mshr-h commented on issue #17546:
URL: https://github.com/apache/tvm/issues/17546#issuecomment-2540695118
Seems like the torch.nn.Linear converter is the root of the problem.
Minimum repro.
```python
import tvm
import torch
import onnx
from tvm import relay
import os
class LinearModel(torch.nn.Module):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.linear = torch.nn.Linear(in_features=128, out_features=512,
bias=True)
def forward(self, x: torch.Tensor) -> torch.Tensor:
return self.linear(x)
def main():
target = "llvm"
dummy_input = torch.randn(2, 56, 56, 128)
linear_model = LinearModel()
# torch frontend
trace_model = torch.jit.trace(linear_model, dummy_input).eval()
mod, params = relay.frontend.from_pytorch(trace_model, [("input",
dummy_input.shape)])
with tvm.transform.PassContext(opt_level=3):
lib = relay.build(mod, target, params=params)
lib.export_library("linear_model_torch.so")
# onnx frontend
torch.onnx.export(
linear_model,
dummy_input,
"linear_model_onnx.onnx",
input_names=["input"],
opset_version=13,
)
onnx_model = onnx.load("linear_model_onnx.onnx")
mod, params = relay.frontend.from_onnx(onnx_model, {"input":
dummy_input.shape})
with tvm.transform.PassContext(opt_level=3):
lib = relay.build(mod, target, params=params)
lib.export_library("linear_model_onnx.so")
print("File size")
print(" linear_model_torch.so : ",
os.path.getsize("linear_model_torch.so"))
print(" linear_model_onnx.onnx: ",
os.path.getsize("linear_model_onnx.onnx"))
print(" linear_model_onnx.so : ",
os.path.getsize("linear_model_onnx.so"))
if __name__ == "__main__":
main()
```
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