diff --git a/.github/workflows/nightly-test-amd-rocm720.yml b/.github/workflows/nightly-test-amd-rocm720.yml index 8e905eaf0..dbe0ff7be 100644 --- a/.github/workflows/nightly-test-amd-rocm720.yml +++ b/.github/workflows/nightly-test-amd-rocm720.yml @@ -45,7 +45,7 @@ on: - nightly-8-gpu-qwen35-rocm720 - nightly-8-gpu-glm5-rocm720 - nightly-8-gpu-glm51-rocm720 - - nightly-8-gpu-minimax-m25-rocm720 + - nightly-8-gpu-minimax-m27-rocm720 - nightly-1-gpu-zimage-turbo-rocm720 - nightly-test-1-gpu-mi35x-rocm720 - nightly-accuracy-8-gpu-mi35x-rocm720 @@ -63,7 +63,6 @@ on: - nightly-8-gpu-mi35x-qwen35-rocm720 - nightly-8-gpu-mi35x-glm5-rocm720 - nightly-8-gpu-mi35x-glm51-rocm720 - - nightly-8-gpu-mi35x-minimax-m25-rocm720 job_filter: description: 'Or type comma-separated job names (overrides dropdown if non-empty)' required: false @@ -754,9 +753,9 @@ jobs: echo "$(> $GITHUB_STEP_SUMMARY || true exit ${TEST_EXIT_CODE:-0} - # 8-GPU MiniMax-M2.5 (Accuracy + Performance combined) ROCm 7.2 - nightly-8-gpu-minimax-m25-rocm720: - if: (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') && (!(inputs.job_filter || inputs.job_select) || (inputs.job_filter || inputs.job_select) == 'all' || contains(format(',{0},', inputs.job_filter || inputs.job_select), ',nightly-8-gpu-minimax-m25-rocm720,')) + # 8-GPU MiniMax-M2.7 (Accuracy + Performance combined, replaces M2.5) ROCm 7.2 + nightly-8-gpu-minimax-m27-rocm720: + if: (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') && (!(inputs.job_filter || inputs.job_select) || (inputs.job_filter || inputs.job_select) == 'all' || contains(format(',{0},', inputs.job_filter || inputs.job_select), ',nightly-8-gpu-minimax-m27-rocm720,')) runs-on: linux-mi325-8gpu-sglang steps: - name: Checkout code @@ -774,18 +773,18 @@ jobs: - name: Install dependencies run: bash scripts/ci/amd/amd_ci_install_dependency.sh --skip-test-time-deps - - name: Accuracy Test ROCm 7.2 (8-GPU MiniMax-M2.5) + - name: Accuracy Test ROCm 7.2 (8-GPU MiniMax-M2.7) timeout-minutes: 120 run: | > github_summary.md # Clear summary file bash scripts/ci/amd/amd_ci_exec.sh -w /sglang-checkout/test \ -e SGLANG_USE_AITER=1 \ -e GITHUB_STEP_SUMMARY="/sglang-checkout/github_summary.md" \ - python3 run_suite.py --hw amd --suite nightly-amd-accuracy-8-gpu-minimax-m25 --nightly --timeout-per-file 3600 ${{ inputs.continue_on_error && '--continue-on-error' || '' }} || TEST_EXIT_CODE=$? + python3 run_suite.py --hw amd --suite nightly-amd-accuracy-8-gpu-minimax-m27 --nightly --timeout-per-file 3600 ${{ inputs.continue_on_error && '--continue-on-error' || '' }} || TEST_EXIT_CODE=$? echo "$(> $GITHUB_STEP_SUMMARY || true exit ${TEST_EXIT_CODE:-0} - - name: Performance Test ROCm 7.2 (8-GPU MiniMax-M2.5) + - name: Performance Test ROCm 7.2 (8-GPU MiniMax-M2.7) timeout-minutes: 120 continue-on-error: true # Perf test failure doesn't fail the job if accuracy passed run: | @@ -793,7 +792,7 @@ jobs: bash scripts/ci/amd/amd_ci_exec.sh -w /sglang-checkout/test \ -e SGLANG_USE_AITER=1 \ -e GITHUB_STEP_SUMMARY="/sglang-checkout/github_summary.md" \ - python3 run_suite.py --hw amd --suite nightly-perf-8-gpu-minimax-m25 --nightly --timeout-per-file 5400 ${{ inputs.continue_on_error && '--continue-on-error' || '' }} || TEST_EXIT_CODE=$? + python3 run_suite.py --hw amd --suite nightly-perf-8-gpu-minimax-m27 --nightly --timeout-per-file 5400 ${{ inputs.continue_on_error && '--continue-on-error' || '' }} || TEST_EXIT_CODE=$? echo "$(> $GITHUB_STEP_SUMMARY || true exit ${TEST_EXIT_CODE:-0} @@ -1411,51 +1410,6 @@ jobs: echo "$(> $GITHUB_STEP_SUMMARY || true exit ${TEST_EXIT_CODE:-0} - # MI35x 8-GPU MiniMax-M2.5 (Accuracy + Performance combined) ROCm 7.2 - nightly-8-gpu-mi35x-minimax-m25-rocm720: - if: (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') && (!(inputs.job_filter || inputs.job_select) || (inputs.job_filter || inputs.job_select) == 'all' || contains(format(',{0},', inputs.job_filter || inputs.job_select), ',nightly-8-gpu-mi35x-minimax-m25-rocm720,')) - runs-on: linux-mi35x-gpu-8 - steps: - - name: Checkout code - uses: actions/checkout@v4 - with: - ref: ${{ inputs.ref || github.ref }} - - - name: Setup docker (ROCm 7.2) - run: | - touch github_summary.md - bash scripts/ci/amd/amd_ci_start_container.sh --rocm-version rocm720 - env: - GITHUB_WORKSPACE: ${{ github.workspace }} - - - name: Install dependencies - run: | - bash scripts/ci/amd/amd_ci_install_dependency.sh --skip-test-time-deps - bash scripts/ci/amd/amd_ci_exec.sh pip install tabulate - - - name: Accuracy Test MI35x ROCm 7.2 (8-GPU MiniMax-M2.5) - timeout-minutes: 120 - run: | - > github_summary.md # Clear summary file - bash scripts/ci/amd/amd_ci_exec.sh -w /sglang-checkout/test \ - -e SGLANG_USE_AITER=1 \ - -e GITHUB_STEP_SUMMARY="/sglang-checkout/github_summary.md" \ - python3 run_suite.py --hw amd --suite nightly-amd-8-gpu-mi35x-minimax-m25 --nightly --timeout-per-file 3600 ${{ inputs.continue_on_error && '--continue-on-error' || '' }} || TEST_EXIT_CODE=$? - echo "$(> $GITHUB_STEP_SUMMARY || true - exit ${TEST_EXIT_CODE:-0} - - - name: Performance Test MI35x ROCm 7.2 (8-GPU MiniMax-M2.5) - timeout-minutes: 120 - continue-on-error: true # Perf test failure doesn't fail the job if accuracy passed - run: | - > github_summary.md # Clear summary file - bash scripts/ci/amd/amd_ci_exec.sh -w /sglang-checkout/test \ - -e SGLANG_USE_AITER=1 \ - -e GITHUB_STEP_SUMMARY="/sglang-checkout/github_summary.md" \ - python3 run_suite.py --hw amd --suite nightly-perf-8-gpu-mi35x-minimax-m25 --nightly --timeout-per-file 5400 ${{ inputs.continue_on_error && '--continue-on-error' || '' }} || TEST_EXIT_CODE=$? - echo "$(> $GITHUB_STEP_SUMMARY || true - exit ${TEST_EXIT_CODE:-0} - # MI35x 8-GPU DeepSeek-V3.2 Performance Test (MTP) ROCm 7.2 nightly-perf-8-gpu-mi35x-deepseek-v32-mtp-rocm720: if: (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') && (!(inputs.job_filter || inputs.job_select) || (inputs.job_filter || inputs.job_select) == 'all' || contains(format(',{0},', inputs.job_filter || inputs.job_select), ',nightly-perf-8-gpu-mi35x-deepseek-v32-mtp-rocm720,')) @@ -1515,7 +1469,7 @@ jobs: - nightly-8-gpu-qwen35-rocm720 - nightly-8-gpu-glm5-rocm720 - nightly-8-gpu-glm51-rocm720 - - nightly-8-gpu-minimax-m25-rocm720 + - nightly-8-gpu-minimax-m27-rocm720 # MI30x ROCm 7.2 Diffusion Tests - nightly-1-gpu-zimage-turbo-rocm720 # MI35x ROCm 7.2 jobs @@ -1535,7 +1489,6 @@ jobs: - nightly-8-gpu-mi35x-qwen35-rocm720 - nightly-8-gpu-mi35x-glm5-rocm720 - nightly-8-gpu-mi35x-glm51-rocm720 - - nightly-8-gpu-mi35x-minimax-m25-rocm720 runs-on: ubuntu-latest steps: - name: Check if any job failed diff --git a/.github/workflows/nightly-test-amd.yml b/.github/workflows/nightly-test-amd.yml index b5f3b2f73..cc93938be 100644 --- a/.github/workflows/nightly-test-amd.yml +++ b/.github/workflows/nightly-test-amd.yml @@ -46,7 +46,7 @@ on: - nightly-8-gpu-glm5 - nightly-8-gpu-glm51 - nightly-8-gpu-glm51-mxfp4 - - nightly-8-gpu-minimax-m25 + - nightly-8-gpu-minimax-m27 - nightly-1-gpu-zimage-turbo - nightly-test-1-gpu-mi35x - nightly-accuracy-8-gpu-mi35x @@ -65,7 +65,6 @@ on: - nightly-8-gpu-mi35x-glm5 - nightly-8-gpu-mi35x-glm51 - nightly-8-gpu-mi35x-glm51-mxfp4 - - nightly-8-gpu-mi35x-minimax-m25 job_filter: description: 'Or type comma-separated job names (overrides dropdown if non-empty)' required: false @@ -760,9 +759,9 @@ jobs: echo "$(> $GITHUB_STEP_SUMMARY || true exit ${TEST_EXIT_CODE:-0} - # 8-GPU MiniMax-M2.5 (Accuracy + Performance combined) - nightly-8-gpu-minimax-m25: - if: (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') && (!(inputs.job_filter || inputs.job_select) || (inputs.job_filter || inputs.job_select) == 'all' || contains(format(',{0},', inputs.job_filter || inputs.job_select), ',nightly-8-gpu-minimax-m25,')) + # 8-GPU MiniMax-M2.7 (Accuracy + Performance combined, replaces M2.5) + nightly-8-gpu-minimax-m27: + if: (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') && (!(inputs.job_filter || inputs.job_select) || (inputs.job_filter || inputs.job_select) == 'all' || contains(format(',{0},', inputs.job_filter || inputs.job_select), ',nightly-8-gpu-minimax-m27,')) runs-on: linux-mi325-8gpu-sglang steps: - name: Checkout code @@ -780,18 +779,18 @@ jobs: - name: Install dependencies run: bash scripts/ci/amd/amd_ci_install_dependency.sh - - name: Accuracy Test (8-GPU MiniMax-M2.5) + - name: Accuracy Test (8-GPU MiniMax-M2.7) timeout-minutes: 120 run: | > github_summary.md # Clear summary file bash scripts/ci/amd/amd_ci_exec.sh -w /sglang-checkout/test \ -e SGLANG_USE_AITER=1 \ -e GITHUB_STEP_SUMMARY="/sglang-checkout/github_summary.md" \ - python3 run_suite.py --hw amd --suite nightly-amd-accuracy-8-gpu-minimax-m25 --nightly --timeout-per-file 3600 ${{ inputs.continue_on_error && '--continue-on-error' || '' }} || TEST_EXIT_CODE=$? + python3 run_suite.py --hw amd --suite nightly-amd-accuracy-8-gpu-minimax-m27 --nightly --timeout-per-file 3600 ${{ inputs.continue_on_error && '--continue-on-error' || '' }} || TEST_EXIT_CODE=$? echo "$(> $GITHUB_STEP_SUMMARY || true exit ${TEST_EXIT_CODE:-0} - - name: Performance Test (8-GPU MiniMax-M2.5) + - name: Performance Test (8-GPU MiniMax-M2.7) timeout-minutes: 120 continue-on-error: true # Perf test failure doesn't fail the job if accuracy passed run: | @@ -799,7 +798,7 @@ jobs: bash scripts/ci/amd/amd_ci_exec.sh -w /sglang-checkout/test \ -e SGLANG_USE_AITER=1 \ -e GITHUB_STEP_SUMMARY="/sglang-checkout/github_summary.md" \ - python3 run_suite.py --hw amd --suite nightly-perf-8-gpu-minimax-m25 --nightly --timeout-per-file 5400 ${{ inputs.continue_on_error && '--continue-on-error' || '' }} || TEST_EXIT_CODE=$? + python3 run_suite.py --hw amd --suite nightly-perf-8-gpu-minimax-m27 --nightly --timeout-per-file 5400 ${{ inputs.continue_on_error && '--continue-on-error' || '' }} || TEST_EXIT_CODE=$? echo "$(> $GITHUB_STEP_SUMMARY || true exit ${TEST_EXIT_CODE:-0} @@ -1420,51 +1419,6 @@ jobs: echo "$(> $GITHUB_STEP_SUMMARY || true exit ${TEST_EXIT_CODE:-0} - # MI35x 8-GPU MiniMax-M2.5 (Accuracy + Performance combined) - nightly-8-gpu-mi35x-minimax-m25: - if: (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') && (!(inputs.job_filter || inputs.job_select) || (inputs.job_filter || inputs.job_select) == 'all' || contains(format(',{0},', inputs.job_filter || inputs.job_select), ',nightly-8-gpu-mi35x-minimax-m25,')) - runs-on: linux-mi35x-gpu-8 - steps: - - name: Checkout code - uses: actions/checkout@v4 - with: - ref: ${{ inputs.ref || github.ref }} - - - name: Setup docker - run: | - touch github_summary.md - bash scripts/ci/amd/amd_ci_start_container.sh - env: - GITHUB_WORKSPACE: ${{ github.workspace }} - - - name: Install dependencies - run: | - bash scripts/ci/amd/amd_ci_install_dependency.sh - bash scripts/ci/amd/amd_ci_exec.sh pip install tabulate - - - name: Accuracy Test MI35x (8-GPU MiniMax-M2.5) - timeout-minutes: 120 - run: | - > github_summary.md # Clear summary file - bash scripts/ci/amd/amd_ci_exec.sh -w /sglang-checkout/test \ - -e SGLANG_USE_AITER=1 \ - -e GITHUB_STEP_SUMMARY="/sglang-checkout/github_summary.md" \ - python3 run_suite.py --hw amd --suite nightly-amd-8-gpu-mi35x-minimax-m25 --nightly --timeout-per-file 3600 ${{ inputs.continue_on_error && '--continue-on-error' || '' }} || TEST_EXIT_CODE=$? - echo "$(> $GITHUB_STEP_SUMMARY || true - exit ${TEST_EXIT_CODE:-0} - - - name: Performance Test MI35x (8-GPU MiniMax-M2.5) - timeout-minutes: 120 - continue-on-error: true # Perf test failure doesn't fail the job if accuracy passed - run: | - > github_summary.md # Clear summary file - bash scripts/ci/amd/amd_ci_exec.sh -w /sglang-checkout/test \ - -e SGLANG_USE_AITER=1 \ - -e GITHUB_STEP_SUMMARY="/sglang-checkout/github_summary.md" \ - python3 run_suite.py --hw amd --suite nightly-perf-8-gpu-mi35x-minimax-m25 --nightly --timeout-per-file 5400 ${{ inputs.continue_on_error && '--continue-on-error' || '' }} || TEST_EXIT_CODE=$? - echo "$(> $GITHUB_STEP_SUMMARY || true - exit ${TEST_EXIT_CODE:-0} - # MI35x 8-GPU DeepSeek-V3.2 Performance Test (MTP) nightly-perf-8-gpu-mi35x-deepseek-v32-mtp: if: (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') && (!(inputs.job_filter || inputs.job_select) || (inputs.job_filter || inputs.job_select) == 'all' || contains(format(',{0},', inputs.job_filter || inputs.job_select), ',nightly-perf-8-gpu-mi35x-deepseek-v32-mtp,')) @@ -1524,7 +1478,7 @@ jobs: - nightly-8-gpu-qwen35 - nightly-8-gpu-glm5 - nightly-8-gpu-glm51 - - nightly-8-gpu-minimax-m25 + - nightly-8-gpu-minimax-m27 # MI30x Diffusion Tests - nightly-1-gpu-zimage-turbo # MI35x jobs @@ -1542,7 +1496,6 @@ jobs: - nightly-8-gpu-mi35x-qwen35 - nightly-8-gpu-mi35x-glm5 - nightly-8-gpu-mi35x-glm51 - - nightly-8-gpu-mi35x-minimax-m25 # MI35x perf jobs excluded from check - perf failures don't block CI # - nightly-perf-8-gpu-mi35x-deepseek-v32-basic # - nightly-perf-8-gpu-mi35x-deepseek-v32-mtp diff --git a/python/sglang/srt/models/minimax_m2.py b/python/sglang/srt/models/minimax_m2.py index eea60e586..b99c2471b 100644 --- a/python/sglang/srt/models/minimax_m2.py +++ b/python/sglang/srt/models/minimax_m2.py @@ -33,7 +33,6 @@ from sglang.jit_kernel.all_reduce import ( from sglang.kernel_api_logging import debug_kernel_api from sglang.srt.batch_overlap.two_batch_overlap import model_forward_maybe_tbo from sglang.srt.distributed import ( - get_bool_env_var, get_moe_expert_parallel_world_size, get_pp_group, get_tensor_model_parallel_world_size, @@ -81,9 +80,16 @@ from sglang.srt.model_loader.weight_utils import ( maybe_remap_kv_scale_name, ) from sglang.srt.server_args import get_global_server_args + +# get_bool_env_var is defined in sglang.srt.utils.common, not sglang.srt.distributed. +# Importing from the wrong module causes this file to fail import, which prevents the +# native MiniMaxM2ForCausalLM from registering in ModelRegistry. The fallback to the +# transformers wrapper then crashes on config.rope_parameters (transformers v5 issue). +# Other files (custom_all_reduce.py, hf_transformers_utils.py) also use sglang.srt.utils. from sglang.srt.utils import ( BumpAllocator, add_prefix, + get_bool_env_var, get_compiler_backend, is_cuda, is_non_idle_and_non_empty, diff --git a/test/registered/amd/accuracy/mi30x/test_minimax_m27_eval_amd.py b/test/registered/amd/accuracy/mi30x/test_minimax_m27_eval_amd.py new file mode 100644 index 000000000..b272986ac --- /dev/null +++ b/test/registered/amd/accuracy/mi30x/test_minimax_m27_eval_amd.py @@ -0,0 +1,245 @@ +"""AMD MiniMax-M2.7 GSM8K Completion Evaluation Test (8-GPU) + +Tests MiniMax-M2.7 with TP=8 + EP=8 configuration using few-shot completion +benchmark on MI325/MI300X. + +Registry: nightly-amd-accuracy-8-gpu-minimax-m27 suite +""" + +import ast +import os +import re +import time +import unittest +from dataclasses import dataclass +from typing import List, Optional, Tuple + +import numpy as np + +from sglang.srt.utils import kill_process_tree +from sglang.test.ci.ci_register import register_amd_ci +from sglang.test.test_utils import ( + DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH, + DEFAULT_URL_FOR_TEST, + is_in_ci, + popen_launch_server, + write_github_step_summary, +) +from sglang.utils import download_and_cache_file, read_jsonl + +register_amd_ci( + est_time=3600, + suite="nightly-amd-accuracy-8-gpu-minimax-m27", + nightly=True, +) + +INVALID = -9999999 + + +@dataclass +class ModelConfig: + """Configuration for a model to test.""" + + model_path: str + tp_size: int = 8 + accuracy_threshold: float = 0.50 + other_args: Optional[List[str]] = None + env_vars: Optional[dict] = None + timeout: Optional[int] = None + variant: Optional[str] = None + + def __post_init__(self): + if self.other_args is None: + self.other_args = [] + if self.env_vars is None: + self.env_vars = {} + + def get_display_name(self) -> str: + if self.variant: + return f"{self.model_path} ({self.variant})" + return self.model_path + + +MINIMAX_M27_MODELS = [ + ModelConfig( + model_path="MiniMaxAI/MiniMax-M2.7", + tp_size=8, + accuracy_threshold=0.93, + timeout=3600, + variant="TP8+EP8", + other_args=[ + "--ep-size", + "8", + "--trust-remote-code", + "--attention-backend", + "aiter", + "--mem-fraction-static", + "0.85", + "--model-loader-extra-config", + '{"enable_multithread_load": true}', + "--watchdog-timeout", + "1200", + ], + env_vars={"SGLANG_USE_AITER": "1"}, + ), +] + + +def get_one_example(lines, i, include_answer): + """Format a single GSM8K example.""" + ret = "Question: " + lines[i]["question"] + "\nAnswer:" + if include_answer: + ret += " " + lines[i]["answer"] + return ret + + +def get_few_shot_examples(lines, k): + """Get k few-shot examples for prompting.""" + ret = "" + for i in range(k): + ret += get_one_example(lines, i, True) + "\n\n" + return ret + + +def get_answer_value(answer_str): + """Extract numerical answer from response.""" + answer_str = answer_str.replace(",", "") + numbers = re.findall(r"\d+", answer_str) + if len(numbers) < 1: + return INVALID + try: + return ast.literal_eval(numbers[-1]) + except SyntaxError: + return INVALID + + +def run_gsm8k_benchmark( + base_url: str, + num_questions: int = 200, + num_shots: int = 5, + parallel: int = 64, +) -> Tuple[float, float, float]: + """Run GSM8K few-shot completion benchmark.""" + import sglang as sgl + from sglang.lang.backend.runtime_endpoint import RuntimeEndpoint + + url = "https://raw.githubusercontent.com/openai/grade-school-math/master/grade_school_math/data/test.jsonl" + data_path = download_and_cache_file(url) + lines = list(read_jsonl(data_path)) + + few_shot_examples = get_few_shot_examples(lines, num_shots) + + questions = [] + labels = [] + for i in range(len(lines[:num_questions])): + questions.append(get_one_example(lines, i, False)) + labels.append(get_answer_value(lines[i]["answer"])) + assert all(l != INVALID for l in labels) + arguments = [{"question": q} for q in questions] + + @sgl.function + def few_shot_gsm8k(s, question): + s += few_shot_examples + question + s += sgl.gen( + "answer", max_tokens=512, stop=["Question", "Assistant:", "<|separator|>"] + ) + + backend = RuntimeEndpoint(base_url) + sgl.set_default_backend(backend) + + tic = time.perf_counter() + states = few_shot_gsm8k.run_batch( + arguments, temperature=0, num_threads=parallel, progress_bar=True + ) + latency = time.perf_counter() - tic + + preds = [get_answer_value(states[i]["answer"]) for i in range(len(states))] + acc = np.mean(np.array(preds) == np.array(labels)) + invalid = np.mean(np.array(preds) == INVALID) + + return float(acc), float(invalid), float(latency) + + +class TestMiniMaxM27EvalAMD(unittest.TestCase): + """MiniMax-M2.7 GSM8K Completion Evaluation Test for AMD MI325/MI300X.""" + + @classmethod + def setUpClass(cls): + cls.models = MINIMAX_M27_MODELS + cls.base_url = DEFAULT_URL_FOR_TEST + cls.num_questions = int(os.environ.get("GSM8K_NUM_QUESTIONS", "200")) + + def test_minimax_m27_accuracy(self): + """Test MiniMax-M2.7 with GSM8K completion benchmark.""" + all_results = [] + summary = "### MiniMax-M2.7 Models (MI325)\n\n" + summary += "| Model | Variant | TP | Accuracy | Threshold | Status |\n" + summary += "| ----- | ------- | -- | -------- | --------- | ------ |\n" + + for config in self.models: + display_name = config.get_display_name() + with self.subTest(model=display_name): + print(f"\n{'='*60}") + print(f"Testing: {display_name}") + print(f"{'='*60}") + + env = os.environ.copy() + for key, value in config.env_vars.items(): + env[key] = value + + other_args = list(config.other_args) + other_args.extend(["--tp", str(config.tp_size)]) + timeout = config.timeout or DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH + + try: + process = popen_launch_server( + model=config.model_path, + base_url=self.base_url, + timeout=timeout, + other_args=other_args, + env=env, + ) + + try: + acc, invalid, latency = run_gsm8k_benchmark( + self.base_url, num_questions=self.num_questions + ) + passed = acc >= config.accuracy_threshold + status = "PASS" if passed else "FAIL" + print( + f" accuracy={acc:.3f} threshold={config.accuracy_threshold} {status}" + ) + + all_results.append( + { + "model": display_name, + "accuracy": acc, + "passed": passed, + } + ) + summary += f"| {config.model_path} | {config.variant or 'N/A'} | {config.tp_size} | {acc:.3f} | {config.accuracy_threshold} | {status} |\n" + + finally: + kill_process_tree(process.pid) + + except Exception as e: + summary += f"| {config.model_path} | {config.variant or 'N/A'} | {config.tp_size} | N/A | {config.accuracy_threshold} | ERROR |\n" + all_results.append( + { + "model": display_name, + "accuracy": None, + "passed": False, + "error": str(e), + } + ) + + if is_in_ci(): + write_github_step_summary(summary) + + failed = [r for r in all_results if not r["passed"]] + if failed: + raise AssertionError(f"Failed models: {[r['model'] for r in failed]}") + + +if __name__ == "__main__": + unittest.main() diff --git a/test/registered/amd/accuracy/mi35x/test_minimax_m27_eval_mi35x.py b/test/registered/amd/accuracy/mi35x/test_minimax_m27_eval_mi35x.py new file mode 100644 index 000000000..68ed39754 --- /dev/null +++ b/test/registered/amd/accuracy/mi35x/test_minimax_m27_eval_mi35x.py @@ -0,0 +1,249 @@ +"""MI35x MiniMax-M2.7 GSM8K Completion Evaluation Test (8-GPU) + +Tests MiniMax-M2.7 with TP=8 + EP=8 configuration using few-shot completion +benchmark on MI35x. + +Registry: nightly-amd-8-gpu-mi35x-minimax-m27 suite +""" + +import ast +import os + +os.environ.setdefault("HF_HOME", "/data2/models/huggingface") +os.environ.setdefault("HF_HUB_CACHE", "/data2/models/huggingface/hub") + +import re +import time +import unittest +from dataclasses import dataclass +from typing import List, Optional, Tuple + +import numpy as np + +from sglang.srt.utils import kill_process_tree +from sglang.test.ci.ci_register import register_amd_ci +from sglang.test.test_utils import ( + DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH, + DEFAULT_URL_FOR_TEST, + is_in_ci, + popen_launch_server, + write_github_step_summary, +) +from sglang.utils import download_and_cache_file, read_jsonl + +register_amd_ci( + est_time=5400, + suite="nightly-amd-8-gpu-mi35x-minimax-m27", + nightly=True, +) + +INVALID = -9999999 + + +@dataclass +class ModelConfig: + """Configuration for a model to test.""" + + model_path: str + tp_size: int = 8 + accuracy_threshold: float = 0.50 + other_args: Optional[List[str]] = None + env_vars: Optional[dict] = None + timeout: Optional[int] = None + variant: Optional[str] = None + + def __post_init__(self): + if self.other_args is None: + self.other_args = [] + if self.env_vars is None: + self.env_vars = {} + + def get_display_name(self) -> str: + if self.variant: + return f"{self.model_path} ({self.variant})" + return self.model_path + + +MI35X_MINIMAX_M27_MODELS = [ + ModelConfig( + model_path="MiniMaxAI/MiniMax-M2.7", + tp_size=8, + accuracy_threshold=0.93, + timeout=5400, + variant="TP8+EP8", + other_args=[ + "--ep-size", + "8", + "--trust-remote-code", + "--attention-backend", + "aiter", + "--mem-fraction-static", + "0.85", + "--model-loader-extra-config", + '{"enable_multithread_load": true}', + "--watchdog-timeout", + "1200", + ], + env_vars={"SGLANG_USE_AITER": "1"}, + ), +] + + +def get_one_example(lines, i, include_answer): + """Format a single GSM8K example.""" + ret = "Question: " + lines[i]["question"] + "\nAnswer:" + if include_answer: + ret += " " + lines[i]["answer"] + return ret + + +def get_few_shot_examples(lines, k): + """Get k few-shot examples for prompting.""" + ret = "" + for i in range(k): + ret += get_one_example(lines, i, True) + "\n\n" + return ret + + +def get_answer_value(answer_str): + """Extract numerical answer from response.""" + answer_str = answer_str.replace(",", "") + numbers = re.findall(r"\d+", answer_str) + if len(numbers) < 1: + return INVALID + try: + return ast.literal_eval(numbers[-1]) + except SyntaxError: + return INVALID + + +def run_gsm8k_benchmark( + base_url: str, + num_questions: int = 200, + num_shots: int = 5, + parallel: int = 64, +) -> Tuple[float, float, float]: + """Run GSM8K few-shot completion benchmark.""" + import sglang as sgl + from sglang.lang.backend.runtime_endpoint import RuntimeEndpoint + + url = "https://raw.githubusercontent.com/openai/grade-school-math/master/grade_school_math/data/test.jsonl" + data_path = download_and_cache_file(url) + lines = list(read_jsonl(data_path)) + + few_shot_examples = get_few_shot_examples(lines, num_shots) + + questions = [] + labels = [] + for i in range(len(lines[:num_questions])): + questions.append(get_one_example(lines, i, False)) + labels.append(get_answer_value(lines[i]["answer"])) + assert all(l != INVALID for l in labels) + arguments = [{"question": q} for q in questions] + + @sgl.function + def few_shot_gsm8k(s, question): + s += few_shot_examples + question + s += sgl.gen( + "answer", max_tokens=512, stop=["Question", "Assistant:", "<|separator|>"] + ) + + backend = RuntimeEndpoint(base_url) + sgl.set_default_backend(backend) + + tic = time.perf_counter() + states = few_shot_gsm8k.run_batch( + arguments, temperature=0, num_threads=parallel, progress_bar=True + ) + latency = time.perf_counter() - tic + + preds = [get_answer_value(states[i]["answer"]) for i in range(len(states))] + acc = np.mean(np.array(preds) == np.array(labels)) + invalid = np.mean(np.array(preds) == INVALID) + + return float(acc), float(invalid), float(latency) + + +class TestMiniMaxM27EvalMI35x(unittest.TestCase): + """MiniMax-M2.7 GSM8K Completion Evaluation Test for AMD MI35x.""" + + @classmethod + def setUpClass(cls): + cls.models = MI35X_MINIMAX_M27_MODELS + cls.base_url = DEFAULT_URL_FOR_TEST + cls.num_questions = int(os.environ.get("GSM8K_NUM_QUESTIONS", "200")) + + def test_minimax_m27_accuracy(self): + """Test MiniMax-M2.7 with GSM8K completion benchmark.""" + all_results = [] + summary = "### MiniMax-M2.7 Models (MI35x)\n\n" + summary += "| Model | Variant | TP | Accuracy | Threshold | Status |\n" + summary += "| ----- | ------- | -- | -------- | --------- | ------ |\n" + + for config in self.models: + display_name = config.get_display_name() + with self.subTest(model=display_name): + print(f"\n{'='*60}") + print(f"Testing: {display_name}") + print(f"{'='*60}") + + env = os.environ.copy() + for key, value in config.env_vars.items(): + env[key] = value + + other_args = list(config.other_args) + other_args.extend(["--tp", str(config.tp_size)]) + timeout = config.timeout or DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH + + try: + process = popen_launch_server( + model=config.model_path, + base_url=self.base_url, + timeout=timeout, + other_args=other_args, + env=env, + ) + + try: + acc, invalid, latency = run_gsm8k_benchmark( + self.base_url, num_questions=self.num_questions + ) + passed = acc >= config.accuracy_threshold + status = "PASS" if passed else "FAIL" + print( + f" accuracy={acc:.3f} threshold={config.accuracy_threshold} {status}" + ) + + all_results.append( + { + "model": display_name, + "accuracy": acc, + "passed": passed, + } + ) + summary += f"| {config.model_path} | {config.variant or 'N/A'} | {config.tp_size} | {acc:.3f} | {config.accuracy_threshold} | {status} |\n" + + finally: + kill_process_tree(process.pid) + + except Exception as e: + summary += f"| {config.model_path} | {config.variant or 'N/A'} | {config.tp_size} | N/A | {config.accuracy_threshold} | ERROR |\n" + all_results.append( + { + "model": display_name, + "accuracy": None, + "passed": False, + "error": str(e), + } + ) + + if is_in_ci(): + write_github_step_summary(summary) + + failed = [r for r in all_results if not r["passed"]] + if failed: + raise AssertionError(f"Failed models: {[r['model'] for r in failed]}") + + +if __name__ == "__main__": + unittest.main() diff --git a/test/registered/amd/perf/mi30x/test_minimax_m27_perf_amd.py b/test/registered/amd/perf/mi30x/test_minimax_m27_perf_amd.py new file mode 100644 index 000000000..6981432ea --- /dev/null +++ b/test/registered/amd/perf/mi30x/test_minimax_m27_perf_amd.py @@ -0,0 +1,140 @@ +"""Nightly performance benchmark for MiniMax-M2.7 on MI325/MI300X (8-GPU). + +This test benchmarks MiniMax-M2.7 with TP=8 + EP=8 configuration. + +The model path can be configured via MINIMAX_M27_MODEL_PATH environment variable. + +Registry: nightly-perf-8-gpu-minimax-m27 suite + +Example usage: + python -m pytest test_minimax_m27_perf_amd.py -v +""" + +import os +import unittest +from typing import List + +from sglang.test.ci.ci_register import register_amd_ci +from sglang.test.nightly_bench_utils import BenchmarkResult +from sglang.test.nightly_utils import NightlyBenchmarkRunner +from sglang.test.test_utils import DEFAULT_URL_FOR_TEST, _parse_int_list_env + +register_amd_ci(est_time=5400, suite="nightly-perf-8-gpu-minimax-m27", nightly=True) + + +def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str: + """Generate a simplified markdown report without traces and cost columns. + + Skips the first result if it's a warmup run (duplicate batch_size). + """ + model_header = results[0].model_path + if results[0].run_name and results[0].run_name != "default": + model_header += f" ({results[0].run_name})" + + gpu_config = os.getenv("GPU_CONFIG", "MI325") + if gpu_config: + model_header += f" [{gpu_config}]" + + summary = f"### {model_header}\n" + summary += "| batch size | input len | latency (s) | input throughput (tok/s) | output throughput (tok/s) | ITL (ms) |\n" + summary += "| ---------- | --------- | ----------- | ------------------------ | ------------------------- | -------- |\n" + + report_results = ( + results[1:] + if len(results) > 1 and results[0].batch_size == results[1].batch_size + else results + ) + + for result in report_results: + itl = 1 / (result.output_throughput / result.batch_size) * 1000 + summary += f"| {result.batch_size} | {result.input_len} | {result.latency:.2f} | {result.input_throughput:.2f} | {result.output_throughput:.2f} | {itl:.2f} |\n" + + return summary + + +MINIMAX_M27_MODEL_PATH = os.environ.get( + "MINIMAX_M27_MODEL_PATH", "MiniMaxAI/MiniMax-M2.7" +) +PROFILE_DIR = "performance_profiles_minimax_m27" + + +class TestNightlyMiniMaxM27Performance(unittest.TestCase): + """Nightly performance benchmark for MiniMax-M2.7 on MI325/MI300X. + + Tests MiniMax-M2.7 with TP=8 + EP=8 configuration. + """ + + @classmethod + def setUpClass(cls): + cls.base_url = DEFAULT_URL_FOR_TEST + cls.batch_sizes = [1, 8, 16, 64] + cls.input_lens = tuple(_parse_int_list_env("NIGHTLY_INPUT_LENS", "4096")) + cls.output_lens = tuple(_parse_int_list_env("NIGHTLY_OUTPUT_LENS", "512")) + + cls.model_config = { + "name": "minimax-m27-tp8-ep8", + "model_path": MINIMAX_M27_MODEL_PATH, + "other_args": [ + "--trust-remote-code", + "--tp", + "8", + "--ep-size", + "8", + "--attention-backend", + "aiter", + "--mem-fraction-static", + "0.85", + "--model-loader-extra-config", + '{"enable_multithread_load": true}', + "--watchdog-timeout", + "1200", + ], + "env_vars": { + "SGLANG_USE_AITER": "1", + }, + } + + cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url) + cls.runner.setup_profile_directory() + cls.runner.full_report = f"## {cls.__name__}\n" + + def test_bench_minimax_m27(self): + """Run benchmark for MiniMax-M2.7.""" + old_env = {} + for key, value in self.model_config.get("env_vars", {}).items(): + old_env[key] = os.environ.get(key) + os.environ[key] = value + print(f"Setting env: {key}={value}") + + try: + result_tuple = self.runner.run_benchmark_for_model( + model_path=self.model_config["model_path"], + batch_sizes=self.batch_sizes, + input_lens=self.input_lens, + output_lens=self.output_lens, + other_args=self.model_config["other_args"], + variant=self.model_config["name"], + extra_bench_args=["--trust-remote-code"], + enable_profile=False, + timeout=5400, + ) + results = result_tuple[0] + success = result_tuple[1] + + if results: + self.runner.full_report += ( + generate_simple_markdown_report(results) + "\n" + ) + + self.assertTrue(success, "Benchmark failed for MiniMax-M2.7") + finally: + for key, value in old_env.items(): + if value is None: + os.environ.pop(key, None) + else: + os.environ[key] = value + self.runner.write_final_report() + + +if __name__ == "__main__": + unittest.main() diff --git