[core] Bump ray to 2.43 (#13994)

Signed-off-by: Rui Qiao <ruisearch42@gmail.com>

.github/dependabot.yml

@@ -23,7 +23,7 @@ updates:
       - dependency-name: "lm-format-enforcer"
       - dependency-name: "gguf"
       - dependency-name: "compressed-tensors"
-      - dependency-name: "ray[adag]"
+      - dependency-name: "ray[cgraph]" # Ray Compiled Graph
       - dependency-name: "lm-eval"
     groups:
       minor-update:

requirements-cuda.txt

@@ -2,7 +2,7 @@
 -r requirements-common.txt
 
 # Dependencies for NVIDIA GPUs
-ray[adag] == 2.40.0 # Required for pipeline parallelism in V1.
+ray[cgraph] >= 2.43.0 # Ray Compiled Graph, required for pipeline parallelism in V1.
 torch == 2.5.1
 torchaudio==2.5.1
 # These must be updated alongside torch

requirements-test.in

@@ -16,7 +16,7 @@ vector_quantize_pytorch # required for minicpmo_26 test
 vocos # required for minicpmo_26 test
 peft
 pqdm
-ray[adag]==2.40.0
+ray[cgraph]>=2.43.0 # Ray Compiled Graph, required by pipeline parallelism tests
 sentence-transformers # required for embedding tests
 soundfile # required for audio tests
 jiwer # required for audio tests

requirements-test.txt

@@ -472,7 +472,7 @@ pyyaml==6.0.2
     #   vocos
 rapidfuzz==3.12.1
     # via jiwer
-ray==2.40.0
+ray==2.43.0
     # via -r requirements-test.in
 redis==5.2.0
     # via tensorizer

vllm/executor/ray_distributed_executor.py

@@ -500,7 +500,7 @@ class RayDistributedExecutor(DistributedExecutorBase):
         import pkg_resources
         from packaging import version
 
-        required_version = version.parse("2.40")
+        required_version = version.parse("2.43.0")
         current_version = version.parse(
             pkg_resources.get_distribution("ray").version)
         if current_version < required_version:
@@ -512,20 +512,19 @@ class RayDistributedExecutor(DistributedExecutorBase):
             "ray.experimental.compiled_dag_ref")
         if cgraph_spec is None:
             raise ValueError("Ray Compiled Graph is not installed. "
-                             "Run `pip install ray[adag]` to install it.")
+                             "Run `pip install ray[cgraph]` to install it.")
 
         cupy_spec = importlib.util.find_spec("cupy")
         if cupy_spec is None and envs.VLLM_USE_RAY_COMPILED_DAG_NCCL_CHANNEL:
             raise ValueError(
                 "cupy is not installed but required since "
                 "VLLM_USE_RAY_COMPILED_DAG_NCCL_CHANNEL is set. "
-                "Run `pip install ray[adag]` and check cupy installation.")
+                "Run `pip install ray[cgraph]` and check cupy installation.")
 
     def _compiled_ray_dag(self, enable_asyncio: bool):
         assert self.parallel_config.use_ray
         self._check_ray_cgraph_installation()
         from ray.dag import InputNode, MultiOutputNode
-        from ray.experimental.channel.torch_tensor_type import TorchTensorType
 
         logger.info("VLLM_USE_RAY_COMPILED_DAG_NCCL_CHANNEL = %s",
                     envs.VLLM_USE_RAY_COMPILED_DAG_NCCL_CHANNEL)
@@ -574,8 +573,7 @@ class RayDistributedExecutor(DistributedExecutorBase):
                         if envs.VLLM_USE_RAY_COMPILED_DAG_NCCL_CHANNEL \
                         else "auto"
                     outputs = [
-                        output.with_type_hint(
-                            TorchTensorType(transport=transport))
+                        output.with_tensor_transport(transport=transport)
                         for output in outputs
                     ]