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/v1.10.3/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 5: 75%|#######5 | 3/4 [00:00<00:00, 102.47it/s, loss=-1.5, v_num=4]
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Epoch 6: 75%|#######5 | 3/4 [00:00<00:00, 101.74it/s, loss=-1.62, v_num=4]
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Epoch 7: 75%|#######5 | 3/4 [00:00<00:00, 103.24it/s, loss=-1.74, v_num=4]
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Epoch 8: 75%|#######5 | 3/4 [00:00<00:00, 102.41it/s, loss=-1.8, v_num=4]
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Epoch 10: 75%|#######5 | 3/4 [00:00<00:00, 103.64it/s, loss=-1.86, v_num=4]
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Epoch 11: 75%|#######5 | 3/4 [00:00<00:00, 103.42it/s, loss=-1.87, v_num=4]
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Epoch 14: 100%|##########| 4/4 [00:00<00:00, 95.45it/s, loss=-1.91, v_num=4]
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Epoch 15: 75%|#######5 | 3/4 [00:00<00:00, 101.36it/s, loss=-1.92, v_num=4]
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Epoch 17: 50%|##### | 2/4 [00:00<00:00, 81.22it/s, loss=-1.93, v_num=4]
Epoch 17: 75%|#######5 | 3/4 [00:00<00:00, 98.49it/s, loss=-1.93, v_num=4]
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Epoch 18: 50%|##### | 2/4 [00:00<00:00, 84.61it/s, loss=-1.94, v_num=4]
Epoch 18: 75%|#######5 | 3/4 [00:00<00:00, 100.69it/s, loss=-1.94, v_num=4]
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Epoch 18: 100%|##########| 4/4 [00:00<00:00, 94.85it/s, loss=-1.94, v_num=4]
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Epoch 19: 25%|##5 | 1/4 [00:00<00:00, 74.02it/s, loss=-1.94, v_num=4]
Epoch 19: 50%|##### | 2/4 [00:00<00:00, 87.17it/s, loss=-1.94, v_num=4]
Epoch 19: 75%|#######5 | 3/4 [00:00<00:00, 104.98it/s, loss=-1.95, v_num=4]
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Epoch 19: 100%|##########| 4/4 [00:00<00:00, 97.89it/s, loss=-1.95, v_num=4]
Epoch 19: 100%|##########| 4/4 [00:00<00:00, 69.49it/s, loss=-1.95, 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/v1.10.3/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, 77.85it/s, loss=25.7, v_num=5]
Epoch 0: 50%|##### | 2/4 [00:00<00:00, 92.44it/s, loss=18.5, v_num=5]
Epoch 0: 75%|#######5 | 3/4 [00:00<00:00, 113.68it/s, loss=14.3, v_num=5]
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Epoch 0: 100%|##########| 4/4 [00:00<00:00, 102.82it/s, loss=14.3, v_num=5]
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Epoch 1: 50%|##### | 2/4 [00:00<00:00, 92.02it/s, loss=10.7, v_num=5]
Epoch 1: 75%|#######5 | 3/4 [00:00<00:00, 113.07it/s, loss=9.67, v_num=5]
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Epoch 2: 50%|##### | 2/4 [00:00<00:00, 89.20it/s, loss=8.14, v_num=5]
Epoch 2: 75%|#######5 | 3/4 [00:00<00:00, 109.08it/s, loss=7.52, v_num=5]
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Epoch 3: 50%|##### | 2/4 [00:00<00:00, 88.84it/s, loss=6.51, v_num=5]
Epoch 3: 75%|#######5 | 3/4 [00:00<00:00, 109.02it/s, loss=6.1, v_num=5]
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Epoch 3: 100%|##########| 4/4 [00:00<00:00, 99.45it/s, loss=6.1, v_num=5]
Epoch 3: 0%| | 0/4 [00:00<?, ?it/s, loss=6.1, v_num=5]
Epoch 4: 0%| | 0/4 [00:00<?, ?it/s, loss=6.1, v_num=5]
Epoch 4: 25%|##5 | 1/4 [00:00<00:00, 76.44it/s, loss=5.73, v_num=5]
Epoch 4: 50%|##### | 2/4 [00:00<00:00, 91.52it/s, loss=5.4, v_num=5]
Epoch 4: 75%|#######5 | 3/4 [00:00<00:00, 112.53it/s, loss=5.11, 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, 101.36it/s, loss=5.11, v_num=5]
Epoch 4: 0%| | 0/4 [00:00<?, ?it/s, loss=5.11, v_num=5]
Epoch 5: 0%| | 0/4 [00:00<?, ?it/s, loss=5.11, v_num=5]
Epoch 5: 25%|##5 | 1/4 [00:00<00:00, 77.84it/s, loss=4.85, v_num=5]
Epoch 5: 50%|##### | 2/4 [00:00<00:00, 92.44it/s, loss=4.62, v_num=5]
Epoch 5: 75%|#######5 | 3/4 [00:00<00:00, 113.48it/s, loss=4.42, 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, 102.97it/s, loss=4.42, v_num=5]
Epoch 5: 0%| | 0/4 [00:00<?, ?it/s, loss=4.42, v_num=5]
Epoch 6: 0%| | 0/4 [00:00<?, ?it/s, loss=4.42, v_num=5]
Epoch 6: 25%|##5 | 1/4 [00:00<00:00, 77.64it/s, loss=4.23, v_num=5]
Epoch 6: 50%|##### | 2/4 [00:00<00:00, 92.28it/s, loss=4.07, v_num=5]
Epoch 6: 75%|#######5 | 3/4 [00:00<00:00, 113.33it/s, loss=2.84, 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, 102.75it/s, loss=2.84, v_num=5]
Epoch 6: 0%| | 0/4 [00:00<?, ?it/s, loss=2.84, v_num=5]
Epoch 7: 0%| | 0/4 [00:00<?, ?it/s, loss=2.84, v_num=5]
Epoch 7: 25%|##5 | 1/4 [00:00<00:00, 75.97it/s, loss=2.32, v_num=5]
Epoch 7: 50%|##### | 2/4 [00:00<00:00, 89.91it/s, loss=2.06, v_num=5]
Epoch 7: 75%|#######5 | 3/4 [00:00<00:00, 110.23it/s, loss=1.85, 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, 99.82it/s, loss=1.85, v_num=5]
Epoch 7: 0%| | 0/4 [00:00<?, ?it/s, loss=1.85, v_num=5]
Epoch 8: 0%| | 0/4 [00:00<?, ?it/s, loss=1.85, v_num=5]
Epoch 8: 25%|##5 | 1/4 [00:00<00:00, 76.15it/s, loss=1.63, v_num=5]
Epoch 8: 50%|##### | 2/4 [00:00<00:00, 91.97it/s, loss=1.44, v_num=5]
Epoch 8: 75%|#######5 | 3/4 [00:00<00:00, 112.87it/s, loss=1.28, 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, 102.42it/s, loss=1.28, v_num=5]
Epoch 8: 0%| | 0/4 [00:00<?, ?it/s, loss=1.28, v_num=5]
Epoch 9: 0%| | 0/4 [00:00<?, ?it/s, loss=1.28, v_num=5]
Epoch 9: 25%|##5 | 1/4 [00:00<00:00, 77.26it/s, loss=1.14, v_num=5]
Epoch 9: 50%|##### | 2/4 [00:00<00:00, 91.77it/s, loss=1.04, v_num=5]
Epoch 9: 75%|#######5 | 3/4 [00:00<00:00, 112.79it/s, loss=0.969, 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, 101.74it/s, loss=0.969, v_num=5]
Epoch 9: 0%| | 0/4 [00:00<?, ?it/s, loss=0.969, v_num=5]
Epoch 10: 0%| | 0/4 [00:00<?, ?it/s, loss=0.969, v_num=5]
Epoch 10: 25%|##5 | 1/4 [00:00<00:00, 78.33it/s, loss=0.895, v_num=5]
Epoch 10: 50%|##### | 2/4 [00:00<00:00, 92.85it/s, loss=0.845, v_num=5]
Epoch 10: 75%|#######5 | 3/4 [00:00<00:00, 113.78it/s, loss=0.804, 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, 102.61it/s, loss=0.804, v_num=5]
Epoch 10: 0%| | 0/4 [00:00<?, ?it/s, loss=0.804, v_num=5]
Epoch 11: 0%| | 0/4 [00:00<?, ?it/s, loss=0.804, v_num=5]
Epoch 11: 25%|##5 | 1/4 [00:00<00:00, 77.32it/s, loss=0.77, v_num=5]
Epoch 11: 50%|##### | 2/4 [00:00<00:00, 90.36it/s, loss=0.74, v_num=5]
Epoch 11: 75%|#######5 | 3/4 [00:00<00:00, 111.16it/s, loss=0.718, 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, 100.43it/s, loss=0.718, v_num=5]
Epoch 11: 0%| | 0/4 [00:00<?, ?it/s, loss=0.718, v_num=5]
Epoch 12: 0%| | 0/4 [00:00<?, ?it/s, loss=0.718, v_num=5]
Epoch 12: 25%|##5 | 1/4 [00:00<00:00, 77.44it/s, loss=0.694, v_num=5]
Epoch 12: 50%|##### | 2/4 [00:00<00:00, 92.52it/s, loss=0.671, v_num=5]
Epoch 12: 75%|#######5 | 3/4 [00:00<00:00, 113.68it/s, loss=0.642, 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, 102.69it/s, loss=0.642, v_num=5]
Epoch 12: 0%| | 0/4 [00:00<?, ?it/s, loss=0.642, v_num=5]
Epoch 13: 0%| | 0/4 [00:00<?, ?it/s, loss=0.642, v_num=5]
Epoch 13: 25%|##5 | 1/4 [00:00<00:00, 78.89it/s, loss=0.615, v_num=5]
Epoch 13: 50%|##### | 2/4 [00:00<00:00, 93.54it/s, loss=0.581, v_num=5]
Epoch 13: 75%|#######5 | 3/4 [00:00<00:00, 114.14it/s, loss=0.55, 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, 103.10it/s, loss=0.55, v_num=5]
Epoch 13: 0%| | 0/4 [00:00<?, ?it/s, loss=0.55, v_num=5]
Epoch 14: 0%| | 0/4 [00:00<?, ?it/s, loss=0.55, v_num=5]
Epoch 14: 25%|##5 | 1/4 [00:00<00:00, 78.30it/s, loss=0.525, v_num=5]
Epoch 14: 50%|##### | 2/4 [00:00<00:00, 93.11it/s, loss=0.493, v_num=5]
Epoch 14: 75%|#######5 | 3/4 [00:00<00:00, 114.13it/s, loss=0.468, 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, 103.17it/s, loss=0.468, v_num=5]
Epoch 14: 0%| | 0/4 [00:00<?, ?it/s, loss=0.468, v_num=5]
Epoch 15: 0%| | 0/4 [00:00<?, ?it/s, loss=0.468, v_num=5]
Epoch 15: 25%|##5 | 1/4 [00:00<00:00, 78.68it/s, loss=0.445, v_num=5]
Epoch 15: 50%|##### | 2/4 [00:00<00:00, 93.70it/s, loss=0.426, v_num=5]
Epoch 15: 75%|#######5 | 3/4 [00:00<00:00, 114.83it/s, loss=0.407, 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, 103.59it/s, loss=0.407, v_num=5]
Epoch 15: 0%| | 0/4 [00:00<?, ?it/s, loss=0.407, v_num=5]
Epoch 16: 0%| | 0/4 [00:00<?, ?it/s, loss=0.407, v_num=5]
Epoch 16: 25%|##5 | 1/4 [00:00<00:00, 78.91it/s, loss=0.391, v_num=5]
Epoch 16: 50%|##### | 2/4 [00:00<00:00, 92.50it/s, loss=0.373, v_num=5]
Epoch 16: 75%|#######5 | 3/4 [00:00<00:00, 113.45it/s, loss=0.362, 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, 102.85it/s, loss=0.362, v_num=5]
Epoch 16: 0%| | 0/4 [00:00<?, ?it/s, loss=0.362, v_num=5]
Epoch 17: 0%| | 0/4 [00:00<?, ?it/s, loss=0.362, v_num=5]
Epoch 17: 25%|##5 | 1/4 [00:00<00:00, 78.83it/s, loss=0.347, v_num=5]
Epoch 17: 50%|##### | 2/4 [00:00<00:00, 93.96it/s, loss=0.332, v_num=5]
Epoch 17: 75%|#######5 | 3/4 [00:00<00:00, 115.06it/s, loss=0.318, 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, 103.81it/s, loss=0.318, v_num=5]
Epoch 17: 0%| | 0/4 [00:00<?, ?it/s, loss=0.318, v_num=5]
Epoch 18: 0%| | 0/4 [00:00<?, ?it/s, loss=0.318, v_num=5]
Epoch 18: 25%|##5 | 1/4 [00:00<00:00, 76.33it/s, loss=0.306, v_num=5]
Epoch 18: 50%|##### | 2/4 [00:00<00:00, 91.32it/s, loss=0.29, v_num=5]
Epoch 18: 75%|#######5 | 3/4 [00:00<00:00, 111.65it/s, loss=0.275, 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, 102.46it/s, loss=0.275, v_num=5]
Epoch 18: 0%| | 0/4 [00:00<?, ?it/s, loss=0.275, v_num=5]
Epoch 19: 0%| | 0/4 [00:00<?, ?it/s, loss=0.275, v_num=5]
Epoch 19: 25%|##5 | 1/4 [00:00<00:00, 77.23it/s, loss=0.259, v_num=5]
Epoch 19: 50%|##### | 2/4 [00:00<00:00, 92.18it/s, loss=0.248, v_num=5]
Epoch 19: 75%|#######5 | 3/4 [00:00<00:00, 112.87it/s, loss=0.236, 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, 102.33it/s, loss=0.236, v_num=5]
Epoch 19: 100%|##########| 4/4 [00:00<00:00, 70.92it/s, loss=0.236, 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/v1.10.3/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, 78.70it/s, loss=33.4, v_num=6]
Epoch 0: 50%|##### | 2/4 [00:00<00:00, 92.02it/s, loss=22.4, v_num=6]
