Tenbatsu24
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# Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This software may be used and distributed in accordance with
# the terms of the DINOv3 License Agreement.
import torch
from torch import Tensor, nn
class RMSNorm(nn.Module):
def __init__(self, dim: int, eps: float = 1e-5):
super().__init__()
self.weight = nn.Parameter(torch.ones(dim))
self.eps = eps
def reset_parameters(self) -> None:
nn.init.constant_(self.weight, 1)
def _norm(self, x: Tensor) -> Tensor:
return x * torch.rsqrt(x.pow(2).mean(-1, keepdim=True) + self.eps)
def forward(self, x: Tensor) -> Tensor:
output = self._norm(x.float()).type_as(x)
return output * self.weight