LostTech.TensorFlow : API Documentation

Type recurrent_v2

Namespace tensorflow.python.keras.layers.recurrent_v2

Methods

Properties

Public static methods

Tensor calculate_sequence_by_mask(IGraphNodeBase mask, object time_major)

object calculate_sequence_by_mask_dyn(object mask, object time_major)

ValueTuple<Tensor, object, object, object> cudnn_gru(object inputs, object init_h, object kernel, object recurrent_kernel, object bias, IGraphNodeBase mask, object time_major, object go_backwards)

object cudnn_gru_dyn(object inputs, object init_h, object kernel, object recurrent_kernel, object bias, object mask, object time_major, object go_backwards)

ValueTuple<Tensor, object, object, object, object> cudnn_lstm(object inputs, object init_h, object init_c, object kernel, object recurrent_kernel, object bias, IGraphNodeBase mask, object time_major, object go_backwards)

object cudnn_lstm_dyn(object inputs, object init_h, object init_c, object kernel, object recurrent_kernel, object bias, object mask, object time_major, object go_backwards)

ValueTuple<object, object, object, object> gru_with_backend_selection(object inputs, object init_h, object kernel, object recurrent_kernel, object bias, object mask, object time_major, object go_backwards, object activation, object recurrent_activation)

object gru_with_backend_selection_dyn(object inputs, object init_h, object kernel, object recurrent_kernel, object bias, object mask, object time_major, object go_backwards, object activation, object recurrent_activation)

Tensor is_sequence_right_padded(IGraphNodeBase mask, bool time_major)

Tensor is_sequence_right_padded(IEnumerable<IGraphNodeBase> mask, bool time_major)

object is_sequence_right_padded_dyn(object mask, object time_major)

ValueTuple<object, object, object, object, object> lstm_with_backend_selection(object inputs, object init_h, object init_c, object kernel, object recurrent_kernel, object bias, object mask, object time_major, object go_backwards, object activation, object recurrent_activation)

object lstm_with_backend_selection_dyn(object inputs, object init_h, object init_c, object kernel, object recurrent_kernel, object bias, object mask, object time_major, object go_backwards, object activation, object recurrent_activation)

ValueTuple<object, object, object, Tensor> standard_gru(object inputs, object init_h, object kernel, object recurrent_kernel, object bias, object activation, object recurrent_activation, IGraphNodeBase mask, object time_major, object go_backwards)

object standard_gru_dyn(object inputs, object init_h, object kernel, object recurrent_kernel, object bias, object activation, object recurrent_activation, object mask, object time_major, object go_backwards)

ValueTuple<object, object, object, object, Tensor> standard_lstm(object inputs, object init_h, object init_c, object kernel, object recurrent_kernel, object bias, object activation, object recurrent_activation, IGraphNodeBase mask, object time_major, object go_backwards)

object standard_lstm_dyn(object inputs, object init_h, object init_c, object kernel, object recurrent_kernel, object bias, object activation, object recurrent_activation, object mask, object time_major, object go_backwards)

Public properties

PythonFunctionContainer calculate_sequence_by_mask_fn get;

PythonFunctionContainer cudnn_gru_fn get;

PythonFunctionContainer cudnn_lstm_fn get;

PythonFunctionContainer gru_with_backend_selection_fn get;

PythonFunctionContainer GRUCell_fn get;

PythonFunctionContainer is_sequence_right_padded_fn get;

PythonFunctionContainer lstm_with_backend_selection_fn get;

PythonFunctionContainer LSTMCell_fn get;

PythonFunctionContainer standard_gru_fn get;

PythonFunctionContainer standard_lstm_fn get;