torch / nn / torch.nn
LocalResponseNorm¶
-
class
torch.nn.
LocalResponseNorm
(size: int, alpha: float = 0.0001, beta: float = 0.75, k: float = 1.0)[source]¶ Applies local response normalization over an input signal composed of several input planes, where channels occupy the second dimension. Applies normalization across channels.
- Parameters
size – amount of neighbouring channels used for normalization
alpha – multiplicative factor. Default: 0.0001
beta – exponent. Default: 0.75
k – additive factor. Default: 1
- Shape:
Input:
Output: (same shape as input)
Examples:
>>> lrn = nn.LocalResponseNorm(2) >>> signal_2d = torch.randn(32, 5, 24, 24) >>> signal_4d = torch.randn(16, 5, 7, 7, 7, 7) >>> output_2d = lrn(signal_2d) >>> output_4d = lrn(signal_4d)
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