chore: import upstream snapshot with attribution

haystack/dataclasses/sparse_embedding.py

@@ -0,0 +1,52 @@
+# 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)