Epoch 0: 75%|#######5 | 3/4 [00:00<00:00, 113.53it/s, loss=21.6, 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, 103.29it/s, loss=21.6, v_num=6]
Epoch 0: 0%| | 0/4 [00:00<?, ?it/s, loss=21.6, v_num=6]
Epoch 1: 0%| | 0/4 [00:00<?, ?it/s, loss=21.6, v_num=6]
Epoch 1: 25%|##5 | 1/4 [00:00<00:00, 78.78it/s, loss=21.9, v_num=6]
Epoch 1: 50%|##### | 2/4 [00:00<00:00, 93.46it/s, loss=21, v_num=6]
Epoch 1: 75%|#######5 | 3/4 [00:00<00:00, 115.71it/s, loss=20.5, 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, 105.14it/s, loss=20.5, v_num=6]
Epoch 1: 0%| | 0/4 [00:00<?, ?it/s, loss=20.5, v_num=6]
Epoch 2: 0%| | 0/4 [00:00<?, ?it/s, loss=20.5, v_num=6]
Epoch 2: 25%|##5 | 1/4 [00:00<00:00, 76.88it/s, loss=20.3, v_num=6]
Epoch 2: 50%|##### | 2/4 [00:00<00:00, 90.15it/s, loss=18.9, v_num=6]
Epoch 2: 75%|#######5 | 3/4 [00:00<00:00, 111.23it/s, loss=17.9, 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, 102.24it/s, loss=17.9, v_num=6]
Epoch 2: 0%| | 0/4 [00:00<?, ?it/s, loss=17.9, v_num=6]
Epoch 3: 0%| | 0/4 [00:00<?, ?it/s, loss=17.9, v_num=6]
Epoch 3: 25%|##5 | 1/4 [00:00<00:00, 77.25it/s, loss=17.4, v_num=6]
Epoch 3: 50%|##### | 2/4 [00:00<00:00, 91.62it/s, loss=17.3, v_num=6]
Epoch 3: 75%|#######5 | 3/4 [00:00<00:00, 112.52it/s, loss=17.1, 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, 102.60it/s, loss=17.1, v_num=6]
Epoch 3: 0%| | 0/4 [00:00<?, ?it/s, loss=17.1, v_num=6]
Epoch 4: 0%| | 0/4 [00:00<?, ?it/s, loss=17.1, v_num=6]
Epoch 4: 25%|##5 | 1/4 [00:00<00:00, 77.34it/s, loss=16.8, v_num=6]
Epoch 4: 50%|##### | 2/4 [00:00<00:00, 92.28it/s, loss=16.3, v_num=6]
Epoch 4: 75%|#######5 | 3/4 [00:00<00:00, 113.55it/s, loss=16.1, 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, 103.69it/s, loss=16.1, v_num=6]
Epoch 4: 0%| | 0/4 [00:00<?, ?it/s, loss=16.1, v_num=6]
Epoch 5: 0%| | 0/4 [00:00<?, ?it/s, loss=16.1, v_num=6]
Epoch 5: 25%|##5 | 1/4 [00:00<00:00, 77.74it/s, loss=15.7, v_num=6]
Epoch 5: 50%|##### | 2/4 [00:00<00:00, 91.86it/s, loss=15.3, v_num=6]
Epoch 5: 75%|#######5 | 3/4 [00:00<00:00, 113.08it/s, loss=15.1, 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, 103.59it/s, loss=15.1, v_num=6]
Epoch 5: 0%| | 0/4 [00:00<?, ?it/s, loss=15.1, v_num=6]
Epoch 6: 0%| | 0/4 [00:00<?, ?it/s, loss=15.1, v_num=6]
Epoch 6: 25%|##5 | 1/4 [00:00<00:00, 78.32it/s, loss=15.1, v_num=6]
Epoch 6: 50%|##### | 2/4 [00:00<00:00, 93.30it/s, loss=15.1, v_num=6]
Epoch 6: 75%|#######5 | 3/4 [00:00<00:00, 114.74it/s, loss=13.8, 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, 104.51it/s, loss=13.8, v_num=6]
Epoch 6: 0%| | 0/4 [00:00<?, ?it/s, loss=13.8, v_num=6]
Epoch 7: 0%| | 0/4 [00:00<?, ?it/s, loss=13.8, v_num=6]
Epoch 7: 25%|##5 | 1/4 [00:00<00:00, 78.17it/s, loss=13.8, v_num=6]
Epoch 7: 50%|##### | 2/4 [00:00<00:00, 88.33it/s, loss=13.1, v_num=6]
Epoch 7: 75%|#######5 | 3/4 [00:00<00:00, 108.06it/s, loss=12.2, 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, 99.20it/s, loss=12.2, v_num=6]
Epoch 7: 0%| | 0/4 [00:00<?, ?it/s, loss=12.2, v_num=6]
Epoch 8: 0%| | 0/4 [00:00<?, ?it/s, loss=12.2, v_num=6]
Epoch 8: 25%|##5 | 1/4 [00:00<00:00, 76.81it/s, loss=11.6, v_num=6]
Epoch 8: 50%|##### | 2/4 [00:00<00:00, 91.90it/s, loss=11.2, v_num=6]
Epoch 8: 75%|#######5 | 3/4 [00:00<00:00, 113.13it/s, loss=10.7, 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, 103.53it/s, loss=10.7, v_num=6]
