module onnxrt.ops_cpu.op_hard_sigmoid

Short summary

module mlprodict.onnxrt.ops_cpu.op_hard_sigmoid

Runtime operator.

source on GitHub

Classes

class	truncated documentation
HardSigmoid	HardSigmoid =========== HardSigmoid takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where the …

Properties

property	truncated documentation
args_default	Returns the list of arguments as well as the list of parameters with the default values (close to the signature). …
args_default_modified	Returns the list of modified parameters.
args_mandatory	Returns the list of optional arguments.
args_optional	Returns the list of optional arguments.
atts_value	Returns all parameters in a dictionary.

Methods

method	truncated documentation
__init__
_run
_run_inplace
to_python

Documentation

Runtime operator.

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_hard_sigmoid.HardSigmoid(onnx_node, desc=None, **options)

Bases: OpRunUnaryNum

---

HardSigmoid takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where the HardSigmoid function, y = max(0, min(1, alpha * x + beta)), is applied to the tensor elementwise.

Attributes

• alpha: Value of alpha. Default value is namealphaf0.20000000298023224typeFLOAT (FLOAT)

• beta: Value of beta. Default value is namebetaf0.5typeFLOAT (FLOAT)

Inputs

• X (heterogeneous)T: Input tensor

Outputs

• Y (heterogeneous)T: Output tensor

Type Constraints

• T tensor(float16), tensor(float), tensor(double): Constrain input and output types to float tensors.

Version

Onnx name: HardSigmoid

This version of the operator has been available since version 6.

Runtime implementation: HardSigmoid

__init__(onnx_node, desc=None, **options)

_run(x, attributes=None, verbose=0, fLOG=None)

Should be overwritten.

source on GitHub

_run_inplace(x)

to_python(inputs)

Returns a python code equivalent to this operator.

Parameters:

inputs – inputs name

Returns:

imports, python code, both as strings

source on GitHub