tinywisdom opened a new issue, #18648:
URL: https://github.com/apache/tvm/issues/18648
### Summary
When using the TVM Relax Torch frontend to import a `torch.export.export`ed
program that involves a `torch.sparse_csr_tensor` registered as a buffer,
`from_exported_program` crashes with a C++ `c10::Error`:
> `layout_impl is only implemented for TensorImpl subclasses.`
`torch.export.export` itself succeeds. The crash happens during
`from_exported_program(ep)`.
---
### Environment
```text
OS: Linux x86_64
PyTorch: 2.9.0+cu128
TVM: 0.22.0
Python: 3.10.x
```
---
### Minimal Reproduction
```python
# repro_92022_export_tvm_frontend.py
import torch
import torch.nn as nn
import tvm
from tvm.relax.frontend.torch import from_exported_program
print("torch version:", torch.__version__)
print("tvm version:", getattr(tvm, "__version__", "unknown"))
class MyModel(nn.Module):
def __init__(self):
super().__init__()
crow_indices = torch.tensor([0, 1, 2], dtype=torch.int64)
col_indices = torch.tensor([0, 1], dtype=torch.int64)
values = torch.tensor([1.0, 1.0], dtype=torch.float32,
requires_grad=True)
csr_tensor = torch.sparse_csr_tensor(
crow_indices, col_indices, values, dtype=torch.float32
)
# Register sparse CSR tensor as a buffer
self.register_buffer("csr_tensor", csr_tensor)
# Explicitly enable grad as well
self.csr_tensor.requires_grad_(True)
def forward(self, x):
# Convert buffer to sparse CSR layout again
csr2 = self.csr_tensor.to_sparse(layout=torch.sparse_csr)
y = torch.matmul(csr2, x)
return y.sum()
def GetInput():
return torch.ones((2, 1), dtype=torch.float32)
def main():
model = MyModel().to("cpu").eval()
x = GetInput().to("cpu")
print("Start torch.export.export ...")
ep = torch.export.export(model, (x,))
print("torch.export.export done.")
print("Start from_exported_program ...")
ir_mod = from_exported_program(ep)
print("from_exported_program done.")
print(ir_mod)
if __name__ == "__main__":
main()
```
---
### Actual Behavior
Output on my machine:
```text
torch version: 2.9.0+cu128
tvm version: 0.22.0
.../SparseCsrTensorImpl.cpp:53: Sparse CSR tensor support is in beta state...
Start torch.export.export ...
torch.export.export done.
Start from_exported_program ...
terminate called after throwing an instance of 'c10::Error'
what(): layout_impl is only implemented for TensorImpl subclasses.
Exception raised from layout_impl at /pytorch/c10/core/TensorImpl.h:1094
(most recent call first):
frame #0: c10::Error::Error(...)
frame #1: c10::detail::torchCheckFail(...)
frame #2: ...
frame #3: torch::autograd::InputMetadata::InputMetadata(at::Tensor const&) +
...
frame #4: ...
<libtorch / libtorch_python frames omitted>
...
Aborted (core dumped)
```
`torch.export.export` completes successfully; the abort occurs only when
calling `from_exported_program(ep)`.
### Triage
Please refer to the list of label tags
[here](https://github.com/apache/tvm/wiki/Issue-Triage-Labels) to find the
relevant tags and add them below in a bullet format (example below).
* needs-triage
* bug
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