tft.bucketize_per_key

Returns a bucketized column, with a bucket index assigned to each input.

tft.bucketize_per_key(
    x: common_types.ConsistentTensorType,
    key: common_types.TensorType,
    num_buckets: int,
    epsilon: Optional[float] = None,
    name: Optional[str] = None
) -> common_types.ConsistentTensorType

Args
x	A numeric input Tensor or SparseTensor with rank 1, whose values should be mapped to buckets. SparseTensors will have their non-missing values mapped and missing values left as missing.
key	A Tensor or SparseTensor with the same shape as x and dtype tf.string. If x is a SparseTensor, key must exactly match x in everything except values, i.e. indices and dense_shape must be identical.
num_buckets	Values in the input x are divided into approximately equal-sized buckets, where the number of buckets is num_buckets.
epsilon	(Optional) see bucketize
name	(Optional) A name for this operation.

Returns
A Tensor of the same shape as x, with each element in the returned tensor representing the bucketized value. Bucketized value is in the range [0, actual_num_buckets). If the computed key vocabulary doesn't have an entry for key then the resulting bucket is -1.

Raises
ValueError	If value of num_buckets is not > 1.