Rename ThresholdPress to DMSPress

Signed-off-by: SimJeg <sjegou@nvidia.com>

Author: SimJeg

README.md

@@ -130,7 +130,7 @@ Several presses inherit from `ScorerPress` ([source](kvpress/presses/scorer_pres
 - `LeverageScorePress` ([source](kvpress/presses/leverage_press.py), [paper](https://arxiv.org/abs/2507.08143)): evicts tokens based on approximate statistical leverage (i.e we preserve outliers in the key space).
 - `CompactorPress` ([source](kvpress/presses/compactor_press.py), [paper](https://arxiv.org/abs/2507.08143)): blends `NonCausalAttnPress` and `LeverageScorePress` based on the compression_ratio.
 - `CURPress` ([source](kvpress/presses/cur_press.py), [paper](https://arxiv.org/abs/2509.15038)): prune keys and values based on the CUR decomposition using approximate leverage scores.
-- `KVzapPress` ([source](kvpress/presses/kvzap/kvzap_press.py), [paper](https://arxiv.org/abs/2601.07891), [training](kvzap)): approximate KVzip+ using a fast surrogate model. To be used in conjunction with the `ThresholdPress`.
+- `KVzapPress` ([source](kvpress/presses/kvzap/kvzap_press.py), [paper](https://arxiv.org/abs/2601.07891), [training](kvzap)): approximate KVzip+ using a fast surrogate model. To be used in conjunction with the `DMSPress`.
 
 Some presses rely on a different logic:
 - `ThinKPress` ([source](kvpress/presses/think_press.py), [paper](https://arxiv.org/abs/2407.21018)): compress the dimensions of the keys based on the channel attention score on the last queries 
@@ -150,7 +150,7 @@ Finally we provide wrapper presses that can be combined with other presses:
 - `BlockPress` ([source](kvpress/presses/block_press.py), [paper](https://arxiv.org/abs/2504.15364)): segments input sequence into non-overlapping blocks and compresses iteratively.
 - `DecodingPress` ([source](kvpress/presses/decoding_press.py)): allows for compression during decoding, see decoding section in this README.
 - `PrefillDecodingPress` ([source](kvpress/presses/prefill_decoding_press.py)): allows to compress both during prefilling and during decoding.
-- `ThresholdPress` ([source](kvpress/presses/threshold_press.py)): evict keys and values with scores below a given threshold of any `ScorerPress` instead of relying on top-k scores. Support both prefilling and decoding (if decoding=True).
+- `DMSPress` ([source](kvpress/presses/dms_press.py), [paper](https://arxiv.org/abs/2506.05345)): evict keys and values with scores below a given threshold of any `ScorerPress` instead of relying on top-k scores. Support both prefilling and decoding (if decoding=True).
 
 For a detailed list of existing KV cache compression methods, check [Awesome-KV-Cache-Compression](https://github.com/October2001/Awesome-KV-Cache-Compression) or [Awesome-LLM-Compression](https://github.com/HuangOwen/Awesome-LLM-Compression?tab=readme-ov-file#kv-cache-compression)
 

evaluation/evaluate.py

@@ -28,7 +28,7 @@
     ObservedAttentionPress,
     ScorerPress,
     ThinKPress,
-    ThresholdPress,
+    DMSPress,
 )
 
 logger = logging.getLogger(__name__)
@@ -256,10 +256,10 @@ def _setup_press(self):
         if isinstance(press, DuoAttentionPress):
             press.head_compression_ratio = compression_ratio
             logger.info(f"Set DuoAttentionPress head_compression_ratio to {compression_ratio}")
-        elif isinstance(press, ThresholdPress):
-            assert self.config.threshold is not None, "threshold must be set for ThresholdPress"
+        elif isinstance(press, DMSPress):
+            assert self.config.threshold is not None, "threshold must be set for DMSPress"
             press.threshold = self.config.threshold
-            logger.info(f"Set ThresholdPress threshold to {press.threshold}")
+            logger.info(f"Set DMSPress threshold to {press.threshold}")
         elif isinstance(press, ComposedPress):
             for ps in press.presses:
                 if isinstance(ps, ThinKPress):

