Note
Click here to download the full example code
Deep CCAΒΆ
This example demonstrates how to easily train Deep CCA models and variants
import numpy as np
import pytorch_lightning as pl
from matplotlib import pyplot as plt
from torch.utils.data import Subset
from cca_zoo.data import Split_MNIST_Dataset
from cca_zoo.deepmodels import (
DCCA,
CCALightning,
get_dataloaders,
architectures,
DCCA_NOI,
DCCA_SDL,
BarlowTwins,
)
def plot_latent_label(model, dataloader, num_batches=100):
fig, ax = plt.subplots(ncols=model.latent_dims)
for j in range(model.latent_dims):
ax[j].set_title(f"Dimension {j}")
ax[j].set_xlabel("View 1")
ax[j].set_ylabel("View 2")
for i, (data, label) in enumerate(dataloader):
z = model(*data)
zx, zy = z
zx = zx.to("cpu").detach().numpy()
zy = zy.to("cpu").detach().numpy()
for j in range(model.latent_dims):
ax[j].scatter(zx[:, j], zy[:, j], c=label.numpy(), cmap="tab10")
if i > num_batches:
plt.colorbar()
break
n_train = 500
n_val = 100
train_dataset = Split_MNIST_Dataset(mnist_type="MNIST", train=True)
val_dataset = Subset(train_dataset, np.arange(n_train, n_train + n_val))
train_dataset = Subset(train_dataset, np.arange(n_train))
train_loader, val_loader = get_dataloaders(train_dataset, val_dataset, batch_size=128)
# The number of latent dimensions across models
latent_dims = 2
# number of epochs for deep models
epochs = 20
encoder_1 = architectures.Encoder(latent_dims=latent_dims, feature_size=392)
encoder_2 = architectures.Encoder(latent_dims=latent_dims, feature_size=392)
Deep CCA
dcca = DCCA(latent_dims=latent_dims, encoders=[encoder_1, encoder_2])
dcca = CCALightning(dcca)
trainer = pl.Trainer(max_epochs=epochs, enable_checkpointing=False)
trainer.fit(dcca, train_loader, val_loader)
plot_latent_label(dcca.model, train_loader)
plt.suptitle("DCCA")
plt.show()
Out:
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/home/docs/checkouts/readthedocs.org/user_builds/cca-zoo/envs/v1.10.2/lib/python3.7/site-packages/pytorch_lightning/trainer/data_loading.py:408: UserWarning: The number of training samples (3) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.
f"The number of training samples ({self.num_training_batches}) is smaller than the logging interval"
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Epoch 0: 75%|#######5 | 3/4 [00:00<00:00, 98.22it/s, loss=-0.679, v_num=4]
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Epoch 5: 75%|#######5 | 3/4 [00:00<00:00, 99.72it/s, loss=-1.53, v_num=4]
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Epoch 7: 75%|#######5 | 3/4 [00:00<00:00, 95.14it/s, loss=-1.77, v_num=4]
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Epoch 8: 75%|#######5 | 3/4 [00:00<00:00, 99.71it/s, loss=-1.82, v_num=4]
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Epoch 10: 75%|#######5 | 3/4 [00:00<00:00, 97.04it/s, loss=-1.88, v_num=4]
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Epoch 11: 75%|#######5 | 3/4 [00:00<00:00, 99.04it/s, loss=-1.9, v_num=4]
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Epoch 13: 100%|##########| 4/4 [00:00<00:00, 91.55it/s, loss=-1.92, v_num=4]
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Epoch 14: 100%|##########| 4/4 [00:00<00:00, 91.81it/s, loss=-1.93, v_num=4]
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Epoch 15: 75%|#######5 | 3/4 [00:00<00:00, 99.09it/s, loss=-1.93, v_num=4]
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Epoch 16: 75%|#######5 | 3/4 [00:00<00:00, 100.39it/s, loss=-1.94, v_num=4]
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Epoch 17: 50%|##### | 2/4 [00:00<00:00, 81.05it/s, loss=-1.95, v_num=4]
Epoch 17: 75%|#######5 | 3/4 [00:00<00:00, 98.18it/s, loss=-1.95, v_num=4]
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Epoch 18: 50%|##### | 2/4 [00:00<00:00, 81.89it/s, loss=-1.95, v_num=4]
Epoch 18: 75%|#######5 | 3/4 [00:00<00:00, 97.58it/s, loss=-1.95, v_num=4]
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Epoch 18: 100%|##########| 4/4 [00:00<00:00, 90.64it/s, loss=-1.95, v_num=4]
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Epoch 19: 25%|##5 | 1/4 [00:00<00:00, 69.38it/s, loss=-1.96, v_num=4]
Epoch 19: 50%|##### | 2/4 [00:00<00:00, 82.56it/s, loss=-1.96, v_num=4]
Epoch 19: 75%|#######5 | 3/4 [00:00<00:00, 100.16it/s, loss=-1.96, v_num=4]
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Epoch 19: 100%|##########| 4/4 [00:00<00:00, 93.86it/s, loss=-1.96, v_num=4]
Epoch 19: 100%|##########| 4/4 [00:00<00:00, 66.36it/s, loss=-1.96, v_num=4]
Deep CCA by Non-Linear Orthogonal Iterations
dcca_noi = DCCA_NOI(
latent_dims=latent_dims, N=len(train_dataset), encoders=[encoder_1, encoder_2]
)
dcca_noi = CCALightning(dcca_noi)
trainer = pl.Trainer(max_epochs=epochs, enable_checkpointing=False)
trainer.fit(dcca_noi, train_loader, val_loader)
plot_latent_label(dcca_noi.model, train_loader)
plt.title("DCCA by Non-Linear Orthogonal Iterations")
plt.show()
Out:
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/home/docs/checkouts/readthedocs.org/user_builds/cca-zoo/envs/v1.10.2/lib/python3.7/site-packages/pytorch_lightning/trainer/data_loading.py:408: UserWarning: The number of training samples (3) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.
