openvino.runtime.opset13.tensor_iterator¶

class openvino.runtime.opset13.tensor_iterator¶

Bases: openvino._pyopenvino.Node

openvino.impl.op.TensorIterator wraps ov::op::v0::TensorIterator

__init__(self: openvino._pyopenvino.op.tensor_iterator) → None¶

Methods

`__add__`(right_node[, auto_broadcast, name])	Return node which applies f(A,B) = A+B to the input nodes element-wise.
`__delattr__`(name, /)	Implement delattr(self, name).
`__dir__`()	Default dir() implementation.
`__div__`(right_node[, auto_broadcast, name])	Return node which applies f(x) = A/B to the input nodes element-wise.
`__eq__`(right_node[, auto_broadcast, name])	Return node which checks if input nodes are equal element-wise.
`__format__`(format_spec, /)	Default object formatter.
`__ge__`(right_node[, auto_broadcast, name])	Return node which checks if left node is greater or equal to the right node element-wise.
`__getattr__`(self, arg0)
`__getattribute__`(name, /)	Return getattr(self, name).
`__gt__`(right_node[, auto_broadcast, name])	Return node which checks if left input node is greater than the right node element-wise.
`__hash__`()	Return hash(self).
`__init__`(self)
`__init_subclass__`	This method is called when a class is subclassed.
`__le__`(right_node[, auto_broadcast, name])	Return node which checks if left input node is less or equal the right node element-wise.
`__lt__`(right_node[, auto_broadcast, name])	Return node which checks if left input node is less than the right node element-wise.
`__mul__`(right_node[, auto_broadcast, name])	Return node which applies f(A,B) = A*B to the input nodes elementwise.
`__ne__`(right_node[, auto_broadcast, name])	Return node which checks if input nodes are unequal element-wise.
`__new__`(**kwargs)
`__radd__`(right)
`__rdiv__`(right)
`__reduce__`()	Helper for pickle.
`__reduce_ex__`(protocol, /)	Helper for pickle.
`__repr__`(self)
`__rmul__`(right)
`__rsub__`(right)
`__rtruediv__`(right)
`__setattr__`(name, value, /)	Implement setattr(self, name, value).
`__sizeof__`()	Size of object in memory, in bytes.
`__str__`()	Return str(self).
`__sub__`(right_node[, auto_broadcast, name])	Return node which applies f(x) = A-B to the input nodes element-wise.
`__subclasshook__`	Abstract classes can override this to customize issubclass().
`__truediv__`(right_node[, auto_broadcast, name])	Return node which applies f(x) = A/B to the input nodes element-wise.
`evaluate`(args, *kwargs)	Overloaded function.
`get_attributes`(self)
`get_body`(self)
`get_concatenated_slices`(self, value, start, ...)
`get_element_type`(self)	Checks that there is exactly one output and returns it's element type.
`get_friendly_name`(self)	Gets the friendly name for a node.
`get_function`(self)
`get_input_descriptions`(self)
`get_input_size`(self)	Returns the number of inputs to the node.
`get_input_tensor`(self, index)	Returns the tensor for the node's input with index i
`get_iter_value`(self, body_value, iteration)
`get_name`(self)	Get the unique name of the node
`get_num_iterations`(self)
`get_output_descriptions`(self)
`get_output_element_type`(self, index)	Returns the element type for output i
`get_output_partial_shape`(self, index)	Returns the partial shape for output i
`get_output_shape`(self, index)	Returns the shape for output i
`get_output_size`(self)	Returns the number of outputs from the node.
`get_output_tensor`(self, index)	Returns the tensor for output i
`get_rt_info`(self)	Returns PyRTMap which is a dictionary of user defined runtime info.
`get_type_info`(self)
`get_type_name`(self)	Returns Type's name from the node.
`input`(self, input_index)	A handle to the input_index input of this node.
`input_value`(self, index)	Returns input of the node with index i
`input_values`(self)	Returns list of node's inputs, in order.
`inputs`(self)	A list containing a handle for each of this node's inputs, in order.
`output`(self, output_index)	A handle to the output_index output of this node.
`outputs`(self)	A list containing a handle for each of this node's outputs, in order.
`set_argument`(self, arg0, arg1)
`set_arguments`(args, *kwargs)	Overloaded function.
`set_attribute`(self, arg0, arg1)
`set_body`(self, body)
`set_friendly_name`(self, name)	Sets a friendly name for a node.
`set_function`(self, func)
`set_input_descriptions`(self, inputs)
`set_invariant_input`(self, body_parameter, value)
`set_merged_input`(self, body_parameter, ...)
`set_output_descriptions`(self, outputs)
`set_sliced_input`(self, parameter, value, ...)
`validate`(self)

