lfxai.utils.math module
- log_density_gaussian(x, mu, logvar)
Calculates log density of a Gaussian.
Parameters:
- x: torch.Tensor or np.ndarray or float
Value at which to compute the density.
- mu: torch.Tensor or np.ndarray or float
Mean.
- logvar: torch.Tensor or np.ndarray or float
Log variance.
- log_importance_weight_matrix(batch_size, dataset_size)
Calculates a log importance weight matrix
Parameters:
- batch_size: int
number of training images in the batch
- dataset_size: int
number of training images in the dataset
- matrix_log_density_gaussian(x, mu, logvar)
Calculates log density of a Gaussian for all combination of bacth pairs of x and mu. I.e. return tensor of shape (batch_size, batch_size, dim) instead of (batch_size, dim) in the usual log density.
Parameters:
- x: torch.Tensor
Value at which to compute the density. Shape: (batch_size, dim).
- mu: torch.Tensor
Mean. Shape: (batch_size, dim).
- logvar: torch.Tensor
Log variance. Shape: (batch_size, dim).
- batch_size: int
number of training images in the batch