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2022-10-15 07:21:29
GPU available: True (cuda), used: True
2022-10-15 07:21:29
TPU available: False, using: 0 TPU cores
2022-10-15 07:21:29
IPU available: False, using: 0 IPUs
2022-10-15 07:21:29
HPU available: False, using: 0 HPUs
2022-10-15 07:21:29
wandb: logging graph, to disable use `wandb.watch(log_graph=False)`
2022-10-15 07:21:31
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1]
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  | Name                   | Type             | Params
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------------------------------------------------------------
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0 | conv_stack             | ConvStack        | 1.6 M
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1 | self_attention_block   | ConformerEncoder | 92.0 K
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2 | frame_tab_output_layer | Sequential       | 24.6 K
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3 | softmax_by_string      | Softmax          | 0
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------------------------------------------------------------
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1.7 M     Trainable params
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0         Non-trainable params
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1.7 M     Total params
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6.873     Total estimated model params size (MB)
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/data/group1/z44543r/vae_separation/venv/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:489: PossibleUserWarning: Your `val_dataloader`'s sampler has shuffling enabled, it is strongly recommended that you turn shuffling off for val/test/predict dataloaders.
2022-10-15 07:21:31
  rank_zero_warn(
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Sanity Checking: 0it [00:00, ?it/s]
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Traceback (most recent call last):
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  File "src/train.py", line 65, in <module>
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    main(kwargs)
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  File "src/train.py", line 25, in main
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    step3(now, kwargs)
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  File "/data/group1/z44543r/vae_separation/src/step3.py", line 213, 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 153, 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 650, in _call_and_handle_interrupt
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    return trainer_fn(*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 143, in advance
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    output = self._evaluation_step(**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 240, in _evaluation_step
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    output = self.trainer._call_strategy_hook(hook_name, *kwargs.values())
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  File "/data/group1/z44543r/vae_separation/venv/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1704, in _call_strategy_hook
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    output = fn(*args, **kwargs)
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  File "/data/group1/z44543r/vae_separation/venv/lib/python3.8/site-packages/pytorch_lightning/strategies/strategy.py", line 370, in validation_step
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    return self.model.validation_step(*args, **kwargs)
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  File "/data/group1/z44543r/vae_separation/src/models.py", line 660, in validation_step
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    self.metrics_container.update(y_hat, y, ilens)
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  File "/data/group1/z44543r/vae_separation/src/loss_func.py", line 229, in update
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    p, r, f, tdr = calculate_metrics(gt.int(), binary_pred.int(), olens)
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  File "/data/group1/z44543r/vae_separation/src/utils.py", line 50, in calculate_metrics
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    F0_from_tab_gt = tab2pitch(gt)
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  File "/data/group1/z44543r/vae_separation/src/utils.py", line 69, in tab2pitch
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    pitch[:,:,rel_string_pitches[string]: rel_string_pitches[string] + 20] += tab[:,:,string, :20]
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RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu!