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Drop torchair (#4814)

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aclgraph is stable and fast now. Let's drop torchair graph mode now.

TODO: some logic to adapt torchair should be cleaned up as well. We'll
do it in the following PR.

- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
Co-authored-by: Mengqing Cao <cmq0113@163.com>
This commit is contained in:
wangxiyuan
2025-12-10 09:20:40 +08:00
committed by GitHub
parent ba9cda9dfd
commit 835b4c8f1d
84 changed files with 77 additions and 16881 deletions
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23
docs/source/user_guide/configuration/additional_config.md
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@@ -27,7 +27,6 @@ The following table lists additional configuration options available in vLLM Asc
| Name | Type | Default | Description |
|-------------------------------------|------|---------|-----------------------------------------------------------------------------------------------------------------------------------------------|
| `xlite_graph_config` | dict | `{}` | Configuration options for xlite graph mode |
| `torchair_graph_config` | dict | `{}` | Configuration options for torchair graph mode |
| `weight_prefetch_config` | dict | `{}` | Configuration options for weight prefetch |
| `refresh` | bool | `false` | Whether to refresh global Ascend configuration content. This is usually used by rlhf or ut/e2e test case. |
| `expert_map_path` | str | `None` | When using expert load balancing for an MoE model, an expert map path needs to be passed in. |
@@ -52,21 +51,6 @@ The details of each configuration option are as follows:
| `enabled` | bool | `False` | Whether to enable xlite graph mode. Currently only Llama or Qwen dense series models are supported. |
| `full_mode` | bool | `False` | Whether to enable xlite for both the prefill and decode stages. By default, xlite is only enabled for the decode stage. |
**torchair_graph_config**
| Name | Type | Default | Description |
| ---- | ---- | ------- | ----------- |
| `enabled` | bool | `False` | Whether to enable torchair graph mode. Currently only DeepSeek series models and PanguProMoE are supported. |
| `mode` | str | `None` | When using reduce-overhead mode for torchair, it needs to be set. |
| `enable_multistream_mla`| bool | `False` | Whether to put vector operators of MLA to another stream. This option only takes effect on models using MLA (for example, DeepSeek). |
| `enable_view_optimize` | bool | `True` | Whether to enable torchair view optimization. |
| `enable_frozen_parameter` | bool | `True` | Whether to fix the memory address of weights during inference to reduce the input address refresh time during graph execution. |
| `use_cached_graph` | bool | `False` | Whether to use cached graph. |
| `graph_batch_sizes` | list[int] | `[]` | The batch size for torchair graph cache. |
| `graph_batch_sizes_init` | bool | `False` | Init graph batch size dynamically if `graph_batch_sizes` is empty. |
| `enable_kv_nz`| bool | `False` | Whether to enable KV Cache NZ layout. This option only takes effect on models using MLA (for example, DeepSeek). |
| `enable_super_kernel` | bool | `False` | Whether to enable super kernel to fuse operators in deepseek moe layers. This option only takes effects on moe models using dynamic w8a8 quantization.|
**weight_prefetch_config**
| Name | Type | Default | Description |
@@ -80,13 +64,6 @@ An example of additional configuration is as follows:
```
{
"torchair_graph_config": {
"enabled": True,
"use_cached_graph": True,
"graph_batch_sizes": [1, 2, 4, 8],
"graph_batch_sizes_init": False,
"enable_kv_nz": False
},
"weight_prefetch_config": {
"enabled": True,
"prefetch_ratio": {