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A denormalization example in the dockblock for transforms.Normalize #8835

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A denormalization example in the dockblock for transforms.Normalize #8835

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8 changes: 8 additions & 0 deletions torchvision/transforms/transforms.py
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Expand Up @@ -252,6 +252,14 @@ class Normalize(torch.nn.Module):
.. note::
This transform acts out of place, i.e., it does not mutate the input tensor.

Passing 0 as mean and 1 as std for a channel keeps the values in this channel unchanged.

As follows from the output formula above, to denormalize the tensor you can apply Normalize again with the following changes
in the mean and std:

* ``mean=[-m / s for m, s in zip(mean, std)]``
* ``std=[1.0 / s for s in std]``

Args:
mean (sequence): Sequence of means for each channel.
std (sequence): Sequence of standard deviations for each channel.
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