f"The number of training samples ({self.num_training_batches}) is smaller than the logging interval"
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Epoch 0: 25%|##5 | 1/4 [00:00<00:00, 72.75it/s, loss=22.2, v_num=5]
Epoch 0: 50%|##### | 2/4 [00:00<00:00, 88.10it/s, loss=15.7, v_num=5]
Epoch 0: 75%|#######5 | 3/4 [00:00<00:00, 108.95it/s, loss=12.4, v_num=5]
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Epoch 0: 100%|##########| 4/4 [00:00<00:00, 99.52it/s, loss=12.4, v_num=5]
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Epoch 1: 50%|##### | 2/4 [00:00<00:00, 86.36it/s, loss=8.87, v_num=5]
Epoch 1: 75%|#######5 | 3/4 [00:00<00:00, 106.95it/s, loss=8.14, v_num=5]
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Epoch 2: 50%|##### | 2/4 [00:00<00:00, 88.66it/s, loss=7.06, v_num=5]
Epoch 2: 75%|#######5 | 3/4 [00:00<00:00, 108.41it/s, loss=6.6, v_num=5]
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Epoch 2: 100%|##########| 4/4 [00:00<00:00, 99.04it/s, loss=6.6, v_num=5]
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Epoch 3: 50%|##### | 2/4 [00:00<00:00, 88.42it/s, loss=5.82, v_num=5]
Epoch 3: 75%|#######5 | 3/4 [00:00<00:00, 108.91it/s, loss=5.49, v_num=5]
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Epoch 3: 100%|##########| 4/4 [00:00<00:00, 99.56it/s, loss=5.49, v_num=5]
Epoch 3: 0%| | 0/4 [00:00<?, ?it/s, loss=5.49, v_num=5]
Epoch 4: 0%| | 0/4 [00:00<?, ?it/s, loss=5.49, v_num=5]
Epoch 4: 25%|##5 | 1/4 [00:00<00:00, 69.74it/s, loss=5.17, v_num=5]
Epoch 4: 50%|##### | 2/4 [00:00<00:00, 84.14it/s, loss=4.87, v_num=5]
Epoch 4: 75%|#######5 | 3/4 [00:00<00:00, 103.98it/s, loss=4.61, v_num=5]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 4: 100%|##########| 4/4 [00:00<00:00, 96.12it/s, loss=4.61, v_num=5]
Epoch 4: 0%| | 0/4 [00:00<?, ?it/s, loss=4.61, v_num=5]
Epoch 5: 0%| | 0/4 [00:00<?, ?it/s, loss=4.61, v_num=5]
Epoch 5: 25%|##5 | 1/4 [00:00<00:00, 72.48it/s, loss=4.38, v_num=5]
Epoch 5: 50%|##### | 2/4 [00:00<00:00, 87.56it/s, loss=4.17, v_num=5]
Epoch 5: 75%|#######5 | 3/4 [00:00<00:00, 107.74it/s, loss=4.01, v_num=5]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 5: 100%|##########| 4/4 [00:00<00:00, 98.42it/s, loss=4.01, v_num=5]
Epoch 5: 0%| | 0/4 [00:00<?, ?it/s, loss=4.01, v_num=5]
Epoch 6: 0%| | 0/4 [00:00<?, ?it/s, loss=4.01, v_num=5]
Epoch 6: 25%|##5 | 1/4 [00:00<00:00, 73.18it/s, loss=3.85, v_num=5]
Epoch 6: 50%|##### | 2/4 [00:00<00:00, 87.47it/s, loss=3.72, v_num=5]
Epoch 6: 75%|#######5 | 3/4 [00:00<00:00, 108.03it/s, loss=2.66, v_num=5]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 6: 100%|##########| 4/4 [00:00<00:00, 98.60it/s, loss=2.66, v_num=5]
Epoch 6: 0%| | 0/4 [00:00<?, ?it/s, loss=2.66, v_num=5]
Epoch 7: 0%| | 0/4 [00:00<?, ?it/s, loss=2.66, v_num=5]
Epoch 7: 25%|##5 | 1/4 [00:00<00:00, 72.45it/s, loss=2.26, v_num=5]
Epoch 7: 50%|##### | 2/4 [00:00<00:00, 87.02it/s, loss=2.02, v_num=5]
Epoch 7: 75%|#######5 | 3/4 [00:00<00:00, 107.12it/s, loss=1.88, v_num=5]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 7: 100%|##########| 4/4 [00:00<00:00, 97.84it/s, loss=1.88, v_num=5]
Epoch 7: 0%| | 0/4 [00:00<?, ?it/s, loss=1.88, v_num=5]
Epoch 8: 0%| | 0/4 [00:00<?, ?it/s, loss=1.88, v_num=5]
Epoch 8: 25%|##5 | 1/4 [00:00<00:00, 72.63it/s, loss=1.75, v_num=5]
Epoch 8: 50%|##### | 2/4 [00:00<00:00, 87.24it/s, loss=1.56, v_num=5]
Epoch 8: 75%|#######5 | 3/4 [00:00<00:00, 107.42it/s, loss=1.39, v_num=5]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 8: 100%|##########| 4/4 [00:00<00:00, 98.21it/s, loss=1.39, v_num=5]
Epoch 8: 0%| | 0/4 [00:00<?, ?it/s, loss=1.39, v_num=5]
Epoch 9: 0%| | 0/4 [00:00<?, ?it/s, loss=1.39, v_num=5]
Epoch 9: 25%|##5 | 1/4 [00:00<00:00, 71.60it/s, loss=1.23, v_num=5]
Epoch 9: 50%|##### | 2/4 [00:00<00:00, 85.92it/s, loss=1.11, v_num=5]
