tft.scale_by_min_max_per_key

Scale a numerical column into a predefined range on a per-key basis.

tft.scale_by_min_max_per_key(
    x, key, output_min=0.0, output_max=1.0, elementwise=False,
    key_vocabulary_filename=None, name=None
)

Args
`x`	A numeric `Tensor` or `SparseTensor`.
`key`	A `Tensor` or `SparseTensor` of dtype tf.string. Must meet one of the following conditions: key is None Both x and key are dense, Both x and key are sparse and `key` must exactly match `x` in everything except values, The axis=1 index of each x matches its index of dense key.
`output_min`	The minimum of the range of output values.
`output_max`	The maximum of the range of output values.
`elementwise`	If true, scale each element of the tensor independently.
`key_vocabulary_filename`	(Optional) The file name for the per-key file. If None, this combiner will assume the keys fit in memory and will not store the analyzer result in a file. If '', a file name will be chosen based on the current TensorFlow scope. If not '', it should be unique within a given preprocessing function.
`name`	(Optional) A name for this operation.

Returns
A `Tensor` or `SparseTensor` containing the input column scaled to [output_min, output_max] on a per-key basis if a key is provided. If the analysis dataset is empty or contains a single distinct value, then `x` is scaled using a sigmoid function.

Raises
`ValueError`	If output_min, output_max have the wrong order.
`NotImplementedError`	If elementwise is True and key is not None.
`InvalidArgumentError`	If indices of sparse x and key do not match.

Args