tyxe/guides.py
def init_to_normal(site, loc=0., std="xavier", gain=1.):
    """Helper function to set site value to a sample from a normal distribution with variance according to
    xavier/kaiming/radford neural network weight initialization methods."""
    if isinstance(std, str):
        std = util.calculate_prior_std(std, site["fn"].sample(), gain=gain)
    return init_to_sample(site, dist.Normal(loc, std))
Helper function to set site value to a sample from a normal distribution with variance according to
    xavier/kaiming/radford neural network weight initialization methods.
Helper function to set site value to a sample from a normal distribution with variance according to
xavier/kaiming/radford neural network weight initialization methods.
Helper function to set site value to a sample from a normal distribution with variance according to xavier / kaiming / radford neural network weight initialization methods .
def init_to_normal(site, loc=0., std="xavier", gain=1.):
    if isinstance(std, str):
        std = util.calculate_prior_std(std, site["fn"].sample(), gain=gain)
    return init_to_sample(site, dist.Normal(loc, std))
def init_to_normal ( site , loc = 0. , std = "xavier" , gain = 1. ) : if isinstance ( std , str ) : std = util . calculate_prior_std ( std , site [ "fn" ] . sample ( ) , gain = gain ) return init_to_sample ( site , dist . Normal ( loc , std ) )
Helper function to set site value to a sample from a normal distribution with variance according to
xavier/kaiming/radford neural network weight initialization methods.
Helper function to set site value to a sample from a normal distribution with variance according to xavier / kaiming / radford neural network weight initialization methods .
"""Helper function to set site value to a sample from a normal distribution with variance according to
    xavier/kaiming/radford neural network weight initialization methods."""
site
loc
std
gain