LostTech.TensorFlow : API Documentation

Type ConvLSTMCell

Namespace tensorflow.contrib.rnn

Parent RNNCell

Interfaces IConvLSTMCell

Convolutional LSTM recurrent network cell.

https://arxiv.org/pdf/1506.04214v1.pdf

Methods

Properties

Public instance methods

Tensor call(IEnumerable<IGraphNodeBase> inputs, IEnumerable<IGraphNodeBase> state, PythonClassContainer scope)

Tensor call(IGraphNodeBase inputs, object state, PythonClassContainer scope)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IEnumerable<IGraphNodeBase> state, IndexedSlices scope)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IEnumerable<IGraphNodeBase> state, IEnumerable<PythonClassContainer> scope)

Tensor call(IGraphNodeBase inputs, object state, int scope)

Tensor call(IGraphNodeBase inputs, object state, IndexedSlices scope)

Tensor call(IGraphNodeBase inputs, object state, IEnumerable<PythonClassContainer> scope)

Tensor call(IGraphNodeBase inputs, PythonClassContainer state, int scope)

Tensor call(IGraphNodeBase inputs, PythonClassContainer state, IEnumerable<PythonClassContainer> scope)

Tensor call(IEnumerable<IGraphNodeBase> inputs, IEnumerable<IGraphNodeBase> state, int scope)

Tensor call(IGraphNodeBase inputs, IEnumerable<IGraphNodeBase> state, PythonClassContainer scope)

Tensor call(IGraphNodeBase inputs, IEnumerable<IGraphNodeBase> state, IndexedSlices scope)

Tensor call(IGraphNodeBase inputs, IEnumerable<IGraphNodeBase> state, IEnumerable<PythonClassContainer> scope)

Tensor call(IEnumerable<IGraphNodeBase> inputs, object state, PythonClassContainer scope)

Tensor call(IEnumerable<IGraphNodeBase> inputs, object state, int scope)

Tensor call(IEnumerable<IGraphNodeBase> inputs, object state, IndexedSlices scope)

Tensor call(IEnumerable<IGraphNodeBase> inputs, object state, IEnumerable<PythonClassContainer> scope)

Tensor call(IEnumerable<IGraphNodeBase> inputs, PythonClassContainer state, PythonClassContainer scope)

Tensor call(IEnumerable<IGraphNodeBase> inputs, PythonClassContainer state, int scope)

Tensor call(IEnumerable<IGraphNodeBase> inputs, PythonClassContainer state, IndexedSlices scope)

Tensor call(IEnumerable<IGraphNodeBase> inputs, PythonClassContainer state, IEnumerable<PythonClassContainer> scope)

Tensor call(IGraphNodeBase inputs, IEnumerable<IGraphNodeBase> state, int scope)

Public static methods

ConvLSTMCell NewDyn(object conv_ndims, object input_shape, object output_channels, object kernel_shape, ImplicitContainer<T> use_bias, ImplicitContainer<T> skip_connection, ImplicitContainer<T> forget_bias, object initializers, ImplicitContainer<T> name)

Construct ConvLSTMCell.
Parameters
object conv_ndims
Convolution dimensionality (1, 2 or 3).
object input_shape
Shape of the input as int tuple, excluding the batch size.
object output_channels
int, number of output channels of the conv LSTM.
object kernel_shape
Shape of kernel as an int tuple (of size 1, 2 or 3).
ImplicitContainer<T> use_bias
(bool) Use bias in convolutions.
ImplicitContainer<T> skip_connection
If set to `True`, concatenate the input to the output of the conv LSTM. Default: `False`.
ImplicitContainer<T> forget_bias
Forget bias.
object initializers
Unused.
ImplicitContainer<T> name
Name of the module.

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;

object 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.

bool stateful 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;

object variables get;

object variables_dyn get;

IList<object> weights get;

object weights_dyn get;