Note
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Deep Variational CCA and Deep Canonically Correlated AutoencodersΒΆ
This example demonstrates multiview models which can reconstruct their inputs
import matplotlib.pyplot as plt
import numpy as np
import pytorch_lightning as pl
from torch.utils.data import Subset
from cca_zoo.data import Noisy_MNIST_Dataset
from cca_zoo.deepmodels import (
CCALightning,
get_dataloaders,
architectures,
DCCAE,
DVCCA,
)
def plot_reconstruction(model, dataset, idx):
(x, y), _ = dataset[idx]
recon_x, recon_y = model.recon(x, y)
if isinstance(recon_x, list):
recon_x = recon_x[0]
recon_y = recon_y[0]
recon_x = recon_x.detach().numpy()
recon_y = recon_y.detach().numpy()
fig, ax = plt.subplots(ncols=4)
ax[0].set_title('Original View 1')
ax[1].set_title('Original View 2')
ax[2].set_title('Reconstruction View 1')
ax[3].set_title('Reconstruction View 2')
ax[0].imshow(x.detach().numpy().reshape((28, 28)))
ax[1].imshow(y.detach().numpy().reshape((28, 28)))
ax[2].imshow(recon_x.reshape((28, 28)))
ax[3].imshow(recon_y.reshape((28, 28)))
n_train = 500
n_val = 100
train_dataset = Noisy_MNIST_Dataset(mnist_type="MNIST", train=True, flatten=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)
# The number of latent dimensions across models
latent_dims = 2
# number of epochs for deep models
epochs = 50
encoder_1 = architectures.Encoder(
latent_dims=latent_dims, feature_size=784, variational=True
)
encoder_2 = architectures.Encoder(
latent_dims=latent_dims, feature_size=784, variational=True
)
decoder_1 = architectures.Decoder(latent_dims=latent_dims, feature_size=784, norm_output=True)
decoder_2 = architectures.Decoder(latent_dims=latent_dims, feature_size=784, norm_output=True)
Deep VCCA
dcca = DVCCA(
latent_dims=latent_dims,
encoders=[encoder_1, encoder_2],
decoders=[decoder_1, decoder_2],
)
dcca = CCALightning(dcca)
trainer = pl.Trainer(max_epochs=epochs, enable_checkpointing=False)
trainer.fit(dcca, train_loader, val_loader)
plot_reconstruction(dcca.model, train_dataset, 0)
plt.suptitle('DVCCA')
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/v1.10.1/lib/python3.7/site-packages/torch/nn/functional.py:1806: UserWarning: nn.functional.sigmoid is deprecated. Use torch.sigmoid instead.
warnings.warn("nn.functional.sigmoid is deprecated. Use torch.sigmoid instead.")
/home/docs/checkouts/readthedocs.org/user_builds/cca-zoo/envs/v1.10.1/lib/python3.7/site-packages/pytorch_lightning/trainer/data_loading.py:408: UserWarning: The number of training samples (1) 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 35: 50%|##### | 1/2 [00:00<00:00, 1.90it/s, loss=1.53, v_num=8]
Epoch 35: 50%|##### | 1/2 [00:00<00:00, 1.90it/s, loss=1.52, v_num=8]
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Epoch 36: 50%|##### | 1/2 [00:00<00:00, 2.33it/s, loss=1.52, v_num=8]
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Epoch 37: 50%|##### | 1/2 [00:00<00:00, 2.28it/s, loss=1.51, v_num=8]
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Epoch 38: 50%|##### | 1/2 [00:00<00:00, 2.31it/s, loss=1.51, v_num=8]
Epoch 38: 50%|##### | 1/2 [00:00<00:00, 2.31it/s, loss=1.5, v_num=8]
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Epoch 39: 50%|##### | 1/2 [00:00<00:00, 2.33it/s, loss=1.5, v_num=8]
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Epoch 39: 100%|##########| 2/2 [00:00<00:00, 3.37it/s, loss=1.5, v_num=8]
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Epoch 40: 50%|##### | 1/2 [00:00<00:00, 2.32it/s, loss=1.5, v_num=8]
Epoch 40: 50%|##### | 1/2 [00:00<00:00, 2.31it/s, loss=1.49, v_num=8]
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Epoch 40: 100%|##########| 2/2 [00:00<00:00, 3.36it/s, loss=1.49, v_num=8]
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Epoch 41: 50%|##### | 1/2 [00:00<00:00, 2.27it/s, loss=1.49, v_num=8]
Epoch 41: 50%|##### | 1/2 [00:00<00:00, 2.27it/s, loss=1.49, v_num=8]
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Epoch 41: 100%|##########| 2/2 [00:00<00:00, 3.31it/s, loss=1.49, v_num=8]
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Epoch 42: 50%|##### | 1/2 [00:00<00:00, 2.29it/s, loss=1.49, v_num=8]
Epoch 42: 50%|##### | 1/2 [00:00<00:00, 2.28it/s, loss=1.48, v_num=8]
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Epoch 43: 50%|##### | 1/2 [00:00<00:00, 2.34it/s, loss=1.48, v_num=8]
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Epoch 44: 50%|##### | 1/2 [00:00<00:00, 2.32it/s, loss=1.48, v_num=8]
Epoch 44: 50%|##### | 1/2 [00:00<00:00, 2.32it/s, loss=1.48, v_num=8]
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Epoch 45: 50%|##### | 1/2 [00:00<00:00, 2.28it/s, loss=1.47, v_num=8]
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Epoch 48: 50%|##### | 1/2 [00:00<00:00, 2.33it/s, loss=1.46, v_num=8]
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Epoch 49: 50%|##### | 1/2 [00:00<00:00, 2.33it/s, loss=1.46, v_num=8]
Epoch 49: 50%|##### | 1/2 [00:00<00:00, 2.33it/s, loss=1.46, v_num=8]
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Epoch 49: 100%|##########| 2/2 [00:00<00:00, 3.36it/s, loss=1.46, v_num=8]
Epoch 49: 100%|##########| 2/2 [00:00<00:00, 2.06it/s, loss=1.46, v_num=8]
Deep VCCA (private) We need to add additional private encoders and change (double) the dimensionality of the decoders.
