[GitHub] [tvm] daniperfer commented on issue #7971: Runtime error when tracing maskrcnn model: Only tensors, lists, tuples of tensors, or dictionary of tensors can be output from traced functions

[GitBox <gi...@apache.org>]

daniperfer commented on issue #7971:
URL: https://github.com/apache/tvm/issues/7971#issuecomment-832759852


   Thanks for answering @masahi.
   I see what you said. I have removed my modifications to the tutorial script, back to the original code, and I've launched again the original script `tutorials/frontend/deploy_object_detection_pytorch.py`, which uses the `TraceWrapper` class.
   
   However, I got a different error this time: **LLVM ERROR: out of memory. Aborted (core dumped)**.
   
   Any thoughts on why that error could have happened?
   
   ```
   (my-vitis-ai-pytorch) Vitis-AI ~/tvm > python tutorials/frontend/deploy_object_detection_pytorch.py
   /home/vitis-ai-user/.conda/envs/my-vitis-ai-pytorch/lib/python3.6/site-packages/torch/tensor.py:593: RuntimeWarning: 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).
     'incorrect results).', category=RuntimeWarning)
   /home/vitis-ai-user/.conda/envs/my-vitis-ai-pytorch/lib/python3.6/site-packages/torch/nn/functional.py:3123: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
     dtype=torch.float32)).float())) for i in range(dim)]
   /home/vitis-ai-user/.conda/envs/my-vitis-ai-pytorch/lib/python3.6/site-packages/torchvision/models/detection/anchor_utils.py:147: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
     torch.tensor(image_size[1] // g[1], dtype=torch.int64, device=device)] for g in grid_sizes]
   /home/vitis-ai-user/.conda/envs/my-vitis-ai-pytorch/lib/python3.6/site-packages/torchvision/ops/boxes.py:128: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
     boxes_x = torch.min(boxes_x, torch.tensor(width, dtype=boxes.dtype, device=boxes.device))
   /home/vitis-ai-user/.conda/envs/my-vitis-ai-pytorch/lib/python3.6/site-packages/torchvision/ops/boxes.py:130: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
     boxes_y = torch.min(boxes_y, torch.tensor(height, dtype=boxes.dtype, device=boxes.device))
   /home/vitis-ai-user/.conda/envs/my-vitis-ai-pytorch/lib/python3.6/site-packages/torchvision/models/detection/transform.py:271: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
     for s, s_orig in zip(new_size, original_size)
   /home/vitis-ai-user/.conda/envs/my-vitis-ai-pytorch/lib/python3.6/site-packages/torchvision/models/detection/roi_heads.py:372: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
     return torch.tensor(M + 2 * padding).to(torch.float32) / torch.tensor(M).to(torch.float32)
   LLVM ERROR: out of memory
   Aborted (core dumped)
   ```


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