def update_data(self, binding_dict):
self.graph.update_binding(binding_dict)
# self.data.update_data(self.graph, self.attr_encoder)
x = self.attr_encoder.get_embedding(self.graph.get_nodes())
edge_index, edge_types = self.graph.get_edge_info()
# edge_attrs = torch.tensor(self.attr_encoder.get_embedding(edge_types))
edge_attr = torch.tensor(edge_types)
edge_index = torch.tensor(edge_index)
x = torch.tensor(x)
batch = torch.zeros(x.shape[0], dtype=torch.int64)
# print(f"previous edge num: {len(self.data.edge_attr)}")
self.data = Data(x=x,
y=self.data.y,
edge_index=edge_index,
edge_attr=edge_attr)
self.data.batch = batch
def update_data(self, binding_dict):
self.graph.update_binding(binding_dict)
# self.data.update_data(self.graph, self.attr_encoder)
x = self.attr_encoder.get_embedding(
[node.name for node in self.graph.nodes])
edge_index, edge_types = self.graph.get_edge_info()
# edge_attrs = torch.tensor(self.attr_encoder.get_embedding(edge_types))
edge_attr = torch.tensor(edge_types, dtype=torch.float)
edge_index = torch.tensor(edge_index)
x = torch.tensor(x)
batch = self.data.batch
# print(f"previous edge num: {len(self.data.edge_attr)}")
self.data = Data(x=x,
y=self.data.y,
edge_index=edge_index,
edge_attr=edge_attr)
self.data.batch = batch
if __name__ == "__main__":
# load the data
data_dir = os.path.abspath(__file__ + "../../../data")
root = os.path.abspath(os.path.join(data_dir, "./processed_dataset"))
config = get_config()
attr_encoder = Encoder(config)
scenes_path = os.path.abspath(
os.path.join(data_dir,
f"./processed_dataset/raw/{cmd_args.scene_file_name}"))
with open(scenes_path, 'r') as scenes_file:
scenes = json.load(scenes_file)
# construct a mini example
target_id = 0
graph = Graph(config, scenes[0], target_id)
x = attr_encoder.get_embedding([node.name for node in graph.nodes])
edge_index, edge_types = graph.get_edge_info()
edge_attrs = torch.tensor(attr_encoder.get_embedding(edge_types))
data_point = Data(x=x,
edge_index=edge_index,
edge_attr=edge_attrs,
y=target_id)
# construct an env
env = Env(data_point, graph, config, attr_encoder)
if __name__ == "__main__":
# load the data
data_dir = os.path.abspath(__file__ + "../../../../data")
root = os.path.abspath(os.path.join(data_dir, "./processed_dataset"))
config = get_config()
attr_encoder = Encoder(config)
scenes_path = os.path.abspath(
os.path.join(data_dir,
f"./processed_dataset/raw/{cmd_args.scene_file_name}"))
with open(scenes_path, 'r') as scenes_file:
scenes = json.load(scenes_file)
# construct a mini example
target_id = 0
graph = Graph(config, scenes[0], target_id)
x = attr_encoder.get_embedding(graph.get_nodes())
edge_index, edge_types = graph.get_edge_info()
edge_attrs = attr_encoder.get_embedding(
[f"edge_{tp}" for tp in edge_types])
data_point = Data(torch.tensor(x), torch.tensor(edge_index),
torch.tensor(edge_attrs), graph.target_id)
# construct an env
env = Env(data_point, graph, config, attr_encoder)
# env.reset(graph)