tf.raw_ops.EnqueueTPUEmbeddingRaggedTensorBatch

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

sample_splits[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 two of the input lists, 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_splits A list of at least 1 Tensor objects with the same type in: int32, int64. A list of rank 1 Tensors specifying the break points for splitting embedding_indices and aggregation_weights into rows. It corresponds to ids.row_splits in embedding_lookup(), when ids is a RaggedTensor.
embedding_indices A list with the same length as sample_splits of Tensor objects with the same type in: int32, int64. A list of rank 1 Tensors, indices into the embedding tables. It corresponds to ids.values in embedding_lookup(), when ids is a RaggedTensor.
aggregation_weights A list with the same length as sample_splits of Tensor objects with the same type in: float32, float64. A list of rank 1 Tensors containing per training example aggregation weights. It corresponds to the values field of a RaggedTensor with the same row_splits as ids in embedding_lookup(), when ids is a RaggedTensor.
mode_override A Tensor of type string. A string input that overrid