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[misc] add hint for AttributeError (vllm-project#5462)
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youkaichao authored and joerunde committed Jun 13, 2024
1 parent b682ab8 commit d4765d4
Showing 1 changed file with 46 additions and 2 deletions.
48 changes: 46 additions & 2 deletions vllm/_custom_ops.py
Original file line number Diff line number Diff line change
@@ -1,13 +1,16 @@
import contextlib
import functools
from typing import List, Optional, Tuple, Type

import torch

from vllm.logger import init_logger

logger = init_logger(__name__)

try:
import vllm._C
except ImportError as e:
from vllm.logger import init_logger
logger = init_logger(__name__)
logger.warning("Failed to import from vllm._C with %r", e)

with contextlib.suppress(ImportError):
Expand All @@ -23,6 +26,25 @@ def is_custom_op_supported(op_name: str) -> bool:
return op is not None


def hint_on_error(fn):

@functools.wraps(fn)
def wrapper(*args, **kwargs):
try:
return fn(*args, **kwargs)
except AttributeError as e:
msg = (
"Error in calling custom op %s: %s\n"
"Possibly you have built or installed an obsolete version of vllm.\n"
"Please try a clean build and install of vllm,"
"or remove old built files such as vllm/*cpython*.so and build/ ."
)
logger.error(msg, fn.__name__, e)
raise e

return wrapper


# activation ops
def silu_and_mul(out: torch.Tensor, x: torch.Tensor) -> None:
torch.ops._C.silu_and_mul(out, x)
Expand Down Expand Up @@ -459,3 +481,25 @@ def dispatch_bgmv_low_level(
h_out,
y_offset,
)


# temporary fix for https://github.com/vllm-project/vllm/issues/5456
# TODO: remove this in v0.6.0
names_and_values = globals()
names_and_values_to_update = {}
# prepare variables to avoid dict size change during iteration
k, v, arg = None, None, None
fn_type = type(lambda x: x)
for k, v in names_and_values.items():
# find functions that are defined in this file and have torch.Tensor
# in their annotations. `arg == "torch.Tensor"` is used to handle
# the case when users use `import __annotations__` to turn type
# hints into strings.
if isinstance(v, fn_type) \
and v.__code__.co_filename == __file__ \
and any(arg is torch.Tensor or arg == "torch.Tensor"
for arg in v.__annotations__.values()):
names_and_values_to_update[k] = hint_on_error(v)

names_and_values.update(names_and_values_to_update)
del names_and_values_to_update, names_and_values, v, k, fn_type

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