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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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15
vllm/model_executor/models/bamba.py
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@@ -1,7 +1,8 @@
# SPDX-License-Identifier: Apache-2.0
"""Inference-only Bamba model."""
# Added by the IBM Team, 2024
from typing import Iterable, Optional, Set, Tuple
from collections.abc import Iterable
from typing import Optional
import torch
from torch import nn
@@ -355,8 +356,8 @@ class BambaModel(nn.Module):
hidden_states, _ = self.final_layernorm(hidden_states, residual)
return hidden_states
def load_weights(self, weights: Iterable[Tuple[str,
torch.Tensor]]) -> Set[str]:
def load_weights(self, weights: Iterable[tuple[str,
torch.Tensor]]) -> set[str]:
stacked_params_mapping = [
# (param_name, shard_name, shard_id)
("qkv_proj", "q_proj", "q"),
@@ -367,7 +368,7 @@ class BambaModel(nn.Module):
]
params_dict = dict(self.named_parameters())
loaded_params: Set[str] = set()
loaded_params: set[str] = set()
for name, loaded_weight in weights:
if "rotary_emb.inv_freq" in name:
continue
@@ -495,7 +496,7 @@ class BambaForCausalLM(nn.Module, HasInnerState, SupportsLoRA, SupportsPP,
return self.mamba_cache.get_seqlen_agnostic_capture_inputs(batch_size)
def _get_mamba_cache_shape(
self) -> Tuple[Tuple[int, int], Tuple[int, int]]:
self) -> tuple[tuple[int, int], tuple[int, int]]:
world_size = get_tensor_model_parallel_world_size()
hidden_size = self.config.hidden_size
@@ -535,7 +536,7 @@ class BambaForCausalLM(nn.Module, HasInnerState, SupportsLoRA, SupportsPP,
sampling_metadata)
return logits
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)
return loader.load_weights(weights)