packed_inception_time#

torch_uncertainty.models.packed_inception_time(in_channels, num_classes, num_estimators, alpha, gamma=1, kernel_size=40, embed_dim=32, num_blocks=6, dropout=0.0, residual=True)[source]#

Packed-Ensembles of InceptionTime.

Parameters:

  • in_channels (int) – Number of input channels.

  • num_classes (int) – Number of output classes.

  • num_estimators (int) – Number of estimators for Packed-Ensembles.

  • alpha (float) – Alpha parameter for Packed-Ensembles.

  • gamma (int) – Gamma parameter for Packed-Ensembles. Default is 1.

  • kernel_size (int) – Size of the convolutional kernels. Default is 40.

  • embed_dim (int) – Dimension of the embedding. Default is 32.

  • num_blocks (int) – Number of inception blocks. Default is 6.

  • dropout (float) – Dropout rate. Default is 0.0.

  • residual (bool) – Whether to use residual connections. Default is True.

Returns:

An instance of the InceptionTime model.

Return type:

_InceptionTime