Fix CuPy runtime deps and restore humming (#43530)

Signed-off-by: Mohammad Miadh Angkad <176301910+mmangkad@users.noreply.github.com>
(cherry picked from commit a970fb5a1a)

docker/Dockerfile

@@ -220,7 +220,8 @@ COPY use_existing_torch.py use_existing_torch.py
 COPY pyproject.toml pyproject.toml
 RUN --mount=type=cache,target=/opt/uv/cache \
     if [ "$(echo $CUDA_VERSION | cut -d. -f1)" = "12" ]; then \
-        sed -i 's/^nvidia-cutlass-dsl\[cu13\]>=/nvidia-cutlass-dsl>=/' requirements/cuda.txt; \
+        sed -i 's/^nvidia-cutlass-dsl\[cu13\]/nvidia-cutlass-dsl/' requirements/cuda.txt; \
+        sed -i 's/^humming-kernels\[cu13\]/humming-kernels[cu12]/' requirements/cuda.txt; \
     fi \
     && if [ "${PYTORCH_NIGHTLY}" = "1" ]; then \
         echo "Installing torch nightly..." \
@@ -746,7 +747,8 @@ COPY requirements/common.txt /tmp/common.txt
 COPY requirements/cuda.txt /tmp/requirements-cuda.txt
 RUN --mount=type=cache,target=/opt/uv/cache \
     if [ "$(echo $CUDA_VERSION | cut -d. -f1)" = "12" ]; then \
-        sed -i 's/^nvidia-cutlass-dsl\[cu13\]>=/nvidia-cutlass-dsl>=/' /tmp/requirements-cuda.txt; \
+        sed -i 's/^nvidia-cutlass-dsl\[cu13\]/nvidia-cutlass-dsl/' /tmp/requirements-cuda.txt; \
+        sed -i 's/^humming-kernels\[cu13\]/humming-kernels[cu12]/' /tmp/requirements-cuda.txt; \
     fi && \
     uv pip install --system -r /tmp/requirements-cuda.txt \
         --extra-index-url ${PYTORCH_CUDA_INDEX_BASE_URL}/cu$(echo $CUDA_VERSION | cut -d. -f1,2 | tr -d '.') && \

requirements/cuda.txt

@@ -25,4 +25,7 @@ nvidia-cutlass-dsl[cu13]==4.5.0
 quack-kernels>=0.3.3
 
 # Tokenspeed_MLA for faster mla with spec decode
-tokenspeed-mla==0.1.2
+tokenspeed-mla==0.1.2
+
+# Humming kernels for quantization gemm
+humming-kernels[cu13]==0.1.2

requirements/kv_connectors.txt

@@ -1,3 +1,6 @@
 lmcache >= 0.3.9
+# CuPy 14.1.0 imports pytest from cupy.testing._random. Use <14.1.0
+# until a fixed newer release is verified for runtime images.
+cupy-cuda13x < 14.1.0
 nixl >= 1.1.0 # Required for disaggregated prefill
 mooncake-transfer-engine >= 0.3.8

setup.py

@@ -1017,6 +1017,8 @@ def get_requirements() -> list[str]:
             if "nvidia-cutlass-dsl[cu13]" in req and cuda_major == "12":
                 # [cu13] extra is the default; strip it on CUDA 12 builds.
                 req = req.replace("nvidia-cutlass-dsl[cu13]", "nvidia-cutlass-dsl")
+            if "humming-kernels[cu13]" in req and cuda_major == "12":
+                req = req.replace("humming-kernels[cu13]", "humming-kernels[cu12]")
             modified_requirements.append(req)
         requirements = modified_requirements
     elif _is_hip():

vllm/model_executor/layers/quantization/humming.py

@@ -43,12 +43,9 @@ from vllm.model_executor.parameter import (
     RowvLLMParameter,
 )
 from vllm.model_executor.utils import set_weight_attrs
+from vllm.platforms import current_platform
 
-if TYPE_CHECKING:
-    from vllm.model_executor.models.utils import WeightsMapper
-
-
-try:
+if current_platform.is_cuda():
     from humming.dtypes import DataType
     from humming.layer import HummingMethod
     from humming.schema import (
@@ -65,16 +62,17 @@ try:
         HummingIndexedExperts,
         get_humming_moe_gemm_type,
     )
-except ModuleNotFoundError:
-    HummingMethod = None
 
-
-def assert_humming_available():
-    assert HummingMethod is not None, (
-        "humming is not available, please run "
-        "'pip install git+https://github.com/inclusionAI/humming' to install it."
+if TYPE_CHECKING:
+    from humming.schema import (
+        BaseInputSchema,
+        BaseWeightSchema,
+        HummingInputSchema,
+        HummingWeightSchema,
     )
 
+    from vllm.model_executor.models.utils import WeightsMapper
+
 
 def prepare_padded_shape(shape, x):
     padded_shape = math.ceil(shape / x) * x
@@ -186,7 +184,6 @@ class HummingConfig(QuantizationConfig):
     packed_modules_mapping: dict[str, list[str]] = {}
 
     def __init__(self, full_config: dict[str, Any] | None = None):
-        assert_humming_available()
         self.full_config: dict[str, Any] = full_config or {}
 
     @classmethod