Epoch 9: 75%|#######5 | 3/4 [00:00<00:00, 106.03it/s, loss=1.01, v_num=5]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 9: 100%|##########| 4/4 [00:00<00:00, 96.66it/s, loss=1.01, v_num=5]
Epoch 9: 0%| | 0/4 [00:00<?, ?it/s, loss=1.01, v_num=5]
Epoch 10: 0%| | 0/4 [00:00<?, ?it/s, loss=1.01, v_num=5]
Epoch 10: 25%|##5 | 1/4 [00:00<00:00, 72.52it/s, loss=0.929, v_num=5]
Epoch 10: 50%|##### | 2/4 [00:00<00:00, 86.90it/s, loss=0.858, v_num=5]
Epoch 10: 75%|#######5 | 3/4 [00:00<00:00, 107.00it/s, loss=0.818, v_num=5]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 10: 100%|##########| 4/4 [00:00<00:00, 98.03it/s, loss=0.818, v_num=5]
Epoch 10: 0%| | 0/4 [00:00<?, ?it/s, loss=0.818, v_num=5]
Epoch 11: 0%| | 0/4 [00:00<?, ?it/s, loss=0.818, v_num=5]
Epoch 11: 25%|##5 | 1/4 [00:00<00:00, 72.73it/s, loss=0.787, v_num=5]
Epoch 11: 50%|##### | 2/4 [00:00<00:00, 87.79it/s, loss=0.765, v_num=5]
Epoch 11: 75%|#######5 | 3/4 [00:00<00:00, 108.42it/s, loss=0.74, v_num=5]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 11: 100%|##########| 4/4 [00:00<00:00, 98.82it/s, loss=0.74, v_num=5]
Epoch 11: 0%| | 0/4 [00:00<?, ?it/s, loss=0.74, v_num=5]
Epoch 12: 0%| | 0/4 [00:00<?, ?it/s, loss=0.74, v_num=5]
Epoch 12: 25%|##5 | 1/4 [00:00<00:00, 73.47it/s, loss=0.708, v_num=5]
Epoch 12: 50%|##### | 2/4 [00:00<00:00, 88.01it/s, loss=0.67, v_num=5]
Epoch 12: 75%|#######5 | 3/4 [00:00<00:00, 108.41it/s, loss=0.628, v_num=5]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 12: 100%|##########| 4/4 [00:00<00:00, 98.04it/s, loss=0.628, v_num=5]
Epoch 12: 0%| | 0/4 [00:00<?, ?it/s, loss=0.628, v_num=5]
Epoch 13: 0%| | 0/4 [00:00<?, ?it/s, loss=0.628, v_num=5]
Epoch 13: 25%|##5 | 1/4 [00:00<00:00, 71.52it/s, loss=0.584, v_num=5]
Epoch 13: 50%|##### | 2/4 [00:00<00:00, 86.26it/s, loss=0.539, v_num=5]
Epoch 13: 75%|#######5 | 3/4 [00:00<00:00, 106.30it/s, loss=0.495, v_num=5]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 13: 100%|##########| 4/4 [00:00<00:00, 97.12it/s, loss=0.495, v_num=5]
Epoch 13: 0%| | 0/4 [00:00<?, ?it/s, loss=0.495, v_num=5]
Epoch 14: 0%| | 0/4 [00:00<?, ?it/s, loss=0.495, v_num=5]
Epoch 14: 25%|##5 | 1/4 [00:00<00:00, 72.66it/s, loss=0.451, v_num=5]
Epoch 14: 50%|##### | 2/4 [00:00<00:00, 87.86it/s, loss=0.418, v_num=5]
Epoch 14: 75%|#######5 | 3/4 [00:00<00:00, 108.36it/s, loss=0.391, v_num=5]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 14: 100%|##########| 4/4 [00:00<00:00, 98.68it/s, loss=0.391, v_num=5]
Epoch 14: 0%| | 0/4 [00:00<?, ?it/s, loss=0.391, v_num=5]
Epoch 15: 0%| | 0/4 [00:00<?, ?it/s, loss=0.391, v_num=5]
Epoch 15: 25%|##5 | 1/4 [00:00<00:00, 72.63it/s, loss=0.368, v_num=5]
Epoch 15: 50%|##### | 2/4 [00:00<00:00, 87.34it/s, loss=0.345, v_num=5]
Epoch 15: 75%|#######5 | 3/4 [00:00<00:00, 107.68it/s, loss=0.33, v_num=5]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 15: 100%|##########| 4/4 [00:00<00:00, 98.15it/s, loss=0.33, v_num=5]
Epoch 15: 0%| | 0/4 [00:00<?, ?it/s, loss=0.33, v_num=5]
Epoch 16: 0%| | 0/4 [00:00<?, ?it/s, loss=0.33, v_num=5]
Epoch 16: 25%|##5 | 1/4 [00:00<00:00, 71.37it/s, loss=0.311, v_num=5]
Epoch 16: 50%|##### | 2/4 [00:00<00:00, 85.71it/s, loss=0.299, v_num=5]
Epoch 16: 75%|#######5 | 3/4 [00:00<00:00, 105.15it/s, loss=0.282, v_num=5]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 16: 100%|##########| 4/4 [00:00<00:00, 95.92it/s, loss=0.282, v_num=5]
Epoch 16: 0%| | 0/4 [00:00<?, ?it/s, loss=0.282, v_num=5]
Epoch 17: 0%| | 0/4 [00:00<?, ?it/s, loss=0.282, v_num=5]
Epoch 17: 25%|##5 | 1/4 [00:00<00:00, 72.58it/s, loss=0.264, v_num=5]
Epoch 17: 50%|##### | 2/4 [00:00<00:00, 87.24it/s, loss=0.247, v_num=5]
Epoch 17: 75%|#######5 | 3/4 [00:00<00:00, 106.98it/s, loss=0.233, v_num=5]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 17: 100%|##########| 4/4 [00:00<00:00, 97.91it/s, loss=0.233, v_num=5]
Epoch 17: 0%| | 0/4 [00:00<?, ?it/s, loss=0.233, v_num=5]
Epoch 18: 0%| | 0/4 [00:00<?, ?it/s, loss=0.233, v_num=5]
Epoch 18: 25%|##5 | 1/4 [00:00<00:00, 73.56it/s, loss=0.218, v_num=5]
Epoch 18: 50%|##### | 2/4 [00:00<00:00, 88.21it/s, loss=0.203, v_num=5]
Epoch 18: 75%|#######5 | 3/4 [00:00<00:00, 108.47it/s, loss=0.195, v_num=5]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 18: 100%|##########| 4/4 [00:00<00:00, 98.46it/s, loss=0.195, v_num=5]
Epoch 18: 0%| | 0/4 [00:00<?, ?it/s, loss=0.195, v_num=5]
Epoch 19: 0%| | 0/4 [00:00<?, ?it/s, loss=0.195, v_num=5]
Epoch 19: 25%|##5 | 1/4 [00:00<00:00, 72.95it/s, loss=0.18, v_num=5]
Epoch 19: 50%|##### | 2/4 [00:00<00:00, 87.90it/s, loss=0.172, v_num=5]
Epoch 19: 75%|#######5 | 3/4 [00:00<00:00, 107.87it/s, loss=0.165, v_num=5]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 19: 100%|##########| 4/4 [00:00<00:00, 97.27it/s, loss=0.165, v_num=5]
Epoch 19: 100%|##########| 4/4 [00:00<00:00, 67.96it/s, loss=0.165, v_num=5]
Deep CCA by Stochastic Decorrelation Loss
dcca_sdl = DCCA_SDL(
latent_dims=latent_dims, N=len(train_dataset), encoders=[encoder_1, encoder_2]
)
dcca_sdl = CCALightning(dcca_sdl)
trainer = pl.Trainer(max_epochs=epochs, enable_checkpointing=False)
trainer.fit(dcca_sdl, train_loader, val_loader)
plot_latent_label(dcca_sdl.model, train_loader)
plt.title("DCCA by Stochastic Decorrelation")
plt.show()
Out:
Validation sanity check: 0it [00:00, ?it/s]
Validation sanity check: 0%| | 0/1 [00:00<?, ?it/s]
/home/docs/checkouts/readthedocs.org/user_builds/cca-zoo/envs/v1.10.2/lib/python3.7/site-packages/pytorch_lightning/trainer/data_loading.py:408: UserWarning: The number of training samples (3) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.
f"The number of training samples ({self.num_training_batches}) is smaller than the logging interval"
Training: 0it [00:00, ?it/s]
Training: 0%| | 0/4 [00:00<?, ?it/s]
Epoch 0: 0%| | 0/4 [00:00<?, ?it/s]
Epoch 0: 25%|##5 | 1/4 [00:00<00:00, 73.45it/s, loss=45.7, v_num=6]
Epoch 0: 50%|##### | 2/4 [00:00<00:00, 86.49it/s, loss=40.7, v_num=6]
Epoch 0: 75%|#######5 | 3/4 [00:00<00:00, 106.89it/s, loss=37.9, v_num=6]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 0: 100%|##########| 4/4 [00:00<00:00, 98.18it/s, loss=37.9, v_num=6]
Epoch 0: 0%| | 0/4 [00:00<?, ?it/s, loss=37.9, v_num=6]
Epoch 1: 0%| | 0/4 [00:00<?, ?it/s, loss=37.9, v_num=6]
Epoch 1: 25%|##5 | 1/4 [00:00<00:00, 72.28it/s, loss=32.1, v_num=6]
Epoch 1: 50%|##### | 2/4 [00:00<00:00, 86.99it/s, loss=27.9, v_num=6]
Epoch 1: 75%|#######5 | 3/4 [00:00<00:00, 107.32it/s, loss=25.6, v_num=6]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 1: 100%|##########| 4/4 [00:00<00:00, 98.74it/s, loss=25.6, v_num=6]
Epoch 1: 0%| | 0/4 [00:00<?, ?it/s, loss=25.6, v_num=6]
Epoch 2: 0%| | 0/4 [00:00<?, ?it/s, loss=25.6, v_num=6]
Epoch 2: 25%|##5 | 1/4 [00:00<00:00, 68.55it/s, loss=24.3, v_num=6]
Epoch 2: 50%|##### | 2/4 [00:00<00:00, 83.54it/s, loss=22.9, v_num=6]
Epoch 2: 75%|#######5 | 3/4 [00:00<00:00, 103.21it/s, loss=21.1, v_num=6]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 2: 100%|##########| 4/4 [00:00<00:00, 95.65it/s, loss=21.1, v_num=6]
Epoch 2: 0%| | 0/4 [00:00<?, ?it/s, loss=21.1, v_num=6]
Epoch 3: 0%| | 0/4 [00:00<?, ?it/s, loss=21.1, v_num=6]
Epoch 3: 25%|##5 | 1/4 [00:00<00:00, 72.18it/s, loss=20.3, v_num=6]
Epoch 3: 50%|##### | 2/4 [00:00<00:00, 87.00it/s, loss=20.1, v_num=6]
Epoch 3: 75%|#######5 | 3/4 [00:00<00:00, 107.32it/s, loss=19.8, v_num=6]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 3: 100%|##########| 4/4 [00:00<00:00, 98.85it/s, loss=19.8, v_num=6]
Epoch 3: 0%| | 0/4 [00:00<?, ?it/s, loss=19.8, v_num=6]
Epoch 4: 0%| | 0/4 [00:00<?, ?it/s, loss=19.8, v_num=6]
Epoch 4: 25%|##5 | 1/4 [00:00<00:00, 73.07it/s, loss=19.4, v_num=6]
Epoch 4: 50%|##### | 2/4 [00:00<00:00, 87.49it/s, loss=18.9, v_num=6]
