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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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37
vllm/model_executor/models/nemotron_vl.py
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@@ -9,7 +9,6 @@
# --------------------------------------------------------
from abc import ABC
from collections.abc import Iterable
from typing import Optional
import torch
import torch.nn as nn
@@ -207,9 +206,9 @@ class NemotronVLProcessor(InternVLProcessor):
tokenizer: AnyTokenizer,
image_processor: BaseImageProcessorFast,
*,
min_dynamic_patch: Optional[int] = None,
max_dynamic_patch: Optional[int] = None,
dynamic_image_size: Optional[bool] = None,
min_dynamic_patch: int | None = None,
max_dynamic_patch: int | None = None,
dynamic_image_size: bool | None = None,
) -> None:
ABC.__init__(self)
self.config = config
@@ -266,9 +265,9 @@ class NemotronVLProcessor(InternVLProcessor):
def _images_to_pixel_values_lst(
self,
images: list[Image.Image],
min_dynamic_patch: Optional[int] = None,
max_dynamic_patch: Optional[int] = None,
dynamic_image_size: Optional[bool] = None,
min_dynamic_patch: int | None = None,
max_dynamic_patch: int | None = None,
dynamic_image_size: bool | None = None,
) -> list[torch.Tensor]:
min_num, max_num = self.resolve_min_max_num(
min_dynamic_patch=min_dynamic_patch,
@@ -292,9 +291,9 @@ class NemotronVLProcessor(InternVLProcessor):
self,
text: list[str],
images: list[Image.Image],
min_dynamic_patch: Optional[int] = None,
max_dynamic_patch: Optional[int] = None,
dynamic_image_size: Optional[bool] = None,
min_dynamic_patch: int | None = None,
max_dynamic_patch: int | None = None,
dynamic_image_size: bool | None = None,
) -> tuple[list[str], dict[str, torch.Tensor]]:
if len(images) == 0:
image_inputs = {}
@@ -326,7 +325,7 @@ class NemotronVLProcessor(InternVLProcessor):
def get_image_repl(
self,
feature_size: int,
num_patches: Optional[int],
num_patches: int | None,
) -> PromptUpdateDetails[str]:
repl_features = IMG_CONTEXT * feature_size
repl_full = IMG_START + repl_features + IMG_END
@@ -362,7 +361,7 @@ class LlamaNemotronVLChatModel(nn.Module, SupportsMultiModal, SupportsPP, Suppor
merge_by_field_config = True
@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 "<image>"
@@ -426,7 +425,7 @@ class LlamaNemotronVLChatModel(nn.Module, SupportsMultiModal, SupportsPP, Suppor
def _init_vision_model(
self,
config: PretrainedConfig,
quant_config: Optional[QuantizationConfig],
quant_config: QuantizationConfig | None,
*,
prefix: str,
):
@@ -482,7 +481,7 @@ class LlamaNemotronVLChatModel(nn.Module, SupportsMultiModal, SupportsPP, Suppor
def _parse_and_validate_image_input(
self, **kwargs: object
) -> Optional[InternVLImageInputs]:
) -> InternVLImageInputs | None:
pixel_values_flat = kwargs.pop("pixel_values_flat", None)
image_num_patches = kwargs.pop("image_num_patches", None)
image_embeds = kwargs.pop("image_embeds", None)
@@ -581,9 +580,9 @@ class LlamaNemotronVLChatModel(nn.Module, SupportsMultiModal, SupportsPP, Suppor
def get_input_embeddings(
self,
input_ids: torch.Tensor,
multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
multimodal_embeddings: MultiModalEmbeddings | None = None,
*,
is_multimodal: Optional[torch.Tensor] = None,
is_multimodal: torch.Tensor | None = None,
handle_oov_mm_token: bool = False,
) -> torch.Tensor:
if multimodal_embeddings is not None and len(multimodal_embeddings) > 0:
@@ -604,8 +603,8 @@ class LlamaNemotronVLChatModel(nn.Module, SupportsMultiModal, SupportsPP, Suppor
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,
) -> IntermediateTensors:
if intermediate_tensors is not None:
@@ -630,7 +629,7 @@ class LlamaNemotronVLChatModel(nn.Module, SupportsMultiModal, SupportsPP, Suppor
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]: