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[Misc] Remove LoRA log (#15388)

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Signed-off-by: Jee Jee Li <pandaleefree@gmail.com>
This commit is contained in:
Jee Jee Li
2025-03-25 11:43:48 +08:00
committed by GitHub
parent 97cfa65df7
commit 6db94571d7
2 changed files with 5 additions and 15 deletions
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6
vllm/config.py
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@@ -2373,12 +2373,6 @@ class LoRAConfig:
self.lora_dtype = model_config.dtype self.lora_dtype = model_config.dtype
elif isinstance(self.lora_dtype, str): elif isinstance(self.lora_dtype, str):
self.lora_dtype = getattr(torch, self.lora_dtype) 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): def verify_with_scheduler_config(self, scheduler_config: SchedulerConfig):
# Reminder: Please update docs/source/features/compatibility_matrix.md # Reminder: Please update docs/source/features/compatibility_matrix.md

14
vllm/lora/punica_wrapper/punica_gpu.py
View File

@@ -78,10 +78,6 @@ class PunicaWrapperGPU(PunicaWrapperBase):
...], scale: float, **kwargs): ...], scale: float, **kwargs):
""" """
Performs GEMM for multiple slices of lora_a. 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: Semantics:
for i in range(len(lora_a_stacked)): for i in range(len(lora_a_stacked)):
@@ -129,7 +125,7 @@ class PunicaWrapperGPU(PunicaWrapperBase):
lora_bias_stacked (Optional[Tuple[torch.Tensor, ...]]): lora_bias_stacked (Optional[Tuple[torch.Tensor, ...]]):
bias's weight bias's weight
output_slices (Tuple[int, ...]): Every slice's size output_slices (Tuple[int, ...]): Every slice's size
add_inputs (bool): Defaults to True. add_inputs (bool): Defaults to True.
""" """
y_org = y y_org = y
y = y.view(-1, y.shape[-1]) y = y.view(-1, y.shape[-1])
@@ -226,7 +222,7 @@ class PunicaWrapperGPU(PunicaWrapperBase):
if buffer is None: if buffer is None:
r = lora_b_stacked[0].size(-1) 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 # https://github.com/triton-lang/triton/issues/1387
buffer = torch.zeros( # type: ignore buffer = torch.zeros( # type: ignore
(len(output_slices), x.size(0), r), (len(output_slices), x.size(0), r),
@@ -268,16 +264,16 @@ class PunicaWrapperGPU(PunicaWrapperBase):
y (torch.Tensor): Output tensor. y (torch.Tensor): Output tensor.
x (torch.Tensor): Input tensor. x (torch.Tensor): Input tensor.
lora_a_stacked (torch.Tensor): lora_a's weights. 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. scale (float): Scaling factor.
buffer (Optional[torch.Tensor]):Default to None. buffer (Optional[torch.Tensor]): Default to None.
""" """
y_org = y y_org = y
y = y.view(-1, y.shape[-1]) y = y.view(-1, y.shape[-1])
x = x.view(-1, x.shape[-1]) x = x.view(-1, x.shape[-1])
r = lora_b_stacked.size(-1) r = lora_b_stacked.size(-1)
if buffer is None: 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 # https://github.com/triton-lang/triton/issues/1387
buffer = torch.zeros((x.size(0), r), buffer = torch.zeros((x.size(0), r),
dtype=torch.float32, dtype=torch.float32,