Fills the input Tensor
with values according to the method
described in Delving deep into rectifiers: Surpassing human-level performance on ImageNet classification
- He, K. et al. (2015), using a
normal distribution.
Arguments
- tensor
an n-dimensional
torch.Tensor
- a
the negative slope of the rectifier used after this layer (only used with
'leaky_relu'
)- mode
either 'fan_in' (default) or 'fan_out'. Choosing 'fan_in' preserves the magnitude of the variance of the weights in the forward pass. Choosing 'fan_out' preserves the magnitudes in the backwards pass.
- nonlinearity
the non-linear function. recommended to use only with 'relu' or 'leaky_relu' (default).
Examples
if (torch_is_installed()) {
w <- torch_empty(3, 5)
nn_init_kaiming_normal_(w, mode = "fan_in", nonlinearity = "leaky_relu")
}
#> torch_tensor
#> 0.2824 -0.0212 0.2276 -0.5135 0.3246
#> 0.7331 -0.4224 0.7006 -1.0394 -0.2069
#> -0.0020 -1.2986 0.1520 -0.5600 0.3546
#> [ CPUFloatType{3,5} ]