Epoch 8: 0%| | 0/4 [00:00<?, ?it/s, loss=10.7, v_num=6]
Epoch 9: 0%| | 0/4 [00:00<?, ?it/s, loss=10.7, v_num=6]
Epoch 9: 25%|##5 | 1/4 [00:00<00:00, 77.75it/s, loss=11.3, v_num=6]
Epoch 9: 50%|##### | 2/4 [00:00<00:00, 92.90it/s, loss=11.5, v_num=6]
Epoch 9: 75%|#######5 | 3/4 [00:00<00:00, 114.38it/s, loss=11.5, 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, 104.33it/s, loss=11.5, v_num=6]
Epoch 9: 0%| | 0/4 [00:00<?, ?it/s, loss=11.5, v_num=6]
Epoch 10: 0%| | 0/4 [00:00<?, ?it/s, loss=11.5, v_num=6]
Epoch 10: 25%|##5 | 1/4 [00:00<00:00, 77.07it/s, loss=11.5, v_num=6]
Epoch 10: 50%|##### | 2/4 [00:00<00:00, 91.60it/s, loss=11.3, v_num=6]
Epoch 10: 75%|#######5 | 3/4 [00:00<00:00, 112.42it/s, loss=10.7, 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, 102.98it/s, loss=10.7, v_num=6]
Epoch 10: 0%| | 0/4 [00:00<?, ?it/s, loss=10.7, v_num=6]
Epoch 11: 0%| | 0/4 [00:00<?, ?it/s, loss=10.7, v_num=6]
Epoch 11: 25%|##5 | 1/4 [00:00<00:00, 77.13it/s, loss=10.6, v_num=6]
Epoch 11: 50%|##### | 2/4 [00:00<00:00, 91.89it/s, loss=10.3, v_num=6]
Epoch 11: 75%|#######5 | 3/4 [00:00<00:00, 111.68it/s, loss=10.2, 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, 102.60it/s, loss=10.2, v_num=6]
Epoch 11: 0%| | 0/4 [00:00<?, ?it/s, loss=10.2, v_num=6]
Epoch 12: 0%| | 0/4 [00:00<?, ?it/s, loss=10.2, v_num=6]
Epoch 12: 25%|##5 | 1/4 [00:00<00:00, 78.73it/s, loss=10.3, v_num=6]
Epoch 12: 50%|##### | 2/4 [00:00<00:00, 93.80it/s, loss=10.3, v_num=6]
Epoch 12: 75%|#######5 | 3/4 [00:00<00:00, 115.25it/s, loss=10.2, 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, 105.14it/s, loss=10.2, v_num=6]
Epoch 12: 0%| | 0/4 [00:00<?, ?it/s, loss=10.2, v_num=6]
Epoch 13: 0%| | 0/4 [00:00<?, ?it/s, loss=10.2, v_num=6]
Epoch 13: 25%|##5 | 1/4 [00:00<00:00, 78.28it/s, loss=10, v_num=6]
Epoch 13: 50%|##### | 2/4 [00:00<00:00, 92.83it/s, loss=9.76, v_num=6]
Epoch 13: 75%|#######5 | 3/4 [00:00<00:00, 114.05it/s, loss=9.34, 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, 104.30it/s, loss=9.34, v_num=6]
Epoch 13: 0%| | 0/4 [00:00<?, ?it/s, loss=9.34, v_num=6]
Epoch 14: 0%| | 0/4 [00:00<?, ?it/s, loss=9.34, v_num=6]
Epoch 14: 25%|##5 | 1/4 [00:00<00:00, 78.59it/s, loss=9.36, v_num=6]
Epoch 14: 50%|##### | 2/4 [00:00<00:00, 93.54it/s, loss=9.4, v_num=6]
Epoch 14: 75%|#######5 | 3/4 [00:00<00:00, 114.87it/s, loss=9.52, 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, 104.75it/s, loss=9.52, v_num=6]
Epoch 14: 0%| | 0/4 [00:00<?, ?it/s, loss=9.52, v_num=6]
Epoch 15: 0%| | 0/4 [00:00<?, ?it/s, loss=9.52, v_num=6]
Epoch 15: 25%|##5 | 1/4 [00:00<00:00, 74.89it/s, loss=9.38, v_num=6]
Epoch 15: 50%|##### | 2/4 [00:00<00:00, 90.83it/s, loss=9.15, v_num=6]
Epoch 15: 75%|#######5 | 3/4 [00:00<00:00, 112.13it/s, loss=8.59, 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, 102.57it/s, loss=8.59, v_num=6]
Epoch 15: 0%| | 0/4 [00:00<?, ?it/s, loss=8.59, v_num=6]
Epoch 16: 0%| | 0/4 [00:00<?, ?it/s, loss=8.59, v_num=6]
Epoch 16: 25%|##5 | 1/4 [00:00<00:00, 76.74it/s, loss=8.42, v_num=6]
Epoch 16: 50%|##### | 2/4 [00:00<00:00, 92.32it/s, loss=8.18, v_num=6]
Epoch 16: 75%|#######5 | 3/4 [00:00<00:00, 112.98it/s, loss=7.82, 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, 103.20it/s, loss=7.82, v_num=6]
Epoch 16: 0%| | 0/4 [00:00<?, ?it/s, loss=7.82, v_num=6]
Epoch 17: 0%| | 0/4 [00:00<?, ?it/s, loss=7.82, v_num=6]
