Sglang benchmark test

.github/workflows/ci-sglang-benchmark.yml

@@ -0,0 +1,88 @@
+# Copyright 2024 Advanced Micro Devices, Inc.
+#
+# Licensed under the Apache License v2.0 with LLVM Exceptions.
+# See https://llvm.org/LICENSE.txt for license information.
+# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+
+name: SGLang Llama Benchmarking Tests
+
+on:
+  workflow_dispatch:
+  schedule:
+    # Weekdays at 4:00 AM UTC = 9:00 PM PST.
+    - cron: "0 4 * * 1-5"
+
+concurrency:
+  # A PR number if a pull request and otherwise the commit hash. This cancels
+  # queued and in-progress runs for the same PR (presubmit) or commit
+  # (postsubmit). The workflow name is prepended to avoid conflicts between
+  # different workflows.
+  group: ${{ github.workflow }}-${{ github.event.number || github.sha }}
+  cancel-in-progress: true
+
+jobs:
+  sglang_bench_serve:
+    name: "SGLang Serving Benchmark Tests"
+    strategy:
+      matrix:
+        version: [3.11]
+      fail-fast: false
+    runs-on: llama-mi300x-3
+    defaults:
+      run:
+        shell: bash
+    env:
+      PIP_CACHE_DIR: "${{ github.workspace }}/.pip-cache"
+    steps:
+      - name: Get Current Date
+        id: date
+        run: echo "::set-output name=date::$(date +'%Y-%m-%d')"
+
+      - name: "Setting up Python"
+        id: setup_python
+        uses: actions/setup-python@0b93645e9fea7318ecaed2b359559ac225c90a2b # v5.3.0
+        with:
+          python-version: ${{matrix.version}}
+
+      - name: "Checkout Code"
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+
+      - name: Cache Pip Packages
+        uses: actions/cache@6849a6489940f00c2f30c0fb92c6274307ccb58a # v4.1.2
+        id: cache-pip
+        with:
+          path: ${{ env.PIP_CACHE_DIR }}
+          key: pip-${{ steps.setup_python.outputs.python-version }}-${{ hashFiles('*requirements.txt') }}
+
+      - name: Install pip deps
+        run: |
+          python -m pip install --no-compile --upgrade pip
+          # Note: We install in three steps in order to satisfy requirements
+          # from non default locations first. Installing the PyTorch CPU
+          # wheels saves multiple minutes and a lot of bandwidth on runner setup.
+          pip install --no-compile -r pytorch-cpu-requirements.txt
+          pip install --no-compile -f https://iree.dev/pip-release-links.html --src deps \
+            -e "git+https://github.com/iree-org/iree-turbine.git#egg=iree-turbine"
+          pip install --no-compile -r requirements.txt -e sharktank/ shortfin/
+
+          # Try with the latest nightly releases, not what iree-turbine pins.
+          # We could also pin to a known working or stable version.
+          # This should eventually stabilize. Do the best we can for now.
+          pip install -f https://iree.dev/pip-release-links.html --upgrade \
+            iree-base-compiler==2.9.0rc20241108 \
+            iree-base-runtime==2.9.0rc20241108 \
+            "numpy<2.0"
+
+      - name: Install SGLang
+        run: pip install "git+https://github.com/nod-ai/sglang.git#subdirectory=python"
+
+      - name: Launch Shortfin Server
+        run: pytest -v app_tests/benchmark_tests/llm/sglang_benchmark_test.py --log-cli-level=INFO --html=out/llm/sglang/index.html
+
+      - name: Deploy to GitHub Pages
+        uses: peaceiris/actions-gh-pages@4f9cc6602d3f66b9c108549d475ec49e8ef4d45e # v4.0.0
+        with:
+          github_token: ${{ secrets.SHARK_PLATFORM_GH_TOKEN }}
+          publish_dir: ./out/llm/sglang
+          destination_dir: ./llm/sglang
+          keep_files: true

.github/workflows/ci-shark-platform.yml

@@ -73,4 +73,4 @@ jobs:
             "numpy<2.0"
 
       - name: Run LLM Integration Tests
-        run: pytest -v build_tools/integration_tests/llm --log-cli-level=INFO
+        run: pytest -v app_tests/integration_tests/llm --log-cli-level=INFO

app_tests/benchmark_tests/llm/conftest.py

@@ -0,0 +1,47 @@
+# Copyright 2024 Advanced Micro Devices, Inc.
+#
+# Licensed under the Apache License v2.0 with LLVM Exceptions.
+# See https://llvm.org/LICENSE.txt for license information.
+# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+
+import json
+import os
+import pytest
+import sys
+
+sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
+from integration_tests.llm.utils import compile_model, export_paged_llm_v1
+
+
+@pytest.fixture(scope="module")
+def pre_process_model(request, tmp_path_factory):
+    tmp_dir = tmp_path_factory.mktemp("sglang_benchmark_test")
+
+    model_path = request.param["model_path"]
+    settings = request.param["settings"]
+    batch_sizes = request.param["batch_sizes"]
+
+    tmp_dir = tmp_path_factory.mktemp("llm_benchmark_test")
+    mlir_path = tmp_dir / "model.mlir"
+    config_path = tmp_dir / "config.json"
+    vmfb_path = tmp_dir / "model.vmfb"
+
+    export_paged_llm_v1(mlir_path, config_path, model_path, batch_sizes)
+
+    config = {
+        "module_name": "module",
+        "module_abi_version": 1,
+        "max_seq_len": 131072,
+        "attn_head_count": 8,
+        "attn_head_dim": 128,
+        "prefill_batch_sizes": batch_sizes,
+        "decode_batch_sizes": batch_sizes,
+        "transformer_block_count": 32,
+        "paged_kv_cache": {"block_seq_stride": 16, "device_block_count": 256},
+    }
+    with open(config_path, "w") as file:
+        json.dump(config, file)
+
+    compile_model(mlir_path, vmfb_path, settings)
+
+    return tmp_dir

app_tests/benchmark_tests/llm/sglang_benchmark_test.py

@@ -0,0 +1,108 @@
+# Copyright 2024 Advanced Micro Devices, Inc.
+#
+# Licensed under the Apache License v2.0 with LLVM Exceptions.
+# See https://llvm.org/LICENSE.txt for license information.
+# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+
+import json
+import logging
+import multiprocessing
+import os
+from pathlib import Path
+import pytest
+import time
+from unittest.mock import patch
+
+pytest.importorskip("sglang")
+from sglang import bench_serving
+
+from utils import SGLangBenchmarkArgs
+
+from integration_tests.llm.utils import (
+    find_available_port,
+    start_llm_server,
+)
+
+logger = logging.getLogger("__name__")
+
+device_settings = {
+    "device_flags": [
+        "--iree-hal-target-backends=rocm",
+        "--iree-hip-target=gfx942",
+    ],
+    "device": "hip",
+}
+
+# TODO: Download on demand instead of assuming files exist at this path
+MODEL_PATH = Path("/data/llama3.1/8b/llama8b_f16.irpa")
+TOKENIZER_DIR = Path("/data/llama3.1/8b/")
+
+
+@pytest.mark.parametrize("request_rate", [1, 2, 4, 8, 16, 32])
+@pytest.mark.parametrize(
+    "pre_process_model",
+    [
+        (
+            {
+                "model_path": MODEL_PATH,
+                "settings": device_settings,
+                "batch_sizes": [1, 4],
+            }
+        )
+    ],
+    indirect=True,
+)
+def test_sglang_benchmark_server(request_rate, pre_process_model):
+    # TODO: Remove when multi-device is fixed
+    os.environ["ROCR_VISIBLE_DEVICES"] = "1"
+
+    tmp_dir = pre_process_model
+
+    config_path = tmp_dir / "config.json"
+    vmfb_path = tmp_dir / "model.vmfb"
+    tokenizer_path = TOKENIZER_DIR / "tokenizer.json"
+
+    # Start shortfin llm server
+    port = find_available_port()
+    server_process = start_llm_server(
+        port,
+        tokenizer_path,
+        config_path,
+        vmfb_path,
+        MODEL_PATH,
+        device_settings,
+        timeout=30,
+    )
+
+    # Run and collect SGLang Serving Benchmark
+    benchmark_args = SGLangBenchmarkArgs(
+        backend="shortfin",
+        num_prompt=10,
+        base_url=f"http://localhost:{port}",
+        tokenizer=TOKENIZER_DIR,
+        request_rate=request_rate,
+    )
+    output_file = (
+        tmp_dir
+        / f"{benchmark_args.backend}_{benchmark_args.num_prompt}_{benchmark_args.request_rate}.jsonl"
+    )
+    benchmark_args.output_file = output_file
+
+    logger.info("Running SGLang Benchmark with the following args:")
+    logger.info(benchmark_args)
+    try:
+        start = time.time()
+        with patch.object(bench_serving, "print", side_effect=logger.info):
+            benchmark_process = multiprocessing.Process(
+                target=bench_serving.run_benchmark,
+                args=(benchmark_args.as_namespace(),),
+            )
+            benchmark_process.start()
+            benchmark_process.join()
+
+        logger.info(f"Benchmark run completed in {str(time.time() - start)} seconds")
+    except Exception as e:
+        logger.info(e)
+
+    server_process.terminate()
+    server_process.wait()

app_tests/benchmark_tests/llm/utils.py

@@ -0,0 +1,55 @@
+# Copyright 2024 Advanced Micro Devices, Inc.
+#
+# Licensed under the Apache License v2.0 with LLVM Exceptions.
+# See https://llvm.org/LICENSE.txt for license information.
+# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+
+from argparse import Namespace
+from dataclasses import dataclass
+from pathlib import Path
+
+
+@dataclass
+class SGLangBenchmarkArgs:
+    base_url: str
+    num_prompt: int
+    request_rate: int
+    tokenizer: str | Path
+
+    seed: int = 1
+    extra_request_body: str | None = None
+    output_file: str | Path | None = None
+    port: int = 8000
+    backend: str = "shortfin"
+
+    def as_namespace(self) -> Namespace:
+        return Namespace(
+            num_prompts=self.num_prompt,
+            base_url=self.base_url,
+            tokenizer=str(self.tokenizer),
+            request_rate=self.request_rate,
+            backend=self.backend,
+            output_file=self.output_file,
+            seed=self.seed,
+            extra_request_body=self.extra_request_body,
+            port=8000,
+            model=None,
+            dataset_name="sharegpt",
+            random_input_len=None,
+            random_output_len=None,
+            dataset_path="",
+            sharegpt_output_len=None,
+            multi=False,
+            disable_tqdm=False,
+            disable_stream=False,
+            disable_ignore_eos=False,
+        )
+
+    def __repr__(self):
+        return (
+            f"Backend: {self.backend}\n"
+            f"Base URL: {self.base_url}\n"
+            f"Num Prompt: {self.num_prompt}\n"
+            f"Tokenizer: {self.tokenizer}\n"
+            f"Request Rate: {self.request_rate}"
+        )