import torch
from torch_geometric.data import Data
from torch_geometric.utils.convert import to_dgl
# 1nd example zero edge
data = Data()
data['x'] = torch.tensor([[0, 1, 2], [2,3,4]])
data.validate()
to_dgl(data)
# AttributeError: 'GlobalStorage' object has no attribute 'adj_t'
# 2nd example, isolated nodes
data = Data()
data['x'] = torch.tensor([[0, 1, 2], [2,3,4]])
data['edge_index'] = torch.tensor([[0],[0]])
data.validate()
to_dgl(data)`
# DGLError: Expect number of features to match number of nodes (len(u)). Got 2 and 1 instead.
The function initialized the dgl graph using data from the edges first. Hence any isolated nodes afterwards will cause node number mismatch.
Versions
Collecting environment information...
PyTorch version: 2.2.2+cpu
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A
OS: Microsoft Windows 10 Enterprise
GCC version: Could not collect
Clang version: Could not collect
CMake version: Could not collect
Libc version: N/A
Python version: 3.9.19 | packaged by conda-forge | (main, Mar 20 2024, 12:38:46) [MSC v.1929 64 bit (AMD64)] (64-bit runtime)
Python platform: Windows-10-10.0.19045-SP0
Is CUDA available: False
CUDA runtime version: No CUDA
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
🐛 Describe the bug
The function initialized the dgl graph using data from the edges first. Hence any isolated nodes afterwards will cause node number mismatch.
Versions
Collecting environment information... PyTorch version: 2.2.2+cpu Is debug build: False CUDA used to build PyTorch: None ROCM used to build PyTorch: N/A
OS: Microsoft Windows 10 Enterprise GCC version: Could not collect Clang version: Could not collect CMake version: Could not collect Libc version: N/A
Python version: 3.9.19 | packaged by conda-forge | (main, Mar 20 2024, 12:38:46) [MSC v.1929 64 bit (AMD64)] (64-bit runtime) Python platform: Windows-10-10.0.19045-SP0 Is CUDA available: False CUDA runtime version: No CUDA CUDA_MODULE_LOADING set to: N/A GPU models and configuration: No CUDA Nvidia driver version: No CUDA cuDNN version: No CUDA HIP runtime version: N/A MIOpen runtime version: N/A Is XNNPACK available: True
CPU:
Revision=
Versions of relevant libraries: [pip3] mypy-extensions==1.0.0 [pip3] numpy==1.26.4 [pip3] numpydoc==1.7.0 [pip3] torch==2.2.2 [pip3] torch_geometric==2.5.2 [pip3] torchdata==0.7.1 [conda] libblas 3.9.0 22_win64_mkl conda-forge [conda] libcblas 3.9.0 22_win64_mkl conda-forge [conda] liblapack 3.9.0 22_win64_mkl conda-forge [conda] mkl 2024.1.0 h66d3029_692 conda-forge [conda] numpy 1.26.4 py39hddb5d58_0 conda-forge [conda] numpydoc 1.7.0 pypi_0 pypi [conda] torch 2.2.2 pypi_0 pypi [conda] torch-geometric 2.5.2 pypi_0 pypi [conda] torchdata 0.7.1 pypi_0 pypi