Epoch 17: 25%|##5 | 1/4 [00:00<00:00, 77.57it/s, loss=8.04, v_num=6]
Epoch 17: 50%|##### | 2/4 [00:00<00:00, 92.79it/s, loss=8.44, v_num=6]
Epoch 17: 75%|#######5 | 3/4 [00:00<00:00, 113.89it/s, loss=8.46, 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, 104.00it/s, loss=8.46, v_num=6]
Epoch 17: 0%| | 0/4 [00:00<?, ?it/s, loss=8.46, v_num=6]
Epoch 18: 0%| | 0/4 [00:00<?, ?it/s, loss=8.46, v_num=6]
Epoch 18: 25%|##5 | 1/4 [00:00<00:00, 77.90it/s, loss=8.46, v_num=6]
Epoch 18: 50%|##### | 2/4 [00:00<00:00, 93.10it/s, loss=8.31, v_num=6]
Epoch 18: 75%|#######5 | 3/4 [00:00<00:00, 114.38it/s, loss=7.9, 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, 104.22it/s, loss=7.9, v_num=6]
Epoch 18: 0%| | 0/4 [00:00<?, ?it/s, loss=7.9, v_num=6]
Epoch 19: 0%| | 0/4 [00:00<?, ?it/s, loss=7.9, v_num=6]
Epoch 19: 25%|##5 | 1/4 [00:00<00:00, 76.99it/s, loss=7.67, v_num=6]
Epoch 19: 50%|##### | 2/4 [00:00<00:00, 90.20it/s, loss=7.46, v_num=6]
Epoch 19: 75%|#######5 | 3/4 [00:00<00:00, 108.84it/s, loss=7.35, 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, 99.18it/s, loss=7.35, v_num=6]
Epoch 19: 100%|##########| 4/4 [00:00<00:00, 69.00it/s, loss=7.35, 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/v1.10.3/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, 70.41it/s, loss=-0.794, v_num=7]
Epoch 0: 50%|##### | 2/4 [00:00<00:00, 81.93it/s, loss=-0.848, v_num=7]
Epoch 0: 75%|#######5 | 3/4 [00:00<00:00, 99.42it/s, loss=-0.896, 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, 93.95it/s, loss=-0.896, v_num=7]
Epoch 0: 0%| | 0/4 [00:00<?, ?it/s, loss=-0.896, v_num=7]
Epoch 1: 0%| | 0/4 [00:00<?, ?it/s, loss=-0.896, v_num=7]
Epoch 1: 25%|##5 | 1/4 [00:00<00:00, 71.49it/s, loss=-0.934, v_num=7]
Epoch 1: 50%|##### | 2/4 [00:00<00:00, 84.70it/s, loss=-0.994, v_num=7]
Epoch 1: 75%|#######5 | 3/4 [00:00<00:00, 102.27it/s, loss=-1.05, 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, 95.71it/s, loss=-1.05, v_num=7]
Epoch 1: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.05, v_num=7]
Epoch 2: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.05, v_num=7]
Epoch 2: 25%|##5 | 1/4 [00:00<00:00, 70.99it/s, loss=-1.11, v_num=7]
Epoch 2: 50%|##### | 2/4 [00:00<00:00, 83.85it/s, loss=-1.17, v_num=7]
Epoch 2: 75%|#######5 | 3/4 [00:00<00:00, 101.26it/s, loss=-1.22, 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, 95.03it/s, loss=-1.22, v_num=7]
Epoch 2: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.22, v_num=7]
Epoch 3: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.22, v_num=7]
Epoch 3: 25%|##5 | 1/4 [00:00<00:00, 71.67it/s, loss=-1.26, v_num=7]
Epoch 3: 50%|##### | 2/4 [00:00<00:00, 84.70it/s, loss=-1.31, v_num=7]
Epoch 3: 75%|#######5 | 3/4 [00:00<00:00, 102.18it/s, loss=-1.35, 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, 95.71it/s, loss=-1.35, v_num=7]
Epoch 3: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.35, v_num=7]
Epoch 4: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.35, v_num=7]
Epoch 4: 25%|##5 | 1/4 [00:00<00:00, 73.15it/s, loss=-1.38, v_num=7]
Epoch 4: 50%|##### | 2/4 [00:00<00:00, 85.63it/s, loss=-1.41, v_num=7]
Epoch 4: 75%|#######5 | 3/4 [00:00<00:00, 102.75it/s, loss=-1.43, 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, 96.03it/s, loss=-1.43, v_num=7]
Epoch 4: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.43, v_num=7]
