R/new-py-types.R

mark_active

Define new keras types

Description

These functions can be used to make custom objects that fit in the family of existing keras types. For example, new_layer_class() will return a class constructor, an object that behaves like other layer functions such as layer_dense(). new_callback_class() will return an object that behaves similarly to other callback functions, like callback_reduce_lr_on_plateau(), and so on. All arguments with a default NULL value are optional methods that can be provided.

Usage

 
mark_active(x) 
 
new_metric_class(classname, ..., initialize, update_state, result) 
 
new_loss_class(classname, ..., call = NULL) 
 
new_callback_class( 
  classname, 
  ..., 
  on_epoch_begin = NULL, 
  on_epoch_end = NULL, 
  on_train_begin = NULL, 
  on_train_end = NULL, 
  on_batch_begin = NULL, 
  on_batch_end = NULL, 
  on_predict_batch_begin = NULL, 
  on_predict_batch_end = NULL, 
  on_predict_begin = NULL, 
  on_predict_end = NULL, 
  on_test_batch_begin = NULL, 
  on_test_batch_end = NULL, 
  on_test_begin = NULL, 
  on_test_end = NULL, 
  on_train_batch_begin = NULL, 
  on_train_batch_end = NULL 
) 
 
new_model_class( 
  classname, 
  ..., 
  initialize = NULL, 
  call = NULL, 
  train_step = NULL, 
  predict_step = NULL, 
  test_step = NULL, 
  compute_loss = NULL, 
  compute_metrics = NULL 
) 
 
new_layer_class( 
  classname, 
  ..., 
  initialize = NULL, 
  build = NULL, 
  call = NULL, 
  get_config = NULL 
) 

Arguments

Arguments	Description
x	A function that should be converted to an active property of the class type.
classname	The classname as a string. Convention is for the classname to be a CamelCase version of the constructor.
…	Additional fields and methods for the new type.
initialize, build, call, get_config, on_epoch_begin, on_epoch_end, on_train_begin, on_train_end, on_batch_begin, on_batch_end, on_predict_batch_begin, on_predict_batch_end, on_predict_begin, on_predict_end, on_test_batch_begin, on_test_batch_end, on_test_begin, on_test_end, on_train_batch_begin, on_train_batch_end, update_state, result, train_step, predict_step, test_step, compute_loss, compute_metrics	Optional methods that can be overridden.

Details

mark_active() is a decorator that can be used to indicate functions that should become active properties of the class instances.

Value

A new class generator object that inherits from the appropriate Keras base class.