private_encoder_1 = architectures.Encoder(
latent_dims=latent_dims, feature_size=784, variational=True
)
private_encoder_2 = architectures.Encoder(
latent_dims=latent_dims, feature_size=784, variational=True
)
private_decoder_1 = architectures.Decoder(latent_dims=2 * latent_dims, feature_size=784)
private_decoder_2 = architectures.Decoder(latent_dims=2 * latent_dims, feature_size=784)
dcca = DVCCA(
latent_dims=latent_dims,
encoders=[encoder_1, encoder_2],
decoders=[private_decoder_1, private_decoder_2],
private_encoders=[private_encoder_1, private_encoder_2],
)
dcca = CCALightning(dcca)
trainer = pl.Trainer(max_epochs=epochs, enable_checkpointing=False)
trainer.fit(dcca, train_loader, val_loader)
plot_reconstruction(dcca.model, train_dataset, 0)
plt.suptitle('DVCCA Private')
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/v1.10.1/lib/python3.7/site-packages/torch/nn/functional.py:1806: UserWarning: nn.functional.sigmoid is deprecated. Use torch.sigmoid instead.
warnings.warn("nn.functional.sigmoid is deprecated. Use torch.sigmoid instead.")
/home/docs/checkouts/readthedocs.org/user_builds/cca-zoo/envs/v1.10.1/lib/python3.7/site-packages/pytorch_lightning/trainer/data_loading.py:408: UserWarning: The number of training samples (1) 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 1: 50%|##### | 1/2 [00:00<00:00, 2.26it/s, loss=1.08e+03, v_num=9]
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Epoch 2: 50%|##### | 1/2 [00:00<00:00, 2.28it/s, loss=1.07e+03, v_num=9]
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Epoch 9: 100%|##########| 2/2 [00:00<00:00, 3.34it/s, loss=962, v_num=9]
Epoch 9: 0%| | 0/2 [00:00<?, ?it/s, loss=962, v_num=9]
Epoch 10: 0%| | 0/2 [00:00<?, ?it/s, loss=962, v_num=9]
Epoch 10: 50%|##### | 1/2 [00:00<00:00, 2.32it/s, loss=962, v_num=9]
Epoch 10: 50%|##### | 1/2 [00:00<00:00, 2.31it/s, loss=949, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 10: 100%|##########| 2/2 [00:00<00:00, 3.35it/s, loss=949, v_num=9]
Epoch 10: 0%| | 0/2 [00:00<?, ?it/s, loss=949, v_num=9]
Epoch 11: 0%| | 0/2 [00:00<?, ?it/s, loss=949, v_num=9]
Epoch 11: 50%|##### | 1/2 [00:00<00:00, 2.31it/s, loss=949, v_num=9]
Epoch 11: 50%|##### | 1/2 [00:00<00:00, 2.31it/s, loss=936, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 11: 100%|##########| 2/2 [00:00<00:00, 3.33it/s, loss=936, v_num=9]
Epoch 11: 0%| | 0/2 [00:00<?, ?it/s, loss=936, v_num=9]
Epoch 12: 0%| | 0/2 [00:00<?, ?it/s, loss=936, v_num=9]
Epoch 12: 50%|##### | 1/2 [00:00<00:00, 2.24it/s, loss=936, v_num=9]
Epoch 12: 50%|##### | 1/2 [00:00<00:00, 2.24it/s, loss=924, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 12: 100%|##########| 2/2 [00:00<00:00, 3.24it/s, loss=924, v_num=9]
Epoch 12: 0%| | 0/2 [00:00<?, ?it/s, loss=924, v_num=9]
Epoch 13: 0%| | 0/2 [00:00<?, ?it/s, loss=924, v_num=9]
Epoch 13: 50%|##### | 1/2 [00:00<00:00, 2.27it/s, loss=924, v_num=9]
Epoch 13: 50%|##### | 1/2 [00:00<00:00, 2.27it/s, loss=912, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 13: 100%|##########| 2/2 [00:00<00:00, 3.30it/s, loss=912, v_num=9]
Epoch 13: 0%| | 0/2 [00:00<?, ?it/s, loss=912, v_num=9]
Epoch 14: 0%| | 0/2 [00:00<?, ?it/s, loss=912, v_num=9]
Epoch 14: 50%|##### | 1/2 [00:00<00:00, 2.31it/s, loss=912, v_num=9]
Epoch 14: 50%|##### | 1/2 [00:00<00:00, 2.31it/s, loss=901, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 14: 100%|##########| 2/2 [00:00<00:00, 3.34it/s, loss=901, v_num=9]
Epoch 14: 0%| | 0/2 [00:00<?, ?it/s, loss=901, v_num=9]
Epoch 15: 0%| | 0/2 [00:00<?, ?it/s, loss=901, v_num=9]
Epoch 15: 50%|##### | 1/2 [00:00<00:00, 2.32it/s, loss=901, v_num=9]
Epoch 15: 50%|##### | 1/2 [00:00<00:00, 2.32it/s, loss=890, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 15: 100%|##########| 2/2 [00:00<00:00, 3.35it/s, loss=890, v_num=9]
Epoch 15: 0%| | 0/2 [00:00<?, ?it/s, loss=890, v_num=9]
Epoch 16: 0%| | 0/2 [00:00<?, ?it/s, loss=890, v_num=9]
Epoch 16: 50%|##### | 1/2 [00:00<00:00, 2.31it/s, loss=890, v_num=9]
Epoch 16: 50%|##### | 1/2 [00:00<00:00, 2.31it/s, loss=879, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 16: 100%|##########| 2/2 [00:00<00:00, 3.35it/s, loss=879, v_num=9]
Epoch 16: 0%| | 0/2 [00:00<?, ?it/s, loss=879, v_num=9]
Epoch 17: 0%| | 0/2 [00:00<?, ?it/s, loss=879, v_num=9]
Epoch 17: 50%|##### | 1/2 [00:00<00:00, 2.33it/s, loss=879, v_num=9]
Epoch 17: 50%|##### | 1/2 [00:00<00:00, 2.33it/s, loss=869, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 17: 100%|##########| 2/2 [00:00<00:00, 3.36it/s, loss=869, v_num=9]
Epoch 17: 0%| | 0/2 [00:00<?, ?it/s, loss=869, v_num=9]
Epoch 18: 0%| | 0/2 [00:00<?, ?it/s, loss=869, v_num=9]
Epoch 18: 50%|##### | 1/2 [00:00<00:00, 2.30it/s, loss=869, v_num=9]
Epoch 18: 50%|##### | 1/2 [00:00<00:00, 2.29it/s, loss=859, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 18: 100%|##########| 2/2 [00:00<00:00, 3.32it/s, loss=859, v_num=9]
Epoch 18: 0%| | 0/2 [00:00<?, ?it/s, loss=859, v_num=9]
Epoch 19: 0%| | 0/2 [00:00<?, ?it/s, loss=859, v_num=9]
Epoch 19: 50%|##### | 1/2 [00:00<00:00, 2.32it/s, loss=859, v_num=9]
Epoch 19: 50%|##### | 1/2 [00:00<00:00, 2.32it/s, loss=850, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 19: 100%|##########| 2/2 [00:00<00:00, 3.35it/s, loss=850, v_num=9]
Epoch 19: 0%| | 0/2 [00:00<?, ?it/s, loss=850, v_num=9]
Epoch 20: 0%| | 0/2 [00:00<?, ?it/s, loss=850, v_num=9]
Epoch 20: 50%|##### | 1/2 [00:00<00:00, 2.32it/s, loss=850, v_num=9]