evaluation/evaluate_config.yaml

@@ -10,7 +10,7 @@ data_dir: "4096"                                  # Subdirectory of the dataset
 press_name: "knorm"                               # see PRESS_REGISTRY in evaluate_registry.py
 compression_ratio: 0.5                            # Compression ratio for the press (0.0 to 1.0)
 key_channel_compression_ratio: null               # For ThinKPress and ComposedPress (0.0 to 1.0)
-threshold: null                                   # For ThresholdPress
+threshold: null                                   # For DMSPress
 
 fraction: 1.0                                     # Fraction of dataset to evaluate (0.0 to 1.0), for quick testing
 max_new_tokens: null                              # Maximum new tokens to generate (null = use dataset default)

evaluation/evaluate_registry.py

@@ -34,7 +34,7 @@
     RandomPress,
     SnapKVPress,
     StreamingLLMPress,
-    ThresholdPress,
+    DMSPress,
     ThinKPress,
     TOVAPress,
     CURPress,
@@ -86,8 +86,8 @@
     "keydiff": KeyDiffPress(),
     "kvzip": KVzipPress(),
     "kvzip_plus": KVzipPress(kvzip_plus_normalization=True),
-    "kvzap_linear": ThresholdPress(press=KVzapPress(model_type="linear")),
-    "kvzap_mlp": ThresholdPress(press=KVzapPress(model_type="mlp")),
+    "kvzap_linear": DMSPress(press=KVzapPress(model_type="linear")),
+    "kvzap_mlp": DMSPress(press=KVzapPress(model_type="mlp")),
     "kvzap_mlp_head": KVzapPress(model_type="mlp"),
     "kvzap_mlp_layer": AdaKVPress(KVzapPress(model_type="mlp")),
     "lagkv": LagKVPress(),

kvpress/__init__.py

@@ -37,7 +37,7 @@
 from kvpress.presses.snapkv_press import SnapKVPress
 from kvpress.presses.streaming_llm_press import StreamingLLMPress
 from kvpress.presses.think_press import ThinKPress
-from kvpress.presses.threshold_press import ThresholdPress
+from kvpress.presses.dms_press import DMSPress
 from kvpress.presses.tova_press import TOVAPress
 
 # Patch the attention functions to support head-wise compression
@@ -80,5 +80,5 @@
     "LeverageScorePress",
     "NonCausalAttnPress",
     "KVzapPress",
-    "ThresholdPress",
+    "DMSPress",
 ]

kvpress/pipeline.py

@@ -16,7 +16,7 @@
 from kvpress.presses.finch_press import FinchPress
 from kvpress.presses.key_rerotation_press import KeyRerotationPress
 from kvpress.presses.prefill_decoding_press import PrefillDecodingPress
-from kvpress.presses.threshold_press import ThresholdPress
+from kvpress.presses.dms_press import DMSPress
 
 logger = logging.getLogger(__name__)
 
@@ -224,7 +224,7 @@ def _forward(
 
         # We only perform decoding compression if the press is a decoding or prefill decoding press
         perform_decoding_compression = press is not None and isinstance(press, (DecodingPress, PrefillDecodingPress))
-        if isinstance(press, ThresholdPress):
+        if isinstance(press, DMSPress):
             perform_decoding_compression = press.decoding
         with press(self.model) if perform_decoding_compression else contextlib.nullcontext():
             # Greedy decoding for each question

kvpress/presses/threshold_press.py kvpress/presses/dms_press.pykvpress/presses/threshold_press.py renamed to kvpress/presses/dms_press.py

@@ -13,11 +13,12 @@
 
 
 @dataclass
-class ThresholdPress(BasePress):
+class DMSPress(BasePress):
     """
+    Based on Dynamic Memory Sparsification (DMS, https://arxiv.org/abs/2506.05345) inference.
     Wraps a ScorerPress and evicts keys/values with scores below a given threshold.
 
