module onnxrt.ops_cpu.op_pow#

Inheritance diagram of mlprodict.onnxrt.ops_cpu.op_pow

Short summary#

module mlprodict.onnxrt.ops_cpu.op_pow

Runtime operator.

source on GitHub

Classes#

class

truncated documentation

Pow

Pow === Pow takes input data (Tensor<T>) and exponent Tensor, and produces one output data (Tensor<T>) where the function …

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__

_infer_shapes

_infer_sizes

_infer_types

_run

to_python

Documentation#

Runtime operator.

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_pow.Pow(onnx_node, desc=None, **options)#

Bases: OpRun

===

Pow takes input data (Tensor<T>) and exponent Tensor, and produces one output data (Tensor<T>) where the function f(x) = x^exponent, is applied to the data tensor elementwise. This operator supports multidirectional (i.e., Numpy-style) broadcasting; for more details please check Broadcasting in ONNX.

Inputs

  • X (heterogeneous)T: First operand, base of the exponent.

  • Y (heterogeneous)T1: Second operand, power of the exponent.

Outputs

  • Z (heterogeneous)T: Output tensor

Type Constraints

  • T tensor(int32), tensor(int64), tensor(float16), tensor(float), tensor(double), tensor(bfloat16): Constrain input X and output types to float/int tensors.

  • T1 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 Y types to float/int tensors.

Version

Onnx name: Pow

This version of the operator has been available since version 15.

Runtime implementation: Pow

__init__(onnx_node, desc=None, **options)#
_infer_shapes(x, b)#

Should be overwritten.

source on GitHub

_infer_sizes(*args, **kwargs)#

Should be overwritten.

source on GitHub

_infer_types(x, b)#

Should be overwritten.

source on GitHub

_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