LostTech.TensorFlow : API Documentation

Type LocallyConnected1D

Namespace tensorflow.keras.layers

Parent Layer

Interfaces ILocallyConnected1D

Locally-connected layer for 1D inputs.

The `LocallyConnected1D` layer works similarly to the `Conv1D` layer, except that weights are unshared, that is, a different set of filters is applied at each different patch of the input.

Show Example
# apply a unshared weight convolution 1d of length 3 to a sequence with
            # 10 timesteps, with 64 output filters
            model = Sequential()
            model.add(LocallyConnected1D(64, 3, input_shape=(10, 32)))
            # now model.output_shape == (None, 8, 64)
            # add a new conv1d on top
            model.add(LocallyConnected1D(32, 3))
            # now model.output_shape == (None, 6, 32) 



Public static methods

LocallyConnected1D NewDyn(object filters, object kernel_size, ImplicitContainer<T> strides, ImplicitContainer<T> padding, object data_format, object activation, ImplicitContainer<T> use_bias, ImplicitContainer<T> kernel_initializer, ImplicitContainer<T> bias_initializer, object kernel_regularizer, object bias_regularizer, object activity_regularizer, object kernel_constraint, object bias_constraint, ImplicitContainer<T> implementation, IDictionary<string, object> kwargs)

Public properties

object activation get; set;

object activity_regularizer get; set;

Optional regularizer function for the output of this layer.

object activity_regularizer_dyn get; set;

object bias get; set;

object bias_constraint get; set;

object bias_initializer get; set;

object bias_regularizer get; set;

bool built get; set;

string data_format get; set;

object dtype get;

object dtype_dyn get;

bool dynamic get;

object dynamic_dyn get;

int filters get; set;

int implementation get; set;

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;

InputSpec input_spec get; set;

object input_spec_dyn get; set;

object kernel get; set;

object kernel_constraint get; set;

IList<object> kernel_idxs get; set;

object kernel_initializer get; set;

object kernel_mask get; set;

object kernel_regularizer get; set;

ValueTuple<object, object, object> kernel_shape get; set;

object kernel_size get; set;

IList<object> losses get;

object losses_dyn get;

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_length get; set;

object output_mask get;

object output_mask_dyn get;

object output_shape get;

object output_shape_dyn get;

object padding get; set;

object PythonObject get;

bool stateful get; set;

object strides 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;

bool use_bias get; set;

object variables get;

object variables_dyn get;

IList<object> weights get;

object weights_dyn get;