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ReLU6

class torch.ao.nn.quantized.ReLU6(inplace=False)[source][source]

Applies the element-wise function:

ReLU6(x)=min(max(x0,x),q(6))\text{ReLU6}(x) = \min(\max(x_0, x), q(6)), where x0x_0 is the zero_point, and q(6)q(6) is the quantized representation of number 6.

Parameters

inplace (bool) – can optionally do the operation in-place. Default: False

Shape:
  • Input: (N,)(N, *) where * means, any number of additional dimensions

  • Output: (N,)(N, *), same shape as the input

../_images/ReLU6.png

Examples:

>>> m = nn.quantized.ReLU6()
>>> input = torch.randn(2)
>>> input = torch.quantize_per_tensor(input, 1.0, 0, dtype=torch.qint32)
>>> output = m(input)

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