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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