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github.com/NeuralMMO/baselines
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Functions
176 in github.com/NeuralMMO/baselines
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Functions
176
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Types & classes
43
↓ 10 callers
Method
__init__
(self, env, input_size=256, hidden_size=256, task_size=2048)
agent_zoo/yaofeng/policy.py:24
↓ 10 callers
Function
orthogonal_init
(layer, gain=1.0)
agent_zoo/yaofeng/policy.py:18
↓ 8 callers
Method
__init__
(self, env, input_size=256, hidden_size=256, task_size=2048)
agent_zoo/neurips23_start_kit/baseline_policy.py:25
↓ 8 callers
Method
__init__
(self, env, policy, input_size=256, hidden_size=256, num_layers=0)
agent_zoo/takeru/policy.py:17
↓ 7 callers
Method
close
(self)
curriculum_generation/task_encoder.py:167
↓ 5 callers
Function
create_basic_tasks
(unit_count)
syllabus_wrapper.py:58
↓ 5 callers
Function
get_init_args
(fn)
train.py:40
↓ 5 callers
Method
get_task_embedding
Compute embeddings for given task specifications and save them to file. Args: task_spec_list: List of task specifications.
curriculum_generation/task_encoder.py:137
↓ 3 callers
Method
seed
(self, seed)
reinforcement_learning/stat_wrapper.py:26
↓ 2 callers
Method
_construct_prompt
Construct a task-specific prompt. Args: reward_to: Reward given to the agent upon successful completion of the task.
curriculum_generation/task_encoder.py:115
↓ 2 callers
Method
_get_embedding
Compute the embeddings of tasks. Args: prompts: List of tasks defined as prompts. Returns: A list of embedd
curriculum_generation/task_encoder.py:66
↓ 2 callers
Method
_get_task_deps_src
Extract source code and dependent functions of the evaluation function. Args: eval_fn: Function for task evaluation.
curriculum_generation/task_encoder.py:90
↓ 2 callers
Method
_reset_episode_stats
(self)
reinforcement_learning/stat_wrapper.py:100
↓ 2 callers
Function
combine_config_args
(parser, args, config)
train.py:85
↓ 2 callers
Function
count_unique_events
(tick_log, experienced, every_event_to_count=EVERY_EVENT_TO_COUNT)
reinforcement_learning/stat_wrapper.py:295
↓ 2 callers
Function
done_training
(data)
reinforcement_learning/clean_pufferl.py:574
↓ 2 callers
Function
event_key_to_str
(event_key)
analysis/proc_task_cond_result.py:22
↓ 2 callers
Function
extract_module_fn
(module: ModuleType)
curriculum_generation/task_encoder.py:16
↓ 2 callers
Function
generate_replay
(args, env_creator, agent_creator, stop_when_all_complete_task=True, seed=None)
train_helper.py:92
↓ 2 callers
Function
get_eval_config
(debug=False)
evaluate.py:25
↓ 2 callers
Function
get_task_predicate
(spec)
neurips23_evaluation/export_embeddings.py:21
↓ 2 callers
Function
init_wandb
(args, resume=True)
train_helper.py:21
↓ 2 callers
Function
load_from_config
(agent, debug=False)
train.py:20
↓ 2 callers
Function
make_agent_creator
()
evaluate.py:97
↓ 2 callers
Function
make_env_creator
(task_file, mode)
evaluate.py:80
↓ 2 callers
Method
observation
Called before observations are returned from the environment Use this to define custom featurizers. Changing the space itself requires you to
reinforcement_learning/stat_wrapper.py:29
↓ 2 callers
Method
observation
Called before observations are returned from the environment Use this to define custom featurizers. Changing the space itself requires you to
agent_zoo/takeru/reward_wrapper.py:25
↓ 2 callers
Function
print_dashboard
(stats, init_performance, performance)
reinforcement_learning/clean_pufferl.py:642
↓ 2 callers
Method
reset
(self, **kwargs)
syllabus_wrapper.py:129
↓ 2 callers
Function
save_checkpoint
(data)
reinforcement_learning/clean_pufferl.py:578
↓ 2 callers
Function
train
(args, env_creator, agent_creator, syllabus=None)
train_helper.py:49
↓ 2 callers
Function
update_args
(args, mode=None)
train.py:111
↓ 1 callers
Method
_process_stats_and_early_stop
Update stats + info and save replays.
