Sparse Tensor not working for `torch.cat`
Labels: module: sparse, triaged

### 🐛 Describe the bug

cc: @rusty1s 
these examples use `collate` which uses cat on torch native sparse tensors:
https://github.com/pyg-team/pytorch_geometric/blob/master/examples/egc.py
https://github.com/pyg-team/pytorch_geometric/blob/master/examples/gcn2_ppi.py
https://github.com/pyg-team/pytorch_geometric/blob/master/examples/multi_gpu/distributed_batching.py
repro:
`cd /opt/pyg; pip uninstall -y torch-geometric torch-scatter torch-sparse torch-spline-conv torch-cluster; rm -rf pytorch_geometric; git clone -b fix-for-collate https://github.com/pyg-team/pytorch_geometric.git; cd /opt/pyg/pytorch_geometric; pip install .; python3 examples/egc.py; python3 examples/gcn2_ppi.py`

error:
```
Traceback (most recent call last):
  File "examples/gcn2_ppi.py", line 93, in <module>
    loss = train()
  File "examples/gcn2_ppi.py", line 67, in train
    for data in train_loader:
  File "/usr/local/lib/python3.8/dist-packages/torch/utils/data/dataloader.py", line 635, in __next__
    data = self._next_data()
  File "/usr/local/lib/python3.8/dist-packages/torch/utils/data/dataloader.py", line 679, in _next_data
    data = self._dataset_fetcher.fetch(index)  # may raise StopIteration
  File "/usr/local/lib/python3.8/dist-packages/torch/utils/data/_utils/fetch.py", line 61, in fetch
    return self.collate_fn(data)
  File "/usr/local/lib/python3.8/dist-packages/torch_geometric/loader/dataloader.py", line 20, in __call__
    return Batch.from_data_list(batch, self.follow_batch,
  File "/usr/local/lib/python3.8/dist-packages/torch_geometric/data/batch.py", line 76, in from_data_list
    batch, slice_dict, inc_dict = collate(
  File "/usr/local/lib/python3.8/dist-packages/torch_geometric/data/collate.py", line 85, in collate
    value, slices, incs = _collate(attr, values, data_list, stores,
  File "/usr/local/lib/python3.8/dist-packages/torch_geometric/data/collate.py", line 178, in _collate
    value = torch.cat(values, dim=cat_dim)
RuntimeError: Sparse CSR tensors do not have is_contiguous
```


### Versions

root@979d4b259838:/opt/pyg/pytorch_geometric# python collect_env.py

Collecting environment information...
PyTorch version: 2.0.0a0+1767026
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.5 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
Clang version: Could not collect
CMake version: version 3.24.1
Libc version: glibc-2.31

Python version: 3.8.10 (default, Nov 14 2022, 12:59:47)  [GCC 9.4.0] (64-bit runtime)
Python platform: Linux-4.15.0-142-generic-x86_64-with-glibc2.29
Is CUDA available: True
CUDA runtime version: 12.1.66
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: 
GPU 0: NVIDIA A40
GPU 1: NVIDIA A40
GPU 2: NVIDIA A40
GPU 3: NVIDIA A40

Nvidia driver version: 515.65.01
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.8.1
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.8.1
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.8.1
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.8.1
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.8.1
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.8.1
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.8.1
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture:                    x86_64
CPU op-mode(s):                  32-bit, 64-bit
Byte Order:                      Little Endian
Address sizes:                   43 bits physical, 48 bits virtual
CPU(s):                          32
On-line CPU(s) list:             0-31
Thread(s) per core:              2
Core(s) per socket:              16
Socket(s):                       1
NUMA node(s):                    1
Vendor ID:                       AuthenticAMD
CPU family:                      23
Model:                           49
Model name:                      AMD EPYC 7282 16-Core Processor
Stepping:                        0
Frequency boost:                 enabled
CPU MHz:                         1493.554
CPU max MHz:                     2800.0000
CPU min MHz:                     1500.0000
BogoMIPS:                        5589.38
Virtualization:                  AMD-V
L1d cache:                       512 KiB
L1i cache:                       512 KiB
L2 cache:                        8 MiB
L3 cache:                        64 MiB
NUMA node0 CPU(s):               0-31
Vulnerability Itlb multihit:     Not affected
Vulnerability L1tf:              Not affected
Vulnerability Mds:               Not affected
Vulnerability Meltdown:          Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1:        Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2:        Mitigation; Full AMD retpoline, IBPB conditional, IBRS_FW, STIBP conditional, RSB filling
Vulnerability Srbds:             Not affected
Vulnerability Tsx async abort:   Not affected
Flags:                           fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology nonstop_tsc cpuid extd_apicid aperfmperf pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate sme ssbd ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif umip rdpid overflow_recov succor smca

Versions of relevant libraries:
[pip3] flake8==5.0.3
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.22.3
[pip3] pytorch-quantization==2.1.2
[pip3] torch==2.0.0a0+1767026
[pip3] torch_geometric==2.4.0
[pip3] torch-tensorrt==1.4.0.dev0
[pip3] torchmetrics==0.9.3
[pip3] torchtext==0.13.0a0+fae8e8c
[pip3] torchvision==0.15.0a0
[pip3] triton==2.0.0
[pip3] tritonclient==2.29.0
[conda] Could not collect


cc @alexsamardzic @nikitaved @pearu @cpuhrsch @amjames @bhosmer