optimum/graphcore/models/bert/modeling_bert.py
def truncated_normal_(tensor, mean=0, std=1):
            """
            Truncated Normal distribution, truncated at 2 sigma
            """
            r = torch.tensor(truncnorm.rvs(-2, 2, loc=mean, scale=std, size=tensor.shape))
            tensor.data.copy_(r)

            Truncated Normal distribution, truncated at 2 sigma
            
Truncated Normal distribution, truncated at 2 sigma
Truncated Normal distribution truncated at 2 sigma
def truncated_normal_(tensor, mean=0, std=1):
            r = torch.tensor(truncnorm.rvs(-2, 2, loc=mean, scale=std, size=tensor.shape))
            tensor.data.copy_(r)
def truncated_normal_ ( tensor , mean = 0 , std = 1 ) : r = torch . tensor ( truncnorm . rvs ( - 2 , 2 , loc = mean , scale = std , size = tensor . shape ) ) tensor . data . copy_ ( r )
Truncated Normal distribution, truncated at 2 sigma
Truncated Normal distribution truncated at 2 sigma
"""
            Truncated Normal distribution, truncated at 2 sigma
            """
tensor
mean
std