219 lines
7.2 KiB
Python
219 lines
7.2 KiB
Python
import logging
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import threading
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import numpy as np
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import gym
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class MinecraftBase(gym.Env):
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_LOCK = threading.Lock()
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def __init__(
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self, actions,
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repeat=1,
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size=(64, 64),
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break_speed=100.0,
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gamma=10.0,
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sticky_attack=30,
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sticky_jump=10,
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pitch_limit=(-60, 60),
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logs=True,
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):
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if logs:
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logging.basicConfig(level=logging.DEBUG)
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self._repeat = repeat
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self._size = size
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if break_speed != 1.0:
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sticky_attack = 0
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# Make env
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with self._LOCK:
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from .import minecraft_minerl
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self._env = minecraft_minerl.MineRLEnv(size, break_speed, gamma).make()
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self._inventory = {}
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# Observations
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self._inv_keys = [
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k for k in self._flatten(self._env.observation_space.spaces) if k.startswith('inventory/')
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if k != 'inventory/log2']
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self._step = 0
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self._max_inventory = None
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self._equip_enum = self._env.observation_space[
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'equipped_items']['mainhand']['type'].values.tolist()
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# Actions
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self._noop_action = minecraft_minerl.NOOP_ACTION
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actions = self._insert_defaults(actions)
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self._action_names = tuple(actions.keys())
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self._action_values = tuple(actions.values())
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message = f'Minecraft action space ({len(self._action_values)}):'
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print(message, ', '.join(self._action_names))
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self._sticky_attack_length = sticky_attack
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self._sticky_attack_counter = 0
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self._sticky_jump_length = sticky_jump
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self._sticky_jump_counter = 0
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self._pitch_limit = pitch_limit
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self._pitch = 0
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@property
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def observation_space(self):
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return gym.spaces.Dict(
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{
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'image': gym.spaces.Box(0, 255, self._size + (3,), np.uint8),
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'inventory': gym.spaces.Box(-np.inf, np.inf, (len(self._inv_keys),), dtype=np.float32),
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'inventory_max': gym.spaces.Box(-np.inf, np.inf, (len(self._inv_keys),), dtype=np.float32),
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'equipped': gym.spaces.Box(-np.inf, np.inf, (len(self._equip_enum),), dtype=np.float32),
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'reward': gym.spaces.Box(-np.inf, np.inf, (1,), dtype=np.float32),
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'health': gym.spaces.Box(-np.inf, np.inf, (1,), dtype=np.float32),
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'hunger': gym.spaces.Box(-np.inf, np.inf, (1,), dtype=np.float32),
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'breath': gym.spaces.Box(-np.inf, np.inf, (1,), dtype=np.float32),
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'is_first': gym.spaces.Box(-np.inf, np.inf, (1,), dtype=np.uint8),
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'is_last': gym.spaces.Box(-np.inf, np.inf, (1,), dtype=np.uint8),
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'is_terminal': gym.spaces.Box(-np.inf, np.inf, (1,), dtype=np.uint8),
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**{f'log_{k}': gym.spaces.Box(-np.inf, np.inf, (1,), dtype=np.int64) for k in self._inv_keys},
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'log_player_pos': gym.spaces.Box(-np.inf, np.inf, (3,), dtype=np.float32),
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}
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)
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@property
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def action_space(self):
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space = gym.spaces.discrete.Discrete(len(self._action_values))
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space.discrete = True
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return space
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def step(self, action):
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action = action.copy()
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print(self._step, action)
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action = self._action_values[action]
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action = self._action(action)
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following = self._noop_action.copy()
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for key in ('attack', 'forward', 'back', 'left', 'right'):
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following[key] = action[key]
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for act in [action] + ([following] * (self._repeat - 1)):
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obs, reward, done, info = self._env.step(act)
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if 'error' in info:
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done = True
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break
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obs['is_first'] = False
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obs['is_last'] = bool(done)
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obs['is_terminal'] = bool(info.get('is_terminal', done))
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obs = self._obs(obs)
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self._step += 1
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assert 'pov' not in obs, list(obs.keys())
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return obs, reward, done, info
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@property
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def inventory(self):
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return self._inventory
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def reset(self):
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# inventory will be added in _obs
