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[Misc] Remove LoRA log #15388

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Merged
merged 1 commit into from
Mar 25, 2025
Merged

[Misc] Remove LoRA log #15388

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6 changes: 0 additions & 6 deletions vllm/config.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2372,12 +2372,6 @@ def verify_with_model_config(self, model_config: ModelConfig):
self.lora_dtype = model_config.dtype
elif isinstance(self.lora_dtype, str):
self.lora_dtype = getattr(torch, self.lora_dtype)
if model_config.quantization and model_config.quantization not in [
"awq", "gptq"
]:
# TODO support marlin
logger.warning("%s quantization is not tested with LoRA yet.",
model_config.quantization)

def verify_with_scheduler_config(self, scheduler_config: SchedulerConfig):
# Reminder: Please update docs/source/features/compatibility_matrix.md
Expand Down
14 changes: 5 additions & 9 deletions vllm/lora/punica_wrapper/punica_gpu.py
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Expand Up @@ -78,10 +78,6 @@ def add_shrink(self, y: torch.Tensor, x: torch.Tensor,
...], scale: float, **kwargs):
"""
Performs GEMM for multiple slices of lora_a.
When `is_prefill is` true, it indicates that it is currently the
prefill stage, and the `_shrink_prefill` function should be called.
Otherwise, it is the decode stage, and the _shrink_decode function
should be called.

Semantics:
for i in range(len(lora_a_stacked)):
Expand Down Expand Up @@ -129,7 +125,7 @@ def add_expand(self,
lora_bias_stacked (Optional[Tuple[torch.Tensor, ...]]):
bias's weight
output_slices (Tuple[int, ...]): Every slice's size
add_inputs (bool): Defaults to True.
add_inputs (bool): Defaults to True.
"""
y_org = y
y = y.view(-1, y.shape[-1])
Expand Down Expand Up @@ -226,7 +222,7 @@ def add_lora_linear(self,

if buffer is None:
r = lora_b_stacked[0].size(-1)
# We set the buffer to be float32 by default ,refer to:
# We set the buffer to be float32 by default, refer to:
# https://github.com/triton-lang/triton/issues/1387
buffer = torch.zeros( # type: ignore
(len(output_slices), x.size(0), r),
Expand Down Expand Up @@ -268,16 +264,16 @@ def add_lora_logits(self,
y (torch.Tensor): Output tensor.
x (torch.Tensor): Input tensor.
lora_a_stacked (torch.Tensor): lora_a's weights.
lora_b_stacked (torch.Tensor):lora_b's weights.
lora_b_stacked (torch.Tensor): lora_b's weights.
scale (float): Scaling factor.
buffer (Optional[torch.Tensor]):Default to None.
buffer (Optional[torch.Tensor]): Default to None.
"""
y_org = y
y = y.view(-1, y.shape[-1])
x = x.view(-1, x.shape[-1])
r = lora_b_stacked.size(-1)
if buffer is None:
# We set the buffer to be float32 by default ,refer to:
# We set the buffer to be float32 by default, refer to:
# https://github.com/triton-lang/triton/issues/1387
buffer = torch.zeros((x.size(0), r),
dtype=torch.float32,
Expand Down