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- from gym_minigrid.minigrid import *
- from gym_minigrid.register import register
- class PutNearEnv(MiniGridEnv):
- """
- Environment in which the agent is instructed to place an object near
- another object through a natural language string.
- """
- def __init__(
- self,
- size=6,
- numObjs=2
- ):
- self.numObjs = numObjs
- super().__init__(gridSize=size, maxSteps=5*size)
- self.reward_range = (0, 1)
- def _genGrid(self, width, height):
- self.grid = Grid(width, height)
- # Generate the surrounding walls
- self.grid.horzWall(0, 0)
- self.grid.horzWall(0, height-1)
- self.grid.vertWall(0, 0)
- self.grid.vertWall(width-1, 0)
- # Types and colors of objects we can generate
- types = ['key', 'ball']
- colors = list(COLORS.keys())
- objs = []
- objPos = []
- def nearObj(p1):
- for p2 in objPos:
- dx = p1[0] - p2[0]
- dy = p1[1] - p2[1]
- if abs(dx) <= 1 and abs(dy) <= 1:
- return True
- return False
- # Until we have generated all the objects
- while len(objs) < self.numObjs:
- objType = self._randElem(types)
- objColor = self._randElem(colors)
- # If this object already exists, try again
- if (objType, objColor) in objs:
- continue
- if objType == 'key':
- obj = Key(objColor)
- elif objType == 'ball':
- obj = Ball(objColor)
- elif objType == 'box':
- obj = Box(objColor)
- while True:
- pos = (
- self._randInt(1, width - 1),
- self._randInt(1, height - 1)
- )
- if nearObj(pos):
- continue
- if pos == self.startPos:
- continue
- self.grid.set(*pos, obj)
- break
- objs.append((objType, objColor))
- objPos.append(pos)
- # Choose a random object to be moved
- objIdx = self._randInt(0, len(objs))
- self.moveType, self.moveColor = objs[objIdx]
- self.movePos = objPos[objIdx]
- # Choose a target object (to put the first object next to)
- while True:
- targetIdx = self._randInt(0, len(objs))
- if targetIdx != objIdx:
- break
- self.targetType, self.targetColor = objs[targetIdx]
- self.targetPos = objPos[targetIdx]
- self.mission = 'put the %s %s near the %s %s' % (
- self.moveColor,
- self.moveType,
- self.targetColor,
- self.targetType
- )
- def step(self, action):
- preCarrying = self.carrying
- obs, reward, done, info = MiniGridEnv.step(self, action)
- u, v = self.getDirVec()
- ox, oy = (self.agentPos[0] + u, self.agentPos[1] + v)
- tx, ty = self.targetPos
- # Pickup/drop action
- if action == self.actions.toggle:
- # If we picked up the wrong object, terminate the episode
- if self.carrying:
- if self.carrying.type != self.moveType or self.carrying.color != self.moveColor:
- done = True
- # If successfully dropping an object near the target
- if preCarrying:
- if self.grid.get(ox, oy) is preCarrying:
- if abs(ox - tx) <= 1 and abs(oy - ty) <= 1:
- reward = 1
- done = True
- return obs, reward, done, info
- class PutNear8x8N3(PutNearEnv):
- def __init__(self):
- super().__init__(size=8, numObjs=3)
- register(
- id='MiniGrid-PutNear-6x6-N2-v0',
- entry_point='gym_minigrid.envs:PutNearEnv'
- )
- register(
- id='MiniGrid-PutNear-8x8-N3-v0',
- entry_point='gym_minigrid.envs:PutNear8x8N3'
- )
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