LostTech.TensorFlow : API Documentation

Type ConvLSTM2D

Namespace tensorflow.keras.layers

Parent ConvRNN2D

Interfaces IConvLSTM2D

Convolutional LSTM.

It is similar to an LSTM layer, but the input transformations and recurrent transformations are both convolutional.

Methods

Properties

Public instance methods

object __call__(IGraphNodeBase inputs, IEnumerable<IGraphNodeBase> initial_state, IDictionary<string, object> constants, IDictionary<string, object> kwargs)

`Bidirectional.__call__` implements the same API as the wrapped `RNN`.

object __call__(IEnumerable<IGraphNodeBase> inputs, IEnumerable<IGraphNodeBase> initial_state, object constants, IDictionary<string, object> kwargs)

`Bidirectional.__call__` implements the same API as the wrapped `RNN`.

object __call__(IEnumerable<IGraphNodeBase> inputs, IEnumerable<IGraphNodeBase> initial_state, string constants, IDictionary<string, object> kwargs)

`Bidirectional.__call__` implements the same API as the wrapped `RNN`.

object __call__(IEnumerable<IGraphNodeBase> inputs, object initial_state, IDictionary<string, object> constants, IDictionary<string, object> kwargs)

`Bidirectional.__call__` implements the same API as the wrapped `RNN`.

object __call__(IEnumerable<IGraphNodeBase> inputs, object initial_state, IEnumerable<IGraphNodeBase> constants, IDictionary<string, object> kwargs)

`Bidirectional.__call__` implements the same API as the wrapped `RNN`.

object __call__(IEnumerable<IGraphNodeBase> inputs, object initial_state, IGraphNodeBase constants, IDictionary<string, object> kwargs)

`Bidirectional.__call__` implements the same API as the wrapped `RNN`.

object __call__(IEnumerable<IGraphNodeBase> inputs, object initial_state, object constants, IDictionary<string, object> kwargs)

`Bidirectional.__call__` implements the same API as the wrapped `RNN`.

object __call__(IEnumerable<IGraphNodeBase> inputs, object initial_state, string constants, IDictionary<string, object> kwargs)

`Bidirectional.__call__` implements the same API as the wrapped `RNN`.

object __call__(IEnumerable<IGraphNodeBase> inputs, IEnumerable<IGraphNodeBase> initial_state, IDictionary<string, object> constants, IDictionary<string, object> kwargs)

`Bidirectional.__call__` implements the same API as the wrapped `RNN`.

object __call__(IGraphNodeBase inputs, IEnumerable<IGraphNodeBase> initial_state, IEnumerable<IGraphNodeBase> constants, IDictionary<string, object> kwargs)

`Bidirectional.__call__` implements the same API as the wrapped `RNN`.

object __call__(IGraphNodeBase inputs, IEnumerable<IGraphNodeBase> initial_state, IGraphNodeBase constants, IDictionary<string, object> kwargs)

`Bidirectional.__call__` implements the same API as the wrapped `RNN`.

object __call__(IGraphNodeBase inputs, IEnumerable<IGraphNodeBase> initial_state, object constants, IDictionary<string, object> kwargs)

`Bidirectional.__call__` implements the same API as the wrapped `RNN`.

object __call__(IGraphNodeBase inputs, IEnumerable<IGraphNodeBase> initial_state, string constants, IDictionary<string, object> kwargs)

`Bidirectional.__call__` implements the same API as the wrapped `RNN`.

object __call__(IGraphNodeBase inputs, object initial_state, IDictionary<string, object> constants, IDictionary<string, object> kwargs)

`Bidirectional.__call__` implements the same API as the wrapped `RNN`.

object __call__(IGraphNodeBase inputs, object initial_state, IEnumerable<IGraphNodeBase> constants, IDictionary<string, object> kwargs)

`Bidirectional.__call__` implements the same API as the wrapped `RNN`.

object __call__(IGraphNodeBase inputs, object initial_state, IGraphNodeBase constants, IDictionary<string, object> kwargs)

`Bidirectional.__call__` implements the same API as the wrapped `RNN`.

object __call__(IGraphNodeBase inputs, object initial_state, object constants, IDictionary<string, object> kwargs)

`Bidirectional.__call__` implements the same API as the wrapped `RNN`.

object __call__(IGraphNodeBase inputs, object initial_state, string constants, IDictionary<string, object> kwargs)

`Bidirectional.__call__` implements the same API as the wrapped `RNN`.

object __call__(IEnumerable<IGraphNodeBase> inputs, IEnumerable<IGraphNodeBase> initial_state, IGraphNodeBase constants, IDictionary<string, object> kwargs)

`Bidirectional.__call__` implements the same API as the wrapped `RNN`.

object __call__(IEnumerable<IGraphNodeBase> inputs, IEnumerable<IGraphNodeBase> initial_state, IEnumerable<IGraphNodeBase> constants, IDictionary<string, object> kwargs)

`Bidirectional.__call__` implements the same API as the wrapped `RNN`.

object __call___dyn(object inputs, object initial_state, object constants, IDictionary<string, object> kwargs)

`Bidirectional.__call__` implements the same API as the wrapped `RNN`.

