[ROCm] [CI] Add More Tests (#542)
Signed-off-by: tjtanaa <tunjian.tan@embeddedllm.com>
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+73
@@ -0,0 +1,73 @@
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#!/bin/bash
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# Helper function to safely login to ECR Public with per-job config isolation
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# Uses DOCKER_CONFIG environment variable to prevent race conditions
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#
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# This script prevents the "device or resource busy" error by giving each
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# Buildkite job its own isolated Docker config directory.
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#
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# Usage:
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# source docker_login_ecr_public.sh && safe_docker_login_ecr_public
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set -euo pipefail
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# Configuration
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ECR_REGISTRY="public.ecr.aws"
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setup_isolated_docker_config() {
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# Use BUILDKITE_JOB_ID for job-specific isolation
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# Fallback to PID if running outside Buildkite
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local job_id="${BUILDKITE_JOB_ID:-$$}"
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# Set Docker config to job-specific directory
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export DOCKER_CONFIG="/tmp/docker-config-${job_id}"
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# Create directory if it doesn't exist
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mkdir -p "$DOCKER_CONFIG"
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echo "[docker-config] Using isolated Docker config: $DOCKER_CONFIG"
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}
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check_docker_auth() {
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# Check if already authenticated to the given registry
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# Returns 0 if authenticated, 1 if not
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local registry="$1"
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# Check if credentials exist in the isolated config
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if [[ -f "$DOCKER_CONFIG/config.json" ]]; then
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# Check if registry is present in config
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if grep -q "$registry" "$DOCKER_CONFIG/config.json" 2>/dev/null; then
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return 0
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fi
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fi
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return 1
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}
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safe_docker_login_ecr_public() {
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# Setup isolated config first
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setup_isolated_docker_config
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local registry="$ECR_REGISTRY"
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# Check if already authenticated (within this job)
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if check_docker_auth "$registry"; then
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echo "[docker-login] Already authenticated to $registry in this job"
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return 0
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fi
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# Perform login to isolated config directory
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echo "[docker-login] Logging in to $ECR_REGISTRY (isolated config)..."
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if aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$ECR_REGISTRY"; then
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echo "[docker-login] Login successful (config: $DOCKER_CONFIG)"
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return 0
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else
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local exit_code=$?
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echo "[docker-login] ERROR: Login failed with exit code $exit_code" >&2
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return $exit_code
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fi
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}
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# Execute if run as script (not sourced)
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if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
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safe_docker_login_ecr_public
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fi
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@@ -66,6 +66,14 @@ done
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echo "--- Pulling container"
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image_name="public.ecr.aws/q9t5s3a7/vllm-ci-test-repo:${BUILDKITE_COMMIT}-rocm-omni"
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container_name="rocm_${BUILDKITE_COMMIT}_$(tr -dc A-Za-z0-9 < /dev/urandom | head -c 10; echo)"
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# Install AWS CLI to authenticate to ECR Public Gallery to get higher rate limit for pulling images
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sudo apt-get update && sudo apt-get install -y awscli
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# Use safe docker login helper to prevent race conditions
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source "$(dirname "${BASH_SOURCE[0]}")/../docker_login_ecr_public.sh"
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safe_docker_login_ecr_public
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# Pull the container from ECR Public Gallery
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docker pull "${image_name}"
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remove_docker_container() {
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@@ -1,10 +1,10 @@
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steps:
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- label: "Diffusion Model Test"
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timeout_in_minutes: 15
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timeout_in_minutes: 20
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agent_pool: mi325_2
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depends_on: amd-build
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mirror_hardwares: [amdexperimental, amdproduction, amdtentative]
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mirror_hardwares: [amdproduction]
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grade: Blocking
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commands:
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- export GPU_ARCHS=gfx942
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@@ -20,7 +20,7 @@ steps:
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timeout_in_minutes: 15
