tf.contrib.layers.crossed_column(columns, hash_bucket_size, combiner=None, ckpt_to_load_from=None, tensor_name_in_ckpt=None, hash_key=None)
See the guide: Layers (contrib) > Feature columns
Creates a _CrossedColumn for performing feature crosses.
columns: An iterable of _FeatureColumn. Items can be an instance of _SparseColumn, _CrossedColumn, or _BucketizedColumn.
hash_bucket_size: An int that is > 1. The number of buckets.
combiner: A combiner string, supports sum, mean, sqrtn.
ckpt_to_load_from: (Optional). String representing checkpoint name/pattern to restore the column weights. Required if
tensor_name_in_ckptis not None.
tensor_name_in_ckpt: (Optional). Name of the
Tensorin the provided checkpoint from which to restore the column weights. Required if
ckpt_to_load_fromis not None.
hash_key: Specify the hash_key that will be used by the
FingerprintCat64function to combine the crosses fingerprints on SparseFeatureCrossOp (optional).
TypeError: if any item in columns is not an instance of _SparseColumn, _CrossedColumn, or _BucketizedColumn, or hash_bucket_size is not an int.
ValueError: if hash_bucket_size is not > 1 or len(columns) is not > 1.