[Misc] Auto fallback to float16 for pre-Ampere GPUs when detected bfloat16 config (vllm-project#17265)

Signed-off-by: Isotr0py <2037008807@qq.com>

Author: Isotr0py

vllm/config.py

@@ -7,7 +7,6 @@
 import inspect
 import json
 import re
-import sys
 import textwrap
 import warnings
 from collections import Counter
@@ -34,7 +33,7 @@
                                                      QuantizationMethods,
                                                      get_quantization_config)
 from vllm.model_executor.models import ModelRegistry
-from vllm.platforms import CpuArchEnum, current_platform
+from vllm.platforms import current_platform
 from vllm.tracing import is_otel_available, otel_import_error_traceback
 from vllm.transformers_utils.config import (
     ConfigFormat, get_config, get_hf_image_processor_config,
@@ -2988,44 +2987,41 @@ def _get_and_verify_dtype(
     if isinstance(dtype, str):
         dtype = dtype.lower()
         if dtype == "auto":
+            # Set default dtype from model config
             if config_dtype == torch.float32:
                 # Following common practice, we use float16 for float32 models
                 torch_dtype = torch.float16
             else:
                 torch_dtype = config_dtype
 
             if config.model_type == "plamo2":
-                logger.info(
+                logger.warning(
                     "For PLaMo2, we cast models to bfloat16 instead of using "
                     "float16 by default. This is because float16 does not work."
                 )
                 torch_dtype = torch.bfloat16
 
+            # Deal with torch dtype fallback for device compatibility.
             from vllm.platforms import current_platform
-            if (current_platform.is_cpu()
-                    and current_platform.get_cpu_architecture()
-                    == CpuArchEnum.POWERPC
-                    and (config_dtype == torch.float16
-                         or config_dtype == torch.float32)):
-                logger.info(
-                    "For POWERPC, we cast models to bfloat16 instead of "
-                    "using float16 by default. Float16 is not currently "
-                    "supported for POWERPC.")
-                torch_dtype = torch.bfloat16
+            if torch_dtype not in current_platform.supported_dtypes:
+                device_name = current_platform.get_device_name()
 
-            # TODO: change this condition to check if the platform support bf16
-            # instead of checking the OS. For instance M2 shall supports bf16
-            # already. But we need to modify `cpu_extension.cmake` to activate
-            # the feature in the build.
-            if (current_platform.is_cpu() and sys.platform.startswith("darwin")
-                    and current_platform.get_cpu_architecture()
-                    == CpuArchEnum.ARM and config_dtype == torch.bfloat16):
-                logger.info("For macOS with Apple Silicon, currently bfloat16 "
-                            "is not supported. Setting dtype to float16.")
-                torch_dtype = torch.float16
+                if ((capability := current_platform.get_device_capability())
+                        is None):
+                    compute_str = ""
+                else:
+                    version_str = capability.as_version_str()
+                    compute_str = f" (with compute capability {version_str})"
+                fallback_dtype = current_platform.supported_dtypes[0]
+                logger.warning(
+                    "Your %s device%s doesn't support %s. " \
+                    "Falling back to %s for compatibility.",
+                    device_name, compute_str, torch_dtype, fallback_dtype
+                    )
+                torch_dtype = fallback_dtype
 
-            if current_platform.is_hpu() and config_dtype == torch.float16:
-                logger.info(
+            if current_platform.is_hpu() and torch_dtype == torch.float16:
+                logger.warning(
                     "For HPU, we cast models to bfloat16 instead of "
                     "using float16 by default. Please specify `dtype` if you "
                     "want to use float16.")

vllm/platforms/cpu.py

@@ -10,7 +10,7 @@
 
 from vllm.logger import init_logger
 
-from .interface import Platform, PlatformEnum, _Backend
+from .interface import CpuArchEnum, Platform, PlatformEnum, _Backend
 
 logger = init_logger(__name__)
 
@@ -26,6 +26,20 @@ class CpuPlatform(Platform):
     device_type: str = "cpu"
     dispatch_key: str = "CPU"
 
+    @property
+    def supported_dtypes(self) -> list:
+        if self.get_cpu_architecture() == CpuArchEnum.POWERPC:
+            return [torch.bfloat16, torch.float32]
+        elif sys.platform.startswith(
+                "darwin") and self.get_cpu_architecture() == CpuArchEnum.ARM:
+            # TODO: change this condition to check if the platform support bf16
+            # instead of checking the OS. For instance M2 shall supports bf16
+            # already. But we need to modify `cpu_extension.cmake` to activate
+            # the feature in the build.
+            return [torch.bfloat16, torch.float32]
+        # x86/aarch64 CPU has supported both bf16 and fp16 natively.
+        return [torch.bfloat16, torch.float16, torch.float32]
+
     @classmethod
     def get_device_name(cls, device_id: int = 0) -> str:
         return "cpu"

vllm/platforms/cuda.py

@@ -73,6 +73,19 @@ class CudaPlatformBase(Platform):
     ray_device_key: str = "GPU"
     device_control_env_var: str = "CUDA_VISIBLE_DEVICES"
 
+    @property
+    def supported_dtypes(self) -> List[torch.dtype]:
+        if self.has_device_capability(80):
+            # Ampere and Hopper or later NVIDIA GPUs.
+            return [torch.bfloat16, torch.float16, torch.float32]
+        elif (not self.has_device_capability(80)
+              ) and self.has_device_capability(60):
+            # Pascal, Volta and Turing NVIDIA GPUs, BF16 is not supported
+            return [torch.float16, torch.float32]
+        # Kepler and Maxwell NVIDIA GPUs, only FP32 is supported,
+        # though vLLM doesn't support these GPUs.
+        return [torch.float32]
+
     @classmethod
     def get_device_capability(cls,
                               device_id: int = 0

vllm/platforms/interface.py

@@ -122,6 +122,14 @@ class Platform:
 
     additional_env_vars: list[str] = []
 
+    @property
+    def supported_dtypes(self) -> list[torch.dtype]:
+        """Returns the supported dtypes for the current platform."""
+        # Be careful with the order of the dtypes. The first dtype will
+        # be used as the default dtype fallback for the current platform,
+        # when encountering unsupported dtypes in "auto" dtype.
+        return [torch.bfloat16, torch.float16, torch.float32]
+
     def is_cuda(self) -> bool:
         return self._enum == PlatformEnum.CUDA