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'''
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This script processes `office_changes.json` to generate a dataset of office manipulation tasks.
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The `CHANGES_DESCRIPTION_FILE` file contains a list of tasks, each with:
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- "name": A natural language description.
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- "init_conditions": An array of conditions to define the starting world state. null if no changes
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- "goal_conditions": An array of conditions that describe the target world state.
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- "actions": A sequence of actions to transition from the initial to the goal state.
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'''
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import json
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import pickle
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from office_graph import office_graph, add_edges
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import copy
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CHANGES_DESCRIPTION_FILE = 'office_changes.json'
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OUT_FILENAME = 'office29.pkl'
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def change_node(node, condition, graph):
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if condition.get("holding", False):
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graph.nodes[node]['holding'] = (condition["holding"]['name'], condition["holding"]['id'])
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if condition["relation"]:
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graph.nodes[node]['related_to'] = (condition["related_to"]["name"], condition["related_to"]["id"])
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graph.nodes[node]['relation'] = condition["relation"]
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if condition["states"]:
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states = condition.get("states", [])
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for state in states:
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if state not in graph.nodes[node]['states']:
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graph.nodes[node]['states'].append(state)
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if state == 'off':
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graph.nodes[node]['states'].remove('on')
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if state == 'on':
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graph.nodes[node]['states'].remove('off')
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if state == 'closed':
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graph.nodes[node]['states'].remove('open')
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if state == 'open':
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graph.nodes[node]['states'].remove('closed')
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if __name__ == "__main__":
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with open(CHANGES_DESCRIPTION_FILE, "r") as file:
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tasks = json.load(file)
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dataset = []
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i=0
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for task in tasks:
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i+=1
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name = task["name"]
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init_graph = copy.deepcopy(office_graph)
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goal_graph = copy.deepcopy(office_graph)
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if task['init_conditions']:
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for condition in task.get("init_conditions", []):
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node = (condition["node"]["name"], condition["node"]["id"])
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change_node(node, condition, init_graph)
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for condition in task.get("goal_conditions", []):
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node = (condition["node"]["name"], condition["node"]["id"])
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change_node(node, condition, goal_graph)
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actions = []
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for action in task.get("actions", []):
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actions.append((action['action'], (action['node']["name"],action['node']["id"])))
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init_graph.remove_edges_from(list(office_graph.edges))
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goal_graph.remove_edges_from(list(office_graph.edges))
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add_edges(init_graph)
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add_edges(goal_graph)
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entity = {
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"id": i,
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"name": name,
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"task": name,
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"init": init_graph,
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"goal": goal_graph,
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"actions": actions,
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}
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dataset.append(entity)
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with open(OUT_FILENAME, "wb") as file:
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pickle.dump(dataset, file)
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