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Convert formatting to use ruff instead of yapf + isort (#26247)

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Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
Harry Mellor
2025-10-05 15:06:22 +01:00
committed by GitHub
parent 17edd8a807
commit d6953beb91
1508 changed files with 115244 additions and 94146 deletions
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37
vllm/transformers_utils/configs/nemotron.py
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@@ -62,7 +62,7 @@ class NemotronConfig(PretrainedConfig):
(MQA) otherwise GQA is used. When converting a multi-head
checkpoint to a GQA checkpoint, each group key and value
head should be constructed by meanpooling all the original
heads within that group. For more details checkout
heads within that group. For more details checkout
[this paper](https://arxiv.org/pdf/2305.13245.pdf). If it
is not specified, will default to `num_attention_heads`.
hidden_act (`str` or `function`, *optional*, defaults to `"relu2"`):
@@ -147,8 +147,9 @@ class NemotronConfig(PretrainedConfig):
self.num_hidden_layers = num_hidden_layers
self.num_attention_heads = num_attention_heads
head_dim = head_dim or kwargs.get("kv_channels")
self.head_dim = head_dim if head_dim is not None else (
hidden_size // num_attention_heads)
self.head_dim = (
head_dim if head_dim is not None else (hidden_size // num_attention_heads)
)
# for backward compatibility
if num_key_value_heads is None:
@@ -162,8 +163,11 @@ class NemotronConfig(PretrainedConfig):
self.rope_theta = rope_theta
self.rope_scaling = rope_scaling
# for backward compatibility
partial_rotary_factor = kwargs.get("rope_percent") or kwargs.get(
"rope_percentage") or partial_rotary_factor
partial_rotary_factor = (
kwargs.get("rope_percent")
or kwargs.get("rope_percentage")
or partial_rotary_factor
)
self.partial_rotary_factor = partial_rotary_factor
self._rope_scaling_validation()
self.attention_bias = attention_bias
@@ -185,21 +189,24 @@ class NemotronConfig(PretrainedConfig):
if self.rope_scaling is None:
return
if not isinstance(self.rope_scaling, dict) or len(
self.rope_scaling) != 2:
if not isinstance(self.rope_scaling, dict) or len(self.rope_scaling) != 2:
raise ValueError(
"`rope_scaling` must be a dictionary with two fields, "
f"`type` and `factor`, got {self.rope_scaling}")
f"`type` and `factor`, got {self.rope_scaling}"
)
rope_scaling_type = self.rope_scaling.get("type", None)
rope_scaling_factor = self.rope_scaling.get("factor", None)
if rope_scaling_type is None or rope_scaling_type not in [
"linear", "dynamic"
]:
if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
raise ValueError(
"`rope_scaling`'s type field must be one of ['linear', "
f"'dynamic'], got {rope_scaling_type}")
if rope_scaling_factor is None or not isinstance(
rope_scaling_factor, float) or rope_scaling_factor <= 1.0:
f"'dynamic'], got {rope_scaling_type}"
)
if (
rope_scaling_factor is None
or not isinstance(rope_scaling_factor, float)
or rope_scaling_factor <= 1.0
):
raise ValueError(
"`rope_scaling`'s factor field must be a float > 1, got "
f"{rope_scaling_factor}")
f"{rope_scaling_factor}"
)