An op enabling differentiation of TPU Embeddings.
Compat aliases for migration
See Migration guide for more details.
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.
float32. A trainable variable, enabling optimizers to find this op.
float32. The embedding activations Tensor to return.
>= 0. The id of the table in the embedding layer configuration from which these activations were computed.
>= 0. Identifier of the set of embedding indices which produced these activations.
name: A name for the operation (optional).
Tensor of type