LostTech.TensorFlow : API Documentation

Type ReLU

Namespace tensorflow.keras.layers

Parent Layer

Interfaces IReLU

Rectified Linear Unit activation function.

With default values, it returns element-wise `max(x, 0)`.

Otherwise, it follows: `f(x) = max_value` for `x >= max_value`, `f(x) = x` for `threshold <= x < max_value`, `f(x) = negative_slope * (x - threshold)` otherwise.

Input shape: Arbitrary. Use the keyword argument `input_shape` (tuple of integers, does not include the samples axis) when using this layer as the first layer in a model.

Output shape: Same shape as the input.



Public static methods

ReLU NewDyn(object max_value, ImplicitContainer<T> negative_slope, ImplicitContainer<T> threshold, IDictionary<string, object> kwargs)

Public properties

PythonFunctionContainer activity_regularizer get; set;

object activity_regularizer_dyn get; set;

bool built 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 max_value 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;

ndarray negative_slope get; set;

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;

bool stateful get; set;

ValueTuple<object> submodules get;

object submodules_dyn get;

bool support_masking get; set;

bool supports_masking get; set;

ndarray threshold 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;

IList<object> weights get;

object weights_dyn get;