Detectron2 to onnx

I have trained a detectron2 model with the following config

COCO-Detection/retinanet_R_101_FPN_3x.yaml

now i tried to convert the model, using tracing, into onnx using this code

import torch
from detectron2.modeling import build_model
from detectron2.config import get_cfg
from detectron2.checkpoint import DetectionCheckpointer
from detectron2.structures import ImageList


cfg = get_cfg()
cfg.merge_from_file("/content/output.yaml")  
cfg.MODEL.WEIGHTS = "/content/output/model_final.pth"  


model = build_model(cfg)
model.eval()


DetectionCheckpointer(model).load(cfg.MODEL.WEIGHTS)


dummy_image = torch.randn(1, 3, 800, 800)  
dummy_inputs = [{"image": dummy_image.squeeze(0)}]  


traced_script_module = torch.jit.trace(model, (dummy_inputs,))


traced_script_module.save("retinanet_traced.pt")
print("Model tracing and saving completed successfully.")

This code raises the following error

###[06/20 08:30:48 d2.checkpoint.detection_checkpoint]: [DetectionCheckpointer] Loading from /content/output/model_final.pth … /usr/local/lib/python3.10/dist-packages/detectron2/structures/image_list.py:85: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can’t record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs! assert t.shape[:-2] == tensors[0].shape[:-2], t.shape /usr/local/lib/python3.10/dist-packages/detectron2/structures/boxes.py:151: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can’t record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs! if tensor.numel() == 0: /usr/local/lib/python3.10/dist-packages/detectron2/structures/boxes.py:155: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can’t record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs! assert tensor.dim() == 2 and tensor.size(-1) == 4, tensor.size() /usr/local/lib/python3.10/dist-packages/detectron2/structures/boxes.py:151: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can’t record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs! if tensor.numel() == 0: /usr/local/lib/python3.10/dist-packages/detectron2/structures/boxes.py:155: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can’t record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs! assert tensor.dim() == 2 and tensor.size(-1) == 4, tensor.size() /usr/local/lib/python3.10/dist-packages/detectron2/structures/boxes.py:151: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can’t record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs! if tensor.numel() == 0: /usr/local/lib/python3.10/dist-packages/detectron2/structures/boxes.py:155: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can’t record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs! assert tensor.dim() == 2 and tensor.size(-1) == 4, tensor.size() /usr/local/lib/python3.10/dist-packages/detectron2/structures/boxes.py:151: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can’t record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs! if tensor.numel() == 0: /usr/local/lib/python3.10/dist-packages/detectron2/structures/boxes.py:155: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can’t record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs! assert tensor.dim() == 2 and tensor.size(-1) == 4, tensor.size() /usr/local/lib/python3.10/dist-packages/detectron2/structures/boxes.py:151: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can’t record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs! if tensor.numel() == 0: /usr/local/lib/python3.10/dist-packages/detectron2/structures/boxes.py:155: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can’t record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs! assert tensor.dim() == 2 and tensor.size(-1) == 4, tensor.size() /usr/local/lib/python3.10/dist-packages/detectron2/structures/boxes.py:151: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can’t record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs! if tensor.numel() == 0: /usr/local/lib/python3.10/dist-packages/detectron2/structures/boxes.py:155: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can’t record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs! assert tensor.dim() == 2 and tensor.size(-1) == 4, tensor.size() /usr/local/lib/python3.10/dist-packages/detectron2/layers/nms.py:17: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can’t record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs! assert boxes.shape[-1] == 4 /usr/local/lib/python3.10/dist-packages/detectron2/structures/boxes.py:151: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can’t record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs! if tensor.numel() == 0: /usr/local/lib/python3.10/dist-packages/detectron2/structures/boxes.py:155: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can’t record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs! assert tensor.dim() == 2 and tensor.size(-1) == 4, tensor.size() /usr/local/lib/python3.10/dist-packages/detectron2/structures/boxes.py:191: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can’t record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs! assert torch.isfinite(self.tensor).all(), “Box tensor contains infinite or NaN!” /usr/local/lib/python3.10/dist-packages/detectron2/structures/boxes.py:192: TracerWarning: Iterating over a tensor might cause the trace to be incorrect. Passing a tensor of different shape won’t change the number of iterations executed (and might lead to errors or silently give incorrect results). h, w = box_size /usr/local/lib/python3.10/dist-packages/detectron2/structures/boxes.py:151: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can’t record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs! if tensor.numel() == 0: /usr/local/lib/python3.10/dist-packages/detectron2/structures/boxes.py:155: TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can’t record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs! assert tensor.dim() == 2 and tensor.size(-1) == 4, tensor.size() ————————————————————————— RuntimeError Traceback (most recent call last) <ipython-input-25-8b8865a0bb21> in <cell line: 24>() 22 23 # Trace the model —> 24 traced_script_module = torch.jit.trace(model, (dummy_inputs,)) 25 26 # Save the traced model 1 frames /usr/local/lib/python3.10/dist-packages/torch/jit/_trace.py in trace_module(mod, inputs, optimize, check_trace, check_inputs, check_tolerance, strict, _force_outplace, _module_class, _compilation_unit, example_inputs_is_kwarg, _store_inputs) 1086 else: 1087 example_inputs = make_tuple(example_inputs) -> 1088 module._c._create_method_from_trace( 1089 method_name, 1090 func, RuntimeError: Tracer cannot infer type of [{‘instances’: Instances(num_instances=0, image_height=800, image_width=800, fields=[pred_boxes: Boxes(tensor([], device=’cuda:0′, size=(tensor(0), tensor(4)), grad_fn=<ViewBackward0>)), scores: tensor([], device=’cuda:0′, grad_fn=<IndexBackward0>), pred_classes: tensor([], device=’cuda:0′, dtype=torch.int64)])}] :Could not infer type of list element: Only tensors and (possibly nested) tuples of tensors, lists, or dictsare supported as inputs or outputs of traced functions, but instead got value of type Instances.###

Any ideas on how to solve this?

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