module onnxrt.ops_cpu.op_softplus#

Inheritance diagram of mlprodict.onnxrt.ops_cpu.op_softplus

Short summary#

module mlprodict.onnxrt.ops_cpu.op_softplus

Runtime operator.

source on GitHub

Classes#

class

truncated documentation

Softplus

Softplus ======== Softplus takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where the softplus …

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_softplus.Softplus(onnx_node, desc=None, **options)#

Bases: OpRunUnaryNum

Softplus takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where the softplus function, y = ln(exp(x) + 1), is applied to the tensor elementwise.

Inputs

  • X (heterogeneous)T: 1D input tensor

Outputs

  • Y (heterogeneous)T: 1D input tensor

Type Constraints

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

Version

Onnx name: Softplus

This version of the operator has been available since version 1.

Runtime implementation: Softplus

__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