CudnnRNNParamsToCanonical

public final class CudnnRNNParamsToCanonical

Retrieves CudnnRNN params in canonical form. It supports the projection in LSTM.

Retrieves a set of weights from the opaque params buffer that can be saved and restored in a way compatible with future runs.

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. num_params_weights: number of weight parameter matrix for all layers. num_params_biases: number of bias parameter vector for all layers. 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. 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 CudnnRNNParamsToCanonical.Options Optional attributes for CudnnRNNParamsToCanonical

Constants

String OP_NAME The name of this op, as known by TensorFlow core engine

Public Methods

List< Output <T>>
static <T extends TNumber > CudnnRNNParamsToCanonical <T>
create ( Scope scope, Operand < TInt32 > numLayers, Operand < TInt32 > numUnits, Operand < TInt32 > inputSize, Operand <T> params, Long numParamsWeights, Long numParamsBiases, Options... options)
Factory method to create a class wrapping a new CudnnRNNParamsToCanonical operation.
static CudnnRNNParamsToCanonical.Options
direction (String direction)
static CudnnRNNParamsToCanonical.Options
dropout (Float dropout)
static CudnnRNNParamsToCanonical.Options
inputMode (String inputMode)
static CudnnRNNParamsToCanonical.Options
numProj (Long numProj)
static CudnnRNNParamsToCanonical.Options
rnnMode (String rnnMode)
static CudnnRNNParamsToCanonical.Options
seed (Long seed)
static CudnnRNNParamsToCanonical.Options
seed2 (Long seed2)
List< Output <T>>

Inherited Methods

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "CudnnRNNParamsToCanonicalV2"

Public Methods

public List< Output <T>> biases ()

public static CudnnRNNParamsToCanonical <T> create ( Scope scope, Operand < TInt32 > numLayers, Operand < TInt32 > numUnits, Operand < TInt32 > inputSize, Operand <T> params, Long numParamsWeights, Long numParamsBiases, Options... options)

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

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

public static CudnnRNNParamsToCanonical.Options direction (String direction)

public static CudnnRNNParamsToCanonical.Options dropout (Float dropout)

public static CudnnRNNParamsToCanonical.Options inputMode (String inputMode)

public static CudnnRNNParamsToCanonical.Options numProj (Long numProj)

public static CudnnRNNParamsToCanonical.Options rnnMode (String rnnMode)

public static CudnnRNNParamsToCanonical.Options seed (Long seed)

public static CudnnRNNParamsToCanonical.Options seed2 (Long seed2)

public List< Output <T>> weights ()