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ANSLibs/OpenVINO/python/openvino/opset15/ops.pyi

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Python

# type: ignore
from __future__ import annotations
from functools import partial
from openvino._pyopenvino import Node
from openvino._pyopenvino import Type
from openvino.opset1.ops import convert_like
from openvino.utils.decorators import binary_op
from openvino.utils.decorators import nameable_op
from openvino.utils.node_factory import _get_node_factory
from openvino.utils.types import as_nodes
import functools
import numpy as np
import openvino._pyopenvino
import openvino.utils.decorators
import typing
"""
Factory functions for ops added to openvino opset15.
"""
__all__ = ['Node', 'NodeInput', 'Type', 'as_nodes', 'binary_op', 'bitwise_left_shift', 'bitwise_right_shift', 'col2im', 'constant', 'convert_like', 'embedding_bag_offsets', 'embedding_bag_packed', 'nameable_op', 'np', 'partial', 'roi_align_rotated', 'scatter_nd_update', 'search_sorted', 'slice_scatter', 'squeeze', 'stft', 'string_tensor_pack', 'string_tensor_unpack']
def bitwise_left_shift(left, right, *args, **kwargs) -> openvino._pyopenvino.Node:
"""
Return node which performs BitwiseLeftShift operation on input nodes element-wise.
:param arg0: Node with data to be shifted.
:param arg1: Node with number of shifts.
:param auto_broadcast: The type of broadcasting specifies rules used for auto-broadcasting of input tensors.
Defaults to “NUMPY”.
:return: The new node performing BitwiseLeftShift operation.
"""
def bitwise_right_shift(left, right, *args, **kwargs) -> openvino._pyopenvino.Node:
"""
Return node which performs BitwiseRightShift operation on input nodes element-wise.
:param arg0: Tensor with data to be shifted.
:param arg1: Tensor with number of shifts.
:param auto_broadcast: The type of broadcasting specifies rules used for auto-broadcasting of input tensors.
Defaults to “NUMPY”.
:return: The new node performing BitwiseRightShift operation.
"""
def col2im(*args, **kwargs) -> openvino._pyopenvino.Node:
"""
Perform data movement operation which combines sliding blocks into an image tensor.
:param data: The node providing input data.
:param output_size: Shape of the spatial dimensions of the output image.
:param kernel_size: Size of the sliding blocks.
:param strides: Stride on the sliding blocks in the input spatial dimensions. Defaults to [1, 1].
:param dilations: The dilation of filter elements (distance between elements). Defaults to [1, 1].
:param pads_begin: The number of pixels added at the beginning along each axis. Defaults to [0, 0].
:param pads_end: The number of pixels added at the end along each axis. Defaults to [0, 0].
:param name: The optional name for the created output node.
:return: The new node performing Col2Im operation.
"""
def embedding_bag_offsets(*args, **kwargs) -> openvino._pyopenvino.Node:
"""
Return a node which performs sums or means of bags of embeddings without the intermediate embeddings.
:param emb_table: Tensor containing the embedding lookup table.
:param indices: 1D Tensor with indices.
:param offsets: 1D Tensor containing the starting index positions of each bag in indices.
:param per_sample_weights: Tensor with weights for each sample.
:param default_index: Scalar containing default index in embedding table to fill empty bags.
If unset or set to -1, empty bags will be filled with 0.
Reverse indexing using negative indices is not supported.
:param reduction: String to select algorithm used to perform reduction of elements in bag.
:param name: Optional name for output node.
:return: The new node performing EmbeddingBagOffsets operation.
"""
def embedding_bag_packed(*args, **kwargs) -> openvino._pyopenvino.Node:
"""
Return a node which performs sums or means of "bags" of embeddings, without the intermediate embeddings.
:param emb_table: Tensor containing the embedding lookup table.
:param indices: 2D Tensor of shape [batch, indices_per_bag] with indices.
:param per_sample_weights: Tensor of weights to be multiplied with embedding table with same shape as indices.
:param reduction: Operator to perform reduction of elements in bag.
:param name: Optional name for output node.
:return: The new node performing EmbeddingBagPacked operation.
"""
def roi_align_rotated(*args, **kwargs) -> openvino._pyopenvino.Node:
"""
Return a node which performs ROIAlignRotated operation.
:param data: Input data.
:param rois: RoIs (Regions of Interest) to pool over.
:param batch_indices: Tensor with each element denoting the index of
the corresponding image in the batch.
