TPUEmbeddingActivations

public final class TPUEmbeddingActivations

An op enabling differentiation of TPU Embeddings.

This op simply returns its first input, which is assumed to have been sliced from the Tensors returned by TPUEmbeddingDequeueActivations. The presence of this op, and its first argument being a trainable Variable, enables automatic differentiation of graphs containing embeddings via the TPU Embedding Python libraries.

Public Methods

Output<Float>
asOutput()
Returns the symbolic handle of a tensor.
static TPUEmbeddingActivations
create(Scope scope, Operand<Float> embeddingVariable, Operand<Float> slicedActivations, Long tableId, Long lookupId)
Factory method to create a class wrapping a new TPUEmbeddingActivations operation.
Output<Float>
output()

Inherited Methods

Public Methods

public Output<Float> 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 TPUEmbeddingActivations create (Scope scope, Operand<Float> embeddingVariable, Operand<Float> slicedActivations, Long tableId, Long lookupId)

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

Parameters
scope current scope
embeddingVariable A trainable variable, enabling optimizers to find this op.
slicedActivations The embedding activations Tensor to return.
tableId The id of the table in the embedding layer configuration from which these activations were computed.
lookupId Identifier of the set of embedding indices which produced these activations.
Returns
  • a new instance of TPUEmbeddingActivations

public Output<Float> output ()