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/home/dmitriishubin/anaconda3/envs/tf_gpu/lib/python3.7/site-packages/torch/cuda/amp/grad_scaler.py:111: UserWarning: torch.cuda.amp.GradScaler is enabled, but CUDA is not available. Disabling.
warnings.warn("torch.cuda.amp.GradScaler is enabled, but CUDA is not available. Disabling.")
/home/dmitriishubin/anaconda3/envs/tf_gpu/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint8 = np.dtype([("qint8", np.int8, 1)])
/home/dmitriishubin/anaconda3/envs/tf_gpu/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint8 = np.dtype([("quint8", np.uint8, 1)])
/home/dmitriishubin/anaconda3/envs/tf_gpu/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint16 = np.dtype([("qint16", np.int16, 1)])
/home/dmitriishubin/anaconda3/envs/tf_gpu/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_quint16 = np.dtype([("quint16", np.uint16, 1)])
/home/dmitriishubin/anaconda3/envs/tf_gpu/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint32 = np.dtype([("qint32", np.int32, 1)])
/home/dmitriishubin/anaconda3/envs/tf_gpu/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
np_resource = np.dtype([("resource", np.ubyte, 1)])
0%| | 0/1 [00:00<?, ?it/s]
Selected Learning rate: 0.001
Only one GPU is available
----------------------------------------------------------------
Layer (type) Output Shape Param #
================================================================
Conv1d-1 [-1, 32, 19000] 3456
BatchNorm1d-2 [-1, 32, 19000] 64
ReLU-3 [-1, 32, 19000] 0
MaxPool1d-4 [-1, 32, 9499] 0
Dropout-5 [-1, 32, 9499] 0
Stem_layer-6 [-1, 32, 9499] 3520
Conv1d-7 [-1, 64, 9499] 18432
BatchNorm1d-8 [-1, 64, 9499] 128
ReLU-9 [-1, 64, 9499] 0
MaxPool1d-10 [-1, 64, 4749] 0
Dropout-11 [-1, 64, 4749] 0
Stem_layer-12 [-1, 64, 4749] 18560
Conv1d-13 [-1, 64, 4749] 36864
Tanh-14 [-1, 64, 4749] 0
Conv1d-15 [-1, 64, 4749] 36864
Sigmoid-16 [-1, 64, 4749] 0
Conv1d-17 [-1, 64, 4749] 4096
Conv1d-18 [-1, 64, 4749] 4096
Wave_block-19 [[-1, 64, 4749], [-1, 64, 4749]] 81920
Conv1d-20 [-1, 64, 4749] 36864
Tanh-21 [-1, 64, 4749] 0
Conv1d-22 [-1, 64, 4749] 36864
Sigmoid-23 [-1, 64, 4749] 0
Conv1d-24 [-1, 64, 4749] 4096
Conv1d-25 [-1, 64, 4749] 4096
Wave_block-26 [[-1, 64, 4749], [-1, 64, 4749]] 81920
Conv1d-27 [-1, 64, 4749] 36864
Tanh-28 [-1, 64, 4749] 0
Conv1d-29 [-1, 64, 4749] 36864
Sigmoid-30 [-1, 64, 4749] 0
Conv1d-31 [-1, 64, 4749] 4096
Conv1d-32 [-1, 64, 4749] 4096
Wave_block-33 [[-1, 64, 4749], [-1, 64, 4749]] 81920
Conv1d-34 [-1, 64, 4749] 36864
Tanh-35 [-1, 64, 4749] 0
Conv1d-36 [-1, 64, 4749] 36864
Sigmoid-37 [-1, 64, 4749] 0
Conv1d-38 [-1, 64, 4749] 4096
Conv1d-39 [-1, 64, 4749] 4096
Wave_block-40 [[-1, 64, 4749], [-1, 64, 4749]] 81920
Conv1d-41 [-1, 64, 4749] 36864
Tanh-42 [-1, 64, 4749] 0
Conv1d-43 [-1, 64, 4749] 36864
Sigmoid-44 [-1, 64, 4749] 0
Conv1d-45 [-1, 64, 4749] 4096
Conv1d-46 [-1, 64, 4749] 4096
Wave_block-47 [[-1, 64, 4749], [-1, 64, 4749]] 81920
Conv1d-48 [-1, 64, 4749] 36864
Tanh-49 [-1, 64, 4749] 0
Conv1d-50 [-1, 64, 4749] 36864
Sigmoid-51 [-1, 64, 4749] 0
Conv1d-52 [-1, 64, 4749] 4096
Conv1d-53 [-1, 64, 4749] 4096
Wave_block-54 [[-1, 64, 4749], [-1, 64, 4749]] 81920
Conv1d-55 [-1, 64, 4749] 36864
Tanh-56 [-1, 64, 4749] 0
Conv1d-57 [-1, 64, 4749] 36864
Sigmoid-58 [-1, 64, 4749] 0
Conv1d-59 [-1, 64, 4749] 4096
Conv1d-60 [-1, 64, 4749] 4096
Wave_block-61 [[-1, 64, 4749], [-1, 64, 4749]] 81920
Conv1d-62 [-1, 64, 4749] 36864
Tanh-63 [-1, 64, 4749] 0
Conv1d-64 [-1, 64, 4749] 36864
Sigmoid-65 [-1, 64, 4749] 0
Conv1d-66 [-1, 64, 4749] 4096
Conv1d-67 [-1, 64, 4749] 4096
Wave_block-68 [[-1, 64, 4749], [-1, 64, 4749]] 81920
Upsample-69 [-1, 64, 9498] 0
Conv1d-70 [-1, 32, 9500] 18432
Dropout-71 [-1, 32, 9500] 0
Stem_layer_upsample-72 [-1, 32, 9500] 18496
Upsample-73 [-1, 32, 19000] 0
Conv1d-74 [-1, 12, 19002] 384
Dropout-75 [-1, 12, 19002] 0
Stem_layer_upsample-76 [-1, 12, 19002] 408
Conv1d-77 [-1, 128, 4741] 73728
Conv1d-78 [-1, 256, 4733] 294912
Linear-79 [-1, 27] 6939
Sigmoid-80 [-1, 27] 0
================================================================
Total params: tensor(1768179)
Trainable params: tensor(1768179)
Non-trainable params: tensor(0)
----------------------------------------------------------------
100%|██████████| 1/1 [00:03<00:00, 3.35s/it]100%|██████████| 1/1 [00:03<00:00, 3.37s/it]
0%| | 0/10 [00:00<?, ?it/s]100%|██████████| 10/10 [00:00<00:00, 244.25it/s]Finding the optimal threshold
Model evaluation...
0%| | 0/1 [00:00<?, ?it/s]| Epoch: 1 | Train_loss: 0.6214169859886169 | Val_loss: 0.6170979738235474 | Metric_train: 0.30902904362620004 | Metric_val: 0.35120973955925405 | Current LR: 0.001
save global val_loss model score 0.6170979738235474
Start generation of predictions
100%|██████████| 1/1 [00:01<00:00, 1.47s/it]100%|██████████| 1/1 [00:01<00:00, 1.51s/it]