flwr.common.parameter의 소스 코드

# Copyright 2020 Flower Labs GmbH. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Parameter conversion."""


from io import BytesIO
from typing import cast

import numpy as np

from .typing import NDArray, NDArrays, Parameters




def ndarrays_to_parameters(ndarrays: NDArrays) -> Parameters:
    """Convert NumPy ndarrays to parameters object."""
    tensors = [ndarray_to_bytes(ndarray) for ndarray in ndarrays]
    return Parameters(tensors=tensors, tensor_type="numpy.ndarray")





def parameters_to_ndarrays(parameters: Parameters) -> NDArrays:
    """Convert parameters object to NumPy ndarrays."""
    return [bytes_to_ndarray(tensor) for tensor in parameters.tensors]





def ndarray_to_bytes(ndarray: NDArray) -> bytes:
    """Serialize NumPy ndarray to bytes."""
    bytes_io = BytesIO()
    # WARNING: NEVER set allow_pickle to true.
    # Reason: loading pickled data can execute arbitrary code
    # Source: https://numpy.org/doc/stable/reference/generated/numpy.save.html
    np.save(bytes_io, ndarray, allow_pickle=False)
    return bytes_io.getvalue()





def bytes_to_ndarray(tensor: bytes) -> NDArray:
    """Deserialize NumPy ndarray from bytes."""
    bytes_io = BytesIO(tensor)
    # WARNING: NEVER set allow_pickle to true.
    # Reason: loading pickled data can execute arbitrary code
    # Source: https://numpy.org/doc/stable/reference/generated/numpy.load.html
    ndarray_deserialized = np.load(bytes_io, allow_pickle=False)
    return cast(NDArray, ndarray_deserialized)