tpu.py

from typing import TYPE_CHECKING, Optional

import torch

from vllm.logger import init_logger

from .interface import Platform, PlatformEnum, _Backend

if TYPE_CHECKING:
    from vllm.config import VllmConfig
else:
    VllmConfig = None

logger = init_logger(__name__)


class TpuPlatform(Platform):
    _enum = PlatformEnum.TPU
    device_name: str = "tpu"
    device_type: str = "tpu"
    dispatch_key: str = "XLA"
    ray_device_key: str = "TPU"
    device_control_env_var: str = "TPU_VISIBLE_CHIPS"

    supported_quantization: list[str] = [
        "tpu_int8", "compressed-tensors", "compressed_tensors"
    ]

    @classmethod
    def get_attn_backend_cls(cls, selected_backend: _Backend, head_size: int,
                             dtype: torch.dtype, kv_cache_dtype: Optional[str],
                             block_size: int, use_v1: bool,
                             use_mla: bool) -> str:
        if selected_backend != _Backend.PALLAS:
            logger.info("Cannot use %s backend on TPU.", selected_backend)
        logger.info("Using Pallas backend.")
        return "vllm.attention.backends.pallas.PallasAttentionBackend"

    @classmethod
    def get_device_name(cls, device_id: int = 0) -> str:
        raise NotImplementedError
    
    @classmethod
    def get_device_total_memory(cls, device_id: int = 0) -> int:
        raise NotImplementedError

    @classmethod
    def get_device_total_memory(cls, device_id: int = 0) -> int:
        raise NotImplementedError

    @classmethod
    def is_async_output_supported(cls, enforce_eager: Optional[bool]) -> bool:
        return True

    @classmethod
    def inference_mode(cls):
        return torch.no_grad()

    @classmethod
    def check_and_update_config(cls, vllm_config: VllmConfig) -> None:
        from vllm.config import CompilationLevel

        cache_config = vllm_config.cache_config
        if cache_config and cache_config.block_size is None:
            cache_config.block_size = 16

        compilation_config = vllm_config.compilation_config
        if compilation_config.level == CompilationLevel.NO_COMPILATION:
            # TPU does not support NO_COMPILATION
            compilation_config.level = CompilationLevel.DYNAMO_ONCE
        assert compilation_config.level < CompilationLevel.PIECEWISE,\
            "TPU does not support Inductor."

        if compilation_config.backend == "":
            compilation_config.backend = "openxla"

        assert vllm_config.speculative_config is None, \
            "TPU does not support speculative decoding"

        assert not vllm_config.scheduler_config.chunked_prefill_enabled, (
            "Chunked prefill is not yet supported for TPU backend")
        assert not vllm_config.speculative_config, (
            "Speculative decoding is not yet supported for TPU backend")
        if vllm_config.model_config.dtype in (torch.float16, torch.float32):
            logger.warning(
                "The TPU backend currently does not support %s. "
                "Using bfloat16 instead.", vllm_config.model_config.dtype)
            vllm_config.model_config.dtype = torch.bfloat16

        parallel_config = vllm_config.parallel_config
        scheduler_config = vllm_config.scheduler_config
        if parallel_config.worker_cls == "auto":
            if scheduler_config.is_multi_step:
                parallel_config.worker_cls = \
                    "vllm.worker.multi_step_tpu_worker.MultiStepTPUWorker"
            else:
                parallel_config.worker_cls = "vllm.worker.tpu_worker.TPUWorker"