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Update Optional[x] -> x | None and Union[x, y] to x | y (#26633)

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Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
Harry Mellor
2025-10-12 17:51:31 +01:00
committed by GitHub
parent 9bb38130cb
commit 8fcaaf6a16
944 changed files with 9490 additions and 10121 deletions
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64
vllm/model_executor/models/qwen2_5_vl.py
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@@ -26,9 +26,9 @@
# limitations under the License.
"""Inference-only Qwen2.5-VL model compatible with HuggingFace weights."""
from collections.abc import Iterable, Mapping, Sequence
from collections.abc import Callable, Iterable, Mapping, Sequence
from functools import lru_cache, partial
from typing import Annotated, Any, Callable, Literal, Optional, Union
from typing import Annotated, Any, Literal, TypeAlias
import torch
import torch.nn as nn
@@ -161,9 +161,9 @@ class Qwen2_5_VLImageEmbeddingInputs(TensorSchema):
]
Qwen2_5_VLImageInputs = Union[
Qwen2_5_VLImagePixelInputs, Qwen2_5_VLImageEmbeddingInputs
]
Qwen2_5_VLImageInputs: TypeAlias = (
Qwen2_5_VLImagePixelInputs | Qwen2_5_VLImageEmbeddingInputs
)
class Qwen2_5_VLVideoPixelInputs(TensorSchema):
@@ -197,7 +197,7 @@ class Qwen2_5_VLVideoPixelInputs(TensorSchema):
]
second_per_grid_ts: Annotated[
Optional[torch.Tensor],
torch.Tensor | None,
TensorShape("nv"),
]
@@ -231,9 +231,9 @@ class Qwen2_5_VLVideoEmbeddingInputs(TensorSchema):
]
Qwen2_5_VLVideoInputs = Union[
Qwen2_5_VLVideoPixelInputs, Qwen2_5_VLVideoEmbeddingInputs
]
Qwen2_5_VLVideoInputs: TypeAlias = (
Qwen2_5_VLVideoPixelInputs | Qwen2_5_VLVideoEmbeddingInputs
)
# === Vision Encoder === #
@@ -245,7 +245,7 @@ class Qwen2_5_VisionMLP(nn.Module):
hidden_features: int,
bias: bool = False,
act_fn: Callable[[torch.Tensor], torch.Tensor] = F.silu,
quant_config: Optional[QuantizationConfig] = None,
quant_config: QuantizationConfig | None = None,
prefix: str = "",
use_data_parallel: bool = False,
):
@@ -301,7 +301,7 @@ class Qwen2_5_VisionAttention(nn.Module):
embed_dim: int,
num_heads: int,
projection_size: int,
quant_config: Optional[QuantizationConfig] = None,
quant_config: QuantizationConfig | None = None,
prefix: str = "",
use_data_parallel: bool = False,
attn_backend: _Backend = _Backend.TORCH_SDPA,
@@ -386,8 +386,8 @@ class Qwen2_5_VisionAttention(nn.Module):
x: torch.Tensor,
cu_seqlens: torch.Tensor,
rotary_pos_emb: torch.Tensor,
max_seqlen: Optional[int] = None, # Only used for Flash Attention
seqlens: Optional[list[int]] = None, # Only used for xFormers
max_seqlen: int | None = None, # Only used for Flash Attention
seqlens: list[int] | None = None, # Only used for xFormers
) -> torch.Tensor:
# [s, b, c] --> [s, b, head * 3 * head_dim]
x, _ = self.qkv(x)
@@ -466,8 +466,8 @@ class Qwen2_5_VisionBlock(nn.Module):
num_heads: int,
mlp_hidden_dim: int,
act_fn: Callable[[torch.Tensor], torch.Tensor] = F.silu,
norm_layer: Optional[Callable[[int], nn.Module]] = None,
quant_config: Optional[QuantizationConfig] = None,
norm_layer: Callable[[int], nn.Module] | None = None,
quant_config: QuantizationConfig | None = None,
prefix: str = "",
use_data_parallel: bool = False,
attn_backend: _Backend = _Backend.TORCH_SDPA,
@@ -503,8 +503,8 @@ class Qwen2_5_VisionBlock(nn.Module):
x: torch.Tensor,
cu_seqlens: torch.Tensor,
rotary_pos_emb: torch.Tensor,
max_seqlen: Optional[int] = None, # Only used for Flash Attention
seqlens: Optional[list[int]] = None, # Only used for xFormers
