CudnnRNNCanonicalToParamsV2

public final class CudnnRNNCanonicalToParamsV2

Converts CudnnRNN params from canonical form to usable form. It supports the projection in LSTM.

Writes a set of weights into the opaque params buffer so they can be used in upcoming training or inferences.

Note that the params buffer may not be compatible across different GPUs. So any save and restoration should be converted to and from the canonical weights and biases.

num_layers: Specifies the number of layers in the RNN model. num_units: Specifies the size of the hidden state. input_size: Specifies the size of the input state. weights: the canonical form of weights that can be used for saving and restoration. They are more likely to be compatible across different generations. biases: the canonical form of biases that can be used for saving and restoration. They are more likely to be compatible across different generations. num_params_weights: number of weight parameter matrix for all layers. num_params_biases: number of bias parameter vector for all layers. rnn_mode: Indicates the type of the RNN model. input_mode: Indicate whether there is a linear projection between the input and The actual computation before the first layer. 'skip_input' is only allowed when input_size == num_units; 'auto_select' implies 'skip_input' when input_size == num_units; otherwise, it implies 'linear_input'. direction: Indicates whether a bidirectional model will be used. dir = (direction == bidirectional) ? 2 : 1 dropout: dropout probability. When set to 0., dropout is disabled. seed: the 1st part of a seed to initialize dropout. seed2: the 2nd part of a seed to initialize dropout. num_proj: The output dimensionality for the projection matrices. If None or 0, no projection is performed.

Nested Classes

class CudnnRNNCanonicalToParamsV2.Options Optional attributes for CudnnRNNCanonicalToParamsV2

Public Methods

Output <T>
asOutput ()
Returns the symbolic handle of a tensor.
static <T extends Number> CudnnRNNCanonicalToParamsV2 <T>
create ( Scope scope, Operand <Integer> numLayers, Operand <Integer> numUnits, Operand <Integer> inputSize, Iterable< Operand <T>> weights, Iterable< Operand <T>> biases, Options... options)
Factory method to create a class wrapping a new CudnnRNNCanonicalToParamsV2 operation.
static CudnnRNNCanonicalToParamsV2.Options
direction (String direction)
static CudnnRNNCanonicalToParamsV2.Options
dropout (Float dropout)
static CudnnRNNCanonicalToParamsV2.Options
inputMode (String inputMode)
static CudnnRNNCanonicalToParamsV2.Options
numProj (Long numProj)
Output <T>
static CudnnRNNCanonicalToParamsV2.Options
rnnMode (String rnnMode)
static CudnnRNNCanonicalToParamsV2.Options
seed (Long seed)
static CudnnRNNCanonicalToParamsV2.Options
seed2 (Long seed2)

Inherited Methods

Public Methods

public Output <T> asOutput ()

Returns the symbolic handle of a tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

public static CudnnRNNCanonicalToParamsV2 <T> create ( Scope scope, Operand <Integer> numLayers, Operand <Integer> numUnits, Operand <Integer> inputSize, Iterable< Operand <T>> weights, Iterable< Operand <T>> biases, Options... options)

Factory method to create a class wrapping a new CudnnRNNCanonicalToParamsV2 operation.

Parameters
scope current scope
options carries optional attributes values
Returns
  • a new instance of CudnnRNNCanonicalToParamsV2

public static CudnnRNNCanonicalToParamsV2.Options direction (String direction)

public static CudnnRNNCanonicalToParamsV2.Options dropout (Float dropout)

public static CudnnRNNCanonicalToParamsV2.Options inputMode (String inputMode)

public static CudnnRNNCanonicalToParamsV2.Options numProj (Long numProj)

public Output <T> params ()

public static CudnnRNNCanonicalToParamsV2.Options rnnMode (String rnnMode)

public static CudnnRNNCanonicalToParamsV2.Options seed (Long seed)

public static CudnnRNNCanonicalToParamsV2.Options seed2 (Long seed2)