tf.raw_ops.TPUEmbeddingActivations

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.