Function he_normal

python/singa/initializer.py:132–146

He normal initializer. It draws samples from a truncated normal distribution centered on 0 with `stddev = sqrt(2 / fan_in)` where `fan_in` is the number of input units in the weight tensor. # Arguments t(Tensor):the tensor to be filled in. # References - [Delvi

(t)

def he_normal(t):
    """He normal initializer.

    It draws samples from a truncated normal distribution centered on 0
    with `stddev = sqrt(2 / fan_in)`
    where `fan_in` is the number of input units in the weight tensor.

    # Arguments
        t(Tensor):the tensor to be filled in.

    # References
        - [Delving Deep into Rectifiers: Surpassing Human-Level Performance on
           ImageNet Classification](http://arxiv.org/abs/1502.01852)
    """
    _random_fill(t, scale=2., mode='fan_in', distribution='normal')

def lecun_normal(t):
    """LeCun normal initializer.