# type: ignore from __future__ import annotations from builtins import list as TensorShape from functools import partial from functools import singledispatch from openvino._pyopenvino import Node from openvino._pyopenvino import Output from openvino._pyopenvino import PartialShape from openvino._pyopenvino import Shape from openvino._pyopenvino import Type from openvino._pyopenvino.op import Constant from openvino._pyopenvino.op import Parameter from openvino._pyopenvino.op import assign from openvino._pyopenvino.op import read_value as _read_value from openvino._pyopenvino.op.util import Variable from openvino._pyopenvino.op.util import VariableInfo from openvino.utils.decorators import nameable_op from openvino.utils.decorators import overloading 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_element_type import functools import numpy as np import openvino._pyopenvino import openvino.utils.decorators import typing __all__ = ['Constant', 'Node', 'NodeInput', 'NumericType', 'Output', 'Parameter', 'PartialShape', 'Shape', 'TensorShape', 'Type', 'Variable', 'VariableInfo', 'as_node', 'as_nodes', 'assign', 'ctc_greedy_decoder_seq_len', 'gather_elements', 'get_element_type', 'mvn', 'nameable_op', 'np', 'overloading', 'partial', 'read_value', 'singledispatch'] def ctc_greedy_decoder_seq_len(*args, **kwargs) -> openvino._pyopenvino.Node: """ Return a node which performs CTCGreedyDecoderSeqLen. :param data: The input 3D tensor. Shape: [batch_size, seq_length, num_classes] :param sequence_length: Input 1D tensor with sequence length. Shape: [batch_size] :param blank_index: Scalar or 1D tensor with specifies the class index to use for the blank class. Optional parameter. Default value is num_classes-1. :return: The new node which performs CTCGreedyDecoderSeqLen. """ def gather_elements(*args, **kwargs) -> openvino._pyopenvino.Node: """ Return a node which performs GatherElements. :param data: N-D tensor with data for gathering :param indices: N-D tensor with indices by which data is gathered :param axis: axis along which elements are gathered :return: The new node which performs GatherElements """ def mvn(*args, **kwargs) -> openvino._pyopenvino.Node: """ Return a node which performs MeanVarianceNormalization (MVN). :param data: The node with data tensor. :param axes: The node with axes to reduce on. :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 eps_mode: how eps is applied (`inside_sqrt` or `outside_sqrt`) :param name: Optional output node name. :return: The new node performing a MVN operation on input tensor. """ NodeInput: typing._UnionGenericAlias # value = typing.Union[openvino._pyopenvino.Node, int, float, numpy.ndarray] NumericType: typing._UnionGenericAlias # value = typing.Union[type, numpy.dtype] _get_node_factory_opset6: functools.partial # value = functools.partial(, 'opset6') read_value: openvino.utils.decorators.MultiMethod # value =