Orthogonal initialization
Fills the input Tensor
with a (semi) orthogonal matrix, as
described in Exact solutions to the nonlinear dynamics of learning in deep linear neural networks
- Saxe, A. et al. (2013). The input tensor must have
at least 2 dimensions, and for tensors with more than 2 dimensions the
trailing dimensions are flattened.
nn_init_orthogonal_(tensor, gain = 1)
tensor |
an n-dimensional |
gain |
optional scaling factor |
if (torch_is_installed()) { w <- torch_empty(3,5) nn_init_orthogonal_(w) }
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