Epoch 5: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.43, v_num=7]
Epoch 5: 25%|##5 | 1/4 [00:00<00:00, 69.34it/s, loss=-1.45, v_num=7]
Epoch 5: 50%|##### | 2/4 [00:00<00:00, 83.45it/s, loss=-1.47, v_num=7]
Epoch 5: 75%|#######5 | 3/4 [00:00<00:00, 101.05it/s, loss=-1.49, 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, 95.23it/s, loss=-1.49, v_num=7]
Epoch 5: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.49, v_num=7]
Epoch 6: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.49, v_num=7]
Epoch 6: 25%|##5 | 1/4 [00:00<00:00, 73.03it/s, loss=-1.51, v_num=7]
Epoch 6: 50%|##### | 2/4 [00:00<00:00, 84.67it/s, loss=-1.52, v_num=7]
Epoch 6: 75%|#######5 | 3/4 [00:00<00:00, 101.80it/s, loss=-1.57, 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, 95.35it/s, loss=-1.57, v_num=7]
Epoch 6: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.57, v_num=7]
Epoch 7: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.57, v_num=7]
Epoch 7: 25%|##5 | 1/4 [00:00<00:00, 72.90it/s, loss=-1.62, v_num=7]
Epoch 7: 50%|##### | 2/4 [00:00<00:00, 84.37it/s, loss=-1.67, v_num=7]
Epoch 7: 75%|#######5 | 3/4 [00:00<00:00, 101.58it/s, loss=-1.71, 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, 95.25it/s, loss=-1.71, v_num=7]
Epoch 7: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.71, v_num=7]
Epoch 8: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.71, v_num=7]
Epoch 8: 25%|##5 | 1/4 [00:00<00:00, 70.74it/s, loss=-1.74, v_num=7]
Epoch 8: 50%|##### | 2/4 [00:00<00:00, 83.43it/s, loss=-1.77, v_num=7]
Epoch 8: 75%|#######5 | 3/4 [00:00<00:00, 100.49it/s, loss=-1.78, 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, 94.39it/s, loss=-1.78, v_num=7]
Epoch 8: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.78, v_num=7]
Epoch 9: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.78, v_num=7]
Epoch 9: 25%|##5 | 1/4 [00:00<00:00, 72.17it/s, loss=-1.8, v_num=7]
Epoch 9: 50%|##### | 2/4 [00:00<00:00, 83.72it/s, loss=-1.81, v_num=7]
Epoch 9: 75%|#######5 | 3/4 [00:00<00:00, 100.36it/s, loss=-1.83, 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, 93.00it/s, loss=-1.83, v_num=7]
Epoch 9: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.83, v_num=7]
Epoch 10: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.83, v_num=7]
Epoch 10: 25%|##5 | 1/4 [00:00<00:00, 71.25it/s, loss=-1.83, v_num=7]
Epoch 10: 50%|##### | 2/4 [00:00<00:00, 84.25it/s, loss=-1.84, v_num=7]
Epoch 10: 75%|#######5 | 3/4 [00:00<00:00, 101.64it/s, loss=-1.84, 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, 95.45it/s, loss=-1.84, v_num=7]
Epoch 10: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.84, v_num=7]
Epoch 11: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.84, v_num=7]
Epoch 11: 25%|##5 | 1/4 [00:00<00:00, 71.96it/s, loss=-1.85, v_num=7]
Epoch 11: 50%|##### | 2/4 [00:00<00:00, 84.88it/s, loss=-1.86, v_num=7]
Epoch 11: 75%|#######5 | 3/4 [00:00<00:00, 102.35it/s, loss=-1.87, 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, 95.69it/s, loss=-1.87, v_num=7]
Epoch 11: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.87, v_num=7]
Epoch 12: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.87, v_num=7]
Epoch 12: 25%|##5 | 1/4 [00:00<00:00, 71.46it/s, loss=-1.87, v_num=7]
Epoch 12: 50%|##### | 2/4 [00:00<00:00, 84.27it/s, loss=-1.88, v_num=7]
