local_response_normalization¶
dragon.vm.tensorflow.nn.
local_response_normalization
(
input,
depth_radius=5,
bias=1.0,
alpha=1.0,
beta=0.5,
data_format='NHWC',
name=None
)[source]¶Apply the local response normalization. [Krizhevsky et.al, 2012].
The normalization is defined as:
\[out_{i} = x_{i}\left(k + \frac{\alpha}{n} \sum_{j=\max(0, i-n/2)}^{\min(N-1,i+n/2)}x_{j}^2 \right)^{-\beta} \]- Parameters:
- input (dragon.Tensor) – The input tensor.
- depth_radius (int, optional, default=5) – The number of neighbouring channels to sum over.
- bias (float, optional, default=1.) – The bias constant \(k\).
- alpha (float, optional, default=1.) – The scale value \(\alpha\).
- beta (float, optional, default=0.5) – The exponent value \(\beta\).
- data_format (str, optional, default='NHWC') –
'NCHW'
or'NHWC'
. - name (str, optional) – The operation name.
- Returns:
dragon.Tensor – The output tensor.