While testing my models with OwLite I came across an unexpected error during OwLite.export. The error occurred when I was trying to export baseline my torchvideo/x3d model. It seems like exporting to ONNX is done successfully but somewhat fails to upload the exported ONNX.

I could track down the error and discover the fact that this only happens with the models with custom torch.autograd.Function. I attach the minimal reproducer of the error I found and the error traceback of it.

I have found a workaround which is just to replace the custom autograd function with the torch native one(torch.nn.SiLU which does basically the same thing). I’d like to know if better way exists since I do not want to fix all the models in the repository myself and am pretty sure that there exists certain cases that I do not have a torch native appropriate replacer.

Also, it would be great to print a appropriate error message rather than just throwing naive http error response. I have suffered a lot to track down to the fact that this error is somewhat related to the torch.autograd.Function, which is completely not inferable from the error that owlite package have thrown.

Environment:

• OS: both on macOS 14.5 and ubuntu 22.04
• python: 3.10
• owlite: 2.1.0
• pytorch: both on 2.2.2 and 2.1.2
• pytorchvideo: 0.1.3

Code:

import torch
from owlite import init

class SwishFunction(torch.autograd.Function):
    @staticmethod
    def forward(ctx, x):
        result = x * torch.sigmoid(x)
        ctx.save_for_backward(x)
        return result

    @staticmethod
    def backward(ctx, grad_output):
        (x,) = ctx.saved_tensors
        sigmoid_x = torch.sigmoid(x)
        return grad_output * (sigmoid_x * (1 + x * (1 - sigmoid_x)))
    
class Bar(torch.nn.Module):
    def __init__(self, *args, **kwargs) -> None:
        super().__init__(*args, **kwargs)
        self.proj = torch.nn.Linear(in_features=100, out_features=10)

    def forward(self, x):
        x = self.proj(x)
        x = SwishFunction.apply(x)
        return x

class Foo(torch.nn.Module):
    def __init__(self, *args, **kwargs) -> None:
        super().__init__(*args, **kwargs)
        self.bar = Bar()

    def forward(self, x):
        x = self.bar(x)
        return x

model = Foo().eval()
args = (torch.randn(100), )

owl = init("bug", "my_custom_autograd")
model = owl.convert(model, *args)
owl.export(model)

Traceback:

(test) ~ # python custom_autograd.py
OwLite [INFO] Created a new project 'bug'
OwLite [INFO] Connecting to the first device at NEST
OwLite [INFO] Device connected: NVIDIA RTX A4000 [TensorRT]
OwLite [INFO] Created a new baseline 'my_custom_autograd' in the project 'bug'
OwLite [INFO] Experiment data will be saved in /Users/hjdbhj/tmp/owlite/bug/my_custom_autograd
OwLite [INFO] Converting the model
OwLite [INFO] Saving exported ONNX proto at /Users/hjdbhj/tmp/owlite/bug/my_custom_autograd/bug_my_custom_autograd_my_custom_autograd.onnx with external data bug_my_custom_autograd_my_custom_autograd.bin
OwLite [INFO] Baseline ONNX saved at /Users/hjdbhj/tmp/owlite/bug/my_custom_autograd/bug_my_custom_autograd_my_custom_autograd.onnx
Traceback (most recent call last):
  File "/Users/hjdbhj/owlite-bug-repro/custom_autograd.py", line 43, in <module>
    owl.export(model)
  File "/Users/hjdbhj/opt/miniconda3/envs/test/lib/python3.10/site-packages/owlite/owlite.py", line 493, in export
    self.target.upload(proto, model)
  File "/Users/hjdbhj/opt/miniconda3/envs/test/lib/python3.10/site-packages/owlite/api/baseline.py", line 149, in upload
    DOVE_API_BASE.post(
  File "/Users/hjdbhj/opt/miniconda3/envs/test/lib/python3.10/site-packages/owlite/owlite_core/api_base.py", line 159, in post
    return self._request(request_callable)
  File "/Users/hjdbhj/opt/miniconda3/envs/test/lib/python3.10/site-packages/owlite/owlite_core/api_base.py", line 107, in _request
    response.raise_for_status()
  File "/Users/hjdbhj/opt/miniconda3/envs/test/lib/python3.10/site-packages/requests/models.py", line 1024, in raise_for_status
    raise HTTPError(http_error_msg, response=self)
requests.exceptions.HTTPError: 400 Client Error: Bad Request for url: https://dove.owlite.ai/upload