module onnxrt.ops_cpu.op_max

Short summary

module mlprodict.onnxrt.ops_cpu.op_max

Runtime operator.

source on GitHub

Classes

class	truncated documentation
Max	Max === Element-wise max of each of the input tensors (with Numpy-style broadcasting support). All inputs and outputs …

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

Documentation

Runtime operator.

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_max.Max(onnx_node, desc=None, **options)

Bases: OpRunBinaryNumpy

===

Element-wise max of each of the input tensors (with Numpy-style broadcasting support). All inputs and outputs must have the same data type. This operator supports multidirectional (i.e., Numpy-style) broadcasting; for more details please check Broadcasting in ONNX.

Inputs

Between 1 and 2147483647 inputs.

• data_0 (variadic, heterogeneous)T: List of tensors for max.

Outputs

• max (heterogeneous)T: Output 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 and output types to numeric tensors.

Version

Onnx name: Max

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

Runtime implementation: Max

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

run(*data, attributes=None, verbose=0, fLOG=None)

Calls method _run.

source on GitHub