qiskit_machine_learning.algorithms.serializable_model का स्रोत निर्देश

# This code is part of Qiskit.
# (C) Copyright IBM 2021, 2022.
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
# Any modifications or derivative works of this code must retain this
# copyright notice, and modified files need to carry a notice indicating
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"""A mixin class for saving and loading models."""

from typing import Any

import dill

[docs]class SerializableModelMixin: """ Provides convenient methods for saving and loading models. """
[docs] def save(self, file_name: str) -> None: """ Saves this model to the specified file. Internally, the model is serialized via ``dill``. All parameters are saved, including a quantum instance that is referenced by internal objects. That means if a model is loaded from a file and is used, for instance, for inference, the same quantum instance and a corresponding backend will be used even if a cloud backend was used. Args: file_name: a file name or path where to save the model. """ with open(file_name, "wb") as handler: dill.dump(self, handler)
[docs] @classmethod def load(cls, file_name: str) -> Any: """ Loads a model from the file. If the loaded model is not an instance of the class whose method was called, then a warning is raised. Nevertheless, the loaded model may be a valid model. Args: file_name: a file name or path to load a model from. Returns: A loaded model. Raises: TypeError: if a loaded model is not an instance of the expected class. """ with open(file_name, "rb") as handler: model = dill.load(handler) if not isinstance(model, cls): raise TypeError(f"Loaded model is of class {type(model)}. Expected class: {cls}.") return model