lih403474-byte opened a new issue, #19971:
URL: https://github.com/apache/tvm/issues/19971
### Expected behavior
The ONNX model should be successfully imported by the TVM Relax ONNX
frontend.
The model contains dynamic shape calculation subgraphs before `Reshape`.
The shape graph operators, such as:
- `Shape`
- `Gather`
- `Slice`
- `Unsqueeze`
- `Concat`
should be converted into Relax `ShapeExpr` / `PrimValue` instead of normal
tensor operations.
---
### Actual behavior
TVM Relax ONNX frontend fails during import.
Error:
```
InternalError:
Concat expects all input tensors to have same ndim.
However, the input contains tensors with ndim 3 and 2
```
The failure happens during `Concat` conversion.
The problematic `Concat` belongs to a dynamic shape construction subgraph,
but it is handled as a normal tensor concatenation operation.
---
### Environment
- TVM: `0.25.dev0` (local source tree)
- PyTorch: `2.12.0+cu130`
- Python: `3.10.20`
- OS: `Ubuntu 22.04 64-bit`
- Target: `llvm` (CPU)
- Frontend: from tvm.relax.frontend.onnx import from_onnx
---
### Steps to reproduce
Load an ONNX model containing a dynamic reshape pattern:
```python
import onnx
from tvm.relax.frontend.onnx import from_onnx
model = onnx.load("model.onnx")
mod = from_onnx(model)
```
The import fails during `Concat` conversion:
```python
InternalError(
'Concat expects all input tensors to have same ndim.
However, the input contains tensors with ndim 3 and 2'
)
```
---
### Analysis
The failure occurs for ONNX graphs containing dynamic reshape patterns.
Example pattern:
```
Input tensor
|
Shape
|
Gather / Slice
|
Unsqueeze
|
Concat
|
Reshape
```
The ONNX graph generates the target shape of `Reshape` dynamically.
These intermediate operators do not perform tensor computation. They only
construct the shape argument required by `Reshape`.
The expected Relax representation is:
```
ShapeExpr
|
PrimValue
|
ShapeExpr
|
Concat
|
ShapeExpr
```
The current issue is that the shape graph `Concat` is incorrectly handled as
tensor `Concat`, causing the dimension mismatch error.
---
### Root cause
The same ONNX operators can appear in both tensor computation graphs and
shape computation graphs.
Tensor graph example:
```
Conv
|
Concat
|
Relu
```
Shape graph example:
```
Shape
|
Gather
|
Unsqueeze
|
Concat
|
Reshape
```
The frontend needs data-flow based detection to distinguish these two cases.
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