max_seqlen: int | None = None, # Only used for Flash Attention
seqlens: list[int] | None = None, # Only used for xFormers
) -> torch.Tensor:
x_attn = self.attn(
self.norm1(x),
@@ -552,9 +552,9 @@ class Qwen2_5_VisionPatchMerger(nn.Module):
self,
d_model: int,
context_dim: int,
norm_layer: Optional[Callable[[int], nn.Module]] = None,
norm_layer: Callable[[int], nn.Module] | None = None,
spatial_merge_size: int = 2,
quant_config: Optional[QuantizationConfig] = None,
quant_config: QuantizationConfig | None = None,
prefix: str = "",
use_data_parallel: bool = False,
) -> None:
@@ -634,7 +634,7 @@ class Qwen2_5_VisionTransformer(nn.Module):
self,
vision_config: Qwen2_5_VLVisionConfig,
norm_eps: float = 1e-6,
quant_config: Optional[QuantizationConfig] = None,
quant_config: QuantizationConfig | None = None,
prefix: str = "",
use_data_parallel: bool = False,
) -> None:
@@ -815,7 +815,7 @@ class Qwen2_5_VisionTransformer(nn.Module):
def compute_attn_mask_seqlen(
self,
cu_seqlens: torch.Tensor,
) -> tuple[Optional[int], Optional[list[int]]]:
) -> tuple[int | None, list[int] | None]:
max_seqlen, seqlens = None, None
if (
self.attn_backend == _Backend.FLASH_ATTN
@@ -1080,12 +1080,12 @@ class Qwen2_5_VLForConditionalGeneration(
cls,
input_tokens: list[int],
hf_config: PretrainedConfig,
image_grid_thw: Union[list[list[int]], torch.Tensor],
video_grid_thw: Union[list[list[int]], torch.Tensor],
image_grid_thw: list[list[int]] | torch.Tensor,
video_grid_thw: list[list[int]] | torch.Tensor,
second_per_grid_ts: list[float],
context_len: int = 0,
seq_len: Optional[int] = None,
audio_feature_lengths: Optional[torch.Tensor] = None,
seq_len: int | None = None,
audio_feature_lengths: torch.Tensor | None = None,
use_audio_in_video: bool = False,
) -> tuple[torch.Tensor, int]:
"""Get mrope input positions and delta value."""
@@ -1202,7 +1202,7 @@ class Qwen2_5_VLForConditionalGeneration(
return llm_positions, mrope_position_delta
@classmethod
def get_placeholder_str(cls, modality: str, i: int) -> Optional[str]:
def get_placeholder_str(cls, modality: str, i: int) -> str | None:
if modality.startswith("image"):
return "<|vision_start|><|image_pad|><|vision_end|>"
if modality.startswith("video"):
@@ -1273,7 +1273,7 @@ class Qwen2_5_VLForConditionalGeneration(
def _parse_and_validate_image_input(
self, **kwargs: object
) -> Optional[Qwen2_5_VLImageInputs]:
) -> Qwen2_5_VLImageInputs | None:
pixel_values = kwargs.pop("pixel_values", None)
image_embeds = kwargs.pop("image_embeds", None)
image_grid_thw = kwargs.pop("image_grid_thw", None)
@@ -1311,7 +1311,7 @@ class Qwen2_5_VLForConditionalGeneration(
def _parse_and_validate_video_input(
self, **kwargs: object
) -> Optional[Qwen2_5_VLVideoInputs]:
) -> Qwen2_5_VLVideoInputs | None:
pixel_values_videos = kwargs.pop("pixel_values_videos", None)
video_embeds = kwargs.pop("video_embeds", None)
video_grid_thw = kwargs.pop("video_grid_thw", None)
@@ -1605,10 +1605,10 @@ class Qwen2_5_VLForConditionalGeneration(
self,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: Optional[IntermediateTensors] = None,
inputs_embeds: Optional[torch.Tensor] = None,
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
**kwargs: object,
) -> Union[torch.Tensor, IntermediateTensors]:
) -> torch.Tensor | IntermediateTensors:
"""Run forward pass for Qwen2.5-VL.
Args:
@@ -1634,7 +1634,7 @@ class Qwen2_5_VLForConditionalGeneration(
def compute_logits(
self,
hidden_states: torch.Tensor,
) -> Optional[torch.Tensor]:
) -> torch.Tensor | None:
return self.language_model.compute_logits(hidden_states)
def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]: