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Looks up embeddings for the given ids
from a list of tensors.
tf.nn.embedding_lookup( params, ids, max_norm=None, name=None )
This function is used to perform parallel lookups on the list of tensors in params
. It is a generalization of tf.gather
, where params
is interpreted as a partitioning of a large embedding tensor.
If len(params) > 1
, each element id
of ids
is partitioned between the elements of params
according to the "div" partition strategy, which means we assign ids to partitions in a contiguous manner. For instance, 13 ids are split across 5 partitions as: [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9, 10], [11, 12]]
.
If the id space does not evenly divide the number of partitions, each of the first (max_id + 1) % len(params)
partitions will be assigned one more id.
The results of the lookup are concatenated into a dense tensor. The returned tensor has shape shape(ids) + shape(params)[1:]
.
Args | |
---|---|
params | A single tensor representing the complete embedding tensor, or a list of tensors all of same shape except for the first dimension, representing sharded embedding tensors following "div" partition strategy. |
ids | A Tensor with type int32 or int64 containing the ids to be looked up in params . |
max_norm | If not None , each embedding is clipped if its l2-norm is larger than this value. |
name | A name for the operation (optional). |
Returns | |
---|---|
A Tensor with the same type as the tensors in params . For instance, if [[1, 2], [3, 4], [5, 6], [7, 8], [9, 10]] or a list of matrices: params[0]: [[1, 2], [3, 4]] params[1]: [[5, 6], [7, 8]] params[2]: [[9, 10]] and [0, 3, 4] The output will be a 3x2 matrix: [[1, 2], [7, 8], [9, 10]] |
Raises | |
---|---|
ValueError | If params is empty. |
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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/nn/embedding_lookup