EngineX/xc-llm-ascend
3
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

[Lint]Style: Convert vllm-ascend/ to ruff format(Batch #10) (#6173)

Browse Source 
### What this PR does / why we need it?
**Scope of Changes**:
| File Path |
| :--- |
|`vllm_ascend/ops/layer_shard_linear.py`|
|`vllm_ascend/ops/linear.py`|
|`vllm_ascend/ops/linear_op.py`|
|`vllm_ascend/worker/worker.py`|
| ` vllm_ascend/patch/worker/patch_bert.py` |
| ` vllm_ascend/patch/worker/patch_deepseek.py` |
| ` vllm_ascend/patch/worker/patch_distributed.py` |
| ` vllm_ascend/patch/worker/patch_module.py` |
| ` vllm_ascend/patch/worker/patch_multimodal_merge.py` |
| ` vllm_ascend/patch/worker/patch_qwen3_next.py` |
| ` vllm_ascend/patch/worker/patch_qwen3_next_mtp.py` |
| ` vllm_ascend/patch/worker/patch_rejection_sampler.py` |
| ` vllm_ascend/patch/worker/patch_rope.py` |
| ` vllm_ascend/patch/worker/patch_triton.py` |
| ` vllm_ascend/patch/worker/patch_unquantized_gemm.py` |
| ` vllm_ascend/patch/worker/patch_v2_egale.py` |
|` vllm_ascend/worker/npu_input_batch.py`|
|` vllm_ascend/worker/v2/aclgraph_utils.py`|
|` vllm_ascend/worker/v2/attn_utils.py`|
|` vllm_ascend/worker/v2/model_runner.py`|
|` vllm_ascend/worker/v2/sample/gumbel.py`|
|` vllm_ascend/worker/v2/sample/penalties.py`|
|` vllm_ascend/worker/v2/sample/sampler.py`|
|` vllm_ascend/worker/v2/spec_decode/__init__.py`|
|` vllm_ascend/worker/v2/spec_decode/eagle.py`|
|` vllm_ascend/worker/v2/states.py`|
### Does this PR introduce _any_ user-facing change?

### How was this patch tested?

- vLLM version: v0.14.0
- vLLM main:
d68209402d

Signed-off-by: MrZ20 <2609716663@qq.com>
Signed-off-by: SILONG ZENG <2609716663@qq.com>
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>
This commit is contained in:
SILONG ZENG
2026-02-06 15:35:06 +08:00
committed by GitHub
parent 65b7f716e6
commit 19b5d44ea8
33 changed files with 938 additions and 1243 deletions
Download Patch File Download Diff File Expand all files Collapse all files

30
vllm_ascend/distributed/utils.py
View File

@@ -1,5 +1,3 @@
from typing import Optional
import torch
import torch.distributed as dist
from vllm.distributed.parallel_state import GroupCoordinator, get_dp_group
@@ -8,7 +6,9 @@ from vllm.forward_context import get_forward_context
from vllm_ascend.distributed.parallel_state import get_fc3_quant_x_group
def fc3_all_gather_and_maybe_unpad_impl(x: torch.Tensor, ) -> torch.Tensor:
def fc3_all_gather_and_maybe_unpad_impl(
x: torch.Tensor,
) -> torch.Tensor:
try:
forward_context = get_forward_context()
except AssertionError:
@@ -22,34 +22,26 @@ def fc3_all_gather_and_maybe_unpad_impl(x: torch.Tensor, ) -> torch.Tensor:
else:
# unpad
num_tokens_across_dp_cpu = dp_metadata.num_tokens_across_dp_cpu
result = torch.empty((num_tokens_across_dp_cpu.sum(), *x.shape[1:]),
device=x.device,
dtype=x.dtype)
result = torch.empty((num_tokens_across_dp_cpu.sum(), *x.shape[1:]), device=x.device, dtype=x.dtype)
dp_size = get_dp_group().world_size
x = x.view(dp_size, forward_context.padded_length, *x.shape[1:])
offset = 0
for idx in range(dp_size):
num_tokens_dp = num_tokens_across_dp_cpu[idx]
result[offset:offset + num_tokens_dp] = x[idx, :num_tokens_dp]
result[offset : offset + num_tokens_dp] = x[idx, :num_tokens_dp]
offset += num_tokens_dp
x = result
return x
def all_gather_async(input: torch.Tensor,
group: GroupCoordinator,
output: Optional[torch.Tensor] = None,
async_op: bool = True):
def all_gather_async(
input: torch.Tensor, group: GroupCoordinator, output: torch.Tensor | None = None, async_op: bool = True
):
if group.world_size == 1:
return input, None
if output is None:
input_size = input.size()
output_size = (input_size[0] * group.world_size, ) + input_size[1:]
output = torch.empty(output_size,
dtype=input.dtype,
device=input.device)
return output, dist.all_gather_into_tensor(output,
input,
group=group.device_group,
async_op=async_op)
output_size = (input_size[0] * group.world_size,) + input_size[1:]
output = torch.empty(output_size, dtype=input.dtype, device=input.device)
return output, dist.all_gather_into_tensor(output, input, group=group.device_group, async_op=async_op)