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
uniform 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_uniform_(w, mode = "fan_in", nonlinearity = "leaky_relu")
}
#> torch_tensor
#> -0.3794 -0.0284 0.9853 0.3868 -0.7160
#> 0.0447 0.2813 -0.1852 -0.3451 0.7731
#> 0.6844 -0.9016 -0.7935 -0.9021 -0.8505
#> [ CPUFloatType{3,5} ]