When I use the NeighborLoader object, it appears RuntimeError: pyg::neighbor_sample() Expected a value of type 'Optional[Tensor]' for argument 'edge_weight' but instead found type 'bool'.

[zhangzhangzhanghui]

🐛 Describe the bug

from torch_geometric.datasets import Planetoid
from torch_geometric.loader import NeighborLoader

data = Planetoid('./', name='Cora')[0]

loader = NeighborLoader(
data,
# Sample 30 neighbors for each node for 2 iterations
num_neighbors=[30] * 2,
# Use a batch size of 128 for sampling training nodes
batch_size=128,
input_nodes=data.train_mask,
)

sampled_data = next(iter(loader))
print(sampled_data.batch_size)
This is an example code about the NeighborLoader class in the Pyg documentation.But when I run this code, I encounter the error mentioned in the title
RuntimeError: pyg::neighbor_sample() Expected a value of type 'Optional[Tensor]' for argument 'edge_weight' but instead found type 'bool'.
Position: 7
Value: True
Declaration: pyg::neighbor_sample(Tensor rowptr, Tensor col, Tensor seed, int[] num_neighbors, Tensor? node_time=None, Tensor? edge_time=None, Tensor? seed_time=None, Tensor? edge_weight=None, bool csc=False, bool replace=False, bool directed=True, bool disjoint=False, str temporal_strategy="uniform", bool return_edge_id=True) -> (Tensor, Tensor, Tensor, Tensor?, int[], int[])
Cast error details: Unable to cast True to Tenso

And in my heterogeneous graph experiment, the loader that builds heterogeneous graphs will appear
pyg::hetero_neighbor_sample() Expected a value of type 'Optional[Dict[str, Tensor]]' for argument 'edge_weight_dict' but instead found type 'bool'
But during the debugging process, I was able to find that the edge_ceight of node_stample in the loader object is None

Versions

PyTorch version: 2.4.0+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A

OS: Microsoft Windows 11 专业版 (10.0.22631 64 位)
GCC version: (Rev2, Built by MSYS2 project) 13.2.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: N/A

Python version: 3.10.12 | packaged by conda-forge | (main, Jun 23 2023, 22:34:57) [MSC v.1936 64 bit (AMD64)] (64-bit runtime)
Python platform: Windows-10-10.0.22621-SP0
Is CUDA available: True
CUDA runtime version: 12.2.91
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3090
Nvidia driver version: 560.94
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Name: Intel(R) Core(TM) i9-10900K CPU @ 3.70GHz
Manufacturer: GenuineIntel
Family: 207
Architecture: 9
ProcessorType: 3
DeviceID: CPU0
CurrentClockSpeed: 3601
MaxClockSpeed: 3601
L2CacheSize: 2560
L2CacheSpeed: None
Revision: None

Versions of relevant libraries:
[pip3] easy-torch==1.3.2
[pip3] numpy==1.22.4
[pip3] onnxruntime==1.19.2
[pip3] pytorch-transformers==1.2.0
[pip3] torch==2.4.0+cu121
[pip3] torch_cluster==1.6.3+pt24cu121
[pip3] torch_geometric==2.4.0
[pip3] torch_scatter==2.1.2+pt24cu121
[pip3] torch_sparse==0.6.18+pt24cu121
[pip3] torch_spline_conv==1.2.2+pt24cu121
[pip3] torchaudio==2.4.0+cu121
[pip3] torchinfo==1.8.0
[pip3] torchsummary==1.5.1
[pip3] torchvision==0.19.0+cu121
[conda] blas 1.0 mkl https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
[conda] easy-torch 1.3.2 pypi_0 pypi
[conda] mkl 2023.1.0 h6b88ed4_46358 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
[conda] mkl-service 2.4.0 py310h2bbff1b_1 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
[conda] mkl_fft 1.3.10 py310h827c3e9_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
[conda] mkl_random 1.2.7 py310hc64d2fc_0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
[conda] numpy 1.22.4 pypi_0 pypi
[conda] pytorch-mutex 1.0 cpu https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch
[conda] pytorch-transformers 1.2.0 pypi_0 pypi
[conda] torch 2.4.0+cu121 pypi_0 pypi
[conda] torch-cluster 1.6.3+pt24cu121 pypi_0 pypi
[conda] torch-geometric 2.4.0 pypi_0 pypi
[conda] torch-scatter 2.1.2+pt24cu121 pypi_0 pypi
[conda] torch-sparse 0.6.18+pt24cu121 pypi_0 pypi
[conda] torch-spline-conv 1.2.2+pt24cu121 pypi_0 pypi
[conda] torchaudio 2.4.0+cu121 pypi_0 pypi
[conda] torchinfo 1.8.0 pypi_0 pypi
[conda] torchsummary 1.5.1 pypi_0 pypi
[conda] torchvision 0.19.0+cu121 pypi_0 pypi