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Timestamps visible
2022-10-20 11:03:35
GPU available: True (cuda), used: True
2022-10-20 11:03:35
TPU available: False, using: 0 TPU cores
2022-10-20 11:03:35
IPU available: False, using: 0 IPUs
2022-10-20 11:03:35
HPU available: False, using: 0 HPUs
2022-10-20 11:03:37
wandb: logging graph, to disable use `wandb.watch(log_graph=False)`
2022-10-20 11:03:41
Initializing distributed: GLOBAL_RANK: 0, MEMBER: 1/4
2022-10-20 11:03:51
----------------------------------------------------------------------------------------------------
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distributed_backend=nccl
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All distributed processes registered. Starting with 4 processes
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----------------------------------------------------------------------------------------------------
2022-10-20 11:03:55
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2,3]
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  | Name                   | Type             | Params
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------------------------------------------------------------
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0 | VAE_encoder            | Conv1DEncoder    | 1.8 M
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1 | fc1                    | Linear           | 23.1 K
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2 | fc2                    | Linear           | 23.1 K
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3 | conv_stack             | ConvStack        | 1.6 M
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4 | z_linear               | Sequential       | 282 K
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5 | self_attention_block   | ConformerEncoder | 92.0 K
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6 | frame_tab_output_layer | Sequential       | 24.6 K
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7 | softmax_by_string      | Softmax          | 0
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------------------------------------------------------------
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3.9 M     Trainable params
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0         Non-trainable params
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3.9 M     Total params
2022-10-20 11:03:55
15.573    Total estimated model params size (MB)
2022-10-20 11:03:58
Sanity Checking: 0it [00:00, ?it/s]batch=[None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None, None]
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Traceback (most recent call last):
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  File "src/train.py", line 76, in <module>
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    main(kwargs)
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  File "src/train.py", line 26, in main
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    step3(kwargs)
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  File "/data/group1/z44543r/vae_separation/src/step3.py", line 235, in step3
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    train(kwargs, use_pretrained_model, pretrained_time, pretrained_epoch, now, test_num, train_data_list,
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  File "/data/group1/z44543r/vae_separation/src/step3.py", line 173, in train
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    trainer.fit(model, train_dataloaders=train_loader,
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  File "/data/group1/z44543r/vae_separation/venv/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 696, in fit
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    self._call_and_handle_interrupt(
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  File "/data/group1/z44543r/vae_separation/venv/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 648, in _call_and_handle_interrupt
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    return self.strategy.launcher.launch(trainer_fn, *args, trainer=self, **kwargs)
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  File "/data/group1/z44543r/vae_separation/venv/lib/python3.8/site-packages/pytorch_lightning/strategies/launchers/subprocess_script.py", line 93, in launch
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    return function(*args, **kwargs)
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  File "/data/group1/z44543r/vae_separation/venv/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 735, in _fit_impl
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    results = self._run(model, ckpt_path=self.ckpt_path)
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  File "/data/group1/z44543r/vae_separation/venv/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1166, in _run
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    results = self._run_stage()
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  File "/data/group1/z44543r/vae_separation/venv/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1252, in _run_stage
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    return self._run_train()
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  File "/data/group1/z44543r/vae_separation/venv/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1274, in _run_train
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    self._run_sanity_check()
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  File "/data/group1/z44543r/vae_separation/venv/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1343, in _run_sanity_check
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    val_loop.run()
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  File "/data/group1/z44543r/vae_separation/venv/lib/python3.8/site-packages/pytorch_lightning/loops/loop.py", line 200, in run
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    self.advance(*args, **kwargs)
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  File "/data/group1/z44543r/vae_separation/venv/lib/python3.8/site-packages/pytorch_lightning/loops/dataloader/evaluation_loop.py", line 155, in advance
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    dl_outputs = self.epoch_loop.run(self._data_fetcher, dl_max_batches, kwargs)
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  File "/data/group1/z44543r/vae_separation/venv/lib/python3.8/site-packages/pytorch_lightning/loops/loop.py", line 200, in run
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    self.advance(*args, **kwargs)
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  File "/data/group1/z44543r/vae_separation/venv/lib/python3.8/site-packages/pytorch_lightning/loops/epoch/evaluation_epoch_loop.py", line 127, in advance
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    batch = next(data_fetcher)
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  File "/data/group1/z44543r/vae_separation/venv/lib/python3.8/site-packages/pytorch_lightning/utilities/fetching.py", line 184, in __next__
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    return self.fetching_function()
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  File "/data/group1/z44543r/vae_separation/venv/lib/python3.8/site-packages/pytorch_lightning/utilities/fetching.py", line 263, in fetching_function
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    self._fetch_next_batch(self.dataloader_iter)
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  File "/data/group1/z44543r/vae_separation/venv/lib/python3.8/site-packages/pytorch_lightning/utilities/fetching.py", line 277, in _fetch_next_batch
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    batch = next(iterator)
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  File "/data/group1/z44543r/vae_separation/venv/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 681, in __next__
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    data = self._next_data()
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  File "/data/group1/z44543r/vae_separation/venv/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 1376, in _next_data
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    return self._process_data(data)
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  File "/data/group1/z44543r/vae_separation/venv/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 1402, in _process_data
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    data.reraise()
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  File "/data/group1/z44543r/vae_separation/venv/lib/python3.8/site-packages/torch/_utils.py", line 461, in reraise
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    raise exception
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TypeError: Caught TypeError in DataLoader worker process 0.
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Original Traceback (most recent call last):
2022-10-20 11:04:03
  File "/data/group1/z44543r/vae_separation/venv/lib/python3.8/site-packages/torch/utils/data/_utils/worker.py", line 302, in _worker_loop
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    data = fetcher.fetch(index)
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  File "/data/group1/z44543r/vae_separation/venv/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 52, in fetch
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    return self.collate_fn(data)
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  File "/data/group1/z44543r/vae_separation/src/step3.py", line 46, in __call__
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    return self.pad_collate(batch)
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  File "/data/group1/z44543r/vae_separation/src/step3.py", line 27, in pad_collate
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    for i, (x1, x2, gt) in enumerate(batch):
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TypeError: cannot unpack non-iterable NoneType object