module onnxrt.ops_cpu.op_category_mapper
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Short summary#
module mlprodict.onnxrt.ops_cpu.op_category_mapper
Runtime operator.
Classes#
class |
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CategoryMapper (ai.onnx.ml) =========================== Converts strings to integers and vice versa. Two sequences of … |
Properties#
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Returns the list of arguments as well as the list of parameters with the default values (close to the signature). … |
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Returns the list of modified parameters. |
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Returns the list of optional arguments. |
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Returns the list of optional arguments. |
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Returns all parameters in a dictionary. |
Methods#
method |
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Documentation#
Runtime operator.
- class mlprodict.onnxrt.ops_cpu.op_category_mapper.CategoryMapper(ai.onnx.ml)#
Bases:
OpRun
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. default value cannot be automatically retrieved (INTS)
cats_strings: The strings of the map. This sequence must be the same length as the ‘cats_int64s’ sequence default value cannot be automatically retrieved (STRINGS)
default_int64: An integer to use when an input string value is not found in the map. One and only one of the ‘default_*’ attributes must be defined. Default value is
namedefaultint64i-1typeINT
(INT)default_string: A string to use when an input integer value is not found in the map. One and only one of the ‘default_*’ attributes must be defined. Default value is
namedefaultstringsUnusedtypeSTRING
(STRING)
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 tensor(string), tensor(int64): The input must be a tensor of strings or integers, either [N,C] or [C].
T2 tensor(string), tensor(int64): The output is a tensor of strings or integers. Its shape will be the same as the input shape.
Version
Onnx name: CategoryMapper
This version of the operator has been available since version 1 of domain ai.onnx.ml.
Runtime implementation:
CategoryMapper
- __init__(onnx_node, desc=None, **options)#
- _run(x, attributes=None, verbose=0, fLOG=None)#
Should be overwritten.