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self._inventory = {}
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self._max_inventory = None
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with self._LOCK:
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obs = self._env.reset()
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obs['is_first'] = True
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obs['is_last'] = False
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obs['is_terminal'] = False
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obs = self._obs(obs)
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self._step = 0
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self._sticky_attack_counter = 0
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self._sticky_jump_counter = 0
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self._pitch = 0
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return obs
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def _obs(self, obs):
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obs = self._flatten(obs)
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obs['inventory/log'] += obs.pop('inventory/log2')
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self._inventory = {
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k.split('/', 1)[1]: obs[k] for k in self._inv_keys
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if k != 'inventory/air'}
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inventory = np.array([obs[k] for k in self._inv_keys], np.float32)
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if self._max_inventory is None:
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self._max_inventory = inventory
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else:
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self._max_inventory = np.maximum(self._max_inventory, inventory)
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index = self._equip_enum.index(obs['equipped_items/mainhand/type'])
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equipped = np.zeros(len(self._equip_enum), np.float32)
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equipped[index] = 1.0
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player_x = obs['location_stats/xpos']
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player_y = obs['location_stats/ypos']
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player_z = obs['location_stats/zpos']
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obs = {
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'image': obs['pov'],
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'inventory': inventory,
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'inventory_max': self._max_inventory.copy(),
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'equipped': equipped,
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'health': np.float32(obs['life_stats/life'] / 20),
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'hunger': np.float32(obs['life_stats/food'] / 20),
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'breath': np.float32(obs['life_stats/air'] / 300),
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'reward': 0.0,
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'is_first': obs['is_first'],
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'is_last': obs['is_last'],
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'is_terminal': obs['is_terminal'],
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**{f'log_{k}': np.int64(obs[k]) for k in self._inv_keys},
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'log_player_pos': np.array([player_x, player_y, player_z], np.float32),
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}
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for key, value in obs.items():
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space = self.observation_space[key]
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if not isinstance(value, np.ndarray):
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value = np.array(value)
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assert (key, value, value.dtype, value.shape, space)
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return obs
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def _action(self, action):
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if self._sticky_attack_length:
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if action['attack']:
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self._sticky_attack_counter = self._sticky_attack_length
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if self._sticky_attack_counter > 0:
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action['attack'] = 1
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action['jump'] = 0
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self._sticky_attack_counter -= 1
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if self._sticky_jump_length:
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if action['jump']:
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self._sticky_jump_counter = self._sticky_jump_length
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if self._sticky_jump_counter > 0:
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action['jump'] = 1
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action['forward'] = 1
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self._sticky_jump_counter -= 1
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if self._pitch_limit and action['camera'][0]:
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lo, hi = self._pitch_limit
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if not (lo <= self._pitch + action['camera'][0] <= hi):
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action['camera'] = (0, action['camera'][1])
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self._pitch += action['camera'][0]
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return action
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def _insert_defaults(self, actions):
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actions = {name: action.copy() for name, action in actions.items()}
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for key, default in self._noop_action.items():
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for action in actions.values():
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if key not in action:
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action[key] = default
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return actions
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def _flatten(self, nest, prefix=None):
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result = {}
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for key, value in nest.items():
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key = prefix + '/' + key if prefix else key
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if isinstance(value, gym.spaces.Dict):
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value = value.spaces
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if isinstance(value, dict):
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result.update(self._flatten(value, key))
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else:
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result[key] = value
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return result
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def _unflatten(self, flat):
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result = {}
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for key, value in flat.items():
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parts = key.split('/')
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node = result
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for part in parts[:-1]:
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if part not in node:
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node[part] = {}
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node = node[part]
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node[parts[-1]] = value
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return result |