ksuit.utils.training.running_stats¶
Classes¶
Calculates statistics of data (min, max, mean and variance) for data normalization purposes. |
Module Contents¶
- class ksuit.utils.training.running_stats.RunningStats(name=None)¶
Calculates statistics of data (min, max, mean and variance) for data normalization purposes.
- Parameters:
name (str | None)
- name = None¶
- push_tensor(x, dim=1)¶
Add a tensor to the statistics. Calculations are carried out in float64 to avoid numerical imprecision. :param x: Tensor with data. :param dim: Which dim (i.e., axis) contains the feature dimension. For example, in a point cloud with shape
(num_points, 3) dim=1 calculates the stats of the x, y and z positions. In an RGB image with shape (batch_size, num_channels, height, width), dim=1 calculates the per-channel statistics.
- Parameters:
x (torch.Tensor)
dim (int)
- Return type:
None
- property min: torch.Tensor¶
- Return type:
torch.Tensor
- property max: torch.Tensor¶
- Return type:
torch.Tensor
- property mean: torch.Tensor¶
- Return type:
torch.Tensor
- property var: torch.Tensor¶
- Return type:
torch.Tensor
- property std: torch.Tensor¶
- Return type:
torch.Tensor
- property logmean: torch.Tensor¶
- Return type:
torch.Tensor
- property logvar: torch.Tensor¶
- Return type:
torch.Tensor
- property logstd: torch.Tensor¶
- Return type:
torch.Tensor