def send_tpu_embedding_gradients(inputs,
config,
learning_rates=None,
name=None):
"""A placeholder op for feeding per-sample gradients to the embedding layer.
Args:
inputs: 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 optimizers specified in the
TPU embedding configuration given to tpu.initialize_system.
config: Serialized TPUEmbeddingConfiguration proto.
learning_rates: 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.
name: A name for the operation (optional).
Returns:
A SendTPUEmbeddingGradients operation.
"""
if learning_rates is None:
learning_rates = []
return gen_tpu_ops.send_tpu_embedding_gradients(
inputs=inputs,
learning_rates=learning_rates,
config=config,
name=name)
def send_tpu_embedding_gradients(inputs,
config,
learning_rates=None,
name=None):
"""A placeholder op for feeding per-sample gradients to the embedding layer.
Args:
inputs: 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 optimizers specified in the
TPU embedding configuration given to tpu.initialize_system.
config: Serialized TPUEmbeddingConfiguration proto.
learning_rates: 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.
name: A name for the operation (optional).
Returns:
A SendTPUEmbeddingGradients operation.
"""
if learning_rates is None:
learning_rates = []
return gen_tpu_ops.send_tpu_embedding_gradients(
inputs=inputs, learning_rates=learning_rates, config=config, name=name)