:param pooled_h: Height of the ROI output feature map.
:param pooled_w: Width of the ROI output feature map.
:param sampling_ratio: Number of bins over height and width to use to calculate
each output feature map element.
:param spatial_scale: Multiplicative spatial scale factor to translate ROI coordinates.
:param clockwise_mode: If true, rotation angle is interpreted as clockwise,
otherwise as counterclockwise
:param name: The optional name for the output node
:return: The new node which performs ROIAlignRotated
"""
def scatter_nd_update(*args, **kwargs) -> openvino._pyopenvino.Node:
"""
Return a node which performs ScatterNDUpdate.
:param data: Node input representing the tensor to be updated.
:param indices: Node input representing the indices at which updates will be applied.
:param updates: Node input representing the updates to be applied.
:param reduction: The type of operation to perform on the inputs. One of "none", "sum",
"sub", "prod", "min", "max".
:param name: Optional name for the output node.
:return: New node performing the ScatterNDUpdate.
"""
def search_sorted(*args, **kwargs) -> openvino._pyopenvino.Node:
"""
Return a node which generates SearchSorted operation.
:param sorted_sequence: The node providing sorted sequence to search in.
:param values: The node providing searched values.
:param right_mode: If set to False, return the first suitable index that is found for given value.
If set to True, return the last such index. Defaults to False.
:param name: The optional name for the created output node.
:return: The new node performing SearchSorted operation.
"""
def slice_scatter(*args, **kwargs) -> openvino._pyopenvino.Node:
"""
Return a node which generates SliceScatter operation.
:param data: The node providing input data.
:param updates: The node providing updates data.
:param start: The node providing start indices (inclusively).
:param stop: The node providing stop indices (exclusively).
:param step: The node providing step values.
:param axes: The optional node providing axes to slice, default [0, 1, ..., len(start)-1].
:param name: The optional name for the created output node.
:return: The new node performing SliceScatter operation.
"""
def squeeze(*args, **kwargs) -> openvino._pyopenvino.Node:
"""
Perform squeeze operation on input tensor.
:param data: The node with data tensor.
:param axes: Optional list of integers, indicating the dimensions to squeeze.
Negative indices are supported. One of: input node or array.
:param allow_axis_skip: If true, shape inference results in a dynamic rank, when
selected axis has value 1 in its dynamic range. Used only if axes input
is given. Defaults to false.
:param name: Optional new name for output node.
:return: The new node performing a squeeze operation on input tensor.
Remove single-dimensional entries from the shape of a tensor.
Takes an optional parameter `axes` with a list of axes to squeeze.
If `axes` is not provided, all the single dimensions will be removed from the shape.
For example:
Inputs: tensor with shape [1, 2, 1, 3, 1, 1], axes=[2, 4]
Result: tensor with shape [1, 2, 3, 1]
"""
def stft(*args, **kwargs) -> openvino._pyopenvino.Node:
"""
Return a node which generates STFT operation.
:param data: The node providing input data.
:param window: The node providing window data.
:param frame_size: The node with scalar value representing the size of Fourier Transform.
:param frame_step: The distance (number of samples) between successive window frames.
:param transpose_frames: Flag to set output shape layout. If true the `frames` dimension is at out_shape[2],
otherwise it is at out_shape[1].
:param name: The optional name for the created output node.
:return: The new node performing STFT operation.
"""
def string_tensor_pack(*args, **kwargs) -> openvino._pyopenvino.Node:
"""
Perform an operation which packs a concatenated batch of strings into a batched string tensor.
:param begins: ND tensor of non-negative integer numbers containing indices of each string's beginnings.
:param ends: ND tensor of non-negative integer numbers containing indices of each string's endings.
:param symbols: 1D tensor of concatenated strings data encoded in utf-8 bytes.
:return: The new node performing StringTensorPack operation.
"""
def string_tensor_unpack(*args, **kwargs) -> openvino._pyopenvino.Node:
"""
Perform an operation which unpacks a batch of strings into three tensors.
:param data: The node providing input data.
:return: The new node performing StringTensorUnpack operation.
"""
NodeInput: typing._UnionGenericAlias # value = typing.Union[openvino._pyopenvino.Node, int, float, numpy.ndarray]
_get_node_factory_opset15: functools.partial # value = functools.partial(<function _get_node_factory at memory_address>, 'opset15')
constant: openvino.utils.decorators.MultiMethod # value = <openvino.utils.decorators.MultiMethod object>