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[Feat] Add custom Embedding tensor model parallel (#2616)

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Similar to #2309 , this PR introduces Embedding tensor model parallel to
achieve decreasing of memory consumption. It support both eager mode and
graph mode.

And this PR refactor module tensor parallel configurations supported in
#2309, #2167, #2120, merge all config into `finegrained_tp_config` in
`additional_config`, including:
`lmhead_tensor_parallel_size`
`oproj_tensor_parallel_size`
`embedding_tensor_parallel_size`
`mlp_tensor_parallel_size`

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

---------

Signed-off-by: zzhx1 <zzh_201018@outlook.com>
Signed-off-by: zzhxx <zhangzihang23@mails.ucas.ac.cn>
Co-authored-by: zzhx1 <zzh_201018@outlook.com>
Co-authored-by: chenxiao <Jaychou1620@Gmail.com>
Co-authored-by: zzhxx <zhangzihang23@mails.ucas.ac.cn>
Co-authored-by: Jade Zheng <zheng.shoujian@outlook.com>
This commit is contained in:
lidenghui1110
2025-12-12 14:41:20 +08:00
committed by GitHub
parent b8a317caac
commit d65fb194d9
9 changed files with 301 additions and 162 deletions
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19
tests/ut/ops/test_linear.py
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@@ -1,4 +1,3 @@
import os
import unittest
from unittest import mock
from unittest.mock import MagicMock, patch
@@ -26,7 +25,8 @@ class BaseLinearTest(unittest.TestCase):
parallel_state._OTP = self.mock_group
self.mock_ascend_config = MagicMock()
self.mock_ascend_config.oproj_tensor_parallel_size = 2
self.mock_ascend_config.finegrained_tp_config.oproj_tensor_parallel_size = 2
self.mock_ascend_config.finegrained_tp_config.mlp_tensor_parallel_size = 2
self.patches = [
patch("vllm_ascend.ascend_config.get_ascend_config",
@@ -81,7 +81,11 @@ class TestAscendUnquantizedLinearMethod(TestBase):
class TestAscendRowParallelLinear(BaseLinearTest):
def test_mlp_optimize(self):
os.environ["VLLM_ASCEND_ENABLE_MLP_OPTIMIZE"] = "1"
ascend_config._ASCEND_CONFIG = MagicMock()
ascend_config._ASCEND_CONFIG.recompute_scheduler_enable = False
ascend_config._ASCEND_CONFIG.finegrained_tp_config.mlp_tensor_parallel_size = 2
ascend_config._ASCEND_CONFIG.ascend_scheduler_config.enabled = False
linear = AscendRowParallelLinear(
input_size=16,
@@ -98,8 +102,9 @@ class TestAscendRowParallelLinear(BaseLinearTest):
config._current_vllm_config = MagicMock()
ascend_config._ASCEND_CONFIG = MagicMock()
ascend_config._ASCEND_CONFIG.oproj_tensor_parallel_size = 2
ascend_config._ASCEND_CONFIG.recompute_scheduler_enable = False
ascend_config._ASCEND_CONFIG.finegrained_tp_config.oproj_tensor_parallel_size = 2
ascend_config._ASCEND_CONFIG.ascend_scheduler_config.enabled = False
linear = AscendRowParallelLinear(
input_size=16,
@@ -115,7 +120,11 @@ class TestAscendRowParallelLinear(BaseLinearTest):
class TestAscendMergedColumnParallelLinear(BaseLinearTest):
def test_merged_mlp_tp_init(self):
os.environ["VLLM_ASCEND_ENABLE_MLP_OPTIMIZE"] = "1"
ascend_config._ASCEND_CONFIG = MagicMock()
ascend_config._ASCEND_CONFIG.recompute_scheduler_enable = False
ascend_config._ASCEND_CONFIG.finegrained_tp_config.mlp_tensor_parallel_size = 2
ascend_config._ASCEND_CONFIG.ascend_scheduler_config.enabled = False
linear = AscendMergedColumnParallelLinear(
input_size=16,