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Update deprecated type hinting in models (#18132)

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Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
Harry Mellor
2025-05-15 06:06:50 +01:00
committed by GitHub
parent 83f74c698f
commit 26d0419309
130 changed files with 971 additions and 901 deletions
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20
vllm/model_executor/models/qwen2_5_omni_thinker.py
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@@ -21,10 +21,10 @@
# limitations under the License.
"""Inference-only Qwen2.5-Omni model (thinker part)."""
from collections.abc import Iterable, Mapping, Sequence
from copy import copy
from functools import partial
from typing import (Any, Dict, Iterable, List, Mapping, Optional, Sequence,
Set, Tuple, Union)
from typing import Any, Optional, Union
import torch
import torch.nn as nn
@@ -138,7 +138,7 @@ class Qwen2_5OmniThinkerProcessingInfo(Qwen2AudioProcessingInfo,
min_pixels: Optional[int] = None,
max_pixels: Optional[int] = None,
size: Optional[dict[str, int]] = None,
fps: Optional[Union[float, List[float]]] = None,
fps: Optional[Union[float, list[float]]] = None,
**kwargs: object,
) -> Qwen2_5OmniProcessor:
if fps is not None:
@@ -550,7 +550,7 @@ class Qwen2_5OmniConditionalGenerationMixin:
def _parse_and_validate_image_input(
self,
**kwargs: Dict[str, Any],
**kwargs: dict[str, Any],
) -> Optional[Qwen2_5_VLImageInputs]:
pixel_values = kwargs.pop("pixel_values", None)
image_embeds = kwargs.pop("image_embeds", None)
@@ -589,7 +589,7 @@ class Qwen2_5OmniConditionalGenerationMixin:
def _parse_and_validate_video_input(
self,
**kwargs: Dict[str, Any],
**kwargs: dict[str, Any],
) -> Optional[Qwen2_5_VLVideoInputs]:
pixel_values_videos = kwargs.pop("pixel_values_videos", None)
video_embeds = kwargs.pop("video_embeds", None)
@@ -627,7 +627,7 @@ class Qwen2_5OmniConditionalGenerationMixin:
def _process_audio_input(
self,
audio_input: Qwen2AudioInputs,
audio_hashes: List[str] = None,
audio_hashes: list[str] = None,
cached_audio_features: torch.Tensor = None,
) -> torch.Tensor:
@@ -676,7 +676,7 @@ class Qwen2_5OmniConditionalGenerationMixin:
def _process_video_input(
self,
video_input: Qwen2_5_VLVideoInputs,
video_hashes: List[str] = None,
video_hashes: list[str] = None,
cached_video_embeds: torch.Tensor = None) -> torch.Tensor:
if video_input["type"] == "video_embeds":
return video_input["video_embeds"].type(self.visual.dtype)
@@ -825,7 +825,7 @@ class Qwen2_5OmniThinkerForConditionalGeneration(
if audio_input is None and image_input is None and video_input is None:
return None
multimodal_embeddings: List[Tuple[NestedTensors, str]] = []
multimodal_embeddings: list[tuple[NestedTensors, str]] = []
if audio_input is not None:
audio_embeds = self._process_audio_input(audio_input)
@@ -891,8 +891,8 @@ class Qwen2_5OmniThinkerForConditionalGeneration(
return self.language_model.compute_logits(hidden_states,
sampling_metadata)
def load_weights(self, weights: Iterable[Tuple[str,
torch.Tensor]]) -> Set[str]:
def load_weights(self, weights: Iterable[tuple[str,
torch.Tensor]]) -> set[str]:
loader = AutoWeightsLoader(
self,
skip_prefixes=["talker.", "token2wav."],