LostTech.TensorFlow : API Documentation

Type Normalization

Namespace tensorflow.python.keras.layers.preprocessing.normalization_v1

Parent Normalization

Interfaces INormalization

Methods

Properties

Public instance methods

void adapt(ndarray data, bool reset_state)

void adapt(IEnumerable<int> data, bool reset_state)

void adapt(Dataset data, bool reset_state)

void adapt(Dataset data, bool reset_state)

object adapt_dyn(object data, ImplicitContainer<T> reset_state)

void set_weights(IEnumerable<object> weights)

object set_weights_dyn(object weights)

Public properties

PythonFunctionContainer activity_regularizer get; set;

object activity_regularizer_dyn get; set;

int axis get; set;

bool built get; set;

object count get; set;

object dtype get;

object dtype_dyn get;

bool dynamic get;

object dynamic_dyn get;

IList<Node> inbound_nodes get;

object inbound_nodes_dyn get;

IList<object> input get;

object input_dyn get;

object input_mask get;

object input_mask_dyn get;

IList<object> input_shape get;

object input_shape_dyn get;

object input_spec get; set;

object input_spec_dyn get; set;

IList<object> losses get;

object losses_dyn get;

object mean get; set;

IList<object> metrics get;

object metrics_dyn get;

object name get;

object name_dyn get;

object name_scope get;

object name_scope_dyn get;

IList<object> non_trainable_variables get;

object non_trainable_variables_dyn get;

IList<object> non_trainable_weights get;

object non_trainable_weights_dyn get;

IList<object> outbound_nodes get;

object outbound_nodes_dyn get;

IList<object> output get;

object output_dyn get;

object output_mask get;

object output_mask_dyn get;

object output_shape get;

object output_shape_dyn get;

object PythonObject get;

PythonClassContainer state_variables get; set;

bool stateful get; set;

ValueTuple<object> submodules get;

object submodules_dyn get;

bool supports_masking get; set;

bool trainable get; set;

object trainable_dyn get; set;

object trainable_variables get;

object trainable_variables_dyn get;

IList<object> trainable_weights get;

object trainable_weights_dyn get;

IList<object> updates get;

object updates_dyn get;

object variables get;

object variables_dyn get;

object variance get; set;

IList<object> weights get;

object weights_dyn get;