AttributeError: partially initialized module 'torch_geometric' has no attribute 'typing' (most likely due to a circular import) Output is truncated

[kaviravipuvi]

😵 Describe the installation problem

AttributeError Traceback (most recent call last)
Cell In[21], line 3
1 import torch
2 import torch.nn as nn
----> 3 import torch_geometric
5 from torch_geometric.nn import MessagePassing
7 print("torch_geometric and MessagePassing imported successfully!")

File c:\Users\HILCPS\anaconda3\envs\GPU\Lib\site-packages\torch_geometric_init_.py:13
11 import torch_geometric.loader
12 import torch_geometric.transforms
---> 13 import torch_geometric.datasets
14 import torch_geometric.nn
15 import torch_geometric.explain

File c:\Users\HILCPS\anaconda3\envs\GPU\Lib\site-packages\torch_geometric\datasets_init_.py:101
99 from .sbm_dataset import RandomPartitionGraphDataset
100 from .mixhop_synthetic_dataset import MixHopSyntheticDataset
--> 101 from .explainer_dataset import ExplainerDataset
102 from .infection_dataset import InfectionDataset
103 from .ba2motif_dataset import BA2MotifDataset

File c:\Users\HILCPS\anaconda3\envs\GPU\Lib\site-packages\torch_geometric\datasets\explainer_dataset.py:9
7 from torch_geometric.datasets.graph_generator import GraphGenerator
8 from torch_geometric.datasets.motif_generator import MotifGenerator
----> 9 from torch_geometric.explain import Explanation
12 class ExplainerDataset(InMemoryDataset):
13 r"""Generates a synthetic dataset for evaluating explainabilty algorithms,
14 as described in the "GNNExplainer: Generating Explanations for Graph [15](file:///C:/Users/HILCPS/anaconda3/envs/GPU/Lib/site-packages/torch_geometric/datasets/explainer_dataset.py:15) Neural Networks" <[https://arxiv.org/abs/1903.03894>](https://arxiv.org/abs/1903.03894%3E%60) paper.
(...)
66 (default: :obj:None)
67 """

File c:\Users\HILCPS\anaconda3\envs\GPU\Lib\site-packages\torch_geometric\explain_init_.py:3
1 from .config import ExplainerConfig, ModelConfig, ThresholdConfig
2 from .explanation import Explanation, HeteroExplanation
----> 3 from .algorithm import * # noqa
4 from .explainer import Explainer
5 from .metric import * # noqa

File c:\Users\HILCPS\anaconda3\envs\GPU\Lib\site-packages\torch_geometric\explain\algorithm_init_.py:1
----> 1 from .base import ExplainerAlgorithm
2 from .dummy_explainer import DummyExplainer
3 from .gnn_explainer import GNNExplainer

File c:\Users\HILCPS\anaconda3\envs\GPU\Lib\site-packages\torch_geometric\explain\algorithm\base.py:14
8 from torch_geometric.explain import Explanation, HeteroExplanation
9 from torch_geometric.explain.config import (
10 ExplainerConfig,
11 ModelConfig,
12 ModelReturnType,
13 )
---> 14 from torch_geometric.nn import MessagePassing
15 from torch_geometric.typing import EdgeType, NodeType
16 from torch_geometric.utils import k_hop_subgraph

File c:\Users\HILCPS\anaconda3\envs\GPU\Lib\site-packages\torch_geometric\nn_init_.py:12
10 from .aggr import * # noqa
11 from .conv import * # noqa
---> 12 from .pool import * # noqa
13 from .glob import * # noqa
14 from .norm import * # noqa

File c:\Users\HILCPS\anaconda3\envs\GPU\Lib\site-packages\torch_geometric\nn\pool_init_.py:10
7 import torch_geometric.typing
8 from torch_geometric.typing import OptTensor, torch_cluster
---> 10 from .asap import ASAPooling
11 from .avg_pool import avg_pool, avg_pool_neighbor_x, avg_pool_x
12 from .edge_pool import EdgePooling

File c:\Users\HILCPS\anaconda3\envs\GPU\Lib\site-packages\torch_geometric\nn\pool\asap.py:9
6 from torch.nn import Linear
8 from torch_geometric.nn import LEConv
----> 9 from torch_geometric.nn.pool.select import SelectTopK
10 from torch_geometric.utils import (
11 add_remaining_self_loops,
12 remove_self_loops,
(...)
17 to_torch_csr_tensor,
18 )
21 class ASAPooling(torch.nn.Module):

File c:\Users\HILCPS\anaconda3\envs\GPU\Lib\site-packages\torch_geometric\nn\pool\select_init_.py:7
1 r"""Node-selection package.
2
3 This package provides classes for node selection methods in graph pooling
4 scenarios.
5 """
----> 7 from .base import Select, SelectOutput
8 from .topk import SelectTopK
10 all = [
11 'Select',
12 'SelectOutput',
13 'SelectTopK',
14 ]

File c:\Users\HILCPS\anaconda3\envs\GPU\Lib\site-packages\torch_geometric\nn\pool\select\base.py:67
63 self.num_clusters = num_clusters
64 self.weight = weight
---> 67 if torch_geometric.typing.WITH_PT113:
68 SelectOutput = torch.jit.script(SelectOutput)
71 class Select(torch.nn.Module):

Environment

• PyG version: 2.5.3
• PyTorch version: 2.4.0
• OS:
• Python version: 3.12
• CUDA/cuDNN version:11.8
• How you installed PyTorch and PyG (conda, pip, source):pip
• Any other relevant information (e.g., version of torch-scatter):