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 | |
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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 | |
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A Tensor of type float32 . |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/raw_ops/TPUEmbeddingActivations