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Unverified Commit 09dc7c69 authored by Cyrus Leung's avatar Cyrus Leung Committed by GitHub
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[Chore][1/2] Drop `v0.14` deprecations (#31285) 


Signed-off-by: default avatarDarkLight1337 <tlleungac@connect.ust.hk>
parent 506eb0f4
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Showing with 28 additions and 405 deletions
docs/api/README.md
View file @ 09dc7c69
......@@ -72,7 +72,6 @@ Internal data structures.
- [vllm.multimodal.inputs.MultiModalFieldConfig][]
- [vllm.multimodal.inputs.MultiModalKwargsItem][]
- [vllm.multimodal.inputs.MultiModalKwargsItems][]
- [vllm.multimodal.inputs.MultiModalKwargs][]
- [vllm.multimodal.inputs.MultiModalInputs][]
### Data Parsing
......
tests/entrypoints/openai/test_chat_error.py
View file @ 09dc7c69
......@@ -13,7 +13,7 @@ from vllm.entrypoints.openai.protocol import ChatCompletionRequest, ErrorRespons
from vllm.entrypoints.openai.serving_chat import OpenAIServingChat
from vllm.entrypoints.openai.serving_models import BaseModelPath, OpenAIServingModels
from vllm.outputs import CompletionOutput, RequestOutput
from vllm.transformers_utils.tokenizer import get_tokenizer
from vllm.tokenizers import get_tokenizer
from vllm.v1.engine.async_llm import AsyncLLM
MODEL_NAME = "openai-community/gpt2"
......
tests/entrypoints/openai/test_completion_error.py
View file @ 09dc7c69
......@@ -13,7 +13,7 @@ from vllm.entrypoints.openai.protocol import CompletionRequest, ErrorResponse
from vllm.entrypoints.openai.serving_completion import OpenAIServingCompletion
from vllm.entrypoints.openai.serving_models import BaseModelPath, OpenAIServingModels
from vllm.outputs import CompletionOutput, RequestOutput
from vllm.transformers_utils.tokenizer import get_tokenizer
from vllm.tokenizers import get_tokenizer
from vllm.v1.engine.async_llm import AsyncLLM
MODEL_NAME = "openai-community/gpt2"
......
tests/entrypoints/openai/test_lora_resolvers.py
View file @ 09dc7c69
......@@ -61,13 +61,13 @@ class MockLoRAResolver(LoRAResolver):
return LoRARequest(
lora_name="test-lora",
lora_int_id=1,
lora_local_path="/fake/path/test-lora",
lora_path="/fake/path/test-lora",
)
elif lora_name == "invalid-lora":
return LoRARequest(
lora_name="invalid-lora",
lora_int_id=2,
lora_local_path="/fake/path/invalid-lora",
lora_path="/fake/path/invalid-lora",
)
return None
......
vllm/entrypoints/context.py
View file @ 09dc7c69
......@@ -41,9 +41,8 @@ from vllm.entrypoints.tool import Tool
from vllm.entrypoints.tool_server import ToolServer
from vllm.outputs import RequestOutput
from vllm.reasoning.abs_reasoning_parsers import ReasoningParser
from vllm.tokenizers.protocol import TokenizerLike
from vllm.tokenizers import TokenizerLike
from vllm.tool_parsers.abstract_tool_parser import ToolParser
from vllm.transformers_utils.tokenizer import AnyTokenizer
from vllm.utils import random_uuid
if TYPE_CHECKING:
......@@ -259,8 +258,8 @@ class ParsableContext(ConversationContext):
self,
*,
response_messages: list[ResponseInputOutputItem],
tokenizer: AnyTokenizer,
reasoning_parser_cls: Callable[[AnyTokenizer], ReasoningParser] | None,
tokenizer: TokenizerLike,
reasoning_parser_cls: Callable[[TokenizerLike], ReasoningParser] | None,
request: ResponsesRequest,
available_tools: list[str] | None,
tool_parser_cls: Callable[[TokenizerLike], ToolParser] | None,
......
