Performs gradient updates of embedding tables.
tf.raw_ops.SendTPUEmbeddingGradients(
inputs, learning_rates, config, name=None
)
| Args | |
|---|---|
inputs | A list of at least 1 Tensor objects with type float32. A TensorList of gradients with which to update embedding tables. This argument has the same length and shapes as the return value of RecvTPUEmbeddingActivations, but contains gradients of the model's loss with respect to the embedding activations. The embedding tables are updated from these gradients via the optimizer specified in the TPU embedding configuration given to tpu.initialize_system. |
learning_rates | A list of Tensor objects with type float32. A TensorList of float32 scalars, one for each dynamic learning rate tag: see the comments in //third_party/tensorflow/core/protobuf/tpu/optimization_parameters.proto. Multiple tables can share the same dynamic learning rate tag as specified in the configuration. If the learning rates for all tables are constant, this list should be empty. |
config | A string. Serialized TPUEmbeddingConfiguration proto. |
name | A name for the operation (optional). |
| Returns | |
|---|---|
| The created Operation. |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/raw_ops/SendTPUEmbeddingGradients