Attributes

`friendly_name`
`name`
`rt_info`
`shape`
`type_info`

__add__(right_node: Union[openvino._pyopenvino.Node, int, float, numpy.ndarray], auto_broadcast: str = 'NUMPY', name: Optional[str] = None) → openvino._pyopenvino.Node¶

Return node which applies f(A,B) = A+B to the input nodes element-wise.

Parameters

left_node – The first input node for add operation.
right_node – The second input node for add operation.
auto_broadcast – The type of broadcasting specifies rules used for auto-broadcasting of input tensors. Defaults to “NUMPY”.
name – The optional name for output new node.

Returns

The node performing element-wise addition.

__class__¶: alias of pybind11_builtins.pybind11_type

__delattr__(name, /)¶: Implement delattr(self, name).

__dir__()¶: Default dir() implementation.

__div__(right_node: Union[openvino._pyopenvino.Node, int, float, numpy.ndarray], auto_broadcast: str = 'NUMPY', name: Optional[str] = None) → openvino._pyopenvino.Node¶

Return node which applies f(x) = A/B to the input nodes element-wise.

Parameters

left_node – The node providing dividend data.
right_node – The node providing divisor data.
auto_broadcast – Specifies rules used for auto-broadcasting of input tensors.
name – Optional name for output node.

Returns

The node performing element-wise division.

__eq__(right_node: Union[openvino._pyopenvino.Node, int, float, numpy.ndarray], auto_broadcast: str = 'NUMPY', name: Optional[str] = None) → openvino._pyopenvino.Node¶

Return node which checks if input nodes are equal element-wise.

Parameters

left_node – The first input node for equal operation.
right_node – The second input node for equal operation.
auto_broadcast – The type of broadcasting specifies rules used for auto-broadcasting of input tensors.
name – The optional name for output new node.

Returns

The node performing element-wise equality check.

__format__(format_spec, /)¶: Default object formatter.

__ge__(right_node: Union[openvino._pyopenvino.Node, int, float, numpy.ndarray], auto_broadcast: str = 'NUMPY', name: Optional[str] = None) → openvino._pyopenvino.Node¶

Return node which checks if left node is greater or equal to the right node element-wise.

Parameters

left_node – The first input node providing data.
right_node – The second input node providing data.
auto_broadcast – The type of broadcasting specifies rules used for auto-broadcasting of input tensors.
name – The optional new name for output node.

Returns

The node performing element-wise check whether left_node is greater than or equal right_node.

__getattr__(self: openvino._pyopenvino.Node, arg0: str) → cpp_function¶

__getattribute__(name, /)¶: Return getattr(self, name).

__gt__(right_node: Union[openvino._pyopenvino.Node, int, float, numpy.ndarray], auto_broadcast: str = 'NUMPY', name: Optional[str] = None) → openvino._pyopenvino.Node¶

Return node which checks if left input node is greater than the right node element-wise.

Parameters

left_node – The first input node providing data.
right_node – The second input node providing data.
auto_broadcast – The type of broadcasting specifies rules used for auto-broadcasting of input tensors.
name – The optional new name for output node.

Returns

The node performing element-wise check whether left_node is greater than right_node.

__hash__()¶: Return hash(self).

__init__(self: openvino._pyopenvino.op.tensor_iterator) → None¶

__init_subclass__()¶

This method is called when a class is subclassed.

The default implementation does nothing. It may be overridden to extend subclasses.

__le__(right_node: Union[openvino._pyopenvino.Node, int, float, numpy.ndarray], auto_broadcast: str = 'NUMPY', name: Optional[str] = None) → openvino._pyopenvino.Node¶

Return node which checks if left input node is less or equal the right node element-wise.