vllm/entrypoints/openai/parser/responses_parser.py
View file @ 09dc7c69
......@@ -19,9 +19,8 @@ from vllm.entrypoints.constants import MCP_PREFIX
from vllm.entrypoints.openai.protocol import ResponseInputOutputItem, ResponsesRequest
from vllm.outputs import CompletionOutput
from vllm.reasoning.abs_reasoning_parsers import ReasoningParser
from vllm.tokenizers.protocol import TokenizerLike
from vllm.tokenizers import TokenizerLike
from vllm.tool_parsers.abstract_tool_parser import ToolParser
from vllm.transformers_utils.tokenizer import AnyTokenizer
from vllm.utils import random_uuid
logger = logging.getLogger(__name__)
......@@ -33,8 +32,8 @@ class ResponsesParser:
def __init__(
self,
*,
tokenizer: AnyTokenizer,
reasoning_parser_cls: Callable[[AnyTokenizer], ReasoningParser],
tokenizer: TokenizerLike,
reasoning_parser_cls: Callable[[TokenizerLike], ReasoningParser],
response_messages: list[ResponseInputOutputItem],
request: ResponsesRequest,
tool_parser_cls: Callable[[TokenizerLike], ToolParser] | None,
......@@ -150,8 +149,8 @@ class ResponsesParser:
def get_responses_parser_for_simple_context(
*,
tokenizer: AnyTokenizer,
reasoning_parser_cls: Callable[[AnyTokenizer], ReasoningParser],
tokenizer: TokenizerLike,
reasoning_parser_cls: Callable[[TokenizerLike], ReasoningParser],
response_messages: list[ResponseInputOutputItem],
request: ResponsesRequest,
tool_parser_cls,
......
vllm/entrypoints/openai/serving_models.py
View file @ 09dc7c69
......@@ -119,7 +119,7 @@ class OpenAIServingModels:
lora_cards = [
ModelCard(
id=lora.lora_name,
root=lora.local_path,
root=lora.path,
parent=lora.base_model_name
if lora.base_model_name
else self.base_model_paths[0].name,
......
vllm/entrypoints/openai/tool_parsers/__init__.py deleted 100644 → 0
View file @ 506eb0f4
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import warnings
def __getattr__(name: str):
if name == "ToolParser":
from vllm.tool_parsers import ToolParser
warnings.warn(
"`vllm.entrypoints.openai.tool_parsers.ToolParser` has been moved to "
"`vllm.tool_parsers.ToolParser`. "
"The old name will be removed in v0.14.",
DeprecationWarning,
stacklevel=2,
)
return ToolParser
if name == "ToolParserManager":
from vllm.tool_parsers import ToolParserManager
warnings.warn(
"`vllm.entrypoints.openai.tool_parsers.ToolParserManager` "
"has been moved to `vllm.tool_parsers.ToolParserManager`. "
"The old name will be removed in v0.14.",
DeprecationWarning,
stacklevel=2,
)
return ToolParserManager
raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
vllm/lora/request.py
View file @ 09dc7c69
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import warnings
import msgspec
......@@ -21,7 +20,6 @@ class LoRARequest(
lora_name: str
lora_int_id: int
lora_path: str = ""
lora_local_path: str | None = msgspec.field(default=None)
long_lora_max_len: int | None = None
base_model_name: str | None = msgspec.field(default=None)
tensorizer_config_dict: dict | None = None
......@@ -29,16 +27,6 @@ class LoRARequest(
def __post_init__(self):
if self.lora_int_id < 1:
raise ValueError(f"id must be > 0, got {self.lora_int_id}")
if self.lora_local_path:
warnings.warn(
"The 'lora_local_path' attribute is deprecated "
"and will be removed in a future version. "
"Please use 'lora_path' instead.",
DeprecationWarning,
stacklevel=2,
)
if not self.lora_path:
self.lora_path = self.lora_local_path or ""
# Ensure lora_path is not empty
assert self.lora_path, "lora_path cannot be empty"
......@@ -55,28 +43,6 @@ class LoRARequest(
def path(self):
return self.lora_path
@property
def local_path(self):
warnings.warn(
"The 'local_path' attribute is deprecated "
"and will be removed in a future version. "
"Please use 'path' instead.",
DeprecationWarning,
stacklevel=2,
)
return self.lora_path
@local_path.setter
def local_path(self, value):
warnings.warn(
"The 'local_path' attribute is deprecated "
"and will be removed in a future version. "
"Please use 'path' instead.",
DeprecationWarning,
stacklevel=2,
)
self.lora_path = value
def __eq__(self, value: object) -> bool:
"""
Overrides the equality method to compare LoRARequest
......
vllm/model_executor/models/interfaces.py
View file @ 09dc7c69
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from collections.abc import Callable, Iterable, Mapping, MutableSequence, Set
from collections.abc import Callable, Iterable, Mapping, MutableSequence
from typing import (
TYPE_CHECKING,
ClassVar,
......@@ -100,17 +100,6 @@ class SupportsMultiModal(Protocol):
in their raw form and not input embeddings.
