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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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27
vllm/model_executor/models/olmo.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
@@ -72,8 +71,8 @@ class OlmoAttention(nn.Module):
def __init__(
self,
config: OlmoConfig,
cache_config: Optional[CacheConfig] = None,
quant_config: Optional[QuantizationConfig] = None,
cache_config: CacheConfig | None = None,
quant_config: QuantizationConfig | None = None,
prefix: str = "",
):
super().__init__()
@@ -152,7 +151,7 @@ class OlmoMLP(nn.Module):
def __init__(
self,
config: OlmoConfig,
quant_config: Optional[QuantizationConfig] = None,
quant_config: QuantizationConfig | None = None,
prefix: str = "",
):
super().__init__()
@@ -201,8 +200,8 @@ class OlmoDecoderLayer(nn.Module):
def __init__(
self,
config: OlmoConfig,
cache_config: Optional[CacheConfig] = None,
quant_config: Optional[QuantizationConfig] = None,
cache_config: CacheConfig | None = None,
quant_config: QuantizationConfig | None = None,
prefix: str = "",
):
super().__init__()
@@ -226,7 +225,7 @@ class OlmoDecoderLayer(nn.Module):
self,
positions: torch.Tensor,
hidden_states: torch.Tensor,
) -> tuple[torch.Tensor, Optional[tuple[torch.Tensor, torch.Tensor]]]:
) -> tuple[torch.Tensor, tuple[torch.Tensor, torch.Tensor] | None]:
# Attention block.
residual = hidden_states
hidden_states = self.input_layernorm(hidden_states)
@@ -276,9 +275,9 @@ class OlmoModel(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:
"""
:param input_ids: A tensor of shape `(batch_size, seq_len)`.
"""
@@ -389,9 +388,9 @@ class OlmoForCausalLM(nn.Module, SupportsPP, SupportsLoRA):
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=input_ids,
positions=positions,
@@ -403,7 +402,7 @@ class OlmoForCausalLM(nn.Module, SupportsPP, SupportsLoRA):
def compute_logits(
self,
hidden_states: torch.Tensor,
) -> Optional[torch.Tensor]:
) -> torch.Tensor | None:
logits = self.logits_processor(self.lm_head, hidden_states)
return logits