-    Unlike most presses that use a fixed compression_ratio, ThresholdPress uses a score threshold
+    Unlike most presses that use a fixed compression_ratio, DMSPress uses a score threshold
     to determine which KV pairs to evict. This allows for adaptive compression where the actual
     compression ratio depends on the input content.
 

kvpress/presses/kvzap_press.py

@@ -50,7 +50,7 @@ class KVzapPress(ScorerPress):
     KVzap (https://arxiv.org/abs/2601.07891) is a fast approximation of KVzip that works
     in both prefilling and decoding. It applies a lightweight surrogate model to the hidden
     states to predict importance scores for every KV pair.
-    KVzapPress is designed to be used in conjunction with the ThresholdPress
+    KVzapPress is designed to be used in conjunction with the DMSPress
     model_type can be "linear" or "mlp".
     """
 

kvzap/README.md

@@ -7,16 +7,16 @@
 
 ## Usage
 
-KVzap is designed to be used by combining the `KVzapPress` and the `ThresholdPress` from kvpress:
+KVzap is designed to be used by combining the `KVzapPress` and the `DMSPress` from kvpress:
 
 ```python
 import requests
 from transformers import pipeline
-from kvpress import KVzapPress, ThresholdPress
+from kvpress import KVzapPress, DMSPress
 
 model = "Qwen/Qwen3-8B"
 pipe = pipeline("kv-press-text-generation", model=model, device_map="auto", dtype="auto")
-press = ThresholdPress(KVzapPress(model_type="mlp"), threshold=-4)
+press = DMSPress(KVzapPress(model_type="mlp"), threshold=-4)
 
 # Prefilling compression only, thinking disabled
 press.decoding = False
@@ -32,7 +32,7 @@ answer = pipe(prompt, press=press, enable_thinking=True, max_new_tokens=2000)["a
 print(f"Compression ratio: {press.compression_ratio:.2%}\nAnswer: {answer}")
 ```
 
-The `KVzapPress` inherits from the `ScorerPress` class and only predicts the scores for every KV pair. The `ThresholdPress` then prunes the KV pairs with a score below a given threshold, rather than using a fixed compression ratio.
+The `KVzapPress` inherits from the `ScorerPress` class and only predicts the scores for every KV pair. The `DMSPress` then prunes the KV pairs with a score below a given threshold, rather than using a fixed compression ratio.
 
 Supported base models are provided in the [KVzap collection](https://huggingface.co/collections/nvidia/kvzap) but can easily be extended to any other model following the instructions in the [training section](#training).
 

kvzap/evaluate_aime.py

@@ -10,7 +10,7 @@
 from transformers import AutoTokenizer, AutoModelForCausalLM
 from datasets import load_dataset
 
-from kvpress import KVzapPress, ThresholdPress
+from kvpress import KVzapPress, DMSPress
 
 
 def calculate_metrics(df):
@@ -56,11 +56,11 @@ def evaluate(
     """
 
     # Create press
-    press: ThresholdPress | type[nullcontext[None]]
+    press: DMSPress | type[nullcontext[None]]
     if kvzap_model_type == "no_press":
         press = nullcontext
     else:
-        press = ThresholdPress(
+        press = DMSPress(
             KVzapPress(model_type=kvzap_model_type),
             threshold=threshold,
             decoding=True,
@@ -86,7 +86,7 @@ def evaluate(
             )
             answer = tokenizer.decode(output_tokens[0, tokens.shape[1] :])
             df.loc[idx, "predicted_answer"] = answer
-            if isinstance(press, ThresholdPress):
+            if isinstance(press, DMSPress):
                 df.loc[idx, "compression_ratio"] = press.compression_ratio
             else:
                 df.loc[idx, "compression_ratio"] = 0