Comments (2)
It feels like solution is very simple: not to upcast but raise a warning...
from pytorch.
It feels like solution is very simple: not to upcast but raise a warning...
Or is it possible to keep the tensor dtype
whenever you call WeightedRandomSampler
with user's choice?
Or handle the tensor type dynamically like weights_tensor = torch.as_tensor(weights, dtype=torch.float32) if weights.device.type=="mps" else torch.as_tensor(weights, dtype=torch.float64)
?
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