Class EnqueueTPUEmbeddingArbitraryTensorBatch.Inputs

java.lang.Object
org.tensorflow.op.RawOpInputs<EnqueueTPUEmbeddingArbitraryTensorBatch>
org.tensorflow.op.tpu.EnqueueTPUEmbeddingArbitraryTensorBatch.Inputs
Enclosing class:
EnqueueTPUEmbeddingArbitraryTensorBatch
public static class EnqueueTPUEmbeddingArbitraryTensorBatch.Inputs extends RawOpInputs<EnqueueTPUEmbeddingArbitraryTensorBatch>

  • Field Details

    • sampleIndicesOrRowSplits

      public final Iterable<Operand<? extends TNumber>> sampleIndicesOrRowSplits
      A list of rank 2 Tensors specifying the training example to which the corresponding embedding_indices and aggregation_weights values belong. If the size of its first dimension is 0, we assume each embedding_indices belongs to a different sample. Both int32 and int64 are allowed and will be converted to int32 internally.

      Or a list of rank 1 Tensors specifying the row splits for splitting embedding_indices and aggregation_weights into rows. It corresponds to ids.row_splits in embedding_lookup(), when ids is a RaggedTensor. When enqueuing N-D ragged tensor, only the last dimension is allowed to be ragged. the row splits is 1-D dense tensor. When empty, we assume a dense tensor is passed to the op Both int32 and int64 are allowed and will be converted to int32 internally.

    • embeddingIndices

      public final Iterable<Operand<? extends TNumber>> embeddingIndices
      A list of rank 1 Tensors, indices into the embedding tables. Both int32 and int64 are allowed and will be converted to int32 internally.

    • aggregationWeights

      public final Iterable<Operand<? extends TNumber>> aggregationWeights
      A list of rank 1 Tensors containing per training example aggregation weights. Both float32 and float64 are allowed and will be converted to float32 internally.

    • modeOverride

      public final Operand<TString> modeOverride
      A string input that overrides the mode specified in the TPUEmbeddingConfiguration. Supported values are {'unspecified', 'inference', 'training', 'backward_pass_only'}. When set to 'unspecified', the mode set in TPUEmbeddingConfiguration is used, otherwise mode_override is used.

    • T1

      public final DataType T1
      The T1 attribute

    • T2

      public final DataType T2
      The T2 attribute

    • T3

      public final DataType T3
      The T3 attribute

    • deviceOrdinal

      public final long deviceOrdinal
      The TPU device to use. Should be >= 0 and less than the number of TPU cores in the task on which the node is placed.

    • combiners

      public final String[] combiners
      A list of string scalars, one for each embedding table that specify how to normalize the embedding activations after weighted summation. Supported combiners are 'mean', 'sum', or 'sqrtn'. It is invalid to have the sum of the weights be 0 for 'mean' or the sum of the squared weights be 0 for 'sqrtn'. If combiners isn't passed, the default is to use 'sum' for all tables.

  • Constructor Details