Epoch 20: 50%|##### | 1/2 [00:00<00:00, 2.32it/s, loss=828, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 20: 100%|##########| 2/2 [00:00<00:00, 3.35it/s, loss=828, v_num=9]
Epoch 20: 0%| | 0/2 [00:00<?, ?it/s, loss=828, v_num=9]
Epoch 21: 0%| | 0/2 [00:00<?, ?it/s, loss=828, v_num=9]
Epoch 21: 50%|##### | 1/2 [00:00<00:00, 2.32it/s, loss=828, v_num=9]
Epoch 21: 50%|##### | 1/2 [00:00<00:00, 2.32it/s, loss=807, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 21: 100%|##########| 2/2 [00:00<00:00, 3.35it/s, loss=807, v_num=9]
Epoch 21: 0%| | 0/2 [00:00<?, ?it/s, loss=807, v_num=9]
Epoch 22: 0%| | 0/2 [00:00<?, ?it/s, loss=807, v_num=9]
Epoch 22: 50%|##### | 1/2 [00:00<00:00, 2.32it/s, loss=807, v_num=9]
Epoch 22: 50%|##### | 1/2 [00:00<00:00, 2.31it/s, loss=787, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 22: 100%|##########| 2/2 [00:00<00:00, 3.34it/s, loss=787, v_num=9]
Epoch 22: 0%| | 0/2 [00:00<?, ?it/s, loss=787, v_num=9]
Epoch 23: 0%| | 0/2 [00:00<?, ?it/s, loss=787, v_num=9]
Epoch 23: 50%|##### | 1/2 [00:00<00:00, 2.33it/s, loss=787, v_num=9]
Epoch 23: 50%|##### | 1/2 [00:00<00:00, 2.32it/s, loss=769, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 23: 100%|##########| 2/2 [00:00<00:00, 3.36it/s, loss=769, v_num=9]
Epoch 23: 0%| | 0/2 [00:00<?, ?it/s, loss=769, v_num=9]
Epoch 24: 0%| | 0/2 [00:00<?, ?it/s, loss=769, v_num=9]
Epoch 24: 50%|##### | 1/2 [00:00<00:00, 2.34it/s, loss=769, v_num=9]
Epoch 24: 50%|##### | 1/2 [00:00<00:00, 2.34it/s, loss=751, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 24: 100%|##########| 2/2 [00:00<00:00, 3.38it/s, loss=751, v_num=9]
Epoch 24: 0%| | 0/2 [00:00<?, ?it/s, loss=751, v_num=9]
Epoch 25: 0%| | 0/2 [00:00<?, ?it/s, loss=751, v_num=9]
Epoch 25: 50%|##### | 1/2 [00:00<00:00, 2.33it/s, loss=751, v_num=9]
Epoch 25: 50%|##### | 1/2 [00:00<00:00, 2.33it/s, loss=735, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 25: 100%|##########| 2/2 [00:00<00:00, 3.36it/s, loss=735, v_num=9]
Epoch 25: 0%| | 0/2 [00:00<?, ?it/s, loss=735, v_num=9]
Epoch 26: 0%| | 0/2 [00:00<?, ?it/s, loss=735, v_num=9]
Epoch 26: 50%|##### | 1/2 [00:00<00:00, 2.29it/s, loss=735, v_num=9]
Epoch 26: 50%|##### | 1/2 [00:00<00:00, 2.29it/s, loss=719, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 26: 100%|##########| 2/2 [00:00<00:00, 3.33it/s, loss=719, v_num=9]
Epoch 26: 0%| | 0/2 [00:00<?, ?it/s, loss=719, v_num=9]
Epoch 27: 0%| | 0/2 [00:00<?, ?it/s, loss=719, v_num=9]
Epoch 27: 50%|##### | 1/2 [00:00<00:00, 2.30it/s, loss=719, v_num=9]
Epoch 27: 50%|##### | 1/2 [00:00<00:00, 2.30it/s, loss=705, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 27: 100%|##########| 2/2 [00:00<00:00, 3.33it/s, loss=705, v_num=9]
Epoch 27: 0%| | 0/2 [00:00<?, ?it/s, loss=705, v_num=9]
Epoch 28: 0%| | 0/2 [00:00<?, ?it/s, loss=705, v_num=9]
Epoch 28: 50%|##### | 1/2 [00:00<00:00, 2.29it/s, loss=705, v_num=9]
Epoch 28: 50%|##### | 1/2 [00:00<00:00, 2.28it/s, loss=691, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 28: 100%|##########| 2/2 [00:00<00:00, 3.32it/s, loss=691, v_num=9]
Epoch 28: 0%| | 0/2 [00:00<?, ?it/s, loss=691, v_num=9]
Epoch 29: 0%| | 0/2 [00:00<?, ?it/s, loss=691, v_num=9]
Epoch 29: 50%|##### | 1/2 [00:00<00:00, 2.29it/s, loss=691, v_num=9]
Epoch 29: 50%|##### | 1/2 [00:00<00:00, 2.29it/s, loss=679, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 29: 100%|##########| 2/2 [00:00<00:00, 3.33it/s, loss=679, v_num=9]
Epoch 29: 0%| | 0/2 [00:00<?, ?it/s, loss=679, v_num=9]
Epoch 30: 0%| | 0/2 [00:00<?, ?it/s, loss=679, v_num=9]
Epoch 30: 50%|##### | 1/2 [00:00<00:00, 2.31it/s, loss=679, v_num=9]
Epoch 30: 50%|##### | 1/2 [00:00<00:00, 2.31it/s, loss=667, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 30: 100%|##########| 2/2 [00:00<00:00, 3.35it/s, loss=667, v_num=9]
Epoch 30: 0%| | 0/2 [00:00<?, ?it/s, loss=667, v_num=9]
Epoch 31: 0%| | 0/2 [00:00<?, ?it/s, loss=667, v_num=9]
Epoch 31: 50%|##### | 1/2 [00:00<00:00, 2.31it/s, loss=667, v_num=9]
Epoch 31: 50%|##### | 1/2 [00:00<00:00, 2.31it/s, loss=656, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 31: 100%|##########| 2/2 [00:00<00:00, 3.35it/s, loss=656, v_num=9]
Epoch 31: 0%| | 0/2 [00:00<?, ?it/s, loss=656, v_num=9]
Epoch 32: 0%| | 0/2 [00:00<?, ?it/s, loss=656, v_num=9]
Epoch 32: 50%|##### | 1/2 [00:00<00:00, 2.31it/s, loss=656, v_num=9]
Epoch 32: 50%|##### | 1/2 [00:00<00:00, 2.30it/s, loss=646, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 32: 100%|##########| 2/2 [00:00<00:00, 3.34it/s, loss=646, v_num=9]
Epoch 32: 0%| | 0/2 [00:00<?, ?it/s, loss=646, v_num=9]
Epoch 33: 0%| | 0/2 [00:00<?, ?it/s, loss=646, v_num=9]
Epoch 33: 50%|##### | 1/2 [00:00<00:00, 2.33it/s, loss=646, v_num=9]
Epoch 33: 50%|##### | 1/2 [00:00<00:00, 2.33it/s, loss=636, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 33: 100%|##########| 2/2 [00:00<00:00, 3.37it/s, loss=636, v_num=9]
Epoch 33: 0%| | 0/2 [00:00<?, ?it/s, loss=636, v_num=9]
Epoch 34: 0%| | 0/2 [00:00<?, ?it/s, loss=636, v_num=9]
Epoch 34: 50%|##### | 1/2 [00:00<00:00, 2.33it/s, loss=636, v_num=9]
Epoch 34: 50%|##### | 1/2 [00:00<00:00, 2.33it/s, loss=627, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 34: 100%|##########| 2/2 [00:00<00:00, 3.37it/s, loss=627, v_num=9]
Epoch 34: 0%| | 0/2 [00:00<?, ?it/s, loss=627, v_num=9]
Epoch 35: 0%| | 0/2 [00:00<?, ?it/s, loss=627, v_num=9]
Epoch 35: 50%|##### | 1/2 [00:00<00:00, 2.33it/s, loss=627, v_num=9]
