nnlayer_norm: Create response normalization layer.

Description Usage Arguments See Also

View source: R/nnlayer.R

Description

Create response normalization layer.

Usage

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nnlayer_norm(layer, kernelshape, inputshape, name, inputname, stride, lowerpad,
  alpha = 1e-04, beta = 0.75, offset = 1, AvgOverFullKernel = TRUE,
  activation = NA)

Arguments

layer

A layer object, e.g. using nnlayer_input, or NULL

kernelshape

Numeric vector describing the number of inputs in each dimension, e.g. c(3, 15, 15)

inputshape

Numeric vector describing the number of inputs in each dimension, e.g. c(3, 15, 15). If layer is specified, this can be NULL.

name

Name of the layer

inputname

Name of the preceding layer. If layer is specified, this can be NULL.

stride

Numeric vector describing the number of inputs in each dimension, e.g. c(3, 15, 15).

lowerpad

Numeric vector describing the number of inputs in each dimension, e.g. c(3, 15, 15).

alpha

Alpha

beta

Beta

offset

Offset

AvgOverFullKernel

Logical. Take average over full kernel.

activation

Activation function, e.g. rlinear

See Also

Other layer.definition.functions: nnlayer_conv, nnlayer_full, nnlayer_input, nnlayer_output, nnlayer_pool


andrie/mxNeuralNetExtra documentation built on June 3, 2017, 7:02 p.m.