Epoch 4: 75%|#######5 | 3/4 [00:00<00:00, 107.70it/s, loss=18.8, v_num=6]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 4: 100%|##########| 4/4 [00:00<00:00, 98.85it/s, loss=18.8, v_num=6]
Epoch 4: 0%| | 0/4 [00:00<?, ?it/s, loss=18.8, v_num=6]
Epoch 5: 0%| | 0/4 [00:00<?, ?it/s, loss=18.8, v_num=6]
Epoch 5: 25%|##5 | 1/4 [00:00<00:00, 71.56it/s, loss=18.4, v_num=6]
Epoch 5: 50%|##### | 2/4 [00:00<00:00, 85.23it/s, loss=17.9, v_num=6]
Epoch 5: 75%|#######5 | 3/4 [00:00<00:00, 105.35it/s, loss=17.8, v_num=6]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 5: 100%|##########| 4/4 [00:00<00:00, 97.24it/s, loss=17.8, v_num=6]
Epoch 5: 0%| | 0/4 [00:00<?, ?it/s, loss=17.8, v_num=6]
Epoch 6: 0%| | 0/4 [00:00<?, ?it/s, loss=17.8, v_num=6]
Epoch 6: 25%|##5 | 1/4 [00:00<00:00, 72.80it/s, loss=17.7, v_num=6]
Epoch 6: 50%|##### | 2/4 [00:00<00:00, 87.03it/s, loss=17.9, v_num=6]
Epoch 6: 75%|#######5 | 3/4 [00:00<00:00, 107.40it/s, loss=16.3, v_num=6]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 6: 100%|##########| 4/4 [00:00<00:00, 98.77it/s, loss=16.3, v_num=6]
Epoch 6: 0%| | 0/4 [00:00<?, ?it/s, loss=16.3, v_num=6]
Epoch 7: 0%| | 0/4 [00:00<?, ?it/s, loss=16.3, v_num=6]
Epoch 7: 25%|##5 | 1/4 [00:00<00:00, 71.62it/s, loss=15.6, v_num=6]
Epoch 7: 50%|##### | 2/4 [00:00<00:00, 85.57it/s, loss=14.5, v_num=6]
Epoch 7: 75%|#######5 | 3/4 [00:00<00:00, 105.67it/s, loss=14.4, v_num=6]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 7: 100%|##########| 4/4 [00:00<00:00, 97.33it/s, loss=14.4, v_num=6]
Epoch 7: 0%| | 0/4 [00:00<?, ?it/s, loss=14.4, v_num=6]
Epoch 8: 0%| | 0/4 [00:00<?, ?it/s, loss=14.4, v_num=6]
Epoch 8: 25%|##5 | 1/4 [00:00<00:00, 72.77it/s, loss=14.3, v_num=6]
Epoch 8: 50%|##### | 2/4 [00:00<00:00, 87.37it/s, loss=13.9, v_num=6]
Epoch 8: 75%|#######5 | 3/4 [00:00<00:00, 107.96it/s, loss=13.5, v_num=6]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 8: 100%|##########| 4/4 [00:00<00:00, 99.51it/s, loss=13.5, v_num=6]
Epoch 8: 0%| | 0/4 [00:00<?, ?it/s, loss=13.5, v_num=6]
Epoch 9: 0%| | 0/4 [00:00<?, ?it/s, loss=13.5, v_num=6]
Epoch 9: 25%|##5 | 1/4 [00:00<00:00, 73.44it/s, loss=13.4, v_num=6]
Epoch 9: 50%|##### | 2/4 [00:00<00:00, 88.09it/s, loss=13.9, v_num=6]
Epoch 9: 75%|#######5 | 3/4 [00:00<00:00, 108.35it/s, loss=14.1, v_num=6]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 9: 100%|##########| 4/4 [00:00<00:00, 100.02it/s, loss=14.1, v_num=6]
Epoch 9: 0%| | 0/4 [00:00<?, ?it/s, loss=14.1, v_num=6]
Epoch 10: 0%| | 0/4 [00:00<?, ?it/s, loss=14.1, v_num=6]
Epoch 10: 25%|##5 | 1/4 [00:00<00:00, 75.53it/s, loss=13.6, v_num=6]
Epoch 10: 50%|##### | 2/4 [00:00<00:00, 90.86it/s, loss=13.3, v_num=6]
Epoch 10: 75%|#######5 | 3/4 [00:00<00:00, 112.17it/s, loss=13.2, v_num=6]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 10: 100%|##########| 4/4 [00:00<00:00, 102.92it/s, loss=13.2, v_num=6]
Epoch 10: 0%| | 0/4 [00:00<?, ?it/s, loss=13.2, v_num=6]
Epoch 11: 0%| | 0/4 [00:00<?, ?it/s, loss=13.2, v_num=6]
Epoch 11: 25%|##5 | 1/4 [00:00<00:00, 71.72it/s, loss=12.9, v_num=6]
Epoch 11: 50%|##### | 2/4 [00:00<00:00, 87.17it/s, loss=12.3, v_num=6]
Epoch 11: 75%|#######5 | 3/4 [00:00<00:00, 108.00it/s, loss=12.4, v_num=6]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 11: 100%|##########| 4/4 [00:00<00:00, 98.84it/s, loss=12.4, v_num=6]
Epoch 11: 0%| | 0/4 [00:00<?, ?it/s, loss=12.4, v_num=6]
Epoch 12: 0%| | 0/4 [00:00<?, ?it/s, loss=12.4, v_num=6]
Epoch 12: 25%|##5 | 1/4 [00:00<00:00, 72.60it/s, loss=12.8, v_num=6]
Epoch 12: 50%|##### | 2/4 [00:00<00:00, 88.75it/s, loss=12.7, v_num=6]
Epoch 12: 75%|#######5 | 3/4 [00:00<00:00, 109.96it/s, loss=12.6, v_num=6]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 12: 100%|##########| 4/4 [00:00<00:00, 101.46it/s, loss=12.6, v_num=6]
Epoch 12: 0%| | 0/4 [00:00<?, ?it/s, loss=12.6, v_num=6]
Epoch 13: 0%| | 0/4 [00:00<?, ?it/s, loss=12.6, v_num=6]
