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deepset-ai--haystack/haystack/dataclasses/sparse_embedding.py
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chore: import upstream snapshot with attribution
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Python

# SPDX-FileCopyrightText: 2022-present deepset GmbH <info@deepset.ai>
#
# SPDX-License-Identifier: Apache-2.0
from dataclasses import asdict, dataclass
from typing import Any
from haystack.utils.dataclasses import _warn_on_inplace_mutation
@_warn_on_inplace_mutation
@dataclass
class SparseEmbedding:
"""
Class representing a sparse embedding.
:param indices: List of indices of non-zero elements in the embedding.
:param values: List of values of non-zero elements in the embedding.
"""
indices: list[int]
values: list[float]
def __post_init__(self) -> None:
"""
Checks if the indices and values lists are of the same length.
Raises a ValueError if they are not.
"""
if len(self.indices) != len(self.values):
raise ValueError("Length of indices and values must be the same.")
def to_dict(self) -> dict[str, Any]:
"""
Convert the SparseEmbedding object to a dictionary.
:returns:
Serialized sparse embedding.
"""
return asdict(self)
@classmethod
def from_dict(cls, sparse_embedding_dict: dict[str, Any]) -> "SparseEmbedding":
"""
Deserializes the sparse embedding from a dictionary.
:param sparse_embedding_dict:
Dictionary to deserialize from.
:returns:
Deserialized sparse embedding.
"""
return cls(**sparse_embedding_dict)