reinforcement_learning/stat_wrapper.py:112
↓ 1 callers
Method
_reset_reward_vars
(self)
agent_zoo/neurips23_start_kit/reward_wrapper.py:30
↓ 1 callers
Method
_reset_reward_vars
(self)
agent_zoo/yaofeng/reward_wrapper.py:53
↓ 1 callers
Method
_save_results
(self, results, file_name)
evaluate.py:193
↓ 1 callers
Method
action
Called before actions are passed from the model to the environment
reinforcement_learning/stat_wrapper.py:35
↓ 1 callers
Method
apply_layer
(self, layer, embeddings, mask, hidden)
agent_zoo/neurips23_start_kit/baseline_policy.py:222
↓ 1 callers
Method
apply_layer
(self, layer, embeddings, mask, hidden)
agent_zoo/yaofeng/policy.py:288
↓ 1 callers
Method
apply_layer
(self, layer, embeddings, mask, hidden)
agent_zoo/takeru/policy.py:327
↓ 1 callers
Method
change_task
(self, new_task)
syllabus_wrapper.py:155
↓ 1 callers
Function
create_pool
(num_proc)
curriculum_generation/manual_curriculum.py:325
↓ 1 callers
Function
create_sequential_curriculum
(task_space)
syllabus_wrapper.py:36
↓ 1 callers
Function
extract_task_name
(task_str)
analysis/proc_task_cond_result.py:48
↓ 1 callers
Function
gather_agent_events_by_task
(data_dir)
analysis/proc_task_cond_result.py:54
↓ 1 callers
Function
get_event_stats
(task_name, task_data)
analysis/proc_task_cond_result.py:72
↓ 1 callers
Method
get_learnable_tasks
( self, num_tasks, max_completed=0.8, # filter out easy tasks min_completed=0
curriculum_generation/task_sampler.py:46
↓ 1 callers
Method
get_pufferl_config
(debug=False)
evaluate.py:151
↓ 1 callers
Function
get_summary_dict
(progress, key)
analysis/proc_eval_result.py:42
↓ 1 callers
Function
get_task_weight
(task_name)
analysis/proc_eval_result.py:34
↓ 1 callers
Method
no_explore_post_processing
(self, logits)
agent_zoo/takeru/policy.py:66
↓ 1 callers
Method
perform_eval
(self, mode, task_file, seed, num_eval_episode, save_file_prefix)
evaluate.py:164
↓ 1 callers
Function
process_eval_files
(policy_store_dir, eval_prefix)
analysis/proc_eval_result.py:79
↓ 1 callers
Function
process_event_log
Process the event log and extract performed actions and achievements.
reinforcement_learning/stat_wrapper.py:216
↓ 1 callers
Method
reward_terminated_truncated_info
Called on reward, terminated, truncated, and info before they are returned from the environment Use this to define custom reward shaping.
