conv: Create a Convolutional Layer for a CNN Architecture

In citoverse/cito: Building and Training Neural Networks

Create a Convolutional Layer for a CNN Architecture

Description

This function creates a conv layer object of class citolayer for use in constructing a Convolutional Neural Network (CNN) architecture. The resulting layer object can be passed to the create_architecture function to define the structure of the network.

Usage

conv(
  n_kernels = NULL,
  kernel_size = NULL,
  stride = NULL,
  padding = NULL,
  dilation = NULL,
  bias = NULL,
  activation = NULL,
  normalization = NULL,
  dropout = NULL
)

Arguments

n_kernels	(integer) The number of kernels (or filters) in this layer.
kernel_size	(integer or tuple) The size of the kernels in this layer. Use a tuple if the kernel size is different in each dimension.
stride	(integer or tuple) The stride of the kernels in this layer. If NULL, the stride is set to the kernel size. Use a tuple if the stride is different in each dimension.
padding	(integer or tuple) The amount of zero-padding added to the input on both sides. Use a tuple if the padding is different in each dimension.
dilation	(integer or tuple) The dilation of the kernels in this layer. Use a tuple if the dilation is different in each dimension.
bias	(boolean) If TRUE, a learnable bias is added to the kernels of this layer.
activation	(character) The activation function applied after this layer. Supported activation functions include "relu", "leaky_relu", "tanh", "elu", "rrelu", "prelu", "softplus", "celu", "selu", "gelu", "relu6", "sigmoid", "softsign", "hardtanh", "tanhshrink", "softshrink", "hardshrink", "log_sigmoid".
normalization	(boolean) If TRUE, batch normalization is applied after this layer.
dropout	(numeric) The dropout rate for this layer. Set to 0 to disable dropout.

Details

This function creates a conv layer object, which is used to define a convolutional layer in a CNN architecture. Parameters that are not specified (and thus set to NULL) will be filled with default values provided to the create_architecture function.

Value

An S3 object of class "conv" "citolayer", representing a convolutional layer in the CNN architecture.

Author(s)

Armin Schenk

See Also

create_architecture

Examples

if(torch::torch_is_installed()){
library(cito)

# A convolutional layer where all available parameters are assigned
# No value will be overwritten by 'create_architecture()'
layer1 <- conv(10, 3, 1, 0, 1, TRUE, "relu", FALSE, 0.5)

# A convolutional layer where only the activation function is assigned
# n_kernels, kernel_size, stride, padding, dilation, bias,
# normalization and dropout are filled with the defaults
# passed to the 'create_architecture()' function
layer2 <- conv(activation="selu")
}

citoverse/cito documentation built on Jan. 16, 2025, 11:49 p.m.