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