tf.compat.v1.nn.embedding_lookup

Looks up ids in a list of embedding tensors.

tf.compat.v1.nn.embedding_lookup(
    params, ids, partition_strategy='mod', name=None, validate_indices=True,
    max_norm=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.

If partition_strategy is "mod", we assign each id to partition p = id % len(params). For instance, 13 ids are split across 5 partitions as: [[0, 5, 10], [1, 6, 11], [2, 7, 12], [3, 8], [4, 9]]

If partition_strategy is "div", we assign ids to partitions in a contiguous manner. In this case, 13 ids are split across 5 partitions as: [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9, 10], [11, 12]]

If the input ids are ragged tensors, partition variables are not supported and the partition strategy and the max_norm are ignored. 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 given `partition_strategy`.
`ids`	A `Tensor` or a 'RaggedTensor' with type `int32` or `int64` containing the ids to be looked up in `params`.
`partition_strategy`	A string specifying the partitioning strategy, relevant if `len(params) > 1`. Currently `"div"` and `"mod"` are supported. Default is `"mod"`.
`name`	A name for the operation (optional).
`validate_indices`	DEPRECATED. If this operation is assigned to CPU, values in `indices` are always validated to be within range. If assigned to GPU, out-of-bound indices result in safe but unspecified behavior, which may include raising an error.
`max_norm`	If not `None`, each embedding is clipped if its l2-norm is larger than this value.

Returns
A `Tensor` or a 'RaggedTensor', depending on the input, with the same type as the tensors in `params`.

Raises
`ValueError`	If `params` is empty.

tf.compat.v1.nn.embedding_lookup

Args

Returns

Raises