module onnxrt.ops_cpu.op_matmul

Short summary

module mlprodict.onnxrt.ops_cpu.op_matmul

Runtime operator.

source on GitHub

Classes

class	truncated documentation
MatMul	MatMul ====== Matrix product that behaves like numpy.matmul: https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.matmul.html …

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
to_python

Documentation

Runtime operator.

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_matmul.MatMul(onnx_node, desc=None, **options)

Bases: OpRunBinaryNum

---

Matrix product that behaves like numpy.matmul: https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.matmul.html

Inputs

• A (heterogeneous)T: N-dimensional matrix A

• B (heterogeneous)T: N-dimensional matrix B

Outputs

• Y (heterogeneous)T: Matrix multiply results from A * B

Type Constraints

• T tensor(float16), tensor(float), tensor(double), tensor(uint32), tensor(uint64), tensor(int32), tensor(int64), tensor(bfloat16): Constrain input and output types to float/int tensors.

Version

Onnx name: MatMul

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

Runtime implementation: MatMul

__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