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I botched this in #7717 when moving from
dtype=torch.float32
todtype=None
as default value. When passingdtype=None
(or more likely don't passdtype
at all), without this fix we also passNone
toget_max_value
and get backvision/torchvision/transforms/_functional_tensor.py
Lines 52 to 55 in 1402eb8
This would be the right maximum value for floating point images, but since we have also switched to
torch.uint8
as default dtype, we now request an integer tensor with bounds [0, 1) aka a full zero tensor.