tf.raw_ops.LoadTPUEmbeddingAdagradParametersGradAccumDebug
Load Adagrad embedding parameters with debug support.
tf.raw_ops.LoadTPUEmbeddingAdagradParametersGradAccumDebug(
parameters, accumulators, gradient_accumulators, num_shards, shard_id,
table_id=-1, table_name='', config='', name=None
)
An op that loads optimization parameters into HBM for embedding. Must be preceded by a ConfigureTPUEmbeddingHost op that sets up the correct embedding table configuration. For example, this op is used to install parameters that are loaded from a checkpoint before a training loop is executed.
| Args | |
|---|---|
parameters |
A Tensor of type float32. Value of parameters used in the Adagrad optimization algorithm. |
accumulators |
A Tensor of type float32. Value of accumulators used in the Adagrad optimization algorithm. |
gradient_accumulators |
A Tensor of type float32. Value of gradient_accumulators used in the Adagrad optimization algorithm. |
num_shards |
An int. |
shard_id |
An int. |
table_id |
An optional int. Defaults to -1. |
table_name |
An optional string. Defaults to "". |
config |
An optional string. Defaults to "". |
name |
A name for the operation (optional). |
| Returns | |
|---|---|
| The created Operation. |
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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/LoadTPUEmbeddingAdagradParametersGradAccumDebug