public final class EnqueueTPUEmbeddingSparseTensorBatch extends PrimitiveOp
sample_indices[i], embedding_indices[i] and aggregation_weights[i] correspond to the ith feature. table_ids[i] indicates which embedding table to look up ith feature.
The tensors at corresponding positions in the three input lists (sample_indices, embedding_indices and aggregation_weights) must have the same shape, i.e. rank 1 with dim_size() equal to the total number of lookups into the table described by the corresponding feature.
Modifier and Type | Class and Description |
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static class |
EnqueueTPUEmbeddingSparseTensorBatch.Options
Optional attributes for
EnqueueTPUEmbeddingSparseTensorBatch |
operation
Modifier and Type | Method and Description |
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static EnqueueTPUEmbeddingSparseTensorBatch.Options |
combiners(List<String> combiners) |
static <T extends Number,U extends Number,V extends Number> |
create(Scope scope,
Iterable<Operand<T>> sampleIndices,
Iterable<Operand<U>> embeddingIndices,
Iterable<Operand<V>> aggregationWeights,
Operand<String> modeOverride,
List<Long> tableIds,
EnqueueTPUEmbeddingSparseTensorBatch.Options... options)
Factory method to create a class wrapping a new EnqueueTPUEmbeddingSparseTensorBatch operation.
|
static EnqueueTPUEmbeddingSparseTensorBatch.Options |
deviceOrdinal(Long deviceOrdinal) |
static EnqueueTPUEmbeddingSparseTensorBatch.Options |
maxSequenceLengths(List<Long> maxSequenceLengths) |
equals, hashCode, op, toString
public static <T extends Number,U extends Number,V extends Number> EnqueueTPUEmbeddingSparseTensorBatch create(Scope scope, Iterable<Operand<T>> sampleIndices, Iterable<Operand<U>> embeddingIndices, Iterable<Operand<V>> aggregationWeights, Operand<String> modeOverride, List<Long> tableIds, EnqueueTPUEmbeddingSparseTensorBatch.Options... options)
scope
- current scopesampleIndices
- A list of rank 1 Tensors specifying the training example to
which the corresponding embedding_indices and aggregation_weights values
belong. It corresponds to sp_ids.indices[:,0] in embedding_lookup_sparse().embeddingIndices
- A list of rank 1 Tensors, indices into the embedding tables.
It corresponds to sp_ids.values in embedding_lookup_sparse().aggregationWeights
- A list of rank 1 Tensors containing per training example
aggregation weights. It corresponds to sp_weights.values in
embedding_lookup_sparse().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.tableIds
- A list of integers specifying the identifier of the embedding table
(offset of TableDescriptor in the TPUEmbeddingConfiguration) to lookup the
corresponding input. The ith input is looked up using table_ids[i]. The size
of the table_ids list must be equal to that of sample_indices,
embedding_indices and aggregation_weights.options
- carries optional attributes valuespublic static EnqueueTPUEmbeddingSparseTensorBatch.Options deviceOrdinal(Long deviceOrdinal)
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.public static EnqueueTPUEmbeddingSparseTensorBatch.Options combiners(List<String> combiners)
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.public static EnqueueTPUEmbeddingSparseTensorBatch.Options maxSequenceLengths(List<Long> maxSequenceLengths)
maxSequenceLengths
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