Epoch 35: 50%|##### | 1/2 [00:00<00:00, 2.32it/s, loss=619, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 35: 100%|##########| 2/2 [00:00<00:00, 3.36it/s, loss=619, v_num=9]
Epoch 35: 0%| | 0/2 [00:00<?, ?it/s, loss=619, v_num=9]
Epoch 36: 0%| | 0/2 [00:00<?, ?it/s, loss=619, v_num=9]
Epoch 36: 50%|##### | 1/2 [00:00<00:00, 2.32it/s, loss=619, v_num=9]
Epoch 36: 50%|##### | 1/2 [00:00<00:00, 2.32it/s, loss=611, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 36: 100%|##########| 2/2 [00:00<00:00, 3.36it/s, loss=611, v_num=9]
Epoch 36: 0%| | 0/2 [00:00<?, ?it/s, loss=611, v_num=9]
Epoch 37: 0%| | 0/2 [00:00<?, ?it/s, loss=611, v_num=9]
Epoch 37: 50%|##### | 1/2 [00:00<00:00, 2.34it/s, loss=611, v_num=9]
Epoch 37: 50%|##### | 1/2 [00:00<00:00, 2.33it/s, loss=604, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 37: 100%|##########| 2/2 [00:00<00:00, 3.38it/s, loss=604, v_num=9]
Epoch 37: 0%| | 0/2 [00:00<?, ?it/s, loss=604, v_num=9]
Epoch 38: 0%| | 0/2 [00:00<?, ?it/s, loss=604, v_num=9]
Epoch 38: 50%|##### | 1/2 [00:00<00:00, 2.33it/s, loss=604, v_num=9]
Epoch 38: 50%|##### | 1/2 [00:00<00:00, 2.32it/s, loss=598, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 38: 100%|##########| 2/2 [00:00<00:00, 3.37it/s, loss=598, v_num=9]
Epoch 38: 0%| | 0/2 [00:00<?, ?it/s, loss=598, v_num=9]
Epoch 39: 0%| | 0/2 [00:00<?, ?it/s, loss=598, v_num=9]
Epoch 39: 50%|##### | 1/2 [00:00<00:00, 2.32it/s, loss=598, v_num=9]
Epoch 39: 50%|##### | 1/2 [00:00<00:00, 2.32it/s, loss=592, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 39: 100%|##########| 2/2 [00:00<00:00, 3.36it/s, loss=592, v_num=9]
Epoch 39: 0%| | 0/2 [00:00<?, ?it/s, loss=592, v_num=9]
Epoch 40: 0%| | 0/2 [00:00<?, ?it/s, loss=592, v_num=9]
Epoch 40: 50%|##### | 1/2 [00:00<00:00, 2.33it/s, loss=592, v_num=9]
Epoch 40: 50%|##### | 1/2 [00:00<00:00, 2.33it/s, loss=586, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 40: 100%|##########| 2/2 [00:00<00:00, 3.36it/s, loss=586, v_num=9]
Epoch 40: 0%| | 0/2 [00:00<?, ?it/s, loss=586, v_num=9]
Epoch 41: 0%| | 0/2 [00:00<?, ?it/s, loss=586, v_num=9]
Epoch 41: 50%|##### | 1/2 [00:00<00:00, 2.31it/s, loss=586, v_num=9]
Epoch 41: 50%|##### | 1/2 [00:00<00:00, 2.31it/s, loss=581, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 41: 100%|##########| 2/2 [00:00<00:00, 3.35it/s, loss=581, v_num=9]
Epoch 41: 0%| | 0/2 [00:00<?, ?it/s, loss=581, v_num=9]
Epoch 42: 0%| | 0/2 [00:00<?, ?it/s, loss=581, v_num=9]
Epoch 42: 50%|##### | 1/2 [00:00<00:00, 2.29it/s, loss=581, v_num=9]
Epoch 42: 50%|##### | 1/2 [00:00<00:00, 2.29it/s, loss=577, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 42: 100%|##########| 2/2 [00:00<00:00, 3.33it/s, loss=577, v_num=9]
Epoch 42: 0%| | 0/2 [00:00<?, ?it/s, loss=577, v_num=9]
Epoch 43: 0%| | 0/2 [00:00<?, ?it/s, loss=577, v_num=9]
Epoch 43: 50%|##### | 1/2 [00:00<00:00, 2.32it/s, loss=577, v_num=9]
Epoch 43: 50%|##### | 1/2 [00:00<00:00, 2.32it/s, loss=572, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 43: 100%|##########| 2/2 [00:00<00:00, 3.36it/s, loss=572, v_num=9]
Epoch 43: 0%| | 0/2 [00:00<?, ?it/s, loss=572, v_num=9]
Epoch 44: 0%| | 0/2 [00:00<?, ?it/s, loss=572, v_num=9]
Epoch 44: 50%|##### | 1/2 [00:00<00:00, 2.29it/s, loss=572, v_num=9]
Epoch 44: 50%|##### | 1/2 [00:00<00:00, 2.29it/s, loss=568, v_num=9]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 44: 100%|##########| 2/2 [00:00<00:00, 3.33it/s, loss=568, v_num=9]
Epoch 44: 0%| | 0/2 [00:00<?, ?it/s, loss=568, v_num=9]
Epoch 45: 0%| | 0/2 [00:00<?, ?it/s, loss=568, v_num=9]
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Epoch 45: 50%|##### | 1/2 [00:00<00:00, 2.30it/s, loss=565, v_num=9]
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Epoch 45: 100%|##########| 2/2 [00:00<00:00, 3.33it/s, loss=565, v_num=9]
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Epoch 46: 50%|##### | 1/2 [00:00<00:00, 2.31it/s, loss=561, v_num=9]
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Epoch 46: 100%|##########| 2/2 [00:00<00:00, 3.34it/s, loss=561, v_num=9]
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Epoch 47: 50%|##### | 1/2 [00:00<00:00, 2.31it/s, loss=561, v_num=9]
Epoch 47: 50%|##### | 1/2 [00:00<00:00, 2.30it/s, loss=558, v_num=9]
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Epoch 47: 100%|##########| 2/2 [00:00<00:00, 3.34it/s, loss=558, v_num=9]
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Epoch 48: 50%|##### | 1/2 [00:00<00:00, 2.31it/s, loss=558, v_num=9]
Epoch 48: 50%|##### | 1/2 [00:00<00:00, 2.31it/s, loss=556, v_num=9]
Validating: 0it [00:00, ?it/s]
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Epoch 48: 100%|##########| 2/2 [00:00<00:00, 3.35it/s, loss=556, v_num=9]
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Epoch 49: 0%| | 0/2 [00:00<?, ?it/s, loss=556, v_num=9]
Epoch 49: 50%|##### | 1/2 [00:00<00:00, 2.32it/s, loss=556, v_num=9]
Epoch 49: 50%|##### | 1/2 [00:00<00:00, 2.32it/s, loss=553, v_num=9]
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Epoch 49: 100%|##########| 2/2 [00:00<00:00, 3.36it/s, loss=553, v_num=9]
Epoch 49: 100%|##########| 2/2 [00:00<00:00, 2.06it/s, loss=553, v_num=9]
DCCAE
encoder_1 = architectures.Encoder(latent_dims=latent_dims, feature_size=784)
encoder_2 = architectures.Encoder(latent_dims=latent_dims, feature_size=784)
dcca = DCCAE(
latent_dims=latent_dims,
encoders=[encoder_1, encoder_2],
decoders=[decoder_1, decoder_2],
)
dcca = CCALightning(dcca)