Parameters

left_node – The first input node providing data.
right_node – The second input node providing data.
auto_broadcast – The type of broadcasting specifies rules used for auto-broadcasting of input tensors.
name – The optional new name for output node.

Returns

The node performing element-wise check whether left_node is less than or equal the right_node.

__lt__(right_node: Union[openvino._pyopenvino.Node, int, float, numpy.ndarray], auto_broadcast: str = 'NUMPY', name: Optional[str] = None) → openvino._pyopenvino.Node¶

Return node which checks if left input node is less than the right node element-wise.

Parameters

left_node – The first input node providing data.
right_node – The second input node providing data.
auto_broadcast – The type of broadcasting specifies rules used for auto-broadcasting of input tensors.
name – The optional new name for output node.

Returns

The node performing element-wise check whether left_node is less than the right_node.

__mul__(right_node: Union[openvino._pyopenvino.Node, int, float, numpy.ndarray], auto_broadcast: str = 'NUMPY', name: Optional[str] = None) → openvino._pyopenvino.Node¶

Return node which applies f(A,B) = A*B to the input nodes elementwise.

Parameters

left_node – The first input node for multiply operation.
right_node – The second input node for multiply operation.
auto_broadcast – The type of broadcasting specifies rules used for auto-broadcasting of input tensors. Defaults to “NUMPY”.
name – The optional name for output new node.

Returns

The node performing element-wise multiplication.

__ne__(right_node: Union[openvino._pyopenvino.Node, int, float, numpy.ndarray], auto_broadcast: str = 'NUMPY', name: Optional[str] = None) → openvino._pyopenvino.Node¶

Return node which checks if input nodes are unequal element-wise.

Parameters

left_node – The first input node for not-equal operation.
right_node – The second input node for not-equal operation.
auto_broadcast – The type of broadcasting specifies rules used for auto-broadcasting of input tensors.
name – The optional name for output new node.

Returns

The node performing element-wise inequality check.

__new__(**kwargs)¶

__radd__(right)¶

__rdiv__(right)¶

__reduce__()¶: Helper for pickle.

__reduce_ex__(protocol, /)¶: Helper for pickle.

__repr__(self: openvino._pyopenvino.op.tensor_iterator) → str¶

__rmul__(right)¶

__rsub__(right)¶

__rtruediv__(right)¶

__setattr__(name, value, /)¶: Implement setattr(self, name, value).

__sizeof__()¶: Size of object in memory, in bytes.

__str__()¶: Return str(self).

__sub__(right_node: Union[openvino._pyopenvino.Node, int, float, numpy.ndarray], auto_broadcast: str = 'NUMPY', name: Optional[str] = None) → openvino._pyopenvino.Node¶

Return node which applies f(x) = A-B to the input nodes element-wise.

Parameters

left_node – The node providing data for left hand side of operator.
right_node – The node providing data for right hand side of operator.
auto_broadcast – The type of broadcasting that specifies mapping of input tensor axes to output shape axes. Range of values: numpy, explicit.
name – The optional name for output node.

Returns

The new output node performing subtraction operation on both tensors element-wise.

__subclasshook__()¶

Abstract classes can override this to customize issubclass().

This is invoked early on by abc.ABCMeta.__subclasscheck__(). It should return True, False or NotImplemented. If it returns NotImplemented, the normal algorithm is used. Otherwise, it overrides the normal algorithm (and the outcome is cached).

__truediv__(right_node: Union[openvino._pyopenvino.Node, int, float, numpy.ndarray], auto_broadcast: str = 'NUMPY', name: Optional[str] = None) → openvino._pyopenvino.Node¶

Return node which applies f(x) = A/B to the input nodes element-wise.

Parameters

left_node – The node providing dividend data.
right_node – The node providing divisor data.
auto_broadcast – Specifies rules used for auto-broadcasting of input tensors.
name – Optional name for output node.

