) -> tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor]:
         """Compute keypoint frames for both assets with offsets applied."""
         import warp as wp
 

source/isaaclab_tasks/isaaclab_tasks/contrib/deploy/mdp/terminations.py

@@ -11,6 +11,7 @@
 from typing import TYPE_CHECKING
 
 import torch
+import warp as wp
 
 import isaaclab.utils.math as math_utils
 from isaaclab.managers import ManagerTermBase, SceneEntityCfg, TerminationTermCfg