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
#> 1.0094 0.3753 -0.9179 -0.7583 -0.9979
#> -0.8419 0.9052 -0.4154 -0.8205 0.0496
#> 0.2092 -0.5503 -0.7778 -0.0985 0.0020
#> [ CPUFloatType{3,5} ]