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agent_pool: mi325_1
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depends_on: amd-build
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mirror_hardwares: [amdexperimental, amdproduction, amdtentative]
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mirror_hardwares: [amdproduction]
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grade: Blocking
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commands:
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- export GPU_ARCHS=gfx942
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@@ -34,11 +34,33 @@ steps:
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- export VLLM_ROCM_USE_AITER_RMSNORM=0
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- pytest -s -v tests/e2e/offline_inference/test_cache_dit.py tests/e2e/offline_inference/test_teacache.py
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- label: "Diffusion Parallelism Test"
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timeout_in_minutes: 15
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agent_pool: mi325_2
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depends_on: amd-build
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mirror_hardwares: [amdproduction]
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grade: Blocking
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commands:
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- export MIOPEN_DEBUG_CONV_DIRECT=0
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- export MIOPEN_DEBUG_CONV_GEMM=0
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- pytest -s -v tests/e2e/offline_inference/test_sequence_parallel.py
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- label: "Diffusion GPU Worker Test"
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timeout_in_minutes: 20
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agent_pool: mi325_2
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depends_on: amd-build
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mirror_hardwares: [amdproduction]
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grade: Blocking
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commands:
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- export MIOPEN_DEBUG_CONV_DIRECT=0
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- export MIOPEN_DEBUG_CONV_GEMM=0
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- pytest -s -v tests/diffusion/test_gpu_worker.py
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- label: "Omni Model Test Qwen2-5-Omni"
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timeout_in_minutes: 15
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agent_pool: mi325_2
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depends_on: amd-build
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mirror_hardwares: [amdexperimental, amdproduction, amdtentative]
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mirror_hardwares: [amdproduction]
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grade: Blocking
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commands:
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- export GPU_ARCHS=gfx942
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@@ -51,3 +73,34 @@ steps:
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- export VLLM_ROCM_USE_AITER_LINEAR=0
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- export VLLM_ROCM_USE_AITER_RMSNORM=0
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- pytest -s -v tests/e2e/offline_inference/test_qwen2_5_omni.py
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- label: "Omni Model Test Qwen3-Omni"
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timeout_in_minutes: 15
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agent_pool: mi325_2
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depends_on: amd-build
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mirror_hardwares: [amdproduction]
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grade: Blocking
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commands:
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- export VLLM_LOGGING_LEVEL=DEBUG
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- export VLLM_WORKER_MULTIPROC_METHOD=spawn
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- export MIOPEN_DEBUG_CONV_DIRECT=0
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- export MIOPEN_DEBUG_CONV_GEMM=0
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- pytest -s -v tests/e2e/offline_inference/test_qwen3_omni.py tests/e2e/online_serving/test_qwen3_omni.py
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- label: "Diffusion Image Edit Test"
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timeout_in_minutes: 15
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agent_pool: mi325_1
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depends_on: amd-build
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mirror_hardwares: [amdproduction]
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grade: Blocking
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commands:
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- export GPU_ARCHS=gfx942
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- export VLLM_LOGGING_LEVEL=DEBUG
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- export VLLM_WORKER_MULTIPROC_METHOD=spawn
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- export MIOPEN_DEBUG_CONV_DIRECT=0
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- export MIOPEN_DEBUG_CONV_GEMM=0
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- export VLLM_ROCM_USE_AITER=1
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- export VLLM_ROCM_USE_AITER_MHA=1
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- export VLLM_ROCM_USE_AITER_LINEAR=0
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- export VLLM_ROCM_USE_AITER_RMSNORM=0
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- pytest -s -v tests/e2e/online_serving/test_i2i_multi_image_input.py
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@@ -13,7 +13,7 @@
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depends_on: ~
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soft_fail: false
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commands:
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- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
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- "source .buildkite/scripts/docker_login_ecr_public.sh && safe_docker_login_ecr_public"
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- "docker build -f docker/Dockerfile.rocm -t {{ docker_image_amd }} --progress plain ."
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- "docker push {{ docker_image_amd }}"
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key: "amd-build"
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@@ -0,0 +1,98 @@
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# Stage config for running Qwen3-Omni-MoE with 3-stage architecture
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# Stage 0: Thinker (multimodal understanding + text generation)
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# Stage 1: Talker (text embeddings → 16-layer RVQ codec codes)
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# Stage 2: Code2Wav (8-layer RVQ codes → audio waveform)
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# The following config has been verified on 2x H100-80G GPUs.
