120 lines
4.5 KiB
Python
120 lines
4.5 KiB
Python
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# type: ignore
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from __future__ import annotations
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from collections.abc import ItemsView
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from collections.abc import Iterator
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from collections.abc import KeysView
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from collections.abc import Mapping
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from collections.abc import ValuesView
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from functools import singledispatchmethod
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from openvino._pyopenvino import ConstOutput
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from openvino._pyopenvino import InferRequest as InferRequestBase
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from openvino._pyopenvino import Tensor
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import collections.abc
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import numpy
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import numpy as np
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import openvino._pyopenvino
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import typing
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__all__ = ['ConstOutput', 'InferRequestBase', 'ItemsView', 'Iterator', 'KeysView', 'Mapping', 'OVDict', 'Tensor', 'ValuesView', 'np', 'singledispatchmethod', 'tensor_from_file']
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class OVDict(collections.abc.Mapping):
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"""
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Custom OpenVINO dictionary with inference results.
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This class is a dict-like object. It provides possibility to
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address data tensors with three key types:
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* `openvino.ConstOutput` - port of the output
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* `int` - index of the output
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* `str` - names of the output
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This class follows `frozenset`/`tuple` concept of immutability.
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It is prohibited to assign new items or edit them.
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To revert to the previous behavior use `to_dict` method which
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return shallow copy of underlaying dictionary.
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Note: It removes addressing feature! New dictionary keeps
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only `ConstOutput` keys.
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If a tuple returns value is needed, use `to_tuple` method which
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converts values to the tuple.
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:Example:
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.. code-block:: python
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# Reverts to the previous behavior of the native dict
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result = request.infer(inputs).to_dict()
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# or alternatively:
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result = dict(request.infer(inputs))
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.. code-block:: python
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# To dispatch outputs of multi-ouput inference:
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out1, out2, out3, _ = request.infer(inputs).values()
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# or alternatively:
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out1, out2, out3, _ = request.infer(inputs).to_tuple()
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"""
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__abstractmethods__: typing.ClassVar[frozenset] # value = frozenset()
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_abc_impl: typing.ClassVar[_abc._abc_data] # value = <_abc._abc_data object>
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@staticmethod
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def _OVDict__getitem_impl(*args, **kwargs) -> numpy.ndarray:
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...
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def _(self, key: str) -> numpy.ndarray:
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...
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def _OVDict__get_key(self, index: int) -> openvino._pyopenvino.ConstOutput:
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...
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def _OVDict__get_names(self) -> dict[openvino._pyopenvino.ConstOutput, set[str]]:
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"""
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Return names of every output key.
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Insert empty set if key has no name.
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"""
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def __getitem__(self, key: typing.Union[openvino._pyopenvino.ConstOutput, int, str]) -> numpy.ndarray:
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...
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def __init__(self, _dict: dict[openvino._pyopenvino.ConstOutput, numpy.ndarray[typing.Any, numpy.dtype[typing.Any]]]) -> None:
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...
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def __iter__(self) -> collections.abc.Iterator:
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...
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def __len__(self) -> int:
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...
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def __repr__(self) -> str:
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...
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def items(self) -> collections.abc.ItemsView[openvino._pyopenvino.ConstOutput, numpy.ndarray[typing.Any, numpy.dtype[typing.Any]]]:
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...
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def keys(self) -> collections.abc.KeysView[openvino._pyopenvino.ConstOutput]:
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...
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def names(self) -> tuple[set[str], ...]:
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"""
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Return names of every output key.
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Insert empty set if key has no name.
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"""
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def to_dict(self) -> dict[openvino._pyopenvino.ConstOutput, numpy.ndarray[typing.Any, numpy.dtype[typing.Any]]]:
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"""
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Return underlaying native dictionary.
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Function performs shallow copy, thus any modifications to
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returned values may affect this class as well.
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"""
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def to_tuple(self) -> tuple:
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"""
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Convert values of this dictionary to a tuple.
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"""
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def values(self) -> collections.abc.ValuesView[numpy.ndarray[typing.Any, numpy.dtype[typing.Any]]]:
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...
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class _InferRequestWrapper(openvino._pyopenvino.InferRequest):
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"""
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InferRequest class with internal memory.
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"""
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def __init__(self, other: openvino._pyopenvino.InferRequest) -> None:
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...
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def _is_single_input(self) -> bool:
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...
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def tensor_from_file(path: str) -> openvino._pyopenvino.Tensor:
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"""
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Create Tensor from file. Data will be read with dtype of unit8.
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"""
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