# type: ignore from __future__ import annotations from builtins import list as TensorShape from functools import partial from openvino._pyopenvino import Node from openvino._pyopenvino import Shape from openvino._pyopenvino.op import Constant from openvino._pyopenvino.op import Parameter from openvino.utils.decorators import binary_op from openvino.utils.decorators import nameable_op from openvino.utils.decorators import unary_op from openvino.utils.input_validation import assert_list_of_ints from openvino.utils.input_validation import check_valid_attributes from openvino.utils.input_validation import is_non_negative_value from openvino.utils.input_validation import is_positive_value from openvino.utils.node_factory import NodeFactory from openvino.utils.node_factory import _get_node_factory from openvino.utils.types import as_node from openvino.utils.types import as_nodes from openvino.utils.types import get_dtype from openvino.utils.types import get_element_type from openvino.utils.types import get_element_type_str from openvino.utils.types import make_constant_node import functools import numpy as np import openvino._pyopenvino import typing import warnings as warnings """ Factory functions for all openvino ops. """ __all__ = ['Constant', 'Node', 'NodeFactory', 'NodeInput', 'NumericData', 'NumericType', 'Parameter', 'ScalarData', 'Shape', 'TensorShape', 'as_node', 'as_nodes', 'assert_list_of_ints', 'batch_to_space', 'binary_op', 'check_valid_attributes', 'gelu', 'get_dtype', 'get_element_type', 'get_element_type_str', 'is_non_negative_value', 'is_positive_value', 'make_constant_node', 'mvn', 'nameable_op', 'np', 'partial', 'reorg_yolo', 'roi_pooling', 'space_to_batch', 'unary_op', 'warnings'] def batch_to_space(*args, **kwargs) -> openvino._pyopenvino.Node: """ Perform BatchToSpace operation on the input tensor. BatchToSpace permutes data from the batch dimension of the data tensor into spatial dimensions. :param data: Node producing the data tensor. :param block_shape: The sizes of the block of values to be moved. :param crops_begin: Specifies the amount to crop from the beginning along each axis of `data`. :param crops_end: Specifies the amount to crop from the end along each axis of `data`. :param name: Optional output node name. :return: The new node performing a BatchToSpace operation. """ def gelu(input_value, *args, **kwargs) -> openvino._pyopenvino.Node: """ Perform Gaussian Error Linear Unit operation element-wise on data from input node. Computes GELU function: \\f[ f(x) = 0.5\\cdot x\\cdot(1 + erf( \\dfrac{x}{\\sqrt{2}}) \\f] For more information refer to [Gaussian Error Linear Unit (GELU)](https://arxiv.org/pdf/1606.08415.pdf>) :param node: Input tensor. One of: input node, array or scalar. :param name: Optional output node name. :return: The new node performing a GELU operation on its input data element-wise. """ def mvn(*args, **kwargs) -> openvino._pyopenvino.Node: """ Perform Mean Variance Normalization operation on data from input node. Computes MVN on the input tensor `data` (called `X`) using formula: \\f[ Y = \\dfrac{X-EX}{\\sqrt{E(X-EX)^2}} \\f] :param data: The node with data tensor. :param across_channels: Denotes if mean values are shared across channels. :param normalize_variance: Denotes whether to perform variance normalization. :param eps: The number added to the variance to avoid division by zero when normalizing the value. Scalar value. :param name: Optional output node name. :return: The new node performing a MVN operation on input tensor. """ def reorg_yolo(*args, **kwargs) -> openvino._pyopenvino.Node: """ Return a node which produces the ReorgYolo operation. :param input: Input data. :param stride: Stride to reorganize input by. :param name: Optional name for output node. :return: ReorgYolo node. """ def roi_pooling(*args, **kwargs) -> openvino._pyopenvino.Node: """ Return a node which produces an ROIPooling operation. :param input: Input feature map `{N, C, ...}`. :param coords: Coordinates of bounding boxes. :param output_roi: Height/Width of ROI output features (shape). :param spatial_scale: Ratio of input feature map over input image size (float). :param method: Method of pooling - string: "max" or "bilinear". Default: "max" :param output_size: (DEPRECATED!) Height/Width of ROI output features (shape). Will override `output_roi` if used and change behavior of the operator. :return: ROIPooling node. """ def space_to_batch(*args, **kwargs) -> openvino._pyopenvino.Node: """ Perform SpaceToBatch operation on the input tensor. SpaceToBatch permutes data tensor blocks of spatial data into batch dimension. The operator returns a copy of the input tensor where values from spatial blocks dimensions are moved in the batch dimension :param data: Node producing the data tensor. :param block_shape: The sizes of the block of values to be moved. :param pads_begin: Specifies the padding for the beginning along each axis of `data`. :param pads_end: Specifies the padding for the ending along each axis of `data`. :param name: Optional output node name. :return: The new node performing a SpaceToBatch operation. """ NodeInput: typing._UnionGenericAlias # value = typing.Union[openvino._pyopenvino.Node, int, float, numpy.ndarray] NumericData: typing._UnionGenericAlias # value = typing.Union[int, float, numpy.ndarray] NumericType: typing._UnionGenericAlias # value = typing.Union[type, numpy.dtype] ScalarData: typing._UnionGenericAlias # value = typing.Union[int, float] _get_node_factory_opset2: functools.partial # value = functools.partial(, 'opset2')