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.
|