Epoch 13: 25%|##5 | 1/4 [00:00<00:00, 76.26it/s, loss=11.9, v_num=6]
Epoch 13: 50%|##### | 2/4 [00:00<00:00, 91.56it/s, loss=11.8, v_num=6]
Epoch 13: 75%|#######5 | 3/4 [00:00<00:00, 112.79it/s, loss=11.1, v_num=6]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 13: 100%|##########| 4/4 [00:00<00:00, 103.07it/s, loss=11.1, v_num=6]
Epoch 13: 0%| | 0/4 [00:00<?, ?it/s, loss=11.1, v_num=6]
Epoch 14: 0%| | 0/4 [00:00<?, ?it/s, loss=11.1, v_num=6]
Epoch 14: 25%|##5 | 1/4 [00:00<00:00, 74.63it/s, loss=10.8, v_num=6]
Epoch 14: 50%|##### | 2/4 [00:00<00:00, 90.24it/s, loss=10.9, v_num=6]
Epoch 14: 75%|#######5 | 3/4 [00:00<00:00, 111.43it/s, loss=10.7, v_num=6]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 14: 100%|##########| 4/4 [00:00<00:00, 102.38it/s, loss=10.7, v_num=6]
Epoch 14: 0%| | 0/4 [00:00<?, ?it/s, loss=10.7, v_num=6]
Epoch 15: 0%| | 0/4 [00:00<?, ?it/s, loss=10.7, v_num=6]
Epoch 15: 25%|##5 | 1/4 [00:00<00:00, 74.10it/s, loss=10.7, v_num=6]
Epoch 15: 50%|##### | 2/4 [00:00<00:00, 89.19it/s, loss=11, v_num=6]
Epoch 15: 75%|#######5 | 3/4 [00:00<00:00, 110.16it/s, loss=10.8, v_num=6]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 15: 100%|##########| 4/4 [00:00<00:00, 101.15it/s, loss=10.8, v_num=6]
Epoch 15: 0%| | 0/4 [00:00<?, ?it/s, loss=10.8, v_num=6]
Epoch 16: 0%| | 0/4 [00:00<?, ?it/s, loss=10.8, v_num=6]
Epoch 16: 25%|##5 | 1/4 [00:00<00:00, 75.28it/s, loss=10.5, v_num=6]
Epoch 16: 50%|##### | 2/4 [00:00<00:00, 90.63it/s, loss=9.86, v_num=6]
Epoch 16: 75%|#######5 | 3/4 [00:00<00:00, 111.62it/s, loss=10.2, v_num=6]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 16: 100%|##########| 4/4 [00:00<00:00, 102.28it/s, loss=10.2, v_num=6]
Epoch 16: 0%| | 0/4 [00:00<?, ?it/s, loss=10.2, v_num=6]
Epoch 17: 0%| | 0/4 [00:00<?, ?it/s, loss=10.2, v_num=6]
Epoch 17: 25%|##5 | 1/4 [00:00<00:00, 73.84it/s, loss=10.4, v_num=6]
Epoch 17: 50%|##### | 2/4 [00:00<00:00, 88.10it/s, loss=10.2, v_num=6]
Epoch 17: 75%|#######5 | 3/4 [00:00<00:00, 108.37it/s, loss=11.2, v_num=6]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 17: 100%|##########| 4/4 [00:00<00:00, 99.65it/s, loss=11.2, v_num=6]
Epoch 17: 0%| | 0/4 [00:00<?, ?it/s, loss=11.2, v_num=6]
Epoch 18: 0%| | 0/4 [00:00<?, ?it/s, loss=11.2, v_num=6]
Epoch 18: 25%|##5 | 1/4 [00:00<00:00, 72.67it/s, loss=11.8, v_num=6]
Epoch 18: 50%|##### | 2/4 [00:00<00:00, 87.73it/s, loss=11.8, v_num=6]
Epoch 18: 75%|#######5 | 3/4 [00:00<00:00, 108.59it/s, loss=11.6, v_num=6]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 18: 100%|##########| 4/4 [00:00<00:00, 99.51it/s, loss=11.6, v_num=6]
Epoch 18: 0%| | 0/4 [00:00<?, ?it/s, loss=11.6, v_num=6]
Epoch 19: 0%| | 0/4 [00:00<?, ?it/s, loss=11.6, v_num=6]
Epoch 19: 25%|##5 | 1/4 [00:00<00:00, 72.13it/s, loss=11.5, v_num=6]
Epoch 19: 50%|##### | 2/4 [00:00<00:00, 85.49it/s, loss=11.4, v_num=6]
Epoch 19: 75%|#######5 | 3/4 [00:00<00:00, 105.69it/s, loss=11.2, v_num=6]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 19: 100%|##########| 4/4 [00:00<00:00, 96.89it/s, loss=11.2, v_num=6]
Epoch 19: 100%|##########| 4/4 [00:00<00:00, 66.88it/s, loss=11.2, v_num=6]
Deep CCA by Barlow Twins
barlowtwins = BarlowTwins(latent_dims=latent_dims, encoders=[encoder_1, encoder_2])
barlowtwins = CCALightning(barlowtwins)
trainer = pl.Trainer(max_epochs=epochs, enable_checkpointing=False)
trainer.fit(dcca, train_loader, val_loader)
plot_latent_label(dcca_sdl.model, train_loader)
plt.title("DCCA by Barlow Twins")
plt.show()
Out:
Validation sanity check: 0it [00:00, ?it/s]
Validation sanity check: 0%| | 0/1 [00:00<?, ?it/s]
/home/docs/checkouts/readthedocs.org/user_builds/cca-zoo/envs/v1.10.2/lib/python3.7/site-packages/pytorch_lightning/trainer/data_loading.py:408: UserWarning: The number of training samples (3) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.
