module onnxrt.ops_cpu.op_less#

Inheritance diagram of mlprodict.onnxrt.ops_cpu.op_less

Short summary#

module mlprodict.onnxrt.ops_cpu.op_less

Runtime operator.

source on GitHub

Classes#

class

truncated documentation

Less

Less ==== Returns the tensor resulted from performing the less logical operation elementwise on the input tensors A

LessOrEqual

LessOrEqual =========== Returns the tensor resulted from performing the less_equal logical operation elementwise on …

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

to_python

to_python

Documentation#

Runtime operator.

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_less.Less(onnx_node, desc=None, **options)#

Bases: OpRunBinaryComparison

Returns the tensor resulted from performing the less logical operation elementwise on the input tensors A and B (with Numpy-style broadcasting support).

This operator supports multidirectional (i.e., Numpy-style) broadcasting; for more details please check Broadcasting in ONNX.

Inputs

  • A (heterogeneous)T: First input operand for the logical operator.

  • B (heterogeneous)T: Second input operand for the logical operator.

Outputs

  • C (heterogeneous)T1: Result tensor.

Type Constraints

  • T tensor(uint8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(int8), tensor(int16), tensor(int32), tensor(int64), tensor(float16), tensor(float), tensor(double), tensor(bfloat16): Constrain input types to all numeric tensors.

  • T1 tensor(bool): Constrain output to boolean tensor.

Version

Onnx name: Less

This version of the operator has been available since version 13.

Runtime implementation: Less

__init__(onnx_node, desc=None, **options)#
_run(a, b, attributes=None, verbose=0, fLOG=None)#

Should be overwritten.

source on GitHub

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_less.LessOrEqual(onnx_node, desc=None, **options)#

Bases: OpRunBinaryComparison

Returns the tensor resulted from performing the less_equal logical operation elementwise on the input tensors A and B (with Numpy-style broadcasting support).

This operator supports multidirectional (i.e., Numpy-style) broadcasting; for more details please check Broadcasting in ONNX.

Inputs

  • A (heterogeneous)T: First input operand for the logical operator.

  • B (heterogeneous)T: Second input operand for the logical operator.

Outputs

  • C (heterogeneous)T1: Result tensor.

Type Constraints

  • T tensor(uint8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(int8), tensor(int16), tensor(int32), tensor(int64), tensor(float16), tensor(float), tensor(double), tensor(bfloat16): Constrain input types to all numeric tensors.

  • T1 tensor(bool): Constrain output to boolean tensor.

Version

Onnx name: LessOrEqual

This version of the operator has been available since version 16.

Runtime implementation: LessOrEqual

__init__(onnx_node, desc=None, **options)#
_run(a, b, attributes=None, verbose=0, fLOG=None)#

Should be overwritten.

source on GitHub

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