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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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35
vllm/model_executor/models/siglip.py
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@@ -5,7 +5,6 @@ within a vision language model."""
import math
from collections.abc import Iterable
from typing import Optional, Union
import torch
from torch import nn
@@ -153,7 +152,7 @@ class SiglipAttention(nn.Module):
def __init__(
self,
config: SiglipVisionConfig,
quant_config: Optional[QuantizationConfig] = None,
quant_config: QuantizationConfig | None = None,
prefix: str = "",
) -> None:
super().__init__()
@@ -211,7 +210,7 @@ class SiglipMLP(nn.Module):
def __init__(
self,
config: SiglipVisionConfig,
quant_config: Optional[QuantizationConfig] = None,
quant_config: QuantizationConfig | None = None,
prefix: str = "",
) -> None:
super().__init__()
@@ -251,7 +250,7 @@ class SiglipEncoderLayer(nn.Module):
def __init__(
self,
config: SiglipVisionConfig,
quant_config: Optional[QuantizationConfig] = None,
quant_config: QuantizationConfig | None = None,
prefix: str = "",
) -> None:
super().__init__()
@@ -293,8 +292,8 @@ class SiglipEncoder(nn.Module):
def __init__(
self,
config: SiglipVisionConfig,
quant_config: Optional[QuantizationConfig] = None,
num_hidden_layers_override: Optional[int] = None,
quant_config: QuantizationConfig | None = None,
num_hidden_layers_override: int | None = None,
prefix: str = "",
) -> None:
super().__init__()
@@ -321,7 +320,7 @@ class SiglipEncoder(nn.Module):
self,
inputs_embeds: torch.Tensor,
return_all_hidden_states: bool,
) -> Union[torch.Tensor, list[torch.Tensor]]:
) -> torch.Tensor | list[torch.Tensor]:
hidden_states_pool = [inputs_embeds]
hidden_states = inputs_embeds
@@ -342,7 +341,7 @@ class SiglipMultiheadAttentionPoolingHead(nn.Module):
def __init__(
self,
config: SiglipVisionConfig,
quant_config: Optional[QuantizationConfig] = None,
quant_config: QuantizationConfig | None = None,
prefix: str = "",
) -> None:
super().__init__()
@@ -375,10 +374,10 @@ class SiglipVisionTransformer(nn.Module):
def __init__(
self,
config: SiglipVisionConfig,
quant_config: Optional[QuantizationConfig] = None,
quant_config: QuantizationConfig | None = None,
*,
num_hidden_layers_override: Optional[int] = None,
require_post_norm: Optional[bool] = None,
num_hidden_layers_override: int | None = None,
require_post_norm: bool | None = None,
prefix: str = "",
) -> None:
super().__init__()
@@ -426,8 +425,8 @@ class SiglipVisionTransformer(nn.Module):
pixel_values: torch.Tensor,
*,
interpolate_pos_encoding: bool = False,
select_layers: Optional[list[int]] = None,
feature_select_strategy: Optional[VisionFeatureSelectStrategy] = None,
select_layers: list[int] | None = None,
feature_select_strategy: VisionFeatureSelectStrategy | None = None,
) -> torch.Tensor:
hidden_states = self.embeddings(
pixel_values,
@@ -464,10 +463,10 @@ class SiglipVisionModel(nn.Module):
def __init__(
self,
config: SiglipVisionConfig,
quant_config: Optional[QuantizationConfig] = None,
quant_config: QuantizationConfig | None = None,
*,
num_hidden_layers_override: Optional[int] = None,
require_post_norm: Optional[bool] = None,
num_hidden_layers_override: int | None = None,
require_post_norm: bool | None = None,
prefix: str = "",
) -> None:
super().__init__()
@@ -491,8 +490,8 @@ class SiglipVisionModel(nn.Module):
self,
pixel_values: torch.Tensor,
interpolate_pos_encoding: bool = False,
select_layers: Optional[list[int]] = None,
feature_select_strategy: Optional[VisionFeatureSelectStrategy] = None,
select_layers: list[int] | None = None,
feature_select_strategy: VisionFeatureSelectStrategy | None = None,
) -> torch.Tensor:
return self.vision_model(
pixel_values=pixel_values,