text-graph-generalization

Code for our paper Compositional Generalization with Grounded Language Models
git clone https://esimon.eu/repos/text-graph-generalization.git
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utils.py (605B)

      1 import networkx as nx
      2 import torch
      3 import numpy as np
      4 import random
      5 
      6 def load_graph_from_path(path: str) -> nx.Graph:
      7     '''
      8     Load a graph from a given path.
      9 
     10     Args:
     11         path (str): The path to the graph file.
     12 
     13     Returns:
     14         G (networkx.Graph): The loaded graph.
     15 
     16     '''
     17     G = nx.read_graphml(f'{path}')
     18     return G
     19 
     20 def set_seed(seed: int) -> None:
     21     torch.manual_seed(seed)
     22     torch.cuda.manual_seed(seed)
     23     torch.cuda.manual_seed_all(seed)
     24     np.random.seed(seed)
     25     random.seed(seed)
     26     torch.backends.cudnn.benchmark = False
     27     torch.backends.cudnn.deterministic = True