trainer = pl.Trainer(max_epochs=epochs, enable_checkpointing=False)
trainer.fit(dcca, train_loader, val_loader)
plot_reconstruction(dcca.model, train_dataset, 0)
plt.suptitle('DCCAE')
plt.show()
Out:
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/home/docs/checkouts/readthedocs.org/user_builds/cca-zoo/envs/v1.10.1/lib/python3.7/site-packages/pytorch_lightning/trainer/data_loading.py:408: UserWarning: The number of training samples (1) 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]
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Epoch 0: 50%|##### | 1/2 [00:00<00:00, 2.47it/s]
Epoch 0: 50%|##### | 1/2 [00:00<00:00, 2.47it/s, loss=0.159, v_num=10]
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Epoch 0: 100%|##########| 2/2 [00:00<00:00, 3.54it/s, loss=0.159, v_num=10]
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Epoch 1: 0%| | 0/2 [00:00<?, ?it/s, loss=0.159, v_num=10]
Epoch 1: 50%|##### | 1/2 [00:00<00:00, 2.42it/s, loss=0.159, v_num=10]
Epoch 1: 50%|##### | 1/2 [00:00<00:00, 2.42it/s, loss=-0.0854, v_num=10]
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Epoch 1: 100%|##########| 2/2 [00:00<00:00, 3.47it/s, loss=-0.0854, v_num=10]
Epoch 1: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.0854, v_num=10]
Epoch 2: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.0854, v_num=10]
Epoch 2: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-0.0854, v_num=10]
Epoch 2: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-0.259, v_num=10]
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Epoch 2: 100%|##########| 2/2 [00:00<00:00, 3.55it/s, loss=-0.259, v_num=10]
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Epoch 3: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-0.259, v_num=10]
Epoch 3: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-0.368, v_num=10]
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Epoch 3: 100%|##########| 2/2 [00:00<00:00, 3.55it/s, loss=-0.368, v_num=10]
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Epoch 4: 50%|##### | 1/2 [00:00<00:00, 2.49it/s, loss=-0.368, v_num=10]
Epoch 4: 50%|##### | 1/2 [00:00<00:00, 2.49it/s, loss=-0.465, v_num=10]
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Epoch 4: 100%|##########| 2/2 [00:00<00:00, 3.56it/s, loss=-0.465, v_num=10]
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Epoch 5: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-0.465, v_num=10]
Epoch 5: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-0.529, v_num=10]
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Epoch 5: 100%|##########| 2/2 [00:00<00:00, 3.55it/s, loss=-0.529, v_num=10]
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Epoch 6: 50%|##### | 1/2 [00:00<00:00, 2.49it/s, loss=-0.529, v_num=10]
Epoch 6: 50%|##### | 1/2 [00:00<00:00, 2.49it/s, loss=-0.582, v_num=10]
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Epoch 6: 100%|##########| 2/2 [00:00<00:00, 3.56it/s, loss=-0.582, v_num=10]
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Epoch 7: 50%|##### | 1/2 [00:00<00:00, 2.49it/s, loss=-0.582, v_num=10]
Epoch 7: 50%|##### | 1/2 [00:00<00:00, 2.49it/s, loss=-0.631, v_num=10]
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Epoch 7: 100%|##########| 2/2 [00:00<00:00, 3.56it/s, loss=-0.631, v_num=10]
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Epoch 8: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-0.631, v_num=10]
Epoch 8: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-0.677, v_num=10]
Validating: 0it [00:00, ?it/s]
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Epoch 8: 100%|##########| 2/2 [00:00<00:00, 3.55it/s, loss=-0.677, v_num=10]
Epoch 8: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.677, v_num=10]
Epoch 9: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.677, v_num=10]
Epoch 9: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-0.677, v_num=10]
Epoch 9: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-0.713, v_num=10]
Validating: 0it [00:00, ?it/s]
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Epoch 9: 100%|##########| 2/2 [00:00<00:00, 3.55it/s, loss=-0.713, v_num=10]
Epoch 9: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.713, v_num=10]
Epoch 10: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.713, v_num=10]
Epoch 10: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-0.713, v_num=10]
Epoch 10: 50%|##### | 1/2 [00:00<00:00, 2.47it/s, loss=-0.745, v_num=10]
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Epoch 10: 100%|##########| 2/2 [00:00<00:00, 3.55it/s, loss=-0.745, v_num=10]
Epoch 10: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.745, v_num=10]
Epoch 11: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.745, v_num=10]
Epoch 11: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-0.745, v_num=10]
Epoch 11: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-0.77, v_num=10]
Validating: 0it [00:00, ?it/s]
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Epoch 11: 100%|##########| 2/2 [00:00<00:00, 3.55it/s, loss=-0.77, v_num=10]
Epoch 11: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.77, v_num=10]
Epoch 12: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.77, v_num=10]
Epoch 12: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-0.77, v_num=10]
Epoch 12: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-0.795, v_num=10]
Validating: 0it [00:00, ?it/s]
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Epoch 12: 100%|##########| 2/2 [00:00<00:00, 3.56it/s, loss=-0.795, v_num=10]
