TensorFlow 1 version
|
View source on GitHub
|
Looks up ids in a list of embedding 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. params may be
a PartitionedVariable as returned by using tf.compat.v1.get_variable()
with a
partitioner.
If len(params) > 1, each element id of ids is partitioned between
the elements of params according to the partition_strategy.
In all strategies, 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 partition_strategy is always "div" currently. This means that 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]]
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 P tensors all of same shape except for the first dimension,
representing sharded embedding tensors. Alternatively, a
PartitionedVariable, created by partitioning along dimension 0. Each
element must be appropriately sized for the '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.
|
Raises | |
|---|---|
ValueError
|
If params is empty.
|