module onnxrt.ops_cpu.op_relu#

Inheritance diagram of mlprodict.onnxrt.ops_cpu.op_relu

Short summary#

module mlprodict.onnxrt.ops_cpu.op_relu

Runtime operator.

source on GitHub

Classes#

class

truncated documentation

Relu

Relu ==== Relu takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where the rectified linear function, …

ThresholdedRelu

ThresholdedRelu =============== ThresholdedRelu takes one input data (Tensor<T>) and produces one output data (Tensor<T>) …

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

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_default_modified

Returns the list of modified parameters.

args_mandatory

Returns the list of optional arguments.

args_mandatory

Returns the list of optional arguments.

args_optional

Returns the list of optional arguments.

args_optional

Returns the list of optional arguments.

atts_value

Returns all parameters in a dictionary.

atts_value

Returns all parameters in a dictionary.

Methods#

method

truncated documentation

__init__

__init__

_run

_run

_run_inplace

_run_inplace

to_python

to_python

Documentation#

Runtime operator.

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_relu.Relu(onnx_node, desc=None, **options)#

Bases: OpRunUnaryNum

Relu takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where the rectified linear function, y = max(0, x), is applied to the tensor elementwise.

Inputs

  • X (heterogeneous)T: Input tensor

Outputs

  • Y (heterogeneous)T: Output tensor

Type Constraints

  • T tensor(float), tensor(int32), tensor(int8), tensor(int16), tensor(int64), tensor(float16), tensor(double), tensor(bfloat16): Constrain input and output types to signed numeric tensors.

Version

Onnx name: Relu

This version of the operator has been available since version 14.

Runtime implementation: Relu

__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

class mlprodict.onnxrt.ops_cpu.op_relu.ThresholdedRelu(onnx_node, desc=None, **options)#

Bases: OpRunUnaryNum

ThresholdedRelu takes one input data (Tensor<T>) and produces one output data (Tensor<T>) where the rectified linear function, y = x for x > alpha, y = 0 otherwise, is applied to the tensor elementwise.

Attributes

  • alpha: Threshold value Default value is namealphaf1.0typeFLOAT (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: ThresholdedRelu

This version of the operator has been available since version 10.

Runtime implementation: ThresholdedRelu

__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