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Functions586 in github.com/MrZihan/HNR-VLN

Method__init__
(self, config)
NeRF/models/etp/vilmodel_cmt.py:535
Method__init__
(self, config)
NeRF/models/etp/vilmodel_cmt.py:569
Method__init__
(self, hidden_size, dropout_rate)
NeRF/models/etp/vilmodel_cmt.py:654
Method__init__
(self, hidden_size, input_size=None)
NeRF/models/etp/vilmodel_cmt.py:666
Method__init__
(self, config)
NeRF/models/etp/vilmodel_cmt.py:680
Method__init__
(self, d_model: int, n_head: int, attn_mask=None)
NeRF/models/encoders/clip.py:32
Method__init__
(self, width: int, layers: int, heads: int, attn_mask = None)
NeRF/models/encoders/clip.py:60
Method__init__
(self, input_resolution: int, patch_size: int, width: int, layers: int, heads: int)
NeRF/models/encoders/clip.py:70
Method__init__
r"""An encoder that uses RNN to encode an instruction. Returns the final hidden state after processing the instruction sequence. Args
NeRF/models/encoders/instruction_encoder.py:10
Method__init__
( self, observation_space, output_size=128, checkpoint="NONE", ba
NeRF/models/encoders/resnet_encoders.py:17
Method__init__
( self, observation_space, output_size, device, spatial_output: b
NeRF/models/encoders/resnet_encoders.py:123
Method__init__
(self, config: Optional[Config] = None)
habitat_extensions/task.py:80
Method__init__
(self, config: Optional[Config] = None)
habitat_extensions/task.py:181
Method__init__
(self, config: Optional[Config] = None)
habitat_extensions/task.py:255
Method__init__
( self, sim: Simulator, config: Config, *args: Any, **kwargs: Any )
habitat_extensions/sensors.py:82
Method__init__
( self, sim: Simulator, config: Config, *args: Any, **kwargs: Any )
habitat_extensions/sensors.py:127
Method__init__
( self, sim: Simulator, config: Config, *args: Any, **kwargs: Any )
habitat_extensions/sensors.py:171
Method__init__
(self, config: Config)
habitat_extensions/habitat_simulator.py:59
Method__init__
( self, sim: HabitatSim, goal_radius: float, return_one_hot: bool = True )
habitat_extensions/shortest_path_follower.py:37
Method__init__
Args: size: A sequence (h, w) or int of the size you wish to resize/center_crop. If int, assumes square crop channels_
habitat_extensions/obs_transformers.py:26
Method__init__
( self, sizes: int, channels_last: bool = True, trans_keys: Tuple[str] = ("rgb
habitat_extensions/obs_transformers.py:99
Method__init__
r""":param sensor_uuids: List of sensor_uuids: Back, Down, Front, Left, Right, Up. :param eq_shape: The shape of the equirectangular output (h
habitat_extensions/obs_transformers.py:227
Method__init__
( self, sim: Simulator, config: Config, *args: Any, **kwargs: Any )
habitat_extensions/measures.py:32
Method__init__
( self, sim: Simulator, config: Config, *args: Any, **kwargs: Any )
habitat_extensions/measures.py:71
Method__init__
( self, sim: Simulator, config: Config, *args: Any, **kwargs: Any )
habitat_extensions/measures.py:117
Method__init__
( self, sim: Simulator, config: Config, *args: Any, **kwargs: Any )
habitat_extensions/measures.py:150
Method__init__
( self, sim: Simulator, config: Config, *args: Any, **kwargs: Any )
habitat_extensions/measures.py:186
Method__init__
( self, sim: Simulator, config: Config, *args: Any, **kwargs: Any )
habitat_extensions/measures.py:221
Method__init__
(self, *args: Any, **kwargs: Any)
habitat_extensions/measures.py:253
Method__init__
( self, sim: Simulator, config: Config, *args: Any, **kwargs: Any )
habitat_extensions/measures.py:349
Method__init__
( self, *args: Any, sim: Simulator, config: Config, **kwargs: Any )
habitat_extensions/measures.py:382
Method__iter__
(self)
NeRF/dagger_trainer.py:167
Method__iter__
(self)
NeRF/common/recollection_dataset.py:290
Method__next__
(self)
NeRF/dagger_trainer.py:156
Method__next__
Takes about 1s to once self._load_next() has finished with a batch size of 5. For this reason, we probably don't need to use extra workers.
