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chore: update siglip_vit.py

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orignal -> original
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Ikko Eltociear Ashimine 2024-10-19 07:16:39 +09:00 committed by GitHub
parent 659982f413
commit 1a42fa6d0a
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janus/models/siglip_vit.py
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@ -92,7 +92,7 @@ def _no_grad_trunc_normal_(tensor, mean, std, a, b):
def trunc_normal_(tensor, mean=0.0, std=1.0, a=-2.0, b=2.0):
# type: (torch.Tensor, float, float, float, float) -> torch.Tensor
r"""The original timm.models.layers.weight_init.trunc_normal_ can not handle bfloat16 yet, here we first
convert the tensor to float32, apply the trunc_normal_() in float32, and then convert it back to its orignal dtype.
convert the tensor to float32, apply the trunc_normal_() in float32, and then convert it back to its original dtype.
Fills the input Tensor with values drawn from a truncated normal distribution. The values are effectively drawn
from the normal distribution :math:`\mathcal{N}(\text{mean}, \text{std}^2)`
with values outside :math:`[a, b]` redrawn until they are within