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 2024-04-26 UTC.
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