ef6abf3dc7
Adds ALL files needed for Dockerfile build:
- qwen3_6_scripts/ (baseline patches + our optimizations)
- vllm/ (full vllm package)
- paged_attention_v2_pytorch.py (V2 with single-bmm optimization)
- Dockerfile + computility-run.yaml
Our optimizations vs baseline:
1. paged_attn.py: pre-gathered context KV (eliminates 194 gather calls),
Triton try/fallback, V2 heuristic, threshold 32K→64K
2. paged_attention_v2_pytorch.py: fills NotImplementedError,
single-bmm Phase 1 (195 launches → 3)
3. patch_enable_triton.py: HAS_TRITON=True with safety fallback
4. patch_triton_tuning.py: BLOCK=64, NUM_WARPS=4 for BI-V100
5. computility-run.yaml: gpu-memory-utilization 0.9→0.95,
max-num-batched-tokens 8192→16384
This repo can now be submitted to dev.modelhub.org.cn as-is.
40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
from functools import lru_cache
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from pathlib import Path
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from typing import Optional
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import vllm.envs as envs
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from vllm.connections import global_http_connection
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from vllm.envs import VLLM_IMAGE_FETCH_TIMEOUT
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vLLM_S3_BUCKET_URL = "https://vllm-public-assets.s3.us-west-2.amazonaws.com"
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def get_cache_dir() -> Path:
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"""Get the path to the cache for storing downloaded assets."""
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path = Path(envs.VLLM_ASSETS_CACHE)
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path.mkdir(parents=True, exist_ok=True)
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return path
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@lru_cache
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def get_vllm_public_assets(filename: str,
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s3_prefix: Optional[str] = None) -> Path:
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"""
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Download an asset file from ``s3://vllm-public-assets``
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and return the path to the downloaded file.
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"""
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asset_directory = get_cache_dir() / "vllm_public_assets"
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asset_directory.mkdir(parents=True, exist_ok=True)
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asset_path = asset_directory / filename
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if not asset_path.exists():
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if s3_prefix is not None:
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filename = s3_prefix + "/" + filename
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global_http_connection.download_file(
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f"{vLLM_S3_BUCKET_URL}/{filename}",
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asset_path,
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timeout=VLLM_IMAGE_FETCH_TIMEOUT)
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return asset_path
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