Fix tests

.github/workflows/test.yml

@@ -23,7 +23,6 @@ jobs:
       - name: Install dependencies
         run: |
           uv sync --all-groups
-          uv pip install torch==2.10
       - run: make test
         env:
           HF_TOKEN: ${{ secrets.HF_TOKEN }}

Makefile

@@ -41,9 +41,9 @@ reports:
 
 .PHONY: test
 test: reports
-	$(UV) pip install flash-attn --no-build-isolation --find-links https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/expanded_assets/v0.7.12
+	$(UV) pip install flash-attn --no-build-isolation --find-links https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/expanded_assets/v0.9.4
 	PYTHONPATH=. \
-	$(UV) run pytest \
+	$(UV) run --no-sync pytest \
 		--cov-report xml:reports/coverage.xml \
 		--cov=kvpress/ \
 		--junitxml=./reports/junit.xml \

kvpress/presses/kvcompose_press.py

@@ -273,11 +273,16 @@ def compute_important_per_layer(self):
         """
         self.compute_composite_scores()
 
-        threshold_head = self.composite_scores_per_head.quantile(self.compression_ratio)
-        self.important_per_head = (self.composite_scores_per_head >= threshold_head).sum(dim=-1).cpu().numpy()
+        n_kept = int(self.composite_scores_per_head.numel() * (1 - self.compression_ratio))
+        kept = self.composite_scores_per_head.reshape(-1).topk(n_kept).indices // self.context_len
+        bins = self.num_layers * self.num_kv_heads
+        self.important_per_head = (
+            torch.bincount(kept, minlength=bins).reshape(self.num_layers, self.num_kv_heads).cpu().numpy()
+        )
 
-        threshold_layer = self.composite_scores_per_layer.quantile(self.compression_ratio)
-        self.important_per_layer = (self.composite_scores_per_layer >= threshold_layer).sum(dim=-1).cpu().numpy()
+        n_kept = int(self.composite_scores_per_layer.numel() * (1 - self.compression_ratio))
+        kept = self.composite_scores_per_layer.reshape(-1).topk(n_kept).indices // self.context_len
+        self.important_per_layer = torch.bincount(kept, minlength=self.num_layers).cpu().numpy()
 
     def prepare_important_masks(self):
         """

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "kvpress"
-version = "0.5.2"
+version = "0.5.3"
 description = "Efficiently compress the KV cache of any pretrained transformer"
 authors = [
     { name = "Simon Jegou" },
@@ -13,7 +13,7 @@ readme = "README.md"
 dependencies = [
     "numpy>=2.0.0,<3",
     "torch>=2.3.1,<3",
-    "transformers>=4.56.0",
+    "transformers>=4.56.0,<5.3",
     "datasets>=2.21.0",
     "pandas>=2.2.2,<3",
     "accelerate>=1.0.0,<2",

tests/fixtures.py

@@ -80,7 +80,9 @@ def kv_press_llama3_1_flash_attn_pipeline():
         device=device,
         model_kwargs={"attn_implementation": attn_implementation, "dtype": torch.bfloat16},
     )
-    return pipe
+    yield pipe
+    del pipe
+    torch.cuda.empty_cache()
 
 
 @pytest.fixture(scope="class")
@@ -94,7 +96,9 @@ def kv_press_llama3_2_flash_attn_pipeline():
         device=device,
         model_kwargs={"attn_implementation": attn_implementation, "dtype": torch.bfloat16},
     )
-    return pipe
+    yield pipe
+    del pipe
+    torch.cuda.empty_cache()
 
 
 @pytest.fixture(scope="class")
@@ -108,4 +112,6 @@ def kv_press_qwen3_flash_attn_pipeline():
         device=device,
         model_kwargs={"attn_implementation": attn_implementation, "dtype": torch.bfloat16},
     )
-    return pipe
+    yield pipe
+    del pipe
+    torch.cuda.empty_cache()