Adjustments and Documentation, recording and new environments, refactoring
This commit is contained in:
Steffen Illium
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import time
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from typing import List, Union, Dict
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import numpy as np
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import random
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from environments.factory.additional.item.item_collections import ItemRegister, Inventories, DropOffLocations
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from environments.factory.additional.item.item_util import Constants, Actions, RewardsItem, ItemProperties
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from environments.factory.base.base_factory import BaseFactory
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from environments.factory.base.objects import Agent, Action
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from environments.factory.base.registers import Entities
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from environments.factory.base.renderer import RenderEntity
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c = Constants
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a = Actions
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# noinspection PyAttributeOutsideInit, PyAbstractClass
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class ItemFactory(BaseFactory):
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# noinspection PyMissingConstructor
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def __init__(self, *args, item_prop: ItemProperties = ItemProperties(), env_seed=time.time_ns(),
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rewards_item: RewardsItem = RewardsItem(), **kwargs):
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if isinstance(item_prop, dict):
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item_prop = ItemProperties(**item_prop)
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if isinstance(rewards_item, dict):
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rewards_item = RewardsItem(**rewards_item)
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self.item_prop = item_prop
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self.rewards_item = rewards_item
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kwargs.update(env_seed=env_seed)
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self._item_rng = np.random.default_rng(env_seed)
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assert (item_prop.n_items <= ((1 + kwargs.get('_pomdp_r', 0) * 2) ** 2)) or not kwargs.get('_pomdp_r', 0)
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super().__init__(*args, **kwargs)
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@property
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def actions_hook(self) -> Union[Action, List[Action]]:
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# noinspection PyUnresolvedReferences
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super_actions = super().actions_hook
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super_actions.append(Action(str_ident=a.ITEM_ACTION))
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return super_actions
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@property
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def entities_hook(self) -> Dict[(str, Entities)]:
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# noinspection PyUnresolvedReferences
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super_entities = super().entities_hook
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empty_tiles = self[c.FLOOR].empty_tiles[:self.item_prop.n_drop_off_locations]
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drop_offs = DropOffLocations.from_tiles(
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empty_tiles, self._level_shape,
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entity_kwargs=dict(
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storage_size_until_full=self.item_prop.max_dropoff_storage_size)
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)
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item_register = ItemRegister(self._level_shape)
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empty_tiles = self[c.FLOOR].empty_tiles[:self.item_prop.n_items]
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item_register.spawn_items(empty_tiles)
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inventories = Inventories(self._obs_shape, self._level_shape)
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inventories.spawn_inventories(self[c.AGENT], self.item_prop.max_agent_inventory_capacity)
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super_entities.update({c.DROP_OFF: drop_offs, c.ITEM: item_register, c.INVENTORY: inventories})
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return super_entities
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def per_agent_raw_observations_hook(self, agent) -> Dict[str, np.typing.ArrayLike]:
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additional_raw_observations = super().per_agent_raw_observations_hook(agent)
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additional_raw_observations.update({c.INVENTORY: self[c.INVENTORY].by_entity(agent).as_array()})
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return additional_raw_observations
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def observations_hook(self) -> Dict[str, np.typing.ArrayLike]:
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additional_observations = super().observations_hook()
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additional_observations.update({c.ITEM: self[c.ITEM].as_array()})
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additional_observations.update({c.DROP_OFF: self[c.DROP_OFF].as_array()})
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return additional_observations
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def do_item_action(self, agent: Agent) -> (dict, dict):
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inventory = self[c.INVENTORY].by_entity(agent)
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if drop_off := self[c.DROP_OFF].by_pos(agent.pos):
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if inventory:
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valid = drop_off.place_item(inventory.pop())
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else:
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valid = c.NOT_VALID
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if valid:
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self.print(f'{agent.name} just dropped of an item at {drop_off.pos}.')
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info_dict = {f'{agent.name}_DROPOFF_VALID': 1, 'DROPOFF_VALID': 1}
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else:
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self.print(f'{agent.name} just tried to drop off at {agent.pos}, but failed.')
