T
- data type for weights()
output@Operator public final class CudnnRNNParamsToCanonicalV2<T extends Number> extends PrimitiveOp
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_weigths: 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.
Modifier and Type | Class and Description |
---|---|
static class |
CudnnRNNParamsToCanonicalV2.Options
Optional attributes for
CudnnRNNParamsToCanonicalV2 |
operation
Modifier and Type | Method and Description |
---|---|
List<Output<T>> |
biases() |
static <T extends Number> |
create(Scope scope,
Operand<Integer> numLayers,
Operand<Integer> numUnits,
Operand<Integer> inputSize,
Operand<T> params,
Long numParamsWeights,
Long numParamsBiases,
CudnnRNNParamsToCanonicalV2.Options... options)
Factory method to create a class wrapping a new CudnnRNNParamsToCanonicalV2 operation.
|
static CudnnRNNParamsToCanonicalV2.Options |
direction(String direction) |
static CudnnRNNParamsToCanonicalV2.Options |
dropout(Float dropout) |
static CudnnRNNParamsToCanonicalV2.Options |
inputMode(String inputMode) |
static CudnnRNNParamsToCanonicalV2.Options |
numProj(Long numProj) |
static CudnnRNNParamsToCanonicalV2.Options |
rnnMode(String rnnMode) |
static CudnnRNNParamsToCanonicalV2.Options |
seed(Long seed) |
static CudnnRNNParamsToCanonicalV2.Options |
seed2(Long seed2) |
List<Output<T>> |
weights() |
equals, hashCode, op, toString
public static <T extends Number> CudnnRNNParamsToCanonicalV2<T> create(Scope scope, Operand<Integer> numLayers, Operand<Integer> numUnits, Operand<Integer> inputSize, Operand<T> params, Long numParamsWeights, Long numParamsBiases, CudnnRNNParamsToCanonicalV2.Options... options)
scope
- current scopenumLayers
- numUnits
- inputSize
- params
- numParamsWeights
- numParamsBiases
- options
- carries optional attributes valuespublic static CudnnRNNParamsToCanonicalV2.Options rnnMode(String rnnMode)
rnnMode
- public static CudnnRNNParamsToCanonicalV2.Options inputMode(String inputMode)
inputMode
- public static CudnnRNNParamsToCanonicalV2.Options direction(String direction)
direction
- public static CudnnRNNParamsToCanonicalV2.Options dropout(Float dropout)
dropout
- public static CudnnRNNParamsToCanonicalV2.Options seed(Long seed)
seed
- public static CudnnRNNParamsToCanonicalV2.Options seed2(Long seed2)
seed2
- public static CudnnRNNParamsToCanonicalV2.Options numProj(Long numProj)
numProj
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