Skip to content

Unsupervised learning with self created dataset #58

@LA11131110128

Description

@LA11131110128

I have tried my dataset on your unsupervised learning framework, which num_of_edge will exceed 10^6.
When I load the data, there is an assertion error.


loading GCC 7.3.1
based on SCL Developer Toolset 7


loading CUDA 10.1 with cuDNN / NCCL
based on cntr cuda:10.1-cudnn7-devel-centos7

/pytorch/aten/src/THC/THCTensorIndex.cu:361: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 1, SrcDim = 1, IdxDim = -2, IndexIsMajor = true]: block: [21,0,0], thread: [6,0,0] Assertion srcIndex < srcSelectDimSize failed.
/pytorch/aten/src/THC/THCTensorIndex.cu:361: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 1, SrcDim = 1, IdxDim = -2, IndexIsMajor = true]: block: [21,0,0], thread: [7,0,0] Assertion srcIndex < srcSelectDimSize failed.
/pytorch/aten/src/THC/THCTensorIndex.cu:361: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 1, SrcDim = 1, IdxDim = -2, IndexIsMajor = true]: block: [21,0,0], thread: [51,0,0] Assertion srcIndex < srcSelectDimSize failed.
/pytorch/aten/src/THC/THCTensorIndex.cu:361: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 1, SrcDim = 1, IdxDim = -2, IndexIsMajor = true]: block: [20,0,0], thread: [88,0,0] Assertion srcIndex < srcSelectDimSize failed.
/pytorch/aten/src/THC/THCTensorIndex.cu:361: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 1, SrcDim = 1, IdxDim = -2, IndexIsMajor = true]: block: [20,0,0], thread: [89,0,0] Assertion srcIndex < srcSelectDimSize failed.
/pytorch/aten/src/THC/THCTensorIndex.cu:361: void indexSelectLargeIndex(TensorInfo<T, IndexType>, TensorInfo<T, IndexType>, TensorInfo<long, IndexType>, int, int, IndexType, IndexType, long) [with T = float, IndexType = unsigned int, DstDim = 1, SrcDim = 1, IdxDim = -2, IndexIsMajor = true]: block: [20,0,0], thread: [90,0,0] Assertion srcIndex < srcSelectDimSize failed.
Processing...
Done!
5264
1

lr: 0.01
num_features: 1
hidden_dim: 32
num_gc_layers: 4

dataset_num_classes: 7
Traceback (most recent call last):
File "gsimclr.py", line 189, in
emb, y = model.encoder.get_embeddings(dataloader_eval)
File "/home/u8411596/GraphCL-master/unsupervised_TU/gin.py", line 83, in get_embeddings
x, _ = self.forward(x, edge_index, batch)
File "/home/u8411596/GraphCL-master/unsupervised_TU/gin.py", line 56, in forward
x = F.relu(self.convs[i](x, edge_index))
File "/home/u8411596/.conda/envs/py36/lib/python3.6/site-packages/torch/nn/modules/module.py", line 532, in call
result = self.forward(*input, **kwargs)
File "/home/u8411596/.conda/envs/py36/lib/python3.6/site-packages/torch_geometric/nn/conv/gin_conv.py", line 67, in forward
out += (1 + self.eps) * x_r
RuntimeError: CUDA error: device-side assert triggered

I am wondering the learning framework may have length of data limitation and want some suggestion from you to solve this problem.
Thank you!

Metadata

Metadata

Assignees

No one assigned

    Labels

    No labels
    No labels

    Projects

    No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions