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[CI Failure] Fix NomicBert max_model_len validation (#31662)

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Signed-off-by: wang.yuqi <yuqi.wang@daocloud.io>
This commit is contained in:
wang.yuqi
2026-01-05 11:06:52 +08:00
committed by GitHub
parent 43e3f8e4a9
commit 8be6432bda
2 changed files with 33 additions and 26 deletions
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53
vllm/model_executor/models/config.py
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@@ -113,8 +113,8 @@ class LlamaBidirectionalConfig(VerifyAndUpdateConfig):
class NomicBertModelConfig(VerifyAndUpdateConfig):
@staticmethod
def verify_and_update_config(vllm_config: "VllmConfig") -> None:
config = vllm_config.model_config.hf_config
def verify_and_update_model_config(model_config: "ModelConfig") -> None:
config = model_config.hf_config
assert config.__class__.__name__ == "NomicBertConfig"
assert config.activation_function in ["swiglu", "gelu"]
@@ -137,6 +137,10 @@ class NomicBertModelConfig(VerifyAndUpdateConfig):
config.intermediate_size = config.n_inner
config.hidden_size = config.n_embd
config.num_hidden_layers = config.n_layer
model_config.model_arch_config.hidden_size = config.hidden_size
model_config.model_arch_config.total_num_hidden_layers = (
config.num_hidden_layers
)
head_dim = config.hidden_size // config.num_attention_heads
max_trained_positions = getattr(config, "max_trained_positions", 2048)
@@ -153,42 +157,43 @@ class NomicBertModelConfig(VerifyAndUpdateConfig):
# The context extension uses vllm style rope_theta and rope_parameters.
# See #17785 #18755
if (
not vllm_config.model_config.hf_overrides
and vllm_config.model_config.original_max_model_len is None
not model_config.hf_overrides
and model_config.original_max_model_len is None
):
# Default
# Reset max_model_len to max_trained_positions.
# nomic-embed-text-v2-moe the length is set to 512
# by sentence_bert_config.json.
max_model_len_before = vllm_config.model_config.max_model_len
max_model_len = min(
vllm_config.model_config.max_model_len, max_trained_positions
max_model_len_before = model_config.max_model_len
max_model_len = min(model_config.max_model_len, max_trained_positions)
model_config.max_model_len = model_config.get_and_verify_max_len(
max_model_len
)
vllm_config.recalculate_max_model_len(max_model_len)
logger.warning(
"Nomic context extension is disabled. "
"Changing max_model_len from %s to %s. "
"To enable context extension, see: "
"https://github.com/vllm-project/vllm/tree/main/examples/offline_inference/context_extension.html",
max_model_len_before,
vllm_config.model_config.max_model_len,
)
if model_config.max_model_len != max_model_len_before:
logger.warning(
"Nomic context extension is disabled. "
"Changing max_model_len from %s to %s. "
"To enable context extension, see: "
"https://github.com/vllm-project/vllm/tree/main/examples/offline_inference/context_extension.html",
max_model_len_before,
model_config.max_model_len,
)
else:
# We need to re-verify max_model_len to avoid lengths
# greater than position_embedding.
model_config = vllm_config.model_config
hf_text_config = model_config.hf_text_config
if isinstance(model_config.hf_overrides, dict):
# hf_overrides_kw
max_model_len = model_config.hf_overrides.get(
"max_model_len", vllm_config.model_config.max_model_len
"max_model_len", model_config.max_model_len
)
else:
# hf_overrides_fn
# This might be overridden by sentence_bert_config.json.
max_model_len = vllm_config.model_config.max_model_len
max_model_len = model_config.max_model_len
# reset hf_text_config for recalculate_max_model_len.
if hasattr(hf_text_config, "max_model_len"):
@@ -196,13 +201,21 @@ class NomicBertModelConfig(VerifyAndUpdateConfig):
hf_text_config.max_position_embeddings = max_trained_positions
hf_text_config.rope_parameters = config.rotary_kwargs["rope_parameters"]
# Update the cached derived_max_model_len to enforce the limit
model_config.model_arch_config.derived_max_model_len_and_key = (
float(max_trained_positions),
"max_position_embeddings",
)
# The priority of sentence_bert_config.json is higher
# than max_position_embeddings
encoder_config = deepcopy(model_config.encoder_config)
encoder_config.pop("max_seq_length", None)
model_config.encoder_config = encoder_config
vllm_config.recalculate_max_model_len(max_model_len)
model_config.max_model_len = model_config.get_and_verify_max_len(
max_model_len
)
class Qwen2ForProcessRewardModelConfig(VerifyAndUpdateConfig):