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test: 回退Docker context到26e6cb40完全一致——验证竞赛平台build

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Dockerfile/qwen3_6_scripts/ex_engine/computility-run.yaml 全部
还原到26e6cb40的精确内容。删除所有26e6cb40不存在的新增文件
(prebuilt/*.so, wheels/*.whl, vendor_overrides/, 新增.cu/.sh等)。

目的：确认26e6cb40的文件内容在当前git状态下仍能通过竞赛平台build。
如果通过，说明问题在新增文件中；如果不通过，说明问题在git仓库层面。
This commit is contained in:
Claude
2026-08-11 18:06:09 +00:00
parent af2258f32a
commit 6f6b7e959b
135 changed files with 10134 additions and 31627 deletions
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20
ex_engine/csrc/ilu/ixformer.h
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@@ -34,9 +34,9 @@ torch::Tensor ixinfer_flash_attn_unpad_with_block_tables(
double scale,
double softcap,
bool sqrt_alibi,
const c10::optional<torch::Tensor>& alibi_slopes,
const c10::optional<torch::Tensor>& sinks,
c10::optional<torch::Tensor>& lse);
const std::optional<torch::Tensor>& alibi_slopes,
const std::optional<torch::Tensor>& sinks,
std::optional<torch::Tensor>& lse);
void silu_and_mul(torch::Tensor& input, torch::Tensor& output);
@@ -51,21 +51,21 @@ torch::Tensor xllm_paged_attention(
torch::Tensor& context_lens,
int64_t block_size,
int64_t max_context_len,
const c10::optional<torch::Tensor>& alibi_slopes,
const std::optional<torch::Tensor>& alibi_slopes,
bool causal,
int32_t window_left,
int32_t window_right,
double softcap,
bool enable_cuda_graph,
bool use_sqrt_alibi,
const c10::optional<torch::Tensor>& sinks);
const std::optional<torch::Tensor>& sinks);
torch::Tensor ixformer_linear(torch::Tensor& input,
torch::Tensor& weight,
int64_t act_type,
const c10::optional<torch::Tensor>& bias,
const c10::optional<torch::Tensor>& out,
const c10::optional<bool> persistent);
const std::optional<torch::Tensor>& bias,
const std::optional<torch::Tensor>& out,
const std::optional<bool> persistent);
torch::Tensor ixformer_linear_ex(torch::Tensor& input,
torch::Tensor& weight,
@@ -92,7 +92,7 @@ void residual_rms_norm(torch::Tensor& input,
torch::Tensor& weight,
torch::Tensor& output,
torch::Tensor& residual_output,
const c10::optional<torch::Tensor>& fused_bias,
const std::optional<torch::Tensor>& fused_bias,
double alpha,
double eps,
bool is_post);
@@ -100,7 +100,7 @@ void residual_rms_norm(torch::Tensor& input,
void rms_norm(torch::Tensor& input,
torch::Tensor& weight,
torch::Tensor& output,
const c10::optional<torch::Tensor>& fused_bias,
const std::optional<torch::Tensor>& fused_bias,
double eps);
void topk_softmax(torch::Tensor& topk_weights,