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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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33
vllm/model_executor/models/phimoe.py
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@@ -26,7 +26,6 @@
from collections.abc import Iterable
from itertools import islice
from typing import Optional, Union
import torch
from torch import nn
@@ -257,9 +256,9 @@ class PhiMoE(nn.Module):
top_k: int,
hidden_size: int,
intermediate_size: int,
params_dtype: Optional[torch.dtype] = None,
quant_config: Optional[QuantizationConfig] = None,
tp_size: Optional[int] = None,
params_dtype: torch.dtype | None = None,
quant_config: QuantizationConfig | None = None,
tp_size: int | None = None,
prefix: str = "",
):
super().__init__()
@@ -304,12 +303,12 @@ class PhiMoEAttention(nn.Module):
hidden_size: int,
num_heads: int,
num_kv_heads: int,
head_dim: Optional[int] = None,
head_dim: int | None = None,
max_position: int = 4096 * 32,
rope_theta: float = 10000,
cache_config: Optional[CacheConfig] = None,
quant_config: Optional[QuantizationConfig] = None,
rope_scaling: Optional[dict] = None,
cache_config: CacheConfig | None = None,
quant_config: QuantizationConfig | None = None,
rope_scaling: dict | None = None,
prefix: str = "",
) -> None:
super().__init__()
@@ -386,8 +385,8 @@ class PhiMoEDecoderLayer(nn.Module):
def __init__(
self,
config: PhiMoEConfig,
cache_config: Optional[CacheConfig] = None,
quant_config: Optional[QuantizationConfig] = None,
cache_config: CacheConfig | None = None,
quant_config: QuantizationConfig | None = None,
prefix: str = "",
) -> None:
super().__init__()
@@ -427,7 +426,7 @@ class PhiMoEDecoderLayer(nn.Module):
self,
positions: torch.Tensor,
hidden_states: torch.Tensor,
residual: Optional[torch.Tensor],
residual: torch.Tensor | None,
) -> torch.Tensor:
residual = hidden_states
@@ -496,9 +495,9 @@ class PhiMoEModel(nn.Module):
self,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: Optional[IntermediateTensors],
inputs_embeds: Optional[torch.Tensor] = None,
) -> Union[torch.Tensor, IntermediateTensors]:
intermediate_tensors: IntermediateTensors | None,
inputs_embeds: torch.Tensor | None = None,
) -> torch.Tensor | IntermediateTensors:
if get_pp_group().is_first_rank:
if inputs_embeds is not None:
hidden_states = inputs_embeds
@@ -674,9 +673,9 @@ class PhiMoEForCausalLM(nn.Module, SupportsLoRA, SupportsPP):
self,
input_ids: torch.Tensor,
positions: torch.Tensor,
intermediate_tensors: Optional[IntermediateTensors] = None,
inputs_embeds: Optional[torch.Tensor] = None,
) -> Union[torch.Tensor, IntermediateTensors]:
intermediate_tensors: IntermediateTensors | None = None,
inputs_embeds: torch.Tensor | None = None,
) -> torch.Tensor | IntermediateTensors:
hidden_states = self.model(
input_ids, positions, intermediate_tensors, inputs_embeds
)