# tf.raw_ops.TPUEmbeddingActivations

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An op enabling differentiation of TPU Embeddings.

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.raw_ops.TPUEmbeddingActivations`](https://www.tensorflow.org/api_docs/python/tf/raw_ops/TPUEmbeddingActivations)

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    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.

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| ## 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). |

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| ## Returns ||
|---|---|
| A `Tensor` of type `float32`. ||

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