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20 lines
546 B
Python
20 lines
546 B
Python
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import torch
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class NumericCalibration(torch.nn.Module):
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def __init__(
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self,
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pos_downsampling_rate: float,
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neg_downsampling_rate: float,
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):
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super().__init__()
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# Using buffer to make sure they are on correct device (and not moved every time).
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# Will also be part of state_dict.
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self.register_buffer(
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"ratio", torch.as_tensor(neg_downsampling_rate / pos_downsampling_rate), persistent=True
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)
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def forward(self, probs: torch.Tensor):
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return probs * self.ratio / (1.0 - probs + (self.ratio * probs))
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