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stage_args:
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- stage_id: 0
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runtime:
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devices: "0,1"
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max_batch_size: 1
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engine_args:
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model_stage: thinker
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model_arch: Qwen3OmniMoeForConditionalGeneration
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worker_cls: vllm_omni.worker.gpu_ar_worker.GPUARWorker
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scheduler_cls: vllm_omni.core.sched.omni_ar_scheduler.OmniARScheduler
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gpu_memory_utilization: 0.6
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enforce_eager: false
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trust_remote_code: true
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engine_output_type: latent # Output hidden states for talker
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distributed_executor_backend: "mp"
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enable_prefix_caching: false
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hf_config_name: thinker_config
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tensor_parallel_size: 2
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load_format: dummy
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final_output: true
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final_output_type: text
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is_comprehension: true
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default_sampling_params:
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temperature: 0.4
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top_p: 0.9
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top_k: 1
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max_tokens: 100
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seed: 42
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detokenize: True
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repetition_penalty: 1.05
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- stage_id: 1
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runtime:
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devices: "1"
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max_batch_size: 1
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engine_args:
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model_stage: talker
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model_arch: Qwen3OmniMoeForConditionalGeneration
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worker_cls: vllm_omni.worker.gpu_ar_worker.GPUARWorker
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scheduler_cls: vllm_omni.core.sched.omni_ar_scheduler.OmniARScheduler
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gpu_memory_utilization: 0.3
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enforce_eager: true
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trust_remote_code: true
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engine_output_type: latent # Output codec codes for code2wav
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# tensor_parallel_size: 2
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enable_prefix_caching: false
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distributed_executor_backend: "mp"
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hf_config_name: talker_config
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load_format: dummy
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engine_input_source: [0]
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custom_process_input_func: vllm_omni.model_executor.stage_input_processors.qwen3_omni.thinker2talker
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# final_output: true
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# final_output_type: text
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default_sampling_params:
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temperature: 0.9
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top_k: 50
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max_tokens: 100
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seed: 42
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detokenize: False
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repetition_penalty: 1.05
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stop_token_ids: [2150]
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- stage_id: 2
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runtime:
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devices: "0"
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max_batch_size: 1
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engine_args:
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model_stage: code2wav
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model_arch: Qwen3OmniMoeForConditionalGeneration
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worker_cls: vllm_omni.worker.gpu_generation_worker.GPUGenerationWorker
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scheduler_cls: vllm_omni.core.sched.omni_generation_scheduler.OmniGenerationScheduler
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enforce_eager: true
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trust_remote_code: true
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enable_prefix_caching: false
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engine_output_type: audio # Final output: audio waveform
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gpu_memory_utilization: 0.1
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distributed_executor_backend: "mp"
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max_num_batched_tokens: 1000000
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hf_config_name: thinker_config
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load_format: dummy
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engine_input_source: [1]
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custom_process_input_func: vllm_omni.model_executor.stage_input_processors.qwen3_omni.talker2code2wav
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final_output: true
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final_output_type: audio
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default_sampling_params:
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temperature: 0.0
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top_p: 1.0
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top_k: -1
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max_tokens: 200
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seed: 42
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detokenize: True
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repetition_penalty: 1.1
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@@ -10,14 +10,20 @@ from pathlib import Path
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import pytest
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from vllm.assets.video import VideoAsset
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from vllm_omni.utils import is_rocm
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from .conftest import OmniRunner
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os.environ["VLLM_WORKER_MULTIPROC_METHOD"] = "spawn"
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models = ["Qwen/Qwen3-Omni-30B-A3B-Instruct"]
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# CI stage config for 2xH100-80G GPUs
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stage_configs = [str(Path(__file__).parent / "stage_configs" / "qwen3_omni_ci.yaml")]
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# CI stage config for 2xH100-80G GPUs or AMD GPU MI325
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if is_rocm():
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# ROCm stage config optimized for MI325 GPU
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stage_configs = [str(Path(__file__).parent / "stage_configs" / "rocm" / "qwen3_omni_ci.yaml")]
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else:
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stage_configs = [str(Path(__file__).parent / "stage_configs" / "qwen3_omni_ci.yaml")]
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# Create parameter combinations for model and stage config
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test_params = [(model, stage_config) for model in models for stage_config in stage_configs]
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@@ -0,0 +1,98 @@
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# Stage config for running Qwen3-Omni-MoE with 3-stage architecture
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# Stage 0: Thinker (multimodal understanding + text generation)
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# Stage 1: Talker (text embeddings → 16-layer RVQ codec codes)
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# Stage 2: Code2Wav (8-layer RVQ codes → audio waveform)
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# The following config has been verified on 2x H100-80G GPUs.