f"The number of training samples ({self.num_training_batches}) is smaller than the logging interval"
Training: 0it [00:00, ?it/s]
Training: 0%| | 0/4 [00:00<?, ?it/s]
Epoch 0: 0%| | 0/4 [00:00<?, ?it/s]
Epoch 0: 25%|##5 | 1/4 [00:00<00:00, 65.12it/s, loss=-1.13, v_num=7]
Epoch 0: 50%|##### | 2/4 [00:00<00:00, 76.52it/s, loss=-1.25, v_num=7]
Epoch 0: 75%|#######5 | 3/4 [00:00<00:00, 92.66it/s, loss=-1.34, v_num=7]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 0: 100%|##########| 4/4 [00:00<00:00, 86.83it/s, loss=-1.34, v_num=7]
Epoch 0: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.34, v_num=7]
Epoch 1: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.34, v_num=7]
Epoch 1: 25%|##5 | 1/4 [00:00<00:00, 62.33it/s, loss=-1.42, v_num=7]
Epoch 1: 50%|##### | 2/4 [00:00<00:00, 74.58it/s, loss=-1.48, v_num=7]
Epoch 1: 75%|#######5 | 3/4 [00:00<00:00, 90.76it/s, loss=-1.52, v_num=7]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 1: 100%|##########| 4/4 [00:00<00:00, 84.77it/s, loss=-1.52, v_num=7]
Epoch 1: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.52, v_num=7]
Epoch 2: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.52, v_num=7]
Epoch 2: 25%|##5 | 1/4 [00:00<00:00, 62.23it/s, loss=-1.56, v_num=7]
Epoch 2: 50%|##### | 2/4 [00:00<00:00, 74.70it/s, loss=-1.59, v_num=7]
Epoch 2: 75%|#######5 | 3/4 [00:00<00:00, 90.51it/s, loss=-1.61, v_num=7]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 2: 100%|##########| 4/4 [00:00<00:00, 86.02it/s, loss=-1.61, v_num=7]
Epoch 2: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.61, v_num=7]
Epoch 3: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.61, v_num=7]
Epoch 3: 25%|##5 | 1/4 [00:00<00:00, 66.18it/s, loss=-1.63, v_num=7]
Epoch 3: 50%|##### | 2/4 [00:00<00:00, 78.38it/s, loss=-1.65, v_num=7]
Epoch 3: 75%|#######5 | 3/4 [00:00<00:00, 94.88it/s, loss=-1.67, v_num=7]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 3: 100%|##########| 4/4 [00:00<00:00, 88.66it/s, loss=-1.67, v_num=7]
Epoch 3: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.67, v_num=7]
Epoch 4: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.67, v_num=7]
Epoch 4: 25%|##5 | 1/4 [00:00<00:00, 66.62it/s, loss=-1.68, v_num=7]
Epoch 4: 50%|##### | 2/4 [00:00<00:00, 79.20it/s, loss=-1.7, v_num=7]
Epoch 4: 75%|#######5 | 3/4 [00:00<00:00, 95.76it/s, loss=-1.71, v_num=7]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 4: 100%|##########| 4/4 [00:00<00:00, 89.54it/s, loss=-1.71, v_num=7]
Epoch 4: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.71, v_num=7]
Epoch 5: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.71, v_num=7]
Epoch 5: 25%|##5 | 1/4 [00:00<00:00, 68.21it/s, loss=-1.72, v_num=7]
Epoch 5: 50%|##### | 2/4 [00:00<00:00, 80.56it/s, loss=-1.73, v_num=7]
Epoch 5: 75%|#######5 | 3/4 [00:00<00:00, 95.85it/s, loss=-1.74, v_num=7]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 5: 100%|##########| 4/4 [00:00<00:00, 90.10it/s, loss=-1.74, v_num=7]
Epoch 5: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.74, v_num=7]
Epoch 6: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.74, v_num=7]
Epoch 6: 25%|##5 | 1/4 [00:00<00:00, 68.09it/s, loss=-1.75, v_num=7]
Epoch 6: 50%|##### | 2/4 [00:00<00:00, 80.81it/s, loss=-1.76, v_num=7]
Epoch 6: 75%|#######5 | 3/4 [00:00<00:00, 97.87it/s, loss=-1.8, v_num=7]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 6: 100%|##########| 4/4 [00:00<00:00, 92.33it/s, loss=-1.8, v_num=7]
Epoch 6: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.8, v_num=7]
Epoch 7: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.8, v_num=7]
Epoch 7: 25%|##5 | 1/4 [00:00<00:00, 68.28it/s, loss=-1.83, v_num=7]
Epoch 7: 50%|##### | 2/4 [00:00<00:00, 80.69it/s, loss=-1.85, v_num=7]
Epoch 7: 75%|#######5 | 3/4 [00:00<00:00, 97.60it/s, loss=-1.86, v_num=7]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 7: 100%|##########| 4/4 [00:00<00:00, 92.16it/s, loss=-1.86, v_num=7]
Epoch 7: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.86, v_num=7]
Epoch 8: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.86, v_num=7]
Epoch 8: 25%|##5 | 1/4 [00:00<00:00, 67.79it/s, loss=-1.87, v_num=7]
Epoch 8: 50%|##### | 2/4 [00:00<00:00, 79.99it/s, loss=-1.88, v_num=7]
Epoch 8: 75%|#######5 | 3/4 [00:00<00:00, 97.35it/s, loss=-1.89, v_num=7]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 8: 100%|##########| 4/4 [00:00<00:00, 91.92it/s, loss=-1.89, v_num=7]
Epoch 8: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.89, v_num=7]
Epoch 9: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.89, v_num=7]
Epoch 9: 25%|##5 | 1/4 [00:00<00:00, 68.69it/s, loss=-1.9, v_num=7]
Epoch 9: 50%|##### | 2/4 [00:00<00:00, 81.80it/s, loss=-1.91, v_num=7]
Epoch 9: 75%|#######5 | 3/4 [00:00<00:00, 97.54it/s, loss=-1.91, v_num=7]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 9: 100%|##########| 4/4 [00:00<00:00, 91.50it/s, loss=-1.91, v_num=7]
Epoch 9: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.91, v_num=7]