Epoch 12: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.795, v_num=10]
Epoch 13: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.795, v_num=10]
Epoch 13: 50%|##### | 1/2 [00:00<00:00, 2.49it/s, loss=-0.795, v_num=10]
Epoch 13: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-0.818, v_num=10]
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Epoch 13: 100%|##########| 2/2 [00:00<00:00, 3.56it/s, loss=-0.818, v_num=10]
Epoch 13: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.818, v_num=10]
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Epoch 14: 50%|##### | 1/2 [00:00<00:00, 2.47it/s, loss=-0.818, v_num=10]
Epoch 14: 50%|##### | 1/2 [00:00<00:00, 2.47it/s, loss=-0.84, v_num=10]
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Epoch 14: 100%|##########| 2/2 [00:00<00:00, 3.54it/s, loss=-0.84, v_num=10]
Epoch 14: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.84, v_num=10]
Epoch 15: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.84, v_num=10]
Epoch 15: 50%|##### | 1/2 [00:00<00:00, 2.49it/s, loss=-0.84, v_num=10]
Epoch 15: 50%|##### | 1/2 [00:00<00:00, 2.49it/s, loss=-0.86, v_num=10]
Validating: 0it [00:00, ?it/s]
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Epoch 15: 100%|##########| 2/2 [00:00<00:00, 3.57it/s, loss=-0.86, v_num=10]
Epoch 15: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.86, v_num=10]
Epoch 16: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.86, v_num=10]
Epoch 16: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-0.86, v_num=10]
Epoch 16: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-0.881, v_num=10]
Validating: 0it [00:00, ?it/s]
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Epoch 16: 100%|##########| 2/2 [00:00<00:00, 3.54it/s, loss=-0.881, v_num=10]
Epoch 16: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.881, v_num=10]
Epoch 17: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.881, v_num=10]
Epoch 17: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-0.881, v_num=10]
Epoch 17: 50%|##### | 1/2 [00:00<00:00, 2.47it/s, loss=-0.896, v_num=10]
Validating: 0it [00:00, ?it/s]
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Epoch 17: 100%|##########| 2/2 [00:00<00:00, 3.55it/s, loss=-0.896, v_num=10]
Epoch 17: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.896, v_num=10]
Epoch 18: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.896, v_num=10]
Epoch 18: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-0.896, v_num=10]
Epoch 18: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-0.912, v_num=10]
Validating: 0it [00:00, ?it/s]
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Epoch 18: 100%|##########| 2/2 [00:00<00:00, 3.55it/s, loss=-0.912, v_num=10]
Epoch 18: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.912, v_num=10]
Epoch 19: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.912, v_num=10]
Epoch 19: 50%|##### | 1/2 [00:00<00:00, 2.49it/s, loss=-0.912, v_num=10]
Epoch 19: 50%|##### | 1/2 [00:00<00:00, 2.49it/s, loss=-0.928, v_num=10]
Validating: 0it [00:00, ?it/s]
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Epoch 19: 100%|##########| 2/2 [00:00<00:00, 3.56it/s, loss=-0.928, v_num=10]
Epoch 19: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.928, v_num=10]
Epoch 20: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.928, v_num=10]
Epoch 20: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-0.928, v_num=10]
Epoch 20: 50%|##### | 1/2 [00:00<00:00, 2.47it/s, loss=-0.995, v_num=10]
Validating: 0it [00:00, ?it/s]
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Epoch 20: 100%|##########| 2/2 [00:00<00:00, 3.54it/s, loss=-0.995, v_num=10]
Epoch 20: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.995, v_num=10]
Epoch 21: 0%| | 0/2 [00:00<?, ?it/s, loss=-0.995, v_num=10]
Epoch 21: 50%|##### | 1/2 [00:00<00:00, 2.50it/s, loss=-0.995, v_num=10]
Epoch 21: 50%|##### | 1/2 [00:00<00:00, 2.50it/s, loss=-1.04, v_num=10]
Validating: 0it [00:00, ?it/s]
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Epoch 21: 100%|##########| 2/2 [00:00<00:00, 3.57it/s, loss=-1.04, v_num=10]
Epoch 21: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.04, v_num=10]
Epoch 22: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.04, v_num=10]
Epoch 22: 50%|##### | 1/2 [00:00<00:00, 2.49it/s, loss=-1.04, v_num=10]
Epoch 22: 50%|##### | 1/2 [00:00<00:00, 2.49it/s, loss=-1.07, v_num=10]
Validating: 0it [00:00, ?it/s]
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Epoch 22: 100%|##########| 2/2 [00:00<00:00, 3.55it/s, loss=-1.07, v_num=10]
Epoch 22: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.07, v_num=10]
Epoch 23: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.07, v_num=10]
Epoch 23: 50%|##### | 1/2 [00:00<00:00, 2.50it/s, loss=-1.07, v_num=10]
Epoch 23: 50%|##### | 1/2 [00:00<00:00, 2.50it/s, loss=-1.1, v_num=10]
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Epoch 23: 100%|##########| 2/2 [00:00<00:00, 3.57it/s, loss=-1.1, v_num=10]
Epoch 23: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.1, v_num=10]
Epoch 24: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.1, v_num=10]
Epoch 24: 50%|##### | 1/2 [00:00<00:00, 2.49it/s, loss=-1.1, v_num=10]
Epoch 24: 50%|##### | 1/2 [00:00<00:00, 2.49it/s, loss=-1.12, v_num=10]
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Epoch 24: 100%|##########| 2/2 [00:00<00:00, 3.57it/s, loss=-1.12, v_num=10]
