Pre-commit fixes

vlfm/mapping/obstacle_map.py

@@ -1,8 +1,9 @@
 # Copyright (c) 2023 Boston Dynamics AI Institute LLC. All rights reserved.
 
+from typing import Any, Union
+
 import cv2
 import numpy as np
-from typing import Union, Any
 from frontier_exploration.frontier_detection import detect_frontier_waypoints
 from frontier_exploration.utils.fog_of_war import reveal_fog_of_war
 

vlfm/mapping/traj_visualizer.py

@@ -36,7 +36,9 @@ def draw_trajectory(
         img = self._draw_agent(img, camera_positions[-1], camera_yaw)
         return img
 
-    def _draw_path(self, img: np.ndarray, camera_positions: Union[np.ndarray, List[np.ndarray]]) -> np.ndarray:
+    def _draw_path(
+        self, img: np.ndarray, camera_positions: Union[np.ndarray, List[np.ndarray]]
+    ) -> np.ndarray:
         """Draws the path on the image and returns it"""
         if len(camera_positions) < 2:
             return img

vlfm/policy/reality_policies.py

@@ -1,7 +1,7 @@
 # Copyright (c) 2023 Boston Dynamics AI Institute LLC. All rights reserved.
 
 from dataclasses import dataclass
-from typing import Any, Dict, List, Tuple, Union, Optional
+from typing import Any, Dict, List, Tuple, Union
 
 import numpy as np
 import torch

vlfm/policy/utils/non_habitat_policy/resnet.py

@@ -6,7 +6,7 @@
 # https://github.com/facebookresearch/habitat-lab/blob/main/habitat-baselines/habitat_baselines/rl/ddppo/policy/resnet.py
 # This is a filtered down version that only support ResNet-18
 
-from typing import List, Optional, Type, cast
+from typing import List, Optional, Type
 
 from torch import Tensor
 from torch import nn as nn

vlfm/policy/utils/non_habitat_policy/rnn_state_encoder.py

@@ -6,7 +6,7 @@
 # https://github.com/facebookresearch/habitat-lab/blob/main/habitat-baselines/habitat_baselines/rl/models/rnn_state_encoder.py
 # This is a filtered down version that only supports LSTM
 
-from typing import Dict, Optional, Tuple, Any
+from typing import Any, Dict, Optional, Tuple
 
 import torch
 import torch.nn as nn
@@ -20,6 +20,7 @@ class RNNStateEncoder(nn.Module):
     is that it takes an addition masks input that resets the hidden state between two adjacent
     timesteps to handle episodes ending in the middle of a rollout.
     """
+
     def __init__(
         self,
         input_size: int,
@@ -131,16 +132,16 @@ def __init__(
     ):
         super().__init__(input_size, hidden_size, num_layers)
 
-    # Note: Type handling mypy errors in pytorch libraries prevent 
+    # Note: Type handling mypy errors in pytorch libraries prevent
     # directly setting hidden_states type
     def pack_hidden(
-        self, hidden_states: Any # type is Tuple[torch.Tensor, torch.Tensor]
+        self, hidden_states: Any  # type is Tuple[torch.Tensor, torch.Tensor]
     ) -> torch.Tensor:
         return torch.cat(hidden_states, 0)
 
     def unpack_hidden(
         self, hidden_states: torch.Tensor
-    ) -> Any: # type is Tuple[torch.Tensor, torch.Tensor]
+    ) -> Any:  # type is Tuple[torch.Tensor, torch.Tensor]
         lstm_states = torch.chunk(hidden_states.contiguous(), 2, 0)
         return (lstm_states[0], lstm_states[1])
 

vlfm/reality/pointnav_env.py

@@ -106,9 +106,7 @@ def _compute_velocities(self, action: Dict[str, Any]) -> Tuple[float, float]:
         lin_vel = lin_dist / self._time_step
         return ang_vel, lin_vel
 
-    def _compute_displacements(
-        self, action: Dict[str, Any]
-    ) -> Tuple[float, float]:
+    def _compute_displacements(self, action: Dict[str, Any]) -> Tuple[float, float]:
         displacements = []
         for action_key, max_dist in (
             ("angular", self._max_ang_dist),

vlfm/utils/geometry_utils.py

@@ -1,7 +1,7 @@
 # Copyright (c) 2023 Boston Dynamics AI Institute LLC. All rights reserved.
 
 import math
-from typing import Tuple, Union
+from typing import Tuple
 
 import numpy as np