[Ops][Misc] Refactor and optimize CausalConv1d for Ascend (#7495)
### What this PR does / why we need it?
During the prefill phase of Qwen3-Next and Qwen3.5, the
`torch.ops._C_ascend.causal_conv1d_fn` operator exhibits significant
performance bottlenecks. To address this, we have re-implemented the
optimization using `torch.ops._C_ascend.npu_causal_conv1d_custom`.
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
1 accuracy test
```
[2026-03-20 16:44:22,961] [ais_bench] [INFO] Start launch task state board ...
+-----------------------------+-----------+------------+-------------+----------+-------------------------------------------+---------------------+
| Task Name | Process | Progress | Time Cost | Status | Log Path | Extend Parameters |
+=============================+===========+============+=============+==========+===========================================+=====================+
| vllm-api-general-chat/gsm8k | 2918978 | NA | 0:00:01 | finish | logs/eval/vllm-api-general-chat/gsm8k.out | None |
+-----------------------------+-----------+------------+-------------+----------+-------------------------------------------+---------------------+
[2026-03-20 16:44:34,284] [ais_bench] [INFO] Evaluation tasks completed.
[2026-03-20 16:44:34,287] [ais_bench] [INFO] Summarizing evaluation results...
dataset version metric mode vllm-api-general-chat
--------- --------- -------- ------ -----------------------
gsm8k 271d0b accuracy gen 96.21
```
2 ut modify test
`pytest -sv
/home/c30006096/vllm-ascend/tests/e2e/nightly/single_node/ops/singlecard_ops/triton/test_causal_conv1d.py::test_ascend_causal_conv1d`
- vLLM version: v0.17.0
- vLLM main:
8b6325758c
Signed-off-by: wenba0 <3054239545@qq.com>
Signed-off-by: jiaojiao <56385650+wenba0@users.noreply.github.com>
This commit is contained in:
@@ -14,7 +14,7 @@
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* \brief
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*/
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#include "register/op_impl_registry.h"
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#include "error_log.h"
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#include "log/log.h"
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using namespace ge;
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@@ -23,27 +23,19 @@ static constexpr int64_t IDX_0 = 0;
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static ge::graphStatus InferShapeCausalConv1d(gert::InferShapeContext* context)
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{
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// OPS_LOG_D(context->GetNodeName(), "Begin to do InferShapeCausalConv1d");
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OP_LOGD(context->GetNodeName(), "Begin to do InferShapeCausalConv1d");
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// get input shapes
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const gert::Shape* xShape = context->GetInputShape(IDX_0);
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OP_CHECK_NULL_WITH_CONTEXT(context, xShape);
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// get output shapes
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gert::Shape* yShape = context->GetOutputShape(IDX_0);
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OP_CHECK_NULL_WITH_CONTEXT(context, yShape);
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// 填充输出shape大小
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auto xShapeSize = xShape->GetDimNum();
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yShape->SetDimNum(xShapeSize);
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for (size_t i = 0; i < xShapeSize; i++) {
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int64_t dim = xShape->GetDim(i);
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yShape->SetDim(i, dim);
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}
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*yShape = *xShape;
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// OPS_LOG_D(context->GetNodeName(), "End to do InferShapeCausalConv1d");
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OP_LOGD(context->GetNodeName(), "End to do InferShapeCausalConv1d");
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return GRAPH_SUCCESS;
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}
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IMPL_OP_INFERSHAPE(CausalConv1d).InferShape(InferShapeCausalConv1d);
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} // namespace ops
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} // namespace ops
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