Epoch 24: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.12, v_num=10]
Epoch 25: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.12, v_num=10]
Epoch 25: 50%|##### | 1/2 [00:00<00:00, 2.50it/s, loss=-1.12, v_num=10]
Epoch 25: 50%|##### | 1/2 [00:00<00:00, 2.50it/s, loss=-1.14, v_num=10]
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Epoch 25: 100%|##########| 2/2 [00:00<00:00, 3.58it/s, loss=-1.14, v_num=10]
Epoch 25: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.14, v_num=10]
Epoch 26: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.14, v_num=10]
Epoch 26: 50%|##### | 1/2 [00:00<00:00, 2.50it/s, loss=-1.14, v_num=10]
Epoch 26: 50%|##### | 1/2 [00:00<00:00, 2.50it/s, loss=-1.16, v_num=10]
Validating: 0it [00:00, ?it/s]
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Epoch 26: 100%|##########| 2/2 [00:00<00:00, 3.58it/s, loss=-1.16, v_num=10]
Epoch 26: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.16, v_num=10]
Epoch 27: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.16, v_num=10]
Epoch 27: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-1.16, v_num=10]
Epoch 27: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-1.17, v_num=10]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 27: 100%|##########| 2/2 [00:00<00:00, 3.55it/s, loss=-1.17, v_num=10]
Epoch 27: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.17, v_num=10]
Epoch 28: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.17, v_num=10]
Epoch 28: 50%|##### | 1/2 [00:00<00:00, 2.49it/s, loss=-1.17, v_num=10]
Epoch 28: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-1.19, v_num=10]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 28: 100%|##########| 2/2 [00:00<00:00, 3.56it/s, loss=-1.19, v_num=10]
Epoch 28: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.19, v_num=10]
Epoch 29: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.19, v_num=10]
Epoch 29: 50%|##### | 1/2 [00:00<00:00, 2.47it/s, loss=-1.19, v_num=10]
Epoch 29: 50%|##### | 1/2 [00:00<00:00, 2.47it/s, loss=-1.2, v_num=10]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 29: 100%|##########| 2/2 [00:00<00:00, 3.55it/s, loss=-1.2, v_num=10]
Epoch 29: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.2, v_num=10]
Epoch 30: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.2, v_num=10]
Epoch 30: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-1.2, v_num=10]
Epoch 30: 50%|##### | 1/2 [00:00<00:00, 2.47it/s, loss=-1.21, v_num=10]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 30: 100%|##########| 2/2 [00:00<00:00, 3.55it/s, loss=-1.21, v_num=10]
Epoch 30: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.21, v_num=10]
Epoch 31: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.21, v_num=10]
Epoch 31: 50%|##### | 1/2 [00:00<00:00, 2.47it/s, loss=-1.21, v_num=10]
Epoch 31: 50%|##### | 1/2 [00:00<00:00, 2.47it/s, loss=-1.22, v_num=10]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 31: 100%|##########| 2/2 [00:00<00:00, 3.55it/s, loss=-1.22, v_num=10]
Epoch 31: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.22, v_num=10]
Epoch 32: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.22, v_num=10]
Epoch 32: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-1.22, v_num=10]
Epoch 32: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-1.23, v_num=10]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 32: 100%|##########| 2/2 [00:00<00:00, 3.56it/s, loss=-1.23, v_num=10]
Epoch 32: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.23, v_num=10]
Epoch 33: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.23, v_num=10]
Epoch 33: 50%|##### | 1/2 [00:00<00:00, 2.49it/s, loss=-1.23, v_num=10]
Epoch 33: 50%|##### | 1/2 [00:00<00:00, 2.49it/s, loss=-1.24, v_num=10]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 33: 100%|##########| 2/2 [00:00<00:00, 3.56it/s, loss=-1.24, v_num=10]
Epoch 33: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.24, v_num=10]
Epoch 34: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.24, v_num=10]
Epoch 34: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-1.24, v_num=10]
Epoch 34: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-1.25, v_num=10]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 34: 100%|##########| 2/2 [00:00<00:00, 3.56it/s, loss=-1.25, v_num=10]
Epoch 34: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.25, v_num=10]
Epoch 35: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.25, v_num=10]
Epoch 35: 50%|##### | 1/2 [00:00<00:00, 2.47it/s, loss=-1.25, v_num=10]
Epoch 35: 50%|##### | 1/2 [00:00<00:00, 2.47it/s, loss=-1.26, v_num=10]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 35: 100%|##########| 2/2 [00:00<00:00, 3.53it/s, loss=-1.26, v_num=10]
Epoch 35: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.26, v_num=10]
Epoch 36: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.26, v_num=10]
Epoch 36: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-1.26, v_num=10]
Epoch 36: 50%|##### | 1/2 [00:00<00:00, 2.47it/s, loss=-1.27, v_num=10]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 36: 100%|##########| 2/2 [00:00<00:00, 3.54it/s, loss=-1.27, v_num=10]
Epoch 36: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.27, v_num=10]
Epoch 37: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.27, v_num=10]
Epoch 37: 50%|##### | 1/2 [00:00<00:00, 2.47it/s, loss=-1.27, v_num=10]