Returns

The node performing element-wise division.

evaluate(*args, **kwargs)¶

Overloaded function.

evaluate(self: openvino._pyopenvino.Node, output_values: List[ov::Tensor], input_values: List[ov::Tensor], evaluationContext: openvino._pyopenvino.RTMap) -> bool

Evaluate the node on inputs, putting results in outputs

param output_tensors

Tensors for the outputs to compute. One for each result.

type output_tensors

List[openvino.runtime.Tensor]

param input_tensors

Tensors for the inputs. One for each inputs.

type input_tensors

List[openvino.runtime.Tensor]

param evaluation_context

Storage of additional settings and attributes that can be used

when evaluating the function. This additional information can be shared across nodes. :type evaluation_context: openvino.runtime.RTMap :rtype: bool
evaluate(self: openvino._pyopenvino.Node, output_values: List[ov::Tensor], input_values: List[ov::Tensor]) -> bool

Evaluate the function on inputs, putting results in outputs

param output_tensors

Tensors for the outputs to compute. One for each result.

type output_tensors

List[openvino.runtime.Tensor]

param input_tensors

Tensors for the inputs. One for each inputs.

type input_tensors

List[openvino.runtime.Tensor]

rtype

bool

property friendly_name¶

get_attributes(self: openvino._pyopenvino.Node) → dict¶

get_body(self: openvino._pyopenvino.op.tensor_iterator) → object¶

get_concatenated_slices(self: openvino._pyopenvino.op.tensor_iterator, value: ov::Output<ov::Node>, start: int, stride: int, part_size: int, end: int, axis: int) → ov::Output<ov::Node>¶

get_element_type(self: openvino._pyopenvino.Node) → openvino._pyopenvino.Type¶

Checks that there is exactly one output and returns it’s element type.

Returns: Type of the output.
Return type: openvino.runtime.Type

get_friendly_name(self: openvino._pyopenvino.Node) → str¶

Gets the friendly name for a node. If no friendly name has been set via set_friendly_name then the node’s unique name is returned.

Returns: Friendly name of the node.
Return type: str

get_function(self: openvino._pyopenvino.op.tensor_iterator) → object¶

get_input_descriptions(self: openvino._pyopenvino.op.tensor_iterator) → list¶

get_input_size(self: openvino._pyopenvino.Node) → int¶

Returns the number of inputs to the node.

Returns: Number of inputs.
Return type: int

get_input_tensor(self: openvino._pyopenvino.Node, index: int) → ov::descriptor::Tensor¶

Returns the tensor for the node’s input with index i

Parameters: index (int) – Index of Input.
Returns: Tensor of the input i
Return type: openvino._pyopenvino.DescriptorTensor

get_iter_value(self: openvino._pyopenvino.op.tensor_iterator, body_value: ov::Output<ov::Node>, iteration: int = -1) → ov::Output<ov::Node>¶

get_name(self: openvino._pyopenvino.Node) → str¶

Get the unique name of the node

Returns: Unique name of the node.
Return type: str

get_num_iterations(self: openvino._pyopenvino.op.tensor_iterator) → int¶

get_output_descriptions(self: openvino._pyopenvino.op.tensor_iterator) → list¶

get_output_element_type(self: openvino._pyopenvino.Node, index: int) → openvino._pyopenvino.Type¶

Returns the element type for output i

Parameters: index (int) – Index of the output.
Returns: Type of the output i
Return type: openvino.runtime.Type

get_output_partial_shape(self: openvino._pyopenvino.Node, index: int) → openvino._pyopenvino.PartialShape¶

Returns the partial shape for output i

Parameters: index (int) – Index of the output.
Returns: PartialShape of the output i
Return type: openvino.runtime.PartialShape

get_output_shape(self: openvino._pyopenvino.Node, index: int) → openvino._pyopenvino.Shape¶

Returns the shape for output i

Parameters: index – Index of the output.
Returns: Shape of the output i
Return type: openvino.runtime.Shape

get_output_size(self: openvino._pyopenvino.Node) → int¶

Returns the number of outputs from the node.

Returns: Number of outputs.
Return type: int

get_output_tensor(self: openvino._pyopenvino.Node, index: int) → ov::descriptor::Tensor¶

Returns the tensor for output i

Parameters: index (int) – Index of the output.
Returns: Tensor of the output i
Return type: openvino._pyopenvino.DescriptorTensor

get_rt_info(self: openvino._pyopenvino.Node) → openvino._pyopenvino.RTMap¶

Returns PyRTMap which is a dictionary of user defined runtime info.

Returns: A dictionary of user defined data.
Return type: openvino.runtime.RTMap

get_type_info(self: openvino._pyopenvino.Node) → ov::DiscreteTypeInfo¶

get_type_name(self: openvino._pyopenvino.Node) → str¶

Returns Type’s name from the node.

Returns: String representing Type’s name.
Return type: str

input(self: openvino._pyopenvino.Node, input_index: int) → ov::Input<ov::Node>¶

A handle to the input_index input of this node.

Parameters: input_index (int) – Index of Input.
Returns: Input of this node.
Return type: openvino.runtime.Input

input_value(self: openvino._pyopenvino.Node, index: int) → ov::Output<ov::Node>¶

Returns input of the node with index i

Parameters: index (int) – Index of Input.
Returns: Input of this node.
Return type: openvino.runtime.Input

input_values(self: openvino._pyopenvino.Node) → List[ov::Output<ov::Node>]¶

Returns list of node’s inputs, in order.

Returns: List of node’s inputs
Return type: List[openvino.runtime.Input]

inputs(self: openvino._pyopenvino.Node) → List[ov::Input<ov::Node>]¶

A list containing a handle for each of this node’s inputs, in order.

Returns: List of node’s inputs.
Return type: List[openvino.runtime.Input]

property name¶

output(self: openvino._pyopenvino.Node, output_index: int) → ov::Output<ov::Node>¶

A handle to the output_index output of this node.

Parameters: output_index (int) – Index of Output.
Returns: Output of this node.
Return type: openvino.runtime.Output

outputs(self: openvino._pyopenvino.Node) → List[ov::Output<ov::Node>]¶

A list containing a handle for each of this node’s outputs, in order.

Returns: List of node’s outputs.
Return type: List[openvino.runtime.Output]

property rt_info¶

set_argument(self: openvino._pyopenvino.Node, arg0: int, arg1: ov::Output<ov::Node>) → None¶

set_arguments(*args, **kwargs)¶

Overloaded function.

set_arguments(self: openvino._pyopenvino.Node, arg0: List[openvino._pyopenvino.Node]) -> None
set_arguments(self: openvino._pyopenvino.Node, arg0: List[ov::Output<ov::Node>]) -> None
set_arguments(self: openvino._pyopenvino.Node, arg0: List[ov::Output<ov::Node>]) -> None

set_attribute(self: openvino._pyopenvino.Node, arg0: str, arg1: object) → None¶

set_body(self: openvino._pyopenvino.op.tensor_iterator, body: ov::Model) → None¶

set_friendly_name(self: openvino._pyopenvino.Node, name: str) → None¶

Sets a friendly name for a node. This does not overwrite the unique name of the node and is retrieved via get_friendly_name(). Used mainly for debugging. The friendly name may be set exactly once.

Parameters: name (str) – Friendly name to set.

set_function(self: openvino._pyopenvino.op.tensor_iterator, func: ov::Model) → None¶

set_input_descriptions(self: openvino._pyopenvino.op.tensor_iterator, inputs: list) → None¶

set_invariant_input(self: openvino._pyopenvino.op.tensor_iterator, body_parameter: openvino._pyopenvino.op.Parameter, value: ov::Output<ov::Node>) → None¶

set_merged_input(self: openvino._pyopenvino.op.tensor_iterator, body_parameter: openvino._pyopenvino.op.Parameter, initial_value: ov::Output<ov::Node>, successive_value: ov::Output<ov::Node>) → None¶

set_output_descriptions(self: openvino._pyopenvino.op.tensor_iterator, outputs: list) → None¶

set_sliced_input(self: openvino._pyopenvino.op.tensor_iterator, parameter: openvino._pyopenvino.op.Parameter, value: ov::Output<ov::Node>, start: int, stride: int, part_size: int, end: int, axis: int) → None¶

property shape¶

property type_info¶

validate(self: openvino._pyopenvino.Node) → None¶