[TPU] Rename tpu_commons to tpu_inference

vllm/distributed/device_communicators/tpu_communicator.py

@@ -10,7 +10,7 @@
 from vllm.config import get_current_vllm_config
 from vllm.logger import init_logger
 from vllm.platforms import current_platform
-from vllm.platforms.tpu import USE_TPU_COMMONS
+from vllm.platforms.tpu import USE_TPU_INFERENCE
 
 from .base_device_communicator import DeviceCommunicatorBase
 
@@ -20,8 +20,8 @@
 
 logger = init_logger(__name__)
 
-if not USE_TPU_COMMONS:
-    logger.info("tpu_commons not found, using vLLM's TpuCommunicator")
+if not USE_TPU_INFERENCE:
+    logger.info("tpu_inference not found, using vLLM's TpuCommunicator")
     if current_platform.is_tpu():
         import torch_xla
         import torch_xla.core.xla_model as xm
@@ -100,9 +100,9 @@ def all_gather(self, input_: torch.Tensor, dim: int = -1) -> torch.Tensor:
         return xm.all_gather(input_, dim=dim)
 
 
-if USE_TPU_COMMONS:
-    from tpu_commons.distributed.device_communicators import (
-        TpuCommunicator as TpuCommonsCommunicator,
+if USE_TPU_INFERENCE:
+    from tpu_inference.distributed.device_communicators import (
+        TpuCommunicator as TpuInferenceCommunicator,
     )
 
-    TpuCommunicator = TpuCommonsCommunicator  # type: ignore
+    TpuCommunicator = TpuInferenceCommunicator  # type: ignore

vllm/model_executor/model_loader/default_loader.py

@@ -222,9 +222,9 @@ def _get_weights_iterator(
                 )
 
         if current_platform.is_tpu():
-            from vllm.platforms.tpu import USE_TPU_COMMONS
+            from vllm.platforms.tpu import USE_TPU_INFERENCE
 
-            if not USE_TPU_COMMONS:
+            if not USE_TPU_INFERENCE:
                 # In PyTorch XLA, we should call `torch_xla.sync`
                 # frequently so that not too many ops are accumulated
                 # in the XLA program.

vllm/platforms/__init__.py

@@ -37,7 +37,7 @@ def tpu_platform_plugin() -> Optional[str]:
     # Check for Pathways TPU proxy
     if envs.VLLM_TPU_USING_PATHWAYS:
         logger.debug("Confirmed TPU platform is available via Pathways proxy.")
-        return "tpu_commons.platforms.tpu_jax.TpuPlatform"
+        return "tpu_inference.platforms.tpu_jax.TpuPlatform"
 
     # Check for libtpu installation
     try:

vllm/platforms/tpu.py

@@ -26,7 +26,7 @@
 
 logger = init_logger(__name__)
 
-USE_TPU_COMMONS = False
+USE_TPU_INFERENCE = False
 
 
 class TpuPlatform(Platform):
@@ -254,10 +254,10 @@ def use_sync_weight_loader(cls) -> bool:
 
 
 try:
-    from tpu_commons.platforms import TpuPlatform as TpuCommonsPlatform
+    from tpu_inference.platforms import TpuPlatform as TpuInferencePlatform
 
-    TpuPlatform = TpuCommonsPlatform  # type: ignore
-    USE_TPU_COMMONS = True
+    TpuPlatform = TpuInferencePlatform  # type: ignore
+    USE_TPU_INFERENCE = True
 except ImportError:
-    logger.info("tpu_commons not found, using vLLM's TpuPlatform")
+    logger.info("tpu_inference not found, using vLLM's TpuPlatform")
     pass

vllm/v1/attention/backends/pallas.py

@@ -35,7 +35,7 @@
 }
 
 try:
-    import tpu_commons  # noqa: F401
+    import tpu_inference  # noqa: F401
 except ImportError:
     # Lazy import torch_xla
     import torch_xla.core.xla_builder as xb

vllm/v1/worker/tpu_worker.py

@@ -23,7 +23,7 @@
 from vllm.lora.request import LoRARequest
 from vllm.model_executor import set_random_seed
 from vllm.platforms import current_platform
-from vllm.platforms.tpu import USE_TPU_COMMONS
+from vllm.platforms.tpu import USE_TPU_INFERENCE
 from vllm.tasks import SupportedTask
 from vllm.utils import STR_DTYPE_TO_TORCH_DTYPE, cdiv
 from vllm.v1.core.sched.output import SchedulerOutput
@@ -36,8 +36,8 @@
 
 _R = TypeVar("_R")
 
-if not USE_TPU_COMMONS:
-    logger.info("tpu_commons not found, using vLLM's TPUWorker.")
+if not USE_TPU_INFERENCE:
+    logger.info("tpu_inference not found, using vLLM's TPUWorker.")
     import torch_xla.core.xla_model as xm
     import torch_xla.debug.profiler as xp
     import torch_xla.runtime as xr
@@ -346,7 +346,7 @@ def apply_model(self, fn: Callable[[nn.Module], _R]) -> _R:
         return fn(self.get_model())
 
 
-if USE_TPU_COMMONS:
-    from tpu_commons.worker import TPUWorker as TPUCommonsWorker
+if USE_TPU_INFERENCE:
+    from tpu_inference.worker import TPUWorker as TpuInferenceWorker
 
-    TPUWorker = TPUCommonsWorker  # type: ignore
+    TPUWorker = TpuInferenceWorker  # type: ignore