Epoch 37: 50%|##### | 1/2 [00:00<00:00, 2.47it/s, loss=-1.28, v_num=10]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 37: 100%|##########| 2/2 [00:00<00:00, 3.54it/s, loss=-1.28, v_num=10]
Epoch 37: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.28, v_num=10]
Epoch 38: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.28, v_num=10]
Epoch 38: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-1.28, v_num=10]
Epoch 38: 50%|##### | 1/2 [00:00<00:00, 2.47it/s, loss=-1.29, v_num=10]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 38: 100%|##########| 2/2 [00:00<00:00, 3.54it/s, loss=-1.29, v_num=10]
Epoch 38: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.29, v_num=10]
Epoch 39: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.29, v_num=10]
Epoch 39: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-1.29, v_num=10]
Epoch 39: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-1.29, v_num=10]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 39: 100%|##########| 2/2 [00:00<00:00, 3.54it/s, loss=-1.29, v_num=10]
Epoch 39: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.29, v_num=10]
Epoch 40: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.29, v_num=10]
Epoch 40: 50%|##### | 1/2 [00:00<00:00, 2.49it/s, loss=-1.29, v_num=10]
Epoch 40: 50%|##### | 1/2 [00:00<00:00, 2.49it/s, loss=-1.3, v_num=10]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 40: 100%|##########| 2/2 [00:00<00:00, 3.56it/s, loss=-1.3, v_num=10]
Epoch 40: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.3, v_num=10]
Epoch 41: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.3, v_num=10]
Epoch 41: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-1.3, v_num=10]
Epoch 41: 50%|##### | 1/2 [00:00<00:00, 2.47it/s, loss=-1.31, v_num=10]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 41: 100%|##########| 2/2 [00:00<00:00, 3.55it/s, loss=-1.31, v_num=10]
Epoch 41: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.31, v_num=10]
Epoch 42: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.31, v_num=10]
Epoch 42: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-1.31, v_num=10]
Epoch 42: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-1.31, v_num=10]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 42: 100%|##########| 2/2 [00:00<00:00, 3.55it/s, loss=-1.31, v_num=10]
Epoch 42: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.31, v_num=10]
Epoch 43: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.31, v_num=10]
Epoch 43: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-1.31, v_num=10]
Epoch 43: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-1.32, v_num=10]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 43: 100%|##########| 2/2 [00:00<00:00, 3.54it/s, loss=-1.32, v_num=10]
Epoch 43: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.32, v_num=10]
Epoch 44: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.32, v_num=10]
Epoch 44: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-1.32, v_num=10]
Epoch 44: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-1.33, v_num=10]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 44: 100%|##########| 2/2 [00:00<00:00, 3.55it/s, loss=-1.33, v_num=10]
Epoch 44: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.33, v_num=10]
Epoch 45: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.33, v_num=10]
Epoch 45: 50%|##### | 1/2 [00:00<00:00, 2.49it/s, loss=-1.33, v_num=10]
Epoch 45: 50%|##### | 1/2 [00:00<00:00, 2.49it/s, loss=-1.33, v_num=10]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 45: 100%|##########| 2/2 [00:00<00:00, 3.57it/s, loss=-1.33, v_num=10]
Epoch 45: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.33, v_num=10]
Epoch 46: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.33, v_num=10]
Epoch 46: 50%|##### | 1/2 [00:00<00:00, 2.48it/s, loss=-1.33, v_num=10]
Epoch 46: 50%|##### | 1/2 [00:00<00:00, 2.47it/s, loss=-1.34, v_num=10]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 46: 100%|##########| 2/2 [00:00<00:00, 3.55it/s, loss=-1.34, v_num=10]
Epoch 46: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.34, v_num=10]
Epoch 47: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.34, v_num=10]
Epoch 47: 50%|##### | 1/2 [00:00<00:00, 2.47it/s, loss=-1.34, v_num=10]
Epoch 47: 50%|##### | 1/2 [00:00<00:00, 2.47it/s, loss=-1.34, v_num=10]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 47: 100%|##########| 2/2 [00:00<00:00, 3.53it/s, loss=-1.34, v_num=10]
Epoch 47: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.34, v_num=10]
Epoch 48: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.34, v_num=10]
Epoch 48: 50%|##### | 1/2 [00:00<00:00, 2.47it/s, loss=-1.34, v_num=10]
Epoch 48: 50%|##### | 1/2 [00:00<00:00, 2.46it/s, loss=-1.34, v_num=10]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 48: 100%|##########| 2/2 [00:00<00:00, 3.54it/s, loss=-1.34, v_num=10]
Epoch 48: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.34, v_num=10]
Epoch 49: 0%| | 0/2 [00:00<?, ?it/s, loss=-1.34, v_num=10]
Epoch 49: 50%|##### | 1/2 [00:00<00:00, 2.47it/s, loss=-1.34, v_num=10]
Epoch 49: 50%|##### | 1/2 [00:00<00:00, 2.47it/s, loss=-1.35, v_num=10]
Validating: 0it [00:00, ?it/s]
Validating: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 49: 100%|##########| 2/2 [00:00<00:00, 3.54it/s, loss=-1.35, v_num=10]
Epoch 49: 100%|##########| 2/2 [00:00<00:00, 2.13it/s, loss=-1.35, v_num=10]
Total running time of the script: ( 2 minutes 41.850 seconds)