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Variational Callbacks

Useful callbacks for GANs, variational-autoencoders or anything with latent spaces.

Note

We rely on the community to keep these updated and working. If something doesn’t work, we’d really appreciate a contribution to fix!


Latent Dim Interpolator

Interpolates latent dims.

Example output:

Example latent space interpolation
class pl_bolts.callbacks.variational.LatentDimInterpolator(interpolate_epoch_interval=20, range_start=- 5, range_end=5, steps=11, num_samples=2, normalize=True)[source]

Bases: pytorch_lightning.callbacks.

Warning

The feature LatentDimInterpolator is currently marked under review. The compatibility with other Lightning projects is not guaranteed and API may change at any time. The API and functionality may change without warning in future releases. More details: https://lightning-bolts.readthedocs.io/en/latest/stability.html

Interpolates the latent space for a model by setting all dims to zero and stepping through the first two dims increasing one unit at a time.

Default interpolates between [-5, 5] (-5, -4, -3, …, 3, 4, 5)

Example:

from pl_bolts.callbacks import LatentDimInterpolator

Trainer(callbacks=[LatentDimInterpolator()])
Parameters
  • interpolate_epoch_interval (int) – default 20

  • range_start (int) – default -5

  • range_end (int) – default 5

  • steps (int) – number of step between start and end

  • num_samples (int) – default 2

  • normalize (bool) – default True (change image to (0, 1) range)

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