Epoch 10: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.91, v_num=7]
Epoch 10: 25%|##5 | 1/4 [00:00<00:00, 68.46it/s, loss=-1.92, v_num=7]
Epoch 10: 50%|##### | 2/4 [00:00<00:00, 81.39it/s, loss=-1.92, v_num=7]
Epoch 10: 75%|#######5 | 3/4 [00:00<00:00, 98.70it/s, loss=-1.93, v_num=7]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 10: 100%|##########| 4/4 [00:00<00:00, 93.01it/s, loss=-1.93, v_num=7]
Epoch 10: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.93, v_num=7]
Epoch 11: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.93, v_num=7]
Epoch 11: 25%|##5 | 1/4 [00:00<00:00, 69.50it/s, loss=-1.93, v_num=7]
Epoch 11: 50%|##### | 2/4 [00:00<00:00, 82.44it/s, loss=-1.93, v_num=7]
Epoch 11: 75%|#######5 | 3/4 [00:00<00:00, 99.73it/s, loss=-1.94, v_num=7]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 11: 100%|##########| 4/4 [00:00<00:00, 92.55it/s, loss=-1.94, v_num=7]
Epoch 11: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.94, v_num=7]
Epoch 12: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.94, v_num=7]
Epoch 12: 25%|##5 | 1/4 [00:00<00:00, 69.08it/s, loss=-1.94, v_num=7]
Epoch 12: 50%|##### | 2/4 [00:00<00:00, 81.80it/s, loss=-1.94, v_num=7]
Epoch 12: 75%|#######5 | 3/4 [00:00<00:00, 99.18it/s, loss=-1.95, v_num=7]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 12: 100%|##########| 4/4 [00:00<00:00, 92.73it/s, loss=-1.95, v_num=7]
Epoch 12: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.95, v_num=7]
Epoch 13: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.95, v_num=7]
Epoch 13: 25%|##5 | 1/4 [00:00<00:00, 68.47it/s, loss=-1.95, v_num=7]
Epoch 13: 50%|##### | 2/4 [00:00<00:00, 81.27it/s, loss=-1.95, v_num=7]
Epoch 13: 75%|#######5 | 3/4 [00:00<00:00, 98.32it/s, loss=-1.95, v_num=7]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 13: 100%|##########| 4/4 [00:00<00:00, 91.81it/s, loss=-1.95, v_num=7]
Epoch 13: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.95, v_num=7]
Epoch 14: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.95, v_num=7]
Epoch 14: 25%|##5 | 1/4 [00:00<00:00, 68.00it/s, loss=-1.96, v_num=7]
Epoch 14: 50%|##### | 2/4 [00:00<00:00, 80.40it/s, loss=-1.96, v_num=7]
Epoch 14: 75%|#######5 | 3/4 [00:00<00:00, 96.19it/s, loss=-1.96, v_num=7]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 14: 100%|##########| 4/4 [00:00<00:00, 90.48it/s, loss=-1.96, v_num=7]
Epoch 14: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.96, v_num=7]
Epoch 15: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.96, v_num=7]
Epoch 15: 25%|##5 | 1/4 [00:00<00:00, 66.90it/s, loss=-1.96, v_num=7]
Epoch 15: 50%|##### | 2/4 [00:00<00:00, 79.45it/s, loss=-1.96, v_num=7]
Epoch 15: 75%|#######5 | 3/4 [00:00<00:00, 95.96it/s, loss=-1.96, v_num=7]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 15: 100%|##########| 4/4 [00:00<00:00, 90.21it/s, loss=-1.96, v_num=7]
Epoch 15: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.96, v_num=7]
Epoch 16: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.96, v_num=7]
Epoch 16: 25%|##5 | 1/4 [00:00<00:00, 65.05it/s, loss=-1.96, v_num=7]
Epoch 16: 50%|##### | 2/4 [00:00<00:00, 77.10it/s, loss=-1.97, v_num=7]
Epoch 16: 75%|#######5 | 3/4 [00:00<00:00, 93.54it/s, loss=-1.97, v_num=7]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 16: 100%|##########| 4/4 [00:00<00:00, 88.62it/s, loss=-1.97, v_num=7]
Epoch 16: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.97, v_num=7]
Epoch 17: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.97, v_num=7]
Epoch 17: 25%|##5 | 1/4 [00:00<00:00, 66.77it/s, loss=-1.97, v_num=7]
Epoch 17: 50%|##### | 2/4 [00:00<00:00, 79.17it/s, loss=-1.97, v_num=7]
Epoch 17: 75%|#######5 | 3/4 [00:00<00:00, 95.79it/s, loss=-1.97, v_num=7]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 17: 100%|##########| 4/4 [00:00<00:00, 90.13it/s, loss=-1.97, v_num=7]
Epoch 17: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.97, v_num=7]
Epoch 18: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.97, v_num=7]
Epoch 18: 25%|##5 | 1/4 [00:00<00:00, 66.83it/s, loss=-1.97, v_num=7]
Epoch 18: 50%|##### | 2/4 [00:00<00:00, 79.18it/s, loss=-1.97, v_num=7]
Epoch 18: 75%|#######5 | 3/4 [00:00<00:00, 95.75it/s, loss=-1.97, v_num=7]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 18: 100%|##########| 4/4 [00:00<00:00, 90.05it/s, loss=-1.97, v_num=7]
Epoch 18: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.97, v_num=7]
Epoch 19: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.97, v_num=7]
Epoch 19: 25%|##5 | 1/4 [00:00<00:00, 66.97it/s, loss=-1.98, v_num=7]
Epoch 19: 50%|##### | 2/4 [00:00<00:00, 79.59it/s, loss=-1.98, v_num=7]
Epoch 19: 75%|#######5 | 3/4 [00:00<00:00, 96.37it/s, loss=-1.98, v_num=7]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 19: 100%|##########| 4/4 [00:00<00:00, 90.84it/s, loss=-1.98, v_num=7]
Epoch 19: 100%|##########| 4/4 [00:00<00:00, 63.90it/s, loss=-1.98, v_num=7]
Total running time of the script: ( 0 minutes 10.590 seconds)