"""
merge_by_field_config: ClassVar[bool | None] = None
"""
[DEPRECATED] A flag that indicates which implementation of
`vllm.multimodal.utils.group_mm_kwargs_by_modality` to use.
"""
multimodal_cpu_fields: ClassVar[Set[str] | None] = None
"""
[DEPRECATED] A set indicating CPU-only multimodal fields.
"""
_processor_factory: ClassVar[_ProcessorFactories]
"""
Set internally by `MultiModalRegistry.register_processor`.
......@@ -277,35 +266,7 @@ def supports_multimodal(model: object) -> TypeIs[SupportsMultiModal]: ...
def supports_multimodal(
model: type[object] | object,
) -> TypeIs[type[SupportsMultiModal]] | TypeIs[SupportsMultiModal]:
res = getattr(model, "supports_multimodal", False)
if res:
# We can remove this starting from v0.14
merge_by_field_config = getattr(model, "merge_by_field_config", None)
if merge_by_field_config is False:
raise ValueError(
"`merge_by_field_config=False` is no longer effective, "
"please update your model to consider the new batching logic "
"in `group_mm_kwargs_by_modality` (refer to "
"https://github.com/vllm-project/vllm/issues/26149), "
"and then remove the override from your model."
)
if merge_by_field_config is True:
logger.warning_once(
"`merge_by_field_config=True` is redundant, "
"please remove the override from your model."
)
multimodal_cpu_fields = getattr(model, "multimodal_cpu_fields", None)
if multimodal_cpu_fields is not None:
raise ValueError(
"`multimodal_cpu_fields` is no longer effective, "
"please set `keep_on_cpu=True` in `MultiModalFieldConfig` "
"(refer to https://github.com/vllm-project/vllm/pull/30181), "
"and then remove the override from your model."
)
return res
return getattr(model, "supports_multimodal", False)
def supports_multimodal_raw_input_only(model: type[object] | object) -> bool:
......
vllm/multimodal/__init__.py
View file @ 09dc7c69
......@@ -6,7 +6,6 @@ from .inputs import (
ModalityData,
MultiModalDataBuiltins,
MultiModalDataDict,
MultiModalKwargs,
MultiModalKwargsItems,
MultiModalPlaceholderDict,
MultiModalUUIDDict,
......@@ -30,7 +29,6 @@ __all__ = [
"MultiModalDataBuiltins",
"MultiModalDataDict",
"MultiModalHasher",
"MultiModalKwargs",
"MultiModalKwargsItems",
"MultiModalPlaceholderDict",
"MultiModalUUIDDict",
......
vllm/multimodal/inputs.py
View file @ 09dc7c69
......@@ -20,7 +20,7 @@ from typing import (
)
import numpy as np
from typing_extensions import NotRequired, TypeVar, deprecated
from typing_extensions import NotRequired, TypeVar
from vllm.utils.collection_utils import full_groupby, is_list_of
from vllm.utils.import_utils import LazyLoader
......@@ -356,8 +356,8 @@ class MultiModalFeatureSpec:
@dataclass
class MultiModalFieldElem:
"""
Represents a keyword argument corresponding to a multi-modal item
in [`MultiModalKwargs`][vllm.multimodal.inputs.MultiModalKwargs].
Represents a keyword argument inside a
[`MultiModalKwargsItem`][vllm.multimodal.inputs.MultiModalKwargsItem].
"""
modality: str
......@@ -369,14 +369,14 @@ class MultiModalFieldElem:
key: str
"""
The key of this field in
[`MultiModalKwargs`][vllm.multimodal.inputs.MultiModalKwargs],
[`MultiModalKwargsItem`][vllm.multimodal.inputs.MultiModalKwargsItem],
i.e. the name of the keyword argument to be passed to the model.
