Type TfLiteRNNCell
Namespace tensorflow.lite.experimental.nn
Parent LayerRNNCell
Interfaces ITfLiteRNNCell
The most basic RNN cell. This is used only for TfLite, it provides hints and it also makes the
variables in the desired for the tflite ops.
Properties
- activity_regularizer
- activity_regularizer_dyn
- built
- dtype
- dtype_dyn
- dynamic
- dynamic_dyn
- graph
- graph_dyn
- inbound_nodes
- inbound_nodes_dyn
- input
- input_dyn
- input_mask
- input_mask_dyn
- input_shape
- input_shape_dyn
- input_spec
- input_spec_dyn
- losses
- losses_dyn
- metrics
- metrics_dyn
- name
- name_dyn
- name_scope
- name_scope_dyn
- non_trainable_variables
- non_trainable_variables_dyn
- non_trainable_weights
- non_trainable_weights_dyn
- outbound_nodes
- outbound_nodes_dyn
- output
- output_dyn
- output_mask
- output_mask_dyn
- output_shape
- output_shape_dyn
- output_size
- output_size_dyn
- PythonObject
- rnncell_scope
- scope_name
- scope_name_dyn
- state_size
- state_size_dyn
- stateful
- submodules
- submodules_dyn
- supports_masking
- trainable
- trainable_dyn
- trainable_variables
- trainable_variables_dyn
- trainable_weights
- trainable_weights_dyn
- updates
- updates_dyn
- variables
- variables_dyn
- weights
- weights_dyn
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;
object graph get;
object graph_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;
InputSpec input_spec get; set;
object input_spec_dyn 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_mask get;
object output_mask_dyn get;
object output_shape get;
object output_shape_dyn get;
object output_size get;
Integer or TensorShape: size of outputs produced by this cell.
object output_size_dyn get;
Integer or TensorShape: size of outputs produced by this cell.
object PythonObject get;
object rnncell_scope get; set;
string scope_name get;
object scope_name_dyn get;
object state_size get;
size(s) of state(s) used by this cell. It can be represented by an Integer, a TensorShape or a tuple of Integers
or TensorShapes.
object state_size_dyn get;
size(s) of state(s) used by this cell. It can be represented by an Integer, a TensorShape or a tuple of Integers
or TensorShapes.