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Sometimes proposal_idx was empty #11

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kevinchan04 opened this issue Oct 18, 2021 · 3 comments
Open

Sometimes proposal_idx was empty #11

kevinchan04 opened this issue Oct 18, 2021 · 3 comments

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@kevinchan04
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Hi, when I tried to run the inference code, I met a problem that the variable proposal_idx was empty. Could you give me any suggestion to debug the code? Thank you very much! The location of code and error information are listed below.

proposal_idx = torch.cat(proposal_idx, dim=0)

Traceback (most recent call last):
File "test_s3dis.py", line 276, in
test(model, model_fn, data_name, cfg.test_epoch)
File "test_s3dis.py", line 70, in test
preds = model_fn(batch, model, epoch)
File "/home/xiaodchen/Generalization/DyCo3D/model/pointgroup/pointgroup.py", line 613, in test_model_fn
ret = model(input_, p2v_map, coords_float, coords[:, 0].int(), batch_offsets, epoch, ins_sample_num=-1, training=False)
File "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/xiaodchen/Generalization/DyCo3D/model/pointgroup/pointgroup.py", line 574, in forward
proposal_idx, proposal_len, scores = self.generate_proposal(mask_logits.squeeze(dim=0).sigmoid(), object_idxs,
File "/home/xiaodchen/Generalization/DyCo3D/model/pointgroup/pointgroup.py", line 454, in generate_proposal
proposal_idx = torch.cat(proposal_idx, dim=0)
RuntimeError: There were no tensor arguments to this function (e.g., you passed an empty list of Tensors), but no fallback function is registered for schema aten::_cat. This usually means that this function requires a non-empty list of Tensors. Available functions are [CPU, CUDA, QuantizedCPU, BackendSelect, Named, AutogradOther, AutogradCPU, AutogradCUDA, AutogradXLA, AutogradNestedTensor, UNKNOWN_TENSOR_TYPE_ID, AutogradPrivateUse1, AutogradPrivateUse2, AutogradPrivateUse3, Tracer, Autocast, Batched, VmapMode].

@tonghe90
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Hi, please check #8 (comment).

@kevinchan04
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Thank you very much. BTW, I wonder how much CUDA memory is needed for inference?

@tonghe90
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That depends on the model you use. If the channel unit (the value of m in the config file) is 16, 1080TI (11G) should be good

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