"""
data: NestedTensors
"""
The tensor data of this field in
[`MultiModalKwargs`][vllm.multimodal.inputs.MultiModalKwargs],
[`MultiModalKwargsItem`][vllm.multimodal.inputs.MultiModalKwargsItem],
i.e. the value of the keyword argument to be passed to the model.
It may be set to `None` if it is determined that the item is cached
......@@ -410,9 +410,9 @@ class MultiModalFieldElem:
@dataclass(frozen=True, kw_only=True)
class BaseMultiModalField(ABC):
"""
Defines how to interpret tensor data belonging to a keyword argument in
[`MultiModalKwargs`][vllm.multimodal.inputs.MultiModalKwargs] for multiple
multi-modal items, and vice versa.
Defines how to interpret tensor data belonging to a keyword argument for
[`MultiModalKwargsItems`][vllm.multimodal.inputs.MultiModalKwargsItems],
and vice versa.
"""
keep_on_cpu: bool = False
......@@ -985,62 +985,6 @@ MultiModalKwargsOptionalItems: TypeAlias = (
)
@deprecated("`MultiModalKwargs` is deprecated and will be removed in v0.14.")
class MultiModalKwargs(UserDict[str, NestedTensors]):
"""
A dictionary that represents the keyword arguments to
[`torch.nn.Module.forward`][].
"""
@staticmethod
@deprecated(
"`MultiModalKwargs.from_hf_inputs` is deprecated and "
"will be removed in v0.14. "
"Please use `MultiModalKwargsItems.from_hf_inputs` and "
"access the tensor data using `.get_data()`."
)
def from_hf_inputs(
hf_inputs: "BatchFeature",
config_by_key: Mapping[str, MultiModalFieldConfig],
):
return MultiModalKwargsItems.from_hf_inputs(hf_inputs, config_by_key).get_data()
@staticmethod
@deprecated(
"`MultiModalKwargs.from_items` is deprecated and "
"will be removed in v0.14. "
"Please use `MultiModalKwargsItems.from_seq` and "
"access the tensor data using `.get_data()`."
)
def from_items(
items: Sequence[MultiModalKwargsItem],
*,
pin_memory: bool = False,
):
return MultiModalKwargsItems.from_seq(items).get_data(pin_memory=pin_memory)
def __getitem__(self, key: str):
if key not in self:
raise KeyError(
f"Keyword argument {key!r} not found. "
f"Available keys: {set(self.keys())}"
)
return super().__getitem__(key)
def __eq__(self, other: object) -> bool:
if not isinstance(other, self.__class__):
return False
for k in self:
if k not in other:
return False
if not nested_tensors_equal(self[k], other[k]):
return False
return True
MultiModalPlaceholderDict: TypeAlias = Mapping[str, Sequence[PlaceholderRange]]
"""
A dictionary containing placeholder ranges for each modality.
......
vllm/multimodal/utils.py
View file @ 09dc7c69
......@@ -4,7 +4,7 @@
import asyncio
import atexit
import mimetypes
from collections.abc import Generator, Set
from collections.abc import Generator
from concurrent.futures import ThreadPoolExecutor
from itertools import groupby
from pathlib import Path
......@@ -462,8 +462,6 @@ def group_mm_kwargs_by_modality(
*,
device: torch.types.Device = None,
pin_memory: bool = False,
merge_by_field_config: bool | None = None,
multimodal_cpu_fields: Set[str] | None = None,
) -> Generator[tuple[str, int, BatchedTensorInputs], None, None]:
"""Group consecutive `MultiModalKwargsItem`s from `mm_kwargs` with the same
modality together into the same `MultiModalKwargs` instance.
......@@ -476,17 +474,6 @@ def group_mm_kwargs_by_modality(
Yields:
A tuple `(modality, num_items, grouped_kwargs)`.
"""
if merge_by_field_config is not None:
logger.warning_once(
"The `merge_by_field_config` argument of `group_mm_kwargs_by_modality` "
"is deprecated and will be removed in v0.14."
)
if multimodal_cpu_fields is not None:
logger.warning_once(
"The `multimodal_cpu_fields` argument of `group_mm_kwargs_by_modality` "
"is deprecated and will be removed in v0.14."
