new_layer_class: Layer

Description

new_layer_class() is an alias for Layer(). See ?Layer() for the full documentation.

Usage

new_layer_class(
  classname,
  initialize = NULL,
  call = NULL,
  build = NULL,
  get_config = NULL,
  ...,
  public = list(),
  private = list(),
  inherit = NULL,
  parent_env = parent.frame()
)

Value

A composing layer constructor, with similar behavior to other layer functions like layer_dense(). The first argument of the returned function will be object, enabling initialize()ing and call() the layer in one step while composing the layer with the pipe, like

layer_foo <- Layer("Foo", ....)
output <- inputs |> layer_foo()

To only initialize() a layer instance and not call() it, pass a missing or NULL value to object, or pass all arguments to initialize() by name.

layer <- layer_dense(units = 2, activation = "relu")
layer <- layer_dense(NULL, 2, activation = "relu")
layer <- layer_dense(, 2, activation = "relu")
# then you can call() the layer in a separate step
outputs <- inputs |> layer()

Arguments

classname: String, the name of the custom class. (Conventionally, CamelCase).
initialize, call, build, get_config: Recommended methods to implement. See description and details sections.
..., public: Additional methods or public members of the custom class.
private: Named list of R objects (typically, functions) to include in instance private environments. private methods will have all the same symbols in scope as public methods (See section "Symbols in Scope"). Each instance will have it's own private environment. Any objects in private will be invisible from the Keras framework and the Python runtime.
inherit: What the custom class will subclass. By default, the base keras class.
parent_env: The R environment that all class methods will have as a grandparent.