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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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14
vllm/model_executor/models/phi3v.py
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@@ -16,7 +16,7 @@
# limitations under the License.
import re
from collections.abc import Iterable, Mapping, Sequence
from typing import Any, List, Literal, Optional, Set, Tuple, TypedDict, Union
from typing import Any, Literal, Optional, TypedDict, Union
import torch
import torch.nn as nn
@@ -94,7 +94,7 @@ def _init_img_processor(hf_config: PretrainedConfig,
class Phi3VImagePixelInputs(TypedDict):
type: Literal["pixel_values"]
data: Union[torch.Tensor, List[torch.Tensor]]
data: Union[torch.Tensor, list[torch.Tensor]]
"""
Shape:
`(batch_size * num_images, 1 + num_patches, num_channels, height, width)`
@@ -113,7 +113,7 @@ class Phi3VImagePixelInputs(TypedDict):
class Phi3VImageEmbeddingInputs(TypedDict):
type: Literal["image_embeds"]
data: Union[torch.Tensor, List[torch.Tensor]]
data: Union[torch.Tensor, list[torch.Tensor]]
"""Shape: `(batch_size * num_images, image_feature_size, hidden_size)`
`hidden_size` must match the hidden size of language model backbone.
@@ -571,8 +571,8 @@ class Phi3VForCausalLM(nn.Module, SupportsMultiModal, SupportsPP,
return data
def _validate_pixel_values(
self, data: Union[torch.Tensor, List[torch.Tensor]]
) -> Union[torch.Tensor, List[torch.Tensor]]:
self, data: Union[torch.Tensor, list[torch.Tensor]]
) -> Union[torch.Tensor, list[torch.Tensor]]:
h = w = CLIP_VIT_LARGE_PATCH14_336_CONFIG.image_size
expected_dims = (3, h, w)
@@ -707,8 +707,8 @@ class Phi3VForCausalLM(nn.Module, SupportsMultiModal, SupportsPP,
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)
autoloaded_weights = loader.load_weights(weights,