)
from vllm.multimodal.inputs import MultiModalKwargsItems
for modality, items in groupby(mm_kwargs, key=lambda item: item.modality):
......
vllm/tokenizers/__init__.py
View file @ 09dc7c69
......@@ -7,7 +7,6 @@ from .registry import (
cached_get_tokenizer,
cached_tokenizer_from_config,
get_tokenizer,
init_tokenizer_from_config,
)
__all__ = [
......@@ -16,5 +15,4 @@ __all__ = [
"cached_get_tokenizer",
"get_tokenizer",
"cached_tokenizer_from_config",
"init_tokenizer_from_config",
]
vllm/tokenizers/registry.py
View file @ 09dc7c69
......@@ -7,7 +7,7 @@ from pathlib import Path
from typing import TYPE_CHECKING
import huggingface_hub
from typing_extensions import TypeVar, assert_never, deprecated
from typing_extensions import TypeVar, assert_never
import vllm.envs as envs
from vllm.logger import init_logger
......@@ -224,10 +224,3 @@ def cached_tokenizer_from_config(model_config: "ModelConfig", **kwargs):
trust_remote_code=model_config.trust_remote_code,
**kwargs,
)
@deprecated(
"Renamed to `cached_tokenizer_from_config`. The old name will be removed in v0.14."
)
def init_tokenizer_from_config(model_config: "ModelConfig"):
return cached_tokenizer_from_config(model_config)
vllm/transformers_utils/tokenizer.py
View file @ 09dc7c69
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import warnings
from typing import Any
from typing_extensions import deprecated
from vllm.logger import init_logger
from vllm.tokenizers import TokenizerLike
logger = init_logger(__name__)
def __getattr__(name: str):
if name == "AnyTokenizer":
warnings.warn(
"`vllm.transformers_utils.tokenizer.AnyTokenizer` has been moved to "
"`vllm.tokenizers.TokenizerLike`. "
"The old name will be removed in v0.14.",
DeprecationWarning,
stacklevel=2,
)
return TokenizerLike
# Keep until lm-eval is updated
if name == "get_tokenizer":
from vllm.tokenizers import get_tokenizer
warnings.warn(
"`vllm.transformers_utils.tokenizer.get_tokenizer` "
"has been moved to `vllm.tokenizers.get_tokenizer`. "
"The old name will be removed in v0.14.",
"The old name will be removed in a future version.",
DeprecationWarning,
stacklevel=2,
)
return get_tokenizer
if name == "cached_get_tokenizer":
from vllm.tokenizers import cached_get_tokenizer
warnings.warn(
"`vllm.transformers_utils.tokenizer.cached_get_tokenizer` "
"has been moved to `vllm.tokenizers.cached_get_tokenizer`. "
"The old name will be removed in v0.14.",
DeprecationWarning,
stacklevel=2,
)
return cached_get_tokenizer
if name == "cached_tokenizer_from_config":
from vllm.tokenizers import cached_tokenizer_from_config
warnings.warn(
"`vllm.transformers_utils.tokenizer.cached_tokenizer_from_config` "
"has been moved to `vllm.tokenizers.cached_tokenizer_from_config`. "
"The old name will be removed in v0.14.",
DeprecationWarning,
stacklevel=2,
)
return cached_tokenizer_from_config
if name == "init_tokenizer_from_configs":
from vllm.tokenizers import cached_tokenizer_from_config
warnings.warn(
"`vllm.transformers_utils.tokenizer.init_tokenizer_from_configs` "
"has been moved to `vllm.tokenizers.cached_tokenizer_from_config`. "
"The old name will be removed in v0.14.",
DeprecationWarning,
stacklevel=2,
)
return cached_tokenizer_from_config
raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
@deprecated("Will be removed in v0.14. Please use `tokenizer.decode()` instead.")
def decode_tokens(
tokenizer: TokenizerLike,
token_ids: list[int],
*,
skip_special_tokens: bool | None = None,
) -> str:
"""
Backend-agnostic equivalent of HF's
`tokenizer.decode(token_ids, ...)`.
`skip_special_tokens=None` means to use the backend's default
settings.