Tensor call(IGraphNodeBase inputs, IGraphNodeBase mask, IGraphNodeBase training, object initial_state, object constants)

Tensor call(IGraphNodeBase inputs, IGraphNodeBase mask, IGraphNodeBase training, PythonClassContainer initial_state, object constants)

Tensor call(IGraphNodeBase inputs, IGraphNodeBase mask, IGraphNodeBase training, IEnumerable<IGraphNodeBase> initial_state, object constants)

Tensor call(IGraphNodeBase inputs, IGraphNodeBase mask, bool training, object initial_state, object constants)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IEnumerable<IGraphNodeBase> mask, IGraphNodeBase training, object initial_state, object constants)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IEnumerable<IGraphNodeBase> mask, bool training, IEnumerable<IGraphNodeBase> initial_state)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IEnumerable<IGraphNodeBase> mask, bool training, IEnumerable<IGraphNodeBase> initial_state, object constants)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IEnumerable<IGraphNodeBase> mask, bool training, PythonClassContainer initial_state, object constants)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IEnumerable<IGraphNodeBase> mask, bool training, object initial_state, object constants)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IEnumerable<IGraphNodeBase> mask, IGraphNodeBase training, IEnumerable<IGraphNodeBase> initial_state, object constants)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IEnumerable<IGraphNodeBase> mask, IGraphNodeBase training, PythonClassContainer initial_state, object constants)

Tensor call(IGraphNodeBase inputs, IGraphNodeBase mask, bool training, IEnumerable<IGraphNodeBase> initial_state, object constants)

Tensor call(IGraphNodeBase inputs, IEnumerable<IGraphNodeBase> mask, IGraphNodeBase training, object initial_state, object constants)

Tensor call(IGraphNodeBase inputs, IGraphNodeBase mask, bool training, PythonClassContainer initial_state, object constants)

Tensor call(IGraphNodeBase inputs, IGraphNodeBase mask, IGraphNodeBase training, IEnumerable<IGraphNodeBase> initial_state)

Tensor call(IGraphNodeBase inputs, IGraphNodeBase mask, bool training, object initial_state)

Tensor call(IGraphNodeBase inputs, IGraphNodeBase mask, bool training, PythonClassContainer initial_state)

Tensor call(IGraphNodeBase inputs, IEnumerable<IGraphNodeBase> mask, IGraphNodeBase training, object initial_state)

Tensor call(IGraphNodeBase inputs, IEnumerable<IGraphNodeBase> mask, IGraphNodeBase training, PythonClassContainer initial_state)

Tensor call(IGraphNodeBase inputs, IGraphNodeBase mask, bool training, IEnumerable<IGraphNodeBase> initial_state)

Tensor call(IGraphNodeBase inputs, IEnumerable<IGraphNodeBase> mask, IGraphNodeBase training, IEnumerable<IGraphNodeBase> initial_state)

Tensor call(IGraphNodeBase inputs, IEnumerable<IGraphNodeBase> mask, bool training, object initial_state)

Tensor call(IGraphNodeBase inputs, IEnumerable<IGraphNodeBase> mask, bool training, PythonClassContainer initial_state)

Tensor call(IGraphNodeBase inputs, IEnumerable<IGraphNodeBase> mask, bool training, IEnumerable<IGraphNodeBase> initial_state)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IGraphNodeBase mask, bool training, PythonClassContainer initial_state, object constants)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IGraphNodeBase mask, IGraphNodeBase training, object initial_state)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IGraphNodeBase mask, IGraphNodeBase training, IEnumerable<IGraphNodeBase> initial_state)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IGraphNodeBase mask, bool training, object initial_state)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IGraphNodeBase mask, bool training, PythonClassContainer initial_state)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IGraphNodeBase mask, bool training, IEnumerable<IGraphNodeBase> initial_state)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IEnumerable<IGraphNodeBase> mask, IGraphNodeBase training, object initial_state)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IEnumerable<IGraphNodeBase> mask, IGraphNodeBase training, PythonClassContainer initial_state)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IEnumerable<IGraphNodeBase> mask, IGraphNodeBase training, IEnumerable<IGraphNodeBase> initial_state)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IEnumerable<IGraphNodeBase> mask, bool training, object initial_state)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IEnumerable<IGraphNodeBase> mask, bool training, PythonClassContainer initial_state)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IGraphNodeBase mask, IGraphNodeBase training, PythonClassContainer initial_state)

Tensor call(IGraphNodeBase inputs, IEnumerable<IGraphNodeBase> mask, IGraphNodeBase training, PythonClassContainer initial_state, object constants)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IGraphNodeBase mask, bool training, IEnumerable<IGraphNodeBase> initial_state, object constants)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IGraphNodeBase mask, IGraphNodeBase training, IEnumerable<IGraphNodeBase> initial_state, object constants)

