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
#>  0.5561  0.5770  0.8912  0.0324  0.5604
#> -0.7783  0.9446  0.9140  1.0139  1.0290
#>  0.4883  1.0078 -0.4267 -0.5072 -0.8373
#> [ CPUFloatType{3,5} ]