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ci: Migrate AMD workflows to new MI325 runners; temporarily disabled failed CI's to be added back (sgl-project#14226)
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6 files changed

+86
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.github/workflows/nightly-test-amd.yml

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@@ -19,7 +19,7 @@ jobs:
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if: github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request'
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strategy:
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matrix:
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runner: [linux-mi300-gpu-2, linux-mi325-gpu-2-nightly]
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runner: [linux-mi325-gpu-2]
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runs-on: ${{matrix.runner}}
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steps:
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- name: Checkout code

.github/workflows/pr-test-amd.yml

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@@ -58,7 +58,7 @@ jobs:
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strategy:
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fail-fast: false
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matrix:
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runner: [linux-mi300-gpu-1]
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runner: [linux-mi325-gpu-1]
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runs-on: ${{matrix.runner}}
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steps:
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- name: Checkout code
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strategy:
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fail-fast: false
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matrix:
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runner: [linux-mi300-gpu-1]
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runner: [linux-mi325-gpu-1]
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runs-on: ${{matrix.runner}}
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steps:
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- name: Checkout code
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strategy:
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fail-fast: false
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matrix:
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runner: [linux-mi300-gpu-1]
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runner: [linux-mi325-gpu-1]
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part: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
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runs-on: ${{matrix.runner}}
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steps:
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strategy:
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fail-fast: false
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matrix:
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runner: [linux-mi300-gpu-2]
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runner: [linux-mi325-gpu-2]
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part: [0, 1]
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runs-on: ${{matrix.runner}}
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steps:
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unit-test-backend-8-gpu-amd:
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needs: [check-changes, unit-test-backend-2-gpu-amd]
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if: always() && !failure() && !cancelled() &&
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# Temporarily disabled - uncomment when ready to re-enable
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if: false && always() && !failure() && !cancelled() &&
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((needs.check-changes.outputs.main_package == 'true') || (needs.check-changes.outputs.sgl_kernel == 'true'))
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env:
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RUNNER_LABELS: linux-mi300-gpu-8
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strategy:
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fail-fast: false
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matrix:
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runner: [linux-mi300-gpu-8]
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part: [0, 1, 2]
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part: [0, 1]
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runs-on: ${{matrix.runner}}
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steps:
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- name: Checkout code
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- name: Install dependencies
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run: bash scripts/ci/amd_ci_install_dependency.sh
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- name: Test RCCL multi-GPU communication
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timeout-minutes: 5
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run: |
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echo "Testing RCCL multi-GPU communication with debug info..."
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docker exec ci_sglang bash -c "cd /sglang-checkout && NCCL_DEBUG=INFO RCCL_DEBUG=INFO torchrun --nproc_per_node=8 scripts/ci/test_rccl_multi_gpu.py"
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- name: Run test
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timeout-minutes: 60
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run: |
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bash scripts/ci/amd_ci_exec.sh python3 run_suite.py --suite per-commit-8-gpu-amd --auto-partition-id ${{ matrix.part }} --auto-partition-size 3 --timeout-per-file 3600
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bash scripts/ci/amd_ci_exec.sh python3 run_suite.py --suite per-commit-8-gpu-amd --auto-partition-id ${{ matrix.part }} --auto-partition-size 2 --timeout-per-file 3600
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performance-test-1-gpu-part-1-amd:
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needs: [check-changes, stage-a-test-1-amd]
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strategy:
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fail-fast: false
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matrix:
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runner: [linux-mi300-gpu-1]
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runner: [linux-mi325-gpu-1]
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runs-on: ${{matrix.runner}}
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steps:
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- name: Checkout code
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strategy:
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fail-fast: false
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matrix:
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runner: [linux-mi300-gpu-1]
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runner: [linux-mi325-gpu-1]
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runs-on: ${{matrix.runner}}
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steps:
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- name: Checkout code
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strategy:
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fail-fast: false
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matrix:
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runner: [linux-mi300-gpu-2]
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runner: [linux-mi325-gpu-2]
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runs-on: ${{matrix.runner}}
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steps:
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- name: Checkout code
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strategy:
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fail-fast: false
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matrix:
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runner: [linux-mi300-gpu-1]
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runner: [linux-mi325-gpu-1]
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runs-on: ${{matrix.runner}}
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steps:
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- name: Checkout code
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strategy:
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fail-fast: false
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matrix:
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runner: [linux-mi300-gpu-2]
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runner: [linux-mi325-gpu-2]
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runs-on: ${{matrix.runner}}
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steps:
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- name: Checkout code
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- name: Evaluate accuracy (TP=2)
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timeout-minutes: 30
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run: |
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bash scripts/ci/amd_ci_exec.sh -e SGLANG_USE_AITER=0 python3 test_moe_eval_accuracy_large.py
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bash scripts/ci/amd_ci_exec.sh -e SGLANG_USE_AITER=0 -e HF_HUB_ENABLE_HF_TRANSFER=0 python3 test_moe_eval_accuracy_large.py
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pr-test-amd-finish:
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needs:
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stage-a-test-1-amd,
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unit-test-backend-1-gpu-amd,
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unit-test-backend-2-gpu-amd,
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unit-test-backend-8-gpu-amd,
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# unit-test-backend-8-gpu-amd, # Temporarily disabled
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performance-test-1-gpu-part-1-amd,
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performance-test-1-gpu-part-2-amd,
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performance-test-2-gpu-amd,

.gitignore

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@@ -247,3 +247,4 @@ lmms-eval
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**/.claude/
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**/.serena/
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ctags/

scripts/ci/amd_ci_start_container.sh

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@@ -151,7 +151,7 @@ echo "Launching container: ci_sglang"
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docker run -dt --user root --device=/dev/kfd ${DEVICE_FLAG} \
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-v "${GITHUB_WORKSPACE:-$PWD}:/sglang-checkout" \
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$CACHE_VOLUME \
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--ipc=host --group-add video \
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--group-add video \
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--shm-size 32g \
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--cap-add=SYS_PTRACE \
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-e HF_TOKEN="${HF_TOKEN:-}" \

scripts/ci/test_rccl_multi_gpu.py

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#!/usr/bin/env python3
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"""
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Simple RCCL test for multi-GPU communication.
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This test verifies that RCCL can initialize and communicate across multiple GPUs.
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"""
6+
import os
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import sys
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import torch
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import torch.distributed as dist
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def test_rccl_allreduce():
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"""Test basic RCCL allreduce operation across all GPUs."""
15+
if not torch.cuda.is_available():
16+
print("CUDA not available, skipping test")
17+
sys.exit(1)
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# Initialize process group with NCCL (RCCL on AMD)
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dist.init_process_group(backend="nccl")
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rank = dist.get_rank()
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world_size = dist.get_world_size()
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print(f"[Rank {rank}/{world_size}] Initialized successfully")
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# Set device
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device = torch.device(f"cuda:{rank}")
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torch.cuda.set_device(device)
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print(f"[Rank {rank}] Device: {torch.cuda.get_device_name(device)}")
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print(
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f"[Rank {rank}] Device memory: {torch.cuda.get_device_properties(device).total_memory / 1e9:.2f} GB"
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)
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# Create a tensor and perform allreduce
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tensor = torch.ones(1000, device=device) * rank
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print(f"[Rank {rank}] Before allreduce: tensor sum = {tensor.sum().item()}")
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dist.all_reduce(tensor, op=dist.ReduceOp.SUM)
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expected_sum = sum(range(world_size)) * 1000
43+
actual_sum = tensor.sum().item()
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print(
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f"[Rank {rank}] After allreduce: tensor sum = {actual_sum}, expected = {expected_sum}"
47+
)
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if abs(actual_sum - expected_sum) < 0.1:
50+
print(f"[Rank {rank}] ✓ RCCL allreduce test PASSED")
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dist.destroy_process_group()
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sys.exit(0)
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else:
54+
print(f"[Rank {rank}] ✗ RCCL allreduce test FAILED")
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dist.destroy_process_group()
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sys.exit(1)
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if __name__ == "__main__":
60+
test_rccl_allreduce()

test/srt/nightly/test_gsm8k_eval_amd.py

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failing_models = {
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"neuralmagic/gemma-2-2b-it-FP8",
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"neuralmagic/DeepSeek-Coder-V2-Lite-Instruct-FP8", # RuntimeError: This GEMM is not supported!
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"zai-org/GLM-4.5-Air-FP8", # TypeError: cannot unpack non-iterable ForwardMetadata object
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}
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