Epoch 12: 75%|#######5 | 3/4 [00:00<00:00, 101.76it/s, loss=-1.88, 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, 94.92it/s, loss=-1.88, v_num=7]
Epoch 12: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.88, v_num=7]
Epoch 13: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.88, v_num=7]
Epoch 13: 25%|##5 | 1/4 [00:00<00:00, 72.31it/s, loss=-1.89, v_num=7]
Epoch 13: 50%|##### | 2/4 [00:00<00:00, 85.21it/s, loss=-1.89, v_num=7]
Epoch 13: 75%|#######5 | 3/4 [00:00<00:00, 102.77it/s, loss=-1.9, 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, 96.15it/s, loss=-1.9, v_num=7]
Epoch 13: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.9, v_num=7]
Epoch 14: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.9, v_num=7]
Epoch 14: 25%|##5 | 1/4 [00:00<00:00, 72.80it/s, loss=-1.9, v_num=7]
Epoch 14: 50%|##### | 2/4 [00:00<00:00, 84.78it/s, loss=-1.9, v_num=7]
Epoch 14: 75%|#######5 | 3/4 [00:00<00:00, 100.86it/s, loss=-1.91, 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, 94.65it/s, loss=-1.91, v_num=7]
Epoch 14: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.91, v_num=7]
Epoch 15: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.91, v_num=7]
Epoch 15: 25%|##5 | 1/4 [00:00<00:00, 72.00it/s, loss=-1.91, v_num=7]
Epoch 15: 50%|##### | 2/4 [00:00<00:00, 84.67it/s, loss=-1.91, v_num=7]
Epoch 15: 75%|#######5 | 3/4 [00:00<00:00, 101.57it/s, loss=-1.92, 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, 94.27it/s, loss=-1.92, v_num=7]
Epoch 15: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.92, v_num=7]
Epoch 16: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.92, v_num=7]
Epoch 16: 25%|##5 | 1/4 [00:00<00:00, 71.12it/s, loss=-1.92, v_num=7]
Epoch 16: 50%|##### | 2/4 [00:00<00:00, 83.54it/s, loss=-1.92, v_num=7]
Epoch 16: 75%|#######5 | 3/4 [00:00<00:00, 100.73it/s, loss=-1.93, 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, 94.64it/s, loss=-1.93, v_num=7]
Epoch 16: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.93, v_num=7]
Epoch 17: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.93, v_num=7]
Epoch 17: 25%|##5 | 1/4 [00:00<00:00, 72.12it/s, loss=-1.93, v_num=7]
Epoch 17: 50%|##### | 2/4 [00:00<00:00, 84.86it/s, loss=-1.93, v_num=7]
Epoch 17: 75%|#######5 | 3/4 [00:00<00:00, 102.30it/s, loss=-1.93, 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, 94.57it/s, loss=-1.93, v_num=7]
Epoch 17: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.93, v_num=7]
Epoch 18: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.93, v_num=7]
Epoch 18: 25%|##5 | 1/4 [00:00<00:00, 71.63it/s, loss=-1.94, v_num=7]
Epoch 18: 50%|##### | 2/4 [00:00<00:00, 83.99it/s, loss=-1.94, v_num=7]
Epoch 18: 75%|#######5 | 3/4 [00:00<00:00, 101.44it/s, loss=-1.94, 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, 95.01it/s, loss=-1.94, v_num=7]
Epoch 18: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.94, v_num=7]
Epoch 19: 0%| | 0/4 [00:00<?, ?it/s, loss=-1.94, v_num=7]
Epoch 19: 25%|##5 | 1/4 [00:00<00:00, 71.29it/s, loss=-1.94, v_num=7]
Epoch 19: 50%|##### | 2/4 [00:00<00:00, 84.32it/s, loss=-1.94, v_num=7]
Epoch 19: 75%|#######5 | 3/4 [00:00<00:00, 101.97it/s, loss=-1.95, 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, 95.72it/s, loss=-1.95, v_num=7]
Epoch 19: 100%|##########| 4/4 [00:00<00:00, 68.03it/s, loss=-1.95, v_num=7]
Total running time of the script: ( 0 minutes 10.427 seconds)