ai.onnx.ml - CategoryMapper#
CategoryMapper - 1 (ai.onnx.ml)#
Version
name: CategoryMapper (GitHub)
domain: ai.onnx.ml
since_version: 1
function: False
support_level: SupportType.COMMON
shape inference: True
This version of the operator has been available since version 1 of domain ai.onnx.ml.
Summary
Converts strings to integers and vice versa.
Two sequences of equal length are used to map between integers and strings, with strings and integers at the same index detailing the mapping.
Each operator converts either integers to strings or strings to integers, depending on which default value attribute is provided. Only one default value attribute should be defined.
If the string default value is set, it will convert integers to strings. If the int default value is set, it will convert strings to integers.
Attributes
cats_int64s: The integers of the map. This sequence must be the same length as the ‘cats_strings’ sequence.
cats_strings: The strings of the map. This sequence must be the same length as the ‘cats_int64s’ sequence
default_int64: An integer to use when an input string value is not found in the map.<br>One and only one of the ‘default_*’ attributes must be defined. Default value is
-1.default_string: A string to use when an input integer value is not found in the map.<br>One and only one of the ‘default_*’ attributes must be defined. Default value is
'_Unused'.
Inputs
X (heterogeneous) - T1: Input data
Outputs
Y (heterogeneous) - T2: Output data. If strings are input, the output values are integers, and vice versa.
Type Constraints
T1 in ( tensor(int64), tensor(string) ): The input must be a tensor of strings or integers, either [N,C] or [C].
T2 in ( tensor(int64), tensor(string) ): The output is a tensor of strings or integers. Its shape will be the same as the input shape.
Examples