NeRF/common/recollection_dataset.py:255
Method__repr__
(self)
NeRF/waypoint_pred/transformer/pytorch_transformer/modeling_utils.py:201
Method_eval_checkpoint
( self, checkpoint_path: str, writer: TensorboardWriter, checkpoint_index:
NeRF/ss_trainer_ETP.py:564
Method_get_observation_space
(self, *args: Any, **kwargs: Any)
habitat_extensions/sensors.py:46
Method_get_observation_space
(self, *args: Any, **kwargs: Any)
habitat_extensions/sensors.py:102
Method_get_observation_space
(self, *args: Any, **kwargs: Any)
habitat_extensions/sensors.py:140
Method_get_sensor_type
(self, *args: Any, **kwargs: Any)
habitat_extensions/sensors.py:43
Method_get_sensor_type
(self, *args: Any, **kwargs: Any)
habitat_extensions/sensors.py:99
Method_get_sensor_type
(self, *args: Any, **kwargs: Any)
habitat_extensions/sensors.py:136
Method_get_sensor_type
(self, *args: Any, **kwargs: Any)
habitat_extensions/sensors.py:183
Method_get_uuid
(self, *args: Any, **kwargs: Any)
habitat_extensions/sensors.py:40
Method_get_uuid
(self, *args: Any, **kwargs: Any)
habitat_extensions/sensors.py:96
Method_get_uuid
(self, *args: Any, **kwargs: Any)
habitat_extensions/sensors.py:133
Method_get_uuid
(self, *args: Any, **kwargs: Any)
habitat_extensions/sensors.py:180
Method_get_uuid
(self, *args: Any, **kwargs: Any)
habitat_extensions/measures.py:40
Method_get_uuid
(self, *args: Any, **kwargs: Any)
habitat_extensions/measures.py:79
Method_get_uuid
(self, *args: Any, **kwargs: Any)
habitat_extensions/measures.py:125
Method_get_uuid
(self, *args: Any, **kwargs: Any)
habitat_extensions/measures.py:157
Method_get_uuid
(self, *args: Any, **kwargs: Any)
habitat_extensions/measures.py:193
Method_get_uuid
(self, *args: Any, **kwargs: Any)
habitat_extensions/measures.py:228
Method_get_uuid
(self, *args: Any, **kwargs: Any)
habitat_extensions/measures.py:256
Method_get_uuid
(self, *args: Any, **kwargs: Any)
habitat_extensions/measures.py:309
Method_get_uuid
(self, *args: Any, **kwargs: Any)
habitat_extensions/measures.py:357
Method_get_uuid
(self, *args: Any, **kwargs: Any)
habitat_extensions/measures.py:391
Method_history_variable
(self, obs)
NeRF/ss_trainer_ETP.py:442
Method_make_dirs
(self)
NeRF/ss_trainer_ETP.py:86
Method_make_dirs
(self)
NeRF/dagger_trainer.py:193
Method_teacher_action
(self, batch_angles, batch_distances, candidate_lengths)
NeRF/ss_trainer_ETP.py:271
Method_teacher_action_new
(self, batch_gmap_vp_ids, batch_no_vp_left)
NeRF/ss_trainer_ETP.py:301
Methodact2
( self, observations, rnn_hidden_states, prev_actions, masks,
NeRF/models/policy.py:67
Methodaction_space
(self)
NeRF/common/recollection_dataset.py:106
Methodactivate
(self)
NeRF/common/aux_losses.py:37
Functionadd_start_docstrings
(*docstr)
NeRF/waypoint_pred/transformer/pytorch_transformer/modeling_utils.py:57
Functionallocate
(number, ep_length, size_per_time)
NeRF/utils.py:46
Functionallocate_by_scene_for_ddp
(number, ep_length, size_per_time)
NeRF/utils.py:128
