tf.raw_ops.TPUEmbeddingActivations
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An op enabling differentiation of TPU Embeddings.
tf.raw_ops.TPUEmbeddingActivations(
embedding_variable, sliced_activations, table_id, lookup_id, name=None
)
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.
Args |
|---|
embedding_variable
|
A Tensor of type float32.
A trainable variable, enabling optimizers to find this op.
|
sliced_activations
|
A Tensor of type float32.
The embedding activations Tensor to return.
|
table_id
|
An int that is >= 0.
The id of the table in the embedding layer configuration from which
these activations were computed.
|
lookup_id
|
An int that is >= 0.
Identifier of the set of embedding indices which produced these
activations.
|
name
|
A name for the operation (optional).
|
Returns |
|---|
A Tensor of type float32.
|
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Last updated 2022-10-27 UTC.
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