EngineX-Hygon/sglang
5
0
Fork 0
Code Issues Pull Requests Actions 7 Projects Releases Wiki Activity

Add typo checker in pre-commit (#6179)

Browse Source 
Co-authored-by: Brayden Zhong <b8zhong@uwaterloo.ca>
This commit is contained in:
applesaucethebun
2025-05-11 00:55:00 -04:00
committed by GitHub
parent de167cf5fa
commit 2ce8793519
99 changed files with 154 additions and 144 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
python/sglang/srt/lora/lora_manager.py
View File

@@ -100,7 +100,7 @@ class LoRAManager:
self.configs[name] = LoRAConfig(path)
self.hf_target_names.update(self.configs[name].target_modules)
# Target lora weight names for lora_a and lora_b modules repectively.
# Target lora weight names for lora_a and lora_b modules respectively.
# e.g., {("qkv_proj", "q_proj"), ("qkv_proj", "kv_proj")}
self.lora_weight_names: Set[Tuple[str]] = set(
[get_stacked_name(module) for module in self.hf_target_names]

8
python/sglang/srt/lora/mem_pool.py
View File

@@ -50,15 +50,15 @@ class LoRAMemoryPool:
self.uid_to_buffer_id: Dict[Optional[str], int] = {}
# Buffer idx -> lora uid in memory pool
# All uids are initalized as empty strings for empty buffer slots
# Here we don't initalize to None since None is a valid uid
# All uids are initialized as empty strings for empty buffer slots
# Here we don't initialize to None since None is a valid uid
self.buffer_id_to_uid: List[Optional[str]] = [""] * self.max_loras_per_batch
def get_lora_A_shape(
self, module_name: str, base_model: torch.nn.Module
) -> Tuple[int]:
"""
Given a module_name (might be a stacked name), return the hidden dims of modules's input and output.
Given a module_name (might be a stacked name), return the hidden dims of modules' input and output.
"""
input_dim, _ = get_hidden_dim(module_name, self.base_hf_config, base_model)
c = get_stacked_multiply(module_name)
@@ -75,7 +75,7 @@ class LoRAMemoryPool:
self, module_name: str, base_model: torch.nn.Module
) -> Tuple[int]:
"""
Given a module_name (might be a stacked name), return the hidden dims of modules's input and output.
Given a module_name (might be a stacked name), return the hidden dims of modules' input and output.
"""
_, output_dim = get_hidden_dim(module_name, self.base_hf_config, base_model)
c = get_stacked_multiply(module_name)

2
python/sglang/srt/lora/triton_ops/gate_up_lora_b.py
View File

@@ -77,7 +77,7 @@ def _gate_up_lora_b_kernel(
k_offset[:, None] * w_stride_2 + n_offset[None, :] * w_stride_1
)
# Iteate to compute the block in output matrix
# Iterate to compute the block in output matrix
partial_sum = tl.zeros((BLOCK_S, BLOCK_N), dtype=tl.float32)
for k in range(0, tl.cdiv(K, BLOCK_K)):
x_tile = tl.load(

2
python/sglang/srt/lora/triton_ops/qkv_lora_b.py
View File

@@ -79,7 +79,7 @@ def _qkv_lora_b_kernel(
k_offset[:, None] * w_stride_2 + n_offset[None, :] * w_stride_1
)
# Iteate to compute the block in output matrix
# Iterate to compute the block in output matrix
partial_sum = tl.zeros((BLOCK_S, BLOCK_N), dtype=tl.float32)
for k in range(0, tl.cdiv(K, BLOCK_K)):
x_tile = tl.load(

2
python/sglang/srt/lora/triton_ops/sgemm_lora_a.py
View File

@@ -67,7 +67,7 @@ def _sgemm_lora_a_kernel(
k_offset[:, None] * w_stride_2 + n_offset[None, :] * w_stride_1
)
# Iteate to compute the block in output matrix
# Iterate to compute the block in output matrix
partial_sum = tl.zeros((BLOCK_S, BLOCK_N), dtype=tl.float32)
for k in range(0, tl.cdiv(K, BLOCK_K)):
x_tile = tl.load(

2
python/sglang/srt/lora/triton_ops/sgemm_lora_b.py
View File

@@ -69,7 +69,7 @@ def _sgemm_lora_b_kernel(
k_offset[:, None] * w_stride_2 + n_offset[None, :] * w_stride_1
)
# Iteate to compute the block in output matrix
# Iterate to compute the block in output matrix
partial_sum = tl.zeros((BLOCK_S, BLOCK_N), dtype=tl.float32)
for k in range(0, tl.cdiv(K, BLOCK_K)):
x_tile = tl.load(

2
python/sglang/srt/lora/utils.py
View File

@@ -79,7 +79,7 @@ def get_hidden_dim(
module_name: str, config: AutoConfig, base_model: torch.nn.Module
) -> Tuple[int]:
"""
Given a module_name (might be a stacked name), return the hidden dims of modules's input and output.
Given a module_name (might be a stacked name), return the hidden dims of modules' input and output.
"""
if hasattr(base_model, "get_hidden_dim"):