reinforcement_learning/stat_wrapper.py:39
↓ 1 callers
Method
run
( self, mode, task_file=EVAL_TASK_FILE, seed=None, num_episode=None, save_file_prefix=None )
evaluate.py:197
↓ 1 callers
Function
seed_everything
(seed, torch_deterministic)
reinforcement_learning/clean_pufferl.py:613
↓ 1 callers
Method
sequential_task_list
(self)
syllabus_wrapper.py:170
↓ 1 callers
Function
setup_agent
(module_name)
train.py:59
↓ 1 callers
Method
setup_evaluator
(self, mode, task_file, seed)
evaluate.py:119
↓ 1 callers
Method
step
(self, action)
reinforcement_learning/stat_wrapper.py:57
↓ 1 callers
Function
summarize_single_eval
(data, weighted_score=False)
analysis/proc_eval_result.py:54
↓ 1 callers
Function
sweep
(args, env_creator, agent_creator)
train_helper.py:72
↓ 1 callers
Function
unroll_nested_dict
(d)
reinforcement_learning/clean_pufferl.py:630
↓ 1 callers
Method
update
(self, infos, prefix="curriculum/")
curriculum_generation/task_sampler.py:25
Function
PracticeEating
The progress, the max of which is 1, should * increase small for each eating * increase big for the 1st and 3rd eating * reach 1 with 10 e
curriculum_generation/curriculum_tutorial.py:45
Method
PracticeFormation
(gs, subject, dist, num_tick)
syllabus_wrapper.py:303
Function
PracticeInventoryManagement
(gs, subject, space, num_tick)
curriculum_generation/manual_curriculum.py:201
Function
PracticeInventoryManagement
(gs, subject, space, num_tick)
curriculum_generation/curriculum_tutorial.py:64
Method
PracticeInventoryManagement
(gs, subject, space, num_tick)
syllabus_wrapper.py:395
Function
PracticeSkillWithTool
(gs, subject, skill, exp)
curriculum_generation/manual_curriculum.py:119
Method
__enter__
(self)
curriculum_generation/task_encoder.py:174
Method
__exit__
(self, exc_type, exc_value, traceback)
curriculum_generation/task_encoder.py:177
Method
__init__
(self, env: gym.Env)
syllabus_wrapper.py:83
Method
__init__
(self, task_file, mode)
evaluate.py:49
Method
__init__
(self, policy_store_dir, debug=False)
evaluate.py:112
Method
__init__
(self, env_args: Namespace)
reinforcement_learning/environment.py:28
Method
__init__
( self, env, eval_mode=False, early_stop_agent_num=0, stat_prefix=None
reinforcement_learning/stat_wrapper.py:10
Method
__init__
(self, env, policy, input_size=256, hidden_size=256, num_layers=1)
agent_zoo/neurips23_start_kit/baseline_policy.py:18
Method
__init__
(self, input_size)
agent_zoo/neurips23_start_kit/baseline_policy.py:86
Method
__init__
(self, input_size, hidden_size)
agent_zoo/neurips23_start_kit/baseline_policy.py:116
Method
__init__
(self, input_size, hidden_size)
agent_zoo/neurips23_start_kit/baseline_policy.py:149
Method
__init__
(self, input_size, hidden_size)
agent_zoo/neurips23_start_kit/baseline_policy.py:174
Method
__init__
(self, input_size, hidden_size)
agent_zoo/neurips23_start_kit/baseline_policy.py:185
Method
__init__
(self, input_size, hidden_size, task_size)
agent_zoo/neurips23_start_kit/baseline_policy.py:194
Method
__init__
(self, input_size, hidden_size)
agent_zoo/neurips23_start_kit/baseline_policy.py:203
Method
__init__
( # BaseStatWrapper args self, env, eval_mode=False, early_stop_agent_
agent_zoo/neurips23_start_kit/reward_wrapper.py:5
Method
__init__
(self, env, policy, input_size=256, hidden_size=256, num_layers=2)
agent_zoo/yaofeng/policy.py:14
Method
__init__
(self, in_planes, img_size=(15, 15))
agent_zoo/yaofeng/policy.py:75
Method
__init__
(self, input_size)
agent_zoo/yaofeng/policy.py:92
Method
__init__
(self, input_size, hidden_size, output_size, num_layers=2)
agent_zoo/yaofeng/policy.py:119
Method
__init__
(self, input_size, hidden_size)
agent_zoo/yaofeng/policy.py:139
Method
__init__
(self, input_size, hidden_size)
agent_zoo/yaofeng/policy.py:188
Method
__init__
(self, input_size, hidden_size)
agent_zoo/yaofeng/policy.py:233
Method
__init__
(self, input_size, hidden_size)
agent_zoo/yaofeng/policy.py:246
Method
__init__
(self, input_size, hidden_size, task_size)
agent_zoo/yaofeng/policy.py:257
Method
__init__
(self, input_size, hidden_size)
agent_zoo/yaofeng/policy.py:268
Method
__init__
( # BaseStatWrapper args self, env, eval_mode=False, early_stop_agent_
agent_zoo/yaofeng/reward_wrapper.py:12
Method
__init__
(self, env, input_size=256, hidden_size=256, task_size=2048)
agent_zoo/takeru/policy.py:24
Method
__init__
(self, input_size)
agent_zoo/takeru/policy.py:86
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