module `onnxrt.ops_cpu.op_unsqueeze`#

Short summary#

module mlprodict.onnxrt.ops_cpu.op_unsqueeze

Runtime operator.

Classes#

class	truncated documentation
`Unsqueeze_1`
`Unsqueeze_11`
`Unsqueeze_13`	Unsqueeze ========= Insert single-dimensional entries to the shape of an input tensor (data). Takes one required input …
`Unsqueeze_13`	Unsqueeze ========= Insert single-dimensional entries to the shape of an input tensor (data). Takes one required input …

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`	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_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_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.
`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.
`atts_value`	Returns all parameters in a dictionary.

Methods#

method	truncated documentation
`__init__`
`__init__`
`__init__`
`__init__`
`_infer_shapes`
`_infer_shapes`
`_infer_shapes`
`_infer_shapes`
`_infer_sizes`
`_infer_sizes`
`_infer_sizes`
`_infer_sizes`
`_infer_types`
`_infer_types`
`_infer_types`
`_infer_types`
`_run`
`_run`
`_run`
`_run`

Documentation#

Runtime operator.

source on GitHub

mlprodict.onnxrt.ops_cpu.op_unsqueeze.Unsqueeze#: alias of mlprodict.onnxrt.ops_cpu.op_unsqueeze.Unsqueeze_13

class mlprodict.onnxrt.ops_cpu.op_unsqueeze.Unsqueeze_1(onnx_node, desc=None, **options)#

Bases: mlprodict.onnxrt.ops_cpu._op.OpRunUnaryNum

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

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

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

_infer_shapes(x)#

Returns the same shape by default.

source on GitHub

_infer_sizes(*args, **kwargs)#

Should be overwritten.

source on GitHub

_infer_types(x)#

Returns the same type by default.

source on GitHub

_run(data)#

Should be overwritten.

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_unsqueeze.Unsqueeze_11(onnx_node, desc=None, **options)#

Bases: mlprodict.onnxrt.ops_cpu.op_unsqueeze.Unsqueeze_1

Parameters

onnx_node – onnx node
desc – internal representation
expected_attributes – expected attributes for this node
options – runtime options

source on GitHub

class mlprodict.onnxrt.ops_cpu.op_unsqueeze.Unsqueeze_13(onnx_node, desc=None, **options)#

Bases: mlprodict.onnxrt.ops_cpu._op.OpRun

Insert single-dimensional entries to the shape of an input tensor (data). Takes one required input axes - which contains a list of dimension indices and this operator will insert a dimension of value 1 into the corresponding index of the output tensor (expanded).

For example:: Given an input tensor (data) of shape [3, 4, 5], then Unsqueeze(data, axes=[0, 4]) outputs a tensor (expanded) containing same data as data but with shape [1, 3, 4, 5, 1].

The input axes should not contain any duplicate entries. It is an error if it contains duplicates. The rank of the output tensor (output_rank) is the rank of the input tensor (data) plus the number of values in axes. Each value in axes should be within the (inclusive) range [-output_rank , output_rank - 1]. The order of values in axes does not matter and can come in any order.

Inputs

data (heterogeneous)T: Original tensor
axes (heterogeneous)tensor(int64): List of integers indicating the dimensions to be inserted. Negative value means counting dimensions from the back. Accepted range is [-r, r-1] where r = rank(expanded).

Outputs

expanded (heterogeneous)T: Reshaped tensor with same data as input.

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 tensor types.

Version

Onnx name: Unsqueeze

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

Runtime implementation: Unsqueeze

Parameters