Index# class myoverse.transforms.Index(indices, dim='time', **kwargs)[source]# Index/slice along a dimension. Parameters: indices (int | slice | list[int]) – Indices to select. dim (str) – Dimension to index. Examples >>> x = torch.randn(64, 2048, names=('channel', 'time')) >>> # Select first 10 channels >>> index = Index(slice(0, 10), dim='channel') >>> y = index(x) # Shape: (10, 2048) Methods __init__(indices[, dim]) _apply(x) Apply the transform.