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stage_args:
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- stage_id: 0
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runtime:
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devices: "0,1"
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max_batch_size: 5
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engine_args:
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model_stage: thinker
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model_arch: Qwen3OmniMoeForConditionalGeneration
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worker_cls: vllm_omni.worker.gpu_ar_worker.GPUARWorker
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scheduler_cls: vllm_omni.core.sched.omni_ar_scheduler.OmniARScheduler
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gpu_memory_utilization: 0.6
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enforce_eager: false
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trust_remote_code: true
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engine_output_type: latent # Output hidden states for talker
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distributed_executor_backend: "mp"
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enable_prefix_caching: false
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hf_config_name: thinker_config
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tensor_parallel_size: 2
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load_format: dummy
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final_output: true
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final_output_type: text
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is_comprehension: true
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default_sampling_params:
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temperature: 0.4
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top_p: 0.9
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top_k: 1
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max_tokens: 100
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seed: 42
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detokenize: True
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repetition_penalty: 1.05
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- stage_id: 1
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runtime:
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devices: "1"
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max_batch_size: 5
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engine_args:
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model_stage: talker
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model_arch: Qwen3OmniMoeForConditionalGeneration
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worker_cls: vllm_omni.worker.gpu_ar_worker.GPUARWorker
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scheduler_cls: vllm_omni.core.sched.omni_ar_scheduler.OmniARScheduler
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gpu_memory_utilization: 0.3
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enforce_eager: true
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trust_remote_code: true
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engine_output_type: latent # Output codec codes for code2wav
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# tensor_parallel_size: 2
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enable_prefix_caching: false
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distributed_executor_backend: "mp"
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hf_config_name: talker_config
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load_format: dummy
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engine_input_source: [0]
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custom_process_input_func: vllm_omni.model_executor.stage_input_processors.qwen3_omni.thinker2talker
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# final_output: true
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# final_output_type: text
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default_sampling_params:
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temperature: 0.9
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top_k: 50
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max_tokens: 100
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seed: 42
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detokenize: False
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repetition_penalty: 1.05
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stop_token_ids: [2150]
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- stage_id: 2
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runtime:
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devices: "0"
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max_batch_size: 1
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engine_args:
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model_stage: code2wav
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model_arch: Qwen3OmniMoeForConditionalGeneration
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worker_cls: vllm_omni.worker.gpu_generation_worker.GPUGenerationWorker
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scheduler_cls: vllm_omni.core.sched.omni_generation_scheduler.OmniGenerationScheduler
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enforce_eager: true
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trust_remote_code: true
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enable_prefix_caching: false
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engine_output_type: audio # Final output: audio waveform
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gpu_memory_utilization: 0.1
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distributed_executor_backend: "mp"
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max_num_batched_tokens: 1000000
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hf_config_name: thinker_config
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load_format: dummy
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engine_input_source: [1]
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custom_process_input_func: vllm_omni.model_executor.stage_input_processors.qwen3_omni.talker2code2wav
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final_output: true
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final_output_type: audio
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default_sampling_params:
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temperature: 0.0
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top_p: 1.0
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top_k: -1
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max_tokens: 200
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seed: 42
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detokenize: True
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repetition_penalty: 1.1
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@@ -20,12 +20,18 @@ import pytest
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from vllm.assets.video import VideoAsset
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from vllm.utils import get_open_port
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from vllm_omni.utils import is_rocm
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os.environ["VLLM_WORKER_MULTIPROC_METHOD"] = "spawn"
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models = ["Qwen/Qwen3-Omni-30B-A3B-Instruct"]
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# CI stage config for 2*H100-80G GPUs
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stage_configs = [str(Path(__file__).parent / "stage_configs" / "qwen3_omni_ci.yaml")]
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# CI stage config for 2xH100-80G GPUs or AMD GPU MI325
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if is_rocm():
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# ROCm stage config optimized for MI325 GPU
|
||||
stage_configs = [str(Path(__file__).parent / "stage_configs" / "rocm" / "qwen3_omni_ci.yaml")]
|
||||
else:
|
||||
stage_configs = [str(Path(__file__).parent / "stage_configs" / "qwen3_omni_ci.yaml")]
|
||||
|
||||
# Create parameter combinations for model and stage config
|
||||
test_params = [(model, stage_config) for model in models for stage_config in stage_configs]
|
||||
|
||||
Reference in new issue
Block a user