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info_dict = {f'{agent.name}_DROPOFF_FAIL': 1, 'DROPOFF_FAIL': 1}
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reward = dict(value=self.rewards_item.DROP_OFF_VALID if valid else self.rewards_item.DROP_OFF_FAIL,
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reason=a.ITEM_ACTION, info=info_dict)
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return valid, reward
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elif item := self[c.ITEM].by_pos(agent.pos):
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item.change_parent_collection(inventory)
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item.set_tile_to(self._NO_POS_TILE)
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self.print(f'{agent.name} just picked up an item at {agent.pos}')
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info_dict = {f'{agent.name}_{a.ITEM_ACTION}_VALID': 1, f'{a.ITEM_ACTION}_VALID': 1}
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return c.VALID, dict(value=self.rewards_item.PICK_UP_VALID, reason=a.ITEM_ACTION, info=info_dict)
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else:
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self.print(f'{agent.name} just tried to pick up an item at {agent.pos}, but failed.')
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info_dict = {f'{agent.name}_{a.ITEM_ACTION}_FAIL': 1, f'{a.ITEM_ACTION}_FAIL': 1}
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return c.NOT_VALID, dict(value=self.rewards_item.PICK_UP_FAIL, reason=a.ITEM_ACTION, info=info_dict)
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def do_additional_actions(self, agent: Agent, action: Action) -> (dict, dict):
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# noinspection PyUnresolvedReferences
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action_result = super().do_additional_actions(agent, action)
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if action_result is None:
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if action == a.ITEM_ACTION:
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action_result = self.do_item_action(agent)
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return action_result
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else:
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return None
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else:
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return action_result
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def reset_hook(self) -> None:
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# noinspection PyUnresolvedReferences
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super().reset_hook()
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self._next_item_spawn = self.item_prop.spawn_frequency
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self.trigger_item_spawn()
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def trigger_item_spawn(self):
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if item_to_spawns := max(0, (self.item_prop.n_items - len(self[c.ITEM]))):
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empty_tiles = self[c.FLOOR].empty_tiles[:item_to_spawns]
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self[c.ITEM].spawn_items(empty_tiles)
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self._next_item_spawn = self.item_prop.spawn_frequency
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self.print(f'{item_to_spawns} new items have been spawned; next spawn in {self._next_item_spawn}')
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else:
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self.print('No Items are spawning, limit is reached.')
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def step_hook(self) -> (List[dict], dict):
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# noinspection PyUnresolvedReferences
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super_reward_info = super().step_hook()
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for item in list(self[c.ITEM].values()):
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if item.auto_despawn >= 1:
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item.set_auto_despawn(item.auto_despawn-1)
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elif not item.auto_despawn:
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self[c.ITEM].delete_env_object(item)
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else:
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pass
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if not self._next_item_spawn:
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self.trigger_item_spawn()
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else:
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self._next_item_spawn = max(0, self._next_item_spawn-1)
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return super_reward_info
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def render_assets_hook(self, mode='human'):
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# noinspection PyUnresolvedReferences
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additional_assets = super().render_assets_hook()
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items = [RenderEntity(c.ITEM, item.tile.pos) for item in self[c.ITEM] if item.tile != self._NO_POS_TILE]
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additional_assets.extend(items)
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drop_offs = [RenderEntity(c.DROP_OFF, drop_off.tile.pos) for drop_off in self[c.DROP_OFF]]
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additional_assets.extend(drop_offs)
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return additional_assets
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if __name__ == '__main__':
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from environments.utility_classes import AgentRenderOptions as aro, ObservationProperties
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render = True
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item_probs = ItemProperties(n_items=30, n_drop_off_locations=6)
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obs_props = ObservationProperties(render_agents=aro.SEPERATE, omit_agent_self=True, pomdp_r=2)
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move_props = {'allow_square_movement': True,
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'allow_diagonal_movement': True,
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'allow_no_op': False}
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factory = ItemFactory(n_agents=6, done_at_collision=False,
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level_name='rooms', max_steps=400,
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obs_prop=obs_props, parse_doors=True,
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record_episodes=True, verbose=True,
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mv_prop=move_props, item_prop=item_probs
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)
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# noinspection DuplicatedCode
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n_actions = factory.action_space.n - 1
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obs_space = factory.observation_space
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obs_space_named = factory.named_observation_space
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for epoch in range(400):
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random_actions = [[random.randint(0, n_actions) for _
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in range(factory.n_agents)] for _
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in range(factory.max_steps + 1)]
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env_state = factory.reset()
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rwrd = 0
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for agent_i_action in random_actions:
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env_state, step_r, done_bool, info_obj = factory.step(agent_i_action)
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rwrd += step_r
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if render:
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factory.render()
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if done_bool:
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break
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print(f'Factory run {epoch} done, reward is:\n {rwrd}')
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pass
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