ConvolutedDog commented on issue #18573:
URL: https://github.com/apache/tvm/issues/18573#issuecomment-3632484624
I have checked the following minimal reproduction example, and it runs
without errors in my environment.
```python
import torch
import torch.nn as nn
from tvm.relax.frontend.torch import from_exported_program
input_size = 28 * 28
num_classes = 10
class SimpleNet(nn.Module):
def __init__(self):
super(SimpleNet, self).__init__()
self.fc1 = nn.Linear(input_size, 128)
self.fc2 = nn.Linear(128, num_classes)
def forward(self, x: torch.Tensor):
x = x.view(x.size(0), -1)
x = torch.relu(self.fc1(x))
x = self.fc2(x)
return x
model = SimpleNet()
example_args = (torch.randn(1, 1, 28, 28).to(torch.device("cpu")),)
exported_program = torch.export.export(model, example_args)
output_path = "model.pt2"
torch.export.save(exported_program, output_path)
##############################
exported_program = torch.export.load("model.pt2")
mod = from_exported_program(exported_program)
mod.show()
```
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