tf.raw_ops.EnqueueTPUEmbeddingSparseTensorBatch

Eases the porting of code that uses tf.nn.embedding_lookup_sparse().

sample_indices[i], embedding_indices[i] and aggregation_weights[i] correspond to the ith feature. table_ids[i] indicates which embedding table to look up ith feature.

The tensors at corresponding positions in the three input lists (sample_indices, embedding_indices and aggregation_weights) must have the same shape, i.e. rank 1 with dim_size() equal to the total number of lookups into the table described by the corresponding feature.

sample_indices A list of at least 1 Tensor objects with the same type in: int32, int64. A list of rank 1 Tensors specifying the training example to which the corresponding embedding_indices and aggregation_weights values belong. It corresponds to sp_ids.indices[:,0] in embedding_lookup_sparse().
embedding_indices A list with the same length as sample_indices of Tensor objects with the same type in: int32, int64. A list of rank 1 Tensors, indices into the embedding tables. It corresponds to sp_ids.values in embedding_lookup_sparse().
aggregation_weights A list with the same length as sample_indices of Tensor objects with the same type in: float32, float64. A list of rank 1 Ten