creates a 'conv' 'citolayer' object that is used by create_architecture.
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
(int) amount of kernels in this layer
- kernel_size
(int or tuple) size of the kernels in this layer. Use a tuple if the kernel size isn't equal in all dimensions
- stride
(int or tuple) stride of the kernels in this layer. NULL sets the stride equal to the kernel size. Use a tuple if the stride isn't equal in all dimensions
- padding
(int or tuple) zero-padding added to both sides of the input. Use a tuple if the padding isn't equal in all dimensions
- dilation
(int or tuple) dilation of the kernels in this layer. Use a tuple if the dilation isn't equal in all dimensions
- bias
(boolean) if TRUE, adds a learnable bias to the kernels of this layer
- activation
(string) activation function that is used after this layer. The following activation functions are supported: "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 used after this layer
- dropout
(float) dropout rate of this layer. Set to 0 for no dropout
Details
This function creates a 'conv' 'citolayer' object that is passed to the create_architecture function.
The parameters that aren't assigned here (and are therefore still NULL) are filled with the default values passed to create_architecture.