module onnxrt.ops_cpu.op_hardmax
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Short summary#
module mlprodict.onnxrt.ops_cpu.op_hardmax
Runtime operator.
Classes#
class |
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Hardmax ======= The operator computes the hardmax values for the given input: Hardmax(element in input, axis) = 1 if … |
Properties#
property |
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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_hardmax.Hardmax(onnx_node, desc=None, **options)#
Bases:
OpRunUnaryNum
The operator computes the hardmax values for the given input:
Hardmax(element in input, axis) = 1 if the element is the first maximum value along the specified axis, 0 otherwise
The “axis” attribute indicates the dimension along which Hardmax will be performed. The output tensor has the same shape and contains the Hardmax values of the corresponding input.
Attributes
axis:
Describes the dimension Hardmax will be performed on. Negative value means counting dimensions from the back. Accepted range is [-r, r-1] where r = rank(input).
Default value is
nameaxisi-1typeINT
(INT)Inputs
input (heterogeneous)T: The input tensor of rank >= axis.
Outputs
output (heterogeneous)T: The output values with the same shape as the input tensor.
Type Constraints
T tensor(float16), tensor(float), tensor(double), tensor(bfloat16): Constrain input and output types to float tensors.
Version
Onnx name: Hardmax
This version of the operator has been available since version 13.
Runtime implementation:
Hardmax
- __init__(onnx_node, desc=None, **options)#
- _run(x, attributes=None, verbose=0, fLOG=None)#
Should be overwritten.
- to_python(inputs)#
Returns a python code equivalent to this operator.
- Parameters:
inputs – inputs name
- Returns:
imports, python code, both as strings