module `onnxrt.ops_cpu.op_expand`#

Short summary#

module mlprodict.onnxrt.ops_cpu.op_expand

Runtime operator.

Classes#

class	truncated documentation
`CommonExpand`
`Expand_13`	Expand ====== Broadcast the input tensor following the given shape and the broadcast rule. The broadcast rule is similar …
`Expand_13`	Expand ====== Broadcast the input tensor following the given shape and the broadcast rule. The broadcast rule is similar …

Functions#

function	truncated documentation
`common_reference_implementation`

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`	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_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_mandatory`	Returns the list of optional arguments.
`args_optional`	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.
`atts_value`	Returns all parameters in a dictionary.

Methods#

method	truncated documentation
`__init__`
`__init__`
`__init__`
`_run`
`_run`
`_run`

Documentation#

Runtime operator.

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_expand.CommonExpand(onnx_node, desc=None, expected_attributes=None, **options)#

Bases: OpRun

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

_run(data, shape, attributes=None, verbose=0, fLOG=None)#

Should be overwritten.

source on GitHub

mlprodict.onnxrt.ops_cpu.op_expand.Expand#: alias of Expand_13

class mlprodict.onnxrt.ops_cpu.op_expand.Expand_13(onnx_node, desc=None, **options)#

Bases: CommonExpand

Expand#

Broadcast the input tensor following the given shape and the broadcast rule. The broadcast rule is similar to numpy.array(input) * numpy.ones(shape): Dimensions are right alignment; Two corresponding dimensions must have the same value, or one of them is equal to 1. Also, this operator is similar to numpy.broadcast_to(input, shape), but the major difference is numpy.broadcast_to() does not allow shape to be smaller than input.size(). It is possible that the output.shape is not equal to shape, when some dimensions in shape is equal to 1, or the shape.ndim < input.shape.ndim.

Inputs

input (heterogeneous)T: Input tensor
shape (heterogeneous)tensor(int64): A 1-D tensor indicates the shape you want to expand to, following the broadcast rule

Outputs

output (heterogeneous)T: Output tensor

Type Constraints

T tensor(uint8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(int8), tensor(int16), tensor(int32), tensor(int64), tensor(bfloat16), tensor(float16), tensor(float), tensor(double), tensor(string), tensor(bool), tensor(complex64), tensor(complex128): Constrain input and output types to all tensors.

Version

Onnx name: Expand

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

Runtime implementation: Expand

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

module onnxrt.ops_cpu.op_expand#