"""
kw_args: dict[str, Any] = {}
if skip_special_tokens is not None:
kw_args["skip_special_tokens"] = skip_special_tokens
return tokenizer.decode(token_ids, **kw_args)
@deprecated("Will be removed in v0.14. Please use `tokenizer.encode()` instead.")
def encode_tokens(
tokenizer: TokenizerLike,
text: str,
*,
truncation: bool | None = None,
max_length: int | None = None,
add_special_tokens: bool | None = None,
) -> list[int]:
"""
Backend-agnostic equivalent of HF's
`tokenizer.encode(text, ...)`.
`add_special_tokens=None` means to use the backend's default
settings.
"""
kw_args: dict[str, Any] = {}
if max_length is not None:
kw_args["max_length"] = max_length
if truncation is not None:
kw_args["truncation"] = truncation
if add_special_tokens is not None:
kw_args["add_special_tokens"] = add_special_tokens
return tokenizer.encode(text, **kw_args)
vllm/transformers_utils/tokenizer_base.py deleted 100644 → 0
View file @ 506eb0f4
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import warnings
def __getattr__(name: str):
if name == "TokenizerBase":
from vllm.tokenizers import TokenizerLike
warnings.warn(
"`vllm.transformers_utils.tokenizer_base.TokenizerBase` has been "
"moved to `vllm.tokenizers.TokenizerLike`. "
"The old name will be removed in v0.14.",
DeprecationWarning,
stacklevel=2,
)
return TokenizerLike
if name == "TokenizerRegistry":
from vllm.tokenizers import TokenizerRegistry
warnings.warn(
"`vllm.transformers_utils.tokenizer_base.TokenizerRegistry` has been "
"moved to `vllm.tokenizers.TokenizerRegistry`. "
"The old name will be removed in v0.14.",
DeprecationWarning,
stacklevel=2,
)
return TokenizerRegistry
raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
vllm/utils/__init__.py
View file @ 09dc7c69
......@@ -2,39 +2,9 @@
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import uuid
import warnings
from typing import Any
import torch
_DEPRECATED_MAPPINGS = {
"cprofile": "profiling",
"cprofile_context": "profiling",
# Used by lm-eval
"get_open_port": "network_utils",
}
def __getattr__(name: str) -> Any: # noqa: D401 - short deprecation docstring
"""Module-level getattr to handle deprecated utilities."""
if name in _DEPRECATED_MAPPINGS:
submodule_name = _DEPRECATED_MAPPINGS[name]
warnings.warn(
f"vllm.utils.{name} is deprecated and will be removed in a future version. "
f"Use vllm.utils.{submodule_name}.{name} instead.",
DeprecationWarning,
stacklevel=2,
)
module = __import__(f"vllm.utils.{submodule_name}", fromlist=[submodule_name])
return getattr(module, name)
raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
def __dir__() -> list[str]:
# expose deprecated names in dir() for better UX/tab-completion
return sorted(list(globals().keys()) + list(_DEPRECATED_MAPPINGS.keys()))
MASK_64_BITS = (1 << 64) - 1
......
vllm/v1/engine/async_llm.py
View file @ 09dc7c69
......@@ -11,7 +11,6 @@ from typing import Any, cast
import numpy as np
import torch
from typing_extensions import deprecated
import vllm.envs as envs
from vllm.config import VllmConfig
......@@ -190,14 +189,6 @@ class AsyncLLM(EngineClient):
else:
self.profiler = None
@property
@deprecated(
"`AsyncLLM.processor` has been renamed to `AsyncLLM.input_processor`. "
"The old name will be removed in v0.14."
)
def processor(self):
return self.input_processor
@classmethod
def from_vllm_config(
cls,
......
vllm/v1/engine/llm_engine.py
View file @ 09dc7c69
......@@ -7,7 +7,7 @@ from copy import copy
from typing import Any, cast
import torch.nn as nn
from typing_extensions import TypeVar, deprecated
from typing_extensions import TypeVar
import vllm.envs as envs
from vllm.config import ParallelConfig, VllmConfig
......@@ -136,14 +136,6 @@ class LLMEngine:
# Don't keep the dummy data in memory
self.reset_mm_cache()
@property
@deprecated(
"`LLMEngine.processor` has been renamed to `LLMEngine.input_processor`. "
"The old name will be removed in v0.14."
)
def processor(self):
return self.input_processor
@classmethod
def from_vllm_config(
cls,
......
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