Tensor call(IGraphNodeBase inputs, IEnumerable<IGraphNodeBase> mask, IGraphNodeBase training, IEnumerable<IGraphNodeBase> initial_state, object constants)

Tensor call(IGraphNodeBase inputs, IEnumerable<IGraphNodeBase> mask, bool training, object initial_state, object constants)

Tensor call(IGraphNodeBase inputs, IEnumerable<IGraphNodeBase> mask, bool training, PythonClassContainer initial_state, object constants)

Tensor call(IGraphNodeBase inputs, IEnumerable<IGraphNodeBase> mask, bool training, IEnumerable<IGraphNodeBase> initial_state, object constants)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IGraphNodeBase mask, IGraphNodeBase training, object initial_state, object constants)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IGraphNodeBase mask, bool training, object initial_state, object constants)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IGraphNodeBase mask, IGraphNodeBase training, PythonClassContainer initial_state, object constants)

Tensor call(IGraphNodeBase inputs, IGraphNodeBase mask, IGraphNodeBase training, object initial_state)

Tensor call(IGraphNodeBase inputs, IGraphNodeBase mask, IGraphNodeBase training, PythonClassContainer initial_state)

object call_dyn(object inputs, object mask, object training, object initial_state, object constants)

object call_dyn(object inputs, object mask, object training, object initial_state)

object compute_output_shape(PythonClassContainer input_shape)

object compute_output_shape(ValueTuple<object, int> input_shape)

object compute_output_shape(IEnumerable<Nullable<int>> input_shape)

object get_initial_state(IEnumerable<object> inputs)

object get_initial_state(IGraphNodeBase inputs)

object get_initial_state_dyn(object inputs)

void reset_states(IEnumerable<ndarray> states)

void reset_states(ndarray states)

void reset_states(PythonClassContainer states)

object reset_states_dyn(object states)

Public static methods

ConvLSTM2D NewDyn(object filters, object kernel_size, ImplicitContainer<T> strides, ImplicitContainer<T> padding, object data_format, ImplicitContainer<T> dilation_rate, ImplicitContainer<T> activation, ImplicitContainer<T> recurrent_activation, ImplicitContainer<T> use_bias, ImplicitContainer<T> kernel_initializer, ImplicitContainer<T> recurrent_initializer, ImplicitContainer<T> bias_initializer, ImplicitContainer<T> unit_forget_bias, object kernel_regularizer, object recurrent_regularizer, object bias_regularizer, object activity_regularizer, object kernel_constraint, object recurrent_constraint, object bias_constraint, ImplicitContainer<T> return_sequences, ImplicitContainer<T> go_backwards, ImplicitContainer<T> stateful, ImplicitContainer<T> dropout, ImplicitContainer<T> recurrent_dropout, IDictionary<string, object> kwargs)

Public properties

object activation get;

object activation_dyn get;

object activity_regularizer get; set;

Optional regularizer function for the output of this layer.

object activity_regularizer_dyn get; set;

object bias_constraint get;

object bias_constraint_dyn get;

object bias_initializer get;

object bias_initializer_dyn get;

object bias_regularizer get;

object bias_regularizer_dyn get;

bool built get; set;

object cell get; set;

IList<InputSpec> constants_spec get; set;

object data_format get;

object data_format_dyn get;

object dilation_rate get;

object dilation_rate_dyn get;

double dropout get;

object dropout_dyn get;

object dtype get;

object dtype_dyn get;

bool dynamic get;

object dynamic_dyn get;

object filters get;

object filters_dyn get;

bool go_backwards 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;

object input_spec get; set;

object input_spec_dyn get; set;

object kernel_constraint get;

object kernel_constraint_dyn get;

object kernel_initializer get;

object kernel_initializer_dyn get;

object kernel_regularizer get;

object kernel_regularizer_dyn get;

object kernel_size get;

object kernel_size_dyn get;

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 padding get;

object padding_dyn get;

object PythonObject get;

object recurrent_activation get;

object recurrent_activation_dyn get;

object recurrent_constraint get;

object recurrent_constraint_dyn get;

double recurrent_dropout get;

object recurrent_dropout_dyn get;

object recurrent_initializer get;

object recurrent_initializer_dyn get;

object recurrent_regularizer get;

object recurrent_regularizer_dyn get;

bool return_sequences get; set;

bool return_state get; set;

IList<InputSpec> state_spec get; set;

bool stateful get; set;

IList<object> states get; set;

object states_dyn get; set;

object strides get;

object strides_dyn get;

ValueTuple<object> submodules get;

object submodules_dyn get;

bool supports_masking get; set;

bool time_major 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;

bool unit_forget_bias get;

object unit_forget_bias_dyn get;

bool unroll get; set;

IList<object> updates get;

object updates_dyn get;

bool use_bias get;

object use_bias_dyn get;

object variables get;

object variables_dyn get;

IList<object> weights get;

object weights_dyn get;

object zero_output_for_mask get; set;