Merge branch 'master' of https://github.com/UKPLab/sentence-transformers

 into v3.4-release

sentence_transformers/losses/AdaptiveLayerLoss.py

@@ -12,6 +12,9 @@
 from sentence_transformers import SentenceTransformer
 from sentence_transformers.losses.CachedGISTEmbedLoss import CachedGISTEmbedLoss
 from sentence_transformers.losses.CachedMultipleNegativesRankingLoss import CachedMultipleNegativesRankingLoss
+from sentence_transformers.losses.CachedMultipleNegativesSymmetricRankingLoss import (
+    CachedMultipleNegativesSymmetricRankingLoss,
+)
 from sentence_transformers.models import Transformer
 
 
@@ -149,7 +152,8 @@ def __init__(
             - `Adaptive Layers <../../examples/training/adaptive_layer/README.html>`_
 
         Requirements:
-            1. The base loss cannot be :class:`CachedMultipleNegativesRankingLoss` or :class:`CachedGISTEmbedLoss`.
+            1. The base loss cannot be :class:`CachedMultipleNegativesRankingLoss`,
+               :class:`CachedMultipleNegativesSymmetricRankingLoss`, or :class:`CachedGISTEmbedLoss`.
 
         Inputs:
             +---------------------------------------+--------+
@@ -192,10 +196,11 @@ def __init__(
         self.kl_div_weight = kl_div_weight
         self.kl_temperature = kl_temperature
         assert isinstance(self.model[0], Transformer)
-        if isinstance(loss, CachedMultipleNegativesRankingLoss):
-            warnings.warn("MatryoshkaLoss is not compatible with CachedMultipleNegativesRankingLoss.", stacklevel=2)
-        if isinstance(loss, CachedGISTEmbedLoss):
-            warnings.warn("MatryoshkaLoss is not compatible with CachedGISTEmbedLoss.", stacklevel=2)
+        if isinstance(
+            loss,
+            (CachedMultipleNegativesRankingLoss, CachedMultipleNegativesSymmetricRankingLoss, CachedGISTEmbedLoss),
+        ):
+            warnings.warn(f"MatryoshkaLoss is not compatible with {loss.__class__.__name__}.", stacklevel=2)
 
     def forward(self, sentence_features: Iterable[dict[str, Tensor]], labels: Tensor) -> Tensor:
         # Decorate the forward function of the transformer to cache the embeddings of all layers

sentence_transformers/losses/Matryoshka2dLoss.py

@@ -79,7 +79,8 @@ def __init__(
             - `Adaptive Layers <../../examples/training/adaptive_layer/README.html>`_
 
         Requirements:
-            1. The base loss cannot be :class:`CachedMultipleNegativesRankingLoss`.
+            1. The base loss cannot be :class:`CachedMultipleNegativesRankingLoss`,
+               :class:`CachedMultipleNegativesSymmetricRankingLoss`, or :class:`CachedGISTEmbedLoss`.
 
         Inputs:
             +---------------------------------------+--------+

sentence_transformers/losses/MatryoshkaLoss.py

@@ -124,6 +124,9 @@ def __init__(
         different embedding dimensions. This is useful for when you want to train a model where users have the option
         to lower the embedding dimension to improve their embedding comparison speed and costs.
 
+        This loss is also compatible with the Cached... losses, which are in-batch negative losses that allow for
+        higher batch sizes. The higher batch sizes allow for more negatives, and often result in a stronger model.
+
         Args:
             model: SentenceTransformer model
             loss: The loss function to be used, e.g.
@@ -143,9 +146,6 @@ def __init__(
             - The concept was introduced in this paper: https://arxiv.org/abs/2205.13147
             - `Matryoshka Embeddings <../../examples/training/matryoshka/README.html>`_
 
-        Requirements:
-            1. The base loss cannot be :class:`CachedMultipleNegativesRankingLoss` or :class:`CachedGISTEmbedLoss`.
-
         Inputs:
             +---------------------------------------+--------+
             | Texts                                 | Labels |