e38ef2c434
### What this PR does / why we need it?
The current library only supports the FullDecodeOnly graph mode, which
enables full graph execution during the decode. This PR extends support
to allow full graph execution in both the prefill and decode, referred
to as FULL graph mode.
- vLLM version: v0.11.0
- vLLM main:
2918c1b49c
Signed-off-by: wangxiaoxin-sherie <wangxiaoxin7@huawei.com>
Co-authored-by: wangxiaoxin-sherie <wangxiaoxin7@huawei.com>
122 lines
4.4 KiB
Python
122 lines
4.4 KiB
Python
#
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# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
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# Copyright 2023 The vLLM team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# This file is a part of the vllm-ascend project.
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# Adapted from vllm/tests/basic_correctness/test_basic_correctness.py
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#
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"""Compare the short outputs of HF and vLLM when using greedy sampling.
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Run `pytest tests/e2e/multicard/test_qwen3_moe.py`.
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"""
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import os
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from vllm import SamplingParams
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from tests.e2e.conftest import VllmRunner
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from tests.e2e.model_utils import check_outputs_equal
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def test_models_distributed_Qwen3_MOE_TP2_WITH_FULL_DECODE_ONLY():
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if 'HCCL_OP_EXPANSION_MODE' in os.environ:
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del os.environ['HCCL_OP_EXPANSION_MODE']
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prompts = [
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"Hello, my name is", "The president of the United States is",
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"The capital of France is", "The future of AI is"
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]
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model = "Qwen/Qwen3-30B-A3B"
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sampling_params = SamplingParams(max_tokens=32, temperature=0.0)
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with VllmRunner(model,
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max_model_len=1024,
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tensor_parallel_size=2,
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enforce_eager=False,
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compilation_config={
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"cudagraph_mode": "FULL_DECODE_ONLY",
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"cudagraph_capture_sizes": [4, 8, 24, 48, 60]
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}) as runner:
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vllm_fullgraph_outputs = runner.model.generate(prompts,
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sampling_params)
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with VllmRunner(
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model,
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max_model_len=1024,
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tensor_parallel_size=2,
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enforce_eager=False,
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) as runner:
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vllm_eager_outputs = runner.model.generate(prompts, sampling_params)
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vllm_fullgraph_outputs_list = []
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for output in vllm_fullgraph_outputs:
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vllm_fullgraph_outputs_list.append(
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(output.outputs[0].index, output.outputs[0].text))
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vllm_eager_outputs_list = []
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for output in vllm_eager_outputs:
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vllm_eager_outputs_list.append(
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(output.outputs[0].index, output.outputs[0].text))
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check_outputs_equal(
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outputs_0_lst=vllm_eager_outputs_list,
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outputs_1_lst=vllm_fullgraph_outputs_list,
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name_0="vllm_eager_outputs",
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name_1="vllm_fullgraph_outputs",
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)
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def test_models_distributed_Qwen3_MOE_TP2_WITH_FULL():
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if 'HCCL_OP_EXPANSION_MODE' in os.environ:
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del os.environ['HCCL_OP_EXPANSION_MODE']
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prompts = [
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"Hello, my name is", "The president of the United States is",
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"The capital of France is", "The future of AI is"
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]
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model = "Qwen/Qwen3-30B-A3B"
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sampling_params = SamplingParams(max_tokens=32, temperature=0.0)
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with VllmRunner(model,
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max_model_len=1024,
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tensor_parallel_size=2,
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enforce_eager=False,
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compilation_config={
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"cudagraph_mode": "FULL",
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"cudagraph_capture_sizes": [4, 8, 24, 48, 60]
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}) as runner:
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vllm_fullgraph_outputs = runner.model.generate(prompts,
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sampling_params)
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with VllmRunner(
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model,
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max_model_len=1024,
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tensor_parallel_size=2,
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enforce_eager=False,
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) as runner:
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vllm_eager_outputs = runner.model.generate(prompts, sampling_params)
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vllm_fullgraph_outputs_list = []
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for output in vllm_fullgraph_outputs:
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vllm_fullgraph_outputs_list.append(
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(output.outputs[0].index, output.outputs[0].text))
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vllm_eager_outputs_list = []
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for output in vllm_eager_outputs:
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vllm_eager_outputs_list.append(
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(output.outputs[0].index, output.outputs[0].text))
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check_outputs_equal(
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outputs_0_lst=vllm_eager_outputs_list,
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outputs_1_lst=vllm_fullgraph_outputs_list,
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name_0="vllm_eager_outputs",
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name_1="vllm_fullgraph_outputs",
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)
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