8030a11b96
project_7 docker build 已在竞赛平台验证成功。 完整搬运 wudixzy/competition stack: - qwen3_5.py 2615 行 (12 个 corex .so 调用) - patch_ops.sh 251 行 (set -eo pipefail + cd dirname) - 12 prebuilt corex .so (SHA256 verified) - 13 CUDA .cu 源码 + 11 build scripts - 9 vendor overrides (block/sampler/scheduler) - transformers-4.55.3 offline wheel - computility-run.yaml: 262144 max-model-len, BI100 env vars - Dockerfile 结构不变 (COPY qwen3_6_scripts + RUN patch_ops.sh)
122 lines
4.1 KiB
Python
122 lines
4.1 KiB
Python
"""Install disabled-by-default M1-48 XFormers timing boundaries."""
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from __future__ import annotations
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from pathlib import Path
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try:
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from patch_utils import package_root, replace_once
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except ModuleNotFoundError:
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from .patch_utils import package_root, replace_once
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IMPORT_OLD = "from vllm.logger import init_logger"
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IMPORT_NEW = """\
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from vllm.bi100_profile import bi100_timer
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from vllm.logger import init_logger"""
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KV_WRITE_OLD = """\
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PagedAttention.write_to_paged_cache(key, value, key_cache,
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value_cache,
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updated_slot_mapping,
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self.kv_cache_dtype,
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k_scale, v_scale)"""
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KV_WRITE_NEW = """\
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with bi100_timer("xformers.kv_write"):
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PagedAttention.write_to_paged_cache(
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key, value, key_cache, value_cache,
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updated_slot_mapping, self.kv_cache_dtype,
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k_scale, v_scale)"""
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DENSE_OLD = """\
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out = self._run_memory_efficient_xformers_forward(
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query, key, value, prefill_meta, attn_type=attn_type)"""
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DENSE_NEW = """\
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with bi100_timer("xformers.dense_prefill"):
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out = self._run_memory_efficient_xformers_forward(
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query, key, value, prefill_meta, attn_type=attn_type)"""
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PAGED_OLD = """\
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out = PagedAttention.forward_prefix(
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query,
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key,
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value,
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self.kv_cache_dtype,
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key_cache,
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value_cache,
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prefill_meta.block_tables,
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prefill_meta.query_start_loc,
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prefill_meta.seq_lens_tensor,
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prefill_meta.context_lens_tensor,
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prefill_meta.max_query_len,
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self.alibi_slopes,
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self.sliding_window,
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k_scale,
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v_scale,
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is_causal_decoder=(attn_type == AttentionType.DECODER),
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)"""
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PAGED_NEW = """\
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with bi100_timer("xformers.paged_prefill"):
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out = PagedAttention.forward_prefix(
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query,
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key,
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value,
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self.kv_cache_dtype,
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key_cache,
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value_cache,
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prefill_meta.block_tables,
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prefill_meta.query_start_loc,
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prefill_meta.seq_lens_tensor,
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prefill_meta.context_lens_tensor,
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prefill_meta.max_query_len,
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self.alibi_slopes,
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self.sliding_window,
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k_scale,
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v_scale,
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is_causal_decoder=(attn_type == AttentionType.DECODER),
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)"""
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def patch_file(path: Path) -> None:
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replace_once(
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path,
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IMPORT_OLD,
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IMPORT_NEW,
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already_contains="from vllm.bi100_profile import bi100_timer",
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)
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replace_once(
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path,
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KV_WRITE_OLD,
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KV_WRITE_NEW,
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already_contains='bi100_timer("xformers.kv_write")',
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)
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replace_once(
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path,
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DENSE_OLD,
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DENSE_NEW,
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already_contains='bi100_timer("xformers.dense_prefill")',
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)
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replace_once(
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path,
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PAGED_OLD,
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PAGED_NEW,
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already_contains='bi100_timer("xformers.paged_prefill")',
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)
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text = path.read_text(encoding="utf-8")
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canonical = "\n".join(line.rstrip(" \t") for line in text.split("\n"))
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if not canonical.endswith("\n"):
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canonical += "\n"
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if canonical != text:
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path.write_text(canonical, encoding="utf-8")
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def main() -> None:
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path = package_root("vllm") / "attention" / "backends" / "xformers.py"
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print("=== patch_xformers_profile (M1-48 diagnostic timers) ===")
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print(f"Target: {path}")
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patch_file(path)
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if __name__ == "__main__":
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main()
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