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
#> 0.3532 -0.1987 0.6656 0.4023 0.9937
#> 0.5454 0.9876 -0.2641 -0.5014 0.9930
#> 0.2620 0.5646 -0.3691 -0.9343 -0.7164
#> [ CPUFloatType{3,5} ]