feat(config): support parsing torch.dtype (#1641)

Signed-off-by: Aaron <[email protected]>

Author: aarnphm

vllm/config.py

@@ -1,4 +1,4 @@
-from typing import Optional
+from typing import Optional, Union
 
 import torch
 from transformers import PretrainedConfig
@@ -58,7 +58,7 @@ def __init__(
         trust_remote_code: bool,
         download_dir: Optional[str],
         load_format: str,
-        dtype: str,
+        dtype: Union[str, torch.dtype],
         seed: int,
         revision: Optional[str] = None,
         tokenizer_revision: Optional[str] = None,
@@ -331,25 +331,31 @@ def _verify_args(self) -> None:
 
 def _get_and_verify_dtype(
     config: PretrainedConfig,
-    dtype: str,
+    dtype: Union[str, torch.dtype],
 ) -> torch.dtype:
     # NOTE: getattr(config, "torch_dtype", torch.float32) is not correct
     # because config.torch_dtype can be None.
     config_dtype = getattr(config, "torch_dtype", None)
     if config_dtype is None:
         config_dtype = torch.float32
 
-    dtype = dtype.lower()
-    if dtype == "auto":
-        if config_dtype == torch.float32:
-            # Following the common practice, we use float16 for float32 models.
-            torch_dtype = torch.float16
+    if isinstance(dtype, str):
+        dtype = dtype.lower()
+        if dtype == "auto":
+            if config_dtype == torch.float32:
+                # Following the common practice, we use float16 for float32
+                # models.
+                torch_dtype = torch.float16
+            else:
+                torch_dtype = config_dtype
         else:
-            torch_dtype = config_dtype
+            if dtype not in _STR_DTYPE_TO_TORCH_DTYPE:
+                raise ValueError(f"Unknown dtype: {dtype}")
+            torch_dtype = _STR_DTYPE_TO_TORCH_DTYPE[dtype]
+    elif isinstance(dtype, torch.dtype):
+        torch_dtype = dtype
     else:
-        if dtype not in _STR_DTYPE_TO_TORCH_DTYPE:
-            raise ValueError(f"Unknown dtype: {dtype}")
-        torch_dtype = _STR_DTYPE_TO_TORCH_DTYPE[dtype]
+        raise ValueError(f"Unknown dtype: {dtype}")
 
     # Verify the dtype.
     if torch_dtype != config_dtype: