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[Misc] Delete LoRA-related redundancy code #17841

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Merged
merged 1 commit into from
May 8, 2025
Merged

[Misc] Delete LoRA-related redundancy code #17841

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2 changes: 1 addition & 1 deletion vllm/lora/models.py
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Expand Up @@ -344,7 +344,7 @@ def __init__(

self.supported_lora_modules = get_supported_lora_modules(self.model)
assert self.supported_lora_modules, "No supported LoRA modules found in"
f"{self.model.__class__.__name__}."
f" {self.model.__class__.__name__}."
if lora_config.long_lora_scaling_factors:
# We need to replace rotary emb layer to do batch computation
# for long lora.
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4 changes: 1 addition & 3 deletions vllm/model_executor/models/grok1.py
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Expand Up @@ -504,9 +504,7 @@ def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):
self.unpadded_vocab_size,
config.hidden_size,
org_num_embeddings=config.vocab_size,
padding_size=DEFAULT_VOCAB_PADDING_SIZE
# We need bigger padding if using lora for kernel compatibility
if not lora_config else lora_config.lora_vocab_padding_size,
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Grok's LoRA probably won't have scenarios involving expanded vocabulary, so this code is also useless.

padding_size=DEFAULT_VOCAB_PADDING_SIZE,
quant_config=quant_config,
prefix=maybe_prefix(prefix, "lm_head"),
)
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8 changes: 0 additions & 8 deletions vllm/model_executor/models/nemotron_nas.py
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Expand Up @@ -334,14 +334,6 @@ class DeciLMForCausalLM(nn.Module, SupportsLoRA, SupportsPP, HasNoOps):
}

# LoRA specific attributes
supported_lora_modules = [
"qkv_proj",
"o_proj",
"gate_up_proj",
"down_proj",
"embed_tokens",
"lm_head",
]
embedding_modules = {
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Static var supported_lora_modules has been deprecated for some time, so delete it directly.

"embed_tokens": "input_embeddings",
"lm_head": "output_embeddings",
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6 changes: 1 addition & 5 deletions vllm/model_executor/models/phi4mm.py
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Expand Up @@ -955,11 +955,7 @@ def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):
self.unpadded_vocab_size,
config.hidden_size,
org_num_embeddings=config.vocab_size,
padding_size=(
DEFAULT_VOCAB_PADDING_SIZE
# We need bigger padding if using lora for kernel
# compatibility
if not lora_config else lora_config.lora_vocab_padding_size),
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DITTO

padding_size=DEFAULT_VOCAB_PADDING_SIZE,
quant_config=quant_config,
)
if config.tie_word_embeddings:
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