Functionallocate_instructions
(instruction_lengths, allocations,ep_length, instruction_ids)
NeRF/utils.py:83
Functionangle_feature
(headings, device=None)
NeRF/models/utils.py:6
Functionangle_feature_with_ele
(headings, device=None)
NeRF/models/utils.py:34
Methodbatch_size
(self)
NeRF/common/recollection_dataset.py:96
Methodbuild_distribution
( self, observations, rnn_hidden_states, prev_actions, masks )
NeRF/models/policy.py:59
Functionbuild_transformer
(args)
NeRF/common/transformer.py:456
Methodcal_heading
(agent_state)
habitat_extensions/nav.py:31
Methodcal_heading
(agent_state)
habitat_extensions/nav.py:169
Functioncalc_position_distance
(a, b)
NeRF/models/utils.py:171
Functioncalculate_vp_rel_pos_fts
(a, b, base_heading=0, base_elevation=0)
NeRF/models/utils.py:143
Methodcand_dist_to_goal
r'''get resulting distance to goal by executing a candidate action
NeRF/common/environments.py:250
Methodcheck_config_paths_exist
(cls, config: Config)
habitat_extensions/task.py:173
Methodcheck_navigability
(self, node: List[float])
NeRF/common/environments.py:85
Methodclear
(self)
NeRF/common/aux_losses.py:10
Methodclose_sims
(self)
NeRF/common/recollection_dataset.py:110
Functioncollate_fn
(batch)
NeRF/dagger_trainer.py:46
Functioncolorize_topdown_map
Same as `maps.colorize_topdown_map` in Habitat-Lab, but with different colors.
habitat_extensions/maps.py:80
Functioncompute_heading_to
Compute the heading that points from position `pos_from` to position `pos_to` in the global XZ coordinate frame. Args: pos_from: [x,y
habitat_extensions/utils.py:753
Functionconstruct_envs_auto_reset_false
( config: Config, env_class: Type[Union[Env, RLEnv]] )
NeRF/common/env_utils.py:130
Functionconstruct_envs_for_rl
r"""Create VectorEnv object with specified config and env class type. To allow better performance, dataset are split into small ones for eac
NeRF/common/env_utils.py:135
Methoddeactivate
(self)
NeRF/common/aux_losses.py:40
Functiondir_angle_feature
(angle_list, device=None)
NeRF/utils.py:192
Functiondir_angle_feature
(angle_list, device=None)
NeRF/models/utils.py:18
Functiondir_angle_feature_with_ele
(angle_list, device=None)
NeRF/utils.py:208
Functiondir_angle_feature_with_ele
(angle_list, device=None)
NeRF/models/utils.py:59
Methoddistance
(self, x, y)
NeRF/models/graph_utils.py:80
Functiondocstring_decorator
(fn)
NeRF/waypoint_pred/transformer/pytorch_transformer/modeling_utils.py:58
Functiondraw_conn
(img, p1, p2, bounds, color)
habitat_extensions/maps.py:298
Functiondraw_mp3d_nodes
( img: np.ndarray, sim: Simulator, episode: VLNEpisode, graph: nx.Graph, meters_per_px: fl
habitat_extensions/maps.py:348
Functiondraw_reference_path
Draws lines between each waypoint in the reference path.
habitat_extensions/maps.py:193
Functiondraw_source_and_target
( img: np.ndarray, sim: Simulator, episode: VLNEpisode, meters_per_px: float )
habitat_extensions/maps.py:254
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