a/test/registered/amd/perf/mi35x/test_minimax_m27_perf_mi35x.py b/test/registered/amd/perf/mi35x/test_minimax_m27_perf_mi35x.py new file mode 100644 index 000000000..90ef9b74d --- /dev/null +++ b/test/registered/amd/perf/mi35x/test_minimax_m27_perf_mi35x.py @@ -0,0 +1,146 @@ +"""MI35x Nightly performance benchmark for MiniMax-M2.7 (8-GPU). + +This test benchmarks MiniMax-M2.7 with TP=8 + EP=8 configuration on MI35x. + +The model path can be configured via MINIMAX_M27_MODEL_PATH environment variable. + +Registry: nightly-perf-8-gpu-mi35x-minimax-m27 suite + +Example usage: + python -m pytest test_minimax_m27_perf_mi35x.py -v +""" + +import os + +os.environ.setdefault("HF_HOME", "/data2/models/huggingface") +os.environ.setdefault("HF_HUB_CACHE", "/data2/models/huggingface/hub") + +import unittest +from typing import List + +from sglang.test.ci.ci_register import register_amd_ci +from sglang.test.nightly_bench_utils import BenchmarkResult +from sglang.test.nightly_utils import NightlyBenchmarkRunner +from sglang.test.test_utils import DEFAULT_URL_FOR_TEST, _parse_int_list_env + +register_amd_ci( + est_time=5400, suite="nightly-perf-8-gpu-mi35x-minimax-m27", nightly=True +) + + +def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str: + """Generate a simplified markdown report without traces and cost columns. + + Skips the first result if it's a warmup run (duplicate batch_size). + """ + model_header = results[0].model_path + if results[0].run_name and results[0].run_name != "default": + model_header += f" ({results[0].run_name})" + + gpu_config = os.getenv("GPU_CONFIG", "MI35x") + if gpu_config: + model_header += f" [{gpu_config}]" + + summary = f"### {model_header}\n" + summary += "| batch size | input len | latency (s) | input throughput (tok/s) | output throughput (tok/s) | ITL (ms) |\n" + summary += "| ---------- | --------- | ----------- | ------------------------ | ------------------------- | -------- |\n" + + report_results = ( + results[1:] + if len(results) > 1 and results[0].batch_size == results[1].batch_size + else results + ) + + for result in report_results: + itl = 1 / (result.output_throughput / result.batch_size) * 1000 + summary += f"| {result.batch_size} | {result.input_len} | {result.latency:.2f} | {result.input_throughput:.2f} | {result.output_throughput:.2f} | {itl:.2f} |\n" + + return summary + + +MINIMAX_M27_MODEL_PATH = os.environ.get( + "MINIMAX_M27_MODEL_PATH", "MiniMaxAI/MiniMax-M2.7" +) +PROFILE_DIR = "performance_profiles_minimax_m27_mi35x" + + +class TestNightlyMiniMaxM27PerformanceMI35x(unittest.TestCase): + """MI35x Nightly performance benchmark for MiniMax-M2.7. + + Tests MiniMax-M2.7 with TP=8 + EP=8 configuration. + """ + + @classmethod + def setUpClass(cls): + cls.base_url = DEFAULT_URL_FOR_TEST + cls.batch_sizes = [1, 8, 16, 64] + cls.input_lens = tuple(_parse_int_list_env("NIGHTLY_INPUT_LENS", "4096")) + cls.output_lens = tuple(_parse_int_list_env("NIGHTLY_OUTPUT_LENS", "512")) + + cls.model_config = { + "name": "minimax-m27-tp8-ep8", + "model_path": MINIMAX_M27_MODEL_PATH, + "other_args": [ + "--trust-remote-code", + "--tp", + "8", + "--ep-size", + "8", + "--attention-backend", + "aiter", + "--mem-fraction-static", + "0.85", + "--model-loader-extra-config", + '{"enable_multithread_load": true}', + "--watchdog-timeout", + "1200", + ], + "env_vars": { + "SGLANG_USE_AITER": "1", + }, + } + + cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url) + cls.runner.setup_profile_directory() + cls.runner.full_report = f"## {cls.__name__}\n" + + def test_bench_minimax_m27(self): + """Run benchmark for MiniMax-M2.7.""" + old_env = {} + for key, value in self.model_config.get("env_vars", {}).items(): + old_env[key] = os.environ.get(key) + os.environ[key] = value + print(f"Setting env: {key}={value}") + + try: + result_tuple = self.runner.run_benchmark_for_model( + model_path=self.model_config["model_path"], + batch_sizes=self.batch_sizes, + input_lens=self.input_lens, + output_lens=self.output_lens, + other_args=self.model_config["other_args"], + variant=self.model_config["name"], + extra_bench_args=["--trust-remote-code"], + enable_profile=False, + timeout=5400, + ) + results = result_tuple[0] + success = result_tuple[1] + + if results: + self.runner.full_report += ( + generate_simple_markdown_report(results) + "\n" + ) + + self.assertTrue(success, "Benchmark failed for MiniMax-M2.7 on MI35x") + finally: + for key, value in old_env.items(): + if value is None: + os.environ.pop(key, None) + else: + os.environ[key] = value + self.runner.write_final_report() + + +if __name__ == "__main__": + unittest.main()