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Home Page: https://arxiv.org/abs/2206.08888
License: Apache License 2.0
Vectorization techniques for fast population-based training.
Home Page: https://arxiv.org/abs/2206.08888
License: Apache License 2.0
You implement LayerNorm in VectorizedLinearLayer but the LayerNorm input is "self._out_features, self._population_size", which means that the eps in LayerNorm is self._population_size. Could you please explain why ?
self._layer_norm = (
torch.nn.LayerNorm(self._out_features, self._population_size)
if use_layer_norm
else None
)
def forward(self, x: torch.Tensor) -> torch.Tensor:
assert x.shape[0] == self._population_size
if self._layer_norm is not None:
return self._layer_norm(x.matmul(self.weight) + self.bias)
return x.matmul(self.weight) + self.bias
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